Paleo-climate modelling is another source of evidence for past climate variability. It is used to enhance process understanding and help in the interpretation of proxy records and has the advantage to investigate single extreme events in high temporal and spatial resolutions, not achievable with proxy archives. MITRA-CliMo addresses the climate modelling objectives of the MITRA project. Its goal is to produce high-resolution climate simulations to analyze the drivers of hydroclimatic variability and extremes in Southwest (SW) Asia from the past 3,500 years into the future. This work is necessary due to the scarcity of high-resolution climate data for this topographically complex region. We use the Weather Research and Forecasting (WRF) model to dynamically downscale existing global Earth system model (CESM) simulations. This method converts coarse global data into high-resolution information at 10 km for the entire region and 3 km for specific case studies, enabling a detailed analysis of the atmospheric processes behind droughts and extreme rainfall in SW Asia.

Our research focuses on four main areas:

• Forcing Impacts: Measuring how external drivers like volcanic eruptions, greenhouse gases and orbital changes compare to natural variability in influencing SW Asia's hydroclimate.
• Extreme Events: Studying the mechanisms and climatic changes in droughts and heavy precipitation events.
• Future Context: Using understanding of past climate behavior to inform projections of future extremes.
• Emulator Development: Testing machine learning methods to create a "climate emulator". This approach aims to combine high-resolution WRF data with global model output to generate a continuous, high-resolution climate record from 1500 BCE to 2100 CE.

The simulations from MITRA-CliMo will generate a high-resolution hydroclimate dataset for SW Asia. This data will support the interpretation of paleo-records developed within MITRA and provide a climatic context for archaeologists and historians studying the region.

WP 3 is led by Prof. Christoph Raible. PhD student Ms Markella Bouchorikou will focus on extreme events (droughts and heavy precipitation), their underlying processes and their variability during the past 3500 yrs and the next 300 yrs. Dr Trang Nguyen will develop a climate emulator testing machine learning and other statistical methods and will generate a transient spatially high-resolution climate evolution of Mesopotamia. This data will set a basis for the envisioned model-proxy intercomparison. 

Alizadeh, O., & Mousavizadeh, M. (2025). Impact of ENSO on extreme precipitation in Southwest Asia. Global and Planetary Change 244: 104645. https://doi.org/10.1016/j.gloplacha.2024.104645

Kim, W. M., Blender, R., Sigl, M., Messmer, M., & Raible, C. C. (2021). Statistical characteristics of extreme daily precipitation during 1501 BCE–1849 CE in the Community Earth System Model. Climate of the Past 17(5): 2031–2053. https://doi.org/10.5194/cp-17-2031-2021