Work

A combined Terra and Aqua MODIS land surface temperature and meteorological station data product for China from 2003 to 2017

Year: 2020

Type: article

Abstract: . Land surface temperature (LST) is a key variable for high temperature and drought monitoring and climate and ecological environment research. Due to the sparse distribution of ground observation stations, thermal infrared remote sensing technology has become an important means of quickly obtaining ground temperatures over large areas. However, there are many missing and low-quality values in satellite-based LST data caused by cloud coverage exceeding 60 % of the global surface every day. This article presents a unique LST dataset in China for 2003–2017, which filters and removes missing values and poor-quality LST pixel values contaminated by clouds from raw LST images and retrieves real surface temperatures under cloud coverage by a reconstruction model. We specifically describe the reconstruction model, which uses a combination of MODIS daily data, monthly data and meteorological station data to reconstruct the true LST under cloud coverage, and then the data performance is further improved by establishing a regression analysis model. The validation indicates that the new LST dataset is highly consistent with the in situ observations. For the six natural subregions with different climatic conditions in China, the RMSE ranges from 1.24 °C to 1.58 °C, the MAE varies from 1.23 °C to 1.37 °C, and the R2 ranges from 0.93 to 0.99. The new dataset adequately captures the spatiotemporal variations in LST at annual, seasonal and monthly scales. From 2003–2017, the overall annual mean LST in China shows a weak increase. Moreover, the warming trend was remarkably unevenly distributed over China. The most significant warming occurred in the central and western areas of the Inner Mongolia Plateau in the Northwest Region (slope > 0.10, R > 0.71, P <0.05), and a strong cooling trend was also observed in some parts of the Northeast Region. Seasonally, there was significant warming in the western part in winter, which was most pronounced in December. The reconstructed dataset exhibited significant improvements and can be used for the spatiotemporal evaluation of LST and high temperature and drought monitoring studies. The data are published in the Zenodo at https://doi.org/10.5281/zenodo.3378912 (Zhao et al., 2019).

Source: Earth system science data

DOI: 10.5194/essd-12-2555-2020