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Tropical cyclones (TCs) are an important component of the hydrological cycle at tropical latitudes. In this study, we investigated the origin of precipitation associated with TCs formed from 1980 to 2018 over the Pacific Ocean in three subbasins: the western North Pacific Ocean (WNP), central and east Pacific Ocean (NEPAC), and South Pacific Ocean (SPO) basins. The analysis was performed throughout the TC lifetime during genesis, when they reached the lifetime maximum intensity (LMI), and the dissipation stage. The backward trajectories of all precipitant atmospheric parcels residing over the TC locations from the global outputs of the Lagrangian Flexible Particle (FLEXPART) dispersion model fed by the ERA-Interim dataset were used to identify moisture sources. The South and East China Seas and the western tropical North Pacific Ocean were identified as the principal moisture sources in the WNP basin, while the atmospheric moisture that precipitated mainly came from the eastern tropical North and South Pacific Ocean in the NEPAC basin, followed by the Caribbean Sea. Meanwhile, the Coral Sea, western tropical South Pacific Ocean, and northern Australia are the origins of the moisture in the SPO. The mean moisture uptake per TC was higher during the hurricane category than during any other stage in each basin.

Moisture transport and changes in the source–sink relationship play a vital role in the atmospheric branch of the hydrological cycle. Lagrangian approaches have emerged as the dominant tool to account for estimations of moisture sources and sinks; those that use the FLEXPART model fed by ERA-Interim reanalysis are most commonly used. With the release of the higher spatial resolution ERA5, it is crucial to compare the representation of moisture sources and sinks using the FLEXPART Lagrangian model with different resolutions in the input data, as well as its version for WRF-ARW input data, the FLEXPART-WRF. In this study, we compare this model for 2014 and moisture sources for the Iberian Peninsula and moisture sinks of North Atlantic and Mediterranean. For comparison criteria, we considered FLEXPARTv9.0 outputs forced by ERA-Interim reanalysis as “control” values. It is concluded that FLEXPARTv10.3 forced with ERA5 data at various horizontal resolutions (0.5° and 1°) represents moisture source and sink zones as represented forced by ERA-Interim (1°). In addition, the version fed with the dynamic downscaling WRF-ARW outputs (∼20 km), previously forced with ERA5, also represents these patterns accurately, allowing this tool to be used in future investigations at higher resolutions and for regional domains. Significance Statement The FLEXPART dispersion model forced with ERA5 reanalysis data at various resolutions represents moisture source and sink zones compared to when it is forced by ERA-Interim. When the Weather Research and Forecasting Model is used to dynamically downscale ERA5, FLEXPART-WRF can also represent moisture sources and sinks, allowing this tool to be used in future investigations requiring higher resolution and regional domains and on regions with a predominance of complex orography due to its ability to represent local moisture transport.

Financiado para publicación en acceso aberto: Universidade de Vigo/CISUG The tropical cyclones (TCs) trajectories are mainly controlled by the large-scale parameters related with the steering flow. We used the HURDAT2 database from 1980 to 2018 for grouping the tracks of TCs formed in the North Atlantic (NATL) main development region into straight moving (SM), recurving landfall (RCL) and recurving ocean (RCO). Based on this classification, we investigated the changes in the moisture sources' contributions to the precipitation along the TCs trajectories for each track category by applying a Lagrangian moisture source diagnostic method to the air parcels pathways from the FLEXPART model. The highest moisture contribution occurred within 3-5° from the average TCs trajectories. The moisture supplied from the Gulf of Mexico represented 19.1% of humidity gained by SM but was negligible for recurving TCs. Likewise, the Caribbean Sea contributed 31.8% for SM, and its humidity support notably decreased for recurving storms to 0.9–8.3%. In addition, the moisture uptake from the tropical NATL was similar for all track types. The western NATL increased the moisture supply from 15.3% for SM to 31.1% for RCO and 42.6% for RCL, while the eastern subtropical NATL provided 3.1% of moisture to SM, 12.5% to RCL and 45.4% to RCO. It was also notable the moisture support from the terrestrial source southeastern United States (5.3%) for RCL tracks. Furthermore, we found that El Niño–Southern Oscillation, the North Atlantic Oscillation, the Atlantic Multidecadal Oscillation and the Atlantic Meridional Mode influence the moisture contributions variability from sources for each track type Xunta de Galicia | Ref. ED481A2020/193 Ministerio de Ciencia, Innovación y Universidades | Ref. PID2021-122314OB-I00 Xunta de Galicia | Ref. ED431C 2021/44 Xunta de Galicia | Ref. ED481A2022/128

