Landing Site Dispersion Analysis and Statistical Assessment for the Mars Phoenix Lander

NASA Technical Reports Server (NTRS)

Bonfiglio, Eugene P.; Adams, Douglas; Craig, Lynn; Spencer, David A.; Strauss, William; Seelos, Frank P.; Seelos, Kimberly D.; Arvidson, Ray; Heet, Tabatha

2008-01-01

The Mars Phoenix Lander launched on August 4, 2007 and successfully landed on Mars 10 months later on May 25, 2008. Landing ellipse predicts and hazard maps were key in selecting safe surface targets for Phoenix. Hazard maps were based on terrain slopes, geomorphology maps and automated rock counts of MRO's High Resolution Imaging Science Experiment (HiRISE) images. The expected landing dispersion which led to the selection of Phoenix's surface target is discussed as well as the actual landing dispersion predicts determined during operations in the weeks, days, and hours before landing. A statistical assessment of these dispersions is performed, comparing the actual landing-safety probabilities to criteria levied by the project. Also discussed are applications for this statistical analysis which were used by the Phoenix project. These include using the statistical analysis used to verify the effectiveness of a pre-planned maneuver menu and calculating the probability of future maneuvers.

Hydrologic Futures: Using Scenario Analysis to Evaluate Impacts of Forecasted Land Use Change on Hydrologic Services

EPA Science Inventory

Land cover and land use changes can substantially alter hydrologic ecosystem services. Water availability and quality can change with modifications to the type or amount of surface vegetation, the permeability of soil and other surfaces, and the introduction of contaminants throu...

Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Koster, Randal D.; deLannoy, Gabrielle J. M.; Forman, Barton A.; Liu, Qing; Mahanama, Sarith P. P.; Toure, Ally

2012-01-01

The Modern-Era Retrospective analysis for Research and Applications (MERRA) is a state-ofthe-art reanalysis that provides, in addition to atmospheric fields, global estimates of soil moisture, latent heat flux, snow, and runoff for 1979-present. This study introduces a supplemental and improved set of land surface hydrological fields ("MERRA-Land") generated by re-running a revised version of the land component of the MERRA system. Specifically, the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameter values in the rainfall interception model, changes that effectively correct for known limitations in the MERRA surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ERA-Interim (ERA-I) reanalysis. MERRA-Land and ERA-I root zone soil moisture skills (against in situ observations at 85 US stations) are comparable and significantly greater than that of MERRA. Throughout the northern hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 18 US basins) of MERRA and MERRA-Land is typically higher than that of ERA-I. With a few exceptions, the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using MERRA output for land surface hydrological studies.

Land surface Verification Toolkit (LVT)

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.

2017-01-01

LVT is a framework developed to provide an automated, consolidated environment for systematic land surface model evaluation Includes support for a range of in-situ, remote-sensing and other model and reanalysis products. Supports the analysis of outputs from various LIS subsystems, including LIS-DA, LIS-OPT, LIS-UE. Note: The Land Information System Verification Toolkit (LVT) is a NASA software tool designed to enable the evaluation, analysis and comparison of outputs generated by the Land Information System (LIS). The LVT software is released under the terms and conditions of the NASA Open Source Agreement (NOSA) Version 1.1 or later. Land Information System Verification Toolkit (LVT) NOSA.

Exploring Remote Sensing Products Online with Giovanni for Studying Urbanization

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina; Kempler, Steve

2012-01-01

Recently, a Large amount of MODIS land products at multi-spatial resolutions have been integrated into the online system, Giovanni, to support studies on land cover and land use changes focused on Northern Eurasia and Monsoon Asia regions. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES-DISC) providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data. The customized Giovanni Web portals (Giovanni-NEESPI and Giovanni-MAIRS) are created to integrate land, atmospheric, cryospheric, and social products, that enable researchers to do quick exploration and basic analyses of land surface changes and their relationships to climate at global and regional scales. This presentation documents MODIS land surface products in Giovanni system. As examples, images and statistical analysis results on land surface and local climate changes associated with urbanization over Yangtze River Delta region, China, using data in Giovanni are shown.

Enhancing Global Land Surface Hydrology Estimates from the NASA MERRA Reanalysis Using Precipitation Observations and Model Parameter Adjustments

NASA Technical Reports Server (NTRS)

Reichle, Rolf; Koster, Randal; DeLannoy, Gabrielle; Forman, Barton; Liu, Qing; Mahanama, Sarith; Toure, Ally

2011-01-01

The Modern-Era Retrospective analysis for Research and Applications (MERRA) is a state-of-the-art reanalysis that provides. in addition to atmospheric fields. global estimates of soil moisture, latent heat flux. snow. and runoff for J 979-present. This study introduces a supplemental and improved set of land surface hydrological fields ('MERRA-Land') generated by replaying a revised version of the land component of the MERRA system. Specifically. the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameters in the rainfall interception model, changes that effectively correct for known limitations in the MERRA land surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ERA-Interim reanalysis. MERRA-Land and ERA-Interim root zone soil moisture skills (against in situ observations at 85 US stations) are comparable and significantly greater than that of MERRA. Throughout the northern hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 15 basins in the western US) of MERRA and MERRA-Land is typically higher than that of ERA-Interim. With a few exceptions. the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using '\\-tERRA output for land surface hydrological studies.

The influence of the fault zone width on land surface vibrations after the high-energy tremor in the "Rydułtowy-Anna" hard coal mine

NASA Astrophysics Data System (ADS)

Pilecka, Elżbieta; Szwarkowski, Dariusz

2018-04-01

In the article, a numerical analysis of the impact of the width of the fault zone on land surface tremors on the area of the "Rydułtowy - Anna" hard coal mine was performed. The analysis covered the dynamic impact of the actual seismic wave after the high-energy tremor of 7 June 2013. Vibrations on the land surface are a measure of the mining damage risk. It is particularly the horizontal components of land vibrations that are dangerous to buildings which is reflected in the Mining Scales of Intensity (GSI) of vibrations. The run of a seismic wave in the rock mass from the hypocenter to the area's surface depends on the lithology of the area and the presence of fault zones. The rock mass network cut by faults of various widths influences the amplitude of tremor reaching the area's surface. The analysis of the impact of the width of the fault zone was done for three alternatives.

Land Surface Verification Toolkit (LVT) - A Generalized Framework for Land Surface Model Evaluation

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Peters-Lidard, Christa D.; Santanello, Joseph; Harrison, Ken; Liu, Yuqiong; Shaw, Michael

2011-01-01

Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT) is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS), it also supports hydrological data products from other, non-LIS environments. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

Assessing soil quality indicator under different land use and soil erosion using multivariate statistical techniques.

PubMed

Nosrati, Kazem

2013-04-01

Soil degradation associated with soil erosion and land use is a critical problem in Iran and there is little or insufficient scientific information in assessing soil quality indicator. In this study, factor analysis (FA) and discriminant analysis (DA) were used to identify the most sensitive indicators of soil quality for evaluating land use and soil erosion within the Hiv catchment in Iran and subsequently compare soil quality assessment using expert opinion based on soil surface factors (SSF) form of Bureau of Land Management (BLM) method. Therefore, 19 soil physical, chemical, and biochemical properties were measured from 56 different sampling sites covering three land use/soil erosion categories (rangeland/surface erosion, orchard/surface erosion, and rangeland/stream bank erosion). FA identified four factors that explained for 82 % of the variation in soil properties. Three factors showed significant differences among the three land use/soil erosion categories. The results indicated that based upon backward-mode DA, dehydrogenase, silt, and manganese allowed more than 80 % of the samples to be correctly assigned to their land use and erosional status. Canonical scores of discriminant functions were significantly correlated to the six soil surface indices derived of BLM method. Stepwise linear regression revealed that soil surface indices: soil movement, surface litter, pedestalling, and sum of SSF were also positively related to the dehydrogenase and silt. This suggests that dehydrogenase and silt are most sensitive to land use and soil erosion.

Detecting Changes of Thermal Environment over the Bohai Coastal Region by Spectral Change Vector Analysis

NASA Astrophysics Data System (ADS)

Hu, Y.; Jia, G.

2009-12-01

Change vector analysis (CVA) is an effective approach for detecting and characterizing land-cover change by comparing pairs of multi-spectral and multi-temporal datasets over certain area derived from various satellite platforms. NDVI is considered as an effective detector for biophysical changes due to its sensitivity to red and near infrared signals, while land surface temperature (LST) is considered as a valuable indicator for changes of ground thermal conditions. Here we try to apply CVA over satellite derived LST datasets to detect changes of land surface thermal properties parallel to climate change and anthropogenic influence in a city cluster since 2001. In this study, monthly land surface temperature datasets from 2001-2008 derived from MODIS collection 5 were used to examine change pattern of thermal environment over the Bohai coastal region by using spectral change vector analysis. The results from principle component analysis (PCA) for LST show that the PC 1-3 contain over 80% information on monthly variations and these PCA components represent the main processes of land thermal environment change over the study area. Time series of CVA magnitude combined with land cover information show that greatest change occurred in urban and heavily populated area, featured with expansion of urban heat island, while moderate change appeared in grassland area in the north. However few changes were observed over large plain area and forest area. Strong signals also are related to economy level and especially the events of surface cover change, such as emergence of railway and port. Two main processes were also noticed about the changes of thermal environment. First, weak signal was detected in mostly natural area influenced by interannual climate change in temperate broadleaf forest area. Second, land surface temperature changes were controlled by human activities as 1) moderate change of LST happened in grassland influenced by grazing and 2) urban heat island was intensifier in major cities, such as Beijing and Tianjin. Further, the continual drier climate combined with human actions over past fifties years have intensified land thermal pattern change and the continuation will be an important aspects to understand land surface processes and local climate change. Land surface temperature trends from 2000-2008 over the Bohai coastal region

Impact of Land Surface Initialization Approach on Subseasonal Forecast Skill: a Regional Analysis in the Southern Hemisphere

NASA Technical Reports Server (NTRS)

Hirsch, Annette L.; Kala, Jatin; Pitman, Andy J.; Carouge, Claire; Evans, Jason P.; Haverd, Vanessa; Mocko, David

2014-01-01

The authors use a sophisticated coupled land-atmosphere modeling system for a Southern Hemisphere subdomain centered over southeastern Australia to evaluate differences in simulation skill from two different land surface initialization approaches. The first approach uses equilibrated land surface states obtained from offline simulations of the land surface model, and the second uses land surface states obtained from reanalyses. The authors find that land surface initialization using prior offline simulations contribute to relative gains in subseasonal forecast skill. In particular, relative gains in forecast skill for temperature of 10%-20% within the first 30 days of the forecast can be attributed to the land surface initialization method using offline states. For precipitation there is no distinct preference for the land surface initialization method, with limited gains in forecast skill irrespective of the lead time. The authors evaluated the asymmetry between maximum and minimum temperatures and found that maximum temperatures had the largest gains in relative forecast skill, exceeding 20% in some regions. These results were statistically significant at the 98% confidence level at up to 60 days into the forecast period. For minimum temperature, using reanalyses to initialize the land surface contributed to relative gains in forecast skill, reaching 40% in parts of the domain that were statistically significant at the 98% confidence level. The contrasting impact of the land surface initialization method between maximum and minimum temperature was associated with different soil moisture coupling mechanisms. Therefore, land surface initialization from prior offline simulations does improve predictability for temperature, particularly maximum temperature, but with less obvious improvements for precipitation and minimum temperature over southeastern Australia.

43 CFR 1610.5-7 - Situations where action can be taken based on another agency's plan, or a land use analysis.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Federal ownership interest in the surface or when coal resources are insufficient to justify plan preparation costs. The land use analysis process, as authorized by the Federal Coal Leasing Amendments Act... Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR GENERAL...

43 CFR 1610.5-7 - Situations where action can be taken based on another agency's plan, or a land use analysis.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Federal ownership interest in the surface or when coal resources are insufficient to justify plan preparation costs. The land use analysis process, as authorized by the Federal Coal Leasing Amendments Act... Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR GENERAL...

43 CFR 1610.5-7 - Situations where action can be taken based on another agency's plan, or a land use analysis.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Federal ownership interest in the surface or when coal resources are insufficient to justify plan preparation costs. The land use analysis process, as authorized by the Federal Coal Leasing Amendments Act... Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR GENERAL...

43 CFR 1610.5-7 - Situations where action can be taken based on another agency's plan, or a land use analysis.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Federal ownership interest in the surface or when coal resources are insufficient to justify plan preparation costs. The land use analysis process, as authorized by the Federal Coal Leasing Amendments Act... Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR GENERAL...

Study on temporal and spatial variations of urban land use based on land change data

NASA Astrophysics Data System (ADS)

Jiang, Ping; Liu, Yanfang; Fan, Min; Zhang, Yang

2009-10-01

With the rapid development of urbanization, demands of urban land increase in succession, hence, to analyze temporal and spatial variations of urban land use becomes more and more important. In this paper, the principle of trend surface analysis and formula of urban land sprawl index ( ULSI) are expatiated at first, and then based on land change data of Jiayu county, the author fits quadratic trend surface by choosing urban land area as dependent variable and urbanization and GDP as independent variables from 1996 to 2006, draws isoline of trend surface and residual values; and then urban land sprawl indexes of towns are calculated on the basis of urban land area of 1996 and 2006 and distribution map of ULSI is plotted. After analyzing those results, we can conclude that there is consanguineous relationship between urban land area and urbanization, economic level etc.

Towards A Synthesis Of Land Dynamics And Hydrological Processes Across Central Asia

NASA Astrophysics Data System (ADS)

Sokolik, I. N.; Tatarskii, V.; Shiklomanov, A. I.; Henebry, G. M.; de Beurs, K.; Laruelle, M.

2016-12-01

We present results from an ongoing project that aims to synthesize land dynamics, hydrological processes, and socio-economic changes across the five countries of Central Asia. We have developed a fully coupled model that takes into account the reconstructed land cover and land use dynamics to simulate dust emissions. A comparable model has been developed to model smoke emissions from wildfires. Both models incorporate land dynamics explicitly. We also present a characterization of land surface change based on a suite of MODIS products including vegetation indices, evapotranspiration, land surface temperature, and albedo. These results are connected with ongoing land privatization reforms that different across the region. We also present a regional analysis of water resources, including the significant impact of using surface water for irrigation in an arid landscape. We applied the University of New Hampshire hydrological model to understand the consequences of changes in climate, water, and land use on regional hydrological processes and water use. Water security and its dynamic have been estimated through an analysis of multiple indices and variables characterizing the water availability and water use. The economic consequences of the water privatization processes will be presented.

Surface Hydrology in Global River Basins in the Off-Line Land-Surface GEOS Assimilation (OLGA) System

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Yang, Runhua; Houser, Paul R.

1998-01-01

Land surface hydrology for the Off-line Land-surface GEOS Analysis (OLGA) system and Goddard Earth Observing System (GEOS-1) Data Assimilation System (DAS) has been examined using a river routing model. The GEOS-1 DAS land-surface parameterization is very simple, using an energy balance prediction of surface temperature and prescribed soil water. OLGA uses near-surface atmospheric data from the GEOS-1 DAS to drive a more comprehensive parameterization of the land-surface physics. The two global systems are evaluated using a global river routing model. The river routing model uses climatologic surface runoff from each system to simulate the river discharge from global river basins, which can be compared to climatologic river discharge. Due to the soil hydrology, the OLGA system shows a general improvement in the simulation of river discharge compared to the GEOS-1 DAS. Snowmelt processes included in OLGA also have a positive effect on the annual cycle of river discharge and source runoff. Preliminary tests of a coupled land-atmosphere model indicate improvements to the hydrologic cycle compared to the uncoupled system. The river routing model has provided a useful tool in the evaluation of the GCM hydrologic cycle, and has helped quantify the influence of the more advanced land surface model.

Understanding land surface evapotranspiration with satellite multispectral measurements

NASA Technical Reports Server (NTRS)

Menenti, M.

1993-01-01

Quantitative use of remote multispectral measurements to study and map land surface evapotranspiration has been a challenging issue for the past 20 years. Past work is reviewed against process physics. A simple two-layer combination-type model is used which is applicable to both vegetation and bare soil. The theoretic analysis is done to show which land surface properties are implicitly defined by such evaporation models and to assess whether they are measurable as a matter of principle. Conceptual implications of the spatial correlation of land surface properties, as observed by means of remote multispectral measurements, are illustrated with results of work done in arid zones. A normalization of spatial variability of land surface evaporation is proposed by defining a location-dependent potential evaporation and surface temperature range. Examples of the application of remote based estimates of evaporation to hydrological modeling studies in Egypt and Argentina are presented.

Land surface sensitivity of monsoon depressions formed over Bay of Bengal using improved high-resolution land state

NASA Astrophysics Data System (ADS)

Rajesh, P. V.; Pattnaik, S.; Mohanty, U. C.; Rai, D.; Baisya, H.; Pandey, P. C.

2017-12-01

Monsoon depressions (MDs) constitute a large fraction of the total rainfall during the Indian summer monsoon season. In this study, the impact of high-resolution land state is addressed by assessing the evolution of inland moving depressions formed over the Bay of Bengal using a mesoscale modeling system. Improved land state is generated using High Resolution Land Data Assimilation System employing Noah-MP land-surface model. Verification of soil moisture using Soil Moisture and Ocean Salinity (SMOS) and soil temperature using tower observations demonstrate promising results. Incorporating high-resolution land state yielded least root mean squared errors with higher correlation coefficient in the surface and mid tropospheric parameters. Rainfall forecasts reveal that simulations are spatially and quantitatively in accordance with observations and provide better skill scores. The improved land surface characteristics have brought about the realistic evolution of surface, mid-tropospheric parameters, vorticity and moist static energy that facilitates the accurate MDs dynamics in the model. Composite moisture budget analysis reveals that the surface evaporation is negligible compared to moisture flux convergence of water vapor, which supplies moisture into the MDs over land. The temporal relationship between rainfall and moisture convergence show high correlation, suggesting a realistic representation of land state help restructure the moisture inflow into the system through rainfall-moisture convergence feedback.

Impacts of spectral nudging on the simulated surface air temperature in summer compared with the selection of shortwave radiation and land surface model physics parameterization in a high-resolution regional atmospheric model

NASA Astrophysics Data System (ADS)

Park, Jun; Hwang, Seung-On

2017-11-01

The impact of a spectral nudging technique for the dynamical downscaling of the summer surface air temperature in a high-resolution regional atmospheric model is assessed. The performance of this technique is measured by comparing 16 analysis-driven simulation sets of physical parameterization combinations of two shortwave radiation and four land surface model schemes of the model, which are known to be crucial for the simulation of the surface air temperature. It is found that the application of spectral nudging to the outermost domain has a greater impact on the regional climate than any combination of shortwave radiation and land surface model physics schemes. The optimal choice of two model physics parameterizations is helpful for obtaining more realistic spatiotemporal distributions of land surface variables such as the surface air temperature, precipitation, and surface fluxes. However, employing spectral nudging adds more value to the results; the improvement is greater than using sophisticated shortwave radiation and land surface model physical parameterizations. This result indicates that spectral nudging applied to the outermost domain provides a more accurate lateral boundary condition to the innermost domain when forced by analysis data by securing the consistency with large-scale forcing over a regional domain. This consequently indirectly helps two physical parameterizations to produce small-scale features closer to the observed values, leading to a better representation of the surface air temperature in a high-resolution downscaled climate.

Multi-temporal analysis of land surface temperature in highly urbanized districts

NASA Astrophysics Data System (ADS)

Kaya, S.; Celik, B.; Sertel, E.; Bayram, B.; Seker, D. Z.

2017-12-01

Istanbul is one of the largest cities around the world with population over 15 million and it has 39 districts. Due to high immigration rate after the 1980s, parallel to the urbanization rapid population increase has occurred in some of these districts. Thus, a significant increase in land surface temperature were monitored and this subject became one of the most popular subject of different researches. Natural landscapes transformed into residential areas with impervious surfaces that causes rise in land surface temperatures which is one of the component of urban heat islands. This study focuses on determining the land use/land cover changes and land surface temperature in highly urbanized districts for last 32 years and examining the relationship between these two parameters using multi-temporal optical and thermal remotely sensed data. In this study, Landsat5 Thematic Mapper and Landsat8 OLI/TIR imagery with acquisition dates June 1984 and June 2016 were used. In order to assess the land use/cover change between 1984 and 2016, Vegetation Impervious Surface-soil (V-I-S) model is used. Each end-member spectra are extracted from ASTER spectral library. Additionally, V-I-S model, NDVI, NDBI and NDBaI indices have been derived for further investigation of land cover changes. The results of the study, presented that in the last 32 years, the amount of impervious surfaces substantially increased along with land surface temperatures.

Identifying drought response of semi-arid aeolian systems using near-surface luminescence profiles and changepoint analysis, Nebraska Sandhills.

NASA Astrophysics Data System (ADS)

Buckland, Catherine; Bailey, Richard; Thomas, David

2017-04-01

Two billion people living in drylands are affected by land degradation. Sediment erosion by wind and water removes fertile soil and destabilises landscapes. Vegetation disturbance is a key driver of dryland erosion caused by both natural and human forcings: drought, fire, land use, grazing pressure. A quantified understanding of vegetation cover sensitivities and resultant surface change to forcing factors is needed if the vegetation and landscape response to future climate change and human pressure are to be better predicted. Using quartz luminescence dating and statistical changepoint analysis (Killick & Eckley, 2014) this study demonstrates the ability to identify step-changes in depositional age of near-surface sediments. Lx/Tx luminescence profiles coupled with statistical analysis show the use of near-surface sediments in providing a high-resolution record of recent system response and aeolian system thresholds. This research determines how the environment has recorded and retained sedimentary evidence of drought response and land use disturbances over the last two hundred years across both individual landforms and the wider Nebraska Sandhills. Identifying surface deposition and comparing with records of climate, fire and land use changes allows us to assess the sensitivity and stability of the surface sediment to a range of forcing factors. Killick, R and Eckley, IA. (2014) "changepoint: An R Package for Changepoint Analysis." Journal of Statistical Software, (58) 1-19.

Broad Perspectives on Mars Landing Site Selection: Geological Factors from Centimeter to Kilometer Scales

NASA Technical Reports Server (NTRS)

Jakosky, B. M.; Golombek, M. P.

2001-01-01

Selection of a landing site for the '03 and later Mars surface missions represents a balance between potential science results and landing site safety. Although safety has to be the prime consideration, it is the melding together of spacecraft hazard analysis with science analysis that provides the key to understanding the nature of the surface for determining both its safety for landing and its scientific potential. Our goal here is to discuss the geological factors that go into a determination of site safety, at scales from centimeters up to kilometers, and to understand the implications for the resulting scientific return that can be expected.

In Situ SIMS and IR Spectroscopy of Well-defined Surfaces Prepared by Soft Landing of Mass-selected Ions

PubMed Central

Johnson, Grant E.; Gunaratne, K. Don Dasitha; Laskin, Julia

2014-01-01

Soft landing of mass-selected ions onto surfaces is a powerful approach for the highly-controlled preparation of materials that are inaccessible using conventional synthesis techniques. Coupling soft landing with in situ characterization using secondary ion mass spectrometry (SIMS) and infrared reflection absorption spectroscopy (IRRAS) enables analysis of well-defined surfaces under clean vacuum conditions. The capabilities of three soft-landing instruments constructed in our laboratory are illustrated for the representative system of surface-bound organometallics prepared by soft landing of mass-selected ruthenium tris(bipyridine) dications, [Ru(bpy)3]2+ (bpy = bipyridine), onto carboxylic acid terminated self-assembled monolayer surfaces on gold (COOH-SAMs). In situ time-of-flight (TOF)-SIMS provides insight into the reactivity of the soft-landed ions. In addition, the kinetics of charge reduction, neutralization and desorption occurring on the COOH-SAM both during and after ion soft landing are studied using in situ Fourier transform ion cyclotron resonance (FT-ICR)-SIMS measurements. In situ IRRAS experiments provide insight into how the structure of organic ligands surrounding metal centers is perturbed through immobilization of organometallic ions on COOH-SAM surfaces by soft landing. Collectively, the three instruments provide complementary information about the chemical composition, reactivity and structure of well-defined species supported on surfaces. PMID:24961913

In Situ SIMS and IR Spectroscopy of Well-Defined Surfaces Prepared by Soft Landing of Mass-Selected Ions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Grant E.; Gunaratne, Kalupathirannehelage Don D.; Laskin, Julia

2014-06-16

Soft landing of mass-selected ions onto surfaces is a powerful approach for the highly-controlled preparation of materials that are inaccessible using conventional synthesis techniques. Coupling soft landing with in situ characterization using secondary ion mass spectrometry (SIMS) and infrared reflection absorption spectroscopy (IRRAS) enables analysis of well-defined surfaces under clean vacuum conditions. The capabilities of three soft-landing instruments constructed in our laboratory are illustrated for the representative system of surface-bound organometallics prepared by soft landing of mass-selected ruthenium tris(bipyridine) dications, [Ru(bpy)3]2+, onto carboxylic acid terminated self-assembled monolayer surfaces on gold (COOH-SAMs). In situ time-of-flight (TOF)-SIMS provides insight into the reactivitymore » of the soft-landed ions. In addition, the kinetics of charge reduction, neutralization and desorption occurring on the COOH-SAM both during and after ion soft landing are studied using in situ Fourier transform ion cyclotron resonance (FT-ICR)-SIMS measurements. In situ IRRAS experiments provide insight into how the structure of organic ligands surrounding metal centers is perturbed through immobilization of organometallic ions on COOH-SAM surfaces by soft landing. Collectively, the three instruments provide complementary information about the chemical composition, reactivity and structure of well-defined species supported on surfaces.« less

Utility of Thermal Infrared Satellite Data For Urban Landscapes

NASA Astrophysics Data System (ADS)

Xian, G.; Crane, M.; Granneman, B.

2006-12-01

Urban landscapes are comprised of a variety of surfaces that are characterized by contrasting radiative, thermal, aerodynamic, and moisture properties. These different surfaces possess diverse physical and thermal attributes that directly influence surface energy balance and our ability to determine surface characteristics in urban areas. Reflectance properties obtained from satellite imagery have proven useful for mapping urban land use and land cover change, as well as ecosystem health. Landsat reflectance bands are commonly used in regression tree models to generate linear equations that correspond to distinct land surface materials. However, urban land cover is generally a heterogeneous mix of bare soil, vegetation, rock, and anthropogenic impervious surfaces. Surface temperature obtained from satellite thermal infrared bands provides valuable information about surface biophysical properties and radiant thermal characteristics of land cover elements, especially for urban environments. This study demonstrates the improved characterization of land cover conditions for Seattle, Washington, and Las Vegas, Nevada, that were achieved by using both the reflectance and thermal bands of Landsat Enhanced Thematic Mapper Plus (ETM+) data. Including the thermal band in the image analysis increased the accuracy of discriminating cover types in heterogeneous landscapes with extreme contrasts, especially for mixed pixels at the urban interface.

Visualization and Analysis of Multi-scale Land Surface Products via Giovanni Portals

NASA Technical Reports Server (NTRS)

Shen, Suhung; Kempler, Steven J.; Gerasimov, Irina V.

2013-01-01

Large volumes of MODIS land data products at multiple spatial resolutions have been integrated into the Giovanni online analysis system to support studies on land cover and land use changes,focused on the Northern Eurasia and Monsoon Asia regions through the LCLUC program. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data.Customized Giovanni Web portals (Giovanni-NEESPI andGiovanni-MAIRS) have been created to integrate land, atmospheric,cryospheric, and societal products, enabling researchers to do quick exploration and basic analyses of land surface changes, and their relationships to climate, at global and regional scales. This presentation shows a sample Giovanni portal page, lists selected data products in the system, and illustrates potential analyses with imagesand time-series at global and regional scales, focusing on climatology and anomaly analysis. More information is available at the GES DISCMAIRS data support project portal: http:disc.sci.gsfc.nasa.govmairs.

Impacts of land cover transitions on surface temperature in China based on satellite observations

NASA Astrophysics Data System (ADS)

Zhang, Yuzhen; Liang, Shunlin

2018-02-01

China has experienced intense land use and land cover changes during the past several decades, which have exerted significant influences on climate change. Previous studies exploring related climatic effects have focused mainly on one or two specific land use changes, or have considered all land use and land cover change types together without distinguishing their individual impacts, and few have examined the physical processes of the mechanism through which land use changes affect surface temperature. However, in this study, we considered satellite-derived data of multiple land cover changes and transitions in China. The objective was to obtain observational evidence of the climatic effects of land cover transitions in China by exploring how they affect surface temperature and to what degree they influence it through the modification of biophysical processes, with an emphasis on changes in surface albedo and evapotranspiration (ET). To achieve this goal, we quantified the changes in albedo, ET, and surface temperature in the transition areas, examined their correlations with temperature change, and calculated the contributions of different land use transitions to surface temperature change via changes in albedo and ET. Results suggested that land cover transitions from cropland to urban land increased land surface temperature (LST) during both daytime and nighttime by 0.18 and 0.01 K, respectively. Conversely, the transition of forest to cropland tended to decrease surface temperature by 0.53 K during the day and by 0.07 K at night, mainly through changes in surface albedo. Decreases in both daytime and nighttime LST were observed over regions of grassland to forest transition, corresponding to average values of 0.44 and 0.20 K, respectively, predominantly controlled by changes in ET. These results highlight the necessity to consider the individual climatic effects of different land cover transitions or conversions in climate research studies. This short-term analysis of land cover transitions in China means our estimates should represent local temperature effects. Changes in ET and albedo explained <60% of the variation in LST change caused by land cover transitions; thus, additional factors that affect surface climate need consideration in future studies.

Operational Derivation of Surface Albedo and Down-Welling Short-Wave Radiation in the Satellite Application Facility for Land Surface Analysis

NASA Astrophysics Data System (ADS)

Geiger, B.; Carrer, D.; Meurey, C.; Roujean, J.-L.

2006-08-01

The Satellite Application Facility for Land Surface Anal- ysis hosted by the Portuguese Meteorological Institute in Lisbon generates and distributes value added satellite products for numerical weather prediction and environ- mental applications in near-real time. Within the project consortium M´et´eo-France is responsible for the land sur- face albedo and down-welling short-wave radiation flux products. Since the beginning of the year 2005 Meteosat Second Generation data are routinely processed by the Land-SAF operational system. In general the validation studies carried out so far show a good consistency with in-situ observations or equivalent products derived from other satellites. After one year of operations a summary of the product characteristics and performances is given. Key words: Surface Albedo; Down-welling Radiation; Land-SAF.

Spatially Complete Global Spectral Surface Albedos: Value-Added Datasets Derived from Terra MODIS Land Products

NASA Technical Reports Server (NTRS)

Moody, Eric G.; King, Michael D.; Platnick, Steven; Schaaf, Crystal B.; Gao, Feng

2004-01-01

Land surface albedo is an important parameter in describing the radiative properties of the earth s surface as it represents the amount of incoming solar radiation that is reflected from the surface. The amount and type of vegetation of the surface dramatically alters the amount of radiation that is reflected; for example, croplands that contain leafy vegetation will reflect radiation very differently than blacktop associated with urban areas. In addition, since vegetation goes through a growth, or phenological, cycle, the amount of radiation that is reflected changes over the course of a year. As a result, albedo is both temporally and spatially dependant upon global location as there is a distribution of vegetated surface types and growing conditions. Land surface albedo is critical for a wide variety of earth system research projects including but not restricted to remote sensing of atmospheric aerosol and cloud properties from space, ground-based analysis of aerosol optical properties from surface-based sun/sky radiometers, biophysically-based land surface modeling of the exchange of energy, water, momentum, and carbon for various land use categories, and surface energy balance studies. These projects require proper representation of the surface albedo s spatial, spectral, and temporal variations, however, these representations are often lacking in datasets prior to the latest generation of land surface albedo products.

Proposal for a lunar landing pod for SKITTER

NASA Technical Reports Server (NTRS)

Herman, David; Huang, Frank; Morelli, Mark; Njaka, Chima; Pope, Michael; Rice, Michael

1987-01-01

The purpose of this project is to design a lunar landing module for the SKITTER vehicle. SKITTER is a three-legged mobile lunar transport and work platform. This lunar landing module must be able to bring SKITTER, with attached crane, from a lunar orbit to the surface of the Moon. This propulsion system is entirely self-contained and removable after touchdown. SKITTER is unmanned and must be able to touch down on the lunar surface and perform assigned tasks independently of other space or lunar vehicles. The propulsion system is designed to ensure that the vehicle will make a lunar landing within the expected velocity range. A landing gear configuration is presented to safely dissipate landing forces on lunar impact and be removed from the SKITTER structure after touchdown. The overall engineering analysis was conducted to determine an economical design to land SKITTER safely on the Moon. SKITTER will perform various tasks on the surface of the Moon. The completion of this project will determine the feasibility of landing SKITTER with the attached crane safely on the lunar surface.

Influence of snow cover changes on surface radiation and heat balance based on the WRF model

NASA Astrophysics Data System (ADS)

Yu, Lingxue; Liu, Tingxiang; Bu, Kun; Yang, Jiuchun; Chang, Liping; Zhang, Shuwen

2017-10-01

The snow cover extent in mid-high latitude areas of the Northern Hemisphere has significantly declined corresponding to the global warming, especially since the 1970s. Snow-climate feedbacks play a critical role in regulating the global radiation balance and influencing surface heat flux exchange. However, the degree to which snow cover changes affect the radiation budget and energy balance on a regional scale and the difference between snow-climate and land use/cover change (LUCC)-climate feedbacks have been rarely studied. In this paper, we selected Heilongjiang Basin, where the snow cover has changed obviously, as our study area and used the WRF model to simulate the influences of snow cover changes on the surface radiation budget and heat balance. In the scenario simulation, the localized surface parameter data improved the accuracy by 10 % compared with the control group. The spatial and temporal analysis of the surface variables showed that the net surface radiation, sensible heat flux, Bowen ratio, temperature and percentage of snow cover were negatively correlated and that the ground heat flux and latent heat flux were positively correlated with the percentage of snow cover. The spatial analysis also showed that a significant relationship existed between the surface variables and land cover types, which was not obviously as that for snow cover changes. Finally, six typical study areas were selected to quantitatively analyse the influence of land cover types beneath the snow cover on heat absorption and transfer, which showed that when the land was snow covered, the conversion of forest to farmland can dramatically influence the net radiation and other surface variables, whereas the snow-free land showed significantly reduced influence. Furthermore, compared with typical land cover changes, e.g., the conversion of forest into farmland, the influence of snow cover changes on net radiation and sensible heat flux were 60 % higher than that of land cover changes, indicating the importance of snow cover changes in the surface-atmospheric feedback system.

Land Surface Precipitation and Hydrology in MERRA-2

NASA Technical Reports Server (NTRS)

Reichle, R.; Koster, R.; Draper, C.; Liu, Q.; Girotto, M.; Mahanama, S.; De Lannoy, G.; Partyka, G.

2017-01-01

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), provides global, 1-hourly estimates of land surface conditions for 1980-present at 50-km resolution. Outside of the high latitudes, MERRA-2 uses observations-based precipitation data products to correct the precipitation falling on the land surface. This paper describes the precipitation correction method and evaluates the MERRA-2 land surface precipitation and hydrology. Compared to monthly GPCPv2.2 observations, the corrected MERRA-2 precipitation (M2CORR) is better than the precipitation generated by the atmospheric models within the cyclingMERRA-2 system and the earlier MERRA reanalysis. Compared to 3-hourlyTRMM observations, the M2CORR diurnal cycle has better amplitude but less realistic phasing than MERRA-2 model-generated precipitation. Because correcting the precipitation within the coupled atmosphere-land modeling system allows the MERRA-2 near-surface air temperature and humidity to respond to the improved precipitation forcing, MERRA-2 provides more self-consistent surface meteorological data than were available from the earlier, offline MERRA-Land reanalysis. Overall, MERRA-2 land hydrology estimates are better than those of MERRA-Land and MERRA. A comparison against GRACE satellite observations of terrestrial water storage demonstrates clear improvements in MERRA-2 over MERRA in South America and Africa but also reflects known errors in the observations used to correct the MERRA-2 precipitation. The MERRA-2 and MERRA-Land surface and root zone soil moisture skill vs. in situ measurements is slightly higher than that of ERA-Interim Land and higher than that of MERRA (significantly for surface soil moisture). Snow amounts from MERRA-2 have lower bias and correlate better against reference data than do those of MERRA-Land and MERRA, with MERRA-2 skill roughly matching that of ERA-Interim Land. Seasonal anomaly R values against naturalized stream flow measurements in the United States are, on balance, highest for MERRA-2 and ERA-Interim Land, somewhat lower for MERRA-Land, and lower still for MERRA.

An analysis of urban thermal characteristics and associated land cover in Tampa Bay and Las Vegas using Landsat satellite data

USGS Publications Warehouse

Xian, George; Crane, Mike

2006-01-01

Remote sensing data from both Landsat 5 and Landsat 7 systems were utilized to assess urban area thermal characteristics in Tampa Bay watershed of west-central Florida, and the Las Vegas valley of southern Nevada. To quantitatively determine urban land use extents and development densities, sub-pixel impervious surface areas were mapped for both areas. The urban–rural boundaries and urban development densities were defined by selecting certain imperviousness threshold values and Landsat thermal bands were used to investigate urban surface thermal patterns. Analysis results suggest that urban surface thermal characteristics and patterns can be identified through qualitatively based urban land use and development density data. Results show the urban area of the Tampa Bay watershed has a daytime heating effect (heat-source), whereas the urban surface in Las Vegas has a daytime cooling effect (heat-sink). These thermal effects strongly correlated with urban development densities where higher percent imperviousness is usually associated with higher surface temperature. Using vegetation canopy coverage information, the spatial and temporal distributions of urban impervious surface and associated thermal characteristics are demonstrated to be very useful sources in quantifying urban land use, development intensity, and urban thermal patterns.

Characteristics of organic soil in black spruce forests: implications for the application of land surface and ecosystem models in cold regions

Treesearch

Shuhua Yi; Kristen Manies; Jennifer Harden; David McGuire

2009-01-01

Soil organic layers (OL) play an important role in land-atmosphere exchanges of water, energy and carbon in cold environments. The proper implementation of OL in land surface and ecosystem models is important for predicting dynamic responses to climate warming. Based on the analysis of OL samples of black spruce (Picea mariana), we recommend that...

Towards the Consideration of Surface and Environment variables for a Microwave Precipitation Algorithm Over Land

NASA Astrophysics Data System (ADS)

Wang, N. Y.; You, Y.; Ferraro, R. R.; Guch, I.

2014-12-01

Microwave satellite remote sensing of precipitation over land is a challenging problem due to the highly variable land surface emissivity, which, if not properly accounted for, can be much greater than the precipitation signal itself, especially in light rain/snow conditions. Additionally, surfaces such as arid land, deserts and snow cover have brightness temperatures characteristics similar to precipitation Ongoing work by NASA's GPM microwave radiometer team is constructing databases for the GPROF algorithm through a variety of means, however, there is much uncertainty as to what is the optimal information needed for the wide array of sensors in the GPM constellation, including examination of regional conditions. The at-launch database focuses on stratification by emissivity class, surface temperature and total precipitable water (TPW). We'll perform sensitivity studies to determine the potential role of environmental factors such as land surface temperature, surface elevation, and relative humidity and storm morphology such as storm vertical structure, height, and ice thickness to improve precipitation estimation over land, including rain and snow. In other words, what information outside of the satellite radiances can help describe the background and subsequent departures from it that are active precipitating regions? It is likely that this information will be a function of the various precipitation regimes. Statistical methods such as Principal Component Analysis (PCA) will be utilized in this task. Databases from a variety of sources are being constructed. They include existing satellite microwave measurements of precipitating and non-precipitating conditions, ground radar precipitation rate estimates, surface emissivity climatology from satellites, surface temperature and TPW from NWP reanalysis. Results from the analysis of these databases with respect to the microwave precipitation sensitivity to the variety of environmental conditions in different climate regimes will be discussed.

Sensitivity of Land Surface Parameters on Thunderstorm Simulation through HRLDAS-WRF Coupling Mode

NASA Astrophysics Data System (ADS)

Kumar, Dinesh; Kumar, Krishan; Mohanty, U. C.; Kisore Osuri, Krishna

2016-07-01

Land surface characteristics play an important role in large scale, regional and mesoscale atmospheric process. Representation of land surface characteristics can be improved through coupling of mesoscale atmospheric models with land surface models. Mesoscale atmospheric models depend on Land Surface Models (LSM) to provide land surface variables such as fluxes of heat, moisture, and momentum for lower boundary layer evolution. Studies have shown that land surface properties such as soil moisture, soil temperature, soil roughness, vegetation cover, have considerable effect on lower boundary layer. Although, the necessity to initialize soil moisture accurately in NWP models is widely acknowledged, monitoring soil moisture at regional and global scale is a very tough task due to high spatial and temporal variability. As a result, the available observation network is unable to provide the required spatial and temporal data for the most part of the globe. Therefore, model for land surface initializations rely on updated land surface properties from LSM. The solution for NWP land-state initialization can be found by combining data assimilation techniques, satellite-derived soil data, and land surface models. Further, it requires an intermediate step to use observed rainfall, satellite derived surface insolation, and meteorological analyses to run an uncoupled (offline) integration of LSM, so that the evolution of modeled soil moisture can be forced by observed forcing conditions. Therefore, for accurate land-state initialization, high resolution land data assimilation system (HRLDAS) is used to provide the essential land surface parameters. Offline-coupling of HRLDAS-WRF has shown much improved results over Delhi, India for four thunder storm events. The evolution of land surface variables particularly soil moisture, soil temperature and surface fluxes have provided more realistic condition. Results have shown that most of domain part became wetter and warmer after assimilation of soil moisture and soil temperature at the initial condition which helped to improve the exchange fluxes at lower atmospheric level. Mixing ratio were increased along with elevated theta-e at lower level giving a signature of improvement in LDAS experiment leading to a suitable condition for convection. In the analysis, moisture convergence, mixing ratio and vertical velocities have improved significantly in terms of intensity and time lag. Surface variables like soil moisture, soil temperature, sensible heat flux and latent heat flux have progressed in a possible realistic pattern. Above discussion suggests that assimilation of soil moisture and soil temperature improves the overall simulations significantly.

Watershed Analysis for Runoff and Erosion Potential on Santa Cruz Watershed: Impact of Climate and Land Cover Changes

EPA Science Inventory

Many empirical studies have established the significant relationship between climate and runoff: climate change may potentially increase or decrease the surface runoff. Increased surface runoff can also increase the risk of soil erosion. Land cover change can alter rainfall-runof...

The potential of 2D Kalman filtering for soil moisture data assimilation

USDA-ARS?s Scientific Manuscript database

We examine the potential for parameterizing a two-dimensional (2D) land data assimilation system using spatial error auto-correlation statistics gleaned from a triple collocation analysis and the triplet of: (1) active microwave-, (2) passive microwave- and (3) land surface model-based surface soil ...

Understanding Decreases in Land Relative Humidity with Global Warming: Conceptual Model and GCM Simulations

NASA Astrophysics Data System (ADS)

Byrne, Michael P.; O'Gorman, Paul A.

2016-12-01

Climate models simulate a strong land-ocean contrast in the response of near-surface relative humidity to global warming: relative humidity tends to increase slightly over oceans but decrease substantially over land. Surface energy balance arguments have been used to understand the response over ocean but are difficult to apply over more complex land surfaces. Here, a conceptual box model is introduced, involving moisture transport between the land and ocean boundary layers and evapotranspiration, to investigate the decreases in land relative humidity as the climate warms. The box model is applied to idealized and full-complexity (CMIP5) general circulation model simulations, and it is found to capture many of the features of the simulated changes in land relative humidity. The box model suggests there is a strong link between fractional changes in specific humidity over land and ocean, and the greater warming over land than ocean then implies a decrease in land relative humidity. Evapotranspiration is of secondary importance for the increase in specific humidity over land, but it matters more for the decrease in relative humidity. Further analysis shows there is a strong feedback between changes in surface-air temperature and relative humidity, and this can amplify the influence on relative humidity of factors such as stomatal conductance and soil moisture.

Global Land Carbon Uptake from Trait Distributions

NASA Astrophysics Data System (ADS)

Butler, E. E.; Datta, A.; Flores-Moreno, H.; Fazayeli, F.; Chen, M.; Wythers, K. R.; Banerjee, A.; Atkin, O. K.; Kattge, J.; Reich, P. B.

2016-12-01

Historically, functional diversity in land surface models has been represented through a range of plant functional types (PFTs), each of which has a single value for all of its functional traits. Here we expand the diversity of the land surface by using a distribution of trait values for each PFT. The data for these trait distributions is from a sub-set of the global database of plant traits, TRY, and this analysis uses three leaf traits: mass based nitrogen and phosphorus content and specific leaf area, which influence both photosynthesis and respiration. The data are extrapolated into continuous surfaces through two methodologies. The first, a categorical method, classifies the species observed in TRY into satellite estimates of their plant functional type abundances - analogous to how traits are currently assigned to PFTs in land surface models. Second, a Bayesian spatial method which additionally estimates how the distribution of a trait changes in accord with both climate and soil covariates. These two methods produce distinct patterns of diversity which are incorporated into a land surface model to estimate how the range of trait values affects the global land carbon budget.

Advancing land surface model development with satellite-based Earth observations

NASA Astrophysics Data System (ADS)

Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

2017-04-01

The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

Quantifying urban land cover change between 2001 and 2006 in the Gulf of Mexico region

USGS Publications Warehouse

Xian, George Z.; Homer, Collin G.; Bunde, Brett; Danielson, Patrick; Dewitz, Jon; Fry, Joyce; Pu, Ruiliang

2012-01-01

We estimated urbanization rates (2001–2006) in the Gulf of Mexico region using the National Land Cover Database (NLCD) 2001 and 2006 impervious surface products. An improved method was used to update the NLCD impervious surface product in 2006 and associated land cover transition between 2001 and 2006. Our estimation reveals that impervious surface increased 416 km2 with a growth rate of 5.8% between 2001 and 2006. Approximately 1110.1 km2 of non-urban lands were converted into urban land, resulting in a 3.2% increase in the region. Hay/pasture, woody wetland, and evergreen forest represented the three most common land cover classes that transitioned to urban. Among these land cover transitions, more than 50% of the urbanization occurred within 50 km of the coast. Our analysis shows that the close-to-coast land cover transition trend, especially within 10 km off the coast, potentially imposes substantial long-term impacts on regional landscape and ecological conditions.

Analysis of the geomorphology surrounding the Chang'e-3 landing site

NASA Astrophysics Data System (ADS)

Li, Chun-Lai; Mu, Ling-Li; Zou, Xiao-Duan; Liu, Jian-Jun; Ren, Xin; Zeng, Xing-Guo; Yang, Yi-Man; Zhang, Zhou-Bin; Liu, Yu-Xuan; Zuo, Wei; Li, Han

2014-12-01

Chang'e-3 (CE-3) landed on the Mare Imbrium basin in the east part of Sinus Iridum (19.51°W, 44.12°N), which was China's first soft landing on the Moon and it started collecting data on the lunar surface environment. To better understand the environment of this region, this paper utilizes the available high-resolution topography data, image data and geological data to carry out a detailed analysis and research on the area surrounding the landing site (Sinus Iridum and 45 km×70 km of the landing area) as well as on the topography, landform, geology and lunar dust of the area surrounding the landing site. A general topographic analysis of the surrounding area is based on a digital elevation model and digital elevation model data acquired by Chang'e-2 that have high resolution; the geology analysis is based on lunar geological data published by USGS; the study on topographic factors and distribution of craters and rocks in the surrounding area covering 4 km×4 km or even smaller is based on images from the CE-3 landing camera and images from the topographic camera; an analysis is done of the effect of the CE-3 engine plume on the lunar surface by comparing images before and after the landing using data from the landing camera. A comprehensive analysis of the results shows that the landing site and its surrounding area are identified as typical lunar mare with flat topography. They are suitable for maneuvers by the rover, and are rich in geological phenomena and scientific targets, making it an ideal site for exploration.

Expansion of oil palm and other cash crops causes an increase of the land surface temperature in the Jambi province in Indonesia

NASA Astrophysics Data System (ADS)

Sabajo, Clifton R.; le Maire, Guerric; June, Tania; Meijide, Ana; Roupsard, Olivier; Knohl, Alexander

2017-10-01

Indonesia is currently one of the regions with the highest transformation rate of land surface worldwide related to the expansion of oil palm plantations and other cash crops replacing forests on large scales. Land cover changes, which modify land surface properties, have a direct effect on the land surface temperature (LST), a key driver for many ecological functions. Despite the large historic land transformation in Indonesia toward oil palm and other cash crops and governmental plans for future expansion, this is the first study so far to quantify the impacts of land transformation on the LST in Indonesia. We analyze LST from the thermal band of a Landsat image and produce a high-resolution surface temperature map (30 m) for the lowlands of the Jambi province in Sumatra (Indonesia), a region which suffered large land transformation towards oil palm and other cash crops over the past decades. The comparison of LST, albedo, normalized differenced vegetation index (NDVI) and evapotranspiration (ET) between seven different land cover types (forest, urban areas, clear-cut land, young and mature oil palm plantations, acacia and rubber plantations) shows that forests have lower surface temperatures than the other land cover types, indicating a local warming effect after forest conversion. LST differences were up to 10.1 ± 2.6 °C (mean ± SD) between forest and clear-cut land. The differences in surface temperatures are explained by an evaporative cooling effect, which offsets the albedo warming effect. Our analysis of the LST trend of the past 16 years based on MODIS data shows that the average daytime surface temperature in the Jambi province increased by 1.05 °C, which followed the trend of observed land cover changes and exceeded the effects of climate warming. This study provides evidence that the expansion of oil palm plantations and other cash crops leads to changes in biophysical variables, warming the land surface and thus enhancing the increase of the air temperature because of climate change.

Land Cover/Land Use Classification and Change Detection Analysis with Astronaut Photography and Geographic Object-Based Image Analysis

NASA Technical Reports Server (NTRS)

Hollier, Andi B.; Jagge, Amy M.; Stefanov, William L.; Vanderbloemen, Lisa A.

2017-01-01

For over fifty years, NASA astronauts have taken exceptional photographs of the Earth from the unique vantage point of low Earth orbit (as well as from lunar orbit and surface of the Moon). The Crew Earth Observations (CEO) Facility is the NASA ISS payload supporting astronaut photography of the Earth surface and atmosphere. From aurora to mountain ranges, deltas, and cities, there are over two million images of the Earth's surface dating back to the Mercury missions in the early 1960s. The Gateway to Astronaut Photography of Earth website (eol.jsc.nasa.gov) provides a publically accessible platform to query and download these images at a variety of spatial resolutions and perform scientific research at no cost to the end user. As a demonstration to the science, application, and education user communities we examine astronaut photography of the Washington D.C. metropolitan area for three time steps between 1998 and 2016 using Geographic Object-Based Image Analysis (GEOBIA) to classify and quantify land cover/land use and provide a template for future change detection studies with astronaut photography.

City landscape changes effects on land surface temperature in Bucharest metropolitan area

NASA Astrophysics Data System (ADS)

Savastru, Dan M.; Zoran, Maria A.; Savastru, Roxana S.; Dida, Adrian I.

2017-10-01

This study investigated the influences of city land cover changes and extreme climate events on land surface temperature in relationship with several biophysical variables in Bucharest metropolitan area of Romania through satellite and in-situ monitoring data. Remote sensing data from IKONOS, Landsat TM/ETM+ and time series MODIS Terra/Aqua and NOAA AVHRR sensors have been used to assess urban land cover- temperature interactions over 2000 - 2016 period. Time series Thermal InfraRed (TIR) satellite remote sensing data in synergy with meteorological data (air temperatureAT, precipitations, wind, solar radiation, etc.) were applied mainly for analyzing land surface temperature (LST) pattern and its relationship with surface landscape characteristics, assessing urban heat island (UHI), and relating urban land cover temperatures (LST). The land surface temperature, a key parameter for urban thermal characteristics analysis, was also analyzed in relation with the Normalized Difference Vegetation Index (NDVI) at city level. Results show that in the metropolitan area ratio of impervious surface in Bucharest increased significantly during investigated period, the intensity of urban heat island and heat wave events being most significant. The correlation analyses revealed that, at the pixel-scale, LST and AT possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at metropolitan scale respectively. The NDVI was significantly correlated with precipitation. The spatial average air temperatures in urban test areas rise with the expansion of the urban size.

ExoMars Entry, Descent, and Landing Science

NASA Astrophysics Data System (ADS)

Karatekin, Özgür; Forget, Francois; Withers, Paul; Colombatti, Giacomo; Aboudan, Alessio; Lewis, Stephen; Ferri, Francesca; Van Hove, Bart; Gerbal, Nicolas

2016-07-01

Schiaparelli, the Entry Demonstrator Module (EDM) of the ESA ExoMars Program will to land on Mars on 19th October 2016. The ExoMars Atmospheric Mars Entry and Landing Investigations and Analysis (AMELIA) team seeks to exploit the Entry Descent and Landing (EDL) engineering measurements of Schiaparelli for scientific investigations of Mars' atmosphere and surface. ExoMars offers a rare opportunity to perform an in situ investigation of the martian environment over a wide altitude range. There has been only 7 successfully landing on the surface of Mars, from the Viking probes in the 1970's to the Mars Science Laboratory (MSL) in 2012. ExoMars EDM is equipped with an instrumented heat shield like MSL. These novel flight sensors complement conventional accelerometer and gyroscope instrumentation, and provide additional information to reconstruct atmospheric conditions with. This abstract outlines general atmospheric reconstruction methodology using complementary set of sensors and in particular the use of surface pressure and radio data. In addition, we discuss the lessons learned from previous EDL and the plans for ExoMars AMELIA data analysis.

Applications of Skylab data to land use and climatological analysis

NASA Technical Reports Server (NTRS)

Alexander, R. H. (Principal Investigator); Lewis, J. E., Jr.; Lins, H. F., Jr.; Jenner, C. B.; Outcalt, S. I.; Pease, R. W.

1976-01-01

The author has identified the following significant results. Skylab study in Central Atlantic Regional Ecological Test Site encompassed two separate but related tasks: (1) evaluation of photographic sensors S190A and B as sources of land use data for planning and managing land resources in major metropolitan regions, and (2) evaluation of the multispectral scanner S192 used in conjunction with associated data and analytical techniques as a data source on urban climates and the surface energy balance. Photographs from the Skylab S190B earth terrain camera were of greatest interest in the land use analysis task; they were of sufficiently high resolution to identify and map many level 2 and 3 land use categories. After being corrected to allow for atmosphere effects, output from thermal and visible bands of the S192 was employed in constructing computer map plots of albedo and surface temperature.

The Autonomous Precision Landing and Hazard Detection and Avoidance Technology (ALHAT)

NASA Technical Reports Server (NTRS)

Epp, Chirold D.; Smith, Thomas B.

2007-01-01

As NASA plans to send humans back to the Moon and develop a lunar outpost, technologies must be developed to place humans and cargo safely, precisely, repeatedly, on the lunar surface with the capability to avoid surface hazards. Exploration Space Architecture Study requirements include the need for global lunar surface access with safe, precise landing without lighting constraints on terrain that may have landing hazards for human scale landing vehicles. Landing accuracies of perhaps 1,000 meters for sortie crew missions to 10 s of meters for Outpost class missions are required. The Autonomous precision Landing Hazard Avoidance Technology (ALHAT) project will develop the new and unique descent and landing Guidance, Navigation and Control (GNC) hardware and software technologies necessary for these capabilities. The ALHAT project will qualify a lunar descent and landing GNC system to a Technology Readiness Level (TRL) of 6 capable of supporting lunar crewed, cargo, and robotic missions. The (ALHAT) development project was chartered by NASA Headquarters in October 2006. The initial effort to write a project plan and define an ALHAT Team was followed by a fairly aggressive research and analysis effort to determine what technologies existed that could be developed and applied to the lunar landing problems indicated above. This paper describes the project development, research, analysis and concept evolution that has occurred since the assignment of the project. This includes the areas of systems engineering, GNC, sensors, sensor algorithms, simulations, fielding testing, laboratory testing, Hardware-In-The-Loop testing, system avionics and system certification concepts.

The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE)

PubMed Central

Tian, Xin; Li, Zengyuan; Chen, Erxue; Liu, Qinhuo; Yan, Guangjian; Wang, Jindi; Niu, Zheng; Zhao, Shaojie; Li, Xin; Pang, Yong; Su, Zhongbo; van der Tol, Christiaan; Liu, Qingwang; Wu, Chaoyang; Xiao, Qing; Yang, Le; Mu, Xihan; Bo, Yanchen; Qu, Yonghua; Zhou, Hongmin; Gao, Shuai; Chai, Linna; Huang, Huaguo; Fan, Wenjie; Li, Shihua; Bai, Junhua; Jiang, Lingmei; Zhou, Ji

2015-01-01

The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE) comprises a network of remote sensing experiments designed to enhance the dynamic analysis and modeling of remotely sensed information for complex land surfaces. Two types of experimental campaigns were established under the framework of COMPLICATE. The first was designed for continuous and elaborate experiments. The experimental strategy helps enhance our understanding of the radiative and scattering mechanisms of soil and vegetation and modeling of remotely sensed information for complex land surfaces. To validate the methodologies and models for dynamic analyses of remote sensing for complex land surfaces, the second campaign consisted of simultaneous satellite-borne, airborne, and ground-based experiments. During field campaigns, several continuous and intensive observations were obtained. Measurements were undertaken to answer key scientific issues, as follows: 1) Determine the characteristics of spatial heterogeneity and the radiative and scattering mechanisms of remote sensing on complex land surfaces. 2) Determine the mechanisms of spatial and temporal scale extensions for remote sensing on complex land surfaces. 3) Determine synergist inversion mechanisms for soil and vegetation parameters using multi-mode remote sensing on complex land surfaces. Here, we introduce the background, the objectives, the experimental designs, the observations and measurements, and the overall advances of COMPLICATE. As a result of the implementation of COMLICATE and for the next several years, we expect to contribute to quantitative remote sensing science and Earth observation techniques. PMID:26332035

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression.

PubMed

Chen, Qiang; Mei, Kun; Dahlgren, Randy A; Wang, Ting; Gong, Jian; Zhang, Minghua

2016-12-01

As an important regulator of pollutants in overland flow and interflow, land use has become an essential research component for determining the relationships between surface water quality and pollution sources. This study investigated the use of ordinary least squares (OLS) and geographically weighted regression (GWR) models to identify the impact of land use and population density on surface water quality in the Wen-Rui Tang River watershed of eastern China. A manual variable excluding-selecting method was explored to resolve multicollinearity issues. Standard regression coefficient analysis coupled with cluster analysis was introduced to determine which variable had the greatest influence on water quality. Results showed that: (1) Impact of land use on water quality varied with spatial and seasonal scales. Both positive and negative effects for certain land-use indicators were found in different subcatchments. (2) Urban land was the dominant factor influencing N, P and chemical oxygen demand (COD) in highly urbanized regions, but the relationship was weak as the pollutants were mainly from point sources. Agricultural land was the primary factor influencing N and P in suburban and rural areas; the relationship was strong as the pollutants were mainly from agricultural surface runoff. Subcatchments located in suburban areas were identified with urban land as the primary influencing factor during the wet season while agricultural land was identified as a more prevalent influencing factor during the dry season. (3) Adjusted R 2 values in OLS models using the manual variable excluding-selecting method averaged 14.3% higher than using stepwise multiple linear regressions. However, the corresponding GWR models had adjusted R 2 ~59.2% higher than the optimal OLS models, confirming that GWR models demonstrated better prediction accuracy. Based on our findings, water resource protection policies should consider site-specific land-use conditions within each watershed to optimize mitigation strategies for contrasting land-use characteristics and seasonal variations. Copyright © 2016 Elsevier B.V. All rights reserved.

Effects of climate and land cover on hydrology in the southeastern U.S.: Potential impacts on watershed planning

USGS Publications Warehouse

LaFontaine, Jacob H.; Hay, Lauren E.; Viger, Roland; Regan, R. Steve; Markstrom, Steven

2015-01-01

The hydrologic response to statistically downscaled general circulation model simulations of daily surface climate and land cover through 2099 was assessed for the Apalachicola-Chattahoochee-Flint River Basin located in the southeastern United States. Projections of climate, urbanization, vegetation, and surface-depression storage capacity were used as inputs to the Precipitation-Runoff Modeling System to simulate projected impacts on hydrologic response. Surface runoff substantially increased when land cover change was applied. However, once the surface depression storage was added to mitigate the land cover change and increases of surface runoff (due to urbanization), the groundwater flow component then increased. For hydrologic studies that include projections of land cover change (urbanization in particular), any analysis of runoff beyond the change in total runoff should include effects of stormwater management practices as these features affect flow timing and magnitude and may be useful in mitigating land cover change impacts on streamflow. Potential changes in water availability and how biota may respond to changes in flow regime in response to climate and land cover change may prove challenging for managers attempting to balance the needs of future development and the environment. However, these models are still useful for assessing the relative impacts of climate and land cover change and for evaluating tradeoffs when managing to mitigate different stressors.

Response of dissolved trace metals to land use/land cover and their source apportionment using a receptor model in a subtropic river, China.

PubMed

Li, Siyue; Zhang, Quanfa

2011-06-15

Water samples were collected for determination of dissolved trace metals in 56 sampling sites throughout the upper Han River, China. Multivariate statistical analyses including correlation analysis, stepwise multiple linear regression models, and principal component and factor analysis (PCA/FA) were employed to examine the land use influences on trace metals, and a receptor model of factor analysis-multiple linear regression (FA-MLR) was used for source identification/apportionment of anthropogenic heavy metals in the surface water of the River. Our results revealed that land use was an important factor in water metals in the snow melt flow period and land use in the riparian zone was not a better predictor of metals than land use away from the river. Urbanization in a watershed and vegetation along river networks could better explain metals, and agriculture, regardless of its relative location, however slightly explained metal variables in the upper Han River. FA-MLR analysis identified five source types of metals, and mining, fossil fuel combustion, and vehicle exhaust were the dominant pollutions in the surface waters. The results demonstrated great impacts of human activities on metal concentrations in the subtropical river of China. Copyright © 2011 Elsevier B.V. All rights reserved.

Linkages between Land Surface Phenology Metrics and Natural and Anthropogenic Events in Drylands (Invited)

NASA Astrophysics Data System (ADS)

de Beurs, K.; Brown, M. E.; Ahram, A.; Walker, J.; Henebry, G. M.

2013-12-01

Tracking vegetation dynamics across landscapes using remote sensing, or 'land surface phenology,' is a key mechanism that allows us to understand ecosystem changes. Land surface phenology models rely on vegetation information from remote sensing, such as the datasets derived from the Advanced Very High Resolution Radiometer (AVHRR), the newer MODIS sensors on Aqua and Terra, and sometimes the higher spatial resolution Landsat data. Vegetation index data can aid in the assessment of variables such as the start of season, growing season length and overall growing season productivity. In this talk we use Landsat, MODIS and AVHRR data and derive growing season metrics based on land surface phenology models that couple vegetation indices with satellite derived accumulated growing degreeday and evapotranspiration estimates. We calculate the timing and the height of the peak of the growing season and discuss the linkage of these land surface phenology metrics with natural and anthropogenic changes on the ground in dryland ecosystems. First we will discuss how the land surface phenology metrics link with annual and interannual price fluctuations in 229 markets distributed over Africa. Our results show that there is a significant correlation between the peak height of the growing season and price increases for markets in countries such as Nigeria, Somalia and Niger. We then demonstrate how land surface phenology metrics can improve models of post-conflict resolution in global drylands. We link the Uppsala Conflict Data Program's dataset of political, economic and social factors involved in civil war termination with an NDVI derived phenology metric and the Palmer Drought Severity Index (PDSI). An analysis of 89 individual conflicts in 42 dryland countries (totaling 892 individual country-years of data between 1982 and 2005) revealed that, even accounting for economic and political factors, countries that have higher NDVI growth following conflict have a lower risk of reverting to civil war. Finally, the patchy and heterogeneous arrangement of vegetation in dryland areas sometimes complicates the extraction of phenological signals using existing remote sensing data. We conclude by demonstrating how the phenological analysis of a range of dryland land cover classes benefits from the availability of synthetic images at Landsat spatial resolution and MODIS time intervals.

Remote Sensing of the Environmental Impacts of Utility-Scale Solar Energy Plants

NASA Astrophysics Data System (ADS)

Edalat, Mohammad Masih

Solar energy has many environmental benefits compared with fossil fuels but solar farming can have environmental impacts especially during construction and development. Thus, in order to enhance environmental sustainability, it is imperative to understand the environmental impacts of utility-scale solar energy (USSE) plants. During recent decades, remote sensing techniques and geographic information systems have become standard techniques in environmental applications. In this study, the environmental impacts of USSE plants are investigated by analyzing changes to land surface characteristics using remote sensing. The surface characteristics studied include land cover, land surface temperature, and hydrological response whereas changes are mapped by comparing pre-, syn-, and post- construction conditions. In order to study the effects of USSE facilities on land cover, the changes in the land cover are measured and analyzed inside and around two USSE facilities. The principal component analysis (PCA), minimum noise fraction (MNF), and spectral mixture analysis (SMA) of remote sensing images are used to estimate the subpixel fraction of four land surface endmembers: high-albedo, low-albedo, shadow, and vegetation. The results revealed that USSE plants do not significantly impact land cover outside the plant boundary. However, land-cover radiative characteristics within the plant area are significantly affected after construction. During the construction phase, site preparation practices including shrub removal and land grading increase high-albedo and decrease low-albedo fractions. The thermal effects of USSE facilities are studied by the time series analysis of remote sensing land surface temperature (LST). A statistical trend analysis of LST, with seasonal trends removed is performed with a particular consideration of panel shadowing by analyzing sun angles for different times of year. The results revealed that the LST outside the boundary of the solar plant does not change, whereas it significantly decreases inside the plant at 10 AM after the construction. The decrease in LST mainly occurred in winters due to lower sun's altitude, which casts longer shadows on the ground. In order to study the hydrological impacts of PV plants, pre- and post-installation hydrological response over single-axis technology is compared. A theoretical reasoning is developed to explain flows under the influence of PV panels. Moreover, a distributed parametric hydrologic model is used to estimate runoff before and after the construction of PV plants. The results revealed that peak flow, peak flow time, and runoff volume alter after panel installation. After panel installation, peak flow decreases and is observed to shift in time, which depends on orientation. Likewise, runoff volume increases irrespective of panel orientation. The increase in the tilt angle of panel results in decrease in the peak flow, peak flow time, and runoff. This study provides an insight into the environmental impacts of USSE development using remote sensing. The research demonstrates that USSE plants are environmentally sustainable due to minimal impact on land cover and surface temperature in their vicinity. In addition, this research explains the role of rainfall shadowing on hydrological behavior at USSE plants.

Verification of land-atmosphere coupling in forecast models, reanalyses and land surface models using flux site observations.

PubMed

Dirmeyer, Paul A; Chen, Liang; Wu, Jiexia; Shin, Chul-Su; Huang, Bohua; Cash, Benjamin A; Bosilovich, Michael G; Mahanama, Sarith; Koster, Randal D; Santanello, Joseph A; Ek, Michael B; Balsamo, Gianpaolo; Dutra, Emanuel; Lawrence, D M

2018-02-01

We confront four model systems in three configurations (LSM, LSM+GCM, and reanalysis) with global flux tower observations to validate states, surface fluxes, and coupling indices between land and atmosphere. Models clearly under-represent the feedback of surface fluxes on boundary layer properties (the atmospheric leg of land-atmosphere coupling), and may over-represent the connection between soil moisture and surface fluxes (the terrestrial leg). Models generally under-represent spatial and temporal variability relative to observations, which is at least partially an artifact of the differences in spatial scale between model grid boxes and flux tower footprints. All models bias high in near-surface humidity and downward shortwave radiation, struggle to represent precipitation accurately, and show serious problems in reproducing surface albedos. These errors create challenges for models to partition surface energy properly and errors are traceable through the surface energy and water cycles. The spatial distribution of the amplitude and phase of annual cycles (first harmonic) are generally well reproduced, but the biases in means tend to reflect in these amplitudes. Interannual variability is also a challenge for models to reproduce. Our analysis illuminates targets for coupled land-atmosphere model development, as well as the value of long-term globally-distributed observational monitoring.

Analysis of landscape character for visual resource management

Treesearch

Paul F. Anderson

1979-01-01

Description, classification and delineation of visual landscape character are initial steps in developing visual resource management plans. Landscape characteristics identified as key factors in visual landscape analysis include land cover/land use and landform. Landscape types, which are combinations of landform and surface features, were delineated for management...

The Water Cycle from Space: Use of Satellite Data in Land Surface Hydrology and Water Resource Management

NASA Technical Reports Server (NTRS)

Laymon, Charles; Blankenship, Clay; Khan, Maudood; Limaye, Ashutosh; Hornbuckle, Brian; Rowlandson, Tracy

2010-01-01

This slide presentation reviews how our understanding of the water cycle is enhanced by our use of satellite data, and how this informs land surface hydrology and water resource management. It reviews how NASA's current and future satellite missions will provide Earth system data of unprecedented breadth, accuracy and utility for hydrologic analysis.

What is the role of historical anthropogenically-induced land-cover change on the surface climate of West Africa? Results from the LUCID intercomparison project

NASA Astrophysics Data System (ADS)

Souleymane, S.

2015-12-01

West Africa has been highlighted as a hot spot of land surface-atmosphere interactions. This study analyses the outputs of the project Land-Use and Climate, IDentification of Robust Impacts (LUCID) over West Africa. LUCID used seven atmosphere-land models with a common experimental design to explore the impacts of Land Use induced Land Cover Change (LULCC) that are robust and consistent across the climate models. Focusing the analysis on Sahel and Guinea, this study shows that, even though the seven climate models use the same atmospheric and land cover forcing, there are significant differences of West African Monsoon variability across the climate models. The magnitude of that variability differs significantly from model to model resulting two major "features": (1) atmosphere dynamics models; (2) how the land-surface functioning is parameterized in the Land surface Model, in particular regarding the evapotranspiration partitioning within the different land-cover types, as well as the role of leaf area index (LAI) in the flux calculations and how strongly the surface is coupled to the atmosphere. The major role that the models'sensitivity to land-cover perturbations plays in the resulting climate impacts of LULCC has been analysed in this study. The climate models show, however, significant differences in the magnitude and the seasonal partitioning of the temperature change. The LULCC induced cooling is directed by decreases in net shortwave radiation that reduced the available energy (QA) (related to changes in land-cover properties other than albedo, such as LAI and surface roughness), which decreases during most part of the year. The biophysical impacts of LULCC were compared to the impact of elevated greenhouse gases resulting changes in sea surface temperatures and sea ice extent (CO2SST). The results show that the surface cooling (related a decrease in QA) induced by the biophysical effects of LULCC are insignificant compared to surface warming (related an increase in QA), which is induced by the regional significance effect of CO2SST due to a small LULCC imposed. In contrast, the decrease of surface water balance resulting from LULCC effect is a similar sign to those resulting from CO2SST but the signal resulting of the biophysical effects of LULCC is stronger than the regional CO2SST impact.

Quantifying the impact of land use change on hydrological responses in the Upper Ganga Basin, India

NASA Astrophysics Data System (ADS)

Tsarouchi, Georgia-Marina; Mijic, Ana; Moulds, Simon; Chawla, Ila; Mujumdar, Pradeep; Buytaert, Wouter

2013-04-01

Quantifying how changes in land use affect the hydrological response at the river basin scale is a challenge in hydrological science and especially in the tropics where many regions are considered data sparse. Earlier work by the authors developed and used high-resolution, reconstructed land cover maps for northern India, based on satellite imagery and historic land-use maps for the years 1984, 1998 and 2010. Large-scale land use changes and their effects on landscape patterns can impact water supply in a watershed by altering hydrological processes such as evaporation, infiltration, surface runoff, groundwater discharge and stream flow. Three land use scenarios were tested to explore the sensitivity of the catchment's response to land use changes: (a) historic land use of 1984 with integrated evolution to 2010; (b) land use of 2010 remaining stable; and (c) hypothetical future projection of land use for 2030. The future scenario was produced with Markov chain analysis and generation of transition probability matrices, indicating transition potentials from one land use class to another. The study used socio-economic (population density), geographic (distances to roads and rivers, and location of protected areas) and biophysical drivers (suitability of soil for agricultural production, slope, aspect, and elevation). The distributed version of the land surface model JULES was integrated at a resolution of 0.01° for the years 1984 to 2030. Based on a sensitivity analysis, the most sensitive parameters were identified. Then, the model was calibrated against measured daily stream flow data. The impact of land use changes was investigated by calculating annual variations in hydrological components, differences in annual stream flow and surface runoff during the simulation period. The land use changes correspond to significant differences on the long-term hydrologic fluxes for each scenario. Once analysed from a future water resources perspective, the results will be beneficial in constructing decision support tools for regional land-use planning and management.

Extensions and applications of a second-order landsurface parameterization

NASA Technical Reports Server (NTRS)

Andreou, S. A.; Eagleson, P. S.

1983-01-01

Extensions and applications of a second order land surface parameterization, proposed by Andreou and Eagleson are developed. Procedures for evaluating the near surface storage depth used in one cell land surface parameterizations are suggested and tested by using the model. Sensitivity analysis to the key soil parameters is performed. A case study involving comparison with an "exact" numerical model and another simplified parameterization, under very dry climatic conditions and for two different soil types, is also incorporated.

Area-averaged evapotranspiration over a heterogeneous land surface: aggregation of multi-point EC flux measurements with a high-resolution land-cover map and footprint analysis

NASA Astrophysics Data System (ADS)

Xu, Feinan; Wang, Weizhen; Wang, Jiemin; Xu, Ziwei; Qi, Yuan; Wu, Yueru

2017-08-01

The determination of area-averaged evapotranspiration (ET) at the satellite pixel scale/model grid scale over a heterogeneous land surface plays a significant role in developing and improving the parameterization schemes of the remote sensing based ET estimation models and general hydro-meteorological models. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER) flux matrix provided a unique opportunity to build an aggregation scheme for area-averaged fluxes. On the basis of the HiWATER flux matrix dataset and high-resolution land-cover map, this study focused on estimating the area-averaged ET over a heterogeneous landscape with footprint analysis and multivariate regression. The procedure is as follows. Firstly, quality control and uncertainty estimation for the data of the flux matrix, including 17 eddy-covariance (EC) sites and four groups of large-aperture scintillometers (LASs), were carefully done. Secondly, the representativeness of each EC site was quantitatively evaluated; footprint analysis was also performed for each LAS path. Thirdly, based on the high-resolution land-cover map derived from aircraft remote sensing, a flux aggregation method was established combining footprint analysis and multiple-linear regression. Then, the area-averaged sensible heat fluxes obtained from the EC flux matrix were validated by the LAS measurements. Finally, the area-averaged ET of the kernel experimental area of HiWATER was estimated. Compared with the formerly used and rather simple approaches, such as the arithmetic average and area-weighted methods, the present scheme is not only with a much better database, but also has a solid grounding in physics and mathematics in the integration of area-averaged fluxes over a heterogeneous surface. Results from this study, both instantaneous and daily ET at the satellite pixel scale, can be used for the validation of relevant remote sensing models and land surface process models. Furthermore, this work will be extended to the water balance study of the whole Heihe River basin.

Assessing uncertainty and sensitivity of model parameterizations and parameters in WRF affecting simulated surface fluxes and land-atmosphere coupling over the Amazon region

NASA Astrophysics Data System (ADS)

Qian, Y.; Wang, C.; Huang, M.; Berg, L. K.; Duan, Q.; Feng, Z.; Shrivastava, M. B.; Shin, H. H.; Hong, S. Y.

