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At least 235 records · Page 13

Lessons learned from replicating services for flood prediction and monitoring in Asia to the assessment of hurricane impacts in Central America

In October and November 2020, two dangerous back-to-back hurricanes, Eta and Iota, made landfall in Central America. The SERVIR program - a joint effort of NASA and the U.S. Agency for International Development, and whose motto is “connecting space to village” was able to leverage two tools originally developed for use in other regions for predicting and assessing the flood impacts of the hurricanes. The GEOGLoWS Streamflow Prediction tool - originally implemented in the Hindu Kush Himalayan region - was used for predicting potential flooding ahead of landfall by Eta and Iota. In conjunction, the Hydrologic Remote Sensing Analysis for Floods (HYDRAFloods) framework - originally developed along with SERVIR-Mekong - was used for post-event flood mapping, leveraging its ability to map floods in cloud-covered areas using synthetic aperture radar (SAR) imagery from the Copernicus program. Both tools were used in support of disaster coordination efforts being led by the Central American Regional Disaster Prevention Center (CEPREDENAC), in conjunction with its sister agency, the Regional Water Resources Committee (CRRH). The support provided to regional entities - and to their stakeholder national governments - served as an example of rapid generation of Earth observation products for disaster response. Feedback on those products was also provided, especially in terms of the implications of (i) calibration of predicted river volumes, and (ii) the latency of the input Earth observation imagery and attempts to map the floods’ maximum extents. An upcoming NASA DEVELOP project will also seek to strengthen the capability of CEPREDENAC and CRRH to apply HYDRAFloods for future extreme events. The application of the tools also provides a useful case study on capacity building, in terms of how Earth observation data and models can be replicated across regions.

Capacity building↗

A detailed model for simulation of catchment scale subsurface hydrologic processes

A catchment scale numerical model is developed based on the three-dimensional transient Richards equation describing fluid flow in variably saturated porous media. The model is designed to take advantage of digital elevation data bases and of information extracted from these data bases by topographic analysis. The practical application of the model is demonstrated in simulations of a small subcatchment of the Konza Prairie reserve near Manhattan, Kansas. In a preliminary investigation of computational issues related to model resolution, we obtain satisfactory numerical results using large aspect ratios, suggesting that horizontal grid dimensions may not be unreasonably constrained by the typically much smaller vertical length scale of a catchment and by vertical discretization requirements. Additional tests are needed to examine the effects of numerical constraints and parameter heterogeneity in determining acceptable grid aspect ratios. In other simulations we attempt to match the observed streamflow response of the catchment, and we point out the small contribution of the streamflow component to the overall water balance of the catchment.

Paniconi, Claudio↗

Stream network analysis and geomorphic flood plain mapping from orbital and suborbital remote sensing imagery application to flood hazard studies in central Texas

The author has identified the following significant results. Development of a quantitative hydrogeomorphic approach to flood hazard evaluation was hindered by (1) problems of resolution and definition of the morphometric parameters which have hydrologic significance, and (2) mechanical difficulties in creating the necessary volume of data for meaningful analysis. Measures of network resolution such as drainage density and basin Shreve magnitude indicated that large scale topographic maps offered greater resolution than small scale suborbital imagery and orbital imagery. The disparity in network resolution capabilities between orbital and suborbital imagery formats depends on factors such as rock type, vegetation, and land use. The problem of morphometric data analysis was approached by developing a computer-assisted method for network analysis. The system allows rapid identification of network properties which can then be related to measures of flood response.

Baker, V. R.↗

Interaction of the Climate System and the Solid Earth: Analysis of Observations and Models

Under SENH funding we have carried out a number of diverse analyses of interactions of the climate system (atmosphere, ocean, land surface hydrology) with the solid Earth. While the original work plan emphasized analysis of excitation of variations in Earth rotation, with a lesser emphasis on time variable gravity, opportunities that developed during the proposal period in connection with preparations for the GRACE mission led us to a more balanced effort between these two topics. The results of our research are outlined in several topical sections: (1) oceanic excitation of variations in Earth rotation; (2) short period atmosphere-ocean excitation of variations in Earth rotation; (3) analysis of coupled climate system simulation; (4) observing system simulation studies for GRACE mission design; and (5) oceanic response to atmospheric pressure loading.

