Get reliable science

The estimation of near surface air temperature (Ta) is useful for a wide range of applications such as agriculture, climate related diseases and climate change studies. Air temperature is commonly obtained from synoptic measurements in weather stations. In Africa, the spatial distribution of weather stations is often limited and the dissemination of temperature data is variable, therefore limiting their use for real-time applications. Compensation for this paucity of information may be obtained by using satellite-based methods. However, the derivation of near surface air temperature (Ta), from the land surface temperature (Ts) derived from satellite is far from straight forward. Some studies have tried to derive maximum Ta from satellites through regression analysis but the accuracy obtained is quite variable according to the study. The main objective of this study was to explore the possibility of retrieving high-resolution Ta data from the Moderate Resolution Imaging Spectroradiometer (MODIS) Ts products over different ecosystems in Africa. First, comparisons between night MODIS Ts data with minimum Ta showed that MODIS nighttime products provide a good estimation of minimum Ta over different ecosystems (with (?Ts - Ta) centered at 0 °C, a mean absolute error (MAE) = 1.73 °C and a standard deviation = 2.4 °C). Secondly, comparisons between day MODIS Ts data with maximum Ta showed that (?Ts - Ta) strongly varies according to the seasonality, the ecosystems, the solar radiation, and cloud-cover. Two factors proposed in the literature to retrieve maximum Ta from Ts, i.e. the Normalized Difference Vegetation Index (NDVI) and the Solar Zenith Angle (SZA), were analyzed. No strong relationship between (?Ts - Ta) and (i) NDVI and (ii) SZA was observed, therefore requiring further research on robust methods to retrieve maximum Ta.