Abstract ID: 217
On the development of a S2S forecasting system for the Arabian Peninsula using convective-permitting ensemble dynamical downscaling
Lead Author: Hoteit Ibrahim
King Abdullah University of Science and Technology, Saudi Arabia
Keywords: Arabian Peninsula, Convection-permitting model, Regional coupled model, Multi-model ensemble
Abstract: Saudi Arabia is increasingly affected by climate extremes such as heat waves and floods, causing surging impacts on society. Anticipating them is a key service to the country. In this context, a new Climate Change Center is established by the Saudi National Center for Meteorology (NCM) in collaboration with King Abdullah University of Science and Technology (KAUST). We are setting an operational high-resolution extended-range ensemble prediction system, based on dynamical downscaling of the ECMWF S2S forecasts with the Weather Research and Forecasting model (WRF) at convection-permitting scale (4 km) over the Arabian Peninsula.
We first implement and assess the skill of this forecasting system at the S2S time scales for the precipitation in the winter by downscaling the 20-year reforecast product. The regional S2S system is enhancing precipitation forecast by providing better physics and fully utilizing ensemble advantages. The prediction skills for heat wave events and human heat stress in the summer is also assessed for the reforecast period.
Next, a regional coupled atmosphere-ocean model is also employed to further enhance the forecast skill at S2S scale. The dynamic ocean in this system is expected to provide a more realistic air-sea interactions, which is important at the S2S scale for coastal temperature, and rainfall forecast. We are implementing this regional prediction system operationally for S2S forecast and exploring multi-model ensemble (MME) forecasting approach to further reduce the model uncertainties.
Thang M. Luong (King Abdullah University of Science and Technology)
Hsin-I Chang (University of Arizona)
Hari P. Dasari (King Abdullah University of Science and Technology)
C. Bayu Risanto (University of Arizona)
Matteo Zampieri (King Abdullah University of Science and Technology)
Prajeesh A. Gopinathan (King Abdullah University of Science and Technology)
Christopher L. Castro (University of Arizona)