A-Train estimates of the sensitivity of warm rain likelihood and efficiency to cloud size, environmental moisture, and aerosols

Mapping Intimacies ◽

10.5194/acp-2020-754 ◽

2020 ◽

Author(s):

Kevin M. Smalley ◽

Anita D. Rapp

Keyword(s):

Cloud Water ◽

Cumulus Cloud ◽

Power Law Distribution ◽

Water Path ◽

Precipitation Efficiency ◽

Warm Rain ◽

Shallow Cumulus ◽

Rain Drop ◽

Increasing Precipitation ◽

Water Contents

Abstract. Precipitation efficiency has been found to play an important role in constraining the sensitivity of the climate through its role in controlling cloud cover, yet understanding of its controls are not fully understood. Here we use CloudSat observations to identify individual contiguous shallow cumulus cloud objects and compute the ratio of cloud water path to rain water path as a proxy for warm rain efficiency (WRE). Cloud objects are then conditionally sampled by cloud-top height, relative humidity, and aerosol optical depth (AOD) to analyze changes in WRE as a function of cloud size (extent). For a fixed cloud-top height, WRE increases with extent and environmental humidity following a double power-law distribution, as a function of extent. Similarly, WRE increases holding environmental moisture constant. There is surprisingly little relationship between WRE and AOD when conditioned by cloud-top height, suggesting that once rain drop formation begins, aerosols may not be as important for WRE as cloud size and depth. Consistent with prior studies, results show an increase in WRE with sea surface temperature. However, for a given depth and SST, WRE is also dependent on cloud size and becomes larger as cloud size increases. Given that larger objects become more frequent with increasing SST, these results imply that increasing precipitation efficiencies with SST are due not only to deeper clouds with greater cloud water contents, but also the propensity for larger clouds which may have more protected updrafts.

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A-Train estimates of the sensitivity of the cloud-to-rainwater ratio to cloud size, relative humidity, and aerosols

Atmospheric Chemistry and Physics ◽

10.5194/acp-21-2765-2021 ◽

2021 ◽

Vol 21 (4) ◽

pp. 2765-2779

Author(s):

Kevin M. Smalley ◽

Anita D. Rapp

Keyword(s):

Relative Humidity ◽

Cloud Water ◽

Power Law Distribution ◽

Precipitation Efficiency ◽

Warm Rain ◽

Shallow Cumulus ◽

Rain Drop ◽

Average Relative Humidity ◽

Increasing Precipitation ◽

Water Contents

Abstract. Precipitation efficiency has been found to play an important role in constraining the sensitivity of the climate through its role in controlling cloud cover, yet its controls are not fully understood. Here we use CloudSat observations to identify individual contiguous shallow cumulus cloud objects and compute the ratio of cloud water path to rainwater (WRR) path as a proxy for warm-rain efficiency. Cloud objects are then conditionally sampled by cloud-top height, relative humidity, and aerosol optical depth (AOD) to analyze changes in WRR as a function of cloud size (extent). For a fixed cloud-top height, WRR increases with extent and environmental humidity following a double power-law distribution, as a function of extent. Similarly, WRR increases, holding average relative humidity at or below 850 mb constant. There is little relationship between WRR and AOD when conditioned by cloud-top height, suggesting that, once rain drop formation begins, aerosols may not be as important for WRR as cloud size and depth. Consistent with prior studies, results show an increase in WRR with sea-surface temperature. However, for a given depth and SST, WRR is also dependent on cloud size and becomes larger as cloud size increases. Given that larger objects become more frequent with increasing SST, these results imply that increasing precipitation efficiencies with SST are due not only to deeper clouds with greater cloud water contents but also to the propensity for larger clouds which may have more protected updrafts.

