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-Rad) and without (3DVAR-NoRain) activate an option to also consider null-echoes of reflectivity without presence of precipitation. PrepBufr data from the GDAS system and radiance data obtained from different sensors on board polar orbiting satellites are also assimilated in all simulation domains. As a case study, the cold front that affected western of Cuba on December 10^th, 2018 is taken, which was preceded by a prefrontal depression that caused heavy rains on the north coast of Havana with significant accumulations in less than three hours. In the development of the work, the WRF model (4.1.2) is used with the WRFDA module (4.3), for which with a period of a month of SisPI simulations, covariance matrices of the background errors of each one of the domains with 27, 9, and 3 km spatial resolution, where in the last case this matrix is generated with the inclusion of hydrometeors as additional control variables. Also with the 3DVAR method, multiple outers loops are used, noting that the resulting cost functions show great similarity, although the 3DVAR-NoRain configuration tends to minimize this function in fewer iterations. The results obtained suggest that the highest Pearson correlation values are reached with the 3DVAR-NoRain configuration in an order of 0.4, while in the first 3 hours this configuration also shows the lowest MAE values compared to the INSMET synoptics stations network.

A dynamic model is developed to represent rip currents on open and sandy beaches, based on a multiple regression adjustment between the estimated longshore current speed and the rip current speed mea sured near Duck, North Carolina at the US Army Corps of Engineers Field Research Center. The speed of the longshore current and the tidal current are calculated at incipient breaking and their correlation is established with the speed of the observed rip current, corresponding to the same wave parameters and with the use of the program computer CurveExpert Professional 2.6.3 of the year 2017, a multiple regression equation was obtained to calculate the speed of the rip current, having the best correlation as the independent variable. It was found that larger waves and wave directions closer to the normal to the shore produced stronger rip currents and that strong flows parallel to the shore correspond to lower rip current intensities. The developed model is consistent in calculating the speed of rip currents on open and sandy beaches, with more than 70% accuracy for the locality where instrumental observations are available.

Atmospheric/plume turbulence parametrization is an important input for the estimation of dispersion of pollutants from the vehicular exhaust. A Three-Phase Turbulence (TPT) model was proposed by Madiraju and Kumar (2021) considering the critical parameters such as initial vertical plume spread, downwind distance, wind velocity, additional spread due to vehicular wake, thermal turbulence, atmospheric turbulence, road width, residence time and mixing height of mobile source dispersion. The flow regime of the TPT model is divided into the initial phase, transition phase, and dispersion phase. The current study considers the use of line-source and area-source using the TPT model for dispersion of exhaust. The paper will present the performance of these two types of modeling approaches based on the current practice using dispersion curves from point sources and the new TPT model. The statistical indicators (including model bias (MB), fractional bias (FB), normalized root mean square error (NMSE), correlation coefficient (r), geometric mean bias (MG), geometric variance (VG)) are used as a performance measure to identify the variations in the model results using observed data from three different field studies. The study will identify the better modeling approach (line-source versus area-source). The changes in the performance of simple mobile source models with the use of the TPT model are observed.

The study of the global energy budget and the energy flow in the Earth system is essential for understanding current climate change. To understand how energy is accumulating and being distributed within the climate system, an observationally constrained reconstruction of energy fluxes at the top of atmosphere has been used to infer the surface energy fluxes from 1985-2018, and the mass-corrected atmospheric energy divergence from ERA5 has been further adjusted to match the observed mean land heat uptake. New satellite and ocean data are combined with an improved methodology to quantify recent variability in meridional and ocean to land heat transports since 1985. A global top of atmosphere net imbalance is found to increase from 0.10 ± 0.61 W m⁻² over 1985–1999 to 0.62 ± 0.1 Wm⁻² over 2000–2016, and the uncertainty of ± 0.61 Wm⁻² is related to the Argo ocean heat content changes (± 0.1 Wm⁻²) and an additional uncertainty applying prior to 2000 relating to homogeneity adjustments.

