NORTH AMERICAN HEAT WAVE PREDICTABILITY: SKILL ATTRIBUTION AND LAND SURFACE INITIALIZATION IN MEDIUM-RANGE FORECAST MODELS

Author

Chi Fai Wong, Southern Illinois University CarbondaleFollow

Date of Award

12-1-2019

Degree Name

Master of Science

Department

Geography and Environmental Resources

First Advisor

Ford, Trent W.

Abstract

A developed seamless extreme heat validation approach (Ford et al. 2018) is applied to three Subseasonl Experiment’s (SubX’s) medium-range forecast models, which arethe U.S. National Oceanic and Atmospheric Administration’s Earth System Research Laboratory FIM-iHYCOM (ESRL), the U.S. National Aeronautics and Space Administration’s Earth System Research Laboratory’s Goddard Earth Observing System Atmosphere-Ocean General Circulation Model, Version 5 (GMAO), and the U.S. National Centers for Environmental Prediction’s Global Ensemble Forecast System, version 11 (GEFS), for evaluating their heat wave predictability. Moreover, two land surface initializations, green vegetation fraction (GVF) and heat fluxes (LE/H), of each model are evaluated for understanding the interaction between heat wave predictability and the inconsistencies in the terrestrial segment of land-atmosphere feedbacks. The validation approach shows the overestimated autocorrelation of maximum temperature heat waves causing (1) the lowest reliability and overestimation of heat waves hindcasts, (2) lower heat wave hindcast skill of ensemble mean, and (3) higher discrimination between heat wave hindcast and observations of each ensemble member over lead times for all three models. Both ESRL and GEFS present the relationship between GVF and heat wave hindcast is positive, but negative relationship is shown on the GMAO. In addition, both ESRL and GEFS modelsunderestimate latent heat flux, but overestimate sensible heat flux in the Midwest. Therefore, for both ESRL and GEFS models, the relationship between heat wave and sensible heat fluxes (or GVF) is positive, and negative for the relationship between heat wave and latent heat flux (or evapotranspiration). In contrast, the GMAO model overestimates both latent and sensible heat fluxes in the Midwest. Therefore, for the GMAO model, the relationship between heat wave and latent/sensible heat fluxes (or GVF) is positive, and negative for the relationship between heat wave and evapotranspiration.