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The Role of Cloud Size and Environmental Moisture in Shallow Cumulus Precipitation

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-19-0145.1 ◽

2020 ◽

Vol 59 (3) ◽

pp. 535-550

Author(s):

Kevin M. Smalley ◽

Anita D. Rapp

Keyword(s):

Satellite Observations ◽

Cumulus Cloud ◽

Power Law Distribution ◽

Cumulus Clouds ◽

Active Sensors ◽

Cloud Models ◽

Shallow Cumulus ◽

Shallow Clouds ◽

Entrainment Mixing

AbstractCloud models show that precipitation is more likely to occur in larger shallow clouds and/or in an environment with more moisture, in part as a result of decreasing the impacts of entrainment mixing on the updrafts. However, the role of cloud size in shallow cloud precipitation onset from global satellite observations has mostly been examined with precipitation proxies from imagers and has not been systematically examined in active sensors, primarily because of sensitivity limitations of previous spaceborne active instruments. Here we use the more sensitive CloudSat/CALIPSO observations to identify and characterize the properties of individual contiguous shallow cumulus cloud objects. The objects are conditionally sampled by cloud-top height to determine the changes in precipitation likelihood with increasing cloud size and column water vapor. On average, raining shallow cumulus clouds are typically taller by a factor of 2 and have a greater horizontal extent than their nonraining counterparts. Results show that for a fixed cloud-top height the likelihood of precipitation increases with increasing cloud size and generally follows a double power-law distribution. This suggests that the smallest cloud objects are able to grow freely within the boundary layer but the largest cloud objects are limited by environmental moisture. This is supported by our results showing that, for a fixed cloud-top height and cloud size, the precipitation likelihood also increases as environmental moisture increases. These results are consistent with the hypothesis that larger clouds occurring in a wetter environment may be better able to protect their updrafts from entrainment effects, increasing their chances of raining.

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The Response of Cloud-Precipitation Recycling in China to Global Warming

Remote Sensing ◽

10.3390/rs13081601 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1601

Author(s):

Qi Guo ◽

Xianjie Cao ◽

Jiening Liang ◽

Zhida Zhang ◽

Min Zhang ◽

...

Keyword(s):

Moisture Flux ◽

Northwest China ◽

Cloud Water ◽

Feedback Mechanism ◽

Climate Feedback ◽

Water Path ◽

Precipitation Efficiency ◽

Meteorological Observatory ◽

Cloud Water Path ◽

Moderate Resolution Imaging Spectroradiometer

Cloud water is an important geophysical quantity that connects the hydrological and radiation characteristics of climate systems and plays an essential role in the global circulation of the atmosphere, water, and energy. However, compared to the contribution of water vapor to precipitation, the understanding of cloud-precipitation transformation and its climate feedback mechanism remains limited. Based on precipitation and temperature datasets of the National Meteorological Observatory and MODIS (Moderate Resolution Imaging Spectroradiometer) satellite remote sensing products, the evolution characteristics of cloud water resources in China over the last twenty years of the 21st century were evaluated. Significant decreasing trends of −3.3 and −4.89 g/m2 decade-1 were found for both the liquid and ice water path. In humid areas with high precipitation, the cloud water path decreased fast. In semiarid areas with an annual precipitation ranging from 500–800 mm, the decreasing trend of the cloud water path was the lowest. The cloud-water period was calculated to represent the relative changes in clouds and precipitation. The national average cloud-water period in China is approximately 12.4 h, with obvious seasonal changes. Over the last 20 years, the cloud water path in dry regions decreased more slowly than that in wet regions, and the cloud-precipitation efficiency significantly increased, which narrowed the climate difference between the dry and wet regions. Finally, the mechanism of the cloud-water period evolution in the different regions were examined from the perspectives of the dynamic and thermal contributions, respectively. Due to the overall low upward moisture flux (UMF) in the dry region, the response of the cloud-water period to the lower tropospheric stability (LTS) mainly first increased and then decreased, which was the opposite in the wet region. The increase in cloud-precipitation efficiency in the dry region of Northwest China is accompanied by a continuous decrease in LTS. The different configurations of regional UMF and LTS play a crucial role in the evolution of cloud-precipitation, which can be used as a diagnostic basis to predict changes in the precipitation intensity to a certain extent.

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Evaluation of WRF-DART (ARW v3.9.1.1 and DART Manhattan release) multiphase cloud water path assimilation for short-term solar irradiance forecasting in a tropical environment

Geoscientific Model Development ◽

10.5194/gmd-12-3939-2019 ◽

2019 ◽

Vol 12 (9) ◽

pp. 3939-3954

Author(s):

Frederik Kurzrock ◽

Hannah Nguyen ◽

Jerome Sauer ◽

Fabrice Chane Ming ◽

Sylvain Cros ◽

...

