Using Model Analysis and Satellite Data to Assess Seedable Clouds and Precipitation over the UAE Region

The present study is undertaken for clarifying the microphysical structures of clouds suitable for seeding and their occurrence frequency over the eastern mountain areas of the United Arab Emirates (UAE). This is underway through the analysis of satellite and ground-based remote sensing data along with the numerical model simulations over these arid and semi-arid regions. The occurrence frequency and microphysical properties of the seedable clouds is determined by the relocated Meteosat-8 to 41.5^oE for the continuation of the Indian Ocean Data Coverage. The Meteosat-8 therefore has advantages with respect to the biases related to angular view and spatial resolution, in comparison to other geostationary satellites, over the UAE and adjoining regions. The initial analysis reveals some distinct biases related to the occurrence of warm and ice clouds derived from Meteosat-10 relative to Meteosat-8. Further, the Meteosat-8 reveals some interesting properties of occurrence of the seedable clouds. The percentage of seedable clouds are high along the mountains located in the eastern part of the UAE including Al Hajar Mountains of the Oman region. The diurnal variation indicates a bimodal distribution of seedable clouds peaking high in the morning (~ 9hrs. Local Time, LT) and night (~ 18hrs. LT). The vertical structure of the seedable cloud properties is also studied through the CloudSat/CALIPSO satellite observations. The combined radar-lidar analysis has an advantage of distinguishing between ice, water and mixed-phase clouds. A preliminary analysis shows that the surface rainfall over the UAE region is dominantly associated with ice-phase processes. Further, the three dimensional properties of cloud properties are studied over the UAE and adjoining regions through the merging of Meteosat-8 and CloudSat data. This facilitates the more comprehensive understanding of the seedable cloud properties in the context of precipitation formation processes.

The satellite analysis is further supported with global cloud-resolving numerical model simulations using the stretch-grid (SG) Non-hydrostatic Icosahedral Atmospheric Model (SG-NICAM). The SG-NICAM has an advantage of saving the computational cost through using the finest resolutions only near the target point to coarser intervals for points away. The strength of stretching is controlled by a parameter called stretching ratio. The simulations are performed using the finest resolutions (~1.4km) with stretching ratio 64. Nevertheless, it is now underway to go beyond (less than 1km) for resolving the clouds over the desert regions. We applied land surface tuning to the default setting of SG-NICAM model in order for the better representation of surface precipitation and temperature relative to the ground based and space-borne observations. The surface precipitation patterns and cold bias in the control simulations are improved by tuning the land surface parameters such as conductivity, soil moisture threshold and the roughness lengths. Moreover, the microphysical properties of clouds are significantly affected by the aerosols in the atmosphere as evident in recent satellite observations. Hence, the aerosol optical properties are simulated using the Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) coupled with the NICAM. Finally, we present NICAM+SPRINTARS model performance to demonstrate how the aerosol and dynamics affect the seedable clouds and their formation of precipitation in addition to the satellite observations over the arid and semi-arid regions of the UAE and adjoining regions.