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 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.

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.

Mesoscale Convective Systems in SCSMEX: Simulated by a Regional Climate Model and a Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Wang, Y.; Qian, I.; Lau, W.; Shie, C.-L.; Starr, David (Technical Monitor)

2002-01-01

A Regional Land-Atmosphere Climate Simulation (RELACS) System is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes, in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water and energy cycles in Indo-China/ South China Sea (SCS)/China, N. America and S. America. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Goddard Parameterization for Land-Atmosphere-C loud Exchange (PLACE) land surface model. PLACE allows for the effects of vegetation, and thus important physical processes such as evapotranspiration and interception are included. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate the atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. RELACS has been used to simulate the onset of the South China Sea Monsoon in 1986, 1997 and 1998. Sensitivity tests on various land surface models, cumulus parameterization schemes (CPSs), sea surface temperature (SST) variations and midlatitude influences have been performed. These tests have indicated that the land surface model has a major impact on the circulation over the S. China Sea. CPSs can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. RELACS has also been used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during 1998. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. Also, the Goddard Cumulus Ensemble (GCE) model which allows for realistic moist processes as well as explicit interactions between cloud and radiation, and cloud and surface processes will be used to simulate convective systems associated with the onset of the South China Sea Monsoon in 1998. The GCE model also includes the same PLACE and radiation scheme used in the RELACS. A detailed comparison between the results from the GCE model and RELACS will be performed.

Mesoscale Convective Systems in SCSMEX: Simulated by a Regional Climate Model and a Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Wang, Y.; Lau, W.; Jia, Y.; Johnson, D.; Shie, C.-L.; Einaudi, Franco (Technical Monitor)

2001-01-01

A Regional Land-Atmosphere Climate Simulation (RELACS) System is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes, in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water and energy cycles in Indo-China/South China Sea (SCS)/China, North America and South America. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Goddard Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model, PLACE allows for the effect A vegetation, and thus important physical processes such as evapotranspiration and interception are included. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate the atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. RELACS has been used to simulate the onset of the South China Sea Monsoon in 1986, 1991 and 1998. Sensitivity tests on various land surface models, cumulus parameterization schemes (CPSs), sea surface temperature (SST) variations and midlatitude influences have been performed. These tests have indicated that the land surface model has a major impact on the circulation over the South China Sea. CPSs can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. RELACS has also been used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during 1998. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. Also, the Goddard Cumulus Ensemble (GCE) model which allows for realistic moist processes as well as explicit interactions between cloud and radiation, and cloud and surface processes will be used to simulate convective systems associated with the onset of the South China Sea Monsoon in 1998. The GCE model also includes the same PLACE and radiation scheme used in the RELACS. A detailed comparison between the results from the GCE model and RELACS will be performed.

An Earth Observation Land Data Assimilation System for Data from Multiple Wavelength Domains: Water and Energy Balance Components

NASA Astrophysics Data System (ADS)

Quaife, T. L.; Davenport, I. J.; Lines, E.; Styles, J.; Lewis, P.; Gurney, R. J.

2012-12-01

Satellite observations offer a spatially and temporally synoptic data source for constraining models of land surface processes, but exploitation of these data for such purposes has been largely ad-hoc to date. In part this is because traditional land surface models, and hence most land surface data assimilation schemes, have tended to focus on a specific component of the land surface problem; typically either surface fluxes of water and energy or biogeochemical cycles such as carbon and nitrogen. Furthermore the assimilation of satellite data into such models tends to be restricted to a single wavelength domain, for example passive microwave, thermal or optical, depending on the problem at hand. The next generation of land surface schemes, such as the Joint UK Land Environment Simulator (JULES) and the US Community Land Model (CLM) represent a broader range of processes but at the expense of increasing overall model complexity and in some cases reducing the level of detail in specific processes to accommodate this. Typically, the level of physical detail used to represent the interaction of electromagnetic radiation with the surface is not sufficient to enable prediction of intrinsic satellite observations (reflectance, brightness temperature and so on) and consequently these are not assimilated directly into the models. A seemingly attractive alternative is to assimilate high-level products derived from satellite observations but these are often only superficially related to the corresponding variables in land surface models due to conflicting assumptions between the two. This poster describes the water and energy balance modeling components of a project funded by the European Space Agency to develop a data assimilation scheme for the land surface and observation operators to translate between models and the intrinsic observations acquired by satellite missions. The rationale behind the design of the underlying process model is to represent the physics of the water and energy balance in as parsimonious manner as possible, using a force-restore approach, but describing the physics of electromagnetic radiation scattering at the surface sufficiently well that it is possible to assimilate the intrinsic observations made by remote sensing instruments. In this manner the initial configuration of the resulting scheme will be able to make optimal use of available satellite observations at arbitrary wavelengths and geometries. Model complexity can then be built up from this point whilst ensuring consistency with satellite observations.

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.

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.

Sensitivity of land surface modeling to parameters: An uncertainty quantification method applied to the Community Land Model

NASA Astrophysics Data System (ADS)

Ricciuto, D. M.; Mei, R.; Mao, J.; Hoffman, F. M.; Kumar, J.

2015-12-01

Uncertainties in land parameters could have important impacts on simulated water and energy fluxes and land surface states, which will consequently affect atmospheric and biogeochemical processes. Therefore, quantification of such parameter uncertainties using a land surface model is the first step towards better understanding of predictive uncertainty in Earth system models. In this study, we applied a random-sampling, high-dimensional model representation (RS-HDMR) method to analyze the sensitivity of simulated photosynthesis, surface energy fluxes and surface hydrological components to selected land parameters in version 4.5 of the Community Land Model (CLM4.5). Because of the large computational expense of conducting ensembles of global gridded model simulations, we used the results of a previous cluster analysis to select one thousand representative land grid cells for simulation. Plant functional type (PFT)-specific uniform prior ranges for land parameters were determined using expert opinion and literature survey, and samples were generated with a quasi-Monte Carlo approach-Sobol sequence. Preliminary analysis of 1024 simulations suggested that four PFT-dependent parameters (including slope of the conductance-photosynthesis relationship, specific leaf area at canopy top, leaf C:N ratio and fraction of leaf N in RuBisco) are the dominant sensitive parameters for photosynthesis, surface energy and water fluxes across most PFTs, but with varying importance rankings. On the other hand, for surface ans sub-surface runoff, PFT-independent parameters, such as the depth-dependent decay factors for runoff, play more important roles than the previous four PFT-dependent parameters. Further analysis by conditioning the results on different seasons and years are being conducted to provide guidance on how climate variability and change might affect such sensitivity. This is the first step toward coupled simulations including biogeochemical processes, atmospheric processes or both to determine the full range of sensitivity of Earth system modeling to land-surface parameters. This can facilitate sampling strategies in measurement campaigns targeted at reduction of climate modeling uncertainties and can also provide guidance on land parameter calibration for simulation optimization.

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...

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.

Archiving, processing, and disseminating ASTER products at the USGS EROS Data Center

USGS Publications Warehouse

Jones, B.; Tolk, B.; ,

2002-01-01

The U.S. Geological Survey EROS Data Center archives, processes, and disseminates Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data products. The ASTER instrument is one of five sensors onboard the Earth Observing System's Terra satellite launched December 18, 1999. ASTER collects broad spectral coverage with high spatial resolution at near infrared, shortwave infrared, and thermal infrared wavelengths with ground resolutions of 15, 30, and 90 meters, respectively. The ASTER data are used in many ways to understand local and regional earth-surface processes. Applications include land-surface climatology, volcanology, hazards monitoring, geology, agronomy, land cover change, and hydrology. The ASTER data are available for purchase from the ASTER Ground Data System in Japan and from the Land Processes Distributed Active Archive Center in the United States, which receives level 1A and level 1B data from Japan on a routine basis. These products are archived and made available to the public within 48 hours of receipt. The level 1A and level 1B data are used to generate higher level products that include routine and on-demand decorrelation stretch, brightness temperature at the sensor, emissivity, surface reflectance, surface kinetic temperature, surface radiance, polar surface and cloud classification, and digital elevation models. This paper describes the processes and procedures used to archive, process, and disseminate standard and on-demand higher level ASTER products at the Land Processes Distributed Active Archive Center.

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 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.

Validation of landsurface processes in the AMIP models

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

Phillips, T J

The Atmospheric Model Intercomparison Project (AMIP) is a commonly accepted protocol for testing the performance of the world's atmospheric general circulation models (AGCMs) under common specifications of radiative forcings (in solar constant and carbon dioxide concentration) and observed ocean boundary conditions (Gates 1992, Gates et al. 1999). From the standpoint of landsurface specialists, the AMIP affords an opportunity to investigate the behaviors of a wide variety of land-surface schemes (LSS) that are coupled to their ''native'' AGCMs (Phillips et al. 1995, Phillips 1999). In principle, therefore, the AMIP permits consideration of an overarching question: ''To what extent does an AGCM'smore » performance in simulating continental climate depend on the representations of land-surface processes by the embedded LSS?'' There are, of course, some formidable obstacles to satisfactorily addressing this question. First, there is the dilemna of how to effectively validate simulation performance, given the present dearth of global land-surface data sets. Even if this data problem were to be alleviated, some inherent methodological difficulties would remain: in the context of the AMIP, it is not possible to validate a given LSS per se, since the associated land-surface climate simulation is a product of the coupled AGCM/LSS system. Moreover, aside from the intrinsic differences in LSS across the AMIP models, the varied representations of land-surface characteristics (e.g. vegetation properties, surface albedos and roughnesses, etc.) and related variations in land-surface forcings further complicate such an attribution process. Nevertheless, it may be possible to develop validation methodologies/statistics that are sufficiently penetrating to reveal ''signatures'' of particular ISS representations (e.g. ''bucket'' vs more complex parameterizations of hydrology) in the AMIP land-surface simulations.« less

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

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

[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.

Diagnosing the Nature of Land-Atmosphere Coupling: A Case Study of Dry/Wet Extremes in the U. S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Santanello, Joseph A. Jr.; Peters-Lidard, Christa D.; Kennedy, Aaron; Kumar, Sujay V.

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address model deficiencies, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land- PBL coupling at the process-level. In this paper, a diagnosis of the nature and impacts of local land-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of 2006 and 2007 in the U.S. Southern Great Plains. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are applied to the dry/wet regimes exhibited in this region, and in the process a thorough evaluation of nine different land-PBL scheme couplings is conducted under the umbrella of a high-resolution regional modeling testbed. Results show that the sign and magnitude of errors in land surface energy balance components are sensitive to the choice of land surface model, regime type, and running mode. In addition, LoCo diagnostics show that the sensitivity of L-A coupling is stronger towards the land during dry conditions, while the PBL scheme coupling becomes more important during the wet regime. Results also demonstrate how LoCo diagnostics can be applied to any modeling system (e.g. reanalysis products) in the context of their integrated impacts on the process-chain connecting the land surface to the PBL and in support of hydrological anomalies.

Diagnosing the Nature of Land-Atmosphere Coupling: A Case Study of Dry/Wet Extremes in the U.S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kennedy, Aaron; Kumar, Sujay V.

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address model deficiencies, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process level. In this paper, a diagnosis of the nature and impacts of local land-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of 2006 and 2007 in the U.S. southern Great Plains. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation is applied to the dry/wet regimes exhibited in this region, and in the process, a thorough evaluation of nine different land-PBL scheme couplings is conducted under the umbrella of a high-resolution regional modeling test bed. Results show that the sign and magnitude of errors in land surface energy balance components are sensitive to the choice of land surface model, regime type, and running mode. In addition, LoCo diagnostics show that the sensitivity of L-A coupling is stronger toward the land during dry conditions, while the PBL scheme coupling becomes more important during the wet regime. Results also demonstrate how LoCo diagnostics can be applied to any modeling system (e.g., reanalysis products) in the context of their integrated impacts on the process chain connecting the land surface to the PBL and in support of hydrological anomalies.

Effects of anthropogenic groundwater exploitation on land surface processes: A case study of the Haihe River Basin, Northern China

NASA Astrophysics Data System (ADS)

Xie, Z.; Zou, J.; Qin, P.; Sun, Q.

2014-12-01

In this study, we incorporated a groundwater exploitation scheme into the land surface model CLM3.5 to investigate the effects of the anthropogenic exploitation of groundwater on land surface processes in a river basin. Simulations of the Haihe River Basin in northern China were conducted for the years 1965-2000 using the model. A control simulation without exploitation and three exploitation simulations with different water demands derived from socioeconomic data related to the Basin were conducted. The results showed that groundwater exploitation for human activities resulted in increased wetting and cooling effects at the land surface and reduced groundwater storage. A lowering of the groundwater table, increased upper soil moisture, reduced 2 m air temperature, and enhanced latent heat flux were detected by the end of the simulated period, and the changes at the land surface were related linearly to the water demands. To determine the possible responses of the land surface processes in extreme cases (i.e., in which the exploitation process either continued or ceased), additional hypothetical simulations for the coming 200 years with constant climate forcing were conducted, regardless of changes in climate. The simulations revealed that the local groundwater storage on the plains could not contend with high-intensity exploitation for long if the exploitation process continues at the current rate. Changes attributable to groundwater exploitation reached extreme values and then weakened within decades with the depletion of groundwater resources and the exploitation process will therefore cease. However, if exploitation is stopped completely to allow groundwater to recover, drying and warming effects, such as increased temperature, reduced soil moisture, and reduced total runoff, would occur in the Basin within the early decades of the simulation period. The effects of exploitation will then gradually disappear, and the land surface variables will approach the natural state and stabilize at different rates. Simulations were also conducted for cases in which exploitation either continues or ceases using future climate scenario outputs from a general circulation model. The resulting trends were almost the same as those of the simulations with constant climate forcing.

DEVELOPMENT OF A LAND-SURFACE MODEL PART I: APPLICATION IN A MESOSCALE METEOROLOGY MODEL

EPA Science Inventory

Parameterization of land-surface processes and consideration of surface inhomogeneities are very important to mesoscale meteorological modeling applications, especially those that provide information for air quality modeling. To provide crucial, reliable information on the diurn...

Soil-geomorphic significance of land surface characteristics in an arid mountain range, Mojave Desert, USA

USGS Publications Warehouse

Hirmas, D.R.; Graham, R.C.; Kendrick, K.J.

2011-01-01

Mountains comprise an extensive and visually prominent portion of the landscape in the Mojave Desert, California. Landform surface properties influence the role these mountains have in geomorphic processes such as dust flux and surface hydrology across the region. The primary goal of this study was to describe and quantify land surface properties of arid-mountain landforms as a step toward unraveling the role these properties have in soil-geomorphic processes. As part of a larger soil-geomorphic study, four major landform types were identified within the southern Fry Mountains in the southwestern Mojave Desert on the basis of topography and landscape position: mountaintop, mountainflank, mountainflat (intra-range low-relief surface), and mountainbase. A suite of rock, vegetation, and morphometric land surface characteristic variables was measured at each of 65 locations across the study area, which included an associated piedmont and playa. Our findings show that despite the variation within types, landforms have distinct land surface properties that likely control soil-geomorphic processes. We hypothesize that surface expression influences a feedback process at this site where water transports sediment to low lying areas on the landscape and wind carries dust and soluble salts to the mountains where they are washed between rocks, incorporated into the soil, and retained as relatively long-term storage. Recent land-based video and satellite photographs of the dust cloud emanating from the Sierra Cucapá Mountains in response to the 7.2-magnitude earthquake near Mexicali, Mexico, support the hypothesis that these landforms are massive repositories of dust.

Understanding the biological underpinnings of ecohydrological processes

NASA Astrophysics Data System (ADS)

Huxman, T. E.; Scott, R. L.; Barron-Gafford, G. A.; Hamerlynck, E. P.; Jenerette, D.; Tissue, D. T.; Breshears, D. D.; Saleska, S. R.

2012-12-01

Climate change presents a challenge for predicting ecosystem response, as multiple factors drive both the physical and life processes happening on the land surface and their interactions result in a complex, evolving coupled system. For example, changes in surface temperature and precipitation influence near-surface hydrology through impacts on system energy balance, affecting a range of physical processes. These changes in the salient features of the environment affect biological processes and elicit responses along the hierarchy of life (biochemistry to community composition). Many of these structural or process changes can alter patterns of soil water-use and influence land surface characteristics that affect local climate. Of the many features that affect our ability to predict the future dynamics of ecosystems, it is this hierarchical response of life that creates substantial complexity. Advances in the ability to predict or understand aspects of demography help describe thresholds in coupled ecohydrological system. Disentangling the physical and biological features that underlie land surface dynamics following disturbance are allowing a better understanding of the partitioning of water in the time-course of recovery. Better predicting the timing of phenology and key seasonal events allow for a more accurate description of the full functional response of the land surface to climate. In addition, explicitly considering the hierarchical structural features of life are helping to describe complex time-dependent behavior in ecosystems. However, despite this progress, we have yet to build an ability to fully account for the generalization of the main features of living systems into models that can describe ecohydrological processes, especially acclimation, assembly and adaptation. This is unfortunate, given that many key ecosystem services are functions of these coupled co-evolutionary processes. To date, both the lack of controlled measurements and experimentation has precluded determination of sufficient theoretical development. Understanding the land-surface response and feedback to climate change requires a mechanistic understanding of the coupling of ecological and hydrological processes and an expansion of theory from the life sciences to appropriately contribute to the broader Earth system science goal.

Large-scale experimental technology with remote sensing in land surface hydrology and meteorology

NASA Technical Reports Server (NTRS)

Brutsaert, Wilfried; Schmugge, Thomas J.; Sellers, Piers J.; Hall, Forrest G.

1988-01-01

Two field experiments to study atmospheric and land surface processes and their interactions are summarized. The Hydrologic-Atmospheric Pilot Experiment, which tested techniques for measuring evaporation, soil moisture storage, and runoff at scales of about 100 km, was conducted over a 100 X 100 km area in France from mid-1985 to early 1987. The first International Satellite Land Surface Climatology Program field experiment was conducted in 1987 to develop and use relationships between current satellite measurements and hydrologic, climatic, and biophysical variables at the earth's surface and to validate these relationships with ground truth. This experiment also validated surface parameterization methods for simulation models that describe surface processes from the scale of vegetation leaves up to scales appropriate to satellite remote sensing.

The NASA-Goddard Multi-Scale Modeling Framework - Land Information System: Global Land/atmosphere Interaction with Resolved Convection

NASA Technical Reports Server (NTRS)

Mohr, Karen Irene; Tao, Wei-Kuo; Chern, Jiun-Dar; Kumar, Sujay V.; Peters-Lidard, Christa D.

2013-01-01

The present generation of general circulation models (GCM) use parameterized cumulus schemes and run at hydrostatic grid resolutions. To improve the representation of cloud-scale moist processes and landeatmosphere interactions, a global, Multi-scale Modeling Framework (MMF) coupled to the Land Information System (LIS) has been developed at NASA-Goddard Space Flight Center. The MMFeLIS has three components, a finite-volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4), a 2D cloud-resolving model (Goddard Cumulus Ensemble, GCE), and the LIS, representing the large-scale atmospheric circulation, cloud processes, and land surface processes, respectively. The non-hydrostatic GCE model replaces the single-column cumulus parameterization of fvGCM. The model grid is composed of an array of fvGCM gridcells each with a series of embedded GCE models. A horizontal coupling strategy, GCE4fvGCM4Coupler4LIS, offered significant computational efficiency, with the scalability and I/O capabilities of LIS permitting landeatmosphere interactions at cloud-scale. Global simulations of 2007e2008 and comparisons to observations and reanalysis products were conducted. Using two different versions of the same land surface model but the same initial conditions, divergence in regional, synoptic-scale surface pressure patterns emerged within two weeks. The sensitivity of largescale circulations to land surface model physics revealed significant functional value to using a scalable, multi-model land surface modeling system in global weather and climate prediction.

Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

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

Yu, Miao; Wang, Guiling; Chen, Haishan

Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, amore » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. Moreover, these uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to be seen in the Northern Hemisphere high latitudes. Including representation of vegetation dynamics is expected to further amplify the model-related uncertainties in projected future changes in surface water and heat fluxes as well as soil moisture content. This is especially the case in the high latitudes of the Northern Hemisphere (e.g., northwestern North America and central North Asia) where the projected vegetation changes are uncertain and in the Tropics (e.g., the Amazon and Congo Basins) where dense vegetation exists. Finally, findings from this study highlight the importance of improving land surface model parameterizations related to soil and snow processes, as well as the importance of improving the accuracy of dynamic vegetation models.« less

Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

DOE PAGES

Yu, Miao; Wang, Guiling; Chen, Haishan

2016-03-01

Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, amore » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. Moreover, these uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to be seen in the Northern Hemisphere high latitudes. Including representation of vegetation dynamics is expected to further amplify the model-related uncertainties in projected future changes in surface water and heat fluxes as well as soil moisture content. This is especially the case in the high latitudes of the Northern Hemisphere (e.g., northwestern North America and central North Asia) where the projected vegetation changes are uncertain and in the Tropics (e.g., the Amazon and Congo Basins) where dense vegetation exists. Finally, findings from this study highlight the importance of improving land surface model parameterizations related to soil and snow processes, as well as the importance of improving the accuracy of dynamic vegetation models.« less

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.

The Continuing Evolution of Land Surface Parameterizations

NASA Technical Reports Server (NTRS)

Koster, Randal; Houser, Paul (Technical Monitor)

2001-01-01

Land surface models (LSMs) play a critical role in the simulation of climate, for they determine the character of a large fraction of the atmosphere's lower boundary. The LSM partitions the net radiative energy at the land surface into sensible heat, latent heat, and energy storage, and it partitions incident precipitation water into evaporation, runoff, and water storage. Numerous modeling experiments and the existing (though very scant) observational evidence suggest that variations in these partitionings can feed back on the atmospheric processes that induce them. This land-atmosphere feedback can in turn have a significant impact on the generation of continental precipitation. For this and other reasons (including the role of the land surface in converting various atmospheric quantities, such as precipitation, into quantities of perhaps higher societal relevance, such as runoff), many modeling groups are placing a high emphasis on improving the treatment of land surface processes in their models. LSMs have evolved substantially from the original bucket model of Manabe et al. This evolution, which is still ongoing, has been documented considerably. The present paper also takes a look at the evolution of LSMs. The perspective here, though, is different - the evolution is considered strictly in terms of the 'balance' between the formulations of evaporation and runoff processes. The paper will argue that a proper balance is currently missing, largely due to difficulties in treating subgrid variability in soil moisture and its impact on the generation of runoff.

The hydrological cycle at European Fluxnet sites: modeling seasonal water and energy budgets at local scale.

NASA Astrophysics Data System (ADS)

Stockli, R.; Vidale, P. L.

2003-04-01

The importance of correctly including land surface processes in climate models has been increasingly recognized in the past years. Even on seasonal to interannual time scales land surface - atmosphere feedbacks can play a substantial role in determining the state of the near-surface climate. The availability of soil moisture for both runoff and evapotranspiration is dependent on biophysical processes occuring in plants and in the soil acting on a wide time-scale from minutes to years. Fluxnet site measurements in various climatic zones are used to drive three generations of LSM's (land surface models) in order to assess the level of complexity needed to represent vegetation processes at the local scale. The three models were the Bucket model (Manabe 1969), BATS 1E (Dickinson 1984) and SiB 2 (Sellers et al. 1996). Evapotranspiration and runoff processes simulated by these models range from simple one-layer soils and no-vegetation parameterizations to complex multilayer soils, including realistic photosynthesis-stomatal conductance models. The latter is driven by satellite remote sensing land surface parameters inheriting the spatiotemporal evolution of vegetation phenology. In addition a simulation with SiB 2 not only including vertical water fluxes but also lateral soil moisture transfers by downslope flow is conducted for a pre-alpine catchment in Switzerland. Preliminary results are presented and show that - depending on the climatic environment and on the season - a realistic representation of evapotranspiration processes including seasonally and interannually-varying state of vegetation is significantly improving the representation of observed latent and sensible heat fluxes on the local scale. Moreover, the interannual evolution of soil moisture availability and runoff is strongly dependent on the chosen model complexity. Biophysical land surface parameters from satellite allow to represent the seasonal changes in vegetation activity, which has great impact on the yearly budget of transpiration fluxes. For some sites, however, the hydrological cycle is simulated reasonably well even with simple land surface representations.

Grand challenges in understanding the interplay of climate and land changes

USDA-ARS?s Scientific Manuscript database

Half of the Earth’s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affects a myriad of land surface processes and our adaptation behaviors. After reviewing the status and major knowledge gap...

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.

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.

Modeling and Observational Framework for Diagnosing Local Land-Atmosphere Coupling on Diurnal Time Scales

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Alonge, Charles; Tao, Wei-Kuo

2009-01-01

Land-atmosphere interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture states. The degree of coupling between the land surface and PBL in numerical weather prediction and climate models remains largely unexplored and undiagnosed due to the complex interactions and feedbacks present across a range of scales. Further, uncoupled systems or experiments (e.g., the Project for Intercomparison of Land Parameterization Schemes, PILPS) may lead to inaccurate water and energy cycle process understanding by neglecting feedback processes such as PBL-top entrainment. In this study, a framework for diagnosing local land-atmosphere coupling is presented using a coupled mesoscale model with a suite of PBL and land surface model (LSM) options along with observations during field experiments in the U. S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to the Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. Within this framework, the coupling established by each pairing of the available PBL schemes in WRF with the LSMs in LIS is evaluated in terms of the diurnal temperature and humidity evolution in the mixed layer. The co-evolution of these variables and the convective PBL is sensitive to and, in fact, integrative of the dominant processes that govern the PBL budget, which are synthesized through the use of mixing diagrams. Results show how the sensitivity of land-atmosphere interactions to the specific choice of PBL scheme and LSM varies across surface moisture regimes and can be quantified and evaluated against observations. As such, 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.

Integrated Water Flow Model (IWFM), A Tool For Numerically Simulating Linked Groundwater, Surface Water And Land-Surface Hydrologic Processes

NASA Astrophysics Data System (ADS)

Dogrul, E. C.; Brush, C. F.; Kadir, T. N.

2006-12-01

The Integrated Water Flow Model (IWFM) is a comprehensive input-driven application for simulating groundwater flow, surface water flow and land-surface hydrologic processes, and interactions between these processes, developed by the California Department of Water Resources (DWR). IWFM couples a 3-D finite element groundwater flow process and 1-D land surface, lake, stream flow and vertical unsaturated-zone flow processes which are solved simultaneously at each time step. The groundwater flow system is simulated as a multilayer aquifer system with a mixture of confined and unconfined aquifers separated by semiconfining layers. The groundwater flow process can simulate changing aquifer conditions (confined to unconfined and vice versa), subsidence, tile drains, injection wells and pumping wells. The land surface process calculates elemental water budgets for agricultural, urban, riparian and native vegetation classes. Crop water demands are dynamically calculated using distributed soil properties, land use and crop data, and precipitation and evapotranspiration rates. The crop mix can also be automatically modified as a function of pumping lift using logit functions. Surface water diversions and groundwater pumping can each be specified, or can be automatically adjusted at run time to balance water supply with water demand. The land-surface process also routes runoff to streams and deep percolation to the unsaturated zone. Surface water networks are specified as a series of stream nodes (coincident with groundwater nodes) with specified bed elevation, conductance and stage-flow relationships. Stream nodes are linked to form stream reaches. Stream inflows at the model boundary, surface water diversion locations, and one or more surface water deliveries per location are specified. IWFM routes stream flows through the network, calculating groundwater-surface water interactions, accumulating inflows from runoff, and allocating available stream flows to meet specified or calculated deliveries. IWFM utilizes a very straight-forward input file structure, allowing rapid development of complex simulations. A key feature of IWFM is a new algorithm for computation of groundwater flow across element faces. Enhancements to version 3.0 include automatic time-tracking of input and output data sets, linkage with the HEC-DSS database, and dynamic crop allocation using logit functions. Utilities linking IWFM to the PEST automated calibration suite are also available. All source code, executables and documentation are available for download from the DWR web site. IWFM is currently being used to develop hydrologic simulations of California's Central Valley (C2VSIM); the west side of California's San Joaquin Valley (WESTSIM); Butte County, CA; Solano County, CA; Merced County, CA; and the Oregon side of the Walla Walla River Basin.

Parameterizing atmosphere-land surface exchange for climate models with satellite data: A case study for the Southern Great Plains CART site

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

Gao, W.

High-resolution satellite data provide detailed, quantitative descriptions of land surface characteristics over large areas so that objective scale linkage becomes feasible. With the aid of satellite data, Sellers et al. and Wood and Lakshmi examined the linearity of processes scaled up from 30 m to 15 km. If the phenomenon is scale invariant, then the aggregated value of a function or flux is equivalent to the function computed from aggregated values of controlling variables. The linear relation may be realistic for limited land areas having no large surface contrasts to cause significant horizontal exchange. However, for areas with sharp surfacemore » contrasts, horizontal exchange and different dynamics in the atmospheric boundary may induce nonlinear interactions, such as at interfaces of land-water, forest-farm land, and irrigated crops-desert steppe. The linear approach, however, represents the simplest scenario, and is useful for developing an effective scheme for incorporating subgrid land surface processes into large-scale models. Our studies focus on coupling satellite data and ground measurements with a satellite-data-driven land surface model to parameterize surface fluxes for large-scale climate models. In this case study, we used surface spectral reflectance data from satellite remote sensing to characterize spatial and temporal changes in vegetation and associated surface parameters in an area of about 350 {times} 400 km covering the southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site of the US Department of Energy`s Atmospheric Radiation Measurement (ARM) Program.« less

Microwave Remote Sensing and the Cold Land Processes Field Experiment

NASA Technical Reports Server (NTRS)

Kim, Edward J.; Cline, Don; Davis, Bert; Hildebrand, Peter H. (Technical Monitor)

2001-01-01

The Cold Land Processes Field Experiment (CLPX) has been designed to advance our understanding of the terrestrial cryosphere. Developing a more complete understanding of fluxes, storage, and transformations of water and energy in cold land areas is a critical focus of the NASA Earth Science Enterprise Research Strategy, the NASA Global Water and Energy Cycle (GWEC) Initiative, the Global Energy and Water Cycle Experiment (GEWEX), and the GEWEX Americas Prediction Project (GAPP). The movement of water and energy through cold regions in turn plays a large role in ecological activity and biogeochemical cycles. Quantitative understanding of cold land processes over large areas will require synergistic advancements in 1) understanding how cold land processes, most comprehensively understood at local or hillslope scales, extend to larger scales, 2) improved representation of cold land processes in coupled and uncoupled land-surface models, and 3) a breakthrough in large-scale observation of hydrologic properties, including snow characteristics, soil moisture, the extent of frozen soils, and the transition between frozen and thawed soil conditions. The CLPX Plan has been developed through the efforts of over 60 interested scientists that have participated in the NASA Cold Land Processes Working Group (CLPWG). This group is charged with the task of assessing, planning and implementing the required background science, technology, and application infrastructure to support successful land surface hydrology remote sensing space missions. A major product of the experiment will be a comprehensive, legacy data set that will energize many aspects of cold land processes research. The CLPX will focus on developing the quantitative understanding, models, and measurements necessary to extend our local-scale understanding of water fluxes, storage, and transformations to regional and global scales. The experiment will particularly emphasize developing a strong synergism between process-oriented understanding, land surface models and microwave remote sensing. The experimental design is a multi-sensor, multi-scale (1-ha to 160,000 km ^ {2}) approach to providing the comprehensive data set necessary to address several experiment objectives. A description focusing on the microwave remote sensing components (ground, airborne, and spaceborne) of the experiment will be presented.

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.

Evaluating soil moisture constraints on surface fluxes in land surface models globally

NASA Astrophysics Data System (ADS)

Harris, Phil; Gallego-Elvira, Belen; Taylor, Christopher; Folwell, Sonja; Ghent, Darren; Veal, Karen; Hagemann, Stefan

2016-04-01

Soil moisture availability exerts a strong control over land evaporation in many regions. However, global climate models (GCMs) disagree on when and where evaporation is limited by soil moisture. Evaluation of the relevant modelled processes has suffered from a lack of reliable, global observations of land evaporation at the GCM grid box scale. Satellite observations of land surface temperature (LST) offer spatially extensive but indirect information about the surface energy partition and, under certain conditions, about soil moisture availability on evaporation. Specifically, as soil moisture decreases during rain-free dry spells, evaporation may become limited leading to increases in LST and sensible heat flux. We use MODIS Terra and Aqua observations of LST at 1 km from 2000 to 2012 to assess changes in the surface energy partition during dry spells lasting 10 days or longer. The clear-sky LST data are aggregated to a global 0.5° grid before being composited as a function dry spell day across many events in a particular region and season. These composites are then used to calculate a Relative Warming Rate (RWR) between the land surface and near-surface air. This RWR can diagnose the typical strength of short term changes in surface heat fluxes and, by extension, changes in soil moisture limitation on evaporation. Offline land surface model (LSM) simulations offer a relatively inexpensive way to evaluate the surface processes of GCMs. They have the benefits that multiple models, and versions of models, can be compared on a common grid and using unbiased forcing. Here, we use the RWR diagnostic to assess global, offline simulations of several LSMs (e.g., JULES and JSBACH) driven by the WATCH Forcing Data-ERA Interim. Both the observed RWR and the LSMs use the same 0.5° grid, which allows the observed clear-sky sampling inherent in the underlying MODIS LST to be applied to the model outputs directly. This approach avoids some of the difficulties in analysing free-running simulations in which land and atmosphere are coupled and, as such, it provides a flexible intermediate step in the assessment of surface processes in GCMs.

Report of the panel on the land surface: Process of change, section 5

NASA Technical Reports Server (NTRS)

Adams, John B.; Barron, Eric E.; Bloom, Arthur A.; Breed, Carol; Dohrenwend, J.; Evans, Diane L.; Farr, Thomas T.; Gillespie, Allan R.; Isaks, B. L.; Williams, Richard S.

1991-01-01

The panel defined three main areas of study that are central to the Solid Earth Science (SES) program: climate interactions with the Earth's surface, tectonism as it affects the Earth's surface and climate, and human activities that modify the Earth's surface. Four foci of research are envisioned: process studies with an emphasis on modern processes in transitional areas; integrated studies with an emphasis on long term continental climate change; climate-tectonic interactions; and studies of human activities that modify the Earth's surface, with an emphasis on soil degradation. The panel concluded that there is a clear requirement for global coverage by high resolution stereoscopic images and a pressing need for global topographic data in support of studies of the land surface.

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.

NASA Cold Land Processes Experiment (CLPX 2002/03): Field measurements of snowpack properties and soil moisture

Treesearch

Kelly Elder; Don Cline; Glen E. Liston; Richard Armstrong

2009-01-01

A field measurement program was undertaken as part NASA's Cold Land Processes Experiment (CLPX). Extensive snowpack and soil measurements were taken at field sites in Colorado over four study periods during the two study years (2002 and 2003). Measurements included snow depth, density, temperature, grain type and size, surface wetness, surface roughness, and...

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.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

PubMed

Midekisa, Alemayehu; Holl, Felix; Savory, David J; Andrade-Pacheco, Ricardo; Gething, Peter W; Bennett, Adam; Sturrock, Hugh J W

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing

PubMed Central

Holl, Felix; Savory, David J.; Andrade-Pacheco, Ricardo; Gething, Peter W.; Bennett, Adam; Sturrock, Hugh J. W.

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth’s land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources. PMID:28953943

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.

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.

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.

Application of Intel Many Integrated Core (MIC) accelerators to the Pleim-Xiu land surface scheme

NASA Astrophysics Data System (ADS)

Huang, Melin; Huang, Bormin; Huang, Allen H.

2015-10-01

The land-surface model (LSM) is one physics process in the weather research and forecast (WRF) model. The LSM includes atmospheric information from the surface layer scheme, radiative forcing from the radiation scheme, and precipitation forcing from the microphysics and convective schemes, together with internal information on the land's state variables and land-surface properties. The LSM is to provide heat and moisture fluxes over land points and sea-ice points. The Pleim-Xiu (PX) scheme is one LSM. The PX LSM features three pathways for moisture fluxes: evapotranspiration, soil evaporation, and evaporation from wet canopies. To accelerate the computation process of this scheme, we employ Intel Xeon Phi Many Integrated Core (MIC) Architecture as it is a multiprocessor computer structure with merits of efficient parallelization and vectorization essentials. Our results show that the MIC-based optimization of this scheme running on Xeon Phi coprocessor 7120P improves the performance by 2.3x and 11.7x as compared to the original code respectively running on one CPU socket (eight cores) and on one CPU core with Intel Xeon E5-2670.

Effects of anthropogenic groundwater exploitation on land surface processes: A case study of the Haihe River Basin, northern China

NASA Astrophysics Data System (ADS)

Zou, Jing; Xie, Zhenghui; Zhan, Chesheng; Qin, Peihua; Sun, Qin; Jia, Binghao; Xia, Jun

2015-05-01

In this study, we incorporated a groundwater exploitation scheme into the land surface model CLM3.5 to investigate the effects of the anthropogenic exploitation of groundwater on land surface processes in a river basin. Simulations of the Haihe River Basin in northern China were conducted for the years 1965-2000 using the model. A control simulation without exploitation and three exploitation simulations with different water demands derived from socioeconomic data related to the Basin were conducted. The results showed that groundwater exploitation for human activities resulted in increased wetting and cooling effects at the land surface and reduced groundwater storage. A lowering of the groundwater table, increased upper soil moisture, reduced 2 m air temperature, and enhanced latent heat flux were detected by the end of the simulated period, and the changes at the land surface were related linearly to the water demands. To determine the possible responses of the land surface processes in extreme cases (i.e., in which the exploitation process either continued or ceased), additional hypothetical simulations for the coming 200 years with constant climate forcing were conducted, regardless of changes in climate. The simulations revealed that the local groundwater storage on the plains could not contend with high-intensity exploitation for long if the exploitation process continues at the current rate. Changes attributable to groundwater exploitation reached extreme values and then weakened within decades with the depletion of groundwater resources and the exploitation process will therefore cease. However, if exploitation is stopped completely to allow groundwater to recover, drying and warming effects, such as increased temperature, reduced soil moisture, and reduced total runoff, would occur in the Basin within the early decades of the simulation period. The effects of exploitation will then gradually disappear, and the variables will approach the natural state and stabilize at different rates. Simulations were also conducted for cases in which exploitation either continues or ceases using future climate scenario outputs from a general circulation model. The resulting trends were almost the same as those of the simulations with constant climate forcing, despite differences in the climate data input. Therefore, a balance between slow groundwater restoration and rapid human development of the land must be achieved to maintain a sustainable water resource.

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.

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.

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

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.

Exploring the Influence of Topography on Belowground C Processes Using a Coupled Hydrologic-Biogeochemical Model

NASA Astrophysics Data System (ADS)

Shi, Y.; Davis, K. J.; Eissenstat, D. M.; Kaye, J. P.; Duffy, C.; Yu, X.; He, Y.

2014-12-01

Belowground carbon processes are affected by soil moisture and soil temperature, but current biogeochemical models are 1-D and cannot resolve topographically driven hill-slope soil moisture patterns, and cannot simulate the nonlinear effects of soil moisture on carbon processes. Coupling spatially-distributed physically-based hydrologic models with biogeochemical models may yield significant improvements in the representation of topographic influence on belowground C processes. We will couple the Flux-PIHM model to the Biome-BGC (BBGC) model. Flux-PIHM is a coupled physically-based land surface hydrologic model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Because PIHM is capable of simulating lateral water flow and deep groundwater, Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. The coupled Flux-PIHM-BBGC model will be tested at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). The abundant observations, including eddy covariance fluxes, soil moisture, groundwater level, sap flux, stream discharge, litterfall, leaf area index, above ground carbon stock, and soil carbon efflux, make SSHCZO an ideal test bed for the coupled model. In the coupled model, each Flux-PIHM model grid will couple a BBGC cell. Flux-PIHM will provide BBGC with soil moisture and soil temperature information, while BBGC provides Flux-PIHM with leaf area index. Preliminary results show that when Biome- BGC is driven by PIHM simulated soil moisture pattern, the simulated soil carbon is clearly impacted by topography.

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.

Diagnosing the Nature of Land-Atmosphere Coupling During the 2006-7 Dry/Wet Extremes in the U. S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Santanello, Joseph A.; Peters-Lidard, Christa D.; Kennedy, Aaron D.; Kumar, Sujay; Dong, Xiquan

2011-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address deficiencies in numerical weather prediction and climate models due to improper treatment of L-A interactions, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process-level. In this study, a diagnosis of the nature and impacts of local land-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of2006-7 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which provides a flexible and high resolution representation and initialization of land surface physics and states. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are examined for the dry/wet regimes of this region, along with the behavior and accuracy of different land-PBL scheme couplings under these conditions. Results demonstrate how LoCo diagnostics can be applied to coupled model components in the context of their integrated impacts on the process-chain connecting the land surface to the PBL and support of hydrological anomalies.

Evapotranspiration and runoff from large land areas: Land surface hydrology for atmospheric general circulation models

NASA Technical Reports Server (NTRS)

Famiglietti, J. S.; Wood, Eric F.

1993-01-01

A land surface hydrology parameterization for use in atmospheric GCM's is presented. The parameterization incorporates subgrid scale variability in topography, soils, soil moisture and precipitation. The framework of the model is the statistical distribution of a topography-soils index, which controls the local water balance fluxes, and is therefore taken to represent the large land area. Spatially variable water balance fluxes are integrated with respect to the topography-soils index to yield our large topography-soils distribution, and interval responses are weighted by the probability of occurrence of the interval. Grid square averaged land surface fluxes result. The model functions independently as a macroscale water balance model. Runoff ratio and evapotranspiration efficiency parameterizations are derived and are shown to depend on the spatial variability of the above mentioned properties and processes, as well as the dynamics of land surface-atmosphere interactions.

Modification of Soil Temperature and Moisture Budgets by Snow Processes

NASA Astrophysics Data System (ADS)

Feng, X.; Houser, P.