Bryan, Frank↗

Montana Water Resources: Developing a Composite Moisture Index Utilizing NASA Earth Observations for Drought Monitoring in the Missouri River Basin

The Missouri River Basin provides irrigation water for a substantial part of the domestic agricultural sector within the United States. Drought events pose a significant threat to the economic livelihoods of dependent individuals, industries, and ecosystems (e.g. farmers, local tribes, hydroelectric power, wildlife). In 2017 alone, the Missouri River Basin experienced a severe drought that resulted in a $2.6 billion loss to the U.S. Northern Plains. In response to such events, organizations throughout the basin, such as the Montana Climate Office, have dedicated efforts for drought monitoring and communicating relevant information to local stakeholders. In an effort to aid regional decision-making capabilities, the project team partnered with the Montana Climate Office, NOAA National Weather Service (NWS) Missouri Basin River Forecast Center, and NOAA Regional Climate Services, Central Region to create a monthly Composite Moisture Index (CMI) that relies on NASA Earth observations from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the Soil Moisture Active Passive (SMAP) mission. From these satellites, as well as the NOAA NWS National Operational Hydrologic Remote Sensing Center’s Snow Data Assimilation System (SNODAS), our team aggregated climate datasets including soil moisture, snow cover, snow depth, and snow water equivalent to compute a CMI that indicates regional moisture conditions during the winter months. The March CMI values produced over the Missouri River headwater subbasin strongly correlate (r = 0.75) with spring and early summer stream discharge, demonstrating the use of this metric to indicate moisture conditions for the snowmelt and growing seasons.

DEVELOP Project Summary↗

Montana Water Resources: Developing a Composite Moisture Index Utilizing NASA Earth Observations for Drought Monitoring in Montana and the Missouri River Basin

The Missouri River Basin provides irrigation water for a substantial part of the domestic agricultural sector within the United States. Drought events pose a significant threat to economic livelihoods of dependent individuals, industries, and ecosystems (e.g., farmers, local tribes, hydroelectric power, wildlife). In 2017 alone, the Missouri River Basin experienced a severe drought that resulted in a $2.6 billion loss to the U.S. Northern Plains. In response to such events, organizations throughout the basin, such as the Montana Climate Office, have dedicated efforts for drought monitoring and communicating relevant information to local stakeholders. In an effort to aid regional decision-making capabilities, the project team partnered with the Montana Climate Office, NOAA National Weather Service (NWS) Missouri Basin River Forecast Center, and NOAA Regional Climate Services, Central Region to create a monthly Composite Moisture Index (CMI) that relies on NASA Earth observations from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the Soil Moisture Active Passive (SMAP) mission. From these satellites, as well as the NOAA NWS National Operational Hydrologic Remote Sensing Center Snow Data Assimilation System (SNODAS), our team aggregated climate datasets including soil moisture, snow cover, snow depth, and snow water equivalent to compute a CMI that indicates regional moisture conditions during the winter months. The March CMI values produced over the Missouri River headwater subbasin strongly correlate (r = 0.75) with spring and early summer stream discharge, demonstrating the use of this metric to indicate moisture conditions for the snowmelt and growing seasons.

DEVELOP Tech Paper↗

PRELIMINARY MODEL FOR SOIL MOISTURE RETRIEVAL USING P-BAND RADIOMETER OBSERVATIONS

Soil Moisture is an important geophysical variable that needs reliable quantification for applications in hydrology, meteorology and agriculture. L-band radiometry has proved to be one of the best methods in soil moisture estimation using microwave signals. However, they provide measurements that correspond to a shallow depth of 5 cm and are also affected by the presence of overlaying vegetation and roughness. In contrast, P-band radiometry is expected to provide moisture information on a deeper layer of soil. Moreover, these lower frequency measurements are expected to be less affected by soil roughness and vegetation contributions. Consequently, this pilot study uses the Polarimetric P-band Multi beam Radiometer(PPMR) at 740 MHz to evaluate the response of theP-band radiometer over a realistic range of surface condition sat the field scale. A preliminary framework of P-band MicrowaveEmission of theBiosphere (P-MEB) has been developed as a forward model that simulates brightness temperature from soil moisture and other ancillary data collected from the field. This paper presents the model for the bare soil condition observed during June 2018 to August 2018. The results show that H-polarized PPMR data has better correlation to the soil moisture over a depth of 10 cm than the V-polarized PPMR data. A model is under improvement by incorporating a more suitable effective temperature formulation.

