Abstract In this paper, we evaluate the impact of assimilating high-resolution surface networks and satellite observations using the WRF-GSI-LETKF over central and north eastern Argentina where the surface and upper air observing networks are relatively coarse. We conducted a case study corresponding to a huge mesoscale convective system (MCS) that developed during November 22, 2018. The accumulated precipitation associated with this MCS was quite high, exceeding 200 mm over northern Argentina and Paraguay.
Highlights A LETKF-WRF system was run successfully in real-time to support RELAMPAGO operations. A reduction in forecast error was shown due to data assimilation cycles. 60-member RRR analyses and forecasts are available for the research community. Abstract This paper describes the lessons learned from the implementation of a regional ensemble data assimilation and forecast system during the intensive observing period of the Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign (central Argentina, November–December 2018).
Abstract: Microwave cloud polarized observations have shown the potential to improve precipitation retrievals since they are linked to the orientation and shape of ice habits. Stratiform clouds show larger brightness temperature (TB) polarization differences (PDs), defined as the vertically polarized TB (TBV) minus the horizontally polarized TB (TBH), with ~10 K PD values at 89 GHz due to the presence of horizontally aligned snowflakes, while convective regions show smaller PD signals, as graupel and/or hail in the updraft tend to become randomly oriented.