Drought events have become more frequent and severe across North America, threatening water availability in river basins and thus ecosystem and socio-economic development. This is why in this study, we investigate the occurrence, evolution, and attribution of drought conditions in nine major North American river basins, the Colorado, Columbia, Fraser, Mackenzie, Mississippi, Rio Grande, Saskatchewan-Nelson, St. Lawrence, and Yukon. The analysis was performed on a spatio-temporal scale for the period 1980-2018. Precipitation data from MSWEP and CRU were used, as well as terrestrial water storage from GRACE. In addition, the Lagrangian moisture contribution from oceanic and terrestrial origin to precipitation over the basins, named PLO and PLT, respectively, were used. Drought indices such as the Standardised Precipitation Index (SPI), Standardised Precipitation-Evapotranspiration Index (SPEI), and Drought Severity Index (DSI) were used to assess the occurrence of dry conditions at various temporal scales. In addition to the attribution of the occurrence and severity of drought extremes due to PLO and PLT deficits, the trend was assessed. The results show that despite the differentiated nature of precipitation origin between the western and eastern basins, in most of them, a joint coupling prevails in the occurrence of positive or negative trends of dry/wet conditions of oceanic and terrestrial origin, which ultimately modulate the evolution of dry/wet conditions in the basins.

Tropical cyclones (TCs) are one the principal natural hazards for coastal regions in tropical and subtropical latitudes. On a global scale, around 90 TCs form annually, and approximately 16% of them originated in the North Atlantic (NATL) basin. Heavy rainfall, one of the major hazards associated with TCs, can cause catastrophic flash flooding, landslide and related health and socio-economic problems. Therefore, understanding the precipitation origin during the passage of TCs is important to significantly aid in disaster mitigation and risk analysis. This work seeks to identify the origin of precipitation moisture within the TCs outer radius in the NATL basin from 1980 to 2018 by applying a Lagrangian moisture tracking method to air parcel trajectories. The TC information (intensity and position) was retrieved from the HURDAT2 database, while the outer radius was from the TCSize dataset. The pathways of air parcels that precipitated within the TC outer radius were obtained from the global outputs of the FLEXible PARTicle dispersion (FLEXPART) model fed by ERA-Interim reanalysis provided by the European Center for Medium-Range Weather Forecasts. The spatial moisture sources pattern exhibited a north-south split around 10ºN, coinciding with the mean position of the Intertropical Convergence Zone (ITCZ) during the boreal summer. The highest moisture contribution (~39%) during the genesis and peak of maximum intensification was from the tropical Atlantic Ocean north of ITCZ, including ~11% from the Caribbean Sean and ~6% from the Gulf of Mexico, followed by the western NATL (WNATL) with 23.8% and eastern NATL (ENATL) with 16.6%. Curiously, ~10% of moisture was from the Atlantic Ocean south of ITCZ and ~2% from the eastern Pacific Ocean. During the dissipation phase, the moisture sources shifted poleward as TCs moved, with the highest moisture support (~60.3%) from the subtropical north Atlantic Ocean (WNATL + ENATL) and ~11.2% from the NATL north of 50ºN. This behaviour shows that moisture sources for TCs precipitation are located circa to their positions. Indeed, by investigating the moisture uptake pattern along the TCs trajectories, we detected that the highest moisture uptake generally occurred within 3-5º from the TC track. Likewise, the moisture uptake within 2000 km from the TC centre was approximately two times higher during the rapid intensification than during the slow intensification process. Furthermore, the relative position of moisture sources to the TC centre changed from 24 hours before the extratropical transition (ET) process to 24 hours after. That is, before ET, the moisture sources were located in the southwest-south sector, while after ET appeared in the west-southwest sector. Overall, this work provides new insights into the TCs' climatology in the NATL basin. Additionally, these findings can be used as a reference to understand future changes in the origin of precipitation moisture for TCs precipitation under different climate changes scenarios.