Edward J Kim↗

The GEWEX Process Evaluation Study: GEWEX-PROES

Progress in realistically simulating the energy and water cycles in weather and climate models has been slower than desirable. Climate models submitted to the Coupled Model Intercomparison Project Phase-5 (CMIP-5), while more comprehensive than their predecessors, have shown little to no improvement in their biases in simulating key features of the climate system. As a result, uncertainties in global climate and hydrological sensitivities, and in the simulation of regional climate change, have not been reduced significantly. It is time to make use of these opportunities to significantly advance our understanding of key energy and water cycle processes at a wide range of space and time scales, and to provide a more insightful evaluation of the representation of these processes within models. This will require new ways of both analyzing the observations and diagnosing model behavior. The keys to success will be in skillfully combining different data sets and exploring relationships between them, as well as in the ability of models to reproduce those relationships correctly. In response to this challenge, a new GEWEX-wide activity, the GEWEX Process Evaluation Study, will take advantage of the opportunities that the combination of many of the existing data sets provide.

climate models↗

Ice Sheet Melt Water Profile Mapping Using Multi-frequency Microwave Radiometry

For understanding englacial hydrology and its impact on ice sheet mass balance, observations of the liquid water content (LWC) within the ice sheets are needed. Earlier studies have shown the complementary nature of multi-frequency microwave radiometer measurements to detect subsurface LWC distribution in addition to surface LWC, which is critical for understanding the seasonal melt dynamics of ice sheets. In this study, we used 1.4 GHz brightness temperature (TB) measurements from the NASA Soil Moisture Active Passive (SMAP) satellite, and 6.9, 10.7, 18.9, and 36.5 GHz TB measurements from the JAXA Global Change Observation Mission-Water Shizuku (GCOM-W) satellite to investigate the multi-frequency response at pan-Greenland scale. The melt indications derived at different frequencies show trends consistent with persistent seasonal subsurface melt water and delayed subsurface refreezing of the seasonal melt water. The result suggests that the seasonal subsurface persistent melt water occurrences that are not captured by the high-frequency retrievals are both temporally and spatially very significant.

Burgin, Mariko↗

Extratropical Influence of Sea Surface Temperature and Wind on Water Recycling Rate Over Oceans and Coastal Lands

Water vapor and precipitation are two important parameters confining the hydrological cycle in the atmosphere and over the ocean surface. In the extratropical areas, due to variations of midlatitude storm tracks and subtropical jetstreams, water vapor and precipitation have large variability. Recently, a concept of water recycling rate defined previously by Chahine et al. (GEWEX NEWS, August, 1997) has drawn increasing attention. The recycling rate of moisture is calculated as the ratio of precipitation to total precipitable water (its inverse is the water residence time). In this paper, using multi-sensor spacebased measurements we will study the role of sea surface temperature and ocean surface wind in determining the water recycling rate over oceans and coastal lands. Response of water recycling rate in midlatitudes to the El Nino event will also be discussed. Sea surface temperature data are derived from satellite observations from the Advanced Very High Resolution Radiometer (AVHRR) blended with in situ measurements, available for the period 1982-1998. Global sea surface wind observations are obtained from spaceborne scatterometers aboard on the European Remote-Sensing Satellite (ERS1 and 2), available for the period 1991-1998. Global total precipitable water provided by the NASA Water Vapor Project (NVAP) is available for the period 1988-1995. Global monthly mean precipitation provided by the Global Precipitation Climatology Project (GPCP) is available for the period 1987-1998.

