Persistent contrails and contrail cirrus are estimated to have a larger impact on climate than all CO2 emissions from global aviation since the introduction of jet engines. However, the measure for this impact, the effective radiative forcing (ERF) or radiative forcing (RF), suffers from uncertainties that are much larger than those for CO2. Despite ongoing research, the so called level of scientific understanding has not improved since the 1999 IPCC Special Report on Aviation and the Global Atmosphere. In this paper, the role of weather variability as a major component of the uncertainty range of contrail cirrus RF is examined. Using 10 years of MOZAIC flights and ERA-5 reanalysis data, we show that natural weather variability causes large variations in the instantaneous radiative forcing (iRF) of persistent contrails, which is a major source for uncertainty. Most contrails (about 80%) have a small positive iRF of up to 20 W m−2. IRF exceeds 20 W m−2 in about 10% of all cases but these have a disproportionally large climate impact, the remaining 10% have a negative iRF. The distribution of iRF values is heavily skewed towards large positive values that show an exponential decay. Monte Carlo experiments reveal the difficulty of determining a precise long-term mean from measurement or campaign data alone. Depending on the chosen sample size, calculated means scatter considerably, which is caused exclusively by weather variability. Considering that many additional natural sources of variation have been deliberately neglected in the present examination, the results suggest that there is a fundamental limit to the precision with which the RF and ERF of contrail cirrus can be determined. In our opinion, this does not imply a low level of scientific understanding; rather the scientific understanding of contrails and contrail cirrus has grown considerably over recent decades. Only the determination of global and annual mean RF and ERF values is still difficult and will probably be so for the coming decades, if not forever. The little precise knowledge of the RF and ERF values is, therefore, no argument to postpone actions to mitigate contrail’s warming impact.

Abstract. In this paper, the effects of ice-supersaturated regions and thin, subvisual cirrus clouds on lapse rates are examined. For that, probability distribution and density functions of the lapse rate and the potential temperature gradients from 10 years of measurement data from the MOZAIC/IAGOS project and ERA5 reanalysis data were produced, and an analysis of an example case of an ice-supersaturated region with a large vertical extent is performed. For the study of the probability distribution and density functions, a distinction is made between ice-subsaturated and ice-supersaturated air masses (persistent contrails) and situations of particularly high ice supersaturation that allow the formation of optically thick and strongly warming contrails. The estimation of the lapse rates involves two adjacent standard pressure levels of the reanalysis surrounding MOZAIC's measurement/flight points. If the upper of these levels is in the stratosphere, the distribution function for subsaturated cases shows much lower lapse rates than those of supersaturated cases. If all levels are in the troposphere, the distributions become more similar, but the average lapse rates are still higher in supersaturated than in subsaturated cases, and the distributions peak at higher values and are narrower in ice-supersaturated regions (ISSRs) than elsewhere. This narrowing is particularly pronounced if there is substantial supersaturation. For the examination of an example case, ERA5 data and forecasts from ICON-EU (DWD) are compared. ERA5 data, in particular, show a large ice-supersaturated region below the tropopause, which was pushed up by uplifting air, while the data of ICON-EU indicate areas of saturation. The lapse rate in this ice-supersaturated region (ISSR), which is large, is associated with clouds and high relative humidity. Supersaturation and cloud formation result from uplifting of air layers. The temperature gradient within an uplifting layer steepens, for both dry and moist air. As soon as condensation or ice formation starts in the upper part of a lifting layer, the release of latent heat begins to decrease the lapse rate, but radiation starts to act in the opposite direction, keeping the lapse rate high. The highest lapse rates close to the stability limit can only be reached in potentially unstable situations.

<p>In Switzerland hail regularly causes substantial damage to agriculture, cars, and infrastructure. However, addressing hail damage is challenging, as hail is related to severe thunderstorms, one of the most complex atmospheric phenomena due to its small spatial scale, vigorous development, and intricate physical interactions. In a changing climate, hail frequency and its patterns of occurrence may change, with potentially negative ramifications, e.g. when considering agricultural losses. According to the new Swiss hail climatologies (Madonna et al. 2018; Nisi et al. 2016; Nisi et al. 2020) there is a significant difference between the interannual hail variability on the north and south sides of the Alps. Understanding the drivers of this variability is essential for possible adaptation strategies. In contrast to North America, where important drivers of interannual variability of severe convection are well studied (see Tippett et al. 2015 and Allen et al. 2020), a comprehensive analysis of the year-to-year variability of hail in Switzerland has only been done for the last 20 years (in preparation by Katharina Schröer<sup>2</sup>). A long-term analysis, however, is still missing.</p> <p>Therefore, this study presents a daily hail time series for Northern and Southern Switzerland from 1950 to today. The time series is produced from radar hail proxies and ERA-5 reanalysis data. Daily POH (Probability of Hail) data from MeteoSwiss is used to identify haildays in the region north and south of the Alps (plus 140km radar buffer) from 2002 to 2021 for the hail months April - September. The decision hailday yes/no is based on surpassing a POH ≥ 80 for a certain minimum footprint area of the domains. Then, a logistic regression model is constructed for each domain to predict the occurrence of a hailday depending on various environmental variables and indices. 70 different variables were tested. The predictors were chosen based on model performance, collinearity, and expert judgement. With the two best models, haildays are reconstructed back to 1950 for each region. The time series is then used to study the local and remote drivers of interannual variability, e.g. central European weather types, large-scale variability patterns, etc., as well as to investigate past changes or shifts in hailstorm seasonality. With this knowledge, we could improve our understanding of the meteorological-climatological variability, and, with the help of climate scenarios, infer about possible changes in the future.</p> <p> </p>

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Climate-impacting contrails need ice (super-)saturation to persist longer than a few minutes. However, this simple criterion cannot be easily applied for the prediction of persistent contrails. The current weather forecast models, which lack humidity data for assimilation in the upper troposphere, have difficulties coping with the enormous variability and sharp gradients in the relative humidity field. Thus, ice supersaturation, which is an extremal state of relative humidity, is hard to forecast at a precise location and time to allow contrail-avoiding flight routing. In this paper, we investigate the possibility of using dynamical proxy variables for improved contrail prediction. This idea is guided by the fact that the probability of ice supersaturation differs in different dynamical regimes. Therefore, we determine probability distributions of temperature, water vapour concentration, vertical velocity, divergence, relative and potential vorticity, geopotential height, and lapse rate conditioned on three situations: (a) contrail persistence not possible; (b) contrail persistence possible; and (c) strongly warming persistent contrails possible. While the atmospheric variables are taken from reanalysis data, the conditions (a–c) are based on airborne measurement data and radiation quantities from the reanalysis. It turns out that the vorticity variables, and in particular geopotential and lapse rate, show quite distinct conditional probabilities, suggesting a possibility to base an improved forecast of persistent contrails not only on the traditional quantities of temperature and relative humidity, but on these dynamical proxies as well. Furthermore, we show the existence of long flight tracks with the formation of strongly warming contrails, which are probably embedded in larger ice-supersaturated regions with conditions that foster such contrails. For forecasting purposes, this is a beneficial property since the humidity forecast is easier on large, rather than small, spatial scales.