Financiado para publicación en acceso aberto: Universidade de Vigo/CISUG In this study, we investigated the moisture sources for precipitation through a Lagrangian approach during the genesis, intensification, and dissipation phases of all tropical cyclones (TCs) that occurred over the two hemispheric sub-basins of the Indian Ocean (IO) from 1980 to 2018. In the North IO (NIO), TCs formed and reached their maximum intensity on both sides of the Indian Peninsula, to the east in the Bay of Bengal (BoB), and to the west in the Arabian Sea (AS). The oceanic areas where TCs occurred were their main moisture sources for precipitation associated with TCs. Additionally, for TCs over the BoB, continental sources from the Ganges River basin and the South China Sea also played a notable role; for TCs over the AS, the Somali Low-Level jet (along the African coast in a northerly direction) also acted as an essential moisture transport. In the South IO (SIO), the western, central, and eastern basins were identified as the preferred areas for the genesis and development of TCs. During TC activity, the central IO and the Wharton and Perth basins mostly supplied atmospheric moisture. The Mascarene High circulation was the main moisture transport mechanism for the precipitation of TCs formed in the SIO basin. In both basins, during their intensification process, TCs gained more moisture (even more intensely when reaching the hurricane category) than during the genesis or dissipation stages. Additionally, the modulation during monsoonal seasons of the moisture contribution to the TCs was more noticeable over the NIO basin than for the SIO. Overall, the moisture uptake for precipitation from the sources for TCs occurred slightly faster in the NIO basin than in the SIO basin. Xunta de Galicia | Ref. ED481B 2019/070 Xunta de Galicia | Ref. ED481A-2020/193 Xunta de Galicia | Ref. ED431C 2021/44 Agencia Estatal de Investigación | Ref. RTI2018-095772-B-I00 Agencia Estatal de Investigación | Ref. PID2021-122314OB-I00

Xunta de Galicia | Ref. ED431C 2021/44 Agencia Estatal de Investigación | Ref. PID2021-122314OB-I00 Universidade de Vigo/CISUG

The terrestrial and oceanic origins of precipitation over 50 major river basins worldwide were investigated for the period 1980–2018. For this purpose, we used a Lagrangian approximation that calculates the humidity that results in precipitation from the entire ocean area (ocean component of the precipitation, PLO) and the entire land area (land component, PLT) as well as the sum of both components (Lagrangian precipitation, PL). PL and its components were highly correlated with precipitation over the basins, where PLT accounted for >50 % of the PL in most of them. This confirmed the importance assigned by previous studies to terrestrial recycling of precipitation and moisture transport within the continents. However, the amount of PLO in almost all North American river basins was highlighted. The assessment of drought conditions through the Standardized Precipitation Index (SPI) at a temporal scale of 1- and 3-months revealed the number of drought episodes that affected each river basin, especially the Amazon, Congo, and Nile, because of the lower number of episodes but higher average severity and duration. A direct relationship between the severity of drought episodes and the respective severity computed on the oceanic and terrestrial SPI series was also found for the majority of basins. This highlights the influence of the severity of the SPI of oceanic origin for most basins in North America. However, for certain basins, we found an inverse relationship between the severity of drought and the associated severity according to the SPI of oceanic or terrestrial origin, thus highlighting the principal drought attribution. Additionally, a copula analysis provided new information that illustrates the estimated conditional probability of drought for each river basin in relation to the occurrence of drought conditions of oceanic or terrestrial origin, which revealed the possible main driver of drought severity in each river basin. Xunta de Galicia | Ref. ED481B-2019/070 Xunta de Galicia | Ref. ED481B-2021/134 Xunta de Galicia | Ref. ED481A-2020/193 Agencia Estatal de Investigación | Ref. RTI2018-095772-B-I00 Agencia Estatal de Investigación | Ref. PID2021-122314OB-I00 Xunta de Galicia | Ref. ED431C 2021/44 Financiado para publicación en acceso aberto: Universidade de Vigo/CISUG