The northward oceanic heat transports are derived from the derived surface fluxes and estimates of ocean heat accumulation. The inferred cross-equatorial oceanic heat transport of 0.50 PW is higher than most previous studies, and the derived mean meridional transport of 1.23 PW at 26° N is very close to 1.22 PW from RAPID observation. The surface flux contribution dominates the magnitude of the oceanic transport, but the integrated ocean heat storage controls the interannual variability.

The inferred surface fluxes are compared with other commonly used flux products. On station-scale, a comprehensive comparison of inferred and buoy-based fluxes is presented. On regional scale, the oceanic energy fluxes in North Atlantic is evaluated against RAPID observations. Results indicate that global land and ocean averages of inferred surface fluxes agree with the observed heat uptake to within 1 W m⁻², while satellite-derived and model-based fluxes show large global mean biases.

Meteorological phenomena may have a positive or negative impact on solar and wind generating facilities. The purpose of this work is to build an impact index that comprises the frequency of occurrence of these phenomena: “Clear Sky”, “fogs”, “Smoke”, “Haze”, “Mist”, “Precipitation”, “Shower” and “Thunderstorms”, weighted each one according to expert’s criteria, for 68 meteorological stations over Cuba and analyze the spatial distribution. The classification is given in five categories, ranging from “very unfavorable” to “very favorable”. Overall it shows that phenomena under study have a greater incidence on solar than on wind facilities, since “clear skies”, “thunderstorms” and “precipitation” have a strong impact, favorable or unfavorable according to the specific phenomenon. “Thunderstorms” are the most influencing phenomenon for wind facilities, with an unfavorable character. The spatial distribution shows favorable zones with regard to solar facilities in the provinces of Pinar del Río, Ciego de Ávila, Camaguey, the north coast of Las Tunas, Holguín and around the Gulf of Guacanayabo, and for wind generators at Pinar del Río, Artemisa, Ciego de Ávila, Camaguey, Las Tunas and the South coast of the Central and Eastern regions.

This research has as purpose to carry out a detailed study of the development and trajectory of Eta from numerical modeling, using the ERA5 re-analysis system as a support and complement to the meteorological research and forecast model (WRF) with dynamic update of sea surface temperature (WRF-SST). Specifically, it is intended to describe the synoptic and general circulation environment in which Eta developed using the ERA5 Re-analysis; design experiments with the WRF model, for the simulation of the case study with greater spatial and temporal resolution; and describe, from the numerical outputs, the meteorological conditions that influenced the two analyzed Eta life periods. Through the experiments carried out with the ERA5 and the WRF, a more detailed analysis of the conditions in which Eta developed and moved was achieved. When analyzing the maps of the ERA5 re-analysis system, a general underestimation of the wind speed during the analyzed periods was identified. The first moment was characterized by a system in the development phase that failed to intensity under the influence of a trough over the southeastern Gulf of Mexico that generated a sheared environment. These conditions were maintained during the second moment, when the organism described an erratic trajectory due to the fact that it was under the influence of weak directing currents, until it entered the flow of a ridge that led it to redirect its trajectory towards the north. Through the experiments that were carried out with the WRF-SST and from the numerical outputs, it was possible to describe with greater precision the meteorological conditions that influenced the development, trajectory and intensity changes of Eta.

In the following work, the design of an LSTM-type neural network model for wind speed and power generation nowcasting, every 10 minutes and up to two hours, is presented. For this, the wind speed measurements were used every 10 minutes at different heights above the ground, coming from the Measurement Tower located in Los Cocos, in the province of Holguín (Cuba), where the wind farms Gibara I and II are located. The real data is complemented with the wind speed numerical hourly forecasts from SisPI. The data covered the period between February 1, 2019 and January 31, 2020, that is, one year of measurement. Several LSTM models were built and evaluated considering only the measurements and combining the measurements with the forecasts generated by SisPI. The results suggest that the constructed models perform better than other more traditional statistical models and than other neural network models used in the country for similar purposes.

