Prof. Kosmas Pavlopoulos: Statistical evaluation of Sorbonne University Abu Dhabi Atmospheric Forecasting System (SUAFS) at Dubai Desert Conservation Reserve (DDCR) (phase 1)

Project summary

Sorbonne University Atmospheric Forecasting System (SUAFS) is an integrated combination of advanced models able to provide detailed weather desert forecasts on various temporal scales over the Arabian Peninsula and the greater UAE areas.. The following predictions currently available by SUAFS (http://forecast.psuad.ac.ae) are:

  • Weather forecast for 72 hrs ahead (3 days)
  • Desert dust forecast for 72 hrs ahead (3 days)

SUAFS is running operationally since July 2018 and an annual archive of weather and desert dust forecasts are almost available for evaluation. This research proposal offers a unique opportunity to initiate the framework for an important collaboration with DDCR in terms of environmental warnings and monitoring. Thus, the main aim of the Phase-1 project is to validate SUAFS forecasts against the atmospheric measurements obtained from DDCR meteorological stations. The entire records and data of the main atmospheric parameters from the network of the meteorological stations of DDCR, as well as the neighbored available stations, will be utilized for comparison with SUAFS forecasts. The extracting statistical scores will be helpful to identify the forecast errors of the system and their propagation into the period of the simulation. The results of this research work will lead SUAFS forecasts to achieve greater accuracy and reliability especially over the area of interest. These results will be the base of the Phase 2, who focus on the air quality monitoring and dust forecasting dedicating for the DDCR. All the results will be at DDCR and SUAD disposal and a report with all the data will be submitted.

Project dates

October 2019 – ongoing

Partnerships

Sorbonne Univeristy Abu Dhabi (PI)
Dubai Desert Conservation Reserve (CoPI)
Harokopio University Athens (CoPI)

Funding

Dubai Desert Conservation Reserve (DDCR)