Tropical-like cyclones (TLCs) are hybrid low-pressure systems formed over the Mediterranean Sea, showing the characteristics of tropical and extratropical cyclones. The literature review revealed that several studies have focused on determining the physical mechanisms that favour their formation; however, their rainfall has received little attention. In this study, we attempted to identify the origin of the precipitation produced by TLCs through a Lagrangian approach based on the analysis of moisture sources for the TLC Qendresa from 6 to 9 November 2014. For the Lagrangian analysis, we used the trajectories of air parcels from the global outputs of the FLEXPART model fed by the ERA-5 reanalysis provided by the European Centre for Medium-Range Weather Forecast and backtracked those parcels that precipitated within the outer radius of the storm up to 10 days. Our results showed that the moisture mainly came from the western Mediterranean Sea, Northern Africa, the central Mediterranean Sea, Western Europe, the eastern North Atlantic, and the eastern Mediterranean Sea with contributions of 35.09%, 27.6%, 18.62%, 10.40%, 6.79%, and 1.5%, respectively. The overall large-scale conditions for the genesis of Qendresa agreed with previous climatological studies. Therefore, our findings contribute to the understanding of precipitation associated with TLCs. Future studies will focus on a climatological analysis of the origin of rainfall produced by these hybrid cyclones. Ministerio de Ciencia, Innovación y Universidades | Ref. RTI2018-095772-B-I00 Ministerio de Ciencia, Innovación y Universidades | Ref. PID2021-122314OB-I00 Xunta de Galicia | Ref. ED431C 2021/44

Resumen Se realizó un estudio de caso de varias configuraciones de modelos de pronóstico numérico para evaluar la habilidad de los mismos en el pronóstico de la intensidad y trayectoria de los ciclones tropicales. Para ello se seleccionaron 4 configuraciones del dominio de cómputo con 27-9 y 18-6 km de resolución para el HWRF (Hurricane Weather Research and Forecasting Model) y 4 configuraciones para el WRF (Weather Research and Forecasting Model), empleando el núcleo dinámico NMM (Non-hydrostatic Mesoscale Model) con la opción de seguimiento de vórtice. Se realizaron las simulaciones correspondientes al huracán Irma desde el 1ro al 12 de septiembre del 2017 inicializadas con salidas de pronóstico del GFS (Global Forecast System). En la evaluación realizada no se observaron diferencias notables entre las 8 configuraciones, aunque fue deficiente el pronóstico de la intensidad del huracán Irma, con un error en el pronóstico de la velocidad máxima del viento superior a los 50 km/h. La comparación de las salidas de cada configuración con los registros de las boyas y estaciones meteorológicas de superficie evidenció que el comportamiento de las variables viento y presión atmosférica tiene una tendencia similar a los valores registrados en las estaciones, con errores inferiores a los 3.8 m/s para la velocidad del viento y 3 hPa para la presión atmosférica. La configuración que mostró mejor habilidad para el pronóstico de ciclones tropicales fue HWRF_18-6-m (referida al modelo y la resolución horizontal empleada), aunque es la que más capacidad de cómputo requiere. Abstract A study of several configurations of numerical forecast models was conducted to evaluate their skill to forecast tropical cyclones track and intensity. For this, four configurations of the horizontal domain were selected with 27-9 and 18-6 km of resolution for HWRF (Hurricane Weather Research and Forecasting Model) and four configurations for the WRF (Weather Research and Forecasting Model), using the dynamic core NMM (Non-hydrostatic Mesoscale Model) with the vortex tracker option. Simulations corresponding to Hurricane Irma were done from 1st to 12th September 2017, initialized with GFS (Global Forecast System) forecast outputs. No notable differences were observed between the eight configurations, although the forecast of the intensity of Hurricane Irma was deficient, with an error in the forecast of the maximum wind speed above 50 km/h. The comparison of the outputs of each configuration with buoys and surface meteorological stations data showed that the behavior of the wind speed and atmospheric pressure variables has a similar tendency to the registered values in the stations, with errors lower than 3.8 m/s for wind speed and 3 hPa for atmospheric pressure. HWRF 18-6-m (referred to the model and the horizontal domain resolution) was the configuration that showed the best ability for tropical cyclones forecast, although it require large time to compute.

Global warming and associated changes in atmospheric circulation patterns are expected to alter the hydrological cycle, including the intensity and position of moisture sources. This study presents predicted changes for the middle and end of the 21st century under different climate scenarios for two important extratropical moisture sources: the North Atlantic Ocean (NATL) and Mediterranean Sea (MED). By the end of the century, moisture from the NATL will increase precipitation over eastern North America in winter, western Europe in spring, and northwestern Africa during winter and summer. Moisture from the MED will increase precipitation over the southern and western portions of the Mediterranean continental area. Precipitation associated with the MED will decrease over eastern Europe, while that associated with the NATL will decrease over western Europe and Africa. Precipitation recycling on the Iberian Peninsula will increase in all seasons except winter. Climate change, as simulated by CESM2 thus modifies atmospheric moisture transport, affecting regional hydrological cycles.

