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At least 109 records · Page 6

Monitoring Crop Yield in USA Using a Satellite-Based Climate-Variability Impact Index

A quantitative index is applied to monitor crop growth and predict agricultural yield in continental USA. The Climate-Variability Impact Index (CVII), defined as the monthly contribution to overall anomalies in growth during a given year, is derived from 1-km MODIS Leaf Area Index. The growing-season integrated CVII can provide an estimate of the fractional change in overall growth during a given year. In turn these estimates can provide fine-scale and aggregated information on yield for various crops. Trained from historical records of crop production, a statistical model is used to produce crop yield during the growing season based upon the strong positive relationship between crop yield and the CVII. By examining the model prediction as a function of time, it is possible to determine when the in-season predictive capability plateaus and which months provide the greatest predictive capacity.

Zhang, Ping↗

Assessing the Impact of Advanced Satellite Observations in the NASA GEOS-5 Forecast System Using the Adjoint Method

The adjoint of a data assimilation system provides a flexible and efficient tool for estimating observation impacts on short-range weather forecasts. The impacts of any or all observations can be estimated simultaneously based on a single execution of the adjoint system. The results can be easily aggregated according to data type, location, channel, etc., making this technique especially attractive for examining the impacts of new hyper-spectral satellite instruments and for conducting regular, even near-real time, monitoring of the entire observing system. In this talk, we present results from the adjoint-based observation impact monitoring tool in NASA's GEOS-5 global atmospheric data assimilation and forecast system. The tool has been running in various off-line configurations for some time, and is scheduled to run as a regular part of the real-time forecast suite beginning in autumn 20 I O. We focus on the impacts of the newest components of the satellite observing system, including AIRS, IASI and GPS. For AIRS and IASI, it is shown that the vast majority of the channels assimilated have systematic positive impacts (of varying magnitudes), although some channels degrade the forecast. Of the latter, most are moisture-sensitive or near-surface channels. The impact of GPS observations in the southern hemisphere is found to be a considerable overall benefit to the system. In addition, the spatial variability of observation impacts reveals coherent patterns of positive and negative impacts that may point to deficiencies in the use of certain observations over, for example, specific surface types. When performed in conjunction with selected observing system experiments (OSEs), the adjoint results reveal both redundancies and dependencies between observing system impacts as observations are added or removed from the assimilation system. Understanding these dependencies appears to pose a major challenge for optimizing the use of the current observational network and defining requirements for future observing systems.

Gelaro, Ron↗

Asteroid collisions: Target size effects and resultant velocity distributions

To study the dynamic fragmentation of rock to simulate asteroid collisions, we use a 2-D, continuum damage numerical hydrocode which models two-body impacts. This hydrocode monitors stress wave propagation and interaction within the target body, and includes a physical model for the formation and growth of cracks in rock. With this algorithm we have successfully reproduced fragment size distributions and mean ejecta speeds from laboratory impact experiments using basalt, and weak and strong mortar as target materials. Using the hydrocode, we have determined that the energy needed to fracture a body has a much stronger dependence on target size than predicted from most scaling theories. In addition, velocity distributions obtained indicate that mean ejecta speeds resulting from large-body collisions do not exceed escape velocities.

Ryan, Eileen V.↗

Possibilities of Using MARSES Instrument for Long-Term Monitoring and Subsurface Studies in Arctic and Arid Lands

The Mars Electromagnetic Sounding Experiment (MARSES) is the sounding instrument developed of searching for groundwater, water-ice or permafrost layers existing in some depth under the visible surface in the dry lands of Mars. One of the more important challenges facing natural resource managers today is how to identify, measure and monitoring the cumulative impacts of land use decisions across space and time. The secondary task is to measure the soil properties of Martian subsurface, which includes porosity, electrical resistance of the liquid phase, thermal conductivity, temperature dependence. A main task of the MARSES monitoring system is to examine changes in the subsurface properties of local areas regolith on the Martian surface on the base of the database of various soil slices in terrestrial conditions. Additional information is contained in the original extended abstract.

