Grant No. ATM-0129892
in connection with the International H2O Project (IHOP)
Prof. Ming Xue12, Principal Investigator
Prof. Frederick H. Carr12, Co-Principal Investigator
Prof. Alan Shapiro12, Co-Principal Investigator
Dr. Keith Brewster2, Co-Principal Investigator
Dr. Jidong Gao2, Co-Principal Investigator
1School of Meteorology (SOM) and 2Center for Analysis and Prediction of Storms
Period of support:
In an effort to better characterize the
four-dimensional distribution of water in the atmosphere with a view toward
improving our understanding of its impact on deep convection, the International
H2O Project (IHOP-2002) field experiment will take place over the
As a former NSF Science and Technology Center whose research has for over a decade focused principally on convective-scale data assimilation and prediction, and which now is heavily involved in the cooperative development of a next-generational operational/research model for the national community, we propose to continue our storm-scale research with particular emphasis on moisture sensitivity and data assimilation in the context of numerical quantitative precipitation forecasting.† Specifically, we seek to:
1) † Develop new and improved techniques, based particularly on variational approaches, for the analysis and assimilation of water and related diabatic fields (e.g., latent and sensible heating) at the scale of individual convective storms and their larger mesoscale clusters. We will focus on the assimilation of direct moisture observations (e.g., from GPS, ground-based radiometers) as well as moisture-related quantities, such as hydrometeors and associated thermal perturbations, retrieved from ground-based Doppler radars.
2) † Study the impact of special and routinely-available, high-resolution observations of water vapor and hydrometeor content on the forecasting of convective storm morphology and quantitative precipitation at resolutions of one to a few kilometers. Both forward and adjoint models will be used to assess sensitivity and data impact.
3) Develop and evaluate techniques for estimating error characteristics (i.e., error covariance matrices) of numerical forecasts at the convective scale so as to improve the quality of 3D and 4D variational data assimilation.†
4) † Apply newly developed single Doppler velocity and thermodynamic retrieval algorithms to the Doppler-On-Wheels (DOW) and SMART-R mobile radar data collected during IHOP, and assimilate the retrieved data into a forecast model. We will also assess both the quality of the retrievals and their impact using multiple-Doppler observations for verification.
5)† Provide real-time, high-resolution (2-3 km) analysis and forecasts, for ranges between 6 and 12 hours, to assist the operational decision-making and targeting of mobile observations during IHOP.†
The project will provide much needed education and training for graduate students and post-docs in the increasingly important areas of variational data assimilation, numerical weather prediction and ensemble forecasting. The research findings will have a direct path to operations through the PIís involvement as one of† the lead scientists in the Weather Research and Forecast (WRF) model system development project. Although much of the work to be performed herein will use the CAPS Advanced Regional Prediction System (ARPS) owing to its maturity and capability, the new WRF will be used whenever possible.† Further, the results obtained here, and the software developed, will be applied to further the development of the WRF model as part of CAPS' involvement in the WRF project.