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The ARM Cloud Radar Simulator for Global Climate Models: A New Tool for Bridging Field Data and Climate Models

Journal Article · · Bulletin of the American Meteorological Society
 [1];  [1];  [1];  [2];  [3];  [4];  [5];  [5];  [6];  [7];  [1];  [8];  [9];  [5];  [10];  [10];  [10]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Univ. of Washington, Seattle, WA (United States)
  3. Stony Brook Univ., NY (United States)
  4. Pennsylvania State Univ., University Park, PA (United States)
  5. Brookhaven National Lab. (BNL), Upton, NY (United States)
  6. Univ. of Colorado, Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences (CIRES); National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States)
  7. Met Office Hadley Centre for Climate Science and Services, Exeter (United Kingdom)
  8. Colorado State Univ., Fort Collins, CO (United States). Cooperative Inst. for Research in the Atmosphere
  9. Argonne National Lab. (ANL), Argonne, IL (United States)
  10. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
+ Show Author Affiliations

Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept of instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to facilitate and to improve the comparison of modeled clouds with observations. Many simulators have been (and continue to be) developed for a variety of instruments and purposes. Finally, a community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Kay et al. 2012; Klein et al. 2013; Suzuki et al. 2013; Zhang et al. 2010).

Research Organization:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Grant/Contract Number:
SC0012704; AC52-07NA27344; AC02-06CH11357
OSTI ID:
1376180
Alternate ID(s):
OSTI ID: 1422299
OSTI ID: 1422585
OSTI ID: 1438806
Report Number(s):
BNL--114163-2017-JA; KP1701000
Journal Information:
Bulletin of the American Meteorological Society, Journal Name: Bulletin of the American Meteorological Society Journal Issue: 1 Vol. 99; ISSN 0003-0007
Publisher:
American Meteorological SocietyCopyright Statement
Country of Publication:
United States
Language:
English

References (15)

An improved hindcast approach for evaluation and diagnosis of physical processes in global climate models: AN IMPROVED HINDCAST APPROACH journal November 2015
The diurnal cycle of clouds and precipitation at the ARM SGP site: Cloud radar observations and simulations from the multiscale modeling framework journal July 2017
Evaluating cloud tuning in a climate model with satellite observations: EVALUATION OF CLOUD TUNING journal August 2013
Are climate model simulations of clouds improving? An evaluation using the ISCCP simulator: EVALUATING CLOUDS IN CLIMATE MODELS journal February 2013
The ERA-Interim reanalysis: configuration and performance of the data assimilation system journal April 2011
Global hydrometeor occurrence as observed by CloudSat: Initial observations from summer 2006: CLOUDSAT HYDROMETEOR OCCURRENCE journal May 2007
A comparison of simulated cloud radar output from the multiscale modeling framework global climate model with CloudSat cloud radar observations journal January 2009
Evaluation of tropical cloud and precipitation statistics of Community Atmosphere Model version 3 using CloudSat and CALIPSO data journal January 2010
Objective Determination of Cloud Heights and Radar Reflectivities Using a Combination of Active Remote Sensors at the ARM CART Sites journal May 2000
Hydrometeor Detection Using Cloudsat —An Earth-Orbiting 94-GHz Cloud Radar journal April 2008
A Technique for the Automatic Detection of Insect Clutter in Cloud Radar Returns journal September 2008
COSP: Satellite simulation software for model assessment journal August 2011
THE CLOUDSAT MISSION AND THE A-TRAIN: A New Dimension of Space-Based Observations of Clouds and Precipitation journal December 2002
A Multipurpose Radar Simulation Package: QuickBeam journal November 2007
Exposing Global Cloud Biases in the Community Atmosphere Model (CAM) Using Satellite Observations and Their Corresponding Instrument Simulators journal August 2012

Cited By (2)

An Overview of the Atmospheric Component of the Energy Exascale Earth System Model journal August 2019
(GO) 2 -SIM: a GCM-oriented ground-observation forward-simulator framework for objective evaluation of cloud and precipitation phase journal January 2018

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Related Subjects

54 ENVIRONMENTAL SCIENCES