Numerical wind mapping is currently the wind power industry’s standard for preliminary assessments for sites of good wind resources. Of the various available numerical models, numerical weather prediction (NWP) models are best suited for modeling mesoscale wind flows across small islands. In this study, the Weather Research and Forecast (WRF) NWP model was optimized for simulating the wind resources of the Caribbean islands of Trinidad and Tobago in terms of spin-up period for developing mesoscale features, the input initial and boundary conditions, and the planetary boundary layer (PBL) parameterizations. Hourly model simulations of wind speed and wind direction for a one-month period were compared with corresponding 10 m level wind observations. The National Center for Environmental Prediction (NCEP)-Department of Energy (DOE) reanalysis of 1.875° horizontal resolution was found to be better suited to provide initial and boundary conditions (ICBCs) over the 1° resolution NCEP final analysis (FNL); 86% of modeled wind speeds were within ±2 m/s of measured values at two locations when the coarse resolution NCEP reanalysis was used as compared with 55–64% of modeled wind speeds derived from FNL. Among seven PBL schemes tested, the Yonsei University PBL scheme with topographic drag enabled minimizes the spatial error in wind speed (mean bias error +0.16 m/s, root-mean-square error 1.53 m/s and mean absolute error 1.21 m/s) and is capable of modeling the bimodal wind speed histogram. These sensitivity tests provide a suitable configuration for the WRF model for mapping the wind resources over Trinidad and Tobago, which is a factor in developing a wind energy sector in these islands.

The day-to-day variability of the atmospheric circulation over the Caribbean region is investigated in this work through the extraction of frequently occurring atmospheric circulation types. A two-stage cluster analysis technique using Ward’s agglomerative algorithm followed by the k-means algorithm was applied to daily circulation defined by the NCEP/DOE reanalysis wind components at the 850 hPa level for the period 1979–2010. Seven atmospheric circulation types (CTs) were extracted. The daily circulation types are distinguished through the extension and location of the well-known quasi-stationary Atlantic and Pacific anticyclones. However, three of the circulation types show a third anticyclonic feature, a Gulf of Mexico anticyclone which is not observed on monthly scales because it is transient with a mean lifetime of 2–3 days and rarely occurs in the July–September period. Other notable characteristics include the decrease in annual frequency of a circulation type defined by the transient Gulf of Mexico anticyclone, a neutral area over the Greater Antilles islands and weaker than average easterly winds. In addition, a second type with south-easterly winds throughout the Caribbean increases in annual frequency. This latter type also had events lasting as long as 85 days. The monthly frequency of the CTs that prevail during the dry season is correlated with several Atlantic and Pacific based teleconnections. The resulting daily atmospheric circulation types in this work comprise the first atmospheric circulation catalogue, of many to come, for the Caribbean region and may be useful in statistical–dynamical downscaling applications to explain the variability of surface weather variables such as wind speeds.

In tropical small islands the application of hydrological modelling is challenged by the scarcity of input data. Using in-situ and statistically estimated data, a hydrological model was calibrated and validated for the Upper Navet watershed in Trinidad, a small Caribbean island. The model was built using the soil water assessment tool (SWAT). The sensitivity analysis, calibration and validation were performed in SWAT calibration and uncertainty program (SWAT-CUP) using sequential uncertainty fitting (SUFI-2). The results revealed that for the estimated volume of water flowing into the reservoir (Flow_In) there were six sensitive parameters. To estimate the reservoir volume (Res_Vol), a modification of only the effective hydraulic conductivity was required. The model’s performance for the Flow_In validation showed acceptable values (R² = 0.91 and NSE = 0.81). The uncertainty analysis indicated lower than recommended values for both theR-factor (0.46) andP-factor (0.31). For Res_Vol, the model’s validation performance indicated acceptable values (R² = 0.72 and NSE = 0.70) and theP- andR-factors were 0.80 and 0.64, respectively. Based on the statistical metrics, the uncertainty for the Res_Vol was regarded as reasonable. However, care must be taken with the model’s use in the dry season, as the simulated Flow_In was generally over-predicted. A second validation of the model was performed for the reservoir under different negative (removal) and positive (addition) water amounts which confirmed the model’s ability to estimate the Res_Vol. The hydrological model established can therefore serve as a useful tool for water managers for the estimation of the Res_Vol at the Navet reservoir.