Contrails inside cirrus clouds predominate with uncertain climate impact

Contrails inside cirrus clouds predominate with uncertain climate impact | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Contrails inside cirrus clouds predominate with uncertain climate impact Andreas Petzold, Neelam F. Khan, Yun Li, Peter Spichtinger, Susanne Rohs, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6837438/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The climate impact of aviation contrails and flight rerouting to avoid persistent contrails is currently under discussion. Proposals focus on avoiding humid areas needed for contrail formation, but neglect that they are often located inside of cirrus clouds, which will change the contrail climate effects significantly. Our analysis of seven years of humidity observations by instrumented passenger aircraft shows that only 20–30% of air masses in major flight areas can develop persistent contrails, of which more than 83% are covered by cirrus. Thin, subvisible cirrus, which contribute 5–15% to all cirrus, amplify the warming effect of contrails, while in thicker, visible cirrus warming is only slightly enhanced, or sometimes even reversed to cooling. We suggest using combined cirrus and humidity forecasts to exclude areas with visible cirrus from flight rerouting, jointly with a thorough assessment of contrail vs. CO 2 climate effects, considering the interaction of persistent contrails and cirrus. Atmospheric Sciences climate impact aviation contrail cirrus Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Main text According to most recent analyses, global aviation operations contribute about 3.5% to the total net anthropogenic warming, quantified by the metric ‘effective radiative forcing (ERF) of climate’ which measures the way these effects perturb the earth-atmosphere energy balance relative to pre-industrialization 1 . The climate impact of aviation results from both the direct emissions of carbon dioxide (CO 2 ), water vapour (H 2 O), nitrogen oxide (NO x ) and aerosol particles (soot, organics, and sulphate) 2 , and from indirect effects like the formation of persistent contrails and contrail-cirrus, NO x -induced ozone depletion (stratosphere) or formation (troposphere), and aerosol–cloud interactions. With an ERF of 60 mW m − 2 contrail-cirrus is estimated to be the largest non-CO 2 ERF contributing 60% to the aviation net total ERF of 100 mW m − 2 3, 4 . Other than the well-understood CO 2 effect and its small uncertainty, the non-CO 2 effects of aviation are associated with large uncertainties, mostly for contrail-cirrus in cold, high-humidity regions 3 , 5 , 6 . The formation and persistence of contrails, including their development into contrail cirrus, occurs when the Schmidt-Appleman criterion (SAC) is fulfilled, i.e. hot and humid aircraft exhaust mixes rapidly with cold and humid ambient air so that the humidity in the exhaust exceeds saturation with respect to liquid water (RH w >100%). Water droplets then form on the existing aerosol particles, which freeze to contrail ice particles during the strong cooling caused by further mixing with the surrounding air. After reaching the ambient temperature, the contrail ice particles grow or shrink in size depending on the ambient humidity. If it remains ice-supersaturated (RH ice > 100%), the contrails grow into contrail cirrus which can persist for up to 5 h or even longer 7 , 8 ; if the ambient air is ice-subsaturated (RH ice < 100%), the ice particles sublimate. For a contrail to survive more than a few minutes and to spread out to so-called contrail-cirrus, ambient RH ice must be close to or above ice-saturation 8 , 9 , 10 . From an observation-based climatology of ice crystal number concentrations as well as from a model analysis of contrail formation conditions we know that long-living contrails and contrail-cirrus exist at temperatures from 205 K to 230 K for ice-supersaturated (RH ice ≥ 100%) 11, 12 and slightly ice-subsaturated (90% ≤ RH ice < 100%) conditions 13 , 14 . Today, the occurrence of contrail-cirrus is discussed in its relationship to cold (T < 235 K) ice-supersaturated regions (ISSR: RH ice ≥ 100%) for which SAC is fulfilled in almost all cases 6 , 15 . In order to include contrail-cirrus also at slight ice-subsaturation in the consideration of aviation climate impacts, we introduce the term “potential contrail-cirrus region” (PCCR) which we define as an air mass with RH ice ≥ 90% and SAC fulfilled. Model calculations of ice crystal sublimation in a dissolving contrail demonstrated that it can take approximately 4 hours for ice particles to sublimate until RH ice declines to below 80% 14 . Thus, PCCRs include ISSRs and represent contrail and contrail-cirrus with lifetimes from 4 to > 10 hours 7 . A first observation-based estimate of the areal fraction of air masses prone to contrail-cirrus formation for the North Atlantic flight corridor yielded an increase from 30% for ISSRs to 43% when considering RH ice ≥ 90% as a sufficient pre-requisite for contrail-cirrus existence, i.e., for PCCRs 14 . This significant increase in the fractional area justifies the definition of a specific term to allow the differentiation from ISSRs. The formation conditions and occurrence characteristics of ice-supersaturated regions (ISSRs) as well as their links to the formation of contrail-cirrus have been intensely studied for both clear sky and in-cloud conditions 16 , 17 , 18 , 19 , 20 . Vertically, ISSRs occur most frequently in the upper troposphere just below the tropopause layer, whereas the upper free troposphere farther below the tropopause layer becomes less humid with respect to ice 20 , 21 . However, the prediction of ISSRs is difficult because they are highly variable in space and time and depend crucially on the driving weather systems 22 , 23 , 24 . As a further complication, forecast models suffer from a underrepresentation of ice-supersaturation in the upper troposphere 19 , 25 which is compensated by assuming model fields of RH ice > 93% as ice-supersaturated 26 or adjust humidity model fields to observations 27 , 28 . In addition, a not yet achieved precision of representation of ISSRs in numerical weather models 29 , 30 , 31 is needed for a better forecast of ISSRs. The known difficulties in predicting ISSRs are assumed to be valid also for PCCRs. There are several measures discussed for reducing aviation’s climate impact, including technological advancements and the availability of sustainable aviation fuels 32 . On the short term, operational concepts for avoiding contrails that individually have the largest warming effects, so-called big hits 19 , have emerged into a key strategy for reducing aviation’s climate impact 33 , 34 , 35 . However, they are intensively discussed with respect to potential trade-offs between longer flight trajectories for avoiding potential contrail-cirrus regions, i.e., PCCRs, and resulting additional CO 2 emission from extra fuel burn 36 , 37 . It is also not clear, how atmospheric conditions in future climate may have an impact on the occurrence of PCCRs 15 . Additionally, a recent study indicates stronger radiative heating by high ice clouds in a warming climate 38 which makes the reduction of anthropogenically generated high ice clouds even more urgent. Both, quantifying the climate impact of aviation as well as evaluating contrail mitigation strategies need sufficiently precise information on the environment in which long-living contrails form. This is because the radiation budget of a region, and thus its climate impact, depends on microphysical and optical properties of the ice particles whose development is more complex inside pre-existing thin or thick cirrus clouds rather than they are formed in otherwise clear sky 5 , 27 , 29 , 39 , 40 . Current approaches assume maximum random overlap between clouds and contrails of which almost no observational data exist 29 , or account for overlapping of contrails above or below clouds in the meteorological model fields 4 , 27 , 41 . Here, we provide an extensive analysis of contrail-cirrus overlap for the two densest air spaces globally and discuss the consequences of moving from ISSRs to PCCRs for the fractional air masses prone to a strong aviation climate impact. The analysis is based on in-situ humidity observations and on cirrus cloud information from reanalysis, which can reliably capture cloud presence by the assimilation of comprehensive satellite radiance measurements. Results PCCRs and ISSRs in major air traffic regions The data base of this study builds on about 7 years of continuous in-situ observations by the European research infrastructure IAGOS 42 which measures, among others, temperature and RH ice by passenger aircraft carrying scientific instrumentation during their regular operations. This extensive data base provides unprecedented in-situ measurements taken exactly in the regions of major air traffic. The fractions of all PCCRs and ISSRs were quantified for the densest airspace globally between North America and Europe (Regions 1 – 3 with approx. 10 Mio flight kilometres; see Figure 1a and Methods) in the Northern midlatitudes and, for comparison, for the second densest airspace globally over Southeast Asia (Region 4 with approx. 6 Mio flight kilometres) in the subtropics. The vertical distribution of data used in our study is illustrated in Figure 1b relative to the pressure of the thermal tropopause according to WMO 43 (p TTP ) which separates the dry lowermost stratosphere with an almost negligible potential of contrail formation from the humid and cold tropopause layer and uppermost troposphere. The definition of the pressure levels follows established IAGOS concepts 20, 44 and is described in the Methods section. The resulting vertical distributions of occurrence of PCCRs and ISSRs are illustrated in Figure 1c and Figure 1d as fractional occurrences per pressure level. It is clearly visible that PCCRs - and associated persistent contrails - occur more frequently than ISSRs. While the cruising levels of civil aviation fall within a certain pressure range globally, the thermal tropopause in the subtropics is located at higher altitudes than in the midlatitudes. Consequently, in the extratropics, e.g., at Northern midlatitudes, civil aviation cruising altitude overlaps with the cold and humid layers just below the thermal tropopause where cirrus clouds are frequent 17, 20 , while in the subtropics, the main cruising levels are located deeper inside the troposphere where the occurrence of PCCRs and ISSRs is significantly lower. Distribution of potential contrail-cirrus in clear sky and inside natural cirrus clouds The differences in the vertical distributions of cruising levels and atmospheric layers of frequent PCCRs and ISSRs occurrence between midlatitudes and subtropics have immediate consequences on the aviation non-CO 2 effects in these different regions of the world. Conditions favouring contrail-cirrus formation at cruise altitude are met frequently in the midlatitudes, while they are sparsely met in the subtropics, which becomes clearly visible in Figure 2. For the midlatitudes, the fraction of air masses in which no contrails can form (SAC not fulfilled), is < 1%, i.e., indistinguishable from the data noise level, while for the warmer subtropical region they can reach up to 15%. Conditions favouring the formation of short-lived contrails (defined as SAC fulfilled, RH ice < 90%) dominate in all regions with fractions of 70% and more (dark and light blue bars in Figure 2). This includes clear sky and cloudy conditions which were classified from reanalysis 43 cloud ice water content (CIWC) using a threshold of 0.001 ppmv (see Method section). Persistent contrails, i.e., those fulfilling the SAC criterium and exceeding the RH ice threshold naturally occur more frequently for PCCR than for ISSR. For the midlatitudes and for both threshold RH ice values, however, the number of persistent contrails or contrail-cirrus forming inside pre-existing clouds exceeds the number of cases in clear sky by at least a factor of five, whereas in the subtropics, contrail