Publications

Chen, LH; Wang, KC (2024). Sampling Error of Mean and Trend of Nighttime Air Temperature at Weather Stations Over China Using Satellite Data as Proxy. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 129(18), e2023JD039914.

Abstract
Meteorological observations of surface air temperature have provided fundamental data for climate change detection and attribution. However, the weather stations are unevenly distributed, and are still very sparse in remote regions. The possible sampling error is well known, but not well quantified because we are lack of the adequate and regularly distributed measurements. The high resolution of satellite land surface temperature retrieval during night time provide a nice proxy for near surface temperature as both temperatures controlled by surface longwave radiative cooling and the nocturnal temperature inversion depress land-atmosphere turbulent exchange. The sampling error of mean value and trend were assessed by comparing station point measurements (pixel of similar to 0.01 degrees) with grid (1 degrees) mean and national mean from 2001 to 2021. This method permits us to make the first assessment of under-sampling error and spatial representative error on both national mean and trend of air temperature during nighttime collected at similar to 2,400 weather stations over China. The sampling error in national mean temperature is more than 3 degrees C. The under-sampling error due to lack of observation explains two thirds and the spatial representative error due to the difference between station and grid/regional mean elevation contribute the other one third. The sampling error in trend account for one third of the national mean trend. The urban heat island effect associated with urbanization around the weather stations (spatial representative error) can explain four fifths of the sampling error in trend, which is consistent with existing studies based on air temperature collected at paired weather station. Meteorological observations provide fundamental measurements of surface air temperature. These station-based temperature records are usually processed to grid data sets considering the uneven distribution of meteorological stations. The gridding procedure represents a non-uniformly sampling. In this paper, we quantified the sampling error over China using remote sensed temperature record as proxy of near surface temperature during nighttime. The causes of sampling error both in mean value and trend were both quantified. Sampling error of mean and trend of temperature collected at weather stations at nighttime over China were investigated The sampling error in national mean temperature were found to be more than 3 degrees C due to uneven distribution of weather stations The sampling error in temperature trend account for one thirds of the national mean temperature trend due to local urbanization

DOI:
10.1029/2023JD039914

ISSN:
2169-8996