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Title: Final Technical Report for "Reducing tropical precipitation biases in CESM"

Abstract

In state-of-the-art climate models, each cloud type is treated using its own separate cloud parameterization and its own separate microphysics parameterization. This use of separate schemes for separate cloud regimes is undesirable because it is theoretically unfounded, it hampers interpretation of results, and it leads to the temptation to overtune parameters. In this grant, we have created a climate model that contains a unified cloud parameterization (“CLUBB”) and a unified microphysics parameterization (“MG2”). In this model, all cloud types --- including marine stratocumulus, shallow cumulus, and deep cumulus --- are represented with a single equation set. This model improves the representation of convection in the Tropics. The model has been compared with ARM observations. The chief benefit of the project is to provide a climate model that is based on a more theoretically rigorous formulation.

Authors:
 [1]
  1. Univ. of Wisconsin, Milwaukee, WI (United States)
Publication Date:
Research Org.:
Univ. of Wisconsin, Milwaukee, WI (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1326797
Report Number(s):
DOE-UWM-8668
DOE Contract Number:
SC0008668
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; climate modeling; cloud parameterization

Citation Formats

Larson, Vincent. Final Technical Report for "Reducing tropical precipitation biases in CESM". United States: N. p., 2016. Web. doi:10.2172/1326797.
Larson, Vincent. Final Technical Report for "Reducing tropical precipitation biases in CESM". United States. doi:10.2172/1326797.
Larson, Vincent. 2016. "Final Technical Report for "Reducing tropical precipitation biases in CESM"". United States. doi:10.2172/1326797. https://www.osti.gov/servlets/purl/1326797.
@article{osti_1326797,
title = {Final Technical Report for "Reducing tropical precipitation biases in CESM"},
author = {Larson, Vincent},
abstractNote = {In state-of-the-art climate models, each cloud type is treated using its own separate cloud parameterization and its own separate microphysics parameterization. This use of separate schemes for separate cloud regimes is undesirable because it is theoretically unfounded, it hampers interpretation of results, and it leads to the temptation to overtune parameters. In this grant, we have created a climate model that contains a unified cloud parameterization (“CLUBB”) and a unified microphysics parameterization (“MG2”). In this model, all cloud types --- including marine stratocumulus, shallow cumulus, and deep cumulus --- are represented with a single equation set. This model improves the representation of convection in the Tropics. The model has been compared with ARM observations. The chief benefit of the project is to provide a climate model that is based on a more theoretically rigorous formulation.},
doi = {10.2172/1326797},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2016,
month = 9
}

Technical Report:

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  • The primary objective of this proposal was to quantify and understand biases in the diurnal cycle of precipitation over land and in the frequency of occurrence of light precipitation. The two specific NOAA/ESRL roles were: to use a cloud-resolving model (WRF) to understand the role of microphysics in this bias. In particular we were concerned that the microphysical representations in cloud models might display sensitivity to aerosol loadings; Analyze radar, precipitation, and radiosonde observations from TWP-ICE and compare the spatial distribution and other precipitation characteristics to those generated by WRF; and Facilitate CLUBB development for use in GCMs
  • In state-of-the-art climate models, each cloud type is treated using its own separate cloud parameterization and its own separate microphysics parameterization. This use of separate schemes for separate cloud regimes is undesirable because it is theoretically unfounded, it hampers interpretation of results, and it leads to the temptation to overtune parameters. In this grant, we are creating a climate model that contains a unified cloud parameterization and a unified microphysics parameterization. This model will be used to address the problems of excessive frequency of drizzle in climate models and excessively early onset of deep convection in the Tropics over land.more » The resulting model will be compared with ARM observations.« less
  • Recent studies have revealed that among all the tropical oceans, the tropical Atlantic has experienced the most pronounced warming trend over the 20th century. Many extreme climate events affecting the U.S., such as hurricanes, severe precipitation and drought events, are influenced by conditions in the Gulf of Mexico and the Atlantic Ocean. It is therefore imperative to have accurate simulations of the climatic mean and variability in the Atlantic region to be able to make credible projections of future climate change affecting the U.S. and other countries adjoining the Atlantic Ocean. Unfortunately, almost all global climate models exhibit large biasesmore » in their simulations of tropical Atlantic climate. The atmospheric convection simulation errors in the Amazon region and the associated errors in the trade wind simulations are hypothesized to be a leading cause of the tropical Atlantic biases in climate models. As global climate models have resolutions that are too coarse to resolve some of the atmospheric and oceanic processes responsible for the model biases, we propose to use a high-resolution coupled regional climate model (CRCM) framework to address the tropical bias issue. We propose to combine the expertise in tropical coupled atmosphere-ocean modeling at Texas A&M University (TAMU) and the coupled land-atmosphere modeling expertise at Pacific Northwest National Laboratory (PNNL) to develop a comprehensive CRCM for the Atlantic sector within a general and flexible modeling framework. The atmospheric component of the CRCM will be the NCAR WRF model and the oceanic component will be the Rutgers/UCLA ROMS. For the land component, we will use CLM modified at PNNL to include more detailed representations of vegetation and soil hydrology processes. The combined TAMU-PNNL CRCM model will be used to simulate the Atlantic climate, and the associated land-atmosphere-ocean interactions at a horizontal resolution of 9 km or finer. A particular focus of the model development effort will be to optimize the performance of WRF and ROMS over several thousand of cores by focusing on both the parallel communication libraries and the I/O interfaces, in order to achieve the sustained throughput needed to perform simulations on such fine resolution grids. The CRCM model will be developed within the framework of the Coupler (CPL7) software that is part of the NCAR Community Earth System Model (CESM). Through efforts at PNNL and within the community, WRF and CLM have already been coupled via CPL7. Using the flux coupler approach for the whole CRCM model will allow us to flexibly couple WRF, ROMS, and CLM with each model running on its own grid at different resolutions. In addition, this framework will allow us to easily port parameterizations between CESM and the CRCM, and potentially allow partial coupling between the CESM and the CRCM. TAMU and PNNL will contribute cooperatively to this research endeavor. The TAMU team led by Chang and Saravanan has considerable experience in studying atmosphere-ocean interactions within tropical Atlantic sector and will focus on modeling issues that relate to coupling WRF and ROMS. The PNNL team led by Leung has extensive expertise in atmosphere-land interaction and will be responsible for improving the land surface parameterization. Both teams will jointly work on integrating WRF-ROMS and WRF-CLM to couple WRF, ROMS, and CLM through CPL7. Montuoro of the TAMU Supercomputing Center will be responsible for improving the MPI and Parallel IO interfaces of the CRCM. Both teams will contribute to the design and execution of the proposed numerical experiments and jointly perform analysis of the numerical experiments.« less
  • This is a final report for a SciDAC grant supported by BER. The project implemented a novel technique for coupling small-scale dynamics and microphysics into a community climate model. The technique uses subcolumns that are sampled in Monte Carlo fashion from a distribution of subgrid variability. The resulting global simulations show several improvements over the status quo.
  • This project examines physics/dynamics coupling, that is, exchange of meteorological profiles and tendencies between an atmospheric model’s dynamical core and its various physics parameterizations. Most model physics parameterizations seek to represent processes that occur on scales smaller than the smallest scale resolved by the dynamical core. As a consequence a key conceptual aspect of parameterizations is an assumption about the subgrid variability of quantities such as temperature, humidity or vertical wind. Most existing parameterizations of processes such as turbulence, convection, cloud, and gravity wave drag make relatively ad hoc assumptions about this variability and are forced to introduce empirical parameters,more » i.e., “tuning knobs” to obtain realistic simulations. These knobs make systematic dependences on model grid size difficult to quantify.« less