Vol.:(0123456789) 1 3 Modeling Earth Systems and Environment https://doi.org/10.1007/s40808-019-00645-4 ORIGINAL ARTICLE Derivation of air temperature of agricultural areas of Morocco from remotely land surface temperature based on the updated Köppen‑Geiger climate classification R. Hadria 1  · T. Benabdelouahab 1  · L. Elmansouri 2  · F. Gadouali 3  · H. Ouatiki 4  · Y. Lebrini 4  · A. Boudhar 4  · A. Salhi 5  · H. Lionboui 1 Received: 1 May 2019 / Accepted: 10 September 2019 © Springer Nature Switzerland AG 2019 Abstract Air temperature is an important meteorological variable in many fields of our life. However, the availability of air temperature measurements over large geographic areas is often limited by the weather stations spatial distribution inadequacy, their low density and difficulties of data quality and collection. In this context, this study consists to develop four simple models to estimate the three components of air temperature (T min , T max and T mean ) from remotely sensed land surface temperature (T s ) derived from NOAA-AVHRR images, and based on the international Köppen-Geiger climate classification of Morocco. The results confirmed the existence of good relationships between the three components of measured air temperatures and land surface temperature derived from NOAA-AVHRR images for the main four climate classes of Morocco. The coefficient of determination, R 2 , varied between 0.69 and 0.80 for T min versus T s , between 0.62 and 0.74 for T max versus T s , and between 0.69 and 0.79 for T mean versus T s . The root mean square error varied between 3.1 °C and 3.3 °C for T min versus T s , between 3.2 and 4.1 °C for T max versus T s and between 2.7 and 3.4 °C for T mean versus T s . K-fold cross validation method was performed to assess the accuracy and the stability of proposed models. The limited number of proposed models is a great advantage to carry further studies requiring air temperature’s components at larger scale. Keywords Air temperature · Surface temperature · NOAA-AVHRR · Morocco · Köppen-Geiger classification Introduction Meteorological data are essential in many fields of our life such as weather forecasting, climate change monitoring and environmental management (Smith et al. 1988). This data is particularly crucial in agricultural studies since climate directly affects crop growth and final production (Hadria et al. 2007). Within all climatic variables, air tem- perature is an important element to understand the physics of many land surface processes; it is often used to monitor * R. Hadria r.hadria@gmail.com T. Benabdelouahab tarik.benabdelouahab@gmail.com L. Elmansouri loubna.elmansouri@yahoo.fr F. Gadouali gadoualif@gmail.com H. Ouatiki hamza.ouatiki@gmail.com Y. Lebrini y.lebrini@gmail.com A. Boudhar ab.boudhar@usms.ma A. Salhi salhi01@gmail.com H. Lionboui lionbouihayat@gmail.com 1 National Institute of Agronomic Research, Rabat, Morocco 2 Hassan II Institute of Agronomy and Veterinary, Rabat, Morocco 3 National Meteorological Office, Casablanca, Morocco 4 Science and Technique Faculty, Sultan Moulay Slimane University, Beni Mellal, Morocco 5 Abdelmalek Essaâdi University, Tétouan, Morocco