In this study, we evaluated the ability of the Numerical Tools for Hurricane Forecast (NTHF) system, operational at the Department of Meteorology of the Higher Institute of Technologies and Applied Sciences, University of Havana, Cuba, for forecasting the intensity and trajectory of the North Atlantic (NATL) tropical cyclones (TCs). To assess the ability of the NTHF system in the first five years (2016–2020) of operational runs, we used the best tracks from the National Hurricane Center HURDAT2 database. The errors in the track forecast increased linearly from 41 km at 6 h to 356 km at 120 h. In addition, NTHF underestimates the intensity of TCs, especially those that reach Category 3+ hurricanes on the Saffir–Simpson wind scale. Overall, the mean absolute error in forecasting the maximum wind speed (minimum pressure) ranged from 26.5 km/h (7 hPa) to 33.7 km/h (11.7 hPa). Moreover, the highest BIAS in the intensity forecast was found in the first 48 h, suggesting that model initialization is the main driver of NTHF errors in the forecast maximum wind speed and the minimum central pressure of TCs in the North Atlantic Basin.

Heavy rainfall events, typically associated with tropical cyclones (TCs), provoke intense flooding, consequently causing severe losses to life and property. Therefore, the amount and distribution of rain associated with TCs must be forecasted precisely within a reasonable time to guarantee the protection of lives and goods. In this study, the skill of the Numerical Tool for Hurricane Forecast (NTHF) for determining rainfall pattern, average rainfall, rainfall volume, and extreme amounts of rain observed during TCs is evaluated against Tropical Rainfall Measuring Mission (TRMM) data. A sample comprising nine systems formed in the North Atlantic basin from 2016 to 2018 is used, where the analysis begins 24 h before landfall. Several statistical indices characterising the abilities of the NTHF and climatology and persistence model for rainfalls (R-CLIPER) for forecasting rain as measured by the TRMM are calculated at 24, 48, and 72 h forecasts for each TC and averaged. The model under consideration presents better forecasting skills than the R-CLIPER for all the attributes evaluated and demonstrates similar performances compared with models reported in the literature. The proposed model predicts the average rainfall well and presents a good description of the rain pattern. However, its forecast of extreme rain is only applicable for 24 h.

In this study, we identified the origin of the moisture associated with the tropical cyclones (TCs) precipitation in the North Atlantic Ocean basin during their three well-differentiated life stages between 1980 and 2018. The HURDAT2 database was used to detect the location of 598 TCs during their genesis, maximum intensification peak, and dissipation phases. The global outputs of the Lagrangian FLEXPART model were then used to determine the moisture sources. Using a K-means cluster analysis technique, seven different regions were identified as the most common locations for the genesis and maximum intensity of the TC phases, while six regions were found for the dissipation points. Our results showed that the origin of moisture precipitating was not entirely local over the areas of TC occurrence. The North Atlantic Ocean to the north of the Inter Tropical Convergence Zone at 10°N (NATL) -especially from tropical latitudes, the Caribbean Sea and the Gulf of Mexico- provides most of the moisture for TCs (∼87%). The Atlantic Ocean basin southward the ITCZ (SATL) played a non-negligible role (∼11%), with its contribution being most pronounced during the TC genesis phase, while the eastern tropical Pacific Ocean made the smallest contribution (∼2%). The moisture supported by TCs varied depending on their category, being higher for hurricanes than for major hurricanes or tropical storms. Additionally, the approach permitted to estimate the mean residence time of the water vapour uptake that produce the precipitation during TC activity, which ranged between 2.6 and 2.9 days.