Ozorovich, Y. R.↗

Possibilities of Using MARSES Instrument for Long-Term Monitoring and Subsurface Studies in Arctic and Arid Lands

The MARSES is the sounding instrument developed of searching for groundwater, water-ice or permafrost layers existing in some depth under the visible surface in the dry lands of Mars. One of the more important challenges facing natural resource managers today is how to identify, measure and monitoring the cumulative impacts of land use decisions across space and time. The secondary task is to measure the soil properties of Martian subsurface, which includes porosity, electrical resistance of the liquid phase, thermal conductivity, temperature dependence. A main task of the MARSES monitoring system is to examine changes in the subsurface properties of local areas regolith on the Martian surface on the base of the database of various soil slices in terrestrial conditions

Ozorovich, Y. R.↗

Climate Extremes and Risks: Links Between Climate Science and Decision-Making

The World Climate Research Programme (WCRP) envisions a future where actionable climate information is universally accessible, supporting decision makers in preparing for and responding to climate change. In this perspective, we advocate for enhancing links between climate science and decision-making through a better and more decision-relevant understanding of climate impacts. The proposed framework comprises three pillars: climate science, impact science, and decision-making, focusing on generating seamless climate information from sub-seasonal, seasonal, decadal to century timescales informed by observed climate events and their impacts. The link between climate science and decision-making has strengthened in recent years, partly owing to undeniable impacts arising from disastrous weather extremes. Enhancing decision-relevant understanding involves utilizing lessons from past extreme events and implementing impact-based early warning systems to improve resilience. Integrated risk assessment and management require a comprehensive approach that encompasses good knowledge about possible impacts, hazard identification, monitoring, and communication of risks while acknowledging uncertainties inherent in climate predictions and projections, but not letting the uncertainty lead to decision paralysis. The importance of data accessibility, especially in the Global South, underscores the need for better coordination and resource allocation. Strategic frameworks should aim to enhance impact-related and open-access climate services around the world. Continuous improvements in predictive modeling and observational data are critical, as is ensuring that climate science remains relevant to decision makers locally and globally. Ultimately, fostering stronger collaborations and dedicated investments to process and tailor climate data will enhance societal preparedness, enabling communities to navigate the complexities of a changing climate effectively.

climate extremes↗

NEXRAD-In-Space: A Geostationary Orbiting Doppler Radar for Hurricane Monitoring and Studies

Under NASA's Earth Science Technology Program, a novel mission concept has been developed for detailed monitoring of hurricanes, cyclones, and severe storms from a geostationary orbit: "NEXRAD in Space" (NIS). By operating in the Geostationary Earth Orbit (GEO), NIS would enable rapid-update sampling (less than or equal to 1 hour cadence) of three dimenional fields of 35 GHz (Ka-band) radar reflectivity factor (Z) and line-of-sight Doppler velocity (VD) profiles, at mesoscale horizontal resolutions (approx. 10 km) over a circular Earth region of approximately 5300 km in diameter (equivalent to much of an oceanic basin, such as the Atlantic). NIS GEO-radar concept was chosen as one of only four potential post-2020 missions for the Weather Focus area in the 2007-2016 NASA Science Mission Directorate (SMD) Science Plan. The results of the first project aiming at developing the NIS concept highlighted the enormous potential of such mission, and the technological challenges presented by it. In essence, it is because of its rapid-cadence capability that NIS science planning is focusing on hurricane monitoring and prediction. Hurricanes, or generically tropical cyclones (TCs), have always been among the most devastating natural phenomena. This has been painfully reiterated in recent years with a number of powerful TCs landfalling in North America and elsewhere. In April 2007, the first NIS Science Workshop was convened at the University of Miami to galvanize the scientific community's interest in NIS's measurement capabilities for improved TC monitoring and prediction. The general consensus of the workshop was that a GEO Doppler radar would provide a major breakthrough in regards to the observation of TCs, and, when combined with cloud-resolving numerical weather prediction (NWP) models. This paper presents brief summaries of the instrument concept, the current technology status, the anticipated impacts on hurricane monitoring and model prediction, and the future science and technology roadmap.