2016-12-01

This study aims to quantify the relative importance and uncertainties of different physical processes and parameters in affecting simulated surface fluxes and land-atmosphere coupling strength over the Amazon region. We used two-legged coupling metrics, which include both terrestrial (soil moisture to surface fluxes) and atmospheric (surface fluxes to atmospheric state or precipitation) legs, to diagnose the land-atmosphere interaction and coupling strength. Observations made using the Department of Energy's Atmospheric Radiation Measurement (ARM) Mobile Facility during the GoAmazon field campaign together with satellite and reanalysis data are used to evaluate model performance. To quantify the uncertainty in physical parameterizations, we performed a 120 member ensemble of simulations with the WRF model using a stratified experimental design including 6 cloud microphysics, 3 convection, 6 PBL and surface layer, and 3 land surface schemes. A multiple-way analysis of variance approach is used to quantitatively analyze the inter- and intra-group (scheme) means and variances. To quantify parameter sensitivity, we conducted an additional 256 WRF simulations in which an efficient sampling algorithm is used to explore the multiple-dimensional parameter space. Three uncertainty quantification approaches are applied for sensitivity analysis (SA) of multiple variables of interest to 20 selected parameters in YSU PBL and MM5 surface layer schemes. Results show consistent parameter sensitivity across different SA methods. We found that 5 out of 20 parameters contribute more than 90% total variance, and first-order effects dominate comparing to the interaction effects. Results of this uncertainty quantification study serve as guidance for better understanding the roles of different physical processes in land-atmosphere interactions, quantifying model uncertainties from various sources such as physical processes, parameters and structural errors, and providing insights for improving the model physics parameterizations.

Demonstrating the Importance of `` Good" Models of Land Surface Hydrological Processes

NASA Astrophysics Data System (ADS)

Pitman, A.; Irannejad, P.; McGuffie, K.; Henderson-Sellers, A.

2003-12-01

To reduce the uncertainty in the prediction of land surface climates,, the Atmospheric Model Intercomparison Project (AMIP) Diagnostic Subproject 12 (DSP 12) and the Project for Intercomparison of Land-surface Parameterisation Schemes (PILPS) have analysed dependence of climate simulations on the land-surface schemes (LSSs). This analysis has comprised three efforts: (i) proving that LSSs matter in coupled simulations; (ii) investigating whether improvements in LSSs have occurred over time; and (iii) searching for novel means of validating LSS predictions. In the first, Irannejad et al. (2003) introduce a novel method for evaluating the dependence of 19 AMIP AGCMs' LH on the LSS by excluding the impact of the atmosphere. Pseudo LSSs (PLSSs) for LH in the form of multi-variable linear models expressing mean monthly LH as a function of atmospheric forcing are developed. Analysis over three large and climatically diverse river basins shows estimates of mean annual LH from the PLSSs agreeing well with the AGCMs' simulations. RMS errors range from 0.4 to 2.2 W m-2 depending on the region and the AGCM. When the PLSSs are driven by single atmospheric forcings, different LSSs behave differently, and the variability of mean annual LH among AGCMs increases. The second strand of our investigation uncovered a clear generational sequence of land-surface schemes: first generation 'no canopy'; second generation ` SiBlings'; and ` recent schemes'. We conclude that although continental surface modelling has improved over the last 30 years, full confidence remains elusive, in part due to tuning to available observations. Finally, we show that stable water isotopes challenge predictions of evaporation and condensation processes. These three-pronged findings prove that LSSs are important to AGCM and coupled climate predictions; demonstrate that new, or changed, land-surface components increase diversity among simulations; underline the need for validation data and also challenge current parameterisations with novel observations.

The influences of land use and land cover on climate; an analysis of the Washington-Baltimore area that couples remote sensing with numerical simulation

USGS Publications Warehouse

Pease, R.W.; Jenner, C.B.; Lewis, J.E.

1980-01-01

The Sun drives the atmospheric heat engine by warming the terrestrial surface which in turn warms the atmosphere above. Climate, therefore, is significantly controlled by complex interaction of energy flows near and at the terrestrial surface. When man alters this delicate energy balance by his use of the land, he may alter his climatic environment as well. Land use climatology has emerged as a discipline in which these energy interactions are studied; first, by viewing the spatial distributions of their surface manifestations, and second, by analyzing the energy exchange processes involved. Two new tools for accomplishing this study are presented: one that can interpret surface energy exchange processes from space, and another that can simulate the complex of energy transfers by a numerical simulation model. Use of a satellite-borne multispectral scanner as an imaging radiometer was made feasible by devising a gray-window model that corrects measurements made in space for the effects of the atmosphere in the optical path. The simulation model is a combination of mathematical models of energy transfer processes at or near the surface. Integration of these two analytical approaches was applied to the Washington-Baltimore area to coincide with the August 5, 1973, Skylab 3 overpass which provided data for constructing maps of the energy characteristics of the Earth's surface. The use of the two techniques provides insights into the relationship of climate to land use and land cover and in predicting alterations of climate that may result from alterations of the land surface.

Rational Use of Land Resource During the Implementation of Transportless System of Coal Strata Surface Mining

NASA Astrophysics Data System (ADS)

Gvozdkova, T.; Tyulenev, M.; Zhironkin, S.; Trifonov, V. A.; Osipov, Yu M.

2017-01-01

Surface mining and open pits engineering affect the environment in a very negative way. Among other pollutions that open pits make during mineral deposits exploiting, particular problem is the landscape changing. Along with converting the land into pits, surface mining is connected with pilling dumps that occupy large ground. The article describes an analysis of transportless methods of several coal seams strata surface mining, applied for open pits of South Kuzbass coal enterprises (Western Siberia, Russia). To improve land-use management of open pit mining enterprises, the characteristics of transportless technological schemes for several coal seams strata surface mining are highlighted and observed. These characteristics help to systematize transportless open mining technologies using common criteria that characterize structure of the bottom part of a strata and internal dumping schemes. The schemes of transportless systems of coal strata surface mining implemented in South Kuzbass are given.

Atmospheric sensitivity to land surface changes: comparing the impact of albedo, roughness, and evaporative resistance on near-surface air temperature using an idealized land model.

NASA Astrophysics Data System (ADS)

Lague, M. M.; Swann, A. L. S.; Bonan, G. B.

2017-12-01

Past studies have demonstrated how changes in vegetation can impact the atmosphere; however, it is often difficult to identify the exact physical pathway through which vegetation changes drive an atmospheric response. Surface properties (such as vegetation color, or height) control surface energy fluxes, which feed back on the atmosphere on both local and global scales by modifying temperatures, cloud cover, and energy gradients. Understanding how land surface properties influence energy fluxes is crucial for improving our understanding of how vegetation change - past, present, and future - impacts the atmosphere, global climate, and people. We explore the sensitivity of the atmosphere to perturbations of three land surface properties - albedo, roughness, and evaporative resistance - using an idealized land model coupled to an Earth System Model. We derive a relationship telling us how large a change in each surface property is required to drive a local 0.1 K change in 2m air temperature. Using this idealized framework, we are able to separate the influence on the atmosphere of each individual surface property. We demonstrate that the impact of each surface property on the atmosphere is spatially variable - that is, a similar change in vegetation can have different climate impacts if made in different locations. This analysis not only improves our understanding of how the land system can influence climate, but also provides us with a set of theoretical limits on the potential climate impact of arbitrary vegetation change (natural or anthropogenic).

Impact of irrigation over India on the land surface fluxes

NASA Astrophysics Data System (ADS)

de Rosnay, P. R.; Polcher, J. P.; Laval, K. L.; Sabre, M. S.

2003-04-01

Irrigation is the main water user in the world with 87 % of the global water consumption being attributed to use on irrigated crop land. There are large spatial variations of the irrigated areas, from 68 % in Asia and 16 % in America, 10 % in Europe and the remaining in Africa and Australia. India is the most important irrigating country in the world with a gross irrigation requirement estimated by the FAO at 457 cubic km by year. The environmental impacts of irrigation are very important: irrigation causes the soil salinization, it affects the water quality and ecology, and increases the incidence of water related diseases. Irrigation is also expected to affect the the land surface energy budget, and thereby the climate system. The work presented here is conducted in the framework of the PROMISE European project. It aims to analyze the sensitivity of the land surface fluxes to the intensive irrigation over Indian peninsula. Numerical experiments are conducted with the land surface scheme ORCHIDEE of the Laboratoire de Meteorologie Dynamique, with a 1 degree spatial resolution. Two 2years simulations, forced by the ISLSCP (1987-88) data sets, are compared, with and without irrigation. The analysis focuses on the effect of land irrigation on the surface fluxes (partition of energy between latent and sensible fluxes), and the river flow.

Assessing the long-term effects of land use changes on runoff patterns and food production in a large lake watershed with policy implications.

PubMed

Sun, Zhandong; Lotz, Tom; Chang, Ni-Bin

2017-12-15

Effects of land use development on runoff patterns are salient at a hydrological response unit scale. However, quantitative analysis at the watershed scale is still a challenge due to the complex spatial heterogeneity of the upstream and downstream hydrological relationships and the inherent structure of drainage systems. This study aims to use the well-calibrated Soil and Water Assessment Tool (SWAT) to assess the response of hydrological processes under different land use scenarios in a large lake watershed (Lake Dongting) in the middle Yangtze River basin in China. Based on possible land use changes, scale-dependent land use scenarios were developed and parameters embedded in SWAT were calibrated and validated for hydrological systems analysis. This approach leads to the simulation of the land use change impacts on the hydrological cycle. Results indicated that evapotranspiration, surface runoff, groundwater flow, and water yield were affected by the land use change scenarios in different magnitudes. Overall, changes of land use and land cover have significant impacts on runoff patterns at the watershed scale in terms of both the total water yield (i.e., groundwater flow, surface runoff, and interflow, minus transmission losses) and the spatial distribution of runoff. The changes in runoff distribution were resulted in opposite impacts within the two land use scenarios including forest and agriculture. Water yield has a decrease of 1.8 percent in the forest-prone landscape scenario and an increase of 4.2 percent in the agriculture-rich scenario during the simulated period. Surface runoff was the most affected component in the hydrological cycle. Whereas surface runoff as part of water yield has a decrease of 8.2 percent in the forest- prone landscape scenario, there is an increase of 8.6 percent in the agriculture-rich landscape scenario. Different runoff patterns associated with each land use scenario imply the potential effect on flood or drought mitigation policy. Based on the results, key areas were identified to show that hydrological extreme mitigation and flood control can be coordinated by some land use regulations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Investigating the role of the land surface in explaining the interannual variation of the net radiation balance over the Western Sahara and sub-Sahara

NASA Technical Reports Server (NTRS)

Smith, Eric A.; Nicholson, Sharon

1987-01-01

The status of the data sets is discussed. Progress was made in both data analysis and modeling areas. The atmospheric and land surface contributions to the net radiation budget over the Sahara-Sahel region is being decoupled. The interannual variability of these two processes was investigated and this variability related to seasonal rainfall fluctuations. A modified Barnes objective analysis scheme was developed which uses an eliptic scan pattern and a 3-pass iteration of the difference fields.

A Multi-scale Approach to Urban Thermal Analysis

NASA Technical Reports Server (NTRS)

Gluch, Renne; Quattrochi, Dale A.

2005-01-01

An environmental consequence of urbanization is the urban heat island effect, a situation where urban areas are warmer than surrounding rural areas. The urban heat island phenomenon results from the replacement of natural landscapes with impervious surfaces such as concrete and asphalt and is linked to adverse economic and environmental impacts. In order to better understand the urban microclimate, a greater understanding of the urban thermal pattern (UTP), including an analysis of the thermal properties of individual land covers, is needed. This study examines the UTP by means of thermal land cover response for the Salt Lake City, Utah, study area at two scales: 1) the community level, and 2) the regional or valleywide level. Airborne ATLAS (Advanced Thermal Land Applications Sensor) data, a high spatial resolution (10-meter) dataset appropriate for an environment containing a concentration of diverse land covers, are used for both land cover and thermal analysis at the community level. The ATLAS data consist of 15 channels covering the visible, near-IR, mid-IR and thermal-IR wavelengths. At the regional level Landsat TM data are used for land cover analysis while the ATLAS channel 13 data are used for the thermal analysis. Results show that a heat island is evident at both the community and the valleywide level where there is an abundance of impervious surfaces. ATLAS data perform well in community level studies in terms of land cover and thermal exchanges, but other, more coarse-resolution data sets are more appropriate for large-area thermal studies. Thermal response per land cover is consistent at both levels, which suggests potential for urban climate modeling at multiple scales.

Exploring new topography-based subgrid spatial structures for improving land surface modeling

DOE PAGES

Tesfa, Teklu K.; Leung, Lai-Yung Ruby

2017-02-22

Topography plays an important role in land surface processes through its influence on atmospheric forcing, soil and vegetation properties, and river network topology and drainage area. Land surface models with a spatial structure that captures spatial heterogeneity, which is directly affected by topography, may improve the representation of land surface processes. Previous studies found that land surface modeling, using subbasins instead of structured grids as computational units, improves the scalability of simulated runoff and streamflow processes. In this study, new land surface spatial structures are explored by further dividing subbasins into subgrid structures based on topographic properties, including surface elevation,more » slope and aspect. Two methods (local and global) of watershed discretization are applied to derive two types of subgrid structures (geo-located and non-geo-located) over the topographically diverse Columbia River basin in the northwestern United States. In the global method, a fixed elevation classification scheme is used to discretize subbasins. The local method utilizes concepts of hypsometric analysis to discretize each subbasin, using different elevation ranges that also naturally account for slope variations. The relative merits of the two methods and subgrid structures are investigated for their ability to capture topographic heterogeneity and the implications of this on representations of atmospheric forcing and land cover spatial patterns. Results showed that the local method reduces the standard deviation (SD) of subgrid surface elevation in the study domain by 17 to 19 % compared to the global method, highlighting the relative advantages of the local method for capturing subgrid topographic variations. The comparison between the two types of subgrid structures showed that the non-geo-located subgrid structures are more consistent across different area threshold values than the geo-located subgrid structures. Altogether the local method and non-geo-located subgrid structures effectively and robustly capture topographic, climatic and vegetation variability, which is important for land surface modeling.« less

Exploring new topography-based subgrid spatial structures for improving land surface modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tesfa, Teklu K.; Leung, Lai-Yung Ruby

Topography plays an important role in land surface processes through its influence on atmospheric forcing, soil and vegetation properties, and river network topology and drainage area. Land surface models with a spatial structure that captures spatial heterogeneity, which is directly affected by topography, may improve the representation of land surface processes. Previous studies found that land surface modeling, using subbasins instead of structured grids as computational units, improves the scalability of simulated runoff and streamflow processes. In this study, new land surface spatial structures are explored by further dividing subbasins into subgrid structures based on topographic properties, including surface elevation,more » slope and aspect. Two methods (local and global) of watershed discretization are applied to derive two types of subgrid structures (geo-located and non-geo-located) over the topographically diverse Columbia River basin in the northwestern United States. In the global method, a fixed elevation classification scheme is used to discretize subbasins. The local method utilizes concepts of hypsometric analysis to discretize each subbasin, using different elevation ranges that also naturally account for slope variations. The relative merits of the two methods and subgrid structures are investigated for their ability to capture topographic heterogeneity and the implications of this on representations of atmospheric forcing and land cover spatial patterns. Results showed that the local method reduces the standard deviation (SD) of subgrid surface elevation in the study domain by 17 to 19 % compared to the global method, highlighting the relative advantages of the local method for capturing subgrid topographic variations. The comparison between the two types of subgrid structures showed that the non-geo-located subgrid structures are more consistent across different area threshold values than the geo-located subgrid structures. Altogether the local method and non-geo-located subgrid structures effectively and robustly capture topographic, climatic and vegetation variability, which is important for land surface modeling.« less

Hydrological Response to Land Cover Changes and Human Activities in Arid Regions Using a Geographic Information System and Remote Sensing

PubMed Central

Mahmoud, Shereif H.; Alazba, A. A.

2015-01-01

The hydrological response to land cover changes induced by human activities in arid regions has attracted increased research interest in recent decades. The study reported herein assessed the spatial and quantitative changes in surface runoff resulting from land cover change in the Al-Baha region of Saudi Arabia between 1990 and 2000 using an ArcGIS-surface runoff model and predicted land cover and surface runoff depth in 2030 using Markov chain analysis. Land cover maps for 1990 and 2000 were derived from satellite images using ArcGIS 10.1. The findings reveal a 26% decrease in forest and shrubland area, 28% increase in irrigated cropland, 1.5% increase in sparsely vegetated land and 0.5% increase in bare soil between 1990 and 2000. Overall, land cover changes resulted in a significant decrease in runoff depth values in most of the region. The decrease in surface runoff depth ranged from 25-106 mm/year in a 7020-km2 area, whereas the increase in such depth reached only 10 mm/year in a 243-km2 area. A maximum increase of 73 mm/year was seen in a limited area. The surface runoff depth decreased to the greatest extent in the central region of the study area due to the huge transition in land cover classes associated with the construction of 25 rainwater harvesting dams. The land cover prediction revealed a greater than twofold increase in irrigated cropland during the 2000-2030 period, whereas forest and shrubland are anticipated to occupy just 225 km2 of land area by 2030, a significant decrease from the 747 km2 they occupied in 2000. Overall, changes in land cover are predicted to result in an annual increase in irrigated cropland and dramatic decline in forest area in the study area over the next few decades. The increase in surface runoff depth is likely to have significant implications for irrigation activities. PMID:25923712

Thermal Band Analysis of Agricultural Land Use and its Effects on Bioclimatic Comfort: The Case of Pasinler

NASA Astrophysics Data System (ADS)

Avdan, Uǧur; Demircioglu Yildiz, Nalan; Dagliyar, Ayse; Yigit Avdan, Zehra; Yilmaz, Sevgi

2014-05-01

Resolving the problems that arise due to the land use are not suitable for the purpose in the rural and urban areas most suitable for land use of parameters to be determined. Unintended and unplanned developments in the use of agricultural land in our country caused increases the losses by soil erosion. In this study, Thermal Band analysis is made in Pasinler city center with the aim of identifying bioclimatic comfort values of the different agricultural area. Satellite images can be applied for assessing the thermal urban environment as well as for defining heat islands in agricultural areas. In this context, temperature map is tried to be produced with land surface temperature (LST) analysis made on Landsat TM5 satellite image. The Landsat 5 images was obtained from USGS for the study area. Using Landsat bands of the study area was mapped by supervised classification with the maximum likelihood classification algorithm of ERDAS imagine 2011 software. Normalized Difference Vegetation Index (NDVI) image was produced by using Landsat images. The digital number of the Landsat thermal infrared band (10.40 - 12.50 µm) is converted to the spectral radiance. The surface emissivity was calculated by using NDVI. The spatial pattern of land surface temperature in the study area is taken to characterize their local effects on agricultural land. Areas having bioclimatic comfort and ecologically urbanized, are interpreted with different graphical presentation technics. The obtained results are important because they create data bases for sustainable urban planning and provide a direction for planners and governors. As a result of rapid changes in land use, rural ecosystems and quality of life are deteriorated and decreased. In the presence of increased building density, for the comfortable living of people natural and cultural resources should be analyzed in detail. For that reason, optimal land use planning should be made in rural area.

An Analysis of Inter-annual Variability and Uncertainty of Continental Surface Heat Fluxes

NASA Astrophysics Data System (ADS)

Huang, S. Y.; Deng, Y.; Wang, J.

2016-12-01

The inter-annual variability and the corresponding uncertainty of land surface heat fluxes during the first decade of the 21st century are re-evaluated at continental scale based on the heat fluxes estimated by the maximum entropy production (MEP) model. The MEP model predicted heat fluxes are constrained by surface radiation fluxes, automatically satisfy surface energy balance, and are independent of temperature/moisture gradient, wind speed, and roughness lengths. The surface radiation fluxes and temperature data from Clouds and the Earth's Radiant Energy System and the surface specific humidity data from Modern-Era Retrospective analysis for Research and Applications were used to reproduce the global surface heat fluxes with land-cover data from the NASA Energy and Water cycle Study (NEWS). Our analysis shows that the annual means of continental latent heat fluxes have increasing trends associated with increasing trends in surface net radiative fluxes. The sensible heat fluxes also have increasing trends over most continents except for South America. Ground heat fluxes have little trends. The continental-scale analysis of the MEP fluxes are compared with other existing global surface fluxes data products and the implications of the results for inter-annual to decadal variability of regional surface energy budget are discussed.

Annual Cycle of Surface Longwave Radiation

NASA Technical Reports Server (NTRS)

Mlynczak, Pamela E.; Smith, G. Louis; Wilber, Anne C.; Stackhouse, Paul W.

2011-01-01

The annual cycles of upward and downward longwave fluxes at the Earth s surface are investigated by use of the NASA/GEWEX Surface Radiation Budget Data Set. Because of the immense difference between the heat capacity of land and ocean, the surface of Earth is partitioned into these two categories. Principal component analysis is used to quantify the annual cycles. Over land, the first principal component describes over 95% of the variance of the annual cycle of the upward and downward longwave fluxes. Over ocean the first term describes more than 87% of these annual cycles. Empirical orthogonal functions show the corresponding geographical distributions of these cycles. Phase plane diagrams of the annual cycles of upward longwave fluxes as a function of net shortwave flux show the thermal inertia of land and ocean.

Temporal change and its spatial variety on land surface temperature and land use changes in the Red River Delta, Vietnam, using MODIS time-series imagery.

PubMed

Van Nguyen, On; Kawamura, Kensuke; Trong, Dung Phan; Gong, Zhe; Suwandana, Endan

2015-07-01

Temporal changes in the land surface temperature (LST) in urbanization areas are important for studying an urban heat island (UHI) and regional climate change. This study examined the LST trends under different land use categories in the Red River Delta, Vietnam, using the Moderate Resolution Imaging Spectroradiometer (MODIS) LST product (MOD11A2) and land cover type product (MCD12Q1) for 11 years (2002-2012). Smoothened time-series MODIS LST data were reconstructed by the Harmonic Analysis of Time Series (HANTS) algorithm. The reconstructed LST (maximum and minimum temperatures) was assessed using the hourly air temperature dataset in two land-based meteorological stations provided by the National Climatic Data Center (NCDC). Significant correlation was obtained between MODIS LST and the air temperature for the daytime (R (2) = 0.73, root mean square error [RMSE] = 1.66 °C) and night time (R (2) = 0.84, RMSE = 1.79 °C). Statistical analysis also showed that LST trends vary strongly depending on the land cover type. Forest, wetland, and cropland had a slight tendency to decline, whereas cropland and urban had sharper increases. In urbanized areas, these increasing trends are even more obvious. This is undeniable evidence of the negative impact of urbanization on a surface urban heat island (SUHI) and global warming.

Rapid prototyping of soil moisture estimates using the NASA Land Information System

NASA Astrophysics Data System (ADS)

Anantharaj, V.; Mostovoy, G.; Li, B.; Peters-Lidard, C.; Houser, P.; Moorhead, R.; Kumar, S.

2007-12-01

The Land Information System (LIS), developed at the NASA Goddard Space Flight Center, is a functional Land Data Assimilation System (LDAS) that incorporates a suite of land models in an interoperable computational framework. LIS has been integrated into a computational Rapid Prototyping Capabilities (RPC) infrastructure. LIS consists of a core, a number of community land models, data servers, and visualization systems - integrated in a high-performance computing environment. The land surface models (LSM) in LIS incorporate surface and atmospheric parameters of temperature, snow/water, vegetation, albedo, soil conditions, topography, and radiation. Many of these parameters are available from in-situ observations, numerical model analysis, and from NASA, NOAA, and other remote sensing satellite platforms at various spatial and temporal resolutions. The computational resources, available to LIS via the RPC infrastructure, support e- Science experiments involving the global modeling of land-atmosphere studies at 1km spatial resolutions as well as regional studies at finer resolutions. The Noah Land Surface Model, available with-in the LIS is being used to rapidly prototype soil moisture estimates in order to evaluate the viability of other science applications for decision making purposes. For example, LIS has been used to further extend the utility of the USDA Soil Climate Analysis Network of in-situ soil moisture observations. In addition, LIS also supports data assimilation capabilities that are used to assimilate remotely sensed soil moisture retrievals from the AMSR-E instrument onboard the Aqua satellite. The rapid prototyping of soil moisture estimates using LIS and their applications will be illustrated during the presentation.

A Catchment-Based Approach to Modeling Land Surface Processes in a GCM. Part 1; Model Structure

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Suarez, Max J.; Ducharne, Agnes; Stieglitz, Marc; Kumar, Praveen

2000-01-01

A new strategy for modeling the land surface component of the climate system is described. The strategy is motivated by an arguable deficiency in most state-of-the-art land surface models (LSMs), namely the disproportionately higher emphasis given to the formulation of one-dimensional, vertical physics relative to the treatment of horizontal heterogeneity in surface properties -- particularly subgrid soil moisture variability and its effects on runoff generation. The new strategy calls for the partitioning of the continental surface into a mosaic of hydrologic catchments, delineated through analysis of high-resolution surface elevation data. The effective "grid" used for the land surface is therefore not specified by the overlying atmospheric grid. Within each catchment, the variability of soil moisture is related to characteristics of the topography and to three bulk soil moisture variables through a well-established model of catchment processes. This modeled variability allows the partitioning of the catchment into several areas representing distinct hydrological regimes, wherein distinct (regime-specific) evaporation and runoff parameterizations are applied. Care is taken to ensure that the deficiencies of the catchment model in regions of little to moderate topography are minimized.

Investigating Satellite Microwave observations of Precipitation in Different Climate Regimes

NASA Astrophysics Data System (ADS)

Wang, N.; Ferraro, R. R.

2013-12-01

Microwave satellite remote sensing of precipitation over land is a challenging problem due to the highly variable land surface emissivity, which, if not properly accounted for, can be much greater than the precipitation signal itself, especially in light rain/snow conditions. Additionally, surfaces such as arid land, deserts and snow cover have brightness temperature characteristics similar to precipitation Ongoing work by GPM microwave radiometer team is constructing databases through a variety of means, however, there is much uncertainty as to what is the optimal information needed for the wide array of sensors in the GPM constellation, including examination of regional conditions. The original data sets will focus on stratification by emissivity class, surface temperature and total perceptible water. We'll perform sensitivity studies to determine the potential role of ancillary data (e.g., land surface temperature, snow cover/water equivalent, etc.) to improve precipitation estimation over land in different climate regimes, including rain and snow. In other words, what information outside of the radiances can help describe the background and subsequent departures from it that are active precipitating regions? It is likely that this information will be a function of the various precipitation regimes. Statistical methods such as Principal Component Analysis (PCA) will be utilized in this task. Databases from a variety of sources are being constructed. They include existing satellite microwave measurements of precipitating and non-precipitating conditions, ground radar precipitation rate estimates, surface emissivity climatology from satellites, surface temperature and TPW from NWP reanalysis. Results from the analysis of these databases with respect to the microwave precipitation sensitivity to the variety of environmental conditions in different climate regimes will be discussed.

GIS-based Landing-Site Analysis and Passive Decision Support

NASA Astrophysics Data System (ADS)

van Gasselt, Stephan; Nass, Andrea

2016-04-01

The increase of surface coverage and the availability and accessibility of planetary data allow researchers and engineers to remotely perform detailed studies on surface processes and properties, in particular on objects such as Mars and the Moon for which Terabytes of multi-temporal data at multiple spatial resolution levels have become available during the last 15 years. Orbiters, rovers and landers have been returning information and insights into the surface evolution of the terrestrial planets in unprecedented detail. While rover- and lander-based analyses are one major research aim to obtain ground truth, resource exploration or even potential establishment of bases using autonomous platforms are others and they require detailed investigation of settings in order to identify spots on the surface that are suitable for spacecraft to land and operate safely and over a long period of time. What has been done using hardcopy material in the past is today being carried by using either in-house developments or off-the-shelf spatial information system technology which allows to manage, integrate and analyse data as well as visualize and create user-defined reports for performing assessments. Usually, such analyses can be broken down (manually) by considering scientific wishes, engineering boundary conditions, potential hazards and various tertiary constraints. We here (1) review standard tasks of landing site analyses, (2) discuss issues inherently related to the analysis using integrated spatial analysis systems and (3) demonstrate a modular analysis framework for integration of data and for the evaluation of results from individual tasks in order to support decisions for landing-site selection.

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1987-01-01

The overall objectives and strategies of the Center for Remote Sensing remain to provide a center for excellence for multidisciplinary scientific expertise to address land-related global habitability and earth observing systems scientific issues. Specific research projects that were underway during the final contract period include: digital classification of coniferous forest types in Michigan's northern lower peninsula; a physiographic ecosystem approach to remote classification and mapping; land surface change detection and inventory; analysis of radiant temperature data; and development of methodologies to assess possible impacts of man's changes of land surface on meteorological parameters. Significant progress in each of the five project areas has occurred. Summaries on each of the projects are provided.

Seasonal-to-Interannual Precipitation Variability and Predictability in a Coupled Land-Atmosphere System

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Suarez, M. J.; Heiser, M.

1998-01-01

In an earlier GCM study, we showed that interactive land surface processes generally contribute more to continental precipitation variance than do variable sea surface temperatures (SSTs). A new study extends this result through an analysis of 16-member ensembles of multi-decade GCM simulations. We can now show that in many regions, although land processes determine the amplitude of the interannual precipitation anomalies, variable SSTs nevertheless control their timing. The GCM data can be processed into indices that describe geographical variations in (1) the potential for seasonal-to-interannual prediction, and (2) the extent to which the predictability relies on the proper representation of land-atmosphere feedback.

Analysis of Summertime Convective Initiation in Central Alabama Using the Land Information System

NASA Technical Reports Server (NTRS)

James, Robert S.; Case, Jonathan L.; Molthan, Andrew L.; Jedlovec, Gary J.

2011-01-01

During the summer months in the southeastern United States, convective initiation presents a frequent challenge to operational forecasters. Thunderstorm development has traditionally been referred to as random due to their disorganized, sporadic appearance and lack of atmospheric forcing. Horizontal variations in land surface characteristics such as soil moisture, soil type, land and vegetation cover could possibly be a focus mechanism for afternoon convection during the summer months. The NASA Land Information System (LIS) provides a stand-alone land surface modeling framework that incorporates these varying soil and vegetation properties, antecedent precipitation, and atmospheric forcing to represent the soil state at high resolution. The use of LIS as a diagnostic tool may help forecasters to identify boundaries in land surface characteristics that could correlate to favored regions of convection initiation. The NASA Shortterm Prediction Research and Transition (SPoRT) team has been collaborating with the National Weather Service Office in Birmingham, AL to help incorporate LIS products into their operational forecasting methods. This paper highlights selected convective case dates from summer 2009 when synoptic forcing was weak, and identifies any boundaries in land surface characteristics that may have contributed to convective initiation. The LIS output depicts the effects of increased sensible heat flux from urban areas on the development of convection, as well as convection along gradients in land surface characteristics and surface sensible and latent heat fluxes. These features may promote mesoscale circulations and/or feedback processes that can either enhance or inhibit convection. With this output previously unavailable to operational forecasters, LIS provides a new tool to forecasters in order to help eliminate the randomness of summertime convective initiation.

LAnd surface remote sensing Products VAlidation System (LAPVAS) and its preliminary application

NASA Astrophysics Data System (ADS)

Lin, Xingwen; Wen, Jianguang; Tang, Yong; Ma, Mingguo; Dou, Baocheng; Wu, Xiaodan; Meng, Lumin

2014-11-01

The long term record of remote sensing product shows the land surface parameters with spatial and temporal change to support regional and global scientific research widely. Remote sensing product with different sensors and different algorithms is necessary to be validated to ensure the high quality remote sensing product. Investigation about the remote sensing product validation shows that it is a complex processing both the quality of in-situ data requirement and method of precision assessment. A comprehensive validation should be needed with long time series and multiple land surface types. So a system named as land surface remote sensing product is designed in this paper to assess the uncertainty information of the remote sensing products based on a amount of in situ data and the validation techniques. The designed validation system platform consists of three parts: Validation databases Precision analysis subsystem, Inter-external interface of system. These three parts are built by some essential service modules, such as Data-Read service modules, Data-Insert service modules, Data-Associated service modules, Precision-Analysis service modules, Scale-Change service modules and so on. To run the validation system platform, users could order these service modules and choreograph them by the user interactive and then compete the validation tasks of remote sensing products (such as LAI ,ALBEDO ,VI etc.) . Taking SOA-based architecture as the framework of this system. The benefit of this architecture is the good service modules which could be independent of any development environment by standards such as the Web-Service Description Language(WSDL). The standard language: C++ and java will used as the primary programming language to create service modules. One of the key land surface parameter, albedo, is selected as an example of the system application. It is illustrated that the LAPVAS has a good performance to implement the land surface remote sensing product validation.

The Face of Alaska: A Look at Land Cover and the Potential Drivers of Change

USGS Publications Warehouse

Jones, Benjamin M.

2008-01-01

The purpose of this report is to provide statewide baseline information on the status and potential drivers of land-cover change in Alaska. The information gathered for this report is based on a review and analysis of published literature and consists of prominent factors contributing to the current state of the land surface of Alaska as well as a synthesis of information about the status and trends of the factors affecting the land surface of Alaska. The land surface of Alaska is sparsely populated and the impacts from humans are far less extensive when compared to the contiguous United States. The changes in the population and the economy of Alaska have historically been driven by boom and bust cycles, primarily from mineral discoveries, logging, military expansion, and oil and gas development; however, the changes as a result of these factors have occurred in relatively small, localized areas. Many of the large-scale statewide changes taking place in the land surface however, are a result of natural or climate driven processes as opposed to direct anthropogenic activities. In recent times, reports such as this have become increasingly useful as a means of synthesizing information about the magnitude and frequency of changes imparted by natural and anthropogenic forces. Thus, it is essential to assess the current state of the land surface of Alaska and identify apparent trends in the surficial changes that are occurring in order to be prepared for the future.

Mars Science Laboratory Heatshield Flight Data Analysis

NASA Technical Reports Server (NTRS)

Mahzari, Milad; White, Todd

2017-01-01

NASA Mars Science Laboratory (MSL), which landed the Curiosity rover on the surface of Mars on August 5th, 2012, was the largest and heaviest Mars entry vehicle representing a significant advancement in planetary entry, descent and landing capability. Hypersonic flight performance data was collected using MSLs on-board sensors called Mars Entry, Descent and Landing Instrumentation (MEDLI). This talk will give an overview of MSL entry and a description of MEDLI sensors. Observations from flight data will be examined followed by a discussion of analysis efforts to reconstruct surface heating from heatshields in-depth temperature measurements. Finally, a brief overview of MEDLI2 instrumentation, which will fly on NASAs Mars2020 mission, will be presented with a discussion on how lessons learned from MEDLI data affected the design of MEDLI2 instrumentation.

Simulating effects of microtopography on wetland specific yield and hydroperiod

USGS Publications Warehouse

Summer, David M.; Wang, Xixi

2011-01-01

Specific yield and hydroperiod have proven to be useful parameters in hydrologic analysis of wetlands. Specific yield is a critical parameter to quantitatively relate hydrologic fluxes (e.g., rainfall, evapotranspiration, and runoff) and water level changes. Hydroperiod measures the temporal variability and frequency of land-surface inundation. Conventionally, hydrologic analyses used these concepts without considering the effects of land surface microtopography and assumed a smoothly-varying land surface. However, these microtopographic effects could result in small-scale variations in land surface inundation and water depth above or below the land surface, which in turn affect ecologic and hydrologic processes of wetlands. The objective of this chapter is to develop a physically-based approach for estimating specific yield and hydroperiod that enables the consideration of microtopographic features of wetlands, and to illustrate the approach at sites in the Florida Everglades. The results indicate that the physically-based approach can better capture the variations of specific yield with water level, in particular when the water level falls between the minimum and maximum land surface elevations. The suggested approach for hydroperiod computation predicted that the wetlands might be completely dry or completely wet much less frequently than suggested by the conventional approach neglecting microtopography. One reasonable generalization may be that the hydroperiod approaches presented in this chapter can be a more accurate prediction tool for water resources management to meet the specific hydroperiod threshold as required by a species of plant or animal of interest.

Geographic Analysis and Monitoring Program

USGS Publications Warehouse

Campbell, Jon C.

2007-01-01

The surface of the Earth is changing rapidly, at local, regional, national, and global scales, with significant repercussions for people, the economy, and the environment. Some changes have natural causes, such as wildland fires or hurricanes, while other changes on the land, such as resource extraction, agricultural practices, and urban growth, are human-induced processes. There are other types of changes that are a combination of natural and human-induced factors; landslides and floods, for example, are fundamentally natural processes that are often intensified or accelerated by human land use practices. Whatever their cause, land-surface changes can have profound environmental and economic impacts.

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

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory

2010-01-01

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.

An Automated Algorithm for Producing Land Cover Information from Landsat Surface Reflectance Data Acquired Between 1984 and Present

NASA Astrophysics Data System (ADS)

Rover, J.; Goldhaber, M. B.; Holen, C.; Dittmeier, R.; Wika, S.; Steinwand, D.; Dahal, D.; Tolk, B.; Quenzer, R.; Nelson, K.; Wylie, B. K.; Coan, M.

2015-12-01

Multi-year land cover mapping from remotely sensed data poses challenges. Producing land cover products at spatial and temporal scales required for assessing longer-term trends in land cover change are typically a resource-limited process. A recently developed approach utilizes open source software libraries to automatically generate datasets, decision tree classifications, and data products while requiring minimal user interaction. Users are only required to supply coordinates for an area of interest, land cover from an existing source such as National Land Cover Database and percent slope from a digital terrain model for the same area of interest, two target acquisition year-day windows, and the years of interest between 1984 and present. The algorithm queries the Landsat archive for Landsat data intersecting the area and dates of interest. Cloud-free pixels meeting the user's criteria are mosaicked to create composite images for training the classifiers and applying the classifiers. Stratification of training data is determined by the user and redefined during an iterative process of reviewing classifiers and resulting predictions. The algorithm outputs include yearly land cover raster format data, graphics, and supporting databases for further analysis. Additional analytical tools are also incorporated into the automated land cover system and enable statistical analysis after data are generated. Applications tested include the impact of land cover change and water permanence. For example, land cover conversions in areas where shrubland and grassland were replaced by shale oil pads during hydrofracking of the Bakken Formation were quantified. Analytical analysis of spatial and temporal changes in surface water included identifying wetlands in the Prairie Pothole Region of North Dakota with potential connectivity to ground water, indicating subsurface permeability and geochemistry.

A Study of Land Surface Temperature Retrieval and Thermal Environment Distribution Based on Landsat-8 in Jinan City

NASA Astrophysics Data System (ADS)

Dong, Fang; Chen, Jian; Yang, Fan

2018-01-01

Based on the medium resolution Landsat 8 OLI/TIRS, the temperature distribution in four seasons of urban area in Jinan City was obtained by using atmospheric correction method for the retrieval of land surface temperature. Quantitative analysis of the spatio-temporal distribution characteristics, development trend of urban thermal environment, the seasonal variation and the relationship between surface temperature and normalized difference vegetation index (NDVI) was studied. The results show that the distribution of high temperature areas is concentrated in Jinan, and there is a tendency to expand from east to west, revealing a negative correlation between land surface temperature distribution and NDVI. So as to provide theoretical references and scientific basis of improving the ecological environment of Jinan City, strengthening scientific planning and making overall plan addressing climate change.

Parametric analysis of synthetic aperture radar data acquired over truck garden vegetation

NASA Technical Reports Server (NTRS)

Wu, S. T.

1984-01-01

An airborne X-band SAR acquired multipolarization and multiflight pass SAR images over a truck garden vegetation area. Based on a variety of land cover and row crop direction variations, the vertical (VV) polarization data contain the highest contrast, while cross polarization contains the least. When the radar flight path is parallel to the row direction, both horizontal (HH) and VV polarization data contain very high return which masks out the specific land cover that forms the row structure. Cross polarization data are not that sensitive to row orientation. The inclusion of like and cross polarization data help delineate special surface features (e.g., row crop against non-row-oriented land cover, very-rough-surface against highly row-oriented surface).

Urban Land: Study of Surface Run-off Composition and Its Dynamics

NASA Astrophysics Data System (ADS)

Palagin, E. D.; Gridneva, M. A.; Bykova, P. G.

2017-11-01

The qualitative composition of urban land surface run-off is liable to significant variations. To study surface run-off dynamics, to examine its behaviour and to discover reasons of these variations, it is relevant to use the mathematical apparatus technique of time series analysis. A seasonal decomposition procedure was applied to a temporary series of monthly dynamics with the annual frequency of seasonal variations in connection with a multiplicative model. The results of the quantitative chemical analysis of surface wastewater of the 22nd Partsjezd outlet in Samara for the period of 2004-2016 were used as basic data. As a result of the analysis, a seasonal pattern of variations in the composition of surface run-off in Samara was identified. Seasonal indices upon 15 waste-water quality indicators were defined. BOD (full), suspended materials, mineralization, chlorides, sulphates, ammonium-ion, nitrite-anion, nitrate-anion, phosphates (phosphorus), iron general, copper, zinc, aluminium, petroleum products, synthetic surfactants (anion-active). Based on the seasonal decomposition of the time series data, the contribution of trends, seasonal and accidental components of the variability of the surface run-off indicators was estimated.

Estimating the relationship between urban 3D morphology and land surface temperature using airborne LiDAR and Landsat-8 Thermal Infrared Sensor data

NASA Astrophysics Data System (ADS)

Lee, J. H.

2015-12-01

Urban forests are known for mitigating the urban heat island effect and heat-related health issues by reducing air and surface temperature. Beyond the amount of the canopy area, however, little is known what kind of spatial patterns and structures of urban forests best contributes to reducing temperatures and mitigating the urban heat effects. Previous studies attempted to find the relationship between the land surface temperature and various indicators of vegetation abundance using remote sensed data but the majority of those studies relied on two dimensional area based metrics, such as tree canopy cover, impervious surface area, and Normalized Differential Vegetation Index, etc. This study investigates the relationship between the three-dimensional spatial structure of urban forests and urban surface temperature focusing on vertical variance. We use a Landsat-8 Thermal Infrared Sensor image (acquired on July 24, 2014) to estimate the land surface temperature of the City of Sacramento, CA. We extract the height and volume of urban features (both vegetation and non-vegetation) using airborne LiDAR (Light Detection and Ranging) and high spatial resolution aerial imagery. Using regression analysis, we apply empirical approach to find the relationship between the land surface temperature and different sets of variables, which describe spatial patterns and structures of various urban features including trees. Our analysis demonstrates that incorporating vertical variance parameters improve the accuracy of the model. The results of the study suggest urban tree planting is an effective and viable solution to mitigate urban heat by increasing the variance of urban surface as well as evaporative cooling effect.

PROCEEDINGS OF THE CROSS DISCIPLINE ECOSYTEM MODELING AND ANALYSIS WORKSHOP

EPA Science Inventory

The complexity of environmental problems we face now and in the future is ever increasing. Process linkages among air, land, surface and subsurface water require interdisciplinary modeling approaches. The dynamics of land use change spurred by population and economic growth, ...

Connecting Satellite Observations with Water Cycle Variables Through Land Data Assimilation: Examples Using the NASA GEOS-5 LDAS

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; De Lannoy, Gabrielle J. M.; Forman, Barton A.; Draper, Clara S.; Liu, Qing

2013-01-01

A land data assimilation system (LDAS) can merge satellite observations (or retrievals) of land surface hydrological conditions, including soil moisture, snow, and terrestrial water storage (TWS), into a numerical model of land surface processes. In theory, the output from such a system is superior to estimates based on the observations or the model alone, thereby enhancing our ability to understand, monitor, and predict key elements of the terrestrial water cycle. In practice, however, satellite observations do not correspond directly to the water cycle variables of interest. The present paper addresses various aspects of this seeming mismatch using examples drawn from recent research with the ensemble-based NASA GEOS-5 LDAS. These aspects include (1) the assimilation of coarse-scale observations into higher-resolution land surface models, (2) the partitioning of satellite observations (such as TWS retrievals) into their constituent water cycle components, (3) the forward modeling of microwave brightness temperatures over land for radiance-based soil moisture and snow assimilation, and (4) the selection of the most relevant types of observations for the analysis of a specific water cycle variable that is not observed (such as root zone soil moisture). The solution to these challenges involves the careful construction of an observation operator that maps from the land surface model variables of interest to the space of the assimilated observations.

Geographic analysis and monitoring at the United States Geological Survey

USGS Publications Warehouse

Findley, J.

2003-01-01

The Geographic Analysis and Monitoring (GAM) Program of the U.S. Geological Survey assesses the Nation's land surface at a variety of spatial and temporal scales to understand the rates, causes, and consequences of natural and human-induced processes and their interactions that affect the landscape over time. The program plays an important role in developing National Map tools and application. The GAM is a science and synthesis program that not only assesses the rates of changes to the Earth's land surface, but also provides reports on the status and trends of the Nation's land resources on a periodic basis, produces a land-use and land- cover database for the periodically updated map and data set-the Geographic Face of the Nation, and conducts research leading to improved understanding and knowledge about geographic processes. Scientific investigations provide comprehensive information needed to understand the environmental, resource, and economic consequences of landscape change. These analyses responds to the needs of resource managers and offers the American public baseline information to help them understand the dynamic nature of our national landscape and to anticipate the opportunities and consequences of our actions.

Impact of land surface conditions on the predictability of hydrologic processes and mountain-valley circulations in the North American Monsoon region

NASA Astrophysics Data System (ADS)

Xiang, T.; Vivoni, E. R.; Gochis, D. J.; Mascaro, G.

2015-12-01

Heterogeneous land surface conditions are essential components of land-atmosphere interactions in regions of complex terrain and have the potential to affect convective precipitation formation. Yet, due to their high complexity, hydrologic processes over mountainous regions are not well understood, and are usually parameterized in simple ways within coupled land-atmosphere modeling frameworks. With the improving model physics and spatial resolution of numerical weather prediction models, there is an urgent need to understand how land surface processes affect local and regional meteorological processes. In the North American Monsoon (NAM) region, the summer rainy season is accompanied by a dramatic greening of mountain ecosystems that adds spatiotemporal variability in vegetation which is anticipated to impact the conditions leading to convection, mountain-valley circulations and mesoscale organization. In this study, we present results from a detailed analysis of a high-resolution (1 km) land surface model, Noah-MP, in a large, mountainous watershed of the NAM region - the Rio Sonora (21,264 km2) in Mexico. In addition to capturing the spatial variations in terrain and soil distributions, recently-developed features in Noah-MP allow the model to read time-varying vegetation parameters derived from remotely-sensed vegetation indices; however, this new implementation has not been fully evaluated. Therefore, we assess the simulated spatiotemporal fields of soil moisture, surface temperature and surface energy fluxes through comparisons to remote sensing products and results from coarser land surface models obtained from the North American Land Data Assimilation System. We focus attention on the impact of vegetation changes along different elevation bands on the diurnal cycle of surface energy fluxes to provide a baseline for future analyses of mountain-valley circulations using a coupled land-atmosphere modeling system. Our study also compares limited streamflow observations in the large watershed to simulations using the terrain and channel routing when Noah-MP is run within the WRF-Hydro modeling framework, with the goals of validating the rainfall-runoff partitioning and translating the spatiotemporal mountain processes into improvements in streamflow predictions.

The Impact of Satellite-Derived Land Surface Temperatures on Numerical Weather Prediction Analyses and Forecasts

NASA Astrophysics Data System (ADS)

Candy, B.; Saunders, R. W.; Ghent, D.; Bulgin, C. E.

2017-09-01

Land surface temperature (LST) observations from a variety of satellite instruments operating in the infrared have been compared to estimates of surface temperature from the Met Office operational numerical weather prediction (NWP) model. The comparisons show that during the day the NWP model can underpredict the surface temperature by up to 10 K in certain regions such as the Sahel and southern Africa. By contrast at night the differences are generally smaller. Matchups have also been performed between satellite LSTs and observations from an in situ radiometer located in Southern England within a region of mixed land use. These matchups demonstrate good agreement at night and suggest that the satellite uncertainties in LST are less than 2 K. The Met Office surface analysis scheme has been adapted to utilize nighttime LST observations. Experiments using these analyses in an NWP model have shown a benefit to the resulting forecasts of near-surface air temperature, particularly over Africa.

A Landscape Indicator Approach to the Identification and Articulation of the Ecological Consequences of Land Cover Change in the Chesapeake Bay Watershed, 1970-2000

USGS Publications Warehouse

Slonecker, Terrence

2008-01-01

The advancement of geographic science in the area of land surface status and trends and land cover change is at the core of the current geographic scientific research of the U.S. Geological Survey (USGS) (McMahon and others, 2005). Perhaps the least developed or articulated aspects of USGS land change science have been the identification and analysis of the ecological consequences of land cover change. Changes in land use and land cover significantly affect the ability of ecosystems to provide essential ecological goods and services, which, in turn, affect the economic, public health, and social benefits that these ecosystems provide. One of the great scientific challenges for geographic science is to understand and calibrate the effects of land use and land cover change and the complex interaction between human and biotic systems at a variety of natural, geographic, and political scales. Understanding the dynamics of land surface change requires an increased understanding of the complex nature of human-environmental systems and will require a suite of scientific tools that include traditional geographic data and analysis methods, such as remote sensing and geographic information systems (GIS), as well as innovative approaches to understanding the dynamics of complex systems. One such approach that has gained much recent scientific attention is the landscape indicator, or landscape assessment, approach, which has been developed with the emergence of the science of landscape ecology.

Revisiting a Hydrological Analysis Framework with International Satellite Land Surface Climatology Project Initiative 2 Rainfall, Net Radiation, and Runoff Fields

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Fekete, Balazs M.; Huffman, George J.; Stackhouse, Paul W.

2006-01-01

The International Satellite Land Surface Climatology Project Initiative 2 (ISLSCP-2) data set provides the data needed to characterize the surface water budget across much of the globe in terms of energy availability (net radiation) and water availability (precipitation) controls. The data, on average, are shown to be consistent with Budyko s decades-old framework, thereby demonstrating the continuing relevance of Budyko s semiempirical relationships. This consistency, however, appears only when a small subset of the data with hydrologically suspicious behavior is removed from the analysis. In general, the precipitation, net radiation, and runoff data also appear consistent in their interannual variability and in the phasing of their seasonal cycles.

Early Evaluation of the VIIRS Calibration, Cloud Mask and Surface Reflectance Earth Data Records

NASA Technical Reports Server (NTRS)

Vermote, Eric; Justice, Chris; Csiszar, Ivan

2014-01-01

Surface reflectance is one of the key products fromVIIRS and as withMODIS, is used in developing several higherorder land products. The VIIRS Surface Reflectance (SR) Intermediate Product (IP) is based on the heritageMODIS Collection 5 product (Vermote, El Saleous, & Justice, 2002). The quality and character of surface reflectance depend on the accuracy of the VIIRS Cloud Mask (VCM), the aerosol algorithms and the adequate calibration of the sensor. The focus of this paper is the early evaluation of the VIIRS SR product in the context of the maturity of the operational processing system, the Interface Data Processing System (IDPS). After a brief introduction, the paper presents the calibration performance and the role of the surface reflectance in calibration monitoring. The analysis of the performance of the cloud mask with a focus on vegetation monitoring (no snow conditions) shows typical problems over bright surfaces and high elevation sites. Also discussed is the performance of the aerosol input used in the atmospheric correction and in particular the artifacts generated by the use of the Navy Aerosol Analysis and Prediction System. Early quantitative results of the performance of the SR product over the AERONET sites showthatwith the fewadjustments recommended, the accuracy iswithin the threshold specifications. The analysis of the adequacy of the SR product (Land PEATE adjusted version) in applications of societal benefits is then presented. We conclude with a set of recommendations to ensure consistency and continuity of the JPSS mission with the MODIS Land Climate Data Record.

Long-Term Effects of Changing Land Use Practices on Surface Water Quality in a Coastal River and Lagoonal Estuary

NASA Astrophysics Data System (ADS)

Rothenberger, Meghan B.; Burkholder, Joann M.; Brownie, Cavell

2009-09-01

The watershed of the Neuse River, a major tributary of the largest lagoonal estuary on the U.S. mainland, has sustained rapid growth of human and swine populations. This study integrated a decade of available land cover and water quality data to examine relationships between land use changes and surface water quality. Geographic Information Systems (GIS) analysis was used to characterize 26 subbasins throughout the watershed for changes in land use during 1992-2001, considering urban, agricultural (cropland, animal as pasture, and densities of confined animal feed operations [CAFOs]), forested, grassland, and wetland categories and numbers of wastewater treatment plants (WWTPs). GIS was also used together with longitudinal regression analysis to identify specific land use characteristics that influenced surface water quality. Total phosphorus concentrations were significantly higher during summer in subbasins with high densities of WWTPs and CAFOs. Nitrate was significantly higher during winter in subbasins with high numbers of WWTPs, and organic nitrogen was higher in subbasins with higher agricultural coverage, especially with high coverage of pastures fertilized with animal manure. Ammonium concentrations were elevated after high precipitation. Overall, wastewater discharges in the upper, increasingly urbanized Neuse basin and intensive swine agriculture in the lower basin have been the highest contributors of nitrogen and phosphorus to receiving surface waters. Although nonpoint sources have been emphasized in the eutrophication of rivers and estuaries such as the Neuse, point sources continue to be major nutrient contributors in watersheds sustaining increasing human population growth. The described correlation and regression analyses represent a rapid, reliable method to relate land use patterns to water quality, and they can be adapted to watersheds in any region.

The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model

NASA Astrophysics Data System (ADS)

Thober, S.; Cuntz, M.; Mai, J.; Samaniego, L. E.; Clark, M. P.; Branch, O.; Wulfmeyer, V.; Attinger, S.

2016-12-01

Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The agility of the models to react to different meteorological conditions is artificially constrained by having hard-coded parameters in their equations. Here we searched for hard-coded parameters in the computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options in addition to the 71 standard parameters. We performed a Sobol' global sensitivity analysis to variations of the standard and hard-coded parameters. The sensitivities of the hydrologic output fluxes latent heat and total runoff, their component fluxes, as well as photosynthesis and sensible heat were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's output fluxes are sensitive to two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for evaporation, which proved to be oversensitive in other land surface models as well. Latent heat and total runoff show very similar sensitivities towards standard and hard-coded parameters. They are sensitive to both soil and plant parameters, which means that model calibrations of hydrologic or land surface models should take both soil and plant parameters into account. Sensible and latent heat exhibit almost the same sensitivities so that calibration or sensitivity analysis can be performed with either of the two. Photosynthesis has almost the same sensitivities as transpiration, which are different from the sensitivities of latent heat. Including photosynthesis and latent heat in model calibration might therefore be beneficial. Surface runoff is sensitive to almost all hard-coded snow parameters. These sensitivities get, however, diminished in total runoff. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Effect of land-applied biosolids on surface-water nutrient yields and groundwater quality in Orange County, North Carolina

USGS Publications Warehouse

Wagner, Chad R.; Fitzgerald, Sharon A.; McSwain, Kristen Bukowski; Harden, Stephen L.; Gurley, Laura N.; Rogers, Shane W.

2015-01-01

The data, analysis, and conclusions associated with this study can be used by regulatory agencies, resource managers, and wastewater-treatment operators to (1) better understand the quantity and characteristics of nutrients, bacteria, metals, and contaminants of emerging concern that are transported away from biosolids land-application fields to surface water and groundwater under current regulations for the purposes of establishing effective total maximum daily loads (TMDLs) and restoring impaired water resources, (2) assess how well existing regulations protect waters of the State and potentially recommend effective changes to regulations or land-application procedures, and (3) establish a framework for developing guidance on effective techniques for monitoring and regulatory enforcement of permitted biosolids land-application fields.

Project ATLANTA (Atlanta Land use Analysis: Temperature and Air Quality): Use of Remote Sensing and Modeling to Analyze How Urban Land Use Change Affects Meteorology and Air Quality Through Time

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.; Estes, Maurice G., Jr.

1999-01-01

This paper presents an overview of Project ATLANTA (ATlanta Land use ANalysis: Temperature and Air-quality) which is an investigation that seeks to observe, measure, model, and analyze how the rapid growth of the Atlanta, Georgia metropolitan area since the early 1970's has impacted the region's climate and air quality. The primary objectives for this research effort are: (1) To investigate and model the relationships between land cover change in the Atlanta metropolitan, and the development of the urban heat island phenomenon through time; (2) To investigate and model the temporal relationships between Atlanta urban growth and land cover change on air quality; and (3) To model the overall effects of urban development on surface energy budget characteristics across the Atlanta urban landscape through time. Our key goal is to derive a better scientific understanding of how land cover changes associated with urbanization in the Atlanta area, principally in transforming forest lands to urban land covers through time, has, and will, effect local and regional climate, surface energy flux, and air quality characteristics. Allied with this goal is the prospect that the results from this research can be applied by urban planners, environmental managers and other decision-makers, for determining how urbanization has impacted the climate and overall environment of the Atlanta area. Multiscaled remote sensing data, particularly high resolution thermal infrared data, are integral to this study for the analysis of thermal energy fluxes across the Atlanta urban landscape.

Disentangling Climate and Land-use Impacts on Grassland Carbon and Water Fluxes

NASA Astrophysics Data System (ADS)

Brunsell, N. A.; Nippert, J. B.

2014-12-01

Regional climate and land cover interact in a complex, non-linear manner to alter the local cycling of mass and energy. It is often difficult to isolate the role of either mechanism on the resultant fluxes. Here, we attempt to isolate these mechanisms through the use of network of 4 Ameriflux eddy covariance towers installed over different land cover and land use classes along a pronounced rainfall gradient. The land cover types include: annually burned C4 grassland, a 4 year burn site experiencing woody encroachment, an abandoned agricultural field and a new perennial agricultural site. We investigated the impact of rainfall variability, drought, and heat waves on the water and carbon budgets using data analysis, remote sensing, and modeling approaches. In addition, we have established a network of mini-meteorological stations at the annually and 4-year burn sites to assess micro-scale variability within the footprints of the towers as a function of topographic position, soil depth and soil water availability. Through the use of a wavelet multiscale decomposition and information theory metrics, we have isolated the role of environmental factors (temperature, humidity, soil moisture, etc.) on the fluxes across the different sites. By applying a similar analysis to model output, we can assess the ability of land-surface models to recreate the observed sensitity. Results indicate the utility of a network of measurement systems used in conjunction with land surface modeling and time series analysis to assess differential impacts to similar regional scale climate forcings. Implications for the role of land cover class in regional and global scale modeling systems will also be discussed.

Variance and Predictability of Precipitation at Seasonal-to-Interannual Timescales

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Suarez, Max J.; Heiser, Mark

1999-01-01

A series of atmospheric general circulation model (AGCM) simulations, spanning a total of several thousand years, is used to assess the impact of land-surface and ocean boundary conditions on the seasonal-to-interannual variability and predictability of precipitation in a coupled modeling system. In the first half of the analysis, which focuses on precipitation variance, we show that the contributions of ocean, atmosphere, and land processes to this variance can be characterized, to first order, with a simple linear model. This allows a clean separation of the contributions, from which we find: (1) land and ocean processes have essentially different domains of influence, i.e., the amplification of precipitation variance by land-atmosphere feedback is most important outside of the regions (mainly in the tropics) that are most affected by sea surface temperatures; and (2) the strength of land-atmosphere feedback in a given region is largely controlled by the relative availability of energy and water there. In the second half of the analysis, the potential for seasonal-to-interannual predictability of precipitation is quantified under the assumption that all relevant surface boundary conditions (in the ocean and on land) are known perfectly into the future. We find that the chaotic nature of the atmospheric circulation imposes fundamental limits on predictability in many extratropical regions. Associated with this result is an indication that soil moisture initialization or assimilation in a seasonal-to-interannual forecasting system would be beneficial mainly in transition zones between dry and humid regions.

Estimation of evapotranspiration for different land covers in a Brazilian semi-arid region: A case study of the Brígida River basin, Brazil

NASA Astrophysics Data System (ADS)

Santos, Celso Augusto Guimarães; Silva, Richarde Marques da; Silva, Alexandro Medeiros; Brasil Neto, Reginaldo Moura

2017-03-01

In this study, the Surface Energy Balance Algorithm for Land (SEBAL) was used to compute the surface albedo, vegetation indices (NDVI, SAVI and LAI), surface temperature, soil heat flux and evapotranspiration (ET) over two contrasting years (dry and wet) in the Brígida River basin, a semi-arid region of north-eastern Brazil. The actual ET was computed during satellite overpass and was integrated for 24 h on a pixel-by-pixel basis for the daily ET distribution. Due to the topographic effects, an attempt was also made to incorporate DEM information to estimate the net radiation. The land cover types identified in the watershed are cropland, bare land, dense canopy, grassland, and caatinga vegetation. In order to study the variation among the biophysical parameters and ET, two-way analysis of variance (ANOVA) was used. The ET calculated by SEBAL ranged between 2.46 and 6.87 mm/day for the dry year (1990) and 1.31 and 6.84 mm/day for the wet year (2009) for the river basin. The results showed that a reduction in vegetation cover is evident in the temporal and spatial analysis over the studied periods in the region and that these facts influence the values of the energy balance and ET. The results showed significant differences in the variables of land cover type and year at the probability level of 0.05 for all land cover types.

A global analysis of the urban heat island effect based on multisensor satellite data

NASA Astrophysics Data System (ADS)

Xiao, J.; Frolking, S. E.; Milliman, T. E.; Schneider, A.; Friedl, M. A.

2017-12-01

Human population is rapidly urbanizing. In much of the world, cities are prone to hotter weather than surrounding rural areas - so-called `urban heat islands' - and this effect can have mortal consequences during heat waves. During the daytime, when the surface energy balance is driven by incoming solar radiation, the magnitude of urban warming is strongly influenced by surface albedo and the capacity to evaporate water (i.e., there is a strong relationship between vegetated land fraction and the ratio of sensible to latent heat loss or Bowen ratio). At nighttime, urban cooling is often inhibited by the thermal inertia of the built environment and anthropogenic heat exhaust from building and transportation energy use. We evaluated a suite of global remote sensing data sets representing a range of urban characteristics against MODIS-derived land-surface temperature differences between urban and surrounding rural areas. We included two new urban datasets in this analysis - MODIS-derived change in global urban extent and global urban microwave backscatter - along with several MODIS standard products and DMSP/OLS nighttime lights time series data. The global analysis spanned a range of urban characteristics that likely influence the magnitude of daytime and/or nighttime urban heat islands - urban size, population density, building density, state of development, impervious fraction, eco-climatic setting. Specifically, we developed new satellite datasets and synthesizing these with existing satellite data into a global database of urban land surface parameters, used two MODIS land surface temperature products to generate time series of daytime and nighttime urban heat island effects for 30 large cities across the globe, and empirically analyzed these data to determine specifically which remote sensing-based characterizations of global urban areas have explanatory power with regard to both daytime and nighttime urban heat islands.

Investigation of Cyprus thermal tenancy using nine year MODIS LST data and Fourier analysis

NASA Astrophysics Data System (ADS)

Skarlatos, D.; Miliaresis, G.; Georgiou, A.

2013-08-01

Land Surface Temperature (LST) is an extremely important parameter that controls the exchange of long wave radiation between surface and atmosphere. It is a good indicator of the energy balance at the Earth's surface and it is one of the key parameters in the physics of land-surface processes on regional as well as global scale. This paper utilizes monthly night and day averaged LST MODIS imagery over Cyprus for a 9 year period. Fourier analysis and Least squares estimation fitting are implemented to analyze mean daily data over Cyprus in an attempt to investigate possible temperature tenancy over these years and possible differences among areas with different land cover and land use, such as Troodos Mountain and Nicosia, the main city in the center of the island. The analysis of data over a long time period, allows questions such as whether there is a tenancy to temperature increase, to be answered in a statistically better way, provided that `noise' is removed correctly. Dealing with a lot of data, always provides a more accurate estimation, but on the other hand, more noise in implemented on the data, especially when dealing with temperature which is subject to daily and annual cycles. A brief description over semi-automated data acquisition and standardization using object-oriented programming and GIS-based techniques, will be presented. The paper fully describes the time series analysis implemented, the Fourier method and how it was used to analyze and filter mean daily data with high frequency. Comparison of mean monthly daily LST against day and night LSTs is also performed over the 9 year period in order to investigate whether use of the extended data series provide significant advantage over short.

Spatial-Temporal Variations of Water Quality and Its Relationship to Land Use and Land Cover in Beijing, China

PubMed Central

Chen, Xiang; Zhou, Weiqi; Pickett, Steward T. A.; Li, Weifeng; Han, Lijian

2016-01-01

Rapid urbanization with intense land use and land cover (LULC) change and explosive population growth has a great impact on water quality. The relationship between LULC characteristics and water quality provides important information for non-point sources (NPS) pollution management. In this study, we first quantified the spatial-temporal patterns of five water quality variables in four watersheds with different levels of urbanization in Beijing, China. We then examined the effects of LULC on water quality across different scales, using Pearson correlation analysis, redundancy analysis, and multiple regressions. The results showed that water quality was improved over the sampled years but with no significant difference (p > 0.05). However, water quality was significantly different among nonurban and both exurban and urban sites (p < 0.05). Forest land was positively correlated with water quality and affected water quality significantly (p < 0.05) within a 200 m buffer zone. Impervious surfaces, water, and crop land were negatively correlated with water quality. Crop land and impervious surfaces, however, affected water quality significantly (p < 0.05) for buffer sizes greater than 800 m. Grass land had different effects on water quality with the scales. The results provide important insights into the relationship between LULC and water quality, and thus for controlling NPS pollution in urban areas. PMID:27128934

Thermophysical Properties of the Phoenix Mars Landing Site Study Regions

NASA Astrophysics Data System (ADS)

Putzig, N. E.; Mellon, M. T.; Golombek, M. P.; Arvidson, R. E.

2006-03-01

Analysis of Phoenix Mars study regions places 4 of 5 in a previously-identified duricrust-dominated thermophysical unit which also contains the Viking and Spirit landing sites. Extrapolation of lander-observed properties to the study regions may be complicated by surface heterogeneity.

Mars Exploration Rovers Entry, Descent, and Landing Trajectory Analysis

NASA Technical Reports Server (NTRS)

Desai, Prasun N.; Knocke, Philip C.

2007-01-01

In this study we present a novel method of land surface classification using surface-reflected GPS signals in combination with digital imagery. Two GPS-derived classification features are merged with visible image data to create terrain-moisture (TM) classes, defined here as visibly identifiable terrain or landcover classes containing a surface/soil moisture component. As compared to using surface imagery alone, classification accuracy is significantly improved for a number of visible classes when adding the GPS-based signal features. Since the strength of the reflected GPS signal is proportional to the amount of moisture in the surface, use of these GPS features provides information about the surface that is not obtainable using visible wavelengths alone. Application areas include hydrology, precision agriculture, and wetlands mapping.

Chemical Analysis of the Moon at the Surveyor VI Landing Site: Preliminary Results.

PubMed

Turkevich, A L; Patterson, J H; Franzgrote, E J

1968-06-07

The alpha-scattering experiment aboard soft-landing Surveyor VI has provided a chemical analysis of the surface of the moon in Sinus Medii. The preliminary results indicate that, within experimental errors, the composition is the same as that found by Surveyor V in Mare Tranquillitatis. This finding suggests that large portions of the lunar maria resemble basalt in composition.

Urban land use monitoring from computer-implemented processing of airborne multispectral data

NASA Technical Reports Server (NTRS)

Todd, W. J.; Mausel, P. W.; Baumgardner, M. F.

1976-01-01

Machine processing techniques were applied to multispectral data obtained from airborne scanners at an elevation of 600 meters over central Indianapolis in August, 1972. Computer analysis of these spectral data indicate that roads (two types), roof tops (three types), dense grass (two types), sparse grass (two types), trees, bare soil, and water (two types) can be accurately identified. Using computers, it is possible to determine land uses from analysis of type, size, shape, and spatial associations of earth surface images identified from multispectral data. Land use data developed through machine processing techniques can be programmed to monitor land use changes, simulate land use conditions, and provide impact statistics that are required to analyze stresses placed on spatial systems.

A study of the utilization of ERTS-1 data from the Wabash River Basin

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Nine projects are defined, five ERTS data applications experiments and four supporting technology tasks. The most significant applications results were achieved in the soil association mapping, earth surface feature identification, and urban land use mapping efforts. Four soil association boundaries were accurately delineated from ERTS-1 imagery. A data bank has been developed to test surface feature classifications obtained from ERTS-1 data. Preliminary forest cover classifications indicated that the number of acres estimated tended to be greater than actually existed by 25%. Urban land use analysis of ERTS-1 data indicated highly accurate classification could be obtained for many urban catagories. The wooded residential category tended to be misclassified as woods or agricultural land. Further statistical analysis revealed that these classes could be separated using sample variance.

Assessment of Spatio-temporal Barren-lands Expansion and Agricultural Adaptation due to Climate Change and Anthropogenic Activity: A Geospatial Approach in Hot Semi-arid Region of Maharashtra State, India

NASA Astrophysics Data System (ADS)

Roy, A.; Inamdar, A. B.

2017-12-01

Major parts of Upper Godavari River Basin are intensely drought prone and climate vulnerable in Maharashtra State, India. The economy of the state depends on the agronomic productivity of this region. So, it is necessary to monitor and regulate the effects of climate change and anthropogenic activity on agricultural land in that region. This study investigates and maps the barren-lands and alteration of agricultural lands, their decadal deviations with the multi-temporal LANDSAT satellite images; and finally quantifies the agricultural adaptations. This work involves the utilization of remote sensing and GIS tools and modeling. First, climatic trend analysis is carried out with dataset obtained from India Meteorological Department. Then, multi-temporal LANDSAT images are classified (Level I, hybrid classification technique are followed) to determine the decadal Land Use Land Cover (LULC) changes and correlated with the agricultural water demand. Finally, various LANDSAT band analysis is conducted to determine irrigated and non-irrigated cropping area estimation and identifying the agricultural adaptations. The analysis of LANDSAT images shows that barren-lands are most increased class during the study period. The overall spatial extent of barren-lands are increased drastically during the study period. The geospatial study (class-to-class conversion study) shows that, most of the conversion of the barren-lands are from the agricultural land and reserve or open forests. The barren-lands are constantly increasing and the agricultural land is linearly decreasing. Hence, there is an inverse correlation between barren-lands and agricultural land. Moreover, there is a shift to non-irrigated and less water demanding crops, from more water demanding crops, which is a noticeable adaptation. The surface-water availability is highly dependent on rainfall and/or climatic conditions. It is changing either way in a random fashion based upon the quantity of rainfall occurred in near preceding years. The agricultural lands are densely replenished around the dams and natural water bodies which serve as the water supply stations for the irrigation purposes. Hence, the study shows there are alteration in LULC, agricultural practices and surface-water availability and expansion of barren-lands.

The Modelling Analysis of the Response of Convective Transport of Energy and Water to Multiscale Surface Heterogeneity over Tibetan Plateau

NASA Astrophysics Data System (ADS)

SUN, G.; Hu, Z.; Ma, Y.; Ma, W.

2017-12-01

The land-atmospheric interactions over a heterogeneous surface is a tricky issue for accurately understanding the energy-water exchanges between land surface and atmosphere. We investigate the vertical transport of energy and water over a heterogeneous land surface in Tibetan Plateau during the evolution of the convective boundary layer using large eddy simulation (WRF_LES). The surface heterogeneity is created according to remote sensing images from high spatial resolution LandSat ETM+ images. The PBL characteristics over a heterogeneous surface are analyzed in terms of secondary circulations under different background wind conditions based on the horizontal and vertical distribution and evolution of wind. The characteristics of vertical transport of energy and heat over a heterogeneous surface are analyzed in terms of the horizontal distribution as well as temporal evolution of sensible and latent heat fluxes at different heights under different wind conditions on basis of the simulated results from WRF_LES. The characteristics of the heat and water transported into the free atmosphere from surface are also analyzed and quantified according to the simulated results from WRF_LES. The convective transport of energy and water are analyzed according to horizontal and vertical distributions of potential temperature and vapor under different background wind conditions. With the analysis based on the WRF_LES simulation, the performance of PBL schemes of mesoscale simulation (WRF_meso) is evaluated. The comparison between horizontal distribution of vertical fluxes and domain-averaged vertical fluxes of the energy and water in the free atmosphere is used to evaluate the performance of PBL schemes of WRF_meso in the simulation of vertical exchange of energy and water. This is an important variable because only the energy and water transported into free atmosphere is able to influence the regional and even global climate. This work would will be of great significance not only for understanding the land atmosphere interactions over a heterogeneous surface by evaluating and improving the performance PBL schemes in WRF-meso, but also for the understanding the profound effect of Tibetan Plateau on the regional and global climate.

Preliminary Analysis of the Performance of the Landsat 8/OLI Land Surface Reflectance Product

NASA Technical Reports Server (NTRS)

Vermote, Eric; Justice, Chris; Claverie, Martin; Franch, Belen

2016-01-01

The surface reflectance, i.e., satellite derived top of atmosphere (TOA) reflectance corrected for the temporally, spatially and spectrally varying scattering and absorbing effects of atmospheric gases and aerosols, is needed to monitor the land surface reliably. For this reason, the surface reflectance, and not TOA reflectance, is used to generate the greater majority of global land products, for example, from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors. Even if atmospheric effects are minimized by sensor design, atmospheric effects are still challenging to correct. In particular, the strong impact of aerosols in the visible and near infrared spectral range can be difficult to correct, because they can be highly discrete in space and time (e.g., smoke plumes) and because of the complex scattering and absorbing properties of aerosols that vary spectrally and with aerosol size, shape, chemistry and density.

Land subsidence and recovery in the Albuquerque Basin, New Mexico, 1993–2014

USGS Publications Warehouse

Driscoll, Jessica M.; Brandt, Justin T.

2017-08-14

The Albuquerque Bernalillo County Water Utility Authority (ABCWUA) drinking water supply was almost exclusively sourced from groundwater from within the Albuquerque Basin before 2008. In 2008, the San Juan-Chama Drinking Water Project (SJCDWP) provided surface-water resources to augment the groundwater supply, allowing for a reduction in groundwater pumping in the Albuquerque Basin. In 2013, the U.S. Geological Survey, in cooperation with the ABCWUA, began a study to measure and compare aquifer-system and land-surface elevation change before and after the SJCDWP in 2008. Three methods of data collection with different temporal and spatial resolutions were used for this study: (1) aquifer-system compaction data collected continuously at a single extensometer from 1994 to 2013; (2) land-surface elevation change from Global Positioning System (GPS) surveys of a network of monuments collected in 1994–95, 2005, and 2014; and (3) spatially distributed Interferometric Synthetic Aperture Radar (InSAR) satellite data from 1993 to 2010. Collection of extensometer data allows for direct and continuous measurement of aquifer-system compaction at the extensometer location. The GPS surveys of a network of monuments allow for periodic measurements of land-surface elevation change at monument locations. Interferograms are limited in time by lifespan of the satellite, orbital pattern, and data quality but allow for measurement of gridded land-surface elevation change over the study area. Each of these methods was employed to provide a better understanding of aquifer-system compaction and land-surface elevation change for the Albuquerque Basin.Results do not show large magnitudes of subsidence in the Albuquerque Basin. High temporal-resolution but low spatial-resolution data measurements of aquifer-system compaction at the Albuquerque extensometer show elastic aquifer-system response to recovering groundwater levels. Results from the GPS survey of the network of monuments show inconsistent land-surface elevation changes over the Albuquerque Basin, likely because of the lack of significant change and the complexity of subsurface stratigraphy in addition to the spatial and temporal heterogeneity of groundwater withdrawals over the study period. Results from the InSAR analysis show areas of land-surface elevation increase after 2008, which could be attributed to elastic recovery of the aquifer system. The spatial extent to which elastic recovery of the aquifer system has resulted in recovery of land-surface elevation is limited to the in-situ measurements at the extensometer. Examination of spatially distributed InSAR data relative to limited spatial extent of the complex heterogeneity subsurface stratigraphy may explain some of the heterogeneity of land-surface elevation changes over this study period.

An Investigation of Land-Atmosphere Coupling from Local to Regional Scales

NASA Astrophysics Data System (ADS)

Brunsell, N. A.; Van Vleck, E.; Rahn, D. A.

2017-12-01

The exchanges of mass and energy between the surface and atmosphere have been shown to depend upon both local and regional climatic influences. However, the degree of control exerted by the land surface on the coupling metrics is not well understood. In particular, we lack an understanding of the relationship between the local microclimate of a site and the regional forces responsible for land-atmosphere coupling. To address this, we investigate a series of metrics calculated from eddy covariance data and ceilometer data, land surface modeling and remotely sensed observations in the central United States to diagnose these interactions and predict the change from one coupling regime (e.g. wet/dry coupling) to another state. The stability of the coupling is quantified using a Lyapunov exponent based methodology. Through the use of a wavelet information theoretic approach, we isolate the roles local energy partitioning, as well as the temperature and moisture gradients on controlling and changing the coupling regime. Taking a multi-scale observational approach, we first examine the relationship at the tower scale. Using land surface models, we quantify to what extent current models are capable of properly diagnosing the dynamics of the coupling regime. In particular, we focus on the role of the surface moisture and vegetation to initiate and maintain precipitation feedbacks. We extend this analysis to the regional scale by utilizing reanalysis and remotely sensed observations. Thus, we are able to quantify the changes in observed coupling patterns with linkages to local interactions to address the question of the local control that the surface exerts over the maintenance of land-atmosphere coupling.