2006-12-01

Snow cover significantly influences the land surface energy and surface moisture budgets. Snow thermally insulates the soil column from large and rapid temperature fluctuations, and snow melting provides an important source for surface runoff and soil moisture. Therefore, it is important to accurately understand and predict the energy and moisture exchange between surface and subsurface associated with snow accumulation and ablation. The objective of this study is to understand the impact of land surface model soil layering treatment on the realistic simulation of soil temperature and soil moisture. We seek to understand how many soil layers are required to fully take into account soil thermodynamic properties and hydrological process while also honoring efficient calculation and inexpensive computation? This work attempts to address this question using field measurements from the Cold Land Processes Field Experiment (CLPX). In addition, to gain a better understanding of surface heat and surface moisture transfer process between land surface and deep soil involved in snow processes, numerical simulations were performed at several Meso-Cell Study Areas (MSAs) of CLPX using the Center for Ocean-Land-Atmosphere (COLA) Simplified Version of the Simple Biosphere Model (SSiB). Measurements of soil temperature and soil moisture were analyzed at several CLPX sites with different vegetation and soil features. The monthly mean vertical profile of soil temperature during October 2002 to July 2003 at North Park Illinois River exhibits a large near surface variation (<5 cm), reveals a significant transition zone from 5 cm to 25 cm, and becomes uniform beyond 25cm. This result shows us that three soil layers are reasonable in solving the vertical variation of soil temperature at these study sites. With 6 soil layers, SSiB also captures the vertical variation of soil temperature during entire winter season, featuring with six soil layers, but the bare soil temperature is underestimated and root-zone soil temperature is overestimated during snow melting; which leads to overestimated temperature variations down to 20 cm. This is caused by extra heat loss from upper soil level and insufficient heat transport from the deep soil. Further work will need to verify if soil temperature displays similar vertical thermal structure for different vegetation and soil types during snow season. This study provides insight to the surface and subsurface thermodynamic and hydrological processes involved in snow modeling which is important for accurate snow simulation.

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.

Interactive Computing and Processing of NASA Land Surface Observations Using Google Earth Engine

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Burks, Jason; Bell, Jordan

2016-01-01

Google's Earth Engine offers a "big data" approach to processing large volumes of NASA and other remote sensing products. h\\ps://earthengine.google.com/ Interfaces include a Javascript or Python-based API, useful for accessing and processing over large periods of record for Landsat and MODIS observations. Other data sets are frequently added, including weather and climate model data sets, etc. Demonstrations here focus on exploratory efforts to perform land surface change detection related to severe weather, and other disaster events.

Investigating the Impacts of Surface Temperature Anomalies due to Burned Area Albedo in Northern sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Gabbert, T.; Matsui, T.; Capehart, W. J.; Ichoku, C. M.; Gatebe, C. K.

2015-12-01

The northern Sub-Saharan African region (NSSA) is an area of intense focus due to periodic severe droughts that have dire consequences on the growing population, which relies mostly on rain fed agriculture for its food supply. This region's weather and hydrologic cycle are very complex and are dependent on the West African Monsoon. Different regional processes affect the West African Monsoon cycle and variability. One of the areas of current investigation is the water cycle response to the variability of land surface characteristics. Land surface characteristics are often altered in NSSA due to agricultural practices, grazing, and the fires that occur during the dry season. To better understand the effects of biomass burning on the hydrologic cycle of the sub-Saharan environment, an interdisciplinary team sponsored by NASA is analyzing potential feedback mechanisms due to the fires. As part of this research, this study focuses on the effects of land surface changes, particularly albedo and skin temperature, that are influenced by biomass burning. Surface temperature anomalies can influence the initiation of convective rainfall and surface albedo is linked to the absorption of solar radiation. To capture the effects of fire perturbations on the land surface, NASA's Unified Weather and Research Forecasting (NU-WRF) model coupled with NASA's Land Information System (LIS) is being used to simulate burned area surface albedo inducing surface temperature anomalies and other potential effects to environmental processes. Preliminary sensitivity results suggest an altered surface radiation budget, regional warming of the surface temperature, slight increase in average rainfall, and a change in precipitation locations.

Microphysics, Radiation and Surface Processes in the Goddard Cumulus Ensemble (GCE) Model

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2002-01-01

In this talk, five specific major GCE improvements: (1) ice microphysics, (2) longwave and shortwave radiative transfer processes, (3) land surface processes, (4) ocean surface fluxes and (5) ocean mixed layer processes are presented. The performance of these new GCE improvements will be examined. Observations are used for model validation.

Diagnosing the Nature of Land-Atmosphere Coupling During the 2006-7 Dry/Wet Extremes in the U.S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Dong, Xiquan; Kennedy, Aaron D.

2011-01-01

Land-atmosphere interactions play a critical role in determining the. diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture states. The degree of coupling between the land surface and PBL in numerical weather prediction and climate models remains largely unexplored and undiagnosed due to the complex interactions and feedbacks present across a range of scales. Further, uncoupled systems or experiments (e.g., the Project for Intercomparison of Land Parameterization Schemes, PILPS) may lead to inaccurate water and energy cycle process understanding by neglecting feedback processes such as PBL-top entrainment. In this study, a framework for diagnosing local land-atmosphere coupling (LoCo) is presented using a coupled mesoscale model with a suite of PBL and land surface model (LSM) options along with observations during the summers of 200617 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are examined for the dry/wet extremes of this region, along with the sensitivity of PBL-LSM coupling to perturbations in soil moisture. As such, this methodology provides a potential pathway to study factors controlling local land-atmosphere coupling (LoCo) using the LIS-WRF system, which is serving as a testbed for LoCo experiments to evaluate coupling diagnostics within the community.

Sensitivity of volatile organic compounds (VOCs) and ozone to land surface processes and vegetation distributions in California

NASA Astrophysics Data System (ADS)

Zhao, C.; Huang, M.; Fast, J. D.; Berg, L. K.; Qian, Y.; Guenther, A. B.; Gu, D.; Shrivastava, M. B.; Liu, Y.; Walters, S.; Jin, J.

2014-12-01

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect secondary organic aerosol (SOA) formation and ultimately aerosol radiative forcing. These uncertainties result from many factors, including coupling strategy between biogenic emissions and land-surface schemes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (VOCs). In this study, sensitivity experiments are conducted using the Weather Research and Forecasting model with chemistry (WRF-Chem) to examine the sensitivity of simulated VOCs and ozone to land surface processes and vegetation distributions in California. The measurements collected during the California Nexus of Air Quality and Climate Experiment (CalNex) and the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted during May and June of 2010 provide a good opportunity to evaluate the simulations. First, the biogenic VOC emissions in the WRF-Chem simulations with the two land surface schemes, Noah and CLM4, are estimated by the Model of Emissions of Gases and Aerosols from Nature version one (MEGANv1), which has been publicly released and widely used with WRF-Chem. The impacts of land surface processes on estimating biogenic VOC emissions and simulating VOCs and ozone are investigated. Second, in this study, a newer version of MEGAN (MEGANv2.1) is coupled with CLM4 as part of WRF-Chem to examine the sensitivity of biogenic VOC emissions to the MEGAN schemes used and determine the importance of using a consistent vegetation map between a land surface scheme and the biogenic VOC emission scheme. Specifically, MEGANv2.1 is embedded into the CLM4 scheme and shares a consistent vegetation map for estimating biogenic VOC emissions. This is unlike MEGANv1 in WRF-Chem that uses a standalone vegetation map that differs from what is used in land surface schemes. Furthermore, we examine the impact of vegetation distribution on simulating VOCs and ozone by comparing coupled WRF-Chem-CLM-MEGANv2.1 simulations using multiple vegetation maps.

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.

Uncertainty in solid precipitation and snow depth prediction for Siberia using the Noah and Noah-MP land surface models

NASA Astrophysics Data System (ADS)

Suzuki, Kazuyoshi; Zupanski, Milija

2018-01-01

In this study, we investigate the uncertainties associated with land surface processes in an ensemble predication context. Specifically, we compare the uncertainties produced by a coupled atmosphere-land modeling system with two different land surface models, the Noah- MP land surface model (LSM) and the Noah LSM, by using the Maximum Likelihood Ensemble Filter (MLEF) data assimilation system as a platform for ensemble prediction. We carried out 24-hour prediction simulations in Siberia with 32 ensemble members beginning at 00:00 UTC on 5 March 2013. We then compared the model prediction uncertainty of snow depth and solid precipitation with observation-based research products and evaluated the standard deviation of the ensemble spread. The prediction skill and ensemble spread exhibited high positive correlation for both LSMs, indicating a realistic uncertainty estimation. The inclusion of a multiple snowlayer model in the Noah-MP LSM was beneficial for reducing the uncertainties of snow depth and snow depth change compared to the Noah LSM, but the uncertainty in daily solid precipitation showed minimal difference between the two LSMs. The impact of LSM choice in reducing temperature uncertainty was limited to surface layers of the atmosphere. In summary, we found that the more sophisticated Noah-MP LSM reduces uncertainties associated with land surface processes compared to the Noah LSM. Thus, using prediction models with improved skill implies improved predictability and greater certainty of prediction.

ExoMars 2018 Landing Site Selection Process

NASA Astrophysics Data System (ADS)

Vago, Jorge L.; Kminek, Gerhard; Rodionov, Daniel

The ExoMars 2018 mission will include two science elements: a Rover and a Surface Platform. The ExoMars Rover will carry a comprehensive suite of instruments dedicated to geology and exobiology research named after Louis Pasteur. The Rover will be able to travel several kilometres searching for traces of past and present signs of life. It will do this by collecting and analysing samples from outcrops, and from the subsurface—down to 2-m depth. The very powerful combination of mobility with the ability to access locations where organic molecules can be well preserved is unique to this mission. After the Rover will have egressed, the ExoMars Surface Platform will begin its science mission to study the surface environment at the landing location. This talk will describe the landing site selection process and introduce the scientific, planetary protection, and engineering requirements that candidate landing sites must comply with in order to be considered for the mission.

Hydogeomorphic Processes in Mountainous Terrain: Effects of Land Management and Implications for Sustainability and Hazards

EPA Science Inventory

The evolving science of hydrogeomorphology encompasses the interaction of water with landforms in time and space. This includes the processes of surface and mass erosion as well as the effects of land management. These hydrogeomorphic processes and management effects are examined...

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.

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

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.

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.

A novel representation of groundwater dynamics in large-scale land surface modelling

NASA Astrophysics Data System (ADS)

Rahman, Mostaquimur; Rosolem, Rafael; Kollet, Stefan

2017-04-01

Land surface processes are connected to groundwater dynamics via shallow soil moisture. For example, groundwater affects evapotranspiration (by influencing the variability of soil moisture) and runoff generation mechanisms. However, contemporary Land Surface Models (LSM) generally consider isolated soil columns and free drainage lower boundary condition for simulating hydrology. This is mainly due to the fact that incorporating detailed groundwater dynamics in LSMs usually requires considerable computing resources, especially for large-scale applications (e.g., continental to global). Yet, these simplifications undermine the potential effect of groundwater dynamics on land surface mass and energy fluxes. In this study, we present a novel approach of representing high-resolution groundwater dynamics in LSMs that is computationally efficient for large-scale applications. This new parameterization is incorporated in the Joint UK Land Environment Simulator (JULES) and tested at the continental-scale.

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.

Generating 30-m land surface albedo by integrating landsat and MODIS data for understanding the disturbance evolution

USDA-ARS?s Scientific Manuscript database

Land cover changes affect climate through both biogeochemical (carbon-cycle) impacts and biogeophysical processes such as changes in surface albedo, temperature, evapotranspiration, atmospheric water vapor, and cloud cover. Recent studies have examined both the greenhouse gas and biophysical consequ...

Generating 30-m land surface albedo by integrating landsat and MODIS data for understanding the disturbance

USDA-ARS?s Scientific Manuscript database

Land cover change affects climate through both biogeochemical (carbon-cycle) impacts and biogeophysical processes such as changes in surface albedo, temperature, evapotranspiration, atmospheric water vapor, and cloud cover. Previous studies have highlighted that forest loss in high latitudes could c...

Using a spatially-distributed hydrologic biogeochemistry model to study the spatial variation of carbon processes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; Davis, K. J.; He, Y.

2016-12-01

Forest carbon processes are affected by, among other factors, soil moisture, soil temperature, soil nutrients and solar radiation. Most of the current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve the topographically driven hill-slope land surface heterogeneity or the spatial pattern of nutrient availability. A spatially distributed forest ecosystem model, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while soil nitrogen is transported among model grids via subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation information, while BBGC provides Flux-PIHM with leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). Model results suggest that the vegetation and soil carbon distribution is primarily constrained by nitorgen availability (affected by nitorgen transport via topographically driven subsurface flow), and also constrained by solar radiation and root zone soil moisture. The predicted vegetation and soil carbon distribution generally agrees with the macro pattern observed within the watershed. The coupled ecosystem-hydrologic model provides an important tool to study the impact of topography on watershed carbon processes, as well as the impact of climate change on water resources.

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.

Parametric design and analysis on the landing gear of a planet lander using the response surface method

NASA Astrophysics Data System (ADS)

Zheng, Guang; Nie, Hong; Luo, Min; Chen, Jinbao; Man, Jianfeng; Chen, Chuanzhi; Lee, Heow Pueh

2018-07-01

The purpose of this paper is to obtain the design parameter-landing response relation for designing the configuration of the landing gear in a planet lander quickly. To achieve this, parametric studies on the landing gear are carried out using the response surface method (RSM), based on a single landing gear landing model validated by experimental results. According to the design of experiment (DOE) results of the landing model, the RS (response surface)-functions of the three crucial landing responses are obtained, and the sensitivity analysis (SA) of the corresponding parameters is performed. Also, two multi-objective optimizations designs on the landing gear are carried out. The analysis results show that the RS (response surface)-model performs well for the landing response design process, with a minimum fitting accuracy of 98.99%. The most sensitive parameters for the three landing response are the design size of the buffers, struts friction and the diameter of the bending beam. Moreover, the good agreement between the simulated model and RS-model results are obtained in two optimized designs, which show that the RS-model coupled with the FE (finite element)-method is an efficient method to obtain the design configuration of the landing gear.

Comparing Noah-MP simulations of energy and water fluxes in the soil-vegetation-atmosphere continuum with plot scale measurements

NASA Astrophysics Data System (ADS)

Gayler, Sebastian; Wöhling, Thomas; Högy, Petra; Ingwersen, Joachim; Wizemann, Hans-Dieter; Wulfmeyer, Volker; Streck, Thilo

2013-04-01

During the last years, land-surface models have proven to perform well in several studies that compared simulated fluxes of water and energy from the land surface to the atmosphere against measured fluxes at the plot-scale. In contrast, considerable deficits of land-surface models have been identified to simulate soil water fluxes and vertical soil moisture distribution. For example, Gayler et al. (2013) showed that simplifications in the representation of root water uptake can result in insufficient simulations of the vertical distribution of soil moisture and its dynamics. However, in coupled simulations of the terrestrial water cycle, both sub-systems, the atmosphere and the subsurface hydrogeo-system, must fit together and models are needed, which are able to adequately simulate soil moisture, latent heat flux, and their interrelationship. Consequently, land-surface models must be further improved, e.g. by incorporation of advanced biogeophysics models. To improve the conceptual realism in biophysical and hydrological processes in the community land surface model Noah, this model was recently enhanced to Noah-MP by a multi-options framework to parameterize individual processes (Niu et al., 2011). Thus, in Noah-MP the user can choose from several alternative models for vegetation and hydrology processes that can be applied in different combinations. In this study, we evaluate the performance of different Noah-MP model settings to simulate water and energy fluxes across the land surface at two contrasting field sites in South-West Germany. The evaluation is done in 1D offline-mode, i.e. without coupling to an atmospheric model. The atmospheric forcing is provided by measured time series of the relevant variables. Simulation results are compared with eddy covariance measurements of turbulent fluxes and measured time series of soil moisture at different depths. The aims of the study are i) to carve out the most appropriate combination of process parameterizations in Noah-MP to simultaneously match the different components of the water and energy cycle at the field sites under consideration, and ii) to estimate the uncertainty in model structure. We further investigate the potential to improve simulation results by incorporating concepts of more advanced root water uptake models from agricultural field scale models into the land-surface-scheme. Gayler S, Ingwersen J, Priesack E, Wöhling T, Wulfmeyer V, Streck T (2013): Assessing the relevance of sub surface processes for the simulation of evapotranspiration and soil moisture dynamics with CLM3.5: Comparison with field data and crop model simulations. Environ. Earth Sci., 69(2), under revision. Niu G-Y, Yang Z-L, Mitchell KE, Chen F, Ek MB, Barlage M, Kumar A, Manning K, Niyogi D, Rosero E, Tewari M and Xia Y (2011): The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. Journal of Geophysical Research 116(D12109).

Observed increase in local cooling effect of deforestation at higher latitudes.

PubMed

Lee, Xuhui; Goulden, Michael L; Hollinger, David Y; Barr, Alan; Black, T Andrew; Bohrer, Gil; Bracho, Rosvel; Drake, Bert; Goldstein, Allen; Gu, Lianhong; Katul, Gabriel; Kolb, Thomas; Law, Beverly E; Margolis, Hank; Meyers, Tilden; Monson, Russell; Munger, William; Oren, Ram; Paw U, Kyaw Tha; Richardson, Andrew D; Schmid, Hans Peter; Staebler, Ralf; Wofsy, Steven; Zhao, Lei

2011-11-16

Deforestation in mid- to high latitudes is hypothesized to have the potential to cool the Earth's surface by altering biophysical processes. In climate models of continental-scale land clearing, the cooling is triggered by increases in surface albedo and is reinforced by a land albedo-sea ice feedback. This feedback is crucial in the model predictions; without it other biophysical processes may overwhelm the albedo effect to generate warming instead. Ongoing land-use activities, such as land management for climate mitigation, are occurring at local scales (hectares) presumably too small to generate the feedback, and it is not known whether the intrinsic biophysical mechanism on its own can change the surface temperature in a consistent manner. Nor has the effect of deforestation on climate been demonstrated over large areas from direct observations. Here we show that surface air temperature is lower in open land than in nearby forested land. The effect is 0.85 ± 0.44 K (mean ± one standard deviation) northwards of 45° N and 0.21 ± 0.53 K southwards. Below 35° N there is weak evidence that deforestation leads to warming. Results are based on comparisons of temperature at forested eddy covariance towers in the USA and Canada and, as a proxy for small areas of cleared land, nearby surface weather stations. Night-time temperature changes unrelated to changes in surface albedo are an important contributor to the overall cooling effect. The observed latitudinal dependence is consistent with theoretical expectation of changes in energy loss from convection and radiation across latitudes in both the daytime and night-time phase of the diurnal cycle, the latter of which remains uncertain in climate models. © 2011 Macmillan Publishers Limited. All rights reserved

Application of SAR Remote Sensing in Land Surface Processes Over Tropical region

NASA Technical Reports Server (NTRS)

Saatchi, Sasan S.

1996-01-01

This paper outlines the potential applications of polarimetric SAR systems over tropical regions such as mapping land use and deforestation, forest regeneration, wetland and inundation studies, and mapping land cover types for biodiversity and habitat conservation studies.

Diagnosing the Nature of Land-Atmosphere Coupling: A Case Study of Dry/Wet Extremes

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa; Kennedy, Aaron D.

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address deficiencies in numerical weather prediction and climate models due to improper treatment of L-A interactions, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process-level. In this study, a diagnosis of the nature and impacts oflocalland-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of2006-7 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are examined for the dry/wet regimes of this region, along with the behavior and accuracy of different land-PBL scheme couplings under these conditions. In addition, we examine the impact of improved specification ofland surface states, anomalies, and fluxes that are obtained through the use of a hew optimization and uncertainty module in LIS, on the L-A coupling in WRF forecasts. Results demonstrate how LoCo diagnostics can be applied to coupled model components in the context of their integrated impacts on the process-chain connecting the land surface to the PBL and support of hydrological anomalies.

The Impacts of Urbanization on Meteorology and Air Quality in the Los Angeles Basin

NASA Astrophysics Data System (ADS)

Li, Y.; Zhang, J.; Sailor, D.; Ban-Weiss, G. A.

2017-12-01

Urbanization has a profound influence on regional meteorology in mega cities like Los Angeles. This influence is driven by changes in land surface physical properties and urban processes, and their corresponding influence on surface-atmosphere coupling. Changes in meteorology from urbanization in turn influences air quality through weather-dependent chemical reaction, pollutant dispersion, etc. Hence, a real-world representation of the urban land surface properties and urban processes should be accurately resolved in regional climate-chemistry models for better understanding the role of urbanization on changing urban meteorology and associated pollutant dynamics. By incorporating high-resolution land surface data, previous research has improved model-observation comparisons of meteorology in urban areas including the Los Angeles basin, and indicated that historical urbanization has increased urban temperatures and altered wind flows significantly. However, the impact of urban expansion on air quality has been less studied. Thus, in this study, we aim to evaluate the effectiveness of resolving high-resolution heterogeneity in urban land surface properties and processes for regional weather and pollutant concentration predictions. We coupled the Weather Research and Forecasting model with Chemistry to the single-layer Urban Canopy Model to simulate a typical summer period in year 2012 for Southern California. Land cover type and urban fraction were determined from National Land Cover Data. MODIS observations were used to determine satellite-derived albedo, green vegetation fraction, and leaf area index. Urban morphology was determined from GIS datasets of 3D building geometries. An urban irrigation scheme was also implemented in the model. Our results show that the improved model captures the diurnal cycle of 2m air temperature (T2) and Ozone (O3) concentrations. However, it tends to overestimate wind speed and underestimate T2, which leads to an underestimation of O3 and fine particulate matter concentrations. By comparing simulations assuming current land cover of the Los Angeles basin versus pre-urbanization land cover, we find that land cover change through urbanization has led to important shifts in regional air pollution via the aforementioned physical and chemical mechanisms.

Grand challenges in understanding the interplay of climate and land changes

DOE PAGES

Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.; ...

2017-03-28

Half of the Earth s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affects a myriad of land surface processes and our adaptation behaviors. We here review the status and major knowledge gaps of studying the interactions of land and atmospheric changes and present eleven grand challenge areas for scientific research and adaptation communities in the coming decade: (1) collective and separate impacts of major land changes and the interactions with non-land-change factors such as atmospheric CO2 increase, (2) carbon and other biogeochemicalmore » cycles, (3) climatically relevant biospheric emissions such as aerosols, (4) water cycle, (5) agriculture, (6) urbanization, (7) gradual acclimation of plants, communities, and ecosystems to climate and environmental changes, (8) plant migration, (9) land use projections, (10) reduction of uncertainties in models and data, and finally (11) adaptation strategies. We conclude that we need to create and maintain a close cross-disciplinary coordination between measurements and process representation in models to analyze complex multi-facet interrelated perturbations and feedbacks between land and climate changes. Along with major scientific research thrusts, land-use and land cover change mitigation and adaptation assessments should be strengthened to identify barriers that need to be overcome, evaluate and prioritize opportunities, and examine how decision making processes work in specific contexts.« less

Grand challenges in understanding the interplay of climate and land changes

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

Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.

Half of the Earth s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affects a myriad of land surface processes and our adaptation behaviors. We here review the status and major knowledge gaps of studying the interactions of land and atmospheric changes and present eleven grand challenge areas for scientific research and adaptation communities in the coming decade: (1) collective and separate impacts of major land changes and the interactions with non-land-change factors such as atmospheric CO2 increase, (2) carbon and other biogeochemicalmore » cycles, (3) climatically relevant biospheric emissions such as aerosols, (4) water cycle, (5) agriculture, (6) urbanization, (7) gradual acclimation of plants, communities, and ecosystems to climate and environmental changes, (8) plant migration, (9) land use projections, (10) reduction of uncertainties in models and data, and finally (11) adaptation strategies. We conclude that we need to create and maintain a close cross-disciplinary coordination between measurements and process representation in models to analyze complex multi-facet interrelated perturbations and feedbacks between land and climate changes. Along with major scientific research thrusts, land-use and land cover change mitigation and adaptation assessments should be strengthened to identify barriers that need to be overcome, evaluate and prioritize opportunities, and examine how decision making processes work in specific contexts.« less

Impact of Land Cover Characterization and Properties on Snow Albedo in Climate Models

NASA Astrophysics Data System (ADS)

Wang, L.; Bartlett, P. A.; Chan, E.; Montesano, P.

2017-12-01

The simulation of winter albedo in boreal and northern environments has been a particular challenge for land surface modellers. Assessments of output from CMIP3 and CMIP5 climate models have revealed that many simulations are characterized by overestimation of albedo in the boreal forest. Recent studies suggest that inaccurate representation of vegetation distribution, improper simulation of leaf area index, and poor treatment of canopy-snow processes are the primary causes of albedo errors. While several land cover datasets are commonly used to derive plant functional types (PFT) for use in climate models, new land cover and vegetation datasets with higher spatial resolution have become available in recent years. In this study, we compare the spatial distribution of the dominant PFTs and canopy cover fractions based on different land cover datasets, and present results from offline simulations of the latest version Canadian Land Surface Scheme (CLASS) over the northern Hemisphere land. We discuss the impact of land cover representation and surface properties on winter albedo simulations in climate models.

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.

Landsat surface reflectance data

USGS Publications Warehouse

,

2015-01-01

Landsat satellite data have been produced, archived, and distributed by the U.S. Geological Survey since 1972. Users rely on these data for historical study of land surface change and require consistent radiometric data processed to the highest science standards. In support of the guidelines established through the Global Climate Observing System, the U.S. Geological Survey has embarked on production of higher-level Landsat data products to support land surface change studies. One such product is Landsat surface reflectance.

Quantitative Estimation of Land Surface Characteristic Parameters and Actual Evapotranspiration in the Nagqu River Basin over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zhong, L.; Ma, Y.; Ma, W.; Zou, M.; Hu, Y.

2016-12-01

Actual evapotranspiration (ETa) is an important component of the water cycle in the Tibetan Plateau. It is controlled by many hydrological and meteorological factors. Therefore, it is of great significance to estimate ETa accurately and continuously. It is also drawing much attention of scientific community to understand land surface parameters and land-atmosphere water exchange processes in small watershed-scale areas. Based on in-situ meteorological data in the Nagqu river basin and surrounding regions, the main meteorological factors affecting the evaporation process were quantitatively analyzed and the point-scale ETa estimation models in the study area were successfully built. On the other hand, multi-source satellite data (such as SPOT, MODIS, FY-2C) were used to derive the surface characteristics in the river basin. A time series processing technique was applied to remove cloud cover and reconstruct data series. Then improved land surface albedo, improved downward shortwave radiation flux and reconstructed normalized difference vegetation index (NDVI) were coupled into the topographical enhanced surface energy balance system to estimate ETa. The model-estimated results were compared with those ETa values determined by combinatory method. The results indicated that the model-estimated ETa agreed well with in-situ measurements with correlation coefficient, mean bias error and root mean square error of 0.836, 0.087 and 0.140 mm/h respectively.

Retrieval of land parameters by multi-sensor information using the Earth Observation Land Data Assimilation System

NASA Astrophysics Data System (ADS)

Chernetskiy, Maxim; Gobron, Nadine; Gomez-Dans, Jose; Disney, Mathias

2016-07-01

Upcoming satellite constellations will substantially increase the amount of Earth Observation (EO) data, and presents us with the challenge of consistently using all these available information to infer the state of the land surface, parameterised through Essential Climate Variables (ECVs). A promising approach to this problem is the use of physically based models that describe the processes that generate the images, using e.g. radiative transfer (RT) theory. However, these models need to be inverted to infer the land surface parameters from the observations, and there is often not enough information in the EO data to satisfactorily achieve this. Data assimilation (DA) approaches supplement the EO data with prior information in the form of models or prior parameter distributions, and have the potential for solving the inversion problem. These methods however are computationally expensive. In this study, we show the use of fast surrogate models of the RT codes (emulators) based on Gaussian Processes (Gomez-Dans et al, 2016) embedded with the Earth Observation Land Data Assimilation System (EO-LDAS) framework (Lewis et al 2012) in order to estimate the surface of the land surface from a heterogeneous set of optical observations. The study uses time series of moderate spatial resolution observations from MODIS (250 m), MERIS (300 m) and MISR (275 m) over one site to infer the temporal evolution of a number of land surface parameters (and associated uncertainties) related to vegetation: leaf area index (LAI), leaf chlorophyll content, etc. These parameter estimates are then used as input to an RT model (semidiscrete or PROSAIL, for example) to calculate fluxes such as broad band albedo or fAPAR. The study demonstrates that blending different sensors in a consistent way using physical models results in a rich and coherent set of land surface parameters retrieved, with quantified uncertainties. The use of RT models also allows for the consistent prediction of fluxes, with a simple mechanism for propagating the uncertainty in the land surface parameters to the flux estimates.

Validation of the Land-Surface Energy Budget and Planetary Boundary Layer for Several Intensive field Experiments

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Schubert, Siegfried; Molod, Andrea; Houser, Paul R.

1999-01-01

Land-surface processes in a data assimilation system influence the lower troposphere and must be properly represented. With the recent incorporation of the Mosaic Land-surface Model (LSM) into the GEOS Data Assimilation System (DAS), the detailed land-surface processes require strict validation. While global data sources can identify large-scale systematic biases at the monthly timescale, the diurnal cycle is difficult to validate. Moreover, global data sets rarely include variables such as evaporation, sensible heat and soil water. Intensive field experiments, on the other hand, can provide high temporal resolution energy budget and vertical profile data for sufficiently long periods, without global coverage. Here, we evaluate the GEOS DAS against several intensive field experiments. The field experiments are First ISLSCP Field Experiment (FIFE, Kansas, summer 1987), Cabauw (as used in PILPS, Netherlands, summer 1987), Atmospheric Radiation Measurement (ARM, Southern Great Plains, winter and summer 1998) and the Surface Heat Budget of the Arctic Ocean (SHEBA, Arctic ice sheet, winter and summer 1998). The sites provide complete surface energy budget data for periods of at least one year, and some periods of vertical profiles. This comparison provides a detailed validation of the Mosaic LSM within the GEOS DAS for a variety of climatologic and geographic conditions.

On the Role of Urban and Vegetative Land Cover in the Identification of Tornado Damage Using Dual-Resolution Multispectral Satellite Imagery

NASA Astrophysics Data System (ADS)

Kingfield, D.; de Beurs, K.

2014-12-01

It has been demonstrated through various case studies that multispectral satellite imagery can be utilized in the identification of damage caused by a tornado through the change detection process. This process involves the difference in returned surface reflectance between two images and is often summarized through a variety of ratio-based vegetation indices (VIs). Land cover type plays a large contributing role in the change detection process as the reflectance properties of vegetation can vary based on several factors (e.g. species, greenness, density). Consequently, this provides the possibility for a variable magnitude of loss, making certain land cover regimes less reliable in the damage identification process. Furthermore, the tradeoff between sensor resolution and orbital return period may also play a role in the ability to detect catastrophic loss. Moderate resolution imagery (e.g. Moderate Resolution Imaging Spectroradiometer (MODIS)) provides relatively coarse surface detail with a higher update rate which could hinder the identification of small regions that underwent a dynamic change. Alternatively, imagery with higher spatial resolution (e.g. Landsat) have a longer temporal return period between successive images which could result in natural recovery underestimating the absolute magnitude of damage incurred. This study evaluates the role of land cover type and sensor resolution on four high-end (EF3+) tornado events occurring in four different land cover groups (agriculture, forest, grassland, urban) in the spring season. The closest successive clear images from both Landsat 5 and MODIS are quality controlled for each case. Transacts of surface reflectance across a homogenous land cover type both inside and outside the damage swath are extracted. These metrics are synthesized through the calculation of six different VIs to rank the calculated change metrics by land cover type, sensor resolution and VI.

The effect of urban heat island on Izmir's city ecosystem and climate.

PubMed

Corumluoglu, Ozsen; Asri, Ibrahim

2015-03-01

Depending on the researches done on urban landscapes, it is found that the heat island intensity caused by the activities in any city has some impact on the ecosystem of the region and on the regional climate. Urban areas located in arid and semiarid lands somehow represent heat increase when it is compared with the heat in the surrounding rural areas. Thus, cities located amid forested and temperate climate regions show moderate temperatures. The impervious surfaces let the rainfall leave the city lands faster than undeveloped areas. This effect reduces water's cooling effects on these lands. More significantly, if trees and other vegetations are rare in any region, it means less evapotranspiration-the process by which trees "exhale" water. Trees also contribute to the cooling of urban lands by their shade. Land cover and land use maps can easily be produced by processing of remote sensing satellites' images, like processing of Landsat's images. As a result of this process, urban regions can be distinguished from vegetation. Analyzed GIS data produced and supported by these images can be utilized to determine the impact of urban land on energy, water, and carbon balances at the Earth's surface. Here in this study, it is found that remote sensing technique with thermal images is a liable technique to asses where urban heat islands and hot spots are located in cities. As an application area, in Izmir, it was found that the whole city was in high level of surface temperature as it was over 28 °C during the summer times. Beside this, the highest temperature values which go up to 47 °C are obtained at industrial regions especially where the iron-steel factories and the related industrial activities are.

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

Land and atmosphere interactions using satellite remote sensing and a coupled mesoscale/land surface model

NASA Astrophysics Data System (ADS)

Hong, Seungbum

Land and atmosphere interactions have long been recognized for playing a key role in climate and weather modeling. However their quantification has been challenging due to the complex nature of the land surface amongst various other reasons. One of the difficult parts in the quantification is the effect of vegetation which are related to land surface processes such soil moisture variation and to atmospheric conditions such as radiation. This study addresses various relational investigations among vegetation properties such as Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), surface temperature (TSK), and vegetation water content (VegWC) derived from satellite sensors such as Moderate Resolution Imaging Spectroradiometer (MODIS) and EOS Advanced Microwave Scanning Radiometer (AMSR-E). The study provides general information about a physiological behavior of vegetation for various environmental conditions. Second, using a coupled mesoscale/land surface model, we examined the effects of vegetation and its relationship with soil moisture on the simulated land-atmospheric interactions through the model sensitivity tests. The Weather Research and Forecasting (WRF) model was selected for this study, and the Noah land surface model (Noah LSM) implemented in the WRF model was used for the model coupled system. This coupled model was tested through two parameterization methods for vegetation fraction using MODIS data and through model initialization of soil moisture from High Resolution Land Data Assimilation System (HRLDAS). Then, this study evaluates the model improvements for each simulation method.

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...

Atmospheric Constraints on Landing Site Selection

NASA Astrophysics Data System (ADS)

Kass, David M.; Schofield, J. T.

2001-01-01

The Martian atmosphere is a significant part of the environment that the Mars Exploration Rovers (MER) will encounter. As such, it imposes important constraints on where the rovers can and cannot land. Unfortunately, as there are no meteorological instruments on the rovers, there is little atmospheric science that can be accomplished, and no scientific preference for landing sites. The atmosphere constrains landing site selection in two main areas, the entry descent and landing (EDL) process and the survivability of the rovers on the surface. EDL is influenced by the density profile and boundary layer winds (up to altitudes of 5 to 10 km). Surface survivability involves atmospheric dust, temperatures and winds. During EDL, the atmosphere is used to slow the lander down, both ballistically and on the parachute. This limits the maximum elevation of the landing site to -1.3 km below the MOLA reference aeroid. The landers need to encounter a sufficiently dense atmosphere to be able to stop, and the deeper the landing site, the more column integrated atmosphere the lander can pass through before reaching the surface. The current limit was determined both by a desire to be able to reach the hematite region and by a set of atmosphere models we developed for EDL simulations. These are based on Thermal Emission Spectrometer (TES) atmospheric profile measurements, Ames Mars General Circulation Model (MGCM) results, and the 1-D Ames GCM radiative/convective model by J. Murphy. The latter is used for the near surface diurnal cycle. The current version of our model encompasses representative latitude bands, but we intend to make specific models for the final candidate landing sites to insure that they fall within the general envelope. The second constraint imposed on potential landing sites through the EDL process is the near surface wind. The wind in the lower approximately 5 km determines the horizontal velocity that the landers have when they land. Due to the mechanics of the landing process, the total velocity (including both the horizontal and vertical components) determines whether or not the landers are successful. Unfortunately, the landing system has no easy way to nullify any horizontal velocity imparted by the wind, so the landing sites selected need to have as little wind as possible. In addition to the mean wind velocity, the landing system is sensitive to vertical wind shear in the lowest kilometer or so. Wind shear can deflect the retro rockets (RADs) from their nominal vertical orientation producing unwanted horizontal spacecraft velocities. Both mean velocity and wind shear are dominated by the the local topography and other surface properties (in particular albedo and thermal inertia which control the surface temperature). This is seen even in simplified 2-D mesoscale models. The effects in a fully 3-D model are expected to he even more topographically dependent. In particular there is potential for wind channeling in canyons and other terrain features. Boundary layer winds and wind shear are currently being modeled based on terrestrial data and boundary layer scaling laws modified for Martian conditions. We hope to supplement this with mesoscale model results (from several sources) once the number of landing sites is reduced to a manageable number.

Comparison of GCM subgrid fluxes calculated using BATS and SiB schemes with a coupled land-atmosphere high-resolution model

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

Shen, Jinmei; Arritt, R.W.

The importance of land-atmosphere interactions and biosphere in climate change studies has long been recognized, and several land-atmosphere interaction schemes have been developed. Among these, the Simple Biosphere scheme (SiB) of Sellers et al. and the Biosphere Atmosphere Transfer Scheme (BATS) of Dickinson et al. are two of the most widely known. The effects of GCM subgrid-scale inhomogeneities of surface properties in general circulation models also has received increasing attention in recent years. However, due to the complexity of land surface processes and the difficulty to prescribe the large number of parameters that determine atmospheric and soil interactions with vegetation,more » many previous studies and results seem to be contradictory. A GCM grid element typically represents an area of 10{sup 4}-10{sup 6} km{sup 2}. Within such an area, there exist variations of soil type, soil wetness, vegetation type, vegetation density and topography, as well as urban areas and water bodies. In this paper, we incorporate both BATS and SiB2 land surface process schemes into a nonhydrostatic, compressible version of AMBLE model (Atmospheric Model -- Boundary-Layer Emphasis), and compare the surface heat fluxes and mesoscale circulations calculated using the two schemes. 8 refs., 5 figs.« less

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.

Climate Responses to Changes in Land-surface Properties due to Wildfires

NASA Astrophysics Data System (ADS)

Liu, Y.; Hao, X.; Qu, J. J.

2015-12-01

Wildfires can feedback the atmosphere by impacting atmospheric radiation transfer and cloud microphysics through emitting smoke particles and the land-air heat and water fluxes through modifying land-surface properties. While the impacts through smoke particles have been extensively investigated recently, very few studies have been conducted to examine the impacts through land-surface property change. This study is to fill this gap by examining the climate responses to the changes in land-surface properties induced by several large wildfires in the United States. Satellite remote sensing tools including MODIS and Landsat are used to quantitatively evaluate the land-surface changes characterized by reduced vegetation coverage and increased albedo over long post-fire periods. Variations in air and soil temperature and moisture of the burned areas are also monitored. Climate modeling is conducted to simulate climate responses and understand the related physical processes and interactions. The preliminary results indicate noticeable changes in water and heat transfers from the ground to the atmosphere through several mechanisms. Larger albedo reduces solar radiation absorbed on the ground, leading to less energy for latent and sensible heat fluxes. With smaller vegetation coverage, water transfer from the soil to the atmosphere through transpiration is reduced. Meanwhile, the Bowen ratio becomes larger after burning and therefore more solar energy absorbed on the ground is converted into sensible heat instead of being used as latent energy for water phase change. In addition, reduced vegetation coverage reduces roughness and increases wind speed, which modify dynamic resistances to water and heat movements. As a result of the changes in the land-air heat and water fluxes, clouds and precipitation as well as other atmospheric processes are affected by wildfires.

Impact of the hard-coded parameters on the hydrologic fluxes of the land surface model Noah-MP

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Mai, Juliane; Samaniego, Luis; Clark, Martyn; Wulfmeyer, Volker; Attinger, Sabine; Thober, Stephan

2016-04-01

Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The process descriptions contain a number of parameters that can be soil or plant type dependent and are typically read from tabulated input files. Land surface models may have, however, process descriptions that contain fixed, hard-coded numbers in the computer code, which are not identified as model parameters. 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 importance of the fixed values on restricting the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options, which are mostly spatially constant values. This is in addition to the 71 standard parameters of Noah-MP, which mostly get distributed spatially by given vegetation and soil input maps. We performed a Sobol' global sensitivity analysis of Noah-MP to variations of the standard and hard-coded parameters for a specific set of process options. 42 standard parameters and 75 hard-coded parameters were active with the chosen process options. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated. These sensitivities were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's hydrologic 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. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs. These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the calculation of hydrologic signatures of the runoff data. Latent heat and total runoff exhibit very similar sensitivities towards standard and hard-coded parameters in Noah-MP because of their tight coupling via the water balance. It should therefore be comparable to calibrate Noah-MP either against latent heat observations or against river runoff data. Latent heat and total runoff are sensitive to both, plant and soil parameters. Calibrating only a parameter sub-set of only soil parameters, for example, thus limits the ability to derive realistic model parameters. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Grand challenges in understanding the interplay of climate and land changes

USGS Publications Warehouse

Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.; Ford, James D.; Fox, Andrew; Gallo, Kevin; Hatfield, Jerry L.; Henebry, Geoffrey M.; Huntington, Thomas G.; Liu, Zhihua; Loveland, Thomas R.; Norby, Richard J.; Sohl, Terry L.; Steiner, Allison L.; Yuan, Wenping; Zhang, Zhao; Zhao, Shuqing

2017-01-01

Half of Earth’s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affect a myriad of land surface processes and the adaptation behaviors. This study reviews the status and major knowledge gaps in the interactions of land and atmospheric changes and present 11 grand challenge areas for the scientific research and adaptation community in the coming decade. These land-cover and land-use change (LCLUC)-related areas include 1) impacts on weather and climate, 2) carbon and other biogeochemical cycles, 3) biospheric emissions, 4) the water cycle, 5) agriculture, 6) urbanization, 7) acclimation of biogeochemical processes to climate change, 8) plant migration, 9) land-use projections, 10) model and data uncertainties, and, finally, 11) adaptation strategies. Numerous studies have demonstrated the effects of LCLUC on local to global climate and weather systems, but these putative effects vary greatly in magnitude and even sign across space, time, and scale and thus remain highly uncertain. At the same time, many challenges exist toward improved understanding of the consequences of atmospheric and climate change on land process dynamics and services. Future effort must improve the understanding of the scale-dependent, multifaceted perturbations and feedbacks between land and climate changes in both reality and models. To this end, one critical cross-disciplinary need is to systematically quantify and better understand measurement and model uncertainties. Finally, LCLUC mitigation and adaptation assessments must be strengthened to identify implementation barriers, evaluate and prioritize opportunities, and examine how decision-making processes work in specific contexts.

