On the Statistical Distribution of Total Water in Cirrus Clouds

Kärcher, B.; Thornberry, T. D.; Krämer, M.; Jensen, E. J.

doi:10.1029/2018gl079780

Cited by 2 publications

(2 citation statements)

References 31 publications

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“…In each stochastic cirrus simulation, we choose initially ice‐saturated conditions, s 0 = 0, without variability in T 0 and q v ; the assumption of mean ice saturation within cirrus is supported by a number of observations (Kärcher et al., 2018; Krämer et al., 2009). We use a resolution in s of 0.02 to build discrete ISSs.…”

Section: Simulation Scenariosmentioning

confidence: 99%

Ice Supersaturation Variability in Cirrus Clouds: Role of Vertical Wind Speeds and Deposition Coefficients

Kärcher,

Jensen,

Pokrifka

et al. 2023

JGR Atmospheres

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Aircraft measurements reveal ice supersaturation statistics in cirrus (ISSs) with broad maxima around ice saturation and pronounced variance. In this study, processes shaping ISSs in midlatitude and tropical upper tropospheric conditions are systematically investigated. Water vapor deposition and sublimation of size‐resolved ice crystal populations are simulated in an air parcel framework. Mesoscale temperature fluctuations (MTFs) due to gravity waves force the temporal evolution of supersaturation. Various levels of background wave forcing and cirrus thickness are distinguished in stochastic ensemble simulations. Kinetic limitations to ice mass growth are brought about by supersaturation‐dependent deposition coefficients that represent efficient and inefficient growth modes as a function of ice crystal size. The simulations identify a wide range of deposition coefficients in cirrus, but most values stay above 0.01 such that kinetic limitations to water uptake remain moderate. Supersaturation quenching times are long, typically 0.5–2 hr. The wave forcing thus causes a remarkably large variability in ISSs and cirrus microphysical properties except in the thickest cirrus, producing ensemble‐mean ISSs in line with in‐situ measurements. ISS variance is controlled by MTFs and increases with decreasing cirrus integral radii. In comparison, the impact of ice crystal growth rates on ISSs is small. These results contribute to efforts directed at identifying and solving issues associated with ice‐supersaturated areas and non‐equilibrium cirrus physics in global models.

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Section: Simulation Scenariosmentioning

confidence: 99%

Ice Supersaturation Variability in Cirrus Clouds: Role of Vertical Wind Speeds and Deposition Coefficients

Kärcher,

Jensen,

Pokrifka

et al. 2023

JGR Atmospheres

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“…First, 3DCLOUD assimilates meteorological profiles (humidity, pressure, temperature, and wind velocity) and solves drastically simplified basic atmospheric equations in order to simulate 3D water content. Second, the Fourier filtering method is used to constrain the intensity of mean water content, ρ, β, and L out , which are values provided by the user (Hogan and Illingworth, 2003;Kärcher et al, 2018).…”

Section: Cloud-generating Modelmentioning

confidence: 99%

Incorporating EarthCARE observations into a multi-lidar cloud climate record: the ATLID (Atmospheric Lidar) cloud climate product

Chepfer¹,

Noël²,

Szczap³

2023

Atmos. Meas. Tech.

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Abstract. 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. The launch of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite in 2006 started the era of long-term spaceborne optical active sounding of Earth's atmosphere, which continued with the CATS (Cloud-Aerosol Transport System) lidar on board the International Space Station (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 (Earth Clouds, Aerosols and Radiation Explorer) mission, expected to launch in 2024. 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's new capabilities. The CLIMP-LT product 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 nighttime, on a profile-to-profile basis in analyzing virtual ATLID (355 nm) and CALIOP (532 nm) 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 simulated daytime CALIOP measurements. This allows for lowering the cloud detection thresholds for ATLID compared to CALIOP and enables ATLID to better 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 CLIMP-ST (Short-Term, related only to the ATLID observational period) product. This product should provide the ability to evaluate optically thin clouds like cirrus 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 GOCCP (GCM-Oriented CALIPSO Cloud Product; general circulation model). Therefore, this approach will be used to build the CLIMP-LT product. The CLIMP-LT data will be merged with the GOCCP data to get a long-term (2006–2030s) 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 years (possible lifetime) to 7 years (best-case scenario) for ATLID merged with CALIPSO measurements according to predictions from the considered climate models. We conclude that a long-term lidar cloud record built from the merging of the actual ATLID-LT data with CALIPSO-GOCCP data will be a useful tool for monitoring cloud changes and evaluating the realism of the cloud changes predicted by climate models.

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On the Statistical Distribution of Total Water in Cirrus Clouds

Cited by 2 publications

References 31 publications

Ice Supersaturation Variability in Cirrus Clouds: Role of Vertical Wind Speeds and Deposition Coefficients

Ice Supersaturation Variability in Cirrus Clouds: Role of Vertical Wind Speeds and Deposition Coefficients

Incorporating EarthCARE observations into a multi-lidar cloud climate record: the ATLID (Atmospheric Lidar) cloud climate product

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