Determination of the Impact of Urbanization on Agricultural Lands using Multi-temporal Satellite Sensor Images

NASA Astrophysics Data System (ADS)

Kaya, S.; Alganci, U.; Sertel, E.; Ustundag, B.

2015-12-01

Throughout the history, agricultural activities have been performed close to urban areas. Main reason behind this phenomenon is the need of fast marketing of the agricultural production to urban residents and financial provision. Thus, using the areas nearby cities for agricultural activities brings out advantage of easy transportation of productions and fast marketing. For decades, heavy migration to cities has directly and negatively affected natural grasslands, forests and agricultural lands. This pressure has caused agricultural lands to be changed into urban areas. Dense urbanization causes increase in impervious surfaces, heat islands and many other problems in addition to destruction of agricultural lands. Considering the negative impacts of urbanization on agricultural lands and natural resources, a periodic monitoring of these changes becomes indisputably important. At this point, satellite images are known to be good data sources for land cover / use change monitoring with their fast data acquisition, large area coverages and temporal resolution properties. Classification of the satellite images provides thematic the land cover / use maps of the earth surface and changes can be determined with GIS based analysis multi-temporal maps. In this study, effects of heavy urbanization over agricultural lands in Istanbul, metropolitan city of Turkey, were investigated with use of multi-temporal Landsat TM satellite images acquired between 1984 and 2011. Images were geometrically registered to each other and classified using supervised maximum likelihood classification algorithm. Resulting thematic maps were exported to GIS environment and destructed agricultural lands by urbanization were determined using spatial analysis.

The Algorithm Theoretical Basis Document for the Derivation of Range and Range Distributions from Laser Pulse Waveform Analysis for Surface Elevations, Roughness, Slope, and Vegetation Heights

NASA Technical Reports Server (NTRS)

Brenner, Anita C.; Zwally, H. Jay; Bentley, Charles R.; Csatho, Bea M.; Harding, David J.; Hofton, Michelle A.; Minster, Jean-Bernard; Roberts, LeeAnne; Saba, Jack L.; Thomas, Robert H.;

Simulation and Analysis of Topographic Effect on Land Surface Albedo over Mountainous Areas

NASA Astrophysics Data System (ADS)

Hao, D.; Wen, J.; Xiao, Q.

2017-12-01

Land surface albedo is one of the significant geophysical variables affecting the Earth's climate and controlling the surface radiation budget. Topography leads to the formation of shadows and the redistribution of incident radiation, which complicates the modeling and estimation of the land surface albedo. Some studies show that neglecting the topography effect may lead to significant bias in estimating the land surface albedo for the sloping terrain. However, for the composite sloping terrain, the topographic effects on the albedo remain unclear. Accurately estimating the sub-topographic effect on the land surface albedo over the composite sloping terrain presents a challenge for remote sensing modeling and applications. In our study, we focus on the development of a simplified estimation method for land surface albedo including black-sky albedo (BSA) and white-sky albedo (WSA) of the composite sloping terrain at a kilometer scale based on the fine scale DEM (30m) and quantitatively investigate and understand the topographic effects on the albedo. The albedo is affected by various factors such as solar zenith angle (SZA), solar azimuth angle (SAA), shadows, terrain occlusion, and slope and aspect distribution of the micro-slopes. When SZA is 30°, the absolute and relative deviations between the BSA of flat terrain and that of rugged terrain reaches 0.12 and 50%, respectively. When the mean slope of the terrain is 30.63° and SZA=30°, the absolute deviation of BSA caused by SAA can reach 0.04. The maximal relative and relative deviation between the WSA of flat terrain and that of rugged terrain reaches 0.08 and 50%. These results demonstrate that the topographic effect has to be taken into account in the albedo estimation.

Diurnal Cycles of High Resolution Land Surface Temperatures (LSTs) Determined from UAV Platforms Across a Range of Surface Types

NASA Astrophysics Data System (ADS)

McCabe, M.; Rosas Aguilar, J.; Parkes, S. D.; Aragon, B.

2017-12-01

Observation of land surface temperature (LST) has many practical uses, from studying boundary layer dynamics and land-atmosphere coupling, to investigating surface properties such as soil moisture status, heat stress and surface heat fluxes. Typically, LST is observed via satellite based sensors such as LandSat or via point measurements using IR radiometers. These measurements provide either good spatial coverage and resolution or good temporal coverage. However, neither are able to provide the needed spatial and temporal resolution for many of the research applications described above. Technological developments in the use of Unmanned Aerial Vehicles (UAVs), together with small thermal frame cameras, has enabled a capacity to overcome this spatiotemporal constraint. Utilising UAV platforms to collect LST measurements across diurnal cycles provides an opportunity to study how meteorological and surface properties vary in both space and time. Here we describe the collection of LST data from a multi-rotor UAV across a study domain that is observed multiple times throughout the day. Flights over crops of Rhodes grass and alfalfa, along with a bare desert surface, were repeated with between 8 and 11 surveys covering the period from early morning to sunset. Analysis of the collected thermal imagery shows that the constructed LST maps illustrate a strong diurnal cycle consistent with expected trends, but with considerable spatial and temporal variability observed within and between the different domains. These results offer new insights into the dynamics of land surface behavior in both dry and wet soil conditions and at spatiotemporal scales that are unable to be replicated using traditional satellite platforms.

Land cover characterization and land surface parameterization research

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Parton, William J.

1997-01-01

The understanding of land surface processes and their parameterization in atmospheric, hydrologic, and ecosystem models has been a dominant research theme over the past decade. For example, many studies have demonstrated the key role of land cover characteristics as controlling factors in determining land surface processes, such as the exchange of water, energy, carbon, and trace gases between the land surface and the lower atmosphere. The requirements for multiresolution land cover characteristics data to support coupled-systems modeling have also been well documented, including the need for data on land cover type, land use, and many seasonally variable land cover characteristics, such as albedo, leaf area index, canopy conductance, surface roughness, and net primary productivity. Recently, the developers of land data have worked more closely with the land surface process modelers in these efforts.

Predictability of Malaria Transmission Intensity in the Mpumalanga Province, South Africa, Using Land Surface Climatology and Autoregressive Analysis

NASA Technical Reports Server (NTRS)

Grass, David; Jasinski, Michael F.; Govere, John

2003-01-01

There has been increasing effort in recent years to employ satellite remotely sensed data to identify and map vector habitat and malaria transmission risk in data sparse environments. In the current investigation, available satellite and other land surface climatology data products are employed in short-term forecasting of infection rates in the Mpumalanga Province of South Africa, using a multivariate autoregressive approach. The climatology variables include precipitation, air temperature and other land surface states computed by the Off-line Land-Surface Global Assimilation System (OLGA) including soil moisture and surface evaporation. Satellite data products include the Normalized Difference Vegetation Index (NDVI) and other forcing data used in the Goddard Earth Observing System (GEOS-1) model. Predictions are compared to long- term monthly records of clinical and microscopic diagnoses. The approach addresses the high degree of short-term autocorrelation in the disease and weather time series. The resulting model is able to predict 11 of the 13 months that were classified as high risk during the validation period, indicating the utility of applying antecedent climatic variables to the prediction of malaria incidence for the Mpumalanga Province.

Evaluating Weather Research and Forecasting Model Sensitivity to Land and Soil Conditions Representative of Karst Landscapes

NASA Astrophysics Data System (ADS)

Johnson, Christopher M.; Fan, Xingang; Mahmood, Rezaul; Groves, Chris; Polk, Jason S.; Yan, Jun

2018-03-01

Due to their particular physiographic, geomorphic, soil cover, and complex surface-subsurface hydrologic conditions, karst regions produce distinct land-atmosphere interactions. It has been found that floods and droughts over karst regions can be more pronounced than those in non-karst regions following a given rainfall event. Five convective weather events are simulated using the Weather Research and Forecasting model to explore the potential impacts of land-surface conditions on weather simulations over karst regions. Since no existing weather or climate model has the ability to represent karst landscapes, simulation experiments in this exploratory study consist of a control (default land-cover/soil types) and three land-surface conditions, including barren ground, forest, and sandy soils over the karst areas, which mimic certain karst characteristics. Results from sensitivity experiments are compared with the control simulation, as well as with the National Centers for Environmental Prediction multi-sensor precipitation analysis Stage-IV data, and near-surface atmospheric observations. Mesoscale features of surface energy partition, surface water and energy exchange, the resulting surface-air temperature and humidity, and low-level instability and convective energy are analyzed to investigate the potential land-surface impact on weather over karst regions. We conclude that: (1) barren ground used over karst regions has a pronounced effect on the overall simulation of precipitation. Barren ground provides the overall lowest root-mean-square errors and bias scores in precipitation over the peak-rain periods. Contingency table-based equitable threat and frequency bias scores suggest that the barren and forest experiments are more successful in simulating light to moderate rainfall. Variables dependent on local surface conditions show stronger contrasts between karst and non-karst regions than variables dominated by large-scale synoptic systems; (2) significant sensitivity responses are found over the karst regions, including pronounced warming and cooling effects on the near-surface atmosphere from barren and forested land cover, respectively; (3) the barren ground in the karst regions provides conditions favourable for convective development under certain conditions. Therefore, it is suggested that karst and non-karst landscapes should be distinguished, and their physical processes should be considered for future model development.

Image Analysis Based Estimates of Regolith Erosion Due to Plume Impingement Effects

NASA Technical Reports Server (NTRS)

Lane, John E.; Metzger, Philip T.

2014-01-01

Characterizing dust plumes on the moon's surface during a rocket landing is imperative to the success of future operations on the moon or any other celestial body with a dusty or soil surface (including cold surfaces covered by frozen gas ice crystals, such as the moons of the outer planets). The most practical method of characterizing the dust clouds is to analyze video or still camera images of the dust illuminated by the sun or on-board light sources (such as lasers). The method described below was used to characterize the dust plumes from the Apollo 12 landing.

Timescales of Land Surface Evapotranspiration Response

NASA Technical Reports Server (NTRS)

Scott, Russell; Entekhabi, Dara; Koster, Randal; Suarez, Max

1997-01-01

Soil and vegetation exert strong control over the evapotranspiration rate, which couples the land surface water and energy balances. A method is presented to quantify the timescale of this surface control using daily general circulation model (GCM) simulation values of evapotranspiration and precipitation. By equating the time history of evaporation efficiency (ratio of actual to potential evapotranspiration) to the convolution of precipitation and a unit kernel (temporal weighting function), response functions are generated that can be used to characterize the timescales of evapotranspiration response for the land surface model (LSM) component of GCMS. The technique is applied to the output of two multiyear simulations of a GCM, one using a Surface-Vegetation-Atmosphere-Transfer (SVAT) scheme and the other a Bucket LSM. The derived response functions show that the Bucket LSM's response is significantly slower than that of the SVAT across the globe. The analysis also shows how the timescales of interception reservoir evaporation, bare soil evaporation, and vegetation transpiration differ within the SVAT LSM.

Monitoring the Global Soil Moisture Climatology Using GLDAS/LIS

NASA Astrophysics Data System (ADS)

Meng, J.; Mitchell, K.; Wei, H.; Gottschalck, J.

2006-05-01

Soil moisture plays a crucial role in the terrestrial water cycle through governing the process of partitioning precipitation among infiltration, runoff and evaporation. Accurate assessment of soil moisture and other land states, namely, soil temperature, snowpack, and vegetation, is critical in numerical environmental prediction systems because of their regulation of surface water and energy fluxes between the surface and atmosphere over a variety of spatial and temporal scales. The Global Land Data Assimilation System (GLDAS) is developed, jointly by NASA Goddard Space Flight Center (GSFC) and NOAA National Centers for Environmental Prediction (NCEP), to perform high-quality global land surface simulation using state-of-art land surface models and further minimizing the errors of simulation by constraining the models with observation- based precipitation, and satellite land data assimilation techniques. The GLDAS-based Land Information System (LIS) infrastructure has been installed on the NCEP supercomputer that serves the operational weather and climate prediction systems. In this experiment, the Noah land surface model is offline executed within the GLDAS/LIS infrastructure, driven by the NCEP Global Reanalysis-2 (GR2) and the CPC Merged Analysis of Precipitation (CMAP). We use the same Noah code that is coupled to the operational NCEP Global Forecast System (GFS) for weather prediction and test bed versions of the NCEP Climate Forecast System (CFS) for seasonal prediction. For assessment, it is crucial that this uncoupled GLDAS/Noah uses exactly the same Noah code (and soil and vegetation parameters therein), and executes with the same horizontal grid, landmask, terrain field, soil and vegetation types, seasonal cycle of green vegetation fraction and surface albedo as in the coupled GFS/Noah and CFS/Noah. This execution is for the 25-year period of 1980-2005, starting with a pre-execution 10-year spin-up. This 25-year GLDAS/Noah global land climatology will be used for both climate variability assessment and as a source of land initial conditions for ensemble CFS/Noah seasonal hindcast experiments. Finally, this GLDAS/Noah climatology will serve as the foundation for a global drought/flood monitoring system that includes near realtime daily updates of the global land states.

Updating representation of land surface-atmosphere feedbacks in airborne campaign modeling analysis

NASA Astrophysics Data System (ADS)

Huang, M.; Carmichael, G. R.; Crawford, J. H.; Chan, S.; Xu, X.; Fisher, J. A.

2017-12-01

An updated modeling system to support airborne field campaigns is being built at NASA Ames Pleiades, with focus on adjusting the representation of land surface-atmosphere feedbacks. The main updates, referring to previous experiences with ARCTAS-CARB and CalNex in the western US to study air pollution inflows, include: 1) migrating the WRF (Weather Research and Forecasting) coupled land surface model from Noah to improved/more complex models especially Noah-MP and Rapid Update Cycle; 2) enabling the WRF land initialization with suitably spun-up land model output; 3) incorporating satellite land cover, vegetation dynamics, and soil moisture data (i.e., assimilating Soil Moisture Active Passive data using the ensemble Kalman filter approach) into WRF. Examples are given of comparing the model fields with available aircraft observations during spring-summer 2016 field campaigns taken place at the eastern side of continents (KORUS-AQ in South Korea and ACT-America in the eastern US), the air pollution export regions. Under fair weather and stormy conditions, air pollution vertical distributions and column amounts, as well as the impact from land surface, are compared. These help identify challenges and opportunities for LEO/GEO satellite remote sensing and modeling of air quality in the northern hemisphere. Finally, we briefly show applications of this system on simulating Australian conditions, which would explore the needs for further development of the observing system in the southern hemisphere and inform the Clean Air and Urban Landscapes (https://www.nespurban.edu.au) modelers.

The Interplay Between Transpiration and Runoff Formulations in Land Surface Schemes Used with Atmospheric Models

NASA Technical Reports Server (NTRS)

Koster, Rindal D.; Milly, P. C. D.

1997-01-01

The Project for Intercomparison of Land-surface Parameterization Schemes (PILPS) has shown that different land surface models (LSMS) driven by the same meteorological forcing can produce markedly different surface energy and water budgets, even when certain critical aspects of the LSMs (vegetation cover, albedo, turbulent drag coefficient, and snow cover) are carefully controlled. To help explain these differences, the authors devised a monthly water balance model that successfully reproduces the annual and seasonal water balances of the different PILPS schemes. Analysis of this model leads to the identification of two quantities that characterize an LSM's formulation of soil water balance dynamics: (1) the efficiency of the soil's evaporation sink integrated over the active soil moisture range, and (2) the fraction of this range over which runoff is generated. Regardless of the LSM's complexity, the combination of these two derived parameters with rates of interception loss, potential evaporation, and precipitation provides a reasonable estimate for the LSM's simulated annual water balance. The two derived parameters shed light on how evaporation and runoff formulations interact in an LSM, and the analysis as a whole underscores the need for compatibility in these formulations.

The interplay between transpiration and Runoff formulations in land surface schemes used with atmospheric models

USGS Publications Warehouse

Koster, R.D.; Milly, P.C.D.

1997-01-01

The Project for Intercomparison of Land-surface Parameterization Schemes (PILPS) has shown that different land surface models (LSMs) driven by the same meteorological forcing can produce markedly different surface energy and water budgets, even when certain critical aspects of the LSMs (vegetation cover, albedo, turbulent drag coefficient, and snowcover) are carefully controlled. To help explain these differences, the authors devised a monthly water balance model that successfully reproduces the annual and seasonal water balances of the different PILPS schemes. Analysis of this model leads to the identification of two quantities that characterize an LSM's formulation of soil water balance dynamics: 1) the efficiency of the soil's evaporation sink integrated over the active soil moisture range, and 2) the fraction of this range over which runoff is generated. Regardless of the LSM's complexity, the combination of these two derived parameters with rates of interception loss, potential evaporation, and precipitation provides a reasonable estimate for the LSM's simulated annual water balance. The two derived parameters shed light on how evaporation and runoff formulations interact in an LSM, and the analysis as a whole underscores the need for compatibility in these formulations.

Geodetic survey as a means of improving fast MASW (Multichannel Analysis Of Surface Waves) profiling in difficult terrain/land conditions

NASA Astrophysics Data System (ADS)

Matuła, Rafał; Lewińska, Paulina

2018-01-01

This paper revolves around newly designed and constructed system that can make 2D seismic measurement in natural, subsoil conditions and role of land survey in obtaining accurate results and linking them to 3D surface maps. A new type of land streamer, designed for shallow subsurface exploration is described in this paper. In land seismic data acquisition methods a vehicle tows a line of seismic cable, lying on construction called streamer. The measurements of points and shots are taken while the line is stationary, arbitrary placed on seismic profile. Exposed land streamer consists of 24 innovatory gimballed 10 Hz geophones. It eliminates the need for hand `planting' of geophones, reducing time and costs. With the use of current survey techniques all data obtained with this instrument are being transferred in to 2D and 3D maps. This process is becoming more automatic.

Flight Mechanics of the Entry, Descent and Landing of the ExoMars Mission

NASA Technical Reports Server (NTRS)

HayaRamos, Rodrigo; Boneti, Davide

2007-01-01

ExoMars is ESA's current mission to planet Mars. A high mobility rover and a fixed station will be deployed on the surface of Mars. This paper regards the flight mechanics of the Entry, Descent and Landing (EDL) phases used for the mission analysis and design of the Baseline and back-up scenarios of the mission. The EDL concept is based on a ballistic entry, followed by a descent under parachutes and inflatable devices (airbags) for landing. The mission analysis and design is driven by the flexibility in terms of landing site, arrival dates and the very stringent requirement in terms of landing accuracy. The challenging requirements currently imposed to the mission need innovative analysis and design techniques to support system design trade-offs to cope with the variability in entry conditions. The concept of the Global Entry Corridor has been conceived, designed, implemented and successfully validated as a key tool to provide a global picture of the mission capabilities in terms of landing site reachability.

Seasonal-scale Observational Data Analysis and Atmospheric Phenomenology for the Cold Land Processes Experiment

NASA Technical Reports Server (NTRS)

Poulos, Gregory S.; Stamus, Peter A.; Snook, John S.

2005-01-01

The Cold Land Processes Experiment (CLPX) experiment emphasized the development of a strong synergism between process-oriented understanding, land surface models and microwave remote sensing. Our work sought to investigate which topographically- generated atmospheric phenomena are most relevant to the CLPX MSA's for the purpose of evaluating their climatic importance to net local moisture fluxes and snow transport through the use of high-resolution data assimilation/atmospheric numerical modeling techniques. Our task was to create three long-term, scientific quality atmospheric datasets for quantitative analysis (for all CLPX researchers) and provide a summary of the meteorologically-relevant phenomena of the three MSAs (see Figure) over northern Colorado. Our efforts required the ingest of a variety of CLPX datasets and the execution an atmospheric and land surface data assimilation system based on the Navier-Stokes equations (the Local Analysis and Prediction System, LAPS, and an atmospheric numerical weather prediction model, as required) at topographically- relevant grid spacing (approx. 500 m). The resulting dataset will be analyzed by the CLPX community as a part of their larger research goals to determine the relative influence of various atmospheric phenomena on processes relevant to CLPX scientific goals.

The Effect of Landing Surface on the Plantar Kinetics of Chinese Paratroopers Using Half-Squat Landing

PubMed Central

Li, Yi; Wu, Ji; Zheng, Chao; Huang, Rong Rong; Na, Yuhong; Yang, Fan; Wang, Zengshun; Wu, Di

2013-01-01

The objective of the study was to determine the effect of landing surface on plantar kinetics during a half-squat landing. Twenty male elite paratroopers with formal parachute landing training and over 2 years of parachute jumping experience were recruited. The subjects wore parachuting boots in which pressure sensing insoles were placed. Each subject was instructed to jump off a platform with a height of 60 cm, and land on either a hard or soft surface in a half-squat posture. Outcome measures were maximal plantar pressure, time to maximal plantar pressure (T-MPP), and pressure-time integral (PTI) upon landing on 10 plantar regions. Compared to a soft surface, hard surface produced higher maximal plantar pressure in the 1st to 4th metatarsal and mid-foot regions, but lower maximal plantar pressure in the 5th metatarsal region. Shorter T- MPP was found during hard surface landing in the 1st and 2nd metatarsal and medial rear foot. Landing on a hard surface landing resulted in a lower PTI than a soft surface in the 1stphalangeal region. For Chinese paratroopers, specific foot prosthesis should be designed to protect the1st to 4thmetatarsal region for hard surface landing, and the 1stphalangeal and 5thmetatarsal region for soft surface landing. Key Points Understanding plantar kinetics during the half-squat landing used by Chinese paratroopers can assist in the design of protective footwear. Compared to landing on a soft surface, a hard surface produced higher maximal plantar pressure in the 1st to 4th metatarsal and mid-foot regions, but lower maximal plantar pressure in the 5th metatarsal region. A shorter time to maximal plantar pressure was found during a hard surface landing in the 1st and 2nd metatarsals and medial rear foot. Landing on a hard surface resulted in a lower pressure-time integral than landing on a soft surface in the 1st phalangeal region. For Chinese paratroopers, specific foot prosthesis should be designed to protect the 1st to 4th metatarsal region for a hard surface landing, and the 1st phalangeal and 5th metatarsal region for a soft surface landing. PMID:24149145

Asymptotic Parachute Performance Sensitivity

NASA Technical Reports Server (NTRS)

Way, David W.; Powell, Richard W.; Chen, Allen; Steltzner, Adam D.

2006-01-01

In 2010, the Mars Science Laboratory mission will pioneer the next generation of robotic Entry, Descent, and Landing systems by delivering the largest and most capable rover to date to the surface of Mars. In addition to landing more mass than any other mission to Mars, Mars Science Laboratory will also provide scientists with unprecedented access to regions of Mars that have been previously unreachable. By providing an Entry, Descent, and Landing system capable of landing at altitudes as high as 2 km above the reference gravitational equipotential surface, or areoid, as defined by the Mars Orbiting Laser Altimeter program, Mars Science Laboratory will demonstrate sufficient performance to land on 83% of the planet s surface. By contrast, the highest altitude landing to date on Mars has been the Mars Exploration Rover at 1.3 km below the areoid. The coupling of this improved altitude performance with latitude limits as large as 60 degrees off of the equator and a precise delivery to within 10 km of a surface target, will allow the science community to select the Mars Science Laboratory landing site from thousands of scientifically interesting possibilities. In meeting these requirements, Mars Science Laboratory is extending the limits of the Entry, Descent, and Landing technologies qualified by the Mars Viking, Mars Pathfinder, and Mars Exploration Rover missions. Specifically, the drag deceleration provided by a Viking-heritage 16.15 m supersonic Disk-Gap-Band parachute in the thin atmosphere of Mars is insufficient, at the altitudes and ballistic coefficients under consideration by the Mars Science Laboratory project, to maintain necessary altitude performance and timeline margin. This paper defines and discusses the asymptotic parachute performance observed in Monte Carlo simulation and performance analysis and its effect on the Mars Science Laboratory Entry, Descent, and Landing architecture.

Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms

Treesearch

Robert E. Kennedy; Zhiqiang Yang; Warren B. Cohen

2010-01-01

We introduce and test LandTrendr (Landsat-based detection of Trends in Disturbance and Recovery), a new approach to extract spectral trajectories of land surface change from yearly Landsat time-series stacks (LTS). The method brings together two themes in time-series analysis of LTS: capture of short-duration events and smoothing of long-term trends. Our strategy is...

Assessment of environments for Mars Science Laboratory entry, descent, and surface operations

USGS Publications Warehouse

Vasavada, Ashwin R.; Chen, Allen; Barnes, Jeffrey R.; Burkhart, P. Daniel; Cantor, Bruce A.; Dwyer-Cianciolo, Alicia M.; Fergason, Robini L.; Hinson, David P.; Justh, Hilary L.; Kass, David M.; Lewis, Stephen R.; Mischna, Michael A.; Murphy, James R.; Rafkin, Scot C.R.; Tyler, Daniel; Withers, Paul G.

2012-01-01

The Mars Science Laboratory mission aims to land a car-sized rover on Mars' surface and operate it for at least one Mars year in order to assess whether its field area was ever capable of supporting microbial life. Here we describe the approach used to identify, characterize, and assess environmental risks to the landing and rover surface operations. Novel entry, descent, and landing approaches will be used to accurately deliver the 900-kg rover, including the ability to sense and "fly out" deviations from a best-estimate atmospheric state. A joint engineering and science team developed methods to estimate the range of potential atmospheric states at the time of arrival and to quantitatively assess the spacecraft's performance and risk given its particular sensitivities to atmospheric conditions. Numerical models are used to calculate the atmospheric parameters, with observations used to define model cases, tune model parameters, and validate results. This joint program has resulted in a spacecraft capable of accessing, with minimal risk, the four finalist sites chosen for their scientific merit. The capability to operate the landed rover over the latitude range of candidate landing sites, and for all seasons, was verified against an analysis of surface environmental conditions described here. These results, from orbital and model data sets, also drive engineering simulations of the rover's thermal state that are used to plan surface operations.

Integrated remote sensing for multi-temporal analysis of urban land cover-climate interactions

NASA Astrophysics Data System (ADS)

Savastru, Dan M.; Zoran, Maria A.; Savastru, Roxana S.

2016-08-01

Climate change is considered to be the biggest environmental threat in the future in the South- Eastern part of Europe. In frame of predicted global warming, urban climate is an important issue in scientific research. Surface energy processes have an essential role in urban weather, climate and hydrosphere cycles, as well in urban heat redistribution. This paper investigated the influences of urban growth on thermal environment in relationship with other biophysical variables in Bucharest metropolitan area of Romania. Remote sensing data from Landsat TM/ETM+ and time series MODIS Terra/Aqua sensors have been used to assess urban land cover- climate interactions over period between 2000 and 2015 years. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban growth. The land surface temperature (Ts), a key parameter for urban thermal characteristics analysis, was also analyzed in relation with the Normalized Difference Vegetation Index (NDVI) at city level. Based on these parameters, the urban growth, and urban heat island effect (UHI) and the relationships of Ts to other biophysical parameters have been analyzed. The correlation analyses revealed that, at the pixel-scale, Ts possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional scale, respectively. This analysis provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.

A Coupled Surface Nudging Scheme for use in Retrospective Weather and Climate Simulations for Environmental Applications

EPA Science Inventory

A surface analysis nudging scheme coupling atmospheric and land surface thermodynamic parameters has been implemented into WRF v3.8 (latest version) for use with retrospective weather and climate simulations, as well as for applications in air quality, hydrology, and ecosystem mo...

Innovative approach to retrieve land surface emissivity and land surface temperature in areas of highly dynamic emissivity changes by using thermal infrared data

NASA Astrophysics Data System (ADS)

Heinemann, S.

2015-12-01

The land surface temperature (LST) is an extremely significant parameter in order to understand the processes of energetic interactions between Earth's surface and atmosphere. This knowledge is significant for various environmental research questions, particularly with regard to the recent climate change. This study shows an innovative approach to retrieve land surface emissivity (LSE) and LST by using thermal infrared (TIR) data from satellite sensors, such as SEVIRI and AATSR. So far there are no methods to derive LSE/LST particularly in areas of highly dynamic emissivity changes. Therefore especially for regions with large surface temperature amplitude in the diurnal cycle such as bare and uneven soil surfaces but also for regions with seasonal changes in vegetation cover including various surface areas such as grassland, mixed forests or agricultural land different methods were investigated to identify the most appropriate one. The LSE is retrieved by using the day/night Temperature-Independent Spectral Indices (TISI) method, and the Generalised Split-Window (GSW) method is used to retrieve the LST. Nevertheless different GSW algorithms show that equal LSEs lead to large LST differences. Additionally LSE is also measured using a NDVI-based threshold method (NDVITHM) to distinguish between soil, dense vegetation cover and pixel composed of soil and vegetation. The data used for this analysis were derived from MODIS TIR. The analysis is implemented with IDL and an intercomparison is performed to determine the most effective methods. To compensate temperature differences between derived and ground truth data appropriate correction terms by comparing derived LSE/LST data with ground-based measurements are developed. One way to calibrate LST retrievals is by comparing the canopy leaf temperature of conifers derived from TIR data with the surrounding air temperature (e.g. from synoptic stations). Prospectively, the derived LSE/LST data become validated with near infrared data obtained from an UVA with a TIR camera (TIRC) onboard, and also compared with ground-based measurements. This study aims to generate an appropriate method by integrating developed correction terms to eventually obtain a high correlation between all, LSE/LST, TIRC and ground truth data.

Spatio-Temporal Analysis of Urban Heat Island and Urban Metabolism by Satellite Imagery over the Phoenix Metropolitan Area

NASA Astrophysics Data System (ADS)

Zhao, Q.; Zhan, S.; Kuai, X.; Zhan, Q.

2015-12-01

The goal of this research is to combine DMSP-OLS nighttime light data with Landsat imagery and use spatio-temporal analysis methods to evaluate the relationships between urbanization processes and temperature variation in Phoenix metropolitan area. The urbanization process is a combination of both land use change within the existing urban environment as well as urban sprawl that enlarges the urban area through the transformation of rural areas to urban structures. These transformations modify the overall urban climate environment, resulting in higher nighttime temperatures in urban areas compared to the surrounding rural environment. This is a well-known and well-studied phenomenon referred to as the urban heat island effect (UHI). What is unknown is the direct relationship between the urbanization process and the mechanisms of the UHI. To better understand this interaction, this research focuses on using nighttime light satellite imagery to delineate and detect urban extent changes and utilizing existing land use/land cover map or newly classified imagery from Landsat to analyze the internal urban land use variations. These data are combined with summer and winter land surface temperature data extracted from Landsat. We developed a time series of these combined data for Phoenix, AZ from 1992 to 2013 to analyze the relationships among land use change, land surface temperature and urban growth.

Land Change Trends in the Great Plains: Linkages to Climate Variability and Socioeconomic Drivers

NASA Astrophysics Data System (ADS)

Drummond, M. A.

2009-12-01

Land use and land cover change have complex linkages to climate variability and change, socioeconomic driving forces, and land management challenges. To assess these land change dynamics and their driving forces in the Great Plains, we compare and contrast contemporary land conversion across seventeen ecoregions using Landsat remote sensing data and statistical analysis. Large area change analysis in agricultural regions is often hampered by the potential for substantial change detection error and the tendency for land conversions to occur in relatively small patches at the local level. To facilitate a regional scale analysis, a statistical sampling design of randomly selected 10-km by 10-km blocks is used in order to efficiently identify the types and rates of land conversions for four time periods between 1972 and 2000, stratified by relatively homogenous ecoregions. Results show a range of rates and processes of land change that vary by ecoregion contingent on the prevailing interactions between socioeconomic and environmental factors such as climate variability, water availability, and land quality. Ecoregions have differential climate and biophysical advantages for agricultural production and other land use change. Human actions further strengthen or dampen the characteristics of change through farm policy, technological advances, economic opportunities, population and demographic shifts, and surface and groundwater irrigation.

Satellite remotely-sensed land surface parameters and their climatic effects for three metropolitan regions

USGS Publications Warehouse

Xian, George

2008-01-01

By using both high-resolution orthoimagery and medium-resolution Landsat satellite imagery with other geospatial information, several land surface parameters including impervious surfaces and land surface temperatures for three geographically distinct urban areas in the United States – Seattle, Washington, Tampa Bay, Florida, and Las Vegas, Nevada, are obtained. Percent impervious surface is used to quantitatively define the spatial extent and development density of urban land use. Land surface temperatures were retrieved by using a single band algorithm that processes both thermal infrared satellite data and total atmospheric water vapor content. Land surface temperatures were analyzed for different land use and land cover categories in the three regions. The heterogeneity of urban land surface and associated spatial extents were shown to influence surface thermal conditions because of the removal of vegetative cover, the introduction of non-transpiring surfaces, and the reduction in evaporation over urban impervious surfaces. Fifty years of in situ climate data were integrated to assess regional climatic conditions. The spatial structure of surface heating influenced by landscape characteristics has a profound influence on regional climate conditions, especially through urban heat island effects.

Impact of high resolution land surface initialization in Indian summer monsoon simulation using a regional climate model

NASA Astrophysics Data System (ADS)

Unnikrishnan, C. K.; Rajeevan, M.; Rao, S. Vijaya Bhaskara

2016-06-01

The direct impact of high resolution land surface initialization on the forecast bias in a regional climate model in recent years over Indian summer monsoon region is investigated. Two sets of regional climate model simulations are performed, one with a coarse resolution land surface initial conditions and second one used a high resolution land surface data for initial condition. The results show that all monsoon years respond differently to the high resolution land surface initialization. The drought monsoon year 2009 and extended break periods were more sensitive to the high resolution land surface initialization. These results suggest that the drought monsoon year predictions can be improved with high resolution land surface initialization. Result also shows that there are differences in the response to the land surface initialization within the monsoon season. Case studies of heat wave and a monsoon depression simulation show that, the model biases were also improved with high resolution land surface initialization. These results show the need for a better land surface initialization strategy in high resolution regional models for monsoon forecasting.

Surface Landing Site Weather Analysis for NASA's Constellation Program

NASA Technical Reports Server (NTRS)

Altino, Karen M.; Burns, K. L.

2008-01-01

Weather information is an important asset for NASA's Constellation Program in developing the next generation space transportation system to fly to the International Space Station, the Moon and, eventually, to Mars. Weather conditions can affect vehicle safety and performance during multiple mission phases ranging from pre-launch ground processing of the Ares vehicles to landing and recovery operations, including all potential abort scenarios. Meteorological analysis is art important contributor, not only to the development and verification of system design requirements but also to mission planning and active ground operations. Of particular interest are the surface weather conditions at both nominal and abort landing sites for the manned Orion capsule. Weather parameters such as wind, rain, and fog all play critical roles in the safe landing of the vehicle and subsequent crew and vehicle recovery. The Marshall Space Flight Center (MSFC) Natural Environments Branch has been tasked by the Constellation Program with defining the natural environments at potential landing zones. This paper wiI1 describe the methodology used for data collection and quality control, detail the types of analyses performed, and provide a sample of the results that cab be obtained.

Improved Modeling of Land-Atmosphere Interactions using a Coupled Version of WRF with the Land Information System

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaCasse, Katherine M.; Santanello, Joseph A., Jr.; Lapenta, William M.; Petars-Lidard, Christa D.

2007-01-01

The exchange of energy and moisture between the Earth's surface and the atmospheric boundary layer plays a critical role in many hydrometeorological processes. Accurate and high-resolution representations of surface properties such as sea-surface temperature (SST), vegetation, soil temperature and moisture content, and ground fluxes are necessary to better understand the Earth-atmosphere interactions and improve numerical predictions of weather and climate phenomena. The NASA/NWS Short-term Prediction Research and Transition (SPORT) Center is currently investigating the potential benefits of assimilating high-resolution datasets derived from the NASA moderate resolution imaging spectroradiometer (MODIS) instruments using the Weather Research and Forecasting (WRF) model and the Goddard Space Flight Center Land Information System (LIS). The LIS is a software framework that integrates satellite and ground-based observational and modeled data along with multiple land surface models (LSMs) and advanced computing tools to accurately characterize land surface states and fluxes. The LIS can be run uncoupled to provide a high-resolution land surface initial condition, and can also be run in a coupled mode with WRF to integrate surface and soil quantities using any of the LSMs available in LIS. The LIS also includes the ability to optimize the initialization of surface and soil variables by tuning the spin-up time period and atmospheric forcing parameters, which cannot be done in the standard WRF. Among the datasets available from MODIS, a leaf-area index field and composite SST analysis are used to improve the lower boundary and initial conditions to the LIS/WRF coupled model over both land and water. Experiments will be conducted to measure the potential benefits from using the coupled LIS/WRF model over the Florida peninsula during May 2004. This month experienced relatively benign weather conditions, which will allow the experiments to focus on the local and mesoscale impacts of the high-resolution MODIS datasets and optimized soil and surface initial conditions. Follow-on experiments will examine the utility of such an optimized WRF configuration for more complex weather scenarios such as convective initiation. This paper will provide an overview of the experiment design and present preliminary results from selected cases in May 2004.

GIS Toolsets for Planetary Geomorphology and Landing-Site Analysis

NASA Astrophysics Data System (ADS)

Nass, Andrea; van Gasselt, Stephan

2015-04-01

Modern Geographic Information Systems (GIS) allow expert and lay users alike to load and position geographic data and perform simple to highly complex surface analyses. For many applications dedicated and ready-to-use GIS tools are available in standard software systems while other applications require the modular combination of available basic tools to answer more specific questions. This also applies to analyses in modern planetary geomorphology where many of such (basic) tools can be used to build complex analysis tools, e.g. in image- and terrain model analysis. Apart from the simple application of sets of different tools, many complex tasks require a more sophisticated design for storing and accessing data using databases (e.g. ArcHydro for hydrological data analysis). In planetary sciences, complex database-driven models are often required to efficiently analyse potential landings sites or store rover data, but also geologic mapping data can be efficiently stored and accessed using database models rather than stand-alone shapefiles. For landings-site analyses, relief and surface roughness estimates are two common concepts that are of particular interest and for both, a number of different definitions co-exist. We here present an advanced toolset for the analysis of image and terrain-model data with an emphasis on extraction of landing site characteristics using established criteria. We provide working examples and particularly focus on the concepts of terrain roughness as it is interpreted in geomorphology and engineering studies.

Mapping of Temporal Surface-water Resources Availability and Agricultural Adaptability due to Climate Change and Anthropogenic Activity in a Hot Semi-arid Region of Maharashtra State, India

NASA Astrophysics Data System (ADS)

Roy, A.; Inamdar, A. B.

2016-12-01

Major part of Godavari River Basin is intensely drought prone and climate vulnerable in the Western Maharashtra State, India. The economy of the state depends on the agronomic productivity of this region. So, it is necessary to regulate the effects of existing and upcoming hydro-meteorological advances in various strata. This study investigates and maps the surface water resources availability and vegetation, their decadal deviations with multi-temporal LANDSAT images; and finally quantifies the agricultural adaptations. This work involves the utilization of Remote Sensing and GIS with Hydrological modeling. First, climatic trend analysis is carried out with NCEP dataset. Then, multi-temporal LANDSAT images are classified to determine the decadal LULC changes and correlated to the community level hydrological demand. Finally, NDVI, NDWI and SWAT model analysis are accomplished to determine irrigated and non-irrigated cropping area for identifying the agricultural adaptations. The analysis shows that the mean value of annual and monsoon rainfall is significantly decreasing, whereas the mean value of annual and summer temperature is increasing significantly and the winter temperature is decreasing. The analysis of LANDSAT images shows that the surface water availability is highly dependent on climatic conditions. Barren-lands are most dynamic during the study period followed by, vegetation, and water bodies. The spatial extent of barren-lands is increased drastically during the climate vulnerable years replacing the vegetation and surface water bodies. Hence, the barren lands are constantly increasing and the vegetation cover is linearly decreasing, whereas the water extent is changing either way in a random fashion. There appears a positive correlation between surface water and vegetation occurrence; as they are fluctuating in a similar fashion in all the years. The vegetation cover is densely replenished around the dams and natural water bodies which serve as the water supply stations for the irrigation purposes. Moreover, there is a shift to non-irrigated and less water demanding crops, from more water demanding crops, which is a conspicuous adaptation. Hence, the study shows there are alteration in meteorological predictors, land cover, agricultural practices and surface water availability.

Topological Relations-Based Detection of Spatial Inconsistency in GLOBELAND30

NASA Astrophysics Data System (ADS)

Kang, S.; Chen, J.; Peng, S.

2017-09-01

Land cover is one of the fundamental data sets on environment assessment, land management and biodiversity protection, etc. Hence, data quality control of land cover is extremely critical for geospatial analysis and decision making. Due to the similar remote-sensing reflectance for some land cover types, omission and commission errors occurred in preliminary classification could result to spatial inconsistency between land cover types. In the progress of post-classification, this error checking mainly depends on manual labour to assure data quality, by which it is time-consuming and labour intensive. So a method required for automatic detection in post-classification is still an open issue. From logical inconsistency point of view, an inconsistency detection method is designed. This method consist of a grids extended 4-intersection model (GE4IM) for topological representation in single-valued space, by which three different kinds of topological relations including disjoint, touch, contain or contained-by are described, and an algorithm of region overlay for the computation of spatial inconsistency. The rules are derived from universal law in nature between water body and wetland, cultivated land and artificial surface. Through experiment conducted in Shandong Linqu County, data inconsistency can be pointed out within 6 minutes through calculation of topological inconsistency between cultivated land and artificial surface, water body and wetland. The efficiency evaluation of the presented algorithm is demonstrated by Google Earth images. Through comparative analysis, the algorithm is proved to be promising for inconsistency detection in land cover data.

Investigation of Seasonal Landscape Freeze/Thaw Cycles in Relation to Cloud Structure in the High Northern Latitudes

NASA Technical Reports Server (NTRS)

Smith, Cosmo

2011-01-01

The seasonal freezing and thawing of Earth's cryosphere (the portion of Earth's surface permanently or seasonally frozen) has an immense impact on Earth's climate as well as on its water, carbon and energy cycles. During the spring, snowmelt and the transition between frozen and non-frozen states lowers Earth's surface albedo. This change in albedo causes more solar radiation to be absorbed by the land surface, raising surface soil and air temperatures as much as 5 C within a few days. The transition of ice into liquid water not only raises the surface humidity, but also greatly affects the energy exchange between the land surface and the atmosphere as the phase change creates a latent energy dominated system. There is strong evidence to suggest that the thawing of the cryosphere during spring and refreezing during autumn is correlated to local atmospheric conditions such as cloud structure and frequency. Understanding the influence of land surface freeze/thaw cycles on atmospheric structure can help improve our understanding of links between seasonal land surface state and weather and climate, providing insight into associated changes in Earth's water, carbon, and energy cycles that are driven by climate change.Information on both the freeze/thaw states of Earth's land surface and cloud characteristics is derived from data sets collected by NOAA's Special Sensor Microwave/Imager (SSM/I), the Advanced Microwave Scanning Radiometer on NASA's Earth Observing System(AMSR-E), NASA's CloudSat, and NASA's SeaWinds-on-QuickSCAT Earth remote sensing satellite instruments. These instruments take advantage of the microwave spectrum to collect an ensemble of atmospheric and land surface data. Our analysis uses data from radars (active instruments which transmit a microwave signal toward Earth and measure the resultant backscatter) and radiometers (passive devices which measure Earth's natural microwave emission) to accurately characterize salient details on Earth's surface and atmospheric states. By comparing the cloud measurements and the surface freeze-thaw data sets, a correlation between the two phenomena can be developed.

Evaluating the Utility of Satellite Soil Moisture Retrievals over Irrigated Areas and the Ability of Land Data Assimilation Methods to Correct for Unmodeled Processes

NASA Technical Reports Server (NTRS)

Kumar, S. V.; Peters-Lidard, C. D.; Santanello, J. A.; Reichle, R. H.; Draper, C. S.; Koster, R. D.; Nearing, G.; Jasinski, M. F.

2015-01-01

Earth's land surface is characterized by tremendous natural heterogeneity and human-engineered modifications, both of which are challenging to represent in land surface models. Satellite remote sensing is often the most practical and effective method to observe the land surface over large geographical areas. Agricultural irrigation is an important human-induced modification to natural land surface processes, as it is pervasive across the world and because of its significant influence on the regional and global water budgets. In this article, irrigation is used as an example of a human-engineered, often unmodeled land surface process, and the utility of satellite soil moisture retrievals over irrigated areas in the continental US is examined. Such retrievals are based on passive or active microwave observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Advanced Microwave Scanning Radiometer 2 (AMSR2), the Soil Moisture Ocean Salinity (SMOS) mission, WindSat and the Advanced Scatterometer (ASCAT). The analysis suggests that the skill of these retrievals for representing irrigation effects is mixed, with ASCAT-based products somewhat more skillful than SMOS and AMSR2 products. The article then examines the suitability of typical bias correction strategies in current land data assimilation systems when unmodeled processes dominate the bias between the model and the observations. Using a suite of synthetic experiments that includes bias correction strategies such as quantile mapping and trained forward modeling, it is demonstrated that the bias correction practices lead to the exclusion of the signals from unmodeled processes, if these processes are the major source of the biases. It is further shown that new methods are needed to preserve the observational information about unmodeled processes during data assimilation.

Drought, Land-Use Change, and Water Availability in California's Central Valley

NASA Astrophysics Data System (ADS)

Faunt, C. C.; Sneed, M.; Traum, J.

2015-12-01

The Central Valley is a broad alluvial-filled structural trough that covers about 52,000 square kilometers and is one of the most productive agricultural regions in the world. Because the valley is semi-arid and the availability of surface water varies substantially from year to year, season to season, and from north to south, agriculture developed a reliance on groundwater for irrigation. During recent drought periods (2007-09 and 2012-present), groundwater pumping has increased due to a combination of factors including drought and land-use changes. In response, groundwater levels have declined to levels approaching or below historical low levels. In the San Joaquin Valley, the southern two thirds of the Central Valley, the extensive groundwater pumpage has caused aquifer system compaction, resulting in land subsidence and permanent loss of groundwater storage capacity. The magnitude and rate of subsidence varies based on geologic materials, consolidation history, and historical water levels. Spatially-variable subsidence has changed the land-surface slope, causing operational, maintenance, and construction-design problems for surface-water infrastructure. It is important for water agencies to plan for the effects of continued water-level declines, storage losses, and/or land subsidence. To combat these effects, excess surface water, when available, is artificially recharged. As surface-water availability, land use, and artificial recharge continue to vary, long-term groundwater-level and land-subsidence monitoring and modelling are critical to understanding the dynamics of the aquifer system. Modeling tools, such as the Central Valley Hydrologic Model, can be used in the analysis and evaluation of management strategies to mitigate adverse impacts due to subsidence, while also optimizing water availability. These analyses will be critical for successful implementation of recent legislation aimed toward sustainable groundwater use.

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

NASA Technical Reports Server (NTRS)

Robertson, F. R.; Bosilovich, M. G.; Roberts, J. B.; Reichle, R. H.; Adler, R.; Ricciardulli, L.; Berg, W.; Huffman, G. J.

2013-01-01

Motivated by the question of whether recent indications of decadal climate variability and a possible "climate shift" may have affected the global water balance, we examine evaporation minus precipitation (E-P) variability integrated over the global oceans and global land from three points of view-remotely sensed retrievals / objective analyses over the oceans, reanalysis vertically-integrated moisture convergence (MFC) over land, and land surface models forced with observations-based precipitation, radiation and near-surface meteorology. Because monthly variations in area-averaged atmospheric moisture storage are small and the global integral of moisture convergence must approach zero, area-integrated E-P over ocean should essentially equal precipitation minus evapotranspiration (P-ET) over land (after adjusting for ocean and land areas). Our analysis reveals considerable uncertainty in the decadal variations of ocean evaporation when integrated to global scales. This is due to differences among datasets in 10m wind speed and near-surface atmospheric specific humidity (2m qa) used in bulk aerodynamic retrievals. Precipitation variations, all relying substantially on passive microwave retrievals over ocean, still have uncertainties in decadal variability, but not to the degree present with ocean evaporation estimates. Reanalysis MFC and P-ET over land from several observationally forced diagnostic and land surface models agree best on interannual variations. However, upward MFC (i.e. P-ET) reanalysis trends are likely related in part to observing system changes affecting atmospheric assimilation models. While some evidence for a low-frequency E-P maximum near 2000 is found, consistent with a recent apparent pause in sea-surface temperature (SST) rise, uncertainties in the datasets used here remain significant. Prospects for further reducing uncertainties are discussed. The results are interpreted in the context of recent climate variability (Pacific Decadal Oscillation, Atlantic Meridional Overturning), and efforts to distinguish these modes from longer-term trends.

Physical Properties of the MER and Beagle II Landing Sites on Mars

NASA Astrophysics Data System (ADS)

Jakosky, B. M.; Pelkey, S. M.; Mellon, M. T.; Putzig, N.; Martinez-Alonso, S.; Murphy, N.; Hynek, B.

2003-12-01

The ESA Beagle II and the NASA Mars Exploration Rover spacecraft are scheduled to land on the martian surface in December 2003 and January 2004, respectively. Mission operations and success depends on the physical properties of the surfaces on which they land. Surface structural characteristics such as the abundances of loose, unconsolidated fine material, of fine material that has been cemented into a duricrust, and of rocks affect the ability to safely land and to successfully sample and traverse the surface. Also, physical properties affect surface and atmospheric temperatures, which affect lander and rover functionality. We are in the process of analyzing surface temperature information for these sites, derived from MGS TES and Odyssey THEMIS daytime and nighttime measurements. Our approach is to: (i) remap thermal inertia using TES data at ~3-km resolution, to obtain the most complete coverage possible; (ii) interpret physical properties from TES coverage in conjunction with other remote-sensing data sets; (iii) map infrared brightness using daytime and nighttime THEMIS data at 100-m resolution, and do qualitative analysis of physical properties and processes; and (iv) derive thermal inertia from THEMIS nighttime data in conjunction with daytime albedo measurements derived from TES, THEMIS, and MOC observations. In addition, we will use measured temperatures and derived thermal inertia to predict surface temperatures for the periods of the missions.

Bridging the Global Precipitation and Soil Moisture Active Passive Missions: Variability of Microwave Surface Emissivity from In situ and Remote Sensing Perspectives

NASA Astrophysics Data System (ADS)

Zheng, Y.; Kirstetter, P.; Hong, Y.; Turk, J.

2016-12-01

The overland precipitation retrievals from satellite passive microwave (PMW) sensors such as the Global Precipitation Mission (GPM) microwave imager (GMI) are impacted by the land surface emissivity. The estimation of PMW emissivity faces challenges because it is highly variable under the influence of surface properties such as soil moisture, surface roughness and vegetation. This study proposes an improved quantitative understanding of the relationship between the emissivity and surface parameters. Surface parameter information is obtained through (i) in-situ measurements from the International Soil Moisture Network and (ii) satellite measurements from the Soil Moisture Active and Passive mission (SMAP) which provides global scale soil moisture estimates. The variation of emissivity is quantified with soil moisture, surface temperature and vegetation at various frequencies/polarization and over different types of land surfaces to sheds light into the processes governing the emission of the land. This analysis is used to estimate the emissivity under rainy conditions. The framework built with in-situ measurements serves as a benchmark for satellite-based analyses, which paves a way toward global scale emissivity estimates using SMAP.

Analysis of On-board Hazard Detection and Avoidance for Safe Lunar Landing

NASA Technical Reports Server (NTRS)

Johnson, Andrew E.; Huertas, Andres; Werner, Robert A.; Montgomery, James F.

2008-01-01

Landing hazard detection and avoidance technology is being pursued within NASA to improve landing safety and increase access to sites of interest on the lunar surface. The performance of a hazard detection and avoidance system depends on properties of the terrain, sensor performance, algorithm design, vehicle characteristics and the overall all guidance navigation and control architecture. This paper analyzes the size of the region that must be imaged, sensor performance parameters and the impact of trajectory angle on hazard detection performance. The analysis shows that vehicle hazard tolerance is the driving parameter for hazard detection system design.

Estimation of Surface Air Temperature from MODIS 1km Resolution Land Surface Temperature Over Northern China

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina

2010-01-01

Surface air temperature is a critical variable to describe the energy and water cycle of the Earth-atmosphere system and is a key input element for hydrology and land surface models. It is a very important variable in agricultural applications and climate change studies. This is a preliminary study to examine statistical relationships between ground meteorological station measured surface daily maximum/minimum air temperature and satellite remotely sensed land surface temperature from MODIS over the dry and semiarid regions of northern China. Studies were conducted for both MODIS-Terra and MODIS-Aqua by using year 2009 data. Results indicate that the relationships between surface air temperature and remotely sensed land surface temperature are statistically significant. The relationships between the maximum air temperature and daytime land surface temperature depends significantly on land surface types and vegetation index, but the minimum air temperature and nighttime land surface temperature has little dependence on the surface conditions. Based on linear regression relationship between surface air temperature and MODIS land surface temperature, surface maximum and minimum air temperatures are estimated from 1km MODIS land surface temperature under clear sky conditions. The statistical errors (sigma) of the estimated daily maximum (minimum) air temperature is about 3.8 C(3.7 C).

Analysis of Vegetation Index Variations and the Asian Monsoon Climate

NASA Technical Reports Server (NTRS)

Shen, Sunhung; Leptoukh, Gregory G.; Gerasimov, Irina

2012-01-01

Vegetation growth depends on local climate. Significant anthropogenic land cover and land use change activities over Asia have changed vegetation distribution as well. On the other hand, vegetation is one of the important land surface variables that influence the Asian Monsoon variability through controlling atmospheric energy and water vapor conditions. In this presentation, the mean and variations of vegetation index of last decade at regional scale resolution (5km and higher) from MODIS have been analyzed. Results indicate that the vegetation index has been reduced significantly during last decade over fast urbanization areas in east China, such as Yangtze River Delta, where local surface temperatures were increased significantly in term of urban heat Island. The relationship between vegetation Index and climate (surface temperature, precipitation) over a grassland in northern Asia and over a woody savannas in southeast Asia are studied. In supporting Monsoon Asian Integrated Regional Study (MAIRS) program, the data in this study have been integrated into Giovanni, the online visualization and analysis system at NASA GES DISC. Most images in this presentation are generated from Giovanni system.

Skid Landings of Airplanes on Rocker-Type Fuselages

NASA Technical Reports Server (NTRS)

Mayo, Wilbur L.

1961-01-01

A study is made of the landing of an airplane on a fuselage with "planned" curvature of its lower surface. Initial contact is considered to stop the vertical motion of a point remote from the center of gravity, thus causing rocking on the curved lower surface which converts sinking-speed energy into angular energy in pitch for dissipation by damping forces. Analysis is made of loads and motions for a given fuselage shape, and the contours required to give desired load histories are determined. Most of the calculations involve initial contact at the tail, but there are two cases of unflared landings with initial contact at the nose. The calculations are checked experimentally for the tail - low case.

Characterizing land surface change and levee stability in the Sacramento-San Joaquin Delta using UAVSAR radar imagery

USGS Publications Warehouse

Jones, C.; Bawden, G.; Deverel, S.; Dudas, J.; Hensley, S.

2011-01-01

The islands of the Sacramento-San Joaquin Delta have been subject to subsidence since they were first reclaimed from the estuary marshlands starting over 100 years ago, with most of the land currently lying below mean sea level. This area, which is the primary water resource of the state of California, is under constant threat of inundation from levee failure. Since July 2009, we have been imaging the area using the quad-polarimetric UAVSAR L-band radar, with eighteen data sets collected as of April 2011. Here we report results of our polarimetric and differential interferometric analysis of the data for levee deformation and land surface change. ?? 2011 IEEE.

Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS)

NASA Astrophysics Data System (ADS)

Turner, Andrew; Bhat, Gs; Evans, Jonathan; Marsham, John; Martin, Gill; Parker, Douglas; Taylor, Chris; Bhattacharya, Bimal; Madan, Ranju; Mitra, Ashis; Mrudula, Gm; Muddu, Sekhar; Pattnaik, Sandeep; Rajagopal, En; Tripathi, Sachida

2015-04-01

The monsoon supplies the majority of water in South Asia, making understanding and predicting its rainfall vital for the growing population and economy. However, modelling and forecasting the monsoon from days to the season ahead is limited by large model errors that develop quickly, with significant inter-model differences pointing to errors in physical parametrizations such as convection, the boundary layer and land surface. These errors persist into climate projections and many of these errors persist even when increasing resolution. At the same time, a lack of detailed observations is preventing a more thorough understanding of monsoon circulation and its interaction with the land surface: a process governed by the boundary layer and convective cloud dynamics. The INCOMPASS project will support and develop modelling capability in Indo-UK monsoon research, including test development of a new Met Office Unified Model 100m-resolution domain over India. The first UK detachment of the FAAM research aircraft to India, in combination with an intensive ground-based observation campaign, will gather new observations of the surface, boundary layer structure and atmospheric profiles to go with detailed information on the timing of monsoon rainfall. Observations will be focused on transects in the northern plains of India (covering a range of surface types from irrigated to rain-fed agriculture, and wet to dry climatic zones) and across the Western Ghats and rain shadow in southern India (including transitions from land to ocean and across orography). A pilot observational campaign is planned for summer 2015, with the main field campaign to take place during spring/summer 2016. This project will advance our ability to forecast the monsoon, through a programme of measurements and modelling that aims to capture the key surface-atmosphere feedback processes in models. The observational analysis will allow a unique and unprecedented characterization of monsoon processes that will feed directly into model development at the UK Met Office and Indian NCMRWF, through model evaluation at a range of scales and leading to model improvement by working directly with parametrization developers. The project will institute a new long-term series of measurements of land surface fluxes, a particularly unconstrained observation for India, through eddy covariance flux towers. Combined with detailed land surface modelling using the Joint UK Land Environment Simulator (JULES) model, this will allow testing of land surface initialization in monsoon forecasts and improved land-atmosphere coupling.

Mesoscale Simulations of a Florida Sea Breeze Using the PLACE Land Surface Model Coupled to a 1.5-Order Turbulence Parameterization

NASA Technical Reports Server (NTRS)

Lynn, Barry H.; Stauffer, David R.; Wetzel, Peter J.; Tao, Wei-Kuo; Perlin, Natal; Baker, R. David; Munoz, Ricardo; Boone, Aaron; Jia, Yiqin

1999-01-01

A sophisticated land-surface model, PLACE, the Parameterization for Land Atmospheric Convective Exchange, has been coupled to a 1.5-order turbulent kinetic energy (TKE) turbulence sub-model. Both have been incorporated into the Penn State/National Center for Atmospheric Research (PSU/NCAR) mesoscale model MM5. Such model improvements should have their greatest effect in conditions where surface contrasts dominate over dynamic processes, such as the simulation of warm-season, convective events. A validation study used the newly coupled model, MM5 TKE-PLACE, to simulate the evolution of Florida sea-breeze moist convection during the Convection and Precipitation Electrification Experiment (CaPE). Overall, eight simulations tested the sensitivity of the MM5 model to combinations of the new and default model physics, and initialization of soil moisture and temperature. The TKE-PLACE model produced more realistic surface sensible heat flux, lower biases for surface variables, more realistic rainfall, and cloud cover than the default model. Of the 8 simulations with different factors (i.e., model physics or initialization), TKE-PLACE compared very well when each simulation was ranked in terms of biases of the surface variables and rainfall, and percent and root mean square of cloud cover. A factor separation analysis showed that a successful simulation required the inclusion of a multi-layered, land surface soil vegetation model, realistic initial soil moisture, and higher order closure of the planetary boundary layer (PBL). These were needed to realistically model the effect of individual, joint, and synergistic contributions from the land surface and PBL on the CAPE sea-breeze, Lake Okeechobee lake breeze, and moist convection.

Accuracy Assessment of Aqua-MODIS Aerosol Optical Depth Over Coastal Regions: Importance of Quality Flag and Sea Surface Wind Speed

NASA Technical Reports Server (NTRS)

Anderson, J. C.; Wang, J.; Zeng, J.; Petrenko, M.; Leptoukh, G. G.; Ichoku, C.

2012-01-01

Coastal regions around the globe are a major source for anthropogenic aerosols in the atmosphere, but the underlying surface characteristics are not favorable for the Moderate Resolution Imaging Spectroradiometer (MODIS) algorithms designed for retrieval of aerosols over dark land or open-ocean surfaces. Using data collected from 62 coastal stations worldwide from the Aerosol Robotic Network (AERONET) from approximately 2002-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard Aqua satellite. It is found that coastal AODs (at 550 nm) characterized respectively by the MODIS Dark Land (hereafter Land) surface algorithm, the Open-Ocean (hereafter Ocean) algorithm, and AERONET all exhibit a log-normal distribution. After filtering by quality flags, the MODIS AODs respectively retrieved from the Land and Ocean algorithms are highly correlated with AERONET (with R(sup 2) is approximately equal to 0.8), but only the Land algorithm AODs fall within the expected error envelope greater than 66% of the time. Furthermore, the MODIS AODs from the Land algorithm, Ocean algorithm, and combined Land and Ocean product show statistically significant discrepancies from their respective counterparts from AERONET in terms of mean, probability density function, and cumulative density function, which suggest a need for future improvement in retrieval algorithms. Without filtering with quality flag, the MODIS Land and Ocean AOD dataset can be degraded by 30-50% in terms of mean bias. Overall, the MODIS Ocean algorithm overestimates the AERONET coastal AOD by 0.021 for AOD less than 0.25 and underestimates it by 0.029 for AOD greater than 0.25. This dichotomy is shown to be related to the ocean surface wind speed and cloud contamination effects on the satellite aerosol retrieval. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) reveals that wind speeds over the global coastal region 25 (with a mean and median value of 2.94 meters per second and 2.66 meters per second, respectively) are often slower than 6 meters per second assumed in the MODIS Ocean algorithm. As a result of high correlation (R(sup 2) greater than 0.98) between the bias in binned MODIS AOD and the corresponding binned wind speed over the coastal sea surface, an empirical scheme for correcting the bias of AOD retrieved from the MODIS Ocean algorithm is formulated and is shown to be effective over the majority of the coastal AERONET stations, and hence can be used in future analysis of AOD trend and MODIS AOD data assimilation.

Evaluation of the AMSR-E Data Calibration Over Land

NASA Technical Reports Server (NTRS)

Njoku, E.; Chan, T.; Crosson, W.; Limaye, A.

2004-01-01

Land observations by the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), particularly of soil and vegetation moisture changes, have numerous applications in hydrology, ecology and climate. Quantitative retrieval of soil and vegetation parameters relies on accurate calibration of the brightness temperature measurements. Analyses of the spectral and polarization characteristics of early versions of the AMSR-E data revealed significant calibration biases over land at 6.9 GHz. The biases were estimated and removed in the current archived version of the data Radiofrequency interference (RFI) observed at 6.9 GHz is more difficult to quanti@ however. A calibration analysis of AMSR-E data over land is presented in this paper for a complete annual cycle from June 2002 through September 2003. The analysis indicates the general high quality of the data for land applications (except for RFI), and illustrates seasonal trends of the data for different land surface types and regions.

Surface Landing Site Weather Analysis for Constellation Program

NASA Technical Reports Server (NTRS)

Altino, Karen M.; Burns, K. Lee

2008-01-01

Weather information is an important asset for NASA's Constellation Program in developing the next generation space transportation system to fly to the International Space Station, the Moon and, eventually, to Mars. Weather conditions can affect vehicle safety and performance during multiple mission phases ranging from pre-launch ground processing to landing and recovery operations, including all potential abort scenarios. Meteorological analysis is an important contributor, not only to the development and verification of system design requirements but also to mission planning and active ground operations. Of particular interest are the surface atmospheric conditions at both nominal and abort landing sites for the manned Orion capsule. Weather parameters such as wind, rain, and fog all play critical roles in the safe landing of the vehicle and subsequent crew and vehicle recovery. The Marshall Space Flight Center Natural Environments Branch has been tasked by the Constellation Program with defining the natural environments at potential landing zones. Climatological time series of operational surface weather observations are used to calculate probabilities of occurrence of various sets of hypothetical vehicle constraint thresholds, Data are available for numerous geographical locations such that statistical analysis can be performed for single sites as well as multiple-site network configurations. Results provide statistical descriptions of how often certain weather conditions are observed at the site(s) and the percentage that specified criteria thresholds are matched or exceeded. Outputs are tabulated by month and hour of day to show both seasonal and diurnal variation. This paper will describe the methodology used for data collection and quality control, detail the types of analyses performed, and provide a sample of the results that can be obtained,

The long-term Global LAnd Surface Satellite (GLASS) product suite and applications

NASA Astrophysics Data System (ADS)

Liang, S.

2015-12-01

Our Earth's environment is experiencing rapid changes due to natural variability and human activities. To monitor, understand and predict environment changes to meet the economic, social and environmental needs, use of long-term high-quality satellite data products is critical. The Global LAnd Surface Satellite (GLASS) product suite, generated at Beijing Normal University, currently includes 12 products, including leaf area index (LAI), broadband shortwave albedo, broadband longwave emissivity, downwelling shortwave radiation and photosynthetically active radiation, land surface skin temperature, longwave net radiation, daytime all-wave net radiation, fraction of absorbed photosynetically active radiation absorbed by green vegetation (FAPAR), fraction of green vegetation coverage, gross primary productivity (GPP), and evapotranspiration (ET). Most products span from 1981-2014. The algorithms for producing these products have been published in the top remote sensing related journals and books. More and more applications have being reported in the scientific literature. The GLASS products are freely available at the Center for Global Change Data Processing and Analysis of Beijing Normal University (http://www.bnu-datacenter.com/), and the University of Maryland Global Land Cover Facility (http://glcf.umd.edu). After briefly introducing the basic characteristics of GLASS products, we will present some applications on the long-term environmental changes detected from GLASS products at both global and local scales. Detailed analysis of regional hotspots, such as Greenland, Tibetan plateau, and northern China, will be emphasized, where environmental changes have been mainly associated with climate warming, drought, land-atmosphere interactions, and human activities.

A Parameterization for Land-Atmosphere-Cloud Exchange (PLACE): Documentation and Testing of a Detailed Process Model of the Partly Cloudy Boundary Layer over Heterogeneous Land.

NASA Astrophysics Data System (ADS)

Wetzel, Peter J.; Boone, Aaron

1995-07-01

This paper presents a general description of, and demonstrates the capabilities of, the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE). The PLACE model is a detailed process model of the partly cloudy atmospheric boundary layer and underlying heterogeneous land surfaces. In its development, particular attention has been given to three of the model's subprocesses: the prediction of boundary layer cloud amount, the treatment of surface and soil subgrid heterogeneity, and the liquid water budget. The model includes a three-parameter nonprecipitating cumulus model that feeds back to the surface and boundary layer through radiative effects. Surface heterogeneity in the PLACE model is treated both statistically and by resolving explicit subgrid patches. The model maintains a vertical column of liquid water that is divided into seven reservoirs, from the surface interception store down to bedrock.Five single-day demonstration cases are presented, in which the PLACE model was initialized, run, and compared to field observations from four diverse sites. The model is shown to predict cloud amount well in these while predicting the surface fluxes with similar accuracy. A slight tendency to underpredict boundary layer depth is noted in all cases.Sensitivity tests were also run using anemometer-level forcing provided by the Project for Inter-comparison of Land-surface Parameterization Schemes (PILPS). The purpose is to demonstrate the relative impact of heterogeneity of surface parameters on the predicted annual mean surface fluxes. Significant sensitivity to subgrid variability of certain parameters is demonstrated, particularly to parameters related to soil moisture. A major result is that the PLACE-computed impact of total (homogeneous) deforestation of a rain forest is comparable in magnitude to the effect of imposing heterogeneity of certain surface variables, and is similarly comparable to the overall variance among the other PILPS participant models. Were this result to be bourne out by further analysis, it would suggest that today's average land surface parameterization has little credibility when applied to discriminating the local impacts of any plausible future climate change.

Chemical analysis of the moon at the surveyor v landing site.

PubMed

Turkevich, A L; Franzgrote, E J; Patterson, J H

1967-11-03

The chemical composition of the lunar surface material at a maria landing site has been determined by the alpha-scattering technique. Oxygen, silicon, and aluminum have been identified in the preliminary evaluation of the data. The general chemical composition is similar to that of a silicate of a basaltic type.

Exploring the Influence of Impervious Surface Density and Shape on Urban Heat Islands in the Northeast USA Using MODIS and Landsat

NASA Technical Reports Server (NTRS)

Zhang, Ping; Imhoff, Marc L.; Bounoua, Lahouri; Wolfe, Robert E.

2011-01-01

Impervious surface area (ISA) from the National Land Cover Database (NLCD) 2001 and land surface temperature (LST) from MODIS averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) signature and its relationship to settlement size and shape, development intensity distribution, and land cover composition for 42 urban settlements embedded in forest biomes in the Northeastern United States. Development intensity zones, based on percent ISA, are defined for each urban area emanating outward from the urban core to nearby rural areas and are used to stratify land surface temperature. The stratification is further constrained by biome type and elevation to insure objective intercomparisons between urban zones within an urban settlement and between settlements. Stratification based on ISA allows the definition of hierarchically ordered urban zones that are consistent across urban settlements and scales. In addition to the surrounding ecological context, we find that the settlement size and shape as well as the development intensity distribution significantly influence the amplitude of summer daytime UHI. Within the Northeastern US temperate broadleaf mixed forest, UHI magnitude is positively related to the logarithm of the urban area size. Our study indicates that for similar urban area sizes, the development intensity distribution is one of the major drivers of UHI. In addition to urban area size and development intensity distribution, this analysis shows that both the shape of the urban area and the land cover composition in the surrounding rural area play an important role in modulating the UHI magnitude in different urban settlements. Our results indicate that remotely sensed urban area size and shape as well as the development intensity distribution influence UHI amplitude across regional scales.

Land Surface Modeling and Data Assimilation to Support Physical Precipitation Retrievals for GPM

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Tian. Yudong; Kumar, Sujay; Geiger, James; Choudhury, Bhaskar

2010-01-01

Objective: The objective of this proposal is to provide a routine land surface modeling and data assimilation capability for GPM in order to provide global land surface states that are 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 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. Therefore, providing a robust capability to routinely provide these critical land states is essential to support GPM-era physical retrieval algorithms over land.

Charge Retention by Organometallic Dications on Self-Assembled Monolayer Surfaces

DOE Office of Scientific and Technical Information (OSTI.GOV)

Laskin, Julia; Wang, Peng

2014-05-15

Charge retention by mass-selected ruthenium trisbipyridine dications, or Ru(bpy)32+, soft-landed onto self-assembled monolayer (SAM) surfaces of 1H, 1H, 2H, 2H-perfluorodecane-1-thiol (FSAM), 11-mercaptoundecanoic acid (COOH-SAM), and 11-amino-1-undecanethiol (HSAM) on gold was examined using in situ time-resolved secondary ion mass spectrometry in a Fourier transform ion cyclotron resonance apparatus (FT-ICR SIMS). FT-ICR SIMS analysis was performed during ion soft-landing and for 8–15 hours after the ion beam was switched off. Our results demonstrate efficient retention of the doubly charged precursor ion on the FSAM and COOH-SAM surfaces manifested by the abundant Ru(bpy)32+ ions in the SIMS spectra. In contrast, only the singlymore » charged Ru(bpy)3+ and Ru(bpy)2+ ions were observed on HSAM, indicating rapid loss of at least one charge by the deposited dications. The signal of Ru(bpy)32+ on COOH-SAM remained almost constant for more than 8 hours after the end of ion soft-landing, while a relatively fast decay followed by a plateau region was observed on the FSAM surface. However, we found that SIMS analysis of Ru(bpy)32+ ions soft-landed onto FSAM is complicated by facile ion-molecule reactivity occurring either on the surface or in the SIMS plume, making it difficult to accurately measure the charge reduction kinetics. Efficient retention of the doubly charged Ru(bpy)32+ ions on COOH-SAM is remarkably different from facile neutralization of protonated peptides deposited onto this surface reported in previous studies. Our results indicate different mechanisms of charge reduction of protonated molecules and permanent ions, such as Ru(bpy)32+, on SAM surfaces. Thus, we propose that proton loss is the major charge reduction channel for the protonated species, while electron transfer through the insulating SAM is responsible for the charge loss by permanent ions. Fundamental understanding of charge reduction phenomena is essential for controlled preparation of catalytically active substrates using ion soft-landing.« less

Potential causes of differences between ground and surface air temperature warming across different ecozones in Alberta, Canada

NASA Astrophysics Data System (ADS)

Majorowicz, Jacek A.; Skinner, Walter R.

1997-10-01

Analysis and modelling of temperature anomalies from 25 selected deep wells in Alberta show that the differences between GST (ground surface temperature) warming for the northern Boreal Forest ecozone and the combined Prairie Grassland ecozone and Aspen Parkland transition region to the south occur during the latter half of this century. This corresponds with recent changes in surface albedo resulting from permanent land development in the northern areas and also to increases in natural forest fires in the past 20 years. Differences between GST and SAT (surface air temperature) warming are much higher in the Boreal Forest ecozone than in the Prairie Grassland ecozone and Aspen Parkland transition region. Various hypotheses which could account for the existing differences between the GST and SAT warming in the different ecozones of Alberta, and western Canada in general, are tested. Analysis of existing data on soil temperature, hydrological piezometric surfaces, snowfall and moisture patterns, and land clearing and forest fires, indicate that large areas of Alberta, characterised by anomalous GST warming, have experienced widespread changes to the surface landscape in this century. It is postulated that this has resulted in a lower surface albedo with a subsequent increase in the absorption of solar energy. Heat flow modelling shows that, after climatic SAT warming, permanent clearing of the land is the most effective and likely cause of the observed changes in the GST warming. The greater GST warming in the Boreal Forest ecozone in the latter half of this century is related to landscape change due to land development and increasing forest fire activity. It appears to account for a portion of the observed SAT warming in this region through a positive feedback loop with the overlying air. The anthropogenic effect on regional climatic warming through 20th century land clearing and landscape alteration requires further study. In future, more accurate quantification of these various forcings will be necessary in order to distinguish between, and to detect, the variety of natural and anthropogenic influences and on climate.

Calculating landscape surface area from digital elevation models

Treesearch

Jeff S. Jenness

2004-01-01

There are many reasons to want to know the true surface area of the landscape, especially in landscape analysis and studies of wildlife habitat. Surface area provides a better estimate of the land area available to an animal than planimetric area, and the ratio of this surface area to planimetric area provides a useful measure of topographic roughness of the landscape...

Nonlocal Sediment Transport on Steep Lateral Moraines, Eastern Sierra Nevada, California, USA

NASA Astrophysics Data System (ADS)

Doane, Tyler H.; Furbish, David Jon; Roering, Joshua J.; Schumer, Rina; Morgan, Daniel J.

2018-01-01

Recent work has highlighted the significance of long-distance particle motions in hillslope sediment transport. Such motions imply that the flux at a given hillslope position is appropriately described as a weighted function of surrounding conditions that influence motions reaching the given position. Although the idea of nonlocal sediment transport is well grounded in theory, limited field evidence has been provided. We test local and nonlocal formulations of the flux and compare their ability to reproduce land surface profiles of steep moraines in California. We show that nonlocal and nonlinear models better reproduce evolved land surface profiles, notably the amount of lowering and concavity near the moraine crest and the lengthening and straightening of the depositional apron. The analysis provides the first estimates of key parameters that set sediment entrainment rates and travel distances in nonlocal formulations and highlights the importance of correctly specifying the entrainment rate when modeling land surface evolution. Moraine evolution associated with nonlocal and nonlinear transport formulations, when described in terms of the evolution of the Fourier transform of the moraine surface, displays a distinct behavior involving growth of certain wave numbers, in contrast to the decay of all wave numbers associated with linear transport. Nonlinear and nonlocal formulations share key mathematical elements yielding a nonlinear relation between the flux and the land surface slope.

High Resolution Land Surface Modeling with the next generation Land Data Assimilation Systems

NASA Astrophysics Data System (ADS)

Kumar, S. V.; Eylander, J.; Peters-Lidard, C.