Soil frost-induced soil moisture precipitation feedback and effects on atmospheric states

NASA Astrophysics Data System (ADS)

Hagemann, Stefan; Blome, Tanja; Ekici, Altug; Beer, Christian

2016-04-01

Permafrost or perennially frozen ground is an important part of the terrestrial cryosphere; roughly one quarter of Earth's land surface is underlain by permafrost. As it is a thermal phenomenon, its characteristics are highly dependent on climatic factors. The impact of the currently observed warming, which is projected to persist during the coming decades due to anthropogenic CO2 input, certainly has effects for the vast permafrost areas of the high northern latitudes. The quantification of these effects, however, is scientifically still an open question. This is partly due to the complexity of the system, where several feedbacks are interacting between land and atmosphere, sometimes counterbalancing each other. Moreover, until recently, many global circulation models (GCMs) and Earth system models (ESMs) lacked the sufficient representation of permafrost physics in their land surface schemes. Within the European Union FP7 project PAGE21, the land surface scheme JSBACH of the Max-Planck-Institute for Meteorology ESM (MPI-ESM) has been equipped with the representation of relevant physical processes for permafrost studies. These processes include the effects of freezing and thawing of soil water for both energy and water cycles, thermal properties depending on soil water and ice contents, and soil moisture movement being influenced by the presence of soil ice. In the present study, it will be analysed how these permafrost relevant processes impact large-scale hydrology and climate over northern hemisphere high latitude land areas. For this analysis, the atmosphere-land part of MPI-ESM, ECHAM6-JSBACH, is driven by prescribed observed SST and sea ice in an AMIP2-type setup with and without the newly implemented permafrost processes. Results show a large improvement in the simulated discharge. On one hand this is related to an improved snowmelt peak of runoff due to frozen soil in spring. On the other hand a subsequent reduction of soil moisture leads to a positive land atmosphere feedback to precipitation over the high latitudes, which reduces the model's wet biases in precipitation and evapotranspiration during the summer. This is noteworthy as soil moisture - atmosphere feedbacks have previously not been in the research focus over the high latitudes. These results point out the importance of high latitude physical processes at the land surface for the regional climate.

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.

Scaling water and energy fluxes in climate systems - Three land-atmospheric modeling experiments

NASA Technical Reports Server (NTRS)

Wood, Eric F.; Lakshmi, Venkataraman

1993-01-01

Three numerical experiments that investigate the scaling of land-surface processes - either of the inputs or parameters - are reported, and the aggregated processes are compared to the spatially variable case. The first is the aggregation of the hydrologic response in a catchment due to rainfall during a storm event and due to evaporative demands during interstorm periods. The second is the spatial and temporal aggregation of latent heat fluxes, as calculated from SiB. The third is the aggregation of remotely sensed land vegetation and latent and sensible heat fluxes using TM data from the FIFE experiment of 1987 in Kansas. In all three experiments it was found that the surface fluxes and land characteristics can be scaled, and that macroscale models based on effective parameters are sufficient to account for the small-scale heterogeneities investigated.

Towards Global Simulation of Irrigation in a Land Surface Model: Multiple Cropping and Rice Paddy in Southeast Asia

NASA Technical Reports Server (NTRS)

Beaudoing, Hiroko Kato; Rodell, Matthew; Ozdogan, Mutlu

2010-01-01

Agricultural land use significantly influences the surface water and energy balances. Effects of irrigation on land surface states and fluxes include repartitioning of latent and sensible heat fluxes, an increase in net radiation, and an increase in soil moisture and runoff. We are working on representing irrigation practices in continental- to global-scale land surface simulation in NASA's Global Land Data Assimilation System (GLDAS). Because agricultural practices across the nations are diverse, and complex, we are attempting to capture the first-order reality of the regional practices before achieving a global implementation. This study focuses on two issues in Southeast Asia: multiple cropping and rice paddy irrigation systems. We first characterize agricultural practices in the region (i.e., crop types, growing seasons, and irrigation) using the Global data set of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000) dataset. Rice paddy extent is identified using remote sensing products. Whether irrigated or rainfed, flooded fields need to be represented and treated explicitly. By incorporating these properties and processes into a physically based land surface model, we are able to quantify the impacts on the simulated states and fluxes.

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.

Land Cover Land Use Change and Soil Organic Carbon under Climate Variability in the Semi-Arid West African Sahel (1960-2050)

ERIC Educational Resources Information Center

Dieye, Amadou M.

2016-01-01

Land Cover Land Use (LCLU) change affects land surface processes recognized to influence climate change at local, national and global levels. Soil organic carbon is a key component for the functioning of agro-ecosystems and has a direct effect on the physical, chemical and biological characteristics of the soil. The capacity to model and project…

Relationship among land surface temperature and LUCC, NDVI in typical karst area.

PubMed

Deng, Yuanhong; Wang, Shijie; Bai, Xiaoyong; Tian, Yichao; Wu, Luhua; Xiao, Jianyong; Chen, Fei; Qian, Qinghuan

2018-01-12

Land surface temperature (LST) can reflect the land surface water-heat exchange process comprehensively, which is considerably significant to the study of environmental change. However, research about LST in karst mountain areas with complex topography is scarce. Therefore, we retrieved the LST in a karst mountain area from Landsat 8 data and explored its relationships with LUCC and NDVI. The results showed that LST of the study area was noticeably affected by altitude and underlying surface type. In summer, abnormal high-temperature zones were observed in the study area, perhaps due to karst rocky desertification. LSTs among different land use types significantly differed with the highest in construction land and the lowest in woodland. The spatial distributions of NDVI and LST exhibited opposite patterns. Under the spatial combination of different land use types, the LST-NDVI feature space showed an obtuse-angled triangle shape and showed a negative linear correlation after removing water body data. In summary, the LST can be retrieved well by the atmospheric correction model from Landsat 8 data. Moreover, the LST of the karst mountain area is controlled by altitude, underlying surface type and aspect. This study provides a reference for land use planning, ecological environment restoration in karst areas.

Hydro-meteorological processes on the Qinghai - Tibet Plateau observed from space

NASA Astrophysics Data System (ADS)

Menenti, Massimo; Colin, Jerome; Jia, Li; D'Urso, Guido; Foken, Thomas; Immerzeel, Walter; Jha, Ramakar; Liu, Qinhuo; Liu, Changming; Ma, Yaoming; Sobrino, Jose Antonio; Yan, Guangjian; Pelgrum, Henk; Porcu, Federico; Wang, Jian; Wang, Jiemin; Shen, Xueshun; Su, Zhongbo; Ueno, Kenichi

2014-05-01

The Qinghai - Tibet Plateau is characterized by a significant intra-annual variability and spatial heterogeneity of surface conditions. Snow and vegetation cover, albedo, surface temperature and wetness change very significantly during the year and from place to place. The influence of temporal changes on convective events and the onset of the monsoon has been documented by ground based measurements of land - atmosphere exchanges of heat and water. The state of the land surface over the entire Plateau can be determined by space observation of surface albedo, temperature, snow and vegetation cover and soil moisture. Fully integrated use of satellite and ground observations is necessary to support water resources management in SE Asia and to clarify the roles of the interactions between the land surface and the atmosphere over the Tibetan Plateau in the Asian monsoon system. New or significantly improved algorithms have been developed and evaluated against ground measurements. Variables retrieved include land surface properties, rain rate, aerosol optical depth, water vapour, snow cover and water equivalent, soil moisture and lake level. The three years time series of gap-free daily and hourly evaporation derived from geostationary data collected by the FY-2D satellite was a major achievement. The hydrologic modeling system has been implemented and applied to the Qinghai Tibet Plateau and the headwaters of the major rivers in South and East Asia. Case studies on response of atmospheric circulation and specifically of convective activity to land surface conditions have been completed and the controlling land surface conditions and processes have been documented. Two new drought indicators have been developed: Normalized Temperature Anomaly Index (NTAI) and Normalized Vegetation Anomaly Index (NVAI). Case study in China and India showed that these indicators capture effectively drought severity and evolution. A new method has been developed for monitoring and early warning of flooded areas at the regional scale.

The impact of anthropogenic land use and land cover change on regional climate extremes.

PubMed

Findell, Kirsten L; Berg, Alexis; Gentine, Pierre; Krasting, John P; Lintner, Benjamin R; Malyshev, Sergey; Santanello, Joseph A; Shevliakova, Elena

2017-10-20

Land surface processes modulate the severity of heat waves, droughts, and other extreme events. However, models show contrasting effects of land surface changes on extreme temperatures. Here, we use an earth system model from the Geophysical Fluid Dynamics Laboratory to investigate regional impacts of land use and land cover change on combined extremes of temperature and humidity, namely aridity and moist enthalpy, quantities central to human physiological experience of near-surface climate. The model's near-surface temperature response to deforestation is consistent with recent observations, and conversion of mid-latitude natural forests to cropland and pastures is accompanied by an increase in the occurrence of hot-dry summers from once-in-a-decade to every 2-3 years. In the tropics, long time-scale oceanic variability precludes determination of how much of a small, but significant, increase in moist enthalpy throughout the year stems from the model's novel representation of historical patterns of wood harvesting, shifting cultivation, and regrowth of secondary vegetation and how much is forced by internal variability within the tropical oceans.

Geographical Applications of Remote Sensing

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

Weng, Qihao; Zhou, Yuyu; Quattrochi, Dale

2013-02-28

Data and Information derived through Earth observation technology have been extensively used in geographic studies, such as in the areas of natural and human environments, resources, land use and land cover, human-environment interactions, and socioeconomic issues. Land-use and land-cover change (LULCC), affecting biodiversity, climate change, watershed hydrology, and other surface processes, is one of the most important research topics in geography.

A review of our understanding of the role played in the climate system by land surface processes (Invited)

NASA Astrophysics Data System (ADS)

Nicholson, S. E.

2013-12-01

The paper provides an historical review of research on the impact of the land surface on climate. It commences will the seminal work of Jule Charney on albedo as a potential cause of drought and follows the trail of follow-up studies on the question of desertification and its role in climate. With the exception of a very early paper by Namias, early work was limited mainly to modeling efforts. At the same time, several observational studies provided evidence that land surface feedbacks could enhance and prolong drought, especially in the African Sahel. Later work emphasized the role of soil moisture rather than albedo. Several important field studies also examined the role of the land surface. Examples include FIFE, HAPEX-Sahel and BOREAS. In recent years some major changes in the concept have occurred. There is now substantial observational evidence of an impact at the mesoscale. The role of land surface feedback on climate has become mainstream. Finally, a new subdiscipline has emerged that emphasizes feedbacks between the water cycle, vegetation and climate, namely ecohydrology.

The impact of CO2 fertilization and historical land use/land cover change on regional climate extremes

NASA Astrophysics Data System (ADS)

Findell, Kirsten; Berg, Alexis; Gentine, Pierre; Krasting, John; Lintner, Benjamin; Malyshev, Sergey; Santanello, Joseph; Shevliakova, Elena

2017-04-01

Recent research highlights the role of land surface processes in heat waves, droughts, and other extreme events. Here we use an earth system model (ESM) from the Geophysical Fluid Dynamics Laboratory (GFDL) to investigate the regional impacts of historical anthropogenic land use/land cover change (LULCC) and the vegetative response to changes in atmospheric CO2 on combined extremes of temperature and humidity. A bivariate assessment allows us to consider aridity and moist enthalpy extremes, quantities central to human experience of near-surface climate conditions. We show that according to this model, conversion of forests to cropland has contributed to much of the upper central US and central Europe experiencing extreme hot, dry summers every 2-3 years instead of every 10 years. In the tropics, historical patterns of wood harvesting, shifting cultivation and regrowth of secondary vegetation have enhanced near surface moist enthalpy, leading to extensive increases in the occurrence of humid conditions throughout the tropics year round. These critical land use processes and practices are not included in many current generation land models, yet these results identify them as critical factors in the energy and water cycles of the midlatitudes and tropics. Current work is targeted at understanding how CO2 fertilization of plant growth impacts water use efficiency and surface flux partitioning, and how these changes influence temperature and humidity extremes. We use this modeling work to explore how remote sensing can be used to determine how different forest ecosystems in different climatological regimes are responding to enhanced CO2 and a warming world.

Measurements and Modeling of Turbulent Fluxes during Persistent Cold Air Pool Events in Salt Lake Valley, Utah

NASA Astrophysics Data System (ADS)

Ivey, C. E.; Sun, X.; Holmes, H.

2017-12-01

Land surface processes are important in meteorology and climate research since they control the partitioning of surface energy and water exchange at the earth's surface. The surface layer is coupled to the planetary boundary layer (PBL) by surface fluxes, which serve as sinks or sources of energy, moisture, momentum, and atmospheric pollutants. Quantifying the surface heat and momentum fluxes at the land-atmosphere interface, especially for different surface land cover types, is important because they can further influence the atmospheric dynamics, vertical mixing, and transport processes that impact local, regional, and global climate. A cold air pool (CAP) forms when a topographic depression (i.e., valley) fills with cold air, where the air in the stagnant layer is colder than the air aloft. Insufficient surface heating, which is not able to sufficiently erode the temperature inversion that forms during the nighttime stable boundary layer, can lead to the formation of persistent CAPs during wintertime. These persistent CAPs can last for days, or even weeks, and are associated with increased air pollution concentrations. Thus, realistic simulations of the land-atmosphere exchange are meaningful to achieve improved predictions of the accumulation, transport, and dispersion of air pollution concentrations. The focus of this presentation is on observations and modeling results using turbulence data collected in Salt Lake Valley, Utah during the 2010-2011 wintertime Persistent Cold Air Pool Study (PCAPS). Turbulent fluxes and the surface energy balance over seven land use types are quantified. The urban site has an energy balance ratio (EBR) larger than one (1.276). Negative Bowen ratio (-0.070) is found at the cropland site. In addition to turbulence observations, half-hourly WRF simulated net radiation, latent heat, sensible heat, ground heat fluxes during one persistent CAP event are evaluated using the PCAPS observations. The results show that sensible and latent heat fluxes during the CAP event are overestimated. The sensitivity of WRF results to large-scale forcing datasets, PBL schemes and land surface models (LSMs) are also investigated. The optimal WRF configuration for simulating surface turbulent fluxes and atmospheric mixing during CAP events is determined.

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.

Intercomparison of land-surface parameterizations launched

NASA Astrophysics Data System (ADS)

Henderson-Sellers, A.; Dickinson, R. E.

One of the crucial tasks for climatic and hydrological scientists over the next several years will be validating land surface process parameterizations used in climate models. There is not, necessarily, a unique set of parameters to be used. Different scientists will want to attempt to capture processes through various methods “for example, Avissar and Verstraete, 1990”. Validation of some aspects of the available (and proposed) schemes' performance is clearly required. It would also be valuable to compare the behavior of the existing schemes [for example, Dickinson et al., 1991; Henderson-Sellers, 1992a].The WMO-CAS Working Group on Numerical Experimentation (WGNE) and the Science Panel of the GEWEX Continental-Scale International Project (GCIP) [for example, Chahine, 1992] have agreed to launch the joint WGNE/GCIP Project for Intercomparison of Land-Surface Parameterization Schemes (PILPS). The principal goal of this project is to achieve greater understanding of the capabilities and potential applications of existing and new land-surface schemes in atmospheric models. It is not anticipated that a single “best” scheme will emerge. Rather, the aim is to explore alternative models in ways compatible with their authors' or exploiters' goals and to increase understanding of the characteristics of these models in the scientific community.

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.

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.

Improved global simulation of groundwater-ecosystem interactions via tight coupling of a dynamic global ecosystem model and a global hydrological model

NASA Astrophysics Data System (ADS)

Braakhekke, Maarten; Rebel, Karin; Dekker, Stefan; Smith, Benjamin; Sutanudjaja, Edwin; van Beek, Rens; van Kampenhout, Leo; Wassen, Martin

2017-04-01

In up to 30% of the global land surface ecosystems are potentially influenced by the presence of a shallow groundwater table. In these regions upward water flux by capillary rise increases soil moisture availability in the root zone, which has a strong effect on evapotranspiration, vegetation dynamics, and fluxes of carbon and nitrogen. Most global hydrological models and several land surface models simulate groundwater table dynamics and their effects on land surface processes. However, these models typically have relatively simplistic representation of vegetation and do not consider changes in vegetation type and structure. Dynamic global vegetation models (DGVMs), describe land surface from an ecological perspective, combining detailed description of vegetation dynamics and structure, and biogeochemical processes and are thus more appropriate to simulate the ecological and biogeochemical effects of groundwater interactions. However, currently virtually all DGVMs ignore these effects, assuming that water tables are too deep to affect soil moisture in the root zone. We have implemented a tight coupling between the dynamic global ecosystem model LPJ-GUESS and the global hydrological model PCR-GLOBWB, which explicitly simulates groundwater dynamics. This coupled model allows us to explicitly account for groundwater effects on terrestrial ecosystem processes at global scale. Results of global simulations indicate that groundwater strongly influences fluxes of water, carbon and nitrogen, in many regions, adding up to a considerable effect at the global scale.

Assessing the effects of the Great Eastern China urbanization on the East Asian summer monsoon by coupling an urban canopy model with a Regional Climate Model

NASA Astrophysics Data System (ADS)

Liu, Z.; Xue, Y.; Liu, S.; Oleson, K. W.

2012-12-01

The urbanization causes one of the most significant land cover changes. Especially over the eastern China from Beijing to Shanghai, the great urbanization occurs during the past half century.It modifies the physical characteristics of land surface, including land surface albedo, surface roughness length and aerodynamicresistanceand thermodynamic conduction over land. All of these play very important role in regional climate change. Afteremploying several WRF/Urban models to tests land use and land cover change(LUCC) caused by urbanization in East Asia, we decided to introducea urban canopy submodule,the Community Land surface Model urban scheme(CLMU)to the WRF and coupled with the WRF-SSiB3 regional climate model. The CLMU and SSIB share the similar principal to treat the surface energy and water balances and aerodynamic resistance between land and atmosphere. In the urban module, the energy balances on the five surface conditions are considered separately: building roof, sun side building wall, shade side building wall, pervious land surface and impervious road. The surface turbulence calculation is based on Monin-Obukhov similarity theory. We have made further improvements for the urban module. Over each surface condition, a method to calculate sky view factor (SVF) is developed based on the physically process while most urban models simply provide an empirical value for SVF. Our approach along with other improvement in short and long wave radiation transfer improves the accuracy of long-wave and shortwave radiation processing over urban surface. The force-restore approximation is employed to calculate the temperature of each outer surfaces of building. The inner side temperature is used as the restore term and was assigned as a tuning constant. Based on the nature of the force-restore method and our tests, we decide to employ the air mean temperature of last 72 hours as a restore term, which substantially improve the surface energy balance. We evaluate the ability of the newly coupled model by two runs: one without and one with the urban canopy module. The coupled model is integrated from March through September, covering a summer monsoon season. The preliminary results show more significant urban heat island (UHI) effect over urban areas with the urban canopy model. The existence of the UHIs enhances the convection in lower atmosphere, affects the water vapor transportation and precipitation of the surrounding area, consistent with the phenomena that occur in urban areas. We further test the effect of urbanization on the monsoon by introducing two maps, one with and one without urbanization and the effect of the urbanization on the monsoon evolution and low level circulation will be discussed in the presentation.

Impact of physical permafrost processes on hydrological change

NASA Astrophysics Data System (ADS)

Hagemann, Stefan; Blome, Tanja; Beer, Christian; Ekici, Altug

2015-04-01

Permafrost or perennially frozen ground is an important part of the terrestrial cryosphere; roughly one quarter of Earth's land surface is underlain by permafrost. As it is a thermal phenomenon, its characteristics are highly dependent on climatic factors. The impact of the currently observed warming, which is projected to persist during the coming decades due to anthropogenic CO2 input, certainly has effects for the vast permafrost areas of the high northern latitudes. The quantification of these effects, however, is scientifically still an open question. This is partly due to the complexity of the system, where several feedbacks are interacting between land and atmosphere, sometimes counterbalancing each other. Moreover, until recently, many global circulation models (GCMs) and Earth system models (ESMs) lacked the sufficient representation of permafrost physics in their land surface schemes. Within the European Union FP7 project PAGE21, the land surface scheme JSBACH of the Max-Planck-Institute for Meteorology ESM (MPI-ESM) has been equipped with the representation of relevant physical processes for permafrost studies. These processes include the effects of freezing and thawing of soil water for both energy and water cycles, thermal properties depending on soil water and ice contents, and soil moisture movement being influenced by the presence of soil ice. In the present study, it will be analysed how these permafrost relevant processes impact projected hydrological changes over northern hemisphere high latitude land areas. For this analysis, the atmosphere-land part of MPI-ESM, ECHAM6-JSBACH, is driven by prescribed SST and sea ice in an AMIP2-type setup with and without the newly implemented permafrost processes. Observed SST and sea ice for 1979-1999 are used to consider induced changes in the simulated hydrological cycle. In addition, simulated SST and sea ice are taken from a MPI-ESM simulation conducted for CMIP5 following the RCP8.5 scenario. The corresponding simulations with ECHAM6-JSBACH are used to assess differences in projected hydrological changes induced by the permafrost relevant processes.

Development of Airport Surface Required Navigation Performance (RNP)

NASA Technical Reports Server (NTRS)

Cassell, Rick; Smith, Alex; Hicok, Dan

1999-01-01

The U.S. and international aviation communities have adopted the Required Navigation Performance (RNP) process for defining aircraft performance when operating the en-route, approach and landing phases of flight. RNP consists primarily of the following key parameters - accuracy, integrity, continuity, and availability. The processes and analytical techniques employed to define en-route, approach and landing RNP have been applied in the development of RNP for the airport surface. To validate the proposed RNP requirements several methods were used. Operational and flight demonstration data were analyzed for conformance with proposed requirements, as were several aircraft flight simulation studies. The pilot failure risk component was analyzed through several hypothetical scenarios. Additional simulator studies are recommended to better quantify crew reactions to failures as well as additional simulator and field testing to validate achieved accuracy performance, This research was performed in support of the NASA Low Visibility Landing and Surface Operations Programs.

The esa earth explorer land surface processes and interactions mission

NASA Astrophysics Data System (ADS)

Labandibar, Jean-Yves; Jubineau, Franck; Silvestrin, Pierluigi; Del Bello, Umberto

2017-11-01

The European Space Agency (ESA) is defining candidate missions for Earth Observation. In the class of the Earth Explorer missions, dedicated to research and pre-operational demonstration, the Land Surface Processes and Interactions Mission (LSPIM) will acquire the accurate quantitative measurements needed to improve our understanding of the nature and evolution of biosphere-atmosphere interactions and to contribute significantly to a solution of the scaling problems for energy, water and carbon fluxes at the Earth's surface. The mission is intended to provide detailed observations of the surface of the Earth and to collect data related to ecosystem processes and radiation balance. It is also intended to address a range of issues important for environmental monitoring, renewable resources assessment and climate models. The mission involves a dedicated maneuvering satellite which provides multi-directional observations for systematic measurement of Land Surface BRDF (BiDirectional Reflectance Distribution Function) of selected sites on Earth. The satellite carries an optical payload : PRISM (Processes Research by an Imaging Space Mission), a multispectral imager providing reasonably high spatial resolution images (50 m over 50 km swath) in the whole optical spectral domain (from 450 nm to 2.35 μm with a resolution close to 10 nm, and two thermal bands from 8.1 to 9.1 μm). This paper presents the results of the Phase A study awarded by ESA, led by ALCATEL Space Industries and concerning the design of LSPIM.

Digital terrain modeling

NASA Astrophysics Data System (ADS)

Wilson, John P.

2012-01-01

This article examines how the methods and data sources used to generate DEMs and calculate land surface parameters have changed over the past 25 years. The primary goal is to describe the state-of-the-art for a typical digital terrain modeling workflow that starts with data capture, continues with data preprocessing and DEM generation, and concludes with the calculation of one or more primary and secondary land surface parameters. The article first describes some of ways in which LiDAR and RADAR remote sensing technologies have transformed the sources and methods for capturing elevation data. It next discusses the need for and various methods that are currently used to preprocess DEMs along with some of the challenges that confront those who tackle these tasks. The bulk of the article describes some of the subtleties involved in calculating the primary land surface parameters that are derived directly from DEMs without additional inputs and the two sets of secondary land surface parameters that are commonly used to model solar radiation and the accompanying interactions between the land surface and the atmosphere on the one hand and water flow and related surface processes on the other. It concludes with a discussion of the various kinds of errors that are embedded in DEMs, how these may be propagated and carried forward in calculating various land surface parameters, and the consequences of this state-of-affairs for the modern terrain analyst.

Comparing the Degree of Land-Atmosphere Interaction in Four Atmospheric General Circulation Models

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Dirmeyer, Paul A.; Hahmann, Andrea N.; Ijpelaar, Ruben; Tyahla, Lori; Cox, Peter; Suarez, Max J.; Houser, Paul R. (Technical Monitor)

2001-01-01

Land-atmosphere feedback, by which (for example) precipitation-induced moisture anomalies at the land surface affect the overlying atmosphere and thereby the subsequent generation of precipitation, has been examined and quantified with many atmospheric general circulation models (AGCMs). Generally missing from such studies, however, is an indication of the extent to which the simulated feedback strength is model dependent. Four modeling groups have recently performed a highly controlled numerical experiment that allows an objective inter-model comparison of land-atmosphere feedback strength. The experiment essentially consists of an ensemble of simulations in which each member simulation artificially maintains the same time series of surface prognostic variables. Differences in atmospheric behavior between the ensemble members then indicates the degree to which the state of the land surface controls atmospheric processes in that model. A comparison of the four sets of experimental results shows that feedback strength does indeed vary significantly between the AGCMs.

Land use and land cover changes in Zêzere watershed (Portugal)--Water quality implications.

PubMed

Meneses, B M; Reis, R; Vale, M J; Saraiva, R

2015-09-15

To understand the relations between land use allocation and water quality preservation within a watershed is essential to assure sustainable development. The land use and land cover (LUC) within Zêzere River watershed registered relevant changes in the last decades. These land use and land cover changes (LUCCs) have impacts in water quality, mainly in surface water degradation caused by surface runoff from artificial and agricultural areas, forest fires and burnt areas, and caused by sewage discharges from agroindustry and urban sprawl. In this context, the impact of LUCCs in the quality of surface water of the Zêzere watershed is evaluated, considering the changes for different types of LUC and establishing their possible correlations to the most relevant water quality changes. The results indicate that the loss of coniferous forest and the increase of transitional woodland-shrub are related to increased water's pH; while the growth in artificial surfaces and pastures leads mainly to the increase of soluble salts and fecal coliform concentration. These particular findings within the Zêzere watershed, show the relevance of addressing water quality impact driven from land use and should therefore be taken into account within the planning process in order to prevent water stress, namely within watersheds integrating drinking water catchments. Copyright © 2015 Elsevier B.V. All rights reserved.

Using a spatially-distributed hydrologic biogeochemistry model to study the spatial variation of carbon processes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; Davis, K. J.; He, Y.

2015-12-01

Forest carbon processes are affected by soil moisture, soil temperature and solar radiation. Most of the current biogeochemical models are 1-D and represent one point in space. Therefore they can neither resolve topographically driven hill-slope soil moisture patterns, nor simulate the nonlinear effects of soil moisture on carbon processes. A spatially-distributed biogeochemistry model, Flux-PIHM-BGC, has been developed by coupling the Biome-BGC (BBGC) model with a coupled physically-based land surface hydrologic model, Flux-PIHM. Flux-PIHM incorporates a land-surface scheme (adapted from the Noah land surface model) into the Penn State Integrated Hydrologic Model (PIHM). Because PIHM is capable of simulating lateral water flow and deep groundwater, Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. Flux-PIHM-BGC model was tested at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). The abundant observations at the SSHCZO, including eddy covariance fluxes, soil moisture, groundwater level, sap flux, stream discharge, litterfall, leaf area index, aboveground carbon stock, and soil carbon efflux, provided an ideal test bed for the coupled model. Model results show that when uniform solar radiation is used, vegetation carbon and soil carbon are positively correlated with soil moisture in space, which agrees with the observations within the watershed. When topographically-driven solar radiation is used, however, the wetter valley floor becomes radiation limited, and produces less vegetation and soil carbon than the drier hillslope due to the assumption that canopy height is uniform in the watershed. This contradicts with the observations, and suggests that a tree height model with dynamic allocation model are needed to reproduce the spatial variation of carbon processes within a watershed.

Mechanics of aeolian processes: Soil erosion and dust production

NASA Technical Reports Server (NTRS)

Mehrabadi, M. M.

1989-01-01

Aeolian (wind) processes occur as a result of atmosphere/land-surface system interactions. A thorough understanding of these processes and their physical/mechanical characterization on a global scale is essential to monitoring global change and, hence, is imperative to the fundamental goal of the Earth observing system (Eos) program. Soil erosion and dust production by wind are of consequence mainly in arid and semi arid regions which cover 36 percent of the Earth's land surface. Some recent models of dust production due to wind erosion of agricultural soils and the mechanics of wind erosion in deserts are reviewed and the difficulties of modeling the aeolian transport are discussed.

Assessing the Effects of Irrigation on Land Surface Processes Utilizing CLM.PF in Los Angeles, California

NASA Astrophysics Data System (ADS)

Reyes, B.; Vahmani, P.; Hogue, T. S.; Maxwell, R. M.

2013-05-01

Irrigation can significantly alter land surface properties including increases in evapotranspiration (ET) and latent heat flux and a decrease in land surface temperatures that have a wide range of effects on the hydrologic cycle. However, most irrigation in land surface modeling studies has generally been limited to large-scale cropland applications while ignoring the, relatively, much smaller use of irrigation in urban areas. Although this assumption may be valid in global studies, as we seek to apply models at higher resolutions and at more local scales, irrigation in urban areas can become a key factor in land-atmosphere interactions. Landscape irrigation can account for large portions of residential urban water use, especially in semi-arid environments (e.g. ~50% in Los Angeles, CA). Previous modeling efforts in urbanized semi-arid regions have shown that disregarding irrigation leads to inaccurate representation of the energy budget. The current research models a 49.5-km2 (19.11-mi2) domain near downtown Los Angeles in the Ballona Creek watershed at a high spatial and temporal resolution using a coupled hydrologic (ParFlow) and land surface model (CLM). Our goals are to (1) provide a sensitivity analysis for urban irrigation parameters including sensitivity to total volume and timing of irrigation, (2) assess the effects of irrigation on varying land cover types on the energy budget, and (3) evaluate if residential water use data is useful in providing estimates for irrigation in land surface modeling. Observed values of land surface parameters from remote sensing products (Land Surface Temperature and ET), water use data from the Los Angeles Department of Water and Power (LADWP), and modeling results from an irrigated version of the NOAH-Urban Canopy Model are being used for comparison and evaluation. Our analysis provides critical information on the degree to which urban irrigation should be represented in high-resolution, semi-arid urban land surface modeling of the region. This research also yields robust upper-boundary conditions for further analysis and modeling in Los Angeles.

Hydrologic impacts of land cover variability and change at seasonal to decadal time scales over North America, 1992-2016

NASA Astrophysics Data System (ADS)

Bohn, T. J.; Vivoni, E. R.

2017-12-01

Land cover variability and change have been shown to influence the terrestrial hydrologic cycle by altering the partitioning of moisture and energy fluxes. However, the magnitude and directionality of the relationship between land cover and surface hydrology has been shown to vary substantially across regions. Here, we provide an assessment of the impacts of land cover change on hydrologic processes at seasonal (vegetation phenology) to decadal scales (land cover conversion) in the United States and Mexico. To this end, we combine time series of remotely-sensed land surface characteristics with land cover maps for different decades as input to the Variable Infiltration Capacity hydrologic model. Land surface characteristics (leaf area index, surface albedo, and canopy fraction derived from normalized difference vegetation index) were obtained from the Moderate Resolution Imaging Spectrometer (MODIS) at 8-day intervals over the period 2000-2016. Land cover maps representing conditions in 1992, 2001, and 2011 were derived by homogenizing the National Land Cover Database over the US and the INEGI Series I through V maps over Mexico. An additional map covering all of North America was derived from the most frequent land cover class observed in each pixel of the MODIS MOD12Q1 product during 2001-2013. Land surface characteristics were summarized over land cover fractions at 1/16 degree (6 km) resolution. For each land cover map, hydrologic simulations were conducted that covered the period 1980-2013, using the best-available, hourly meteorological forcings at a similar spatial resolution. Based on these simulations, we present a comparison of the contributions of land cover change and climate variability at seasonal to decadal scales on the hydrologic and energy budgets, identifying the dominant components through time and space. This work also offers a valuable dataset on land cover variability and its hydrologic response for continental-scale assessments and modeling.

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 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.

Evaluate the urban effect on summer convective precipitation by coupling a urban canopy model with a Regional Climate Model

NASA Astrophysics Data System (ADS)

Liu, Z.; Liu, S.; Xue, Y.; Oleson, K. W.

2013-12-01

One of the most significant urbanization in the world occurred in Great Beijing Area of China during the past several decades. The land use and land cover changes modifies the land surface physical characteristics, including the anthropogenic heat and thermo-dynamic conduction. All of those play important roles in the urban regional climate changes. We developed a single layer urban canopy module based on the Community Land Surface Model Urban Module (CLMU). We have made further improvements in the urban module: the energy balances on the five surface conditions are considered separately: building roof, sun side and shade side wall, pervious and impervious land surface. Over each surface, a method to calculate sky view factor (SVF) is developed based on the physically process while most urban models simply provide an empirical value; A new scheme for calculating the latent heat flux is applied on both wall and impervious land; anthropogenic heat is considered in terms of industrial production, domestic wastes, vehicle and air condition. All of these developments improve the accuracy of surface energy balance processing in urban area. The urban effect on summer convective precipitation under the unstable atmospheric condition in the Great Beijing Area was investigated by simulating a heavy rainfall event in July 21st 2012. In this storm, strong meso-scale convective complexes (MCC) brought precipitation of averagely 164 mm within 6 hours, which is the record of past 60 years in the region. Numerical simulating experiment was set up by coupling MCLMU with WRF. Several condition/blank control cases were also set up. The horizontal resolution in all simulations was 2 km. While all of the control results drastically underestimate the urban precipitation, the result of WRF-MCLMU is much closer to the observation though still underestimated. More sensitive experiments gave a preliminary conclusion of how the urban canopy physics processing affects the local precipitation: the existence of large area of impervious surfaces restrain the surface evaporation and latent heat flux in urban while the anthropogenic heat and enhanced sensible heat flux warm up the lower atmospheric layer and strengthen the vertical stratification instability; In this storm event, the water supply of the MCC was thought to be sufficient, thus the instability of the vertical stratification was the key factor for precipitation.

NASA Cold Land Processes Experiment (CLPX 2002/03): Ground-based and near-surface meteorological observations

Treesearch

Kelly Elder; Don Cline; Angus Goodbody; Paul Houser; Glen E. Liston; Larry Mahrt; Nick Rutter

2009-01-01

A short-term meteorological database has been developed for the Cold Land Processes Experiment (CLPX). This database includes meteorological observations from stations designed and deployed exclusively for CLPXas well as observations available from other sources located in the small regional study area (SRSA) in north-central Colorado. The measured weather parameters...

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...

Observed increase in local cooling effect of deforestation at higher latitudes

Treesearch

Xuhui Lee; Michael L. Goulden; David Y. Hollinger; Alan Barr; T. Andrew Black; Gil Bohrer; Rosvel Bracho; Bert Drake; Allen Goldstein; Lianhong Gu; Gabriel Katul; Thomas Kolb; Beverly E. Law; Hank Margolis; Tilden Meyers; Russell Monson; William Munger; Ram Oren; Kyaw Tha Paw U; Andrew D. Richardson; Hans Peter Schmid; Ralf Staebler; Steven Wofsy; Lei Zhao

2011-01-01

Deforestation in mid- to high latitudes is hypothesized to have the potential to cool the Earth's surface by altering biophysical processes. In climate models of continental-scale land clearing, the cooling is triggered by increases in surface albedo and is reinforced by a land albedo–sea ice feedback. This feedback is crucial in the model predictions; without it...

Possible rainfall reduction through reduced surface temperatures due to overgrazing

NASA Technical Reports Server (NTRS)

Otterman, J.

1975-01-01

Surface temperature reduction in terrain denuded of vegetation (as by overgrazing) is postulated to decrease air convection, reducing cloudiness and rainfall probability during weak meteorological disturbances. By reducing land-sea daytime temperature differences, the surface temperature reduction decreases daytime circulation of thermally driven local winds. The described desertification mechanism, even when limited to arid regions, high albedo soils, and weak meteorological disturbances, can be an effective rainfall reducing process in many areas including most of the Mediterranean lands.

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-Atmosphere Coupling in the Multi-Scale Modelling Framework

NASA Astrophysics Data System (ADS)

Kraus, P. M.; Denning, S.

2015-12-01

The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced conceptual gap between model resolution and parameterized processes.

Pairing FLUXNET sites to validate model representations of land-use/land-cover change

NASA Astrophysics Data System (ADS)

Chen, Liang; Dirmeyer, Paul A.; Guo, Zhichang; Schultz, Natalie M.

2018-01-01

Land surface energy and water fluxes play an important role in land-atmosphere interactions, especially for the climatic feedback effects driven by land-use/land-cover change (LULCC). These have long been documented in model-based studies, but the performance of land surface models in representing LULCC-induced responses has not been investigated well. In this study, measurements from proximate paired (open versus forest) flux tower sites are used to represent observed deforestation-induced changes in surface fluxes, which are compared with simulations from the Community Land Model (CLM) and the Noah Multi-Parameterization (Noah-MP) land model. Point-scale simulations suggest the CLM can represent the observed diurnal and seasonal changes in net radiation (Rnet) and ground heat flux (G), but difficulties remain in the energy partitioning between latent (LE) and sensible (H) heat flux. The CLM does not capture the observed decreased daytime LE, and overestimates the increased H during summer. These deficiencies are mainly associated with models' greater biases over forest land-cover types and the parameterization of soil evaporation. Global gridded simulations with the CLM show uncertainties in the estimation of LE and H at the grid level for regional and global simulations. Noah-MP exhibits a similar ability to simulate the surface flux changes, but with larger biases in H, G, and Rnet change during late winter and early spring, which are related to a deficiency in estimating albedo. Differences in meteorological conditions between paired sites is not a factor in these results. Attention needs to be devoted to improving the representation of surface heat flux processes in land models to increase confidence in LULCC simulations.

Vegetation controls on the biophysical surface properties at global scale

NASA Astrophysics Data System (ADS)

Forzieri, Giovanni; Cescatti, Alessandro

2016-04-01

Leaf area index (LAI) plays an important role in determining resistances to heat, moisture and momentum exchanges between the land surface and atmosphere. Exploring how variations in LAI may induce changes in the surface energy balance is a key to understanding vegetation-climate interactions and for predicting biophysical climate impacts associated to changes in land cover. To this end, we analyzed remote sensing-observed dynamics in LAI, surface energy fluxes and climate drivers at global scale. We investigated the link between interannual variability of LAI and the components of the surface energy budget under diverse climate gradients. Results show that a 25% increase in annual LAI may induce up to 2% increase in available surface energy, as consequence of higher short wave absorption due to reduced albedos, up to 20% increase and 10% decrease in latent and sensible heat, respectively, leading to a decrease of the Bowen ratio in densely vegetated canopies. Opposite patterns are found for a reduction in LAI of similar magnitude. Such changes are strongly modulated by concurrent year-to-year variations and climatological means of air temperature, precipitation and snow cover as well as by land cover-specific physiological processes. Boreal and semi-arid regions appear to be mostly exposed to large changes in biophysical surface processes induced by interannual fluctuations in LAI. The combination of the emergent patters translates into variations in the long-wave outgoing radiation that reflect the surface warming/cooling associated to LAI changes. These findings provide a deeper understanding of the vegetation control on biophysical surface properties and define a set of observational-based diagnostics of LAI-dependent land surface-atmosphere interactions.

Sensitivity of biogenic volatile organic compounds to land surface parameterizations and vegetation distributions in California

NASA Astrophysics Data System (ADS)

Zhao, Chun; Huang, Maoyi; Fast, Jerome D.; Berg, Larry K.; Qian, Yun; Guenther, Alex; Gu, Dasa; Shrivastava, Manish; Liu, Ying; Walters, Stacy; Pfister, Gabriele; Jin, Jiming; Shilling, John E.; Warneke, Carsten

2016-05-01

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface scheme CLM4 (Community Land Model version 4.0) in the Weather Research and Forecasting model with chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a stand-alone vegetation map that differs from what is used by land surface schemes. This improved modeling framework is used to investigate the impact of two land surface schemes, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provided an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface schemes do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry and, consequently, secondary organic aerosol formation.

Simulation of the Indian Summer Monsoon Using Comprehensive Atmosphere-land Interactions, in the Absence of Two-way Air-sea Interactions

NASA Technical Reports Server (NTRS)

Lim, Young-Kwon; Shin, D. W.; Cocke, Steven; Kang, Sung-Dae; Kim, Hae-Dong

2011-01-01

Community Land Model version 2 (CLM2) as a comprehensive land surface model and a simple land surface model (SLM) were coupled to an atmospheric climate model to investigate the role of land surface processes in the development and the persistence of the South Asian summer monsoon. Two-way air-sea interactions were not considered in order to identify the reproducibility of the monsoon evolution by the comprehensive land model, which includes more realistic vertical soil moisture structures, vegetation and 2-way atmosphere-land interactions at hourly intervals. In the monsoon development phase (May and June). comprehensive land-surface treatment improves the representation of atmospheric circulations and the resulting convergence/divergence through the improvements in differential heating patterns and surface energy fluxes. Coupling with CLM2 also improves the timing and spatial distribution of rainfall maxima, reducing the seasonal rainfall overestimation by approx.60 % (1.8 mm/d for SLM, 0.7 mm/dI for CLM2). As for the interannual variation of the simulated rainfall, correlation coefficients of the Indian seasonal rainfall with observation increased from 0.21 (SLM) to 0.45 (CLM2). However, in the mature monsoon phase (July to September), coupling with the CLM2 does not exhibit a clear improvement. In contrast to the development phase, latent heat flux is underestimated and sensible heat flux and surface temperature over India are markedly overestimated. In addition, the moisture fluxes do not correlate well with lower-level atmospheric convergence, yielding correlation coefficients and root mean square errors worse than those produced by coupling with the SLM. A more realistic representation of the surface temperature and energy fluxes is needed to achieve an improved simulation for the mature monsoon period.

