Engineering topics

Leptoukh, Gregory

Publications and source records attributed to Leptoukh, Gregory.

At least 37 records · Page 2

NASA NTRS2010

Community-Based Services that Facilitate Interoperability and Intercomparison of Precipitation Datasets from Multiple Sources

Over the past 12 years, large volumes of precipitation data have been generated from space-based observatories (e.g., TRMM), merging of data products (e.g., gridded 3B42), models (e.g., GMAO), climatologies (e.g., Chang SSM/I derived rain indices), field campaigns, and ground-based measuring stations. The science research, applications, and education communities have greatly benefited from the unrestricted availability of these data from the Goddard Earth Sciences Data and Information Services Center (GES DISC) and, in particular, the services tailored toward precipitation data access and usability. In addition, tools and services that are responsive to the expressed evolving needs of the precipitation data user communities have been developed at the Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google NASA PDISC), located at the GES DISC, to provide users with quick data exploration and access capabilities. In recent years, data management and access services have become increasingly sophisticated, such that they now afford researchers, particularly those interested in multi-data set science analysis and/or data validation, the ability to homogenize data sets, in order to apply multi-variant, comparison, and evaluation functions. Included in these services is the ability to capture data quality and data provenance. These interoperability services can be directly applied to future data sets, such as those from the Global Precipitation Measurement (GPM) mission. This presentation describes the data sets and services at the PDISC that are currently used by precipitation science and applications researchers, and which will be enhanced in preparation for GPM and associated multi-sensor data research. Specifically, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) will be illustrated. Giovanni enables scientific exploration of Earth science data without researchers having to perform the complicated data access and match-up processes. In addition, PDISC tool and service capabilities being adapted for GPM data will be described, including the Google-like Mirador data search and access engine; semantic technology to help manage large amounts of multi-sensor data and their relationships; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion to various formats (e.g., netCDF, HDF, KML (for Google Earth)); visualization and analysis of Level 2 data profiles and maps; parameter and spatial subsetting; time and temporal aggregation; regridding; data version control and provenance; continuous archive verification; and expertise in data-related standards and interoperability. The goal of providing these services is to further the progress towards a common framework by which data analysis/validation can be more easily accomplished.

Liu, Zhong↗

NASA NTRS2010

The Multi-Sensor Aerosol Products Sampling System (MAPSS) for Integrated Analysis of Satellite Retrieval Uncertainties

Among the known atmospheric constituents, aerosols represent the greatest uncertainty in climate research. Although satellite-based aerosol retrieval has practically become routine, especially during the last decade, there is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. As long as there is no consensus and the inconsistencies are not well characterized and understood ', there will be no way of developing reliable climate data records from satellite aerosol measurements. Fortunately, the most globally representative well-calibrated ground-based aerosol measurements corresponding to the satellite-retrieved products are available from the Aerosol Robotic Network (AERONET). To adequately utilize the advantages offered by this vital resource,., an online Multi-sensor Aerosol Products Sampling System (MAPSS) was recently developed. The aim of MAPSS is to facilitate detailed comparative analysis of satellite aerosol measurements from different sensors (Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and Calipso-CALIOP) based on the collocation of these data products over AERONET stations. In this presentation, we will describe the strategy of the MAPSS system, its potential advantages for the aerosol community, and the preliminary results of an integrated comparative uncertainty analysis of aerosol products from multiple satellite sensors.

Ichoku, Charles↗

NASA NTRS2010

Sensitivity of Aerosol Multi-Sensor Daily Data Intercomparison to the Level 3 Dataday Definition

Topics include: why people use Level 3 products, why someone might go wrong with Level 3 products, differences in L3 from different sensors, Level 3 data day definition, MODIS vs. MODIS, AOD MODIS Terra vs. Aqua in Pacific, AOD Aqua MODIS vs. MISR correlation map, MODIS vs MISR on Terra, MODIS atmospheric data day definition, orbit time difference for Terra and Aqua 2009-01-06, maximum time difference for Terra (Calendar day), artifact explains, data day definitions, local time distribution, spatial (local time) data day definition, maximum time difference between Terra and Aqua, Removing the artifact in 16-day AOD correlation, MODIS cloud top pressure, and MODIS Terra and Aqua vs. AIRS cloud top pressure.

