of the assimilation of non-precipitating echoes reflectivity data on the short-term numerical forecast of SisPI.

The research carries out an evaluation of the 3DVAR method with different options for the assimilation of reflectivity data, which are applied to the SisPI system with the purpose of determining which scheme presents the best results in the short-term numerical weather prediction. For this, data from 6 meteorological radars with coverage over a domain with 3km of spatial resolution are used, using the indirect method with (3DVAR-NoRain) and without (3DVAR) activate an option to consider null-echoes of without presence of precipitation. As a test case, the cold front that affected Cuba on December 10th, 2018 is taken. Abstract GDAS Prepbufr and Nexrad Level II radar data with the WRFDA and using the 3DVAR method. The use of CV3, CV5 and CV7 covariance matrices is compared. radar data assimilation experiments with the 3DVAR method but with covariance matrices that employ previous runs from 1 week to 45 days. It was evaluated for the first time in Cuba different methods such as 3DVAR, 3DEnVAR and 4DEnVAR, highlighting the advantages and the best results obtained with hybrid schemes, with which the advantages can be appreciated over 3DVAR method, because the contribution of the members of the ensemble provide information about hydrometeors control variables even in areas where radar data is not available. The author evaluates different options implemented in the WRFDA for the assimilation of reflectivity data, highlighting the indirect method with the inclusion of hydrometeors. These last works have been limited only to the use of NOAA radar data, hence in this work it was decided to make efforts to use complete coverage throughout the maximum resolution domain of SisPI, with also data from the radar network of the INSMET. A null-echo is defined as a region with non-precipitation echoes within the radar observation range. The model removes excessive humidity and four types of hydrometeors (wet and dry snow, graupel, and rain) based on the radar reflectivity by using a three-dimensional variational (3D-Var) data assimilation technique within the WRFDA system.


Introduction Forecaster
Data Assimilation (DA) of meteorological observations Insert the information from the meteorological observations in the Numerical Weather Forecast Models and apply consistency restrictions and dynamic balance between all the meteorological variables, to produce a field of analysis that constitutes the initialization of the model.
Armas (2015) With DA Without DA

RADAR OBS
Center for Atmospheric Physics, Institute of Meteorology Impact of the assimilation of non-precipitating echoes reflectivity data on the short-term numerical forecast of SisPI. Center for Atmospheric Physics, Institute of Meteorology Impact of the assimilation of non-precipitating echoes reflectivity data on the short-term numerical forecast of SisPI.
It was evaluated for the first time in Cuba different methods such as 3DVAR, 3DEnVAR and 4DEnVAR, highlighting the advantages and the best results obtained with hybrid schemes, with which the advantages can be appreciated over 3DVAR method, because the contribution of the members of the ensemble provide information about hydrometeors control variables even in areas where radar data is not available. Aguiar (2021) The author evaluates different options implemented in the WRFDA for the assimilation of reflectivity data, highlighting the indirect method with the inclusion of hydrometeors. These last works have been limited only to the use of NOAA radar data, hence in this work it was decided to make efforts to use complete coverage throughout the maximum resolution domain of SisPI, with also data from the radar network of the INSMET.
Impact of the assimilation of non-precipitating echoes reflectivity data on the short-term numerical forecast of SisPI.

Lee et al. (2020)
A null-echo is defined as a region with non-precipitation echoes within the radar observation range. The model removes excessive humidity and four types of hydrometeors (wet and dry snow, graupel, and rain) based on the radar reflectivity by using a three-dimensional variational (3D-Var) data assimilation technique within the WRFDA system.

Recently available in WRFDA
Min & Kim (2016) radar_non_precip_opt Center for Atmospheric Physics, Institute of Meteorology Impact of the assimilation of non-precipitating echoes reflectivity data on the short-term numerical forecast of SisPI.

Objectives
• The main objective of this research is to evaluate the impact of assimilating reflectivity data of non-precipitating echoes (radar_non_precip_opt parameter of WRFDA namelist) in the short-term numerical weather forecast of SisPI, which is a recently available option in the WRFDA module, and nowadays its use in the country has not been evaluated.
• On the other hand, it is also intended to carry out an experiment in which a total coverage of reflectivity information can be available in the domain of maximum spatial resolution.
Center for Atmospheric Physics, Institute of Meteorology Impact of the assimilation of non-precipitating echoes reflectivity data on the short-term numerical forecast of SisPI.

Materials and Methods
For the accomplishment of this work the WRF model (4.1.2) and the WRFDA module (4.3) are used. The assimilation of satellite and prepbufr data from the GDAS system is carried out for all domains, and in the case of domain 3, data from the INSMET and NOAA radar network are also assimilated, guaranteeing with this a total coverage of reflectivity information on the domain of maximum spatial resolution.
A radar data conversion tool in Nexrad Level II format to FM-128 format implemented in Python by Ferrer and Borrajero (2019)

BE Matrix (NMC method) CV7 with Hydrometeors and W
Impact of the assimilation of non-precipitating echoes reflectivity data on the short-term numerical forecast of SisPI.

GFS + GDAS + Radar + Null echoes
Impact of the assimilation of non-precipitating echoes reflectivity data on the short-term numerical forecast of SisPI. Impact of the assimilation of non-precipitating echoes reflectivity data on the short-term numerical forecast of SisPI. Impact of the assimilation of non-precipitating echoes reflectivity data on the short-term numerical forecast of SisPI. Impact of the assimilation of non-precipitating echoes reflectivity data on the short-term numerical forecast of SisPI. Impact of the assimilation of non-precipitating echoes reflectivity data on the short-term numerical forecast of SisPI.

Conclusions
• The Null-echoes assimilation option proved to be an important option in the assimilation of radar data. It allows more realistic construction of moisture fields and its vertical structure in areas of observed reflectivity echoes.
• The use of this option contributes to improving the precipitation forecast and adequately reproduces the convective processes in the first time steps.
• The simulation with radar data assimilation but without the use of this option did not adequately represent the reflectivity echoes and the brightness temperatures of cloud tops in the first 2 hours of simulation.
• The verification with synoptic stations data showed that the use of the radar_non_precip_opt option made it possible to obtain lower Mean Absolute Error values in the forecast of accumulated precipitation in the first 3 hours of simulation.
Center for Atmospheric Physics, Institute of Meteorology Impact of the assimilation of non-precipitating echoes reflectivity data on the short-term numerical forecast of SisPI.

Recommendations
• Explore the impact of assimilating reflectivity data of non-precipitating echoes (radar_non_precip_opt) using hybrids DA methods (3DEnVAR and 4DEnVAR).
• Insert in the initialization the data of the network of meteorological stations of the INSMET.
• Work on implementing quality control of Cuban radars data.