This research proposes to carry out a principal component analysis using the maximum covariance method, with the aim of finding the most robust spatio-temporal relationships between several candidate predictors and th...This research proposes to carry out a principal component analysis using the maximum covariance method, with the aim of finding the most robust spatio-temporal relationships between several candidate predictors and the accumulated monthly precipitation recorded in Cuba during the period 1980-2020. This process will make it possible to establish quantitative relationships that, together with theoretical considerations, make it possible to reduce the list of predictors to be used for the purpose of obtaining seasonal predictions. The values of the predictors are represented through monthly averages obtained from ERA5 reanalysis, while monthly accumulated precipitation data were obtained from a national-scope grid with 4 km of spatial resolution, used as predictand. The results obtained reflect the highest spatio-temporal correlation values with the first variability mode in all cases, indicating that the usual regime conditions are predominant and have a greater coupling with the precipitation variability in the analyzed temporal scale. In addition, they suggest that the candidates that explain the transport of moisture at low levels, as well as the gradients between the middle and lower troposphere, show the most robust associations. In the same way, the surface temperature of tropical Atlantic Sea, the flow related to Quasi-Biennial Oscillation and the thermodynamic indices, K Index and Galvez-Davison Index, present good degrees of association, for which reason they can be considered the most recommendable for carrying out forecasting experiments.展开更多
A set of 15 combinations of microphysics and cumulus parameterizations for the WRF numerical model were tested in the forecast of a rain event on January 16 2018 over Panama. GPM satellite, upper air soundings and gro...A set of 15 combinations of microphysics and cumulus parameterizations for the WRF numerical model were tested in the forecast of a rain event on January 16 2018 over Panama. GPM satellite, upper air soundings and ground weather stations were used to evaluate the performance of each configuration. Different metrics were used to obtain the configurations that produced the best forecasts. The analysis showed a strong fluctuation of the diurnal precipitation cycle from one region to another. From the set of tests carried, BMJ with Morrison performed slightly above the other combinations in representing well the diurnal cycle for some domain areas, followed by Thom-Gr, WSM6-BMJ and WSM6-KF. While the experiments had a better performance forecasting over sea, they were not able to match the highest values of total precipitation. Regarding spatial rain distribution, all BMJ cumulus combinations showed the best skills mainly over the area comprising the Panama Canal while the others tended to overestimate the rain. Finally, most BMJ experiments showed the highest correlation factor and performed quite well representing the vertical profiles of relative humidity, temperature and wind.展开更多
Possible changes in the structure and seasonal variability of the subtropical ridge may lead to changes in the rainfall’s variability modes over Caribbean region. This generates additional difficulties around water r...Possible changes in the structure and seasonal variability of the subtropical ridge may lead to changes in the rainfall’s variability modes over Caribbean region. This generates additional difficulties around water resource planning, therefore, obtaining seasonal prediction models that allow these variations to be characterized in detail, it’s a concern, specially for island states. This research proposes the construction of statistical-dynamic models based on PCA regression methods. It is used as predictand the monthly precipitation accumulated, while the predictors (6) are extracted from the ECMWF-SEAS5 ensemble mean forecasts with a lag of one month with respect to the target month. In the construction of the models, two sequential training schemes are evaluated, obtaining that only the shorter preserves the seasonal characteristics of the predictand. The evaluation metrics used, where cell-point and dichotomous methodologies are combined, suggest that the predictors related to sea surface temperatures do not adequately represent the seasonal variability of the predictand, however, others such as the temperature at 850 hPa and the Outgoing Longwave Radiation are represented with a good approximation regardless of the model chosen. In this sense, the models built with the nearest neighbor methodology were the most efficient. Using the individual models with the best results, an ensemble is built that allows improving the individual skill of the models selected as members by correcting the underestimation of precipitation in the dynamic model during the wet season, although problems of overestimation persist for thresholds lower than 50 mm.展开更多
