Page 143 - GIS for Science, Volume 3 Preview

RISING HEAT
Thermometer readings around the world show that temperatures have been rising since the Industrial Revolution. Scientists have high confidence that global temperatures will continue to rise for decades, largely due to greenhouse gases produced by human activities. Because the warming is superimposed on a naturally varying climate, the temperature rise has not been, and will not be, uniform or smooth across a country or over time. Scientists benefit from a high-resolution daily dataset that provides a long temporal range of weather data. The Daymet dataset provides gridded, continuous measurements of near-surface meteorological conditions often where no instrumentation exists. Weather parameters generated include daily surfaces of minimum and maximum temperature, precipitation, vapor pressure, shortwave radiation, snow water equivalent, and day length produced on a 1 km × 1 km gridded surface.
Daymet is a data product founded on ground-based observational data. It is derived from a collection of algorithms and computer software designed to interpolate and extrapolate from daily discrete meteorological observations to produce continuous gridded estimates of daily weather parameters. Having estimates of these surfaces is critical to understanding many processes in the terrestrial biogeochemical system.
Additional model inputs include a digital elevation model derived from the NASA Shuttle Radar Topography Mission (SRTM), derived horizon files, and a land water
Daymet produces gridded estimates of multiple weather parameters for North America. This group of maps showcases a sampling of parameters: Annual Total of Daily Precipitation, and Annual Average of Daily Vapor Pressure, Daily Maximum Temperature, and Daily Minimum Temperature.
mask derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Water Mask. Observations of daily maximum temperature, minimum temperature, and precipitation from ground-based meteorological stations are provided by the National Centers for Environmental Information.
In the Daymet algorithm, researchers perform spatially and temporally explicit empirical analyses of the relationships between temperature and precipitation to elevation. A daily precipitation occurrence algorithm is introduced as a precursor to the prediction of daily precipitation amount. Water vapor pressure is generated as a function of the predicted daily minimum temperature and the predicted daily average daylight temperature. Daily incident solar radiation is estimated as a function of sun-slope geometry and interpolated diurnal temperature range. Snowpack, quantified as snow water equivalent, is estimated as part of the Daymet processing to reduce biases in shortwave radiation estimates.
Studying the relationship between living organisms and climate is an important component in understanding biodiversity, ecological forecasting, and biogeochem- ical cycles. It also helps to understand ecosystems in terms of structure and func- tion. Further analysis of these data allows researchers to detect trends and patterns over space and time.
This map focuses on the eastern United States, displaying Average Daily Minimum Temperature in 2006. Tracking temperature change can help us understand its impact on forest biomass and tree species distribution. Datasets like Daymet allow us to an- alyze the relationship of terrestrial ecosystems, and living organisms, responses to ex- treme weather by calculating anomalies, and other higher-level bioclimatic variables.
Mapping Extreme Events from Space 131