2005-12-01

Knowledge of land surface processes is important to many real-world applications such as agricultural production, water resources management, and flood predication. The Air Force Weather Agency (AFWA) has provided the USDA and other customers global soil moisture and temperature data for the past 30 years using the agrometeorological data assimilation model (now called AGRMET), merging atmospheric data. Further, accurate initialization of land surface conditions has been shown to greatly influence and improve weather forecast model and seasonal-to-interannual climate predictions. The AFWA AGRMET model exploits real time precipitation observations and analyses, global forecast model and satellite data to generate global estimates of soil moisture, soil temperature and other land surface states at 48km spatial resolution. However, to truly address the land surface initialization and climate prediction problem, and to mitigate the errors introduced by the differences in spatial scales of models, representations of land surface conditions need to be developed at the same fine scales such as that of cloud resolving models. NASA's Goddard Space Flight Center has developed an offline land data assimilation system known as the Land Information System (LIS) capable of modeling land atmosphere interactions at spatial resolutions as fine as 1km. LIS provides a software architecture that integrates the use of the state of the art land surface models, data assimilation techniques, and high performance computing and data management tools. LIS also employs many high resolution surface parameters such as the NASA Earth Observing System (EOS)-era products. In this study we describe the development of a next generation high resolution land surface modeling and data assimilation system, combining the capabilities of LIS and AGRMET. We investigate the influence of high resolution land surface data and observations on the land surface conditions by comparing with the operational AGRMET outputs.

Progress in remote sensing of global land surface heat fluxes and evaporations with a turbulent heat exchange parameterization method

NASA Astrophysics Data System (ADS)

Chen, Xuelong; Su, Bob

2017-04-01

Remote sensing has provided us an opportunity to observe Earth land surface with a much higher resolution than any of GCM simulation. Due to scarcity of information for land surface physical parameters, up-to-date GCMs still have large uncertainties in the coupled land surface process modeling. One critical issue is a large amount of parameters used in their land surface models. Thus remote sensing of land surface spectral information can be used to provide information on these parameters or assimilated to decrease the model uncertainties. Satellite imager could observe the Earth land surface with optical, thermal and microwave bands. Some basic Earth land surface status (land surface temperature, canopy height, canopy leaf area index, soil moisture etc.) has been produced with remote sensing technique, which already help scientists understanding Earth land and atmosphere interaction more precisely. However, there are some challenges when applying remote sensing variables to calculate global land-air heat and water exchange fluxes. Firstly, a global turbulent exchange parameterization scheme needs to be developed and verified, especially for global momentum and heat roughness length calculation with remote sensing information. Secondly, a compromise needs to be innovated to overcome the spatial-temporal gaps in remote sensing variables to make the remote sensing based land surface fluxes applicable for GCM model verification or comparison. A flux network data library (more 200 flux towers) was collected to verify the designed method. Important progress in remote sensing of global land flux and evaporation will be presented and its benefits for GCM models will also be discussed. Some in-situ studies on the Tibetan Plateau and problems of land surface process simulation will also be discussed.

Integrated modelling of anthropogenic land-use and land-cover change on the global scale

NASA Astrophysics Data System (ADS)

Schaldach, R.; Koch, J.; Alcamo, J.

2009-04-01

In many cases land-use activities go hand in hand with substantial modifications of the physical and biological cover of the Earth's surface, resulting in direct effects on energy and matter fluxes between terrestrial ecosystems and the atmosphere. For instance, the conversion of forest to cropland is changing climate relevant surface parameters (e.g. albedo) as well as evapotranspiration processes and carbon flows. In turn, human land-use decisions are also influenced by environmental processes. Changing temperature and precipitation patterns for example are important determinants for location and intensity of agriculture. Due to these close linkages, processes of land-use and related land-cover change should be considered as important components in the construction of Earth System models. A major challenge in modelling land-use change on the global scale is the integration of socio-economic aspects and human decision making with environmental processes. One of the few global approaches that integrates functional components to represent both anthropogenic and environmental aspects of land-use change, is the LandSHIFT model. It simulates the spatial and temporal dynamics of the human land-use activities settlement, cultivation of food crops and grazing management, which compete for the available land resources. The rational of the model is to regionalize the demands for area intensive commodities (e.g. crop production) and services (e.g. space for housing) from the country-level to a global grid with the spatial resolution of 5 arc-minutes. The modelled land-use decisions within the agricultural sector are influenced by changing climate and the resulting effects on biomass productivity. Currently, this causal chain is modelled by integrating results from the process-based vegetation model LPJmL model for changing crop yields and net primary productivity of grazing land. Model output of LandSHIFT is a time series of grid maps with land-use/land-cover information that can serve as basis for further impact analysis. An exemplary simulation study with LandSHIFT is presented, based on scenario assumptions from the UNEP Global Environmental Outlook 4. Time horizon of the analysis is the year 2050. Changes of future food production on country level are computed by the agro-economy model IMPACT as a function of demography, economic development and global trade pattern. Together with scenario assumptions on climatic change and population growth, this data serves as model input to compute the changing land-use und land-cover. The continental and global scale model results are then analysed with respect to changes in the spatial pattern of natural vegetation as well as the resulting effects on evapotranspiration processes and land surface parameters. Furthermore, possible linkages of LandSHIFT to the different components of Earth System models (e.g. climate and natural vegetation) are discussed.

Assessing the relative influence of surface soil moisture and ENSO SST on precipitation predictability over the contiguous United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoon, Jin-Ho; Leung, Lai-Yung R.

This study assesses the relative influence of soil moisture memory and tropical sea surface temperature (SST) in seasonal rainfall over the contiguous United States. Using observed precipitation, the NINO3.4 index and soil moisture and evapotranspiration simulated by a land surface model for 61 years, analysis was performed using partial correlations to evaluate to what extent land surface and SST anomaly of El Niño and Southern Oscillation (ENSO) can affect seasonal precipitation over different regions and seasons. Results show that antecedent soil moisture is as important as concurrent ENSO condition in controlling rainfall anomalies over the U.S., but they generally dominatemore » in different seasons with SST providing more predictability during winter while soil moisture, through its linkages to evapotranspiration and snow water, has larger influence in spring and early summer. The proposed methodology is applicable to climate model outputs to evaluate the intensity of land-atmosphere coupling and its relative importance.« less

ICESat Laser Altimeter Pointing, Ranging and Timing Calibration from Integrated Residual Analysis: A Summary of Early Mission Results

NASA Technical Reports Server (NTRS)

Lutchke, Scott B.; Rowlands, David D.; Harding, David J.; Bufton, Jack L.; Carabajal, Claudia C.; Williams, Teresa A.

2003-01-01

On January 12, 2003 the Ice, Cloud and land Elevation Satellite (ICESat) was successfUlly placed into orbit. The ICESat mission carries the Geoscience Laser Altimeter System (GLAS), which consists of three near-infrared lasers that operate at 40 short pulses per second. The instrument has collected precise elevation measurements of the ice sheets, sea ice roughness and thickness, ocean and land surface elevations and surface reflectivity. The accurate geolocation of GLAS's surface returns, the spots from which the laser energy reflects on the Earth's surface, is a critical issue in the scientific application of these data Pointing, ranging, timing and orbit errors must be compensated to accurately geolocate the laser altimeter surface returns. Towards this end, the laser range observations can be fully exploited in an integrated residual analysis to accurately calibrate these geolocation/instrument parameters. Early mission ICESat data have been simultaneously processed as direct altimetry from ocean sweeps along with dynamic crossovers resulting in a preliminary calibration of laser pointing, ranging and timing. The calibration methodology and early mission analysis results are summarized in this paper along with future calibration activities

Development and Implementation of the DTOPLATS-MP land surface model over the Continental US at 30 meters

NASA Astrophysics Data System (ADS)

Chaney, N.; Wood, E. F.

2014-12-01

The increasing accessibility of high-resolution land data (< 100 m) and high performance computing allows improved parameterizations of subgrid hydrologic processes in macroscale land surface models. Continental scale fully distributed modeling at these spatial scales is possible; however, its practicality for operational use is still unknown due to uncertainties in input data, model parameters, and storage requirements. To address these concerns, we propose a modeling framework that provides the spatial detail of a fully distributed model yet maintains the benefits of a semi-distributed model. In this presentation we will introduce DTOPLATS-MP, a coupling between the NOAH-MP land surface model and the Dynamic TOPMODEL hydrologic model. This new model captures a catchment's spatial heterogeneity by clustering high-resolution land datasets (soil, topography, and land cover) into hundreds of hydrologic similar units (HSUs). A prior DEM analysis defines the connections between each HSU. At each time step, the 1D land surface model updates each HSU; the HSUs then interact laterally via the subsurface and surface. When compared to the fully distributed form of the model, this framework allows a significant decrease in computation and storage while providing most of the same information and enabling parameter transferability. As a proof of concept, we will show how this new modeling framework can be run over CONUS at a 30-meter spatial resolution. For each catchment in the WBD HUC-12 dataset, the model is run between 2002 and 2012 using available high-resolution continental scale land and meteorological datasets over CONUS (dSSURGO, NLCD, NED, and NCEP Stage IV). For each catchment, the model is run with 1000 model parameter sets obtained from a Latin hypercube sample. This exercise will illustrate the feasibility of running the model operationally at continental scales while accounting for model parameter uncertainty.

Assessment of surface turbulent fluxes using geostationary satellite surface skin temperatures and a mixed layer planetary boundary layer scheme

NASA Technical Reports Server (NTRS)

Diak, George R.; Stewart, Tod R.

1989-01-01

A method is presented for evaluating the fluxes of sensible and latent heating at the land surface, using satellite-measured surface temperature changes in a composite surface layer-mixed layer representation of the planetary boundary layer. The basic prognostic model is tested by comparison with synoptic station information at sites where surface evaporation climatology is well known. The remote sensing version of the model, using satellite-measured surface temperature changes, is then used to quantify the sharp spatial gradient in surface heating/evaporation across the central United States. An error analysis indicates that perhaps five levels of evaporation are recognizable by these methods and that the chief cause of error is the interaction of errors in the measurement of surface temperature change with errors in the assigment of surface roughness character. Finally, two new potential methods for remote sensing of the land-surface energy balance are suggested which will relay on space-borne instrumentation planned for the 1990s.

Assessment of MERRA-2 Land Surface Energy Flux Estimates

NASA Technical Reports Server (NTRS)

Draper, Clara; Reichle, Rolf; Koster, Randal

2017-01-01

In MERRA-2, observed precipitation is inserted in place of model-generated precipitation at the land surface. The use of observed precipitation was originally developed for MERRA-Land(a land-only replay of MERRA with model-generated precipitation replaced with observations).Previously shown that the land hydrology in MERRA-2 and MERRA-Land is better than MERRA. We test whether the improved land surface hydrology in MERRA-2 leads to the expected improvements in the land surface energy fluxes and 2 m air temperatures (T2m).

Geostatistical Analysis of Surface Temperature and In-Situ Soil Moisture Using LST Time-Series from Modis

NASA Astrophysics Data System (ADS)

Sohrabinia, M.; Rack, W.; Zawar-Reza, P.

2012-07-01

The objective of this analysis is to provide a quantitative estimate of the fluctuations of land surface temperature (LST) with varying near surface soil moisture (SM) on different land-cover (LC) types. The study area is located in the Canterbury Plains in the South Island of New Zealand. Time series of LST from the MODerate resolution Imaging Spectro-radiometer (MODIS) have been analysed statistically to study the relationship between the surface skin temperature and near-surface SM. In-situ measurements of the skin temperature and surface SM with a quasi-experimental design over multiple LC types are used for validation. Correlations between MODIS LST and in-situ SM, as well as in-situ surface temperature and SM are calculated. The in-situ measurements and MODIS data are collected from various LC types. Pearson's r correlation coefficient and linear regression are used to fit the MODIS LST and surface skin temperature with near-surface SM. There was no significant correlation between time-series of MODIS LST and near-surface SM from the initial analysis, however, careful analysis of the data showed significant correlation between the two parameters. Night-time series of the in-situ surface temperature and SM from a 12 hour period over Irrigated-Crop, Mixed-Grass, Forest, Barren and Open- Grass showed inverse correlations of -0.47, -0.68, -0.74, -0.88 and -0.93, respectively. These results indicated that the relationship between near-surface SM and LST in short-terms (12 to 24 hours) is strong, however, remotely sensed LST with higher temporal resolution is required to establish this relationship in such time-scales. This method can be used to study near-surface SM using more frequent LST observations from a geostationary satellite over the study area.

The EUSTACE project: delivering global, daily information on surface air temperature

NASA Astrophysics Data System (ADS)

Ghent, D.; Rayner, N. A.

2017-12-01

Day-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. A global daily analysis cannot be achieved with measurements made in situ alone, so incorporation of satellite retrievals is needed. To achieve this, in the EUSTACE project (2015-2018, https://www.eustaceproject.eu) we have developed an understanding of the relationships between traditional (land and marine) surface air temperature measurements and retrievals of surface skin temperature from satellite measurements, i.e. Land Surface Temperature, Ice Surface Temperature, Sea Surface Temperature and Lake Surface Water Temperature. Here we discuss the science needed to produce a fully-global daily analysis (or ensemble of analyses) of surface air temperature on the centennial scale, integrating different ground-based and satellite-borne data types. Information contained in the satellite retrievals is used to create globally-complete fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place. This includes developing new "Big Data" analysis methods as the data volumes involved are considerable. We will present recent progress along this road in the EUSTACE project, i.e.: • identifying inhomogeneities in daily surface air temperature measurement series from weather stations and correcting for these over Europe; • estimating surface air temperature over all surfaces of Earth from surface skin temperature retrievals; • using new statistical techniques to provide information on higher spatial and temporal scales than currently available, making optimum use of information in data-rich eras. Information will also be given on how interested users can become involved.

Multi-Temporal Multi-Sensor Analysis of Urbanization and Environmental/Climate Impact in China for Sustainable Urban Development

NASA Astrophysics Data System (ADS)

Ban, Yifang; Gong, Peng; Gamba, Paolo; Taubenbock, Hannes; Du, Peijun

2016-08-01

The overall objective of this research is to investigate multi-temporal, multi-scale, multi-sensor satellite data for analysis of urbanization and environmental/climate impact in China to support sustainable planning. Multi- temporal multi-scale SAR and optical data have been evaluated for urban information extraction using innovative methods and algorithms, including KTH- Pavia Urban Extractor, Pavia UEXT, and an "exclusion- inclusion" framework for urban extent extraction, and KTH-SEG, a novel object-based classification method for detailed urban land cover mapping. Various pixel- based and object-based change detection algorithms were also developed to extract urban changes. Several Chinese cities including Beijing, Shanghai and Guangzhou are selected as study areas. Spatio-temporal urbanization patterns and environmental impact at regional, metropolitan and city core were evaluated through ecosystem service, landscape metrics, spatial indices, and/or their combinations. The relationship between land surface temperature and land-cover classes was also analyzed.The urban extraction results showed that urban areas and small towns could be well extracted using multitemporal SAR data with the KTH-Pavia Urban Extractor and UEXT. The fusion of SAR data at multiple scales from multiple sensors was proven to improve urban extraction. For urban land cover mapping, the results show that the fusion of multitemporal SAR and optical data could produce detailed land cover maps with improved accuracy than that of SAR or optical data alone. Pixel-based and object-based change detection algorithms developed with the project were effective to extract urban changes. Comparing the urban land cover results from mulitemporal multisensor data, the environmental impact analysis indicates major losses for food supply, noise reduction, runoff mitigation, waste treatment and global climate regulation services through landscape structural changes in terms of decreases in service area, edge contamination and fragmentation. In terms ofclimate impact, the results indicate that land surface temperature can be related to land use/land cover classes.

Modeling the Effects of Irrigation on Land Surface Fluxes and States over the Conterminous United States: Sensitivity to Input Data and Model Parameters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leng, Guoyong; Huang, Maoyi; Tang, Qiuhong

2013-09-16

Previous studies on irrigation impacts on land surface fluxes/states were mainly conducted as sensitivity experiments, with limited analysis of uncertainties from the input data and model irrigation schemes used. In this study, we calibrated and evaluated the performance of irrigation water use simulated by the Community Land Model version 4 (CLM4) against observations from agriculture census. We investigated the impacts of irrigation on land surface fluxes and states over the conterminous United States (CONUS) and explored possible directions of improvement. Specifically, we found large uncertainty in the irrigation area data from two widely used sources and CLM4 tended to producemore » unrealistically large temporal variations of irrigation demand for applications at the water resources region scale over CONUS. At seasonal to interannual time scales, the effects of irrigation on surface energy partitioning appeared to be large and persistent, and more pronounced in dry than wet years. Even with model calibration to yield overall good agreement with the irrigation amounts from the National Agricultural Statistics Service (NASS), differences between the two irrigation area datasets still dominate the differences in the interannual variability of land surface response to irrigation. Our results suggest that irrigation amount simulated by CLM4 can be improved by (1) calibrating model parameter values to account for regional differences in irrigation demand and (2) accurate representation of the spatial distribution and intensity of irrigated areas.« less

São Paulo urban heat islands have a higher incidence of dengue than other urban areas.

PubMed

Araujo, Ricardo Vieira; Albertini, Marcos Roberto; Costa-da-Silva, André Luis; Suesdek, Lincoln; Franceschi, Nathália Cristina Soares; Bastos, Nancy Marçal; Katz, Gizelda; Cardoso, Vivian Ailt; Castro, Bronislawa Ciotek; Capurro, Margareth Lara; Allegro, Vera Lúcia Anacleto Cardoso

2015-01-01

Urban heat islands are characterized by high land surface temperature, low humidity, and poor vegetation, and considered to favor the transmission of the mosquito-borne dengue fever that is transmitted by the Aedes aegypti mosquito. We analyzed the recorded dengue incidence in Sao Paulo city, Brazil, in 2010-2011, in terms of multiple environmental and socioeconomic variables. Geographical information systems, thermal remote sensing images, and census data were used to classify city areas according to land surface temperature, vegetation cover, population density, socioeconomic status, and housing standards. Of the 7415 dengue cases, a majority (93.1%) mapped to areas with land surface temperature >28°C. The dengue incidence rate (cases per 100,000 inhabitants) was low (3.2 cases) in high vegetation cover areas, but high (72.3 cases) in low vegetation cover areas where the land surface temperature was 29±2°C. Interestingly, a multiple cluster analysis phenogram showed more dengue cases clustered in areas of land surface temperature >32°C, than in areas characterized as low socioeconomic zones, high population density areas, or slum-like areas. In laboratory experiments, A. aegypti mosquito larval development, blood feeding, and oviposition associated positively with temperatures of 28-32°C, indicating these temperatures to be favorable for dengue transmission. Thus, among all the variables studied, dengue incidence was most affected by the temperature. Copyright © 2014 Elsevier Editora Ltda. All rights reserved.

Disagreement between Hydrological and Land Surface models on the water budgets in the Arctic: why is this and which of them is right?

NASA Astrophysics Data System (ADS)

Blyth, E.; Martinez-de la Torre, A.; Ellis, R.; Robinson, E.

2017-12-01

The fresh-water budget of the Artic region has a diverse range of impacts: the ecosystems of the region, ocean circulation response to Arctic freshwater, methane emissions through changing wetland extent as well as the available fresh water for human consumption. But there are many processes that control the budget including a seasonal snow packs building and thawing, freezing soils and permafrost, extensive organic soils and large wetland systems. All these processes interact to create a complex hydrological system. In this study we examine a suite of 10 models that bring all those processes together in a 25 year reanalysis of the global water budget. We assess their performance in the Arctic region. There are two approaches to modelling fresh-water flows at large scales, referred to here as `Hydrological' and `Land Surface' models. While both approaches include a physically based model of the water stores and fluxes, the Land Surface models links the water flows to an energy-based model for processes such as snow melt and soil freezing. This study will analyse the impact of that basic difference on the regional patterns of evapotranspiration, runoff generation and terrestrial water storage. For the evapotranspiration, the Hydrological models tend to have a bigger spatial range in the model bias (difference to observations), implying greater errors compared to the Land-Surface models. For instance, some regions such as Eastern Siberia have consistently lower Evaporation in the Hydrological models than the Land Surface models. For the Runoff however, the results are the other way round with a slightly higher spatial range in bias for the Land Surface models implying greater errors than the Hydrological models. A simple analysis would suggest that Hydrological models are designed to get the runoff right, while Land Surface models designed to get the evapotranspiration right. Tracing the source of the difference suggests that the difference comes from the treatment of snow and evapotranspiration. The study reveals that expertise in the role of snow on runoff generation and evapotranspiration in Hydrological and Land Surface could be combined to improve the representation of the fresh water flows in the Arctic in both approaches. Improved observations are essential to make these modelling advances possible.

LSD (Landing System Development) Impact Simulation

NASA Astrophysics Data System (ADS)

Ullio, R.; Riva, N.; Pellegrino, P.; Deloo, P.

2012-07-01

In the frame of the Exploration Programs, a soft landing on the planet surface is foreseen. To ensure a successful final landing phase, a landing system by using leg tripod design landing legs with adequate crushable damping system was selected, capable of absorbing the residual velocities (vertical, horizontal and angular) at touch- down, insuring stability. TAS-I developed a numerical non linear dynamic methodology for the landing impact simulation of the Lander system by using a commercial explicit finite element analysis code (i.e. Altair RADIOSS). In this paper the most significant FE modeling approaches and results of the analytical simulation of landing impact are reported, especially with respect to the definition of leg dimensioning loads and the design update of selected parts (if necessary).

A Texas Flood from Land to Ocean Observed by SMAP

NASA Astrophysics Data System (ADS)

Fournier, S.; Reager, J. T., II; Lee, T.; Vazquez, J.; David, C. H.; Gierach, M. M.

2016-12-01

Floods are natural hazards that can have damaging impacts not only on affected land areas but also on the adjacent coastal waters. NASA's Soil Moisture Active Passive (SMAP) mission provides measurements of both surface soil moisture and sea surface salinity (SSS), offering the opportunity to study the effects of flooding events on both terrestrial and marine environments. Here, we present analysis of a severe flood that occurred in May 2015 in Texas using SMAP observations and ancillary satellite and in situ data that describe the precipitation intensity, the evolving saturation state of the land surface, the flood discharge peak, and the resulting freshwater plume in the Gulf of Mexico. We describe the spatiotemporal evolution of the different variables, their relationships, and the associated physical processes. Specifically, we identify a freshwater plume in the north-central Gulf, being distinct from the typical Mississippi River plume, that is attributable to the Texas flood.

Land subsidence in the San Joaquin Valley, California, USA, 2007-2014

NASA Astrophysics Data System (ADS)

Sneed, M.; Brandt, J. T.

2015-11-01

Rapid land subsidence was recently measured using multiple methods in two areas of the San Joaquin Valley (SJV): between Merced and Fresno (El Nido), and between Fresno and Bakersfield (Pixley). Recent land-use changes and diminished surface-water availability have led to increased groundwater pumping, groundwater-level declines, and land subsidence. Differential land subsidence has reduced the flow capacity of water-conveyance systems in these areas, exacerbating flood hazards and affecting the delivery of irrigation water. Vertical land-surface changes during 2007-2014 were determined by using Interferometric Synthetic Aperture Radar (InSAR), Continuous Global Positioning System (CGPS), and extensometer data. Results of the InSAR analysis indicate that about 7600 km2 subsided 50-540 mm during 2008-2010; CGPS and extensometer data indicate that these rates continued or accelerated through December 2014. The maximum InSAR-measured rate of 270 mm yr-1 occurred in the El Nido area, and is among the largest rates ever measured in the SJV. In the Pixley area, the maximum InSAR-measured rate during 2008-2010 was 90 mm yr-1. Groundwater was an important part of the water supply in both areas, and pumping increased when land use changed or when surface water was less available. This increased pumping caused groundwater-level declines to near or below historical lows during the drought periods 2007-2009 and 2012-present. Long-term groundwater-level and land-subsidence monitoring in the SJV is critical for understanding the interconnection of land use, groundwater levels, and subsidence, and evaluating management strategies that help mitigate subsidence hazards to infrastructure while optimizing water supplies.

A Hybrid FPGA/Tilera Compute Element for Autonomous Hazard Detection and Navigation

NASA Technical Reports Server (NTRS)

Villalpando, Carlos Y.; Werner, Robert A.; Carson, John M., III; Khanoyan, Garen; Stern, Ryan A.; Trawny, Nikolas

2013-01-01

To increase safety for future missions landing on other planetary or lunar bodies, the Autonomous Landing and Hazard Avoidance Technology (ALHAT) program is developing an integrated sensor for autonomous surface analysis and hazard determination. The ALHAT Hazard Detection System (HDS) consists of a Flash LIDAR for measuring the topography of the landing site, a gimbal to scan across the terrain, and an Inertial Measurement Unit (IMU), along with terrain analysis algorithms to identify the landing site and the local hazards. An FPGA and Manycore processor system was developed to interface all the devices in the HDS, to provide high-resolution timing to accurately measure system state, and to run the surface analysis algorithms quickly and efficiently. In this paper, we will describe how we integrated COTS components such as an FPGA evaluation board, a TILExpress64, and multi-threaded/multi-core aware software to build the HDS Compute Element (HDSCE). The ALHAT program is also working with the NASA Morpheus Project and has integrated the HDS as a sensor on the Morpheus Lander. This paper will also describe how the HDS is integrated with the Morpheus lander and the results of the initial test flights with the HDS installed. We will also describe future improvements to the HDSCE.

A hybrid FPGA/Tilera compute element for autonomous hazard detection and navigation

NASA Astrophysics Data System (ADS)

Villalpando, C. Y.; Werner, R. A.; Carson, J. M.; Khanoyan, G.; Stern, R. A.; Trawny, N.

To increase safety for future missions landing on other planetary or lunar bodies, the Autonomous Landing and Hazard Avoidance Technology (ALHAT) program is developing an integrated sensor for autonomous surface analysis and hazard determination. The ALHAT Hazard Detection System (HDS) consists of a Flash LIDAR for measuring the topography of the landing site, a gimbal to scan across the terrain, and an Inertial Measurement Unit (IMU), along with terrain analysis algorithms to identify the landing site and the local hazards. An FPGA and Manycore processor system was developed to interface all the devices in the HDS, to provide high-resolution timing to accurately measure system state, and to run the surface analysis algorithms quickly and efficiently. In this paper, we will describe how we integrated COTS components such as an FPGA evaluation board, a TILExpress64, and multi-threaded/multi-core aware software to build the HDS Compute Element (HDSCE). The ALHAT program is also working with the NASA Morpheus Project and has integrated the HDS as a sensor on the Morpheus Lander. This paper will also describe how the HDS is integrated with the Morpheus lander and the results of the initial test flights with the HDS installed. We will also describe future improvements to the HDSCE.

The potential for land use change to reduce flood risk in mid-sized catchments in the Myjava region of Slovakia

NASA Astrophysics Data System (ADS)

Rončák, Peter; Lisovszki, Evelin; Szolgay, Ján; Hlavčová, Kamila; Kohnová, Silvia; Csoma, Rózsa; Poórová, Jana

2017-06-01

The effects of land use management practices on surface runoff are evident on a local scale, but evidence of their impact on the scale of a watershed is limited. This study focuses on an analysis of the impact of land use changes on the flood regime in the Myjava River basin, which is located in Western Slovakia. The Myjava River basin has an area of 641.32 km2 and is typified by the formation of fast runoff processes, intensive soil erosion, and muddy floods. The main factors responsible for these problems with flooding and soil erosion are the basin's location, geology, pedology, agricultural land use, and cropping practices. The GIS-based, spatially distributed WetSpa rainfall-runoff model was used to simulate mean daily discharges in the outlet of the basin as well as the individual components of the water balance. The model was calibrated based on the period between 1997 and 2012 with outstanding results (an NS coefficient of 0.702). Various components of runoff (e.g., surface, interflow and groundwater) and several elements of the hydrological balance (evapotranspiration and soil moisture) were simulated under various land use scenarios. Six land use scenarios (`crop', `grass', `forest', `slope', `elevation' and `optimal') were developed. The first three scenarios exhibited the ability of the WetSpa model to simulate runoff under changed land use conditions and enabled a better adjustment of the land use parameters of the model. Three other "more realistic" land use scenarios, which were based on the distribution of land use classes (arable land, grass and forest) regarding permissible slopes in the catchment, confirmed the possibility of reducing surface runoff and maximum discharges with applicable changes in land use and land management. These scenarios represent practical, realistic and realizable land use management solutions and they could be economically implemented to mitigate soil erosion processes and enhance the flood protection measures in the Myjava River basin.

Advances in land modeling of KIAPS based on the Noah Land Surface Model

NASA Astrophysics Data System (ADS)

Koo, Myung-Seo; Baek, Sunghye; Seol, Kyung-Hee; Cho, Kyoungmi

2017-08-01

As of 2013, the Noah Land Surface Model (LSM) version 2.7.1 was implemented in a new global model being developed at the Korea Institute of Atmospheric Prediction Systems (KIAPS). This land surface scheme is further refined in two aspects, by adding new physical processes and by updating surface input parameters. Thus, the treatment of glacier land, sea ice, and snow cover are addressed more realistically. Inconsistencies in the amount of absorbed solar flux at ground level by the land surface and radiative processes are rectified. In addition, new parameters are available by using 1-km land cover data, which had usually not been possible at a global scale. Land surface albedo/emissivity climatology is newly created using Moderate-Resolution Imaging Spectroradiometer (MODIS) satellitebased data and adjusted parameterization. These updates have been applied to the KIAPS-developed model and generally provide a positive impact on near-surface weather forecasting.

Martian thermal tides from the surface to the atmosphere

NASA Astrophysics Data System (ADS)

Holstein-Rathlou, C.; Withers, P.

2017-12-01

The presence of observational platforms both in orbit and on the surface of Mars today provides a unique opportunity to simultaneously study the effects of thermal tides at the surface, above that surface location and in the atmosphere. Thermal tides are an important aspect of the atmospheric dynamics on Mars and the unique opportunity to unify landed and orbital measurements can provide a comprehensive understanding of thermal tides. Ideally, pressure measurements from the Curiosity lander and atmospheric temperature profiles from the Mars Climate Sounder (MCS) onboard Mars Reconnaissance Orbiter provide a complimentary pair of surface and atmospheric observations to study. However, the unique landing site of Curiosity, in Gale crater, introduces several complicating factors to the analysis of tidal behavior, two of which are crater circulation and the impact of the dichotomy boundary topography. In order to achieve a baseline understanding of thermal tidal behavior another complimentary pair of observations is necessary. For this purpose, the equatorial and relatively topographically flat landing site of the Viking 1 (VIK1) lander, along with its lengthy record of surface pressures, is the candidate surface dataset. There are no concurrent atmospheric observational data, so atmospheric profiles were obtained from the Mars Climate Database to ensure maximum coverage in space and time. 2-dimensional Fourier analysis in local time and longitude has yielded amplitude and phases for the four major tidal modes on Mars (diurnal and semidiurnal migrating tides, DK1 and DK2). We will present current results regarding amplitude and phase dependence on season and altitude at the VIK1 landing site. These results will (in time) be tied to tidal amplitude and phase behavior from observed MCS atmospheric temperature profiles from "appropriately quiet" Mars years (years without major dust storms). The understanding gathered from this approach will then allow us to return to the pressure measurements from Curiosity in Gale Crater, and assess to what degree the "pure" tidal signatures are muddled by various complicating factors, e.g. topography.

Martian thermal tides from the surface to the atmosphere

NASA Astrophysics Data System (ADS)

Holstein-Rathlou, Christina; Withers, Paul

2017-10-01

The presence of observational platforms both in orbit and on the surface of Mars today provides a unique opportunity to simultaneously study the effects of thermal tides at the surface, above that surface location and in the atmosphere. Thermal tides are an important aspect of the atmospheric dynamics on Mars and the unique opportunity to unify landed and orbital measurements can provide a comprehensive understanding of thermal tides.Ideally, pressure measurements from the Curiosity lander and atmospheric temperature profiles from the Mars Climate Sounder (MCS) onboard Mars Reconnaissance Orbiter provide a complimentary pair of surface and atmospheric observations to study. However, the unique landing site of Curiosity, in Gale crater, introduces several complicating factors to the analysis of tidal behavior, two of which are crater circulation and the impact of the dichotomy boundary topography.In order to achieve a baseline understanding of thermal tidal behavior another complimentary pair of observations is necessary. For this purpose, the equatorial and relatively topographically flat landing site of the Viking 1 (VIK1) lander, along with its lengthy record of surface pressures, is the candidate surface dataset. There are no concurrent atmospheric observational data, so atmospheric profiles were obtained from the Mars Climate Database to ensure maximum coverage in space and time.2-dimensional Fourier analysis in local time and longitude has yielded amplitude and phases for the four major tidal modes on Mars (diurnal and semidiurnal migrating tides, DK1 and DK2). We will present current results regarding amplitude and phase dependence on season and altitude at the VIK1 landing site. These results will (in time) be tied to tidal amplitude and phase behavior from observed MCS atmospheric temperature profiles from “appropriately quiet” Mars years (years without major dust storms). The understanding gathered from this approach will then allow us to return to the pressure measurements from Curiosity in Gale Crater, and assess to what degree the “pure” tidal signatures are muddled by various complicating factors, e.g. topography.

Simulation of urban land surface temperature based on sub-pixel land cover in a coastal city

NASA Astrophysics Data System (ADS)

Zhao, Xiaofeng; Deng, Lei; Feng, Huihui; Zhao, Yanchuang

2014-11-01

The sub-pixel urban land cover has been proved to have obvious correlations with land surface temperature (LST). Yet these relationships have seldom been used to simulate LST. In this study we provided a new approach of urban LST simulation based on sub-pixel land cover modeling. Landsat TM/ETM+ images of Xiamen city, China on both the January of 2002 and 2007 were used to acquire land cover and then extract the transformation rule using logistic regression. The transformation possibility was taken as its percent in the same pixel after normalization. And cellular automata were used to acquire simulated sub-pixel land cover on 2007 and 2017. On the other hand, the correlations between retrieved LST and sub-pixel land cover achieved by spectral mixture analysis in 2002 were examined and a regression model was built. Then the regression model was used on simulated 2007 land cover to model the LST of 2007. Finally the LST of 2017 was simulated for urban planning and management. The results showed that our method is useful in LST simulation. Although the simulation accuracy is not quite satisfactory, it provides an important idea and a good start in the modeling of urban LST.

NASA Cold Land Processes Experiment (CLPX 2002/03): Atmospheric analyses datasets

Treesearch

Glen E. Liston; Daniel L. Birkenheuer; Christopher A. Hiemstra; Donald W. Cline; Kelly Elder

2008-01-01

This paper describes the Local Analysis and Prediction System (LAPS) and the 20-km horizontal grid version of the Rapid Update Cycle (RUC20) atmospheric analyses datasets, which are available as part of the Cold Land Processes Field Experiment (CLPX) data archive. The LAPS dataset contains spatially and temporally continuous atmospheric and surface variables over...

Temporal and spatial changes of land use and landscape in a coal mining area in Xilingol grassland

NASA Astrophysics Data System (ADS)

Guan, Chunzhu; Zhang, Baolin; Li, Jiannan; Zhao, Junling

2017-01-01

Coal mining, particularly surface mining, inevitably disturbs land. According to Landsat images acquired over Xilingol grassland in 2005, 2009 and 2015, land uses were divided into seven classes, i. e., open stope, stripping area, waste-dump area, mine industrial area, farmland, urban area and the original landscape (grassland), using supervised classification and human-computer interactive interpretation. The overall classification accuracies were 97.72 %, 98.43 % and 96.73 %, respectively; the Kappa coefficients were 0.95, 0.97 and 0.95, respectively. Analysis on LUCC (Land Use and Cover Change) showed that surface coal mining disturbed grassland ecosystem: grassland decreased by 8661.15 hm2 in 2005-2015. The area and proportion of mining operation areas (open stope, stripping area, waste-dump area, mine industrial field) increased, but those of grassland decreased continuously. Transfer matrix of land use changes showed that waste-dump had the largest impacts in mining disturbance, and that effective reclamation of waste-dump areas would mitigate eco-environment destruction, as would be of great significance to protect fragile grassland eco-system. Six landscape index showed that landscape fragmentation increased, and the influences of human activity on landscape was mainly reflected in the expansion of mining area and urban area. Remote sensing monitoring of coal surface mining in grassland would accurately demonstrate the dynamics and trend of LUCC, providing scientific supports for ecological reconstruction in surface mining area.

Analysis of Water and Energy Budgets and Trends Using the NLDAS Monthly Data Sets

NASA Technical Reports Server (NTRS)

Vollmer, Bruce E.; Rui, Hualan; Mocko, David M.; Teng, William L.; Lei, Guang-Dih

2012-01-01

The North American Land Data Assimilation System (NLDAS) is a collaborative project between NASA GSFC, NOAA, Princeton University, and the University of Washington. NLDAS has created surface meteorological forcing data sets using the best-available observations and reanalyses. The forcing data sets are used to drive four separate land-surface models (LSMs), Mosaic, Noah, VIC, and SAC, to produce data sets of soil moisture, snow, runoff, and surface fluxes. NLDAS hourly data, accessible from the NASA GES DISC Hydrology Data Holdings Portal, http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings, are widely used by various user communities in modeling, research, and applications, such as drought and flood monitoring, watershed and water quality management, and case studies of extreme events. More information is available at http://ldas.gsfc.nasa.gov/. To further facilitate analysis of water and energy budgets and trends, NLDAS monthly data sets have been recently released by NASA GES DISC.

Estimation of Land Surface Fluxes and Their Uncertainty via Variational Data Assimilation Approach

NASA Astrophysics Data System (ADS)

Abdolghafoorian, A.; Farhadi, L.

2016-12-01

Accurate estimation of land surface heat and moisture fluxes as well as root zone soil moisture is crucial in various hydrological, meteorological, and agricultural applications. "In situ" measurements of these fluxes are costly and cannot be readily scaled to large areas relevant to weather and climate studies. Therefore, there is a need for techniques to make quantitative estimates of heat and moisture fluxes using land surface state variables. In this work, we applied a novel approach based on the variational data assimilation (VDA) methodology to estimate land surface fluxes and soil moisture profile from the land surface states. This study accounts for the strong linkage between terrestrial water and energy cycles by coupling the dual source energy balance equation with the water balance equation through the mass flux of evapotranspiration (ET). Heat diffusion and moisture diffusion into the column of soil are adjoined to the cost function as constraints. This coupling results in more accurate prediction of land surface heat and moisture fluxes and consequently soil moisture at multiple depths with high temporal frequency as required in many hydrological, environmental and agricultural applications. One of the key limitations of VDA technique is its tendency to be ill-posed, meaning that a continuum of possibilities exists for different parameters that produce essentially identical measurement-model misfit errors. On the other hand, the value of heat and moisture flux estimation to decision-making processes is limited if reasonable estimates of the corresponding uncertainty are not provided. In order to address these issues, in this research uncertainty analysis will be performed to estimate the uncertainty of retrieved fluxes and root zone soil moisture. The assimilation algorithm is tested with a series of experiments using a synthetic data set generated by the simultaneous heat and water (SHAW) model. We demonstrate the VDA performance by comparing the (synthetic) true measurements (including profile of soil moisture and temperature, land surface water and heat fluxes, and root water uptake) with VDA estimates. In addition, the feasibility of extending the proposed approach to use remote sensing observations is tested by limiting the number of LST observations and soil moisture observations.

Uncertainty analysis of the Operational Simplified Surface Energy Balance (SSEBop) model at multiple flux tower sites

USGS Publications Warehouse

Chen, Mingshi; Senay, Gabriel B.; Singh, Ramesh K.; Verdin, James P.

2016-01-01

Evapotranspiration (ET) is an important component of the water cycle – ET from the land surface returns approximately 60% of the global precipitation back to the atmosphere. ET also plays an important role in energy transport among the biosphere, atmosphere, and hydrosphere. Current regional to global and daily to annual ET estimation relies mainly on surface energy balance (SEB) ET models or statistical and empirical methods driven by remote sensing data and various climatological databases. These models have uncertainties due to inevitable input errors, poorly defined parameters, and inadequate model structures. The eddy covariance measurements on water, energy, and carbon fluxes at the AmeriFlux tower sites provide an opportunity to assess the ET modeling uncertainties. In this study, we focused on uncertainty analysis of the Operational Simplified Surface Energy Balance (SSEBop) model for ET estimation at multiple AmeriFlux tower sites with diverse land cover characteristics and climatic conditions. The 8-day composite 1-km MODerate resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) was used as input land surface temperature for the SSEBop algorithms. The other input data were taken from the AmeriFlux database. Results of statistical analysis indicated that the SSEBop model performed well in estimating ET with an R2 of 0.86 between estimated ET and eddy covariance measurements at 42 AmeriFlux tower sites during 2001–2007. It was encouraging to see that the best performance was observed for croplands, where R2 was 0.92 with a root mean square error of 13 mm/month. The uncertainties or random errors from input variables and parameters of the SSEBop model led to monthly ET estimates with relative errors less than 20% across multiple flux tower sites distributed across different biomes. This uncertainty of the SSEBop model lies within the error range of other SEB models, suggesting systematic error or bias of the SSEBop model is within the normal range. This finding implies that the simplified parameterization of the SSEBop model did not significantly affect the accuracy of the ET estimate while increasing the ease of model setup for operational applications. The sensitivity analysis indicated that the SSEBop model is most sensitive to input variables, land surface temperature (LST) and reference ET (ETo); and parameters, differential temperature (dT), and maximum ET scalar (Kmax), particularly during the non-growing season and in dry areas. In summary, the uncertainty assessment verifies that the SSEBop model is a reliable and robust method for large-area ET estimation. The SSEBop model estimates can be further improved by reducing errors in two input variables (ETo and LST) and two key parameters (Kmax and dT).

The characteristics and interpretability of land surface change and implications for project design

USGS Publications Warehouse

Sohl, Terry L.; Gallant, Alisa L.; Loveland, Thomas R.

2004-01-01

The need for comprehensive, accurate information on land-cover change has never been greater. While remotely sensed imagery affords the opportunity to provide information on land-cover change over large geographic expanses at a relatively low cost, the characteristics of land-surface change bring into question the suitability of many commonly used methodologies. Algorithm-based methodologies to detect change generally cannot provide the same level of accuracy as the analyses done by human interpreters. Results from the Land Cover Trends project, a cooperative venture that includes the U.S. Geological Survey, Environmental Protection Agency, and National Aeronautics and Space Administration, have shown that land-cover conversion is a relatively rare event, occurs locally in small patches, varies geographically and temporally, and is spectrally ambiguous. Based on these characteristics of change and the type of information required, manual interpretation was selected as the primary means of detecting change in the Land Cover Trends project. Mixtures of algorithm-based detection and manual interpretation may often prove to be the most feasible and appropriate design for change-detection applications. Serious examination of the expected characteristics and measurability of change must be considered during the design and implementation phase of any change analysis project.

Land Cover Change Community-based Processing and Analysis System (LC-ComPS): Lessons Learned from Technology Infusion

NASA Astrophysics Data System (ADS)

Masek, J.; Rao, A.; Gao, F.; Davis, P.; Jackson, G.; Huang, C.; Weinstein, B.

2008-12-01

The Land Cover Change Community-based Processing and Analysis System (LC-ComPS) combines grid technology, existing science modules, and dynamic workflows to enable users to complete advanced land data processing on data available from local and distributed archives. Changes in land cover represent a direct link between human activities and the global environment, and in turn affect Earth's climate. Thus characterizing land cover change has become a major goal for Earth observation science. Many science algorithms exist to generate new products (e.g., surface reflectance, change detection) used to study land cover change. The overall objective of the LC-ComPS is to release a set of tools and services to the land science community that can be implemented as a flexible LC-ComPS to produce surface reflectance and land-cover change information with ground resolution on the order of Landsat-class instruments. This package includes software modules for pre-processing Landsat-type satellite imagery (calibration, atmospheric correction, orthorectification, precision registration, BRDF correction) for performing land-cover change analysis and includes pre-built workflow chains to automatically generate surface reflectance and land-cover change products based on user input. In order to meet the project objectives, the team created the infrastructure (i.e., client-server system with graphical and machine interfaces) to expand the use of these existing science algorithm capabilities in a community with distributed, large data archives and processing centers. Because of the distributed nature of the user community, grid technology was chosen to unite the dispersed community resources. At that time, grid computing was not used consistently and operationally within the Earth science research community. Therefore, there was a learning curve to configure and implement the underlying public key infrastructure (PKI) interfaces, required for the user authentication, secure file transfer and remote job execution on the grid network of machines. In addition, science support was needed to vet that the grid technology did not have any adverse affects of the science module outputs. Other open source, unproven technologies, such as a workflow package to manage jobs submitted by the user, were infused into the overall system with successful results. This presentation will discuss the basic capabilities of LC-ComPS, explain how the technology was infused, and provide lessons learned for using and integrating the various technologies while developing and operating the system, and finally outline plans moving forward (maintenance and operations decisions) based on the experience to date.

An improved hindcast approach for evaluation and diagnosis of physical processes in global climate models

DOE PAGES

Ma, H. -Y.; Chuang, C. C.; Klein, S. A.; ...

2015-11-06

Here, we present an improved procedure of generating initial conditions (ICs) for climate model hindcast experiments with specified sea surface temperature and sea ice. The motivation is to minimize errors in the ICs and lead to a better evaluation of atmospheric parameterizations' performance in the hindcast mode. We apply state variables (horizontal velocities, temperature and specific humidity) from the operational analysis/reanalysis for the atmospheric initial states. Without a data assimilation system, we apply a two-step process to obtain other necessary variables to initialize both the atmospheric (e.g., aerosols and clouds) and land models (e.g., soil moisture). First, we nudge onlymore » the model horizontal velocities towards operational analysis/reanalysis values, given a 6-hour relaxation time scale, to obtain all necessary variables. Compared to the original strategy in which horizontal velocities, temperature and specific humidity are nudged, the revised approach produces a better representation of initial aerosols and cloud fields which are more consistent and closer to observations and model's preferred climatology. Second, we obtain land ICs from an offline land model simulation forced with observed precipitation, winds, and surface fluxes. This approach produces more realistic soil moisture in the land ICs. With this refined procedure, the simulated precipitation, clouds, radiation, and surface air temperature over land are improved in the Day 2 mean hindcasts. Following this procedure, we propose a “Core” integration suite which provides an easily repeatable test allowing model developers to rapidly assess the impacts of various parameterization changes on the fidelity of modelled cloud-associated processes relative to observations.« less

An improved hindcast approach for evaluation and diagnosis of physical processes in global climate models

NASA Astrophysics Data System (ADS)

Ma, H.-Y.; Chuang, C. C.; Klein, S. A.; Lo, M.-H.; Zhang, Y.; Xie, S.; Zheng, X.; Ma, P.-L.; Zhang, Y.; Phillips, T. J.

2015-12-01

We present an improved procedure of generating initial conditions (ICs) for climate model hindcast experiments with specified sea surface temperature and sea ice. The motivation is to minimize errors in the ICs and lead to a better evaluation of atmospheric parameterizations' performance in the hindcast mode. We apply state variables (horizontal velocities, temperature, and specific humidity) from the operational analysis/reanalysis for the atmospheric initial states. Without a data assimilation system, we apply a two-step process to obtain other necessary variables to initialize both the atmospheric (e.g., aerosols and clouds) and land models (e.g., soil moisture). First, we nudge only the model horizontal velocities toward operational analysis/reanalysis values, given a 6 h relaxation time scale, to obtain all necessary variables. Compared to the original strategy in which horizontal velocities, temperature, and specific humidity are nudged, the revised approach produces a better representation of initial aerosols and cloud fields which are more consistent and closer to observations and model's preferred climatology. Second, we obtain land ICs from an off-line land model simulation forced with observed precipitation, winds, and surface fluxes. This approach produces more realistic soil moisture in the land ICs. With this refined procedure, the simulated precipitation, clouds, radiation, and surface air temperature over land are improved in the Day 2 mean hindcasts. Following this procedure, we propose a "Core" integration suite which provides an easily repeatable test allowing model developers to rapidly assess the impacts of various parameterization changes on the fidelity of modeled cloud-associated processes relative to observations.

Using semi-variogram analysis for providing spatially distributed information on soil surface condition for land surface modeling

NASA Astrophysics Data System (ADS)

Croft, Holly; Anderson, Karen; Kuhn, Nikolaus J.

2010-05-01

The ability to quantitatively and spatially assess soil surface roughness is important in geomorphology and land degradation studies. Soils can experience rapid structural degradation in response to land cover changes, resulting in increased susceptibility to erosion and a loss of Soil Organic Matter (SOM). Changes in soil surface condition can also alter sediment detachment, transport and deposition processes, infiltration rates and surface runoff characteristics. Deriving spatially distributed quantitative information on soil surface condition for inclusion in hydrological and soil erosion models is therefore paramount. However, due to the time and resources involved in using traditional field sampling techniques, there is a lack of spatially distributed information on soil surface condition. Laser techniques can provide data for a rapid three dimensional representation of the soil surface at a fine spatial resolution. This provides the ability to capture changes at the soil surface associated with aggregate breakdown, flow routing, erosion and sediment re-distribution. Semi-variogram analysis of the laser data can be used to represent spatial dependence within the dataset; providing information about the spatial character of soil surface structure. This experiment details the ability of semi-variogram analysis to spatially describe changes in soil surface condition. Soil for three soil types (silt, silt loam and silty clay) was sieved to produce aggregates between 1 mm and 16 mm in size and placed evenly in sample trays (25 x 20 x 2 cm). Soil samples for each soil type were exposed to five different durations of artificial rainfall, to produce progressively structurally degraded soil states. A calibrated laser profiling instrument was used to measure surface roughness over a central 10 x 10 cm plot of each soil state, at 2 mm sample spacing. The laser data were analysed within a geostatistical framework, where semi-variogram analysis quantitatively represented the change in soil surface structure during crusting. The laser data were also used to create digital surface models (DSM) of the soil states for visual comparison. This research has shown that aggregate breakdown and soil crusting can be shown quantitatively by a decrease in sill variance (silt soil: 11.67 (control) to 1.08 (after 90 mins rainfall)). Features present within semi-variograms were spatially linked to features at the soil surface, such as soil cracks, tillage lines and areas of deposition. Directional semi-variograms were used to provide a spatially orientated component, where the directional sill variance associated with a soil crack was shown to increase from 7.95 to 19.33. Periodicity within semi-variogram was also shown to quantify the spatial scale of soil cracking networks and potentially surface flowpaths; an average distance between soil cracks of 37 mm closely corresponded to the distance of 38 mm shown in the semi-variogram. The results provide a strong basis for the future retrieval of spatio-temporal variations in soil surface condition. Furthermore, the presence of process-based information on hydrological pathways within semi-variograms may work towards an inclusion of geostatisically-derived information in land surface models and the understanding of complex surface processes at different spatial scales.

ARC-2012-ACD12-0020-006

NASA Image and Video Library

2012-02-16

Snapshot from a simulation run on the Pleiades supercomputer. It depicts a fluctuating pressure field on aircraft nose landing gear and fuselage surfaces. The simulation helped scientists better understand the effects of landing gear and acoustic noise. The goal of the study was to improve the current understanding of aircraft nose landing gear noise, which will lead to quieter, more efficient airframe components for future aircraft designs. The visualization was produced with help from the NAS Data Analysis & Visualization group. Investigator: Mehdi Khorrami, NASA Langley Research Center.

glopara files

Science.gov Websites

prepbufr BUFR biascr.$CDUMP.$CDATE Time dependent sat bias correction file abias text satang.$CDUMP.$CDATE Angle dependent sat bias correction satang text sfcanl.$CDUMP.$CDATE surface analysis sfcanl binary tcvitl.$CDUMP.$CDATE Tropical Storm Vitals syndata.tcvitals.tm00 text adpsfc.$CDUMP.$CDATE Surface land

Revegetation for aesthetics

Treesearch

Bernard M. Slick

1980-01-01

Surface mining is changing the landscape character of forests in the East. Aesthetic visual aspects of the landscape are considered in the analysis, planning, and design of revegetation strategies. Application of landscape architectural design techniques in the revegetation of surface-mined lands, as well as knowledge of biological characteristics, will enhance the...

Retrieval of Aerosol Microphysical Properties Based on the Optimal Estimation Method: Information Content Analysis for Satellite Polarimetric Remote Sensing Measurements

NASA Astrophysics Data System (ADS)

Hou, W. Z.; Li, Z. Q.; Zheng, F. X.; Qie, L. L.

2018-04-01

This paper evaluates the information content for the retrieval of key aerosol microphysical and surface properties for multispectral single-viewing satellite polarimetric measurements cantered at 410, 443, 555, 670, 865, 1610 and 2250 nm over bright land. To conduct the information content analysis, the synthetic data are simulated by the Unified Linearized Vector Radiative Transfer Model (UNLVTM) with the intensity and polarization together over bare soil surface for various scenarios. Following the optimal estimation theory, a principal component analysis method is employed to reconstruct the multispectral surface reflectance from 410 nm to 2250 nm, and then integrated with a linear one-parametric BPDF model to represent the contribution of polarized surface reflectance, thus further to decouple the surface-atmosphere contribution from the TOA measurements. Focusing on two different aerosol models with the aerosol optical depth equal to 0.8 at 550 nm, the total DFS and DFS component of each retrieval aerosol and surface parameter are analysed. The DFS results show that the key aerosol microphysical properties, such as the fine- and coarse-mode columnar volume concentration, the effective radius and the real part of complex refractive index at 550 nm, could be well retrieved with the surface parameters simultaneously over bare soil surface type. The findings of this study can provide the guidance to the inversion algorithm development over bright surface land by taking full use of the single-viewing satellite polarimetric measurements.

Impact of Land Model Calibration on Coupled Land-Atmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry and wet land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through calibration of the Noah land surface model using the new optimization and uncertainty estimation subsystem in NASA's Land Information System (LIS-OPT/UE). The impact of the calibration on the a) spinup of the land surface used as initial conditions, and b) the simulated heat and moisture states and fluxes of the coupled WRF simulations is then assessed. Changes in ambient weather and land-atmosphere coupling are evaluated along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Results indicate that the offline calibration leads to systematic improvements in land-PBL fluxes and near-surface temperature and humidity, and in the process provide guidance on the questions of what, how, and when to calibrate land surface models for coupled model prediction.

The EUSTACE project: delivering global, daily information on surface air temperature

NASA Astrophysics Data System (ADS)

Rayner, Nick

2017-04-01

Day-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. A global daily analysis cannot be achieved with measurements made in situ alone, so incorporation of satellite retrievals is needed. To achieve this, in the EUSTACE project (2015-June 2018, https://www.eustaceproject.eu) we are developing an understanding of the relationships between traditional (land and marine) surface air temperature measurements and retrievals of surface skin temperature from satellite measurements, i.e. Land Surface Temperature, Ice Surface Temperature, Sea Surface Temperature and Lake Surface Water Temperature. Here we discuss the science needed to produce a fully-global daily analysis (or ensemble of analyses) of surface air temperature on the centennial scale, integrating different ground-based and satellite-borne data types. Information contained in the satellite retrievals is used to create globally-complete fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place. As the data volumes involved are considerable, such work needs to include development of new "Big Data" analysis methods. We will present recent progress along this road in the EUSTACE project: 1. providing new, consistent, multi-component estimates of uncertainty in surface skin temperature retrievals from satellites; 2. identifying inhomogeneities in daily surface air temperature measurement series from weather stations and correcting for these over Europe; 3. estimating surface air temperature over all surfaces of Earth from surface skin temperature retrievals; 4. using new statistical techniques to provide information on higher spatial and temporal scales than currently available, making optimum use of information in data-rich eras. Information will also be given on how interested users can become involved.

The EUSTACE project: delivering global, daily information on surface air temperature

NASA Astrophysics Data System (ADS)

Ghent, D.; Rayner, N. A.

2016-12-01

Day-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. A global daily analysis cannot be achieved with measurements made in situ alone, so incorporation of satellite retrievals is needed. To achieve this, in the EUSTACE project (2015-June 2018, https://www.eustaceproject.eu) we are developing an understanding of the relationships between traditional (land and marine) surface air temperature measurements and retrievals of surface skin temperature from satellite measurements, i.e. Land Surface Temperature, Ice Surface Temperature, Sea Surface Temperature and Lake Surface Water Temperature. Here we discuss the science needed to produce a fully-global daily analysis (or ensemble of analyses) of surface air temperature on the centennial scale, integrating different ground-based and satellite-borne data types. Information contained in the satellite retrievals is used to create globally-complete fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place. As the data volumes involved are considerable, such work needs to include development of new "Big Data" analysis methods. We will present recent progress along this road in the EUSTACE project, i.e.: • providing new, consistent, multi-component estimates of uncertainty in surface skin temperature retrievals from satellites; • identifying inhomogeneities in daily surface air temperature measurement series from weather stations and correcting for these over Europe; • estimating surface air temperature over all surfaces of Earth from surface skin temperature retrievals; • using new statistical techniques to provide information on higher spatial and temporal scales than currently available, making optimum use of information in data-rich eras. Information will also be given on how interested users can become involved.

Simulating carbon, water and energy fluxes of a rainforest and an oil palm plantation using the Community Land Model (CLM4.5)

NASA Astrophysics Data System (ADS)

Fan, Yuanchao; Bernoux, Martial; Roupsard, Olivier; Panferov, Oleg; Le Maire, Guerric; Tölle, Merja; Knohl, Alexander

2014-05-01

Deforestation and forest degradation driven by the expansion of oil palm (Elaeis guineensis) plantations has become the major source of GHG emission in Indonesia. Changes of land surface properties (e.g. vegetation composition, soil property, surface albedo) associated with rainforest to oil palm conversion might alter the patterns of land-atmosphere energy, water and carbon cycles and therefore affect local or regional climate. Land surface modeling has been widely used to characterize the two-way interactions between climate and human disturbances on land surface. The Community Land Model (CLM) is a third-generation land model that simulates a wide range of biogeophysical and biogeochemical processes. This project utilizes the land-cover/land-use change (LCLUC) capability of the latest CLM versions 4/4.5 to characterize quantitatively how anthropogenic land surface dynamics in Indonesia affect land-atmosphere carbon, water and energy fluxes. Before simulating land use changes, the first objective is to parameterize and validate the CLM model at local rainforest and oil palm plantation sites through separate point simulations. This entails creation and parameterization of a new plant functional type (PFT) for oil palm, as well as sensitivity analysis and adaptation of model parameters for the rainforest PFTs. CLM modelled fluxes for the selected sites are to be compared with field observations from eddy covariance (EC) flux towers (e.g. a rainforest site in Bariri, Sulawesi; an oil palm site in Jambi, Sumatra). After validation, the project will proceed to parameterize land-use transformation system using remote sensing data and to simulate the impacts of historical LUCs on carbon, water and energy fluxes. Last but not least, the effects of future LUCs in Indonesia on the fluxes and carbon sequestration capacity will be investigated through scenario study. Historical land cover changes, especially oil palm coverage, are retrieved from Landsat or MODIS archival images. Oil palm concession boundaries are used to define and project future land use scenarios. Initial results include outputs from a single-point simulation for the Bariri rainforest site forced with locally measured meteorological data which already showed significant advantage over global forcing data in predicting net ecosystem exchange and latent and sensible heat fluxes. Modeled fluxes are being compared with EC flux observations and with Mixfor-SVAT model outputs from another project at the same site. In the next few months, focus will be on sensitivity analyses of model parameters including PFT optical, morphological and physiological parameters that are necessary to configure the new oil palm PFT and represent rainforest to oil palm conversion. The new parameterization will contribute to the development of the CLM model and its implementation in the modelling of LUC effects in tropical regions will help understanding land-climate interactions.

National housing and impervious surface scenarios for integrated climate impact assessments

PubMed Central

Bierwagen, Britta G.; Theobald, David M.; Pyke, Christopher R.; Choate, Anne; Groth, Philip; Thomas, John V.; Morefield, Philip

2010-01-01

Understanding the impacts of climate change on people and the environment requires an understanding of the dynamics of both climate and land use/land cover changes. A range of future climate scenarios is available for the conterminous United States that have been developed based on widely used international greenhouse gas emissions storylines. Climate scenarios derived from these emissions storylines have not been matched with logically consistent land use/cover maps for the United States. This gap is a critical barrier to conducting effective integrated assessments. This study develops novel national scenarios of housing density and impervious surface cover that are logically consistent with emissions storylines. Analysis of these scenarios suggests that combinations of climate and land use/cover can be important in determining environmental conditions regulated under the Clean Air and Clean Water Acts. We found significant differences in patterns of habitat loss and the distribution of potentially impaired watersheds among scenarios, indicating that compact development patterns can reduce habitat loss and the number of impaired watersheds. These scenarios are also associated with lower global greenhouse gas emissions and, consequently, the potential to reduce both the drivers of anthropogenic climate change and the impacts of changing conditions. The residential housing and impervious surface datasets provide a substantial first step toward comprehensive national land use/land cover scenarios, which have broad applicability for integrated assessments as these data and tools are publicly available. PMID:21078956

The global signature of post-1900 land ice wastage on vertical land motion

NASA Astrophysics Data System (ADS)

Riva, Riccardo; Frederikse, Thomas; King, Matt; Marzeion, Ben; van den Broeke, Michiel

2017-04-01

The amount of ice stored on land has strongly declined during the 20th century, and melt rates showed a significant acceleration over the last two decades. Land ice wastage is well known to be one of the main drivers of global mean sea-level rise, as widely discussed in the literature and reflected in the last assessment report of the IPCC. A less obvious effect of melting land ice is the response of the solid earth to mass redistribution on its surface, which, in the first approximation, results in land uplift where the load reduces (e.g., close to the meltwater sources) and land subsidence where the load increases (e.g., under the rising oceans). This effect is nowadays well known within the cryospheric and sea level communities. However, what is often not realized is that the solid earth response is a truly global effect: a localized mass change does cause a large deformation signal in its proximity, but also causes a change of the position of every other point on the Earth's surface. The theory of the Earth's elastic response to changing surface loads forms the basis of the 'sea-level equation', which allows sea-level fingerprints of continental mass change to be computed. In this paper, we provide the first dedicated analysis of global vertical land motion driven by land ice wastage. By means of established techniques to compute the solid earth elastic response to surface load changes and the most recent datasets of glacier and ice sheet mass change, we show that land ice loss currently leads to vertical deformation rates of several tenths of mm per year at mid-latitudes, especially over the Northern Hemisphere where most sources are located. In combination with the improved accuracy of space geodetic techniques (e.g., Global Navigation Satellite Systems), this means that the effect of ice melt is non-negligible over a large part of the continents. In particular, we show how deformation rates have been strongly varying through the last century, which implies that they should be properly modelled before interpreting and extrapolating recent observations of vertical land motion and sea level change.

Quantifying the climate impacts of albedo changes due to biofuel production: a comparison with biogeochemical effects

NASA Astrophysics Data System (ADS)

Caiazzo, Fabio; Malina, Robert; Staples, Mark D.; Wolfe, Philip J.; Yim, Steve H. L.; Barrett, Steven R. H.

2014-01-01

Lifecycle analysis is a tool widely used to evaluate the climate impact of greenhouse gas emissions attributable to the production and use of biofuels. In this paper we employ an augmented lifecycle framework that includes climate impacts from changes in surface albedo due to land use change. We consider eleven land-use change scenarios for the cultivation of biomass for middle distillate fuel production, and compare our results to previous estimates of lifecycle greenhouse gas emissions for the same set of land-use change scenarios in terms of CO2e per unit of fuel energy. We find that two of the land-use change scenarios considered demonstrate a warming effect due to changes in surface albedo, compared to conventional fuel, the largest of which is for replacement of desert land with salicornia cultivation. This corresponds to 222 gCO2e/MJ, equivalent to 3890% and 247% of the lifecycle GHG emissions of fuels derived from salicornia and crude oil, respectively. Nine of the land-use change scenarios considered demonstrate a cooling effect, the largest of which is for the replacement of tropical rainforests with soybean cultivation. This corresponds to - 161 gCO2e/MJ, or - 28% and - 178% of the lifecycle greenhouse gas emissions of fuels derived from soybean and crude oil, respectively. These results indicate that changes in surface albedo have the potential to dominate the climate impact of biofuels, and we conclude that accounting for changes in surface albedo is necessary for a complete assessment of the aggregate climate impacts of biofuel production and use.

Irrigated acreage and other land uses on the Snake River Plain, Idaho and eastern Oregon

USGS Publications Warehouse

Lindholm, Gerald F.; Goodell, S.A.

1986-01-01

Prompted by the need for a current, accurate, and repeatable delineation of irrigated acreage on the Snake River Plain, the U.S. Geological Survey entered into a cooperative agreement with the Idaho Department of Water Resources Image Analysis Facility and the U.S. Bureau of Reclamation to delineate 1980 land use form Landsat data. Irrigated acreage data were needed as input to groundwater flow models developed by the U.S. Geological Survey in a study of the regional aquifer system underlying the Snake River Plain. Single-date digital multispectral scanner data analyzed to delineate land-use classes. Source of irrigation water (surface water, ground water, and combined) was determined from county maps of 1975 water-related land use, data from previous investigations, and field checking. Surface-water diversions for irrigation on the Snake River Plain began in the 1840's. With the stimulus of Federal aid authorized by the Desert Land Act, Carey Act, and Reclamation Act, irrigated area increased rapidly in the early 1900's. By 1929, 2.2 million acres were irrigated. Ground water became and important source of irrigation water after World War II. In 1980, about 3.1 million acres of the Snake River Plain were irrigate: 2.0 million acres with surface water, 1.0 million with ground water, and 0.1 million with combined surface and ground water. About 5.2 million acres (half of the plain) are undeveloped rangeland, 1.0 million acres (one-tenth) are classified as barren. The remaining land is a mixture of dryland agriculture, water bodies, wetland, forests, and urban areas.

Consequences of land-cover misclassification in models of impervious surface

USGS Publications Warehouse

McMahon, G.

2007-01-01

Model estimates of impervious area as a function of landcover area may be biased and imprecise because of errors in the land-cover classification. This investigation of the effects of land-cover misclassification on impervious surface models that use National Land Cover Data (NLCD) evaluates the consequences of adjusting land-cover within a watershed to reflect uncertainty assessment information. Model validation results indicate that using error-matrix information to adjust land-cover values used in impervious surface models does not substantially improve impervious surface predictions. Validation results indicate that the resolution of the landcover data (Level I and Level II) is more important in predicting impervious surface accurately than whether the land-cover data have been adjusted using information in the error matrix. Level I NLCD, adjusted for land-cover misclassification, is preferable to the other land-cover options for use in models of impervious surface. This result is tied to the lower classification error rates for the Level I NLCD. ?? 2007 American Society for Photogrammetry and Remote Sensing.

Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

NASA Astrophysics Data System (ADS)

Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

2017-12-01

Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

NASA Astrophysics Data System (ADS)

Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

2018-06-01

Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

Basin-Scale Assessment of the Land Surface Water Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 Systems

NASA Technical Reports Server (NTRS)

Xia, Youlong; Cosgrove, Brian A.; Mitchell, Kenneth E.; Peters-Lidard, Christa D.; Ek, Michael B.; Brewer, Michael; Mocko, David; Kumar, Sujay V.; Wei, Helin; Meng, Jesse;

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

NASA Technical Reports Server (NTRS)

Peters-Lidar, Christa D.; Tian, Yudong; Kenneth, Tian; Harrison, Kenneth; Kumar, Sujay

2011-01-01

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).

ICESAT Laser Altimeter Pointing, Ranging and Timing Calibration from Integrated Residual Analysis

NASA Technical Reports Server (NTRS)

Luthcke, Scott B.; Rowlands, D. D.; Carabajal, C. C.; Harding, D. H.; Bufton, J. L.; Williams, T. A.

2003-01-01

On January 12, 2003 the Ice, Cloud and land Elevation Satellite (ICESat) was successfully placed into orbit. The ICESat mission carries the Geoscience Laser Altimeter System (GLAS), which has a primary measurement of short-pulse laser- ranging to the Earth s surface at 1064nm wavelength at a rate of 40 pulses per second. The instrument has collected precise elevation measurements of the ice sheets, sea ice roughness and thickness, ocean and land surface elevations and surface reflectivity. The accurate geolocation of GLAS s surface returns, the spots from which the laser energy reflects on the Earth s surface, is a critical issue in the scientific application of these data. Pointing, ranging, timing and orbit errors must be compensated to accurately geolocate the laser altimeter surface returns. Towards this end, the laser range observations can be fully exploited in an integrated residual analysis to accurately calibrate these geolocation/instrument parameters. ICESat laser altimeter data have been simultaneously processed as direct altimetry from ocean sweeps along with dynamic crossovers in order to calibrate pointing, ranging and timing. The calibration methodology and current calibration results are discussed along with future efforts.

Land subsidence in the San Joaquin Valley, California, USA, 2007-14

USGS Publications Warehouse

Sneed, Michelle; Brandt, Justin

2015-01-01

Rapid land subsidence was recently measured using multiple methods in two areas of the San Joaquin Valley (SJV): between Merced and Fresno (El Nido), and between Fresno and Bakersfield (Pixley). Recent land-use changes and diminished surface-water availability have led to increased groundwater pumping, groundwater-level declines, and land subsidence. Differential land subsidence has reduced the flow capacity of water-conveyance systems in these areas, exacerbating flood hazards and affecting the delivery of irrigation water. Vertical land-surface changes during 2007–2014 were determined by using Interferometric Synthetic Aperture Radar (InSAR), Continuous Global Positioning System (CGPS), and extensometer data. Results of the InSAR analysis indicate that about 7600 km2 subsided 50–540 mm during 2008–2010; CGPS and extensometer data indicate that these rates continued or accelerated through December 2014. The maximum InSAR-measured rate of 270 mm yr−1 occurred in the El Nido area, and is among the largest rates ever measured in the SJV. In the Pixley area, the maximum InSAR-measured rate during 2008–2010 was 90 mm yr−1. Groundwater was an important part of the water supply in both areas, and pumping increased when land use changed or when surface water was less available. This increased pumping caused groundwater-level declines to near or below historical lows during the drought periods 2007–2009 and 2012–present. Long-term groundwater-level and land-subsidence monitoring in the SJV is critical for understanding the interconnection of land use, groundwater levels, and subsidence, and evaluating management strategies that help mitigate subsidence hazards to infrastructure while optimizing water supplies.

Characterizing Impacts of Land Grabbing on Terrestrial Vegetation and Ecohydrologic change in Mozambique through Multiple-sensor Remote Sensing and Models

NASA Astrophysics Data System (ADS)

Flores, A. N.; Lakshmi, V.; Al-Barakat, R.; Maksimowicz, M.

2017-12-01

Land grabbing, the acquisition of large areas of land by external entities, results from interactions of complex global economic, social, and political processes. These transactions are controversial because they can result in large-scale disruptions to historical land uses, including increased intensity of agricultural practices and significant conversions in land cover. These large-scale disruptions have the potential to impact surface water and energy balance because vegetation controls the partitioning of incoming energy into latent and sensible heat fluxes and precipitation into runoff and infiltration. Because large-scale land acquisitions can impact local ecosystem services, it is important to document changes in terrestrial vegetation associated with these acquisitions to support the assessment of associated impacts on regional surface water and energy balance, spatiotemporal scales of those changes, and interactions and feedbacks with other processes, particularly in the atmosphere. We use remote sensing data from multiple satellite platforms to diagnose and characterize changes in terrestrial vegetation and ecohydrology in Mozambique during periods that bracket periods associated with significant. The Advanced very High Resolution Radiometer (AVHRR) sensor provides long-term continuous data that can document historical seasonal cycles of vegetation greenness. These data are augmented with analyses from Landsat multispectral data, which provides significantly higher spatial resolution. Here we quantify spatiotemporal changes in vegetation are associated with periods of significant land acquisitions in Mozambique. This analysis complements a suite of land-atmosphere modeling experiments designed to deduce potential changes in land surface water and energy budgets associated with these acquisitions. This work advance understanding of how telecouplings between global economic and political forcings and regional hydrology and climate.

Determining urban land uses through building-associated element attributes derived from lidar and aerial photographs

NASA Astrophysics Data System (ADS)

Meng, Xuelian

Urban land-use research is a key component in analyzing the interactions between human activities and environmental change. Researchers have conducted many experiments to classify urban or built-up land, forest, water, agriculture, and other land-use and land-cover types. Separating residential land uses from other land uses within urban areas, however, has proven to be surprisingly troublesome. Although high-resolution images have recently become more available for land-use classification, an increase in spatial resolution does not guarantee improved classification accuracy by traditional classifiers due to the increase of class complexity. This research presents an approach to detect and separate residential land uses on a building scale directly from remotely sensed imagery to enhance urban land-use analysis. Specifically, the proposed methodology applies a multi-directional ground filter to generate a bare ground surface from lidar data, then utilizes a morphology-based building detection algorithm to identify buildings from lidar and aerial photographs, and finally separates residential buildings using a supervised C4.5 decision tree analysis based on the seven selected building land-use indicators. Successful execution of this study produces three independent methods, each corresponding to the steps of the methodology: lidar ground filtering, building detection, and building-based object-oriented land-use classification. Furthermore, this research provides a prototype as one of the few early explorations of building-based land-use analysis and successful separation of more than 85% of residential buildings based on an experiment on an 8.25-km2 study site located in Austin, Texas.

Biophysical Impacts of Tropical Land Transformation from Forest to Oil Palm and Rubber Plantations in Indonesia

NASA Astrophysics Data System (ADS)

Knohl, Alexander; Meijide, Ana; Fan, Yuanchao; Gunawan, Dodo; Hölscher, Dirk; June, Tania; Niu, Furong; Panferov, Oleg; Ringeler, Andre; Röll, Alexander; Sabajo, Clifton; Tiralla, Nina

2016-04-01

Indonesia currently experiences rapid and large-scale land-use changes resulting in forest loss and the expansion of cash crop plantations such as oil palm and rubber. Such land transformations are associated with changes in surface properties that affect biophysical processes influencing the atmosphere. Yet, the overall effect of such land transformations on the atmosphere at local and regional scale remains unclear. In our study, we combine measurements of microclimate, transpiration via sap-flux, surface energy fluxes via eddy covariance, surface temperature via remote sensing, land surface (CLM) and regional climate modeling (WRF) for Jambi Province in Indonesia. Our microclimatic measurements showed that air temperature within the canopy was on average 0.7-0.8°C higher in monoculture plantations (oil palm and rubber) compared to forest. Remote sensing analysis using MODIS and Landsat revealed a higher canopy surface temperature for oil palm plantations (+1.5°C) compared to forest, but only little differences for rubber plantations. Transpiration (T) and evapotranspiration (ET) as well as the contribution of T to ET of oil palm showed a strong age-dependent increase. The sensible to latent heat flux ratio decreased with age. Overall, rubber plantations showed the lowest transpirations rates (320 mm year-1), oil palm intermediate rates (414 mm year-1), and forest the highest rates (558 mm year-1) indicating substantial differences in water use. Despite the differences in water use and the higher within-canopy and surface temperatures of the plantations compared to the forest, there was only a minor effect of land transformation on the atmosphere at the regional scale (<0.2 °C), irrespectively of the large spatial extend of the transformation. In conclusion, our study shows a strong local scale biophysical impact affecting the conditions at the stand level, which is however mitigated in the atmosphere at the regional level.

Biophysical Impacts of Tropical Land Transformation from Forest to Oil Palm and Rubber Plantations in Indonesia

NASA Astrophysics Data System (ADS)

Knohl, A.; Meijide, A.; Fan, Y.; Hölscher, D.; June, T.; Niu, F.; Panferov, O.; Ringeler, A.; Röll, A.; Sabajo, C.; Tiralla, N.

2015-12-01

Indonesia currently experiences rapid and large-scale land-use changes resulting in forest loss and the expansion of cash crop plantations such as oil palm and rubber. Such land transformations are associated with changes in surface properties that affect biophysical processes influencing the atmosphere. Yet, the overall effect of such land transformations on the atmosphere at local and regional scale remains unclear. In our study, we combine measurements of microclimate, transpiration via sap-flux, surface energy fluxes via eddy covariance, surface temperature via remote sensing, land surface (CLM) and regional climate modeling (WRF) for Jambi Province in Indonesia. Our microclimatic measurements showed that air temperature within the canopy was on average 0.7-0.8°C higher in monoculture plantations (oil palm and rubber) compared to forest. Remote sensing analysis using MODIS and Landsat revealed a higher canopy surface temperature for oil palm plantations (+1.5°C) compared to forest, but only little differences for rubber plantations. Transpiration (T) and evapotranspiration (ET) as well as the contribution of T to ET of oil palm showed a strong age-dependent increase. The sensible to latent heat flux ratio decreased with age. Overall, rubber plantations showed the lowest transpirations rates (320 mm year-1), oil palm intermediate rates (414 mm year-1), and forest the highest rates (558 mm year-1) indicating substantial differences in water use. Despite the differences in water use and the higher within-canopy and surface temperatures of the plantations compared to the forest, there was only a minor effect of land transformation on the atmosphere at the regional scale (<0.2 °C), irrespectively of the large spatial extend of the transformation. In conclusion, our study shows a strong local scale biophysical impact affecting the conditions at the stand level, which is however mitigated in the atmosphere at the regional level.

