U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights


Regime Dependence of Cloud Water Variability
Published: May 10, 2016
Posted: July 29, 2016

Using ARM data from multiple observational sites around the globe, scientists gain insights into cloud variability.

The Science
Physical processes, such as the interaction of clouds with sunlight or the rate at which clouds produce rain, depend on the amount of cloud water available locally at scales smaller than can be represented by current global model grid resolutions.

The Impact
Using observations from U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program sites across the world, scientists have improved understanding of how the amount of water in clouds varies at small scales. Based on these observations, a new way of describing how cloud water varies with cloud regime has been developed for use in global weather and climate models. The new parameterization will enable models to calculate more accurate process rates by providing a better representation of how the amount of cloud water varies within the cloud at these subgrid scales.

Summary
A number of different retrieval products for cloud condensate from ARM observations are assessed for five different geographical regions for multiple years and seasons. The retrieval reliability varies with cloud type, but for cloud categories largely unaffected by precipitation, a comparison across sites and longer time periods is possible. These observations confirm previously documented variability behavior as a function of cloud fraction, but also reveal a systematic regime dependence that is not captured by existing parameterizations. Condensate variability measured as a fractional standard deviation (FSD) in warm boundary-layer clouds is greater in the tropics than in the mid- and high-latitudes for scenes with comparable cloud type and fraction, with the observed FSD varying from 1.2 in the tropics to 0.4 in the Arctic. A parameterization of the cloud liquid condensate FSD based on the grid box mean total water amount and cloud fraction is formulated and shown to better capture the observed range of FSD values across the different geographical sites and seasons.

Contacts (BER PM)
Shaima Nasiri
ASR Program Manager
Shaima.Nasiri@science.doe.gov
Sally McFarlane
ARM Program Manager
Sally.McFarlane@science.doe.gov

 (PI Contact)
Maike Ahlgrimm
European Centre for Medium-Range Weather Forecasts
maike.ahlgrimm@ecmwf.int

Funding
This work was supported by the U.S. Department of Energy's Office of Science, Office of Biological and Environmental Research through the Atmospheric System Research (ASR) activity. Grant Number: DE-SC0005259. Data was obtained from the Atmospheric Radiation Measurement (ARM) Climate Research Facility.

Publication
Ahlgrimm, M., and R. M. Forbes. 2016. “Regime Dependence of Cloud Condensate Variability Observed at the Atmospheric Radiation Measurement Sites,” Quarterly Journal of the Royal Meteorological Society 142(697), 1605-17. DOI: 10.1002/qj.2783. (Reference link)

Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Research Area: Atmospheric System Research
  • Facility: DOE ARM User Facility

Division: SC-23.1 Climate and Environmental Sciences Division, BER

 

BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER

Recent Highlights

May 10, 2019
Quantifying Decision Uncertainty in Water Management via a Coupled Agent-Based Model
Considering risk perception can improve the representation of human decision-making processes in age [more...]

May 09, 2019
Projecting Global Urban Area Growth Through 2100 Based on Historical Time Series Data and Future Scenarios
Study provides country-specific urban area growth models and the first dataset on country-level urba [more...]

May 05, 2019
Calibrating Building Energy Demand Models to Refine Long-Term Energy Planning
A new, flexible calibration approach improved model accuracy in capturing year-to-year changes in bu [more...]

May 03, 2019
Calibration and Uncertainty Analysis of Demeter for Better Downscaling of Global Land Use and Land Cover Projections
Researchers improved the Demeter model’s performance by calibrating key parameters and establi [more...]

Apr 22, 2019
Representation of U.S. Warm Temperature Extremes in Global Climate Model Ensembles
Representation of warm temperature events varies considerably among global climate models, which has [more...]

List all highlights (possible long download time)