Earth and Space Science Informatics [IN]

IN53B
 MC:3014  Friday  1340h

Making Earth Science Data Records II


Presiding:  H K Ramapriyan, NASA; M Maiden, NASA; R Kakar, NASA

IN53B-01 INVITED

NASA's MEaSUREs Program: Making Earth System data records for Use in Research Environments

* Maiden, M E martha.e.maiden@nasa.gov, NASA Headquarters, Earth Science Division, Washington, DC 20546, United States
Ramapriyan, H K hampapuram.k.ramapriyan@nasa.gov, NASA Goddard Space Flight Center, Code 423, Greenbelt, MD 20771, United States

A major need stated by the NASA Earth science research strategy is to develop long-term, consistent, and calibrated data and products that are valid across multiple missions and satellite sensors. NASA coined the term Earth System Data Record, or ESDR, and defined the term to mean a unified and coherent set of observations of a given parameter of the Earth system, which is optimized to meet specific requirements in addressing science questions. For creating these basic records, a science measurement focus brings together expertise in multiple instrument characterization and calibration, data processing, science-based product generation and distribution, science tools, and interactive relationships with the broader science community. There is a sense that these important records must have a maturity that includes vetting within the community that utilizes them. Responsible NASA Managers ensure that each Project seeks guidance from community scrutiny and review of product quality and acceptability. MEaSUREs Projects have requirements to make data available on a nonexclusive basis. For example, each Project must maintain a public WWW-compliant presence and plan on transferring the final version of the data products to a NASA-designated Data Center. Principal Investigators for these Projects enter into Cooperative Agreements (instead of Grants) with NASA. Nominally, an alternate Data Rights section in these Agreements codifies an agreement that the input data, the scientific software used for processing the raw instrument data into scientific data, including source code, and the ESDRs with accompanying metadata and quality assessments, is exchanged without restriction as to its disclosure, use, or duplication. For these important records, complete scientific validation must be enabled and full utilization encouraged. The first request for proposals under the MEaSUREs Program was sent out by NASA in late 2006 and resulted in the selection of 29 projects covering generation of ESDRs in several Earth science disciplines including: atmospheric dynamics, atmospheric composition, land cover, topography, solid Earth, ocean biology, hydrology, cryosphere, climate change, and physical oceanography. Some of these projects are continuations or refinements of ESDRs from earlier NASA projects or satellite missions. The products from most of the new projects are expected to start becoming publicly available by 2010.

IN53B-02 INVITED

Relating A-Train Water Vapor Observations to Cloud Classes from CloudSat

* Fetzer, E J Eric.J.Fetzer@jpl.nasa.gov, Jet Propulsion Laboratory/California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109,
Kahn, B H Brian.H.Kahn@jpl.nasa.gov, Jet Propulsion Laboratory/California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109,
Teixeira, J Joao.Teixeira@jpl.nasa.gov, Jet Propulsion Laboratory/California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109,
Fishbein, E F Evan.F.Fishbein@jpl.nasa.gov, Jet Propulsion Laboratory/California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109,
Wilson, B D Brian.D.Wilson@jpl.nasa.gov, Jet Propulsion Laboratory/California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109,
Waliser, D E Duane.E.Waliser@jpl.nasa.gov, Jet Propulsion Laboratory/California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109,

Three of the standard data sets from the NASA A-Train satellite constellation are CloudSat cloud classes, Atmospheric Infrared Sounder (AIRS) moist thermodynamic observations, and Advanced Microwave Sounding Radiometer for EOS (AMSR-E) total precipitable water vapor. We describe AIRS and AMSR-E water vapor observability, and the associated climatologies, conditional on CloudSat cloud classes. Because cloud classes represent unique physical processes, each scene type can be expected to have distinct temperature and water vapor signatures. Understanding the sampling characteristics of the water vapor observations is critical to interpreting them in the context of changing cloud and water vapor regimes.

IN53B-03

Improvement of the NVAP Global Water Vapor Data Set for Climate, Hydrological and Weather Studies

* Forsythe, J M forsythe@cira.colostate.edu
Vonder Haar, T H vonderhaar@cira.colostate.edu
Bytheway, J janice@atmos.colostate.edu

The NASA Water Vapor Project (NVAP) dataset is an existing multisensor, global, daily climate data record of water vapor from 1988-2001. A variety of satellite retrievals of water vapor, both total column and layered, are blended together to create the dataset. NVAP has been valuable for a variety of studies of phenomena on different timescales. Examples include monsoons, the Madden-Julian Oscillation, and global effects of El Nino. The variety of NVAP users requires a dataset designed to meet the needs of a diverse group. Sample applications of the NVAP dataset for weather studies to interannual and decadal variability will be shown. A reanalysis and continuation of NVAP beyond 2001 has begun under the NASA MEaSURES program. Current efforts to continue NVAP beyond 2001 into the era of the NASA Aqua spacecraft will be described. The Aqua water vapor products from 2002 to the present are being used to understand the inputs to the NVAP reanalysis, which include SSM/I, TOVS, and AMSU and SSM/T-2. The overlap between these instruments and the Aqua spacecraft instruments will allow an understanding of the differences between these datasets, and guide a reanalysis of NVAP. In addition, the Aqua results will themselves be incorporated into the new NVAP dataset.

