1. Algorithm for VIIRS Dust Detection
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Evaluating NCEP Global Dust Forecasts using VIIRS Dust Mask Index and VIIRS Aerosol Observations
Sarah Lu1,2*, Partha Bhattacharjee1,3, Pubu Ciren3,4, Jun Wang1,3, and Shobha Kondragunta4
1NOAA/NCEP; 2 University at Albany, State University of New York; 3I.M.Systems Group Inc.; 4NOAA/NESDIS/STAR
*Corresponding author,
Algorithm for VIIRS Dust Detection
NEMS Global Aerosol Component (NGAC)
Why Include Aerosols in the Predictive Systems?
VIIRS Dust Aerosol Index: An algorithm based on observations from deep-blue and shortwave-IR developed for MODIS has been adapted for VIIRS.
The first global in-line aerosol forecast system at NOAA/NCEP
Model Configuration:
AGCM: NOAA/NCEP’s NEMS GFS
Aerosols: NASA/GSFC’s GOCART
120-hr dust-only forecast once per day (00Z)
Initialization: Aerosols from previous day forecast and meteorology from operational GDAS
Implemented into NCEP production suite in Sept 2012
The implementation of multi-species forecasts (dust, sea salt, sulfate, and carbonaceous aerosols) using near-real-time smoke emissions is planned in FY15
Improve weather forecasts and climate predictions by taking into account of aerosol effects on radiation and clouds
Improve the handling of satellite observations by properly accounting for aerosol effects during the assimilation procedure
Provide aerosol (lateral and upper) boundary conditions for regional air quality predictions
Produce quality aerosol information that address societal needs and stakeholder requirements
Dust Aerosol Index (DAI) Algorithm
for MODIS
Pubu Ciren and Shobha Kondragunta
JGR-Atmos, 03/2014 DOI: /2013JD020855
DAI after cloud screening
NDAI after cloud screening
Sunglint
flag
Dust flag
Final dust flag
Sahara dust outbreak (July 30, 2013)
This dust outbreak was reported in news media, e.g.,
Nightly News: Massive dust storm sweeps over Atlantic, reported by NBC’s Brian Williams (July 31, 2013)
KSAT (San Antonio, TX): Saharan dust cloud over San Antonio irritates residents (Aug 9, 2013)
Seguin Gazette (Sequin TX) : Sahara dust sweeps through Texas (Aug 11, 2013)
Long range dust transport across the Atlantic
Jul 2013
Aug 2013 A B C D E F
OMPS Aerosol Index (Jul 29, 2013)
VIIRS image (Jul )
Dust AOD from NGAC (top) and VIIRS (bottom) for Jul-Aug VIIRS dust mask and AOD are combined to generate VIIRS dust AOD.
A B
Dust AOD forecast by NGAC (A) and the ICAP multi-model ensemble (B) on Aug 7, 2013
Saharan dust travels across Atlantic, shown by VIIRS AOD (A), VIIRS DAI (B), NGAC dust AOD (C), and total AOD from MODIS (D), MODIS Deep Blue (E), and OMI (F). A
Summary
Dust Aerosol Index algorithm for MODIS has been adapted for VIIRS globally.
NGAC dust forecasts are evaluated using VIIRS aerosol products.
Long range dust transport across Atlantic are captured by NGAC
The VIIRS DAI is correlated with NGAC dust AOD (R=0.64) for the dust event presented here.
The VIIRS dust detection capability contributes toward the monitoring of dust plumes and the evaluation of dust forecasts. For the areas with the presence of non-dust aerosols, the information from VIIRS dust detection is particularly useful. B
ICAP (International Cooperative for Aerosol Prediction) MME is based on aerosol forecasts from NCEP (NGAC), ECMWF, NRL, GMAO, JMA, BSC.
NGAC dust AOD (in y-axis) versus VIIRS DAI (in x-axis), averaged from Jul 27 to Aug 5, 2013,, over the 10S-40N & 80W-20E domain,
Acknowledgment: The development and implementation of NGAC has been supported by NASA Applied Science Program, Joint Center for Satellite Data Assimilation (JCSDA), and NOAA National Weather Services (NWS). The team thanks Didier Tanre and Olga Mayol-Bracero for the efforts in establishing and maintaining Dakar and San Juan site, respectively.
NGAC dust AOD (black), AERONET AOD (yellow) and VIIRS AOD (green) at Dakar (A) and San Juan (B) sites. The time period when VIIRS DAI exceeding [less than] 2 is marked by red [blue]
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