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Real-time integration of remote sensing, surface meteorology, and ecological models.

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Presentation on theme: "Real-time integration of remote sensing, surface meteorology, and ecological models."— Presentation transcript:

1 Real-time integration of remote sensing, surface meteorology, and ecological models

2 Goals Provide Nowcast/Forecasts of water and carbon cycle variables for the conterminous United States with the Terrestrial Observation and Prediction System (TOPS)

3 Need for integration Integration of remote sensing, surface meteorology, and ecological models provides the best opportunity for comprehensive assessment of the state and activity of landscape processes Disciplines are traditionally separate but can be highly complementary

4 Remote sensing alone … Useful for describing short- and long-term variation in terrestrial vegetation –Photosynthetic activity, leaf area index, absorbed radiation –Phenological development –Land use and land cover changes Less useful for detecting plant stress and hydrologic cycles

5 Surface meteorology alone... Provides critical information needed to describe land-atmosphere interactions Inadequate for assessment of landscape processes

6 Prognostic ecological models Simulate past and future climate scenarios Mass-balance simulations of carbon, water, and nutrient cycles Often do not ingest vegetation observations Thus less useful for real-time management applications

7 What we need A non-prognostic ecological model ingesting real-time satellite and surface meteorology observations

8 TOPS Overview 1 kilometer spatial resolution Remotely-sensed leaf area index (LAI) Rapid Update Cycle meteorology (RUC) Land surface model (LSM)

9 Terrestrial Observation and Prediction System

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11 Remotely-sensed LAI Currently: Advanced Very High Resolution Radiometer (AVHRR) Future: Moderate Resolution Imaging Spectroradiometer (MODIS) Algorithm –Main: MODIS backup –Cloud contamination: historical averages

12 Week of May 12 - May 18

13 Week of May 19 - May 25

14 Week of May 26 - June 1

15 Week of June 2 - June 8

16 Week of June 9 - June 15

17 RUC-2 Produced by the National Centers for Environmental Prediction Hourly outputs 20 kilometer resolution Automated scripts gather data and process hourly values to daily values Future developments will include downscaling algorithms

18 Example RUC-2 meteorology

19 Temp = 20 deg CDEM Downscaling: use of lapse rates and digital elevation model to adjust temperatures within each 40 km pixel

20 Ecological model Based on BIOME-BGC No complete carbon balance Forced with observed LAI

21 Results Beta version June 18

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32 Plant stress index: higher values indicate higher stress

33 Planned transformed variables Accumulated stress/fire danger –incorporate lightning strike information Anomalies/departures from normal Water deficit/irrigation requirements

34 Forecasts Six-month goal: incorporate Forecast Systems Laboratory (FSL) short- to medium-term forecasts –seven-day forecasts –one to three month climatological forecasts One year goal: Ingest long-lead forecasts from ECPC/NCEP.

35 Real-time and forecast modes Must be run simultaneously –unconstrained use of forecast data leads to catastrophic errors in hydrologic cycles –important for regional scale climate models to accurately parameterize the land surface, especially in the Southwest

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37 Conclusions Real-time management needs can be addressed with an approach integrating remote sensing, surface meteorology, and ecological modeling TOPS will provide real-time simulations of water and carbon cycles through a web-based interface within two months Within six months we will add forecast simulations constrained by current conditions System is flexible and can be adapted to variable spatial resolutions and inputs


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