Improving land evaporative processes and land-atmosphere interactions in the NCEP Global Forecast System (GFS) and Climate Forecast System (CFS)

Introduction to the Problem: Surface evapotranspiration is often considered the climate linchpin variable because it forms the bridge across the water, energy and carbon cycles. Evaporation plays a central role in coupling the land and atmosphere, and operates over fast (diurnal) and slow (seasonal) time scales. Evaporation from water bodies, vegetation intercepted precipitation or soil surfaces, and transpiration from plants combine to return available water at the surface layer back to the bulk atmosphere in a process referred to as evapotranspiration (ET). Controls on terrestrial ET are particularly complicated and are constrained by the surface radiation, the state of the vegetation-soil system, or the atmospheric boundary layer and its surface meteorology. Accurately modeling terrestrial evapotranspiration processes, including land-atmospheric coupling and recycling, is fundamental to climate predictions and projections. Errors in ET directly cascade through the water, energy and carbon cycles at all time scales. The goal of the proposed project is to analyze, evaluate and improve land evaporative processes in the Noah land surface component of the NOAA National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) and Climate Forecast System (CFS) that will directly lead to improved climate predictions in these and other NCEP models. The focus of the project is on warm season terrestrial evaporative processes that include free evaporation from water bodies and canopy intercepted precipitation, evaporation of soil water, and transpiration by vegetation. All of the above processes are parameterized separately in the GFS/CFS but collectively considered as ET or, in its energy form, latent heat flux. 

Rationale: Over the last ten years a significant body of research has shown that little agreement exists among climate models in their simulations of land evaporative fluxes, even for current 20th C climate. Analyses of land-atmospheric coupling, as measured by metrics like the inferred lifting condensation level (LCL), show wide disparity from weak to extremely tight coupling. Careful assessments of the parameterizations that control vegetation response to soil drying show that values being used are inconsistent with vegetation characteristics and provide unrealistic responses. Collectively, analyses to date show that climate models do a poor job in representing land evaporative processes. Given the central role of evaporative processes in the climate system, resolving these inadequacies is extremely relevant to improvements in climate models. Recent years have seen advancements in the analysis of evaporative processes (especially in the understanding of how surface heat fluxes couple to the boundary layer), in measuring land evaporative fluxes through eddy correlation techniques from towers under the AmeriFlux (and globally the FluxNet) initiatives, and in measuring atmospheric and surface properties from spaceborne sensors. These and other advances will be used to analyze and evaluate the land evaporative processes in the NCEP climate models and to develop improved parameterizations. 

Summary of work to be completed: 1. Data set selection and compilation of the in-situ flux tower and remote sensing data sets for long-term flux tower sites that represent a range of climates and vegetation types for the modeling and diagnostic analyses. 2: Generation of off-line and coupled climate model runs using the Noah off-line version of the NCEP land surface scheme using forcing data for the tower sites and extending existing GLACE-2 hindcasts to nearer realtime. 3. Diagnostic analyses of off-line and coupled runs of evaporative processes using metrics of land contribution to climate prediction skill and land-atmosphere coupling. 4. Model experiments for assessing process deficiencies. 5. Developing and testing new ET parameterizations including calibration of existing parameterizations, inclusion of canopy physiology models, sub-grid scale soil moisture variations, prognostic canopy airspace parameterizations, and improved canopy interception.