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Title: Process-oriented evaluation using ARM observations to improve clouds and radiation in a global atmospheric model

Abstract

The goal of the research is to improve understanding of cloud, radiation and precipitation processes and their representation in numerical models for weather and climate using observations from the ARM/ASR program. Global models need to represent all cloud types across different weather regimes from the tropics to the poles and ARM provides long-term observations at different geographical sites that cover these different regimes. Combined with satellite data to give a global context, the observations are used to evaluate the systematic errors in a global model for predictions of cloud, radiation and precipitation. The focus is on understanding the links to underlying physical processes to pinpoint the sources of error and improve the model representation of these processes. The research covers boundary layer cloud over the continental U.S., marine stratocumulus and shallow cumulus in the subtropics, mixed-phase clouds over the Arctic and Southern Ocean, and high-altitude cirrus ice clouds in the tropics. The model used is the operational global weather prediction system at the European Centre for Medium-range Weather Forecasts (ECMWF). The research has led to numerous developments, several of which have been implemented operationally leading to improvements in everyday forecasts. Many of the systematic errors are common across different modellingmore » systems and the wider implications from the research for other weather and climate models are highlighted.« less

Authors:
ORCiD logo;
Publication Date:
Research Org.:
ECMWF
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23). Climate and Environmental Sciences Division
Contributing Org.:
European Centre for medium-Range Weather Forecasts
OSTI Identifier:
1572091
Report Number(s):
DOE-ECMWF-0005259
DOE Contract Number:  
SC0005259
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Global atmospheric model Numerical weather prediction Cloud processes Radiation Precipitation Model Evaluation ARM observations Systematic errors ECMWF

Citation Formats

Forbes, Richard M, and Ahlgrimm, Maike. Process-oriented evaluation using ARM observations to improve clouds and radiation in a global atmospheric model. United States: N. p., 2019. Web.
Forbes, Richard M, & Ahlgrimm, Maike. Process-oriented evaluation using ARM observations to improve clouds and radiation in a global atmospheric model. United States.
Forbes, Richard M, and Ahlgrimm, Maike. Mon . "Process-oriented evaluation using ARM observations to improve clouds and radiation in a global atmospheric model". United States.
@article{osti_1572091,
title = {Process-oriented evaluation using ARM observations to improve clouds and radiation in a global atmospheric model},
author = {Forbes, Richard M and Ahlgrimm, Maike},
abstractNote = {The goal of the research is to improve understanding of cloud, radiation and precipitation processes and their representation in numerical models for weather and climate using observations from the ARM/ASR program. Global models need to represent all cloud types across different weather regimes from the tropics to the poles and ARM provides long-term observations at different geographical sites that cover these different regimes. Combined with satellite data to give a global context, the observations are used to evaluate the systematic errors in a global model for predictions of cloud, radiation and precipitation. The focus is on understanding the links to underlying physical processes to pinpoint the sources of error and improve the model representation of these processes. The research covers boundary layer cloud over the continental U.S., marine stratocumulus and shallow cumulus in the subtropics, mixed-phase clouds over the Arctic and Southern Ocean, and high-altitude cirrus ice clouds in the tropics. The model used is the operational global weather prediction system at the European Centre for Medium-range Weather Forecasts (ECMWF). The research has led to numerous developments, several of which have been implemented operationally leading to improvements in everyday forecasts. Many of the systematic errors are common across different modelling systems and the wider implications from the research for other weather and climate models are highlighted.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {10}
}

Technical Report:
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Works referenced in this record:

The Impact of Low Clouds on Surface Shortwave Radiation in the ECMWF Model
journal, November 2012


Introduction to CAUSES: Description of Weather and Climate Models and Their Near‐Surface Temperature Errors in 5 day Hindcasts Near the Southern Great Plains
journal, March 2018

  • Morcrette, C. J.; Van Weverberg, K.; Ma, H. ‐Y.
  • Journal of Geophysical Research: Atmospheres, Vol. 123, Issue 5
  • DOI: doi.org/10.1002/2017JD027199

CAUSES: Attribution of Surface Radiation Biases in NWP and Climate Models near the U.S. Southern Great Plains
journal, April 2018

  • Van Weverberg, K.; Morcrette, C. J.; Petch, J.
  • Journal of Geophysical Research: Atmospheres, Vol. 123, Issue 7
  • DOI: doi.org/10.1002/2017JD027188

Improving the Representation of Low Clouds and Drizzle in the ECMWF Model Based on ARM Observations from the Azores
journal, February 2014


Understanding Global Model Systematic Shortwave Radiation Errors in Subtropical Marine Boundary Layer Cloud Regimes
journal, August 2018

  • Ahlgrimm, Maike; Forbes, Richard M.; Hogan, Robin J.
  • Journal of Advances in Modeling Earth Systems, Vol. 10, Issue 8
  • DOI: doi.org/10.1029/2018MS001346

Regime dependence of ice cloud heterogeneity - a convective life-cycle effect?: Ice Cloud Heterogeneity
journal, October 2017

  • Ahlgrimm, Maike; Forbes, Richard M.
  • Quarterly Journal of the Royal Meteorological Society, Vol. 143, Issue 709
  • DOI: doi.org/10.1002/qj.3178

Regime dependence of cloud condensate variability observed at the Atmospheric Radiation Measurement Sites: Regime Dependence of Cloud Condensate Variability
journal, April 2016

  • Ahlgrimm, Maike; Forbes, Richard M.
  • Quarterly Journal of the Royal Meteorological Society, Vol. 142, Issue 697
  • DOI: doi.org/10.1002/qj.2783

ARM’s Impact on Numerical Weather Prediction at ECMWF
journal, April 2016


On the Representation of High-Latitude Boundary Layer Mixed-Phase Cloud in the ECMWF Global Model
journal, September 2014


CAUSES: On the Role of Surface Energy Budget Errors to the Warm Surface Air Temperature Error Over the Central United States
journal, March 2018