Naresh R. Seegobin

Many Caribbean low-latitude small island states lack wind maps tailored to capture their wind features at high resolutions. However, high-resolution mesoscale modeling is computationally expensive. This study proposes a statistical–dynamical downscaling (SDD) method that integrates an atmospheric-circulation-type (CT) approach with a high-resolution numerical weather prediction (NWP) model to map the wind resources of a case study, Trinidad and Tobago. The SDD method uses a novel wind class generation technique derived directly from reanalysis wind field patterns. For the Caribbean, 82 wind classes were defined from an atmospheric circulation catalog of seven types derived from 850 hPa daily wind fields from the NCEP-DOE reanalysis over 32 years. Each wind class was downscaled using the Weather Research and Forecasting (WRF) model and weighted by frequency to produce 1 km × 1 km climatological wind maps. The 10 m wind maps, validated using measured wind data at Piarco and Crown Point, exhibit a small positive average bias (+0.5 m/s in wind speed and +11 W m⁻² in wind power density (WPD)) and capture the shape of the wind speed distributions and a significant proportion of the interannual variability. The 80 m wind map indicates from good to moderate wind resources, suitable for determining priority areas for a detailed wind measurement program in Trinidad and Tobago. The proposed SDD methodology is applicable to other regions worldwide beyond low-latitude tropical islands.

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.