Data Assimilation & Prediction

(COMPLETED) Advancing coupled land-atmosphere modeling with NASA-Unified WRF via process studies and satellite-scale data assimilation

Project Period: July 28, 2013 to July 29, 2017
Principal Investigator(s): Christa Peters-Lidard (NASA Goddard Space Flight Center)
Co-Principal Investigator(s): A. Hou and T. Matsui (NASA/GSFC)
Graduate Students, Postdoctoral and Other Investigators: J. Case (ENSCO Inc.), M. Chin (NASA/GSFC), J. Geiger (NASA/GSFC), Y. Liu (NASA/GSFC/ESSIC), J. Santanello (NASA/GSFC), J.J. Shi (NASA/GSFC), Q. Tan (NASA/GSFC/USRA), Wei-Kuo Tao (NASA/GSFC), Z. Tao (NASA/GSFC/USRA), B. Zaitchik (Johns Hopkins University), B. Zavodsky (NASA/MSFC), Sara Q. Zhang (NASA/GSFC), Milija Zupanski

Sponsor(s): National Aeronautics and Space Administration (NASA)



This project builds on the successful development and application of the NASA Unified Weather Research and Forecasting (NU-WRF) modeling system, with the goal of integrating and enhancing existing land and atmospheric data assimilation capabilities to advance regional-scale coupled land-atmosphere modeling for process studies. The NU-WRF currently combines the capabilities of the WRF with the Land Information System (LIS), the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, advanced microphysics and coupling between clouds and aerosols to better represent cloud-aerosol-precipitation-land surface processes. Outputs can be directly compared with satellite L1B data via the Goddard Satellite Data Simulator Unit (G-SDSU). Further, the NU-WRF connects with global-scale modeling efforts, including the GEOS-5 and the MERRA, which can be used as atmospheric boundary and initial conditions. This project will focus on advanced component couplings and integration of existing land (LIS-DA) and atmospheric (WRF-EDA) data assimilation in NU-WRF.



This proposal represents a continuation of the core development for NU-WRF, as described in the call. Specifically, we will (1) Characterize and/or reduce uncertainties in models and products (by evaluating the case studies with and without data assimilation, as well as after physics and chemistry refinements); (2) Extend the range of model or product validity by using new components (by incorporating and generalizing the LIS-DA and the WRF-EDA); and (3) Enable independent community validation and characterization (by distributing the NU-WRF code to partners). The proposed data assimilation and physics enhancements to NU-WRF further the core MAP program interests in regional observation-driven modeling and data assimilation.



Recent results have indicated the critical role that incorporating land surface and atmospheric observations can play in helping further advance our ability to represent coupled land-atmosphere processes. As part of this work, we will first enhance the couplings between key NU-WRF components, such as wet deposition, dust and biogenic emissions, aerosol-cloud- precipitation interactions, and mesoscale circulations. Next, we will fully incorporate and advance LIS-DA in the NU-WRF to assimilate satellite-based land surface products such as soil moisture, snow cover and depth, and skin temperature, while also updating land parameters such as real-time green vegetation fraction, albedo, and irrigated area. We will also fully incorporate and advance the WRF-EDA in the NU-WRF to assimilate cloud-precipitation-affected microwave radiances to advance the representation of clouds and precipitation in the NU-WRF. Finally, we will conduct case studies demonstrating the impact of the LIS-DA and the WRF- EDA on land-atmosphere processes for high-impact weather-to-climate scenarios such as tropical cyclones, droughts, floods, heat waves and extreme storms; as well as impacts on atmospheric chemical constituents including severe air quality degrading events.