Using dry spell dynamics of land surface temperature to evaluate large-scale model representation of soil moisture control on evapotranspiration

NASA Astrophysics Data System (ADS)

Taylor, Christopher M.; Harris, Philip P.; Gallego-Elvira, Belen; Folwell, Sonja S.

2017-04-01

The soil moisture control on the partition of land surface fluxes between sensible and latent heat is a key aspect of land surface models used within numerical weather prediction and climate models. As soils dry out, evapotranspiration (ET) decreases, and the excess energy is used to warm the atmosphere. Poor simulations of this dynamic process can affect predictions of mean, and in particular, extreme air temperatures, and can introduce substantial biases into projections of climate change at regional scales. The lack of reliable observations of fluxes and root zone soil moisture at spatial scales that atmospheric models use (typically from 1 to several hundred kilometres), coupled with spatial variability in vegetation and soil properties, makes it difficult to evaluate the flux partitioning at the model grid box scale. To overcome this problem, we have developed techniques to use Land Surface Temperature (LST) to evaluate models. As soils dry out, LST rises, so it can be used under certain circumstances as a proxy for the partition between sensible and latent heat. Moreover, long time series of reliable LST observations under clear skies are available globally at resolutions of the order of 1km. Models can exhibit large biases in seasonal mean LST for various reasons, including poor description of aerodynamic coupling, uncertainties in vegetation mapping, and errors in down-welling radiation. Rather than compare long-term average LST values with models, we focus on the dynamics of LST during dry spells, when negligible rain falls, and the soil moisture store is drying out. The rate of warming of the land surface, or, more precisely, its warming rate relative to the atmosphere, emphasises the impact of changes in soil moisture control on the surface energy balance. Here we show the application of this approach to model evaluation, with examples at continental and global scales. We can compare the behaviour of both fully-coupled land-atmosphere models, and land surface models forced by observed meteorology. This approach provides insight into a fundamental process that affects predictions on multiple time scales, and which has an important impact for society.

Simulation of Soil Frost and Thaw Fronts Dynamics with Community Land Model 4.5

NASA Astrophysics Data System (ADS)

Gao, J.; Xie, Z.

2016-12-01

Freeze-thaw processes in soils, including changes in frost and thaw fronts (FTFs) , are important physical processes. The movement of FTFs affects soil water and thermal characteristics, as well as energy and water exchanges between land surface and the atmosphere, and then the land surface hydrothermal process. In this study, a two-directional freeze and thaw algorithm for simulating FTFs is incorporated into the community land surface model CLM4.5, which is called CLM4.5-FTF. The simulated FTFs depth and soil temperature of CLM4.5-FTF compared well with the observed data both in D66 station (permafrost) and Hulugou station (seasonally frozen soil). Because the soil temperature profile within a soil layer can be estimated according to the position of FTFs, CLM4.5 performed better in soil temperature simulation. Permafrost and seasonally frozen ground conditions in China from 1980 to 2010 were simulated using the CLM4.5-FTF. Numerical experiments show that the spatial distribution of simulated maximum frost depth by CLM4.5-FTF has seasonal variation obviously. Significant positive active-layer depth trends for permafrost regions and negative maximum freezing depth trends for seasonal frozen soil regions are simulated in response to positive air temperature trends except west of Black Sea.

PROCESS DESIGN MANUAL FOR LAND TREATMENT OF MUNICIPAL WASTEWATER

EPA Science Inventory

The USEPA guidance on land treatment of municipal and industrial wastewater is updated for the first time since 1984. The significant new technilogical changes include phytoremediation, vadose zone monitoring, new design approaches to surface irrigation, center pivot irrigation,...

Assessing the Impact of Land Use and Land Cover Change on Global Water Resources

NASA Astrophysics Data System (ADS)

Batra, N.; Yang, Y. E.; Choi, H. I.; Islam, A.; Charlotte, D. F.; Cai, X.; Kumar, P.

2007-12-01

Land use and land cover changes (LULCC) significantly modify the hydrological regime of the watersheds, affecting water resources and environment from regional to global scale. This study seeks to advance and integrate water and energy cycle observation, scientific understanding, and human impacts to assess future water availability. To achieve the research objective, we integrate and interpret past and current space based and in situ observations into a global hydrologic model (GHM). GHM is developed with enhanced spatial and temporal resolution, physical complexity, hydrologic theory and processes to quantify the impact of LULCC on physical variables: surface runoff, subsurface flow, groundwater, infiltration, ET, soil moisture, etc. Coupled with the common land model (CLM), a 3-dimensional volume averaged soil-moisture transport (VAST) model is expanded to incorporate the lateral flow and subgrid heterogeneity. The model consists of 11 soil-hydrology layers to predict lateral as well as vertical moisture flux transport based on Richard's equations. The primary surface boundary conditions (SBCs) include surface elevation and its derivatives, land cover category, sand and clay fraction profiles, bedrock depth and fractional vegetation cover. A consistent global GIS-based dataset is constructed for the SBCs of the model from existing observational datasets comprising of various resolutions, map projections and data formats. Global ECMWF data at 6-hour time steps for the period 1971 through 2000 is processed to get the forcing data which includes incoming longwave and shortwave radiation, precipitation, air temperature, pressure, wind components, boundary layer height and specific humidity. Land use land cover data, generated using IPCC scenarios for every 10 years from 2000 to 2100 is used for future assessment on water resources. Alterations due to LULCC on surface water balance components: ET, groundwater recharge and runoff are then addressed in the study. Land use change disrupts the hydrological cycle through increasing the water yield at some places leading to floods while diminishing, or even eliminating the low flow at other places.

Anticipating land surface change

PubMed Central

Streeter, Richard; Dugmore, Andrew J.

2013-01-01

The interplay of human actions and natural processes over varied spatial and temporal scales can result in abrupt transitions between contrasting land surface states. Understanding these transitions is a key goal of sustainability science because they can represent abrupt losses of natural capital. This paper recognizes flickering between alternate land surface states in advance of threshold change and critical slowing down in advance of both threshold changes and noncritical transformation. The early warning signals we observe are rises in autocorrelation, variance, and skewness within millimeter-resolution thickness measurements of tephra layers deposited in A.D. 2010 and A.D. 2011. These signals reflect changing patterns of surface vegetation, which are known to provide early warning signals of critical transformations. They were observed toward migrating soil erosion fronts, cryoturbation limits, and expanding deflation zones, thus providing potential early warning signals of land surface change. The record of the spatial patterning of vegetation contained in contemporary tephra layers shows how proximity to land surface change could be assessed in the widespread regions affected by shallow layers of volcanic fallout (those that can be subsumed within the existing vegetation cover). This insight shows how we could use tephra layers in the stratigraphic record to identify “near misses,” close encounters with thresholds that did not lead to tipping points, and thus provide additional tools for archaeology, sustainability science, and contemporary land management. PMID:23530230

AERO: A Decision Support Tool for Wind Erosion Assessment in Rangelands and Croplands

NASA Astrophysics Data System (ADS)

Galloza, M.; Webb, N.; Herrick, J.

2015-12-01

Wind erosion is a key driver of global land degradation, with on- and off-site impacts on agricultural production, air quality, ecosystem services and climate. Measuring rates of wind erosion and dust emission across land use and land cover types is important for quantifying the impacts and identifying and testing practical management options. This process can be assisted by the application of predictive models, which can be a powerful tool for land management agencies. The Aeolian EROsion (AERO) model, a wind erosion and dust emission model interface provides access by non-expert land managers to a sophisticated wind erosion decision-support tool. AERO incorporates land surface processes and sediment transport equations from existing wind erosion models and was designed for application with available national long-term monitoring datasets (e.g. USDI BLM Assessment, Inventory and Monitoring, USDA NRCS Natural Resources Inventory) and monitoring protocols. Ongoing AERO model calibration and validation are supported by geographically diverse data on wind erosion rates and land surface conditions collected by the new National Wind Erosion Research Network. Here we present the new AERO interface, describe parameterization of the underpinning wind erosion model, and provide a summary of the model applications across agricultural lands and rangelands in the United States.

The Proposed Surface Water and Ocean Topography (SWOT) Mission

NASA Astrophysics Data System (ADS)

Fu, Lee-Lueng; Alsdorf, Douglas; Rodriguez, Ernesto; Morrow, Rosemary; Mognard, Nelly; Vaze, Parag; Lafon, Thierry

2013-09-01

A new space mission concept called Surface Water and Ocean Topography (SWOT) is being developed jointly by a collaborative effort of the international oceanographic and hydrological communities for making high-resolution measurement of the water elevation of both the ocean and land surface water to answer the questions about the oceanic submesoscale processes and the storage and discharge of land surface water. The key instrument payload would be a Ka-band radar interferometer capable of making high-resolution wide-swath altimetry measurement. This paper describes the proposed science objectives and requirements as well as the measurement approach of SWOT, which is baselined to be launched in 2019. SWOT would demonstrate this new approach to advancing both oceanography and land hydrology and set a standard for future altimetry missions.

The Proposed Surface Water and Ocean Topography (SWOT) Mission

NASA Technical Reports Server (NTRS)

Fu, Lee-Lueng; Alsdorf, Douglas; Rodriguez, Ernesto; Morrow, Rosemary; Mognard, Nelly; Vaze, Parag; Lafon, Thierry

2012-01-01

A new space mission concept called Surface Water and Ocean Topography (SWOT) is being developed jointly by a collaborative effort of the international oceanographic and hydrological communities for making high-resolution measurement of the water elevation of both the ocean and land surface water to answer the questions about the oceanic submesoscale processes and the storage and discharge of land surface water. The key instrument payload would be a Ka-band radar interferometer capable of making high-resolution wide-swath altimetry measurement. This paper describes the proposed science objectives and requirements as well as the measurement approach of SWOT, which is baselined to be launched in 2019. SWOT would demonstrate this new approach to advancing both oceanography and land hydrology and set a standard for future altimetry missions.

Regional seasonal warming anomalies and land-surface feedbacks

NASA Astrophysics Data System (ADS)

Coffel, E.; Horton, R. M.

2017-12-01

Significant seasonal variations in warming are projected in some regions, especially central Europe, the southeastern U.S., and central South America. Europe in particular may experience up to 2°C more warming during June, July, and August than in the annual mean, enhancing the risk of extreme summertime heat. Previous research has shown that heat waves in Europe and other regions are tied to seasonal soil moisture variations, and that in general land-surface feedbacks have a strong effect on seasonal temperature anomalies. In this study, we show that the seasonal anomalies in warming are also due in part to land-surface feedbacks. We find that in regions with amplified warming during the hot season, surface soil moisture levels generally decline and Bowen ratios increase as a result of a preferential partitioning of incoming energy into sensible vs. latent. The CMIP5 model suite shows significant variability in the strength of land-atmosphere coupling and in projections of future precipitation and soil moisture. Due to the dependence of seasonal warming on land-surface processes, these inter-model variations influence the projected summertime warming amplification and contribute to the uncertainty in projections of future extreme heat.

Evaluation of snow modeling with Noah and Noah-MP land surface models in NCEP GFS/CFS system

NASA Astrophysics Data System (ADS)

Dong, J.; Ek, M. B.; Wei, H.; Meng, J.

2017-12-01

Land surface serves as lower boundary forcing in global forecast system (GFS) and climate forecast system (CFS), simulating interactions between land and the atmosphere. Understanding the underlying land model physics is a key to improving weather and seasonal prediction skills. With the upgrades in land model physics (e.g., release of newer versions of a land model), different land initializations, changes in parameterization schemes used in the land model (e.g., land physical parametrization options), and how the land impact is handled (e.g., physics ensemble approach), it always prompts the necessity that climate prediction experiments need to be re-conducted to examine its impact. The current NASA LIS (version 7) integrates NOAA operational land surface and hydrological models (NCEP's Noah, versions from 2.7.1 to 3.6 and the future Noah-MP), high-resolution satellite and observational data, and land DA tools. The newer versions of the Noah LSM used in operational models have a variety of enhancements compared to older versions, where the Noah-MP allows for different physics parameterization options and the choice could have large impact on physical processes underlying seasonal predictions. These impacts need to be reexamined before implemented into NCEP operational systems. A set of offline numerical experiments driven by the GFS forecast forcing have been conducted to evaluate the impact of snow modeling with daily Global Historical Climatology Network (GHCN).

The influence of subsurface hydrodynamics on convective precipitation

NASA Astrophysics Data System (ADS)

Rahman, A. S. M. M.; Sulis, M.; Kollet, S. J.

2014-12-01

The terrestrial hydrological cycle comprises complex processes in the subsurface, land surface, and atmosphere, which are connected via complex non-linear feedback mechanisms. The influence of subsurface hydrodynamics on land surface mass and energy fluxes has been the subject of previous studies. Several studies have also investigated the soil moisture-precipitation feedback, neglecting however the connection with groundwater dynamics. The objective of this study is to examine the impact of subsurface hydrodynamics on convective precipitation events via shallow soil moisture and land surface processes. A scale-consistent Terrestrial System Modeling Platform (TerrSysMP) that consists of an atmospheric model (COSMO), a land surface model (CLM), and a three-dimensional variably saturated groundwater-surface water flow model (ParFlow), is used to simulate hourly mass and energy fluxes over days with convective rainfall events over the Rur catchment, Germany. In order to isolate the effect of groundwater dynamics on convective precipitation, two different model configurations with identical initial conditions are considered. The first configuration allows the groundwater table to evolve through time, while a spatially distributed, temporally constant groundwater table is prescribed as a lower boundary condition in the second configuration. The simulation results suggest that groundwater dynamics influence land surface soil moisture, which in turn affects the atmospheric boundary layer (ABL) height by modifying atmospheric thermals. It is demonstrated that because of this sensitivity of ABL height to soil moisture-temperature feedback, the onset and magnitude of convective precipitation is influenced by subsurface hydrodynamics. Thus, the results provide insight into the soil moisture-precipitation feedback including groundwater dynamics in a physically consistent manner by closing the water cycle from aquifers to the atmosphere.

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

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Mai, Juliane; Samaniego, Luis; Clark, Martyn; Wulfmeyer, Volker; Branch, Oliver; Attinger, Sabine; Thober, Stephan

2016-09-01

Land surface models incorporate a large number of process descriptions, containing a multitude of parameters. These parameters are typically read from tabulated input files. Some of these parameters might be fixed numbers in the computer code though, which hinder model agility during calibration. Here we identified 139 hard-coded parameters in the model code of the Noah land surface model with multiple process options (Noah-MP). We performed a Sobol' global sensitivity analysis of Noah-MP for a specific set of process options, which includes 42 out of the 71 standard parameters and 75 out of the 139 hard-coded parameters. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated at 12 catchments within the United States with very different hydrometeorological regimes. Noah-MP's hydrologic output fluxes are sensitive to two thirds of its applicable standard parameters (i.e., Sobol' indexes above 1%). The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for direct evaporation, which proved to be oversensitive in other land surface models as well. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs. These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the calculation of hydrologic signatures of the runoff data. Latent heat and total runoff exhibit very similar sensitivities because of their tight coupling via the water balance. A calibration of Noah-MP against either of these fluxes should therefore give comparable results. Moreover, these fluxes are sensitive to both plant and soil parameters. Calibrating, for example, only soil parameters hence limit the ability to derive realistic model parameters. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Upscaling Empirically Based Conceptualisations to Model Tropical Dominant Hydrological Processes for Historical Land Use Change

NASA Astrophysics Data System (ADS)

Toohey, R.; Boll, J.; Brooks, E.; Jones, J.

2009-12-01

Surface runoff and percolation to ground water are two hydrological processes of concern to the Atlantic slope of Costa Rica because of their impacts on flooding and drinking water contamination. As per legislation, the Costa Rican Government funds land use management from the farm to the regional scale to improve or conserve hydrological ecosystem services. In this study, we examined how land use (e.g., forest, coffee, sugar cane, and pasture) affects hydrological response at the point, plot (1 m2), and the field scale (1-6ha) to empirically conceptualize the dominant hydrological processes in each land use. Using our field data, we upscaled these conceptual processes into a physically-based distributed hydrological model at the field, watershed (130 km2), and regional (1500 km2) scales. At the point and plot scales, the presence of macropores and large roots promoted greater vertical percolation and subsurface connectivity in the forest and coffee field sites. The lack of macropores and large roots, plus the addition of management artifacts (e.g., surface compaction and a plough layer), altered the dominant hydrological processes by increasing lateral flow and surface runoff in the pasture and sugar cane field sites. Macropores and topography were major influences on runoff generation at the field scale. Also at the field scale, antecedent moisture conditions suggest a threshold behavior as a temporal control on surface runoff generation. However, in this tropical climate with very intense rainstorms, annual surface runoff was less than 10% of annual precipitation at the field scale. Significant differences in soil and hydrological characteristics observed at the point and plot scales appear to have less significance when upscaled to the field scale. At the point and plot scales, percolation acted as the dominant hydrological process in this tropical environment. However, at the field scale for sugar cane and pasture sites, saturation-excess runoff increased as irrigation intensity and duration (e.g., quantity) increased. Upscaling our conceptual models to the watershed and regional scales, historical data (1970-2004) was used to investigate whether dominant hydrological processes changed over time due to land use change. Preliminary investigations reveal much higher runoff coefficients (<30%) at the larger watershed scales. The increase in importance of runoff at the larger geographic scales suggests an emerging process and process non-linearity between the smaller and larger scales. Upscaling is an important and useful concept when investigating catchment response using the tools of field work and/or physically distributed hydrological modeling.

Weak Hydrological Sensitivity to Temperature Change over Land, Independent of Climate Forcing

NASA Technical Reports Server (NTRS)

Samset, B. H.; Myhre, G.; Forster, P. M.; Hodnebrog, O.; Andrews, T.; Boucher, O.; Faluvegi, G.; Flaeschner, D.; Kasoar, M.; Kharin, V.;

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;

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.

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.

Assessment of Mars Pathfinder landing site predictions

USGS Publications Warehouse

Golombek, M.P.; Moore, H.J.; Haldemann, A.F.C.; Parker, T.J.; Schofield, J.T.

1999-01-01

Remote sensing data at scales of kilometers and an Earth analog were used to accurately predict the characteristics of the Mars Pathfinder landing site at a scale of meters. The surface surrounding the Mars Pathfinder lander in Ares Vallis appears consistent with orbital interpretations, namely, that it would be a rocky plain composed of materials deposited by catastrophic floods. The surface and observed maximum clast size appears similar to predictions based on an analogous surface of the Ephrata Fan in the Channeled Scabland of Washington state. The elevation of the site measured by relatively small footprint delay-Doppler radar is within 100 m of that determined by two-way ranging and Doppler tracking of the spacecraft. The nearly equal elevations of the Mars Pathfinder and Viking Lander 1 sites allowed a prediction of the atmospheric conditions with altitude (pressure, temperature, and winds) that were well within the entry, descent, and landing design margins. High-resolution (~38 m/pixel) Viking Orbiter 1 images showed a sparsely cratered surface with small knobs with relatively low slopes, consistent with observations of these features from the lander. Measured rock abundance is within 10% of that expected from Viking orbiter thermal observations and models. The fractional area covered by large, potentially hazardous rocks observed is similar to that estimated from model rock distributions based on data from the Viking landing sites, Earth analog sites, and total rock abundance. The bulk and fine-component thermal inertias measured from orbit are similar to those calculated from the observed rock size-frequency distribution. A simple radar echo model based on the reflectivity of the soil (estimated from its bulk density), and the measured fraction of area covered by rocks was used to approximate the quasi-specular and diffuse components of the Earth-based radar echos. Color and albedo orbiter data were used to predict the relatively dust free or unweathered surface around the Pathfinder lander compared to the Viking landing sites. Comparisons with the experiences of selecting the Viking landing sites demonstrate the enormous benefit the Viking data and its analyses and models had on the successful predictions of the Pathfinder site. The Pathfinder experience demonstrates that, in certain locations, geologic processes observed in orbiter data can be used to infer surface characteristics where those processes dominate over other processes affecting the Martian surface layer. Copyright 1999 by the American Geophysical Union.

Effects of Land Cover / Land Use, Soil Texture, and Vegetation on the Water Balance of Lake Chad Basin

NASA Astrophysics Data System (ADS)

Babamaaji, R. A.; Lee, J.

2013-12-01

Lake Chad Basin (LCB) has experienced drastic changes of land cover and poor water management practices during the last 50 years. The successive droughts in the 1970s and 1980s resulted in the shortage of surface water and groundwater resources. This problem of drought has a devastating implication on the natural resources of the Basin with great consequence on food security, poverty reduction and quality of life of the inhabitants in the LCB. Therefore, understanding the effects of land use / land cover must be a first step to find how they disturb cycle especially the groundwater in the LCB. The abundance of groundwater is affected by the climate change through the interaction with surface water, such as lakes and rivers, and disuse recharge through an infiltration process. Quantifying the impact of climate change on the groundwater resource requires reliable forecasting of changes in the major climatic variables and other spatial variations including the land use/land cover, soil texture, topographic slope, and vegetation. In this study, we employed a spatially distributed water balance model WetSpass to simulate a long-term average change of groundwater recharge in the LCB of Africa. WetSpass is a water balance-based model to estimate seasonal and spatial distribution of surface runoff, interception, evapotranspiration, and groundwater recharge. The model is especially suitable for studying the effect of land use/land cover change on the water regime in the LCB. The present study describes the concept of the model and its application to the development of recharge map of the LCB. The study shows that major role in the water balance of LCB. The mean yearly actual evapotranspiration (ET) from the basin range from 60mm - 400 mm, which is 90 % (69mm - 430) of the annual precipitation from 2003 - 2010. It is striking that about 50 - 60 % of the total runoff is produced on build-up (impervious surfaces), while much smaller contributions are obtained from vegetated, bare soil and open water surfaces. The result of this study also shows that runoff is high in the clay, clay loam and sandy-clay loam due to the lack of infiltration process in clay soil from capping or crusting or sealing of the soil pores, therefore this situation will aid runoff. The application of the WetSpass model shows that precipitation, soil texture and land use / land cover are three controlling factors affecting the water balance in the LCB. Key words: Groundwater recharge, surface runoff, evapotranspiration, water balance, meteorological, draught, Landuse changes, climate changes, WetSpass, GIS.

Development of an Operational Land Water Mask for MODIS Collection 6, and Influence on Downstream Data Products

NASA Technical Reports Server (NTRS)

Carroll, M. L.; DiMiceli, C. M.; Townshend, J. R. G.; Sohlberg, R. A.; Elders, A. I.; Devadiga, S.; Sayer, A. M.; Levy, R. C.

2016-01-01

Data from the Moderate Resolution Imaging Spectro-radiometer (MODIS)on-board the Earth Observing System Terra and Aqua satellites are processed using a land water mask to determine when an algorithm no longer needs to be run or when an algorithm needs to follow a different pathway. Entering the fourth reprocessing (Collection 6 (C6)) the MODIS team replaced the 1 km water mask with a 500 m water mask for improved representation of the continental surfaces. The new water mask represents more small water bodies for an overall increase in water surface from 1 to 2 of the continental surface. While this is still a small fraction of the overall global surface area the increase is more dramatic in certain areas such as the Arctic and Boreal regions where there are dramatic increases in water surface area in the new mask. MODIS products generated by the on-going C6 reprocessing using the new land water mask show significant impact in areas with high concentrations of change in the land water mask. Here differences between the Collection 5 (C5) and C6 water masks and the impact of these differences on the MOD04 aerosol product and the MOD11 land surface temperature product are shown.

High-resolution climate and land surface interactions modeling over Belgium: current state and decennial scale projections

NASA Astrophysics Data System (ADS)

Jacquemin, Ingrid; Henrot, Alexandra-Jane; Beckers, Veronique; Berckmans, Julie; Debusscher, Bos; Dury, Marie; Minet, Julien; Hamdi, Rafiq; Dendoncker, Nicolas; Tychon, Bernard; Hambuckers, Alain; François, Louis

2016-04-01

The interactions between land surface and climate are complex. Climate changes can affect ecosystem structure and functions, by altering photosynthesis and productivity or inducing thermal and hydric stresses on plant species. These changes then impact socio-economic systems, through e.g., lower farming or forestry incomes. Ultimately, it can lead to permanent changes in land use structure, especially when associated with other non-climatic factors, such as urbanization pressure. These interactions and changes have feedbacks on the climate systems, in terms of changing: (1) surface properties (albedo, roughness, evapotranspiration, etc.) and (2) greenhouse gas emissions (mainly CO2, CH4, N2O). In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), we aim at improving regional climate model projections at the decennial scale over Belgium and Western Europe by combining high-resolution models of climate, land surface dynamics and socio-economic processes. The land surface dynamics (LSD) module is composed of a dynamic vegetation model (CARAIB) calculating the productivity and growth of natural and managed vegetation, and an agent-based model (CRAFTY), determining the shifts in land use and land cover. This up-scaled LSD module is made consistent with the surface scheme of the regional climate model (RCM: ALARO) to allow simulations of the RCM with a fully dynamic land surface for the recent past and the period 2000-2030. In this contribution, we analyze the results of the first simulations performed with the CARAIB dynamic vegetation model over Belgium at a resolution of 1km. This analysis is performed at the species level, using a set of 17 species for natural vegetation (trees and grasses) and 10 crops, especially designed to represent the Belgian vegetation. The CARAIB model is forced with surface atmospheric variables derived from the monthly global CRU climatology or ALARO outputs (from a 4 km resolution simulation) for the recent past and the decennial projections. Evidently, these simulations lead to a first analysis of the impact of climate change on carbon stocks (e.g., biomass, soil carbon) and fluxes (e.g., gross and net primary productivities (GPP and NPP) and net ecosystem production (NEP)). The surface scheme is based on two land use/land cover databases, ECOPLAN for the Flemish region and, for the Walloon region, the COS-Wallonia database and the Belgian agricultural statistics for agricultural land. Land use and land cover are fixed through time (reference year: 2007) in these simulations, but a first attempt of coupling between CARAIB and CRAFTY will be made to establish dynamic land use change scenarios for the next decades. A simulation with variable land use would allow an analysis of land use change impacts not only on crop yields and the land carbon budget, but also on climate relevant parameters, such as surface albedo, roughness length and evapotranspiration towards a coupling with the RCM.

The mark of vegetation change on Earth's surface energy balance: data-driven diagnostics and model validation

NASA Astrophysics Data System (ADS)

Cescatti, A.; Duveiller, G.; Hooker, J.

2017-12-01

Changing vegetation cover not only affects the atmospheric concentration of greenhouse gases but also alters the radiative and non-radiative properties of the surface. The result of competing biophysical processes on Earth's surface energy balance varies spatially and seasonally, and can lead to warming or cooling depending on the specific vegetation change and on the background climate. To date these effects are not accounted for in land-based climate policies because of the complexity of the phenomena, contrasting model predictions and the lack of global data-driven assessments. To overcome the limitations of available observation-based diagnostics and of the on-going model inter-comparison, here we present a new benchmarking dataset derived from satellite remote sensing. This global dataset provides the potential changes induced by multiple vegetation transitions on the single terms of the surface energy balance. We used this dataset for two major goals: 1) Quantify the impact of actual vegetation changes that occurred during the decade 2000-2010, showing the overwhelming role of tropical deforestation in warming the surface by reducing evapotranspiration despite the concurrent brightening of the Earth. 2) Benchmark a series of ESMs against data-driven metrics of the land cover change impacts on the various terms of the surface energy budget and on the surface temperature. We anticipate that the dataset could be also used to evaluate future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes.

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.

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.

Numerical Study on the Stomatal Responses to Dry-Hot Wind Episodes and Its Effects on Land-Atmosphere Interactions.

PubMed

Wang, Shu; Zheng, Hui; Liu, Shuhua; Miao, Yucong; Li, Jing

2016-01-01

The wheat production in midland China is under serious threat by frequent Dry-Hot Wind (DHW) episodes with high temperature, low moisture and specific wind as well as intensive heat transfer and evapotranspiration. The numerical simulations of these episodes are important for monitoring grain yield and estimating agricultural water demand. However, uncertainties still remain despite that enormous experiments and modeling studies have been conducted concerning this issue, due to either inaccurate synoptic situation derived from mesoscale weather models or unrealistic parameterizations of stomatal physiology in land surface models. Hereby, we investigated the synoptic characteristics of DHW with widely-used mesoscale model Weather Research and Forecasting (WRF) and the effects of leaf physiology on surface evapotranspiration by comparing two land surface models: The Noah land surface model, and Peking University Land Model (PKULM) with stomata processes included. Results show that the WRF model could well replicate the synoptic situations of DHW. Two types of DHW were identified: (1) prevailing heated dry wind stream forces the formation of DHW along with intense sensible heating and (2) dry adiabatic processes overflowing mountains. Under both situations, the PKULM can reasonably model the stomatal closure phenomena, which significantly decreases both evapotranspiration and net ecosystem exchange of canopy, while these phenomena cannot be resolved in the Noah simulations. Therefore, our findings suggest that the WRF-PKULM coupled method may be a more reliable tool to investigate and forecast DHW as well as be instructive to crop models.

Numerical Study on the Stomatal Responses to Dry-Hot Wind Episodes and Its Effects on Land-Atmosphere Interactions

PubMed Central

Zheng, Hui; Liu, Shuhua; Miao, Yucong; Li, Jing

2016-01-01

The wheat production in midland China is under serious threat by frequent Dry-Hot Wind (DHW) episodes with high temperature, low moisture and specific wind as well as intensive heat transfer and evapotranspiration. The numerical simulations of these episodes are important for monitoring grain yield and estimating agricultural water demand. However, uncertainties still remain despite that enormous experiments and modeling studies have been conducted concerning this issue, due to either inaccurate synoptic situation derived from mesoscale weather models or unrealistic parameterizations of stomatal physiology in land surface models. Hereby, we investigated the synoptic characteristics of DHW with widely-used mesoscale model Weather Research and Forecasting (WRF) and the effects of leaf physiology on surface evapotranspiration by comparing two land surface models: The Noah land surface model, and Peking University Land Model (PKULM) with stomata processes included. Results show that the WRF model could well replicate the synoptic situations of DHW. Two types of DHW were identified: (1) prevailing heated dry wind stream forces the formation of DHW along with intense sensible heating and (2) dry adiabatic processes overflowing mountains. Under both situations, the PKULM can reasonably model the stomatal closure phenomena, which significantly decreases both evapotranspiration and net ecosystem exchange of canopy, while these phenomena cannot be resolved in the Noah simulations. Therefore, our findings suggest that the WRF-PKULM coupled method may be a more reliable tool to investigate and forecast DHW as well as be instructive to crop models. PMID:27648943

Simulation of 1986 South China Sea Monsoon with a Regional Climate Model

NASA Technical Reports Server (NTRS)

Tao, W. -K.; Lau, W. K.-M.; Jia, Y.; Juang, H.; Wetzel, P.; Qian, J.; Chen, C.

1999-01-01

A Regional Land-Atmosphere Climate Simulation System (RELACS) project is being developed at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes and in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water/energy cycles in the IndoChina/South China Sea (SCS) region. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. The original MM5 model (without PLACE) includes the option for either a simple slab soil model or a five-layer soil model (MRF) in which the soil moisture availability evolves over time. However, the MM5 soil models do not include the effects of vegetation, and thus important physical processes such as evapotranspiration and interception are precluded. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. In addition, the Penn State/NCAR MM5 atmospheric modeling system has been: (1) coupled to the Goddard Ice Microphysical scheme; (2) coupled to a turbulent kinetic energy (TKE) scheme; (3) modified to ensure cloud budget balance; and (4) incorporated initialization with the Goddard EOS data sets at NASA/Goddard Laboratory for Atmospheres. The improved MM5 with two nested domains (60 and 20 km horizontal resolution) was used to simulate convective activity over IndoChina and the South China Sea, during the monsoon season, from May 6 to May 20, 1986. The model results captured several dominant observed features, such as twin cyclones, a depression system over the Bay of Bengal, strong south-westerly winds over IndoChina before and during the on-set of convection over the SCS, and a vortex over the SCS. Two additional MM5 runs with different land process models, Blackadar and MRF, were performed, and their results are compared to the run with PLACE. The preliminary results indicate that the MM5 results using PLACE and Blackadar are in very good agreement, but the results using MRF do not contain the south-westerly wind over IndoChina prior to the on-set of convection over the SCS.

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, ...

75 FR 65625 - Agency Information Collection Activities; Proposed Collection; Comment Request; Hazardous Waste...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-26

... ICR are: Tank systems, Surface impoundments, Waste piles, Land treatment, Landfills, Incinerators..., Process vents, Equipment leaks, Containment buildings, Recovery/recycling. With each information...: Waste Piles 17 Subpart M: Land Treatment 0 Subpart N: Landfills 37 [[Page 65627

Geologic and climatic controls on streamflow generation processes in a complex eogenetic karst basin

NASA Astrophysics Data System (ADS)

Vibhava, F.; Graham, W. D.; Maxwell, R. M.

2012-12-01

Streamflow at any given location and time is representative of surface and subsurface contributions from various sources. The ability to fully identify the factors controlling these contributions is key to successfully understanding the transport of contaminants through the system. In this study we developed a fully integrated 3D surface water-groundwater-land surface model, PARFLOW, to evaluate geologic and climatic controls on streamflow generation processes in a complex eogenetic karst basin in North Central Florida. In addition to traditional model evaluation criterion, such as comparing field observations to model simulated streamflow and groundwater elevations, we quantitatively evaluated the model's predictions of surface-groundwater interactions over space and time using a suite of binary end-member mixing models that were developed using observed specific conductivity differences among surface and groundwater sources throughout the domain. Analysis of model predictions showed that geologic heterogeneity exerts a strong control on both streamflow generation processes and land atmospheric fluxes in this watershed. In the upper basin, where the karst aquifer is overlain by a thick confining layer, approximately 92% of streamflow is "young" event flow, produced by near stream rainfall. Throughout the upper basin the confining layer produces a persistent high surficial water table which results in high evapotranspiration, low groundwater recharge and thus negligible "inter-event" streamflow. In the lower basin, where the karst aquifer is unconfined, deeper water tables result in less evapotranspiration. Thus, over 80% of the streamflow is "old" subsurface flow produced by diffuse infiltration through the epikarst throughout the lower basin, and all surface contributions to streamflow originate in the upper confined basin. Climatic variability provides a secondary control on surface-subsurface and land-atmosphere fluxes, producing significant seasonal and interannual variability in these processes. Spatial and temporal patterns of evapotranspiration, groundwater recharge and streamflow generation processes reveal potential hot spots and hot moments for surface and groundwater contamination in this basin.

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.

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.

Enhancements to NASA's Land Atmosphere Near real-time Capability for EOS (LANCE)

NASA Astrophysics Data System (ADS)

Michael, K.; Davies, D. K.; Schmaltz, J. E.; Boller, R. A.; Mauoka, E.; Ye, G.; Vermote, E.; Harrison, S.; Rinsland, P. L.; Protack, S.; Durbin, P. B.; Justice, C. O.

2016-12-01

NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) supports application users interested in monitoring a wide variety of natural and man-made phenomena. Near Real-Time (NRT) data and imagery from the AIRS, AMSR2, MISR, MLS, MODIS, OMI and VIIRS instruments are available much quicker than routine processing allows. Most data products are available within 3 hours from satellite observation. NRT imagery are generally available 3-5 hours after observation. This article describes LANCE and enhancements made to LANCE over the last year. These enhancements include: the addition of MISR L1 Georeferenced Radiance and L2 Cloud Motion Vector products, AMSR2 Unified L2B Half-Orbit 25 km EASE-Grid Surface Soil Moisture products and VIIRS VIIRS Day/Night Band, Land Surface Reflectance and Corrected Surface reflectance products. In addition, the selection of LANCE NRT imagery that can be interactively viewed through Worldview and the Global Imagery Browse Services (GIBS) has been expanded. LANCE is also working to ingest and process data from OMPS.

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.

Asian Monsoons: Variability, Predictability, and Sensitivity to External Forcing

NASA Technical Reports Server (NTRS)

Yang, Song; Lau, K.-M.; Kim, K.-M.

1999-01-01

In this study, we have addressed the interannual variations of Asian monsoons including both broad-scale and regional monsoon components. Particular attention is devoted to the identities of the South China Sea monsoon and Indian monsoon. We use CPC Merged Analysis of Precipitation and NCEP reanalyses to define regional monsoon indices and to depict the various monsoons. Parallel modeling studies have also been carried out to assess the potential predictability of the broad-scale and regional monsoons. Each monsoon is characterized by its unique features. While the South Asian monsoon represents a classical monsoon in which anomalous circulation is governed by Rossby-wave dynamics, the Southeast Asian monsoon symbolizes a "hybrid" monsoon that features multi-cellular meridional circulation over eastern Asia. The broad-scale Asian monsoon links to the basin-wide atmospheric circulation over the Indian-Pacific oceans. Both Sea Surface Temperatures (SST) and land surface processes are important for determining the variations of all monsoons. For the broad-scale monsoon, SST anomalies are more important than land surface processes. However, for regional monsoons, land surface processes may become equally important. Both observation and model shows that the broad-scale monsoon is potentially more predictable than regional monsoons, and that the Southeast Asian monsoon may possess higher predictability than the South Asian monsoon.

Long-term records of global radiation, carbon and water fluxes derived from multi-satellite data and a process-based model

NASA Astrophysics Data System (ADS)

Ryu, Youngryel; Jiang, Chongya

2016-04-01

To gain insights about the underlying impacts of global climate change on terrestrial ecosystem fluxes, we present a long-term (1982-2015) global radiation, carbon and water fluxes products by integrating multi-satellite data with a process-based model, the Breathing Earth System Simulator (BESS). BESS is a coupled processed model that integrates radiative transfer in the atmosphere and canopy, photosynthesis (GPP), and evapotranspiration (ET). BESS was designed most sensitive to the variables that can be quantified reliably, fully taking advantages of remote sensing atmospheric and land products. Originally, BESS entirely relied on MODIS as input variables to produce global GPP and ET during the MODIS era. This study extends the work to provide a series of long-term products from 1982 to 2015 by incorporating AVHRR data. In addition to GPP and ET, more land surface processes related datasets are mapped to facilitate the discovery of the ecological variations and changes. The CLARA-A1 cloud property datasets, the TOMS aerosol datasets, along with the GLASS land surface albedo datasets, were input to a look-up table derived from an atmospheric radiative transfer model to produce direct and diffuse components of visible and near infrared radiation datasets. Theses radiation components together with the LAI3g datasets and the GLASS land surface albedo datasets, were used to calculate absorbed radiation through a clumping corrected two-stream canopy radiative transfer model. ECMWF ERA interim air temperature data were downscaled by using ALP-II land surface temperature dataset and a region-dependent regression model. The spatial and seasonal variations of CO2 concentration were accounted by OCO-2 datasets, whereas NOAA's global CO2 growth rates data were used to describe interannual variations. All these remote sensing based datasets are used to run the BESS. Daily fluxes in 1/12 degree were computed and then aggregated to half-month interval to match with the spatial-temporal resolution of LAI3g dataset. The BESS GPP and ET products were compared to other independent datasets including MPI-BGC and CLM. Overall, the BESS products show good agreement with the other two datasets, indicating a compelling potential for bridging remote sensing and land surface models.

Towards a more efficient and robust representation of subsurface hydrological processes in Earth System Models

NASA Astrophysics Data System (ADS)

Rosolem, R.; Rahman, M.; Kollet, S. J.; Wagener, T.

2017-12-01

Understanding the impacts of land cover and climate changes on terrestrial hydrometeorology is important across a range of spatial and temporal scales. Earth System Models (ESMs) provide a robust platform for evaluating these impacts. However, current ESMs lack the representation of key hydrological processes (e.g., preferential water flow, and direct interactions with aquifers) in general. The typical "free drainage" conceptualization of land models can misrepresent the magnitude of those interactions, consequently affecting the exchange of energy and water at the surface as well as estimates of groundwater recharge. Recent studies show the benefits of explicitly simulating the interactions between subsurface and surface processes in similar models. However, such parameterizations are often computationally demanding resulting in limited application for large/global-scale studies. Here, we take a different approach in developing a novel parameterization for groundwater dynamics. Instead of directly adding another complex process to an established land model, we examine a set of comprehensive experimental scenarios using a very robust and establish three-dimensional hydrological model to develop a simpler parameterization that represents the aquifer to land surface interactions. The main goal of our developed parameterization is to simultaneously maximize the computational gain (i.e., "efficiency") while minimizing simulation errors in comparison to the full 3D model (i.e., "robustness") to allow for easy implementation in ESMs globally. Our study focuses primarily on understanding both the dynamics for groundwater recharge and discharge, respectively. Preliminary results show that our proposed approach significantly reduced the computational demand while model deviations from the full 3D model are considered to be small for these processes.

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.

Understanding the Impacts of Climate Change and Land Use Dynamics Using a Fully Coupled Hydrologic Feedback Model between Surface and Subsurface Systems

NASA Astrophysics Data System (ADS)

Park, C.; Lee, J.; Koo, M.

2011-12-01

Climate is the most critical driving force of the hydrologic system of the Earth. Since the industrial revolution, the impacts of anthropogenic activities to the Earth environment have been expanded and accelerated. Especially, the global emission of carbon dioxide into the atmosphere is known to have significantly increased temperature and affected the hydrologic system. Many hydrologists have contributed to the studies regarding the climate change on the hydrologic system since the Intergovernmental Panel on Climate Change (IPCC) was created in 1988. Among many components in the hydrologic system groundwater and its response to the climate change and anthropogenic activities are not fully understood due to the complexity of subsurface conditions between the surface and the groundwater table. A new spatio-temporal hydrologic model has been developed to estimate the impacts of climate change and land use dynamics on the groundwater. The model consists of two sub-models: a surface model and a subsurface model. The surface model involves three surface processes: interception, runoff, and evapotranspiration, and the subsurface model does also three subsurface processes: soil moisture balance, recharge, and groundwater flow. The surface model requires various input data including land use, soil types, vegetation types, topographical elevations, and meteorological data. The surface model simulates daily hydrological processes for rainfall interception, surface runoff varied by land use change and crop growth, and evapotranspiration controlled by soil moisture balance. The daily soil moisture balance is a key element to link two sub-models as it calculates infiltration and groundwater recharge by considering a time delay routing through a vadose zone down to the groundwater table. MODFLOW is adopted to simulate groundwater flow and interaction with surface water components as well. The model is technically flexible to add new model or modify existing model as it is developed with an object-oriented language - Python. The model also can easily be localized by simple modification of soil and crop properties. The actual application of the model after calibration was successful and results showed reliable water balance and interaction between the surface and subsurface hydrologic systems.

