Rainfall in the Greater and Lesser Antilles: Performance of five gridded datasets on a daily timescale

Bathelemy, Ralph; Brigode, Pierre; Boisson, Dominique; Tric, Emmanuel

doi:10.1016/j.ejrh.2022.101203

Cited by 11 publications

(10 citation statements)

References 75 publications

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“…The results from this study highlight the value of utilizing and evaluating gridded and insitu observational precipitation datasets in the Caribbean. This study found several large biases in PERSIANN and ERA5 precipitation compared to station rainfall data, supporting the claim that other studies (e.g., Centella-Artola et al 2020;Bathelemy et al 2022) have made regarding the usage of these datasets versus better performing datasets (MSWEPv2, GPCC025, and CHIRPSv2), and highlights that the higher spatial resolution precipitation datasets do not necessarily perform better than coarser datasets.…”

Section: Discussionsupporting

confidence: 85%

An Evaluation of the Seasonal Caribbean Hydroclimate in Low and High-Resolution CESM and other CMIP6 Models

Martinez¹,

Simpson²,

Fasullo³

et al. 2023

Preprint

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The Caribbean and Central American hydroclimate is understudied and complex in part due to its data sparsity, varied topographies, and multi-faceted interactions with the tropics and mid-latitudes. Recent work developed a refined and comprehensive understanding of the observed hydroclimate that has yet to be explored in global circulation models. This study investigates the simulation of the Caribbean hydroclimate using a suite of station and gridded observational datasets, the Community Earth System Model version 1 (CESM1) at high (0.25x0.25°) and low (0.9x1.25°) resolution, CESM2 at low (0.9x1.25°) resolution, the Coupled Model Intercomparison Project phase 6 (CMIP6) High-Resolution Model Intercomparison Project (HighResMIP), and the Geophysical Fluid Dynamics Laboratory Seamless System for Prediction and Earth System Research (GFDL-SPEAR). The simulated climatologies (1983-2014) of the annual rainfall cycle and total moisture fluxes, and climatological correlation coefficients of sea surface temperatures (SST), sea-level pressure (SLP), and zonal/meridional low-level winds onto indices of seasonal Caribbean rainfall totals are calculated to investigate inter-model differences. Generally, fully coupled CESM, GFDL-SPEAR-MED, and CMIP6 simulations underestimate precipitation across the Caribbean, with some improvements using high-resolution (<0.5°) simulations. The underestimations are largest during the Early-Rainy Season (ERS; mid-April to mid-June). Coupled models also show a moisture divergence bias associated with a stronger/west-displaced North Atlantic Subtropical High (NASH), a weaker / southward displaced Intertropical Convergence Zone (ITCZ), and stronger Caribbean Low-Level Jet (CLLJ). Precipitation and large-scale dynamic biases in experiments with observation-based SSTs are smaller, regardless of their spatial resolution, suggesting SST biases in coupled models may contribute to precipitation and dynamic biases. The findings emphasize the importance of both high-resolution and accurate simulation of coupled dynamical interactions in global circulation models to accurately simulate the Caribbean’s hydroclimate, and, therefore, provide reliable future climate projections for the region.

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Section: Discussionsupporting

confidence: 85%

An Evaluation of the Seasonal Caribbean Hydroclimate in Low and High-Resolution CESM and other CMIP6 Models

Martinez¹,

Simpson²,

Fasullo³

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…Among the evergreens, there are low altitude rainforests, it occurs in metamorphic rocks (Santo Domingo, Sierra Purial) up to 400 m asl. The area of this rainforest agrees with the area with the highest rainfall in Cuba, since more than 3,000 mm fall [10]. Frequently there is on the surface of the IOP Publishing doi:10.1088/1755-1315/1212/1/012029 4 soil a layer of roots and rootlets with a thickness of 3 to 5 cm, in other places such a layer does not form; these rootlets, along with the first few centimeters of soil, make up the main nutrient absorption and recycling subsystem in this ecosystem (figure 2b).…”

Section: Resultssupporting

confidence: 74%

Landslide processes as a natural disturbance in ecosystems in the Alejandro de Humboldt National Park, Cuba

Pospehov,

Savon-Vaciano,

Hernandez-Columbie

2023

IOP Conf. Ser.: Earth Environ. Sci.

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The present work addressed the occurrence of landslide processes as a disturbing element for some ecosystems in the Alejandro de Humboldt National Park in the northeastern part of the Republic of Cuba. A landslide inventory was carried out with Sentinel images as the main source of information. Factors such as geology, relief and soil were also considered as conditioning elements for the occurrence of landslides. The vegetation was classified according to O.J Reyes 2012 and the inventory of vertebrate species in Cuba was used, according to the International Union for Conservation of Nature. A total of 206 landslides in the park were inventoried. The areas with the highest density of landslides developed mainly in a very abrupt relief, where sedimentary rocks and brown soils predominate; These areas coincide with those of low altitude rainforest development and where the largest number of vertebrate species is found.

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“…Five statistical measures, including the coefficient of correlation (CC), mean absolute error (MAE), percent bias (PBias), root-mean-square error (RMSE), and the Kling-Gupta efficiency (KGE), were used in the validation. These metrics are commonly used in assessing the accuracy and reliability of rainfall estimation models [67,68]. Equations ( 3)- (7) show the aforementioned statistical measures, where S and G represent satellite/gridded and gauge precipitation, respectively, and n is the total number of measurements, i is the index of data, S is the average value of S i , and G is the average value of G i .…”

Section: Phase 5: Data Validationmentioning

confidence: 99%

Sequential Data Processing for IMERG Satellite Rainfall Comparison and Improvement Using LSTM and ADAM Optimizer

et al. 2023

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This study introduces a systematic methodology whereby different technologies were utilized to download, pre-process, and interactively compare the rainfall datasets from the Integrated Multi-Satellite Retrievals for Global Precipitation Mission (IMERG) satellite and rain gauges. To efficiently handle the large volume of data, we developed automated shell scripts for downloading IMERG data and storing it, along with rain gauge data, in a relational database system. Hypertext pre-processor (pHp) programs were built to visualize the result for better analysis. In this study, the performance of IMERG estimations over the east coast of Peninsular Malaysia for the duration of 10 years (2011–2020) against rain gauge observation data is evaluated. Moreover, this study aimed to improve the daily IMERG estimations with long short-term memory (LSTM) developed with Python. Findings show that the LSTM with Adaptive Moment Estimation (ADAM) optimizer trained against the mean square error (MSE) loss enhances the accuracy of satellite estimations. At the point-to-pixel scale, the correlation between satellite estimations and ground observations was increased by about 15%. The bias was reduced by 81–118%, MAE was reduced by 18–59%, the root-mean-square error (RMSE) was reduced by 1–66%, and the Kling–Gupta efficiency (KGE) was increased by approximately 200%. The approach developed in this study establishes a comprehensive and scalable data processing and analysis pipeline that can be applied to diverse datasets and regions encountering similar domain-specific challenges.

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Rainfall in the Greater and Lesser Antilles: Performance of five gridded datasets on a daily timescale

Cited by 11 publications

References 75 publications

An Evaluation of the Seasonal Caribbean Hydroclimate in Low and High-Resolution CESM and other CMIP6 Models

An Evaluation of the Seasonal Caribbean Hydroclimate in Low and High-Resolution CESM and other CMIP6 Models

Landslide processes as a natural disturbance in ecosystems in the Alejandro de Humboldt National Park, Cuba

Sequential Data Processing for IMERG Satellite Rainfall Comparison and Improvement Using LSTM and ADAM Optimizer

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