Hu, Hua↗

Assessing the Needs of NASA's Near Real-Time Earth Observation Products

"The 2017-2027 Decadal Survey for Earth Science and Applications from Space stated that NASA's Earth Science with planned implementation of applications provides sustained earth observations for societal benefits [1]. The Decadal Survey indicated that data latency is invaluable for time-sensitive applications including disaster risk reduction, wildland fire carbon emissions quantification, real-time measurements of the state of the hydrologic systems and many more. Data latency refers to the time between earth observation and data products available to users. During the past 13 years, NASA's Land, Atmosphere Near Real-Time Capability for Earth Observing Systems (LANCE) continues to provide free access to earth observation products that are made available much quicker than routine processing allows. The latency of most LANCE data products is Near Real-time (NRT) which is defined as less than three hours from satellite observations [2]. LANCE is managed by the Earth Science Data and Information System (ESDIS) Project at NASA Goddard Space Flight Center [3], and a User Working Group (UWG) is responsible for providing guidance to LANCE. LANCE data are used by direct users and brokers who add value to the data [4]. NASA Earth Applied Sciences Program (ASP) is one of the primary users of LANCE, which collaborates with partner organizations and provides support to scientists to solve problems in applications of earth observations. ASP promotes the use of LANCE NRT data products to demonstrate applications in decision making, facilitates end-user feedback to the science team to improve data products, and provides information on future demands for research. LANCE supports applications that need a rapid response including detecting wildland fires and volcanic eruptions, tracking smoke, ash and dust plumes, monitoring air quality and tracking extreme weather events such as hurricanes, landslides, and floods. To gather feedback regarding the availability, accessibility and actionability of NASA's NRT data products for societal benefit, three surveys and a few discussions with experts involved in the topic within ASP were conducted from the perspective of users. Feedback has been collected from users who are interested in using low latency NASA data within application communities of agriculture, disasters, water resources, health and air quality, ecological conservation, wildland fires and capacity building. Analysis-ready NRT data products in a variety of formats have been mentioned many times in the collected feedback, especially for applied users with little to no experience using research-grade earth observation products. Users prefer to have products that can be easily integrated into their existing workflows and take their analysis to the data. HDF5 is a commonly used data format for research, but typically requires some conversion to a more friendly format for applications and regular use in decision-making. Users prefer the GeoTIFF data format that can be directly ingested into a GIS mapping software and platform for data analysis and visualization. For example, LANCE’s fire, flood, SO2 and Black Marble Nighttime Blue/Yellow Composite data products have been integrated into NASA Disasters Mapping Portal, which is an GIS-based open data portal, for users in the disaster management community. There are 291 LANCE NRT layers available through GIBS and Worldview, where users can download a snapshot in GeoTIFF format. Operational users expect data to be processed as close to the user as possible. The collected feedback indicates that LANCE fire products within 3 hours latency would meet the needs of the wildland fire community. The ideal latency for volcanic application is 10-15 minutes. Users in Volcanic Ash Advisory Centers (VAAC) reported that the first forecast volcanic product should be issued within 75 minutes from the volcano eruption [5]. Overall, for disaster applications, data latency within 3 hours is useful while latency greater than 12 hours is not timely enough for operational use. Capacity building and training are critical for users to be able to access, interpret and use data products and tools for their decision making, especially for applied users with limited experience using earth observation products. LANCE data products have been used in a number of capacity building projects domestically and internationally [6]. As LANCE continues to bring new products into the system, users request training to utilize LANCE new and upcoming data products and capabilities in their applications. Due to the limitation of bandwidth and downstream flow paths, users in some developing countries need tools to select and download data for a specific area of interest instead of bulk downloads. The collected feedback also shows the lack of available SAR satellite low latency data products. The advantages of SAR to monitor conditions and changes on the ground through darkness, clouds, volcanic ash, and other atmospheric conditions, are appealing to low latency users. For example, terabytes of low latency but cloudy optical images are not helpful in rapidly identifying the extent of flood or fire impacts. LANCE could be complemented with low latency measurements via the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR) mission [7]. Requests for higher spatial resolution products are expressed. A user from the wildland fire management community reported that products with 30-m spatial resolution could be used to detect small fires. The 30-m Landsat OLI fire data is now part of NASA’s Fire Information for Resource Management System (FIRMS) US/Canada [8]. Within the open and free NASA resources, LANCE disseminates NRT data products in a manner that allows them to be accessible and understandable to both scientific and applied users. In many application areas, latency plays an important or even decisive role where low latency earth observations help people to observe areas of interest, detect and track changes in the environment and make timely decisions. NASA’s Earth Applied Sciences Program promotes the use of LANCE NRT products and builds a bridge between application users and research teams. The collected feedback indicates data latency within 3 hours is useful for most of the applications, and shows the needs of user-friendly, analysis-ready products, and requests training on LANCE’s new and upcoming data products. User feedback has been provided to LANCE UWG for guidance and recommendations, and for translating findings into something actionable.