The version 2.1 of PETROMAR-3D model, created in the Center for Marine Meteorology of the Meteorology Institute of Cuba, is presented. This Lagrangian model has been designed to describe the physical processes of mari...The version 2.1 of PETROMAR-3D model, created in the Center for Marine Meteorology of the Meteorology Institute of Cuba, is presented. This Lagrangian model has been designed to describe the physical processes of marine oil spills in the face of multiple scenarios of the marine environment. Although it is applicable to any part of the world, it is mainly designed for inter-American seas. The novelty has been to integrate the processes of drift and weathering into a model, with updated methods that incorporate 3D phenomena, a very favorable situation to achieve an operating system in Cuba and the region for the immediate and medium term. Python was chosen as the programming language because it has advanced libraries for numerical modeling, automation work and other useful tools for pre-and post-processing. By means of adapters, an important number of atmospheric, hydrodynamic and wave models have been considered to create the scenarios efficiently. The modular distribution in which the code has been created facilitates its use for other dispersion analysis and biophysical applications. Finally, a set of simple images are presented, aimed at informing decision-makers in order to mitigate the effects of the spill on the environment.展开更多
This research develops a comparative study between different multiplicative weights that are assigned to the covariance matrix that represents the background error in two hybrid assimilation schemes: 3DEnVAR and 4DEnV...This research develops a comparative study between different multiplicative weights that are assigned to the covariance matrix that represents the background error in two hybrid assimilation schemes: 3DEnVAR and 4DEnVAR. These weights are distributed between the static and time-invariant matrix and the matrix generated from the perturbations of a previous ensemble. The assigned values are 25%, 50%, and 75%, always having as a reference the ensemble matrix. The experiments are applied to the short-range Prediction System (SisPI) that works operationally at the Institute of Meteorology. The impact of Tropical Storm Eta on November 7 and 8, 2020 was selected as a study case. The results suggest that by giving the main weight to the ensemble matrix more realistic solutions are achieved because it shows a better representation of the synoptic flow. On the other hand, it is observed that 3DEnVAR method is more sensitive to multiplicative weight change of the first guess. More realistic results are obtained with 50% and 75% relations with 4DEnVAR method, whereas with 3DEnVAR a weight of 75% for the ensemble matrix is required.展开更多
1. Overview The 2016 Quadrennial Ozone Symposium （QOS-2016） was held on 4-9 September 2016 in Edinburgh, UK. The Symposium was organized by the International Ozone Commission （IO3C）, the NERC Centre for Ecology ＆...1. Overview The 2016 Quadrennial Ozone Symposium （QOS-2016） was held on 4-9 September 2016 in Edinburgh, UK. The Symposium was organized by the International Ozone Commission （IO3C）, the NERC Centre for Ecology ＆ Hydrology and the University of Edinburgh, and was co-sponsored by the International Union of Geodesy and Geophysics, the International Association of Meteorology and Atmospheric Sciences, and the World Meteorological Organization.展开更多
文摘This research proposes to carry out a principal component analysis using the maximum covariance method, with the aim of finding the most robust spatio-temporal relationships between several candidate predictors and the accumulated monthly precipitation recorded in Cuba during the period 1980-2020. This process will make it possible to establish quantitative relationships that, together with theoretical considerations, make it possible to reduce the list of predictors to be used for the purpose of obtaining seasonal predictions. The values of the predictors are represented through monthly averages obtained from ERA5 reanalysis, while monthly accumulated precipitation data were obtained from a national-scope grid with 4 km of spatial resolution, used as predictand. The results obtained reflect the highest spatio-temporal correlation values with the first variability mode in all cases, indicating that the usual regime conditions are predominant and have a greater coupling with the precipitation variability in the analyzed temporal scale. In addition, they suggest that the candidates that explain the transport of moisture at low levels, as well as the gradients between the middle and lower troposphere, show the most robust associations. In the same way, the surface temperature of tropical Atlantic Sea, the flow related to Quasi-Biennial Oscillation and the thermodynamic indices, K Index and Galvez-Davison Index, present good degrees of association, for which reason they can be considered the most recommendable for carrying out forecasting experiments.
