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Global Precipitation Measurement: Summary of the First GPM Partners Planning Workshop - Report 1

This report provides a synopsis of the proceedings of the First Global Precipitation Measurement (GPM) Partners Planning Workshop held at the University of Maryland, College Park, from May 16 to 18, 2001. GPM consists of a multi-member global satellite constellation (i.e., an international set of satellite missions) and the accompanying scientific research program, with the main goal of providing frequent, accurate, and globally distributed precipitation measurements essential in understanding several fundamental issues associated with the global water and energy cycle (GWEC). The exchange of scientific and technical information at this and subsequent GPM workshops between representatives from around the world represents a key step in the formulation phase of GPM mission development. The U.S. National Aeronautics and Space Agency (NASA), the National Space Development Agency of Japan (NASDA), and other interested agencies from nations around the world seek to observe, understand, and model the Earth system to learn how it is changing and what consequences these changes have on life, particularly as they pertain to hydrological processes and the availability of fresh water resources. GWEN processes are central to a broader understanding of the Earth system.

Shepherd, J. Marshall↗

Welcome to NASA's Earth Science Enterprise: Educational CD-ROM Activity Supplement

Since its inception in 1958, NASA has been studying the Earth and its changing environment by observing the atmosphere, oceans, land, ice, and snow, and their influence on weather and climate. We now understand that the key to gaining a better understanding of the global environment is exploring how the Earth's systems of air, land, water, and life interact with each other. This approach-called Earth Systems Science-blends together fields like meteorology, oceanography, geology, and biology. In 1991, NASA launched a more comprehensive program to study the Earth as an integrated environmental system. They call it NASA's Earth Science Enterprise. A major component of the Earth Science Enterprise is the Earth Observing System (EOS). EOS is series of satellites to be launched over the next two decades that will be used to intensively study the Earth, with the hopes of expanding our under- standing of how natural processes affect us, and how we might be affecting them. Such studies will yield improved weather forecasts, tools for managing agriculture and forests, information for fishermen and local planners, and, eventually, the ability to predict how the climate will change in the future. Today's program is laying the foundation for long-term environmental and climate monitoring and prediction. Potentially, this will provide the understanding needed in the future to support difficult decisions regarding the Earth's environment.

Source record↗

Earth Observing System: Global Observations to Study the Earth's Environment

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During the last couple of years, four EOS science missions were launched, representing observations of (1) total solar irradiance, (2) Earth radiation budget, (3) land cover & land use change, (4) ocean processes (vector wind, sea surface temperature, and ocean color), (5) atmospheric processes (aerosol and cloud properties, water vapor, and temperature and moisture profiles), and (6) tropospheric chemistry. In succeeding years many more satellites will be launched that will contribute immeasurably to our understanding of the Earth's environment. In this presentation I will describe how scientists are using NASA's Earth science data to examine land use and natural hazards, environmental air quality, including dust storms over the world's deserts, cloud and radiation properties, sea surface temperature, and winds over the ocean.

King, Michael D.↗

Earth Observing System: Global Observations to Study the Earth's Environment

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During the last couple of years, four EOS science missions were launched, representing observations of (i) total solar irradiance, (ii) Earth radiation budget, (iii) land cover & land use change, (iv) ocean processes (vector wind, sea surface temperature, and ocean color), (v) atmospheric processes (aerosol and cloud properties, water vapor, and temperature and moisture profiles), and (vi) tropospheric chemistry. In succeeding years many more satellites will be launched that will contribute immeasurably to our understanding of the Earth's environment. In this presentation I will describe how scientists are using NASA's Earth science data to examine land use and natural hazards, environmental air quality, including: dust storms over the worlds deserts, cloud and radiation properties, sea surface temperature, and winds over the ocean, with a special emphasis on satellite observations available for studying the southern African environment.

