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Interactive Vegetation Phenology, Soil Moisture, and Monthly Temperature ForecastsThe time scales that characterize the variations of vegetation phenology are generally much longer than those that characterize atmospheric processes. The explicit modeling of phenological processes in an atmospheric forecast system thus has the potential to provide skill to subseasonal or seasonal forecasts. We examine this possibility here using a forecast system fitted with a dynamic vegetation phenology model. We perform three experiments, each consisting of 128 independent warm-season monthly forecasts: 1) an experiment in which both soil moisture states and carbon states (e.g., those determining leaf area index) are initialized realistically, 2) an experiment in which the carbon states are prescribed to climatology throughout the forecasts, and 3) an experiment in which both the carbon and soil moisture states are prescribed to climatology throughout the forecasts. Evaluating the monthly forecasts of air temperature in each ensemble against observations, as well as quantifying the inherent predictability of temperature within each ensemble, shows that dynamic phenology can indeed contribute positively to subseasonal forecasts, though only to a small extent, with an impact dwarfed by that of soil moisture.
Document ID
20160006707
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Koster, R. D.
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Walker, G. K.
(Science Systems and Applications, Inc. Lanham, MD, United States)
Date Acquired
May 31, 2016
Publication Date
July 29, 2015
Publication Information
Publication: Journal of Hydrometeorology
Publisher: AMS
Volume: 16
e-ISSN: 1525-7541
Subject Category
Meteorology And Climatology
Report/Patent Number
GSFC-E-DAA-TN31838
Funding Number(s)
CONTRACT_GRANT: NNG12HP06C
Distribution Limits
Public
Copyright
Other
Keywords
Seasonal Forecasting
Forecasting Techniques
Soil Moisture

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