Keyword(s):

Data Assimilation ◽

Weather Prediction ◽

Cloud Water ◽

Specific Humidity ◽

Reunion Island ◽

Short Term ◽

Water Path ◽

Réunion Island ◽

Cloud Water Path ◽

The Impact

Abstract. Numerical weather prediction models tend to underestimate cloud presence and therefore often overestimate global horizontal irradiance (GHI). The assimilation of cloud water path (CWP) retrievals from geostationary satellites using an ensemble Kalman filter (EnKF) led to improved short-term GHI forecasts of the Weather Research and Forecasting (WRF) model in midlatitudes in case studies. An evaluation of the method under tropical conditions and a quantification of this improvement for study periods of more than a few days are still missing. This paper focuses on the assimilation of CWP retrievals in three phases (ice, supercooled, and liquid) in a 6-hourly cycling procedure and on the impact of this method on short-term forecasts of GHI for Réunion Island, a tropical island in the southwest Indian Ocean. The multilayer gridded cloud properties of NASA Langley's Satellite ClOud and Radiation Property retrieval System (SatCORPS) are assimilated using the EnKF of the Data Assimilation Research Testbed (DART) Manhattan release (revision 12002) and the advanced research WRF (ARW) v3.9.1.1. The ability of the method to improve cloud analyses and GHI forecasts is demonstrated, and a comparison using independent radiosoundings shows a reduction of specific humidity bias in the WRF analyses, especially in the low and middle troposphere. Ground-based GHI observations at 12 sites on Réunion Island are used to quantify the impact of CWP DA. Over a total of 44 d during austral summertime, when averaged over all sites, CWP data assimilation has a positive impact on GHI forecasts for all lead times between 5 and 14 h. Root mean square error and mean absolute error are reduced by 4 % and 3 %, respectively.

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Understanding the Extratropical Liquid Water Path Feedback in Mixed-Phase Clouds with an Idealized Global Climate Model

Journal of Climate ◽

10.1175/jcli-d-21-0334.1 ◽

2022 ◽

pp. 1-48

Author(s):

Yi Ming

Keyword(s):

Water Content ◽

Liquid Water ◽

Climate Model ◽

Global Climate Model ◽

Cloud Water ◽

Mixed Phase ◽

Liquid Water Path ◽

Water Path ◽

Cloud Water Content ◽

Mixed Phase Clouds

Abstract A negative shortwave cloud feedback associated with higher extratropical liquid water content in mixed-phase clouds is a common feature of global warming simulations, and multiple mechanisms have been hypothesized. A set of process-level experiments performed with an idealized global climate model (a dynamical core with passive water and cloud tracers and full Rotstayn-Klein single-moment microphysics) show that the common picture of the liquid water path (LWP) feedback in mixed-phase clouds being controlled by the amount of ice susceptible to phase change is not robust. Dynamic condensate processes—rather than static phase partitioning—directly change with warming, with varied impacts on liquid and ice amounts. Here, three principal mechanisms are responsible for the LWP response, namely higher adiabatic cloud water content, weaker liquid-to-ice conversion through the Bergeron-Findeisen process, and faster melting of ice and snow to rain. Only melting is accompanied by a substantial loss of ice, while the adiabatic cloud water content increase gives rise to a net increase in ice water path (IWP) such that total cloud water also increases without an accompanying decrease in precipitation efficiency. Perturbed parameter experiments with a wide range of climatological LWP and IWP demonstrate a strong dependence of the LWP feedback on the climatological LWP and independence from the climatological IWP and supercooled liquid fraction. This idealized setup allows for a clean isolation of mechanisms and paints a more nuanced picture of the extratropical mixed-phase cloud water feedback than simple phase change.

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Improved rain-rate and drop-size retrievals from airborne and spaceborne Doppler radar

10.5194/acp-2017-280 ◽

2017 ◽

Author(s):

Shannon L. Mason ◽

J. Christine Chiu ◽

Robin J. Hogan ◽

Lin Tian

Keyword(s):