Relationships between landscape pattern and land surface temperature and their applications to the study of West Nile Virus: As case studies in cities of Indianapolis and Chicago, United States

NASA Astrophysics Data System (ADS)

Liu, Hua

A new synthesis of remote sensing and landscape ecology approaches was developed to establish relationships between the landscape patterns and land surface temperatures (LST) in the city of Indianapolis, Indiana, United States. Land use and land cover (LULC) and LST images were derived from Terra Satellite's Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. An analytical procedure using landscape metrics was developed, applying configuration analysis of landscape patterns and land surface temperature zones. Detailed landscape pattern analyses at the landscape and class scales were conducted using landscape metrics in the City of Indianapolis. The effects of spatial resolution on the identification of the relationship were examined in the same city. The best level of equalization between the LULC and LST maps was determined based on minimum distance analysis in landscape metrics space. The analyses of relationships between the landscape patterns and land surface temperatures, and scaling effects were applied to the spread of West Nile Virus (WNV) in the City of Chicago, Illinois. Results show that urban, forest, and grassland were the main landscape components in Indianapolis. They possessed relatively higher fractal dimensions but lower spatial aggregation levels in April 5, 2004, June 16, 2001, and October 3, 2000, but not in February 6, 2006. Obvious seasonal differences existed with the most distinct landscape pattern detected on February 6, 2006. Urban was the dominant LULC type in high-temperature zones, while water and vegetation mainly fell in low-temperature zones. For each individual date, the metrics of LST zones apparently corresponded to the metrics of LULC types. In the study of scaling-up effect analysis, Patch Percentage, Patch Density, and Landscape Shape index were found to be able to effectively quantify the spatial changes of LULC types and temperature zones at different scales without contradiction. Urban, forest, and grassland in each season were more easily affected by the process in Patch Density and Landscape Shape index. Ninety meters was believed to be the optimal spatial resolution to examine relationships between landscape patterns and LSTs in the City of Indianapolis. In the study of the spread of West Nile Virus in the City of Chicago, WNV was found to have been spread throughout all of Cook County since 2001. Landscape factors, like landscape aggregation index and areas of urban, grass, and water showed a strong correlation with the number of WNV infections. Socioeconomic conditions, like population above 65 years old also showed a strong relationship with the spread of WNV in Cook County. Thermal conditions of water had a lower but still significant correlation to the spread of WNV. This research offers an opportunity to explore the mechanism of interaction between urban landscape patterns and land surface temperatures at different spatial scales, and show the effects of landscape pattern and land surface temperature on the spread of West Nile Virus. This study can be useful for urban planning and environmental management practices in the studied areas. It also contributes to public health management and protection.

Fraser River watershed, Colorado : assessment of available water-quantity and water-quality data through water year 1997

USGS Publications Warehouse

Apodaca, Lori Estelle; Bails, Jeffrey B.

1999-01-01

The water-quantity and water-quality data for the Fraser River watershed through water year 1997 were compiled for ground-water and surface-water sites. In order to assess the water-quality data, the data were related to land use/land cover in the watershed. Data from 81 water-quantity and water-quality sites, which consisted of 9 ground-water sites and 72 surface-water sites, were available for analysis. However, the data were limited and frequently contained only one or two water-quality analyses per site.The Fraser River flows about 28 miles from its headwaters at the Continental Divide to the confluence with the Colorado River. Ground-water resources in the watershed are used for residential and municipal drinking-water supplies. Surface water is available for use, but water diversions in the upper parts of the watershed reduce the flow in the river. Land use/land cover in the watershed is predominantly forested land, but increasing urban development has the potential to affect the quantity and quality of the water resources.Analysis of the limited ground-water data in the watershed indicates that changes in the land use/land cover affect the shallow ground-water quality. Water-quality data from eight shallow monitoring wells in the alluvial aquifer show that iron and manganese concentrations exceeded the U.S. Environmental Protection Agency secondary maximum contaminant level. Radon concentrations from these monitoring wells exceeded the U.S. Environmental Protection Agency proposed maximum contaminant level. The proposed radon contaminant level is currently being revised. The presence of volatile organic compounds at two monitoring wells in the watershed indicates that land use affects the shallow ground water. In addition, bacteria detected in three samples are at concentrations that would be a concern for public health if the water was to be used as a drinking supply. Methylene blue active substances were detected in the ground water at some sites and are a possible indication of contamination from wastewater. Age of the alluvial ground water ranged from 10 to 30 years; therefore, results of land-management practices to improve water quality may not be apparent for many years.Surface-water-quality data for the Fraser River watershed are sparse. The surface-water-quality data show that elevated concentrations of selected constituents generally are related to specific land uses in the watershed. For one sample (about 2 percent; 1 of 53), dissolved manganese concentration exceeded the U.S. Environmental Protection Agency secondary maximum contaminant level. Two samples from two surface-water sites in the watershed exceeded the un-ionized ammonia chronic criterion. Spatial distribution of nutrient species (ammonia, nitrite, nitrate, and total phosphorus) shows that elevated concentrations occur primarily downstream from urban areas. Sites with five or more years of record were analyzed for temporal trends in concentration of nutrient species. Downward trends were identified for ammonia and nitrite for three surface-water sites. For nitrate, no trends were observed at two sites and a downward trend was observed at one site. Total phosphorus showed no trend for the site near the mouth of the Fraser River. Downward trends in the nutrient species may reflect changes in the wastewater-treatment facilities in the watershed. Bacteria sampling completed in the watershed indicates that more bacteria are present in the water near urban settings.The limited ground-water and surface-water data for the Fraser River watershed provide a general assessment of the quantity and quality of these resources. Concentrations of most water-quality constituents generally are less than ground- and surface-water-quality standards, but the presence of bacteria, some volatile organic compounds, methylene blue active substances, and increased nutrients in the water may indicate that land use is affecting the water quality..

Aquifer configuration and geostructural links control the groundwater quality in thin-bedded carbonate-siliciclastic alternations of the Hainich CZE, central Germany

NASA Astrophysics Data System (ADS)

Kohlhepp, Bernd; Lehmann, Robert; Seeber, Paul; Küsel, Kirsten; Trumbore, Susan E.; Totsche, Kai U.

2017-12-01

The quality of near-surface groundwater reservoirs is controlled, but also threatened, by manifold surface-subsurface interactions. Vulnerability studies typically evaluate the variable interplay of surface factors (land management, infiltration patterns) and subsurface factors (hydrostratigraphy, flow properties) in a thorough way, but disregard the resulting groundwater quality. Conversely, hydrogeochemical case studies that address the chemical evolution of groundwater often lack a comprehensive analysis of the structural buildup. In this study, we aim to reconstruct the actual spatial groundwater quality pattern from a synoptic analysis of the hydrostratigraphy, lithostratigraphy, pedology and land use in the Hainich Critical Zone Exploratory (Hainich CZE). This CZE represents a widely distributed yet scarcely described setting of thin-bedded mixed carbonate-siliciclastic strata in hillslope terrains. At the eastern Hainich low-mountain hillslope, bedrock is mainly formed by alternated marine sedimentary rocks of the Upper Muschelkalk (Middle Triassic) that partly host productive groundwater resources. Spatial patterns of the groundwater quality of a 5.4 km long well transect are derived by principal component analysis and hierarchical cluster analysis. Aquifer stratigraphy and geostructural links were deduced from lithological drill core analysis, mineralogical analysis, geophysical borehole logs and mapping data. Maps of preferential recharge zones and recharge potential were deduced from digital (soil) mapping, soil survey data and field measurements of soil hydraulic conductivities (Ks). By attributing spatially variable surface and subsurface conditions, we were able to reconstruct groundwater quality clusters that reflect the type of land management in their preferential recharge areas, aquifer hydraulic conditions and cross-formational exchange via caprock sinkholes or ascending flow. Generally, the aquifer configuration (spatial arrangement of strata, valley incision/outcrops) and related geostructural links (enhanced recharge areas, karst phenomena) control the role of surface factors (input quality and locations) vs. subsurface factors (water-rock interaction, cross-formational flow) for groundwater quality in the multi-layered aquifer system. Our investigation reveals general properties of alternating sequences in hillslope terrains that are prone to forming multi-layered aquifer systems. This synoptic analysis is fundamental and indispensable for a mechanistic understanding of ecological functioning, sustainable resource management and protection.

Terrain stiffness and ankle biomechanics during simulated half-squat parachute landing.

PubMed

Niu, Wenxin; Fan, Yubo

2013-12-01

A hard surface is potentially one of the risk factors for ankle injuries during parachute landing, but this has never been experimentally validated. This study was designed to evaluate the effects of terrain stiffness on ankle biomechanics during half-squat parachute landing (HSPL). Eight male and eight female healthy participants landed on three surfaces with standard HSPL technique. The three surfaces were cushioned mats with different thicknesses (0 mm, 4 mm, and 8 mm). The effects of terrain hardness and gender and their interaction with ground reaction forces, ankle kinematics, and electromyograms of selected lower-extremity muscles were statistically analyzed with multivariate analysis of variance. The effects of terrain stiffness and the interaction between factors on all variables were not statistically significant. The effects of gender were not statistically significant on most variables. The peak angular velocity of the ankle dorsiflexion was significantly lower in men (mean 1345 degree x s(-1)) than in women (mean 1965 degree x s(-1)). A spongy surface even eliminated the differences between men compared to women in the activity of their tibialis anterior during simulated HSPL. Terrain stiffness, in the ranges tested, did not appear to influence ankle biomechanics among individuals performing HSPL. Additional studies are required to know whether this finding is applicable to realistic parachuting.

Effects of leaf area index on the coupling between water table, land surface energy fluxes, and planetary boundary layer at the regional scale

NASA Astrophysics Data System (ADS)

Lu, Y.; Rihani, J.; Langensiepen, M.; Simmer, C.

2013-12-01

Vegetation plays an important role in the exchange of moisture and energy at the land surface. Previous studies indicate that vegetation increases the complexity of the feedbacks between the atmosphere and subsurface through processes such as interception, root water uptake, leaf surface evaporation, and transpiration. Vegetation cover can affect not only the interaction between water table depth and energy fluxes, but also the development of the planetary boundary layer. Leaf Area Index (LAI) is shown to be a major factor influencing these interactions. In this work, we investigate the sensitivity of water table, surface energy fluxes, and atmospheric boundary layer interactions to LAI as a model input. We particularly focus on the role LAI plays on the location and extent of transition zones of strongest coupling and how this role changes over seasonal timescales for a real catchment. The Terrestrial System Modelling Platform (TerrSysMP), developed within the Transregional Collaborative Research Centre 32 (TR32), is used in this study. TerrSysMP consists of the variably saturated groundwater model ParFlow, the land surface model Community Land Model (CLM), and the regional climate and weather forecast model COSMO (COnsortium for Small-scale Modeling). The sensitivity analysis is performed over a range of LAI values for different vegetation types as extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset for the Rur catchment in Germany. In the first part of this work, effects of vegetation structure on land surface energy fluxes and their connection to water table dynamics are studied using the stand-alone CLM and the coupled subsurface-surface components of TerrSysMP (ParFlow-CLM), respectively. The interconnection between LAI and transition zones of strongest coupling are investigated and analyzed through a subsequent set of subsurface-surface-atmosphere coupled simulations implementing the full TerrSysMP model system.

New Approach for Monitoring Seismic and Volcanic Activities Using Microwave Radiometer Data

NASA Astrophysics Data System (ADS)

Maeda, Takashi; Takano, Tadashi

Interferograms formed from the data of satellite-borne synthetic aperture radar (SAR) enable us to detect slight land-surface deformations related to volcanic eruptions and earthquakes. Currently, however, we cannot determine when land-surface deformations occurred with high time resolution since the time lag between two scenes of SAR used to form interferograms is longer than the recurrent period of the satellite carrying it (several tens of days). In order to solve this problem, we are investigating new approach to monitor seismic and vol-canic activities with higher time resolution from satellite-borne sensor data, and now focusing on a satellite-borne microwave radiometer. It is less subject to clouds and rainfalls over the ground than an infrared spectrometer, so more suitable to observe an emission from land sur-faces. With this advantage, we can expect that thermal microwave energy by increasing land surface temperatures is detected before a volcanic eruption. Additionally, laboratory experi-ments recently confirmed that rocks emit microwave energy when fractured. This microwave energy may result from micro discharges in the destruction of materials, or fragment motions with charged surfaces of materials. We first extrapolated the microwave signal power gener-ated by rock failures in an earthquake from the experimental results and concluded that the microwave signals generated by rock failures near the land surface are strong enough to be detected by a satellite-borne radiometer. Accordingly, microwave energy generated by rock failures associated with a seismic activity is likely to be detected as well. However, a satellite-borne microwave radiometer has a serious problem that its spatial res-olution is too coarse compared to SAR or an infrared spectrometer. In order to raise the possibility of detection, a new methodology to compensate the coarse spatial resolution is es-sential. Therefore, we investigated and developed an analysis method to detect local and faint changes from the data of the Advanced Microwave Scanning Radiometer for Earth-Observation System (AMSR-E) aboard the Aqua satellite, and then an algorithm to evaluate microwave energy from land surfaces. Finally, using this algorithm, we have detected characteristic microwave signals emitted from land surfaces in association with some large earthquakes which occurred in Morocco (2004), Sumatra (2007) and Wenchuan (2008) and some large volcanic eruptions which occurred at Reventador in Ecuador (2002) and Chaiten in Chile (2008). In this presentation, the results of these case studies are presented.

Regional surface soil heat flux estimate from multiple remote sensing data in a temperate and semiarid basin

NASA Astrophysics Data System (ADS)

Li, Nana; Jia, Li; Lu, Jing; Menenti, Massimo; Zhou, Jie

2017-01-01

The regional surface soil heat flux (G0) estimation is very important for the large-scale land surface process modeling. However, most of the regional G0 estimation methods are based on the empirical relationship between G0 and the net radiation flux. A physical model based on harmonic analysis was improved (referred to as "HM model") and applied over the Heihe River Basin northwest China with multiple remote sensing data, e.g., FY-2C, AMSR-E, and MODIS, and soil map data. The sensitivity analysis of the model was studied as well. The results show that the improved model describes the variation of G0 well. Land surface temperature (LST) and thermal inertia (Γ) are the two key input variables to the HM model. Compared with in situ G0, there are some differences, mainly due to the differences between remote-sensed LST and the in situ LST. The sensitivity analysis shows that the errors from -7 to -0.5 K in LST amplitude and from -300 to 300 J m-2 K-1 s-0.5 in Γ will cause about 20% errors, which are acceptable for G0 estimation.

Landsat - What is operational in water resources

NASA Technical Reports Server (NTRS)

Middleton, E. M.; Munday, J. C., Jr.

1981-01-01

Applications of Landsat data in hydrology and water quality measurement were examined to determine which applications are operational. In hydrology, the principal applications have been surface water inventory, and land cover analysis for (1) runoff modeling and (2) abatement planning for non-point pollution and erosion. In water quality measurement, the principal applications have been: (1) trophic state assessment, and (2) measurement of turbidity and suspended sediment. The following applications were found to be operational: mapping of surface water, snow cover, and land cover (USGS Level 1) for watershed applications; measurement of turbidity, Secchi disk depth, suspended sediment concentration, and water depth.

Radiation analysis for manned missions to the Jupiter system

NASA Technical Reports Server (NTRS)

De Angelis, G.; Clowdsley, M. S.; Nealy, J. E.; Tripathi, R. K.; Wilson, J. W.

2004-01-01

An analysis for manned missions targeted to the Jovian system has been performed in the framework of the NASA RASC (Revolutionary Aerospace Systems Concepts) program on Human Exploration beyond Mars. The missions were targeted to the Jupiter satellite Callisto. The mission analysis has been divided into three main phases, namely the interplanetary cruise, the Jupiter orbital insertion, and the surface landing and exploration phases. The interplanetary phase is based on departure from the Earth-Moon L1 point. Interplanetary trajectories based on the use of different propulsion systems have been considered, with resulting overall cruise phase duration varying between two and five years. The Jupiter-approach and the orbital insertion trajectories are considered in detail, with the spacecraft crossing the Jupiter radiation belts and staying around the landing target. In the surface exploration phase the stay on the Callisto surface is considered. The satellite surface composition has been modeled based on the most recent results from the GALILEO spacecraft. In the transport computations the surface backscattering has been duly taken into account. Particle transport has been performed with the HZETRN heavy ion code for hadrons and with an in-house developed transport code for electrons and bremsstrahlung photons. The obtained doses have been compared to dose exposure limits. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

Radiation analysis for manned missions to the Jupiter system.

PubMed

De Angelis, G; Clowdsley, M S; Nealy, J E; Tripathi, R K; Wilson, J W

2004-01-01

An analysis for manned missions targeted to the Jovian system has been performed in the framework of the NASA RASC (Revolutionary Aerospace Systems Concepts) program on Human Exploration beyond Mars. The missions were targeted to the Jupiter satellite Callisto. The mission analysis has been divided into three main phases, namely the interplanetary cruise, the Jupiter orbital insertion, and the surface landing and exploration phases. The interplanetary phase is based on departure from the Earth-Moon L1 point. Interplanetary trajectories based on the use of different propulsion systems have been considered, with resulting overall cruise phase duration varying between two and five years. The Jupiter-approach and the orbital insertion trajectories are considered in detail, with the spacecraft crossing the Jupiter radiation belts and staying around the landing target. In the surface exploration phase the stay on the Callisto surface is considered. The satellite surface composition has been modeled based on the most recent results from the GALILEO spacecraft. In the transport computations the surface backscattering has been duly taken into account. Particle transport has been performed with the HZETRN heavy ion code for hadrons and with an in-house developed transport code for electrons and bremsstrahlung photons. The obtained doses have been compared to dose exposure limits. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

40 CFR 503.8 - Sampling and analysis.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 30 2011-07-01 2011-07-01 false Sampling and analysis. 503.8 Section... FOR THE USE OR DISPOSAL OF SEWAGE SLUDGE General Provisions § 503.8 Sampling and analysis. (a) Sampling. Representative samples of sewage sludge that is applied to the land, placed on a surface disposal...

40 CFR 503.8 - Sampling and analysis.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 29 2010-07-01 2010-07-01 false Sampling and analysis. 503.8 Section... FOR THE USE OR DISPOSAL OF SEWAGE SLUDGE General Provisions § 503.8 Sampling and analysis. (a) Sampling. Representative samples of sewage sludge that is applied to the land, placed on a surface disposal...

Assessment of the water and energy budget simulation of three land surface models: CLM4.5, CoLM2014, and CoLM2005

NASA Astrophysics Data System (ADS)

Li, C.; Lu, H.; Wen, X.

2015-12-01

Land surface model (LSM), which simulates energy, water and momentum exchanges between land and atmosphere, is an important component of Earth System Models (ESM). As shown in CMIP5, different ESMs usually use different LSMs and represent various land surface status. In order to select a land surface model which could be embedded into the ESM developed in Tsinghua University, we firstly evaluate the performance of three LSMs: Community Land Model (CLM4.5) and two different versions of Common Land Model (CoLM2005 and CoLM2014). All of three models were driven by CRUNCEP data and simulation results from 1980 to 2010 were used in this study. Diagnostic data provided by NCAR, global latent and sensible heat flux map estimated by Jung, net radiation from SRB, and in situ observation collected from FluxNet were used as reference data. Two variables, surface runoff and snow depth, were used for evaluating the model performance in water budget simulation, while three variables including net radiation, sensible heat, and latent heat were used for assessing energy budget simulation. For 30 years averaged runoff, global average value of Colm2014 is 0.44mm/day and close to the diagnostic value of 0.75 mm/day, while that of Colm2005 is 0.44mm/day and that of CLM is 0.20mm/day. For snow depth simulation, three models all have overestimation in the Northern Hemisphere and underestimation in the Southern Hemisphere compare to diagnostic data. For 30 years energy budget simulation, at global scale, CoLM2005 performs best in latent heat estimation, CoLM2014 performs best in sensible heat simulation, and CoLM2005 and CoLM2014 make similar performance in net radiation estimation but is still better than CLM. At regional and local scale, comparing to the four years average of flux tower observation, RMSE of CoLM2005 is the smallest for latent heat (9.717 W/m2) , and for sensible heat simulation, RMSE of CoLM2005 (13.048 W/m2) is slightly greater than CLM(10.767 W/m2) but still better than CoLM2014(30.085 W/m2). Our analysis shows that both CoLM 2005 and CoLM 2014 are able to reproduce comparable land surface water and energy fluxes. It implies that the ESM developed in Tsinghua University may use CoLM, a LSM developed and maintained in China, as the land surface component. .

Characterizing Temporal and Spatial Changes in Land Surface Temperature across the Amazon Basin using Thermal and Infrared Satellite Data

NASA Astrophysics Data System (ADS)

Cak, A. D.

2017-12-01

The Amazon Basin has faced innumerable pressures in recent years, including logging, mining and resource extraction, agricultural expansion, road building, and urbanization. These changes have drastically altered the landscape, transforming a predominantly forested environment into a mosaic of different types of land cover. The resulting fragmentation has caused dramatic and negative impacts on its structure and function, including on biodiversity and the transfer of water and energy to and from soil, vegetation, and the atmosphere (e.g., evapotranspiration). Because evapotranspiration from forested areas, which is affected by factors including temperature and water availability, plays a significant role in water dynamics in the Amazon Basin, measuring land surface temperature (LST) across the region can provide a dynamic assessment of hydrological, vegetation, and land use and land cover changes. It can also help to identify widespread urban development, which often has a higher LST signal relative to surrounding vegetation. Here, we discuss results from work to measure and identify drivers of change in LST across the entire Amazon Basin through analysis of past and current thermal and infrared satellite imagery. We leverage cloud computing resources in new ways to allow for more efficient analysis of imagery over the Amazon Basin across multiple years and multiple sensors. We also assess potential drivers of change in LST using spatial and multivariate statistical analyses with additional data sources of land cover, urban development, and demographics.

New Versions of MISR Aerosol and Land Surface Products Available

Atmospheric Science Data Center

2018-02-14

New Versions of MISR Aerosol and Land Surface Products Available Monday, February 12, ... the release of new versions of the MISR Level 2 (L2) Aerosol Product, the MISR L2 Land Surface Product, and the Level 3 (L3) Component Global Aerosol and Land Surface Products.   The new MISR L2 Aerosol Product ...

Assimilation of Freeze - Thaw Observations into the NASA Catchment Land Surface Model

NASA Technical Reports Server (NTRS)

Farhadi, Leila; Reichle, Rolf H.; DeLannoy, Gabrielle J. M.; Kimball, John S.

2014-01-01

The land surface freeze-thaw (F-T) state plays a key role in the hydrological and carbon cycles and thus affects water and energy exchanges and vegetation productivity at the land surface. In this study, we developed an F-T assimilation algorithm for the NASA Goddard Earth Observing System, version 5 (GEOS-5) modeling and assimilation framework. The algorithm includes a newly developed observation operator that diagnoses the landscape F-T state in the GEOS-5 Catchment land surface model. The F-T analysis is a rule-based approach that adjusts Catchment model state variables in response to binary F-T observations, while also considering forecast and observation errors. A regional observing system simulation experiment was conducted using synthetically generated F-T observations. The assimilation of perfect (error-free) F-T observations reduced the root-mean-square errors (RMSE) of surface temperature and soil temperature by 0.206 C and 0.061 C, respectively, when compared to model estimates (equivalent to a relative RMSE reduction of 6.7 percent and 3.1 percent, respectively). For a maximum classification error (CEmax) of 10 percent in the synthetic F-T observations, the F-T assimilation reduced the RMSE of surface temperature and soil temperature by 0.178 C and 0.036 C, respectively. For CEmax=20 percent, the F-T assimilation still reduces the RMSE of model surface temperature estimates by 0.149 C but yields no improvement over the model soil temperature estimates. The F-T assimilation scheme is being developed to exploit planned operational F-T products from the NASA Soil Moisture Active Passive (SMAP) mission.

Large-Eddy Atmosphere-Land-Surface Modelling over Heterogeneous Surfaces: Model Development and Comparison with Measurements

NASA Astrophysics Data System (ADS)

Shao, Yaping; Liu, Shaofeng; Schween, Jan H.; Crewell, Susanne

2013-08-01

A model is developed for the large-eddy simulation (LES) of heterogeneous atmosphere and land-surface processes. This couples a LES model with a land-surface scheme. New developments are made to the land-surface scheme to ensure the adequate representation of atmosphere-land-surface transfers on the large-eddy scale. These include, (1) a multi-layer canopy scheme; (2) a method for flux estimates consistent with the large-eddy subgrid closure; and (3) an appropriate soil-layer configuration. The model is then applied to a heterogeneous region with 60-m horizontal resolution and the results are compared with ground-based and airborne measurements. The simulated sensible and latent heat fluxes are found to agree well with the eddy-correlation measurements. Good agreement is also found in the modelled and observed net radiation, ground heat flux, soil temperature and moisture. Based on the model results, we study the patterns of the sensible and latent heat fluxes, how such patterns come into existence, and how large eddies propagate and destroy land-surface signals in the atmosphere. Near the surface, the flux and land-use patterns are found to be closely correlated. In the lower boundary layer, small eddies bearing land-surface signals organize and develop into larger eddies, which carry the signals to considerably higher levels. As a result, the instantaneous flux patterns appear to be unrelated to the land-use patterns, but on average, the correlation between them is significant and persistent up to about 650 m. For a given land-surface type, the scatter of the fluxes amounts to several hundred W { m }^{-2}, due to (1) large-eddy randomness; (2) rapid large-eddy and surface feedback; and (3) local advection related to surface heterogeneity.

Incorporating Land-Use Mapping Uncertainty in Remote Sensing Based Calibration of Land-Use Change Models

NASA Astrophysics Data System (ADS)

Cockx, K.; Van de Voorde, T.; Canters, F.; Poelmans, L.; Uljee, I.; Engelen, G.; de Jong, K.; Karssenberg, D.; van der Kwast, J.

2013-05-01

Building urban growth models typically involves a process of historic calibration based on historic time series of land-use maps, usually obtained from satellite imagery. Both the remote sensing data analysis to infer land use and the subsequent modelling of land-use change are subject to uncertainties, which may have an impact on the accuracy of future land-use predictions. Our research aims to quantify and reduce these uncertainties by means of a particle filter data assimilation approach that incorporates uncertainty in land-use mapping and land-use model parameter assessment into the calibration process. This paper focuses on part of this work, more in particular the modelling of uncertainties associated with the impervious surface cover estimation and urban land-use classification adopted in the land-use mapping approach. Both stages are submitted to a Monte Carlo simulation to assess their relative contribution to and their combined impact on the uncertainty in the derived land-use maps. The approach was applied on the central part of the Flanders region (Belgium), using a time-series of Landsat/SPOT-HRV data covering the years 1987, 1996, 2005 and 2012. Although the most likely land-use map obtained from the simulation is very similar to the original classification, it is shown that the errors related to the impervious surface sub-pixel fraction estimation have a strong impact on the land-use map's uncertainty. Hence, incorporating uncertainty in the land-use change model calibration through particle filter data assimilation is proposed to address the uncertainty observed in the derived land-use maps and to reduce uncertainty in future land-use predictions.

Climate change and socio-economic scenarios, land use modelling implications on water resources in an inner alpine area, Switzerland

NASA Astrophysics Data System (ADS)

Rey, Emmanuel; Schneider, Flurina; Liniger, Hanspeter; Weingartner, Rolf; Herweg, Karl

2014-05-01

The MontanAqua project aims to study the water resources management in the region Sierre-Montana (Valais, Switzerland). Land use is known to have an influence on the water resources (soil moisture dynamic, soil sealing, surface runoff and deep percolation). Thus land use modelling is of importance for the water resources management. An actual land use map was produced using infrared imagery (Niklaus 2012, Fig.1). Land use changes are known to be mainly drived by socio-economic factors as well as climatic factors (Dolman et al. 2003). Potential future Land uses was separatly predicted according to 1-. socio-economic and 2-. climatic/abiotic drivers : 1. 4 socio-economic scenarios were developped with stakeholders (Schneider et al. 2013) between 2010 and 2012. We modeled those socio-economic scenarios into a GIS application using Python programming (ModelBuilder in ArcGIS 10) to get a cartographic transcription of the wishes of the stakeholders for their region in 2050. 2. Uncorrelated climatic and abiotic drivers were used in a BIOMOD2 (Georges et al. 2013) framework. 4 models were used: Maximum Entropy (MAXENT), Multiple Adaptive Regression Splines (MARS), Classification Tree Analysis (CTA) and the Flexible Discriminant Analysis (FDA) to predict grassland, alpine pasture, vineyards and forest in our study region. Climatic scenarios were then introduced into the models to predict potential land use in 2050 driven only by climatic and abiotic factors The comparison of all the outputs demonstrates that the socio-economic drivers will have a more important impact in the region than the climatic drivers (e.g. -70% grassland surface for the worst socio-economic scenario vs. -40% of grassland surface for the worst climatic models). Further analysis also brings out the sensitivity of the grassland/alpine pasture system to the climate change and to socio-economic changes. Future work will be to cross the different land use maps obtained by the two model types and to use them to implement soil moisture and evaporation data for the near-future in the region Sierre-Montana. REFERENCES Niklaus M. 2012. An Object-oriented Approach for Mapping Current Land Use/Land Cover in the Study Area Crans-Montana-Sierre, Valais. MSc, Geography Institute, University of Bern Dolman A.J., Verhagen A. & Rovers C.A. 2003. Global environmental change and land use. Kluwer Academic Publisher. Dordrecht. Schneider F. & Rist S. 2013. Envisioning sustainable water futures in a transdisciplinary learning process: combining normative, explorative, and participatory scenario approaches. Sustainability Science, in press. Georges D. & Thuiller W. 2012. An example of species distribution modelling with biomod2. biomod2 version : 2.0.17

Land use change analysis using spectral similarity and vegetation indices and its effect on runoff and sediment yield in tropical environment

NASA Astrophysics Data System (ADS)

Christanto, N.; Sartohadi, J.; Setiawan, M. A.; Shrestha, D. B. P.; Jetten, V. G.

2018-04-01

Land use change influences the hydrological as well as landscape processes such as runoff and sediment yields. The main objectives of this study are to assess the land use change and its impact on the runoff and sediment yield of the upper Serayu Catchment. Land use changes of 1991 to 2014 have been analyzed. Spectral similarity and vegetation indices were used to classify the old image. Therefore, the present and the past images are comparable. The influence of the past and present land use on runoff and sediment yield has been compared with field measurement. The effect of land use changes shows the increased surface runoff which is the result of change in the curve number (CN) values. The study shows that it is possible to classify previously obtained image based on spectral characteristics and indices of major land cover types derived from recently obtained image. This avoids the necessity of having training samples which will be difficult to obtain. On the other hand, it also demonstrates that it is possible to link land cover changes with land degradation processes and finally to sedimentation in the reservoir. The only condition is the requirement for having the comparable dataset which should not be difficult to generate. Any variation inherent in the data which are other than surface reflectance has to be corrected.

Results from Assimilating AMSR-E Soil Moisture Estimates into a Land Surface Model Using an Ensemble Kalman Filter in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Crosson, William L.; Case, Jonathan L.; Hale, Robert

2010-01-01

Improve simulations of soil moisture/temperature, and consequently boundary layer states and processes, by assimilating AMSR-E soil moisture estimates into a coupled land surface-mesoscale model Provide a new land surface model as an option in the Land Information System (LIS)

Validation of Land Surface Temperature from Sentinel-3

NASA Astrophysics Data System (ADS)

Ghent, D.

2017-12-01

One of the main objectives of the Sentinel-3 mission is to measure sea- and land-surface temperature with high-end accuracy and reliability in support of environmental and climate monitoring in an operational context. Calibration and validation are thus key criteria for operationalization within the framework of the Sentinel-3 Mission Performance Centre (S3MPC). Land surface temperature (LST) has a long heritage of satellite observations which have facilitated our understanding of land surface and climate change processes, such as desertification, urbanization, deforestation and land/atmosphere coupling. These observations have been acquired from a variety of satellite instruments on platforms in both low-earth orbit and in geostationary orbit. Retrieval accuracy can be a challenge though; surface emissivities can be highly variable owing to the heterogeneity of the land, and atmospheric effects caused by the presence of aerosols and by water vapour absorption can give a bias to the underlying LST. As such, a rigorous validation is critical in order to assess the quality of the data and the associated uncertainties. Validation of the level-2 SL_2_LST product, which became freely available on an operational basis from 5th July 2017 builds on an established validation protocol for satellite-based LST. This set of guidelines provides a standardized framework for structuring LST validation activities. The protocol introduces a four-pronged approach which can be summarised thus: i) in situ validation where ground-based observations are available; ii) radiance-based validation over sites that are homogeneous in emissivity; iii) intercomparison with retrievals from other satellite sensors; iv) time-series analysis to identify artefacts on an interannual time-scale. This multi-dimensional approach is a necessary requirement for assessing the performance of the LST algorithm for the Sea and Land Surface Temperature Radiometer (SLSTR) which is designed around biome-based coefficients, thus emphasizing the importance of non-traditional forms of validation such as radiance-based techniques. Here we present examples of the ongoing routine application of the protocol to operational Sentinel-3 LST data.

Effects of rainfall patterns and land cover on the subsurface flow generation of sloping Ferralsols in southern China

PubMed Central

Yang, Jie; Tang, Chongjun; Chen, Lihua; Liu, Yaojun; Wang, Lingyun

2017-01-01

Rainfall patterns and land cover are two important factors that affect the runoff generation process. To determine the surface and subsurface flows associated with different rainfall patterns on sloping Ferralsols under different land cover types, observational data related to surface and subsurface flows from 5 m × 15 m plots were collected from 2010 to 2012. The experiment was conducted to assess three land cover types (grass, litter cover and bare land) in the Jiangxi Provincial Soil and Water Conservation Ecological Park. During the study period, 114 natural rainfall events produced subsurface flow and were divided into four groups using k-means clustering according to rainfall duration, rainfall depth and maximum 30-min rainfall intensity. The results showed that the total runoff and surface flow values were highest for bare land under all four rainfall patterns and lowest for the covered plots. However, covered plots generated higher subsurface flow values than bare land. Moreover, the surface and subsurface flows associated with the three land cover types differed significantly under different rainfall patterns. Rainfall patterns with low intensities and long durations created more subsurface flow in the grass and litter cover types, whereas rainfall patterns with high intensities and short durations resulted in greater surface flow over bare land. Rainfall pattern I had the highest surface and subsurface flow values for the grass cover and litter cover types. The highest surface flow value and lowest subsurface flow value for bare land occurred under rainfall pattern IV. Rainfall pattern II generated the highest subsurface flow value for bare land. Therefore, grass or litter cover are able to convert more surface flow into subsurface flow under different rainfall patterns. The rainfall patterns studied had greater effects on subsurface flow than on total runoff and surface flow for covered surfaces, as well as a greater effect on surface flows associated with bare land. PMID:28792507

Aeroacoustic Analysis of a Simplified Landing Gear

NASA Technical Reports Server (NTRS)

Lockard, David P.; Khorrami, Mehdi, R.; Li, Fei

2004-01-01

A hybrid approach is used to investigate the noise generated by a simplified landing gear without small scale parts such as hydraulic lines and fasteners. The Ffowcs Williams and Hawkings equation is used to predict the noise at far-field observer locations from flow data provided by an unsteady computational fluid dynamics calculation. A simulation with 13 million grid points has been completed, and comparisons are made between calculations with different turbulence models. Results indicate that the turbulence model has a profound effect on the levels and character of the unsteadiness. Flow data on solid surfaces and a set of permeable surfaces surrounding the gear have been collected. Noise predictions using the porous surfaces appear to be contaminated by errors caused by large wake fluctuations passing through the surfaces. However, comparisons between predictions using the solid surfaces with the near-field CFD solution are in good agreement giving confidence in the far-field results.

Effect of water table dynamics on land surface hydrologic memory

NASA Astrophysics Data System (ADS)

Lo, Min-Hui; Famiglietti, James S.

2010-11-01

The representation of groundwater dynamics in land surface models has received considerable attention in recent years. Most studies have found that soil moisture increases after adding a groundwater component because of the additional supply of water to the root zone. However, the effect of groundwater on land surface hydrologic memory (persistence) has not been explored thoroughly. In this study we investigate the effect of water table dynamics on National Center for Atmospheric Research Community Land Model hydrologic simulations in terms of land surface hydrologic memory. Unlike soil water or evapotranspiration, results show that land surface hydrologic memory does not always increase after adding a groundwater component. In regions where the water table level is intermediate, land surface hydrologic memory can even decrease, which occurs when soil moisture and capillary rise from groundwater are not in phase with each other. Further, we explore the hypothesis that in addition to atmospheric forcing, groundwater variations may also play an important role in affecting land surface hydrologic memory. Analyses show that feedbacks of groundwater on land surface hydrologic memory can be positive, negative, or neutral, depending on water table dynamics. In regions where the water table is shallow, the damping process of soil moisture variations by groundwater is not significant, and soil moisture variations are mostly controlled by random noise from atmospheric forcing. In contrast, in regions where the water table is very deep, capillary fluxes from groundwater are small, having limited potential to affect soil moisture variations. Therefore, a positive feedback of groundwater to land surface hydrologic memory is observed in a transition zone between deep and shallow water tables, where capillary fluxes act as a buffer by reducing high-frequency soil moisture variations resulting in longer land surface hydrologic memory.

Observations of land-atmosphere interactions using satellite data

NASA Astrophysics Data System (ADS)

Green, Julia; Gentine, Pierre; Konings, Alexandra; Alemohammad, Hamed; Kolassa, Jana

2016-04-01

Observations of land-atmosphere interactions using satellite data Julia Green (1), Pierre Gentine (1), Alexandra Konings (1,2), Seyed Hamed Alemohammad (3), Jana Kolassa (4) (1) Columbia University, Earth and Environmental Engineering, NY, NY, USA, (2) Stanford University, Environmental Earth System Science, Stanford, CA, USA, (3) Massachusetts Institute of Technology, Civil and Environmental Engineering, Cambridge, MA, USA, (4) National Aeronautics and Space Administration/Goddard Space Flight Center, Greenbelt, MD, USA. Previous studies of global land-atmosphere hotspots have often relied solely on data from global models with the consequence that they are sensitive to model error. On the other hand, by only analyzing observations, it can be difficult to distinguish causality from mere correlation. In this study, we present a general framework for investigating land-atmosphere interactions using Granger Causality analysis applied to remote sensing data. Based on the near linear relationship between chlorophyll sun induced fluorescence (SIF) and photosynthesis (and thus its relationship with transpiration), we use the GOME-2 fluorescence direct measurements to quantify the surface fluxes between the land and atmosphere. By using SIF data to represent the flux, we bypass the need to use soil moisture data from FLUXNET (limited spatially and temporally) or remote sensing (limited by spatial resolution, canopy interference, measurement depth, and radio frequency interference) thus eliminating additional uncertainty. The Granger Causality analysis allows for the determination of the strength of the two-way causal relationship between SIF and several climatic variables: precipitation, radiation and temperature. We determine that warm regions transitioning from water to energy limitation exhibit strong feedbacks between the land surface and atmosphere due to their high sensitivity to climate and weather variability. Tropical rainforest regions show low magnitudes of causal feedback likely due to other factors influencing the land surface such as phenological controls (e.g. leaf area index), nutrient limitations or soil texture. These results were then compared to CMIP5 GCM results using GPP in place of SIF. GCM results varied greatly between models as well as with the observational data analysis indicating deficiencies in the representation of certain modeled phenomena such as low level clouds and boundary layer development. This study highlights the need for GCM improvement to more accurately capture the feedbacks between the land and atmosphere. These results have the potential to improve our understanding of the underlying mechanisms between land and atmosphere coupling, which could ultimately be used to improve weather and climate predictions.

Effects of Topography-based Subgrid Structures on Land Surface Modeling

NASA Astrophysics Data System (ADS)

Tesfa, T. K.; Ruby, L.; Brunke, M.; Thornton, P. E.; Zeng, X.; Ghan, S. J.

2017-12-01

Topography has major control on land surface processes through its influence on atmospheric forcing, soil and vegetation properties, network topology and drainage area. Consequently, accurate climate and land surface simulations in mountainous regions cannot be achieved without considering the effects of topographic spatial heterogeneity. To test a computationally less expensive hyper-resolution land surface modeling approach, we developed topography-based landunits within a hierarchical subgrid spatial structure to improve representation of land surface processes in the ACME Land Model (ALM) with minimal increase in computational demand, while improving the ability to capture the spatial heterogeneity of atmospheric forcing and land cover influenced by topography. This study focuses on evaluation of the impacts of the new spatial structures on modeling land surface processes. As a first step, we compare ALM simulations with and without subgrid topography and driven by grid cell mean atmospheric forcing to isolate the impacts of the subgrid topography on the simulated land surface states and fluxes. Recognizing that subgrid topography also has important effects on atmospheric processes that control temperature, radiation, and precipitation, methods are being developed to downscale atmospheric forcings. Hence in the second step, the impacts of the subgrid topographic structure on land surface modeling will be evaluated by including spatial downscaling of the atmospheric forcings. Preliminary results on the atmospheric downscaling and the effects of the new spatial structures on the ALM simulations will be presented.

Multi-sensor analysis of urban ecosystems

USGS Publications Warehouse

Gallo, Kevin P.; Ji, Lei

2004-01-01

This study examines the synthesis of multiple space-based sensors to characterize the urban environment Single scene data (e.g., ASTER visible and near-IR surface reflectance, and land surface temperature data), multi-temporal data (e.g., one year of 16-day MODIS and AVHRR vegetation index data), and DMSP-OLS nighttime light data acquired in the early 1990s and 2000 were evaluated for urban ecosystem analysis. The advantages of a multi-sensor approach for the analysis of urban ecosystem processes are discussed.

Landing System Development- Design and Test Prediction of a Lander Leg Using Nonlinear Analysis

NASA Astrophysics Data System (ADS)

Destefanis, Stefano; Buchwald, Robert; Pellegrino, Pasquale; Schroder, Silvio

2014-06-01

Several mission studies have been performed focusing on a soft and precision landing using landing legs. Examples for such missions are Mars Sample Return scenarios (MSR), Lunar landing scenarios (MoonNEXT, Lunar Lander) and small body sample return studies (Marco Polo, MMSR, Phootprint). Such missions foresee a soft landing on the planet surface for delivering payload in a controlled manner and limiting the landing loads.To ensure a successful final landing phase, a landing system is needed, capable of absorbing the residual velocities (vertical, horizontal and angular) at touch- down, and insuring a controlled attitude after landing. Such requirements can be fulfilled by using landing legs with adequate damping.The Landing System Development (LSD) study, currently in its phase 2, foresees the design, analysis, verification, manufacturing and testing of a representative landing leg breadboard based on the Phase B design of the ESA Lunar Lander. Drop tests of a single leg will be performed both on rigid and soft ground, at several impact angles. The activity is covered under ESA contract with TAS-I as Prime Contractor, responsible for analysis and verification, Astrium GmbH for design and test and QinetiQ Space for manufacturing. Drop tests will be performed at the Institute of Space Systems of the German Aerospace Center (DLR-RY) in Bremen.This paper presents an overview of the analytical simulations (test predictions and design verification) performed, comparing the results produced by Astrium made multi body model (rigid bodies, nonlinearities accounted for in mechanical joints and force definitions, based on development tests) and TAS-I made nonlinear explicit model (fully deformable bodies).

Land surface-precipitation feedback analysis for a landfalling monsoon depression in the Indian region

NASA Astrophysics Data System (ADS)

Baisya, Himadri; Pattnaik, Sandeep; Rajesh, P. V.

2017-03-01

A series of numerical experiments are carried out to investigate the sensitivity of a landfalling monsoon depression to land surface conditions using the Weather Research and Forecasting (WRF) model. Results suggest that precipitation is largely modulated by moisture influx and precipitation efficiency. Three cloud microphysical schemes (WSM6, WDM6, and Morrison) are examined, and Morrison is chosen for assessing the land surface-precipitation feedback analysis, owing to better precipitation forecast skills. It is found that increased soil moisture facilitates Moisture Flux Convergence (MFC) with reduced moisture influx, whereas a reduced soil moisture condition facilitates moisture influx but not MFC. A higher Moist Static Energy (MSE) is noted due to increased evapotranspiration in an elevated moisture scenario which enhances moist convection. As opposed to moist surface, sensible heat dominates in a reduced moisture scenario, ensued by an overall reduction in MSE throughout the Planetary Boundary Layer (PBL). Stability analysis shows that Convective Available Potential Energy (CAPE) is comparable in magnitude for both increased and decreased moisture scenarios, whereas Convective Inhibition (CIN) shows increased values for the reduced moisture scenario as a consequence of drier atmosphere leading to suppression of convection. Simulations carried out with various fixed soil moisture levels indicate that the overall precipitation features of the storm are characterized by initial soil moisture condition, but precipitation intensity at any instant is modulated by soil moisture availability. Overall results based on this case study suggest that antecedent soil moisture plays a crucial role in modulating precipitation distribution and intensity of a monsoon depression.

Analysis and modelling of surface Urban Heat Island in 20 Canadian cities under climate and land-cover change.

PubMed

Gaur, Abhishek; Eichenbaum, Markus Kalev; Simonovic, Slobodan P

2018-01-15

Surface Urban Heat Island (SUHI) is an urban climate phenomenon that is expected to respond to future climate and land-use land-cover change. It is important to further our understanding of physical mechanisms that govern SUHI phenomenon to enhance our ability to model future SUHI characteristics under changing geophysical conditions. In this study, SUHI phenomenon is quantified and modelled at 20 cities distributed across Canada. By analyzing MODerate Resolution Imaging Spectroradiometer (MODIS) sensed surface temperature at the cities over 2002-2012, it is found that 16 out of 20 selected cities have experienced a positive SUHI phenomenon while 4 cities located in the prairies region and high elevation locations have experienced a negative SUHI phenomenon in the past. A statistically significant relationship between observed SUHI magnitude and city elevation is also recorded over the observational period. A Physical Scaling downscaling model is then validated and used to downscale future surface temperature projections from 3 GCMs and 2 extreme Representative Concentration Pathways in the urban and rural areas of the cities. Future changes in SUHI magnitudes between historical (2006-2015) and future timelines: 2030s (2026-2035), 2050s (2046-2055), and 2090s (2091-2100) are estimated. Analysis of future projected changes indicate that 15 (13) out of 20 cities can be expected to experience increases in SUHI magnitudes in future under RCP 2.6 (RCP 8.5). A statistically significant relationship between projected future SUHI change and current size of the cities is also obtained. The study highlights the role of city properties (i.e. its size, elevation, and surrounding land-cover) towards shaping their current and future SUHI characteristics. The results from this analysis will help decision-makers to manage Canadian cities more efficiently under rapidly changing geophysical and demographical conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimating time and spatial distribution of snow water equivalent in the Hakusan area

NASA Astrophysics Data System (ADS)

Tanaka, K.; Matsui, Y.; Touge, Y.

2015-12-01

In the Sousei program, on-going Japanese research program for risk information on climate change, assessing the impact of climate change on water resources is attempted using the integrated water resources model which consists of land surface model, irrigation model, river routing model, reservoir operation model, and crop growth model. Due to climate change, reduction of snowfall amount, reduction of snow cover and change in snowmelt timing, change in river discharge are of increasing concern. So, the evaluation of snow water amount is crucial for assessing the impact of climate change on water resources in Japan. To validate the snow simulation of the land surface model, time and spatial distribution of the snow water equivalent was estimated using the observed surface meteorological data and RAP (Radar Analysis Precipitation) data. Target area is Hakusan. Hakusan means 'white mountain' in Japanese. Water balance of the Tedori River Dam catchment was checked with daily inflow data. Analyzed runoff was generally well for the period from 2010 to 2012. From the result for 2010-2011 winter, maximum snow water equivalent in the headwater area of the Tedori River dam reached more than 2000mm in early April. On the other hand, due to the underestimation of RAP data, analyzed runoff was under estimated from 2006 to 2009. This underestimation is probably not from the lack of land surface model, but from the quality of input precipitation data. In the original RAP, only the rain gauge data of JMA (Japan Meteorological Agency) were used in the analysis. Recently, other rain gauge data of MLIT (Ministry of Land, Infrastructure, Transport and Tourism) and local government have been added in the analysis. So, the quality of the RAP data especially in the mountain region has been greatly improved. "Reanalysis" of the RAP precipitation is strongly recommended using all the available off-line rain gauges information. High quality precipitation data will contribute to validate hydrological model, satellite based precipitation product, GCM output, etc.

Decreased NK-Cell Cytotoxicity after Short Flights on the Space Shuttle

NASA Technical Reports Server (NTRS)

Mehta, Satish K.; Grimm, Elizabeth A.; Smid, Christine; Kaur, Indreshpal; Feeback, Daniel L.; Pierson, Duane L.

2000-01-01

Cytotoxic activity of natural killer (NK) cells and cell surface marker expression of peripheral blood mononuclear cells (PBMCs) isolated from 11 U.S. astronauts on two different missions were determined before and after 9 or 10 days of spaceflight aboard the space shuttle. Blood samples were collected 10 and 3 days before launch, within 3 hours after landing, and 3 days after landing. All PBMC preparations were cryopreserved and analyzed simultaneously in a 4-hour cytotoxicity "Cr-release assay using NK-sensitive K-562 target cells. Compared to preflight values, NK-cell cytotoxicity (corrected for lymphopenia observed on landing day) was significantly decreased at landing (P < 0.0125). It then apparently began to recover and approached preflight values by 3 days after landing. Consistent with decreased NK-cell cytotoxicity, significant increases from preflight values were found in plasma adrenocorticotropic hormone at landing. Plasma and urinary cortisol levels did not change significantly from preflight values. Expression of major lymphocyte surface markers (CD3, CD4, CD8, CD14, CD16, CD56), determined by flow cytometric analysis, revealed no consistent phenotypic changes in relative percent of NK or other lymphoid cells after 10 days of spaceflight.

Multicriteria analysis for sources of renewable energy using data from remote sensing

NASA Astrophysics Data System (ADS)

Matejicek, L.

2015-04-01

Renewable energy sources are major components of the strategy to reduce harmful emissions and to replace depleting fossil energy resources. Data from remote sensing can provide information for multicriteria analysis for sources of renewable energy. Advanced land cover quantification makes it possible to search for suitable sites. Multicriteria analysis, together with other data, is used to determine the energy potential and socially acceptability of suggested locations. The described case study is focused on an area of surface coal mines in the northwestern region of the Czech Republic, where the impacts of surface mining and reclamation constitute a dominant force in land cover changes. High resolution satellite images represent the main input datasets for identification of suitable sites. Solar mapping, wind predictions, the location of weirs in watersheds, road maps and demographic information complement the data from remote sensing for multicriteria analysis, which is implemented in a geographic information system (GIS). The input spatial datasets for multicriteria analysis in GIS are reclassified to a common scale and processed with raster algebra tools to identify suitable sites for sources of renewable energy. The selection of suitable sites is limited by the CORINE land cover database to mining and agricultural areas. The case study is focused on long term land cover changes in the 1985-2015 period. Multicriteria analysis based on CORINE data shows moderate changes in mapping of suitable sites for utilization of selected sources of renewable energy in 1990, 2000, 2006 and 2012. The results represent map layers showing the energy potential on a scale of a few preference classes (1-7), where the first class is linked to minimum preference and the last class to maximum preference. The attached histograms show the moderate variability of preference classes due to land cover changes caused by mining activities. The results also show a slight increase in the more preferred classes for utilization of sources of renewable energy due to an increase area of reclaimed sites. Using data from remote sensing, such as the multispectral images and the CORINE land cover datasets, can reduce the financial resources currently required for finding and assessing suitable areas.

Determination of dominant sources of nitrate contamination in transboundary (Russian Federation/Ukraine) catchment with heterogeneous land use.

PubMed

Vystavna, Y; Diadin, D; Grynenko, V; Yakovlev, V; Vergeles, Y; Huneau, F; Rossi, P M; Hejzlar, J; Knöller, K

2017-09-18

Nitrate contamination of surface water and shallow groundwater was studied in transboundary (Russia/Ukraine) catchment with heterogeneous land use. Dominant sources of nitrate contamination were determined by applying a dual δ 15 N-NO 3 and δ 18 O-NO 3 isotope approach, multivariate statistics, and land use analysis. Nitrate concentration was highly variable from 0.25 to 22 mg L -1 in surface water and from 0.5 to 100 mg L -1 in groundwater. The applied method indicated that sewage to surface water and sewage and manure to groundwater were dominant sources of nitrate contamination. Nitrate/chloride molar ratio was added to support the dual isotope signature and indicated the contribution of fertilizers to the nitrate content in groundwater. Groundwater temperature was found to be an additional indicator of manure and sewerage leaks in the shallow aquifer which has limited protection and is vulnerable to groundwater pollution.

Using machine learning to produce near surface soil moisture estimates from deeper in situ records at U.S. Climate Reference Network (USCRN) locations: Analysis and applications to AMSR-E satellite validation

USDA-ARS?s Scientific Manuscript database

Surface soil moisture is critical parameter for understanding the energy flux at the land atmosphere boundary. Weather modeling, climate prediction, and remote sensing validation are some of the applications for surface soil moisture information. The most common in situ measurement for these purpo...

A numerical forecast model for road meteorology

NASA Astrophysics Data System (ADS)

Meng, Chunlei

2017-05-01

A fine-scale numerical model for road surface parameters prediction (BJ-ROME) is developed based on the Common Land Model. The model is validated using in situ observation data measured by the ROSA road weather stations of Vaisala Company, Finland. BJ-ROME not only takes into account road surface factors, such as imperviousness, relatively low albedo, high heat capacity, and high heat conductivity, but also considers the influence of urban anthropogenic heat, impervious surface evaporation, and urban land-use/land-cover changes. The forecast time span and the update interval of BJ-ROME in vocational operation are 24 and 3 h, respectively. The validation results indicate that BJ-ROME can successfully simulate the diurnal variation of road surface temperature both under clear-sky and rainfall conditions. BJ-ROME can simulate road water and snow depth well if the artificial removing was considered. Road surface energy balance in rainy days is quite different from that in clear-sky conditions. Road evaporation could not be neglected in road surface water cycle research. The results of sensitivity analysis show solar radiation correction coefficient, asphalt depth, and asphalt heat conductivity are important parameters in road interface temperatures simulation. The prediction results could be used as a reference of maintenance decision support system to mitigate the traffic jam and urban water logging especially in large cities.

Impact of land cover change on the environmental hydrology characteristics in Kelantan river basin, Malaysia

NASA Astrophysics Data System (ADS)

Saadatkhah, Nader; Mansor, Shattri; Khuzaimah, Zailani; Asmat, Arnis; Adnan, Noraizam; Adam, Siti Noradzah

2016-09-01

Changing the land cover/ land use has serious environmental impacts affecting the ecosystem in Malaysia. The impact of land cover changes on the environmental functions such as surface water, loss water, and soil moisture is considered in this paper on the Kelantan river basin. The study area at the east coast of the peninsular Malaysia has suffered significant land cover changes in the recent years. The current research tried to assess the impact of land cover changes in the study area focused on the surface water, loss water, and soil moisture from different land use classes and the potential impact of land cover changes on the ecosystem of Kelantan river basin. To simulate the impact of land cover changes on the environmental hydrology characteristics, a deterministic regional modeling were employed in this study based on five approaches, i.e. (1) Land cover classification based on Landsat images; (2) assessment of land cover changes during last three decades; (3) Calculation the rate of water Loss/ Infiltration; (4) Assessment of hydrological and mechanical effects of the land cover changes on the surface water; and (5) evaluation the impact of land cover changes on the ecosystem of the study area. Assessment of land cover impact on the environmental hydrology was computed with the improved transient rainfall infiltration and grid based regional model (Improved-TRIGRS) based on the transient infiltration, and subsequently changes in the surface water, due to precipitation events. The results showed the direct increased in surface water from development area, agricultural area, and grassland regions compared with surface water from other land covered areas in the study area. The urban areas or lower planting density areas tend to increase for surface water during the monsoon seasons, whereas the inter flow from forested and secondary jungle areas contributes to the normal surface water.

Translation of Land Surface Model Accuracy and Uncertainty into Coupled Land-Atmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A.; Kumar, Sujay; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Zhou, Shuija

2012-01-01

Land-atmosphere (L-A) Interactions playa critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (US-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF Simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

Antibiotic resistance and community analysis of surface and subsurface drainage waters in the South Fork Iowa River watershed

USDA-ARS?s Scientific Manuscript database

The Midwest is a center for swine production leading to application of swine manure onto lands that have artificial subsurface drainage. Previous reports have indicated elevated levels of antibiotic resistance genes (ARGs) in surface water and groundwater around confined animal feeding operations w...

Antibiotic resistance and community analysis of surface and subsurface drainage waters in the South Fork Iowa River watershed

USDA-ARS?s Scientific Manuscript database

The Midwest is a center for swine production leading to application of swine manure onto lands that have artificial subsurface drainage. Previous reports have indicated elevated levels of antibiotic resistance genes (ARGs) in surface water and groundwater around confined animal feeding operations wh...

Global Land Data Assimilation System (GLDAS) Products, Services and Application from NASA Hydrology Data and Information Services Center (HDISC)

NASA Technical Reports Server (NTRS)

Fang, Hongliang; Beaudoing, Hiroko K.; Rodell, matthew; Teng, William L.; Vollmer, Bruce E.

2009-01-01

The Global Land Data Assimilation System (GLDAS) is generating a series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) products simulated by four land surface models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information Services Center (HDISC), a component of the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data holdings include a set of 1.0 degree resolution data products from the four models, covering 1979 to the present; and a 0.25 degree data product from the Noah model, covering 2000 to the present. The products are in Gridded Binary (GRIB) format and can be accessed through a number of interfaces. Users can search the products through keywords and perform on-the-fly spatial and parameter subsetting and format conversion of selected data. More advanced visualization, access and analysis capabilities will be available in the future. The long term GLDAS data are used to develop climatology of water cycle components and to explore the teleconnections of droughts and pluvial.

Global Land Data Assimilation System (GLDAS) Products from NASA Hydrology Data and Information Services Center (HDISC)

NASA Technical Reports Server (NTRS)

Fang, Hongliang; Hrubiak, Patricia; Kato, Hiroko; Rodell, Matthew; Teng, William L.; Vollmer, Bruce E.

2008-01-01

The Global Land Data Assimilation System (GLDAS) is generating a series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) products simulated by four land surface models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information Services Center (HDISC), a component of the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data holdings include a set of 1.0 degree resolution data products from the four models, covering 1979 to the present; and a 0.25 degree data product from the Noah model, covering 2000 to the present. The products are in Gridded Binary (GRIB) format and can be accessed through a number of interfaces. New data formats (e.g., netCDF), temporal averaging and spatial subsetting will be available in the future. The HDISC has the capability to support more hydrology data products and more advanced analysis tools. The goal is to develop HDISC as a data and services portal that supports weather and climate forecast, and water and energy cycle research.

Saturn Apollo Program

NASA Image and Video Library

1969-03-05

The third stage (S-IVB) of the Saturn V launch vehicle for the Apollo 11 lunar landing mission is hoisted in the vehicle assembly building at the NASA Kennedy Space Center (KSC) for mating with the second stage (S-II). The vehicle, designated as AS-506, projected the first lunar landing mission, Apollo 11, on a trajectory for the Moon. The Apollo 11 mission launched from KSC in Florida via the Marshall Space Flight Center (MSFC) developed Saturn V launch vehicle on July 16, 1969 and safely returned to Earth on July 24, 1969. Astronauts onboard included Neil A. Armstrong, commander; Michael Collins, Command Module (CM) pilot; and Edwin E. Aldrin, Jr., Lunar Module (LM) pilot. The CM, “Columbia”, piloted by Collins, remained in a parking orbit around the Moon while the LM, “Eagle’’, carrying astronauts Armstrong and Aldrin, landed on the Moon. On July 20, 1969, Armstrong was the first human to ever stand on the lunar surface, followed by Aldrin. During 2½ hours of surface exploration, the crew collected 47 pounds of lunar surface material for analysis back on Earth. With the success of Apollo 11, the national objective to land men on the Moon and return them safely to Earth had been accomplished.

Saturn Apollo Program

NASA Image and Video Library

1969-07-09

In preparation of the nation’s first lunar landing mission, Apollo 11, crew members underwent training to practice activities they would be performing during the mission. In this photograph Neil Armstrong approaches the helicopter he flew to practice landing the Lunar Module (LM) on the Moon. The Apollo 11 mission launched from the Kennedy Space Center (KSC) in Florida via the Marshall Space Flight Center (MSFC) developed Saturn V launch vehicle on July 16, 1969 and safely returned to Earth on July 24, 1969. Aboard the space craft were astronauts Neil A. Armstrong, commander; Michael Collins, Command Module (CM) pilot; and Edwin E. (Buzz) Aldrin Jr., Lunar Module (LM) pilot. The CM, “Columbia”, piloted by Collins, remained in a parking orbit around the Moon while the LM, “Eagle’’, carrying astronauts Armstrong and Aldrin, landed on the Moon. On July 20, 1969, Armstrong was the first human to ever stand on the lunar surface, followed by Aldrin. During 2½ hours of surface exploration, the crew collected 47 pounds of lunar surface material for analysis back on Earth. With the success of Apollo 11, the national objective to land men on the Moon and return them safely to Earth had been accomplished

Molecular characters of melon (Cucumismelo L. "Tacapa") in response to karst critical land

NASA Astrophysics Data System (ADS)

Rachmawati, Yuanita; Daryono, Budi Setiadi; Aristya, Ganies Riza

2017-06-01

Yogyakarta district has 158.600 ha critical land and spread off in three Agro Ecosystem zones. Two of them are karsts critical land. Critical lands which contain calcium carbonate in high concentration and water dehydration in upper surface give abiotic stress in wide range of plant. Melon cultivar TACAPA has superior characteristic derived from parental crossing, ♀ Action 434 and ♂ PI 371795 and potential to be developed in karsts critical land. Abscicic acid (ABA) is a phytohormone expressed by plant in abiotic stress condition. CmBG1 is a gene which regulate ABA hormone in melon. The purposes of this research were examining the molecular character of melon cultivar TACAPA in response to karsts critical land in order to study molecular characterization of CmBG1 gene. Analysis was done qualitatively by using Reverse Transcriptase-PCR (RT-PCR) and Electrophoresis, while quantitative analysis was conducted by observing absorbance score in spectrophotometer. CmBG1 gene expression is examined by using Real time PCR (qPCR). Molecular characters obtained are CmBG1 detected in size ±1258 bp, CmBG1 gene concentrations in melon which planted in control media are lower than melon in critical lands media. These results are similar with the real time quantitative analysis method. It also be revealed that melon TACAPA is more potential plant compared to another cultivar that can be developed in karst critical land area.

Study on a Dynamic Vegetation Model for Simulating Land Surface Flux Exchanges at Lien-Hua-Chih Flux Observation Site in Taiwan

NASA Astrophysics Data System (ADS)

Yeh, T. Y.; Li, M. H.; Chen, Y. Y.; Ryder, J.; McGrath, M.; Otto, J.; Naudts, K.; Luyssaert, S.; MacBean, N.; Bastrikov, V.

2016-12-01

Dynamic vegetation model ORCHIDEE (Organizing Carbon and Hydrology In Dynamic EcosystEms) is a state of art land surface component of the IPSL (Institute Pierre Simon Laplace) Earth System Model. It has been used world-wide to investigate variations of water, carbon, and energy exchanges between the land surface and the atmosphere. In this study we assessed the applicability of using ORCHIDEE-CAN, a new feature with 3-D CANopy structure (Naudts et al., 2015; Ryder et al., 2016), to simulate surface fluxes measured at tower-based eddy covariance fluxes at the Lien-Hua-Chih experimental watershed in Taiwan. The atmospheric forcing including radiation, air temperature, wind speed, and the dynamics of vertical canopy structure for driving the model were obtained from the observations site. Suitable combinations of default plant function types were examined to meet in-situ observations of soil moisture and leaf area index from 2009 to 2013. The simulated top layer soil moisture was ranging from 0.1 to 0.4 and total leaf area was ranging from 2.2 to 4.4, respectively. A sensitivity analysis was performed to investigate the sensitive of model parameters and model skills of ORCHIDEE-CAN on capturing seasonal variations of surface fluxes. The most sensitive parameters were suggested and calibrated by an automatic data assimilation tool ORCHDAS (ORCHIDEE Data Assimilation Systems; http://orchidas.lsce.ipsl.fr/). Latent heat, sensible heat, and carbon fluxes simulated by the model were compared with long-term observations at the site. ORCHIDEE-CAN by making use of calibrated surface parameters was used to study variations of land-atmosphere interactions on a variety of temporal scale in associations with changes in both land and atmospheric conditions. Ref: Naudts, K., et al.,: A vertically discretised canopy description for ORCHIDEE (SVN r2290) and the modifications to the energy, water and carbon fluxes, Geoscientific Model Development, 8, 2035-2065, doi:10.5194/gmd-8-2035-2015,2015. Ryder, J., et al. : A multi-layer land surface energy budget model for implicit coupling with global atmospheric simulations, Geoscientific Model Development, 9, 223-245, doi:10.5194/gmd-9-223-2016, 2016.

Prediction of optimal safe ground water yield and land subsidence in the Los Banos-Kettleman City area, California, using a calibrated numerical simulation model

NASA Astrophysics Data System (ADS)

Larson, K. J.; Başaǧaoǧlu, H.; Mariño, M. A.

2001-02-01

Land subsidence caused by the excessive use of ground water resources has traditionally caused serious and costly damage to the Los Banos-Kettleman City area of California's San Joaquin Valley. Although the arrival of surface water from the Central Valley Project has reduced subsidence in recent decades, the growing instability of surface water supplies has refocused attention on the future of land subsidence in the region. This paper uses integrated numerical ground water and land subsidence models to simulate land subsidence caused by ground water overdraft. The simulation model is calibrated using observed data from 1972 to 1998, and the responsiveness of the model to variations in subsidence parameters are analyzed through a sensitivity analysis. A probable future drought scenario is used to evaluate the effect on land subsidence of three management alternatives over the next thirty years. The model reveals that maintaining present practices virtually eliminates unrecoverable land subsidence, but may not be a sustainable alternative because of a growing urban population to the south and concern over the ecological implications of water exportation from the north. The two other proposed management alternatives reduce the dependency on surface water by increasing ground water withdrawal. Land subsidence is confined to tolerable levels in the more moderate of these proposals, while the more aggressive produces significant long-term subsidence. Finally, an optimization model is formulated to determine maximum ground water withdrawal from nine pumping sub-basins without causing irrecoverable subsidence during the forecast period. The optimization model reveals that withdrawal can be increased in certain areas on the eastern side of the study area without causing significant inelastic subsidence.

Spatial variability in airborne bacterial communities across land-use types and their relationship to the bacterial communities of potential source environments

PubMed Central

Bowers, Robert M; McLetchie, Shawna; Knight, Rob; Fierer, Noah

2011-01-01

Although bacteria are ubiquitous in the near-surface atmosphere and they can have important effects on human health, airborne bacteria have received relatively little attention and their spatial dynamics remain poorly understood. Owing to differences in meteorological conditions and the potential sources of airborne bacteria, we would expect the atmosphere over different land-use types to harbor distinct bacterial communities. To test this hypothesis, we sampled the near-surface atmosphere above three distinct land-use types (agricultural fields, suburban areas and forests) across northern Colorado, USA, sampling five sites per land-use type. Microbial abundances were stable across land-use types, with ∼105–106 bacterial cells per m3 of air, but the concentrations of biological ice nuclei, determined using a droplet freezing assay, were on average two and eight times higher in samples from agricultural areas than in the other two land-use types. Likewise, the composition of the airborne bacterial communities, assessed via bar-coded pyrosequencing, was significantly related to land-use type and these differences were likely driven by shifts in the sources of bacteria to the atmosphere across the land-uses, not local meteorological conditions. A meta-analysis of previously published data shows that atmospheric bacterial communities differ from those in potential source environments (leaf surfaces and soils), and we demonstrate that we may be able to use this information to determine the relative inputs of bacteria from these source environments to the atmosphere. This work furthers our understanding of bacterial diversity in the atmosphere, the terrestrial controls on this diversity and potential approaches for source tracking of airborne bacteria. PMID:21048802

Analysis of Synthetic Aperture Radar data acquired over a variety of land cover

NASA Technical Reports Server (NTRS)

Wu, S. T.

1983-01-01

An analysis has been conducted of two-look-angle, multipolarization X-band SAR results. On the basis of the variety of land covers studied, the vertical-vertical polarization (VV) data is judged to contain the highest degree of contrast, while the horizontal-vertical (HV) polarization contained the least. VV polarization data is accordingly recommended for forest vegetation classification in those cases where only one data channel is available. The inclusion of horizontal-horizontal polarization data, however, is noted to be capable of delineating special surface features.

Mars Pathfinder [foldout].

PubMed

1997-12-05

The following foldout present images and analysis from the Mars Pathfinder Mission that are discussed in seven subsequent Reports. The center is a four-page panorama of the surface of Mars around the lander (Plate 1). The back of the foldout contains surface images (Plate 7), a different perspective of the landing site (Plate 2), rover targets (Plate 3), locations of rocks and other features (Plate 6) and data analysis (Plates 4, 4, 8, 9, and 10).

Using NASA Earth Observing Satellites and Statistical Model Analysis to Monitor Vegetation and Habitat Rehabilitation in Southwest Virginia's Reclaimed Mine Lands

NASA Astrophysics Data System (ADS)

Tate, Z.; Dusenge, D.; Elliot, T. S.; Hafashimana, P.; Medley, S.; Porter, R. P.; Rajappan, R.; Rodriguez, P.; Spangler, J.; Swaminathan, R. S.; VanGundy, R. D.

2014-12-01

The majority of the population in southwest Virginia depends economically on coal mining. In 2011, coal mining generated $2,000,000 in tax revenue to Wise County alone. However, surface mining completely removes land cover and leaves the land exposed to erosion. The destruction of the forest cover directly impacts local species, as some are displaced and others perish in the mining process. Even though surface mining has a negative impact on the environment, land reclamation efforts are in place to either restore mined areas to their natural vegetated state or to transform these areas for economic purposes. This project aimed to monitor the progress of land reclamation and the effect on the return of local species. By incorporating NASA Earth observations, such as Landsat 8 Operational Land Imager (OLI) and Landsat 5 Thematic Mapper (TM), re-vegetation process in reclamation sites was estimated through a Time series analysis using the Normalized Difference Vegetation Index (NDVI). A continuous source of cloud free images was accomplished by utilizing the Spatial and Temporal Adaptive Reflectance Fusion Model (STAR-FM). This model developed synthetic Landsat imagery by integrating the high-frequency temporal information from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and high-resolution spatial information from Landsat sensors In addition, the Maximum Entropy Modeling (MaxENT), an eco-niche model was used to estimate the adaptation of animal species to the newly formed habitats. By combining factors such as land type, precipitation from Tropical Rainfall Measuring Mission (TRMM), and slope from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the MaxENT model produced a statistical analysis on the probability of species habitat. Altogether, the project compiled the ecological information which can be used to identify suitable habitats for local species in reclaimed mined areas.

Mapping Impervious Surfaces Globally at 30m Resolution Using Global Land Survey Data

NASA Technical Reports Server (NTRS)

DeColstoun, Eric Brown; Huang, Chengquan; Tan, Bin; Smith, Sarah Elizabeth; Phillips, Jacqueline; Wang, Panshi; Ling, Pui-Yu; Zhan, James; Li, Sike; Taylor, Michael P.;

Mapping Impervious Surfaces Globally at 30m Resolution Using Landsat Global Land Survey Data

NASA Astrophysics Data System (ADS)

Brown de Colstoun, E.; Huang, C.; Wolfe, R. E.; Tan, B.; Tilton, J.; Smith, S.; Phillips, J.; Wang, P.; Ling, P.; Zhan, J.; Xu, X.; Taylor, M. P.

2013-12-01

Impervious surfaces, mainly artificial structures and roads, cover less than 1% of the world's land surface (1.3% over USA). Regardless of the relatively small coverage, impervious surfaces have a significant impact on the environment. They are the main source of the urban heat island effect, and affect not only the energy balance, but also hydrology and carbon cycling, and both land and aquatic ecosystem services. In the last several decades, the pace of converting natural land surface to impervious surfaces has increased. Quantitatively monitoring the growth of impervious surface expansion and associated urbanization has become a priority topic across both the physical and social sciences. The recent availability of consistent, global scale data sets at 30m resolution such as the Global Land Survey from the Landsat satellites provides an unprecedented opportunity to map global impervious cover and urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such a buildings, roads and parking lots. With long term GLS data now available for the 1975, 1990, 2000, 2005 and 2010 time periods, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. In the Global Land Survey - Imperviousness Mapping Project (GLS-IMP), we are producing the first global 30 m spatial resolution impervious cover data set. We have processed the GLS 2010 data set to surface reflectance (8500+ TM and ETM+ scenes) and are using a supervised classification method using a regression tree to produce continental scale impervious cover data sets. A very large set of accurate training samples is the key to the supervised classifications and is being derived through the interpretation of high spatial resolution (~2 m or less) commercial satellite data (Quickbird and Worldview2) available to us through the unclassified archive of the National Geospatial Intelligence Agency (NGA). For each continental area several million training pixels are derived by analysts using image segmentation algorithms and tools and then aggregated to the 30m resolution of Landsat. Here we will discuss the production/testing of this massive data set for Europe, North and South America and Africa, including assessments of the 2010 surface reflectance data. This type of analysis is only possible because of the availability of long term 30m data sets from GLS and shows much promise for integration of Landsat 8 data in the future.

Including land cover change in analysis of greenness trends using all available Landsat 5, 7, and 8 images: A case study from Guangzhou, China (2000–2014)

USGS Publications Warehouse

Zhu, Zhe; Fu, Yingchun; Woodcock, Curtis; Olofsson, Pontus; Vogelmann, James; Holden, Christopher; Wang, Min; Dai, Shu; Yu, Yang

2016-01-01

An assessment of the consistency of surface reflectance from Landsat 8 with past Landsat sensors indicates biases in the visible bands of Landsat 8, especially the blue band. Landsat 8 NDVI values were found to have a larger bias than the EVI values; therefore, EVI was used in the analysis of greenness trends for Guangzhou. In spite of massive amounts of development in Guangzhou from 2000 to 2014, greenness was found to increase, mostly as a result of gradual change. Comparison of the greening magnitudes estimated from the approach presented here and a Simple Linear Trend (SLT) method indicated large differences for certain time intervals as the SLT method does not include consideration for abrupt land cover changes. Overall, this analysis demonstrates the importance of considering land cover change when analyzing trends in greenness from satellite time series in areas where land cover change is common.

Land Surface Data Assimilation

NASA Astrophysics Data System (ADS)

Houser, P. R.

2012-12-01

Information about land surface water, energy and carbon conditions is of critical importance to real-world applications such as agricultural production, water resource management, flood prediction, water supply, weather and climate forecasting, and environmental preservation. While ground-based observational networks are improving, the only practical way to observe these land surface states on continental to global scales is via satellites. Remote sensing can make spatially comprehensive measurements of various components of the terrestrial system, but it cannot provide information on the entire system (e.g. evaporation), and the observations represent only an instant in time. Land surface process models may be used to predict temporal and spatial terrestrial dynamics, but these predictions are often poor, due to model initialization, parameter and forcing, and physics errors. Therefore, an attractive prospect is to combine the strengths of land surface models and observations (and minimize the weaknesses) to provide a superior terrestrial state estimate. This is the goal of land surface data assimilation. Data Assimilation combines observations into a dynamical model, using the model's equations to provide time continuity and coupling between the estimated fields. Land surface data assimilation aims to utilize both our land surface process knowledge, as embodied in a land surface model, and information that can be gained from observations. Both model predictions and observations are imperfect and we wish to use both synergistically to obtain a more accurate result. Moreover, both contain different kinds of information, that when used together, provide an accuracy level that cannot be obtained individually. Model biases can be mitigated using a complementary calibration and parameterization process. Limited point measurements are often used to calibrate the model(s) and validate the assimilation results. This presentation will provide a brief background on land surface observation, modeling and data assimilation, followed by a discussion of various hydrologic data assimilation challenges, and finally conclude with several land surface data assimilation case studies.

