The Data Assimilation Research Testbed; a Suite of Tools for
Understanding the Earth System with Confidence.
Abstract
Society’s ability to make wise decisions depends onan accurate
understanding of the current state of Earthand on an ability to predict
future states.The Data Assimilation Research Testbed (DART) is an
example of a suite of toolsdesigned to improve our understanding through
the combination of observationswith our theoretical understanding
embodied in forecast models.DART’s ensemble based data assimilation
provides uncertainty quantification as a function of time, location, and
variable.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 atmosphere and ocean
forecasting system using DART and WRF for the Red Sea Initiative.
Understanding air pollution using a global meteorology-aerosol-chemistry
prediction 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 software.