King, Michael D.↗

Understanding Sea Level Changes

Today more than 100 million people worldwide live on coastlines within one meter of mean sea level; any short-term or long-term sea level change relative to vertical ground motion is of great societal and economic concern. As palm-environment and historical data have clearly indicated the existence and prevalence of such changes in the past, new scientific information regarding to the nature and causes and a prediction capability are of utmost importance for the future. The 10-20 cm global sea-level rise recorded over the last century has been broadly attributed to two effects: (1) the steric effect (thermal expansion and salinity-density compensation of sea water) following global climate; (2) mass-budget changes due to a number of competing geophysical and hydrological processes in the Earth-atmosphere-hydrosphere-cryosphere system, including water exchange from polar ice sheets and mountain glaciers to the ocean, atmospheric water vapor and land hydrological variations, and anthropogenic effects such as water impoundment in artificial reservoirs and extraction of groundwater, all superimposed on the vertical motions of solid Earth due to tectonics, rebound of the mantle from past and present deglaciation, and other local ground motions. As remote-sensing tools, a number of space geodetic measurements of sea surface topography (e.g., TOPEX/Poseidon, Jason), ice mass (e.g., ICESat), time-variable gravity (e.g. GRACE), and ground motions (SLR, VLBI, GPS, InSAR, Laser altimetry, etc.) become directly relevant. Understanding sea level changes "anywhere, anytime" in a well-defined terrestrial reference frame in terms of climate change and interactions among ice masses, oceans, and the solid Earth, and being able to predict them, emerge as one of the scientific challenges in the Solid Earth Science Working Group (SESWG, 2003) conclusions.

Chao, Benjamin F.↗

Quality Control and Calibration of the Dual-Polarization Radar at Kwajalein, RMI

Weather radars, recording information about precipitation around the globe, will soon be significantly upgraded. Most of today s weather radars transmit and receive microwave energy with horizontal orientation only, but upgraded systems have the capability to send and receive both horizontally and vertically oriented waves. These enhanced "dual-polarimetric" (DP) radars peer into precipitation and provide information on the size, shape, phase (liquid / frozen), and concentration of the falling particles (termed hydrometeors). This information is valuable for improved rain rate estimates, and for providing data on the release and absorption of heat in the atmosphere from condensation and evaporation (phase changes). The heating profiles in the atmosphere influence global circulation, and are a vital component in studies of Earth s changing climate. However, to provide the most accurate interpretation of radar data, the radar must be properly calibrated and data must be quality controlled (cleaned) to remove non-precipitation artifacts; both of which are challenging tasks for today s weather radar. The DP capability maximizes performance of these procedures using properties of the observed precipitation. In a notable paper published in 2005, scientists from the Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) at the University of Oklahoma developed a method to calibrate radars using statistically averaged DP measurements within light rain. An additional publication by one of the same scientists at the National Severe Storms Laboratory (NSSL) in Norman, Oklahoma introduced several techniques to perform quality control of radar data using DP measurements. Following their lead, the Topical Rainfall Measuring Mission (TRMM) Satellite Validation Office at NASA s Goddard Space Flight Center has fine-tuned these methods for specific application to the weather radar at Kwajalein Island in the Republic of the Marshall Islands, approximately 2100 miles southwest of Hawaii and 1400 miles east of Guam in the tropical North Pacific Ocean. This tropical oceanic location is important because the majority of rain, and therefore the majority of atmospheric heating, occurs in the tropics where limited ground-based radar data are available.

Marks, David A.↗

Hydrologic Baseline Conditions and Projected Trends for Kennedy Space Center and the Cape Canaveral Barrier Island Complex

The purpose of this document is the creation of a comprehensive collection of data, information and knowledge on the eco-hydrologic setting, and current and predicted (2030 -2080) hydrologic conditions that will directly and indirectly influence the Kennedy Space Center (KSC) industrial and ecological system. Focus is on identification of existing data sources (web based, published, in-house) and identification of future possible needs. The document will aid in assessment of risks to the National Aeronautics and Space Administration (NASA) and stakeholder missions associated with changing local, regional and global conditions. This living document will allow for rapid updates as new data and improved spatial data (LiDAR elevations, land use, land cover, runoff coefficients, etc.) are accumulated by the Environmental Management Branch (EMB), stakeholders, and supporting staff from the NASA Environmental and Medical Contract (NEMCON) currently managed by Herndon Solutions Group LLC. (HSG).The report summarizes and visualizes hydrologic conditions supporting long-term trends monitoring, management and regulatory compliance needs, climate risk mitigation, and achievement of KSC and stakeholder’s sustainability goals. Future utility may extend to implementation actions of the KSC future development plan, KSC updates to future KSC Environmental Resource Documents (ERD), and the regional multi-agency Indian River Lagoon Health Initiative.

