Public Abstract

DE-SC0016324: Representation of clouds and convection across scales in ACME

Award Status: Inactive

Institution: Research Foundation for the State University of New York d/b/a RFSUNY - Stony Brook University, Stony Brook, NY
UEI: M746VC6XMNH9
DUNS: 804878247

Most Recent Award Date: 04/24/2019
Number of Support Periods: 3
PM: Davis, Xujing

Current Budget Period: 09/01/2018 - 08/31/2020
Current Project Period: 09/01/2016 - 08/31/2020
PI: Zhang, Minghua

Supplement Budget Period: N/A

Public Abstract

Project Objectives: Clouds continue to be one of the largest sources of uncertainty in climate models. Clouds are also central to DOE’s scientific goals for the Accelerated Climate Modeling for Energy (ACME), especially as they relate to how the hydrological cycle and water resources interact with the climate system on local to global scales. Reducing uncertainties from clouds and improving regional simulation skill requires both higher resolution and improved physical parameterizations of clouds, both of which will be the main focus areas of this project. Project Description: ACME is pushing the limits of horizontal resolution in climate models: ACME version 1 (v1) is targeting a globally uniform horizontal resolution of 25 km, with even higher resolution planned for subsequent versions. Therefore, ACME is entering the “grey zone”: a range where the resolution is (1) too high for traditional cloud and convective parameterizations, but (2) too coarse to rely solely on parameterizations found in explicit high resolution models such as large eddy simulations (LES). The goal of this project is to evaluate the treatment of clouds and convection in ACME at resolutions that fall within the grey zone using regionally refined model (RRM) grids, LES simulations, and new ARM datasets. Methods The validation efforts of the project will target any relevant version of ACME (v1, development versions, or configurations with new parameterizations from other projects as they become available). Simulations will be run both at globally uniform resolution (25 km) and at higher resolutions using the regionally refined modeling (RRM) framework. RRM grids will be constructed to target regions rich in ARM observations, including the Southern Great Plains (SGP), Eastern North Atlantic (ENA), and Tropical Western Pacific (TWP) Darwin sties. New datasets, including 3-dimensional gridded ARM constrained variational analysis (VAR) datasets, will be developed from ARM observations at the various sites. By design, these regions cover a wide range of cloud regimes, thus providing the opportunity to validate ACME for many regimes. Impact This work will benefit ACME by extending the ACME RRM capability to the ARM sites in tropical and Atlantic regions and providing a process-oriented diagnostic package to facilitate ACME model evaluation with ARM data.

Project Objectives:

Clouds continue to be one of the largest sources of uncertainty in climate models. Clouds are also central to DOE’s scientific goals for the Accelerated Climate Modeling for Energy (ACME), especially as they relate to how the hydrological cycle and water resources interact with the climate system on local to global scales. Reducing uncertainties from clouds and improving regional simulation skill requires both higher resolution and improved physical parameterizations of clouds, both of which will be the main focus areas of this project.

Project Description:

ACME is pushing the limits of horizontal resolution in climate models: ACME version 1 (v1) is targeting a globally uniform horizontal resolution of 25 km, with even higher resolution planned for subsequent versions. Therefore, ACME is entering the “grey zone”: a range where the resolution is (1) too high for traditional cloud and convective parameterizations, but (2) too coarse to rely solely on parameterizations found in explicit high resolution models such as large eddy simulations (LES).

The goal of this project is to evaluate the treatment of clouds and convection in ACME at resolutions that fall within the grey zone using regionally refined model (RRM) grids, LES simulations, and new ARM datasets.

Methods

The validation efforts of the project will target any relevant version of ACME (v1, development versions, or configurations with new parameterizations from other projects as they become available). Simulations will be run both at globally uniform resolution (25 km) and at higher resolutions using the regionally refined modeling (RRM) framework. RRM grids will be constructed to target regions rich in ARM observations, including the Southern Great Plains (SGP), Eastern North Atlantic (ENA), and Tropical Western Pacific (TWP) Darwin sties. New datasets, including 3-dimensional gridded ARM constrained variational analysis (VAR) datasets, will be developed from ARM observations at the various sites. By design, these regions cover a wide range of cloud regimes, thus providing the opportunity to validate ACME for many regimes.

Impact

This work will benefit ACME by extending the ACME RRM capability to the ARM sites in tropical and Atlantic regions and providing a process-oriented diagnostic package to facilitate ACME model evaluation with ARM data.