Improving NOAA UFS subseasonal-to-seasonal (S2S) prediction via implementing data assimilation of vegetation characteristics in jedi and enhanced plant hydraulics physics project goal: this proposal…

Improving NOAA UFS subseasonal-to-seasonal (S2S) prediction via implementing data assimilation of vegetation characteristics in jedi and enhanced plant hydraulics physics project goal: this proposal aims to incorporate a vegetation data assimilation (DA) capability into jedi and a novel plant hydraulics scheme into UFS to improve subseasonal-to-seasonal (S2S) predictions in the coupled jedi-UFS system. Problem statement: NOAA UFS currently relies on climatological vegetation representation and does not explicitly represent plant hydraulic processes, which contributes to crucial uncertainties in UFS-simulated land conditions, land-atmosphere interactions, and consequently S2S predictions. Vegetation DA, which is currently lacking in jedi, can effectively reduce uncertainties in representing vegetation characteristics in S2S predictions. Methodology and activities: 1. Implement the capability of assimilating leaf area index (LAI) and solar-induced fluorescence (SIF) into jedi and a novel plant hydraulics scheme into UFS; 2. Evaluate their impacts on S2S predictions; 3. Quantify processes/mechanisms that contribute to S2S prediction performance changes and roles of vegetation DA and enhanced plant hydraulics. Project products and outputs: new vegetation DA capability and code in jedi and documentation; updated UFS model code with enhanced plant hydraulics and documentation; enhanced S2S prediction capability in jedi-UFS; publications and conference/workshop presentations; education and outreach activities via this project. Expected outcomes and benefits: improved knowledge of vegetation effects on S2S predictions; improved accuracy in land surface process modeling and S2S predictions; providing more accurate prediction information to the public and stakeholders for enhanced preparation for extremes and hazards, better resource management and decision making, and reduced losses in socio-economy and human life. Intended beneficiaries and recipients: NOAA/EMC, NOAA/epic, jcsda