persistence is only met inside clouds. For the Northern midlatitudes, the total fraction of PCCRs (ISSRs) with respect to all probed air masses varies between 23% (16%) over Western Europe and 33% (24%) over the North Atlantic. Our observations over Europe are in good agreement with results from radiosonde-based studies 45, 46 , while for the North Atlantic no reference data are available. Overall, the increase in the fractional area prone to contrail-cirrus formation is almost 10% for the midlatitudes when considering PCCR instead of ISSR only, which is in accordance with earlier analyses of IAGOS data 14 . For Southeast Asia, the respective PCCR (ISSR) fraction is less than 14% (7%), reflecting the larger distance of cruising altitudes to the tropopause level and thus reduced RH ice levels compared to the midlatitudes. For the potential climate impact of contrail-cirrus, it is of mere importance whether they form in clear sky, subvisible clouds, or inside optically thick clouds. Subvisible clouds are distinguished from optically thick clouds by means CIWC < 1.0 ppmv. A statistical analysis on the conditions and the climate impact of these three formation categories and an assessment of their potential climate impact (see below) are given in Table 1. Details on the definition of the regions, CIWC categorization, and the results of the full statistical analysis are given in Methods and in Table S1 of the supplementary information. Table 1. Regional split of coverage areas with Schmidt-Appleman criterion (SAC) fulfilled and further subdivided into classes of potential climate impact for areas with SAC fulfilled, and respective contrail-cirrus overlap; data are based on IAGOS in-situ RH ice observations, SAC from T observations, and ERA5 CIWC cloud categorisation; regions are Eastern North America (Region 1), the North Atlantic (Region 2), Western Europe (Region 3) and Southeast Asian Subtropics (Region 4). Fraction of potential contrail-cirrus areas with SAC fulfilled Potential climate impact Contrail – cirrus overlap Region Threshold clear sky subvisible clouds visible clouds total stronger weaker no all cirrus visible cirrus RH ice CIWC < 0.001 ppmv 0.001 ppmv £ CIWC < 1.0 ppmv CIWC ³ 1.0 ppmv CIWC ³ 0.001 ppmv CIWC ³ 1.0 ppmv column a b c a + b + c a + b c 100 – (a + b + c) 100 (b + c) / (a + b + c) 100 c / (a + b + c) 1 PCCR (³ 90%) 1.9% 7.1% 19.2% 28.2% 9.0% 19.2% 71.8% 93.3% 68.0% 1 ISSR (³ 100%) 0.9% 4.3% 14.6% 19.8% 5.2% 14.6% 80.2% 95.4% 73.8% 2 PCCR 4.2% 10.7% 18.3% 33.2% 14.9% 18.3% 66.8% 87.3% 55.2% 2 ISSR 2.1% 7.1% 14.7% 23.9% 9.2% 14.7% 76.1% 91.3% 61.5% 3 PCCR 3.8% 8.1% 11.1% 23.0% 11.9% 11.1% 77.0% 83.3% 48.1% 3 ISSR 2.0% 5.3% 8.3% 15.6% 7.3% 8.3% 84.4% 86.7% 52.9% 4 PCCR 0.3% 1.1% 12.7% 14.1% 1.4% 12.7% 85.9% 98.3% 90.3% 4 ISSR 0.1% 0.5% 6.3% 6.9% 0.6% 6.3% 93.1% 98.7% 91.0% From this categorization it can be deduced that in the Northern midlatitudes, PCCR (ISSR), i.e., conditions prone to persistent contrail and contrail-cirrus formation (see Figure 2), are found for max. 4% (max. 2% or less) in clear sky, max. 11% (max. 7%) inside subvisible cirrus clouds, and max. 19% (max. 15%) inside visible cirrus clouds. That means, most contrail-cirrus potentially form in regions already covered by natural cirrus. For the subtropics, the distribution is even more pronounced with almost all PCCR and ISSR conditions observed inside visible clouds, while observations in clear sky or subvisible clouds contribute max. 1% which, however, is considered below the noise level. The overlap between air masses prone to contrail-cirrus formation (SAC fulfilled; PCCR or ISSR) and in-cloud conditions is calculated from the number of observations of PCCR or ISSR conditions, respectively, inside clouds normalised to the total number of observations with SAC fulfilled; see Table 1. The resulting PCCR (ISSR) overlap is 93% (95%) for Eastern North America, 87% (91%) for the North Atlantic, and 83% (87%) over Western Europe. For Asian Subtropics, the overlap between contrail persistence and in-cloud conditions is almost 100%. Concerning the seasonal distributions of PCCR and ISSR we focused on the midlatitudes and show the horizontal and seasonal distributions of occurrence of potential contrail-cirrus regions in Figure S1 of the supplementary information. Considering contrail-cirrus persistence in ISSR only, we clearly identify winter and spring over the North Atlantic as highly potent contrail-cirrus area and season. Lowering the threshold value for contrail-cirrus persistence to PCCR conditions results in a significant increase of potential contrail-cirrus regions over the North Atlantic also during the summer and fall months. RH ice distributions in clear sky and inside cirrus clouds The distribution of RH ice inside clouds is important for the understanding of respective cloud types. Figure 3a to c illustrate the frequencies of measured RH ice for the midlatitude regions with their peak RH ice values slightly above 100% inside visible (thick) cirrus clouds, slightly below 100% in subvisible (thin) cirrus, and at low RH ice values in clear sky. We interpret our observations such that subvisible cirrus are mostly slowly dissolving clouds observed at sub-saturated conditions, while visible cirrus clouds are more often in the developing stage at or above ice-saturation. For the Southeast Asian Subtropics (Figure 3d), the peak value of RH ice inside clouds is found at slightly sub-saturated conditions, while subvisible clouds are almost not present. That can be understood because (i) in the subtropics the cruising level of civil aviation is at lower altitudes and thus farther below the ice-supersaturated layer near the tropopause where cirrus form regularly, and (ii) the relative occurrence of ice-subsaturated air masses inside clouds increases with the distance from the cloud top 47 . Thus, in the subtropics, contrail-cirrus occur almost exclusively in physically and optically thick clouds closer to the cloud base. For clear-sky conditions, the most frequently observed RH ice values represent dry conditions with RH ice < 25% at temperatures above 225 K, while the coldest air masses probed at temperatures below 215 K are frequently close to ice-saturation. RH ice distribution patterns like the IAGOS-based observations have been reported for cirrus clouds in the midlatitude uppermost troposphere e.g., 9, 44, 48, 49 , but without the separation of subvisible from visible cirrus. The cloud categorisation successfully applied here, in combination with the visibility criterion now allows the separation of clear-sky and in-cloud conditions with consideration of cloud thickness and thus optical depth. Discussion The potential climate effects of contrail-cirrus of typical mean optical depths of 0.34 (median 0.24, modal 0.1) 50 are illustrated in Figure 4 which has been adapted from Krämer et al. 11 . The strongest potential climate impact is expected for areas otherwise free of clouds (clear-sky), or for contrail-cirrus forming in subvisible cirrus where the added optical depth of the contrail-cirrus may change the overall radiative forcing of the modified cirrus clouds significantly. For these two cases, we assume a potentially stronger climate impact of contrail-cirrus by increasing the warming potential of the clear sky or subvisible cirrus significantly. For optically thick cirrus clouds, the additional optical thickness contributed by embedded contrail-cirrus likely has only a minor effect, and we associate a potentially weaker climate impact to this case. One further case, though of unknown relevance may occur when the embedded contrail-cirrus shifts the already optically thick cloud from warming to cooling. These effects are generally known 6 but have not yet been considered in the quantification of the contrail-cirrus climate impact 29 , except for the impact of pre-existing cirrus on contrail formation in the early vortex phase of which, however, the relevance is rated as limited 39 . However, adding a persistent contrail-cirrus of mean optical depth of 0.3 to subvisible clouds with optical depths over midlatitudes reaching from 0.01 down to 10 -4 or visible cirrus with an optical depth of 0.1 52 may have a significant effect on the resulting optical depth of the modified cirrus cloud which needs to be taken into account. To quantify the potential impacts of contrail-cirrus in clear sky, subvisible or visible cirrus, we analysed the frequencies of areas with (i) no potential climate impact (SAC not fulfilled, or only short-lived contrails), (ii) weaker potential climate impact (pre-existing visible cirrus: SAC fulfilled, RH ice > threshold RH ice , and CIWC ³ 1.0 ppmv), and (iii) stronger potential climate impact (clear-sky: SAC fulfilled, RH ice > threshold RH ice , and CIWC threshold RH ice , and 0.001 ppmv £ CIWC < 1.0 ppmv). The results shown in Figure 5a clearly indicate that in the Northern midlatitudes areas of potential stronger climate impact by contrail-cirrus (red bars) occur only in less than 15% of all observed cases for PCCR conditions and in less than 10% for ISSR conditions, and are almost not observed over Southeast Asia. For a lower CIWC threshold for cloud visibility of 0.1 ppmv, the fraction of areas of potential stronger climate impact decreases to less than 10% for PCCR and about 5% for ISSR conditions, while doubling the CIWC threshold for cloud visibility to 2.0 ppmv has only a marginal impact; see Figure 5b for the North Atlantic region. According to Figure 4, in-situ formed cirrus clouds in slow of fast updraft regions are responsible for the optically thin warming cirrus clouds, whereas optically thick liquid-origin cirrus clouds have a potential cooling effect. From a trajectory-based classification of ERA-Interim ice clouds in the region of the North Atlantic storm track 51 we conclude that at typical cruising altitude pressure levels between 200 and 245 hPa 14 , in-situ formed cirrus clouds with an associated stronger climate impact are more than twice as abundant as liquid-origin cirrus clouds above 300 hPa and reach near totality above 200 hPa, independent of the season. Thus, areas of a potentially stronger climate impact of contrail-cirrus can likely be associated with clear-sky and in-situ origin cirrus regions. Finally, Figure 6 displays the regional and seasonal distributions of PCCRs with potential stronger (panels a, c, e, and g) and weaker (panels b, d, f, and h) climate impacts, following the definitions above. In fall, winter and spring months, areas covered with natural thick cirrus predominate, where embedded contrail cirrus have a weaker climate impact. For contrail-cirrus embedded in subvisible cirrus with potential stronger climate impact the differences between seasons are less pronounced, but again with a slight tendency towards higher frequencies in winter and spring months. Concluding, strong climate effects from contrail-cirrus do not occur that often, and when they do occur it is mostly in subvisible in-situ origin cirrus in winter/spring. This could be the focus of appropriate strategies to minimize aviation effects. Particularly the design of and decision on contrail avoidance strategies needs to include these findings, by combining cirrus cloud and humidity forecasts to exclude areas covered by visible cirrus from flight rerouting. This approach, combined with the option of considering PCCRs instead of ISSRs only, should help minimizing trade-off effects between rerouting of aircraft for contrail avoidance and additional fuel burn with associated CO 2 emissions 37 from the rerouting. Flight rerouting strategies for reducing aviation’s climate impact seem to be most appropriate for the Northern Midlatitudes where civil aviation cruising levels largely overlap with the cold and humid air masses just below the tropopause region, thus allowing for contrail-cirrus formation in clear sky and inside subvisible cirrus. In contrast, for regions at lower latitudes the cruising levels are located farther away from the tropopause regions outside of the cold and humid air masses such that contrail-cirrus may form in almost all cases inside thick natural cirrus clouds. The resulting climate impact is likely smaller compared to the midlatitudes and the efficiency of flight rerouting for the reduction of aviation climate impact becomes debatable for these regions. Methods IAGOS in-situ RH ice and cloud datasets, ERA5 cloud ice water content The analysed data set covers the period from June 2014 to December 2021 and contains in total more than 17´10 6 data points with each datapoint corresponding to 4 sec sampling time, or 1 km flown distance at an average cruising speed of 250 m s -1 , respectively. Figure 1a shows the normalized data density per 5°x5° grid. Four regions of interest were identified for in-depth statistical analyses, with three of them located in the Northern midlatitudes (30–60°N), namely Eastern North America (Region 1: 105–65°W, 1.57´10 6 data points), the North Atlantic flight corridor (Region 2: 65–5°W, 4.43´10 6 data points), and Western Europe (Region 3: 5°W–30°E, 4.72´10 6 data points), and one in the Southeast Asian subtropics (Region 4: 0–30°N, 45–120°E, 6.14 ´10 6 data points). The Southeast Asian tropical and subtropical region is of potential interest because of the high traffic density, though the cruise levels are farther below the tropopause level than in the midlatitudes where cruise altitudes are close to the tropopause; see Figure 1b. The combined IAGOS RH ice , N ice , and ERA5 CIWC dataset spans from June 2014 to December 2021. To restrict the analysis on the air masses of the upper troposphere and the tropopause layer with respect to the thermal tropopause (TTP) and to focus on ice clouds only, data were selected based on the following criteria 20 : pressure below 350 hPa (approx. 