The work addresses the issue of how much cloud cover data obtained using model-interpolation techniques are suitable for monitoring the transparency of the atmosphere and determining conditions for the Earth's airglow observations at a local geophysical observatory. For this purpose, we compared the temporal dynamics of cloud cover from ECMWF's ERA5 with the night atmosphere transparency according to a digital camera. We considered the dynamics of the addressed parameters over December 2020 at the Geophysical Observatory of the Institute of Solar-Terrestrial Physics, located in the Baikal Natural Territory near the village Tory (Republic of Buryatia, Russia). The comparative analysis showed a generally good agreement between cloud cover data from ECMWF's ERA5 climate reanalysis and those observed with the camera. Disadvantages are the lack of information on rapid variations in cloud cover in the reanalysis and positive and negative delays in the dynamics of cloud fields that last about two hours.

The study was financially supported by the Ministry of Science and Higher Education of the Russian Federation (Subsidy no.075-GZ/C3569/278) and the grant No. 075-15-2020-787 for implementation of Major scientific projects on priority areas of scientific and technological development (the project «Fundamentals, methods and technologies for digital monitoring and forecasting of the environmental situation on the Baikal natural territory»).

The analysis of vortex structures in the atmosphere can be performed using various approaches. One of these approaches is based on the analysis of the decomposition of vorticity fields into empirical orthogonal functions (EOFs). We consider an atmospheric vortex that exists quasi-permanently in a certain region (the Hawaiian anticyclone was chosen as the study object). It is proposed to consider evolution of an individual atmospheric vortex based on the vorticity budget equation known from dynamic meteorology (Kislov et al., 2017). The spatial structure analysis of the vorticity field of the Hawaiian anticyclone showed that the first mode of EOF decomposition describes more than 50% of the total variability. This allows us to consider the equation only for the principal component (PC) in the first EOF mode. The study of the equation components describing the vorticity dynamics allows to estimate more and less significant processes for vortex evolution. It was shown that the evolution of vorticity in a subtropical anticyclone is significantly affected by horizontal layer-average temperature advection, which may be due to a significant temperature gradient between low and high latitudes. Vertical movements and vorticity advection at upper troposphere can also be a significant factor in the evolution of a subtropical anticyclone. The sensible heat flux and the radiation balance have a less significant effect on the vortex dynamics, and the role of the latent heat flux is minimal. The vorticity balance equation was tested using ERA5 reanalysis data (Hersbach et al., 2018). This leads to the appearance of a discrepancy in the equation, due to the underestimation of a number of factors and the imperfection of the reanalysis data. The resulting discrepancy was approximated by regression through the first EOF mode PC and the white noise term.

The study was supported by grant of Moscow State University (121051400081-7).

This paper presents a study of the variation of South West Monsoon Rainfall (SWMR) over two East Coast States(namely West Bengal and Orissa), Western part(Rajasthan and Gujrat), extreme North East(Assam)of India. The main stress has been given to reveal the correlation of this variation with the Sun’s Spot Number (SSN) of More Active Period (MAP) during 124 years (1880-2003).Firstly, it is found that in many cases SSN of MAP has tendency to increase with time having imbedded oscillation of period 22 years (similar to double solar cycle period).

The analysis of SWMR of those states separately or combined reveals that it is moderately influenced by Solar Activities provided SSN lies between 90 and 130. When SSN is less than 90 it becomes too weak to influence - there does not appear any definite pattern of change of SWMR. But when SSN increases from 90 to 130, SWMR tends to decrease. This implies that there may exist a range of critical SSN after which SSN has inverse significant effect on SWMR.

Lastly, when linear trend lines for SWMR are compared it becomes apparent that gradients of SWMR for West Bengal is slightly positive, that for Orissa is slightly negative and almost zero for total SWMR. This implies that overall there is no change in amount of Rainfall due to South West Monsoon in the combined area of West Bengal and Orissa.