Global change research related to the Earth's energy and hydrologic cycle

NASA Technical Reports Server (NTRS)

Perkey, Donald J.

1994-01-01

The following are discussed: Geophysical Modeling and Processes; Land Surface Processes and Atmospheric Interactions; Remote Sensing Technology and Geophysical Retrievals; and Scientific Data Management and Visual Analysis.

Constraining the JULES land-surface model for different land-use types using citizen-science generated hydrological data

NASA Astrophysics Data System (ADS)

Chou, H. K.; Ochoa-Tocachi, B. F.; Buytaert, W.

2017-12-01

Community land surface models such as JULES are increasingly used for hydrological assessment because of their state-of-the-art representation of land-surface processes. However, a major weakness of JULES and other land surface models is the limited number of land surface parameterizations that is available. Therefore, this study explores the use of data from a network of catchments under homogeneous land-use to generate parameter "libraries" to extent the land surface parameterizations of JULES. The network (called iMHEA) is part of a grassroots initiative to characterise the hydrological response of different Andean ecosystems, and collects data on streamflow, precipitation, and several weather variables at a high temporal resolution. The tropical Andes are a useful case study because of the complexity of meteorological and geographical conditions combined with extremely heterogeneous land-use that result in a wide range of hydrological responses. We then calibrated JULES for each land-use represented in the iMHEA dataset. For the individual land-use types, the results show improved simulations of streamflow when using the calibrated parameters with respect to default values. In particular, the partitioning between surface and subsurface flows can be improved. But also, on a regional scale, hydrological modelling was greatly benefitted from constraining parameters using such distributed citizen-science generated streamflow data. This study demonstrates the modelling and prediction on regional hydrology by integrating citizen science and land surface model. In the context of hydrological study, the limitation of data scarcity could be solved indeed by using this framework. Improved predictions of such impacts could be leveraged by catchment managers to guide watershed interventions, to evaluate their effectiveness, and to minimize risks.

Estimating morning changes in land surface temperature from MODIS day/night land surface temperature: Applications for surface energy balance modeling

USDA-ARS?s Scientific Manuscript database

Observations of land surface temperature (LST) are crucial for the monitoring of surface energy fluxes from satellite. Methods that require high temporal resolution LST observations (e.g., from geostationary orbit) can be difficult to apply globally because several geostationary sensors are required...

A COUPLED LAND-SURFACE AND DRY DEPOSITION MODEL AND COMPARISON TO FIELD MEASUREMENTS OF SURFACE HEAT, MOISTURE, AND OZONE FLUXES

EPA Science Inventory

We have developed a coupled land-surface and dry deposition model for realistic treatment of surface fluxes of heat, moisture, and chemical dry deposition within a comprehensive air quality modeling system. A new land-surface model (LSM) with explicit treatment of soil moisture...

Climate and the equilibrium state of land surface hydrology parameterizations

NASA Technical Reports Server (NTRS)

Entekhabi, Dara; Eagleson, Peter S.

1991-01-01

For given climatic rates of precipitation and potential evaporation, the land surface hydrology parameterizations of atmospheric general circulation models will maintain soil-water storage conditions that balance the moisture input and output. The surface relative soil saturation for such climatic conditions serves as a measure of the land surface parameterization state under a given forcing. The equilibrium value of this variable for alternate parameterizations of land surface hydrology are determined as a function of climate and the sensitivity of the surface to shifts and changes in climatic forcing are estimated.

Mapping and analyzing change of impervious surface for two decades using multi-temporal Landsat imagery in Missouri

NASA Astrophysics Data System (ADS)

Zhou, Bo; He, Hong S.; Nigh, Timothy A.; Schulz, John H.

2012-08-01

Human population growth and associated sprawl has rapidly converted open lands to developed use and affected their distinctive ecological characteristics. Missouri reflects a full range of sprawl characteristics that include large metropolitan centers, which led growth in 1980s, and smaller metropolitan and rural areas, which led growth in 1990s. In order to study the historical patterns of sprawl, there is a need to quantitatively and geographically depict the extent and density of impervious surface for three time periods of 1980, 1990, and 2000 for the entire state of Missouri. We mapped impervious surface using Sub-pixel Classifier™, an add-on module of Erdas Imagine for the three time periods, where impervious surface growth was derived as the subtraction of impervious surface mapped from the different time periods. Accuracy assessment was performed by comparing satellite derived impervious surface images with ground-truth acquired from high resolution air photos. Results show that during 1980-2000, 129,853 ha of land were converted to impervious surface. Sprawl was prominent on urban fringe (within the urban boundaries) during 1980s with 23,674 ha of land converted to impervious surface compared to 22,918 ha in 1990s. There was a temporal shift in the rural landscapes (outside the urban boundaries) in the 1990s with 48,079 ha of land converted to impervious surface compared to 35,180 ha in 1980s. Major findings based on analysis of the impervious surface growth include: (i) new growth of impervious surfaces are concentrated on areas with 0.5-1.0% road cover; (ii) most new growths are either inside or close to urban watersheds; and (iii) most new growths are either inside or close to counties with metropolitan cities. This research goes beyond the usual hot spots of metropolitan areas to include rural landscapes where negative impact was exerted to the ecosystem due to the low density development and larger affected areas.

Atmospheric correction for retrieving ground brightness temperature at commonly-used passive microwave frequencies.

PubMed

Han, Xiao-Jing; Duan, Si-Bo; Li, Zhao-Liang

2017-02-20

An analysis of the atmospheric impact on ground brightness temperature (Tg) is performed for numerous land surface types at commonly-used frequencies (i.e., 1.4 GHz, 6.93 GHz, 10.65 GHz, 18.7 GHz, 23.8 GHz, 36.5 GHz and 89.0 GHz). The results indicate that the atmosphere has a negligible impact on Tg at 1.4 GHz for land surfaces with emissivities greater than 0.7, at 6.93 GHz for land surfaces with emissivities greater than 0.8, and at 10.65 GHz for land surfaces with emissivities greater than 0.9 if a root mean square error (RMSE) less than 1 K is desired. To remove the atmospheric effect on Tg, a generalized atmospheric correction method is proposed by parameterizing the atmospheric transmittance τ and upwelling atmospheric brightness temperature Tba↑. Better accuracies with Tg RMSEs less than 1 K are achieved at 1.4 GHz, 6.93 GHz, 10.65 GHz, 18.7 GHz and 36.5 GHz, and worse accuracies with RMSEs of 1.34 K and 4.35 K are obtained at 23.8 GHz and 89.0 GHz, respectively. Additionally, a simplified atmospheric correction method is developed when lacking sufficient input data to perform the generalized atmospheric correction method, and an emissivity-based atmospheric correction method is presented when the emissivity is known. Consequently, an appropriate atmospheric correction method can be selected based on the available data, frequency and required accuracy. Furthermore, this study provides a method to estimate τ and Tba↑ of different frequencies using the atmospheric parameters (total water vapor content in observation direction Lwv, total cloud liquid water content Lclw and mean temperature of cloud Tclw), which is important for simultaneously determining the land surface parameters using multi-frequency passive microwave satellite data.

Unique relation between surface-limited evaporation and relative humidity profiles holds in both field data and climate model simulations

NASA Astrophysics Data System (ADS)

Salvucci, G.; Rigden, A. J.; Gentine, P.; Lintner, B. R.

2013-12-01

A new method was recently proposed for estimating evapotranspiration (ET) from weather station data without requiring measurements of surface limiting factors (e.g. soil moisture, leaf area, canopy conductance) [Salvucci and Gentine, 2013, PNAS, 110(16): 6287-6291]. Required measurements include diurnal air temperature, specific humidity, wind speed, net shortwave radiation, and either measured or estimated incoming longwave radiation and ground heat flux. The approach is built around the idea that the key, rate-limiting, parameter of typical ET models, the land-surface resistance to water vapor transport, can be estimated from an emergent relationship between the diurnal cycle of the relative humidity profile and ET. The emergent relation is that the vertical variance of the relative humidity profile is less than what would occur for increased or decreased evaporation rates, suggesting that land-atmosphere feedback processes minimize this variance. This relation was found to hold over a wide range of climate conditions (arid to humid) and limiting factors (soil moisture, leaf area, energy) at a set of Ameriflux field sites. While the field tests in Salvucci and Gentine (2013) supported the minimum variance hypothesis, the analysis did not reveal the mechanisms responsible for the behavior. Instead the paper suggested, heuristically, that the results were due to an equilibration of the relative humidity between the land surface and the surface layer of the boundary layer. Here we apply this method using surface meteorological fields simulated by a global climate model (GCM), and compare the predicted ET to that simulated by the climate model. Similar to the field tests, the GCM simulated ET is in agreement with that predicted by minimizing the profile relative humidity variance. A reasonable interpretation of these results is that the feedbacks responsible for the minimization of the profile relative humidity variance in nature are represented in the climate model. The climate model components, in particular the land surface model and boundary layer representation, can thus be analyzed in controlled numerical experiments to discern the specific processes leading to the observed behavior. Results of this analysis will be presented.

Regulating services as measures of ecological resilience on DoD lands

USGS Publications Warehouse

Angermeier, Paul; Villamagna, Amy M.

2015-01-01

Knowledge of the capacity and flow of ecosystem services can help DoD land managers make decisions that enhance cost-effectiveness, minimize environmental damage, and maximize resources available for military missions. We demonstrated a methodology to quantify and map selected regulating services (RS), which helps land managers envision tradeoffs. Our objectives were to 1) estimate current capacity of and demand for selected RS within DoD lands, 2) examine the effects of future DoD land management and climate changes on the capacity and flow of these RS, and 3) project how land-use and climate changes in nearby lands affect future demand for RS. Our approach incorporates widely accepted models and equations, remote sensing, GIS analysis, and stakeholder involvement. Required data include land cover/use, soil type, precipitation, and air temperature. We integrated data into the a) Surface Curve Number Method and b) Revised Universal Soil Loss Equation to estimate capacity of sediment, nitrogen (N) and surface-water regulation. Capacities and flows of RS vary greatly across landscapes and are likely to vary as climate changes or development occurs. Analyses of RS capacity and flow can help managers and planners prioritize actions in the context of best management practices and compatible use buffers. Staff surveys indicated that our approach was informative and easy to use. Implementation may be most limited by on-installation personnel time.

Pharmaceutical Occurrence in Groundwater and Surface Waters in Forests Land-Applied with Municipal Wastewater

PubMed Central

McEachran, Andrew D.; Shea, Damian; Bodnar, Wanda; Nichols, Elizabeth Guthrie

2016-01-01

The occurrence and fate of pharmaceutical and personal care products in the environment are of increasing public importance because of their ubiquitous nature and documented effects on wildlife, ecosystems, and potentially humans. One potential, yet undefined, source of entry of pharmaceuticals into the environment is via the land application of municipal wastewater onto permitted lands. The objective of the present study is to determine the extent to which pharmaceuticals are mitigated by or exported from managed tree plantations irrigated with municipal wastewater. A specific focus of the present study is the presence of pharmaceutical compounds in groundwater and surface water discharge. The study site is a municipality that land-applies secondary treated wastewater onto 930 hectares of a 2000-hectare managed hardwood and pine plantation. A suite of 33 pharmaceuticals and steroid hormones was targeted in the analysis, which consisted of monthly grab sampling of groundwater, surface water, and wastewater, followed by concentration and cleanup via solid phase extraction and separation, detection, and quantification via liquid chromatography coupled with tandem mass spectrometry. More than one-half of all compounds detected in irrigated wastewater were not present in groundwater and subsequent surface water. However, antibiotics, nonsteroidal anti-inflammatory drugs, caffeine, and other prescription and over-the-counter drugs remained in groundwater and were transported into surface water at concentrations up to 10 ng/L. These results provide important documentation for pharmaceutical fate and transport in forest systems irrigated with municipal wastewater, a previously undocumented source of environmental entry. PMID:26297815

Land surface temperature measurements from EOS MODIS data

NASA Technical Reports Server (NTRS)

Wan, Zhengming

1994-01-01

A generalized split-window method for retrieving land-surface temperature (LST) from AVHRR and MODIS data has been developed. Accurate radiative transfer simulations show that the coefficients in the split-window algorithm for LST must depend on the viewing angle, if we are to achieve a LST accuracy of about 1 K for the whole scan swath range (+/-55.4 deg and +/-55 deg from nadir for AVHRR and MODIS, respectively) and for the ranges of surface temperature and atmospheric conditions over land, which are much wider than those over oceans. We obtain these coefficients from regression analysis of radiative transfer simulations, and we analyze sensitivity and error by using results from systematic radiative transfer simulations over wide ranges of surface temperatures and emissivities, and atmospheric water vapor abundance and temperatures. Simulations indicated that as atmospheric column water vapor increases and viewing angle is larger than 45 deg it is necessary to optimize the split-window method by separating the ranges of the atmospheric column water vapor and lower boundary temperature, and the surface temperature into tractable sub-ranges. The atmospheric lower boundary temperature and (vertical) column water vapor values retrieved from HIRS/2 or MODIS atmospheric sounding channels can be used to determine the range where the optimum coefficients of the split-window method are given. This new LST algorithm not only retrieves LST more accurately but also is less sensitive than viewing-angle independent LST algorithms to the uncertainty in the band emissivities of the land-surface in the split-window and to the instrument noise.

Incorporating JULES into NASA's Land Information System (LIS) and Investigations of Land-Atmosphere Coupling

NASA Technical Reports Server (NTRS)

Santanello, Joseph

2011-01-01

NASA's Land Information System (LIS; lis.gsfc.nasa.gov) is a flexible land surface modeling and data assimilation framework developed over the past decade with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. LIS features a high performance and flexible design, and operates on an ensemble of land surface models for extension over user-specified regional or global domains. The extensible interfaces of LIS allow the incorporation of new domains, land surface models (LSMs), land surface parameters, meteorological inputs, data assimilation and optimization algorithms. In addition, LIS has also been demonstrated for parameter estimation and uncertainty estimation, and has been coupled to the Weather Research and Forecasting (WRF) mesoscale model. A visiting fellowship is currently underway to implement JULES into LIS and to undertake some fundamental science on the feedbacks between the land surface and the atmosphere. An overview of the LIS system, features, and sample results will be presented in an effort to engage the community in the potential advantages of LIS-JULES for a range of applications. Ongoing efforts to develop a framework for diagnosing land-atmosphere coupling will also be presented using the suite of LSM and PBL schemes available in LIS and WRF along with observations from the U. S .. Southern Great Plains. This methodology provides a potential pathway to study factors controlling local land-atmosphere coupling (LoCo) using the LIS-WRF system, which will serve as a testbed for future experiments to evaluate coupling diagnostics within the community.

The ERTS-1 investigation (ER-600): A compendium of analysis results of the utility of ERTS-1 data for land resources management

NASA Technical Reports Server (NTRS)

Erb, R. B.

1974-01-01

The results of the ERTS-1 investigations conducted by the Earth Observations Division at the NASA Lyndon B. Johnson Space Center are summarized in this report, which is an overview of documents detailing individual investigations. Conventional image interpretation and computer-aided classification procedures were the two basic techniques used in analyzing the data for detecting, identifying, locating, and measuring surface features related to earth resources. Data from the ERTS-1 multispectral scanner system were useful for all applications studied, which included agriculture, coastal and estuarine analysis, forestry, range, land use and urban land use, and signature extension. Percentage classification accuracies are cited for the conventional and computer-aided techniques.

Estimating surface fluxes over middle and upper streams of the Heihe River Basin with ASTER imagery

NASA Astrophysics Data System (ADS)

Ma, W.; Ma, Y.; Hu, Z.; Su, Z.; Wang, J.; Ishikawa, H.

2011-05-01

Land surface heat fluxes are essential measures of the strengths of land-atmosphere interactions involving energy, heat and water. Correct parameterization of these fluxes in climate models is critical. Despite their importance, state-of-the-art observation techniques cannot provide representative areal averages of these fluxes comparable to the model grid. Alternative methods of estimation are thus required. These alternative approaches use (satellite) observables of the land surface conditions. In this study, the Surface Energy Balance System (SEBS) algorithm was evaluated in a cold and arid environment, using land surface parameters derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. Field observations and estimates from SEBS were compared in terms of net radiation flux (Rn), soil heat flux (G0), sensible heat flux (H) and latent heat flux (λE) over a heterogeneous land surface. As a case study, this methodology was applied to the experimental area of the Watershed Allied Telemetry Experimental Research (WATER) project, located on the mid-to-upstream sections of the Heihe River in northwest China. ASTER data acquired between 3 May and 4 June 2008, under clear-sky conditions were used to determine the surface fluxes. Ground-based measurements of land surface heat fluxes were compared with values derived from the ASTER data. The results show that the derived surface variables and the land surface heat fluxes furnished by SEBS in different months over the study area are in good agreement with the observed land surface status under the limited cases (some cases looks poor results). So SEBS can be used to estimate turbulent heat fluxes with acceptable accuracy in areas where there is partial vegetation cover in exceptive conditions. It is very important to perform calculations using ground-based observational data for parameterization in SEBS in the future. Nevertheless, the remote-sensing results can provide improved explanations of land surface fluxes over varying land coverage at greater spatial scales.

Impact of Calibrated Land Surface Model Parameters on the Accuracy and Uncertainty of Land-Atmosphere Coupling in WRF Simulations

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (LIS-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

Has the conversion of natural wetlands to agricultural land increased the incidence and severity of damaging freezes in south Florida?

USGS Publications Warehouse

Marshall, C.H.; Pielke, R.A.; Steyaert, L.T.

2004-01-01

On several occasions, winter freezes have wrought severe destruction on Florida agriculture. A series of devastating freezes around the turn of the twentieth century, and again during the 1980s, were related to anomalies in the large-scale flow of the ocean–atmosphere system. During the twentieth century, substantial areas of wetlands in south Florida were drained and converted to agricultural land for winter fresh vegetable and sugarcane production. During this time, much of the citrus industry also was relocated to those areas to escape the risk of freeze farther to the north. The purpose of this paper is to present a modeling study designed to investigate whether the conversion of the wetlands to agriculture itself could have resulted in or exacerbated the severity of recent freezes in those agricultural areas of south Florida.For three recent freeze events, a pair of simulations was undertaken with the Regional Atmospheric Modeling System. One member of each pair employed land surface properties that represent pre-1900s (near natural) land cover, whereas the other member of each pair employed data that represent near-current land-use patterns as derived from analysis of Landsat data valid for 1992/93. These two different land cover datasets capture well the conversion of wetlands to agriculture in south Florida during the twentieth century. Use of current land surface properties resulted in colder simulated minimum temperatures and temperatures that remained below freezing for a longer period at locations of key agricultural production centers in south Florida that were once natural wetlands. Examination of time series of the surface energy budget from one of the cases reveals that when natural land cover is used, a persistent moisture flux from the underlying wetlands during the nighttime hours served to prevent the development of below-freezing temperatures at those same locations. When the model results were subjected to an important sensitivity factor, the depth of standing water in the wetlands, the outcome remained consistent. These results provide another example of the potential for humans to perturb the climate system in ways that can have severe socioeconomic consequences by altering the land surface alone.

Advanced Land Surface Processes in the Coupled WRF/CMAQ with MODIS Input

EPA Science Inventory

Land surface modeling (LSM) is important in WRF/CMAQ for simulating the exchange of heat, moisture, momentum, trace atmospheric chemicals, and windblown dust between the land surface and the atmosphere.? Vegetation and soil treatments are crucial in LSM for surface energy budgets...

Evolution of Indian land surface biases in the seasonal hindcasts from the Met Office Global Seasonal Forecasting System GloSea5

NASA Astrophysics Data System (ADS)

Chevuturi, Amulya; Turner, Andrew G.; Woolnoug, Steve J.; Martin, Gill

2017-04-01

In this study we investigate the development of biases over the Indian region in summer hindcasts of the UK Met Office coupled initialised global seasonal forecasting system, GloSea5-GC2. Previous work has demonstrated the rapid evolution of strong monsoon circulation biases over India from seasonal forecasts initialised in early May, together with coupled strong easterly wind biases on the equator. These mean state biases lead to strong precipitation errors during the monsoon over the subcontinent. We analyse a set of three springtime start dates for the 20-year hindcast period (1992-2011) and fifteen total ensemble members for each year. We use comparisons with variety of observations to assess the evolution of the mean state biases over the Indian land surface. All biases within the model develop rapidly, particularly surface heat and radiation flux biases. Strong biases are present within the model climatology from pre-monsoon (May) in the surface heat fluxes over India (higher sensible / lower latent heat fluxes) when compared to observed estimates. The early evolution of such biases prior to onset rains suggests possible problems with the land surface scheme or soil moisture errors. Further analysis of soil moisture over the Indian land surface shows a dry bias present from the beginning of the hindcasts during the pre-monsoon. This lasts until the after the monsoon develops (July) after which there is a wet bias over the region. Soil moisture used for initialization of the model also shows a dry bias when compared against the observed estimates, which may lead to the same in the model. The early dry bias in the model may reduce local moisture availability through surface evaporation and thus may possibly limit precipitation recycling. On this premise, we identify and test the sensitivity of the monsoon in the model against higher soil moisture forcing. We run sensitivity experiments initiated using gridpoint-wise annual soil moisture maxima over the Indian land surface as input for experiments in the atmosphere-only version of the model. We plan to analyse the response of the sensitivity experiments on seasonal forecasting of surface heat fluxes and subsequently monsoon precipitation.

A New Neural Network Approach Including First-Guess for Retrieval of Atmospheric Water Vapor, Cloud Liquid Water Path, Surface Temperature and Emissivities Over Land From Satellite Microwave Observations

NASA Technical Reports Server (NTRS)

Aires, F.; Prigent, C.; Rossow, W. B.; Rothstein, M.; Hansen, James E. (Technical Monitor)

2000-01-01

The analysis of microwave observations over land to determine atmospheric and surface parameters is still limited due to the complexity of the inverse problem. Neural network techniques have already proved successful as the basis of efficient retrieval methods for non-linear cases, however, first-guess estimates, which are used in variational methods to avoid problems of solution non-uniqueness or other forms of solution irregularity, have up to now not been used with neural network methods. In this study, a neural network approach is developed that uses a first-guess. Conceptual bridges are established between the neural network and variational methods. The new neural method retrieves the surface skin temperature, the integrated water vapor content, the cloud liquid water path and the microwave surface emissivities between 19 and 85 GHz over land from SSM/I observations. The retrieval, in parallel, of all these quantities improves the results for consistency reasons. A data base to train the neural network is calculated with a radiative transfer model and a a global collection of coincident surface and atmospheric parameters extracted from the National Center for Environmental Prediction reanalysis, from the International Satellite Cloud Climatology Project data and from microwave emissivity atlases previously calculated. The results of the neural network inversion are very encouraging. The r.m.s. error of the surface temperature retrieval over the globe is 1.3 K in clear sky conditions and 1.6 K in cloudy scenes. Water vapor is retrieved with a r.m.s. error of 3.8 kg/sq m in clear conditions and 4.9 kg/sq m in cloudy situations. The r.m.s. error in cloud liquid water path is 0.08 kg/sq m . The surface emissivities are retrieved with an accuracy of better than 0.008 in clear conditions and 0.010 in cloudy conditions. Microwave land surface temperature retrieval presents a very attractive complement to the infrared estimates in cloudy areas: time record of land surface temperature will be produced.

Does the spatial arrangement of vegetation and anthropogenic land cover features matter? Case studies of urban warming and cooling in Phoenix and Las Vegas

NASA Astrophysics Data System (ADS)

Myint, S. W.; Zheng, B.; Fan, C.; Kaplan, S.; Brazel, A.; Middel, A.; Smith, M.

2014-12-01

While the relationship between fractional cover of anthropogenic and vegetation features and the urban heat island has been well studied, the effect of spatial arrangements (e.g., clustered, dispersed) of these features on urban warming or cooling are not well understood. The goal of this study is to examine if and how spatial configuration of land cover features influence land surface temperatures (LST) in urban areas. This study focuses on Phoenix, AZ and Las Vegas, NV that have undergone dramatic urban expansion. The data used to classify detailed urban land cover types include Geoeye-1 (Las Vegas) and QuickBird (Phoenix). The Geoeye-1 image (3 m resolution) was acquired on October 12, 2011 and the QuickBird image (2.4 m resolution) was taken on May 29, 2007. Classification was performed using object based image analysis (OBIA). We employed a spatial autocorrelation approach (i.e., Moran's I) that measures the spatial dependence of a point to its neighboring points and describes how clustered or dispersed points are arranged in space. We used Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data acquired over Phoenix (daytime on June 10, 2011 and nighttime on October 17, 2011) and Las Vegas (daytime on July 6, 2005 and nighttime on August 27, 2005) to examine daytime and nighttime LST with regards to the spatial arrangement of anthropogenic and vegetation features. We spatially correlate Moran's I values of each land cover per surface temperature, and develop regression models. The spatial configuration of grass and trees shows strong negative correlations with LST, implying that clustered vegetation lowers surface temperatures more effectively. In contrast, a clustered spatial arrangement of anthropogenic land-cover features, especially impervious surfaces, significantly elevates surface temperatures. Results from this study suggest that the spatial configuration of anthropogenic and vegetation features influence urban warming and cooling.

Radiation fluxes at the FIFE site

NASA Technical Reports Server (NTRS)

Walter-Shea, Elizabeth A.; Blad, Blaine L.; Zara, Pedro; Vining, Roel; Hays, Cynthia J.; Mesarch, Mark A.

1993-01-01

The main objective of the International Satellite Land Surface Climatology Project (ISLSCP) has been stated as 'the development of techniques that may be applied to satellite observations of the radiation reflected and emitted from the Earth to yield quantitative information concerning land surface climatological conditions'. The major field study, FIFE (the First ISLSCP Field Experiment), was conducted in 1987-89 to accomplish this objective. Four intensive field campaigns (IFC's) were carried out in 1987 and one in 1989. Factors contributing to observed reflected radiation from the FIFE site must be understood before the radiation observed by satellites can be used to quantify surface processes. Our last report (Walter-Shea et al., 1992b) focused on slope effects on incoming and outgoing shortwave radiation and net radiation from data collected in 1989. We report here on the final analysis of the slope data as well as results from thermal radiation studies conducted during the FIFE experiment. The specific areas reported are the following: (1) analysis of slope effects on measured reflectance values and estimates of surface albedo; (2) using remotely-measured surface temperatures as a means of estimating sensible heat flux from the Konza Prairie; (3) extracting canopy temperatures from remotely-measured composite surface temperatures; (4) modeling the measured composite temperature of partially vegetated surfaces; and (5) estimating gap distribution in partially vegetated surfaces from reflectance measurements.

Lunar Surface Architecture Utilization and Logistics Support Assessment

NASA Astrophysics Data System (ADS)

Bienhoff, Dallas; Findiesen, William; Bayer, Martin; Born, Andrew; McCormick, David

2008-01-01

Crew and equipment utilization and logistics support needs for the point of departure lunar outpost as presented by the NASA Lunar Architecture Team (LAT) and alternative surface architectures were assessed for the first ten years of operation. The lunar surface architectures were evaluated and manifests created for each mission. Distances between Lunar Surface Access Module (LSAM) landing sites and emplacement locations were estimated. Physical characteristics were assigned to each surface element and operational characteristics were assigned to each surface mobility element. Stochastic analysis was conducted to assess probable times to deploy surface elements, conduct exploration excursions, and perform defined crew activities. Crew time is divided into Outpost-related, exploration and science, overhead, and personal activities. Outpost-related time includes element deployment, EVA maintenance, IVA maintenance, and logistics resupply. Exploration and science activities include mapping, geological surveys, science experiment deployment, sample analysis and categorizing, and physiological and biological tests in the lunar environment. Personal activities include sleeping, eating, hygiene, exercising, and time off. Overhead activities include precursor or close-out tasks that must be accomplished but don't fit into the other three categories such as: suit donning and doffing, airlock cycle time, suit cleaning, suit maintenance, post-landing safing actions, and pre-departure preparations. Equipment usage time, spares, maintenance actions, and Outpost consumables are also estimated to provide input into logistics support planning. Results are normalized relative to the NASA LAT point of departure lunar surface architecture.

Radiation fluxes at the FIFE site. Final report, 1 January 1991-31 July 1992

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walter-Shea, E.A.; Blad, B.L.; Zara, P.

1993-01-01

The main objective of the International Satellite Land Surface Climatology Project (ISLSCP) has been stated as 'the development of techniques that may be applied to satellite observations of the radiation reflected and emitted from the Earth to yield quantitative information concerning land surface climatological conditions'. The major field study, FIFE (the First ISLSCP Field Experiment), was conducted in 1987-89 to accomplish this objective. Four intensive field campaigns (IFC's) were carried out in 1987 and one in 1989. Factors contributing to observed reflected radiation from the FIFE site must be understood before the radiation observed by satellites can be used tomore » quantify surface processes. Our last report (Walter-Shea et al.) focused on slope effects on incoming and outgoing shortwave radiation and net radiation from data collected in 1989. We report here on the final analysis of the slope data as well as results from thermal radiation studies conducted during the FIFE experiment. The specific areas reported are the following: (1) analysis of slope effects on measured reflectance values and estimates of surface albedo; (2) using remotely-measured surface temperatures as a means of estimating sensible heat flux from the Konza Prairie; (3) extracting canopy temperatures from remotely-measured composite surface temperatures; (4) modeling the measured composite temperature of partially vegetated surfaces; and (5) estimating gap distribution in partially vegetated surfaces from reflectance measurements.« less

Saturn Apollo Program

NASA Image and Video Library

1979-05-01

This montage depicts the flight crew patches for the manned Apollo 7 thru Apollo 17 missions. The Apollo 7 through 10 missions were basically manned test flights that paved the way for lunar landing missions. Primary objectives met included the demonstration of the Command Service Module (CSM) crew performance; crew/space vehicle/mission support facilities performance and testing during a manned CSM mission; CSM rendezvous capability; translunar injection demonstration; the first manned Apollo docking, the first Apollo Extra Vehicular Activity (EVA), performance of the first manned flight of the lunar module (LM); the CSM-LM docking in translunar trajectory, LM undocking in lunar orbit, LM staging in lunar orbit, and manned LM-CSM docking in lunar orbit. Apollo 11 through 17 were lunar landing missions with the exception of Apollo 13 which was forced to circle the moon without landing due to an onboard explosion. The craft was,however, able to return to Earth safely. Apollo 11 was the first manned lunar landing mission and performed the first lunar surface EVA. Landing site was the Sea of Tranquility. A message for mankind was delivered, the U.S. flag was planted, experiments were set up and 47 pounds of lunar surface material was collected for analysis back on Earth. Apollo 12, the 2nd manned lunar landing mission landed in the Ocean of Storms and retrieved parts of the unmanned Surveyor 3, which had landed on the Moon in April 1967. The Apollo Lunar Surface Experiments Package (ALSEP) was deployed, and 75 pounds of lunar material was gathered. Apollo 14, the 3rd lunar landing mission landed in Fra Mauro. ALSEP and other instruments were deployed, and 94 pounds of lunar materials were gathered, using a hand cart for first time to transport rocks. Apollo 15, the 4th lunar landing mission landed in the Hadley-Apennine region. With the first use of the Lunar Roving Vehicle (LRV), the crew was bale to gather 169 pounds of lunar material. Apollo 16, the 5th lunar landing mission, landed in the Descartes Highlands for the first study of highlands area. Selected surface experiments were deployed, the ultraviolet camera/spectrograph was used for first time on the Moon, and the LRV was used for second time for a collection of 213 pounds of lunar material. The Apollo program came to a close with Apollo 17, the 6th and final manned lunar landing mission that landed in the Taurus-Littrow highlands and valley area. This mission hosted the first scientist-astronaut, Schmitt, to land on the Moon. The 6th automated research station was set up, and 243 ponds of lunar material was gathered using the LRV.

Montage of Apollo Crew Patches

NASA Technical Reports Server (NTRS)

1979-01-01

This montage depicts the flight crew patches for the manned Apollo 7 thru Apollo 17 missions. The Apollo 7 through 10 missions were basically manned test flights that paved the way for lunar landing missions. Primary objectives met included the demonstration of the Command Service Module (CSM) crew performance; crew/space vehicle/mission support facilities performance and testing during a manned CSM mission; CSM rendezvous capability; translunar injection demonstration; the first manned Apollo docking, the first Apollo Extra Vehicular Activity (EVA), performance of the first manned flight of the lunar module (LM); the CSM-LM docking in translunar trajectory, LM undocking in lunar orbit, LM staging in lunar orbit, and manned LM-CSM docking in lunar orbit. Apollo 11 through 17 were lunar landing missions with the exception of Apollo 13 which was forced to circle the moon without landing due to an onboard explosion. The craft was,however, able to return to Earth safely. Apollo 11 was the first manned lunar landing mission and performed the first lunar surface EVA. Landing site was the Sea of Tranquility. A message for mankind was delivered, the U.S. flag was planted, experiments were set up and 47 pounds of lunar surface material was collected for analysis back on Earth. Apollo 12, the 2nd manned lunar landing mission landed in the Ocean of Storms and retrieved parts of the unmanned Surveyor 3, which had landed on the Moon in April 1967. The Apollo Lunar Surface Experiments Package (ALSEP) was deployed, and 75 pounds of lunar material was gathered. Apollo 14, the 3rd lunar landing mission landed in Fra Mauro. ALSEP and other instruments were deployed, and 94 pounds of lunar materials were gathered, using a hand cart for first time to transport rocks. Apollo 15, the 4th lunar landing mission landed in the Hadley-Apennine region. With the first use of the Lunar Roving Vehicle (LRV), the crew was bale to gather 169 pounds of lunar material. Apollo 16, the 5th lunar landing mission, landed in the Descartes Highlands for the first study of highlands area. Selected surface experiments were deployed, the ultraviolet camera/spectrograph was used for first time on the Moon, and the LRV was used for second time for a collection of 213 pounds of lunar material. The Apollo program came to a close with Apollo 17, the 6th and final manned lunar landing mission that landed in the Taurus-Littrow highlands and valley area. This mission hosted the first scientist-astronaut, Schmitt, to land on the Moon. The 6th automated research station was set up, and 243 ponds of lunar material was gathered using the LRV.

Short-Term Retrospective Land Data Assimilation Schemes

NASA Technical Reports Server (NTRS)

Houser, P. R.; Cosgrove, B. A.; Entin, J. K.; Lettenmaier, D.; ODonnell, G.; Mitchell, K.; Marshall, C.; Lohmann, D.; Schaake, J. C.; Duan, Q.;

Detection of heat wave using Kalpana-1 VHRR land surface temperature product over India

NASA Astrophysics Data System (ADS)

Shah, Dhiraj; Pandya, Mehul R.; Pathak, Vishal N.; Darji, Nikunj P.; Trivedi, Himanshu J.

2016-05-01

Heat Waves can have notable impacts on human mortality, ecosystem, economics and energy supply. The effect of heat wave is much more intense during summer than the other seasons. During the period of April to June, spells of very hot weather occur over certain regions of India and global warming scenario may result in further increases of such temperature anomalies and corresponding heat waves conditions. In this paper, satellite observations have been used to detect the heat wave conditions prevailing over India for the period of May-June 2015. The Kalpana-1 VHRR derived land surface temperature (LST) products have been used in the analysis to detect the heat wave affected regions over India. Results from the analysis shows the detection of heat wave affected pixels over Indian land mass. It can be seen that during the study period the parts of the west India, Indo-gangetic plane, Telangana and part of Vidarbh was under severe heat wave conditions which is also confirmed with Automatic Weather Station (AWS) air temperature observations.

The Value of GRACE Data in Improving, Assessing and Evaluating Land Surface and Climate Models

NASA Astrophysics Data System (ADS)

Yang, Z.

2011-12-01

I will review how the Gravity Recovery and Climate Experiment (GRACE) satellite measurements have improved land surface models that are developed for weather, climate, and hydrological studies. GRACE-derived terrestrial water storage (TWS) changes have been successfully used to assess and evaluate the improved representations of land-surface hydrological processes such as groundwater-soil moisture interaction, frozen soil and infiltration, and the topographic control on runoff production, as evident in the simulations from the latest Noah-MP, the Community Land Model, and the Community Climate System Model. GRACE data sets have made it possible to estimate key terrestrial water storage components (snow mass, surface water, groundwater or water table depth), biomass, and surface water fluxes (evapotranspiration, solid precipitation, melt of snow/ice). Many of the examples will draw from my Land, Environment and Atmosphere Dynamics group's work on land surface model developments, snow mass retrieval, and multi-sensor snow data assimilation using the ensemble Karman filter and the ensemble Karman smoother. Finally, I will briefly outline some future directions in using GRACE in land surface modeling.

Continuation of measurement of hydrologic soil-cover complex with airborne scatterometers. [Texas

NASA Technical Reports Server (NTRS)

Blanchard, B. J.; Nieber, J. L.; Blanchard, A. J. (Principal Investigator)

1979-01-01

The author has identified the following significant results. Analysis of radar scatterometry data obtained over five flight lines in Texas by NASA C-130 aircraft demonstrated that multivariant radar data can be used to distinguish difference in land use, and hence be an indicator of surface runoff characteristics. The capability of using microwave sensors to detect flood inundation of timbered land was also determined.

Possibility of microscopic liquid water formation at landing sites on Mars and their observational potential

NASA Astrophysics Data System (ADS)

Pál, B.; Kereszturi, Á.

2017-01-01

Microscopic liquid brines, especially calcium-perchlorate could emerge by deliquescence on Mars during night time hours. Using climate model computations and orbital humidity observations, the ideal periods and their annual plus daily characteristics at various past, current and future landing sites were compared. Such results provide context for future analysis and targeting the related observations by the next missions for Mars. Based on the analysis, at most (but not all) past missions' landing sites, microscopic brine could emerge during night time for different durations. Analysing the conditions at ExoMars rover's primary landing site at Oxia Planum, the best annual period was found to be between Ls 115-225, and in Local Time 2-5, after midnight. In an ideal case, 4 h of continuous liquid phase can emerge there. Local conditions might cause values to differ from those estimated by the model. Thermal inertia could especially make such differences (low TI values favour fast cooling and H2O cold trapping at loose surfaces) and the concentration of calcium-perchlorate salt in the regolith also influences the process (it might occur preferentially at long-term exposed surfaces without recent loose dust coverage). These factors should be taken into account while targeting future liquid water observations on Mars.

Trend analysis of time-series phenology of North America derived from satellite data

USGS Publications Warehouse

Reed, B.C.

2006-01-01

Remote sensing information has been used in studies of the seasonal dynamics (phenology) of the land surface since the 1980s. While our understanding of remote sensing phenology is still in development, it is regarded as a key to understanding land-surface processes over large areas. Phenologic metrics, including start of season, end of season, duration of season, and seasonally integrated greenness, were derived from 8 km advanced very high resolution radiometer (AVHRR) data over North America spanning the years 1982-2003. Trend analysis was performed on annual summaries of the metrics to determine areas with increasing or decreasing growing season trends for the time period under study. Results show a trend toward earlier starts of season in limited areas of the mixed boreal forest, and a trend toward later end of season in well-defined areas of New England and southeastern Canada. Results in Saskatchewan, Canada, include a trend toward longer duration of season over a well-defined area, principally as a result of regional changes in land use practices. Changing seasonality appears to be an integrated response to a complex of factors, including climate change, but also, in many places, changes in land use practices. Copyright ?? 2006 by V. H. Winston & Son, Inc. All rights reserved.

Selecting landing sites for lunar lander missions using spatial analysis

NASA Astrophysics Data System (ADS)

Djachkova, Maia; Lazarev, Evgeniy

Russian Federal Space Agency (Roscosmos) is planning to launch two spacecrafts to the Moon with lander missions in 2015 and 2017. [1] Here, we present an approach to create a method of landing sites selection. We researched the physical features of the Moon using spatial analysis techniques presented in ArcGIS Desktop Software in accordance with its suitability for automatic landing. Hence we analyzed Russian lunar program and received the technical characteristics of the spacecrafts and scientific goals that they should meet [1]. Thus we identified the criteria of surface suitability for landing. We divided them into two groups: scientific criteria (the hydrogen content of the regolith [2] and day and night sur-face temperature [3]) and safety criteria (surface slopes and roughness, sky view factor, the Earth altitude, presence of polar permanently shadowed regions). In conformity with some investigations it is believed that the south polar region of the Moon is the most promising territory where water ice can be found (finding water ice is the main goal for Russian lunar missions [1]). According to the selected criteria and selected area of research we used remote sensing data from LRO (Lunar Reconnaissance Orbiter) [4] as basic data, because it is the most actual and easily available. The data was processed and analyzed using spatial analysis techniques of ArcGIS Desktop Software, so we created a number of maps depicting the criteria and then combined and overlaid them. As a result of overlay process we received five territories where the landing will be safe and the scientific goals will have being met. It should be noted that our analysis is only the first order assessment and the results cannot be used as actual landing sites for the lunar missions in 2015 and 2017, since a number of factors, which can only be analyzed in a very large scale, was not taken into account. However, an area of researching is narrowed to five territories, what can make the future research much easier. The analysis of these five areas in a large scale will be the subject of further research. References: [1] Mitrofanov I. G. et al. (2011) LPS XLII, Abstract #1798 [2] Mitrofanov I. G., et al. Hydrogen Mapping of the Lunar South Pole Using the LRO Neutron Detector Experiment LEND // Science vol. 330 2010, pp. 483-486 [3] Paige D.A. et al. (2011) LPS XLII, Abstract #2544 [4] Zuber M.T. et al. (2010) Space Sci. Rev., 150, 63-80

Estimating snow water equivalent from GPS vertical site-position observations in the western United States

PubMed Central

Ouellette, Karli J; de Linage, Caroline; Famiglietti, James S

2013-01-01

[1] Accurate estimation of the characteristics of the winter snowpack is crucial for prediction of available water supply, flooding, and climate feedbacks. Remote sensing of snow has been most successful for quantifying the spatial extent of the snowpack, although satellite estimation of snow water equivalent (SWE), fractional snow covered area, and snow depth is improving. Here we show that GPS observations of vertical land surface loading reveal seasonal responses of the land surface to the total weight of snow, providing information about the stored SWE. We demonstrate that the seasonal signal in Scripps Orbit and Permanent Array Center (SOPAC) GPS vertical land surface position time series at six locations in the western United States is driven by elastic loading of the crust by the snowpack. GPS observations of land surface deformation are then used to predict the water load as a function of time at each location of interest and compared for validation to nearby Snowpack Telemetry observations of SWE. Estimates of soil moisture are included in the analysis and result in considerable improvement in the prediction of SWE. Citation: Ouellette, K. J., C. de Linage, and J. S. Famiglietti (2013), Estimating snow water equivalent from GPS vertical site-position observations in the western United States, Water Resour. Res., 49, 2508–2518, doi:10.1002/wrcr.20173. PMID:24223442

GLORI: A GNSS-R Dual Polarization Airborne Instrument for Land Surface Monitoring

PubMed Central

Motte, Erwan; Zribi, Mehrez; Fanise, Pascal; Egido, Alejandro; Darrozes, José; Al-Yaari, Amen; Baghdadi, Nicolas; Baup, Frédéric; Dayau, Sylvia; Fieuzal, Remy; Frison, Pierre-Louis; Guyon, Dominique; Wigneron, Jean-Pierre

2016-01-01

Global Navigation Satellite System-Reflectometry (GNSS-R) has emerged as a remote sensing tool, which is complementary to traditional monostatic radars, for the retrieval of geophysical parameters related to surface properties. In the present paper, we describe a new polarimetric GNSS-R system, referred to as the GLObal navigation satellite system Reflectometry Instrument (GLORI), dedicated to the study of land surfaces (soil moisture, vegetation water content, forest biomass) and inland water bodies. This system was installed as a permanent payload on a French ATR42 research aircraft, from which simultaneous measurements can be carried out using other instruments, when required. Following initial laboratory qualifications, two airborne campaigns involving nine flights were performed in 2014 and 2015 in the Southwest of France, over various types of land cover, including agricultural fields and forests. Some of these flights were made concurrently with in situ ground truth campaigns. Various preliminary applications for the characterisation of agricultural and forest areas are presented. Initial analysis of the data shows that the performance of the GLORI instrument is well within specifications, with a cross-polarization isolation better than −15 dB at all elevations above 45°, a relative polarimetric calibration accuracy better than 0.5 dB, and an apparent reflectivity sensitivity better than −30 dB, thus demonstrating its strong potential for the retrieval of land surface characteristics. PMID:27213393

GLORI: A GNSS-R Dual Polarization Airborne Instrument for Land Surface Monitoring.

PubMed

Motte, Erwan; Zribi, Mehrez; Fanise, Pascal; Egido, Alejandro; Darrozes, José; Al-Yaari, Amen; Baghdadi, Nicolas; Baup, Frédéric; Dayau, Sylvia; Fieuzal, Remy; Frison, Pierre-Louis; Guyon, Dominique; Wigneron, Jean-Pierre

2016-05-20

Global Navigation Satellite System-Reflectometry (GNSS-R) has emerged as a remote sensing tool, which is complementary to traditional monostatic radars, for the retrieval of geophysical parameters related to surface properties. In the present paper, we describe a new polarimetric GNSS-R system, referred to as the GLObal navigation satellite system Reflectometry Instrument (GLORI), dedicated to the study of land surfaces (soil moisture, vegetation water content, forest biomass) and inland water bodies. This system was installed as a permanent payload on a French ATR42 research aircraft, from which simultaneous measurements can be carried out using other instruments, when required. Following initial laboratory qualifications, two airborne campaigns involving nine flights were performed in 2014 and 2015 in the Southwest of France, over various types of land cover, including agricultural fields and forests. Some of these flights were made concurrently with in situ ground truth campaigns. Various preliminary applications for the characterisation of agricultural and forest areas are presented. Initial analysis of the data shows that the performance of the GLORI instrument is well within specifications, with a cross-polarization isolation better than -15 dB at all elevations above 45°, a relative polarimetric calibration accuracy better than 0.5 dB, and an apparent reflectivity sensitivity better than -30 dB, thus demonstrating its strong potential for the retrieval of land surface characteristics.

Watershed Characteristics and Land Management in the Nonpoint-Source Evaluation Monitoring Watersheds in Wisconsin

USGS Publications Warehouse

Rappold, K.F.; Wierl, J.A.; Amerson, F.U.

1997-01-01

In 1992, the Wisconsin Department of Natural Resources, in cooperation with the U.S. Geological Survey, began a land-use inventory to identify sources of contaminants and track the land-management changes for eight evaluation monitoring watersheds in Wisconsin. An important component of the land-use inventory has been developing descriptions and preliminary assessments for the eight watersheds. These descriptions establish a baseline for future data analysis. The watershed descriptions include sections on location, reference watersheds, climate, land use, soils and topography, and surface-water resources. The land-management descriptions include sections on objectives, sources of nonpoint contamination and goals of contaminant reduction, and implementation of best-management practices. This information was compiled primarily from the nonpoint-source control plans, county soil surveys, farm conservation plans, Federal and State agency data reports, and data collected through the land-use inventory.

Thermal Infrared Remote Sensing for Analysis of Landscape Ecological Processes: Current Insights and Trends. Chapter 3

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.

2014-01-01

NASA or NOAA Earth-observing satellites are not the only space-based TIR platforms. The European Space Agency (ESA), the Chinese, and other countries have in orbit or plan to launch TIR remote sensing systems. Satellite remote sensing provides an excellent opportunity to study land-atmosphere energy exchanges at the regional scale. A predominant application of TIR data has been in inferring evaporation, evapotranspiration (ET), and soil moisture. In addition to using TIR data for ET and soil moisture analysis over vegetated surfaces, there is also a need for using these data for assessment of drought conditions. The concept of ecological thermodynamics provides a quantification of surface energy fluxes for landscape characterization in relation to the overall amount of energy input and output from specific land cover types.

Evaluation of subsurface exploration, sampling, and water-quality-analysis methods at an abandoned wood-preserving plant site at Jackson, Tennessee

USGS Publications Warehouse

Parks, W.S.; Carmichael, J.K.; Mirecki, J.E.

1993-01-01

Direct Push Technology (DPT) and a modified-auger method of sampling were used at an abandoned wood-preserving plant site at Jackson, Tennessee, to collect lithologic data and ground-water samples in an area known to be affected by a subsurface creosote plume. The groundwater samples were analyzed using (1) gas chromatography with photo-ionization detection (GS/PID), (2) high- performance liquid chromatography (HPLC), (3) colonmetric phenol analysis, and (4) toxicity bioassay. DPT piezocone and cone-penetrometer-type tools provided lithologic data and ground-water samples at two onsite stations to a depth of refusal of about 35 feet below land surface. With the assistance of an auger rig, this depth was extended to about 65 feet by pushing the tools in advance of the augers. Following the DPT work, a modified-auger method was tested by the USGS. This method left doubt as to the integrity of the samples collected once zones of contamination were penetrated. GC/PID and HPLC methods of water-quality analysis provided the most data concerning contaminants in the ground-water and proved to be the most effective in creosote plume detection. Analyses from these methods showed that the highest concentrations of contaminants were detected at depths less than about 35 feet below land surface. Phenol analyses provided data supplemental to the HPLC analyses. Bioassay data indicated that toxicity associated with the plume extended to depths of about 55 feet below land surface.

Comparison of two perturbation methods to estimate the land surface modeling uncertainty

NASA Astrophysics Data System (ADS)

Su, H.; Houser, P.; Tian, Y.; Kumar, S.; Geiger, J.; Belvedere, D.

2007-12-01

In land surface modeling, it is almost impossible to simulate the land surface processes without any error because the earth system is highly complex and the physics of the land processes has not yet been understood sufficiently. In most cases, people want to know not only the model output but also the uncertainty in the modeling, to estimate how reliable the modeling is. Ensemble perturbation is an effective way to estimate the uncertainty in land surface modeling, since land surface models are highly nonlinear which makes the analytical approach not applicable in this estimation. The ideal perturbation noise is zero mean Gaussian distribution, however, this requirement can't be satisfied if the perturbed variables in land surface model have physical boundaries because part of the perturbation noises has to be removed to feed the land surface models properly. Two different perturbation methods are employed in our study to investigate their impact on quantifying land surface modeling uncertainty base on the Land Information System (LIS) framework developed by NASA/GSFC land team. One perturbation method is the built-in algorithm named "STATIC" in LIS version 5; the other is a new perturbation algorithm which was recently developed to minimize the overall bias in the perturbation by incorporating additional information from the whole time series for the perturbed variable. The statistical properties of the perturbation noise generated by the two different algorithms are investigated thoroughly by using a large ensemble size on a NASA supercomputer and then the corresponding uncertainty estimates based on the two perturbation methods are compared. Their further impacts on data assimilation are also discussed. Finally, an optimal perturbation method is suggested.

Land surface phenology of Northeast China during 2000-2015: temporal changes and relationships with climate changes.

PubMed

Zhang, Yue; Li, Lin; Wang, Hongbin; Zhang, Yao; Wang, Naijia; Chen, Junpeng

2017-10-01

As an important crop growing area, Northeast China (NEC) plays a vital role in China's food security, which has been severely affected by climate change in recent years. Vegetation phenology in this region is sensitive to climate change, and currently, the relationship between the phenology of NEC and climate change remains unclear. In this study, we used a satellite-derived normalized difference vegetation index (NDVI) to obtain the temporal patterns of the land surface phenology in NEC from 2000 to 2015 and validated the results using ground phenology observations. We then explored the relationships among land surface phenology, temperature, precipitation, and sunshine hours for relevant periods. Our results showed that the NEC experienced great phenological changes in terms of spatial heterogeneity during 2000-2015. The spatial patterns of land surface phenology mainly changed with altitude and land cover type. In most regions of NEC, the start date of land surface phenology had advanced by approximately 1.0 days year -1 , and the length of land surface phenology had been prolonged by approximately 1.0 days year -1 except for the needle-leaf and cropland areas, due to the warm conditions. We found that a distinct inter-annual variation in land surface phenology related to climate variables, even if some areas presented non-significant trends. Land surface phenology was coupled with climate variables and distinct responses at different combinations of temperature, precipitation, sunshine hours, altitude, and anthropogenic influence. These findings suggest that remote sensing and our phenology extracting methods hold great potential for helping to understand how land surface phenology is sensitive to global climate change.

Numerical evaluation of surface modifications at landing site due to spacecraft (soft) landing on the moon

NASA Astrophysics Data System (ADS)

Mishra, Sanjeev Kumar; Prasad, K. Durga

2018-07-01

Understanding surface modifications at landing site during spacecraft landing on planetary surfaces is important for planetary missions from scientific as well as engineering perspectives. An attempt has been made in this work to numerically investigate the disturbance caused to the lunar surface during soft landing. The variability of eject velocity of dust, eject mass flux rate, ejecta amount etc. has been studied. The effect of lander hovering time and hovering altitude on the extent of disturbance is also evaluated. The study thus carried out will help us in understanding the surface modifications during landing thereby making it easier to plan a descent trajectory that minimizes the extent of disturbance. The information about the extent of damage will also be helpful in interpreting the data obtained from experiments carried on the lunar surface in vicinity of the lander.

LandingNav: a precision autonomous landing sensor for robotic platforms on planetary bodies

NASA Astrophysics Data System (ADS)

Katake, Anup; Bruccoleri, Chrisitian; Singla, Puneet; Junkins, John L.

2010-01-01

Increased interest in the exploration of extra terrestrial planetary bodies calls for an increase in the number of spacecraft landing on remote planetary surfaces. Currently, imaging and radar based surveys are used to determine regions of interest and a safe landing zone. The purpose of this paper is to introduce LandingNav, a sensor system solution for autonomous landing on planetary bodies that enables landing on unknown terrain. LandingNav is based on a novel multiple field of view imaging system that leverages the integration of different state of the art technologies for feature detection, tracking, and 3D dense stereo map creation. In this paper we present the test flight results of the LandingNav system prototype. Sources of errors due to hardware limitations and processing algorithms were identified and will be discussed. This paper also shows that addressing the issues identified during the post-flight test data analysis will reduce the error down to 1-2%, thus providing for a high precision 3D range map sensor system.

Numerical Study of the Effect of Urbanization on the Climate of Desert Cities

NASA Astrophysics Data System (ADS)

Kamal, Samy

This study uses the Weather Research and Forecasting (WRF) model to simulate and predict the changes in local climate attributed to the urbanization for five desert cities. The simulations are performed in the fashion of climate downscaling, constrained by the surface boundary conditions generated from high resolution land-use maps. For each city, the land-use maps of 1985 and 2010 from Landsat satellite observation, and a projected land-use map for 2030, are used to represent the past, present, and future. An additional set of simulations for Las Vegas, the largest of the five cities, uses the NLCD 1992 and 2006 land-use maps and an idealized historical land-use map with no urban coverage for 1900. The study finds that urbanization in Las Vegas produces a classic urban heat island (UHI) at night but a minor cooling during the day. A further analysis of the surface energy balance shows that the decrease in surface Albedo and increase effective emissivity play an important role in shaping the local climate change over urban areas. The emerging urban structures slow down the diurnal wind circulation over the city due to an increased effective surface roughness. This leads to a secondary modification of temperature due to the interaction between the mechanical and thermodynamic effects of urbanization. The simulations for the five desert cities for 1985 and 2010 further confirm a common pattern of the climatic effect of urbanization with significant nighttime warming and moderate daytime cooling. This effect is confined to the urban area and is not sensitive to the size of the city or the detail of land cover in the surrounding areas. The pattern of nighttime warming and daytime cooling remains robust in the simulations for the future climate of the five cities using the projected 2030 land-use maps. Inter-city differences among the five urban areas are discussed.

A Continental United States High Resolution NLCD Land Cover – MODIS Albedo Database to Examine Albedo and Land Cover Change Relationships

EPA Science Inventory

Surface albedo influences climate by affecting the amount of solar radiation that is reflected at the Earth’s surface, and surface albedo is, in turn, affected by land cover. General Circulation Models typically use modeled or prescribed albedo to assess the influence of land co...

Slope effects on shortwave radiation components and net radiation

NASA Technical Reports Server (NTRS)

Walter-Shea, Elizabeth A.; Blad, Blaine L.; Hays, Cynthia J.; Mesarch, Mark A.

1992-01-01

The main objective of the International Satellite Land Surface Climatology Project (ISLSCP) has been stated as 'the development of techniques that may be applied to satellite observations of the radiation reflected and emitted from the Earth to yield quantitative information concerning land surface climatological conditions.' The major field study, FIFE (the First ISLSCP Field Experiment), was conducted in 1978-89 to accomplish this objective. Four intensive field campaigns (IFC's) were carried out in 1987 and one in 1989. Factors contributing to observed reflected radiation from the FIFE site must be understood before the radiation observed by satellites can be used to quantify surface processes. Analysis since our last report has focused on slope effects on incoming and outgoing shortwave radiation and net radiation from data collected in 1989.

Northern Everglades, Florida, satellite image map

USGS Publications Warehouse

Thomas, Jean-Claude; Jones, John W.

2002-01-01

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program with support from the Everglades National Park. The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

77 FR 34402 - Notice of Availability of the Final Land Use Analysis and Final Environmental Impact Statement...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-11

... mining would occur directly beneath the lake itself and no surface mining would take place. East Lynn... Rockspring have approved mining and reclamation plans from the West Virginia Department of Environmental... plan purposes if leases were to be issued and mine plans approved. The Office of Surface Mining...

Landing Characteristics of a Lenticular-Shaped Reentry Vehicle

NASA Technical Reports Server (NTRS)

Blanchard, Ulysse J.

1961-01-01

An experimental investigation was made of the landing characteristics of a 1/9-scale dynamic model of a lenticular-shaped reentry vehicle having extendible tail panels for control after reentry and for landing control (flare-out). The landing tests were made by catapulting a free model onto a hard-surface runway and onto water. A "belly-landing" technique in which the vehicle was caused to skid and rock on its curved undersurface (heat shield), converting sinking speed into angular energy, was investigated on a hard-surface runway. Landings were made in calm water and in waves both with and without auxiliary landing devices. Landing motions and acceleration data were obtained over a range of landing attitudes and initial sinking speeds during hard-surface landings and for several wave conditions during water landings. A few vertical landings (parachute letdown) were made in calm water. The hard-surface landing characteristics were good. Maximum landing accelerations on a hard surface were 5g and 18 radians per sq second over a range of landing conditions. Horizontal landings on water resulted in large violent rebounds and some diving in waves. Extreme attitude changes during rebound at initial impact made the attitude of subsequent impact random. Maximum accelerations for water landings were approximately 21g and 145 radians per sq second in waves 7 feet high. Various auxiliary water-landing devices produced no practical improvement in behavior. Reduction of horizontal speed and positive control of impact attitude did improve performance in calm water. During vertical landings in calm water maximum accelerations of 15g and 110 radians per sq second were measured for a contact attitude of -45 deg and a vertical velocity of 70 feet per second.

LIS-HYMAP coupled Hydrological Modeling in the Nile River Basin and the Greater Horn of Africa

NASA Astrophysics Data System (ADS)

Jung, H. C.; Getirana, A.; Policelli, F. S.

2015-12-01

Water scarcity and resources in Africa have been exacerbated by periodic droughts and floods. However, few studies show the quantitative analysis of water balance or basin-scale hydrological modeling in Northeast Africa. The NASA Land Information System (LIS) is implemented to simulate land surface processes in the Nile River Basin and the Greater Horn of Africa. In this context, the Noah land surface model (LSM) and the Hydrological Modeling and Analysis Platform (HYMAP) are used to reproduce the water budget and surface water (rivers and floodplains) dynamics in that region. The Global Data Assimilation System (GDAS) meteorological dataset is used to force the system . Due to the unavailability of recent ground-based observations, satellite data are considered to evaluate first model outputs. Water levels at 10 Envisat virtual stations and water discharges at a gauging station are used to provide model performance coefficients (e.g. Nash-Sutcliffe, delay index, relative error). We also compare the spatial and temporal variations of flooded areas from the model with the Global Inundation Extent from Multi-Satellites (GIEMS) and the Alaska Satellite Facility (ASF)'s MEaSUREs Wetland data. Finally, we estimate surface water storage variations using a hypsographic curve approach with Shuttle Radar Topography Mission (SRTM) topographic data and evaluate the model-derived water storage changes in both river and floodplain. This study demonstrates the feasibility of using LIS-HYMAP coupled modeling to support seasonal forecast methods for prediction of decision-relevant metrics of hydrologic extremes.

Land surface-precipitation feedback and ramifications on storm dynamics.

NASA Astrophysics Data System (ADS)

Baisya, H.; PV, R.; Pattnaik, S.

2017-12-01

A series of numerical experiments are carried out to investigate the sensitivity of a landfalling monsoon depression to land surface conditions using the Weather Research and Forecasting (WRF) model. Results suggest that precipitation is largely modulated by moisture influx and precipitation efficiency. Three cloud microphysical schemes (WSM6, WDM6, and Morrison) are examined, and Morrison is chosen for assessing the land surface-precipitation feedback analysis, owing to better precipitation forecast skills. It is found that increased soil moisture facilitates Moisture Flux Convergence (MFC) with reduced moisture influx, whereas a reduced soil moisture condition facilitates moisture influx but not MFC. A higher Moist Static Energy (MSE) is noted due to increased evapotranspiration in an elevated moisture scenario which enhances moist convection. As opposed to moist surface, sensible heat dominates in a reduced moisture scenario, ensued by an overall reduction in MSE throughout the Planetary Boundary Layer (PBL). Stability analysis shows that Convective Available Potential Energy (CAPE) is comparable in magnitude for both increased and decreased moisture scenarios, whereas Convective Inhibition (CIN) shows increased values for the reduced moisture scenario as a consequence of drier atmosphere leading to suppression of convection. Simulations carried out with various fixed soil moisture levels indicate that the overall precipitation features of the storm are characterized by initial soil moisture condition, but precipitation intensity at any instant is modulated by soil moisture availability. Overall results based on this case study suggest that antecedent soil moisture plays a crucial role in modulating precipitation distribution and intensity of a monsoon depression.

Real Time Land-Surface Hydrologic Modeling Over Continental US

NASA Technical Reports Server (NTRS)

Houser, Paul R.

1998-01-01

The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.

Surface reflectance retrieval from satellite and aircraft sensors: Results of sensor and algorithm comparisons during FIFE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Markham, B.L.; Halthore, R.N.; Goetz, S.J.

1992-11-30

This work is part of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), an international land-surface-atmosphere experiment aimed at improving the way climate models represent energy, water, heat, and carbon exchanges, and improving the utilization of satellite based remote sensing to monitor such parameters. This paper reports on comparison of measurement systems which were deployed to measure surface reflectance factors, from aircraft or satellites. These instruments look over the general range of 0.4 to 2.5[mu]m. Instruments studied include Landsat 5 thematic mapper (TM), the SPOT 1 high-resolution visible sensor (HRV) 1, the NS001 thematic mapper simulator,more » and the modular multispectral radiometers (MMRs). The study looked at the radiometric consistency of the different instruments, and the adequacy of the atmospheric correction routines applied to data analysis.« less

Generation of High Resolution Land Surface Parameters in the Community Land Model

NASA Astrophysics Data System (ADS)

Ke, Y.; Coleman, A. M.; Wigmosta, M. S.; Leung, L.; Huang, M.; Li, H.

2010-12-01

The Community Land Model (CLM) is the land surface model used for the Community Atmosphere Model (CAM) and the Community Climate System Model (CCSM). It examines the physical, chemical, and biological processes across a variety of spatial and temporal scales. Currently, efforts are being made to improve the spatial resolution of the CLM, in part, to represent finer scale hydrologic characteristics. Current land surface parameters of CLM4.0, in particular plant functional types (PFT) and leaf area index (LAI), are generated from MODIS and calculated at a 0.05 degree resolution. These MODIS-derived land surface parameters have also been aggregated to coarser resolutions (e.g., 0.5, 1.0 degrees). To evaluate the response of CLM across various spatial scales, higher spatial resolution land surface parameters need to be generated. In this study we examine the use of Landsat TM/ETM+ imagery and data fusion techniques for generating land surface parameters at a 1km resolution within the Pacific Northwest United States. . Land cover types and PFTs are classified based on Landsat multi-season spectral information, DEM, National Land Cover Database (NLCD) and the USDA-NASS Crop Data Layer (CDL). For each PFT, relationships between MOD15A2 high quality LAI values, Landsat-based vegetation indices, climate variables, terrain, and laser-altimeter derived vegetation height are used to generate monthly LAI values at a 30m resolution. The high-resolution PFT and LAI data are aggregated to create a 1km model grid resolution. An evaluation and comparison of CLM land surface response at both fine and moderate scale is presented.

Supplementing land-use statistics with landscape metrics: some methodological considerations.

PubMed

Herzog, F; Lausch, A

2001-11-01

Landscape monitoring usually relies on land-use statistics which reflect the share of land-sue/land cover types. In order to understand the functioning of landscapes, landscape pattern must be considered as well. Indicators which address the spatial configuration of landscapes are therefore needed. The suitability of landscape metrics, which are computed from the type, geometry and arrangement of patches, is examined. Two case studies in a surface mining region show that landscape metrics capture landscape structure but are highly dependent on the data model and on the methods of data analysis. For landscape metrics to become part of policy-relevant sets of environmental indicators, standardised procedures for their computation from remote sensing images must be developed.

Assessment of Mars Exploration Rover Landing Site Predictions

NASA Astrophysics Data System (ADS)

Golombek, M. P.

2005-05-01

Comprehensive analyses of remote sensing data during the 3-year effort to select the Mars Exploration Rover landing sites at Gusev crater and Meridiani Planum correctly predicted the safe and trafficable surfaces explored by the two rovers. Gusev crater was predicted to be a relatively low relief surface that was comparably dusty, but less rocky than the Viking landing sites. Available data for Meridiani Planum indicated a very flat plain composed of basaltic sand to granules and hematite that would look completely unlike any of the existing landing sites with a dark, low albedo surface, little dust and very few rocks. Orbital thermal inertia measurements of 315 J m-2 s-0.5 K-1 at Gusev suggested surfaces dominated by duricrust to cemented soil-like materials or cohesionless sand or granules, which is consistent with observed soil characteristics and measured thermal inertias from the surface. THEMIS thermal inertias along the traverse at Gusev vary from 285 at the landing site to 330 around Bonneville rim and show systematic variations that can be related to the observed increase in rock abundance (5-30%). Meridiani has an orbital bulk inertia of ~200, similar to measured surface inertias that correspond to observed surfaces dominated by 0.2 mm sand size particles. Rock abundance derived from orbital thermal differencing techniques suggested that Meridiani Planum would have very low rock abundance, consistent with the rock free plain traversed by Opportunity. Spirit landed in an 8% orbital rock abundance pixel, consistent with the measured 7% of the surface covered by rocks >0.04 m diameter at the landing site, which is representative of the plains away from craters. The orbital albedo of the Spirit traverse varies from 0.19 to 0.30, consistent with surface measurements in and out of dust devil tracks. Opportunity is the first landing in a low albedo portion of Mars as seen from orbit, which is consistent with the dark, dust-free surface and measured albedos. The close correspondence between surface characteristics inferred from orbital remote sensing data and that found at the landing sites argues that future efforts to select safe landing sites will be successful. Linking the five landing sites to their remote sensing signatures suggests that they span most of the important, likely safe surfaces available for landing on Mars.

Sensitivity Analysis of the Land Surface Model NOAH-MP for Different Model Fluxes

NASA Astrophysics Data System (ADS)

Mai, Juliane; Thober, Stephan; Samaniego, Luis; Branch, Oliver; Wulfmeyer, Volker; Clark, Martyn; Attinger, Sabine; Kumar, Rohini; Cuntz, Matthias

2015-04-01

Land Surface Models (LSMs) use a plenitude of process descriptions to represent the carbon, energy and water cycles. They are highly complex and computationally expensive. Practitioners, however, are often only interested in specific outputs of the model such as latent heat or surface runoff. In model applications like parameter estimation, the most important parameters are then chosen by experience or expert knowledge. Hydrologists interested in surface runoff therefore chose mostly soil parameters while biogeochemists interested in carbon fluxes focus on vegetation parameters. However, this might lead to the omission of parameters that are important, for example, through strong interactions with the parameters chosen. It also happens during model development that some process descriptions contain fixed values, which are supposedly unimportant parameters. However, these hidden parameters remain normally undetected although they might be highly relevant during model calibration. Sensitivity analyses are used to identify informative model parameters for a specific model output. Standard methods for sensitivity analysis such as Sobol indexes require large amounts of model evaluations, specifically in case of many model parameters. We hence propose to first use a recently developed inexpensive sequential screening method based on Elementary Effects that has proven to identify the relevant informative parameters. This reduces the number parameters and therefore model evaluations for subsequent analyses such as sensitivity analysis or model calibration. In this study, we quantify parametric sensitivities of the land surface model NOAH-MP that is a state-of-the-art LSM and used at regional scale as the land surface scheme of the atmospheric Weather Research and Forecasting Model (WRF). NOAH-MP contains multiple process parameterizations yielding a considerable amount of parameters (˜ 100). Sensitivities for the three model outputs (a) surface runoff, (b) soil drainage and (c) latent heat are calculated on twelve Model Parameter Estimation Experiment (MOPEX) catchments ranging in size from 1020 to 4421 km2. This allows investigation of parametric sensitivities for distinct hydro-climatic characteristics, emphasizing different land-surface processes. The sequential screening identifies the most informative parameters of NOAH-MP for different model output variables. The number of parameters is reduced substantially for all of the three model outputs to approximately 25. The subsequent Sobol method quantifies the sensitivities of these informative parameters. The study demonstrates the existence of sensitive, important parameters in almost all parts of the model irrespective of the considered output. Soil parameters, e.g., are informative for all three output variables whereas plant parameters are not only informative for latent heat but also for soil drainage because soil drainage is strongly coupled to transpiration through the soil water balance. These results contrast to the choice of only soil parameters in hydrological studies and only plant parameters in biogeochemical ones. The sequential screening identified several important hidden parameters that carry large sensitivities and have hence to be included during model calibration.

[A review on research of land surface water and heat fluxes].

PubMed

Sun, Rui; Liu, Changming

2003-03-01

Many field experiments were done, and soil-vegetation-atmosphere transfer(SVAT) models were stablished to estimate land surface heat fluxes. In this paper, the processes of experimental research on land surface water and heat fluxes are reviewed, and three kinds of SVAT model(single layer model, two layer model and multi-layer model) are analyzed. Remote sensing data are widely used to estimate land surface heat fluxes. Based on remote sensing and energy balance equation, different models such as simplified model, single layer model, extra resistance model, crop water stress index model and two source resistance model are developed to estimate land surface heat fluxes and evapotranspiration. These models are also analyzed in this paper.

Impacts of urban and industrial development on Arctic land surface temperature in Lower Yenisei River Region.

NASA Astrophysics Data System (ADS)

Li, Z.; Shiklomanov, N. I.

2015-12-01

Urbanization and industrial development have significant impacts on arctic climate that in turn controls settlement patterns and socio-economic processes. In this study we have analyzed the anthropogenic influences on regional land surface temperature of Lower Yenisei River Region of the Russia Arctic. The study area covers two consecutive Landsat scenes and includes three major cities: Norilsk, Igarka and Dudingka. Norilsk industrial region is the largest producer of nickel and palladium in the world, and Igarka and Dudingka are important ports for shipping. We constructed a spatio-temporal interpolated temperature model by including 1km MODIS LST, field-measured climate, Modern Era Retrospective-analysis for Research and Applications (MERRA), DEM, Landsat NDVI and Landsat Land Cover. Those fore-mentioned spatial data have various resolution and coverage in both time and space. We analyzed their relationships and created a monthly spatio-temporal interpolated surface temperature model at 1km resolution from 1980 to 2010. The temperature model then was used to examine the characteristic seasonal LST signatures, related to several representative assemblages of Arctic urban and industrial infrastructure in order to quantify anthropogenic influence on regional surface temperature.

Does surface roughness dominate biophysical forcing of land use and land cover change in the eastern United States?

NASA Astrophysics Data System (ADS)

Burakowski, E. A.; Tawfik, A. B.; Ouimette, A.; Lepine, L. C.; Ollinger, S. V.; Bonan, G. B.; Zarzycki, C. M.; Novick, K. A.

2016-12-01

Changes in land use, land cover, or both promote changes in surface temperature that can amplify or dampen long-term trends driven by natural and anthropogenic climate change by modifying the surface energy budget, primarily through differences in albedo, evapotranspiration, and aerodynamic roughness. Recent advances in variable resolution global models provide the tools necessary to investigate local and global impacts of land use and land cover change by embedding a high-resolution grid over areas of interest in a seamless and computationally efficient manner. Here, we used two eddy covariance tower clusters in the Eastern US (University of New Hampshire UNH and Duke Forest) to validate simulation of surface energy fluxes and properties by the uncoupled Community Land Model (PTCLM4.5) and coupled land-atmosphere Variable-Resolution Community Earth System Model (VR-CESM1.3). Surface energy fluxes and properties are generally well captured by the models for grassland sites, however forested sites tend to underestimate latent heat and overestimate sensible heat flux. Surface roughness emerged as the dominant biophysical forcing factor affecting surface temperature in the eastern United States, generally leading to warmer nighttime temperatures and cooler daytime temperatures. However, the sign and magnitude of the roughness effect on surface temperature was highly sensitive to the calculation of aerodynamic resistance to heat transfer.

Estimation of Key Parameters of the Coupled Energy and Water Model by Assimilating Land Surface Data

NASA Astrophysics Data System (ADS)

Abdolghafoorian, A.; Farhadi, L.

2017-12-01

Accurate estimation of land surface heat and moisture fluxes, as well as root zone soil moisture, is crucial in various hydrological, meteorological, and agricultural applications. Field measurements of these fluxes are costly and cannot be readily scaled to large areas relevant to weather and climate studies. Therefore, there is a need for techniques to make quantitative estimates of heat and moisture fluxes using land surface state observations that are widely available from remote sensing across a range of scale. In this work, we applies the variational data assimilation approach to estimate land surface fluxes and soil moisture profile from the implicit information contained Land Surface Temperature (LST) and Soil Moisture (SM) (hereafter the VDA model). The VDA model is focused on the estimation of three key parameters: 1- neutral bulk heat transfer coefficient (CHN), 2- evaporative fraction from soil and canopy (EF), and 3- saturated hydraulic conductivity (Ksat). CHN and EF regulate the partitioning of available energy between sensible and latent heat fluxes. Ksat is one of the main parameters used in determining infiltration, runoff, groundwater recharge, and in simulating hydrological processes. In this study, a system of coupled parsimonious energy and water model will constrain the estimation of three unknown parameters in the VDA model. The profile of SM (LST) at multiple depths is estimated using moisture diffusion (heat diffusion) equation. In this study, the uncertainties of retrieved unknown parameters and fluxes are estimated from the inverse of Hesian matrix of cost function which is computed using the Lagrangian methodology. Analysis of uncertainty provides valuable information about the accuracy of estimated parameters and their correlation and guide the formulation of a well-posed estimation problem. The results of proposed algorithm are validated with a series of experiments using a synthetic data set generated by the simultaneous heat and water (SHAW) model. In addition, the feasibility of extending this algorithm to use remote sensing observations that have low temporal resolution is examined by assimilating the limited number of land surface moisture and temperature observations.

What We Learned From the Venus Surface in-situ Exploration And What Looks Promising to do Next

NASA Astrophysics Data System (ADS)

Basilevsky, A. T.; Head, J. W.