8.1 km) to focus on cruise altitude, pressure above p TTP – 15 hPa to exclude dry stratospheric air masses that are too dry for cirrus clouds, and temperature below 235 K (the threshold for spontaneous freezing of water droplets) to exclude air masses containing supercooled liquid water droplets. According to WMO 43 , the thermal tropopause (TTP) is defined as the lowest level at which the lapse rate decreases to 2 K km -1 or less. In our study, vertical atmospheric layers relative to the thermal tropopause are defined as: Thermal tropopause layer TTP: p = p TTP ± 15 hPa Upper troposphere layer UT1: p TTP + 15 hPa £ p < p TTP + 45 hPa Upper troposphere layer UT2: p TTP + 45 hPa £ p < p TTP + 75 hPa Upper troposphere layer UT3: p TTP + 75 hPa £ p < p TTP +105 hPa The separation of UT layers was only used for the analysis of the ISSR occurrence with altitude (Figure 1b). For all other analyses, the pressure band reaching from 350 hPa down to p TTP -15 hPa was considered. We quantified the contrail formation conditions for all sampled air masses by applying the Schmidt-Appleman criterion (SAC) 8 , and added the information on cloudiness by applying the herein developed cloud categorisation based on ERA5 Cloud Ice Water Content (CIWC). The observations were then sub-divided into clear-sky and in-cloud sequences. For each subset, conditions were rated as “no contrail formation” if SAC was not fulfilled, as favouring the formation of “short-lived contrails” if SAC was fulfilled and RH ice threshold RH ice . The complete overview over the statistical analysis is compiled in Table S1 of the supplementary information. The in-situ RH ice data are calculated from direct measurements of relative humidity with respect to liquid water (RH liq ) and ambient temperature by the IAGOS Capacitive Hygrometer (ICH). The ICH combining a thin-film HUMICAP® capacitive sensor (Vaisala) with a platinum resistance temperature sensor Pt100, is calibrated in the laboratory against an MBW dew-point chilled mirror analyser for RH liq 52 . The conversion to RH ice uses the equations by Sonntag 53 . A comparison of the ICH with the research-grade FISH fluorescence hygrometer indicates an uncertainty of ±(5-6)% RH liq and ±0.5 K 54 . The IAGOS cloud dataset includes ice cloud particle number density (N ice ) measurements from the Backscatter Cloud Probe BCP, 55 , which is an optical particle spectrometer. The BCP detects ice particles of sizes ranging from 5 to 75 µm optical equivalent diameter but does not cover larger ice particles (D > 75 µm) nor thin cirrus clouds (N ice < 0.01 cm -3 ) and thus misses almost all thin cirrus clouds 44 . In our study, it was therefore not used for the cloud categorisation. The along-track cloud ice water content (CIWC) is derived by collocating the 5 th version of ECMWF’s atmospheric reanalysis meteorological fields, ERA5 56 , to IAGOS flight trajectories. The interpolation of ERA5 data at flight positions were conducted at a downgraded spatial and temporal resolution of 1°×1° longitude/latitude resolution and 6h time resolution. The 137 levels in the vertical from the surface to 0.01 hPa remained unchanged. The CIWC at T air < 235 K is treated as ice water content and serves as the cloud indicator, given that supercooled liquid water droplets freeze instantaneously into ice crystals at temperatures below 235 K. Along-track CIWC, air temperature T ERA5 and specific humidity SH are extracted using a weighted-mean method, i.e., selecting the ERA5 grid points that are temporally and spatially closest to the IAGOS observations and calculate the mean values based on their proximity. Additionally, the WMO thermal tropopause height 43 is calculated along flight tracks to distinguish between upper tropospheric and lower stratospheric air masses. ERA5 CIWC - based cloud categorisation To our best knowledge, the ERA5 CIWC has not yet been applied as a cloud indicator to field observations, apart from climatological comparisons with satellite observations 57 , or a machine-learning approach towards adjusting ERA5 humidity data to IAGOS observations 58 . In this study, we establish an appropriate CIWC threshold to indicate in-cloud conditions by evaluating ERA5 CIWC against the high-sophisticated NIXE-CAPS 10 cloud probe and validate the selected threshold by the in-situ measured RH ice distributions. The NIXE-CAPS instrument measured cloud particle number density, size, shape, and ice water content as part of the Mid-Latitude CIRRUS (ML-CIRRUS) field study conducted over Central and Western Europe and the Northeast Atlantic 59 . NIXE-CAPS detects ice particles of diameters between 3 μm and 937 μm at number concentrations N ice as low as 10 -4 cm -3 . This extensive measurement range makes the NIXE-CAPS highly suitable for the definition of the cloud indicator. Panel (a) of Figure 7 displays the probability distribution of ERA5 RH ice in relation to various ERA5 CIWC thresholds, at cruise altitude (< 350 hPa and T amb < 235 K) with RH ice and CIWC, collocated to ML-CIRRUS flight trajectories. The blue curve, representing ERA5 CIWC = 0.000 ppmv, illustrates ideal clear-sky conditions, where ice-supersaturation is rarely observed. As the CIWC threshold increases to 0.001, 0.005, and finally 0.05 ppmv, the frequency of ice-supersaturation gradually rises, and a “shoulder” of the RH ice distribution function develops around RH ice = 100%. The NIXE-CAPS instrument has a lower detection limit for CIWC of 0.05 ppmv 60 . In theory, regions with NIXE CIWC < 0.05 ppmv should be classified as cloud-free. However, the noticeable local maximum in the 80–120% RH ice range (black curve in Figure 7) for air masses classified as cloud free (NIXE CIWC < 0.05 ppmv), suggests that NIXE-CAPS may have missed detecting some cloud particles on the sampled air which caused the increased CIWC in this nominally cloud-free air masses. When the ERA5 CIWC threshold is raised to 0.05 ppmv (red curve in Figure 7a), again the occurrence of ice supersaturation significantly increases compared to lower CIWC thresholds. Consequently, we adopt an ERA5 CIWC threshold of 0.001 ppmv as an indicator of cloud presence in the reanalysis data, because for CIWC ³ 0.001 ppmv, the typical “shoulder” of the RH ice PDF at ice saturation starts to emerge. The relation between a local maximum in the RH ice distribution function around 100% and the presence of ice crystals is validated by simulating the occurrence frequencies of RH ice at different thresholds of ice crystal number concentrations, using the Ice module within the Chemical Lagrangian Model of the Stratosphere CLaMS 61 . These simulations are based on ML-Cirrus flight trajectories. CLaMS-ice employs a two-moment ice microphysics scheme, incorporating both heterogeneous and homogeneous freezing mechanisms. The model runs 24-hour forward with boundary conditions provided by reanalysis data. Clear-sky air masses are defined as those that did not encounter cloud formation during the backward trajectories. As shown in Figure 7b, increasing the N ice threshold from 0.002 cm⁻³ to 0.05 cm⁻³ enhances the fraction of ice supersaturation, with the typical local maximum emerging at RH ice @ 100%. The high occurrence of low RH ice values in Figure 7b arises from the inclusion of stratospheric air masses within the 150–500 hPa vertical range, which is not the case for the air mases analysed in Figure 7a, which are restricted to the tropopause layer and below. Cloud optical depth estimates To estimate the cloud optical depth from the cloud ice water content, we used the relationships between cloud optical depth, CIWC and ice crystal effective diameter (D eff ) as provided by Equation (3.9a) of Fu 62 and by Equation (3) of Gayet 63 , and assumed a vertical extension of the cloud of 500 m, which is a typical extension for a fully developed contrail 64 . The conversion of CIWC from ppmv into g m -3 was conducted for fixed temperature values (in Kelvin) and a related mean pressure inside cirrus clouds following the empirical relationship p mean = 2.89319´10 -4 ´T 2.66906 - 247.724 hPa 65 . Effective diameter values D eff were taken from sources based on observations, from which we selected D eff = 10 µm for a contrail at T = 217 K and older than 30 minutes 66 , D eff = 20 µm for a young cirrus at 10.6 km altitude and T = 213 K 66 , and D eff = 40 µm as the most probable effective diameter for cirrus clouds with CIWC values between 0.1 ppmv and 1.0 ppmv at Northern Midlatitudes 14, 67 . The discrimination threshold between subvisible and visible cirrus was taken from two sources. From lidar observations 68 an overall optical depth in the visible spectral range of 0.03 is generally accepted as visibility threshold. From theoretical calculations 69 , a limiting extinction coefficient of 2 – 3´10 -5 m -1 is reported, which turns into an optical depth of 0.01 to 0.015 for a cloud of 500 m vertical extension. The results shown in Figure 8 indicate that a CIWC of 1.0 ppmv, a vertical extension of 500 m, and a temperature range from 205 K to 230 K produce a cloud optical thickness between the visibility thresholds of the two sources, independent of the selected relationship between optical depth, CIWC and D eff . Therefore, we used a CIWC value of 1.0 ppmv to distinguish subvisible from visible clouds. Declarations Data Availability IAGOS data are available through the IAGOS Data Portal https://doi.org/10.25326/20 . Acknowledgements IAGOS data were created with support from the European Commission, national agencies in Germany (BMBF), France (MESR), and the UK (NERC), and the IAGOS member institutions (http://www.iagos.org/partners). The participating airlines (Deutsche Lufthansa, Air France, China Airlines, Hawaiian Airlines, Air Canada, Iberia, Discover, Cathay Pacific) support IAGOS by carrying the measurement equipment free of charge. The data are available at http://www.iagos.fr thanks to additional support from AERIS. PS acknowledges support by the DFG within the Transregional Collaborative Research Centre TRR 301 TPChange, project ID 428312742, project B7. YL acknowledges support from the SESAR 3 Joint Undertaking under grant agreement No 101114613 (CICONIA) under European Union’s Horizon Europe research and innovation programme. Author Contributions AP and MK designed the study and coordinated the analyses and interpretation. NFK performed the IAGOS data analyses. The figures in the manuscript were prepared by AP and NFK. PS contributed the calculations of the cloud optical properties. YL evaluated the ERA5 cloud categorisation and prepared the IAGOS water vapour data set used for this study. SR performed the quality assessments of the IAGOS water vapour data. AP and MK wrote the manuscript with assistance from PS, YL, SR, SC and AW. Competing interests The authors declare no competing interests. 