Members of the ARM Climate Research Facility’s science team are major contributors to radiation and cloud research. Scientists and investigators using ARM facilities publish about 150 refereed journal articles per year, and ARM Facility data are used in many studies published by other scientific organizations. These documented research efforts represent tangible evidence of the ARM Facility’s contribution to advances in almost all areas of atmospheric radiation and cloud research.
Research Highlights
Recent Highlights
Using ARM cloud observations to confront model cloud transitions
12 April 2018
Mechem, David B.
Supported by:
Research area: Cloud Processes
Low clouds are represented in Earth System Models (ESMs) using parameterizations that are often based on benchmark simulations from high-resolution process models. But how reliable are the cloud properties and processes produced by these models? A new paper explores model cloud and precipitation transitions in a highly variable meteorological environment [...]
The relative role of surface energy budget on the warm surface air temperature bias
11 April 2018
Klein, Stephen
Supported by:
Research area: Surface Properties
Scientists at Lawrence Livermore National Laboratory within the Atmospheric, Earth, and Energy Division, along with collaborators from the U.K. Met Office and other modeling centers around the world, organized an international multi-model intercomparison project, name CAUSES (Clouds Above the United States and Errors at the Surface), to identify possible causes [...]
Diagnosis of the summertime warm bias in CMIP5 climate models at ARM's SGP site
9 April 2018
Klein, Stephen; Xie, Shaocheng
Supported by:
Research area: Radiation Processes
Department of Energy scientists, along with collaborators from the U.K. Met Office, organized an international multi-model intercomparison project, named CAUSES (Clouds Above the United States and Errors at the Surface), to identify possible causes for the large warm surface air temperature bias seen in many weather forecast and climate model [...]