Regional Scale/Regional Climate Model Development and Its Applications at Goddard

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lau, W.; Qian, J.; Jia, Y.; Wetzel, P.; Chou, M.-D.; Wang, Y.; Lynn, B.

2000-01-01

A Regional Land-Atmosphere Climate Simulation System (RELACS) is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model (Penn State/NCAR MM5) with improved physical processes and in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water/energy cycles in the Indo-China/South China Sea (SCS)/China, N. America and S. America region.

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.

Improving winter leaf area index estimation in coniferous forests and its significance in estimating the land surface albedo

NASA Astrophysics Data System (ADS)

Wang, Rong; Chen, Jing M.; Pavlic, Goran; Arain, Altaf

2016-09-01

Winter leaf area index (LAI) of evergreen coniferous forests exerts strong control on the interception of snow, snowmelt and energy balance. Simulation of winter LAI and associated winter processes in land surface models is challenging. Retrieving winter LAI from remote sensing data is difficult due to cloud contamination, poor illumination, lower solar elevation and higher radiation reflection by snow background. Underestimated winter LAI in evergreen coniferous forests is one of the major issues limiting the application of current remote sensing LAI products. It has not been fully addressed in past studies in the literature. In this study, we used needle lifespan to correct winter LAI in a remote sensing product developed by the University of Toronto. For the validation purpose, the corrected winter LAI was then used to calculate land surface albedo at five FLUXNET coniferous forests in Canada. The RMSE and bias values for estimated albedo were 0.05 and 0.011, respectively, for all sites. The albedo map over coniferous forests across Canada produced with corrected winter LAI showed much better agreement with the GLASS (Global LAnd Surface Satellites) albedo product than the one produced with uncorrected winter LAI. The results revealed that the corrected winter LAI yielded much greater accuracy in simulating land surface albedo, making the new LAI product an improvement over the original one. Our study will help to increase the usability of remote sensing LAI products in land surface energy budget modeling.

A dataset mapping the potential biophysical effects of vegetation cover change

NASA Astrophysics Data System (ADS)

Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

2018-02-01

Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes.

A dataset mapping the potential biophysical effects of vegetation cover change

PubMed Central

Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

2018-01-01

Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes. PMID:29461538

Climate changes impact the surface albedo of a forest ecosystem based on MODIS satellite data

NASA Astrophysics Data System (ADS)

Zoran, M. A.; Nemuc, A. V.

2007-10-01

Surface albedo is one of the most important biophysical parameter responsible for energy balance control and the surface temperature and boundary-layer structure of the atmosphere. Forest land surface albedo is also highly variable temporally showing both diurnal as well as seasonal variations. In forest systems, albedo controls the microclimate conditions which affects ecosystem physical, physiological, and biogeochemical processes such as energy balance, evapotranspiration, photosynthesis. Due to anthropogenic and natural factors, land cover and land use changes result is the land surfaces albedo change. The main aim of this paper is to investigate the albedo patterns due to the impact of atmospheric pollution and climate variations of a forest ecosystem Branesti-Cernica, placed to the North-East of Bucharest city, Romania based on satellite Landsat ETM+, IKONOS and MODIS data and climate station observations. Our study focuses on 3 years of data (2003-2005), each of which had a different climatic regime. As the physical climate system is very sensitive to surface albedo, forest ecosystems could significantly feedback to the projected climate change modeling scenarios through albedo changes. The results of this research have a number of applications in weather forecasting, climate change, and forest ecosystem studies.

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.

Reconstructing satellite images to quantify spatially explicit land surface change caused by fires and succession: A demonstration in the Yukon River Basin of interior Alaska

USGS Publications Warehouse

Huang, Shengli; Jin, Suming; Dahal, Devendra; Chen, Xuexia; Young, Claudia; Liu, Heping; Liu, Shuguang

2013-01-01

Land surface change caused by fires and succession is confounded by many site-specific factors and requires further study. The objective of this study was to reveal the spatially explicit land surface change by minimizing the confounding factors of weather variability, seasonal offset, topography, land cover, and drainage. In a pilot study of the Yukon River Basin of interior Alaska, we retrieved Normalized Difference Vegetation Index (NDVI), albedo, and land surface temperature (LST) from a postfire Landsat image acquired on August 5th, 2004. With a Landsat reference image acquired on June 26th, 1986, we reconstructed NDVI, albedo, and LST of 1987–2004 fire scars for August 5th, 2004, assuming that these fires had not occurred. The difference between actual postfire and assuming-no-fire scenarios depicted the fires and succession impact. Our results demonstrated the following: (1) NDVI showed an immediate decrease after burning but gradually recovered to prefire levels in the following years, in which burn severity might play an important role during this process; (2) Albedo showed an immediate decrease after burning but then recovered and became higher than prefire levels; and (3) Most fires caused surface warming, but cooler surfaces did exist; time-since-fire affected the prefire and postfire LST difference but no absolute trend could be found. Our approach provided spatially explicit land surface change rather than average condition, enabling a better understanding of fires and succession impact on ecological consequences at the pixel level.

A prototype for automation of land-cover products from Landsat Surface Reflectance Data Records

NASA Astrophysics Data System (ADS)

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

2014-12-01

Landsat data records of surface reflectance provide a three-decade history of land surface processes. Due to the vast number of these archived records, development of innovative approaches for automated data mining and information retrieval were necessary. Recently, we created a prototype utilizing open source software libraries for automatically generating annual Anderson Level 1 land cover maps and information products from data acquired by the Landsat Mission for the years 1984 to 2013. The automated prototype was applied to two target areas in northwestern and east-central North Dakota, USA. The approach required the National Land Cover Database (NLCD) and two user-input target acquisition year-days. The Landsat archive was mined for scenes acquired within a 100-day window surrounding these target dates, and then cloud-free pixels where chosen closest to the specified target acquisition dates. The selected pixels were then composited before completing an unsupervised classification using the NLCD. Pixels unchanged in pairs of the NLCD were used for training decision tree models in an iterative process refined with model confidence measures. The decision tree models were applied to the Landsat composites to generate a yearly land cover map and related information products. Results for the target areas captured changes associated with the recent expansion of oil shale production and agriculture driven by economics and policy, such as the increase in biofuel production and reduction in Conservation Reserve Program. Changes in agriculture, grasslands, and surface water reflect the local hydrological conditions that occurred during the 29-year span. Future enhancements considered for this prototype include a web-based client, ancillary spatial datasets, trends and clustering algorithms, and the forecasting of future land cover.

40 CFR 257.3-6 - Disease.

Code of Federal Regulations, 2010 CFR

2010-07-01

... this section. (1) Sewage sludge that is applied to the land surface or is incorporated into the soil is... incorporated into the soil are treated by a Process to Significantly Reduce Pathogens (as listed in appendix II... surface or are incorporated into the soil are treated by a Process to Further Reduce Pathogens, prior to...

40 CFR 257.3-6 - Disease.

Code of Federal Regulations, 2012 CFR

2012-07-01

... this section. (1) Sewage sludge that is applied to the land surface or is incorporated into the soil is... incorporated into the soil are treated by a Process to Significantly Reduce Pathogens (as listed in appendix II... surface or are incorporated into the soil are treated by a Process to Further Reduce Pathogens, prior to...

40 CFR 257.3-6 - Disease.

Code of Federal Regulations, 2014 CFR

2014-07-01

... this section. (1) Sewage sludge that is applied to the land surface or is incorporated into the soil is... incorporated into the soil are treated by a Process to Significantly Reduce Pathogens (as listed in appendix II... surface or are incorporated into the soil are treated by a Process to Further Reduce Pathogens, prior to...

40 CFR 257.3-6 - Disease.

Code of Federal Regulations, 2013 CFR

2013-07-01

... this section. (1) Sewage sludge that is applied to the land surface or is incorporated into the soil is... incorporated into the soil are treated by a Process to Significantly Reduce Pathogens (as listed in appendix II... surface or are incorporated into the soil are treated by a Process to Further Reduce Pathogens, prior to...

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.

Improving wind energy forecasts using an Ensemble Kalman Filter data assimilation technique in a fully coupled hydrologic and atmospheric model

NASA Astrophysics Data System (ADS)

Williams, J. L.; Maxwell, R. M.; Delle Monache, L.

2012-12-01

Wind power is rapidly gaining prominence as a major source of renewable energy. Harnessing this promising energy source is challenging because of the chaotic nature of wind and its propensity to change speed and direction over short time scales. Accurate forecasting tools are critical to support the integration of wind energy into power grids and to maximize its impact on renewable energy portfolios. Numerous studies have shown that soil moisture distribution and land surface vegetative processes profoundly influence atmospheric boundary layer development and weather processes on local and regional scales. Using the PF.WRF model, a fully-coupled hydrologic and atmospheric model employing the ParFlow hydrologic model with the Weather Research and Forecasting model coupled via mass and energy fluxes across the land surface, we have explored the connections between the land surface and the atmosphere in terms of land surface energy flux partitioning and coupled variable fields including hydraulic conductivity, soil moisture and wind speed, and demonstrated that reductions in uncertainty in these coupled fields propagate through the hydrologic and atmospheric system. We have adapted the Data Assimilation Research Testbed (DART), an implementation of the robust Ensemble Kalman Filter data assimilation algorithm, to expand our capability to nudge forecasts produced with the PF.WRF model using observational data. Using a semi-idealized simulation domain, we examine the effects of assimilating observations of variables such as wind speed and temperature collected in the atmosphere, and land surface and subsurface observations such as soil moisture on the quality of forecast outputs. The sensitivities we find in this study will enable further studies to optimize observation collection to maximize the utility of the PF.WRF-DART forecasting system.

A New Scheme for Considering Soil Water-Heat Transport Coupling Based on Community Land Model: Model Description and Preliminary Validation

NASA Astrophysics Data System (ADS)

Wang, Chenghai; Yang, Kai

2018-04-01

Land surface models (LSMs) have developed significantly over the past few decades, with the result that most LSMs can generally reproduce the characteristics of the land surface. However, LSMs fail to reproduce some details of soil water and heat transport during seasonal transition periods because they neglect the effects of interactions between water movement and heat transfer in the soil. Such effects are critical for a complete understanding of water-heat transport within a soil thermohydraulic regime. In this study, a fully coupled water-heat transport scheme (FCS) is incorporated into the Community Land Model (version 4.5) to replaces its original isothermal scheme, which is more complete in theory. Observational data from five sites are used to validate the performance of the FCS. The simulation results at both single-point and global scale show that the FCS improved the simulation of soil moisture and temperature. FCS better reproduced the characteristics of drier and colder surface layers in arid regions by considering the diffusion of soil water vapor, which is a nonnegligible process in soil, especially for soil surface layers, while its effects in cold regions are generally inverse. It also accounted for the sensible heat fluxes caused by liquid water flow, which can contribute to heat transfer in both surface and deep layers. The FCS affects the estimation of surface sensible heat (SH) and latent heat (LH) and provides the details of soil heat and water transportation, which benefits to understand the inner physical process of soil water-heat migration.

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.

High Performance Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System at NASA/GSFC

NASA Astrophysics Data System (ADS)

Peters-Lidard, C. D.; Kumar, S. V.; Santanello, J. A.; Tian, Y.; Rodell, M.; Mocko, D.; Reichle, R.

2008-12-01

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters-Lidard et al., 2007) is a flexible land surface modeling framework that has been developed 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. The LIS software was the co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts - North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell et al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of these systems, now use specific configurations of the LIS software in their current implementations. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through 'plugins'. In addition to these capabilities, LIS has also been demonstrated for parameter estimation (Peters-Lidard et al., 2008; Santanello et al., 2007) and data assimilation (Kumar et al., 2008). Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, land data assimilation and parameter estimation will be presented.

30 CFR 875.14 - Eligible lands and water after certification.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... 875.14 Section 875.14 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT... such mining or processing, and abandoned or left in an inadequate reclamation status before August 3, 1977. However, for Federal lands, waters, and facilities under the jurisdiction of the Forest Service...

Thermodynamic limits set relevant constraints to the soil-plant-atmosphere system and to optimality in terrestrial vegetation

NASA Astrophysics Data System (ADS)

Kleidon, Axel; Renner, Maik

2016-04-01

The soil-plant-atmosphere system is a complex system that is strongly shaped by interactions between the physical environment and vegetation. This complexity appears to demand equally as complex models to fully capture the dynamics of the coupled system. What we describe here is an alternative approach that is based on thermodynamics and which allows for comparatively simple formulations free of empirical parameters by assuming that the system is so complex that its emergent dynamics are only constrained by the thermodynamics of the system. This approach specifically makes use of the second law of thermodynamics, a fundamental physical law that is typically not being considered in Earth system science. Its relevance to land surface processes is that it fundamentally sets a direction as well as limits to energy conversions and associated rates of mass exchange, but it requires us to formulate land surface processes as thermodynamic processes that are driven by energy conversions. We describe an application of this approach to the surface energy balance partitioning at the diurnal scale. In this application the turbulent heat fluxes of sensible and latent heat are described as the result of a convective heat engine that is driven by solar radiative heating of the surface and that operates at its thermodynamic limit. The predicted fluxes from this approach compare very well to observations at several sites. This suggests that the turbulent exchange fluxes between the surface and the atmosphere operate at their thermodynamic limit, so that thermodynamics imposes a relevant constraint to the land surface-atmosphere system. Yet, thermodynamic limits do not entirely determine the soil-plant-atmosphere system because vegetation affects these limits, for instance by affecting the magnitude of surface heating by absorption of solar radiation in the canopy layer. These effects are likely to make the conditions at the land surface more favorable for photosynthetic activity, which then links this thermodynamic approach to optimality in vegetation. We also contrast this approach to common, semi-empirical approaches of surface-atmosphere exchange and discuss how thermodynamics may set a broader range of transport limitations and optimality in the soil-plant-atmosphere system.

Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns

NASA Astrophysics Data System (ADS)

Dong, Jingnuo; Ochsner, Tyson E.

2018-03-01

Soil moisture patterns are commonly thought to be dominated by land surface characteristics, such as soil texture, at small scales and by atmospheric processes, such as precipitation, at larger scales. However, a growing body of evidence challenges this conceptual model. We investigated the structural similarity and spatial correlations between mesoscale (˜1-100 km) soil moisture patterns and land surface and atmospheric factors along a 150 km transect using 4 km multisensor precipitation data and a cosmic-ray neutron rover, with a 400 m diameter footprint. The rover was used to measure soil moisture along the transect 18 times over 13 months. Spatial structures of soil moisture, soil texture (sand content), and antecedent precipitation index (API) were characterized using autocorrelation functions and fitted with exponential models. Relative importance of land surface characteristics and atmospheric processes were compared using correlation coefficients (r) between soil moisture and sand content or API. The correlation lengths of soil moisture, sand content, and API ranged from 12-32 km, 13-20 km, and 14-45 km, respectively. Soil moisture was more strongly correlated with sand content (r = -0.536 to -0.704) than with API for all but one date. Thus, land surface characteristics exhibit coherent spatial patterns at scales up to 20 km, and those patterns often exert a stronger influence than do precipitation patterns on mesoscale spatial patterns of soil moisture.

Spatio-temporal patterns in land use and management affecting surface runoff response of agricultural catchments - a review

NASA Astrophysics Data System (ADS)

Fiener, P.; Auerswald, K.; van Oost, K.

2009-04-01

In many landscapes, land use creates a complex pattern in addition to the patterns resulting from soil, topography and rain. Despite the static layout of fields, a spatio-temporally highly variable situation regarding the surface runoff and erosion processes results from the asynchronous seasonal variation associated with different land uses. While the behaviour of individual land-uses and their seasonal variation is analyzed in many studies, the spatio-temporal interaction related to this pattern is rarely studied despite its crucial influence on hydrological and geomorphic response of catchments. The difficulty in studying such interactions mainly results from the fact that it is impossible to set up a replicated experiment on the landscape scale. The purpose of this review is to present the advances made thus far in quantifying the effects of patchiness of land use and management on surface runoff response in agricultural catchments. We will focus on the effects of spatio-temporal patterns in land use patches on hydraulic connectivity between patches and within catchments. This will include the temporal patterns in land management affecting infiltration, surface roughness and hence runoff concentration within single fields or land use patches insofar as these effects must be known to evaluate the combined effect of patch behaviour in space and time on catchment connectivity and surface runoff. Surface runoff effects of patchiness and connectivity between patches or within a catchment, can either be addressed by modelling studies or by comprehensive catchment field measurements, e.g. paired-watershed experiments or landscape scale studies on different scales. This limits our review to studies at the scale of small catchments < 10 km², where the time constant of the network (i.e. travel time through it) is smaller than the infiltration phase. Despite this limitation, these small catchments are important as they constitute 2/3 of the total surface of large water drainage networks.

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.

Land-Atmosphere Interactions: Successes, Problems and Prospects

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Mocko, D. M.

1999-01-01

After two decades of active research, a much better understanding of the broader role of biospheric processes on the local climate has emerged. A surface-albedo increase, particularly in desert border regions of the subtropics (as well as the deforested tropical regions), leads to a net surface energy deficit, which in turn leads to a relative sinking and reduced rainfall. On the other hand, studies of the influence of altered ratios of evapotranspiration and sensible fluxes, in situations where the net solar income is unchanged, show that evapotranspiration is a more desirable flux for increased precipitation and vitality of the biosphere. Besides providing water vapor and convective available potential energy (CAPE) to the lower troposphere, evapotranspiration helps in building larger CAPE before "turning on" the moist-convection. Larger CAPE in the lower troposphere enables convection to reach into the deeper atmosphere thereby heating the upper troposphere; indeed, moist-convection is also accompanied by the evaporation of falling precipitation that cools and moistens the lower atmosphere. While convective, as opposed to stratiform, precipitation reduces the fractional cloud cover; it also allows more solar radiation to reach the surface thereby invigorating surface fluxes. These, together with moist convection and associated downdrafts help to maintain the characteristic upper temperature limit(s) of the moist-land as well as oceanic regions. Regardless of the above understanding, several important problems continue to hinder the accurate simulation of a realistic land atmosphere interaction in a numerical model (both GCM and/or Meso-scale models). Among the unsolved problems are parameterization of sub-grid scale land processes that include small-scale variability of soil moisture, snow-cover and snow-physics, the biodiversity of the biosphere, orography, local drainage characteristics under natural conditions, and surface flow over the natural terrain. A well-known non-linear response of surface fluxes to these variations makes the problem of parameterizing land-atmosphere interaction processes hard-to-address and simulate, particularly in a GCM. In our presentation, we will discuss how orographic, snow-cover, and water table interactions can be included into a Simple Biosphere Model such as SiB/SSiB. Figure I shows how, in the Russian region, spring snowmelt affects the soil moisture profile. Corresponding figure 2 shows how interaction with the water table decreases the natural evapotranspiration in the Sahel region simulation. While these simulations need better validation with data, the simulations reveal that surface processes are sensitive to these parameterizations. With these developments, we continue to advance our understanding of the interaction of land with the atmosphere aloft, but the intrinsic variability of the newer parameters, e. g., hydraulic properties of the soil, diminish the positive influences of these advances on the improved climate simulation with GCMs.

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.

Classification of Land Cover and Land Use Based on Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Yang, Chun; Rottensteiner, Franz; Heipke, Christian

2018-04-01

Land cover describes the physical material of the earth's surface, whereas land use describes the socio-economic function of a piece of land. Land use information is typically collected in geospatial databases. As such databases become outdated quickly, an automatic update process is required. This paper presents a new approach to determine land cover and to classify land use objects based on convolutional neural networks (CNN). The input data are aerial images and derived data such as digital surface models. Firstly, we apply a CNN to determine the land cover for each pixel of the input image. We compare different CNN structures, all of them based on an encoder-decoder structure for obtaining dense class predictions. Secondly, we propose a new CNN-based methodology for the prediction of the land use label of objects from a geospatial database. In this context, we present a strategy for generating image patches of identical size from the input data, which are classified by a CNN. Again, we compare different CNN architectures. Our experiments show that an overall accuracy of up to 85.7 % and 77.4 % can be achieved for land cover and land use, respectively. The classification of land cover has a positive contribution to the classification of the land use classification.

Validation of Land-Surface Mosaic Heterogeneity in the GEOS DAS

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Molod, Andrea; Houser, Paul R.; Schubert, Siegfried

1999-01-01

The Mosaic Land-surface Model (LSM) has been included into the current GEOS Data Assimilation System (DAS). The LSM uses a more advanced representation of physical processes than previous versions of the GEOS DAS, including the representation of sub-grid heterogeneity of the land-surface through the Mosaic approach. As a first approximation, Mosaic assumes that all similar surface types within a grid-cell can be lumped together as a single'tile'. Within one GCM grid-cell, there might be 1 - 5 different tiles or surface types. All tiles are subjected to the grid-scale forcing (radiation, air temperature and specific humidity, and precipitation), and the sub-grid variability is a function of the tile characteristics. In this paper, we validate the LSM sub-grid scale variability (tiles) using a variety of surface observing stations from the Southern Great Plains (SGP) site of the Atmospheric Radiation Measurement (ARM) Program. One of the primary goals of SGP ARM is to study the variability of atmospheric radiation within a G,CM grid-cell. Enough surface data has been collected by ARM to extend this goal to sub-grid variability of the land-surface energy and water budgets. The time period of this study is the Summer of 1998 (June I - September 1). The ARM site data consists of surface meteorology, energy flux (eddy correlation and bowen ratio), soil water observations spread over an area similar to the size of a G-CM grid-cell. Various ARM stations are described as wheat and alfalfa crops, pasture and range land. The LSM tiles considered at the grid-space (2 x 2.5) nearest the ARM site include, grassland, deciduous forests, bare soil and dwarf trees. Surface energy and water balances for each tile type are compared with observations. Furthermore, we will discuss the land-surface sub-grid variability of both the ARM observations and the DAS.

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

Zhao, Chun; Huang, Maoyi; Fast, Jerome D.

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface scheme CLM4 (Community Land Model version 4.0) in the Weather Research and Forecasting model withmore » chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a stand-alone vegetation map that differs from what is used by land surface schemes. This improved modeling framework is used to investigate the impact of two land surface schemes, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provided an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface schemes do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry and, consequently, secondary organic aerosol formation.« less

Prescription of land-surface boundary conditions in GISS GCM 2: A simple method based on high-resolution vegetation data bases

NASA Technical Reports Server (NTRS)

Matthews, E.

1984-01-01

A simple method was developed for improved prescription of seasonal surface characteristics and parameterization of land-surface processes in climate models. This method, developed for the Goddard Institute for Space Studies General Circulation Model II (GISS GCM II), maintains the spatial variability of fine-resolution land-cover data while restricting to 8 the number of vegetation types handled in the model. This was achieved by: redefining the large number of vegetation classes in the 1 deg x 1 deg resolution Matthews (1983) vegetation data base as percentages of 8 simple types; deriving roughness length, field capacity, masking depth and seasonal, spectral reflectivity for the 8 types; and aggregating these surface features from the 1 deg x 1 deg resolution to coarser model resolutions, e.g., 8 deg latitude x 10 deg longitude or 4 deg latitude x 5 deg longitude.

Exploiting Soil Moisture, Precipitation, and Streamflow Observations to Evaluate Soil Moisture/Runoff Coupling in Land Surface Models

NASA Astrophysics Data System (ADS)

Crow, W. T.; Chen, F.; Reichle, R. H.; Xia, Y.; Liu, Q.

2018-05-01

Accurate partitioning of precipitation into infiltration and runoff is a fundamental objective of land surface models tasked with characterizing the surface water and energy balance. Temporal variability in this partitioning is due, in part, to changes in prestorm soil moisture, which determine soil infiltration capacity and unsaturated storage. Utilizing the National Aeronautics and Space Administration Soil Moisture Active Passive Level-4 soil moisture product in combination with streamflow and precipitation observations, we demonstrate that land surface models (LSMs) generally underestimate the strength of the positive rank correlation between prestorm soil moisture and event runoff coefficients (i.e., the fraction of rainfall accumulation volume converted into stormflow runoff during a storm event). Underestimation is largest for LSMs employing an infiltration-excess approach for stormflow runoff generation. More accurate coupling strength is found in LSMs that explicitly represent subsurface stormflow or saturation-excess runoff generation processes.

Snow Physics and Meltwater Hydrology of the SSiB Model Employed for Climate Simulation Studies with GEOS 2 GCM

NASA Technical Reports Server (NTRS)

Mocko, David M.; Sud, Y. C.; Einaudi, Franco (Technical Monitor)

2000-01-01

Present-day climate models produce large climate drifts that interfere with the climate signals simulated in modelling studies. The simplifying assumptions of the physical parameterization of snow and ice processes lead to large biases in the annual cycles of surface temperature, evapotranspiration, and the water budget, which in turn causes erroneous land-atmosphere interactions. Since land processes are vital for climate prediction, and snow and snowmelt processes have been shown to affect Indian monsoons and North American rainfall and hydrology, special attention is now being given to cold land processes and their influence on the simulated annual cycle in GCMs. The snow model of the SSiB land-surface model being used at Goddard has evolved from a unified single snow-soil layer interacting with a deep soil layer through a force-restore procedure to a two-layer snow model atop a ground layer separated by a snow-ground interface. When the snow cover is deep, force-restore occurs within the snow layers. However, several other simplifying assumptions such as homogeneous snow cover, an empirical depth related surface albedo, snowmelt and melt-freeze in the diurnal cycles, and neglect of latent heat of soil freezing and thawing still remain as nagging problems. Several important influences of these assumptions will be discussed with the goal of improving them to better simulate the snowmelt and meltwater hydrology. Nevertheless, the current snow model (Mocko and Sud, 2000, submitted) better simulates cold land processes as compared to the original SSiB. This was confirmed against observations of soil moisture, runoff, and snow cover in global GSWP (Sud and Mocko, 1999) and point-scale Valdai simulations over seasonal snow regions. New results from the current snow model SSiB from the 10-year PILPS 2e intercomparison in northern Scandinavia will be presented.

Integrating land management into Earth system models: the importance of land use transitions at sub-grid-scale

NASA Astrophysics Data System (ADS)

Pongratz, Julia; Wilkenskjeld, Stiig; Kloster, Silvia; Reick, Christian

2014-05-01

Recent studies indicate that changes in surface climate and carbon fluxes caused by land management (i.e., modifications of vegetation structure without changing the type of land cover) can be as large as those caused by land cover change. Further, such effects may occur on substantial areas: while about one quarter of the land surface has undergone land cover change, another fifty percent are managed. This calls for integration of management processes in Earth system models (ESMs). This integration increases the importance of awareness and agreement on how to diagnose effects of land use in ESMs to avoid additional model spread and thus unnecessary uncertainties in carbon budget estimates. Process understanding of management effects, their model implementation, as well as data availability on management type and extent pose challenges. In this respect, a significant step forward has been done in the framework of the current IPCC's CMIP5 simulations (Coupled Model Intercomparison Project Phase 5): The climate simulations were driven with the same harmonized land use dataset that, different from most datasets commonly used before, included information on two important types of management: wood harvest and shifting cultivation. However, these new aspects were employed by only part of the CMIP5 models, while most models continued to use the associated land cover maps. Here, we explore the consequences for the carbon cycle of including subgrid-scale land transformations ("gross transitions"), such as shifting cultivation, as example of the current state of implementation of land management in ESMs. Accounting for gross transitions is expected to increase land use emissions because it represents simultaneous clearing and regrowth of natural vegetation in different parts of the grid cell, reducing standing carbon stocks. This process cannot be captured by prescribing land cover maps ("net transitions"). Using the MPI-ESM we find that ignoring gross transitions underestimates emissions substantially, for historical times by about 40%. Implementation of land management such as gross transitions is a step forward in terms of comprehensiveness of simulated processes. However, it has increased model spread in carbon fluxes, because land management processes have been considered by only a subset of recent ESMs contributing to major projects such as IPCC or the Global Carbon Project. This model spread still causes the net land use flux to be the most uncertain component in the global carbon budget. Other causes have previously been identified as differences in land use datasets, differing types of vegetation model, accounting of nutrient limitation, the inclusion of land use feedbacks (increase in atmospheric CO2 due to land use emissions causing terrestrial carbon uptake), and a confusion of whether the net land use flux in ESMs should be reported as instantaneous emissions, or also account for delayed carbon responses and regrowth. These differences explain a factor 2-6 difference between model estimates and are expected to be further affected by interactions with land management. This highlights the importance of an accurate protocol for future model intercomparisons of carbon fluxes from land cover change and land management to ensure comparison of the same processes and fluxes.

Coupling fast all-season soil strength land surface model with weather research and forecasting model to assess low-level icing in complex terrain

NASA Astrophysics Data System (ADS)

Sines, Taleena R.

Icing poses as a severe hazard to aircraft safety with financial resources and even human lives hanging in the balance when the decision to ground a flight must be made. When analyzing the effects of ice on aviation, a chief cause for danger is the disruption of smooth airflow, which increases the drag force on the aircraft therefore decreasing its ability to create lift. The Weather Research and Forecast (WRF) model Advanced Research WRF (WRF-ARW) is a collaboratively created, flexible model designed to run on distributed computing systems for a variety of applications including forecasting research, parameterization research, and real-time numerical weather prediction. Land-surface models, one of the physics options available in the WRF-ARW, output surface heat and moisture flux given radiation, precipitation, and surface properties such as soil type. The Fast All-Season Soil STrength (FASST) land-surface model was developed by the U.S. Army ERDC-CRREL in Hanover, New Hampshire. Designed to use both meteorological and terrain data, the model calculates heat and moisture within the surface layer as well as the exchange of these parameters between the soil, surface elements (such as snow and vegetation), and atmosphere. Focusing on the Presidential Mountain Range of New Hampshire under the NASA Experimental Program to Stimulate Competitive Research (EPSCoR) Icing Assessments in Cold and Alpine Environments project, one of the main goals is to create a customized, high resolution model to predict and assess ice accretion in complex terrain. The purpose of this research is to couple the FASST land-surface model with the WRF to improve icing forecasts in complex terrain. Coupling FASST with the WRF-ARW may improve icing forecasts because of its sophisticated approach to handling processes such as meltwater, freezing, thawing, and others that would affect the water and energy budget and in turn affect icing forecasts. Several transformations had to take place in order for the FASST land-surface model and WRF-ARW to work together as fully coupled models. Changes had to be made to the WRF-ARW build mechanisms (Chapter 1, section a) so that FASST would be recognized as a new option that could be chosen through the namelist and compiled with other modules. Similarly, FASST had to be altered to no longer read meteorological data from a file, but accept input from WRF-ARW at each time step in a way that did not alter the integrity or run-time processes of the model. Several icing events were available to test the newly coupled model as well as the performance of other available land-surface models from the WRF-ARW. A variation of event intensities and durations from these events were chosen to give a broader view of the land-surface models' abilities to accurately predict icing in complex terrain. Non- icing events were also used in testing to ensure the land-surface models were not predicting ice in the events where none occurred. When compared to the other land-surface models and observations FASST showed a warm bias in several regions. As the forecasts progressed, FASST appeared to attempt to correct this bias and performed similarly to the other land-surface models and at times better than these land-surface models in areas of the domain not affected by this bias. To correct this warm bias, future investigation should be conducted into the reasoning behind this warm bias, including but not limited to: FASST operation and elevation modeling, WRF-ARW variables and forecasting methods, as well as allowing for spin-up prior to forecast times. Following the correction to the warm bias, FASST can be parallelized to allow for operational forecast performance and included in the WRF-ARW forecasting suite for future software releases. (Abstract shortened by UMI.).

Sensitivity of boundary layer variables to PBL schemes over the central Tibetan Plateau

NASA Astrophysics Data System (ADS)

Xu, L.; Liu, H.; Wang, L.; Du, Q.; Liu, Y.

2017-12-01

Planetary Boundary Layer (PBL) parameterization schemes play critical role in numerical weather prediction and research. They describe physical processes associated with the momentum, heat and humidity exchange between land surface and atmosphere. In this study, two non-local (YSU and ACM2) and two local (MYJ and BouLac) planetary boundary layer parameterization schemes in the Weather Research and Forecasting (WRF) model have been tested over the central Tibetan Plateau regarding of their capability to model boundary layer parameters relevant for surface energy exchange. The model performance has been evaluated against measurements from the Third Tibetan Plateau atmospheric scientific experiment (TIPEX-III). Simulated meteorological parameters and turbulence fluxes have been compared with observations through standard statistical measures. Model results show acceptable behavior, but no particular scheme produces best performance for all locations and parameters. All PBL schemes underestimate near surface air temperatures over the Tibetan Plateau. By investigating the surface energy budget components, the results suggest that downward longwave radiation and sensible heat flux are the main factors causing the lower near surface temperature. Because the downward longwave radiation and sensible heat flux are respectively affected by atmosphere moisture and land-atmosphere coupling, improvements in water vapor distribution and land-atmosphere energy exchange is meaningful for better presentation of PBL physical processes over the central Tibetan Plateau.

Analyses of Rock Size-Frequency Distributions and Morphometry of Modified Hawaiian Lava Flows: Implications for Future Martian Landing Sites

NASA Technical Reports Server (NTRS)

Craddock, Robert A.; Golombek, Matthew; Howard, Alan D.

2000-01-01

Both the size-frequency distribution and morphometry of rock populations emplaced by a variety of geologic processes in Hawaii indicate that such information may be useful in planning future landing sites on Mars and interpreting the surface geology.

Coupling a three-dimensional subsurface flow model with a land surface model to simulate stream-aquifer-land interactions

NASA Astrophysics Data System (ADS)

Huang, M.; Bisht, G.; Zhou, T.; Chen, X.; Dai, H.; Hammond, G. E.; Riley, W. J.; Downs, J.; Liu, Y.; Zachara, J. M.

2016-12-01

A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively-parallel multi-physics reactive tranport model (PFLOTRAN). The coupled model (CLM-PFLOTRAN) is applied to a 400m×400m study domain instrumented with groundwater monitoring wells in the Hanford 300 Area along the Columbia River. CLM-PFLOTRAN simulations are performed at three different spatial resolutions over the period 2011-2015 to evaluate the impact of spatial resolution on simulated variables. To demonstrate the difference in model simulations with and without lateral subsurface flow, a vertical-only CLM-PFLOTRAN simulation is also conducted for comparison. Results show that the coupled model is skillful in simulating stream-aquifer interactions, and the land-surface energy partitioning can be strongly modulated by groundwater-river water interactions in high water years due to increased soil moisture availability caused by elevated groundwater table. In addition, spatial resolution does not seem to impact the land surface energy flux simulations, although it is a key factor for accurately estimating the mass exchange rates at the boundaries and associated biogeochemical reactions in the aquifer. The coupled model developed in this study establishes a solid foundation for understanding co-evolution of hydrology and biogeochemistry along the river corridors under historical and future hydro-climate changes.

Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream-aquifer-land interactions (CP v1.0)

NASA Astrophysics Data System (ADS)

Bisht, Gautam; Huang, Maoyi; Zhou, Tian; Chen, Xingyuan; Dai, Heng; Hammond, Glenn E.; Riley, William J.; Downs, Janelle L.; Liu, Ying; Zachara, John M.

2017-12-01

A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively parallel multiphysics reactive transport model (PFLOTRAN). The coupled model, named CP v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. CP v1.0 simulations are performed at three spatial resolutions (i.e., 2, 10, and 20 m) over a 5-year period to evaluate the impact of hydroclimatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater-river-water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30 000 dams constructed worldwide during the past half-century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater-river-water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Meanwhile, CLM4.5 fails to capture the key hydrologic process (i.e., groundwater-river-water exchange) at the site, and consequently simulates drastically different water and energy budgets. Furthermore, spatial resolution is found to significantly impact the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within 6 to 7 meters below the surface. Inclusion of lateral subsurface flow influenced both the surface energy budget and subsurface transport processes as a result of river-water intrusion into the subsurface in response to an elevated river stage that increased soil moisture for evapotranspiration and suppressed available energy for sensible heat in the warm season. The coupled model developed in this study can be used for improving mechanistic understanding of ecosystem functioning and biogeochemical cycling along river corridors under historical and future hydroclimatic changes. The dataset presented in this study can also serve as a good benchmarking case for testing other integrated models.

Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream–aquifer–land interactions (CP v1.0)

DOE PAGES

Bisht, Gautam; Huang, Maoyi; Zhou, Tian; ...

2017-12-12

A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively parallel multiphysics reactive transport model (PFLOTRAN). The coupled model, named CP v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. CP v1.0 simulations are performed at three spatial resolutions (i.e., 2, 10, and 20 m) over a 5-year periodmore » to evaluate the impact of hydroclimatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater–river-water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30 000 dams constructed worldwide during the past half-century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater–river-water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Meanwhile, CLM4.5 fails to capture the key hydrologic process (i.e., groundwater–river-water exchange) at the site, and consequently simulates drastically different water and energy budgets. Furthermore, spatial resolution is found to significantly impact the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within 6 to 7 meters below the surface. Inclusion of lateral subsurface flow influenced both the surface energy budget and subsurface transport processes as a result of river-water intrusion into the subsurface in response to an elevated river stage that increased soil moisture for evapotranspiration and suppressed available energy for sensible heat in the warm season. The coupled model developed in this study can be used for improving mechanistic understanding of ecosystem functioning and biogeochemical cycling along river corridors under historical and future hydroclimatic changes. The dataset presented in this study can also serve as a good benchmarking case for testing other integrated models.« less

Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream–aquifer–land interactions (CP v1.0)

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

Bisht, Gautam; Huang, Maoyi; Zhou, Tian

A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively parallel multiphysics reactive transport model (PFLOTRAN). The coupled model, named CP v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. CP v1.0 simulations are performed at three spatial resolutions (i.e., 2, 10, and 20 m) over a 5-year period to evaluate themore » impact of hydroclimatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater–river-water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30 000 dams constructed worldwide during the past half-century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater–river-water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Meanwhile, CLM4.5 fails to capture the key hydrologic process (i.e., groundwater–river-water exchange) at the site, and consequently simulates drastically different water and energy budgets. Furthermore, spatial resolution is found to significantly impact the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within 6 to 7 meters below the surface. Inclusion of lateral subsurface flow influenced both the surface energy budget and subsurface transport processes as a result of river-water intrusion into the subsurface in response to an elevated river stage that increased soil moisture for evapotranspiration and suppressed available energy for sensible heat in the warm season. The coupled model developed in this study can be used for improving mechanistic understanding of ecosystem functioning and biogeochemical cycling along river corridors under historical and future hydroclimatic changes. The dataset presented in this study can also serve as a good benchmarking case for testing other integrated models.« less

Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream–aquifer–land interactions (CP v1.0)

DOE PAGES

Bisht, Gautam; Huang, Maoyi; Zhou, Tian; ...

2017-01-01

A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively parallel multiphysics reactive transport model (PFLOTRAN). The coupled model, named CP v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. CP v1.0 simulations are performed at three spatial resolutions (i.e., 2, 10, and 20 m) over a 5-year period to evaluate themore » impact of hydroclimatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater–river-water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30 000 dams constructed worldwide during the past half-century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater–river-water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Meanwhile, CLM4.5 fails to capture the key hydrologic process (i.e., groundwater–river-water exchange) at the site, and consequently simulates drastically different water and energy budgets. Furthermore, spatial resolution is found to significantly impact the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within 6 to 7 meters below the surface. Inclusion of lateral subsurface flow influenced both the surface energy budget and subsurface transport processes as a result of river-water intrusion into the subsurface in response to an elevated river stage that increased soil moisture for evapotranspiration and suppressed available energy for sensible heat in the warm season. The coupled model developed in this study can be used for improving mechanistic understanding of ecosystem functioning and biogeochemical cycling along river corridors under historical and future hydroclimatic changes. The dataset presented in this study can also serve as a good benchmarking case for testing other integrated models.« less

Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream–aquifer–land interactions (CP v1.0)

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

Bisht, Gautam; Huang, Maoyi; Zhou, Tian

A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively parallel multiphysics reactive transport model (PFLOTRAN). The coupled model, named CP v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. CP v1.0 simulations are performed at three spatial resolutions (i.e., 2, 10, and 20 m) over a 5-year periodmore » to evaluate the impact of hydroclimatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater–river-water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30 000 dams constructed worldwide during the past half-century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater–river-water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Meanwhile, CLM4.5 fails to capture the key hydrologic process (i.e., groundwater–river-water exchange) at the site, and consequently simulates drastically different water and energy budgets. Furthermore, spatial resolution is found to significantly impact the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within 6 to 7 meters below the surface. Inclusion of lateral subsurface flow influenced both the surface energy budget and subsurface transport processes as a result of river-water intrusion into the subsurface in response to an elevated river stage that increased soil moisture for evapotranspiration and suppressed available energy for sensible heat in the warm season. The coupled model developed in this study can be used for improving mechanistic understanding of ecosystem functioning and biogeochemical cycling along river corridors under historical and future hydroclimatic changes. The dataset presented in this study can also serve as a good benchmarking case for testing other integrated models.« less

Land use and surface process domains on alpine hillslopes

NASA Astrophysics Data System (ADS)

Kuhn, Nikolaus J.; Caviezel, Chatrina; Hunziker, Matthias

2015-04-01

Shrubs and trees are generally considered to protect hillslopes from erosion. As a consequence, shrub encroachment on mountain pastures after abandoning grazing is not considered a threat to soils. However, the abandonment of mown or grazed grasslands causes a shift in vegetation composition and thus a change in landscape ecology and geomorphology. On many alpine slopes, current changes in land use and vegetation cover are accompanied by climate change, potentially generating a new geomorphic regime. Most of the debate focuses on the effect of land abandonment on water erosion rates. Generally, an established perennial vegetation cover improves the mechanical anchoring of the soil and the regulation of the soil water budget, including runoff generation and erosion. However, changing vegetation composition affects many other above- and below-ground properties like root density, -diversity and -geometry, soil structure, pore volume and acidity. Each combination of these properties can lead to a distinct scenario of dominating surface processes, often not reflected by common erosion risk assessment procedures. The study of soil properties along a chronosequence of green alder (alnusviridis) encroachment on the Unteralptal in central Switzerland reveals that shrub encroachment changes soil and vegetation properties towards an increase of resistance to run-off related erosion processes, but a decrease of slope stability against shallow landslides. The latter are a particular threat because of the currently increasing frequency of slide-triggering high magnitude rainfalls. The potential change of process domain on alpine pastures highlights the need for a careful use of erosion models when assessing future land use and climate scenarios. In mountains, but also other intensively managed agricultural landscapes, risk assessment without the appropriate reflection on the shifting relevance of surface processes carries the risk of missing future threats to environmental quality, services and hazards.