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Supplementary Files ISSRPCCRncommPetzoldSupplement.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6837438","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":467592874,"identity":"bba5c01e-4d47-4a04-bbe8-e4ef9ad3f01a","order_by":0,"name":"Andreas Petzold","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIie3RsWrDMBCA4TMH6nKVVxWC8woKBWeo6bO4CNKxW+jWdPGUvtOFG7yYzAlZAoHMHjMYWsUNtIvcjoXqR4ME+kBnA8Rif7gR1K97AALQCArOazA+323E9kT9nmyc7Q8KfiDp4np1aLuC9PaALYwkU1d43MO8CBLD2lmmGd3sHFgguVWophbWs4FHUW7YCNndE7uO5KFCUiapJCjGTNMTW0+24mciebmQ9yDxj8qBS082mCw8KdUn4SCZiHamYT9L49B/uMdJhSo35doFSVa/rdrnrsh0Ldgmy7txmsrRtPP78PhI3w7J8rIpwwD6H/7VafBqLBaL/dM+AEruSYpuOQuOAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-2504-1680","institution":"Forschungszentrum Jülich GmbH","correspondingAuthor":true,"prefix":"","firstName":"Andreas","middleName":"","lastName":"Petzold","suffix":""},{"id":467592875,"identity":"155a3ca4-18e0-41c1-a468-cb2e4e96cff5","order_by":1,"name":"Neelam F. 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inserted boxes indicate the regions of interest Eastern North America (Region 1), the North Atlantic (Region 2), Western Europe (Region 3) and Southeast Asian Subtropics (Region 4); Panel (b): vertical distribution of data for four pressure levels of thickness 30 hPa relative to the pressure level of the thermal tropopause p\u003csub\u003eTTP\u003c/sub\u003e; Panel (c) fraction of potential contrail-cirrus regions (PCCR; RH\u003csub\u003eice\u003c/sub\u003e ³ 90%) for each pressure level; Panel (d) same as Panel (c) but for ice-supersaturated regions (ISSR; RH\u003csub\u003eice\u003c/sub\u003e ³ 100%).\u003c/p\u003e","description":"","filename":"F1Globaldatadistribution.png","url":"https://assets-eu.researchsquare.com/files/rs-6837438/v1/e45ca1b13489c30bc5684fad.png"},{"id":84379359,"identity":"5787e290-5a31-41a2-8edb-048498acfee5","added_by":"auto","created_at":"2025-06-11 08:54:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":262834,"visible":true,"origin":"","legend":"\u003cp\u003eFraction of air masses promoting no contrail formation (Schmidt-Appleman criterion not fulfilled), formation of short-lived contrails (Schmidt-Appleman criterion fulfilled, RH\u003csub\u003eice\u003c/sub\u003e \u0026lt; threshold RH\u003csub\u003eice\u003c/sub\u003e) and formation of persistent contrails and contrail-cirrus (Schmidt-Appleman criterion fulfilled, RH\u003csub\u003eice\u003c/sub\u003e ³ threshold RH\u003csub\u003eice\u003c/sub\u003e); dark blue bars indicate clear-sky conditions (CIWC\u003csub\u003eERA5\u003c/sub\u003e \u0026lt; 0.001 ppmv), light blue bars in-cloud conditions (CIWC\u003csub\u003eERA5\u003c/sub\u003e ³ 0.001 ppmv).\u003c/p\u003e","description":"","filename":"F2Contrailfractions.png","url":"https://assets-eu.researchsquare.com/files/rs-6837438/v1/d7a9aba6495fb39e48e8fd05.png"},{"id":84378100,"identity":"52eac660-5c91-45db-b7d5-ee36856681b5","added_by":"auto","created_at":"2025-06-11 08:46:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":504439,"visible":true,"origin":"","legend":"\u003cp\u003eOccurrence probabilities of RHI\u003csub\u003eice\u003c/sub\u003e values obtained from IAGOS in-situ observations below the thermal tropopause for Eastern North America (a), over the North Atlantic (b), Western Europe (c) and Southeast Asia (d); green lines represent clear-sky conditions with CIWC \u0026lt; 0.001 ppmv, blue lines in-cloud conditions for CIWC ³ 0.001 ppmv; thin, subvisible clouds refer to CIWC \u0026lt; 1.0 ppmv, thick, visible clouds to CIWC ³ 1 ppmv.\u003c/p\u003e","description":"","filename":"F3RHicePDF.png","url":"https://assets-eu.researchsquare.com/files/rs-6837438/v1/821b032fbc82842c8906583b.png"},{"id":84379712,"identity":"5178178f-a287-4a22-aa1d-e7112a153a94","added_by":"auto","created_at":"2025-06-11 09:02:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1283036,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic of the impact of contrail-cirrus embedded in natural cirrus, adapted from Krämer et al. \u003csup\u003e11\u003c/sup\u003e; red arrows illustrate stronger climate impacts, and blue arrows weaker climate impacts.\u003c/p\u003e","description":"","filename":"F4ImpactScheme.png","url":"https://assets-eu.researchsquare.com/files/rs-6837438/v1/83f6d98007b4939f8a9c48a7.png"},{"id":84378095,"identity":"625068f1-4145-40d8-9d6d-67266ab17571","added_by":"auto","created_at":"2025-06-11 08:46:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":235412,"visible":true,"origin":"","legend":"\u003cp\u003ePanel (a): Fractions of air masses with almost no aviation climate impact (SAC not fulfilled or short-lived contrails only), weaker climate impact (contrail-cirrus in visible cirrus with CIWC ³ 1.0 ppmv), and stronger climate impact (contrail-cirrus in clear sky or in subvisible cirrus); Panel (b): air mass fractions as in Panel (a) for various CIWC threshold values of cloud visibility. All analyses were performed for both PCCR (RH\u003csub\u003eice\u003c/sub\u003e ³ 90%) and ISSR (RH\u003csub\u003eice\u003c/sub\u003e ³ 100%) conditions.\u003c/p\u003e","description":"","filename":"F5ClimateImpactPlotCIWC.png","url":"https://assets-eu.researchsquare.com/files/rs-6837438/v1/18dd98b86a132a2a20f91407.png"},{"id":84378105,"identity":"85eaa3d3-faaa-4e89-b530-9be1277d3f64","added_by":"auto","created_at":"2025-06-11 08:46:56","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3380144,"visible":true,"origin":"","legend":"\u003cp\u003eSeasonal distribution of areas of contrail-cirrus coverage with stronger climate impact (contrail-cirrus in clear sky or in subvisible cirrus with CIWC \u0026lt; 1.0 ppmv; panels a, c, e, g), and weaker climate impact (contrail-cirrus inside optically thick cirrus with CIWC ³ 1.0 ppmv; panels b, d, f, h). The maps were determined for potential contrail-cirrus regions (PCCR) with a threshold humidity of RH\u003csub\u003eice\u003c/sub\u003e = 90%.\u003c/p\u003e","description":"","filename":"F6PCCRClimateImpactMaps.png","url":"https://assets-eu.researchsquare.com/files/rs-6837438/v1/3ba2988545b442e6c62b2a5e.png"},{"id":84379713,"identity":"98393d5b-a698-4dfb-a789-d23d762ab847","added_by":"auto","created_at":"2025-06-11 09:02:56","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":174929,"visible":true,"origin":"","legend":"\u003cp\u003ePanel (a) ERA5 RH\u003csub\u003eice, \u003c/sub\u003eoccurrence frequency distributions at various ERA5 CIWC thresholds; panel (b) RH\u003csub\u003eice\u003c/sub\u003e occurrence frequencies at various N\u003csub\u003eice\u003c/sub\u003e thresholds simulated by CLaMS-Ice.\u003c/p\u003e","description":"","filename":"F7Cloudindicator.png","url":"https://assets-eu.researchsquare.com/files/rs-6837438/v1/ecb78fa4f451fdad26cfe6aa.png"},{"id":84378107,"identity":"a97676df-f65c-4a51-b19d-8996b2f75106","added_by":"auto","created_at":"2025-06-11 08:46:56","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1131960,"visible":true,"origin":"","legend":"\u003cp\u003eCloud optical depth estimate for various ERA5 cloud ice water content (CIWC) values and ice crystal effective diameters (D\u003csub\u003eeff\u003c/sub\u003e); curves shown in Panel (a) used the the radiative scheme by Fu \u003csup\u003e62\u003c/sup\u003e, those shown in Panel (b) the scheme by Gayet et al. \u003csup\u003e63\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"F8CWCODPlot.png","url":"https://assets-eu.researchsquare.com/files/rs-6837438/v1/4a88f66baea1ce569ce50ef4.png"},{"id":84380485,"identity":"7074c85d-5390-4beb-884d-6dc412ae86b3","added_by":"auto","created_at":"2025-06-11 09:11:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":10196562,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6837438/v1/6387f36e-729b-435f-9727-f0073ed9830f.pdf"},{"id":84379360,"identity":"27c97704-e58c-4cc5-a249-5f81a8560f0c","added_by":"auto","created_at":"2025-06-11 08:54:56","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":886595,"visible":true,"origin":"","legend":"","description":"","filename":"ISSRPCCRncommPetzoldSupplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-6837438/v1/1399f2988dd04e73171d4eba.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eContrails inside cirrus clouds predominate with uncertain climate impact\u003c/p\u003e","fulltext":[{"header":"Main text","content":"\u003cp\u003eAccording to most recent analyses, global aviation operations contribute about 3.5% to the total net anthropogenic warming, quantified by the metric \u0026lsquo;effective radiative forcing (ERF) of climate\u0026rsquo; which measures the way these effects perturb the earth-atmosphere energy balance relative to pre-industrialization\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The climate impact of aviation results from both the direct emissions of carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e), water vapour (H\u003csub\u003e2\u003c/sub\u003eO), nitrogen oxide (NO\u003csub\u003ex\u003c/sub\u003e) and aerosol particles (soot, organics, and sulphate)\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, and from indirect effects like the formation of persistent contrails and contrail-cirrus, NO\u003csub\u003ex\u003c/sub\u003e-induced ozone depletion (stratosphere) or formation (troposphere), and aerosol\u0026ndash;cloud interactions. With an ERF of 60 mW m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e contrail-cirrus is estimated to be the largest non-CO\u003csub\u003e2\u003c/sub\u003e ERF contributing 60% to the aviation net total ERF of 100 mW m\u003csup\u003e\u0026minus;\u0026thinsp;2 3, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Other than the well-understood CO\u003csub\u003e2\u003c/sub\u003e effect and its small uncertainty, the non-CO\u003csub\u003e2\u003c/sub\u003e effects of aviation are associated with large uncertainties, mostly for contrail-cirrus in cold, high-humidity regions\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe formation and persistence of contrails, including their development into contrail cirrus, occurs when the Schmidt-Appleman criterion (SAC) is fulfilled, i.e. hot and humid aircraft exhaust mixes rapidly with cold and humid ambient air so that the humidity in the exhaust exceeds saturation with respect to liquid water (RH\u003csub\u003ew\u003c/sub\u003e \u0026gt;100%). Water droplets then form on the existing aerosol particles, which freeze to contrail ice particles during the strong cooling caused by further mixing with the surrounding air. After reaching the ambient temperature, the contrail ice particles grow or shrink in size depending on the ambient humidity. If it remains ice-supersaturated (RH\u003csub\u003eice\u003c/sub\u003e \u0026gt; 100%), the contrails grow into contrail cirrus which can persist for up to 5 h or even longer\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e; if the ambient air is ice-subsaturated (RH\u003csub\u003eice\u003c/sub\u003e \u0026lt; 100%), the ice particles sublimate. For a contrail to survive more than a few minutes and to spread out to so-called contrail-cirrus, ambient RH\u003csub\u003eice\u003c/sub\u003e must be close to or above ice-saturation\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFrom an observation-based climatology of ice crystal number concentrations as well as from a model analysis of contrail formation conditions we know that long-living contrails and contrail-cirrus exist at temperatures from 205 K to 230 K for ice-supersaturated (RH\u003csub\u003eice\u003c/sub\u003e \u0026ge; 100%)\u003csup\u003e11, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e and slightly ice-subsaturated (90% \u0026le; RH\u003csub\u003eice\u003c/sub\u003e \u0026lt; 100%) conditions\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Today, the occurrence of contrail-cirrus is discussed in its relationship to cold (T\u0026thinsp;\u0026lt;\u0026thinsp;235 K) ice-supersaturated regions (ISSR: RH\u003csub\u003eice\u003c/sub\u003e \u0026ge; 100%) for which SAC is fulfilled in almost all cases\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. In order to include contrail-cirrus also at slight ice-subsaturation in the consideration of aviation climate impacts, we introduce the term \u0026ldquo;potential contrail-cirrus region\u0026rdquo; (PCCR) which we define as an air mass with RH\u003csub\u003eice\u003c/sub\u003e \u0026ge; 90% and SAC fulfilled. Model calculations of ice crystal sublimation in a dissolving contrail demonstrated that it can take approximately 4 hours for ice particles to sublimate until RH\u003csub\u003eice\u003c/sub\u003e declines to below 80% \u003csup\u003e14\u003c/sup\u003e. Thus, PCCRs include ISSRs and represent contrail and contrail-cirrus with lifetimes from 4 to \u0026gt;\u0026thinsp;10 hours\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA first observation-based estimate of the areal fraction of air masses prone to contrail-cirrus formation for the North Atlantic flight corridor yielded an increase from 30% for ISSRs to 43% when considering RH\u003csub\u003eice\u003c/sub\u003e \u0026ge; 90% as a sufficient pre-requisite for contrail-cirrus existence, i.e., for PCCRs\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. This significant increase in the fractional area justifies the definition of a specific term to allow the differentiation from ISSRs.