IN53B-04

Reviving the Goddard Satellite-based Surface Turbulent Fluxes (GSSTF) Dataset

* Shie, C Chung-Lin.Shie-1@nasa.gov, NASA/GSFC, Code 613.1, Greenbetl, MD 20771, United States
* Shie, C Chung-Lin.Shie-1@nasa.gov, UMBC/GEST, 1000 Hilltop Circle, Baltimore, MD 21250, United States
Chiu, L lchiu@gmu.edu, GMU/CEOSR, 4400 University Drive, Fairfax, VA 22030, United States
Adler, R Robert.F.Adler@nasa.gov, UMCP/ESSIC, UMCP, Greenbelt Road, College Park, MD 20742, United States
Adler, R Robert.F.Adler@nasa.gov, NASA/GSFC, Code 613.1, Greenbetl, MD 20771, United States
Nelkin, E Eric.J.Nelkin@nasa.gov, SSAI, 10210 Greenbelt Road, Suite 600, Lanham, MD 20706, United States
Nelkin, E Eric.J.Nelkin@nasa.gov, NASA/GSFC, Code 613.1, Greenbetl, MD 20771, United States
Lin, I iilin@webmail.as.ntu.edu.tw, NTU/Dept of Atmospheric Sciences, No. 1, Sec. 4, Roosevelt Road, Taipei, 10617, Taiwan
Xie, P Pingping.Xie@noaa.gov, NOAA/CPC, 5200 Auth Road, Camp Springs, MD 20746, United States

The Goddard Satellite-based Surface Turbulent Fluxes datasets, GSSTF1 and GSSTF2 (versions 1 and 2), were officially released in 2000 and 2001, respectively. These datasets (especially GSSTF2 with a longer period and a finer spatial resolution) have been widely used by scientific communities for global energy and water cycle research, and regional and short period data analyses. Accurate sea surface flux measurements are crucial to understand the global water and energy cycles. The oceanic evaporation, which is a major component of the global oceanic fresh water flux, is particularly useful for predicting oceanic circulation and transport. Remote sensing is a valuable tool for global monitoring of these flux measurements. The GSSTF algorithm has been developed and applied to remote sensing research and applications. The research project that produced GSSTF2 (covering a data period of July 1987-December 2000), however, ended in 2001. We have very recently been funded by NASA to resume processing of, and to reprocess, the GSSTF dataset with an objective of continually producing a uniform dataset of sea surface turbulent fluxes, derived from remote sensing data and analysis. The dataset is to be reprocessed and brought up-to-date using improved input datasets. The input datasets, which are currently under processing, include a recently released NCEP sea surface temperature analysis, and a uniform (across satellites) surface wind and microwave brightness temperature V6 dataset (Version 6) from the Special Sensor Microwave Imager (SSM/I) on board the Defense Meteorological Satellite Program (DMSP) satellites produced by Frank Wentz's group of Remote Sensing Systems. Wentz indicated that spurious trends in their wind speed retrievals were removed. Our preliminary analysis indeed shows such an improvement in the retrieved wind speed data from SSM/I V4 to SSM/I V6. A second new product with a finer temporal (12-hr) and spatial (0.25° × 0.25°) resolution (upgraded from the current daily and 1° × 1° GSSTF2) is planned, using an improved SST from Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) and TRMM Microwave Imager (TMI), and ocean surface wind vector from the Quick Scatterometer (QuikSCAT) and Advanced Earth Observing Satellite II (ADEOS2) SeaWinds. These two developing products (1) daily and 1o x 1o GSSTF2b (July 1987-Dec 2008), and (2) 12-hr and 0.25° × 0.25° GSSTF3 (July 1999-Dec 2009) are scheduled to be completed and released for research community use by late 2009 and early 2011, respectively.

IN53B-05 INVITED

An Earth System Data Record for Land Surface Freeze/Thaw State: Quantifying Terrestrial Water Mobility Constraints to Global Ecosystem Processes

* Kimball, J S johnk@ntsg.umt.edu, Flathead Lake Biological Station, Division of Biological Sciences, The University of Montana, 32125 Bio Station Lane, Polson, MT 59860-6815, United States
McDonald, K C kyle.mcdonald@jpl.nasa.gov, Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109-8099, United States

