GMAO Contributes to Winning Proposals

09.01.2020

Recently, scientists from the Global Modeling and Assimilation Office (GMAO) have won several proposal solicitations as either principle investigator (PI) or co-investigator (Co-I). GMAO was part of several winning proposals including NASA ROSES 2019 NNH19ZDA001N-MAP A.16: Studies with the Modeling, Analysis, and Prediction (MAP) program proposal.

Eric Hackert is the PI of a project funded by NASA’s Ocean Salinity Sciences Team Program, entitled "Towards Full Utilization of Satellite Sea Surface Salinity for El Niño/Southern Oscillation Prediction". This work will examine the impacts of assimilating Sea-Surface Salinity (SSS) information from NASA’s Aquarius and SMAP satellites into the Global Earth Observing System (GEOS) sub-seasonal to seasonal prediction system (GEOS-S2S). A series of Observing System Evaluation (OSEs) experiments will be conducted in order in order to explore the impacts of assimilating SSS on the variability of the predicted El-Niño/Southern Oscillation (ENSO) signals at forecast lead times of weeks to months. The science team also consists of GMAO-based Co-Is Santha Akella and Robin Kovach, and collaborators Hamideh Ebrahimi (from the Joint Center for Satellite Data Assimilation), Tony Busalacchi (UCAR) and J. Ballabera-Poy (ICM/CSIC in France).

A project funded by NASA ROSES 2019 NNH19ZDA001N-MAP A.16: Studies with the MAP program, entitled "Effectively constraining both atmosphere and ocean components in an Integrated Earth System Analysis (IESA) Data Assimilation System" is led by PI Santha Akella. One of the main goals of an IESA project is to assimilate disparate observations of different components of the Earth system into a unified modeling and data assimilation system. For example, the ocean component assimilates sea level anomalies or sea surface height from satellite altimeters and atmosphere component assimilates satellite measurements that are sensitive to atmospheric temperature, water vapor, etc. We propose to develop an important aspect of the Earth system analysis that consistently combines observations of the atmosphere with the ocean, specifically focusing on atmospheric water vapor, ionospheric correction and satellite altimetry. This work would extend upon systems developed by the GMAO and Geodesy and Geophysics Laboratory (GGL) at NASA Goddard Space Flight Center (GSFC). The science team also consists of Co-Is Eric Hackert (610.1), Richard Ray (61A0), Brian Beckley (61A0, STG), and James Carton (Univ Maryland).

The project funded by NASA ROSES 2019 NNH19ZDA001N-MAP A.16: MAP program, entitled "Further Interoperability of MAPL and ESMF", is led by PI Ralph Dunlap (NCAR), is to build on prior efforts to unify the Modeling Analysis and Prediction Layer (MAPL) with the National Unified Operational Prediction Capability (NUOPC), and also ensure that the Earth System Modeling Framework (ESMF) core operations meet the computational performance requirements of GEOS in the next 5-8 years. MAPL is an integration layer for GEOS and was developed independently of NUOPC which serves a somewhat analogous purpose for other applications built upon the ESMF. The specific objectives of this proposal are to (1) increase the adoption of NUOPC in GEOS in the major top-level components ExtData, History, Atmosphere, and Ocean; (2) expand ESMF and the NUOPC layer to support advanced data staging capabilities and integrate with GEOS asynchronous I/O capability; (3) optimize core ESMF operations at scales expected for GEOS operational runs in the next 5-8 years; and (4) align testing and code management practices between MAPL and the NUOPC Layer to ensure ongoing coordinated development and promote code unification and sharing. The science team also consists of Co-Is Thomas Clune (610.1), as well as collaborators Arlindo do Silva (610.1) and Gerhard Theurich (SAIC).

Dimitris Menemenlis (JPL) is the PI of a project funded by NASA ROSES 2019 NNH19ZDA001N-MAP A.16: Modeling, Analysis, and Prediction (MAP) program, entitled "Toward seamless simulation, estimation, and prediction of weather and climate with the GEOS/ECCO coupled model and data assimilation system". This work aims to make incremental but significant advances in NASA's interannual-to-decadal prediction capability by combining expertise from two flagship NASA modeling and data assimilation efforts, GEOS and the Estimating the Circulation and Climate of the Ocean (ECCO). One set of breakthroughs will be spurred by a fully coupled atmosphere-ocean-ice simulation, where all three fluids are integrated globally with km-scale horizontal grid spacing. Both GEOS and ECCO have been run, separately, at groundbreaking resolutions, providing valuable scientific insights and guidance for subgridscale parameterizations in the two fluids. The ultra-high-resolution run that we propose to carry out will illuminate coupled air-sea exchange mechanisms that cannot be resolved by current-generation coupled simulations. A second set of breakthroughs will be spurred by the incorporation of certain aspects of ECCO data assimilation tools into GEOS toward improved interannual-to-decadal prediction capability. The science team also consists of Jean-Michel Campin (MIT), Gael Forget (MIT), Patrice Klein (JPL), An Nguyen (UT Austin), Ehud Strobach (610.1/ESSIC), Atanas Trayanov (610.1/SSAI), Patrick Heimbach (UT Austin), Chris Hill (MIT), and Andrea Molod (610.1).

Michael Bosilovich is a Co-I on a NASA Energy and Water Cycle Studies (NEWS) program funded project titled "Global and Regional Water and Energy Variations Under a Changing Climate" lead by co-principal investigators Tristan L'Ecuyer (U Wisconsin) and Matthew Rodell (NASA GSFC), and including a team that spans three NASA centers and several universities. Building on a previous NASA effort, this project will develop a global representation of the Earth's coupled water and energy cycles based on the highest quality observations with supplemental statistical and modeled information and include climate variability. The GMAO effort will entail regional studies of the year to year variations of the water and energy cycles, with special emphasis on understanding the uncertainties in the modeled data. The GMAO’s Modern Era Retrospective analysis for Research and Applications (MERRA-2) contributes an observation based depiction of the water and energy cycle that covers the globe. While we teach the water cycle to third grade science classes, the quantitative accuracy based on observation requires further study, improved analysis techniques and better models.

Christoph Keller (610.1/USRA) is the co-investigator of a project funded by the Science to Achieve Results (STAR) Program of the U.S. Environmental Protection Agency, entitled "A diagnostic package to facilitate and enhance chemical mechanism implementations within regional and global atmospheric chemistry models". This project will develop a diagnostic software package, based on machine learning, to identify key elements of a chemical mechanism to aid the future development of air quality models. The software package will also offer a chemical mechanism emulator that can be used as an alternative, computationally inexpensive method to simulate atmospheric chemistry. The project will greatly simplify application-specific atmospheric chemistry model development, as will be demonstrated using the regional CMAQ and global GEOS-Chem model. The project team further consists of principal investigator Julie Nicely (Earth System Science Interdisciplinary Center) and co-investigators Melanie Follette-Cook (Morgan State University) and Daniel Tong (University of Maryland).

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