precipitation↗

The Giotto dust impact detection system

The Giotto Dust Impact Detection System (DIDSY) consists of six independent subsystems to register the impact of all particulates of significant mass incident on the probe during the post-perihelion encounter with Comet Halley. Mounted on Giotto's front dust shield, the detectors will determine the mass spectrum of the dust, with a limiting sensitivity of 10 to the minus 17th power f, increasing to the largest grain masses encountered along Giotto's trajectory throught the cometary environment with an ultimate spatial resolution of 70 km. An additional detector is located on the rear shield to monitor dust particles that penetrate the from dust shield. An ambient plasma monitor measures the impact plasma generated by dust and gass impacts on the spacecraft.

Mcdonnell, J. A. M.↗

Assessing the Impact of Observations on Numerical Weather Forecasts Using the Adjoint Method

The adjoint of a data assimilation system provides a flexible and efficient tool for estimating observation impacts on short-range weather forecasts. The impacts of any or all observations can be estimated simultaneously based on a single execution of the adjoint system. The results can be easily aggregated according to data type, location, channel, etc., making this technique especially attractive for examining the impacts of new hyper-spectral satellite instruments and for conducting regular, even near-real time, monitoring of the entire observing system. This talk provides a general overview of the adjoint method, including the theoretical basis and practical implementation of the technique. Results are presented from the adjoint-based observation impact monitoring tool in NASA's GEOS-5 global atmospheric data assimilation and forecast system. When performed in conjunction with standard observing system experiments (OSEs), the adjoint results reveal both redundancies and dependencies between observing system impacts as observations are added or removed from the assimilation system. Understanding these dependencies may be important for optimizing the use of the current observational network and defining requirements for future observing systems

Gelaro, Ronald↗

Assimilation of GRACE Terrestrial Water Storage into a Land Surface Model: Evaluation 1 and Potential Value for Drought Monitoring in Western and Central Europe

A land surface model s ability to simulate states (e.g., soil moisture) and fluxes (e.g., runoff) is limited by uncertainties in meteorological forcing and parameter inputs as well as inadequacies in model physics. In this study, anomalies of terrestrial water storage (TWS) observed by the Gravity Recovery and Climate Experiment (GRACE) satellite mission were assimilated into the NASA Catchment land surface model in western and central Europe for a 7-year period, using a previously developed ensemble Kalman smoother. GRACE data assimilation led to improved runoff correlations with gauge data in 17 out of 18 hydrological basins, even in basins smaller than the effective resolution of GRACE. Improvements in root zone soil moisture were less conclusive, partly due to the shortness of the in situ data record. In addition to improving temporal correlations, GRACE data assimilation also reduced increasing trends in simulated monthly TWS and runoff associated with increasing rates of precipitation. GRACE assimilated root zone soil moisture and TWS fields exhibited significant changes in their dryness rankings relative to those without data assimilation, suggesting that GRACE data assimilation could have a substantial impact on drought monitoring. Signals of drought in GRACE TWS correlated well with MODIS Normalized Difference Vegetation Index (NDVI) data in most areas. Although they detected the same droughts during warm seasons, drought signatures in GRACE derived TWS exhibited greater persistence than those in NDVI throughout all seasons, in part due to limitations associated with the seasonality of vegetation.

Li, Bailing↗

Remote sensing on Indian and public lands

The use of remote sensing techniques by the Bureaus of Indian Affairs and Land Management in planning resource problems, making decisions, writing environmental impact statements, and monitoring their respective programs is investigated. For Indian affairs, data cover the Papago, Fort Apache, San Carlos, and South Dakota Reservations. For the Land Management Office, data cover cadastral surveys, California desert study, range watersheds, and efforts to establish a natural resources information system.