Financiado para publicación en acceso aberto: Universidade de Vigo/CISUG In this study was performed a comparative climatology of outer tropical cyclone (TCs) size using radial wind profiles. A wind speed of 2 ms (4 kt) was taken as the threshold to define the TC size. The method proposed by Willoughby et al. (2006) (W06) to determine the wind profile showed the least variance and the smallest coefficient of variation of all profiles. W06 correctly described the radial wind structure of storms such as Hurricane Irma (2017) and Cyclone Giri (2010), compared with the European Centre for Medium-Range Weather Forecasts ERA-5 reanalysis data. Thus, W06 was used to develop the climatological TC size (TCSize) database. It was found that the tropical cyclones are largest when the maximum wind speed ranges between 20 and 40 ms and they most frequently reach a size between 700 and 800 km. The TCs exhibit their maximum size when they are in extratropical latitudes, while the smallest are observed in the low latitudes of both hemispheres. The global mean size is 748.7 km with a 95% confidence interval of [748.2,749.2] km. Median storm size is largest in the North Atlantic basin and smallest in the North Indian Ocean. The method proposed here is designed to be an objective metric that can be quickly applied to any TC when its position, maximum wind speed, and minimum central pressure are known. As a result, a TCSize database was created for all ocean basins, which could be useful for many applications, including different risk analyses. Xunta de Galicia | Ref. ED481A-2020/193 Xunta de Galicia | Ref. ED481B 2019/070 Xunta de Galicia | Ref. ED431C 2021/44

In this study, the moisture sources for the explosive cyclogenesis Miguel that occurred during 4–9 June 2019 in the North Atlantic were investigated. To determine the moisture sources, the Lagrangian FLEXPART particle dispersion model was used. The moisture uptake pattern revealed the western North Atlantic Ocean extending to north-western North America, the south-eastern coast of Greenland, and the central North Atlantic Ocean around 45° N and 50°–20° W as the main moisture sources for Miguel explosive cyclogenesis. Furthermore, the moisture uptake from these regions was higher than the climatology. During the intensification of Miguel, the moisture contribution from oceanic sources was higher than terrestrial sources. Although the total amount of atmospheric moisture achieved during the explosive intensification was similar to that absorbed the 24 h prior, they changed in intensity geographically, being more intense the local support over central and northern North Atlantic basin.

This study examined the water budget of Hurricane Irma (2017) through a Lagrangian approach. To identify the moisture sources for the Hurricane Irma genesis and intensification the particle dispersion model FLEXPART was used. The North Atlantic Ocean between 15° and 30° North latitude and the South Atlantic Ocean were identified as the main moisture sources for Irma development. From the perspective of the water budget, the maximum accumulated precipitation along Irma’s trajectory coincides with the maximum water budget efficiency, which suggests that total precipitation depends largely on the water vapour supplied, rather than the storm intensity. Furthermore, the moisture supply from the surface under the area delimited by hurricane size is small, thus, the water vapour supply from the environment through the secondary circulation transports more moisture inward. Ministerio de Ciencia, Innovación y Universidades | Ref. RTI2018-095772-B-I00 Xunta de Galicia | Ref. ED431C 2017/64-GRC Xunta de Galicia | Ref. ED481A-2020/193 Xunta de Galicia | Ref. ED481B 2019/070 Xunta de Galicia | Ref. ED431C 2021/44

The short-term prediction of precipitation is a difficult spatio-temporal task due to the non-uniform characterization of meteorological structures over time. Currently, neural networks such as convolutional LSTM have shown ability for the spatio-temporal prediction of complex problems. In this research, we propose an LSTM convolutional neural network (CNN-LSTM) architecture for immediate prediction of various short-term precipitation events using satellite data. The CNN-LSTM is trained with NASA Global Precipitation Measurement (GPM) precipitation data sets, each at 30-min intervals. The trained neural network model is used to predict the sixteenth precipitation data of the corresponding fifteen precipitation sequence and up to a time interval of 180 min. The results show that the increase in the number of layers, as well as in the amount of data in the training data set, improves the quality of the forecast.

This study evaluates the performance of the Numerical Tools for Hurricane Forecast (NTHF) system during the 2020 North Atlantic (NATL) tropical cyclones (TCs) season. The system is configured to provide 5-day forecasts with basic input from the National Hurricane Center (NHC) and the Global Forecast System. For the NTHF validation, the NHC operational best track was used. The average track errors for 2020 NATL TCs ranged from 62 km at 12 h to 368 km at 120 h. The NTHF track forecast errors displayed an improvement over 60% above the guidance Climatology and Persistence (CLIPER) model from 36 h to 96 h, although the NTHF was better than the CLIPER in all forecast periods. The forecast errors for the maximum wind speed (minimum central pressure) ranged between 20 km/h and 25 km/h (4 hPa to 8 hPa), but the NTHF model intensity forecasts showed only marginal improvement of less than 20% after 78 h over the baseline Decay Statistical Hurricane Intensity Prediction Scheme (D-SHIPS) model. Nevertheless, the NTHF’s ability to provide accurate intensity forecasts for the 2020 NATL TCs was higher than the NTHF’s average ability during the 2016–2019 period.