Size Distribution ◽

Drop Size ◽

Rain Rate ◽

Doppler Radar ◽

Number Concentration ◽

Doppler Velocity ◽

Light Rain ◽

Warm Rain ◽

Rain Drop ◽

Drop Number

Abstract. Satellite radar remote-sensing of rain is important for quantifying of the global hydrological cycle, atmospheric energy budget, and many microphysical cloud and precipitation processes; however, radar estimates of rain rate are sensitive to assumptions about the raindrop size distribution. The upcoming EarthCARE satellite will feature a 94-GHz Doppler radar alongside lidar and radiometer instruments, presenting opportunities for enhanced global retrievals of the rain drop size distribution. In this paper we demonstrate the capability to retrieve both rain rate and a parameter of the rain drop size distribution from an airborne 94-GHz Doppler radar using CAPTIVATE, the variational retrieval algorithm developed for EarthCARE radar–lidar synergy. For a range of rain regimes observed during the Tropical Composition, Cloud and Climate Coupling (TC4) field campaign in the eastern Pacific in 2007, we explore the contributions of Doppler velocity and path-integrated attenuation (PIA) to the retrievals, and evaluate the retrievals against independent measurements from a second, less attenuated, Doppler radar aboard the same aircraft. Retrieved drop number concentration varied over five orders of magnitude between light rain from melting ice, and warm rain from liquid clouds. Doppler velocity can be used to estimate rain rate over land, and retrievals of rain rate and drop number concentration are possible in profiles of light rain over land; in moderate warm rain, drop number concentration can be retrieved without Doppler velocity. These results suggest that EarthCARE rain retrievals facilitated by Doppler radar will make substantial improvements to the global understanding of the interaction of clouds and precipitation.

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Entrainment of aerosols and their activation in a shallow cumulus cloud studied with a coupled LCM–LES approach

Atmospheric Research ◽

10.1016/j.atmosres.2014.12.008 ◽

2015 ◽

Vol 156 ◽

pp. 43-57 ◽

Cited By ~ 27

Author(s):

F. Hoffmann ◽

S. Raasch ◽

Y. Noh

Keyword(s):

Cumulus Cloud ◽

Shallow Cumulus

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Comments on: Deconvolution of Boundary Layer Depth and Aerosol Constraints on Cloud Water Path in Subtropical Stratocumuli

10.5194/acp-2019-833-rc1 ◽

2019 ◽

Author(s):

Anonymous

Keyword(s):

Boundary Layer ◽

Cloud Water ◽

Layer Depth ◽

Water Path ◽

Cloud Water Path

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A Study of the Distribution and Variability of Cloud Water Using ISCCP, SSM/I Cloud Product, and Reanalysis Datasets

Journal of Climate ◽

10.1175/jcli-d-13-00031.1 ◽

2014 ◽

Vol 27 (9) ◽

pp. 3114-3128 ◽

Cited By ~ 6

Author(s):

Zhiwei Heng ◽

Yunfei Fu ◽

Guosheng Liu ◽

Renjun Zhou ◽

Yu Wang ◽

...

Keyword(s):

Cloud Water ◽

Positive Anomaly ◽

Liquid Water Path ◽

Water Path ◽

The North ◽

Increasing Trend ◽

Moderate Resolution ◽

Moderate Resolution Imaging Spectroradiometer ◽

Microwave Imager ◽

Ice Water

Abstract In this paper, the global distribution of cloud water based on International Satellite Cloud Climatology Project (ISCCP), Moderate Resolution Imaging Spectroradiometer (MODIS), CloudSat Cloud Profiling Radar (CPR), European Center for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim), and Climate Forecast System Reanalysis (CFSR) datasets is presented, and the variability of cloud water from ISCCP, the Special Sensor Microwave Imager (SSM/I), ERA-Interim, and CFSR data over the time period of 1995 through 2009 is discussed. The results show noticeable differences in cloud water over land and over ocean, as well as latitudinal variations. Large values of cloud water are mainly distributed over the North Pacific and Atlantic Oceans, eastern ITCZ, regions off the west coast of the continents as well as tropical rain forest. Cloud water path (CWP), liquid water path (LWP), and ice water path (IWP) from these datasets show a relatively good agreement in distributions and zonal means. The results of trend analyzing show an increasing trend in CWP, and also a significant increasing trend of LWP can be found in the dataset of ISCCP, ERA-Interim, and CFSR over the ocean. Besides the long-term variation trend, rises of cloud water are found when temperature and water vapor exhibit a positive anomaly. EOF analyses are also applied to the anomalies of cloud water, the first dominate mode of CWP and IWP are similar, and a phase change can be found in the LWP time coefficient around 1999 in ISCCP and CFSR and around 2002 in ERA-Interim.

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