文摘A set of 15 combinations of microphysics and cumulus parameterizations for the WRF numerical model were tested in the forecast of a rain event on January 16 2018 over Panama. GPM satellite, upper air soundings and ground weather stations were used to evaluate the performance of each configuration. Different metrics were used to obtain the configurations that produced the best forecasts. The analysis showed a strong fluctuation of the diurnal precipitation cycle from one region to another. From the set of tests carried, BMJ with Morrison performed slightly above the other combinations in representing well the diurnal cycle for some domain areas, followed by Thom-Gr, WSM6-BMJ and WSM6-KF. While the experiments had a better performance forecasting over sea, they were not able to match the highest values of total precipitation. Regarding spatial rain distribution, all BMJ cumulus combinations showed the best skills mainly over the area comprising the Panama Canal while the others tended to overestimate the rain. Finally, most BMJ experiments showed the highest correlation factor and performed quite well representing the vertical profiles of relative humidity, temperature and wind.
文摘Possible changes in the structure and seasonal variability of the subtropical ridge may lead to changes in the rainfall’s variability modes over Caribbean region. This generates additional difficulties around water resource planning, therefore, obtaining seasonal prediction models that allow these variations to be characterized in detail, it’s a concern, specially for island states. This research proposes the construction of statistical-dynamic models based on PCA regression methods. It is used as predictand the monthly precipitation accumulated, while the predictors (6) are extracted from the ECMWF-SEAS5 ensemble mean forecasts with a lag of one month with respect to the target month. In the construction of the models, two sequential training schemes are evaluated, obtaining that only the shorter preserves the seasonal characteristics of the predictand. The evaluation metrics used, where cell-point and dichotomous methodologies are combined, suggest that the predictors related to sea surface temperatures do not adequately represent the seasonal variability of the predictand, however, others such as the temperature at 850 hPa and the Outgoing Longwave Radiation are represented with a good approximation regardless of the model chosen. In this sense, the models built with the nearest neighbor methodology were the most efficient. Using the individual models with the best results, an ensemble is built that allows improving the individual skill of the models selected as members by correcting the underestimation of precipitation in the dynamic model during the wet season, although problems of overestimation persist for thresholds lower than 50 mm.
文摘The version 2.1 of PETROMAR-3D model, created in the Center for Marine Meteorology of the Meteorology Institute of Cuba, is presented. This Lagrangian model has been designed to describe the physical processes of marine oil spills in the face of multiple scenarios of the marine environment. Although it is applicable to any part of the world, it is mainly designed for inter-American seas. The novelty has been to integrate the processes of drift and weathering into a model, with updated methods that incorporate 3D phenomena, a very favorable situation to achieve an operating system in Cuba and the region for the immediate and medium term. Python was chosen as the programming language because it has advanced libraries for numerical modeling, automation work and other useful tools for pre-and post-processing. By means of adapters, an important number of atmospheric, hydrodynamic and wave models have been considered to create the scenarios efficiently. The modular distribution in which the code has been created facilitates its use for other dispersion analysis and biophysical applications. Finally, a set of simple images are presented, aimed at informing decision-makers in order to mitigate the effects of the spill on the environment.
文摘This research develops a comparative study between different multiplicative weights that are assigned to the covariance matrix that represents the background error in two hybrid assimilation schemes: 3DEnVAR and 4DEnVAR. These weights are distributed between the static and time-invariant matrix and the matrix generated from the perturbations of a previous ensemble. The assigned values are 25%, 50%, and 75%, always having as a reference the ensemble matrix. The experiments are applied to the short-range Prediction System (SisPI) that works operationally at the Institute of Meteorology. The impact of Tropical Storm Eta on November 7 and 8, 2020 was selected as a study case. The results suggest that by giving the main weight to the ensemble matrix more realistic solutions are achieved because it shows a better representation of the synoptic flow. On the other hand, it is observed that 3DEnVAR method is more sensitive to multiplicative weight change of the first guess. More realistic results are obtained with 50% and 75% relations with 4DEnVAR method, whereas with 3DEnVAR a weight of 75% for the ensemble matrix is required.
文摘1. Overview The 2016 Quadrennial Ozone Symposium （QOS-2016） was held on 4-9 September 2016 in Edinburgh, UK. The Symposium was organized by the International Ozone Commission （IO3C）, the NERC Centre for Ecology ＆ Hydrology and the University of Edinburgh, and was co-sponsored by the International Union of Geodesy and Geophysics, the International Association of Meteorology and Atmospheric Sciences, and the World Meteorological Organization.
