摘要：We present time series analyses of recently compiled climate station data which allowed us
to assess contemporary trends in growing season weather across Kazakhstan as drivers of a
significant decline in growing season normalized difference vegetation index (NDVI)
recently observed by satellite remote sensing across much of Central Asia. We
used a robust nonparametric time series analysis method, the seasonal Kendall
trend test to analyze georeferenced time series of accumulated growing season
precipitation (APPT) and accumulated growing degree-days (AGDD). Over the
period 2000–2006 we found geographically extensive, statistically significant (p<0.05) decreasing trends in APPT and increasing trends in AGDD. The temperature trends were
especially apparent during the warm season and coincided with precipitation decreases in
northwest Kazakhstan, indicating that pervasive drought conditions and higher
temperature excursions were the likely drivers of NDVI declines observed in Kazakhstan
over the same period. We also compared the APPT and AGDD trends at individual
stations with results from trend analysis of gridded monthly precipitation data from the
Global Precipitation Climatology Centre (GPCC) Full Data Reanalysis v4 and gridded
daily near surface air temperature from the National Centers for Climate Prediction
Reanalysis v2 (NCEP R2). We found substantial deviation between the station
and the reanalysis trends, suggesting that GPCC and NCEP data substantially
underestimate the geographic extent of recent drought in Kazakhstan. Although gridded
climate products offer many advantages in ease of use and complete coverage,
our findings for Kazakhstan should serve as a caveat against uncritical use of
GPCC and NCEP reanalysis data and demonstrate the importance of compiling
and standardizing daily climate data from data-sparse regions like Central Asia.
