Prof. Avelino F. Arellano (January 20, 2022, 09:00-10:30)
|Affiliation||University of Arizona, USA|
|Title||The Impact of Precipitable Water Vapor Data Assimilation on North American Monsoon Precipitation Forecast in Northern Mexico|
While precipitation during the North American Monsoon (NAM) significantly contributes to the hydrometeorology of the southwest United States
and northwest Mexico, current numerical weather prediction (NWP) systems lack the necessary skill in forecasting NAM precipitation, especially
on events associated with weak synoptic forcing. This is in part due to the lack of relevant observational constraints in this semi-arid to a
rid region that is mostly influenced by complex topography. Here, we present a couple of observational, modeling, and assimilation activities
that we have been developing over the past 5 years or so to improve short-term NWP forecasts of monsoon precipitation in this region.
In particular, we use a custom-built NWP system consisting of: a) precipitable water vapor retrievals taken from a Global Navigation Satellite System (GNSS)
ground-based GPS network that my colleagues have deployed during summer of 2013 and 2017 over northwest Mexico; b) convective-permitting (CPM)
Advanced Research Weather and Forecasting Model (WRF-ARW) with NCEP GFS (and NAM) as initial and lateral boundary conditions (IC/BCs);
and c) an ensemble adjustment Kalman Filter (EAKF) implemented in the NCAR Data Assimilation Research Testbed (DART).