Leptoukh, Gregory↗

NASA NTRS2010

NASA Goddard Giovanni Support for YOTC

The fundamental challenges to overcoming our shortcomings in understanding and modeling/predicting tropical convection have been twofold: I) the need to represent the broad range of scales applicable to the tropical organization problem (i.e. cumulus to planetary), and II) the lack of observations that adequately and simultaneously characterize this broad range of scales and that also provide three-dimensional information on thermodynamic, radiative and dynamical interactions, including cloud microphysical processes. In regards to the second challenge, it should be stressed that this problem will not be solved through the production and examination of one or a few high quality long-term records of fundamental quantities (e.g., SST, water vapor, cloud fraction). Rather, an alternative and more comprehensive paradigm is needed, one that integrates the multitude of applicable resources and measures of tropical convection in a manner that that can be better utilized by the diagnostic, modeling and forecasting communities to more completely and coherently focus on the problem.Because the goal of YOTC involves examining a scientifically complex, multi-scale process , rather than documenting the characteristics of a single parameter (e.g., SST, cloud cover), YOTC has an IOP perspective that targets a period, May 2008 April 2010, long enough to encompass many cases of tropical convection activity in many of its most challenging yet influential forms. This includes mesoscale and synoptic variability, easterly waves and hurricanes, convectively coupled waves, the MJO and the culmination of these in terms of the monsoon, their interactions with the extra-tropics, and mean characteristics such as tropical-to-subtropical transitions. The YOTC time period and length are driven in part by the following: 1) keeping the multi-sensor/multi-platform and model-analyses data sets and associated infrastructure manageable, 2) facilitating a focused effort by the research and operational communities on a specific scientific problem, and 3) capitalizing on the recent key additions to the armada of satellites (e.g., CloudSat and CALIPSO). The proposed dissemination framework for the YOTC satellite data archive is based on the Giovanni system. Giovanni is a web-based application developed by the NASA Goddard Earth Science (GES) Data and Information Service Center (DISC) that provides a simple and intuitive way to visualize, analyze, and access/download vast amounts of Earth science remote sensing data. A prototype YOTC Giovanni System (hereafter YOTC-GS) is in the process of being developed. YOTC-GS will provide access to level 2 (i.e. swath level data) and/or level 3 (i.e. gridded/mapped data) forms of satellite data, the choice or both depending on what is appropriate and relevant. The former is needed and better suited for detailed process examination, exploiting the highest temporal-spatial resolutions available and comparison to regional cloud-system resolving model / cloud resolving model (CSRM/CRM) model output. The latter is needed and more well suited for examination of phenomena, conditions and processes on large to global scales, and for comparisons to global model analyses, prediction and simulation output.

Ostrenga, Dana↗

NASA NTRS2010

Utilizing Higher Resolution Land Surface Remote Sensing Data for Assessing Recent Trends over Asia Monsoon Region

The slide presentation discusses the integration of 1-kilometer spatial resolution land temperature data from the Moderate Resolution Imaging Spectroradiometer (MODIS), with 8-day temporal resolution, into the NASA Monsoon-Asia Integrated Regional Study (MAIRS) Data Center. The data will be available for analysis and visualization in the Giovanni data system. It discusses the NASA MAIRS Data Center, presents an introduction to the data access tools, and an introduction of Products available from the service, discusses the higher resolution Land Surface Temperature (LST) and presents preliminary results of LST Trends over China.

Shen, Suhung↗

NASA NTRS2009

Short-term Aerosol Trends: Reality or Myth?