Tian Yao↗

Simulation of High-Latitude Hydrological Processes in the Torne-Kalix Basin: PILPS Phase 2(e): Equivalent Model Representation and Sensitivity Experiments - 3

The Project for Intercomparison of Land Surface Parameterization Schemes (PILPS) Phase 2(e) showed that in cold regions the annual runoff production in Land Surface Schemes (LSSs) is closely related to the maximum snow accumulation, which in turn is controlled in large part by winter sublimation. To help further explain the relationship between snow cover, turbulent exchanges and runoff production, a simple equivalent model-(SEM) was devised to reproduce the seasonal and annual fluxes simulated by 13 LSSs that participated in PILPS Phase 2(e). The design of the SEM relates the annual partitioning of precipitation and energy in the LSSs to three primary parameters: snow albedo, effective aerodynamic resistance and evaporation efficiency. Isolation of each of the parameters showed that the annual runoff production was most sensitive to the aerodynamic resistance. The SEM was somewhat successful in reproducing the observed LSS response to a decrease in shortwave radiation and changes in wind speed forcings. SEM parameters derived from the reduced shortwave forcings suggested that increased winter stability suppressed turbulent heat fluxes over snow. Because winter sensible heat fluxes were largely negative, reductions in winter shortwave radiation imply an increase in annual average sensible heat.

Bowling, Laura C.↗

Central America Disasters: Using Earth Observations to Map Flooding for Disaster Monitoring, Inform Potential Risk, and Prepare for Possible Response

In November 2020, Hurricanes Eta and Iota hit Central America within weeks of each other, causing severe flooding, landslides, and widespread damage. NASA DEVELOP partnered with Comité Regional de Recursos Hidráulicos (CRRH), Centro de Coordinación para la Prevención de los Desastres en América Central y República Dominicana (CEPREDENAC), and Sistema de la Integración Centroamericana (SICA) to better understand how flooding throughout Central America has impacted and will continue to affect communities, focusing on sites in Guatemala, Honduras, El Salvador, Belize, Nicaragua, western Panama, and eastern Costa Rica from January 2015 to October 2021. The team utilized surface reflectance data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Sentinel-2 MultiSpectral Instrument (MSI), Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Terra Moderate Resolution Imaging Spectroradiometer (MODIS). This project also utilized backscatter data from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR) and elevation data from the Shuttle Radar Topography Mission (SRTM). Incorporating these Earth observations in NASA SERVIR’s Hydrologic Remote Sensing Analysis for Floods (HYDRAFloods) tool run on Google Earth Engine (GEE), the team produced historical surface water maps, a case study analysis of the two hurricanes, and a code tutorial. These results indicated that surface water increased in priority sites from 2015 to 2021, optical and SAR imagery detected similar flood patterns and extent after the hurricanes, and rainfall was concentrated on the east coast of the region. These products allow partners to make informed decisions around flooding preparation and disaster mitigation.

Caroline Williams↗

Global Precipitation Measurement, Validation, and Applications Integrated Hydrologic Validation to Improve Physical Precipitation Retrievals for GPM

Land surface modeling and data assimilation can provide dynamic land surface state variables necessary to support physical precipitation retrieval algorithms over land. It is well-known that surface emission, particularly over the range of frequencies to be included in the Global Precipitation Measurement Mission (GPM), is sensitive to land surface states, including soil properties, vegetation type and greenness, soil moisture, surface temperature, and snow cover, density, and grain size. In order to investigate the robustness of both the land surface model states and the microwave emissivity and forward radiative transfer models, we have undertaken a multi-site investigation as part of the NASA Precipitation Measurement Missions (PMM) Land Surface Characterization Working Group. Specifically, we will demonstrate the performance of the Land Information System (LIS; http://lis.gsfc.nasa.gov; Peters-Lidard et aI., 2007; Kumar et al., 2006) coupled to the Joint Center for Satellite Data Assimilation (JCSDA's) Community Radiative Transfer Model (CRTM; Weng, 2007; van Deist, 2009). The land surface is characterized by complex physical/chemical constituents and creates temporally and spatially heterogeneous surface properties in response to microwave radiation scattering. The uncertainties in surface microwave emission (both surface radiative temperature and emissivity) and very low polarization ratio are linked to difficulties in rainfall detection using low-frequency passive microwave sensors (e.g.,Kummerow et al. 2001). Therefore, addressing these issues is of utmost importance for the GPM mission. There are many approaches to parameterizing land surface emission and radiative transfer, some of which have been customized for snow (e.g., the Helsinki University of Technology or HUT radiative transfer model;) and soil moisture (e.g., the Land Surface Microwave Emission Model or LSMEM).