Extending the Confrontation of Weather and Climate Models from Soil Moisture to Surface Flux Data

NASA Astrophysics Data System (ADS)

Dirmeyer, P.; Chen, L.; Wu, J.

2016-12-01

The atmosphere and land components of weather and climate models are typically developed separately and coupled as a last step before new model versions are released. Separate testing of land surface models (LSMs) and atmospheric models is often quite extensive in the development phase, but validation of coupled land-atmosphere behavior is often minimal if performed at all. This is partly because of this piecemeal model development approach and partly because the necessary in situ data to confront coupled land-atmosphere models (LAMs) has been meager until quite recently. Over the past 10-20 years there has been a growing number of networks of measurements of land surface states, surface fluxes, radiation and near-surface meteorology, although they have been largely uncoordinated and frequently incomplete across the range of variables necessary to validate LAMs. We extend recent work "confronting" a variety of LSMs and LAMs with in situ observations of soil moisture from cross-standardized networks to comparisons with measurements of surface latent and sensible heat fluxes at FLUXNET sites in a variety of climate regimes around the world. The motivation is to determine how well LSMs represent observed statistics of variability and co-variability, how much models differ from one another, and how those statistics change when the LSMs are coupled to atmospheric models. Furthermore, comparisons are made to several LAMs in both open-loop (free running) and reanalysis configurations. This shows to what extent data assimilation can constrain the processes involved in flux variability, and helps illuminate model development pathways to improve coupled land-atmosphere interactions in weather and climate models.

The Joint UK Land Environment Simulator (JULES), model description - Part 2: Carbon fluxes and vegetation dynamics

NASA Astrophysics Data System (ADS)

Clark, D. B.; Mercado, L. M.; Sitch, S.; Jones, C. D.; Gedney, N.; Best, M. J.; Pryor, M.; Rooney, G. G.; Essery, R. L. H.; Blyth, E.; Boucher, O.; Harding, R. J.; Huntingford, C.; Cox, P. M.

2011-09-01

The Joint UK Land Environment Simulator (JULES) is a process-based model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Many studies have demonstrated the important role of the land surface in the functioning of the Earth System. Different versions of JULES have been employed to quantify the effects on the land carbon sink of climate change, increasing atmospheric carbon dioxide concentrations, changing atmospheric aerosols and tropospheric ozone, and the response of methane emissions from wetlands to climate change. This paper describes the consolidation of these advances in the modelling of carbon fluxes and stores, in both the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model. The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model.

Spatial heterogeneity of leaf area index across scales from simulation and remote sensing

NASA Astrophysics Data System (ADS)

Reichenau, Tim G.; Korres, Wolfgang; Montzka, Carsten; Schneider, Karl

2016-04-01

Leaf area index (LAI, single sided leaf area per ground area) influences mass and energy exchange of vegetated surfaces. Therefore LAI is an input variable for many land surface schemes of coupled large scale models, which do not simulate LAI. Since these models typically run on rather coarse resolution grids, LAI is often inferred from coarse resolution remote sensing. However, especially in agriculturally used areas, a grid cell of these products often covers more than a single land-use. In that case, the given LAI does not apply to any single land-use. Therefore, the overall spatial heterogeneity in these datasets differs from that on resolutions high enough to distinguish areas with differing land-use. Detailed process-based plant growth models simulate LAI for separate plant functional types or specific species. However, limited availability of observations causes reduced spatial heterogeneity of model input data (soil, weather, land-use). Since LAI is strongly heterogeneous in space and time and since processes depend on LAI in a nonlinear way, a correct representation of LAI spatial heterogeneity is also desirable on coarse resolutions. The current study assesses this issue by comparing the spatial heterogeneity of LAI from remote sensing (RapidEye) and process-based simulations (DANUBIA simulation system) across scales. Spatial heterogeneity is assessed by analyzing LAI frequency distributions (spatial variability) and semivariograms (spatial structure). Test case is the arable land in the fertile loess plain of the Rur catchment near the Germany-Netherlands border.

Constraints and Approach for Selecting the Mars Surveyor '01 Landing Site

NASA Technical Reports Server (NTRS)

Golombek, M.; Bridges, N.; Gilmore, M.; Haldemann, A.; Parker, T.; Saunders, R.; Spencer, D.; Smith, J.; Weitz, C.

1999-01-01

There are many similarities between the Mars Surveyor '01 (MS '01) landing site selection process and that of Mars Pathfinder. The selection process includes two parallel activities in which engineers define and refine the capabilities of the spacecraft through design, testing and modeling and scientists define a set of landing site constraints based on the spacecraft design and landing scenario. As for Pathfinder, the safety of the site is without question the single most important factor, for the simple reason that failure to land safely yields no science and exposes the mission and program to considerable risk. The selection process must be thorough and defensible and capable of surviving multiple withering reviews similar to the Pathfinder decision. On Pathfinder, this was accomplished by attempting to understand the surface properties of sites using available remote sensing data sets and models based on them. Science objectives are factored into the selection process only after the safety of the site is validated. Finally, as for Pathfinder, the selection process is being done in an open environment with multiple opportunities for community involvement including open workshops, with education and outreach opportunities.

Constraints, Approach and Present Status for Selecting the Mars Surveyor 2001 Landing Site

NASA Technical Reports Server (NTRS)

Golombek, M.; Anderson, F.; Bridges, N.; Briggs, G.; Gilmore, M.; Gulick, V.; Haldemann, A.; Parker, T.; Saunders, R.; Spencer, D.;

On the predictability of land surface fluxes from meteorological variables

NASA Astrophysics Data System (ADS)

Haughton, Ned; Abramowitz, Gab; Pitman, Andy J.

2018-01-01

Previous research has shown that land surface models (LSMs) are performing poorly when compared with relatively simple empirical models over a wide range of metrics and environments. Atmospheric driving data appear to provide information about land surface fluxes that LSMs are not fully utilising. Here, we further quantify the information available in the meteorological forcing data that are used by LSMs for predicting land surface fluxes, by interrogating FLUXNET data, and extending the benchmarking methodology used in previous experiments. We show that substantial performance improvement is possible for empirical models using meteorological data alone, with no explicit vegetation or soil properties, thus setting lower bounds on a priori expectations on LSM performance. The process also identifies key meteorological variables that provide predictive power. We provide an ensemble of empirical benchmarks that are simple to reproduce and provide a range of behaviours and predictive performance, acting as a baseline benchmark set for future studies. We reanalyse previously published LSM simulations and show that there is more diversity between LSMs than previously indicated, although it remains unclear why LSMs are broadly performing so much worse than simple empirical models.

The observed cooling effect of desert blooms based on high-resolution Moderate Resolution Imaging Spectroradiometer products

NASA Astrophysics Data System (ADS)

He, Bin; Huang, Ling; Liu, Junjie; Wang, Haiyan; Lż, Aifeng; Jiang, Weiguo; Chen, Ziyue

2017-05-01

Desert greening through planting or irrigation is a potential approach to mitigate desertification and climate warming, but its influence on regional climate is unclear due to scarcity of observations. "Desert blooms," which are natural phenomena usually associated with the El Niño-Southern Oscillation, regularly occur in the world's driest desert, the Atacama Desert. This sudden conversion of land cover likely has a large impact on regional climate through alteration of local energy budgets and provides a unique opportunity to study the potential climatic and environmental consequences of desert greening. Here we evaluated the land surface effects of blooms in the Atacama Desert using vegetation and climate data acquired from remote sensing. The rapid vegetation growth during blooms led to an increase in evapotranspiration and a decrease in albedo. These two processes caused a 0.31°C ± 0.05°C decrease in daytime land surface temperature. During nighttime, we observed a 0.02°C ± 0.02°C increase in land surface temperature due to enhanced heat capacity associated with blooms. This asymmetric diurnal variation in land surface temperature produced a net decrease in daily land surface temperature of 0.29°C ± 0.07°C. Our observations demonstrate the potential benefits of desert blooms on local climate. Results from this study also provide new evidence for plausible climate consequences expected from local "desert greening" strategies.

Land Surface Model Biases and their Impacts on the Assimilation of Snow-related Observations

NASA Astrophysics Data System (ADS)

Arsenault, K. R.; Kumar, S.; Hunter, S. M.; Aman, R.; Houser, P. R.; Toll, D.; Engman, T.; Nigro, J.

2007-12-01

Some recent snow modeling studies have employed a wide range of assimilation methods to incorporate snow cover or other snow-related observations into different hydrological or land surface models. These methods often include taking both model and observation biases into account throughout the model integration. This study focuses more on diagnosing the model biases and presenting their subsequent impacts on assimilating snow observations and modeled snowmelt processes. In this study, the land surface model, the Community Land Model (CLM), is used within the Land Information System (LIS) modeling framework to show how such biases impact the assimilation of MODIS snow cover observations. Alternative in-situ and satellite-based observations are used to help guide the CLM LSM in better predicting snowpack conditions and more realistic timing of snowmelt for a western US mountainous region. Also, MODIS snow cover observation biases will be discussed, and validation results will be provided. The issues faced with inserting or assimilating MODIS snow cover at moderate spatial resolutions (like 1km or less) will be addressed, and the impacts on CLM will be presented.

Erosion and lateral surface processes

USDA-ARS?s Scientific Manuscript database

: Erosion can cause serious agricultural and environmental hazards. It can generate severe damage to the landscape, lead to significant loss of agricultural land and consequently to reduction in agricultural productivity, induce surface water pollution due to the transport of sediments and suspende...

Boulder Distributions at Legacy Landing Sites: Assessing Regolith Production Rates and Landing Site Hazards

NASA Technical Reports Server (NTRS)

Watkins, R. N.; Jolliff, B. L.; Lawrence, S. J.; Hayne, P. O.; Ghent, R. R.

2017-01-01

Understanding how the distribution of boulders on the lunar surface changes over time is key to understanding small-scale erosion processes and the rate at which rocks become regolith. Boulders degrade over time, primarily as a result of micrometeorite bombardment so their residence time at the surface can inform the rate at which rocks become regolith or become buried within regolith. Because of the gradual degradation of exposed boulders, we expect that the boulder population around an impact crater will decrease as crater age increases. Boulder distributions around craters of varying ages are needed to understand regolith production rates, and Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images provide one of the best tools for conducting these studies. Using NAC images to assess how the distribution of boulders varies as a function of crater age provides key constraints for boulder erosion processes. Boulders also represent a potential hazard that must be addressed in the planning of future lunar landings. A boulder under a landing leg can contribute to deck tilt, and boulders can damage spacecraft during landing. Using orbital data to characterize boulder populations at locations where landers have safely touched down (Apollo, Luna, Surveyor, Chang'e-3) provides validation for landed mission hazard avoidance planning. Additionally, counting boulders at legacy landing sites is useful because: 1) LROC has extensive coverage of these sites at high resolutions (approximately 0.5 meters per pixel). 2) Returned samples from craters at these sites have been radiometrically dated, allowing assessment of how boulder distributions vary as a function of crater age. 3) Surface photos at these sites can be used to correlate with remote sensing measurements.

The role of soil moisture in land surface-atmosphere coupling: climate model sensitivity experiments over India

NASA Astrophysics Data System (ADS)

Williams, Charles; Turner, Andrew

2015-04-01

It is generally acknowledged that anthropogenic land use changes, such as a shift from forested land into irrigated agriculture, may have an impact on regional climate and, in particular, rainfall patterns in both time and space. India provides an excellent example of a country in which widespread land use change has occurred during the last century, as the country tries to meet its growing demand for food. Of primary concern for agriculture is the Indian summer monsoon (ISM), which displays considerable seasonal and subseasonal variability. Although it is evident that changing rainfall variability will have a direct impact on land surface processes (such as soil moisture variability), the reverse impact is less well understood. However, the role of soil moisture in the coupling between the land surface and atmosphere needs to be properly explored before any potential impact of changing soil moisture variability on ISM rainfall can be understood. This paper attempts to address this issue, by conducting a number of sensitivity experiments using a state-of-the-art climate model from the UK Meteorological Office Hadley Centre: HadGEM2. Several experiments are undertaken, with the only difference between them being the extent to which soil moisture is coupled to the atmosphere. Firstly, the land surface is fully coupled to the atmosphere, globally (as in standard model configurations); secondly, the land surface is entirely uncoupled from the atmosphere, again globally, with soil moisture values being prescribed on a daily basis; thirdly, the land surface is uncoupled from the atmosphere over India but fully coupled elsewhere; and lastly, vice versa (i.e. the land surface is coupled to the atmosphere over India but uncoupled elsewhere). Early results from this study suggest certain 'hotspot' regions where the impact of soil moisture coupling/uncoupling may be important, and many of these regions coincide with previous studies. Focusing on the third experiment, i.e. uncoupled over India and coupled elsewhere, preliminary results suggest an increase in rainfall, surface temperature and pressure over northern India and the Himalayas, as well as a decrease in rainfall over the Bay of Bengal and the Maritime Continent. Other metrics, such as the northward propagation of intraseasonal rainfall variability and sensible and latent heat fluxes, are also discussed.

Radon Measurements of Atmospheric Mixing (RAMIX) 2006–2014 Final Campaign Summary

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

Fischer, ML; Biraud, SC

2015-05-01

Uncertainty in vertical mixing between the surface layer, boundary layer, and free troposphere leads to large uncertainty in “top-down” estimates of regional land-atmosphere carbon exchange (i.e., estimates based on measurements of atmospheric CO2 mixing ratios. Radon-222 (222Rn) is a valuable tracer for measuring atmospheric mixing because it is emitted from the land surface and has a short enough half-life (3.8 days) to allow characterization of mixing processes based on vertical profile measurements.

Radon Measurements of Atmospheric Mixing (RAMIX) 2006–2014 Final Campaign Summary

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

Fischer, ML; Biraud, SC; Hirsch, A

2015-05-01

Uncertainty in vertical mixing between the surface layer, boundary layer, and free troposphere leads to large uncertainty in “top-down” estimates of regional land-atmosphere carbon exchange (i.e., estimates based on measurements of atmospheric CO 2 mixing ratios). The radioisotope radon-222 ( 222Rn) is a valuable tracer for measuring atmospheric mixing because it is emitted from the land surface and has a short enough half-life (3.8 days) to allow characterization of mixing processes based on vertical profile measurements.

Responses of Surface Ozone Air Quality to Anthropogenic Nitrogen Deposition

NASA Astrophysics Data System (ADS)

Zhang, L.; Zhao, Y.; Tai, A. P. K.; Chen, Y.; Pan, Y.

2017-12-01

Human activities have substantially increased atmospheric deposition of reactive nitrogen to the Earth's surface, inducing unintentional effects on ecosystems with complex environmental and climate consequences. One consequence remaining unexplored is how surface air quality might respond to the enhanced nitrogen deposition through surface-atmosphere exchange. We combine a chemical transport model (GEOS-Chem) and a global land model (Community Land Model) to address this issue with a focus on ozone pollution in the Northern Hemisphere. We consider three processes that are important for surface ozone and can be perturbed by addition of atmospheric deposited nitrogen: emissions of biogenic volatile organic compounds (VOCs), ozone dry deposition, and soil nitrogen oxide (NOx) emissions. We find that present-day anthropogenic nitrogen deposition (65 Tg N a-1 to the land), through enhancing plant growth (represented as increases in vegetation leaf area index (LAI) in the model), could increase surface ozone from increased biogenic VOC emissions, but could also decrease ozone due to higher ozone dry deposition velocities. Meanwhile, deposited anthropogenic nitrogen to soil enhances soil NOx emissions. The overall effect on summer mean surface ozone concentrations show general increases over the globe (up to 1.5-2.3 ppbv over the western US and South Asia), except for some regions with high anthropogenic NOx emissions (0.5-1.0 ppbv decreases over the eastern US, Western Europe, and North China). We compare the surface ozone changes with those driven by the past 20-year climate and historical land use changes. We find that the impacts from anthropogenic nitrogen deposition can be comparable to the climate and land use driven surface ozone changes at regional scales, and partly offset the surface ozone reductions due to land use changes reported in previous studies. Our study emphasizes the complexity of biosphere-atmosphere interactions, which can have important implications for future air quality prediction.

An Integrated High Resolution Hydrometeorological Modeling Testbed using LIS and WRF

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Peters-Lidard, Christa D.; Eastman, Joseph L.; Tao, Wei-Kuo

2007-01-01

Scientists have made great strides in modeling physical processes that represent various weather and climate phenomena. Many modeling systems that represent the major earth system components (the atmosphere, land surface, and ocean) have been developed over the years. However, developing advanced Earth system applications that integrates these independently developed modeling systems have remained a daunting task due to limitations in computer hardware and software. Recently, efforts such as the Earth System Modeling Ramework (ESMF) and Assistance for Land Modeling Activities (ALMA) have focused on developing standards, guidelines, and computational support for coupling earth system model components. In this article, the development of a coupled land-atmosphere hydrometeorological modeling system that adopts these community interoperability standards, is described. The land component is represented by the Land Information System (LIS), developed by scientists at the NASA Goddard Space Flight Center. The Weather Research and Forecasting (WRF) model, a mesoscale numerical weather prediction system, is used as the atmospheric component. LIS includes several community land surface models that can be executed at spatial scales as fine as 1km. The data management capabilities in LIS enable the direct use of high resolution satellite and observation data for modeling. Similarly, WRF includes several parameterizations and schemes for modeling radiation, microphysics, PBL and other processes. Thus the integrated LIS-WRF system facilitates several multi-model studies of land-atmosphere coupling that can be used to advance earth system studies.

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.

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

Liu, zhifeng; He, Chunyang; Zhou, Yuyu

Urbanization has transformed the world’s landscapes, resulting in a series of ecological and environmental problems. To assess urbanization impacts and improve sustainability, one of the first questions that we must address is: how much of the world’s land has been urbanized? Unfortunately, the estimates of the global urban land reported in the literature vary widely from less than 1% to 3% primarily because different definitions of urban land were used. To evade confusion, here we propose a hierarchical framework for representing and communicating the spatial extent of the world’s urbanized land at the global, regional, and more local levels. Themore » hierarchical framework consists of three spatially nested definitions: “urban area” that is delineated by administrative boundaries, “built-up area” that is dominated by artificial surfaces, and “impervious surface area” that is devoid of life. These are really three different measures of urbanization. In 2010, the global urban land was close to 3%, the global built-up area was 0.65%, and the global impervious surface area was 0.45%, of the word’s total land area (excluding Antarctica and Greenland). We argue that this hierarchy of urban land measures, in particular the ratios between them, can also facilitate better understanding the biophysical and socioeconomic processes and impacts of urbanization.« less

Global observation-based diagnosis of soil moisture control on land surface flux partition

NASA Astrophysics Data System (ADS)

Gallego-Elvira, Belen; Taylor, Christopher M.; Harris, Phil P.; Ghent, Darren; Veal, Karen L.; Folwell, Sonja S.

2016-04-01

Soil moisture plays a central role in the partition of available energy at the land surface between sensible and latent heat flux to the atmosphere. As soils dry out, evapotranspiration becomes water-limited ("stressed"), and both land surface temperature (LST) and sensible heat flux rise as a result. This change in surface behaviour during dry spells directly affects critical processes in both the land and the atmosphere. Soil water deficits are often a precursor in heat waves, and they control where feedbacks on precipitation become significant. State-of-the-art global climate model (GCM) simulations for the Coupled Model Intercomparison Project Phase 5 (CMIP5) disagree on where and how strongly the surface energy budget is limited by soil moisture. Evaluation of GCM simulations at global scale is still a major challenge owing to the scarcity and uncertainty of observational datasets of land surface fluxes and soil moisture at the appropriate scale. Earth observation offers the potential to test how well GCM land schemes simulate hydrological controls on surface fluxes. In particular, satellite observations of LST provide indirect information about the surface energy partition at 1km resolution globally. Here, we present a potentially powerful methodology to evaluate soil moisture stress on surface fluxes within GCMs. Our diagnostic, Relative Warming Rate (RWR), is a measure of how rapidly the land warms relative to the overlying atmosphere during dry spells lasting at least 10 days. Under clear skies, this is a proxy for the change in sensible heat flux as soil dries out. We derived RWR from MODIS Terra and Aqua LST observations, meteorological re-analyses and satellite rainfall datasets. Globally we found that on average, the land warmed up during dry spells for 97% of the observed surface between 60S and 60N. For 73% of the area, the land warmed faster than the atmosphere (positive RWR), indicating water stressed conditions and increases in sensible heat flux. Higher RWRs were observed for shorter vegetation and bare soil compared to tall, deep-rooted vegetation due to differences in both aerodynamic and hydrological properties. The variation of RWR with antecedent rainfall provides information on which evaporation regime a particular region lies in climatologically. Different drying stages for a given antecedent rainfall can thus be observed depending on land cover type. For instance, our results suggest that forests in a continental climate remain unstressed during a 10 day dry spell provided the previous month saw at least 95 mm of rain. Conversely, RWR values indicate that under similar conditions regions of grass/crop cover are water-stressed.

Coupling integrated assessment and earth system models: concepts and an application to land use change

NASA Astrophysics Data System (ADS)

O'Neill, B. C.; Lawrence, P.; Ren, X.

2016-12-01

Collaboration between the integrated assessment modeling (IAM) and earth system modeling (ESM) communities is increasing, driven by a growing interest in research questions that require analysis integrating both social and natural science components. This collaboration often takes the form of integrating their respective models. There are a number of approaches available to implement this integration, ranging from one-way linkages to full two-way coupling, as well as approaches that retain a single modeling framework but improve the representation of processes from the other framework. We discuss the pros and cons of these different approaches and the conditions under which a two-way coupling of IAMs and ESMs would be favored over a one-way linkage. We propose a criterion that is necessary and sufficient to motivate two-way coupling: A human process must have an effect on an earth system process that is large enough to cause a change in the original human process that is substantial compared to other uncertainties in the problem being investigated. We then illustrate a test of this criterion for land use-climate interactions based on work using the Community Earth System Model (CESM) and land use scenarios from the Representative Concentration Pathways (RCPs), in which we find that the land use effect on regional climate is unlikely to meet the criterion. We then show an example of implementing a one-way linkage of land use and agriculture between an IAM, the integrated Population-Economy-Technology-Science (iPETS) model, and CESM that produces fully consistent outcomes between iPETS and the CESM land surface model. We use the linked system to model the influence of climate change on crop yields, agricultural land use, crop prices and food consumption under two alternative future climate scenarios. This application demonstrates the ability to link an IAM to a global land surface and climate model in a computationally efficient manner.

Decoding the origins of vertical land motions observed today at coasts

NASA Astrophysics Data System (ADS)

Pfeffer, J.; Spada, G.; Mémin, A.; Boy, J.-P.; Allemand, P.

2017-07-01

In recent decades, geodetic techniques have allowed detecting vertical land motions and sea-level changes of a few millimetres per year, based on measurements taken at the coast (tide gauges), on board of satellite platforms (satellite altimetry) or both (Global Navigation Satellite System). Here, contemporary vertical land motions are analysed from January 1993 to July 2013 at 849 globally distributed coastal sites. The vertical displacement of the coastal platform due to surface mass changes is modelled using elastic and viscoelastic Green's functions. Special attention is paid to the effects of glacial isostatic adjustment induced by past and present-day ice melting. Various rheological and loading parameters are explored to provide a set of scenarios that could explain the coastal observations of vertical land motions globally. In well-instrumented regions, predicted vertical land motions explain more than 80 per cent of the variance observed at scales larger than a few hundred kilometres. Residual vertical land motions show a strong local variability, especially in the vicinity of plate boundaries due to the earthquake cycle. Significant residual signals are also observed at scales of a few hundred kilometres over nine well-instrumented regions forming observation windows on unmodelled geophysical processes. This study highlights the potential of our multitechnique database to detect geodynamical processes, driven by anthropogenic influence, surface mass changes (surface loading and glacial isostatic adjustment) and tectonic activity (including the earthquake cycle, sediment and volcanic loading, as well as regional tectonic constraints). Future improvements should be aimed at densifying the instrumental network and at investigating more thoroughly the uncertainties associated with glacial isostatic adjustment models.

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.

Meter-scale slopes of candidate MER landing sites from point photoclinometry

USGS Publications Warehouse

Beyer, R.A.; McEwen, A.S.; Kirk, R.L.

2003-01-01

Photoclinometry was used to analyze the small-scale roughness of areas that fall within the proposed Mars Exploration Rover (MER) 2003 landing ellipses. The landing ellipses presented in this study were those in Athabasca Valles, Elysium Planitia, Eos Chasma, Gusev Crater, Isidis Planitia, Melas Chasma, and Meridiani Planum. We were able to constrain surface slopes on length scales comparable to the image resolution (1.5 to 12 m/pixel). The MER 2003 mission has various engineering constraints that each candidate landing ellipse must satisfy. These constraints indicate that the statistical slope values at 5 m baselines are an important criterion. We used our technique to constrain maximum surface slopes across large swaths of each image, and built up slope statistics for the images in each landing ellipse. We are confident that all MER 2003 landing site ellipses in this study, with the exception of the Melas Chasma ellipse, are within the small-scale roughness constraints. Our results have provided input into the landing hazard assessment process. In addition to evaluating the safety of the landing sites, our mapping of small-scale roughnesses can also be used to better define and map morphologic units. The morphology of a surface is characterized by the slope distribution and magnitude of slopes. In looking at how slopes are distributed, we can better define landforms and determine the boundaries of morphologic units. Copyright 2003 by the American Geophysical Union.

Near-surface turbulence as a missing link in modeling evapotranspiration-soil moisture relationships

NASA Astrophysics Data System (ADS)

Haghighi, Erfan; Kirchner, James W.

2017-07-01

Despite many efforts to develop evapotranspiration (ET) models with improved parametrizations of resistance terms for water vapor transfer into the atmosphere, estimates of ET and its partitioning remain prone to bias. Much of this bias could arise from inadequate representations of physical interactions near nonuniform surfaces from which localized heat and water vapor fluxes emanate. This study aims to provide a mechanistic bridge from land-surface characteristics to vertical transport predictions, and proposes a new physically based ET model that builds on a recently developed bluff-rough bare soil evaporation model incorporating coupled soil moisture-atmospheric controls. The newly developed ET model explicitly accounts for (1) near-surface turbulent interactions affecting soil drying and (2) soil-moisture-dependent stomatal responses to atmospheric evaporative demand that influence leaf (and canopy) transpiration. Model estimates of ET and its partitioning were in good agreement with available field-scale data, and highlight hidden processes not accounted for by commonly used ET schemes. One such process, nonlinear vegetation-induced turbulence (as a function of vegetation stature and cover fraction) significantly influences ET-soil moisture relationships. Our results are particularly important for water resources and land use planning of semiarid sparsely vegetated ecosystems where soil surface interactions are known to play a critical role in land-climate interactions. This study potentially facilitates a mathematically tractable description of the strength (i.e., the slope) of the ET-soil moisture relationship, which is a core component of models that seek to predict land-atmosphere coupling and its feedback to the climate system in a changing climate.

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.

Preliminary Assessment of Mars Exploration Rover Landing Site Predictions

NASA Technical Reports Server (NTRS)

Golombek, M.; Grant, J.; Parker, T.; Crisp, J.; Squyres, S.; Carr, M.; Haldemann, A.; Arvidson, R.; Ehlmann, B.; Bell, J.

2004-01-01

Selection of the Mars Exploration Rover (MER) landing sites took place over a three year period in which engineering constraints were identified, 155 possible sites were downselected to the final two, surface environments and safety considerations were developed, and the potential science return at the sites was considered. Landing sites in Gusev crater and Meridiani Planum were selected because they appeared acceptably safe for MER landing and roving and had strong morphologic and mineralogical indicators of liquid water in their past and thus appeared capable of addressing the science objectives of the MER missions, which are to determine the aqueous, climatic, and geologic history of sites on Mars where conditions may have been favorable to the preservation of evidence of possible pre-biotic or biotic processes. Engineering constraints important to the selection included: latitude (10 N-15 S) for maximum solar power; elevation (<-1.3 km) for sufficient atmosphere to slow the lander; low horizontal winds, shear and turbulence in the last few kilometers to minimize horizontal velocity; low 10-m scale slopes to reduce airbag spinup and bounce; moderate rock abundance to reduce abrasion or stroke-out of the airbags; and a radar-reflective, load-bearing and trafficable surface safe for landing and roving that is not dominated by fine-grained dust. In selecting the MER landing sites these engineering constraints were addressed via comprehensive evaluation of surface and atmospheric characteristics from existing remote sensing data and models as well as targeted orbital information acquired from Mars Global Surveyor and Mars Odyssey. This evaluation resulted in a number of predictions of the surface characteristics of the sites, which are tested in this abstract. Relating remote sensing signatures to surface characteristics at landing sites allows these sites to be used as ground truth for the orbital data, is essential for selecting and validating landing sites for future missions, and is required for correctly interpreting the surfaces and materials globally present on Mars.

Evaluation of Ten Methods for Initializing a Land Surface Model

NASA Technical Reports Server (NTRS)

Rodell, M.; Houser, P. R.; Berg, A. A.; Famiglietti, J. S.

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).

Landsat: A global land-observing program

USGS Publications Warehouse

,

2005-01-01

Landsat represents the world’s longest continuously acquired collection of space-based land remote sensing data. The Landsat Project is a joint initiative of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) designed to gather Earth resource data from space. NASA developed and launched the spacecrafts, while the USGS handles the operations, maintenance, and management of all ground data reception, processing, archiving, product generation, and distribution.Landsat satellites have been collecting images of the Earth’s surface for more than thirty years. Landsat’s Global Survey Mission is to repeatedly capture images of the Earth’s land mass, coastal boundaries, and coral reefs, and to ensure that sufficient data are acquired to support the observation of changes on the Earth’s land surface and surrounding environment. NASA launched the first Landsat satellite in 1972, and the most recent one, Landsat 7, in 1999. Landsats 5 and 7 continue to capture hundreds of additional images of the Earth’s surface each day. These images provide a valuable resource for people who work

Modeling green infrastructure land use changes on future air ...

EPA Pesticide Factsheets

Green infrastructure can be a cost-effective approach for reducing stormwater runoff and improving water quality as a result, but it could also bring co-benefits for air quality: less impervious surfaces and more vegetation can decrease the urban heat island effect, and also result in more removal of air pollutants via dry deposition with increased vegetative surfaces. Cooler surface temperatures can also decrease ozone formation through the increases of NOx titration; however, cooler surface temperatures also lower the height of the boundary layer resulting in more concentrated pollutants within the same volume of air, especially for primary emitted pollutants (e.g. NOx, CO, primary particulate matter). To better understand how green infrastructure impacts air quality, the interactions between all of these processes must be considered collectively. In this study, we use a comprehensive coupled meteorology-air quality model (WRF-CMAQ) to simulate the influence of planned land use changes that include green infrastructure in Kansas City (KC) on regional meteorology and air quality. Current and future land use data was provided by the Mid-America Regional Council for 2012 and 2040 (projected land use due to population growth, city planning and green infrastructure implementation). These land use datasets were incorporated into the WRF-CMAQ modeling system allowing the modeling system to propagate the changes in vegetation and impervious surface coverage on meteoro

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.

Optimization of Modeled Land-Atmosphere Exchanges of Water and Energy in an Isotopically-Enabled Land Surface Model by Bayesian Parameter Calibration

NASA Astrophysics Data System (ADS)

Wong, T. E.; Noone, D. C.; Kleiber, W.

2014-12-01

The single largest uncertainty in climate model energy balance is the surface latent heating over tropical land. Furthermore, the partitioning of the total latent heat flux into contributions from surface evaporation and plant transpiration is of great importance, but notoriously poorly constrained. Resolving these issues will require better exploiting information which lies at the interface between observations and advanced modeling tools, both of which are imperfect. There are remarkably few observations which can constrain these fluxes, placing strict requirements on developing statistical methods to maximize the use of limited information to best improve models. Previous work has demonstrated the power of incorporating stable water isotopes into land surface models for further constraining ecosystem processes. We present results from a stable water isotopically-enabled land surface model (iCLM4), including model experiments partitioning the latent heat flux into contributions from plant transpiration and surface evaporation. It is shown that the partitioning results are sensitive to the parameterization of kinetic fractionation used. We discuss and demonstrate an approach to calibrating select model parameters to observational data in a Bayesian estimation framework, requiring Markov Chain Monte Carlo sampling of the posterior distribution, which is shown to constrain uncertain parameters as well as inform relevant values for operational use. Finally, we discuss the application of the estimation scheme to iCLM4, including entropy as a measure of information content and specific challenges which arise in calibration models with a large number of parameters.

New capabilities for characterizing smoke and dust aerosol over land using MODIS

NASA Astrophysics Data System (ADS)

Levy, R. C.; Remer, L. A.

2006-12-01

Smoke and dust aerosol have different chemical, optical and physical properties and both types affect many processes within the climate system. As earth's surface and atmosphere are continuously altered by natural and anthropogenic processes, the emission and presumably the effects of these aerosols are also changing. Thus it is necessary to observe and characterize aerosols on a global and climatic scale. While MODIS has been reporting characteristics of smoke and dust aerosol over land and ocean since shortly after Terra launch, the uncertainties in the over-land retrieval have been larger than expected. To better characterize different aerosol types closer to their source regions with greater accuracy, we have developed a new operational algorithm for retrieving aerosol properties over dark land surfaces from MODIS-observed visible (VIS) and infrared (IR) reflectance. Like earlier versions, this algorithm estimates the total loading (aerosol optical depth-τ) and relative weighting of fine (non-dust) and coarse (dust) -dominated aerosol to the total τ (fine weighting-η) over dark land surfaces. However, the fundamental mathematics and major assumptions have been overhauled. The new algorithm performs simultaneous multi-channel inversion that includes information about coarse aerosol in the IR channels, while assuming a fine-tuned relationship between VIS and IR surface reflectances, that is itself a function of scattering angle and vegetation condition. Finally, the suite of expected aerosol optical models described by the lookup table have been revised to closer resemble the AERONET climatology, including for smoke and dust aerosol. Beginning in April 2006, this algorithm has been used for forward processing and backward re- processing of the entire MODIS dataset observed from both Terra and Aqua. "Collection 5" products were completed for Aqua reprocessing by July 2006 and should be complete for Terra by December 2006. In this study, we used the complete Aqua dataset (July 2002-Aug 2006) and two years of Terra (2005-Aug 2006) data to evaluate the products in regions known to be dominated by smoke and/or dust. We compared with sunphotometer data at selected AERONET sites and found improved τ retrievals,within prescribed accuracy.

Retrieval of tropospheric aerosol properties over land from visible and near-infrared spectral reflectance: Application over Maryland

NASA Astrophysics Data System (ADS)

Levy, Robert Carroll

Aerosols are major components of the Earth's global climate system, affecting the radiation budget and cloud processes of the atmosphere. When located near the surface, high concentrations lead to lowered visibility, increased health problems and generally reduced quality of life for the human population. Over the United States mid-Atlantic region, aerosol pollution is a problem mainly during the summer. Satellites, such as the MODerate Imaging Spectrometer (MODIS), from their vantage point above the atmosphere, provide unprecedented coverage of global and regional aerosols over land. During MODIS' eight-year operation, exhaustive data validation and analyses have shown how the algorithm should be improved. This dissertation describes the development of the 'second-generation' operational algorithm for retrieval of global tropospheric aerosol properties over dark land surfaces, from MODIS-observed spectral reflectance. New understanding about global aerosol properties, land surface reflectance characteristics, and radiative transfer properties were learned in the process. This new operational algorithm performs a simultaneous inversion of reflectance in two visible channels (0.47 and 0.66 mum) and one shortwave infrared channel (2.12 mum), thereby having increased sensitivity to coarse aerosol. Inversion of the three channels retrieves the aerosol optical depth (tau) at 0.55 mum, the percentage of non-dust (fine model) aerosol (eta) and the surface reflectance. This algorithm is applied globally, and retrieves tau that is highly correlated (y = 0.02 + 1.0x, R=0.9) with ground-based sunphotometer measurements. The new algorithm estimates the global, over-land, long-term averaged tau ˜ 0.21, a 25% reduction from previous MODIS estimates. This leads to reducing estimates of global, non-desert, over-land aerosol direct radiative effect (all aerosols) by 1.7 W·m-2 (0.5 W·m-2 over the entire globe), which significantly impacts assessment of aerosol direct radiative forcing (contribution from anthropogenic aerosols only). Over the U.S. mid-Atlantic region, validated retrievals of tau (an integrated column property) can help to estimate surface PM2.5 concentration, a monitored criteria air quality property. The 3-dimensional aerosol loading in the region is characterized using aircraft measurements and the Community Multi-scale Air Quality Model (CMAQ) model, leading to some convergence of observed quantities and modeled processes.

Reconstructed Historical Land Cover and Biophysical Parameters for Studies of Land-Atmosphere Interactions within the Eastern United States

NASA Technical Reports Server (NTRS)

Steyaert, Louis T.; Knox, Robert G.

2007-01-01

The local environment where we live within the Earth's biosphere is often taken for granted. This environment can vary depending on whether the land cover is a forest, grassland, wetland, water body, bare soil, pastureland, agricultural field, village, residential suburb, or an urban complex with concrete, asphalt, and large buildings. In general, the type and characteristics of land cover influence surface temperatures, sunlight exposure and duration, relative humidity, wind speed and direction, soil moisture amount, plant life, birds, and other wildlife in our backyards. The physical and biological properties (biophysical characteristics) of land cover help to determine our surface environment because they directly affect surface radiation, heat, and soil moisture processes, and also feedback to regional weather and climate. Depending on the spatial scale and land use intensity, land cover changes can have profound impacts on our local and regional environment. Over the past 350 years, the eastern half of the United States, an area extending from the grassland prairies of the Great Plains to the Gulf and Atlantic coasts, has experienced extensive land cover and land use changes that began with land clearing in the 1600s, led to extensive deforestation and intensive land use practices by 1920, and then evolved to the present-day landscape. Determining the consequences of such land cover changes on regional and global climate is a major research issue. Such research requires detailed historical land cover data and modeling experiments simulating historical climates. Given the need to understand the effects of historical land cover changes in the eastern United States, some questions include: - What were the most important land cover transformations and how did they alter biophysical characteristics of the land cover at key points in time since the mid-1600s? - How have land cover and land use changes over the past 350 years affected the land surface environment including surface weather, hydrologic, and climatic variability? - How do the potential effects of regional human-induced land cover change on the environment compare to similar changes that are caused by the natural variations of the Earth's climate system? To help answer these questions, we reconstructed a fractional land cover and biophysical parameter dataset for the eastern United States at 1650, 1850, 1920, and 1992 time-slices. Each land cover fraction is associated with a biophysical parameter class, a suite of parameters defining the biophysical characteristics of that kind of land cover. This new dataset is designed for use in computer models of land-atmosphere interactions, to understand and quantify the effects of historical land cover changes on the water, energy, and carbon cycles

Simulating crop phenology in the Community Land Model and its impact on energy and carbon fluxes

USDA-ARS?s Scientific Manuscript database

A reasonable representation of crop phenology and biophysical processes in land surface models is necessary to accurately simulate energy, water and carbon budgets at the field, regional, and global scales. However, the evaluation of crop models that can be coupled to earth system models is relative...

Investigating habitat value to inform contaminant remediation options: approach

Treesearch

Rebecca A. Efroymson; Mark J. Peterson; Christopher J. Welsh; Daniel L. Druckenbrod; Michael G. Ryon; John G. Smith; William W. Hargrove; Neil R. Giffen; W. Kelly Roy; Harry D. Quarles

2008-01-01

Habitat valuation methods are most often developed and used to prioritize candidate lands for conservation. In this study the intent of habitat valuation was to inform the decision-making process for remediation of chemical contaminants on specific lands or surface water bodies. Methods were developed to summarize dimensions of habitat value for six representative...

Land–atmosphere feedbacks amplify aridity increase over land under global warming

USGS Publications Warehouse

Berg, Alexis; Findell, Kirsten; Lintner, Benjamin; Giannini, Alessandra; Seneviratne, Sonia I.; van den Hurk, Bart; Lorenz, Ruth; Pitman, Andy; Hagemann, Stefan; Meier, Arndt; Cheruy, Frédérique; Ducharne, Agnès; Malyshev, Sergey; Milly, Paul C. D.

2016-01-01

The response of the terrestrial water cycle to global warming is central to issues including water resources, agriculture and ecosystem health. Recent studies indicate that aridity, defined in terms of atmospheric supply (precipitation, P) and demand (potential evapotranspiration, Ep) of water at the land surface, will increase globally in a warmer world. Recently proposed mechanisms for this response emphasize the driving role of oceanic warming and associated atmospheric processes. Here we show that the aridity response is substantially amplified by land–atmosphere feedbacks associated with the land surface’s response to climate and CO2 change. Using simulations from the Global Land Atmosphere Coupling Experiment (GLACE)-CMIP5 experiment, we show that global aridity is enhanced by the feedbacks of projected soil moisture decrease on land surface temperature, relative humidity and precipitation. The physiological impact of increasing atmospheric CO2 on vegetation exerts a qualitatively similar control on aridity. We reconcile these findings with previously proposed mechanisms by showing that the moist enthalpy change over land is unaffected by the land hydrological response. Thus, although oceanic warming constrains the combined moisture and temperature changes over land, land hydrology modulates the partitioning of this enthalpy increase towards increased aridity.

The 1 km AVHRR global land data set: first stages in implementation

USGS Publications Warehouse

Eidenshink, J.C.; Faundeen, J.L.

