AgroClimatology
The AgroClimatology group studies the interactions between climate and agriculture focusing on regional and seasonal space and time scales, respectively.
Research Interests
Seasonal climate predictions: the ocean and land surface provide the inertia for long-term climate processes. Therefore, numerical climate prediction models require coupling the atmospheric model to an ocean and land surface models. In the case of Israel, it is still unclear how the Mediterranean Sea affects seasonal prediction skill. This is one of the topics to be investigated in my lab.
Crop modeling: seasonal climate predictions combined with crop models can provide farmers information about the optimal choice of crop for the next season, sowing time, and crop prospects. Also, it can be used to give information on the optimal space allocation for crops.
Soil-vegetation-atmosphere interactions: agriculture is directly affected by the regional climate conditions. Soil-vegetation-atmosphere interactions impact the exchange of heat, water, and, as a result, the crops. in recent years, it has been realized that plants are not only affected by the atmospheric conditions, but they can also impact regional micro-climate conditions. My research will quantify these interactions from a regional perspective relevant to Israel.
Machine learning and pattern recognition: the climate system, is characterized by various patterns with characteristic synoptic scales (thousands of kilometers) in the atmosphere and mesoscales (tens to hundreds of kilometers) in the ocean. Three-dimensional identification of these patterns boundaries can provide information about their interactions with the land and sea. As part of our research, we will develop various tools to identify synoptic systems and quantify their interactions with the environment.