The main questions addressed in this slide presentation involve short-term trends of MODIS aerosol optical thickness (AOT) over 6 years: (1) Why are the trends different in different regions? (2) How are these trends so high? (3) Why are they "coherent" in many areas? (4) Are these changes in aerosol concentrations real, i.e., are they monotonic changes in emissions? Several views of the Spatial Distribution of AOT from Terra are shown. In conclusion there are several trends: (1) There is a broad spatial inhomogenueity in AOT trends over 6 years of MODIS Terra and Aqua (2) Some of the areas demonstrate clear positive trends related to increase of emission (e.g., Eastern China) (3) Strong trends in some other areas are superficial and might be attributed, in part, to: (3a) Least squares linear trend sensitivity to outliers (need to use more robust linear fitting method) (3b) Spatial and temporal shifts or trends in meteorological conditions, especially in wind patterns responsible for aerosol transport (6) Aerosol trends should be studied together with changes in meteorology patterns as they might closely linked together

Leptoukh, Gregory↗

NASA NTRS2009

Utilizing Remote Sensing Data to Ascertain Soil Moisture Applications and Air Quality Conditions

Recognizing the significance of NASA remote sensing Earth science data in monitoring and better understanding our planet's natural environment, NASA Earth Applied Sciences has implemented the 'Decision Support Through Earth Science Research Results' program. Several applications support systems through collaborations with benefiting organizations have been implemented. The Goddard Earth Sciences Data and Information Services Center (GES DISC) has participated in this program on two projects (one complete, one ongoing), and has had opportune ad hoc collaborations utilizing NASA Earth science data. GES DISC's understanding of Earth science missions and resulting data and information enables the GES DISC to identify challenges that come with bringing science data to research applications. In this presentation we describe applications research projects utilizing NASA Earth science data and a variety of resulting GES DISC applications support system project experiences. In addition, defining metrics that really evaluate success will be exemplified.

Leptoukh, Gregory↗

NASA NTRS2008

A-Train Data Depot (ATDD)

ATDD is a web based tool which provides collocated data and display products for a number of A-train instruments Cloudsat, Calipso, OMI, AIRS, MODIS, MLS, POLDER-3, and ECWMF model data. Products provided include Clouds, Aerosols, Water Vapor, Temperatures and trace gases. All input data is online and in HDF4, HDF5 format. Display products include curtain images, horizontal strips, line plot overlays, and GE kmz files. Sample products are shown for two type of events. Hurricane event, Norbert, Oct 8, 2008 and a dust storm event over the Arabian Sea, Nov 13-14, 2008.

Smith, Peter M.↗

NASA NTRS2008

Experiences in Bridging the Gap between Science and Decision Making at NASA's GSFC Earth Science Data and Information Services Center (GES DISC)

Recognizing the significance of NASA remote sensing Earth science data in monitoring and better understanding our planet s natural environment, NASA has implemented the Decision Support Through Earth Science Research Results program (NASA ROSES solicitations). a) This successful program has yielded several monitoring, surveillance, and decision support systems through collaborations with benefiting organizations. b) The Goddard Space Flight Center (GSFC) Earth Sciences Data and Information Services Center (GES DISC) has participated in this program on two projects (one complete, one ongoing), and has had opportune ad hoc collaborations gaining much experience in the formulation, management, development, and implementation of decision support systems utilizing NASA Earth science data. c) In addition, GES DISC s understanding of Earth science missions and resulting data and information, including data structures, data usability and interpretation, data interoperability, and information management systems, enables the GES DISC to identify challenges that come with bringing science data to decision makers. d) The purpose of this presentation is to share GES DISC decision support system project experiences in regards to system sustainability, required data quality (versus timeliness), data provider understanding of how decisions are made, and the data receivers willingness to use new types of information to make decisions, as well as other topics. In addition, defining metrics that really evaluate success will be exemplified.