Carlton Hall↗

Satellite Sounder-Based OLR-, Cloud- and Atmospheric Temperature Climatologies for Climate Analyses

Global energy balance of the Earth-atmosphere system may change due to natural and man-made climate variations. For example, changes in the outgoing longwave radiation (OLR) can be regarded as a crucial indicator of climate variations. Clouds play an important role -still insufficiently assessed in the global energy balance on all spatial and temporal scales, and satellites provide an ideal platform to measure cloud and large-scale atmospheric variables simultaneously. The TOVS series of satellites were the first to provide this type of information since 1979. OLR [Mehta and Susskind], cloud cover and cloud top pressure [Susskind et al] are among the key climatic parameters computed by the TOVS Pathfinder Path-A algorithm using mainly the retrieved temperature and moisture profiles. AIRS, regarded as the new and improved TOVS , has a much higher spectral resolution and greater S/N ratio, retrieving climatic parameters with higher accuracy. First we present encouraging agreements between MODIS and AIRS cloud top pressure (C(sub tp) and effective (A(sub eff), a product of infrared emissivity at 11 microns and physical cloud cover or A(sub c)) cloud fraction seasonal and interannual variabilities for selected months. Next we present validation efforts and preliminary trend analyses of TOVS-retrieved C(sub tp) and A(sub eff). For example, decadal global trends of the TOVS Path-A and ISCCP-D2 P(sub c), and A(sub eff)/A(sub c), values are similar. Furthermore, the TOVS Path-A and ISCCP-AVHRR [available since 19831 cloud fractions correlate even more strongly, including regional trends. We also present TOVS and AIRS OLR validation effort results and (for the longer-term TOVS Pathfinder Path-A dataset) trend analyses. OLR interannual spatial variabilities from the available state-of-the-art CERES measurements and both from the AIRS [Susskind et al] and TOVS OLR computations are in remarkably good agreement. Global monthly mean CERES and TOVS OLR time series show very good agreement in absolute values also. Finally, we will assess correlations among long-term trends of selected parameters, derived simultaneously from the TOVS Pathfinder Path-A datase

Molnar, Gyula I.↗

Observations of Greenhouse Gases as Climate Indicators

Humans have significantly altered the energy balance of the Earth’s climate system mainly not only by extracting and burning fossil fuels but also by altering the biosphere and using halocarbons. The 3rd US National Climate Assessment pointed to a need for a system of indicators of climate and global change based on long-term data that could be used to support assessments and this led to the development of the National Climate Indicators System (NCIS). Here we identify a representative set of key atmospheric indicators of changes in atmospheric radiative forcing due to greenhouse gases (GHGs), and we evaluate atmospheric composition measurements, including non-CO2GHGs for use as climate change indicators in support of the US National Climate Assessment. GHG abundances and their changes over time can provide valuable information on the success of climate mitigation policies, as well as insights into possible carbon-climate feedback processes that may ultimately affect the success of those policies. To ensure that reliable information for assessing GHG emission changes can be provided on policy-relevant scales, expanded observational efforts are needed. Furthermore, the ability to detect trends resulting from changing emissions requires a commitment to supporting long-term observations. Long-term measurements of greenhouse gases, aerosols, and clouds and related climate indicators used with a dimming/brightening index could provide a foundation for quantifying forcing and its attribution and reducing error in existing indicators that do not account for complicated cloud processes.

greenhouse gases↗

Making NASA Earth Observing System Satellite Data Accessible to the K-12 and Citizen Scientist Communities

The Atmospheric Sciences Data Center (ASDC) at NASA s Langley Research Center houses over 700 data sets related to Earth s radiation budget, clouds, aerosols and tropospheric chemistry. These data sets are produced to increase academic understanding of the natural and anthropogenic perturbations that influence global climate change. The Mentoring and inquirY using NASA Data on Atmospheric and earth science for Teachers and Amateurs (MY NASA DATA) project has been established to systematically support educational activities at all levels of formal and informal education by reducing these large data holdings to microsets that will be easily explored and understood by the K-12 and the amateur scientist communities