The phenomenon of drought is one of the most dangerous for small islands because of its impacts on freshwater availability. Thus, in this study, the spatio-temporal evolution of meteorological drought that affected the main island of Puerto Rico in the period 1950–2019 was investigated. In doing so, the Standardized Precipitation–Evapotranspiration Index (SPEI), using monthly values of minimum and maximum temperatures and precipitation derived from Daymet Version 4 daily data at a 1 km × 1 km spatial resolution, was used. At a 1 month temporal scale, the SPEI showed great temporal variability, but there was a clear tendency towards wetting in the last years of the study period. A total of 85 meteorological drought episodes were identified. The spatial analysis also revealed that major affectation by moderate drought conditions occurred across the half west and south of the island, by severe drought also in the west half of the island but also along the eastern coast, and finally the extreme drought conditions, which were less frequent, principally affected the northeast of the country. A trend analysis of the area affected by moderate, severe, and extreme drought conditions revealed a tendency to decrease, which is reflected by the prevalence of positive spatial trends of the SPEI1 across the country.

Resumen En el Aeropuerto Internacional “José Martí” de La Habana (MUHA), el nivel de exactitud que presentan los pronósticos de dirección del viento se aproximan a un 70%, los mismos no cumplen con los requisitos establecidos por las regulaciones aeronáuticas que exigen que la efectividad sea mayor al 85%. Por ello, se implementó un pronóstico numérico del campo de viento a mesoescala y a corto plazo utilizando los modelos WRF-NMM y Masa Consistente, que pretende mejorar el pronóstico realizado por el Ogimet, herramienta numérica de pronóstico del viento empleada en el MUHA. Se experimentó con distintos métodos de interpolación, obteniendo los mejores resultados con el vecino natural con la corrección del modelo de Masa Consistente. Se desarrolló una herramienta computacional capaz de ofrecer los pronósticos numéricos de campo de viento para el MUHA correspondientes a las 0000, 0600, 1200, 1800 UTC, con una habilidad superior al Ogimet y con una efectividad del 91% para el pronóstico numérico del campo de viento. Abstract At the “José Martí” International Airport in Havana (MUHA), the level of accuracy presented by wind direction forecasts is close to 70%, they do not meet the requirements established by the aeronautical regulations which effectiveness must be higher than 85%. Therefore, a numerical forecast of the wind field was implemented at mesoscale, in a short term, using the WRF-NMM and Consistent Mass models that are aimed to improve the forecast made by the Ogimet, a wind forecast numerical tool used in the MUHA. It was experimented with different interpolation methods; the best results were obtained on the natural neighbor with the correction of Consistent Mass model. A computational tool was developed which provided the numerical wind field forecasts for the MUHA corresponding to the 0000, 0600, 1200 and 1800 UTC which have a greater ability than the Ogimet and with an effectivity of 91% for numerical forecast of the wind field.

Precipitation extremes such as heavy rainfall and floods are of great interest for climate scientists, particularly for small islands vulnerable to weather phenomena such as hurricanes. In this study, we investigated the spatio-temporal evolution of extreme rainfall over Cuba from 1980 to 2019, separating the dry and rainy periods. In addition, a ranking of extreme precipitation events was performed, which provides the number of events, the area affected, and a ranking of their magnitude by considering the magnitude of anomalies. The analysis was conducted using daily data from the multi-source weighted-ensemble precipitation (MSWEPv2). In determining the extreme precipitation ranking, the daily extreme precipitation anomaly was calculated with respect to the 95th percentile climatological distribution, giving a measure of the rarity of the event for each day and each grid point. For a more detailed analysis regarding the ranking, a separation was made by regions applying the K-mean methodology. The months belonging to the rainy period of the year presented the highest amount of precipitation above the 95th percentile compared to results obtained for the dry period. Of the six months belonging to the cyclonic season, in five of them Cuba was affected, directly or indirectly, by a tropical cyclone. The years 1982–83 and 1998 presented the highest-ranking value for the dry and rainy periods, respectively. Moreover, a trend analysis revealed an increase in the trend of occurrence of extreme events and a decrease in the percentage of the area affected. The analysis by regions showed a similar behavior to that carried out for all of Cuba. It was found that the warm phase of the ENSO events influenced approximately ~22% of the occurrence of extreme events for both periods. Xunta de Galicia | Ref. ED431C 2021/44

