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During the Arctic night, clouds regulate surface energy budgets through longwave warming alone. During fall, any increase in low‐level clouds will increase surface cloud warming and could potentially delay sea ice formation. While an increase in clouds due to fall sea ice loss has been observed, quantifying the surface warming is observationally challenging. Here, we use a new observational data set of surface cloud warming at instantaneous 330 m × 90 m spatial resolution. By instantaneously co‐locating surface cloud warming and sea ice observations in regions where sea ice varies, we find October large surface cloud warming values (>80 W m−2) are much more frequent (∼+50%) over open water than over sea ice. Notably, in November large surface cloud warming values (>80 W m−2) occur more frequently (∼+200%) over open water than over sea ice. These results suggest more surface warming caused by low‐level opaque clouds in the future as open water persists later into the fall. Plain Language Summary: Over the past 40 years, Arctic sea ice cover has decreased in all months of the year, but especially in late summer and early fall. Through their impact on energy budgets, clouds have the potential to increase or decrease sea ice decline. More low‐level clouds over open water than over sea ice during non‐summer seasons have already been observed. But quantifying their radiative effect remains challenging. Therefore, this study seeks to answer the following question: By how much late fall Arctic clouds can change surface warming in response to sea ice loss? Using cloud surface warming data at high spatio‐temporal resolution, we found that large surface cloud warming values, higher than 80 W m−2, occurs much more frequently over open water than over sea ice during October and November months. This suggests that Arctic clouds favor sea ice loss by delaying sea ice recovery. As the Arctic continues to warm up due to human activities, cloud surface warming will delay sea ice freeze‐up later into the fall and may amplify Arctic sea ice loss. Key Points: During October, large surface cloud warming with values higher than 80 W m−2 occurs ∼+50% more often over open water than over sea iceCompared to October, November large surface cloud warming (>80 W m−2) occurs even more frequently (∼+200%) over open water than over sea iceMore frequent large surface warming caused by low‐level opaque clouds occurs as open water persists later into the fall [ABSTRACT FROM AUTHOR]

We present the measurement principle and the optical design of a Quad Mach Zehnder (QMZ) interferometer as HSRL technique, allowing simultaneous measurements of particle backscattering and wind velocity. Key features of this concept is to operate with a multimodal laser and do not require any frequency stabilization. These features are relevant especially for space applications for which high technical readiness level is required.

Despite significant advances in atmospheric measurements and modeling, clouds response to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. Documenting how the cloud detailed vertical structure, the cloud cover and opacity evolve on a global scale over several decades is a necessary step towards understanding and predicting the cloud response to climate warming. Among satellite-based remote sensing techniques, active sounding plays a special role, owing to its high vertical and horizontal resolution and high sensitivity. The launch of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) in 2006 started the era of space-borne optical active sounding of the Earth's atmosphere, which continued with the CATS (Cloud-Aerosol Transport System) lidar on-board ISS in 2015 and the Atmospheric Laser Doppler INstrument (ALADIN) lidar on-board Aeolus in 2018. The next important step is the ATmospheric LIDar (ATLID) instrument from the EarthCARE mission expected to launch in 2023. With ATLID, the scientific community will continue receiving invaluable vertically resolved information of atmospheric optical properties needed for the estimation of cloud occurrence frequency, thickness, and height. In this article, we define the ATLID Climate Product, Short-Term (CLIMP-ST) and ATLID Climate Product, Long-Term (CLIMP-LT). The purpose of CLIMP-ST is to help evaluate the description of cloud processes in climate models, beyond what is already done with existing space lidar observations, thanks to ATLID new capabilities. The CLIMP-LT will merge the ATLID cloud observations with previous space lidar observations to build a long-term cloud lidar record useful to evaluate the cloud climate variability predicted by climate models. We start with comparing the cloud detection capabilities of ATLID and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) in day- and night-time, on a profile-to-profile basis in analyzing virtual ATLID and CALIOP measurements over synthetic cirrus and stratocumulus cloud scenes. We show that solar background noise affects the cloud detectability in daytime conditions differently for ATLID and CALIPSO. We found that the simulated daytime ATLID measurements have lower noise than the CALIOP day-time simulated measurements. This allows lowering the cloud detection thresholds for ATLID compared to CALIOP and enables ATLID to detect optically thinner clouds than CALIOP in daytime at high horizontal resolution without false cloud detection. These lower threshold values will be used to build the ATLID-ST. Therefore, CLIMP-ST should provide an advance to evaluate optically thin clouds like cirrus or ice polar clouds in climate models compared to the current existing capability. We also found that ATLID and CALIPSO may detect similar clouds if we convert ATLID 355 nm profiles to 532 nm profiles and apply the same cloud detection thresholds as the ones used in GOCCCP (GCM Oriented Calipso Cloud Product). Therefore, this approach will be used to build the CLIMP-LT. The CLIMP-LT data will be merged with the GOCCP data to get a long-term (2006–2030's) cloud climate record. Finally, we investigate the detectability of cloud changes induced by human-caused climate warming within a virtual long-term cloud monthly gridded lidar dataset over the 2008–2034 period that we obtained from two ocean-atmosphere-coupled climate models coupled with a lidar simulator. We found that a long-term trend of opaque cloud cover should emerge from short-term natural climate variability after 4 to 7 years of ATLID measurements (merged with CALIPSO measurements) according to predictions from the considered climate models. We conclude that a long-term lidar cloud record build from the merge of the actual ATLID-LT data with CALIPSO-GOCCP data will be a useful tool to monitor cloud changes and to evaluate the realism of the cloud changes predicted by climate models. [ABSTRACT FROM AUTHOR]