The landscape transition between seasonally frozen and non-frozen conditions occurs each year over more than 50 million km2 of the global biosphere, affecting surface hydrology and ecological trace gas dynamics profoundly. Satellite microwave remote sensing can detect large changes in landscape dielectric properties between frozen and non-frozen conditions. We are constructing an Earth System Data Record (ESDR) quantifying freeze-thaw (F/T) dynamics for the global vegetated land surface. The F/T ESDR (F/T- ESDR) involves multi-frequency satellite microwave remote sensing records spanning multiple missions and sensors. These records provide a contiguous global time series extending from 1979 onward with some overlap between missions. We employ a temporal change detection analysis of daily backscatter and brightness temperatures to map F/T changes associated with temporal shifts in landscape dielectric properties between predominantly frozen and non-frozen conditions. Empirical methods and radar backscatter and microwave emissions models are used for merging overlapping sensor time series into calibrated F/T time series. The F/T state variable provides a surrogate measure of landscape water mobility and associated cold temperature constraints to biological processes, including vegetation productivity and carbon exchange. The F/T-ESDR will also help refine baseline conditions for future F/T measurements from the NASA Soil Moisture Active-Passive (SMAP) mission. Initial F/T-ESDR results are available, while data processing continues through 2012. This work was performed at the University of Montana and Jet Propulsion Laboratory, California Institute of Technology under contract to NASA.

http://freezethaw.ntsg.umt.edu

IN53B-06

Elements of Successful Cryospheric Climate Data Records

* Robinson, D A drobins@rci.rutgers.edu, Department of Geography, Rutgers University, 54 Joyce Kilmer Avenue, Piscataway, NJ 08854,

For the past four decades, data from satellite-borne sensors have provided environmental information at a variety of spatial scales. So too in recent years has considerable progress been made in assembling, digitizing and documenting ground-based station observations. These data have led to valuable insights regarding Earth's land, atmosphere, oceans and cryosphere systems. Time series of elements within these systems have been scrutinized in attempts to better understand climate variability and to identify critical trends that may signal changes in the climate system. From these studies, has emerged a growing appreciation for the importance of climate data records (CDRs) that possess the accuracy, longevity and stability to facilitate credible climate monitoring. These CDRs provide important information to assist those making decisions regarding the fate of our environment. Considerable work remains to assemble many environmental data records into credible CDRs. In 2005, the author chaired a National Research Council committee that identified 14 key elements for creating CDRs. The focus was mainly on satellite records however they were divided into three general categories that include organizational, generation and sustaining elements, many of which are applicable to any CDR endeavor. This presentation will address the elements using cryospheric records as examples of environmental datasets that are in the process of being developed into CDRs.

IN53B-07

An Inundated Wetlands Earth System Data Record: Global Monitoring of Wetland Extent and Dynamics

* Podest, E erika.podest@jpl.nasa.gov, Jet Propulsion Laboratory/California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, United States
McDonald, K kyle.mcdonald@jpl.nasa.gov, Jet Propulsion Laboratory/California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, United States
Chapman, B bruce.chapman@jpl.nasa.gov, Jet Propulsion Laboratory/California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, United States
Hess, L lola@icess.ucsb.edu, University of California in Santa Barbara, Institute for Computational Earth System Science, 6712 Ellison Hall, Santa Barbara, CA 93106, United States
Moghaddam, M mmoghadd@umich.edu, The University of Michigan, Dept. of Electrical Eng. and Computer Science, 1301 Beal Ave., Ann Arbor, MI 48109, United States
Kimball, J S johnk@ntsg.umt.edu, University of Montana, Flathead Lake Biological Station, 32125 Bio Station Lane, Polson, MT 59860, United States
Matthews, E ematthews@giss.nasa.gov, Goddard Institute for Space Studies, 2880 Broadway, New York, NY 10025, United States
Prigent, C catherine.prigent@obspm.fr, CNRS, Observatoire de Paris, 61 Av. de l'Observatoire, Paris, 75014, France

Wetlands exert major impacts on global biogeochemistry, hydrology, and biological diversity. The extent and seasonal, interannual, and decadal variation of inundated wetlands play key roles in ecosystem dynamics. Despite the importance of these environments in the global cycling of carbon and water and to current and future climate, the extent and dynamics of global wetlands remain poorly characterized and modeled. This is primarily because of the scarcity of suitable regional-to-global remote-sensing data for characterizing wetland distribution and dynamics. As part of a NASA MEaSUREs project, we are constructing a global-scale Earth System Data Record (ESDR) of inundated wetlands to facilitate investigations on their role in climate, biogeochemistry, hydrology, and biodiversity. The ESDR is being generated using legacy algorithms developed from spaceborne remote sensing data sets and is comprised of two complementary components. The first are fine resolution (100 m) maps of wetland extent, vegetation type, and seasonal inundation dynamics, derived from Synthetic Aperture Radar (SAR), for continental-scale areas covering crucial wetland regions. The second are global monthly maps of inundation extent at ~25 km resolution for the period 1992- 2009, derived from multiple satellite observations. We present details of the ESDR construction including remote sensing algorithm applications, cross-product harmonization, and planned data set distribution. The status of current efforts to assemble this ESDR, including data processing, wetland classifications, and open water change mappings derived from L-band data for the state of Alaska and select basins in Eurasia are presented. This ESDR will provide the first accurate, consistent and comprehensive global-scale data set of wetland inundation and vegetation, including continental-scale multitemporal and multi-year monthly inundation dynamics at multiple scales. Portions of this work were carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.