\u003c/p\u003e \u003cp\u003eThe formation conditions and occurrence characteristics of ice-supersaturated regions (ISSRs) as well as their links to the formation of contrail-cirrus have been intensely studied for both clear sky and in-cloud conditions\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Vertically, ISSRs occur most frequently in the upper troposphere just below the tropopause layer, whereas the upper free troposphere farther below the tropopause layer becomes less humid with respect to ice\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. However, the prediction of ISSRs is difficult because they are highly variable in space and time and depend crucially on the driving weather systems\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. As a further complication, forecast models suffer from a underrepresentation of ice-supersaturation in the upper troposphere\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e which is compensated by assuming model fields of RH\u003csub\u003eice\u003c/sub\u003e \u0026gt; 93% as ice-supersaturated\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e or adjust humidity model fields to observations\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. In addition, a not yet achieved precision of representation of ISSRs in numerical weather models\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e is needed for a better forecast of ISSRs. The known difficulties in predicting ISSRs are assumed to be valid also for PCCRs.\u003c/p\u003e \u003cp\u003eThere are several measures discussed for reducing aviation\u0026rsquo;s climate impact, including technological advancements and the availability of sustainable aviation fuels\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. On the short term, operational concepts for avoiding contrails that individually have the largest warming effects, so-called big hits\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, have emerged into a key strategy for reducing aviation\u0026rsquo;s climate impact\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. However, they are intensively discussed with respect to potential trade-offs between longer flight trajectories for avoiding potential contrail-cirrus regions, i.e., PCCRs, and resulting additional CO\u003csub\u003e2\u003c/sub\u003e emission from extra fuel burn\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. It is also not clear, how atmospheric conditions in future climate may have an impact on the occurrence of PCCRs\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Additionally, a recent study indicates stronger radiative heating by high ice clouds in a warming climate\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e which makes the reduction of anthropogenically generated high ice clouds even more urgent.\u003c/p\u003e \u003cp\u003eBoth, quantifying the climate impact of aviation as well as evaluating contrail mitigation strategies need sufficiently precise information on the environment in which long-living contrails form. This is because the radiation budget of a region, and thus its climate impact, depends on microphysical and optical properties of the ice particles whose development is more complex inside pre-existing thin or thick cirrus clouds rather than they are formed in otherwise clear sky\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Current approaches assume maximum random overlap between clouds and contrails of which almost no observational data exist\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, or account for overlapping of contrails above or below clouds in the meteorological model fields\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Here, we provide an extensive analysis of contrail-cirrus overlap for the two densest air spaces globally and discuss the consequences of moving from ISSRs to PCCRs for the fractional air masses prone to a strong aviation climate impact. The analysis is based on in-situ humidity observations and on cirrus cloud information from reanalysis, which can reliably capture cloud presence by the assimilation of comprehensive satellite radiance measurements.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePCCRs and ISSRs in major air traffic regions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data base of this study builds on about 7 years of continuous in-situ observations by the European research infrastructure IAGOS\u003csup\u003e42\u003c/sup\u003e which measures, among others, temperature and RH\u003csub\u003eice\u003c/sub\u003e by passenger aircraft carrying scientific instrumentation during their regular operations. This extensive data base provides unprecedented in-situ measurements taken exactly in the regions of major air traffic. The fractions of all PCCRs and ISSRs were quantified for the densest airspace globally between North America and Europe (Regions 1 \u0026ndash; 3 with approx. 10 Mio flight kilometres; see Figure 1a and Methods) in the Northern midlatitudes and, for comparison, for the second densest airspace globally over Southeast Asia (Region 4 with approx. 6 Mio flight kilometres) in the subtropics.\u003c/p\u003e\n\u003cp\u003eThe vertical distribution of data used in our study is illustrated in Figure 1b relative to the pressure of the thermal tropopause according to WMO\u003csup\u003e43\u003c/sup\u003e (p\u003csub\u003eTTP\u003c/sub\u003e) which separates the dry lowermost stratosphere with an almost negligible potential of contrail formation from the humid and cold tropopause layer and uppermost troposphere. The definition of the pressure levels follows established IAGOS concepts\u003csup\u003e20, 44\u003c/sup\u003e and is described in the Methods section. The resulting vertical distributions of occurrence of PCCRs and ISSRs are illustrated in Figure 1c and Figure 1d as fractional occurrences per pressure level. It is clearly visible that PCCRs - and associated persistent contrails - occur more frequently than ISSRs.\u003c/p\u003e\n\u003cp\u003eWhile the cruising levels of civil aviation fall within a certain pressure range globally, the thermal tropopause in the subtropics is located at higher altitudes than in the midlatitudes. Consequently, in the extratropics, e.g., at Northern midlatitudes, civil aviation cruising altitude overlaps with the cold and humid layers just below the thermal tropopause where cirrus clouds are frequent\u003csup\u003e17, 20\u003c/sup\u003e, while in the subtropics, the main cruising levels are located deeper inside the troposphere where the occurrence of PCCRs and ISSRs is significantly lower.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDistribution of potential contrail-cirrus in clear sky and inside natural cirrus clouds\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe differences in the vertical distributions of cruising levels and atmospheric layers of frequent PCCRs and ISSRs occurrence between midlatitudes and subtropics have immediate consequences on the aviation non-CO\u003csub\u003e2\u003c/sub\u003e effects in these different regions of the world. Conditions favouring contrail-cirrus formation at cruise altitude are met frequently in the midlatitudes, while they are sparsely met in the subtropics, which becomes clearly visible in Figure 2. For the midlatitudes, the fraction of air masses in which no contrails can form (SAC not fulfilled), is \u0026lt; 1%, i.e., indistinguishable from the data noise level, while for the warmer subtropical region they can reach up to 15%.\u003c/p\u003e\n\u003cp\u003eConditions favouring the formation of short-lived contrails (defined as SAC fulfilled, RH\u003csub\u003eice\u003c/sub\u003e \u0026lt; 90%) dominate in all regions with fractions of 70% and more (dark and light blue bars in Figure 2). This includes clear sky and cloudy conditions which were classified from reanalysis\u003csup\u003e43\u003c/sup\u003e cloud ice water content (CIWC) using a threshold of 0.001 ppmv (see Method section). Persistent contrails, i.e., those fulfilling the SAC criterium and exceeding the RH\u003csub\u003eice\u003c/sub\u003e threshold naturally occur more frequently for PCCR than for ISSR. For the midlatitudes and for both threshold RH\u003csub\u003eice\u003c/sub\u003e values, however, the number of persistent contrails or contrail-cirrus forming inside pre-existing clouds exceeds the number of cases in clear sky by at least a factor of five, whereas in the subtropics, contrail persistence is only met inside clouds.\u003c/p\u003e\n\u003cp\u003eFor the Northern midlatitudes, the total fraction of PCCRs (ISSRs) with respect to all probed air masses varies between 23% (16%) over Western Europe and 33% (24%) over the North Atlantic. Our observations over Europe are in good agreement with results from radiosonde-based studies\u003csup\u003e45, 46\u003c/sup\u003e, while for the North Atlantic no reference data are available. Overall, the increase in the fractional area prone to contrail-cirrus formation is almost 10% for the midlatitudes when considering PCCR instead of ISSR only, which is in accordance with earlier analyses of IAGOS data\u003csup\u003e14\u003c/sup\u003e. For Southeast Asia, the respective PCCR (ISSR) fraction is less than 14% (7%), reflecting the larger distance of cruising altitudes to the tropopause level and thus reduced RH\u003csub\u003eice\u003c/sub\u003e levels compared to the midlatitudes.\u003c/p\u003e\n\u003cp\u003eFor the potential climate impact of contrail-cirrus, it is of mere importance whether they form in clear sky, subvisible clouds, or inside optically thick clouds. Subvisible clouds are distinguished from optically thick clouds by means CIWC \u0026lt; 1.0 ppmv. A statistical analysis on the conditions and the climate impact of these three formation categories and an assessment of their potential climate impact (see below) are given in Table 1. Details on the definition of the regions, CIWC categorization, and the results of the full statistical analysis are given in Methods and in Table S1 of the supplementary information.\u003c/p\u003e\n\u003cp\u003eTable 1.\u0026nbsp;Regional split of coverage areas with Schmidt-Appleman criterion (SAC) fulfilled and further subdivided into classes of potential climate impact for areas with SAC fulfilled, and respective contrail-cirrus overlap; data are based on IAGOS in-situ RH\u003csub\u003eice\u003c/sub\u003e observations, SAC from T observations, and ERA5 CIWC cloud categorisation;\u0026nbsp;regions are\u0026nbsp;Eastern North America (Region 1), the North Atlantic (Region 2), Western Europe (Region 3) and Southeast Asian Subtropics (Region 4).