Aerosols have a large impact on climate, air quality, and biogeochemical cycles. Their concentrations are highly variable in space and time, and a key variability is in their vertical distribution, because it influences atmospheric heating profiles, aerosols life-time and, as a result, surface concentrations, and because it has an impact on aerosol-cloud interactions. On the side of model-oriented aerosols research, using a lidar aerosol simulator ensures consistent comparisons between the modeled aerosols and the observed aerosols. In the current study, we present the lidar aerosol simulator implemented within the COSPv2 satellite lidar simulator. We estimate the attenuated total backscattered signal (ATB) and the backscatter ratios (SR) that would be observed at 532 nm by the lidar CALIOP overflying the atmosphere predicted by the E3SMv1 climate model. The simulator performs the computations at the same vertical resolution as the CALIOP lidar, making use of aerosol optics from the E3SMv1 model as inputs, and assuming that aerosols are uniformly distributed horizontally within each model grid-box. It applies a cloud masking and an aerosol detection threshold, to get the ATB and SR profiles that would be observed above clouds by CALIOP with its actual aerosol detection capability. Our comparison shows that the aerosol distribution simulated at a seasonal timescale is generally in good agreement with observations, with however a discrepancy in the Southern Hemisphere, as the observed SR maximum is not reproduced in simulations there. Comparison between cloud-screened and non cloud-screened computed SRs shows little differences, indicating that the cloud screening by potentially incorrect model clouds does not affect the mean aerosol signal averaged over a season. Consequently, the differences between observed and simulated SR values are not due to sampling errors, and allow to point out some weaknesses in the aerosol representation in models. The use of lidar observations at several wavelengths can give further indication on the nature of the aerosols that need to be improved. [ABSTRACT FROM AUTHOR]

