Abstract

Society's ability to make wise decisions depends on an accurate understanding of the current state of Earth and on an ability to predict future states. The Data Assimilation Research Testbed (DART) is an example of a suite of tools designed to improve our understanding through the combination of ... Show moreSociety's ability to make wise decisions depends on an accurate understanding of the current state of Earth and on an ability to predict future states. The Data Assimilation Research Testbed (DART) is an example of a suite of tools designed to improve our understanding through the combination of observations with our theoretical understanding embodied in forecast models. DART's ensemble based data assimilation provides heterogeneous uncertainty quantification. Current research using DART includes: Improving streamflow prediction during intense rainfall events, which lead to flooding, using DART and the Weather Research and Forecasting model and the Noah-MP land model (WRF-Hydro). Building an integrated atmospheric and ocean forecasting system using DART and WRF for the Red Sea Initiative. Understanding Global air pollution using a global meteorology-aerosol-chemistry assimilation system that assimilates aerosol optical depth, carbon monoxide, and weather observations into the Community Atmosphere Model with Chemistry (CAM-Chem). Assimilating observations of the Earth system from satellites into the Model for Prediction Across Scales (MPAS; regional and global) using observation operators from the Joint Effort for Data assimilation Integration (JEDI), bias correction for satellite retrievals from the Gridpoint Statistical Interpolation (GSI), and the assimilation environment of DART. Deciphering the flow dependency of forecast errors in the tropics and the relative importance of wind and mass information for tropical analyses. Connecting the U.S. Department of Energy's E3SM atmospheric model with a broad spectrum of observations to perform short ensemble hindcast simulations for model development and evaluation. Generating atmospheric reanalysis data sets from CAM, which enables efficient data assimilation in other components of the Earth system; ocean, land, cryosphere, ... Improving DART by giving users more control over how observations are assimilated, and supporting the assimilation of additional observations, such as radiances through the use of the RTTOV library. Show less