1994-01-01

The global land 1 km data set project represents an international effort to acquire, archive, process, and distribute 1 km AVHRR data of the entire global land surface in order to meet the needs of the international science community. A network of 26 high resolution picture transmission (HRPT) stations, along with data recorded by the National Oceanic and Atmospheric Administration (NOAA), has been acquiring daily global land coverage since 1 April 1992. A data set of over 30000 AVHRR images has been archived and made available for distribution by the United States Geological Survey, EROS Data Center and the European Space Agency. Under the guidance of the International Geosphere Biosphere programme, processing standards for the AVHRR data have been developed for calibration, atmospheric correction, geometric registration, and the production of global 10-day maximum normalized difference vegetation index (NDVI) composites. The major uses of the composites are related to the study of surface vegetation cover. A prototype 10-day composite was produced for the period of 21–30 June 1992. Production of an 18-month time series of 10-day composites is underway.

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.

Improving the Fit of a Land-Surface Model to Data Using its Adjoint

NASA Astrophysics Data System (ADS)

Raoult, N.; Jupp, T. E.; Cox, P. M.; Luke, C.

2015-12-01

Land-surface models (LSMs) are of growing importance in the world of climate prediction. They are crucial components of larger Earth system models that are aimed at understanding the effects of land surface processes on the global carbon cycle. The Joint UK Land Environment Simulator (JULES) is the land-surface model used by the UK Met Office. It has been automatically differentiated using commercial software from FastOpt, resulting in an analytical gradient, or 'adjoint', of the model. Using this adjoint, the adJULES parameter estimation system has been developed, to search for locally optimum parameter sets by calibrating against observations. adJULES presents an opportunity to confront JULES with many different observations, and make improvements to the model parameterisation. In the newest version of adJULES, multiple sites can be used in the calibration, to giving a generic set of parameters that can be generalised over plant functional types. We present an introduction to the adJULES system and its applications to data from a variety of flux tower sites. We show that calculation of the 2nd derivative of JULES allows us to produce posterior probability density functions of the parameters and how knowledge of parameter values is constrained by observations.

Incorporating dynamic root growth enhances the performance of Noah-MP at two contrasting winter wheat field sites

NASA Astrophysics Data System (ADS)

Gayler, Sebastian; Wöhling, Thomas; Ingwersen, Joachim; Wizemann, Hans-Dieter; Warrach-Sagi, Kirsten; Attinger, Sabine; Streck, Thilo; Wulmeyer, Volker

2014-05-01

Interactions between the soil, the vegetation, and the atmospheric boundary layer require close attention when predicting water fluxes in the hydrogeosystem, agricultural systems, weather and climate. However, land-surface schemes used in large scale models continue to show deficits in consistently simulating fluxes of water and energy from the subsurface through vegetation layers to the atmosphere. In this study, the multi-physics version of the Noah land-surface model (Noah-MP) was used to identify the processes, which are most crucial for a simultaneous simulation of water and heat fluxes between land-surface and the lower atmosphere. Comprehensive field data sets of latent and sensible heat fluxes, ground heat flux, soil moisture, and leaf area index from two contrasting field sites in South-West Germany are used to assess the accuracy of simulations. It is shown that an adequate representation of vegetation-related processes is the most important control for a consistent simulation of energy and water fluxes in the soil-plant-atmosphere system. In particular, using a newly implemented sub-module to simulate root growth dynamics has enhanced the performance of Noah-MP at both field sites. We conclude that further advances in the representation of leaf area dynamics and root/soil moisture interactions are the most promising starting points for improving the simulation of feedbacks between the sub-soil, land-surface and atmosphere in fully-coupled hydrological and atmospheric models.

Hydrogeological controls of groundwater - land surface interactions

NASA Astrophysics Data System (ADS)

Bresciani, Etienne; Batelaan, Okke; Goderniaux, Pascal

2017-04-01

Interaction of groundwater with the land surface impacts a wide range of climatic, hydrologic, ecologic and geomorphologic processes. Many site-specific studies have successfully focused on measuring and modelling groundwater-surface water interaction, but upscaling or estimation at catchment or regional scale appears to be challenging. The factors controlling the interaction at regional scale are still poorly understood. In this contribution, a new 2-D (cross-sectional) analytical groundwater flow solution is used to derive a dimensionless criterion that expresses the conditions under which the groundwater outcrops at the land surface (Bresciani et al., 2016). The criterion gives insights into the functional relationships between geology, topography, climate and the locations of groundwater discharge along river systems. This sheds light on the debate about the topographic control of groundwater flow and groundwater-surface water interaction, as effectively the topography only influences the interaction when the groundwater table reaches the land surface. The criterion provides a practical tool to predict locations of groundwater discharge if a limited number of geomorphological and hydrogeological parameters (recharge, hydraulic conductivity and depth to impervious base) are known, and conversely it can provide regional estimates of the ratio of recharge over hydraulic conductivity if locations of groundwater discharge are known. A case study with known groundwater discharge locations located in South-West Brittany, France shows the feasibility of regional estimates of the ratio of recharge over hydraulic conductivity. Bresciani, E., Goderniaux, P. and Batelaan, O., 2016, Hydrogeological controls of water table-land surface interactions. Geophysical Research Letters 43(18): 9653-9661. http://dx.doi.org/10.1002/2016GL070618

Statistical modelling predicts almost complete loss of major periglacial processes in Northern Europe by 2100.

PubMed

Aalto, Juha; Harrison, Stephan; Luoto, Miska

2017-09-11

The periglacial realm is a major part of the cryosphere, covering a quarter of Earth's land surface. Cryogenic land surface processes (LSPs) control landscape development, ecosystem functioning and climate through biogeochemical feedbacks, but their response to contemporary climate change is unclear. Here, by statistically modelling the current and future distributions of four major LSPs unique to periglacial regions at fine scale, we show fundamental changes in the periglacial climate realm are inevitable with future climate change. Even with the most optimistic CO 2 emissions scenario (Representative Concentration Pathway (RCP) 2.6) we predict a 72% reduction in the current periglacial climate realm by 2050 in our climatically sensitive northern Europe study area. These impacts are projected to be especially severe in high-latitude continental interiors. We further predict that by the end of the twenty-first century active periglacial LSPs will exist only at high elevations. These results forecast a future tipping point in the operation of cold-region LSP, and predict fundamental landscape-level modifications in ground conditions and related atmospheric feedbacks.Cryogenic land surface processes characterise the periglacial realm and control landscape development and ecosystem functioning. Here, via statistical modelling, the authors predict a 72% reduction of the periglacial realm in Northern Europe by 2050, and almost complete disappearance by 2100.

Asian Monsoons: Variability, Predictability, and Sensitivity to External Forcing

NASA Technical Reports Server (NTRS)

Yang, Song; Lau, K.-M.

1999-01-01

In this study, we have addressed the interannual variations of Asian monsoons including both broad-scale and regional monsoon components. Particular attention is devoted to the identities of the South China Sea monsoon and Indian monsoon. We use CPC Merged Analysis of Precipitation and NCEP reanalyses to define regional monsoon indices and to depict the various monsoons. Parallel modeling studies have also been carried out to assess the role of boundary forcing and the potential predictability of the monsoons. Each monsoon is characterized by its unique features. While the South Asian monsoon represents a classical monsoon in which anomalous circulation is governed by Rossby-wave dynamics, the Southeast Asian monsoon symbolizes a "hybrid" monsoon that features multi-cellular meridional circulation over eastern Asia. The broad-scale Asian monsoon links to the basin-wide atmospheric circulation over the Indian-Pacific oceans. Both SST and land surface processes are important for determining the variations of all monsoons. For the broad-scale monsoon, SST anomalies are more important than land surface processes. For regional monsoons, however, land surface processes may become equally important. Both observation and model shows that the broad-scale monsoon is potentially more predictable than regional monsoons, and that the Southeast Asian monsoon may possess higher predictability than the South Asian monsoon.

Mapping the global land surface using 1 km AVHRR data

USGS Publications Warehouse

Lauer, D.T.; Eidenshink, J.C.

1998-01-01

The scientific requirements for mapping the global land surface using 1 km advanced very high resolution radiometer (AVHRR) data have been set forth by the U.S. Global Change Research Program; the International Geosphere Biosphere Programme (IGBP); The United Nations; the National Oceanic and Atmospheric Administration (NOAA); the Committee on Earth Observations Satellites; and the National Aeronautics and Space Administration (NASA) mission to planet Earth (MTPE) program. Mapping the global land surface using 1 km AVHRR data is an international effort to acquire, archive, process, and distribute 1 km AVHRR data to meet the needs of the international science community. A network of AVHRR receiving stations, along with data recorded by NOAA, has been acquiring daily global land coverage since April 1, 1992. A data set of over 70,000 AVHRR images is archived and distributed by the United States Geological Survey (USGS) EROS Data Center, and the European Space Agency. Under the guidance of the IGBP, processing standards have been developed for calibration, atmospheric correction, geometric registration, and the production of global 10-day maximum normalized difference vegetation index (NDVI) composites. The major uses of the composites are for the study of surface vegetation condition, mapping land cover, and deriving biophysical characteristics of terrestrial ecosystems. A time-series of 54 10-day global vegetation index composites for the period of April 1, 1992 through September 1993 has been produced. The production of a time-series of 33 10-day global vegetation index composites using NOAA-14 data for the period of February 1, 1995 through December 31, 1995 is underway. The data products are available from the USGS, in cooperation with NASA's MTPE program and other international organizations.

Recent Enhancements in NOAA's JPSS Land Product Suite and Key Operational Applications

NASA Astrophysics Data System (ADS)

Csiszar, I. A.; Yu, Y.; Zhan, X.; Vargas, M.; Ek, M. B.; Zheng, W.; Wu, Y.; Smirnova, T. G.; Benjamin, S.; Ahmadov, R.; James, E.; Grell, G. A.

2017-12-01

A suite of operational land products has been produced as part of NOAA's Joint Polar Satellite System (JPSS) program to support a wide range of operational applications in environmental monitoring, prediction, disaster management and mitigation, and decision support. The Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (NPP) and the operational JPSS satellite series forms the basis of six fundamental and multiple additional added-value environmental data records (EDRs). A major recent improvement in the land-based VIIRS EDRs has been the development of global gridded products, providing a format and science content suitable for ingest into NOAA's operational land surface and coupled numerical weather prediction models. VIIRS near-real-time Green Vegetation Fraction is now in the process of testing for full operational use, while land surface temperature and albedo are under testing and evaluation. The operational 750m VIIRS active fire product, including fire radiative power, is used to support emission modeling and air quality applications. Testing the evaluation for operational NOAA implementation of the improved 375m VIIRS active fire product is also underway. Added-value and emerging VIIRS land products include vegetation health, phenology, near-real-time surface type and surface condition change, and other biogeophysical variables. As part of the JPSS program, a global soil moisture data product has also been generated from the Advanced Microwave Scanning Radiometer 2 (AMSR2) sensor on the GCOM-W1 (Global Change Observation Mission - Water 1) satellite since July 2012. This product is included in the blended NESDIS Soil Moisture Operational Products System, providing soil moisture data as a critical input for land surface modeling.

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.

Diagnosing the Sensitivity of Local Land-Atmosphere Coupling via the Soil Moisture-Boundary Layer Interaction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.

2011-01-01

The inherent coupled nature of earth s energy and water cycles places significant importance on the proper representation and diagnosis of land atmosphere (LA) interactions in hydrometeorological prediction models. However, the precise nature of the soil moisture precipitation relationship at the local scale is largely determined by a series of nonlinear processes and feedbacks that are difficult to quantify. To quantify the strength of the local LA coupling (LoCo), this process chain must be considered both in full and as individual components through their relationships and sensitivities. To address this, recent modeling and diagnostic studies have been extended to 1) quantify the processes governing LoCo utilizing the thermodynamic properties of mixing diagrams, and 2) diagnose the sensitivity of coupled systems, including clouds and moist processes, to perturbations in soil moisture. This work employs NASA s Land Information System (LIS) coupled to the Weather Research and Forecasting (WRF) mesoscale model and simulations performed over the U.S. Southern Great Plains. The behavior of different planetary boundary layers (PBL) and land surface scheme couplings in LIS WRF are examined in the context of the evolution of thermodynamic quantities that link the surface soil moisture condition to the PBL regime, clouds, and precipitation. Specifically, the tendency toward saturation in the PBL is quantified by the lifting condensation level (LCL) deficit and addressed as a function of time and space. The sensitivity of the LCL deficit to the soil moisture condition is indicative of the strength of LoCo, where both positive and negative feedbacks can be identified. Overall, this methodology can be applied to any model or observations and is a crucial step toward improved evaluation and quantification of LoCo within models, particularly given the advent of next-generation satellite measurements of PBL and land surface properties along with advances in data assimilation schemes.

[The progress in retrieving land surface temperature based on thermal infrared and microwave remote sensing technologies].

PubMed

Zhang, Jia-Hua; Li, Xin; Yao, Feng-Mei; Li, Xian-Hua

2009-08-01

Land surface temperature (LST) is an important parameter in the study on the exchange of substance and energy between land surface and air for the land surface physics process at regional and global scales. Many applications of satellites remotely sensed data must provide exact and quantificational LST, such as drought, high temperature, forest fire, earthquake, hydrology and the vegetation monitor, and the models of global circulation and regional climate also need LST as input parameter. Therefore, the retrieval of LST using remote sensing technology becomes one of the key tasks in quantificational remote sensing study. Normally, in the spectrum bands, the thermal infrared (TIR, 3-15 microm) and microwave bands (1 mm-1 m) are important for retrieval of the LST. In the present paper, firstly, several methods for estimating the LST on the basis of thermal infrared (TIR) remote sensing were synthetically reviewed, i. e., the LST measured with an ground-base infrared thermometer, the LST retrieval from mono-window algorithm (MWA), single-channel algorithm (SCA), split-window techniques (SWT) and multi-channels algorithm(MCA), single-channel & multi-angle algorithm and multi-channels algorithm & multi-angle algorithm, and retrieval method of land surface component temperature using thermal infrared remotely sensed satellite observation. Secondly, the study status of land surface emissivity (epsilon) was presented. Thirdly, in order to retrieve LST for all weather conditions, microwave remotely sensed data, instead of thermal infrared data, have been developed recently, and the LST retrieval method from passive microwave remotely sensed data was also introduced. Finally, the main merits and shortcomings of different kinds of LST retrieval methods were discussed, respectively.

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.

Sensitivity of Climate Simulations to Land-Surface and Atmospheric Boundary-Layer Treatments-A Review.

NASA Astrophysics Data System (ADS)

Garratt, J. R.

1993-03-01

Aspects of the land-surface and boundary-layer treatments in some 20 or so atmospheric general circulation models (GCMS) are summarized. In only a small fraction of these have significant sensitivity studies been carried out and published. Predominantly, the sensitivity studies focus upon the parameterization of land-surface processes and specification of land-surface properties-the most important of these include albedo, roughness length, soil moisture status, and vegetation density. The impacts of surface albedo and soil moisture upon the climate simulated in GCMs with bare-soil land surfaces are well known. Continental evaporation and precipitation tend to decrease with increased albedo and decreased soil moisture availability. For example, results from numerous studies give an average decrease in continental precipitation of 1 mm day1 in response to an average albedo increase of 0.13. Few conclusive studies have been carried out on the impact of a gross roughness-length change-the primary study included an important statistical assessment of the impact upon the mean July climate around the globe of a decreased continental roughness (by three orders of magnitude). For example, such a decrease reduced the precipitation over Amazonia by 1 to 2 mm day1.The inclusion of a canopy scheme in a GCM ensures the combined impacts of roughness (canopies tend to be rougher than bare soil), albedo (canopies tend to be less reflective than bare soil), and soil-moisture availability (canopies prevent the near-surface soil region from drying out and can access the deep soil moisture) upon the simulated climate. The most revealing studies to date involve the regional impact of Amazonian deforestation. The results of four such studies show that replacing tropical forest with a degraded pasture results in decreased evaporation ( 1 mm day1) and precipitation (1-2 mm day1), and increased near-surface air temperatures (2 K).Sensitivity studies as a whole suggest the need for a realistic surface representation in general circulation models of the atmosphere. It is not yet clear how detailed this representation needs to be, but even allowing for the importance of surface processes, the parameterization of boundary-layer and convective clouds probably represents a greater challenge to improved climate simulations. This is illustrated in the case of surface net radiation for Aniazonia, which is not well simulated and tends to be overestimated, leading to evaporation rates that are too large. Underestimates in cloudiness, cloud albedo, and clear-sky shortwave absorption, rather than in surface albedo, appear to be the main culprits.There are three major tasks that confront the researcher so far as the development and validation of atmospheric boundary-layer (ABL) and surface schemes in GCMs are concerned:(i) There is a need to as' critically the impact of `improved' parameterization schemes on WM simulations, taking into account the problem of natural variability and hence the statistical significance of the induced changes.(ii) There is a need to compare GCM simulations of surface and ABL behavior (particularly regarding the diurnal cycle of surface fluxes, air temperature, and ABL depth) with observations over a range of surface types (vegetation, desert, ocean). In this context, area-average values of surface fluxes will be required to calibrate directly the ABL/land-surface scheme in the GCM.(iii) There is a need for intercomparisons of ABL and land-surface schemes used in GCMS, both for one- dimensional stand-alone models and for GCMs that incorporate the respective schemes.

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.

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.

Contrasting self-aggregation over land and ocean surfaces

NASA Astrophysics Data System (ADS)

Inda Diaz, H. A.; O'Brien, T. A.

2017-12-01

The spontaneous organization of convection into clusters, or self-aggregation, demonstrably changes the nature and statistics of precipitation. While there has been much recent progress in this area, the processes that control self-aggregation are still poorly understood. Most of the work to date has focused on self-aggregation over ocean-like surfaces, but it is particularly pressing to understand what controls convective aggregation over land, since the associated change in precipitation statistics—between non-aggregated and aggregated convection—could have huge impacts on society and infrastructure. Radiative-convective equilibrium (RCE), has been extensively used as an idealized framework to study the tropical atmosphere. Self-aggregation manifests in numerous numerical models of RCE, nevertheless, there is still a lack of understanding in how it relates to convective organization in the observed world. Numerous studies have examined self-aggregation using idealized Cloud Resolving Models (CRMs) and General Circulation Models over the ocean, however very little work has been done on RCE and self-aggregation over land. Idealized models of RCE over ocean have shown that aggregation is sensitive to sea surface temperature (SST), more intense precipitation occurs in aggregated systems, and a variety of feedbacks—such as surface flux, cloud radiative, and upgradient moisture transport— contribute to the maintenance of aggregation, however it is not clear if these results apply over land. Progress in this area could help relate understanding of self-aggregation in idealized simulations to observations. In order to explore the behavior of self-aggregation over land, we use a CRM to simulate idealized RCE over land. In particular, we examine the aggregation of convection and how it compares with aggregation over ocean. Based on previous studies, where a variety of different CRMs exhibit a SST threshold below which self-aggregation does not occur, we hypothesize that idealized land simulations will exhibit similar threshold behavior when there is an adequate surface moisture supply. We systematically explore this by varying parameters that exert strong control on the surface enthalpy and moisture budget, such as type of land, surface albedo, and greenhouse gas concentration.

The Joint UK Land Environment Simulator (JULES), Model description - Part 2: Carbon fluxes and vegetation

NASA Astrophysics Data System (ADS)

Clark, D. B.; Mercado, L. M.; Sitch, S.; Jones, C. D.; Gedney, N.; Best, M. J.; Pryor, M.; Rooney, G. G.; Essery, R. L. H.; Blyth, E.; Boucher, O.; Harding, R. J.; Cox, P. M.

2011-03-01

The Joint UK Land Environment Simulator (JULES) is a process-based model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Past studies with JULES have demonstrated the important role of the land surface in the Earth System. Different versions of JULES have been employed to quantify the effects on the land carbon sink of separately changing atmospheric aerosols and tropospheric ozone, and the response of methane emissions from wetlands to climate change. There was a need to consolidate these and other advances into a single model code so as to be able to study interactions in a consistent manner. This paper describes the consolidation of these advances into the modelling of carbon fluxes and stores, in the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model. The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model.

Benchmarking sensitivity of biophysical processes to leaf area changes in land surface models

NASA Astrophysics Data System (ADS)

Forzieri, Giovanni; Duveiller, Gregory; Georgievski, Goran; Li, Wei; Robestson, Eddy; Kautz, Markus; Lawrence, Peter; Ciais, Philippe; Pongratz, Julia; Sitch, Stephen; Wiltshire, Andy; Arneth, Almut; Cescatti, Alessandro

2017-04-01

Land surface models (LSM) are widely applied as supporting tools for policy-relevant assessment of climate change and its impact on terrestrial ecosystems, yet knowledge of their performance skills in representing the sensitivity of biophysical processes to changes in vegetation density is still limited. This is particularly relevant in light of the substantial impacts on regional climate associated with the changes in leaf area index (LAI) following the observed global greening. Benchmarking LSMs on the sensitivity of the simulated processes to vegetation density is essential to reduce their uncertainty and improve the representation of these effects. Here we present a novel benchmark system to assess model capacity in reproducing land surface-atmosphere energy exchanges modulated by vegetation density. Through a collaborative effort of different modeling groups, a consistent set of land surface energy fluxes and LAI dynamics has been generated from multiple LSMs, including JSBACH, JULES, ORCHIDEE, CLM4.5 and LPJ-GUESS. Relationships of interannual variations of modeled surface fluxes to LAI changes have been analyzed at global scale across different climatological gradients and compared with satellite-based products. A set of scoring metrics has been used to assess the overall model performances and a detailed analysis in the climate space has been provided to diagnose possible model errors associated to background conditions. Results have enabled us to identify model-specific strengths and deficiencies. An overall best performing model does not emerge from the analyses. However, the comparison with other models that work better under certain metrics and conditions indicates that improvements are expected to be potentially achievable. A general amplification of the biophysical processes mediated by vegetation is found across the different land surface schemes. Grasslands are characterized by an underestimated year-to-year variability of LAI in cold climates, ultimately affecting the amount of absorbed radiation. In addition patterns of simulated turbulent fluxes appear opposite to observations. Such systematic errors shed light on the current partial understanding of some of the mechanisms controlling the surface energy balance. In contrast forests appear reasonably well represented with respect to the interactions between LAI and turbulent fluxes across most climatological gradients, while for net radiation this is only true for warm climates. These proven strengths increase the confidence on how certain processes are simulated in LSMs. The model capacity to mimic the vegetation-biophysics interplay has been tested over the real scenario of greening that occurred in the last 30 years. We found that the modeled trends in surface heat fluxes associated with the long-term changes in leaf area could vary largely from those observed, with different discrepancies across models and climate zones. Our findings help to identify knowledge gaps and improve model representation of the sensitivity of biophysical processes to changes in leaf area density. In particular, comparing models and observations over a wide range of climate and vegetation conditions, as analyzed here, allowed capturing non-linearity of system responses that may emerge more frequently in future climate scenarios.

Diagnosing Hydrologic Flow Paths in Forest and Pasture Land Uses within the Panama Canal Watershed Using Simulated Rainfall and Electrical Resistivity Tomography

NASA Astrophysics Data System (ADS)

Ogden, F. L.; Mojica, A.; Kempema, E. W.; Briceno, J. C.; Regina, J. A.

2014-12-01

Hydrological processes in the humid tropics are poorly understood and an important topic when it comes to water management in the seasonal tropics. The Smithsonian Tropical Research Institute, Panama Canal Watershed Experiment, Agua Salud Project, seeks to understand these processes and quantify the long-term effects of different land cover and use across the Panama Canal Watershed. In this study we used an ARS-type rainfall simulator to apply rainfall rates up to 200 mm per hour over a 2m by 6m area on deep saprolitic soils in forest and pasture land covers. A salinity contrast added to the applied rainwater allowed observation of bulk flow paths and velocities in the subsurface. The observed effects of land cover and land use on hydrological response were striking. In the forest site, we were unable to produce surface runoff even after the application of 600 mm of rainfall in three hours, and observed flow in soils down to approximately 2 m depth, and no downslope macropore flow. In the pasture site, surface runoff was produced, and we measured the permeability of the area with applied rainfall. Observed flow paths were much shallower, less than 1 m depth, with significant macropore flow observed at downslope positions. We hypothesize that land use and land cover have significant impacts on flow paths as they affect creation, connectivity, and function of biologically created macropores in the soil.

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.

National Centers for Environmental Prediction

Science.gov Websites

Processing Land Surface Software Engineering Hurricanes Model Information Documentation Performance Statistics Observational Data Processing Data Assimilation Monsoon Desk Model Transition Seminars Seminar Series Other Information Collaborators In-House Website Transition to Operations Presentations

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.

Land-atmosphere-aerosol coupling in North China during 2000­-2013

NASA Astrophysics Data System (ADS)

Wei, J.; Jin, Q.; Yang, Z. L.; Zhou, L.

2017-12-01

North China is one of the most densely populated regions in the world. To its west, north, and northwest, the world's largest afforestation project has been going on for decades. At the same time, North China has been suffering from air pollution because of its large fossil fuel consumption. Here we show that the changes in land cover and aerosol concentration are coupled with the variations of land surface temperature, cloud cover, and surface solar radiation during the summer 2000-2013. Model experiments show that the interannual variation of aerosol concentration in North China is mainly a result of the varying atmospheric circulation. The increasing vegetation cover due to afforestation has enhanced surface evapotranspiration (ET) and cooled the local surface, and precipitation is observed to be increasing with ET. The model with prescribed increasing vegetation cover can simulate the increasing ET but cannot reproduce the increasing precipitation. Although this may be caused by model biases, the lack of aerosol processes in the model could also be a potential cause.

Weak hydrological sensitivity to temperature change over land, independent of climate forcing

NASA Astrophysics Data System (ADS)

Samset, Bjorn H.

2017-04-01

As the global surface temperature changes, so will patterns and rates of precipitation. Theoretically, these changes can be understood in terms of changes to the energy balance of the atmosphere, caused by introducing drivers of climate change such as greenhouse gases, aerosols and altered insolation. Climate models, however, disagree strongly in their prediction of precipitation changes, both for historical and future emission pathways, and per degree of surface warming in idealized experiments. The latter value, often termed the apparent hydrological sensitivity, has also been found to differ substantially between climate drivers. Here, we present the global and regional hydrological sensitivity (HS) to surface temperature changes, for perturbations to CO2, CH4, sulfate and black carbon concentrations, and solar irradiance. Based on results from 10 climate models participating in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), we show how modeled global mean precipitation increases by 2-3 % per kelvin of global mean surface warming, independent of driver, when the effects of rapid adjustments are removed. Previously reported differences in response between drivers are therefore mainly ascribable to rapid atmospheric adjustment processes. All models show a sharp contrast in behavior over land and over ocean, with a strong surface temperature driven (slow) ocean HS of 3-5 %/K, while the slow land HS is only 0-2 %/K. Separating the response into convective and large-scale cloud processes, we find larger inter-model differences, in particular over land regions. Large-scale precipitation changes are most relevant at high latitudes, while the equatorial HS is dominated by convective precipitation changes. Black carbon stands out as the driver with the largest inter-model slow HS variability, and also the strongest contrast between a weak land and strong sea response. Convective precipitation in the Arctic and large scale precipitation around the Equator are found to be topics where further model investigations and observational constraints may provide rapid improvements to modelling of the precipitation response to future, CO2 dominated climate change.

Distributed parameterization of complex terrain

NASA Astrophysics Data System (ADS)

Band, Lawrence E.

1991-03-01

This paper addresses the incorporation of high resolution topography, soils and vegetation information into the simulation of land surface processes in atmospheric circulation models (ACM). Recent work has concentrated on detailed representation of one-dimensional exchange processes, implicitly assuming surface homogeneity over the atmospheric grid cell. Two approaches that could be taken to incorporate heterogeneity are the integration of a surface model over distributed, discrete portions of the landscape, or over a distribution function of the model parameters. However, the computational burden and parameter intensive nature of current land surface models in ACM limits the number of independent model runs and parameterizations that are feasible to accomplish for operational purposes. Therefore, simplications in the representation of the vertical exchange processes may be necessary to incorporate the effects of landscape variability and horizontal divergence of energy and water. The strategy is then to trade off the detail and rigor of point exchange calculations for the ability to repeat those calculations over extensive, complex terrain. It is clear the parameterization process for this approach must be automated such that large spatial databases collected from remotely sensed images, digital terrain models and digital maps can be efficiently summarized and transformed into the appropriate parameter sets. Ideally, the landscape should be partitioned into surface units that maximize between unit variance while minimizing within unit variance, although it is recognized that some level of surface heterogeneity will be retained at all scales. Therefore, the geographic data processing necessary to automate the distributed parameterization should be able to estimate or predict parameter distributional information within each surface unit.

Aeolian processes at the Mars Exploration Rover Meridiani Planum landing site.

PubMed

Sullivan, R; Banfield, D; Bell, J F; Calvin, W; Fike, D; Golombek, M; Greeley, R; Grotzinger, J; Herkenhoff, K; Jerolmack, D; Malin, M; Ming, D; Soderblom, L A; Squyres, S W; Thompson, S; Watters, W A; Weitz, C M; Yen, A

2005-07-07

The martian surface is a natural laboratory for testing our understanding of the physics of aeolian (wind-related) processes in an environment different from that of Earth. Martian surface markings and atmospheric opacity are time-variable, indicating that fine particles at the surface are mobilized regularly by wind. Regolith (unconsolidated surface material) at the Mars Exploration Rover Opportunity's landing site has been affected greatly by wind, which has created and reoriented bedforms, sorted grains, and eroded bedrock. Aeolian features here preserve a unique record of changing wind direction and wind strength. Here we present an in situ examination of a martian bright wind streak, which provides evidence consistent with a previously proposed formational model for such features. We also show that a widely used criterion for distinguishing between aeolian saltation- and suspension-dominated grain behaviour is different on Mars, and that estimated wind friction speeds between 2 and 3 m s(-1), most recently from the northwest, are associated with recent global dust storms, providing ground truth for climate model predictions.

Aeolian processes at the Mars Exploration Rover Meridiani Planum landing site

USGS Publications Warehouse

Sullivan, R.; Banfield, D.; Bell, J.F.; Calvin, W.; Fike, D.; Golombek, M.; Greeley, R.; Grotzinger, J.; Herkenhoff, K.; Jerolmack, D.; Malin, M.; Ming, D.; Soderblom, L.A.; Squyres, S. W.; Thompson, S.; Watters, W.A.; Weitz, C.M.; Yen, A.

2005-01-01

The martian surface is a natural laboratory for testing our understanding of the physics of aeolian (wind-related) processes in an environment different from that of Earth. Martian surface markings and atmospheric opacity are time-variable, indicating that fine particles at the surface are mobilized regularly by wind. Regolith (unconsolidated surface material) at the Mars Exploration Rover Opportunity's landing site has been affected greatly by wind, which has created and reoriented bedforms, sorted grains, and eroded bedrock. Aeolian features here preserve a unique record of changing wind direction and wind strength. Here we present an in situ examination of a martian bright wind streak, which provides evidence consistent with a previously proposed formational model for such features. We also show that a widely used criterion for distinguishing between aeolian saltation- and suspension-dominated grain behaviour is different on Mars, and that estimated wind friction speeds between 2 and 3 m s-1, most recently from the northwest, are associated with recent global dust storms, providing ground truth for climate model predictions.

Constraints, Approach, and Status of Mars Surveyor 2001 Landing Site Selection

NASA Technical Reports Server (NTRS)

Golombek, M.; Bridges, N.; Briggs, G.; Gilmore, M.; Haldemann, A.; Parker, T.; Saunders, R.; Spencer, D.; Smith, J.; Soderblom, L.

1999-01-01

There are many similarities between the Mars Surveyor '01 (MS '01) landing site selection process and that of Mars Pathfinder. The selection process includes two parallel activities in which engineers define and refine the capabilities of the spacecraft through design, testing and modeling and scientists define a set of landing site constraints based on the spacecraft design and landing scenario. As for Pathfinder, the safety of the site is without question the single most important factor, for the simple reason that failure to land safely yields no science and exposes the mission and program to considerable risk. The selection process must be thorough and defensible and capable of surviving multiple withering reviews similar to the Pathfinder decision. On Pathfinder, this was accomplished by attempting to understand the surface properties of sites using available remote sensing data sets and models based on them. Science objectives are factored into the selection process only after the safety of the site is validated. Finally, as for Pathfinder, the selection process is being done in an open environment with multiple opportunities for community involvement including open workshops, with education and outreach opportunities. Additional information is contained in the original extended abstract.

Sources of Uncertainty in Predicting Land Surface Fluxes Using Diverse Data and Models

NASA Technical Reports Server (NTRS)

Dungan, Jennifer L.; Wang, Weile; Michaelis, Andrew; Votava, Petr; Nemani, Ramakrishma

2010-01-01

In the domain of predicting land surface fluxes, models are used to bring data from large observation networks and satellite remote sensing together to make predictions about present and future states of the Earth. Characterizing the uncertainty about such predictions is a complex process and one that is not yet fully understood. Uncertainty exists about initialization, measurement and interpolation of input variables; model parameters; model structure; and mixed spatial and temporal supports. Multiple models or structures often exist to describe the same processes. Uncertainty about structure is currently addressed by running an ensemble of different models and examining the distribution of model outputs. To illustrate structural uncertainty, a multi-model ensemble experiment we have been conducting using the Terrestrial Observation and Prediction System (TOPS) will be discussed. TOPS uses public versions of process-based ecosystem models that use satellite-derived inputs along with surface climate data and land surface characterization to produce predictions of ecosystem fluxes including gross and net primary production and net ecosystem exchange. Using the TOPS framework, we have explored the uncertainty arising from the application of models with different assumptions, structures, parameters, and variable definitions. With a small number of models, this only begins to capture the range of possible spatial fields of ecosystem fluxes. Few attempts have been made to systematically address the components of uncertainty in such a framework. We discuss the characterization of uncertainty for this approach including both quantifiable and poorly known aspects.

Atmosphere, ocean, and land: Critical gaps in Earth system models

NASA Technical Reports Server (NTRS)

Prinn, Ronald G.; Hartley, Dana

1992-01-01

We briefly review current knowledge and pinpoint some of the major areas of uncertainty for the following fundamental processes: (1) convection, condensation nuclei, and cloud formation; (2) oceanic circulation and its coupling to the atmosphere and cryosphere; (3) land surface hydrology and hydrology-vegetation coupling; (4) biogeochemistry of greenhouse gases; and (5) upper atmospheric chemistry and circulation.

Photosynthesis sensitivity to climate change in land surface models

NASA Astrophysics Data System (ADS)

Manrique-Sunen, Andrea; Black, Emily; Verhoef, Anne; Balsamo, Gianpaolo

2016-04-01

Accurate representation of vegetation processes within land surface models is key to reproducing surface carbon, water and energy fluxes. Photosynthesis determines the amount of CO2 fixated by plants as well as the water lost in transpiration through the stomata. Photosynthesis is calculated in land surface models using empirical equations based on plant physiological research. It is assumed that CO2 assimilation is either CO2 -limited, radiation -limited ; and in some models export-limited (the speed at which the products of photosynthesis are used by the plant) . Increased levels of atmospheric CO2 concentration tend to enhance photosynthetic activity, but the effectiveness of this fertilization effect is regulated by environmental conditions and the limiting factor in the photosynthesis reaction. The photosynthesis schemes at the 'leaf level' used by land surface models JULES and CTESSEL have been evaluated against field photosynthesis observations. Also, the response of photosynthesis to radiation, atmospheric CO2 and temperature has been analysed for each model, as this is key to understanding the vegetation response that climate models using these schemes are able to reproduce. Particular emphasis is put on the limiting factor as conditions vary. It is found that while at present day CO2 concentrations export-limitation is only relevant at low temperatures, as CO2 levels rise it becomes an increasingly important restriction on photosynthesis.

Remote Sensing of Urban Thermal Landscape Characteristics and Their Affects on Local and Regional Meteorology and Air Quality: An Overview of NASA EOS-IDS Project Atlanta

NASA Technical Reports Server (NTRS)

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

1999-01-01

As an entity, the city is a manifestation of human "management" of the land. The act of city-building, however, drastically alters the biophysical environment, which ultimately, impacts local and regional land-atmosphere energy exchange processes. Because of the complexity of both the urban landscape and the attendant energy fluxes that result from urbanization, remote sensing offers the only real way to synoptically quantify these processes. One of the more important land-atmosphere fluxes that occurs over cities relates to the way that thermal energy is partitioned across the heterogeneous urban landscape. The individual land cover and surface material types that comprise the city, such as pavements and buildings, each have their own thermal energy regimes. As the collective urban landscape, the individual thermal energy responses from specific surfaces come together to form the urban heat island phenomena, which prevails as a dome of elevated air temperatures over cities. Although the urban heat island has been known to exist for well over 150 years, it is not understood how differences in thermal energy responses for land covers across the city interact to produce this phenomenon, or how the variability in thermal energy responses from different surface types drive its development. Additionally, it can be hypothesized that as cities grow in size through time, so do their urban heat islands. The interrelationships between urban sprawl and the respective growth of the urban heat island, however, have not been investigated. Moreover, little is known of the consequential effects of urban growth, land cover change, and the urban heat island as they impact local and regional meteorology and air quality.

Estimation of Land Surface Energy Balance Using Satellite Data of Spatial Reduced Resolution

NASA Astrophysics Data System (ADS)

Vintila, Ruxandra; Radnea, Cristina; Savin, Elena; Poenaru, Violeta

2010-12-01

The paper presents preliminary results concerning the monitoring at national level of several geo-biophysical variables retrieved by remote sensing, in particular those related to drought or aridisation. The study, which is in progress, represents also an exercise for to the implementation of a Land Monitoring Core Service for Romania, according to the Kopernikus Program and in compliance with the INSPIRE Directive. The SEBS model has been used to retrieve land surface energy balance variables, such as turbulent heat fluxes, evaporative fraction and daily evaporation, based on three information types: (1) surface albedo, emissivity, temperature, fraction of vegetation cover (fCover), leaf area index (LAI) and vegetation height; (2) air pressure, temperature, humidity and wind speed at the planetary boundary layer (PBL) height; (3) downward solar radiation and downward longwave radiation. AATSR and MERIS archived reprocessed images have provided several types of information. Thus, surface albedo, emissivity, and land surface temperature have been retrieved from AATSR, while LAI and fCover have been estimated from MERIS. The vegetation height has been derived from CORINE Land Cover and PELCOM Land Use databases, while the meteorological information at the height of PBL have been estimated from the measurements provided by the national weather station network. Other sources of data used during this study have been the GETASSE30 digital elevation model with 30" spatial resolution, used for satellite image orthorectification, and the SIGSTAR-200 geographical information system of soil resources of Romania, used for water deficit characterisation. The study will continue by processing other AATSR and MERIS archived images, complemented by the validation of SEBS results with ground data collected on the most important biomes for Romania at various phenological stages, and the transformation of evaporation / evapotranspiration into a drought index using the soil texture data. It is also foreseen to develop procedures for processing near-real time AATSR and MERIS images from the rolling archives, as well as procedures for dealing with SENTINEL 3 images in the future, for timely delivery of reliable information to authorities and planning for drought to reduce its effects on citizens.

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

Zoran, Maria; Savastru, Roxana; Savastru, Dan

This paper presents a complex multidisciplinary approach concept to explain the nature of short-term earthquake precursors observed in land surface, atmosphere, ionosphere and magnetosphere for strong intermediate depth earthquakes recorded in Vrancea region in Romania. A developed Lithosphere-Surfacesphere-Atmosphere-Ionosphere (LSAI) coupling model can explain most of these presignals as a synergy between different anomalies of geophysical/geochemical parameters. These anomalies prior to medium to strong earthquakes are attributed to the thermodynamic, degassing and ionization processes in the Earth-Atmosphere system and micro-fracturing in the rocks especially along area’s active faults. The main outcome of this paper is an unified concept for systematic validationmore » of different types of earthquake precursors of which Land Surface Temperature (LST), outgoing Long wave Radiation (OLR), Surface Latent Heat Flux (SLHF), Air Temperature (AT), radon gas concentration, ionospheric Total Electron Content (TEC) are the most reliable parameters within the chain of the processes described by LSAI model.« less

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

Analysis of relationships between land surface temperature and land use changes in the Yellow River Delta

NASA Astrophysics Data System (ADS)

Ning, Jicai; Gao, Zhiqiang; Meng, Ran; Xu, Fuxiang; Gao, Meng

2018-06-01

This study analyzed land use and land cover changes and their impact on land surface temperature using Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager and Thermal Infrared Sensor imagery of the Yellow River Delta. Six Landsat images comprising two time series were used to calculate the land surface temperature and correlated vegetation indices. The Yellow River Delta area has expanded substantially because of the deposited sediment carried from upstream reaches of the river. Between 1986 and 2015, approximately 35% of the land use area of the Yellow River Delta has been transformed into salterns and aquaculture ponds. Overall, land use conversion has occurred primarily from poorly utilized land into highly utilized land. To analyze the variation of land surface temperature, a mono-window algorithm was applied to retrieve the regional land surface temperature. The results showed bilinear correlation between land surface temperature and the vegetation indices (i.e., Normalized Difference Vegetation Index, Adjusted-Normalized Vegetation Index, Soil-Adjusted Vegetation Index, and Modified Soil-Adjusted Vegetation Index). Generally, values of the vegetation indices greater than the inflection point mean the land surface temperature and the vegetation indices are correlated negatively, and vice versa. Land surface temperature in coastal areas is affected considerably by local seawater temperature and weather conditions.

Application of Physics Based Distributed Hydrologic Models to Assess Anthropologic Land Disturbance in Watersheds

NASA Astrophysics Data System (ADS)

Downer, C. W.; Ogden, F. L.; Byrd, A. R.