Kempler, Steven↗

NASA NTRS2008

Data Visualization and Analysis for Climate Studies using NASA Giovanni Online System

With many global earth observation systems and missions focused on climate systems and the associated large volumes of observational data available for exploring and explaining how climate is changing and why, there is an urgent need for climate services. Giovanni, the NASA GES DISC Interactive Online Visualization ANd ANalysis Infrastructure, is a simple to use yet powerful tool for analysing these data for research on global warming and climate change, as well as for applications to weather. air quality, agriculture, and water resources,

Rui, Hualan↗

NASA NTRS2008

The NASA NEESPI Data Portal: Products, Information, and Services

Studies have indicated that land cover and use changes in Northern Eurasia influence global climate system. However, the procedures are not fully understood and it is challenging to understand the interactions between the land changes in this region and the global climate. Having integrated data collections form multiple disciplines are important for studies of climate and environmental changes. Remote sensed and model data are particularly important die to sparse in situ measurements in many Eurasia regions especially in Siberia. The NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) NEESPI data portal has generated infrastructure to provide satellite remote sensing and numerical model data for atmospheric, land surface, and cryosphere. Data searching, subsetting, and downloading functions are available. ONe useful tool is the Web-based online data analysis and visualization system, Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure), which allows scientists to assess easily the state and dynamics of terrestrial ecosystems in Northern Eurasia and their interactions with global climate system. Recently, we have created a metadata database prototype to expand the NASA NEESPI data portal for providing a venue for NEESPI scientists fo find the desired data easily and leveraging data sharing within NEESPI projects. The database provides product level information. The desired data can be found through navigation and free text search and narrowed down by filtering with a number of constraints. In addition, we have developed a Web Map Service (WMS) prototype to allow access data and images from difference data resources.

Shen, Suhung↗

NASA NTRS2008

The NASA NEESPI Data Portal to Support Studies of Climate and Environmental Changes in Non-Boreal Europe

NASA NEESPI (Northern Eurasia Earth Science Partnership Initiative) data portal is a NASA funded project that focuses on collecting satellite remote sensing data, providing tools, information, and services in support of NEESPI scientific objectives (Leptoukh, et al., 2007). The data can be accessed online through anonymous ftp, through an advanced data searching and ordering system Mirador that uses keywords to find data quickly in a Google-like interface, and through the Goddard Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni). The portal provides preprocessed data from different satellite sensors and numerical models to the same spatial and temporal resolution and the same projection so that the data can be used easily to perform inter-comparison or relationship studies. In addition, it provides parameter and spatially subsetted data for regional studies. Studies of regional carbon, hydrology, aerosols in non-boreal Europe and their interactions with global climate are very challenging research topics. The NASA NEESPI data portal makes many satellite data available for such studies, including information on land cover types, fire, vegetation index, aerosols, land surface temperature, soil moisture, precipitation, snow/ice, and other parameters. This paper will introduce the features and products available in the system, focusing on the online data 1 tool, Giovanni NEESPI. An example that explores different data through Giovanni NEESPI in temperate region of non-boreal Europe will be presented.

Shen, Suhung↗

NASA NTRS2008

Using the NASA NEESPI Portal Data to Study Land, Climate, and Socio-Economic Changes in Northern Eurasia

A large number of fires detected in July of 2003 - a nearly 200-time increase in fire detections compared to other years during 2001-2006. despite the summer monsoon suppression of large fire occurrence. Traditional vegetation indices (NDVI and EVI) included in operational fire danger assessment provide little information on the fuel state in this ecosystem pre- or post-fire. No considerable differences in surface temperature and soil moisture in July were observed between the catastrophic year of 2003 and the two subsequent years of low summer fire occurrence of 2004 and 2005. However, the temporal analysis indicates that dry spring conditions in 2003 (detected through low soil moisture measurements in April and May) may have led to a stressed vegetative state and created conditions conducive to catastrophic fire occurrence.

