Evaluation of downscaled, gridded climate data for the conterminous United States

Abstract

Weather and climate affect many ecological processes, making spatially continuous yet fine-resolution weather data desirable for ecological research and predictions. Numerous downscaled weather data sets exist, but little attempt has been made to evaluate them systematically. Here we address this shortcoming by focusing on four major questions: (1) How accurate are downscaled, gridded climate data sets in terms of temperature and precipitation estimates? (2) Are there significant regional differences in accuracy among data sets? (3) How accurate are their mean values compared with extremes? (4) Does their accuracy depend on spatial resolution? We compared eight widely used downscaled data sets that provide gridded daily weather data for recent decades across the United States. We found considerable differences among data sets and between downscaled and weather station data. Temperature is represented more accurately than precipitation, and climate averages are more accurate than weather extremes. The data set exhibiting the best agreement with station data varies among ecoregions. Surprisingly, the accuracy of the data sets does not depend on spatial resolution. Although some inherent differences among data sets and weather station data are to be expected, our findings highlight how much different interpolation methods affect downscaled weather data, even for local comparisons with nearby weather stations located inside a grid cell. More broadly, our results highlight the need for careful consideration among different available data sets in terms of which variables they describe best, where they perform best, and their resolution, when selecting a downscaled weather data set for a given ecological application.

Bias correcting instantaneous peak flows generated using a continuous, semi‐distributed hydrologic model

“…The calibrated parameter values are also dependent upon the available climatic inputs to the system (Starks and Moriasi 2009). The gridded values from the Maurer et al () data set have been shown to be close to observed values (Behnke et al, ; Maurer et al, ), and herein, statistics between gridded and local precipitation were well matched (Table ). Nonetheless, differences in precipitation intensity and spatial representation would affect model calibration.…”

“…Hydrological modelling studies have illustrated that the Maurer et al () data set can accurately simulate surface runoff as demonstrated using several large test basins forced with the gridded precipitation and temperature data (Behnke et al, ; Maurer et al, ). In fact, the Maurer et al data set consistently showed stronger agreement with observed precipitation and temperature than other gridded products, including PRISM, NLDAS2, TopoWx, and Dayment data sets (Behnke et al, ).…”

“…Hydrological modelling studies have illustrated that the Maurer et al () data set can accurately simulate surface runoff as demonstrated using several large test basins forced with the gridded precipitation and temperature data (Behnke et al, ; Maurer et al, ). In fact, the Maurer et al data set consistently showed stronger agreement with observed precipitation and temperature than other gridded products, including PRISM, NLDAS2, TopoWx, and Dayment data sets (Behnke et al, ). Therefore, as the Maurer et al data set is reasonably well established at accurately simulating the hydrological system and is frequently used as a means for deriving bias‐correction factors for GCM precipitation and temperature outputs (Meehl, Covey, McAvaney, Latif, & Stouffer, ), it was deemed an appropriate forcing for the SWAT models herein.…”

Mapping evaporative water loss in desert passerines reveals an expanding threat of lethal dehydration

“…Our model focuses on meteorological T air , which for birds in hot desert environments, is typically a minimum index of thermal stress in the absence of radiative and convective heat fluxes, and approximates the thermal conditions in a completely shaded and ventilated meteorological thermoscreen. There is also evidence that North American Land Data Assimilation System (NLDAS) and other gridded climate products often underestimate maximum temperatures by 1°C or more (22), underscoring the conservative nature of our analysis. Nevertheless, it may be possible for individuals to use cooler microsites (e.g., burrows and sites in dense vegetation) (23).…”

Towards connecting biodiversity and geodiversity across scales with satellite remote sensing

“…For this reason, spatial models of species distributions and biodiversity have traditionally used topographic data as a proxy variable for climatic or environmental variance, often combining them with gridded data interpolated from weather stations (Waltari, Schroeder, McDonald, Anderson, & Carnaval, ). However, recent work highlighted the wide range of methods and accuracies among products, showing that there is no “best” product and that higher‐resolution products are not necessarily more accurate (Behnke et al, ). Recent satellite missions, such as Landsat 8, Sentinel‐1, Sentinel‐2 and ICESat‐2, enable accurate and continuous acquisition of global geodiversity data in space and time (Figure b; Supporting Information Appendix A).…”