Peters-Lidar, Christa D.↗

Causes of Long-Term Drought in the United States Great Plains

The United States Great Plains (USGP) experienced a number of multi-year droughts during the last century, most notably the droughts of the 1930s and 1950s. This study examines the causes of such droughts using ensembles of long term (1930-1999) simulations carried out with the NASA Seasonal-to-Interannual Prediction Project (NSIPP-1) atmospheric general circulation model (AGCM) forced with observed sea surface temperatures (SSTs). The results show that the model produces long-term (multi-year) variations in the USGP precipitation that are similar to those observed. A correlative analysis suggests that the ensemble mean low frequency (time scales longer than about 6 years) rainfall variations in the USGP are linked to a pan-Pacific pattern of SST variability that is the leading empirical orthogonal function (EOF) in the low frequency SST data. The link between the SST and the Great Plains precipitation is confirmed in idealized AGCM simulations, in which the model is forced by the 2 polarities of the pan-Pacific SST pattern. The idealized simulations further show that it is primarily the tropical part of the SST anomalies that influence the USGP. As such, the USGP tend to have above normal precipitation when the tropical Pacific SSTs are above normal, while there is a tendency for drought when the tropical SSTs are cold. The upper tropospheric response to the pan-Pacific SST EOF shows a global-scale pattern with a strong wave response in the Pacific and a substantial zonally-symmetric component in which USGP pluvial (drought) conditions are associated with reduced (enhanced) heights throughout the extra-tropics. The potential predictability of rainfall in the USGP associated with SSTs is rather modest, with on average about 1/3 of the total low frequency rainfall variance forced by SST anomalies. Further idealized experiments with climatological SST, suggest that the remaining low frequency variance in the USGP precipitation is the result of interactions with soil moisture. In particular, simulations with soil moisture feedback show a six-fold increase in the variance in annual USGP precipitation compared with simulations in which the soil feedback is excluded. In addition to increasing variance, the interactions with the soil introduce year-to-year memory in the hydrological cycle that is consistent with a red noise process, in which the low frequencies in the deep soil are the result of integrating a net forcing (precipitation-evaporation-runoff) that is white noise on interannual time scales. As such, the role of low frequency SST variability is to introduce a bias to the net forcing on the soil moisture that drives the random process preferentially to either wet or dry conditions.

Schubert, Siegfried D.↗

Application of Spaceborne Scatterometer for Mapping Freeze-Thaw State in Northern Landscapes as a Measure of Ecological and Hydrological Processes

Landscape freeze/thaw transitions coincide with marked shifts in albedo, surface energy and mass exchange, and associated snow dynamics. Monitoring landscape freeze/thaw dynamics would improve our ability to quantify the interannual variability of boreal hydrology and river runoff/flood dynamics. The annual duration of frost-free period also bounds the period of photosynthetic activity in boreal and arctic regions thus affecting the annual carbon budget and the interannual variability of regional carbon fluxes. In this study, we use the NASA scatterometer (NSCAT) to monitor the temporal change in the radar backscatter signature across selected ecoregions of the boreal zone. We have measured vegetation tissue temperatures, soil temperature profiles, and micrometeorological parameters in situ at selected sites along a north-south transect extending across Alaska from Prudhoe Bay to the Kenai Peninsula and in Siberia near the Yenisey River. Data from these stations have been used to quantify the scatterometer's sensitivity to freeze/thaw state under a variety of terrain and landcover conditions. Analysis of the NSCAT temporal response over the 1997 spring thaw cycle shows a 3 to 5 dB change in measured backscatter that is well correlated with the landscape springtime thaw process. Having verified the instrument's capability to monitor freeze/thaw transitions, regional scale mosaicked data are applied to derive temporal series of freeze/thaw transition maps for selected circumpolar high latitude regions. These maps are applied to derive areal extent of frozen and thawed landscape and demonstrate the utility of spaceborne radar for operational monitoring of seasonal freeze-thaw dynamics and associated biophysical processes for the circumpolar high latitudes.