Leptoukh, Gregory↗

NASA NTRS2007

A-Train Data Depot - Bringing Atmospheric Measurements Together

This paper describes the satellite data processing and services that constitute current functionalities of the A-Train Data Depot. We first provide a brief introduction to the original geometrical intricacies of the platforms and instruments of the A-Train constellation, and then proceed with description of our ATrain collocation processing algorithm that provides subsets that facilitate synergistic use of the various instruments. Finally, we present some sample image products from our web-based Giovanni tool which allows users to display, compare and download coregistered A-Train related data.

Savtchenko, Andrey↗

NASA NTRS2007

Spatial Aspects of Multi-Sensor Data Fusion: Aerosol Optical Thickness

The Goddard Earth Sciences Data and Information Services Center (GES DISC) investigated the applicability and limitations of combining multi-sensor data through data fusion, to increase the usefulness of the multitude of NASA remote sensing data sets, and as part of a larger effort to integrate this capability in the GES-DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni). This initial study focused on merging daily mean Aerosol Optical Thickness (AOT), as measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, to increase spatial coverage and produce complete fields to facilitate comparison with models and station data. The fusion algorithm used the maximum likelihood technique to merge the pixel values where available. The algorithm was applied to two regional AOT subsets (with mostly regular and irregular gaps, respectively) and a set of AOT fields that differed only in the size and location of artificially created gaps. The Cumulative Semivariogram (CSV) was found to be sensitive to the spatial distribution of gap areas and, thus, useful for assessing the sensitivity of the fused data to spatial gaps.

Leptoukh, Gregory↗

NASA NTRS2007

Exploiting the Capabilities of NASA's Giovanni System for Oceanographic Education

The NASA Goddard Earth Science Data and Information Services Center (GES DISC) Giovanni system [GES DISC Interactive Online Visualization ANd aNalysis Infrastructure] has significant capabilities for oceanographic education and independent research utilizing ocean color radiometry data products. Giovanni allows Web-based data discovery and basic analyses, and can be used both for guided illustration of a variety of marine processes and phenomena, and for independent research investigations. Giovanni's capabilities are particularly suited for advanced secondary school science and undergraduate (college) education. This presentation will describe a variety of ways that Giovanni can be used for oceanographic education. Auxiliary information resources that can be utilized will also be described. Several testimonies of Giovanni usage for instruction will be provided, and a recent case history of Giovanni utilization for instruction and research at the undergraduate level is highlighted.

Acker, James G.↗

NASA NTRS2007

Application of NASA Giovanni to Coastal Zone Remote Sensing Research

The Goddard Earth Sciences Data and Information Services Center (GES DISC) Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) provides rapid access to, and enables effective utilization of, remotely-sensed data that are applicable to investigations of coastal environmental processes. Data sets in Giovanni include precipitation data from the Tropical Rainfall Measuring Mission (TRMM), particularly useful for coastal storm investigations; ocean color radiometry data from the Sea-viewing Wide Field-of-view Sensor (SeaWIFS) and Moderate Resolution Imaging Spectroradiometer (MODIS), useful for water quality evaluation, phytoplankton blooms, and terrestrial-marine interactions; and atmospheric data from MODIS and the Advanced Infrared Sounder (AIRS), providing the capability to characterize atmospheric variables. Giovanni provides a simple interface allowing discovery and analysis of environmental data sets with accompanying graphic visualizations. Examples of Giovanni investigations of the coastal zone include hurricane and storm impacts, hydrologically-induced phytoplankton blooms, chlorophyll trend analysis, and dust storm characterization. New and near-future capabilities of Giovanni will be described.

Acker, James↗

NASA NTRS2007

Exploring NASA and ESA Atmospheric Data Using GIOVANNI, the Online Visualization and Analysis Tool

Giovanni, the NASA Goddard online visualization and analysis tool (http://giovanni.gsfc.nasa.gov) allows users explore various atmospheric phenomena without learning remote sensing data formats and downloading voluminous data. Using NASA MODIS (Terra and Aqua) and ESA MERIS (ENVISAT) aerosol data as an example, we demonstrate Giovanni usage for online multi-sensor remote sensing data comparison and analysis.

Leptoukh, Gregory↗