UAE-NATURE: Using Advanced Experimental – Numerical Approaches To Untangle Rain Enhancement
A project funded by the UAE Research Program for Rain Enhancement Science (UAEREP)
Background
UAE-NATURE is proposed by a consortium of research institutes and universities from China, Hungary, UAE and USA to conduct innovative research on rain enhancement based on advanced laboratory experiments and state-of-the-art numerical models. It is impossible to address cloud seeding effect using spatially- and temporally-limited observations only. Numerical models that reasonably represent the main dynamical and physical processes associated with cloud seeding are extremely useful to not only understand how seeding impacts clouds and rainfall but also quantify the seeding effect given the model results are carefully validated by observations. The theories of cloud dynamics and microphysics, field and laboratory instrumentations, numerical modeling techniques and computing power have advanced dramatically during the last decade to a level that the seeding effect on UAE clouds and rainfall can be quantitatively assessed.
Objectives
The core objectives of this proposed study are to 1) improve knowledge of hygroscopic seeding impact on the warm rain initiation using both chamber experiments and a Direct Numerical Simulation (DNS) cloud model; 2) discriminate the dynamical and microphysical processes by which natural and seeded precipitation forms and evolves within clouds using cloud-resolving simulations with piggybacking approach validated by available observations; and 3) quantify the potential seeding impact and uncertainties on UAE rainfall in a 10-year period using high-resolution regional climate and ensemble seeding simulations.
The additional objectives are to: 4) understand how cloud seeding affects the cloud cover, lifetime, and the subsequent effect on evapotranspiration and groundwater availability using seeding simulations; 5) quantify the rainfall spatial and temporal distributions in UAE using the high-resolution regional climate simulations; and 6) identify large-scale and synoptic conditions suitable for seeding using regional climate simulation data.
Innovation
The innovative aspects of this proposal include: 1) the first DNS cloud simulation of hygroscopic seeding impact on clouds; 2) piggybacking simulations to separate seeding impact on microphysics from the impact on dynamics; 3) development of the first long-term high-resolution meteorological data set for UAE; and 4) the first study of cloud seeding impact on cloud cover, lifetime, and its effect on evapotranspiration and groundwater availability.
Significance
The significance of the proposed research is that the new laboratory and advanced modeling capabilities will fill gaps in the understanding, such that the effect of cloud seeding on rainfall and associated uncertainties can be quantified, the microphysical effects of the seeding response can be discriminated from dynamic effects, new insights on the physical chain of events from seeding across spatial and temporal scales can be gained, and possible new practical approach to enhance groundwater can be developed.
Broader Impacts
The broader impacts and benefits of this proposed research include improved knowledge on hygroscopic seeding effect on clouds, new knowledge on cloud seeding radiation interaction to improve groundwater security. In addition, this proposed study will design a new mixed-phase aerosol-cloud chamber for weather modification research and facilitate international collaborations in UAE. Moreover, a workshop and a conference will be held in the final year of this study to provide a venue for exchange of ideas and innovations.