This study examines how satellite observed relative humidity (RH) profiles, cloud covers, and cloud altitudes vary with sea surface temperature (SST) in low cloud regions on different temporal and spatial scales over the tropical oceans (30°N–30°S). We split low clouds into optically opaque and optically thin clouds and characterize for the first time their altitude variations with SST using space lidar observations. On the process scale, the median instantaneous observations at high spatial resolution show simultaneously decreasing low opaque cloud top altitude, decreasing low opaque cloud cover, increasing middle‐tropospheric RH, and decreasing lower‐tropospheric RH with SST. Collectively, these observational results suggest decreasing opaque marine boundary layer cloud cover and enhanced mixing between the middle and lower troposphere with SST on the process scale, consistent with previous Large‐Eddy Simulation studies. The covariations between opaque cloud cover and RH with SST are quantified on all time and space scales (from the process scale to the annual tropical mean scale). Meanwhile, on the process scale, low optically thin clouds, coexisting with opaque clouds, rise with SST (consistent with the literature mechanism), while the low optically thin cloud cover is insensitive to SST (not consistent with the literature mechanism). These results are then compared to a general circulation model, which captures the observed sign of change of opaque cloud cover and middle‐tropospheric RH with SST but fails to reproduce the observed vertical shrinkage of low opaque clouds with SST and the variations of low thin clouds with SST. Plain Language Summary: Tropical low clouds, those confined to the lowest atmospheric layer, cool the planet by reflecting incoming solar radiation. Even so, it is not clear how these clouds will respond to climate changes. Previous works have run model simulations with high resolution and found that the horizontal extent of these low clouds decreases as the sea surface temperature increases, because the warmer surface causes more mixing between the lowest atmospheric layer and the layer above. We use satellite observations of high resolution and find support for both decreasing low optically thick cloud cover (horizontal extent) and more mixing as sea surface temperature increases, and we find these results on both the short and small scales, where cloud and moisture processes occur, and in annual variations over the tropical oceans. We also observe that the top of these optically thick clouds lower when sea surface temperature increases. We then compare the observed results to a climate model, which reproduces the optically thick cloud cover decrease with sea surface temperature but fails to reproduce the observed lowering of low opaque cloud tops and the overall responses of low optically thin clouds. Key Points: Over sea surface temperature (SST) < 297 K low opaque clouds shrink vertically and horizontally with SST and the difference between low and mid‐tropospheric relative humidity decreasesOver SST > 298 K low opaque clouds lower in altitude with sea surface temperature, but keep about the same vertical extentOptically thin clouds are numerous in all tropical low cloud regions and rise with sea surface temperature [ABSTRACT FROM AUTHOR]

This study examines variations in high cloud properties and relative humidity (RH) with sea surface temperature (SST) over tropical oceans (30°N–30°S) using spaceborne lidar and microwave radiometer observations. The mean values over the tropics indicate that middle‐tropospheric RH increases, high cloud covers decrease and cloud altitudes rise with SST. These signatures are consistent with the hypotheses proposed in the literature. The analysis of this same data set but at the scale of local processes shows different behaviors for SSTs <302 K and SSTs >302 K. Between 299 and 302 K, middle‐tropospheric RH, opaque cloud cover, and cloud top altitude increase together with SST, while optically thin cloud cover decreases. Over SSTs >302 K, middle‐tropospheric RH, opaque cloud cover, and opaque cloud top altitude decrease with SST, while the cover of optically thin clouds increases. Interestingly, the altitude of high clouds (not the cloud top) increases monotonically with SST from 299 to 305 K on a range of space and time scales, and the altitude of optically thin clouds remains higher than that of opaque clouds. The observed relationships on different time and space scales are compared to simulations of a global atmospheric model. Despite systematic biases, the model reproduces the sensitivity of the middle‐tropospheric RH and cloud altitude to SST rather well but fails to reproduce the variations of the balance between high opaque cloud cover and high optically thin cloud cover. Plain Language Summary: High tropical clouds both cool and warm the planet by simultaneously reflecting incoming solar radiation and trapping energy that would have been emitted to space in cloud‐free skies. It is unclear how these clouds will evolve when the climate warms. We use satellite observations over the tropical oceans and find that tropical mean variations show that the high clouds associated with thunderstorms rise and stay at about the same temperature, while their horizontal extent decrease. On the short and small scales where cloud and moisture processes occur, we find however that these high clouds become more opaque to radiation with sea surface temperature (SST) when it is colder than 302 K, and less opaque to radiation over waters warmer than 302 K. Simultaneously, the temperature of these clouds slightly decreases when they rise. Because models are the only tool to predict future climate change, we then compare the observed results to a global atmospheric model. The model reproduces roughly the observed middle‐tropospheric humidity and cloud altitude variations but fails to reproduce the observed moisture variations in the lower and upper part of the troposphere, as well as the evolution of the opaque and thin high cloud covers with SST. Key Points: The altitude of high clouds increases with sea surface temperature (SST) in observations over a range of space and time scalesThe opaque high cloud cover and middle‐tropospheric relative humidity peak over SSTs of 302 K in the observationsA global model reproduces the observed sensitivity of cloud altitudes to SST, but not the cloud opacity [ABSTRACT FROM AUTHOR]