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"737\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 302px;\"\u003e\n \u003cp\u003eFraction of potential contrail-cirrus areas with SAC fulfilled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 180px;\"\u003e\n \u003cp\u003ePotential climate impact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 161px;\"\u003e\n \u003cp\u003eContrail \u0026ndash; cirrus overlap\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eThreshold\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eclear sky\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003esubvisible clouds\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003evisible clouds\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003etotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003estronger\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eweaker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eall cirrus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003evisible cirrus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eRH\u003csub\u003eice\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eCIWC \u0026lt; 0.001 ppmv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.001 ppmv\u0026nbsp;\u0026pound;\u0026nbsp;CIWC \u0026lt; 1.0 ppmv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eCIWC\u0026nbsp;\u0026sup3;\u0026nbsp; \u0026nbsp; \u0026nbsp;1.0 ppmv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eCIWC\u0026nbsp;\u0026sup3;\u0026nbsp;0.001 ppmv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eCIWC\u0026nbsp;\u0026sup3;\u0026nbsp; \u0026nbsp; \u0026nbsp;1.0 ppmv\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003ecolumn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ec\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003ea + b + c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003ea + b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003ec\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e100 \u0026ndash; (a + b + c)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e100 (b + c) / (a + b + c)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e100 c / (a + b + c)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCCR\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(\u0026sup3;\u0026nbsp;90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e1.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e7.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e19.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.2%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e9.0%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e19.2%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e71.8%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e93.3%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e68.0%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eISSR\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(\u0026sup3;\u0026nbsp;100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e14.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e19.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e5.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e14.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e80.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e95.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e73.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCCR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e4.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e10.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e18.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e33.2%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14.9%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18.3%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e66.8%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e87.3%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e55.2%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eISSR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e7.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e14.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e23.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e9.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e14.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e76.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e91.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e61.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCCR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e3.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e8.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e11.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e23.0%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11.9%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11.1%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e77.0%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e83.3%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e48.1%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eISSR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e8.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e15.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e7.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e8.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e84.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e86.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e52.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCCR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e12.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14.1%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.4%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12.7%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e85.9%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e98.3%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e90.3%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eISSR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e6.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e6.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e6.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e93.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e98.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e91.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eFrom this categorization it can be deduced that in the Northern midlatitudes, PCCR (ISSR), i.e., conditions prone to persistent contrail and contrail-cirrus formation (see Figure 2), are found for max. 4% (max. 2% or less) in clear sky, max. 11% (max. 7%) inside subvisible cirrus clouds, and max. 19% (max. 15%) inside visible cirrus clouds. That means, most contrail-cirrus potentially form in regions already covered by natural cirrus. For the subtropics, the distribution is even more pronounced with almost all PCCR and ISSR conditions observed inside visible clouds, while observations in clear sky or subvisible clouds contribute max. 1% which, however, is considered below the noise level.\u003c/p\u003e\n\u003cp\u003eThe overlap between air masses prone to contrail-cirrus formation (SAC fulfilled; PCCR or ISSR) and in-cloud conditions is calculated from the number of observations of PCCR or ISSR conditions, respectively, inside clouds normalised to the total number of observations with SAC fulfilled; see Table 1. The resulting PCCR (ISSR) overlap is 93% (95%) for Eastern North America, 87% (91%) for the North Atlantic, and 83% (87%) over Western Europe. For Asian Subtropics, the overlap between contrail persistence and in-cloud conditions is almost 100%.\u003c/p\u003e\n\u003cp\u003eConcerning the seasonal distributions of PCCR and ISSR we focused on the midlatitudes and show the horizontal and seasonal distributions of occurrence of potential contrail-cirrus regions in Figure S1 of the supplementary information. Considering contrail-cirrus persistence in ISSR only, we clearly identify winter and spring over the North Atlantic as highly potent contrail-cirrus area and season. Lowering the threshold value for contrail-cirrus persistence to PCCR conditions results in a significant increase of potential contrail-cirrus regions over the North Atlantic also during the summer and fall months.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRH\u003csub\u003eice\u003c/sub\u003e distributions in clear sky and inside cirrus clouds\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe distribution of RH\u003csub\u003eice\u003c/sub\u003e inside clouds is important for the understanding of respective cloud types. Figure 3a to c illustrate the frequencies of measured RH\u003csub\u003eice\u0026nbsp;\u003c/sub\u003efor the midlatitude regions with their peak RH\u003csub\u003eice\u003c/sub\u003e values slightly above 100% inside visible (thick) cirrus clouds, slightly below 100% in subvisible (thin) cirrus, and at low RH\u003csub\u003eice\u003c/sub\u003e values in clear sky. We interpret our observations such that subvisible cirrus are mostly slowly dissolving clouds observed at sub-saturated conditions, while visible cirrus clouds are more often in the developing stage at or above ice-saturation.\u003c/p\u003e\n\u003cp\u003eFor the Southeast Asian Subtropics (Figure 3d), the peak value of RH\u003csub\u003eice\u003c/sub\u003e inside clouds is found at slightly sub-saturated conditions, while subvisible clouds are almost not present. That can be understood because (i) in the subtropics the cruising level of civil aviation is at lower altitudes and thus farther below the ice-supersaturated layer near the tropopause where cirrus form regularly, and (ii) the relative occurrence of ice-subsaturated air masses inside clouds increases with the distance from the cloud top\u003csup\u003e47\u003c/sup\u003e. Thus, in the subtropics, contrail-cirrus occur almost exclusively in physically and optically thick clouds closer to the cloud base.\u003c/p\u003e\n\u003cp\u003eFor clear-sky conditions, the most frequently observed RH\u003csub\u003eice\u003c/sub\u003e values represent dry conditions with RH\u003csub\u003eice\u003c/sub\u003e \u0026lt; 25% at temperatures above 225 K, while the coldest air masses probed at temperatures below 215 K are frequently close to ice-saturation.\u003c/p\u003e\n\u003cp\u003eRH\u003csub\u003eice\u003c/sub\u003e distribution patterns like the IAGOS-based observations have been reported for cirrus clouds in the midlatitude uppermost troposphere\u003csup\u003ee.g.,\u0026nbsp;\u003c/sup\u003e\u003csup\u003e9, 44, 48, 49\u003c/sup\u003e, but without the separation of subvisible from visible cirrus. The cloud categorisation successfully applied here, in combination with the visibility criterion now allows the separation of clear-sky and in-cloud conditions with consideration of cloud thickness and thus optical depth.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe potential climate effects of contrail-cirrus of typical mean optical depths of 0.34 (median 0.24, modal 0.1) \u003csup\u003e50\u003c/sup\u003e are illustrated in Figure 4 which has been adapted from Kr\u0026auml;mer et al.\u003csup\u003e11\u003c/sup\u003e. The strongest potential climate impact is expected for areas otherwise free of clouds (clear-sky), or for contrail-cirrus forming in subvisible cirrus where the added optical depth of the contrail-cirrus may change the overall radiative forcing of the modified cirrus clouds significantly. For these two cases, we assume a potentially stronger climate impact of contrail-cirrus by increasing the warming potential of the clear sky or subvisible cirrus significantly. For optically thick cirrus clouds, the additional optical thickness contributed by embedded contrail-cirrus likely has only a minor effect, and we associate a potentially weaker climate impact to this case. One further case, though of unknown relevance may occur when the embedded contrail-cirrus shifts the already optically thick cloud from warming to cooling. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese effects are generally known\u003csup\u003e6\u003c/sup\u003e but have not yet been considered in the quantification of the contrail-cirrus climate impact\u003csup\u003e29\u003c/sup\u003e, except for the impact of pre-existing cirrus on contrail formation in the early vortex phase of which, however, the relevance is rated as limited\u003csup\u003e39\u003c/sup\u003e. However, adding a \u0026nbsp;persistent contrail-cirrus of mean optical depth of 0.3 to \u0026nbsp;subvisible clouds with optical depths over midlatitudes reaching from 0.01 down to 10\u003csup\u003e-4\u0026nbsp;\u003c/sup\u003e or visible cirrus with an optical depth of 0.1 \u003csup\u003e52\u003c/sup\u003e\u0026nbsp; may have a significant effect on the resulting optical depth of the modified cirrus cloud which needs to be taken into account. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo quantify the potential impacts of contrail-cirrus in clear sky, subvisible or visible cirrus, we analysed the frequencies of areas with (i) no potential climate impact (SAC not fulfilled, or only short-lived contrails), (ii) weaker potential climate impact (pre-existing visible cirrus: SAC fulfilled, RH\u003csub\u003eice\u003c/sub\u003e \u0026gt; threshold RH\u003csub\u003eice\u003c/sub\u003e, and CIWC\u0026nbsp;\u0026sup3;\u0026nbsp;1.0 ppmv), and (iii) stronger potential climate impact (clear-sky: SAC fulfilled, RH\u003csub\u003eice\u003c/sub\u003e \u0026gt; threshold RH\u003csub\u003eice\u003c/sub\u003e, and CIWC \u0026lt; 0.001 ppmv; or subvisible cirrus: SAC fulfilled, RH\u003csub\u003eice\u003c/sub\u003e \u0026gt; threshold RH\u003csub\u003eice\u003c/sub\u003e, and 0.001 ppmv \u0026pound; CIWC \u0026lt; 1.0 ppmv). The results shown in Figure 5a clearly indicate that in the Northern midlatitudes areas of potential stronger climate impact by contrail-cirrus (red bars) occur only in less than 15% of all observed cases for PCCR conditions and in less than 10% for ISSR conditions, and are almost not observed over Southeast Asia. For a lower CIWC threshold for cloud visibility of 0.1 ppmv, the fraction of areas of potential stronger climate impact decreases to less than 10% for PCCR and about 5% for ISSR conditions, while doubling the CIWC threshold for cloud visibility to 2.0 ppmv has only a marginal impact; see Figure 5b for the North Atlantic region.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAccording to Figure 4, in-situ formed cirrus clouds in slow of fast updraft regions are responsible for the optically thin warming cirrus clouds, whereas optically thick liquid-origin cirrus clouds have a potential cooling effect. From a trajectory-based classification of ERA-Interim ice clouds in the region of the North Atlantic storm track\u003csup\u003e51\u003c/sup\u003e we conclude that at typical cruising altitude pressure levels between 200 and 245 hPa \u003csup\u003e14\u003c/sup\u003e, in-situ formed cirrus clouds with an associated stronger climate impact are more than twice as abundant as liquid-origin cirrus clouds above 300 hPa and reach near totality above 200 hPa, independent of the season. Thus, areas of a potentially stronger climate impact of contrail-cirrus can likely be associated with clear-sky and in-situ origin cirrus regions. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinally, Figure 6 displays the regional and seasonal distributions of PCCRs with potential stronger (panels a, c, e, and g) and weaker (panels b, d, f, and h) climate impacts, following the definitions above. In fall, winter and spring months, areas covered with natural thick cirrus predominate, where embedded contrail cirrus have a weaker climate impact. For contrail-cirrus embedded in subvisible cirrus with potential stronger climate impact the differences between seasons are less pronounced, but again with a slight tendency towards higher frequencies in winter and spring months. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConcluding, strong climate effects from contrail-cirrus do not occur that often, and when they do occur it is mostly in subvisible in-situ origin cirrus in winter/spring. This could be the focus of appropriate strategies to minimize aviation effects. Particularly the design of and decision on contrail avoidance strategies needs to include these findings, by combining cirrus cloud and humidity forecasts to exclude areas covered by visible cirrus from flight rerouting. This approach, combined with the option of considering PCCRs instead of ISSRs only, should help minimizing trade-off effects between rerouting of aircraft for contrail avoidance and additional fuel burn with associated CO\u003csub\u003e2\u003c/sub\u003e emissions\u003csup\u003e37\u003c/sup\u003e from the rerouting.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFlight rerouting strategies for reducing aviation\u0026rsquo;s climate impact seem to be most appropriate for the Northern Midlatitudes where civil aviation cruising levels largely overlap with the cold and humid air masses just below the tropopause region, thus allowing for contrail-cirrus formation in clear sky and inside subvisible cirrus. In contrast, for regions at lower latitudes the cruising levels are located farther away from the tropopause regions outside of the cold and humid air masses such that contrail-cirrus may form in almost all cases inside thick natural cirrus clouds. The resulting climate impact is likely smaller compared to the midlatitudes and the efficiency of flight rerouting for the reduction of aviation climate impact becomes debatable for these regions.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eIAGOS in-situ RH\u003csub\u003eice\u003c/sub\u003e and cloud datasets, ERA5 cloud ice water content\u003c/h2\u003e\n\u003cp\u003eThe analysed data set covers the period from June 2014 to December 2021 and contains in total more than 17\u0026acute;10\u003csup\u003e6\u003c/sup\u003e data points with each datapoint corresponding to 4 sec sampling time, or 1 km flown distance at an average cruising speed of 250 m s\u003csup\u003e-1\u003c/sup\u003e, respectively. Figure 1a shows the normalized data density per 5\u0026deg;x5\u0026deg; grid. Four regions of interest were identified for in-depth statistical analyses, with three of them located in the Northern midlatitudes (30\u0026ndash;60\u0026deg;N), namely Eastern North America (Region 1: 105\u0026ndash;65\u0026deg;W, 1.57\u0026acute;10\u003csup\u003e6\u003c/sup\u003e data points), the North Atlantic flight corridor (Region 2: 65\u0026ndash;5\u0026deg;W, 4.43\u0026acute;10\u003csup\u003e6\u003c/sup\u003e data points), and Western Europe (Region 3: 5\u0026deg;W\u0026ndash;30\u0026deg;E, 4.72\u0026acute;10\u003csup\u003e6\u003c/sup\u003e data points), and one in the Southeast Asian subtropics (Region 4: 0\u0026ndash;30\u0026deg;N, 45\u0026ndash;120\u0026deg;E, 6.14 \u0026acute;10\u003csup\u003e6\u003c/sup\u003e data points). The Southeast Asian tropical and subtropical region is of potential interest because of the high traffic density, though the cruise levels are farther below the tropopause level than in the midlatitudes where cruise altitudes are close to the tropopause; see Figure 1b.\u003c/p\u003e\n\u003cp\u003eThe combined IAGOS RH\u003csub\u003eice\u003c/sub\u003e, N\u003csub\u003eice\u003c/sub\u003e, and ERA5 CIWC dataset spans from June 2014 to December 2021. To restrict the analysis on the air masses of the upper troposphere and the tropopause layer with respect to the thermal tropopause (TTP) and to focus on ice clouds only, data were selected based on the following criteria\u003csup\u003e20\u003c/sup\u003e:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003epressure below 350 hPa (approx. 8.1 km) to focus on cruise altitude,\u003c/li\u003e\n \u003cli\u003epressure above p\u003csub\u003eTTP\u003c/sub\u003e \u0026ndash; 15 hPa to exclude dry stratospheric air masses that are too dry for cirrus clouds, and\u003c/li\u003e\n \u003cli\u003etemperature below 235 K (the threshold for spontaneous freezing of water droplets) to exclude air masses containing supercooled liquid water droplets.\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eAccording to WMO\u003csup\u003e43\u003c/sup\u003e, the thermal tropopause (TTP) is defined as the lowest level at which the lapse rate decreases to 2\u0026nbsp;K km\u003csup\u003e-1\u003c/sup\u003e or less. In our study, vertical atmospheric layers relative to the thermal tropopause are defined as:\u003c/p\u003e\n\u003cp\u003eThermal tropopause layer TTP: p = p\u003csub\u003eTTP\u003c/sub\u003e \u0026plusmn;\u0026nbsp;15 hPa\u003c/p\u003e\n\u003cp\u003eUpper troposphere layer UT1: p\u003csub\u003eTTP\u003c/sub\u003e + 15 hPa\u0026nbsp;\u0026pound;\u0026nbsp;p \u0026lt; p\u003csub\u003eTTP\u003c/sub\u003e + 45 hPa\u003c/p\u003e\n\u003cp\u003eUpper troposphere layer UT2: p\u003csub\u003eTTP\u003c/sub\u003e + 45 hPa \u0026pound; p \u0026lt; p\u003csub\u003eTTP\u003c/sub\u003e + 75 hPa\u003c/p\u003e\n\u003cp\u003eUpper troposphere layer UT3: p\u003csub\u003eTTP\u003c/sub\u003e + 75 hPa \u0026pound; p \u0026lt; p\u003csub\u003eTTP\u003c/sub\u003e +105 hPa\u003c/p\u003e\n\u003cp\u003eThe separation of UT layers was only used for the analysis of the ISSR occurrence with altitude (Figure 1b). For all other analyses, the pressure band reaching from 350 hPa down to p\u003csub\u003eTTP\u003c/sub\u003e -15 hPa was considered.\u003c/p\u003e\n\u003cp\u003eWe quantified the contrail formation conditions for all sampled air masses by applying the Schmidt-Appleman criterion (SAC)\u003csup\u003e8\u003c/sup\u003e, and\u0026nbsp;added the information on cloudiness by applying the herein developed cloud categorisation based on ERA5 Cloud Ice Water Content (CIWC). The observations were then sub-divided into clear-sky and in-cloud sequences. For each subset, conditions were rated as \u0026ldquo;no contrail formation\u0026rdquo; if SAC was not fulfilled, as favouring the formation of \u0026ldquo;short-lived contrails\u0026rdquo; if SAC was fulfilled and RH\u003csub\u003eice\u003c/sub\u003e \u0026lt; threshold RH\u003csub\u003eice\u003c/sub\u003e (threshold for contrail-cirrus occurrence), and as favouring the formation of \u0026ldquo;contrail-cirrus\u0026rdquo; if SAC was fulfilled and RH\u003csub\u003eice\u003c/sub\u003e \u0026gt; threshold RH\u003csub\u003eice\u003c/sub\u003e. The complete overview over the statistical analysis is compiled in Table S1 of the supplementary information.\u003c/p\u003e\n\u003cp\u003eThe in-situ RH\u003csub\u003eice\u003c/sub\u003e data are calculated from direct measurements of relative humidity with respect to liquid water (RH\u003csub\u003eliq\u003c/sub\u003e) and ambient temperature by the IAGOS Capacitive Hygrometer (ICH). The ICH combining a thin-film HUMICAP\u0026reg; capacitive sensor (Vaisala) with a platinum resistance temperature sensor Pt100, is calibrated in the laboratory against an MBW dew-point chilled mirror analyser for RH\u003csub\u003eliq\u003c/sub\u003e \u003csup\u003e52\u003c/sup\u003e. The conversion to RH\u003csub\u003eice\u003c/sub\u003e uses the equations by Sonntag\u003csup\u003e53\u003c/sup\u003e. A comparison of the ICH with the\u0026nbsp;research-grade\u0026nbsp;FISH fluorescence hygrometer indicates an uncertainty of \u0026plusmn;(5-6)% RH\u003csub\u003eliq\u003c/sub\u003e and \u0026plusmn;0.5 K \u003csup\u003e54\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe IAGOS cloud dataset includes ice cloud particle number density (N\u003csub\u003eice\u003c/sub\u003e) measurements from the Backscatter Cloud Probe BCP, \u003csup\u003e55\u003c/sup\u003e, which is an optical particle spectrometer. The BCP detects ice particles of sizes ranging from 5 to 75 \u0026micro;m optical equivalent diameter but does not cover larger ice particles (D \u0026gt; 75 \u0026micro;m) nor thin cirrus clouds (N\u003csub\u003eice\u003c/sub\u003e \u0026lt; 0.01 cm\u003csup\u003e-3\u003c/sup\u003e) and thus misses almost all thin cirrus clouds\u003csup\u003e44\u003c/sup\u003e. In our study, it was therefore not used for the cloud categorisation. