Data assimilation docs

Last year I finished my PhD (you can read my dissertation here, in Spanish) and now I finished documenting the technical part of my data assimilation experiments into a website. The website compiles a series of examples, tutorials, scripts and in general a comprehensive documentation around the GSI system V3.7 - EnKF V1.3. It focus on the use of GSI as a observation operator along with the EnKF version. It covers everything you need to know from how to deal with observations (in bufr format), how to configure the system to assimilate conventional and radiance observations to how to read and interpret GSI outputs.

Utilización de datos satelitales para la evaluación y mejora de los pronósticos numéricos en alta resolución a muy corto plazo

Luego de casi 6 años de trabajo, me doctoré! La tesis en cuestión está escrita usando RMarkdown y thesisdown para generar al mismo tiempo un hermoso pdf con el formato que requiere la universidad y una web abierta y disponible para todo el mundo. Resumen En la Argentina, los fenómenos meteorológicos extremos producen cuantiosas pérdidas humanas y materiales. Muchos de estos fenómenos, por ejemplo tornados, ráfagas intensas, precipitaciones extremas en cortos períodos de tiempo, granizo de gran tamaño y actividad eléctrica, están asociados a la ocurrencia de convección profunda.

Hourly Assimilation of Different Sources of Observations Including Satellite Radiances in a Mesoscale Convective System Case During RELAMPAGO campaign

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.

A rapid refresh ensemble based data assimilation and forecast system for the RELAMPAGO field campaign

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).

A Parameterization of the Cloud Scattering Polarization Signal Derived From GPM Observations for Microwave Fast Radative Transfer Models

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.

Assimilation of conventional and satellite observations in a deep convection case during RELAMPAGO using the WRF-GSI-LETFK system

Evaluate the impact of assimilate different observation types into a regional frequent-update ensemble-based data assimilation system using a case study approach involving a Mesoscale Convective System (MCS) developed over Southern South America during 22-23 November 2018 during the IOP period of the RELAMPAGO field campaign.