Results from this study provide global climate data recommendations for the models used in the Spatial Analytical Framework for Advanced Risk Information Systems (SAFARIS) project – a collaboration between the Center for Integrated Pest Management (CIPM) at NC State University and the United States Department of Agriculture (USDA) Animal and Plant Health Inspection Service (APHIS). The goal of SAFARIS is to contribute forecasts of the behavior of potentially harmful pests to APHIS’ Plant Protection and Quarantine (PPQ) program. These pest forecasts inform risk assessment and management for the United States and the entire globe.
This study quantitatively analyzes minimum and maximum temperature as well as precipitation data for two global climate datasets – Climate Forecast System Reanalysis (CFSR) and Climate Forecast System Version 2 (CFSv2) – to determine the level of accuracy as compared to Global Historical Climatology Network-Monthly (GHCN-M) data. Global error and bias of the two Climate Forecast System datasets are calculated using ground-station – grid-point pairs all over the world. In addition, a regional scale analysis is performed for each continent and sub-region within the continental United States.