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe along-track cloud ice water content (CIWC) is derived by collocating the 5\u003csup\u003eth\u003c/sup\u003e version of ECMWF\u0026rsquo;s atmospheric reanalysis meteorological fields, ERA5\u003csup\u003e56\u003c/sup\u003e, to IAGOS flight trajectories. The interpolation of ERA5 data at flight positions were conducted at a downgraded spatial and temporal resolution of 1\u0026deg;\u0026times;1\u0026deg; longitude/latitude resolution and 6h time resolution. The 137 levels in the vertical from the surface to 0.01\u0026nbsp;hPa remained unchanged. The CIWC at T\u003csub\u003eair\u0026nbsp;\u003c/sub\u003e\u0026lt; 235 K is treated as ice water content and serves as the cloud indicator, given that supercooled liquid water droplets freeze instantaneously into ice crystals at temperatures below 235 K. Along-track CIWC, air temperature T\u003csub\u003eERA5\u003c/sub\u003e and specific humidity SH are extracted using a weighted-mean method, i.e., selecting the ERA5 grid points that are temporally and spatially closest to the IAGOS observations and calculate the mean values based on their proximity. Additionally, the WMO thermal tropopause height \u003csup\u003e43\u003c/sup\u003e is calculated along flight tracks to distinguish between upper tropospheric and lower stratospheric air masses.\u003c/p\u003e\n\u003ch2\u003eERA5 CIWC - based cloud categorisation\u003c/h2\u003e\n\u003cp\u003eTo our best knowledge, the ERA5 CIWC has not yet been applied as a cloud indicator to field observations, apart from climatological comparisons with satellite observations\u003csup\u003e57\u003c/sup\u003e, or a machine-learning approach towards adjusting ERA5 humidity data to IAGOS observations\u003csup\u003e58\u003c/sup\u003e.\u0026nbsp;In this study, we establish an appropriate CIWC threshold to indicate in-cloud conditions by evaluating ERA5 CIWC against the high-sophisticated NIXE-CAPS\u003csup\u003e10\u003c/sup\u003e cloud probe and validate the selected threshold by the in-situ measured RH\u003csub\u003eice\u003c/sub\u003e distributions. The NIXE-CAPS instrument measured cloud particle number density, size, shape, and ice water content as part of the Mid-Latitude CIRRUS (ML-CIRRUS) field study conducted over Central and Western Europe and the Northeast Atlantic\u003csup\u003e59\u003c/sup\u003e.\u0026nbsp;NIXE-CAPS detects ice particles of diameters between 3 \u0026mu;m and 937 \u0026mu;m at number concentrations N\u003csub\u003eice\u003c/sub\u003e as low as 10\u003csup\u003e-4\u003c/sup\u003e cm\u003csup\u003e-3\u003c/sup\u003e. This extensive measurement range makes the NIXE-CAPS highly suitable for the definition of the cloud indicator.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePanel (a) of\u0026nbsp;Figure 7\u0026nbsp;displays the probability distribution of ERA5 RH\u003csub\u003eice\u003c/sub\u003e in relation to various ERA5 CIWC thresholds, at cruise altitude (\u0026lt; 350 hPa and T\u003csub\u003eamb\u0026nbsp;\u003c/sub\u003e\u0026lt; 235 K) with RH\u003csub\u003eice\u003c/sub\u003e and CIWC, collocated to ML-CIRRUS flight trajectories. The blue curve, representing ERA5 CIWC = 0.000 ppmv, illustrates ideal clear-sky conditions, where ice-supersaturation is rarely observed. As the CIWC threshold increases to 0.001, 0.005, and finally 0.05 ppmv, the frequency of ice-supersaturation gradually rises, and a \u0026ldquo;shoulder\u0026rdquo; of the RH\u003csub\u003eice\u003c/sub\u003e distribution function develops around RH\u003csub\u003eice\u003c/sub\u003e = 100%.\u003c/p\u003e\n\u003cp\u003eThe NIXE-CAPS instrument has a lower detection limit for CIWC of 0.05 ppmv \u003csup\u003e60\u003c/sup\u003e. In theory, regions with NIXE CIWC \u0026lt; 0.05 ppmv should be classified as cloud-free. However, the noticeable local maximum in the 80\u0026ndash;120% RH\u003csub\u003eice\u003c/sub\u003e range (black curve in Figure 7) for air masses classified as cloud free (NIXE CIWC \u0026lt; 0.05 ppmv), suggests that NIXE-CAPS may have missed detecting some cloud particles on the sampled air which caused the increased CIWC in this nominally cloud-free air masses. When the ERA5 CIWC threshold is raised to 0.05 ppmv (red curve in Figure 7a), again the occurrence of ice supersaturation significantly increases compared to lower CIWC thresholds. Consequently, we adopt an ERA5 CIWC threshold of 0.001 ppmv as an indicator of cloud presence in the reanalysis data, because for CIWC \u0026sup3; 0.001 ppmv, the typical \u0026ldquo;shoulder\u0026rdquo; of the RH\u003csub\u003eice\u003c/sub\u003e PDF at ice saturation starts to emerge.\u003c/p\u003e\n\u003cp\u003eThe relation between a local maximum in the RH\u003csub\u003eice\u003c/sub\u003e distribution function around 100% and the presence of ice crystals is validated by simulating the occurrence frequencies of RH\u003csub\u003eice\u003c/sub\u003e at different thresholds of ice crystal number concentrations, using the Ice module within the Chemical Lagrangian Model of the Stratosphere CLaMS\u003csup\u003e61\u003c/sup\u003e. These simulations are based on ML-Cirrus flight trajectories. CLaMS-ice employs a two-moment ice microphysics scheme, incorporating both heterogeneous and homogeneous freezing mechanisms. The model runs 24-hour forward with boundary conditions provided by\u0026nbsp;reanalysis data.\u0026nbsp;Clear-sky air masses are defined as those that did not encounter cloud formation during the backward trajectories. As shown in\u0026nbsp;Figure 7b, increasing the N\u003csub\u003eice\u003c/sub\u003e threshold from 0.002 cm⁻\u0026sup3; to 0.05 cm⁻\u0026sup3; enhances the fraction of ice supersaturation, with the typical local maximum emerging at RH\u003csub\u003eice\u003c/sub\u003e @ 100%. The high occurrence of low RH\u003csub\u003eice\u003c/sub\u003e values in Figure 7b arises from the inclusion of stratospheric air masses within the 150\u0026ndash;500 hPa vertical range, which is not the case for the air mases analysed in Figure 7a, which are restricted to the tropopause layer and below.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eCloud optical depth estimates\u003c/h2\u003e\n\u003cp\u003eTo estimate the cloud optical depth from the cloud ice water content, we used the relationships between cloud optical depth, CIWC and ice crystal effective diameter (D\u003csub\u003eeff\u003c/sub\u003e) as provided by Equation (3.9a) of Fu\u003csup\u003e62\u003c/sup\u003e and by Equation (3) of Gayet\u003csup\u003e63\u003c/sup\u003e, and assumed a vertical extension of the cloud of 500 m, which is a typical extension for a fully developed contrail \u003csup\u003e64\u003c/sup\u003e. The conversion of CIWC from ppmv into g m\u003csup\u003e-3\u003c/sup\u003e was conducted for fixed temperature values (in Kelvin) and a related mean pressure inside cirrus clouds following the empirical relationship p\u003csub\u003emean\u003c/sub\u003e = 2.89319\u0026acute;10\u003csup\u003e-4\u003c/sup\u003e \u0026acute;T\u003csup\u003e2.66906\u003c/sup\u003e\u0026nbsp; - 247.724 hPa \u003csup\u003e65\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eEffective diameter values D\u003csub\u003eeff\u003c/sub\u003e were taken from sources based on observations, from which we selected D\u003csub\u003eeff\u003c/sub\u003e = 10 \u0026micro;m for a contrail at T = 217 K and older than 30 minutes\u003csup\u003e66\u003c/sup\u003e, D\u003csub\u003eeff\u003c/sub\u003e = 20 \u0026micro;m for a young cirrus at 10.6 km altitude and T = 213 K \u003csup\u003e66\u003c/sup\u003e, and D\u003csub\u003eeff\u003c/sub\u003e = 40 \u0026micro;m as the most probable effective diameter for cirrus clouds with CIWC values between 0.1 ppmv and 1.0 ppmv at Northern Midlatitudes\u003csup\u003e14, 67\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe discrimination threshold between subvisible and visible cirrus was taken from two sources. From lidar observations\u003csup\u003e68\u003c/sup\u003e an overall optical depth in the visible spectral range of 0.03 is generally accepted as visibility threshold. From theoretical calculations\u003csup\u003e69\u003c/sup\u003e, a limiting extinction coefficient of 2 \u0026ndash; 3\u0026acute;10\u003csup\u003e-5\u003c/sup\u003e m\u003csup\u003e-1\u003c/sup\u003e is reported, which turns into an optical depth of 0.01 to 0.015 for a cloud of 500 m vertical extension.\u003c/p\u003e\n\u003cp\u003eThe results shown in Figure 8 indicate that a CIWC of 1.0 ppmv, a vertical extension of 500 m, and a temperature range from 205 K to 230 K produce a cloud optical thickness between the visibility thresholds of the two sources, independent of the selected relationship between optical depth, CIWC and D\u003csub\u003eeff\u003c/sub\u003e. Therefore, we used a CIWC value of 1.0 ppmv to distinguish subvisible from visible clouds.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eIAGOS data are available through the IAGOS Data Portal https://doi.org/10.25326/20 .\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eIAGOS data were created with support from the European Commission, national agencies in Germany (BMBF), France (MESR), and the UK (NERC), and the IAGOS member institutions (http://www.iagos.org/partners). The participating airlines (Deutsche Lufthansa, Air France, China Airlines, Hawaiian Airlines, Air Canada, Iberia, Discover, Cathay Pacific) support IAGOS by carrying the measurement equipment free of charge. The data are available at http://www.iagos.fr thanks to additional support from AERIS. PS acknowledges support by the DFG within the Transregional Collaborative Research Centre TRR 301 TPChange, project ID 428312742, project B7. YL acknowledges support from the SESAR 3 Joint Undertaking under grant agreement No 101114613 (CICONIA) under European Union\u0026rsquo;s Horizon Europe research and innovation programme.\u003c/p\u003e\n\u003ch2\u003eAuthor Contributions\u003c/h2\u003e\n\u003cp\u003eAP and MK designed the study and coordinated the analyses and interpretation. NFK performed the IAGOS data analyses. The figures in the manuscript were prepared by AP and NFK. PS contributed the calculations of the cloud optical properties. YL evaluated the ERA5 cloud categorisation and prepared the IAGOS water vapour data set used for this study. SR performed the quality assessments of the IAGOS water vapour data. AP and MK wrote the manuscript with assistance from PS, YL, SR, SC and AW.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003ch2\u003eAdditional information\u003c/h2\u003e\n\u003cp\u003eSupplementary information: The online version contains supplementary material available at \u0026hellip;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLee DS, Allen MR, Cumpsty N, Owen B, Shine KP, Skowron A. 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Proposals focus on avoiding humid areas needed for contrail formation, but neglect that they are often located inside of cirrus clouds, which will change the contrail climate effects significantly. Our analysis of seven years of humidity observations by instrumented passenger aircraft shows that only 20\u0026ndash;30% of air masses in major flight areas can develop persistent contrails, of which more than 83% are covered by cirrus. Thin, subvisible cirrus, which contribute 5\u0026ndash;15% to all cirrus, amplify the warming effect of contrails, while in thicker, visible cirrus warming is only slightly enhanced, or sometimes even reversed to cooling. We suggest using combined cirrus and humidity forecasts to exclude areas with visible cirrus from flight rerouting, jointly with a thorough assessment of contrail vs. CO\u003csub\u003e2\u003c/sub\u003e climate effects, considering the interaction of persistent contrails and cirrus.\u003c/p\u003e","manuscriptTitle":"Contrails inside cirrus clouds predominate with uncertain climate impact","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-11 08:46:51","doi":"10.21203/rs.3.rs-6837438/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"94e98313-4ec6-46bc-afbb-7a9de8568717","owner":[],"postedDate":"June 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":49659218,"name":"Atmospheric Sciences"}],"tags":[],"updatedAt":"2025-06-11T08:46:52+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-11 08:46:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6837438","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6837438","identity":"rs-6837438","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}