McDonald, Kyle↗

Premonsoon Aerosol Characterization and Radiative Effects Over the Indo-Gangetic Plains: Implications for Regional Climate Warming

The Himalayas have a profound effect on the South Asian climate and the regional hydrological cycle, as it forms a barrier for the strong monsoon winds and serves as an elevated heat source, thus controlling the onset and distribution of precipitation during the Indian summer monsoon. Recent studies have suggested that radiative heating by absorbing aerosols, such as dust and black carbon over the Indo-Gangetic Plains (IGP) and slopes of the Himalayas, may significantly accelerate the seasonal warming of the Hindu Kush-Himalayas-Tibetan Plateau (HKHT) and influence the subsequent evolution of the summer monsoon. This paper presents a detailed characterization of aerosols over the IGP and their radiative effects during the premonsoon season (April-May-June) when dust transport constitutes the bulk of the regional aerosol loading, using ground radiometric and spaceborne observations. During the dust-laden period, there is a strong response of surface shortwave flux to aerosol absorption indicated by the diurnally averaged forcing efficiency of -70 W/sq m per unit optical depth. The simulated aerosol single-scattering albedo, constrained by surface flux and aerosol measurements, is estimated to be 0.89+/- 0.01 (at approx.550 nm) with diurnal mean surface and top-of-atmosphere forcing values ranging from -11 to -79.8 W/sq m and +1.4 to +12 W/sq m, respectively, for the premonsoon period. The model-simulated solar heating rate profile peaks in the lower troposphere with enhanced heating penetrating into the middle troposphere (5-6 km), caused by vertically extended aerosols over the IGP with peak altitude of approx.5 km as indicated by spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization observations. On a long-term climate scale, our analysis, on the basis of microwave satellite measurements of tropospheric temperatures from 1979 to 2007, indicates accelerated annual mean warming rates found over the Himalayan-Hindu Kush region (0.21 C/decade+/-0.08 C/decade) and underscores the potential role of enhanced aerosol solar absorption in the maximum warming localized over the western Himalayas (0.26 C/decade f 0.09 C/decade) that significantly exceed the entire HKHT and global warming rates. We believe the accelerated warming rates reported here are critical to both the South Asian summer monsoon and hydro-glaciological resource variability in the Himalayan-Hindu Kush snowpack and therefore to the densely populated downstream regions.

Gautam, Ritesh↗

Information Systems Coordinate Emergency Management

The rescue crews have been searching for the woman for nearly a week. Hurricane Katrina devastated Hancock County, the southernmost point in Mississippi, and the woman had stayed through the storm in her beach house. There is little hope of finding her alive; the search teams know she is gone because the house is gone. Late at night in the art classroom of the school that is serving as the county s emergency operations center, Craig Harvey is discussing the search with the center s commander. Harvey is the Chief Operating Officer of a unique company called NVision Solutions Inc., based at NASA s Stennis Space Center in Bay St. Louis, only a couple of miles away. He and his entire staff have set up a volunteer operation in the art room, supporting the emergency management efforts using technology and capabilities the company developed through its NASA partnerships. As he talks to the commander, Harvey feels an idea taking shape that might lead them to the woman s location. Working with surface elevation data and hydrological principles, Harvey creates a map showing how the floodwaters from the storm would have flowed along the topography of the region around the woman s former home. Using the map, search crews find the woman s body in 15 minutes. Recovering individuals who have been lost is a sad reality of emergency management in the wake of a disaster like Hurricane Katrina in 2005. But the sooner answers can be provided, the sooner a community s overall recovery can take place. When damage is extensive, resources are scattered, and people are in dire need of food, shelter, and medical assistance, the speed and efficiency of emergency operations can be the key to limiting the impact of a disaster and speeding the process of recovery. And a key to quick and effective emergency planning and response is geographic information. With a host of Earth-observing satellites orbiting the globe at all times, NASA generates an unmatched wealth of data about our ever-changing planet. This information can be captured, analyzed, and visualized by geographic information systems (GIS) to produce maps, charts, and other tools that can reveal information essential to a wide variety of applications including emergency management. Knowing precise, real-time information about the size, location, environmental conditions, and resulting damage of an event like a flood or wildfire as well as the location and numbers of emergency responders and other resources contributes directly to the effectiveness of disaster mitigation. The need for such information is also evident when responding to homeland security threats, such as a terrorist attack. Recognizing the value of its geospatial information resources for this and other purposes, in 1998 Stennis and the state of Mississippi partnered to form what became the Enterprise for Innovative Geospatial Solutions (EIGS) industry cluster, supporting the growth of remote sensing and GIS-based research and business. As part of EIGS, several companies partnered with NASA through dual use and Small Business Innovation Research (SBIR) contracts. Among those was NVision.

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