GES DISC PARTICIPATION AT THE 2008 AGU JOINT ASSEMBLY

Several GES DISC staff members will be participating and presenting at the 2008 American Geophysical Union (AGU) Joint Assembly meeting in Fort Lauderdale, Florida, May 27-30, 2008.   In addition to presentations, staff members will demonstrated the A-Train Data Depot (ATDD) capabilities during the meeting.

Presentations

Tools for Accessing Cloud Properties From Multiple Heterogeneous A-Train Sensors

Steven Kempler, Peter Smith, Andrey Savtchenko, Gregory Leptoukh, Graeme Stephens, and David Winker

Abstract:

To perform multi-satellite research with A-Train data originating from heterogeneous missions, scientists must discover, access, subset, visualize, and analyze user specified datasets, in ways unique to each dataset. Then, the datasets need to be co-registered.  Specifically, scientists attempting to retrieve cloud data and extract information that supports their science research, each must perform these laborious steps.
 
The A-Train Data Depot (ATDD), http://disc.gsfc.nasa.gov/atdd, has been developed to save each scientist the effort and expense of developing the functions to perform these tasks individually.  The ATDD, operational for over a year, successfully serves co-registered data, as spatially and temporally specified (dynamically) by the researcher, from the Cloudsat, CALIOP, AIRS, MODIS, OMI, and now POLDER instruments.  
 
This paper will demonstrate the value of the ATDD in easily and efficiently acquiring the data and information that would allow scientists to just focus on their science research, and not the access to the data.  A significant step implemented in the ATDD, concerns overlaying OMI, POLDER, MODIS, and AIRS 2-D cloud pressure data on the vertical profiles that follow the A-Train track.  Once parameters of interest for cloud studies are visualized, various collocated and subsetted data sets as well as PNG image files can be downloaded.  This user specified visualization of A-Train data greatly aids researchers by conveniently availing them of specific data of interest, while affording more time for research.

Assessment of U.S Particulate Air Quality using MODIS, OMI, CALIPSO, and surface PM2.5 measurements via Giovanni

Prados, A I, Leptoukh, G., Labow, G. , Savtchenko, A., Gopalan, A., and Johnson, J.

Abstract:

To improve our understanding of the relationship between Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) and U.S particulate air quality, we combine MODIS Aqua AOD, Ozone Monitoring Instrument (OMI) Aerosol Index (AI), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIOP) measurements over the continental U.S. The purpose is to use additional remote sensing information to help improve the utility of MODIS AOD observations for assessing surface aerosols over the U.S.

We present several case studies of the use A-Train data to analyze the transport and vertical evolution of smoke and pollution plumes, and the use of simultaneous OMI AI and MODIS AOD observations to improve the correlation between surface PM2.5 and MODIS Aqua AOD. We focus on October 21-26 2007, when intense fires in Southern California lead to serious National Ambient Air Quality Standard (NAAQS) PM2.5 exceedances.

Then, we examine U.S air quality on August 1-4, 2007 when the U.S Northeast, Southeast, and Mid-Atlantic region experienced moderately hazy conditions due to local sources and transported smoke, while the Central and Western U.S were impacted by dense smoke plumes. Our analysis includes imagery and data obtained through the NASA Goddard online system Giovanni (http://giovanni.gsfc.nasa.gov). PM2.5 monitor data are acquired from the EPA at DataFed and then imported via WCS into Giovanni. Giovanni tools include maps, time series, AOD/PM2.5 correlation maps and scatter plots, and image animations for examining the long range transport of air aerosols during these pollution events.

This preliminary analysis indicates that constraining the MODIS data by additional information from OMI and CALIPSO improves the correlation between MODIS AOD and surface PM2.5.

Deep Convection and Upper Tropospheric Humidity -- A Look from the A-Train

Andrey Savtchenko and Steve Platnick

Introduction:

• The relationship between the deep convection and the humidifying of the upper troposphere has been given attention since early days of TOVS, given the importance of this problem in the assessment of the greenhouse effects.
• The establishment of the A-Train formation gives an opportunity to look at this problem from many new, much more detailed, aspects.
• A-Train is rich on vertical sounders, yielding unprecedented data on the vertical structure of clouds and atmospheric water content. This  presentation, however, focuses on retrievals from CloudSat and AIRS, and GDAS model data.

Dr. Steven Lloyd will also be giving a talk to the Geophysical Information for Teachers (GIFT) Workshop. His talk is entitled Giovanni and the Goddard Hurricane Portal.