Moore, Susan W.↗

NeMO-Net - The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. By combining spatial and spectral information from varying resolutions, we seek to augment and improve the classification accuracy of previously low-resolution datasets at large temporal scales.NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive learning and training software, currently being developed at NASA Ames, is aimed at assessing the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. The latest iteration uses fully convolutional networks to segment and identify coral imagery taken by UAVs and satellites, including WorldView-2 and Sentinel. We present results taken from the Indian Ocean where classification accuracy has exceeded 91% for 24 geomorphological classes given ample training data. In addition, we utilize deep Laplacian Pyramid Super-Resolution Networks (LapSRN) to reconstruct high resolution information from low resolution imagery, trained from various UAV and satellite datasets. Finally, in the case of insufficient training data, we have developed an interactive online platform that allows users to easily segment and submit their classifications, which has been integrated with the current NeMO-Net workflow. Specifically, we present results from the Fiji islands in which preliminary user data has allowed for the accurate identification of 9 separate classes, despite issues such as cloud shadowing and spectral variation. The project is being supported by NASA's Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Neural↗

Schools of the Pacific rainfall climate experiment

The SPaRCE program is a cooperative rainfall climate field project involving high school and college level students and teachers from various Pacific island and atoll nations. The goals of the SPaRCE program are: (1) to foster interest and increase understanding among Pacific-area students and teachers of climate and climate change; (2) to educate the students and teachers as to the importance of rainfall in the Pacific area to climate studies; (3) to provide the students and teachers an opportunity of making a major contribution to the global climate research effort by collecting and analyzing Pacific rainfall data; and (4) to incorporate collected rainfall observations into a comprehensive Pacific daily rainfall data base to be used for climate research purposes. Schools participating in SPaRCE have received standard raingauges with which to measure rainfall at their sites. Students learned to site and use their raingauges by viewing a video produced at the University of Oklahoma. Four more videos will be produced which will include information on Earth's atmosphere, global climate and climate change, regional climate and implications of climate change, and how to analyze and use the rainfall data they are collecting. The videos are accompanied by workbooks which summarize the main points of each video, and contain concrete learning activities to help the student better understand climate and climate change. Following each video, interactive sessions are held with the students using the PEACESAT (Pan-Pacific Education And Communication Experiments by Satellite) satellite radio communication system.

Postawko, S. E.↗

The Development of a Long-Term, Continually Updated Global Solar Resource at 10 km Resolution: Preliminary Results From Test Processing and Continuing Plans

Background: Considering the likelihood of global climatic weather pattern changes and the global competition for energy resources, there is an increasing need to provide improved and continuously updated global Earth surface solar resource information. Toward this end, a project was funded under the NASA Applied Science program involving the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC), National Renewable Energy Laboratory (NREL), the State University of New York/Albany (SUNY) and the NOAA National Climatic Data Center (NCDC) to provide NREL with a global long-term advanced global solar mapping production system for improved depiction of historical solar resources and variability and to provide a mechanism for continual updates of solar resource information. This new production system is made possible by the efforts of NOAA and NASA to completely reprocess the International Satellite Cloud Climatology Project (ISCCP) data set that provides satellite visible and infrared radiances together with retrieved cloud and surface properties on a 3-hourly basis beginning from July 1983. The old version of the ISCCP data provided this information for all the world TMs available geosynchronous satellite systems and NOAA TMs AVHRR data sets at a 30 km effective resolution. This new version aims to provide a new and improved satellite calibration at an effective 10 km resolution. Thus, working with SUNY, NASA will develop and test an improved production system that will enable NREL to continually update the Earth TM solar resource. Objective and Methods: In this presentation, we provide a general overview of this project together with samples of the new solar irradiance mapped data products and comparisons to surface measurements at various locations across the world. An assessment of the solar resource values relative to calibration uncertainty and assumptions are presented. Errors resulting assumptions in snow cover and background aerosol amount are described. These uncertainties and the statistics of the agreement between the measurements and new satellite estimates are also reviewed and compared to other solar data sets. Findings and Conclusions: Preliminary results show that insolation values show an overall small bias (less than 1%) with a RMS of 25% relative to surface measurements. Exceptions at certain locations were found and will be discussed relative to the uncertainties identified above. Lastly, we will identify the next steps in the development and improvement of this production system including some accuracy goals in preparation for ultimate delivery to NREL.