2005-12-01

The in-situ study of Venus surface started on Dec 15, 1970 with the landing of the Soviet Venera 7 probe, which sent back to Earth data on the surface temperature and atmosphere pressure. Then, since 1972 till 1985 there were successful landings of the Soviet Venera 9 to 14 and Vega 1-2 probes. The Day probe, part of the US Pioneer Venus Multiprobe (1978), also sent the data from the Venus surface. Gained by these missions we have the results of gamma-spectrometry measurements of K, U, and Th contents in the surface material in five sites and the X-ray fluorescence measurements of major elements contents in three sites as well as TV panoramas of four landing sites. In addition, in some of these sites there have been measured the surface material density, bearing capacity and electro conductivity as well as albedo and color. The results of the geochemical measurements, all characterizing Venusian plains, are consistent with basaltic composition of the surface material in all seven sampled sites. Recent comparisons of the Venusian compositions with those of the extended database of terrestrial magmatic rocks from different geodynamic environments within the oceanic crust showed that except one (Venera 14) all other measurements suggest enrichment in LIL elements and differ from N-MORB compositions. The surface in the imaged landing sites was found to consist of very dark finely layered and mechanically weak rock and even darker soil. Recent joint analysis of the Veneras' and Magellan data showed that the layered rock most likely is thermally sintered airborn sediment of fine debris derived from ejecta of impact craters. This sediment, although of small thickness, seems to be widespread on the Venus surface that should be taken into account in planning new missions. The future landings have to provide more compositional knowledge on Venus surface by significantly improving the analyses accuracies and detection limits and extending sampled geologic formations beyond the already sampled plains. Determination of mineralogic composition of the surface material as well as the redox-controlling components of the atmosphere are of a key value. Seismic and other geophysical sounding of Venus interior should be also planned. Sample return mission(s) as distant but necessary step in Venus studies should be considered too.

Using land-cover change as dynamic variables in surface-water and water-quality models

USGS Publications Warehouse

Karstensen, Krista A.; Warner, Kelly L.; Kuhn, Anne

2010-01-01

Land-cover data are typically used in hydrologic modeling to establish or describe land surface dynamics. This project is designed to demonstrate the use of land-cover change data in surface-water and water-quality models by incorporating land-cover as a variable condition. The project incorporates three different scenarios that vary hydrologically and geographically: 1) Agriculture in the Plains, 2) Loon habitat in New England, and 3) Forestry in the Ozarks.

DasPy – Open Source Multivariate Land Data Assimilation Framework with High Performance Computing

NASA Astrophysics Data System (ADS)

Han, Xujun; Li, Xin; Montzka, Carsten; Kollet, Stefan; Vereecken, Harry; Hendricks Franssen, Harrie-Jan

2015-04-01

Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. Multivariate data assimilation refers to the simultaneous assimilation of observation data for multiple model state variables into a simulation model. Our main motivation was to develop an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with C++ and Fortran language. This system has been evaluated in several soil moisture, L-band brightness temperature and land surface temperature assimilation studies. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be represented by perturbed atmospheric forcings, perturbed soil and vegetation properties and model initial conditions. The CLM4.5 (Community Land Model) was integrated as the model operator. The CMEM (Community Microwave Emission Modelling Platform), COSMIC (COsmic-ray Soil Moisture Interaction Code) and the two source formulation were integrated as observation operators for assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy is parallelized using the hybrid MPI (Message Passing Interface) and OpenMP (Open Multi-Processing) techniques. All the input and output data flow is organized efficiently using the commonly used NetCDF file format. Online 1D and 2D visualization of data assimilation results is also implemented to facilitate the post simulation analysis. In summary, DasPy is a ready to use open source parallel multivariate land data assimilation framework.

Effects of land use and land cover on selected soil quality indicators in the headwater area of the Blue Nile basin of Ethiopia.

PubMed

Teferi, Ermias; Bewket, Woldeamlak; Simane, Belay

2016-02-01

Understanding changes in soil quality resulting from land use and land management changes is important to design sustainable land management plans or interventions. This study evaluated the influence of land use and land cover (LULC) on key soil quality indicators (SQIs) within a small watershed (Jedeb) in the Blue Nile Basin of Ethiopia. Factor analysis based on principal component analysis (PCA) was used to determine different SQIs. Surface (0-15 cm) soil samples with four replications were collected from five main LULC types in the watershed (i.e., natural woody vegetation, plantation forest, grassland, cultivated land, and barren land) and at two elevation classes (upland and midland), and 13 soil properties were measured for each replicate. A factorial (2 × 5) multivariate analysis of variance (MANOVA) showed that LULC and altitude together significantly affected organic matter (OM) levels. However, LULC alone significantly affected bulk density and altitude alone significantly affected bulk density, soil acidity, and silt content. Afforestation of barren land with eucalypt trees can significantly increase the soil OM in the midland part but not in the upland part. Soils under grassland had a significantly higher bulk density than did soils under natural woody vegetation indicating that de-vegetation and conversion to grassland could lead to soil compaction. Thus, the historical LULC change in the Jedeb watershed has resulted in the loss of soil OM and increased soil compaction. The study shows that a land use and management system can be monitored if it degrades or maintains or improves the soil using key soil quality indicators.

Online Time Series Analysis of Land Products over Asia Monsoon Region via Giovanni

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina

2011-01-01

Time series analysis is critical to the study of land cover/land use changes and climate. Time series studies at local-to-regional scales require higher spatial resolution, such as 1km or less, data. MODIS land products of 250m to 1km resolution enable such studies. However, such MODIS land data files are distributed in 10ox10o tiles, due to large data volumes. Conducting a time series study requires downloading all tiles that include the study area for the time period of interest, and mosaicking the tiles spatially. This can be an extremely time-consuming process. In support of the Monsoon Asia Integrated Regional Study (MAIRS) program, NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) has processed MODIS land products at 1 km resolution over the Asia monsoon region (0o-60oN, 60o-150oE) with a common data structure and format. The processed data have been integrated into the Giovanni system (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) that enables users to explore, analyze, and download data over an area and time period of interest easily. Currently, the following regional MODIS land products are available in Giovanni: 8-day 1km land surface temperature and active fire, monthly 1km vegetation index, and yearly 0.05o, 500m land cover types. More data will be added in the near future. By combining atmospheric and oceanic data products in the Giovanni system, it is possible to do further analyses of environmental and climate changes associated with the land, ocean, and atmosphere. This presentation demonstrates exploring land products in the Giovanni system with sample case scenarios.

A NEW LAND-SURFACE MODEL IN MM5

EPA Science Inventory

There has recently been a general realization that more sophisticated modeling of land-surface processes can be important for mesoscale meteorology models. Land-surface models (LSMs) have long been important components in global-scale climate models because of their more compl...

30 CFR 740.10 - Information collection.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR FEDERAL LANDS PROGRAM GENERAL REQUIREMENTS FOR SURFACE COAL MINING AND RECLAMATION OPERATIONS ON FEDERAL LANDS... surface coal mining operations on Federal lands. Persons intending to conduct such operations must respond...

30 CFR 740.10 - Information collection.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR FEDERAL LANDS PROGRAM GENERAL REQUIREMENTS FOR SURFACE COAL MINING AND RECLAMATION OPERATIONS ON FEDERAL LANDS... surface coal mining operations on Federal lands. Persons intending to conduct such operations must respond...

Photometric Properties of Soils at the Mars Phoenix Landing Site: Preliminary Analysis from CRISM EPF Data

NASA Astrophysics Data System (ADS)

Cull, S. C.; Arvidson, R. E.; Seelos, F.; Wolff, M. J.

2010-03-01

Using data from CRISM's Emission Phase Function observations, we attempt to constrain Phoenix soil scattering properties, including soil grain size, single-scattering albedo, and surface phase function.

Human Land-Use Practices Lead to Global Long-Term Increases in Photosynthetic Capacity

NASA Technical Reports Server (NTRS)

Mueller, Thomas; Tucker, Compton J.; Dressler, Gunnar; Pinzon, Jorge E.; Leimgruber, Peter; Dubayah, Ralph O.; Hurtt, George C.; Boehning-Gaese, Katrin; Fagan, William F.

2014-01-01

Long-term trends in photosynthetic capacity measured with the satellite-derived Normalized Difference Vegetation Index (NDVI) are usually associated with climate change. Human impacts on the global land surface are typically not accounted for. Here, we provide the first global analysis quantifying the effect of the earth's human footprint on NDVI trends. Globally, more than 20% of the variability in NDVI trends was explained by anthropogenic factors such as land use, nitrogen fertilization, and irrigation. Intensely used land classes, such as villages, showed the greatest rates of increase in NDVI, more than twice than those of forests. These findings reveal that factors beyond climate influence global long-term trends in NDVI and suggest that global climate change models and analyses of primary productivity should incorporate land use effects.

Capability of Integrated MODIS Imagery and ALOS for Oil Palm, Rubber and Forest Areas Mapping in Tropical Forest Regions

PubMed Central

Razali, Sheriza Mohd; Marin, Arnaldo; Nuruddin, Ahmad Ainuddin; Shafri, Helmi Zulhaidi Mohd; Hamid, Hazandy Abdul

2014-01-01

Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions. PMID:24811079

Capability of integrated MODIS imagery and ALOS for oil palm, rubber and forest areas mapping in tropical forest regions.

PubMed

Razali, Sheriza Mohd; Marin, Arnaldo; Nuruddin, Ahmad Ainuddin; Shafri, Helmi Zulhaidi Mohd; Hamid, Hazandy Abdul

2014-05-07

Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions.

High-resolution surface analysis for extended-range downscaling with limited-area atmospheric models

NASA Astrophysics Data System (ADS)

Separovic, Leo; Husain, Syed Zahid; Yu, Wei; Fernig, David

2014-12-01

High-resolution limited-area model (LAM) simulations are frequently employed to downscale coarse-resolution objective analyses over a specified area of the globe using high-resolution computational grids. When LAMs are integrated over extended time frames, from months to years, they are prone to deviations in land surface variables that can be harmful to the quality of the simulated near-surface fields. Nudging of the prognostic surface fields toward a reference-gridded data set is therefore devised in order to prevent the atmospheric model from diverging from the expected values. This paper presents a method to generate high-resolution analyses of land-surface variables, such as surface canopy temperature, soil moisture, and snow conditions, to be used for the relaxation of lower boundary conditions in extended-range LAM simulations. The proposed method is based on performing offline simulations with an external surface model, forced with the near-surface meteorological fields derived from short-range forecast, operational analyses, and observed temperatures and humidity. Results show that the outputs of the surface model obtained in the present study have potential to improve the near-surface atmospheric fields in extended-range LAM integrations.

Summer U.S. Surface Air Temperature Variability: Controlling Factors and AMIP Simulation Biases

NASA Astrophysics Data System (ADS)

Merrifield, A.; Xie, S. P.

2016-02-01

This study documents and investigates biases in simulating summer surface air temperature (SAT) variability over the continental U.S. in the Coupled Model Intercomparison Project (CMIP5) Atmospheric Model Intercomparison Project (AMIP). Empirical orthogonal function (EOF) and multivariate regression analyses are used to assess the relative importance of circulation and the land surface feedback at setting summer SAT over a 30-year period (1979-2008). In observations, regions of high SAT variability are closely associated with midtropospheric highs and subsidence, consistent with adiabatic theory (Meehl and Tebaldi 2004, Lau and Nath 2012). Preliminary analysis shows the majority of the AMIP models feature high SAT variability over the central U.S., displaced south and/or west of observed centers of action (COAs). SAT COAs in models tend to be concomitant with regions of high sensible heat flux variability, suggesting an excessive land surface feedback in these models modulate U.S. summer SAT. Additionally, tropical sea surface temperatures (SSTs) play a role in forcing the leading EOF mode for summer SAT, in concert with internal atmospheric variability. There is evidence that models respond to different SST patterns than observed. Addressing issues with the bulk land surface feedback and the SST-forced component of atmospheric variability may be key to improving model skill in simulating summer SAT variability over the U.S.

SAR-aided method for rural soil evaluation

NASA Astrophysics Data System (ADS)

Lay-Ekuakille, Aime; Dellisanti, Carmelo; Pelillo, Vincenza; Tralli, Francesco

2003-03-01

The principal land characteristics that can be estimated by means of airphoto interpretation are bedrock type, landform, soil texture, site drainage conditions, susceptibility to flooding, and depth of unconsolidated materials over bedrock. In addition, the slope of the land surface can be estimated by airphoto interpretation and measured by phptpgrammetric methods. The aim of this paper is to show an experimental use of satellite images in determining soil quality affected by anthropic activities as rock crushing, or scarifying. Scarifying activities began, in Murgia area, Apulia Region, Italy), as land improvement for agriculture uses. Scarifying is defined as loosening (the surface of soil) by using an agricultural tool or a machine with prongs. This kind of activity is facilitated by the availability, on the market, of scarifying machines and the objective is to get a stratum of agriculture-useful loose material on the soil surface. Apulia Region Government has permitted calcareous stone scarifying with Regional Law n.54 (August 31, 1981) according to National Law n.984 (Dicember 27,1977), that provides for encouraging to transform grazing in sown land in order to create new possibility of forage production to increase zootecnical facilities. We have used ERS-2/SAR images as contribution in the process of soil characterization.The area we have considered is in Puglia Region and is subject to soil transformation due to rocks crushed on land for agricultural facilities. European Union, through the same Apulia Region Government, has renewed funds for the improvement of meadow and grazing for an overall surface of 2000 hectares. In this way it is clear to understand the importance of qualitative and quantitative evaluation of rock crushing or scarifying by using airphoto interpretation. We have evaluated the soil quality by introducing a multicriteria, analysis by using a qualitative and quantitative methodology, so that it will be possible to prevent damages on soil, sub-soil and hydrology. Decision analysis in Impact assessment is a set of procedures for analyzing complex decision problems. The strategy is to divide the decision problem into small, understandable parts; analyze each part; and integrate the parts in a logical manner to produce a meaningful solution. The terms multicriteria decision making (MCDM) and multicriteria decision analysis (MCDA) are used interchangeably.

Simulation of the Onset of the Southeast Asian Monsoon During 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lau, W.; Baker, R.

2004-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated with a coupled mesoscale atmospheric model (MM5) and a detailed land surface model. The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The simulation with the land surface model captured basic signatures of the monsoon onset processes and associated rainfall statistics. The sensitivity tests indicated that land surface processes had a greater impact on the simulated rainfall results than that of a small sea surface temperature change during the onset period. In both the 1997 and 1998 cases, the simulations were significantly improved by including the land surface processes. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation; the southwest low-level flow over the Indo-China peninsula and the northern cold front intrusion from southern China. The surface sensible and latent heat exchange between the land and atmosphere modified the low-level temperature distribution and gradient, and therefore the low-level. The more realistic forcing of the sensible and latent heat from the detailed land surface model improved the monsoon rainfall and associated wind simulation. The model results will be compared to the simulation of the 6-7 May 2000 Missouri flash flood event. In addition, the impact of model initialization and land surface treatment on timing, intensity, and location of extreme precipitation will be examined.

Simulation of the Onset of the Southeast Asian Monsoon during 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Wang, Y.; Lau, W.; Baker, R. D.

2004-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated with a coupled mesoscale atmospheric model (MM5) and a detailed land surface model. The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The simulation with the land surface model captured basic signatures of the monsoon onset processes and associated rainfall statistics. The sensitivity tests indicated that land surface processes had a greater impact on the simulated rainfall results than that of a small sea surface temperature change during the onset period. In both the 1997 and 1998 cases, the simulations were significantly improved by including the land surface processes. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation; the southwest low-level flow over the Indo-China peninsula and the northern cold front intrusion from southern China. The surface sensible and latent heat exchange between the land and atmosphere modified the low-level temperature distribution and gradient, and therefore the low-level. The more realistic forcing of the sensible and latent heat from the detailed land surface model improved the monsoon rainfall and associated wind simulation. The model results will be compared to the simulation of the 6-7 May 2000 Missouri flash flood event. In addition, the impact of model initialization and land surface treatment on timing, intensity, and location of extreme precipitation will be examined.

The role of land surface fluxes in Saudi-KAU AGCM: Temperature climatology over the Arabian Peninsula for the period 1981-2010

NASA Astrophysics Data System (ADS)

Ashfaqur Rahman, M.; Almazroui, Mansour; Nazrul Islam, M.; O'Brien, Enda; Yousef, Ahmed Elsayed

2018-02-01

A new version of the Community Land Model (CLM) was introduced to the Saudi King Abdulaziz University Atmospheric Global Climate Model (Saudi-KAU AGCM) for better land surface component representation, and so to enhance climate simulation. CLM replaced the original land surface model (LSM) in Saudi-KAU AGCM, with the aim of simulating more accurate land surface fluxes globally, but especially over the Arabian Peninsula. To evaluate the performance of Saudi-KAU AGCM, simulations were completed with CLM and LSM for the period 1981-2010. In comparison with LSM, CLM generates surface air temperature values that are closer to National Centre for Environmental Prediction (NCEP) observations. The global annual averages of land surface air temperature are 9.51, 9.52, and 9.57 °C for NCEP, CLM, and LSM respectively, although the same atmospheric radiative and surface forcing from Saudi-KAU AGCM are provided to both LSM and CLM at every time step. The better temperature simulations when using CLM can be attributed to the more comprehensive plant functional type and hierarchical tile approach to the land cover type in CLM, along with better parameterization of upward land surface fluxes compared to LSM. At global scale, CLM exhibits smaller annual and seasonal mean biases of temperature with respect to NCEP data. Moreover, at regional scale, CLM demonstrates reasonable seasonal and annual mean temperature over the Arabian Peninsula as compared to the Climatic Research Unit (CRU) data. Finally, CLM generated better matches to single point-wise observations of surface air temperature and surface fluxes for some case studies.

Integration of land use and land cover inventories for landscape management and planning in Italy.

PubMed

Sallustio, Lorenzo; Munafò, Michele; Riitano, Nicola; Lasserre, Bruno; Fattorini, Lorenzo; Marchetti, Marco

2016-01-01

There are both semantic and technical differences between land use (LU) and land cover (LC) measurements. In cartographic approaches, these differences are often neglected, giving rise to a hybrid classification. The aim of this paper is to provide a better understanding and characterization of the two classification schemes using a comparison that allows maximization of the informative power of both. The analysis was carried out in the Molise region (Central Italy) using sample information from the Italian Land Use Inventory (IUTI). The sampling points were classified with a visual interpretation of aerial photographs for both LU and LC in order to estimate surfaces and assess the changes that occurred between 2000 and 2012. The results underscore the polarization of land use and land cover changes resulting from the following: (a) recolonization of natural surfaces, (b) strong dynamisms between the LC classes in the natural and semi-natural domain and (c) urban sprawl on the lower hills and plains. Most of the observed transitions are attributable to decreases in croplands, natural grasslands and pastures, owing to agricultural abandonment. The results demonstrate that a comparison between LU and LC estimates and their changes provides an understanding of the causes of misalignment between the two criteria. Such information may be useful for planning policies in both natural and semi-natural contexts as well as in urban areas.

Understanding Mesoscale Land-Atmosphere Interactions in Arctic Region

NASA Astrophysics Data System (ADS)

Hong, X.; Wang, S.; Nachamkin, J. E.

2017-12-01

Land-atmosphere interactions in Arctic region are examined using the U.S. Navy Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS©*) with the Noah Land Surface Model (LSM). Initial land surface variables in COAMPS are interpolated from the real-time NASA Land Information System (LIS). The model simulations are configured for three nest grids with 27-9-3 km horizontal resolutions. The simulation period is set for October 2015 with 12-h data assimilation update cycle and 24-h integration length. The results are compared with those simulated without using LSM and evaluated with observations from ONR Sea State R/V Sikuliaq cruise and the North Slope of Alaska (NSA). There are complex soil and vegetation types over the surface for simulation with LSM, compared to without LSM simulation. The results show substantial differences in surface heat fluxes between bulk surface scheme and LSM, which may have an important impact on the sea ice evolution over the Arctic region. Evaluations from station data show surface air temperature and relative humidity have smaller biases for simulation using LSM. Diurnal variation of land surface temperature, which is necessary for physical processes of land-atmosphere, is also better captured than without LSM.

Accuracy assessment of land surface temperature retrievals from Landsat 7 ETM + in the Dry Valleys of Antarctica using iButton temperature loggers and weather station data.

PubMed

Brabyn, Lars; Zawar-Reza, Peyman; Stichbury, Glen; Cary, Craig; Storey, Bryan; Laughlin, Daniel C; Katurji, Marwan

2014-04-01

The McMurdo Dry Valleys of Antarctica are the largest snow/ice-free regions on this vast continent, comprising 1% of the land mass. Due to harsh environmental conditions, the valleys are bereft of any vegetation. Land surface temperature is a key determinate of microclimate and a driver for sensible and latent heat fluxes of the surface. The Dry Valleys have been the focus of ecological studies as they arguably provide the simplest trophic structure suitable for modelling. In this paper, we employ a validation method for land surface temperatures obtained from Landsat 7 ETM + imagery and compared with in situ land surface temperature data collected from four transects totalling 45 iButtons. A single meteorological station was used to obtain a better understanding of daily and seasonal cycles in land surface temperatures. Results show a good agreement between the iButton and the Landsat 7 ETM + product for clear sky cases. We conclude that Landsat 7 ETM + derived land surface temperatures can be used at broad spatial scales for ecological and meteorological research.

Comprehensive data set of global land cover change for land surface model applications

NASA Astrophysics Data System (ADS)

Sterling, Shannon; Ducharne, AgnèS.

2008-09-01

To increase our understanding of how humans have altered the Earth's surface and to facilitate land surface modeling experiments aimed to elucidate the direct impact of land cover change on the Earth system, we create and analyze a database of global land use/cover change (LUCC). From a combination of sources including satellite imagery and other remote sensing, ecological modeling, and country surveys, we adapt and synthesize existing maps of potential land cover and layers of the major anthropogenic land covers, including a layer of wetland loss, that are then tailored for land surface modeling studies. Our map database shows that anthropogenic land cover totals to approximately 40% of the Earth's surface, consistent with literature estimates. Almost all (92%) of the natural grassland on the Earth has been converted to human use, mostly grazing land, and the natural temperate savanna with mixed C3/C4 is almost completely lost (˜90%), due mostly to conversion to cropland. Yet the resultant change in functioning, in terms of plant functional types, of the Earth system from land cover change is dominated by a loss of tree cover. Finally, we identify need for standardization of percent bare soil for global land covers and for a global map of tree plantations. Estimates of land cover change are inherently uncertain, and these uncertainties propagate into modeling studies of the impact of land cover change on the Earth system; to begin to address this problem, modelers need to document fully areas of land cover change used in their studies.

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

2011-01-01

Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

Evaluation of reanalysis datasets against observational soil temperature data over China

NASA Astrophysics Data System (ADS)

Yang, Kai; Zhang, Jingyong

2018-01-01

Soil temperature is a key land surface variable, and is a potential predictor for seasonal climate anomalies and extremes. Using observational soil temperature data in China for 1981-2005, we evaluate four reanalysis datasets, the land surface reanalysis of the European Centre for Medium-Range Weather Forecasts (ERA-Interim/Land), the second modern-era retrospective analysis for research and applications (MERRA-2), the National Center for Environmental Prediction Climate Forecast System Reanalysis (NCEP-CFSR), and version 2 of the Global Land Data Assimilation System (GLDAS-2.0), with a focus on 40 cm soil layer. The results show that reanalysis data can mainly reproduce the spatial distributions of soil temperature in summer and winter, especially over the east of China, but generally underestimate their magnitudes. Owing to the influence of precipitation on soil temperature, the four datasets perform better in winter than in summer. The ERA-Interim/Land and GLDAS-2.0 produce spatial characteristics of the climatological mean that are similar to observations. The interannual variability of soil temperature is well reproduced by the ERA-Interim/Land dataset in summer and by the CFSR dataset in winter. The linear trend of soil temperature in summer is well rebuilt by reanalysis datasets. We demonstrate that soil heat fluxes in April-June and in winter are highly correlated with the soil temperature in summer and winter, respectively. Different estimations of surface energy balance components can contribute to different behaviors in reanalysis products in terms of estimating soil temperature. In addition, reanalysis datasets can mainly rebuild the northwest-southeast gradient of soil temperature memory over China.

Effects of explicit convection on global land-atmosphere coupling in the superparameterized CAM

NASA Astrophysics Data System (ADS)

Sun, Jian; Pritchard, Michael S.

2016-09-01

Conventional global climate models are prone to producing unrealistic land-atmosphere coupling signals. Cumulus and convection parameterizations are natural culprits but the effect of bypassing them with explicitly resolved convection on global land-atmosphere coupling dynamics has not been explored systematically. We apply a suite of modern land-atmosphere coupling diagnostics to isolate the effect of cloud Superparameterization in the Community Atmosphere Model (SPCAM) v3.5, focusing on both the terrestrial segment (i.e., soil moisture and surface turbulent fluxes interaction) and atmospheric segment (i.e., surface turbulent fluxes and precipitation interaction) in the water pathway of the land-atmosphere feedback loop. At daily timescales, SPCAM produces stronger uncoupled terrestrial signals (negative sign) over tropical rainforests in wet seasons, reduces the terrestrial coupling strength in the Central Great Plain in American, and reverses the coupling sign (from negative to positive) over India in the boreal summer season—all favorable improvements relative to reanalysis-forced land modeling. Analysis of the triggering feedback strength (TFS) and amplification feedback strength (AFS) shows that SPCAM favorably reproduces the observed geographic patterns of these indices over North America, with the probability of afternoon precipitation enhanced by high evaporative fraction along the eastern United States and Mexico, while conventional CAM does not capture this signal. We introduce a new diagnostic called the Planetary Boundary Layer (PBL) Feedback Strength (PFS), which reveals that SPCAM exhibits a tight connection between the responses of the lifting condensation level, the PBL height, and the rainfall triggering to surface turbulent fluxes; a triggering disconnect is found in CAM.

RCRA, superfund and EPCRA hotline training module. Introduction to: Land disposal units (40 cfr parts 264/265, subparts k, l, m, n) updated July 1996

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1996-07-01

The module provides an overview of the requirements for landfills, surface impoundments, waste piles, and land treatment units. It summarizes the differences between interim status (Part 265) and permitted (Part 264) standards for land disposal units. It defines `surface impoundment` and distinguishes surface impoundments from tanks and describes surface impoundment retrofitting and retrofitting variance procedures. It explains the connection between land disposal standards, post-closure, and groundwater monitoring.

Shallow to Deep Convection Transition over a Heterogeneous Land Surface Using the Land Model Coupled Large-Eddy Simulation

NASA Astrophysics Data System (ADS)

Lee, J.; Zhang, Y.; Klein, S. A.

2017-12-01

The triggering of the land breeze, and hence the development of deep convection over heterogeneous land should be understood as a consequence of the complex processes involving various factors from land surface and atmosphere simultaneously. That is a sub-grid scale process that many large-scale models have difficulty incorporating it into the parameterization scheme partly due to lack of our understanding. Thus, it is imperative that we approach the problem using a high-resolution modeling framework. In this study, we use SAM-SLM (Lee and Khairoutdinov, 2015), a large-eddy simulation model coupled to a land model, to explore the cloud effect such as cold pool, the cloud shading and the soil moisture memory on the land breeze structure and the further development of cloud and precipitation over a heterogeneous land surface. The atmospheric large scale forcing and the initial sounding are taken from the new composite case study of the fair-weather, non-precipitating shallow cumuli at ARM SGP (Zhang et al., 2017). We model the land surface as a chess board pattern with alternating leaf area index (LAI). The patch contrast of the LAI is adjusted to encompass the weak to strong heterogeneity amplitude. The surface sensible- and latent heat fluxes are computed according to the given LAI representing the differential surface heating over a heterogeneous land surface. Separate from the surface forcing imposed from the originally modeled surface, the cases that transition into the moist convection can induce another layer of the surface heterogeneity from the 1) radiation shading by clouds, 2) adjusted soil moisture pattern by the rain, 3) spreading cold pool. First, we assess and quantifies the individual cloud effect on the land breeze and the moist convection under the weak wind to simplify the feedback processes. And then, the same set of experiments is repeated under sheared background wind with low level jet, a typical summer time wind pattern at ARM SGP site, to account for more realistic situations. Our goal is to assist answering the question: "Do the sub-grid scale land surface heterogeneity matter for the weather and climate modeling?" This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS- 736011.

Investigation of remote sensing to detect near-surface groundwater on irrigated lands

NASA Technical Reports Server (NTRS)

Ryland, D. W.; Schmer, F. A.; Moore, D. G.

1975-01-01

The application of remote sensing techniques was studied for detecting areas with high water tables in irrigated agricultural lands. Aerial data were collected by the LANDSAT-1 satellite and aircraft over the Kansas/Bostwick Irrigation District in Republic and Jewell Counties, Kansas. LANDSAT-1 data for May 12 and August 10, 1973, and aircraft flights (midday and predawn) on August 10 and 11, 1973, and June 25 and 26, 1974, were obtained. Surface and water table contour maps and active observation well hydrographs were obtained from the Bureau of Reclamation for use in the analysis. Results of the study reveal that LANDSAT-1 data (May MSS band 6 and August MSS band 7) correlate significantly (0.01 level) with water table depth for 144 active observation wells located throughout the Kansas/Bostwick Irrigation District. However, a map of water table depths of less than 1.83 meters prepared from the LANDSAT-1 data did not compare favorably with a map of seeped lands of less than 1.22 m (4 feet) to the water table. Field evaluation of the map is necessary for a complete analysis. Analysis of three fields on a within or single-field basis for the 1973 LANDSAT-1 data also showed significant correlation results.

Improving land surface emissivty parameter for land surface models using portable FTIR and remote sensing observation in Taklimakan Desert

NASA Astrophysics Data System (ADS)

Liu, Yongqiang; Mamtimin, Ali; He, Qing

2014-05-01

Because land surface emissivity (ɛ) has not been reliably measured, global climate model (GCM) land surface schemes conventionally set this parameter as simply assumption, for example, 1 as in the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) model, 0.96 for soil and wetland in the Global and Regional Assimilation and Prediction System (GRAPES) Common Land Model (CoLM). This is the so-called emissivity assumption. Accurate broadband emissivity data are needed as model inputs to better simulate the land surface climate. It is demonstrated in this paper that the assumption of the emissivity induces errors in modeling the surface energy budget over Taklimakan Desert where ɛ is far smaller than original value. One feasible solution to this problem is to apply the accurate broadband emissivity into land surface models. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has routinely measured spectral emissivities in six thermal infrared bands. The empirical regression equations have been developed in this study to convert these spectral emissivities to broadband emissivity required by land surface models. In order to calibrate the regression equations, using a portable Fourier Transform infrared (FTIR) spectrometer instrument, crossing Taklimakan Desert along with highway from north to south, to measure the accurate broadband emissivity. The observed emissivity data show broadband ɛ around 0.89-0.92. To examine the impact of improved ɛ to radiative energy redistribution, simulation studies were conducted using offline CoLM. The results illustrate that large impacts of surface ɛ occur over desert, with changes up in surface skin temperature, as well as evident changes in sensible heat fluxes. Keywords: Taklimakan Desert, surface broadband emissivity, Fourier Transform infrared spectrometer, MODIS, CoLM

The impact of climatic and non-climatic factors on land surface temperature in southwestern Romania

NASA Astrophysics Data System (ADS)

Roşca, Cristina Florina; Harpa, Gabriela Victoria; Croitoru, Adina-Eliza; Herbel, Ioana; Imbroane, Alexandru Mircea; Burada, Doina Cristina

2017-11-01

Land surface temperature is one of the most important parameters related to global warming. It depends mainly on soil type, discontinuous vegetation cover, or lack of precipitation. The main purpose of this paper is to investigate the relationship between high LST, synoptic conditions and air masses trajectories, vegetation cover, and soil type in one of the driest region in Romania. In order to calculate the land surface temperature and normalized difference vegetation index, five satellite images of LANDSAT missions 5 and 7, covering a period of 26 years (1986-2011), were selected, all of them collected in the month of June. The areas with low vegetation density were derived from normalized difference vegetation index, while soil types have been extracted from Corine Land Cover database. HYSPLIT application was employed to identify the air masses origin based on their backward trajectories for each of the five study cases. Pearson, logarithmic, and quadratic correlations were used to detect the relationships between land surface temperature and observed ground temperatures, as well as between land surface temperature and normalized difference vegetation index. The most important findings are: strong correlation between land surface temperature derived from satellite images and maximum ground temperature recorded in a weather station located in the area, as well as between areas with land surface temperature equal to or higher than 40.0 °C and those with lack of vegetation; the sandy soils are the most prone to high land surface temperature and lack of vegetation, followed by the chernozems and brown soils; extremely severe drought events may occur in the region.

The CEOS constellation for land surface imaging

USGS Publications Warehouse

Bailey, G.B.; Berger, Marsha; Jeanjean, H.; Gallo, K.P.

2007-01-01

A constellation of satellites that routinely and frequently images the Earth's land surface in consistently calibrated wavelengths from the visible through the microwave and in spatial detail that ranges from sub-meter to hundreds of meters would offer enormous potential benefits to society. A well-designed and effectively operated land surface imaging satellite constellation could have great positive impact not only on the quality of life for citizens of all nations, but also on mankind's very ability to sustain life as we know it on this planet long into the future. The primary objective of the Committee on Earth Observation Satellites (CEOS) Land Surface Imaging (LSI) Constellation is to define standards (or guidelines) that describe optimal future LSI Constellation capabilities, characteristics, and practices. Standards defined for a LSI Constellation will be based on a thorough understanding of user requirements, and they will address at least three fundamental areas of the systems comprising a Land Surface Imaging Constellation: the space segments, the ground segments, and relevant policies and plans. Studies conducted by the LSI Constellation Study Team also will address current and shorter-term problems and issues facing the land remote sensing community today, such as seeking ways to work more cooperatively in the operation of existing land surface imaging systems and helping to accomplish tangible benefits to society through application of land surface image data acquired by existing systems. 2007 LSI Constellation studies are designed to establish initial international agreements, develop preliminary standards for a mid-resolution land surface imaging constellation, and contribute data to a global forest assessment.

Accessing Recent Trend of Land Surface Temperature from Satellite Observations

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.; Romanov, Peter

2011-01-01

Land surface temperature (Ts) is an important element to measure the state of terrestrial ecosystems and to study surface energy budgets. In support of the land cover/land use change-related international program MAIRS (Monsoon Asia Integrated Regional Study), we have collected global monthly Ts measured by MODIS since the beginning of the missions. The MODIS Ts time series have approximately 11 years of data from Terra since 2000 and approximately 9 years of data from Aqua since 2002, which makes possible to study the recent climate, such as trend. In this study, monthly climatology from two platforms are calculated and compared with that from AIRS. The spatial patterns of Ts trends are accessed, focusing on the Eurasia region. Furthermore, MODIS Ts trends are compared with those from AIRS and NASA's atmospheric assimilation model, MERRA (Modern Era Retrospective-analysis for Research and Applications). The preliminary results indicate that the recent 8-year Ts trend shows an oscillation-type spatial variation over Eurasia. The pattern is consistent for data from MODIS, AIRS, and MERRA, with the positive center over Eastern Europe, and the negative center over Central Siberia. The calculated climatology and anomaly of MODIS Ts will be integrated into the online visualization system, Giovanni, at NASA GES DISC for easy use by scientists and general public.

Land Capability Potential Index (LCPI) for the Lower Missouri River Valley

USGS Publications Warehouse

Jacobson, Robert B.; Chojnacki, Kimberly A.; Reuter, Joanna M.

2007-01-01

The Land Capability Potential Index (LCPI) was developed to serve as a relatively coarse-scale index to delineate broad land capability classes in the valley of the Lower Missouri River. The index integrates fundamental factors that determine suitability of land for various uses, and may provide a useful mechanism to guide land-management decisions. The LCPI was constructed from integration of hydrology, hydraulics, land-surface elevations, and soil permeability (or saturated hydraulic conductivity) datasets for an area of the Lower Missouri River, river miles 423–670. The LCPI estimates relative wetness based on intersecting water-surface elevations, interpolated from measurements or calculated from hydraulic models, with a high-resolution land-surface elevation dataset. The potential for wet areas to retain or drain water is assessed using soil-drainage classes that are estimated from saturated hydraulic conductivity of surface soils. Terrain mapping that delineates areas with convex, concave, and flat parts of the landscape provides another means to assess tendency of landscape patches to retain surface water.

Inclusion of Solar Elevation Angle in Land Surface Albedo Parameterization Over Bare Soil Surface.

PubMed

Zheng, Zhiyuan; Wei, Zhigang; Wen, Zhiping; Dong, Wenjie; Li, Zhenchao; Wen, Xiaohang; Zhu, Xian; Ji, Dong; Chen, Chen; Yan, Dongdong

2017-12-01

Land surface albedo is a significant parameter for maintaining a balance in surface energy. It is also an important parameter of bare soil surface albedo for developing land surface process models that accurately reflect diurnal variation characteristics and the mechanism behind the solar spectral radiation albedo on bare soil surfaces and for understanding the relationships between climate factors and spectral radiation albedo. Using a data set of field observations, we conducted experiments to analyze the variation characteristics of land surface solar spectral radiation and the corresponding albedo over a typical Gobi bare soil underlying surface and to investigate the relationships between the land surface solar spectral radiation albedo, solar elevation angle, and soil moisture. Based on both solar elevation angle and soil moisture measurements simultaneously, we propose a new two-factor parameterization scheme for spectral radiation albedo over bare soil underlying surfaces. The results of numerical simulation experiments show that the new parameterization scheme can more accurately depict the diurnal variation characteristics of bare soil surface albedo than the previous schemes. Solar elevation angle is one of the most important factors for parameterizing bare soil surface albedo and must be considered in the parameterization scheme, especially in arid and semiarid areas with low soil moisture content. This study reveals the characteristics and mechanism of the diurnal variation of bare soil surface solar spectral radiation albedo and is helpful in developing land surface process models, weather models, and climate models.

The CSIRO Mk3L climate system model v1.0 coupled to the CABLE land surface scheme v1.4b: evaluation of the control climatology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mao, Jiafu; Phipps, S.J.; Pitman, A.J.

The CSIRO Mk3L climate system model, a reduced-resolution coupled general circulation model, has previously been described in this journal. The model is configured for millennium scale or multiple century scale simulations. This paper reports the impact of replacing the relatively simple land surface scheme that is the default parameterisation in Mk3L with a sophisticated land surface model that simulates the terrestrial energy, water and carbon balance in a physically and biologically consistent way. An evaluation of the new model s near-surface climatology highlights strengths and weaknesses, but overall the atmospheric variables, including the near-surface air temperature and precipitation, are simulatedmore » well. The impact of the more sophisticated land surface model on existing variables is relatively small, but generally positive. More significantly, the new land surface scheme allows an examination of surface carbon-related quantities including net primary productivity which adds significantly to the capacity of Mk3L. Overall, results demonstrate that this reduced-resolution climate model is a good foundation for exploring long time scale phenomena. The addition of the more sophisticated land surface model enables an exploration of important Earth System questions including land cover change and abrupt changes in terrestrial carbon storage.« less

A simple hydrologically based model of land surface water and energy fluxes for general circulation models

NASA Technical Reports Server (NTRS)

Liang, XU; Lettenmaier, Dennis P.; Wood, Eric F.; Burges, Stephen J.

1994-01-01

A generalization of the single soil layer variable infiltration capacity (VIC) land surface hydrological model previously implemented in the Geophysical Fluid Dynamics Laboratory (GFDL) general circulation model (GCM) is described. The new model is comprised of a two-layer characterization of the soil column, and uses an aerodynamic representation of the latent and sensible heat fluxes at the land surface. The infiltration algorithm for the upper layer is essentially the same as for the single layer VIC model, while the lower layer drainage formulation is of the form previously implemented in the Max-Planck-Institut GCM. The model partitions the area of interest (e.g., grid cell) into multiple land surface cover types; for each land cover type the fraction of roots in the upper and lower zone is specified. Evapotranspiration consists of three components: canopy evaporation, evaporation from bare soils, and transpiration, which is represented using a canopy and architectural resistance formulation. Once the latent heat flux has been computed, the surface energy balance is iterated to solve for the land surface temperature at each time step. The model was tested using long-term hydrologic and climatological data for Kings Creek, Kansas to estimate and validate the hydrological parameters, and surface flux data from three First International Satellite Land Surface Climatology Project Field Experiment (FIFE) intensive field campaigns in the summer-fall of 1987 to validate the surface energy fluxes.

Simulation of the Onset of the Southeast Asian Monsoon During 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Wang, Yansen; Tao, W.-K.; Lau, K.-M.; Wetzel, Peter J.

2003-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated with a coupled mesoscale atmospheric model (MM5) and a detailed land surface model. The rainfall results from the simulations were compared with observed satellite data fiom the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The simulation with the land surface model captured basic signatures of the monsoon onset processes and associated rainfall statistics. The sensitivity tests indicated that land surface processes had a greater impact on the simulated rainfall results than that of a small sea surface temperature change during the onset period. In both the 1997 and 1998 cases, the simulations were significantly improved by including the land surface processes. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation; the southwest low-level flow over the Indo- China peninsula and the northern cold front intrusion from southern China. The surface sensible and latent heat exchange between the land and atmosphere modified the lowlevel temperature distribution and gradient, and therefore the low-level. The more realistic forcing of the sensible and latent heat from the detailed land surface model improved the monsoon rainfall and associated wind simulation.

Soil chemical and physical properties that differentiate urban land-use and cover types

Treesearch

R.V. Pouyat; I.D. Yesilonis; J. Russell-Anelli; N.K. Neerchal

2007-01-01

We investigated the effects of land use and cover and surface geology on soil properties in Baltimore, MD, with the objectives to: (i) measure the physical and chemical properties of surface soils (0?10 cm) by land use and cover; and (ii) ascertain whether land use and cover explain differences in these properties relative to surface geology. Mean and median values of...

Pharmaceutical occurrence in groundwater and surface waters in forests land-applied with municipal wastewater.

PubMed

McEachran, Andrew D; Shea, Damian; Bodnar, Wanda; Nichols, Elizabeth Guthrie

2016-04-01

The occurrence and fate of pharmaceutical and personal care products in the environment are of increasing public importance because of their ubiquitous nature and documented effects on wildlife, ecosystems, and potentially humans. One potential, yet undefined, source of entry of pharmaceuticals into the environment is via the land application of municipal wastewater onto permitted lands. The objective of the present study is to determine the extent to which pharmaceuticals are mitigated by or exported from managed tree plantations irrigated with municipal wastewater. A specific focus of the present study is the presence of pharmaceutical compounds in groundwater and surface water discharge. The study site is a municipality that land-applies secondary treated wastewater onto 930 hectares of a 2000-hectare managed hardwood and pine plantation. A suite of 33 pharmaceuticals and steroid hormones was targeted in the analysis, which consisted of monthly grab sampling of groundwater, surface water, and wastewater, followed by concentration and cleanup via solid phase extraction and separation, detection, and quantification via liquid chromatography coupled with tandem mass spectrometry. More than one-half of all compounds detected in irrigated wastewater were not present in groundwater and subsequent surface water. However, antibiotics, nonsteroidal anti-inflammatory drugs, caffeine, and other prescription and over-the-counter drugs remained in groundwater and were transported into surface water at concentrations up to 10 ng/L. These results provide important documentation for pharmaceutical fate and transport in forest systems irrigated with municipal wastewater, a previously undocumented source of environmental entry. © 2015 SETAC.

Surface and Atmospheric Contributions to Passive Microwave Brightness Temperatures

NASA Technical Reports Server (NTRS)

Jackson, Gail Skofronick; Johnson, Benjamin T.

2010-01-01

Physically-based passive microwave precipitation retrieval algorithms require a set of relationships between satellite observed brightness temperatures (TB) and the physical state of the underlying atmosphere and surface. These relationships are typically non-linear, such that inversions are ill-posed especially over variable land surfaces. In order to better understand these relationships, this work presents a theoretical analysis using brightness temperature weighting functions to quantify the percentage of the TB resulting from absorption/emission/reflection from the surface, absorption/emission/scattering by liquid and frozen hydrometeors in the cloud, the emission from atmospheric water vapor, and other contributors. The results are presented for frequencies from 10 to 874 GHz and for several individual precipitation profiles as well as for three cloud resolving model simulations of falling snow. As expected, low frequency channels (<89 GHz) respond to liquid hydrometeors and the surface, while the higher frequency channels become increasingly sensitive to ice hydrometeors and the water vapor sounding channels react to water vapor in the atmosphere. Low emissivity surfaces (water and snow-covered land) permit energy downwelling from clouds to be reflected at the surface thereby increasing the percentage of the TB resulting from the hydrometeors. The slant path at a 53deg viewing angle increases the hydrometeor contributions relative to nadir viewing channels and show sensitivity to surface polarization effects. The TB percentage information presented in this paper answers questions about the relative contributions to the brightness temperatures and provides a key piece of information required to develop and improve precipitation retrievals over land surfaces.

Saturn Apollo Program

NASA Image and Video Library

1968-07-09

In this photograph, Apollo 11 astronaut Michael Collins carries his coffee with him as he arrives at the flight crew training building of the NASA Kennedy Space Center (KSC) in Florida, one week before the nation’s first lunar landing mission. The Apollo 11 mission launched from KSC via the Marshall Space Flight Center (MSFC) developed Saturn V launch vehicle on July 16, 1969 and safely returned to Earth on July 24, 1969. Aboard the space craft were astronauts Neil A. Armstrong, commander; Michael Collins, Command Module (CM) pilot; and Edwin E. (Buzz) Aldrin Jr., Lunar Module (LM) pilot. The CM, “Columbia”, piloted by Collins, remained in a parking orbit around the Moon while the LM, “Eagle’’, carrying astronauts Armstrong and Aldrin, landed on the Moon. On July 20, 1969, Armstrong was the first human to ever stand on the lunar surface, followed by Aldrin. During 2½ hours of surface exploration, the crew collected 47 pounds of lunar surface material for analysis back on Earth. With the success of Apollo 11, the national objective to land men on the Moon and return them safely to Earth had been accomplished.

Saturn Apollo Program

NASA Image and Video Library

1969-07-16

Every console was manned in firing room 1 of the Kennedy Space Flight Center (KSC) control center during the launch countdown for Apollo 11. Apollo 11, the first lunar landing mission, launched from KSC in Florida via the Marshall Space Flight Center (MSFC) developed Saturn V launch vehicle on July 16, 1969 and safely returned to Earth on July 24, 1969. Aboard the space craft were astronauts Neil A. Armstrong, commander; Michael Collins, Command Module (CM) pilot; and Edwin E. (Buzz) Aldrin Jr., Lunar Module (LM) pilot. The CM, “Columbia”, piloted by Collins, remained in a parking orbit around the Moon while the LM, “Eagle’’, carrying astronauts Armstrong and Aldrin, landed on the Moon. On July 20, 1969, Armstrong was the first human to ever stand on the lunar surface, followed by Aldrin. During 2½ hours of surface exploration, the crew collected 47 pounds of lunar surface material for analysis back on Earth. With the success of Apollo 11, the national objective to land men on the Moon and return them safely to Earth had been accomplished.

Saturn Apollo Program

NASA Image and Video Library

1969-07-15

Dr. Kurt Debus, director of the Kennedy Space Flight Center (KSC), participated in the countdown demonstration test for the Apollo 11 mission in firing room 1 of the KSC control center. The Apollo 11 mission, the first lunar landing mission, launched from KSC in Florida via the Marshall Space Flight Center (MSFC) developed Saturn V launch vehicle on July 16, 1969 and safely returned to Earth on July 24, 1969. Aboard the space craft were astronauts Neil A. Armstrong, commander; Michael Collins, Command Module (CM) pilot; and Edwin E. (Buzz) Aldrin Jr., Lunar Module (LM) pilot. The CM, “Columbia”, piloted by Collins, remained in a parking orbit around the Moon while the LM, “Eagle’’, carrying astronauts Armstrong and Aldrin, landed on the Moon. On July 20, 1969, Armstrong was the first human to ever stand on the lunar surface, followed by Aldrin. During 2½ hours of surface exploration, the crew collected 47 pounds of lunar surface material for analysis back on Earth. With the success of Apollo 11, the national objective to land men on the Moon and return them safely to Earth had been accomplished.

Assessing and monitoring the risk of land degradation in Baragan Plain, Romania, using spectral mixture analysis and Landsat imagery.

PubMed

Vorovencii, Iosif

2016-07-01

The fall of the communist regime in Romania at the end of 1989 and the ensuing transition to the market economy brought about many changes in the use of agricultural land. These changes combined with the action of climatic factors led, in most cases, to negative effects increasing the risk of degradation of agricultural land. This study aims to assess and monitor the risk of land degradation in Baragan Plain, Romania, for the period 1988-2011 using Landsat Thematic Mapper (TM) and Spectral Mixture Analysis (SMA). Each satellite image was classified through the Decision Tree Classifier (DTC) method; then, on the basis of certain threshold values, we obtained maps of land degradation and maps showing the passage from various classes of land use/land cover (LULC) to land degradation. The results indicate that during the intermediary periods there was an ascending and descending trend in the risk of land degradation determined by the interaction of climatic factors with the social-economic ones. For the entire period, the overall trend was ascending, the risk of land degradation increasing by around 4.60 % of the studied surface. Out of the climatic factors, high temperatures and, implicitly, drought were the most significant. The social-economic factors are the result of the changes which occurred after the fall of the communist regime, the most important being the fragmentation of agricultural land and the destruction of the irrigation system.

Method and Early Results of Applying the Global Land Data Assimilation System (GLDAS) in the Third Global Reanalysis of NCEP

NASA Astrophysics Data System (ADS)

Meng, J.; Mitchell, K.; Wei, H.; Yang, R.; Kumar, S.; Geiger, J.; Xie, P.

2008-05-01

Over the past several years, the Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) of the U.S. National Weather Service has developed a Global Land Data Assimilation System (GLDAS). For its computational infrastructure, the GLDAS applies the NASA Land Information System (LIS), developed by the Hydrological Science Branch of NASA Goddard Space Flight Center. The land model utilized in the NCEP GLDAS is the NCEP Noah Land Surface Model (Noah LSM). This presentation will 1) describe how the GLDAS component has been included in the development of NCEP's third global reanalysis (with special attention to the input sources of global precipitation), and 2) will present results from the GLDAS component of pilot tests of the new NCEP global reanalysis. Unlike NCEP's past two global reanalysis projects, this new NCEP global reanalysis includes both a global land data assimilation system (GLDAS) and a global ocean data assimilation system (GODAS). The new global reanalysis will span 30-years (1979-2008) and will include a companion realtime operational component. The atmospheric, ocean, and land states of this global reanalysis will provide the initial conditions for NCEP's 3rd- generation global coupled Climate Forecast System (CFS). NCEP is now preparing to launch a 28-year seasonal reforecast project with its new CFS, to provide the reforecast foundation for operational NCEP seasonal climate forecasts using the new CFS. Together, the new global reanalysis and companion CFS reforecasts constitute what NCEP calls the Climate Forecast System Reanalysis and Reforecast (CFSRR) project. Compared to the previous two generations of NCEP global reanalysis, the hallmark of the GLDAS component of CFSRR is GLDAS use of global analyses of observed precipitation to drive the land surface component of the reanalysis (rather than the typical reanalysis approach of using precipitation from the assimilating background atmospheric model). Specifically, the GLDAS merges two global analyses of observed precipitation produced by the Climate Prediction Center (CPC) of NCEP, as follows: 1) a new CPC daily gauge-only land-only global precipitation analysis at 0.5-degree resolution and 2) the well-known CPC CMAP global 2.0 x 2.5 degree 5-day precipitation analysis, which utilizes satellite estimates of precipitation, as well as some gauge observations. The presentation will describe how these two analyses are merged with latitude-dependent weights that favor the gauge-only analysis in mid-latitudes and the satellite-dominated CMAP analysis in tropical latitudes. Finally, we will show some impacts of using GLDAS to initialize the land states of seasonal CFS reforecasts, versus using the previous generation of NCEP global reanalysis as the source for CFS initial land states.

Determining Reflectance Spectra of Surfaces and Clouds on Exoplanets

NASA Astrophysics Data System (ADS)

Cowan, Nicolas B.; Strait, Talia E.

2013-03-01

Planned missions will spatially resolve temperate terrestrial planets from their host star. Although reflected light from such a planet encodes information about its surface, it has not been shown how to establish surface characteristics of a planet without assuming known surfaces to begin with. We present a reanalysis of disk-integrated, time-resolved, multiband photometry of Earth obtained by the Deep Impact spacecraft as part of the EPOXI Mission of Opportunity. We extract reflectance spectra of clouds, ocean, and land without a priori knowledge of the numbers or colors of these surfaces. We show that the inverse problem of extracting surface spectra from such data is a novel and extreme instance of spectral unmixing, a well-studied problem in remote sensing. Principal component analysis is used to determine an appropriate number of model surfaces with which to interpret the data. Shrink-wrapping a simplex to the color excursions of the planet yields a conservative estimate of the planet's endmember spectra. The resulting surface maps are unphysical, however, requiring negative or larger-than-unity surface coverage at certain locations. Our "rotational unmixing" supersedes the endmember analysis by simultaneously solving for the surface spectra and their geographical distributions on the planet, under the assumption of diffuse reflection and known viewing geometry. We use a Markov Chain Monte Carlo to determine best-fit parameters and their uncertainties. The resulting albedo spectra are similar to clouds, ocean, and land seen through a Rayleigh-scattering atmosphere. This study suggests that future direct-imaging efforts could identify and map unknown surfaces and clouds on exoplanets.

Mapping the Dynamics of Surface Water Extent 1999-2015 with Landsat 5, 7, and 8 Archives

NASA Astrophysics Data System (ADS)

Pickens, A. H.; Hansen, M.; Hancher, M.; Potapov, P.

2016-12-01

Surface water extent fluctuates through both seasons and years due to changes in climatic conditions and human extraction and impoundments. This study maps the presence of surface water every month since January 1999, evaluates the detection reliability, visualizes the trends, and explores future applications. The Global Land Analysis and Discovery group at the University of Maryland developed a 30-m mask of persistent water during the growing seasons of 2000-2012 in conjunction with the Global Forest Change product published by Hansen et al. in 2013. A total of 654,178 Landsat 7 scenes were used for the study. Persistent water was defined as all pixels with water classified in more than 50% of observations over the study period. We validated this mask by stratifying and comparing against a random sample of 135 RapidEye, single-date images at 5-m resolution. It was found to have estimated user's and producer's accuracies of 94% and 88%, respectively. This estimated error is due primarily to temporal differences, such as dam construction, and to mixed water-land pixels along water body edges and narrow rivers. In order to investigate temporal extent dynamics, we expanded our analysis of surface water to classify every Landsat 5, 7, and 8 scene since 1999, augmented with elevation data from SRTM and ASTER, via a series of decision trees applied using Google Earth Engine. The water and land observations are aggregated per each month of each year. We developed a model to visualize the dynamic trend in surface water presence since 1999, either per month or annually as shown below. This model can be used directly to assess the seasonal and inter-annual trends globally or regionally, or the raw monthly counts can be used for more intensive hydrological analysis and as inputs for other related studies such as wetland mapping.

Skin Temperature Analysis and Bias Correction in a Coupled Land-Atmosphere Data Assimilation System

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Radakovich, Jon D.; daSilva, Arlindo; Todling, Ricardo; Verter, Frances

2006-01-01

In an initial investigation, remotely sensed surface temperature is assimilated into a coupled atmosphere/land global data assimilation system, with explicit accounting for biases in the model state. In this scheme, an incremental bias correction term is introduced in the model's surface energy budget. In its simplest form, the algorithm estimates and corrects a constant time mean bias for each gridpoint; additional benefits are attained with a refined version of the algorithm which allows for a correction of the mean diurnal cycle. The method is validated against the assimilated observations, as well as independent near-surface air temperature observations. In many regions, not accounting for the diurnal cycle of bias caused degradation of the diurnal amplitude of background model air temperature. Energy fluxes collected through the Coordinated Enhanced Observing Period (CEOP) are used to more closely inspect the surface energy budget. In general, sensible heat flux is improved with the surface temperature assimilation, and two stations show a reduction of bias by as much as 30 Wm(sup -2) Rondonia station in Amazonia, the Bowen ratio changes direction in an improvement related to the temperature assimilation. However, at many stations the monthly latent heat flux bias is slightly increased. These results show the impact of univariate assimilation of surface temperature observations on the surface energy budget, and suggest the need for multivariate land data assimilation. The results also show the need for independent validation data, especially flux stations in varied climate regimes.

Analysis of Surface Heterogeneity Effects with Mesoscale Terrestrial Modeling Platforms

NASA Astrophysics Data System (ADS)

Simmer, C.

2015-12-01

An improved understanding of the full variability in the weather and climate system is crucial for reducing the uncertainty in weather forecasting and climate prediction, and to aid policy makers to develop adaptation and mitigation strategies. A yet unknown part of uncertainty in the predictions from the numerical models is caused by the negligence of non-resolved land surface heterogeneity and the sub-surface dynamics and their potential impact on the state of the atmosphere. At the same time, mesoscale numerical models using finer horizontal grid resolution [O(1)km] can suffer from inconsistencies and neglected scale-dependencies in ABL parameterizations and non-resolved effects of integrated surface-subsurface lateral flow at this scale. Our present knowledge suggests large-eddy-simulation (LES) as an eventual solution to overcome the inadequacy of the physical parameterizations in the atmosphere in this transition scale, yet we are constrained by the computational resources, memory management, big-data, when using LES for regional domains. For the present, there is a need for scale-aware parameterizations not only in the atmosphere but also in the land surface and subsurface model components. In this study, we use the recently developed Terrestrial Systems Modeling Platform (TerrSysMP) as a numerical tool to analyze the uncertainty in the simulation of surface exchange fluxes and boundary layer circulations at grid resolutions of the order of 1km, and explore the sensitivity of the atmospheric boundary layer evolution and convective rainfall processes on land surface heterogeneity.

Determining the impact of urban components on land surface temperature of Istanbul by using remote sensing indices.

PubMed

Bektaş Balçik, Filiz

2014-02-01

For the past 60 years, Istanbul has been experiencing an accelerated urban expansion. This urban expansion is leading to the replacement of natural surfaces by various artificial materials. This situation has a critical impact on the environment due to the alteration of heat energy balance. In this study, the effect upon the urban heat island (UHI) of Istanbul was analyzed using 2009 dated Landsat 5 Thematic Mapper (TM) data. An Index Based Built-up Index (IBI) was used to derive artificial surfaces in the study area. To produce the IBI index, Soil-Adjusted Vegetation Index, Normalized Difference Built-up Index, and Modified Normalized Difference Water Index were calculated. Land surface temperature (LST) distribution was derived from Landsat 5 TM images using a mono-window algorithm. In addition, 24 transects were selected, and different regression models were applied to explore the correlation between LST and IBI index. The results show that artificial surfaces have a positive exponential relationship with LST rather than a simple linear one. An ecological evaluation index of the region was calculated to explore the impact of both the vegetated land and the artificial surfaces on the UHI. Therefore, the quantitative relationship of urban components (artificial surfaces, vegetation, and water) and LST was examined using multivariate statistical analysis, and the correlation coefficient was obtained as 0.829. This suggested that the areas with a high rate of urbanization will accelerate the rise of LST and UHI in Istanbul.

Analysis of a terminal landing on Mars

NASA Astrophysics Data System (ADS)

Tuckness, Dan G.

1995-01-01

This study consists of a preliminary performance and sensitivity assessment of trajectory and guidance capabilities of a Mars terminal landing phase. The phase begins with the end of the entry phase, which is at parachute deployment. Therefore, the trajectory investigated in this study starts at parachute deployment and continues through parachute jettison and finally propulsive deceleration and maneuvering to a specified landing site. Various landing navigation maneuver schemes and environmental conditions for the lander are investigated and their performance analyzed. Effects of atmospheric density and surface wind deviations on landing guidance are investigated using stochastic wind and density models. Simulation shows that the lander guidance is robust to wind and density dispersions. Density dispersions are found to be more critical for a precision landing than wind dispersions. Also, because of the aerodynamic characteristics of current aeroshell vehicle designs, very little terminal maneuvering is allowed for navigation.

Using Landsat Thematic Mapper (TM) sensor to detect change in land surface temperature in relation to land use change in Yazd, Iran

NASA Astrophysics Data System (ADS)

Zareie, Sajad; Khosravi, Hassan; Nasiri, Abouzar; Dastorani, Mostafa

2016-11-01

Land surface temperature (LST) is one of the key parameters in the physics of land surface processes from local to global scales, and it is one of the indicators of environmental quality. Evaluation of the surface temperature distribution and its relation to existing land use types are very important to the investigation of the urban microclimate. In arid and semi-arid regions, understanding the role of land use changes in the formation of urban heat islands is necessary for urban planning to control or reduce surface temperature. The internal factors and environmental conditions of Yazd city have important roles in the formation of special thermal conditions in Iran. In this paper, we used the temperature-emissivity separation (TES) algorithm for LST retrieving from the TIRS (Thermal Infrared Sensor) data of the Landsat Thematic Mapper (TM). The root mean square error (RMSE) and coefficient of determination (R2) were used for validation of retrieved LST values. The RMSE of 0.9 and 0.87 °C and R2 of 0.98 and 0.99 were obtained for the 1998 and 2009 images, respectively. Land use types for the city of Yazd were identified and relationships between land use types, land surface temperature and normalized difference vegetation index (NDVI) were analyzed. The Kappa coefficient and overall accuracy were calculated for accuracy assessment of land use classification. The Kappa coefficient values are 0.96 and 0.95 and the overall accuracy values are 0.97 and 0.95 for the 1998 and 2009 classified images, respectively. The results showed an increase of 1.45 °C in the average surface temperature. The results of this study showed that optical and thermal remote sensing methodologies can be used to research urban environmental parameters. Finally, it was found that special thermal conditions in Yazd were formed by land use changes. Increasing the area of asphalt roads, residential, commercial and industrial land use types and decreasing the area of the parks, green spaces and fallow lands in Yazd caused a rise in surface temperature during the 11-year period.

Machine processing of remotely sensed data; Proceedings of the Fifth Annual Symposium, Purdue University, West Lafayette, Ind., June 27-29, 1979

NASA Technical Reports Server (NTRS)

Tendam, I. M. (Editor); Morrison, D. B.

1979-01-01

Papers are presented on techniques and applications for the machine processing of remotely sensed data. Specific topics include the Landsat-D mission and thematic mapper, data preprocessing to account for atmospheric and solar illumination effects, sampling in crop area estimation, the LACIE program, the assessment of revegetation on surface mine land using color infrared aerial photography, the identification of surface-disturbed features through a nonparametric analysis of Landsat MSS data, the extraction of soil data in vegetated areas, and the transfer of remote sensing computer technology to developing nations. Attention is also given to the classification of multispectral remote sensing data using context, the use of guided clustering techniques for Landsat data analysis in forest land cover mapping, crop classification using an interactive color display, and future trends in image processing software and hardware.

Updates from the MSL-RAD Experiment on the Mars Curiosity Rover

NASA Technical Reports Server (NTRS)

Zeitlin, Cary

2015-01-01

The MSL-RAD instrument continues to operate flawlessly on Mars. As of this writing, some 1040 sols (Martian days) of data have been successfully acquired. Several improvements have been made to the instrument's configuration, particularly aimed at enabling the analysis of neutral-particle data. The dose rate since MSL's landing in August 2012 has remained remarkably stable, reflecting the unusual and very weak solar maximum of Cycle 24. Only a few small SEP events have been observed by RAD, which is shielded by the Martian atmosphere. Gale Crater, where Curiosity landed, is 4.4 km below the mean surface of Mars, and the column depth of atmosphere above is approximately 20 g/sq cm, which provides significant attenuation of GCR heavy ions and SEPs. Recent analysis results will be presented, including updated estimates of the neutron contributions to dose and dose equivalent in cruise and on the surface of Mars.

Integrating seasonal optical and thermal infrared spectra to characterize urban impervious surfaces with extreme spectral complexity: a Shanghai case study

NASA Astrophysics Data System (ADS)

Wang, Wei; Yao, Xinfeng; Ji, Minhe

2016-01-01

Despite recent rapid advancement in remote sensing technology, accurate mapping of the urban landscape in China still faces a great challenge due to unusually high spectral complexity in many big cities. Much of this complication comes from severe spectral confusion of impervious surfaces with polluted water bodies and bright bare soils. This paper proposes a two-step land cover decomposition method, which combines optical and thermal spectra from different seasons to cope with the issue of urban spectral complexity. First, a linear spectral mixture analysis was employed to generate fraction images for three preliminary endmembers (high albedo, low albedo, and vegetation). Seasonal change analysis on land surface temperature induced from thermal infrared spectra and coarse component fractions obtained from the first step was then used to reduce the confusion between impervious surfaces and nonimpervious materials. This method was tested with two-date Landsat multispectral data in Shanghai, one of China's megacities. The results showed that the method was capable of consistently estimating impervious surfaces in highly complex urban environments with an accuracy of R2 greater than 0.70 and both root mean square error and mean average error less than 0.20 for all test sites. This strategy seemed very promising for landscape mapping of complex urban areas.

Further Analysis on the Mystery of the Surveyor III Dust Deposits

NASA Technical Reports Server (NTRS)

Metzger, Philip; Hintze, Paul; Trigwell, Steven; Lane, John

2011-01-01

The Apollo 12 lunar module (LM) landing near the Surveyor 1lI spacecraft at the end of 1969 has remained the primary experimental verification of the predicted physics of plume ejecta effects from a rocket engine interacting with the surface of the moon. This was made possible by the return of the Surveyor 1lI camera housing by the Apollo 12 astronauts, allowing detailed analysis of the composition of dust deposited by the Apollo 12 LM plume. It was soon realized after the initial analysis of the camera housing that the LM plume tended to remove more dust than it had deposited. In the present study, coupons from the camera housing were reexamined by a KSC research team using SEM/EDS and XPS analysis. In addition, plume effects recorded in landing videos from each Apollo mission have been studied for possible clues. Several likely scenarios are proposed to explain the Surveyor III dust observations. These include electrostatic attraction of the dust to the surface of the Surveyor as a result of electrostatic charging of the jet gas exiting the engine nozzle during descent; dust blown by the Apollo 12 LM fly-by while on its descent trajectory; dust ejected from the lunar surface due to gas forced into the soil by the Surveyor 1lI rocket nozzle, based on Darcy's law; and mechanical movement of dust during the Surveyor landing. Even though an absolute answer is not possible based on available data and theory, various computational models are employed to estimate the feasibility of each of these proposed mechanisms. Scenarios are then discussed which combine multiple mechanisms to produce results consistent with observations.

Effect of spatial organisation behaviour on upscaling the overland flow formation in an arable land

NASA Astrophysics Data System (ADS)

Silasari, Rasmiaditya; Blöschl, Günter

2014-05-01

Overland flow during rainfall events on arable land is important to investigate as it affects the land erosion process and water quality in the river. The formation of overland flow may happen through different ways (i.e. Hortonian overland flow, saturation excess overland flow) which is influenced by the surface and subsurface soil characteristics (i.e. land cover, soil infiltration rate). As the soil characteristics vary throughout the entire catchment, it will form distinct spatial patterns with organised or random behaviour. During the upscaling of hydrological processes from plot to catchment scale, this behaviour will become substantial since organised patterns will result in higher spatial connectivity and thus higher conductivity. However, very few of the existing studies explicitly address this effect of spatial organisations of the patterns in upscaling the hydrological processes to the catchment scale. This study will assess the upscaling of overland flow formation with concerns of spatial organisation behaviour of the patterns by application of direct field observations under natural conditions using video camera and soil moisture sensors and investigation of the underlying processes using a physical-based hydrology model. The study area is a Hydrological Open Air Laboratory (HOAL) located at Petzenkirchen, Lower Austria. It is a 64 ha catchment with land use consisting of arable land (87%), forest (6%), pasture (5%) and paved surfaces (2%). A video camera is installed 7m above the ground on a weather station mast in the middle of the arable land to monitor the overland flow patterns during rainfall events in a 2m x 6m plot scale. Soil moisture sensors with continuous measurement at different depth (5, 10, 20 and 50cm) are installed at points where the field is monitored by the camera. The patterns of overland flow formation and subsurface flow state at the plot scale will be generated using a coupled surface-subsurface flow physical-based hydrology model. The observation data will be assimilated into the model to verify the corresponding processes between surface and subsurface flow during the rainfall events. The patterns of conductivity then will be analyzed at catchment scale using the spatial stochastic analysis based on the classification of soil characteristics of the entire catchment. These patterns of conductivity then will be applied in the model at catchment scale to see how the organisational behaviour can affect the spatial connectivity of the hydrological processes and the results of the catchment response. A detailed modelling of the underlying processes in the physical-based model will allow us to see the direct effect of the spatial connectivity to the occurring surface and subsurface flow. This will improve the analysis of the effect of spatial organisations of the patterns in upscaling the hydrological processes from plot to catchment scale.

Combining Satellite Data and Models to Assess the Impacts of Urbanization on the Continental US Surface Climate

NASA Technical Reports Server (NTRS)

Bounoua, L.; Zhang, P.; Imhoff, M.; Santanello, J.; Kumar, S.; Shepherd, M.; Quattrochi, D.; Silva, J.; Rosenzweigh, C.; Gaffin, S.;

Terrestrial Ecosystems - Land Surface Forms of the Conterminous United States

USGS Publications Warehouse

Cress, Jill J.; Sayre, Roger G.; Comer, Patrick; Warner, Harumi

2009-01-01

As part of an effort to map terrestrial ecosystems, the U.S. Geological Survey has generated land surface form classes to be used in creating maps depicting standardized, terrestrial ecosystem models for the conterminous United States, using an ecosystems classification developed by NatureServe . A biophysical stratification approach, developed for South America and now being implemented globally, was used to model the ecosystem distributions. Since land surface forms strongly influence the differentiation and distribution of terrestrial ecosystems, they are one of the key input layers in this biophysical stratification. After extensive investigation into various land surface form mapping methodologies, the decision was made to use the methodology developed by the Missouri Resource Assessment Partnership (MoRAP). MoRAP made modifications to Hammond's land surface form classification, which allowed the use of 30-meter source data and a 1-km2 window for analyzing the data cell and its surrounding cells (neighborhood analysis). While Hammond's methodology was based on three topographic variables, slope, local relief, and profile type, MoRAP's methodology uses only slope and local relief. Using the MoRAP method, slope is classified as gently sloping when more than 50 percent of the area in a 1-km2 neighborhood has slope less than 8 percent, otherwise the area is considered moderately sloping. Local relief, which is the difference between the maximum and minimum elevation in a neighborhood, is classified into five groups: 0-15 m, 16-30 m, 31-90 m, 91-150 m, and >150 m. The land surface form classes are derived by combining slope and local relief to create eight landform classes: flat plains (gently sloping and local relief = 90 m), low hills (not gently sloping and local relief = 150 m). However, in the USGS application of the MoRAP methodology, an additional local relief group was used (> 400 m) to capture additional local topographic variation. As a result, low mountains were redefined as not gently sloping and 151 m 400 m. The final application of the MoRAP methodology was implemented using the USGS 30-meter National Elevation Dataset and an existing USGS slope dataset that had been derived by calculating the slope from the NED in Universal Transverse Mercator (UTM) coordinates in each UTM zone, and then combining all of the zones into a national dataset. This map shows a smoothed image of the nine land surface form classes based on MoRAP's methodology. Additional information about this map and any data developed for the ecosystems modeling of the conterminous United States is available online at http://rmgsc.cr.usgs.gov/ecosystems/.

Impacts of Urbanization in the Coastal Tropical City of San Juan, Puerto Rico

NASA Technical Reports Server (NTRS)

Comarazamy, Daniel E.; Gonzalez, Jorge E.; Luvall, Jeffrey C.; Rickman, Douglass

2007-01-01

Urban sprawl in tropical locations is rapidly accelerating and it is more evident in islands where a large percentage of the population resides along the coasts. This paper focuses on the analysis of the impacts of land use and land cover for urbanization in the tropical coastal city of San Juan, in the Caribbean island of Puerto Rico. A mesoscale numerical model, the Regional Atmospheric Modeling System (RAMS), is used to study the impacts of land use for urbanization in the environment including specific characteristics of the urban heat island in the San Juan Metropolitan Area (SJMA), one of the most noticeable urban cores of the Caribbean. The research also makes use of the observations obtained during the airborne San Juan Atlas Mission. Surface and raw insonde data from the mission are used to validate the atmospheric model yielding satisfactory results. Airborne high resolution remote sensing data are used to update the model's surface characteristics in order to obtain a more accurate and detailed configuration of the SJMA and perform a climate impact analysis based on land cover/land use (LCLU) changes. The impact analysis showed that the presence of the urban landscape of San Juan has an impact reflected in higher air temperatures over the area occupied by the city, with positive values of up to 2.5 degrees C, for the simulations that have specified urban LCLU indexes in the model's bottom boundary. One interesting result of the impact analysis was the finding of a precipitation disturbance shown as a difference in total accumulated rainfall between the present urban landscape and with a potential natural vegetation, apparently induced by the presence of the urban area. Results indicate that the urban-enhanced cloud formation and precipitation development occur mainly downwind of the city, including the accumulated precipitation. This spatial pattern can be explained by the presence of a larger urbanized area in the southwest sector of the city, and of the approaching northeasterly trade winds.

Optimizing Mars Sphere of Influence Maneuvers for NASA's Evolvable Mars Campaign

NASA Technical Reports Server (NTRS)

Merrill, Raymond G.; Komar, D. R.; Chai, Patrick; Qu, Min

2016-01-01

NASA's Human Spaceflight Architecture Team is refining human exploration architectures that will extend human presence to the Martian surface. For both Mars orbital and surface missions, NASA's Evolvable Mars Campaign assumes that cargo and crew can be delivered repeatedly to the same destination. Up to this point, interplanetary trajectories have been optimized to minimize the total propulsive requirements of the in-space transportation systems, while the pre-deployed assets and surface systems are optimized to minimize their respective propulsive requirements separate from the in-space transportation system. There is a need to investigate the coupled problem of optimizing the interplanetary trajectory and optimizing the maneuvers within Mars's sphere of influence. This paper provides a description of the ongoing method development, analysis and initial results of the effort to resolve the discontinuity between the interplanetary trajectory and the Mars sphere of influence trajectories. Assessment of Phobos and Deimos orbital missions shows the in-space transportation and crew taxi allocations are adequate for missions in the 2030s. Because the surface site has yet to be selected, the transportation elements must be sized to provide enough capability to provide surface access to all landing sites under consideration. Analysis shows access to sites from elliptical parking orbits with a lander that is designed for sub-periapsis landing location is either infeasible or requires expensive orbital maneuvers for many latitude ranges. In this case the locus of potential arrival perigee vectors identifies the potential maximum north or south latitudes accessible. Higher arrival velocities can decrease reorientation costs and increase landing site availability. Utilizing hyperbolic arrival and departure vectors in the optimization scheme will increase transportation site accessibility and provide more optimal solutions.

Interannual, seasonal and diurnal Mars surface environmental cycles observed from Viking to Curiosity

NASA Astrophysics Data System (ADS)

Martinez, German; Vicente-Retortillo, Álvaro; Kemppinen, Osku; Fischer, Erik; Fairen, Alberto G.; Guzewich, Scott David; Haberle, Robert; Lemmon, Mark T.; Newman, Claire E.; Renno, Nilton O.; Richardson, Mark I.; Smith, Michael D.; De la Torre, Manuel; Vasavada, Ashwin R.

2016-10-01

We analyze in-situ environmental data from the Viking landers to the Curiosity rover to estimate atmospheric pressure, near-surface air and ground temperature, relative humidity, wind speed and dust opacity with the highest confidence possible. We study the interannual, seasonal and diurnal variability of these quantities at the various landing sites over a span of more than twenty Martian years to characterize the climate on Mars and its variability. Additionally, we characterize the radiative environment at the various landing sites by estimating the daily UV irradiation (also called insolation and defined as the total amount of solar UV energy received on flat surface during one sol) and by analyzing its interannual and seasonal variability.In this study we use measurements conducted by the Viking Meteorology Instrument System (VMIS) and Viking lander camera onboard the Viking landers (VL); the Atmospheric Structure Instrument/Meteorology (ASIMET) package and the Imager for Mars Pathfinder (IMP) onboard the Mars Pathfinder (MPF) lander; the Miniature Thermal Emission Spectrometer (Mini-TES) and Pancam instruments onboard the Mars Exploration Rovers (MER); the Meteorological Station (MET), Thermal Electrical Conductivity Probe (TECP) and Phoenix Surface Stereo Imager (SSI) onboard the Phoenix (PHX) lander; and the Rover Environmental Monitoring Station (REMS) and Mastcam instrument onboard the Mars Science Laboratory (MSL) rover.A thorough analysis of in-situ environmental data from past and present missions is important to aid in the selection of the Mars 2020 landing site. We plan to extend our analysis of Mars surface environmental cycles by using upcoming data from the Temperature and Wind sensors (TWINS) instrument onboard the InSight mission and the Mars Environmental Dynamics Analyzer (MEDA) instrument onboard the Mars 2020 mission.

Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.

2011-01-01

The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

NASA Technical Reports Server (NTRS)

1974-01-01

A number of problems related to the design, construction and evaluation of an autonomous roving planetary vehicle and its control and operating systems intended for an unmanned exploration of Mars are studied. Vehicle configuration, dynamics, control, systems and propulsion; systems analysis; terrain sensing and modeling and path selection; and chemical analysis of samples are included.

30 CFR 740.15 - Bonds on Federal lands.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR FEDERAL LANDS PROGRAM GENERAL REQUIREMENTS FOR SURFACE COAL MINING AND RECLAMATION OPERATIONS ON FEDERAL LANDS... surface coal mining, the applicant for a mining permit, if unable to obtain the written consent of the...

Using SMOS brightness temperature and derived surface-soil moisture to characterize surface conditions and validate land surface models.

NASA Astrophysics Data System (ADS)

Polcher, Jan; Barella-Ortiz, Anaïs; Piles, Maria; Gelati, Emiliano; de Rosnay, Patricia

2017-04-01

The SMOS satellite, operated by ESA, observes the surface in the L-band. On continental surface these observations are sensitive to moisture and in particular surface-soil moisture (SSM). In this presentation we will explore how the observations of this satellite can be exploited over the Iberian Peninsula by comparing its results with two land surface models : ORCHIDEE and HTESSEL. Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies. When comparing the surface-soil moisture of the models with the product derived operationally by ESA from SMOS observations similar results are found. The spatial correlation over the IP between SMOS and ORCHIDEE SSM estimates is poor (ρ 0.3). A single value decomposition (SVD) analysis of rainfall and SSM shows that the co-varying patterns of these variables are in reasonable agreement between both products. Moreover the first three SVD soil moisture patterns explain over 80% of the SSM variance simulated by the model while the explained fraction is only 52% of the remotely sensed values. These results suggest that the rainfall-driven soil moisture variability may not account for the poor spatial correlation between SMOS and ORCHIDEE products. Other reasons have to be sought to explain the poor agreement in spatial patterns between satellite derived and modelled SSM. This presentation will hopefully contribute to the discussion of how SMOS and other observations can be used to prepare, carry-out and exploit a field campaign over the Iberian Peninsula which aims at improving our understanding of semi-arid land surface processes.

South Florida Everglades: satellite image map

USGS Publications Warehouse

Jones, John W.; Thomas, Jean-Claude; Desmond, G.B.

2001-01-01

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program (http://access.usgs.gov/) with support from the Everglades National Park (http://www.nps.gov/ever/). The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

Underwater MASW to evaluate stiffness of water-bottom sediments

USGS Publications Warehouse

Park, C.B.; Miller, R.D.; Xia, J.; Ivanov, J.; Sonnichsen, G.V.; Hunter, J.A.; Good, R.L.; Burns, R.A.; Christian, H.

2005-01-01

The multichannel analysis of surface waves (MASW) is initially intended as a land survey method to investigate the near-surface materials for their elastic properties. The acquired data are first analyzed for dispersion characteristics and, from these the shear-wave velocity is estimated using an inversion technique. Land applications show the potential of the MASW method to map 2D bedrock surface, zones of low strength, Poisson's ratio, voids, as well as to generate shear-wave profiles for various othe geotechnical problems. An overview is given of several underwater applications of the MASW method to characterize stiffness distribution of water-bottom sediments. The first application details the survey under shallow-water (1-6 m) in the Fraser River (Canada). The second application is an innovative experimental marine seismic survey in the North Atlantic Ocean near oil fields in Grand Bank offshore Newfoundland.

Impervious Surfaces Alter Soil Bacterial Communities in Urban Areas: A Case Study in Beijing, China

PubMed Central

Hu, Yinhong; Dou, Xiaolin; Li, Juanyong; Li, Feng

2018-01-01

The rapid expansion of urbanization has caused land cover change, especially the increasing area of impervious surfaces. Such alterations have significant effects on the soil ecosystem by impeding the exchange of gasses, water, and materials between soil and the atmosphere. It is unclear whether impervious surfaces have any effects on soil bacterial diversity and community composition. In the present study, we conducted an investigation of bacterial communities across five typical land cover types, including impervious surfaces (concrete), permeable pavement (bricks with round holes), shrub coverage (Buxus megistophylla Levl.), lawns (Festuca elata Keng ex E. Alexeev), and roadside trees (Sophora japonica Linn.) in Beijing, to explore the response of bacteria to impervious surfaces. The soil bacterial communities were addressed by high-throughput sequencing of the bacterial 16S rRNA gene. We found that Proteobacteria, Actinobacteria, Acidobacteria, Bacteroidetes, Chloroflexi, and Firmicutes were the predominant phyla in urban soils. Soil from impervious surfaces presented a lower bacterial diversity, and differed greatly from other types of land cover. Soil bacterial diversity was predominantly affected by Zn, dissolved organic carbon (DOC), and soil moisture content (SMC). The composition of the bacterial community was similar under shrub coverage, roadside trees, and lawns, but different from beneath impervious surfaces and permeable pavement. Variance partitioning analysis showed that edaphic properties contributed to 12% of the bacterial community variation, heavy metal pollution explained 3.6% of the variation, and interaction between the two explained 33% of the variance. Together, our data indicate that impervious surfaces induced changes in bacterial community composition and decrease of bacterial diversity. Interactions between edaphic properties and heavy metals were here found to change the composition of the bacterial community and diversity across areas with different types of land cover, and soil properties play a more important role than heavy metals. PMID:29545776

Evaluation of MODIS and VIIRS Albedo Products Using Ground and Airborne Measurements and Development of Ceos/Wgcv/Lpv Albedo Ecv Protocols

NASA Astrophysics Data System (ADS)

Wang, Z.; Roman, M. O.; Schaaf, C.; Sun, Q.; Liu, Y.; Saenz, E. J.; Gatebe, C. K.

2014-12-01

Surface albedo, defined as the ratio of the hemispheric reflected solar radiation flux to the incident flux upon the surface, is one of the essential climate variables and quantifies the radiation interaction between the atmosphere and the land surface. An absolute accuracy of 0.02-0.05 for global surface albedo is required by climate models. The MODerate resolution Imaging Spectroradiometer (MODIS) standard BRDF/albedo product makes use of a linear "kernel-driven" RossThick-LiSparse Reciprocal (RTLSR) BRDF model to describe the reflectance anisotropy. The surface albedo is calculated by integrating the BRDF over the above ground hemisphere. While MODIS Terra was launched in Dec 1999 and MODIS Aqua in 2002, the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi-NPP satellite was launched more recently on October 28, 2011. Thus a long term record of BRDF, albedo and Nadir BRDF-Adjusted Reflectance (NBAR) products from VIIRS can be generated through MODIS heritage algorithms. Several investigations have evaluated the MODIS albedo products during the growing season, as well as during dormant and snow covered periods. The Land Product Validation (LPV) sub-group of the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) aims to address the challenges associated with the validation of global land products. The validation of global surface radiation/albedo products is one of the LPV subgroup activities. In this research, a reference dataset covering various land surface types and vegetation structure is assembled to assess the accuracy of satellite albedo products. This dataset includes in situ data (Baseline Surface Radiation Network (BSRN), FLUXNET and Long Term Ecological Research network (LTER) etc.) and airborne measurements (e.g. Cloud Absorption Radiometer (CAR)). Spatially representative analysis is applied to each site to establish whether the ground measurements can adequately represent moderate spatial resolution remotely sensed albedo products.

Sedimentology of Martian Gravels from Mardi Twilight Imaging: Techniques

NASA Technical Reports Server (NTRS)

Garvin, James B.; Malin, Michael C.; Minitti, M. E.

2014-01-01

Quantitative sedimentologic analysis of gravel surfaces dominated by pebble-sized clasts has been employed in an effort to untangle aspects of the provenance of surface sediments on Mars using Curiosity's MARDI nadir-viewing camera operated at twilight Images have been systematically acquired since sol 310 providing a representative sample of gravel-covered surfaces since the rover departed the Shaler region. The MARDI Twilight imaging dataset offers approximately 1 millimeter spatial resolution (slightly out of focus) for patches beneath the rover that cover just under 1 m2 in area, under illumination that makes clast size and inter-clast spacing analysis relatively straightforward using semi- automated codes developed for use with nadir images. Twilight images are utilized for these analyses in order to reduce light scattering off dust deposited on the front MARDI lens element during the terminal stages of Curiosity's entry, descent and landing. Such scattering is worse when imaging bright, directly-illuminated surfaces; twilight imaging times yield diffusely-illuminated surfaces that improve the clarity of the resulting MARDI product. Twilight images are obtained between 10-30 minutes after local sunset, governed by the timing of the end of the no-heat window for the camera. Techniques were also utilized to examine data terrestrial locations (the Kau Desert in Hawaii and near Askja Caldera in Iceland). Methods employed include log hyperbolic size distribution (LHD) analysis and Delauney Triangulation (DT) inter-clast spacing analysis. This work extends the initial results reported in Yingst et al., that covered the initial landing zone, to the Rapid-Transit Route (RTR) towards Mount Sharp.

Surface Heat Balance Analysis of Tainan City on March 6, 2001 Using ASTER and Formosat-2 Data

PubMed Central

Kato, Soushi; Yamaguchi, Yasushi; Liu, Cheng-Chien; Sun, Chen-Yi

2008-01-01

The urban heat island phenomenon occurs as a mixed result of anthropogenic heat discharge, decreased vegetation, and increased artificial impervious surfaces. To clarify the contribution of each factor to the urban heat island, it is necessary to evaluate the surface heat balance. Satellite remote sensing data of Tainan City, Taiwan, obtained from Terra ASTER and Formosat-2 were used to estimate surface heat balance in this study. ASTER data is suitable for analyzing heat balance because of the wide spectral range. We used Formosat-2 multispectral data to classify the land surface, which was used to interpolate some surface parameters for estimating heat fluxes. Because of the high spatial resolution of the Formosat-2 image, more roads, open spaces and small vegetation areas could be distinguished from buildings in urban areas; however, misclassifications of land cover in such areas using ASTER data would overestimate the sensible heat flux. On the other hand, the small vegetated areas detected from the Formosat-2 image slightly increased the estimation of latent heat flux. As a result, the storage heat flux derived from Formosat-2 is higher than that derived from ASTER data in most areas. From these results, we can conclude that the higher resolution land coverage map increases accuracy of the heat balance analysis. Storage heat flux occupies about 60 to 80% of the net radiation in most of the artificial surface areas in spite of their usages. Because of the homogeneity of the building roof materials, there is no contrast between the storage heat flux in business and residential areas. In sparsely vegetated urban areas, more heat is stored and latent heat is smaller than that in the forested suburbs. This result implies that density of vegetation has a significant influence in decreasing temperatures. PMID:27873856

A guide to potential soil carbon sequestration; land-use management for mitigation of greenhouse gas emissions

USGS Publications Warehouse

Markewich, H.W.; Buell, G.R.

2001-01-01

Terrestrial carbon sequestration has a potential role in reducing the recent increase in atmospheric carbon dioxide (CO2) that is, in part, contributing to global warming. Because the most stable long-term surface reservoir for carbon is the soil, changes in agriculture and forestry can potentially reduce atmospheric CO2 through increased soil-carbon storage. If local governments and regional planning agencies are to effect changes in land-use management that could mitigate the impacts of increased greenhouse gas (GHG) emissions, it is essential to know how carbon is cycled and distributed on the landscape. Only then can a cost/benefit analysis be applied to carbon sequestration as a potential land-use management tool for mitigation of GHG emissions. For the past several years, the U.S. Geological Survey (USGS) has been researching the role of terrestrial carbon in the global carbon cycle. Data from these investigations now allow the USGS to begin to (1) 'map' carbon at national, regional, and local scales; (2) calculate present carbon storage at land surface; and (3) identify those areas having the greatest potential to sequester carbon.

[Distribution characteristics of organochlorine pesticides in soil from Daiyun Mountain Range in Fujian, China].

PubMed

Qu, Cheng-Kai; Qi, Shi-Hua; Zhang, Li; Huang, Huan-Fang; Zhang, Jia-Quan; Zhang, Yuan; Yang, Dan; Liu, Hong-Xia; Chen, Wei

2013-11-01

Totally 101 typical surface soil samples were collected from Daiyun Mountain Range, and 20 compounds of OCPs were analyzed by a Ni electron capture detector (GC-ECD) to investigate the horizontal distribution and composition of organochlorine pesticides (OCPs) in the surface soil of Daiyun Mountain Range. The results showed that all OCPs were detected in the soil samples. The detection ratios of OCPs were all over 90%, except for Endrin and beta-HCH. The sum concentration of HCHs, DDTs, Endosulfan and Endosulfan sulfate, accounted for 79.51% of the total OCPs, which were considered to be the dominant OCPs in the Daiyun Mountain Range. The OCPs concentrations in the surface soils ranged from 2.56 to 465.99 ng x g(-1) with a mean value of 38.00 ng x g)(-1). Compared with other regions, the concentrations of HCHs and DDTs in this study stayed in a low pollution level. Endosulfan and Endosulfan sulfate showed a certain degree of risk in the surface soil of the study area. Source analysis showed that new input of lindane and dicofol might occur in the survey region. The historical application was the prime source of Endosulfan. The residue level of OCPs in different lands was in the following order: paddy land > vegetable land > orchard. The OCPs pollution of orchard soil was primarily due to the new input of lindane and dicofol, while the pollution of paddy land was mainly from the usage of Endosulfan.

To the National Map and beyond

USGS Publications Warehouse

Kelmelis, J.

2003-01-01

Scientific understanding, technology, and social, economic, and environmental conditions have driven a rapidly changing demand for geographic information, both digital and analog. For more than a decade, the U.S. Geological Survey (USGS) has been developing innovative partnerships with other government agencies and private industry to produce and distribute geographic information efficiently; increase activities in remote sensing to ensure ongoing monitoring of the land surface; and develop new understanding of the causes and consequences of land surface change. These activities are now contributing to a more robust set of geographic information called The National Map (TNM). The National Map is designed to provide an up-to-date, seamless, horizontally and vertically integrated set of basic digital geographic data, a frequent monitoring of changes on the land surface, and an understanding of the condition of the Earth's surface and many of the processes that shape it. The USGS has reorganized its National Mapping Program into three programs to address the continuum of scientific activities-describing (mapping), monitoring, understanding, modeling, and predicting. The Cooperative Topographic Mapping Program focuses primarily on the mapping and revision aspects of TNM. The National Map also includes results from the Land Remote Sensing and Geographic Analysis and Monitoring Programs that provide continual updates, new insights, and analytical tools. The National Map is valuable as a framework for current research, management, and operational activities. It also provides a critical framework for the development of distributed, spatially enabled decision support systems.

Insights in time dependent cross compartment sensitivities from ensemble simulations with the fully coupled subsurface-land surface-atmosphere model TerrSysMP

NASA Astrophysics Data System (ADS)

Schalge, Bernd; Rihani, Jehan; Haese, Barbara; Baroni, Gabriele; Erdal, Daniel; Haefliger, Vincent; Lange, Natascha; Neuweiler, Insa; Hendricks-Franssen, Harrie-Jan; Geppert, Gernot; Ament, Felix; Kollet, Stefan; Cirpka, Olaf; Saavedra, Pablo; Han, Xujun; Attinger, Sabine; Kunstmann, Harald; Vereecken, Harry; Simmer, Clemens

2017-04-01

Currently, an integrated approach to simulating the earth system is evolving where several compartment models are coupled to achieve the best possible physically consistent representation. We used the model TerrSysMP, which fully couples subsurface, land surface and atmosphere, in a synthetic study that mimicked the Neckar catchment in Southern Germany. A virtual reality run at a high resolution of 400m for the land surface and subsurface and 1.1km for the atmosphere was made. Ensemble runs at a lower resolution (800m for the land surface and subsurface) were also made. The ensemble was generated by varying soil and vegetation parameters and lateral atmospheric forcing among the different ensemble members in a systematic way. It was found that the ensemble runs deviated for some variables and some time periods largely from the virtual reality reference run (the reference run was not covered by the ensemble), which could be related to the different model resolutions. This was for example the case for river discharge in the summer. We also analyzed the spread of model states as function of time and found clear relations between the spread and the time of the year and weather conditions. For example, the ensemble spread of latent heat flux related to uncertain soil parameters was larger under dry soil conditions than under wet soil conditions. Another example is that the ensemble spread of atmospheric states was more influenced by uncertain soil and vegetation parameters under conditions of low air pressure gradients (in summer) than under conditions with larger air pressure gradients in winter. The analysis of the ensemble of fully coupled model simulations provided valuable insights in the dynamics of land-atmosphere feedbacks which we will further highlight in the presentation.

Bi-scale analysis of multitemporal land cover fractions for wetland vegetation mapping

NASA Astrophysics Data System (ADS)

Michishita, Ryo; Jiang, Zhiben; Gong, Peng; Xu, Bing

2012-08-01

Land cover fractions (LCFs) derived through spectral mixture analysis are useful in understanding sub-pixel information. However, few studies have been conducted on the analysis of time-series LCFs. Although multi-scale comparisons of spectral index, hard classification, and land surface temperature images have received attention, rarely have these approaches been applied to LCFs. This study compared the LCFs derived through Multiple Endmember Spectral Mixture Analysis (MESMA) using the time-series Landsat Thematic Mapper (TM) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data acquired in the Poyang Lake area, China between 2004 and 2005. Specifically, we aimed to: (1) propose an approach for optimal endmember (EM) selection in time-series MESMA; (2) understand the trends in time-series LCFs derived from the TM and MODIS data; and (3) examine the trends in the correlation between the bi-scale LCFs derived from the time-series TM and MODIS data. Our results indicated: (1) the EM spectra chosen according to the proposed hierarchical three-step approach (overall, seasonal, and individual) accurately modeled the both the TM and MODIS images; (2) green vegetation (GV) and NPV/soil/impervious surface (N/S/I) classes followed sine curve trends in the overall area, while the two water classes displayed the water level change pattern in the areas primarily covered with wetland vegetation; and (3) GV, N/S/I, and bright water classes indicated a moderately high agreement between the TM and MODIS LCFs in the whole area (adjusted R2 ⩾ 0.6). However, low levels of correlations were found in the areas primarily dominated by wetland vegetation for all land cover classes.

Reconstructed historical land cover and biophysical parameters for studies of land-atmosphere interactions within the eastern United States

USGS Publications Warehouse

Steyaert, Louis T.; Knox, R.G.

2008-01-01

Over the past 350 years, the eastern half of the United States experienced extensive land cover changes. These began with land clearing in the 1600s, continued with widespread deforestation, wetland drainage, and intensive land use by 1920, and then evolved to the present-day landscape of forest regrowth, intensive agriculture, urban expansion, and landscape fragmentation. Such changes alter biophysical properties that are key determinants of land-atmosphere interactions (water, energy, and carbon exchanges). To understand the potential implications of these land use transformations, we developed and analyzed 20-km land cover and biophysical parameter data sets for the eastern United States at 1650, 1850, 1920, and 1992 time slices. Our approach combined potential vegetation, county-level census data, soils data, resource statistics, a Landsat-derived land cover classification, and published historical information on land cover and land use. We reconstructed land use intensity maps for each time slice and characterized the land cover condition. We combined these land use data with a mutually consistent set of biophysical parameter classes, to characterize the historical diversity and distribution of land surface properties. Time series maps of land surface albedo, leaf area index, a deciduousness index, canopy height, surface roughness, and potential saturated soils in 1650, 1850, 1920, and 1992 illustrate the profound effects of land use change on biophysical properties of the land surface. Although much of the eastern forest has returned, the average biophysical parameters for recent landscapes remain markedly different from those of earlier periods. Understanding the consequences of these historical changes will require land-atmosphere interactions modeling experiments.

Hyperspectral Thermal Infrared Remote Sensing of the Land Surface and Target Identification using Airborne Interferometry

DTIC Science & Technology

2009-10-01

variational data assimilation technique are profiles of temperature, water vapour and ozone , surface temperature and spectrally varying emissivity. HOW TO...that are insensitive to the land surface because of the complexity of the land surface emissivity. We have utilised the techniques described here for...state as well as surface properties. Furthermore with by utilising a variational assimilation technique and a state of the art Numerical Weather

Internal Physical Features of a Land Surface Model Employing a Tangent Linear Model

NASA Technical Reports Server (NTRS)

Yang, Runhua; Cohn, Stephen E.; daSilva, Arlindo; Joiner, Joanna; Houser, Paul R.

1997-01-01

The Earth's land surface, including its biomass, is an integral part of the Earth's weather and climate system. Land surface heterogeneity, such as the type and amount of vegetative covering., has a profound effect on local weather variability and therefore on regional variations of the global climate. Surface conditions affect local weather and climate through a number of mechanisms. First, they determine the re-distribution of the net radiative energy received at the surface, through the atmosphere, from the sun. A certain fraction of this energy increases the surface ground temperature, another warms the near-surface atmosphere, and the rest evaporates surface water, which in turn creates clouds and causes precipitation. Second, they determine how much rainfall and snowmelt can be stored in the soil and how much instead runs off into waterways. Finally, surface conditions influence the near-surface concentration and distribution of greenhouse gases such as carbon dioxide. The processes through which these mechanisms interact with the atmosphere can be modeled mathematically, to within some degree of uncertainty, on the basis of underlying physical principles. Such a land surface model provides predictive capability for surface variables including ground temperature, surface humidity, and soil moisture and temperature. This information is important for agriculture and industry, as well as for addressing fundamental scientific questions concerning global and local climate change. In this study we apply a methodology known as tangent linear modeling to help us understand more deeply, the behavior of the Mosaic land surface model, a model that has been developed over the past several years at NASA/GSFC. This methodology allows us to examine, directly and quantitatively, the dependence of prediction errors in land surface variables upon different vegetation conditions. The work also highlights the importance of accurate soil moisture information. Although surface variables are predicted imperfectly due to inherent uncertainties in the modeling process, our study suggests how satellite observations can be combined with the model, through land surface data assimilation, to improve their prediction.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cowan, Nicolas B.; Strait, Talia E., E-mail: n-cowan@northwestern.edu

Planned missions will spatially resolve temperate terrestrial planets from their host star. Although reflected light from such a planet encodes information about its surface, it has not been shown how to establish surface characteristics of a planet without assuming known surfaces to begin with. We present a reanalysis of disk-integrated, time-resolved, multiband photometry of Earth obtained by the Deep Impact spacecraft as part of the EPOXI Mission of Opportunity. We extract reflectance spectra of clouds, ocean, and land without a priori knowledge of the numbers or colors of these surfaces. We show that the inverse problem of extracting surface spectramore » from such data is a novel and extreme instance of spectral unmixing, a well-studied problem in remote sensing. Principal component analysis is used to determine an appropriate number of model surfaces with which to interpret the data. Shrink-wrapping a simplex to the color excursions of the planet yields a conservative estimate of the planet's endmember spectra. The resulting surface maps are unphysical, however, requiring negative or larger-than-unity surface coverage at certain locations. Our ''rotational unmixing'' supersedes the endmember analysis by simultaneously solving for the surface spectra and their geographical distributions on the planet, under the assumption of diffuse reflection and known viewing geometry. We use a Markov Chain Monte Carlo to determine best-fit parameters and their uncertainties. The resulting albedo spectra are similar to clouds, ocean, and land seen through a Rayleigh-scattering atmosphere. This study suggests that future direct-imaging efforts could identify and map unknown surfaces and clouds on exoplanets.« less

Flood Hazard Assessment of the coastal lowland in the Kujukuri Plain of Chiba Prefecture, Japan, using GIS and multicriteria decision analysis

NASA Astrophysics Data System (ADS)

CHEN, Huali; Tokunaga, Tomochika; Ito, Yuka; Sawamukai, Marie

2014-05-01

Floods, the most common natural disaster in the world, cause serious loss of life and economic damage. Flood is one of the disasters in the coastal lowland along the Kujukuri Plain, Chiba Prefecture, Japan. Many natural and human activities have changed the surface environment of the Plain. These include agricultural development, urban and industrial development, change of the drainage patterns of the land surface, deposition and/or erosion of the river valleys, and so on. In addition, wide spread occurrence of land subsidence has been caused by the abstraction of natural gas dissolved in groundwater. The locations of the groundwater extraction include nearby the coast, and it may increase the flood risk. Hence, it is very important to evaluate flood hazard by taking into account the temporal change of land elevation caused by land subsidence, and to develop hazard maps for protecting surface environment and land-use planning. Multicriteria decision analysis (MCDA) provides methodology and techniques for analyzing complex decision problems, which often involve incommensurable data or criteria. Also, Geographical Information System (GIS) is the powerful tool since it manages large amount of spatial data involved in MCDA. The purpose of this study is to present a flood hazard model using MCDA techniques with GIS support in a region where primary data are scare. The model incorporates six parameters: river system, topography, land-use, flood control project, passing flood from coast, and precipitation. Main data sources used are 10 meter resolution topography data, airborne laser scanning data, leveling data, Landsat-TM data, two 1:30,000 scale river watershed map, and precipitation data from precipitation observation stations around the study area. River system map was created by merging the river order, the line density, and the river sink point density layers. Land-use data were derived from Landsat-TM images. A final hazard map for 2004, as an example, was obtained using an algorithm that combines factors in weighted linear combinations. The assignment of the weight/rank values and their analysis were realized by the application of the Analytic Hierarchy Process (AHP) method. This study is the preliminary work to investigate the flood hazard at the Kujukuri Plain. Flood hazard map of the other years will be analyzed to investigate the temporal change of the flood hazard area, and more data will be collected and added to improve the assessment.

Estimation of effective aerodynamic roughness with altimeter measurements

NASA Technical Reports Server (NTRS)

Menenti, M.; Ritchie, J. C.

1992-01-01

A new method is presented for estimating the aerodynamic roughness length of heterogeneous land surfaces and complex landscapes using elevation measurements performed with an airborne laser altimeter and the Seasat radar altimeter. Land surface structure is characterized at increasing length scales by considering three basic landscape elements: (1) partial to complete canopies of herbaceous vegetation; (2) sparse obstacles (e.g., shrubs and trees); and (3) local relief. Measured parameters of land surface geometry are combined to obtain an effective aerodynamic roughness length which parameterizes the total atmosphere-land surface stress.

Land cover mapping, fire regeneration, and scaling studies in the Canadian boreal forest with 1 km AVHRR and Landsat TM data

NASA Astrophysics Data System (ADS)

Steyaert, L. T.; Hall, F. G.; Loveland, T. R.

1997-12-01

A multitemporal 1 km advanced very high resolution radiometer (AVHRR) land cover analysis approach was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. The land cover classification was developed by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly normalized difference vegetation index (NDVI) image composites (April-September 1992). Quantitative areal proportions of the major boreal forest components were determined for a 821 km × 619 km region, ranging from the southern grasslands-boreal forest ecotone to the northern boreal transitional forest. The boreal wetlands (mostly lowland black spruce, tamarack, mosses, fens, and bogs) occupied approximately 33% of the region, while lakes accounted for another 13%. Upland mixed coniferous-deciduous forests represented 23% of the ecosystem. A SW-NE productivity gradient across the region is manifested by three levels of tree stand density for both the boreal wetland conifer and the mixed forest classes, which are generally aligned with isopleths of regional growing degree days. Approximately 30% of the region was directly affected by fire disturbance within the preceding 30-35 years, especially in the Canadian Shield Zone where large fire-regeneration patterns contribute to the heterogeneous boreal landscape. Intercomparisons with land cover classifications derived from 30-m Landsat Thematic Mapper (TM) data provided important insights into the relative accuracy of the 1 km AVHRR land cover classification. Primarily due to the multitemporal NDVI image compositing process, the 1 km AVHRR land cover classes have an effective spatial resolution in the 3-4 km range; therefore fens, bogs, small water bodies, and small patches of dry jack pine cannot be resolved within the wet conifer mosaic. Major differences in the 1-km AVHRR and 30-m Landsat TM-derived land cover classes are most likely due to differences in the spatial resolution of the data sets. In general, the 1 km AVHRR land cover classes are vegetation mosaics consisting of mixed combinations of the Landsat classes. Detailed mapping of the global boreal forest with this approach will benefit from algorithms for cloud screening and to atmospherically correct reflectance data for both aerosol and water vapor effects. We believe that this 1 km AVHRR land cover analysis provides new and useful information for regional water, energy, carbon, and trace gases studies in BOREAS, especially given the significant spatial variability in land cover type and associated biophysical land cover parameters (e.g., albedo, leaf area index, FPAR, and surface roughness). Multiresolution land cover comparisons (30 m, l km, and 100 km grid cells) also illustrated how heterogeneous landscape patterns are represented in land cover maps with differing spatial scales and provided insights on the requirements and challenges for parameterizing landscape heterogeneity as part of land surface process research.

Land cover mapping, fire regeneration, and scaling studies in the Canadian boreal forest with 1 km AVHRR and Landsat TM data

USGS Publications Warehouse

Steyaert, L.T.; Hall, F.G.; Loveland, Thomas R.

1997-01-01

A multitemporal 1 km advanced very high resolution radiometer (AVHRR) land cover analysis approach was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. The land cover classification was developed by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly normalized difference vegetation index (NDVI) image composites (April-September 1992). Quantitative areal proportions of the major boreal forest components were determined for a 821 km ?? 619 km region, ranging from the southern grasslands-boreal forest ecotone to the northern boreal transitional forest. The boreal wetlands (mostly lowland black spruce, tamarack, mosses, fens, and bogs) occupied approximately 33% of the region, while lakes accounted for another 13%. Upland mixed coniferous-deciduous forests represented 23% of the ecosystem. A SW-NE productivity gradient across the region is manifested by three levels of tree stand density for both the boreal wetland conifer and the mixed forest classes, which are generally aligned with isopleths of regional growing degree days. Approximately 30% of the region was directly affected by fire disturbance within the preceding 30-35 years, especially in the Canadian Shield Zone where large fire-regeneration patterns contribute to the heterogeneous boreal landscape. Intercomparisons with land cover classifications derived from 30-m Landsat Thematic Mapper (TM) data provided important insights into the relative accuracy of the 1 km AVHRR land cover classification. Primarily due to the multitemporal NDVI image compositing process, the 1 km AVHRR land cover classes have an effective spatial resolution in the 3-4 km range; therefore fens, bogs, small water bodies, and small patches of dry jack pine cannot be resolved within the wet conifer mosaic. Major differences in the 1-km AVHRR and 30-m Landsat TM-derived land cover classes are most likely due to differences in the spatial resolution of the data sets. In general, the 1 km AVHRR land cover classes are vegetation mosaics consisting of mixed combinations of the Landsat classes. Detailed mapping of the global boreal forest with this approach will benefit from algorithms for cloud screening and to atmospherically correct reflectance data for both aerosol and water vapor effects. We believe that this 1 km AVHRR land cover analysis provides new and useful information for regional water, energy, carbon, and trace gases studies in BOREAS, especially given the significant spatial variability in land cover type and associated biophysical land cover parameters (e.g., albedo, leaf area index, FPAR, and surface roughness). Multiresolution land cover comparisons (30 m, 1 km, and 100 km grid cells) also illustrated how heterogeneous landscape patterns are represented in land cover maps with differing spatial scales and provided insights on the requirements and challenges for parameterizing landscape heterogeneity as part of land surface process research.

Estimating the extent of impervious surfaces and turf grass across large regions

USGS Publications Warehouse

Claggett, Peter; Irani, Frederick M.; Thompson, Renee L.

2013-01-01

The ability of researchers to accurately assess the extent of impervious and pervious developed surfaces, e.g., turf grass, using land-cover data derived from Landsat satellite imagery in the Chesapeake Bay watershed is limited due to the resolution of the data and systematic discrepancies between developed land-cover classes, surface mines, forests, and farmlands. Estimates of impervious surface and turf grass area in the Mid-Atlantic, United States that were based on 2006 Landsat-derived land-cover data were substantially lower than estimates based on more authoritative and independent sources. New estimates of impervious surfaces and turf grass area derived using land-cover data combined with ancillary information on roads, housing units, surface mines, and sampled estimates of road width and residential impervious area were up to 57 and 45% higher than estimates based strictly on land-cover data. These new estimates closely approximate estimates derived from authoritative and independent sources in developed counties.

Exploitation of multi-temporal Earth Observation imagery for monitoring land cover change in mining sites

NASA Astrophysics Data System (ADS)

Petropoulos, G.; Partsinevelos, P.; Mitraka, Z.

2012-04-01

Surface mining has been shown to cause intensive environmental degradation in terms of landscape, vegetation and biological communities. Nowadays, the commercial availability of remote sensing imagery at high spatiotemporal scales, has improved dramatically our ability to monitor surface mining activity and evaluate its impact on the environment and society. In this study we investigate the potential use of Landsat TM imagery combined with diverse classification techniques, namely artificial neural networks and support vector machines for delineating mining exploration and assessing its effect on vegetation in various surface mining sites in the Greek island of Milos. Assessment of the mining impact in the study area is validated through the analysis of available QuickBird imagery acquired nearly concurrently to the TM overpasses. Results indicate the capability of the TM sensor combined with the image analysis applied herein as a potential economically viable solution to provide rapidly and at regular time intervals information on mining activity and its impact to the local environment. KEYWORDS: mining environmental impact, remote sensing, image classification, change detection, land reclamation, support vector machines, neural networks

Geomorphic degradations on the surface of venus: an analysis of venera 9 and venera 10 data.

PubMed

Florensky, C P; Ronca, L B; Basilevsky, A T

1977-05-20

On the basis of the physical and chemical measurements made on the surface of Venus and transmitted back to Earth by the Soviet automatic landers Venera 9 and Venera 10, a geomorphically inactive environment should be expected. An analysis of the television photographs reveals, however, that at least two processes of degradation occur. One operates on a scale of decimeters to meters and is responsible for the fracturing of a layered source rock and the subsequent downslope movement of the fragments. Mass-wasting, perhaps activated by venusian quakes or by unknown geological processes, is likely to be the agent. Another geomorphic degradation process occurs on the scale of a centimeter or less and is responsible for the rounding of edges and the pitting of rock surfaces. The agents of this process are not known, but atmospheric action, perhaps in connection with volcanic episodes, may be the cause. From a geomorphic point of view, the landscape of the Venera 9 landing site can be considered young and that of the Venera 10 landing site, mature.

Augmentation of Water Resources Potential and Cropping Intensification Through Watershed Programs.

PubMed

Mondal, Biswajit; Singh, Alka; Singh, S D; Kalra, B S; Samal, P; Sinha, M K; Ramajayam, D; Kumar, Suresh

2018-02-01

  This paper presents the biophysical impact of various interventions made under watershed development programs, in terms of the creation of additional water resources, and resultant changes in land use and cropping patterns in the Bundelkhand region of Madhya Pradesh State, India. Both primary and secondary data gathered from randomly selected watersheds and their corresponding control villages were used in this study. Analysis revealed that emphasis was given primarily to the creation of water resources potential during implementation of the programs, which led to augmentation of surface and groundwater availability for both irrigation and non-agricultural purposes. In addition, other land based interventions for soil and moisture conservation, plantation activities, and so forth, were taken up on both arable and nonarable land, which helped to improve land slope and land use, cropping pattern, agricultural productivity, and vegetation cover.

Simulation of the Onset of the Southeast Asian Monsoon during 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Wang, Yansen; Tao, W.-K.; Lau, K.-M.; Wetzel, Peter J.

2004-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated by coupling a mesoscale atmospheric model (MM5) and a detailed, land surface model, PLACE (the Parameterization for Land-Atmosphere-Cloud Exchange). The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The control simulation with the PLACE land surface model and variable sea surface temperature captured the basic signatures of the monsoon onset processes and associated rainfall statistics. Sensitivity tests indicated that simulations were sigmficantly improved by including the PLACE land surface model. The mechanism by which the land surface processes affect the moisture transport and the convection during the onset of the southeast Asian monsoon were analyzed. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation: the southwest low-level flow over the Indo-china peninsula and the northern, cold frontal intrusion from southern China. The surface sensible and latent heat fluxes modified the low-level temperature distribution and gradient, and therefore the low-level wind due to the thermal wind effect. The more realistic forcing of the sensible and latent heat fluxes from the detailed, land surface model improved the low-level wind simulation apd associated moisture transport and convection.

Simulation of the Onset of the Southeast Asian Monsoon during 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Wang, Yansen; Tao, W.-K.; Lau, K.-M.; Wetzel, Peter J.

2004-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated by coupling a mesoscale atmospheric model (MM5) and a detailed, land surface model, PLACE (the Parameterization for Land-Atmosphere-Cloud Exchange). The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The control simulation with the PLACE land surface model and variable sea surface temperature captured the basic signatures of the monsoon onset processes and associated rainfall statistics. Sensitivity tests indicated that simulations were significantly improved by including the PLACE land surface model. The mechanism by which the land surface processes affect the moisture transport and the convection during the onset of the southeast Asian monsoon were analyzed. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation: the southwest low-level flow over the Indo-China peninsula and the northern, cold frontal intrusion from southern China. The surface sensible and latent heat fluxes modified the low-level temperature distribution and merit, and therefore the low-level wind due to the thermal wind effect. The more realistic forcing of the sensible and latent heat fluxes from the detailed, land surface model improved the low-level wind simulation and associated moisture transport and convection.

Hazard Detection Software for Lunar Landing

NASA Technical Reports Server (NTRS)

Huertas, Andres; Johnson, Andrew E.; Werner, Robert A.; Montgomery, James F.

2011-01-01

The Autonomous Landing and Hazard Avoidance Technology (ALHAT) Project is developing a system for safe and precise manned lunar landing that involves novel sensors, but also specific algorithms. ALHAT has selected imaging LIDAR (light detection and ranging) as the sensing modality for onboard hazard detection because imaging LIDARs can rapidly generate direct measurements of the lunar surface elevation from high altitude. Then, starting with the LIDAR-based Hazard Detection and Avoidance (HDA) algorithm developed for Mars Landing, JPL has developed a mature set of HDA software for the manned lunar landing problem. Landing hazards exist everywhere on the Moon, and many of the more desirable landing sites are near the most hazardous terrain, so HDA is needed to autonomously and safely land payloads over much of the lunar surface. The HDA requirements used in the ALHAT project are to detect hazards that are 0.3 m tall or higher and slopes that are 5 or greater. Steep slopes, rocks, cliffs, and gullies are all hazards for landing and, by computing the local slope and roughness in an elevation map, all of these hazards can be detected. The algorithm in this innovation is used to measure slope and roughness hazards. In addition to detecting these hazards, the HDA capability also is able to find a safe landing site free of these hazards for a lunar lander with diameter .15 m over most of the lunar surface. This software includes an implementation of the HDA algorithm, software for generating simulated lunar terrain maps for testing, hazard detection performance analysis tools, and associated documentation. The HDA software has been deployed to Langley Research Center and integrated into the POST II Monte Carlo simulation environment. The high-fidelity Monte Carlo simulations determine the required ground spacing between LIDAR samples (ground sample distances) and the noise on the LIDAR range measurement. This simulation has also been used to determine the effect of viewing on hazard detection performance. The software has also been deployed to Johnson Space Center and integrated into the ALHAT real-time Hardware-in-the-Loop testbed.

DasPy 1.0 - the Open Source Multivariate Land Data Assimilation Framework in combination with the Community Land Model 4.5

NASA Astrophysics Data System (ADS)

Han, X.; Li, X.; He, G.; Kumbhar, P.; Montzka, C.; Kollet, S.; Miyoshi, T.; Rosolem, R.; Zhang, Y.; Vereecken, H.; Franssen, H.-J. H.

2015-08-01

Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. Multivariate data assimilation refers to the simultaneous assimilation of observation data from multiple model state variables into a simulation model. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. We developed an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with the C++ and Fortran programming languages. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be introduced by perturbed atmospheric forcing data, and represented by perturbed soil and vegetation parameters and model initial conditions. The Community Land Model (CLM) was integrated as the model operator. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. The Community Microwave Emission Modelling platform (CMEM), COsmic-ray Soil Moisture Interaction Code (COSMIC) and the Two-Source Formulation (TSF) were integrated as observation operators for the assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy has been evaluated in several assimilation studies of neutron count intensity (soil moisture), L-band brightness temperature and land surface temperature. DasPy is parallelized using the hybrid Message Passing Interface and Open Multi-Processing techniques. All the input and output data flows are organized efficiently using the commonly used NetCDF file format. Online 1-D and 2-D visualization of data assimilation results is also implemented to facilitate the post simulation analysis. In summary, DasPy is a ready to use open source parallel multivariate land data assimilation framework.

Iceland: Eyjafjallajökull Volcano

Atmospheric Science Data Center

2013-04-17

... erroneous impression that they are below the land surface. A quantitative computer analysis is necessary to separate out wind and height. ... MD. The MISR data were obtained from the NASA Langley Research Center Atmospheric Science Data Center in Hampton, VA. Image ...

Sensitivity of June Near-Surface Temperatures and Precipitation in the Eastern United States to Historical Land Cover Changes Since European Settlement

NASA Technical Reports Server (NTRS)

Strack, John E.; Pielke, Roger A.; Steyaert, Louis T.; Knox, Robert G.

2008-01-01

Land cover changes alter the near surface weather and climate. Changes in land surface properties such as albedo, roughness length, stomatal resistance, and leaf area index alter the surface energy balance, leading to differences in near surface temperatures. This study utilized a newly developed land cover data set for the eastern United States to examine the influence of historical land cover change on June temperatures and precipitation. The new data set contains representations of the land cover and associated biophysical parameters for 1650, 1850, 1920, and 1992, capturing the clearing of the forest and the expansion of agriculture over the eastern United States from 1650 to the early twentieth century and the subsequent forest regrowth. The data set also includes the inferred distribution of potentially water-saturated soils at each time slice for use in the sensitivity tests. The Regional Atmospheric Modeling System, equipped with the Land Ecosystem-Atmosphere Feedback (LEAF-2) land surface parameterization, was used to simulate the weather of June 1996 using the 1992, 1920, 1850, and 1650 land cover representations. The results suggest that changes in surface roughness and stomatal resistance have caused present-day maximum and minimum temperatures in the eastern United States to warm by about 0.3 C and 0.4 C, respectively, when compared to values in 1650. In contrast, the maximum temperatures have remained about the same, while the minimums have cooled by about 0.1 C when compared to 1920. Little change in precipitation was found.

Sensitivity of June near‐surface temperatures and precipitation in the eastern United States to historical land cover changes since European settlement

USGS Publications Warehouse

Strack, John E.; Pielke, Roger A.; Steyaert, Louis T.; Knox, Robert G.

2008-01-01

Land cover changes alter the near surface weather and climate. Changes in land surface properties such as albedo, roughness length, stomatal resistance, and leaf area index alter the surface energy balance, leading to differences in near surface temperatures. This study utilized a newly developed land cover data set for the eastern United States to examine the influence of historical land cover change on June temperatures and precipitation. The new data set contains representations of the land cover and associated biophysical parameters for 1650, 1850, 1920, and 1992, capturing the clearing of the forest and the expansion of agriculture over the eastern United States from 1650 to the early twentieth century and the subsequent forest regrowth. The data set also includes the inferred distribution of potentially water‐saturated soils at each time slice for use in the sensitivity tests. The Regional Atmospheric Modeling System, equipped with the Land Ecosystem‐Atmosphere Feedback (LEAF‐2) land surface parameterization, was used to simulate the weather of June 1996 using the 1992, 1920, 1850, and 1650 land cover representations. The results suggest that changes in surface roughness and stomatal resistance have caused present‐day maximum and minimum temperatures in the eastern United States to warm by about 0.3°C and 0.4°C, respectively, when compared to values in 1650. In contrast, the maximum temperatures have remained about the same, while the minimums have cooled by about 0.1°C when compared to 1920. Little change in precipitation was found.

Application of ERTS-A imagery to fracture related mine safety hazards in the coal mining industry

NASA Technical Reports Server (NTRS)

Wier, C. E.; Wobber, F. J. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The most important result to date is the demonstration of the special value of repetitive ERTS-1 multiband coverage for detecting previously unknown fracture lineaments despite the presence of a deep glacial overburden. The Illinois Basin is largely covered with glacial drift and few rock outcrops are present. A contribution to the geological understanding of Illinois and Indiana has been made. Analysis of ERTS-1 imagery has provided useful information to the State of Indiana concerning the surface mined lands. The contrast between healthy vegetation and bare ground as imaged by Band 7 is sharp and substantial detail can be obtained concerning the extent of disturbed lands, associated water bodies, large haul roads, and extent of mined lands revegetation. Preliminary results of analysis suggest a reasonable correlation between image-detected fractures and mine roof fall accidents for a few areas investigated. ERTS-1 applications to surface mining operations appear probable, but further investigations are required. The likelihood of applying ERTS-1 derived fracture data to improve coal mine safety in the entire Illinois Basin is suggested from studies conducted in Indiana.

Feedback attribution of the land-sea warming contrast in a global warming simulation of the NCAR CCSM4

DOE PAGES

Sejas, Sergio A.; Albert, Oriene S.; Cai, Ming; ...

2014-12-02

One of the salient features in both observations and climate simulations is a stronger land warming than sea. This paper provides a quantitative understanding of the main processes that contribute to the land-sea warming asymmetry in a global warming simulation of the NCAR CCSM4. The CO 2 forcing alone warms the surface nearly the same for both land and sea, suggesting that feedbacks are responsible for the warming contrast. Our analysis on one hand confirms that the principal contributor to the above-unity land-to-sea warming ratio is the evaporation feedback; on the other hand the results indicate that the sensible heatmore » flux feedback has the largest land-sea warming difference that favors a greater ocean than land warming. Furthermore, the results uniquely highlight the importance of other feedbacks in establishing the above-unity land-to-sea warming ratio. Particularly, the SW cloud feedback and the ocean heat storage in the transient response are key contributors to the greater warming over land than sea.« less

Feedback attribution of the land-sea warming contrast in a global warming simulation of the NCAR CCSM4

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sejas, Sergio A.; Albert, Oriene S.; Cai, Ming

One of the salient features in both observations and climate simulations is a stronger land warming than sea. This paper provides a quantitative understanding of the main processes that contribute to the land-sea warming asymmetry in a global warming simulation of the NCAR CCSM4. The CO 2 forcing alone warms the surface nearly the same for both land and sea, suggesting that feedbacks are responsible for the warming contrast. Our analysis on one hand confirms that the principal contributor to the above-unity land-to-sea warming ratio is the evaporation feedback; on the other hand the results indicate that the sensible heatmore » flux feedback has the largest land-sea warming difference that favors a greater ocean than land warming. Furthermore, the results uniquely highlight the importance of other feedbacks in establishing the above-unity land-to-sea warming ratio. Particularly, the SW cloud feedback and the ocean heat storage in the transient response are key contributors to the greater warming over land than sea.« less

Modelling surface runoff and water fluxes over contrasted soils in pastoral Sahel: evaluation of the ALMIP2 land surface models over the Gourma region in Mali

USDA-ARS?s Scientific Manuscript database

Land surface processes play an important role in West African monsoon variability and land –atmosphere coupling has been shown to be particularly important in the Sahel. In addition, the evolution of hydrological systems in this region, and particularly the increase of surface water and runoff coeff...

Analysis of Multiple Precipitation Products and Preliminary Assessment of Their Impact on Global Land Data Assimilation System (GLDAS) Land Surface States

NASA Technical Reports Server (NTRS)

Gottschalck, Jon; Meng, Jesse; Rodel, Matt; Houser, paul

2005-01-01

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. NASA's Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type). Precipitation is arguably the most important input to LSMs. Many precipitation datasets have been produced using satellite and rain gauge observations and weather forecast models. In this study, seven different global precipitation datasets were evaluated over the United States, where dense rain gauge networks contribute to reliable precipitation maps. We then used the seven datasets as inputs to GLDAS simulations, so that we could diagnose their impacts on output stocks and fluxes of water. In terms of totals, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) had the closest agreement with the US rain gauge dataset for all seasons except winter. The CMAP precipitation was also the most closely correlated in time with the rain gauge data during spring, fall, and winter, while the satellitebased estimates performed best in summer. The GLDAS simulations revealed that modeled soil moisture is highly sensitive to precipitation, with differences in spring and summer as large as 45% depending on the choice of precipitation input.

Surface and Atmospheric Contributions to Passive Microwave Brightness Temperatures for Falling Snow Events

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail; Johnson, Benjamin T.

2011-01-01

Physically based passive microwave precipitation retrieval algorithms require a set of relationships between satellite -observed brightness temperatures (TBs) and the physical state of the underlying atmosphere and surface. These relationships are nonlinear, such that inversions are ill ]posed especially over variable land surfaces. In order to elucidate these relationships, this work presents a theoretical analysis using TB weighting functions to quantify the percentage influence of the TB resulting from absorption, emission, and/or reflection from the surface, as well as from frozen hydrometeors in clouds, from atmospheric water vapor, and from other contributors. The percentage analysis was also compared to Jacobians. The results are presented for frequencies from 10 to 874 GHz, for individual snow profiles, and for averages over three cloud-resolving model simulations of falling snow. The bulk structure (e.g., ice water path and cloud depth) of the underlying cloud scene was found to affect the resultant TB and percentages, producing different values for blizzard, lake effect, and synoptic snow events. The slant path at a 53 viewing angle increases the hydrometeor contributions relative to nadir viewing channels. Jacobians provide the magnitude and direction of change in the TB values due to a change in the underlying scene; however, the percentage analysis provides detailed information on how that change affected contributions to the TB from the surface, hydrometeors, and water vapor. The TB percentage information presented in this paper provides information about the relative contributions to the TB and supplies key pieces of information required to develop and improve precipitation retrievals over land surfaces.

Landsat Evapotranspiration for Historical Field-scale Water Use (1984-2015) in the Upper Rio Grande River Basin

NASA Astrophysics Data System (ADS)

Senay, G. B.; Schauer, M.; Singh, R. K.; Friedrichs, M.

2017-12-01

Field-scale water use maps derived from evapotranspiration (ET) can characterize water use patterns and the impacts of water management decisions. This project generated historical (1984-2015) Landsat-based ET maps for the entire Upper Rio Grande basin which makes this one of the largest regions in the United States with remotely sensed historical ET at Landsat resolution. More than 10,000 Landsat images spanning 32 years were processed using the Operational Simplified Surface Energy Balance (SSEBop) model which integrates weather data and remotely sensed images to estimate monthly and annual ET. Time-series analysis focused on three water-intensive study areas within the basin: the San Luis Valley in Colorado, irrigated fields along the Rio Grande River near Albuquerque, NM, and irrigated fields near Las Cruces, NM. Preliminary analysis suggests land use changes result in declining water use in irrigated areas of the basin which corresponds with increases in land surface temperatures. Time-series analysis of water use patterns at multiple temporal and spatial scales demonstrates the impact of water management decisions on the availability of water in the basin. Comparisons with cropland data from the USDA (NASS CDL) demonstrate how water use for particular crop types changes over time in response to land use changes and shifts in water management. This study illustrates a useful application of "Big Data" earth observation science for quantifying impacts of climate and land use changes on water availability within the United States as well as applications in planning water resource allocation, managing water rights, and sustaining agricultural production in the Upper Rio Grande basin.

The Use of CASES-97 Observations to Assess and Parameterize the Impact of Land-Surface Heterogeneity on Area-Average Surface Heat Fluxes for Large-Scale Coupled Atmosphere-Hydrology Models

NASA Technical Reports Server (NTRS)

Chen, Fei; Yates, David; LeMone, Margaret

2001-01-01

To understand the effects of land-surface heterogeneity and the interactions between the land-surface and the planetary boundary layer at different scales, we develop a multiscale data set. This data set, based on the Cooperative Atmosphere-Surface Exchange Study (CASES97) observations, includes atmospheric, surface, and sub-surface observations obtained from a dense observation network covering a large region on the order of 100 km. We use this data set to drive three land-surface models (LSMs) to generate multi-scale (with three resolutions of 1, 5, and 10 kilometers) gridded surface heat flux maps for the CASES area. Upon validating these flux maps with measurements from surface station and aircraft, we utilize them to investigate several approaches for estimating the area-integrated surface heat flux for the CASES97 domain of 71x74 square kilometers, which is crucial for land surface model development/validation and area water and energy budget studies. This research is aimed at understanding the relative contribution of random turbulence versus organized mesoscale circulations to the area-integrated surface flux at the scale of 100 kilometers, and identifying the most important effective parameters for characterizing the subgrid-scale variability for large-scale atmosphere-hydrology models.

Impact of soil moisture and winter wheat height from the Loess Plateau in Northwest China on surface spectral albedo

NASA Astrophysics Data System (ADS)

Li, Zhenchao; Yang, Jiaxi; Gao, Xiaoqing; Zheng, Zhiyuan; Yu, Ye; Hou, Xuhong; Wei, Zhigang

2018-02-01

The understanding of surface spectral radiation and reflected radiation characteristics of different surfaces in different climate zones aids in the interpretation of regional surface energy transfers and the development of land surface models. This study analysed surface spectral radiation variations and corresponding surface albedo characteristics at different wavelengths as well as the relationship between 5-cm soil moisture and surface albedo on typical sunny days during the winter wheat growth period. The analysis was conducted using observational Loess Plateau winter wheat data from 2015. The results show that the ratio of atmospheric downward radiation to global radiation on typical sunny days is highest for near-infrared wavelengths, followed by visible wavelengths and ultraviolet wavelengths, with values of 57.3, 38.7 and 4.0%, respectively. The ratio of reflected spectral radiation to global radiation varies based on land surface type. The visible radiation reflected by vegetated surfaces is far less than that reflected by bare ground, with surface albedos of 0.045 and 0.27, respectively. Thus, vegetated surfaces absorb more visible radiation than bare ground. The atmospheric downward spectral radiation to global radiation diurnal variation ratios vary for near-infrared wavelengths versus visible and ultraviolet wavelengths on typical sunny days. The near-infrared wavelengths ratio is higher in the morning and evening and lower at noon. The visible and ultraviolet wavelengths ratios are lower in the morning and evening and higher at noon. Visible and ultraviolet wavelength surface albedo is affected by 5-cm soil moisture, demonstrating a significant negative correlation. Excluding near-infrared wavelengths, correlations between surface albedo and 5-cm soil moisture pass the 99% confidence test at each wavelength. The correlation with 5-cm soil moisture is more significant at shorter wavelengths. However, this study obtained surface spectral radiation characteristics that were affected by land surface vegetation coverage as well as by soil physical properties.

Coupling of Community Land Model with RegCM4 for Indian Summer Monsoon Simulation

NASA Astrophysics Data System (ADS)

Maurya, R. K. S.; Sinha, P.; Mohanty, M. R.; Mohanty, U. C.

2017-11-01

Three land surface schemes available in the regional climate model RegCM4 have been examined to understand the coupling between land and atmosphere for simulation of the Indian summer monsoon rainfall. The RegCM4 is coupled with biosphere-atmosphere transfer scheme (BATS) and the National Center for Atmospheric Research (NCAR) Community Land Model versions 3.5, and 4.5 (CLM3.5 and CLM4.5, respectively) and model performance is evaluated for recent drought (2009) and normal (2011) monsoon years. The CLM4.5 has a more distinct category of surface and it is capable of representing better the land surface characteristics. National Centers for Environmental Prediction (NCEP) and Department of Energy (DOE) reanalysis version 2 (NNRP2) datasets are considered as driving force to conduct the experiments for the Indian monsoon region (30°E-120°E; 30°S-50°N). The NNRP2 and India Meteorological Department (IMD) gridded precipitation data are used for verification analysis. The results indicate that RegCM4 simulations with CLM4.5 (RegCM4-CLM4.5) and CLM3.5 (RegCM4-CLM3.5) surface temperature (at 2 ms) have very low warm biases ( 1 °C), while with BATS (RegCM4-BATS) has a cold bias of about 1-3 °C in peninsular India and some parts of central India. Warm bias in the RegCM4-BATS is observed over the Indo-Gangetic plain and northwest India and the bias is more for the deficit year as compared to the normal year. However, the warm (cold) bias is less in RegCM4-CLM4.5 than other schemes for both the deficit and normal years. The model-simulated maximum (minimum) surface temperature and sensible heat flux at the surface are positively (negatively) biased in all the schemes; however, the bias is higher in RegCM4-BATS and lower in RegCM4-CLM4.5 over India. All the land surface schemes overestimated the precipitation in peninsular India and underestimated in central parts of India for both the years; however, the biases are less in RegCM4-CLM4.5 and more in RegCM4-CLM3.5 and RegCM4-BATS. During both the years, BATS scheme in RegCM4 failed to represent low precipitation over the leeward than windward side of the Western Ghats, while CLM schemes (both versions) in the RegCM4 are able to depict this feature. In the topographic regions, such as the Western Ghats, northeast India and state of Jammu and Kashmir, RegCM4-BATS overestimates the rainfall amount with higher bias. Statistical analysis using anomaly correlation coefficient, root mean square error, equitable threat score, and critical success index confirms that RegCM4-CLM performs better than RegCM4-BATS in the simulation of the Indian summer monsoon.

Estimating daily surface NO2 concentrations from satellite data - a case study over Hong Kong using land use regression models

NASA Astrophysics Data System (ADS)

Anand, Jasdeep S.; Monks, Paul S.

2017-07-01

Land use regression (LUR) models have been used in epidemiology to determine the fine-scale spatial variation in air pollutants such as nitrogen dioxide (NO2) in cities and larger regions. However, they are often limited in their temporal resolution, which may potentially be rectified by employing the synoptic coverage provided by satellite measurements. In this work a mixed-effects LUR model is developed to model daily surface NO2 concentrations over the Hong Kong SAR during the period 2005-2015. In situ measurements from the Hong Kong Air Quality Monitoring Network, along with tropospheric vertical column density (VCD) data from the OMI, GOME-2A, and SCIAMACHY satellite instruments were combined with fine-scale land use parameters to provide the spatiotemporal information necessary to predict daily surface concentrations. Cross-validation with the in situ data shows that the mixed-effects LUR model using OMI data has a high predictive power (adj. R2 = 0. 84), especially when compared with surface concentrations derived using the MACC-II reanalysis model dataset (adj. R2 = 0. 11). Time series analysis shows no statistically significant trend in NO2 concentrations during 2005-2015, despite a reported decline in NOx emissions. This study demonstrates the utility in combining satellite data with LUR models to derive daily maps of ambient surface NO2 for use in exposure studies.

Protein Chips Compatible with MALDI Mass Spectrometry Prepared by Ambient Ion Landing.

PubMed

Pompach, Petr; Benada, Oldřich; Rosůlek, Michal; Darebná, Petra; Hausner, Jiří; Růžička, Viktor; Volný, Michael; Novák, Petr

2016-09-06

We present a technology that allows the preparation of matrix-assisted laser desorption/ionization (MALDI)-compatible protein chips by ambient ion landing of proteins and successive utilization of the resulting protein chips for the development of bioanalytical assays. These assays are based on the interaction between the immobilized protein and the sampled analyte directly on the protein chip and subsequent in situ analysis by MALDI mass spectrometry. The electrosprayed proteins are immobilized on dry metal and metal oxide surfaces, which are nonreactive under normal conditions. The ion landing of electrosprayed protein molecules is performed under atmospheric pressure by an automated ion landing apparatus that can manufacture protein chips with a predefined array of sample positions or any other geometry of choice. The protein chips prepared by this technique are fully compatible with MALDI ionization because the metal-based substrates are conductive and durable enough to be used directly as MALDI plates. Compared to other materials, the nonreactive surfaces show minimal nonspecific interactions with chemical species in the investigated sample and are thus an ideal substrate for selective protein chips. Three types of protein chips were used in this report to demonstrate the bioanalytical applications of ambient ion landing. The protein chips with immobilized proteolytic enzymes showed the usefulness for fast in situ peptide MALDI sequencing; the lectin-based protein chips showed the ability to enrich glycopeptides from complex mixtures with subsequent MALDI analysis, and the protein chips with immobilized antibodies were used for a novel immunoMALDI workflow that allowed the enrichment of antigens from the serum followed by highly specific MALDI detection.

Mapping Urban Ecosystem Services Using High Resolution Aerial Photography

NASA Astrophysics Data System (ADS)

Pilant, A. N.; Neale, A.; Wilhelm, D.

2010-12-01

Ecosystem services (ES) are the many life-sustaining benefits we receive from nature: e.g., clean air and water, food and fiber, cultural-aesthetic-recreational benefits, pollination and flood control. The ES concept is emerging as a means of integrating complex environmental and economic information to support informed environmental decision making. The US EPA is developing a web-based National Atlas of Ecosystem Services, with a component for urban ecosystems. Currently, the only wall-to-wall, national scale land cover data suitable for this analysis is the National Land Cover Data (NLCD) at 30 m spatial resolution with 5 and 10 year updates. However, aerial photography is acquired at higher spatial resolution (0.5-3 m) and more frequently (1-5 years, typically) for most urban areas. Land cover was mapped in Raleigh, NC using freely available USDA National Agricultural Imagery Program (NAIP) with 1 m ground sample distance to test the suitability of aerial photography for urban ES analysis. Automated feature extraction techniques were used to extract five land cover classes, and an accuracy assessment was performed using standard techniques. Results will be presented that demonstrate applications to mapping ES in urban environments: greenways, corridors, fragmentation, habitat, impervious surfaces, dark and light pavement (urban heat island). Automated feature extraction results mapped over NAIP color aerial photograph. At this scale, we can look at land cover and related ecosystem services at the 2-10 m scale. Small features such as individual trees and sidewalks are visible and mappable. Classified aerial photo of Downtown Raleigh NC Red: impervious surface Dark Green: trees Light Green: grass Tan: soil

Using the FORE-SCE model to project land-cover change in the southeastern United States

USGS Publications Warehouse

Sohl, Terry; Sayler, Kristi L.

2008-01-01

A wide variety of ecological applications require spatially explicit current and projected land-use and land-cover data. The southeastern United States has experienced massive land-use change since European settlement and continues to experience extremely high rates of forest cutting, significant urban development, and changes in agricultural land use. Forest-cover patterns and structure are projected to change dramatically in the southeastern United States in the next 50 years due to population growth and demand for wood products [Wear, D.N., Greis, J.G. (Eds.), 2002. Southern Forest Resource Assessment. General Technical Report SRS-53. U.S. Department of Agriculture, Forest Service, Southern Research Station, Asheville, NC, 635 pp]. Along with our climate partners, we are examining the potential effects of southeastern U.S. land-cover change on regional climate. The U.S. Geological Survey (USGS) Land Cover Trends project is analyzing contemporary (1973-2000) land-cover change in the conterminous United States, providing ecoregion-by-ecoregion estimates of the rates of change, descriptive transition matrices, and changes in landscape metrics. The FORecasting SCEnarios of future land-cover (FORE-SCE) model used Land Cover Trends data and theoretical, statistical, and deterministic modeling techniques to project future land-cover change through 2050 for the southeastern United States. Prescriptions for future proportions of land cover for this application were provided by ecoregion-based extrapolations of historical change. Logistic regression was used to develop relationships between suspected drivers of land-cover change and land cover, resulting in the development of probability-of-occurrence surfaces for each unique land-cover type. Forest stand age was initially established with Forest Inventory and Analysis (FIA) data and tracked through model iterations. The spatial allocation procedure placed patches of new land cover on the landscape until the scenario prescriptions were met, using measured Land Cover Trends data to guide patch characteristics and the probability surfaces to guide placement. The approach provides an efficient method for extrapolating historical land-cover trends and is amenable to the incorporation of more detailed and focused studies for the establishment of scenario prescriptions.

Landing Characteristics of the Apollo Spacecraft with Deployed Heat Shield Impact Attenuation Systems

NASA Technical Reports Server (NTRS)

Stubbs, Sandy M.

1965-01-01

An experimental investigation was made to determine the landing characteristics of a 1/4-scale dynamic model of the Apollo spacecraft command module using two different active (heat shield deployed prior to landing) landing systems for impact attenuation. One landing system (configuration 1) consisted of six hydraulic struts and eight crushable honeycomb struts. The other landing system (configuration 2), consisted of four hydraulic struts and six strain straps. Tests made on water and the hard clay-gravel composite landing surfaces simulated parachute letdown (vertical) velocities of 23 ft/sec (7.0 m/s) (full scale). Landings made on the sand landing surface simulated vertical velocities of 30 ft/sec (9.1 m/s). Horizontal velocities of from 0 to 50 ft/sec (15 m/s) were simulated. Landing attitudes ranged from -30'degrees to 20 degrees, and the roll attitudes were O degrees, 90 degrees, and 180 degrees. For configuration 1, maximum normal accelerations at the vehicle center of gravity for landings on water, sand, and the hard clay-gravel composite surface were 9g, 20g, and 18g, respectively. The maximum normal center-of-gravity acceleration for configuration 2 which was landed only on the hard clay-gravel landing surface was approximately 19g. Accelerations for configuration 2 were generally equal to or lower than accelerations for configuration 1 and normal.

Lunar Soil Erosion Physics for Landing Rockets on the Moon

NASA Technical Reports Server (NTRS)

Clegg, Ryan N.; Metzger, Philip T.; Huff, Stephen; Roberson, Luke B.

2008-01-01

To develop a lunar outpost, we must understand the blowing of soil during launch and landing of the new Altair Lander. For example, the Apollo 12 Lunar Module landed approximately 165 meters from the deactivated Surveyor Ill spacecraft, scouring its surfaces and creating numerous tiny pits. Based on simulations and video analysis from the Apollo missions, blowing lunar soil particles have velocities up to 2000 m/s at low ejection angles relative to the horizon, reach an apogee higher than the orbiting Command and Service Module, and travel nearly the circumference of the Moon [1-3]. The low ejection angle and high velocity are concerns for the lunar outpost.

Impact of Optimized land Surface Parameters on the Land-Atmosphere Coupling in WRF Simulations of Dry and Wet Extremes

NASA Technical Reports Server (NTRS)

Kumar, Sujay; Santanello, Joseph; Peters-Lidard, Christa; Harrison, Ken

2011-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty module in NASA's Land Information System (LIS-OPT), whereby parameter sets are calibrated in the Noah land surface model and classified according to the land cover and soil type mapping of the observations and the full domain. The impact of the calibrated parameters on the a) spin up of land surface states used as initial conditions, and b) heat and moisture fluxes of the coupled (LIS-WRF) simulations are then assessed in terms of ambient weather, PBL budgets, and precipitation along with L-A coupling diagnostics. In addition, the sensitivity of this approach to the period of calibration (dry, wet, normal) is investigated. Finally, tradeoffs of computational tractability and scientific validity (e.g.,. relating to the representation of the spatial dependence of parameters) and the feasibility of calibrating to multiple observational datasets are also discussed.

LS3MIP (v1.0) Contribution to CMIP6: The Land Surface, Snow and Soil Moisture Model Intercomparison Project Aims, Setup and Expected Outcome.

NASA Technical Reports Server (NTRS)

Van Den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; Seneviratne, Sonia I.; Derksen, Chris; Oki, Taikan; Douville, Herve; Colin, Jeanne; Ducharne, Agnes; Cheruy, Frederique;

LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

DOE PAGES

van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; ...

2016-08-24

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less

LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

DOE Office of Scientific and Technical Information (OSTI.GOV)

van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less

Systematic Biases of Present-day's Land Surface Air Temperature and Precipitation and Associated Tendency of Future Projection in the Asia Monsoon of the CMIP5 models

NASA Astrophysics Data System (ADS)

Ose, T.

2016-12-01

Seasonally varying land surface air temperature (SAT) is basically responsible for the occurrence of the Asia Monsoon precipitation whereas the precipitation may play more important roles in the appearance and variability of the Asia Monsoon circulations. A simple and basic analysis on model biases of land SAT simulations over the Eurasian Continent is done to find necessary improvements of land surface treatment in the models, their relationship with model precipitation and their influences to future projections. Specifically, the Empirical Orthogonal Function (EOF) analysis is applied to land SATs of the CMIP5 present-day's simulation (the June-July-August average during 1975-1999) ensemble. Associated biases of precipitation and other Asia Monsoon elements are obtained by the regression method onto the obtained EOF coefficients. The first EOF is the SAT bias over the dry region of the Eurasia. Positive deviations of the 1st EOF coefficient indicate northwestward shift of the Asia Monsoon System; northwestward (or inner-continent-ward) shifts of precipitation, the Tibetan High, the low-level jet, the Pacific High and so on. The second EOF is the SAT bias over the northeast Eurasia. It is interesting that warmer land SAT bias over the northeast Asia is related to more wet condition over East Asia like in early summer; southward shift of westerly jet and precipitation band in East Asia. The third one indicates the SAT bias over the Eurasian region between the 1st and 2nd EOF SAT regions. However, this EOF may be characterized by the accompanied model precipitation bias over the subtropical Northwest Pacific like in late summer; northeastward shift of upper westerly jet in the eastern Asia and the weak Pacific High in the subtropical Northwest Pacific. The most intrigued feature is a connection of the 3rd EOF with the future change of SAT in the extra-tropical Northern Hemisphere in the CMIP5 projections. This fact may indicate that precipitation climatology in the Asia Monsoon is an important factor in the heat budget of the northern summer in the future change as well as the present-day simulation.

A protocol for validating Land Surface Temperature from Sentinel-3

NASA Astrophysics Data System (ADS)

Ghent, D.

2015-12-01

One of the main objectives of the Sentinel-3 mission is to measure sea- and land-surface temperature with high-end accuracy and reliability in support of environmental and climate monitoring in an operational context. Calibration and validation are thus key criteria for operationalization within the framework of the Sentinel-3 Mission Performance Centre (S3MPC).Land surface temperature (LST) has a long heritage of satellite observations which have facilitated our understanding of land surface and climate change processes, such as desertification, urbanization, deforestation and land/atmosphere coupling. These observations have been acquired from a variety of satellite instruments on platforms in both low-earth orbit and in geostationary orbit. Retrieval accuracy can be a challenge though; surface emissivities can be highly variable owing to the heterogeneity of the land, and atmospheric effects caused by the presence of aerosols and by water vapour absorption can give a bias to the underlying LST. As such, a rigorous validation is critical in order to assess the quality of the data and the associated uncertainties. The Sentinel-3 Cal-Val Plan for evaluating the level-2 SL_2_LST product builds on an established validation protocol for satellite-based LST. This set of guidelines provides a standardized framework for structuring LST validation activities, and is rapidly gaining international recognition. The protocol introduces a four-pronged approach which can be summarised thus: i) in situ validation where ground-based observations are available; ii) radiance-based validation over sites that are homogeneous in emissivity; iii) intercomparison with retrievals from other satellite sensors; iv) time-series analysis to identify artefacts on an interannual time-scale. This multi-dimensional approach is a necessary requirement for assessing the performance of the LST algorithm for SLSTR which is designed around biome-based coefficients, thus emphasizing the importance of non-traditional forms of validation such as radiance-based techniques. Here we present examples of the application of the protocol to data produced within the ESA DUE GlobTemperature Project. The lessons learnt here are helping to fine-tune the methodology in preparation for Sentinel-3 commissioning.

43 CFR 1610.7-1 - Designation of areas unsuitable for surface mining.

Code of Federal Regulations, 2011 CFR

2011-10-01

... surface mining. 1610.7-1 Section 1610.7-1 Public Lands: Interior Regulations Relating to Public Lands... mining. (a)(1) The planning process is the chief process by which public land is reviewed to assess whether there are areas unsuitable for all or certain types of surface coal mining operations under...

Simulating the biogeochemical and biogeophysical impacts of transient land cover change and wood harvest in the Community Climate System Model (CCSM4) from 1850 to 2100

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lawrence, Peter J.; Feddema, Johannes J.; Bonan, Gordon B.

To assess the climate impacts of historical and projected land cover change and land use in the Community Climate System Model (CCSM4) we have developed new time series of transient Community Land Model (CLM4) Plant Functional Type (PFT) parameters and wood harvest parameters. The new parameters capture the dynamics of the Coupled Model Inter-comparison Project phase 5 (CMIP5) land cover change and wood harvest trajectories for the historical period from 1850 to 2005, and for the four Representative Concentration Pathways (RCP) periods from 2006 to 2100. Analysis of the biogeochemical impacts of land cover change in CCSM4 with the parametersmore » found the model produced an historical cumulative land use flux of 148.4 PgC from 1850 to 2005, which was in good agreement with other global estimates of around 156 PgC for the same period. The biogeophysical impacts of only applying the transient land cover change parameters in CCSM4 were cooling of the near surface atmospheric over land by -0.1OC, through increased surface albedo and reduced shortwave radiation absorption. When combined with other transient climate forcings, the higher albedo from land cover change was overwhelmed at global scales by decreases in snow albedo from black carbon deposition and from high latitude warming. At regional scales however the land cover change forcing persisted resulting in reduced warming, with the biggest impacts in eastern North America. The future CCSM4 RCP simulations showed that the CLM4 transient PFT and wood harvest parameters could be used to represent a wide range of human land cover change and land use scenarios. Furthermore, these simulations ranged from the RCP 4.5 reforestation scenario that was able to draw down 82.6 PgC from the atmosphere, to the RCP 8.5 wide scale deforestation scenario that released 171.6 PgC to the atmosphere.« less

Socially optimal drainage system and agricultural biodiversity: a case study for Finnish landscape.

PubMed

Saikkonen, Liisa; Herzon, Irina; Ollikainen, Markku; Lankoski, Jussi

2014-12-15

This paper examines the socially optimal drainage choice (surface/subsurface) for agricultural crop cultivation in a landscape with different land qualities (fertilities) when private profits and nutrient runoff damages are taken into account. We also study the measurable social costs to increase biodiversity by surface drainage when the locations of the surface-drained areas in a landscape affect the provided biodiversity. We develop a general theoretical model and apply it to empirical data from Finnish agriculture. We find that for low land qualities the measurable social returns are higher to surface drainage than to subsurface drainage, and that the profitability of subsurface drainage increases along with land quality. The measurable social costs to increase biodiversity by surface drainage under low land qualities are negative. For higher land qualities, these costs depend on the land quality and on the biodiversity impacts. Biodiversity conservation plans for agricultural landscapes should focus on supporting surface drainage systems in areas where the measurable social costs to increase biodiversity are negative or lowest. Copyright © 2014 Elsevier Ltd. All rights reserved.

Photogrammetric analysis of horizon panoramas: The Pathfinder landing site in Viking orbiter images

USGS Publications Warehouse

Oberst, J.; Jaumann, R.; Zeitler, W.; Hauber, E.; Kuschel, M.; Parker, T.; Golombek, M.; Malin, M.; Soderblom, L.

1999-01-01

Tiepoint measurements, block adjustment techniques, and sunrise/sunset pictures were used to obtain precise pointing data with respect to north for a set of 33 IMP horizon images. Azimuth angles for five prominent topographic features seen at the horizon were measured and correlated with locations of these features in Viking orbiter images. Based on this analysis, the Pathfinder line/sample coordinates in two raw Viking images were determined with approximate errors of 1 pixel, or 40 m. Identification of the Pathfinder location in orbit imagery yields geological context for surface studies of the landing site. Furthermore, the precise determination of coordinates in images together with the known planet-fixed coordinates of the lander make the Pathfinder landing site the most important anchor point in current control point networks of Mars. Copyright 1999 by the American Geophysical Union.

Evapotranspiration from combined reflected solar and emitted terrestrial radiation - Preliminary FIFE results from AVHRR data

NASA Technical Reports Server (NTRS)

Goward, S. N.; Hope, A. S.

1989-01-01

The relation between remotely sensed spectral vegetation indices and thermal IR measurements is studied. Land surface evapotranspiration is evaluated based on this relationship. Analysis of the AVHRR data, obtained in Kansas in 1987, reveal a strong correlation between the spectral vegetation indices and surface temperature and this relation covaries with surface moisture conditions. It is noted that the relation between remotely sensed measurements of canopy green foliage and surface temperature is useful for examining variations in the interface thermal inertia and energy balance Bowen ratio.

Effect of land model ensemble versus coupled model ensemble on the simulation of precipitation climatology and variability

NASA Astrophysics Data System (ADS)

Wei, Jiangfeng; Dirmeyer, Paul A.; Yang, Zong-Liang; Chen, Haishan

2017-10-01

Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.