- Intended Uses
- Decision Support System
Detailed, state-of-the-science climate maps have been created for the People's Republic of China and the USA by: (1) collecting station climate data from all possible sources and performing quality checks; and (2) interpolating the station data to a 4-km resolution grid using the PRISM climate mapping system.
Collection and Quality Control of Observational Data
For the USA, approximately 9,000 stations have been used. For the PRC, only 160 stations were initially permitted to be given to non-Chinese. Over a period of 3 years and much cooperative effort, a total of 3,274 stations for precipitation and 2,562 stations for minimum and maximum for temperature have been assembled. This data set represents the most comprehensive station data sets currently available for this region.
The target averaging period has been the thirty years from 1961 through 1990. Overall, the vast majority of stations had at least ten years of record. Quality checks were made to both the metadata and monthly data themselves. The location and elevation metadata were checked by plotting each station on a 30-second digital elevation model (DEM) from the ETOPO-30 global elevation dataset.
The mean monthly station data were checked for reasonableness by applying a version of PRISM that performs jackknife cross-validation on each station in the dataset. Stations with large observation-prediction errors were flagged. The PRISM Graphical User Interface was used to display climate-elevation scatterplots in the vicinity of the questionable stations to determine if the station fit in with the others, or was an obvious outlier. Outliers were removed from the dataset. In general, few monthly outliers were found, giving us confidence that the climate data were of good quality.
Interpolation of the Station Data
Spatial modeling of the climate data was performed at 2.5-minute (~ 4-km) resolution. A 2.5-minute DEM was derived from the ETOPO-30 DEM series. GIS was used to prepare supplementary grids used in the interpolation. These included a coastal proximity grid, estimates of wintertime temperature inversion heights, and a terrain steepness grid.
Select the country, climate factor, and period from the lists below to display the various maps. You may also create new species suitability maps with the dynamic Internet Map Server application (http://mistral.coas.oregonstate.edu/forages/).