P9 Towards operational data assimilation with global MPAS at convective-allowing resolution.
Cipriani, James, Ken Dixon, and Brett Wilt, The Weather Company, an IBM Business
In August 2018,
The Weather Company (TWC) operationalized a custom version of the NCAR Model
for Prediction Across Scales (MPAS) at uniform 15-km resolution, which runs out
to 72 hours (and experimentally out to 144 hours) to replace a 13-km WRF-based
global system. The 4x-daily forecasts are initialized with the 0.25-degree
NCEP GFS analyses, NASA SPoRT 2-km SST, and 4-km NESDIS VIIRS green vegetation
fraction data.
In parallel, TWC is developing an hourly-updating “Global High Resolution
Atmospheric Forecasting” system, based on variable resolution (15/3-km) MPAS
and the Gridpoint Statistical Interpolation data assimilation software. The
forecasts target 15-hour lead times, in part to drive TWC’s short-term
“Forecast On-Demand” and “Currents On-Demand” capabilities. To facilitate
rapid improvement of this system, a re-forecast environment evaluates how
changes to the model or data assimilation impact forecast quality.
Verification is performed through a combination of the DTC Model Evaluation
Tools for gridded precipitation and point comparisons via a custom database.
In this presentation, we will describe the development and implementation of
the (i) data assimilation, (ii) re-forecast, and (iii) verification
frameworks. We will also summarize the assimilation experiment results to date
and discuss on-going work to implement a cycled forecast system and acquire
low-latency observations.