This study investigated the number of tropical cyclones (TCs) that affected Puerto Rico during the June-November hurricane season in the period 1980-2016, and their contribution to total precipitation. Special attention was dedicated to assessing the role of atmospheric-oceanic teleconnections in the formation of TCs that affect this island. The HURDAT2 tropical cyclone climatology database and the multi-source weighted set precipitation (MSWEP) v2 data with a spatial resolution of 0.1 ° x 0.1 ° were used. A total of 92 TCs within a 500-km radius of Puerto Rico were identified for the study period. Contrary to what was expected, a similar percentage of affectation was found between those TCs formed under El Nino (17.39 %) and La Nina (17.39 %) conditions. Regarding the North Atlantic Oscillation, a 23.91 % of the 92 TCs that affected Puerto Rico formed under the negative phase, while the 13.04 % during the positive phase, which is explained in agreement with previous findings with the weakening and shift to the south and west of the Azores High during the negative phase of NAO. The role of the Sea Surface Temperature on the genesis of TCs that affected Puerto Rico was also assessed through the Atlantic Meridional Mode (AMM) and the Atlantic Warm Pool area. In the positive (negative) phase of the AMM was formed the 23.91 % (3.26 %) of the total number of TCs, while under larger (smaller) AWP formed the 61.96 % (16.3 %). It confirms that the affectation of TCs in Puerto Rico is highly related to the eastward extension of the AWP and the SST gradient in the tropical North Atlantic region. Indeed, a westward shift in genesis position was found from July to November. The mean TC rainfall contribution for the cyclonic season was ~ 9 %. It experimented a great interannual variability during the study period and a positive but non-significant trend. As expected, the correlation of the TC rainfall contribution is positively correlated (r = 0.54) with the amount of TCs. Finally, a monthly analysis revealed that in August and September the maximum contribution of rain from CT occurred (~ 17 %), followed by October (~ 6 %) and November (~ 4 %).

Atmospheric moisture transport plays an important role in the genesis of tropical cyclones (TCs). In this study, the moisture sources associated with the genesis of TCs in the tropical Atlantic Ocean near West Africa, from June to November in the period 1980–2018, were identified. To detect the location of the TCs geneses, the HURDAT2 database from the National Hurricane Center was used. Additionally, global outputs of the Lagrangian FLEXPART model were used to determine the moisture sources that provided water vapor for the genesis of TCs. This model permitted us to track backward in time the air masses from the genesis region of the TCs and identify regions where air masses uptake moisture before reach the target regions. The results reveal that 18.1% (108 TC) of the total number of TCs that formed in the North Atlantic basin were originated in the region of study. The largest frequency for the TCs geneses was observed in August and September, with each one representing approximately 45% of the total. The transport of moisture associated with the genesis of TCs mainly comes from the east of the North and South Atlantic Ocean, as well as from West Africa and the Sahel region. The patterns of moisture uptake confirmed an interhemispheric moisture transport. Finally, during the El Nino, the moisture uptake is more intense over the Atlantic Ocean close to West Africa around 15 °N of latitude, while during La Nina, the pattern is slightly weaker but covers a wider area over the Atlantic Ocean and the north of Africa.

A sensitivity study was developed with Lin, Morrison 2-moment, weather research and forecasting (WRF) single-moment 5-class (WSM5), and WRF single-moment 6-class (WSM6) microphysics schemes available in the weather research and forecasting-advanced research WRF (WRF-ARW) for the numerical forecast of the wind field at Jose Marti International Airport, in Cuba. The selection of these schemes was based on their use in numerical weather forecast systems operating in Cuba. As case studies, five storms associated with synoptic patterns that cause dangerous conditions at this aerodrome were selected. The simulations were initialized at 0000 UTC with the forecast outputs of the global forecast system (GFS) model. The schemes were evaluated according to the wind field’s representation in the region where the airport is located, the headlands, and the center of the runway. The errors observed are strongly dependent on the occurrence of convection, especially on the intensity and the factors that cause it. During the dry season (November–April), the lowest errors are observed, while the worst performance is appreciable for the rainy period (May–October). Lin and WSM6 schemes reproduce the best behavior of the wind field on the aerodrome.