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09. 1. FY12-13 GIMPAP Project Proposal Title Page date: 7 August 2012. Title : Enhanced use of GOES for estimating land surface wetness with application to wildfire forecasting at the NOAA Storm Prediction Center Status : Progress Report Project Leads:

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1. FY12-13 GIMPAP Project Proposal Title Pagedate: 7 August 2012

Title: Enhanced use of GOES for estimating land surface wetness with application to wildfire forecasting at the NOAA Storm Prediction Center

Status: Progress Report

Project Leads:

Robert M RabinNOAA/[email protected]

Phillip Bothwell NOAA/NWS/[email protected]

Other Participants:

Marouane Temimi NOAA/CREST/CCNY

Jan Stepinski CREST/CCNY student

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2. Project Summary

  • Provide estimates of surface dryness from rate of daytime warming
  • Validate GOES-based dryness index with independent estimates:

AMSR-E, SMOS, and in-situ data

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3. Motivation / Justification

  • Supports NOAA Mission Goal(s):Weather and Water, Climate
  • Addresses need for improved estimates of surface dryness and

fuel loads for forecasting wildfires (SPC) and model initialization

  • New use of GOES observations
  • Implementation completed but validation needed

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4. Methodology

Validate GOES-based Dryness Index with temporal and spatial patterns of:

University of Amsterdam/NASA multi-sensor products of surface soil moisture, vegetation water content, and land surface temperature (Owe et al. 2008, Holmes et al., 2009)

SMOS L-Band estimates of soil moisture (European Space Agency)

In situ soil moisture: such as are available CREST network, OK meso network

Surface Bowen ratio and evapotranspiration from the GOES-based ALEXI model (previously funded GIMPAP project).

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5. Expected Outcomes

New tool to provide fire weather forecasters daily changes in surface wetness and fuel loads.

It is expected that the products will be enhanced with the availability of GOES-R data; especially with the enhanced resolution and capability of directly estimating NDVI from the ABI

Index will be more readily accepted with further validation

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6. First Year - Preliminary Results

  • Began comparisons of GOES dryness index with the University of Amsterdam products of surface soil moisture, vegetation water content (based on AMSR-E) for 2011.
  • Expect negative correlation between soil moisture and GOES dryness index. Magnitude of correlation:
  • depends on land surface type
  • exhibits a seasonal dependence

Shrub, Grassland: negative early in growing season

Forest, Crop: negative later in growing season

Starting comparisons with in-situ soil moisture

(Milbrook, NY NOAA/CREST station)

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GOES-13

Heating Rate: 25 June-09 July 2011

Yellow/Red: Dry Green: Wet

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GOES-13

Heating Rate Anomaly: 25 June-09 July 2011

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Sample scatterplot

Surface type: scrub

Correlation: -.60

Date of Scatter plot

AMSR-E problem sensing moisture through dense vegetation?

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Forest

Crop

Grasslands

corr = -0.38

corr = -0.29

corr = -0.10

corr = 0.12

corr = 0.48

corr = 0.37

Unexpected positive Correlation: Lack of data?

Next steps: Segregate results by NDVI

USGS land use

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7. Possible Path to Operations

Already available in NAWIPS at SPC

Further Refinement as needed

Implement at NESDIS SAB

Make product available to AWIPS2

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8. FY13 Milestones

FY 2012:

1. Acquire and process data for validation

2. Analyze and compare AMSR-E, SMOS (if available) and in situ data

FY 2013:

1. Publish results

2. Implement and train for use at SAB and elsewhere

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10. Spending Plan FY13

Travel support (NSSL): $1.5 K

$ 1.5K Travel (R. Rabin) Q2 and Q3

2 trips Norman-NESDIS/SAB (Maryland)

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