Stackhouse, P.↗

Global Landslide Hazard Assessment for Situational Awareness (LHASA) Version 2: New Activities and Future Plans

A remote sensing-based system has been developed to characterize the potential for rainfall-triggered landslides across the globe in near real-time. The Landslide Hazard Assessment for Situational Awareness (LHASA) model uses a decision tree framework to combine a static susceptibility map derived from information on slope, rock characteristics, forest loss, distance to fault zones and distance to road networks with satellite precipitation estimates from the Global Precipitation Measurement (GPM) mission. Since 2016, the LHASA model has been providing near real-time and retrospective estimates of potential landslide activity. Results of this work are available at https://landslides.nasa.gov. In order to advance LHASA’s capabilities to characterize landslide hazards and impacts dynamically, we have implemented a new approach that leverages machine learning, new parameters, and new inventories. LHASA 2.0 uses the XGBoost machine learning model to bring in dynamic variables as well as additional static variables to better represent landslide hazard globally. Global rainfall forecasts are also being evaluated to provide a 1-3 day forecast of potential landslide activity. Additional factors such as recent seismicity and burned areas are also being considered to represent the preconditioning or changing interactions with subsequent rainfall over affected areas. A series of parameters are being tested within this structure using NASA’s Global Landslide Catalog as well as many other event-based and multi-temporal inventories mapped by the project team or provided by project partners. In addition to estimates of landslide hazard, LHASA Version 2 will incorporate dynamic estimates of exposure including population, roads and infrastructure to highlight the potential impacts that rainfall-triggered landslides. The ultimate goal of LHASA Version 2.0 is to approximate the relative probabilities of landslide hazard and exposure across different space and time scales to inform hazard assessment retrospectively over the past 20 years, in near real-time, and in the future. In addition to the hazard. This presentation will outline the new activities for LHASA Version 2.0 and present some next steps for this system.

Dalia Kirschbaum↗

E-Theatre

Mesoscale/severe storms and results from Terra Fritz Hasler (NASA/Goddard) will show the latest spectacular animations of the hurricanes and tropical storms: Floyd, Georges, Mitch, Bonnie etc. from Geostationary Operational Environmental Satellites (GOES) and Tropical Rain Measuring Mission (TRMM) supported by MMS 3D nested numerical model results. See dust storms in Africa and smoke plumes from fires in Mexico. See how High-Definition Television (HDTV) is revolutionizing entertainment and the way we communicate scientific results. Fly in from space and take a tour of Africa. Drop in on Albuquerque using 1-m Ikonos 'Spy Satellite' technology. See data from the new Earth Observing System (EOS) Terra satellite as well as Landsat 7, and SeaWiFS. See climate change in action with Global Land and Ocean productivity changes over the last 20 years. Remote sensing observations of Sea Surface Temperature (SST), El Nino, height, winds and ocean color from GOES, National Oceanic and Atmosphere Administration Advanced Very High Resolution Radiometer (AVHRR), Special Sensor Microwave Imager (SSMI), and SeaWiFS put in context with ten year LANL global ocean model. Compare the Gulf Stream observed by Terra with the simulations. Additional information is contained in the original extended abstract.

Hasler, Arthur F.↗

Integrating Remote Sensing Observations with NASA's GEOS-5 Modeling Framework in Support of Retrospective Analyses and Seasonal Prediction of Biosphere-Atmosphere CO2 Flux