Torbert, G. B.↗

ERTS program of the US Army Corps of Engineers

The Army Corps of Engineers research and development efforts associated with the ERTS Program are confined to applications of investigation, design, construction, operation, and maintenance of water resource projects. Problems investigated covered: (1) resource inventory; (2) environmental impact; (3) pollution monitoring; (4) water circulation; (5) sediment transport; (6) data collection systems; (7) engineering; and (8) model verification. These problem areas were investigated in relation to bays, reservoirs, lakes, rivers, coasts, and regions. ERTS-1 imagery has been extremely valuable in developing techniques and is now being used in everyday applications.

Jarman, J. W.↗

Comparative utility of LANDSAT-1 and Skylab data for coastal wetland mapping and ecological studies

Skylab 190-A photography and LANDSAT-1 analog data have been analyzed to determine coastal wetland mapping potential as a near term substitute for aircraft data and as a long term monitoring tool. The level of detail and accuracy of each was compared. Skylab data provides more accurate classification of wetland types, better delineation of freshwater marshes and more detailed analysis of drainage patterns. LANDSAT-1 analog data is useful for general classification, boundary definition and monitoring of human impact in wetlands.

Anderson, R.↗

AVHRR for monitoring global tropical deforestation

Advanced Very High Resolution Radiometer (AVHRR) data have been used to assess the dynamics of forest trnsformations in three parts of the tropical belt. A large portion of the Amazon Basin has been systematically covered by Local Area Coverage (LAC) data in the 1985-1987 period. The analysis of the vegetation index and thermal data led to the identification and measurement of large areas of active deforestation. The Kalimantan/Borneo forest fires were monitored and their impact was evaluated using the Global Area Coverage (GAC) 4 km resolution data. Finally, High Resolution Picture Transmission (HRPT) data have provided preliminary information on current activities taking place at the boundary between the savanna and the forest in the Southern part of West Africa. The AVHRR approach is found to be a highly valuable means for carrying out deforestation assessments in regional and global perspectives.

Malingreau, J. P.↗

Atmospheric effects on NOAA AVHRR data over Sahelian regions

Variable atmospheric conditions have a significant impact on satellite monitoring of vegetation in the Sahelian zone of Africa. The effects of atmospheric O3, H2O, and aerosols on spectral, directional reflectances and derived measures, such as the normalized difference vegetation index are discussed using a sensitivity study. An atmospheric correction scheme is presented based on measurements of optical thicknesses from the ground and is applied to NOAA AVHRR data. The use of the reflectance of the ocean surface close to the terrestrial target to estimate atmospheric effects on terrestrial reflectance is also discussed.

Soufflet, V.↗

Validating Prehistoric and Current Social Phenomena Upon the Landscape of the Peten, Guatemala

The Peten, once inhabited by a population of several million before the collapse of the ancient Maya in the 10th and 11th centuries, is being repopulated toward its former demographic peak. Environmental dynamics, however, impose severe constraints to further development. Current practices in subsistence, commercial agriculture, and cattle raising are causing rapid deforestation on a scale that can only result in soil loss and regional degradation. In view of the current deforestation trends, the question emerges as to how millions of ancient Maya lived successfully in the area for centuries when relatively fewer occupants today threaten the sustainability of the landscape with current agricultural practices. The use of remote sensing technology is a cost-effective methodology for addressing issues in Maya archeology as well as monitoring the environmental impacts being experienced by the current population.

Sever, Thomas L.↗

The Ancient Maya Landscape from Space

The Peten, once inhabited by a population of several million before the collapse of the ancient Maya in the 10th and 11th centuries, is being repopulated toward its former demographic peak. Environmental dynamics, however, impose severe constraints to further development. Current practices in subsistence, commercial agriculture, and cattle raising are causing rapid deforestation resulting in the destruction of environmental and archeological resources. The use of remote sensing and Geographic Information Systems (GIS) technology is a cost-effective methodology for addressing issues in Maya archeology as well as monitoring the environmental impacts being experienced by the current population.

Sever, T.↗