65th IHC Booklet/Program (pdf - 4.9MB) - Office of the Federal ...

The Experimental HWRF-HEDAS system: Model Evaluation in Preparation for Satellite
Microwave Data Assimilation Inside the Hurricane Precipitation Area
Svetla Hristova-Veleva 1 , Sundararaman Gopalakrishnan 2 ,
Tomislava Vukicevic 2 , Ziad Haddad 1 and Thiago Quirino 2
(Svetla.Hristova@jpl.nasa.gov)
1 Jet Propulsion Laboratory, California Institute of Technology; 2 NOAA/HRD/AOML
Over the last two decades, data assimilation of satellite observations outside precipitation has
lead to significant improvement in the ability of global models to represent the large-scale
synoptic environment. This has resulted in measured improvement in the hurricane track
forecast skills of the global models. However, improving the accuracy of hurricane intensity
changes remains a very challenging problem. The main source of error for the large-scale
models is their limited ability, due to the use of convective parameterizations, to resolve
convective scale events and their interaction with the large-scale environment. Regional models
have the resolution, and the physics to properly represent the convective processes. However,
even today, there is large uncertainty regarding the assumptions used by the convective-scale
parameterizations (e.g. parameterizations of the microphysical processes, the boundary layer
processes and the ocean-atmosphere fluxes).
Assimilation of satellite observations inside the precipitation presents the next opportunity for
hurricane intensity forecast improvements. It offers two benefits: the ability to improve the
model forecasts through constantly pushing the model toward the observed precipitation
structures; the ability to improve the model physics through parameter estimation as part of the
data assimilation.
The data to be assimilated could be either the satellite-based retrievals of geophysical
parameters, or, the observed radiances themselves. Assimilation of geophysical parameters is
often easier since they are more closely related to the state variables. However, instantaneous
satellite retrievals carry a lot of uncertainty. Assimilating the observed radiances is the more
promising approach at the moment. However, to allow the model to efficiently assimilate the
observed data, we need to first assure that the model-produced satellite observables compare well
to the observations themselves.
To facilitate the model evaluation, we are developing the Tropical Cyclone Information System
(TCIS- http://topicalcyclone.jpl.nasa.gov). As part of TCIS, a dedicated portal was developed to
facilitate the NASA/NOAA/NSF hurricane field campaigns of 2010 (http://grip.jpl.nasa.gov).
We used it to identify a number of cases to allow the evaluation of different hurricane forecasts.
In particular, we focused on evaluating the performance of the Experimental version of HWRF
(HWRFX) in forecasting the evolution of hurricane Earl. In a previous study we used the model
forecast of the thermodynamic and hydrometeor fields to forward simulate satellite observables
(microwave brightness temperatures). We compared the overall structure of the observed and
the forecasted storms as depicted by the brightness temperatures at 37 and 89 GHz channels. We
found that the model was highly capable in depicting the 2D structure of the precipitation field
and its evolution. However, the previous study was mostly qualitative.
Session 10 – Page 6