The absorption of nearly half of all anthropogenic carbon dioxide (CO2) emissions by terrestrial and marine ecosystems has played a critical role in mitigating climate change. However, a persistent lack of understanding of these uptake processes impedes attribution, and thereby introduces large uncertainties into projections of the trajectory of carbon and climate in coming decades. A better understanding and quantification of the seasonal and interannual variability of carbon flux between the atmosphere and ocean and terrestrial biospheres is critically needed to improve predictions from Earth system models. We propose to bring together a diverse suite of remote sensing observations, mechanistic models, and NASA's Goddard Earth Observing System, version 5 (GEOS-5) model to address two objective 1) quantify the processes controlling the temporal variability of biosphere-atmosphere CO2 flux on seasonal and interannual timescales from 1989 to 2018 and 2) evaluating the predictability of the components of carbon flux on seasonal timescales. Because GEOS-5 has been developed to incorporate a variety of Earth system observations and includes a complete and physically consistent depiction of the atmosphere, land, and ocean carbon cycles, it represents a unique and ideal synthesis framework for this effort. By expanding the realism of processes that could be included in GEOS-5 seasonal forecasts, this effort supports NASA's goals toward an integrated Earth system modeling and prediction framework.We propose to integrate a number of observations into the GEOS-5 modeling system to refine retrospective estimates of both terrestrial and marine carbon flux and to test hypotheses regarding the effects of climate drivers on terrestrial carbon flux. This will include assimilating several satellite ocean color products in the NASA Ocean Biogeochemistry Model (NOBM) to improve the representation of ocean biology. We will also utilize remote sensing datasets to increase the temporal resolution of global land-use change estimates and fire emissions to better constrain the temporal variability of the terrestrial carbon cycle. This information will be incorporated into two NASA terrestrial biosphere models Catchment-CN, a dynamic vegetation model that is integrated within GEOS-5 and the Ecosystem Demography (ED) model, a core modeling resource supporting the Global Ecosystem Dynamics Investigation (GEDI) mission to map biomass. Fluxes will be evaluated through 1) comparison to top-down flux estimates inferred from surface CO2 observations and 2) comparison against available aircraft and satellite observations.By combining predictions of net ecosystem exchange and air-sea CO2 flux from land and ocean models with statistical predictions of land use change, fire, and fossil fuel emissions, we propose to create the first dynamical CO2 forecast on seasonal timescales. Because of the experimental nature of this endeavor, an important project objective will be to evaluate the limits to the predictability of different carbon cycle processes over lead times of 1-12 months using different satellite and surface data streams.

Ott, Lesley↗

The Use of a Geographic Information System and Remote Sensing Technology for Monitoring Land Use and Soil Carbon Change in the Subtropical Dry Forest Life Zone of Puerto Rico

Aerial photography, one of the first form of remote sensing technology, has long been an invaluable means to monitor activities and conditions at the Earth's surface. Geographic Information Systems or GIS is the use of computers in showing and manipulating spatial data. This report will present the use of geographic information systems and remote sensing technology for monitoring land use and soil carbon change in the subtropical dry forest life zone of Puerto Rico. This research included the south of Puerto Rico that belongs to the subtropical dry forest life zone. The Guanica Commonwealth Forest Biosphere Reserve and the Jobos Bay National Estuarine Research Reserve are studied in detail, because of their location in the subtropical dry forest life zone. Aerial photography, digital multispectral imagery, soil samples, soil survey maps, field inspections, and differential global positioning system (DGPS) observations were used.

Velez-Rodriguez, Linda L.↗

Merging the MODIS and NESDIS Monthly Snow-Cover Records to Study Decade-Scale Changes in Northern Hemisphere Snow Cover

A decade-scale record of Northern Hemisphere snow cover has been available from the National Oceanic and Atmospheric Administration (NOAA) National Environmental Satellite Data and Information Service (NESDIS) and has been reconstructed and validated by Rutgers University following adjustments for inconsistencies that were discovered in the early years of the data set. This record provides weekly, monthly (and, in recent years, daily) snow cover from 1966 to the present for the Northern Hemisphere. With the December 1999 launch of NASA's Earth observing System (EOS) Terra satellite, snow maps are being produced globally, using automated algorithms, on a daily, weekly and monthly basis from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument. The resolution of the MODIS monthly snow maps (0.05deg or about 5 km) is an improvement over that of the NESDIS-derived monthly snow maps (>approx.10 km) the maps, it is necessary to study the datasets carefully to determine if it is possible to merge the datasets into a continuous record. The months in which data are available for both the NESDIS and MODIS maps (March 2000 to the present) will be compared quantitatively to analyze differences in North American and Eurasian snow cover. Results from the NESDIS monthly maps show that for North America (including all 12 months), there is a trend toward slightly less snow cover in each succeeding decade. Interannual snow-cover extent has varied significantly since 2000 as seen in both the NESDIS and MODIS maps. As the length of the satellite record increases through the MODIS era, and into the National Polar-orbiting Environmental Satellite System (NPOESS) era, it should become easier to identify trends in areal extent of snow cover, if present, that may have climatic significance. Thus it is necessary to analyze the validity of merging the NESDIS and MODIS, and, in the future, the NPOESS datasets for determination of long-term continuity in measurement of Northern Hemisphere snow cover.

Hall, Dorothy K.↗