2008-12-01

The Department of Defense (DoD) manages approximately 200,000 km2 of land within the United States on military installations and flood control and river improvement projects. The Watershed Systems Group (WSG) within the Coastal and Hydraulics Laboratory of the Engineer Research and Development Center (ERDC) supports the US Army and the US Army Corps of Engineers in both military and civil operations through the development, modification and application of surface and sub-surface hydrologic models. The US Army has a long history of land management and the development of analytical tools to assist with the management of US Army lands. The US Army has invested heavily in the distributed hydrologic model GSSHA and its predecessor CASC2D. These tools have been applied at numerous military and civil sites to analyze the effects of landscape alteration on hydrologic response and related consequences, changes in erosion and sediment transport, along with associated contaminants. Examples include: impacts of military training and land management activities, impact of changing land use (urbanization or environmental restoration), as well as impacts of management practices employed to abate problems, i.e. Best Management Practices (BMPs). Traditional models such as HSPF and SWAT, are largely conceptual in nature. GSSHA attempts to simulate the physical processes actually occurring in the watershed allowing the user to explicitly simulate changing parameter values in response to changes in land use, land cover, elevation, etc. Issues of scale raise questions: How do we best include fine-scale land use or management features in models of large watersheds? Do these features have to be represented explicitly through physical processes in the watershed domain? Can a point model, physical or empirical, suffice? Can these features be lumped into coarsely resolved numerical grids or sub-watersheds? In this presentation we will discuss the US Army's distributed hydrologic models in terms of how they simulate the relevant processes and present multiple applications of the models used for analyzing land management and land use change. Using these applications as a basis we will discuss issues related to the analysis of anthropogenic alterations in the landscape.

Benefits and Pitfalls of GRACE Terrestrial Water Storage Data Assimilation

NASA Technical Reports Server (NTRS)

Girotto, Manuela

2018-01-01

Satellite observations of terrestrial water storage (TWS) from the Gravity Recovery and Climate Experiment (GRACE) mission have a coarse resolution in time (monthly) and space (roughly 150,000 sq km at midlatitudes) and vertically integrate all water storage components over land, including soil moisture and groundwater. Nonetheless, data assimilation can be used to horizontally downscale and vertically partition GRACE-TWS observations. This presentation illustrates some of the benefits and drawbacks of assimilating TWS observations from GRACE into a land surface model over the continental United States and India. The assimilation scheme yields improved skill metrics for groundwater compared to the no-assimilation simulations. A smaller impact is seen for surface and root-zone soil moisture. Further, GRACE observes TWS depletion associated with anthropogenic groundwater extraction. Results from the assimilation emphasize the importance of representing anthropogenic processes in land surface modeling and data assimilation systems.

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.

Application of LANDSAT data to monitor land reclamation progress in Belmont County, Ohio

NASA Technical Reports Server (NTRS)

Bloemer, H. H. L.; Brumfield, J. O.; Campbell, W. J.; Witt, R. G.; Bly, B. G.

1981-01-01

Strip and contour mining techniques are reviewed as well as some studies conducted to determine the applicability of LANDSAT and associated digital image processing techniques to the surficial problems associated with mining operations. A nontraditional unsupervised classification approach to multispectral data is considered which renders increased classification separability in land cover analysis of surface mined areas. The approach also reduces the dimensionality of the data and requires only minimal analytical skills in digital data processing.

Investigation of a long time series of CO2 from a tall tower using WRF-SPA

NASA Astrophysics Data System (ADS)

Smallman, Luke; Williams, Mathew; Moncrieff, John B.

2013-04-01

Atmospheric observations from tall towers are an important source of information about CO2 exchange at the regional scale. Here, we have used a forward running model, WRF-SPA, to generate a time series of CO2 at a tall tower for comparison with observations from Scotland over multiple years (2006-2008). We use this comparison to infer strength and distribution of sources and sinks of carbon and ecosystem process information at the seasonal scale. The specific aim of this research is to combine a high resolution (6 km) forward running meteorological model (WRF) with a modified version of a mechanistic ecosystem model (SPA). SPA provides surface fluxes calculated from coupled energy, hydrological and carbon cycles. This closely coupled representation of the biosphere provides realistic surface exchanges to drive mixing within the planetary boundary layer. The combined model is used to investigate the sources and sinks of CO2 and to explore which land surfaces contribute to a time series of hourly observations of atmospheric CO2 at a tall tower, Angus, Scotland. In addition to comparing the modelled CO2 time series to observations, modelled ecosystem specific (i.e. forest, cropland, grassland) CO2 tracers (e.g., assimilation and respiration) have been compared to the modelled land surface assimilation to investigate how representative tall tower observations are of land surface processes. WRF-SPA modelled CO2 time series compares well to observations (R2 = 0.67, rmse = 3.4 ppm, bias = 0.58 ppm). Through comparison of model-observation residuals, we have found evidence that non-cropped components of agricultural land (e.g., hedgerows and forest patches) likely contribute a significant and observable impact on regional carbon balance.

Relationships between aerodynamic roughness and land use and land cover in Baltimore, Maryland

USGS Publications Warehouse

Nicholas, F.W.; Lewis, J.E.

1980-01-01

Urbanization changes the radiative, thermal, hydrologic, and aerodynamic properties of the Earth's surface. Knowledge of these surface characteristics, therefore, is essential to urban climate analysis. Aerodynamic or surface roughness of urban areas is not well documented, however, because of practical constraints in measuring the wind profile in the presence of large buildings. Using an empirical method designed by Lettau, and an analysis of variance of surface roughness values calculated for 324 samples averaging 0.8 hectare (ha) of land use and land cover sample in Baltimore, Md., a strong statistical relation was found between aerodynamic roughness and urban land use and land cover types. Assessment of three land use and land cover systems indicates that some of these types have significantly different surface roughness characteristics. The tests further indicate that statistically significant differences exist in estimated surface roughness values when categories (classes) from different land use and land cover classification systems are used as surrogates. A Level III extension of the U.S. Geological Survey Level II land use and land cover classification system provided the most reliable results. An evaluation of the physical association between the aerodynamic properties of land use and land cover and the surface climate by numerical simulation of the surface energy balance indicates that changes in surface roughness within the range of values typical of the Level III categories induce important changes in the surface climate.

A two-step framework for reconstructing remotely sensed land surface temperatures contaminated by cloud

NASA Astrophysics Data System (ADS)

Zeng, Chao; Long, Di; Shen, Huanfeng; Wu, Penghai; Cui, Yaokui; Hong, Yang

2018-07-01

Land surface temperature (LST) is one of the most important parameters in land surface processes. Although satellite-derived LST can provide valuable information, the value is often limited by cloud contamination. In this paper, a two-step satellite-derived LST reconstruction framework is proposed. First, a multi-temporal reconstruction algorithm is introduced to recover invalid LST values using multiple LST images with reference to corresponding remotely sensed vegetation index. Then, all cloud-contaminated areas are temporally filled with hypothetical clear-sky LST values. Second, a surface energy balance equation-based procedure is used to correct for the filled values. With shortwave irradiation data, the clear-sky LST is corrected to the real LST under cloudy conditions. A series of experiments have been performed to demonstrate the effectiveness of the developed approach. Quantitative evaluation results indicate that the proposed method can recover LST in different surface types with mean average errors in 3-6 K. The experiments also indicate that the time interval between the multi-temporal LST images has a greater impact on the results than the size of the contaminated area.

Climate Simulations based on a different-grid nested and coupled model

NASA Astrophysics Data System (ADS)

Li, Dan; Ji, Jinjun; Li, Yinpeng

2002-05-01

An atmosphere-vegetation interaction model (A VIM) has been coupled with a nine-layer General Cir-culation Model (GCM) of Institute of Atmospheic Physics/State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (IAP/LASG), which is rhomboidally truncated at zonal wave number 15, to simulate global climatic mean states. A VIM is a model having inter-feedback between land surface processes and eco-physiological processes on land. As the first step to couple land with atmosphere completely, the physiological processes are fixed and only the physical part (generally named the SVAT (soil-vegetation-atmosphere-transfer scheme) model) of AVIM is nested into IAP/LASG L9R15 GCM. The ocean part of GCM is prescribed and its monthly sea surface temperature (SST) is the climatic mean value. With respect to the low resolution of GCM, i.e., each grid cell having lon-gitude 7.5° and latitude 4.5°, the vegetation is given a high resolution of 1.5° by 1.5° to nest and couple the fine grid cells of land with the coarse grid cells of atmosphere. The coupling model has been integrated for 15 years and its last ten-year mean of outputs was chosen for analysis. Compared with observed data and NCEP reanalysis, the coupled model simulates the main characteris-tics of global atmospheric circulation and the fields of temperature and moisture. In particular, the simu-lated precipitation and surface air temperature have sound results. The work creates a solid base on coupling climate models with the biosphere.

Climatological Downscaling and Evaluation of AGRMET Precipitation Analyses Over the Continental U.S.

NASA Astrophysics Data System (ADS)

Garcia, M.; Peters-Lidard, C. D.; Eylander, J. B.; Daly, C.; Tian, Y.; Zeng, J.

2007-05-01

The spatially distributed application of a land surface model (LSM) over a region of interest requires the application of similarly distributed precipitation fields that can be derived from various sources, including surface gauge networks, surface-based radar, and orbital platforms. The spatial variability of precipitation influences the spatial organization of soil temperature and moisture states and, consequently, the spatial variability of land- atmosphere fluxes. The accuracy of spatially-distributed precipitation fields can contribute significantly to the uncertainty of model-based hydrological states and fluxes at the land surface. Collaborations between the Air Force Weather Agency (AFWA), NASA, and Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS-based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and near-real-time simulations in regions of interest. This work focuses on value added to the AGRMET precipitation product by the inclusion of high-quality climatological information on a monthly time scale. The AGRMET method uses microwave-based satellite precipitation estimates from various polar-orbiting platforms (NOAA POES and DMSP), infrared-based estimates from geostationary platforms (GOES, METEOSAT, etc.), related cloud analysis products, and surface gauge observations in a complex and hierarchical blending process. Results from processing of the legacy AGRMET precipitation products over the U.S. using LIS-based methods for downscaling, both with and without climatological factors, are evaluated against high-resolution monthly analyses using the PRISM knowledge- based method (Daly et al. 2002). It is demonstrated that the incorporation of climatological information in a downscaling procedure can significantly enhance the accuracy, and potential utility, of AFWA precipitation products for military and civilian customer applications.

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.

Upscaling surface energy fluxes over the North Slope of Alaska using airborne eddy-covariance measurements and environmental response functions

NASA Astrophysics Data System (ADS)

Serafimovich, Andrei; Metzger, Stefan; Hartmann, Jörg; Kohnert, Katrin; Zona, Donatella; Sachs, Torsten

2018-03-01

The objective of this study was to upscale airborne flux measurements of sensible heat and latent heat and to develop high resolution flux maps. In order to support the evaluation of coupled atmospheric/land-surface models we investigated spatial patterns of energy fluxes in relation to land-surface properties. We used airborne eddy-covariance measurements acquired by the POLAR 5 research aircraft in June-July 2012 to analyze surface fluxes. Footprint-weighted surface properties were then related to 21 529 sensible heat flux observations and 25 608 latent heat flux observations using both remote sensing and modelled data. A boosted regression tree technique was used to estimate environmental response functions between spatially and temporally resolved flux observations and corresponding biophysical and meteorological drivers. In order to improve the spatial coverage and spatial representativeness of energy fluxes we used relationships extracted across heterogeneous Arctic landscapes to infer high-resolution surface energy flux maps, thus directly upscaling the observational data. These maps of projected sensible heat and latent heat fluxes were used to assess energy partitioning in northern ecosystems and to determine the dominant energy exchange processes in permafrost areas. This allowed us to estimate energy fluxes for specific types of land cover, taking into account meteorological conditions. Airborne and modelled fluxes were then compared with measurements from an eddy-covariance tower near Atqasuk. Our results are an important contribution for the advanced, scale-dependent quantification of surface energy fluxes and provide new insights into the processes affecting these fluxes for the main vegetation types in high-latitude permafrost areas.

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.

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.

Simulation of future land use change and climate change impacts on hydrological processes in a tropical catchment

NASA Astrophysics Data System (ADS)

Marhaento, H.; Booij, M. J.; Hoekstra, A. Y.

2017-12-01

Future hydrological processes in the Samin catchment (278 km2) in Java, Indonesia have been simulated using the Soil and Water Assessment Tool (SWAT) model using inputs from predicted land use distributions in the period 2030 - 2050, bias corrected Regional Climate Model (RCM) output and output of six Global Climate Models (GCMs) to include climate model uncertainty. Two land use change scenarios namely a business-as-usual (BAU) scenario, where no measures are taken to control land use change, and a controlled (CON) scenario, where the future land use follows the land use planning, were used in the simulations together with two climate change scenarios namely Representative Concentration Pathway (RCP) 4.5 and 8.5. It was predicted that in 2050 settlement and agriculture area of the study catchment will increase by 33.9% and 3.5%, respectively under the BAU scenario, whereas agriculture area and evergreen forest will increase by 15.2% and 10.2%, respectively under the CON scenario. In comparison to the baseline conditions (1983 - 2005), the predicted mean annual maximum and minimum temperature in 2030 - 2050 will increase by an average of +10C, while changes in the mean annual rainfall range from -20% to +19% under RCP 4.5 and from -25% to +15% under RCP 8.5. The results show that land use change and climate change individually will cause changes in the water balance components, but that more pronounced changes are expected if the drivers are combined, in particular for changes in annual stream flow and surface runoff. It was observed that combination of the RCP 4.5 climate scenario and BAU land use scenario resulted in an increase of the mean annual stream flow from -7% to +64% and surface runoff from +21% to +102%, which is 40% and 60% more than when land use change is acting alone. Furthermore, under the CON scenario the annual stream flow and surface runoff could be potentially reduced by up to 10% and 30%, respectively indicating the effectiveness of applied land use planning. The findings of this study will be useful for the water resource managers to mitigate future risks associated with land use and climate changes in the study catchment. Keywords: land use change, climate change, hydrological impact assessment, Samin catchment

Impact of fire on global land carbon, water, and energy budgets and climate during the 20th century through changing ecosystems

NASA Astrophysics Data System (ADS)

Li, F.; Lawrence, D. M.; Bond-Lamberty, B. P.; Levis, S.

2016-12-01

Fire is an integral Earth system process and the primary form of terrestrial ecosystem disturbance on a global scale. Here we provide the first quantitative assessment and understanding on fire's impact on global land carbon, water, and energy budgets and climate through changing ecosystems. This is done by quantifying the difference between 20th century fire-on and fire-off simulations using the Community Earth System Model (CESM1.2). Results show that fire decreases the net carbon gain of global terrestrial ecosystems by 1.0 Pg C/yr averaged across the 20th century, as a result of biomass and peat burning (1.9 Pg C/yr) partly offset by changing gross primary productivity, respiration, and land-use carbon loss (-0.9 Pg C/yr). In addition, fire's effect on global carbon budget intensifies with time. Fire significantly reduces land evapotranspiration (ET) by 600 km3/yr and increases runoff, but has limited impact on precipitation. The impact on ET and runoff is most clearly seen in the tropical savannas, African rainforest, and some boreal and Southern Asian forests mainly due to fire-induced reduction in the vegetation canopy. It also weakens both the significant upward trend in global land ET prior to the 1950s and the downward trend from 1950 to 1985 by 35%. Fire-induced changes in land ecosystems affects global energy budgets by significantly reducing latent heating and surface net radiation. Fire changes surface radiative budget dominantly by raising surface upward longwave radiation and net longwave radiation. It also increases the global land average surface air temperature (Tas) by 0.04°C, and significantly increases wind speed and decreases surface relative humidity. The fire-induced change in wind speed, Tas, and relative humidity implies a positive feedback loop between fire and climate. Moreover, fire-induced changes in land ecosystems contribute 20% of strong global land warming during 1910-1940, which provides a new mechanism for the early 20th century global land warming. The results emphasize the importance of fire disturbance in the Earth's carbon, water, and energy cycles and climate by changing terrestrial ecosystems.

Characterizing the Mineralogy of Potential Lunar Landing Sites

NASA Technical Reports Server (NTRS)

Pieters, Carle; Head, James W., III; Mustard, Jack; Boardman, Joe; Buratti, Bonnie; Clark, Roger; Green, Rob; Head, James W, III; McCord, Thomas B.; Mustard, Jack;

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.

Responses of surface ozone air quality to anthropogenic nitrogen deposition in the Northern Hemisphere

NASA Astrophysics Data System (ADS)

Zhao, Yuanhong; Zhang, Lin; Tai, Amos P. K.; Chen, Youfan; Pan, Yuepeng

2017-08-01

Human activities have substantially increased atmospheric deposition of reactive nitrogen to the Earth's surface, inducing unintentional effects on ecosystems with complex environmental and climate consequences. One consequence remaining unexplored is how surface air quality might respond to the enhanced nitrogen deposition through surface-atmosphere exchange. Here we combine a chemical transport model (GEOS-Chem) and a global land model (Community Land Model, CLM) to address this issue with a focus on ozone pollution in the Northern Hemisphere. We consider three processes that are important for surface ozone and can be perturbed by the addition of atmospheric deposited nitrogen - namely, emissions of biogenic volatile organic compounds (VOCs), ozone dry deposition, and soil nitrogen oxide (NOx) emissions. We find that present-day anthropogenic nitrogen deposition (65 Tg N a-1 to the land), through enhancing plant growth (represented as increases in vegetation leaf area index, LAI, in the model), could increase surface ozone from increased biogenic VOC emissions (e.g., a 6.6 Tg increase in isoprene emission), but it could also decrease ozone due to higher ozone dry deposition velocities (up to 0.02-0.04 cm s-1 increases). Meanwhile, deposited anthropogenic nitrogen to soil enhances soil NOx emissions. The overall effect on summer mean surface ozone concentrations shows general increases over the globe (up to 1.5-2.3 ppbv over the western US and South Asia), except for some regions with high anthropogenic NOx emissions (0.5-1.0 ppbv decreases over the eastern US, western Europe, and North China). We compare the surface ozone changes with those driven by the past 20-year climate and historical land use changes. We find that the impacts from anthropogenic nitrogen deposition can be comparable to the climate- and land-use-driven surface ozone changes at regional scales and partly offset the surface ozone reductions due to land use changes reported in previous studies. Our study emphasizes the complexity of biosphere-atmosphere interactions, which can have important implications for future air quality prediction.

Assessing the Reliability of Land-Use Data in Slovenia: A Case Study of Terraced Landscapes

NASA Astrophysics Data System (ADS)

Ažman Momirski, Lucija

2017-10-01

Land use relates to the exploitation of land through human activity in the landscape. Land use is also one of the best indicators of a landscape’s structure and processes. Land cover comprises manmade surfaces, agricultural areas, forest and semi-natural areas, wetlands, and bodies of water. In Slovenia more than half of the land (63%) is forested. Manmade surfaces represent less than 5%. A large proportion of relatively inaccessible forest is the main reason why society had a less critical impact on forests in the past in Slovenia in comparison to the majority of central European countries. Regarding the high-quality landscape in the country, Slovenia’s natural features are characterized by a mix of forest and farmland. These land categories (i.e., complex cultivation patterns and land principally used for agriculture with significant areas of natural vegetation) cover 23% of Slovenia. Land-use data for farmland are gathered and provided to the relevant institutions by landowners, who are not specialists in land-use data. In addition, land use is only a two-dimensional tool, which does not recognize elevation differences and terraced slopes. Terraced areas are either omitted from the inventory of land-use data because landowners do not report them, or they are included in the inventory because landowners do not realize that their land is not terraced. Consequently, the differences between the official data on vineyards, orchards, and olive groves on terraces and actual terraced slopes with such land use may differ significantly.

Insights on How NASA's Earth Observing System (EOS) Monitors Our World Environment

NASA Technical Reports Server (NTRS)

King, Michael D.

2000-01-01

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

Generating daily high spatial land surface temperatures by combining ASTER and MODIS land surface temperature products for environmental process monitoring.

PubMed

Wu, Mingquan; Li, Hua; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

2015-08-01

There is a shortage of daily high spatial land surface temperature (LST) data for use in high spatial and temporal resolution environmental process monitoring. To address this shortage, this work used the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), and the Spatial and Temporal Data Fusion Approach (STDFA) to estimate high spatial and temporal resolution LST by combining Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LST and Moderate Resolution Imaging Spectroradiometer (MODIS) LST products. The actual ASTER LST products were used to evaluate the precision of the combined LST images using the correlation analysis method. This method was tested and validated in study areas located in Gansu Province, China. The results show that all the models can generate daily synthetic LST image with a high correlation coefficient (r) of 0.92 between the synthetic image and the actual ASTER LST observations. The ESTARFM has the best performance, followed by the STDFA and the STARFM. Those models had better performance in desert areas than in cropland. The STDFA had better noise immunity than the other two models.

Modelling Soil Heat and Water Flow as a Coupled Process in Land Surface Models

NASA Astrophysics Data System (ADS)

García González, Raquel; Verhoef, Anne; Vidale, Pier Luigi; Braud, Isabelle

2010-05-01

To improve model estimates of soil water and heat flow by land surface models (LSMs), in particular in the first few centimetres of the near-surface soil profile, we have to consider in detail all the relevant physical processes involved (see e.g. Milly, 1982). Often, thermal and iso-thermal vapour fluxes in LSMs are neglected and the simplified Richard's equation is used as a result. Vapour transfer may affect the water fluxes and heat transfer in LSMs used for hydrometeorological and climate simulations. Processes occurring in the top 50 cm soil may be relevant for water and heat flux dynamics in the deeper layers, as well as for estimates of evapotranspiration and heterotrophic respiration, or even for climate and weather predictions. Water vapour transfer, which was not incorporated in previous versions of the MOSES/JULES model (Joint UK Land Environment Simulator; Cox et al., 1999), has now been implemented. Furthermore, we also assessed the effect of the soil vertical resolution on the simulated soil moisture and temperature profiles and the effect of the processes occurring at the upper boundary, mainly in terms of infiltration rates and evapotranspiration. SiSPAT (Simple Soil Plant Atmosphere Transfer Model; Braud et al., 1995) was initially used to quantify the changes that we expect to find when we introduce vapour transfer in JULES, involving parameters such as thermal vapour conductivity and diffusivity. Also, this approach allows us to compare JULES to a more complete and complex numerical model. Water vapour flux varied with soil texture, depth and soil moisture content, but overall our results suggested that water vapour fluxes change temperature gradients in the entire soil profile and introduce an overall surface cooling effect. Increasing the resolution smoothed and reduced temperature differences between liquid (L) and liquid/vapour (LV) simulations at all depths, and introduced a temperature increase over the entire soil profile. Thermal gradients rather than soil water potential gradients seem to cause temporal and spatial (vertical) soil temperature variability. We conclude that a multi-soil layer configuration may improve soil water dynamics, heat transfer and coupling of these processes, as well as evapotranspiration estimates and land surface-atmosphere coupling. However, a compromise should be reached between numerical and process-simulation aspects. References: Braud I., A.C. Dantas-Antonino, M. Vauclin, J.L. Thony and P. Ruelle, 1995b: A Simple Soil Plant Atmo- sphere Transfer model (SiSPAT), Development and field verification, J. Hydrol, 166: 213-250 Cox, P.M., R.A. Betts, C.B. Bunton, R.L.H. Essery, P.R. Rowntree, and J. Smith (1999), The impact of new land surface physics on the GCM simulation of climate and climate sensitivity. Clim. Dyn., 15, 183-203. Milly, P.C.D., 1982. Moisture and heat transport in hysteric inhomogeneous porous media: a matric head- based formulation and a numerical model, Water Resour. Res., 18:489-498

Generating Land Surface Reflectance for the New Generation of Geostationary Satellite Sensors with the MAIAC Algorithm

NASA Astrophysics Data System (ADS)

Wang, W.; Wang, Y.; Hashimoto, H.; Li, S.; Takenaka, H.; Higuchi, A.; Lyapustin, A.; Nemani, R. R.

2017-12-01

The latest generation of geostationary satellite sensors, including the GOES-16/ABI and the Himawari 8/AHI, provide exciting capability to monitor land surface at very high temporal resolutions (5-15 minute intervals) and with spatial and spectral characteristics that mimic the Earth Observing System flagship MODIS. However, geostationary data feature changing sun angles at constant view geometry, which is almost reciprocal to sun-synchronous observations. Such a challenge needs to be carefully addressed before one can exploit the full potential of the new sources of data. Here we take on this challenge with Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, recently developed for accurate and globally robust applications like the MODIS Collection 6 re-processing. MAIAC first grids the top-of-atmosphere measurements to a fixed grid so that the spectral and physical signatures of each grid cell are stacked ("remembered") over time and used to dramatically improve cloud/shadow/snow detection, which is by far the dominant error source in the remote sensing. It also exploits the changing sun-view geometry of the geostationary sensor to characterize surface BRDF with augmented angular resolution for accurate aerosol retrievals and atmospheric correction. The high temporal resolutions of the geostationary data indeed make the BRDF retrieval much simpler and more robust as compared with sun-synchronous sensors such as MODIS. As a prototype test for the geostationary-data processing pipeline on NASA Earth Exchange (GEONEX), we apply MAIAC to process 18 months of data from Himawari 8/AHI over Australia. We generate a suite of test results, including the input TOA reflectance and the output cloud mask, aerosol optical depth (AOD), and the atmospherically-corrected surface reflectance for a variety of geographic locations, terrain, and land cover types. Comparison with MODIS data indicates a general agreement between the retrieved surface reflectance products. Furthermore, the geostationary results satisfactorily capture the movement of clouds and variations in atmospheric dust/aerosol concentrations, suggesting that high quality land surface and vegetation datasets from the advanced geostationary sensors can help complement and improve the corresponding EOS products.

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).

The Development in modeling Tibetan Plateau Land/Climate Interaction

NASA Astrophysics Data System (ADS)

Xue, Yongkang; Liu, Ye; li, qian; Maheswor Shrestha, Maheswor; Ma, Hsi-Yen; Cox, Peter; Sun, shufen; Koike, Toshio

2015-04-01

Tibetan Plateau (TP) plays an important role in influencing the continental and planetary scale climate, including East Asian and South Asian monsoon, circulation and precipitation over West Pacific and Indian Oceans. The numerical study has identified TP as the area with strongest land/atmosphere interactions over the midlatitude land. The land degradation there has also affected the monsoon precipitation in TP along the monsoon pathway. The water cycle there affects water sources for major Asian river systems, which include the Tarim, Amu Darya, Indus, Ganges, Brahmaputra, Irrawaddy, Salween, Mekong, Yellow, and Yangtze Rivers. Despite the importance of TP land process in the climate system, the TP land surface processes are poorly modeled due to lack of data available for model validation. To better understand, simulate, and project the role of Tibetan Plateau land surface processes, better parameterization of the Tibetan Land surface processes have been developed and evaluated. The recently available field measurement there and satellite observation have greatly helped this development. This paper presents these new developments and preliminary results using the newly developed biophysical/dynamic vegetation model, frozen soil model, and glacier model. In recent CMIP5 simulation, the CMIP5 models with dynamic vegetation model show poor performance in simulating the TP vegetation and climate. To better simulate the TP vegetation condition and its interaction with climate, we have developed biophysical/dynamic vegetation model, the Simplified Simple Biosphere Model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID), based on water, carbon, and energy balance. The simulated vegetation variables are updates, driven by carbon assimilation, allocation, and accumulation, as well as competition between plant functional types. The model has been validated with the station data, including those measured over the TP. The offline SSiB4/TRIFFID is integrated using the observed precipitation and reanalysis-based meteorological forcing from 1948 to 2008 with 1 degree horizontal resolution. The simulated vegetation conditions and surface hydrology are compared well with observational data with some bias, and shows strong decadal and interannual variabilities with a linear trend associated with the global warming. The TP region is covered by both discontinuous and sporadic permafrost with irregular snow layers above. A frozen soil model is developed to take the coupling effect of mass and heat transport into consideration and includes a detailed description of mass balances of volumetric liquid water, ice, as well as vapor content. It also considers contributions' of heat conduction to the energy balance. The model has been extensively tested using a number of TP station data, which included soil temperature and soil water measurements. The results suggest that it is important to include the frozen sol process to adequately simulate the surface energy balance during the freezing and thawing periods and surface temperature variability, including its diurnal variation. Issues in simulating permafrost process will also be addressed. To better understand the glacier variations under climate change scenarios, an integrated modeling system with an energy budget-based multilayer scheme for clean glaciers, a single-layer scheme for debris-covered glaciers and multilayer scheme for seasonal snow over glacier, soil and forest are developed within a distributed biosphere hydrological modeling framework (WEB-DHM-S model). Discharge simulations using this model show good agreement with observations for Hunza River Basin (13,733 km2) in the Karakoram region of Pakistan for three hydrologic years (2002-2004). Flow composition analysis reveals that the runoff regime is strongly controlled by the snow and glacier melt runoff (50% snowmelt and 33% glacier melt) and suggests that both topography and glacier hypsometry play key roles in glacier mass balance. This study provides a basis for potential application of such an integrated model to the entire Hindu-Kush-Karakoram-Himalaya region.

Development and verification of a new wind speed forecasting system using an ensemble Kalman filter data assimilation technique in a fully coupled hydrologic and atmospheric model

NASA Astrophysics Data System (ADS)

Williams, John L.; Maxwell, Reed M.; Monache, Luca Delle

2013-12-01

Wind power is rapidly gaining prominence as a major source of renewable energy. Harnessing this promising energy source is challenging because of the chaotic nature of wind and its inherently intermittent nature. Accurate forecasting tools are critical to support the integration of wind energy into power grids and to maximize its impact on renewable energy portfolios. We have adapted the Data Assimilation Research Testbed (DART), a community software facility which includes the ensemble Kalman filter (EnKF) algorithm, to expand our capability to use observational data to improve forecasts produced with a fully coupled hydrologic and atmospheric modeling system, the ParFlow (PF) hydrologic model and the Weather Research and Forecasting (WRF) mesoscale atmospheric model, coupled via mass and energy fluxes across the land surface, and resulting in the PF.WRF model. Numerous studies have shown that soil moisture distribution and land surface vegetative processes profoundly influence atmospheric boundary layer development and weather processes on local and regional scales. We have used the PF.WRF model to explore the connections between the land surface and the atmosphere in terms of land surface energy flux partitioning and coupled variable fields including hydraulic conductivity, soil moisture, and wind speed and demonstrated that reductions in uncertainty in these coupled fields realized through assimilation of soil moisture observations propagate through the hydrologic and atmospheric system. The sensitivities found in this study will enable further studies to optimize observation strategies to maximize the utility of the PF.WRF-DART forecasting system.

Assessing the impact of future land use and land cover changes on climate over Brazilian semiarid

NASA Astrophysics Data System (ADS)

Cunha, A. M.; Alvalá, R. S.; Kubota, P. Y.; Vieira, R.

2013-12-01

The continental surface vegetal cover has been considerably changed by human activities, mainly through natural vegetation conversion in grasslands. Such changes in surface cover may impact the regional and global climates, through of the changes in biophysical processes and CO2 exchanges between vegetation and atmosphere. In recent decades, most of the Brazilian territory has been presenting transformation in the land use/cover spatial patterns. The typical vegetation of the Brazilian semiarid, known as caatinga (closed shrubland) had been replaced by pasture lands. Based on that, the main objective of this work was to investigate the impacts of future land cover and land use changes (LCLUC) on surface processes and on the climate of Brazilian semiarid region. Numerical experiments using the AGCM/CPTEC/IBIS were performed in order to investigate the impacts of LCLUC on the climate of Brazilian semiarid due to the replacement of natural vegetation by pasture and degraded areas. The climate impacts of LUCC were assessed using climate simulations considering two scenarios of vegetation distribution: i) Potential Vegetation (Control) and ii) Future scenario of the vegetation: maximum pasture limited by areas of desert and semidesert. These degraded areas were obtained from the future projection of the biome distribution in South America developed by Salazar Velasquez (2009) using CPTEC PVMReg and emission scenarios A2 of the Intergovernmental Panel on Climate Change (IPCC). In general, the simulation results showed that the LCLUC, due to the changes in relevant surface variables, has caused alterations in local and neighborhood regions climate. The LCLUC leads to a decrease in mean rainfall during dry season at study area. A meridional dipole pattern with near surface temperature increase (reduction) in the northern (southern) areas of semiarid was found. The results also highlight that LUCC led to changes in the components of the surface energy and carbon balance. These results suggest that LCLUC, even on a small scale in Brazil's semiarid region, can cause climate impacts, in local and regional scale. Finally, we highlight that the diagnosis of the evolution of LUCC and its climatic implications are essential to guide policy makers in regard to resources application and on policies development, in order to achieve a better management and planning for this important region of the country.

Land Surface Microwave Emissivity Dynamics: Observations, Analysis and Modeling

NASA Technical Reports Server (NTRS)

Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Kumar, Sujay; Ringerud, Sarah

2014-01-01

Land surface microwave emissivity affects remote sensing of both the atmosphere and the land surface. The dynamical behavior of microwave emissivity over a very diverse sample of land surface types is studied. With seven years of satellite measurements from AMSR-E, we identified various dynamical regimes of the land surface emission. In addition, we used two radiative transfer models (RTMs), the Community Radiative Transfer Model (CRTM) and the Community Microwave Emission Modeling Platform (CMEM), to simulate land surface emissivity dynamics. With both CRTM and CMEM coupled to NASA's Land Information System, global-scale land surface microwave emissivities were simulated for five years, and evaluated against AMSR-E observations. It is found that both models have successes and failures over various types of land surfaces. Among them, the desert shows the most consistent underestimates (by approx. 70-80%), due to limitations of the physical models used, and requires a revision in both systems. Other snow-free surface types exhibit various degrees of success and it is expected that parameter tuning can improve their performances.

Application of computer processed multispectral data to the discrimination of land collapse (sinkhole) prone areas in Florida

NASA Technical Reports Server (NTRS)

Coker, A. E.; Marshall, R.; Thomson, N. S.

1977-01-01

Data were collected near Bartow, Florida, for the purpose of studying land collapse phenomena using remote sensing techniques. Data obtained using the multispectral scanner system consisted of various combinations of 18 spectral bands ranging from 0.4-14.0 microns and several types of photography. The multispectral data were processed on a special-purpose analog computer in order to detect moisture-stressed vegetation and to enhance terrain surface temperatures. The processed results were printed on film to show the patterns of distribution of the proposed hydrogeologic indicators.

Identifying the fingerprints of the anthropogenic component of land use/land cover changes on regional climate of the USA high plains

NASA Astrophysics Data System (ADS)

Mutiibwa, D.; Irmak, S.

2011-12-01

The majority of recent climate change studies have largely focused on detection and attribution of anthropogenic forcings of greenhouse gases, aerosols, stratospheric and tropospheric ozone. However, there is growing evidence that land cover/land use (LULC) change can significantly impact atmospheric processes from local to regional weather and climate variability. Human activities such as conversion of natural ecosystem to croplands and urban-centers, deforestation and afforestation impact biophysical properties of the land surfaces including albedo, energy balance, moisture-holding capacity of soil, and surface roughness. Alterations in these properties affect the heat and moisture exchanges between the land surface and atmospheric boundary layer, and ultimately impact the climate system. The challenge is to demonstrate that LULC changes produce a signal that can be discerned from natural climate noise. In this study, we attempt to detect the signature of anthropogenic forcing of LULC change on climate on regional scale. The signal projector investigated for detecting the signature of LULC changes on regional climate of the High Plains of the USA is the Normalized Difference Vegetation Index (NDVI). NDVI is an indicator that captures short and long-term geographical distribution of vegetation surfaces. The study develops an enhanced signal processing procedure to maximize the signal to noise ratio by introducing a pre-filtering technique of ARMA processes on the investigated climate and signal variables, before applying the optimal fingerprinting technique to detect the signals of LULC changes on observed climate, temperature, in the High Plains. The intent is to filter out as much noise as possible while still retaining the essential features of the signal by making use of the known characteristics of the noise and the anticipated signal. The study discusses the approach of identifying and suppressing the autocorrelation in optimal fingerprint analysis by applying linear transformation of ARMA processes to the analysis variables. With the assumption that natural climate variability is a near stationary process, the pre-filters are developed to generate stationary residuals. The High Plains region although impacted by droughts over the last three decades has had an increase in agricultural lands, both irrigated and non-irrigated. The study shows that for the most part of the High Plains region there is significant influence of evaporative cooling on regional climate during the summer months. As the vegetation coverage increases coupled with increased in irrigation application, the regional daytime surface energy in summer is increasingly redistributed into latent heat flux which increases the effect of evaporative cooling on summer temperatures. We included the anthropogenic forcing of CO2 on regional climate with the main purpose of surpassing the radiative heating effect of greenhouse gases from natural climate noise, to enhance the LULC signal-to-noise ratio. The warming signal due to greenhouse gas forcing is observed to be weakest in the central part of the High Plains. The results showed that the CO2 signal in the region was weak or is being surpassed by the evaporative cooling effect.

Hydrologic connections between environmental and societal change at the Bonneville Salt Flats, Utah

NASA Astrophysics Data System (ADS)

Bowen, B. B.; Harman, C. J.; Kipnis, E. L.; Liu, T.; Bernau, J. A.; Horel, J.

2017-12-01

The Bonneville Salt Flats (BSF) is an ephemeral and valued salt pan in northwestern Utah where a century of land speed racing and potash mining have created a complex and intertwined social and hydrologic system. The character of BSF changes on daily, weekly, monthly, annual, and geologic time scales in response to fluctuations in water balance, solute flux, and groundwater flow which is impacted by both local meteorology and water management associated with potash mining. In addition, the texture of the salt surface is changed by land use including racing activities, which impacts water fluxes through the crust. Ongoing research is focused on characterizing physical changes in the BSF environment and attributing observed changes in the landscape to specific processes and drivers. Five years of field observations and sampling, analyses of satellite imagery dating back the 1980s, and geochemical analysis of surface brines have shown that spatiotemporal changes in surface water and fluctuations in the surface salt footprint are linked to both climate and land use. Climate data over the last 30 years are examined to identify annual patterns in surface water balance at BSF to identify annual and seasonal climate constraints on flooding, evaporation, and desiccation cycles. A new weather station installed in the Fall of 2016 in the middle of BSF allows for unprecedented analyses of halite surface dynamics. Spatiotemporally dispersed stable isotope analyses of BSF surface brine samples constrain brine sources and evolution. An understanding of the processes that change the surface composition and texture through time inform interpretation of subsurface saline deposits at BSF. The wide range of temporal and spatial scales of observation help to guide to best management practices of this iconic natural resource.

Comparing crop growth and carbon budgets simulated across AmeriFlux agricultural sites using the community land model (CLM)

USDA-ARS?s Scientific Manuscript database

Improving process-based crop models is needed to achieve high fidelity forecasts of regional energy, water, and carbon exchange. However, most state-of-the-art Land Surface Models (LSMs) assessed in the fifth phase of the Coupled Model Inter-comparison project (CMIP5) simulated crops as simple C3 or...

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.

Soft- and reactive landing of ions onto surfaces: Concepts and applications: CONCEPTS AND APPLICATIONS

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

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

2015-04-16

Soft- and reactive landing of mass-selected ions is gaining attention as a promising approach for the precisely-controlled preparation of materials on surfaces that are not amenable to deposition using conventional methods. A broad range of ionization sources and mass-filters are available that make ion soft-landing a versatile tool for surface modification using beams of hyperthermal (< 100 eV) ions. The ability to select the mass-to-charge ratio of the ion, its kinetic energy and charge state, along with precise control of the size, shape, and position of the ion beam on the deposition target distinguishes ion soft landing from other surfacemore » modification techniques. Soft- and reactive landing have been used to prepare interfaces for practical applications as well as precisely-defined model surfaces for fundamental investigations in chemistry, physics, and materials science. For instance, soft- and reactive landing have been applied to study the surface chemistry of ions isolated in the gas-phase, prepare arrays of proteins for high-throughput biological screening, produce novel carbon-based and polymer materials, enrich the secondary structure of peptides and the chirality of organic molecules, immobilize electrochemically-active proteins and organometallics on electrodes, create thin films of complex molecules, and immobilize catalytically active organometallics as well as ligated metal clusters. In addition, soft landing has enabled investigation of the size-dependent behavior of bare metal clusters in the critical subnanometer size regime where chemical and physical properties do not scale predictably with size. The morphology, aggregation, and immobilization of larger bare metal nanoparticles, which are directly relevant to the design of catalysts as well as improved memory and electronic devices, have also been studied using ion soft landing. This review article begins in section 1 with a brief introduction to the existing applications of ion soft- and reactive landing. Section 2 provides an overview of the ionization sources and mass filters that have been used to date for soft landing of mass-selected ions. A discussion of the competing processes that occur during ion deposition as well as the types of ions and surfaces that have been investigated follows in section 3. Section 4 discusses the physical phenomena that occur during and after ion soft landing including retention and reduction of ionic charge along with factors that impact the efficiency of ion deposition. The influence of soft landing on the secondary structure and biological activity of complex ions is addressed in section 5. Lastly, an overview of the structure and mobility as well as the catalytic, optical, magnetic, and redox properties of bare ionic clusters and nanoparticles deposited onto surfaces is presented in section 6.« less

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.

Global land-atmosphere coupling associated with cold climate processes

NASA Astrophysics Data System (ADS)

Dutra, Emanuel

This dissertation constitutes an assessment of the role of cold processes, associated with snow cover, in controlling the land-atmosphere coupling. The work was based on model simulations, including offline simulations with the land surface model HTESSEL, and coupled atmosphere simulations with the EC-EARTH climate model. A revised snow scheme was developed and tested in HTESSEL and EC-EARTH. The snow scheme is currently operational at the European Centre for Medium-Range Weather Forecasts integrated forecast system, and in the default configuration of EC-EARTH. The improved representation of the snowpack dynamics in HTESSEL resulted in improvements in the near surface temperature simulations of EC-EARTH. The new snow scheme development was complemented with the option of multi-layer version that showed its potential in modeling thick snowpacks. A key process was the snow thermal insulation that led to significant improvements of the surface water and energy balance components. Similar findings were observed when coupling the snow scheme to lake ice, where lake ice duration was significantly improved. An assessment on the snow cover sensitivity to horizontal resolution, parameterizations and atmospheric forcing within HTESSEL highlighted the role of the atmospheric forcing accuracy and snowpack parameterizations in detriment of horizontal resolution over flat regions. A set of experiments with and without free snow evolution was carried out with EC-EARTH to assess the impact of the interannual variability of snow cover on near surface and soil temperatures. It was found that snow cover interannual variability explained up to 60% of the total interannual variability of near surface temperature over snow covered regions. Although these findings are model dependent, the results showed consistency with previously published work. Furthermore, the detailed validation of the snow dynamics simulations in HTESSEL and EC-EARTH guarantees consistency of the results.

Assessing simulated summer 10-m wind speed over China: influencing processes and sensitivities to land surface schemes

NASA Astrophysics Data System (ADS)

Zeng, Xin-Min; Wang, Ming; Wang, Ning; Yi, Xiang; Chen, Chaohui; Zhou, Zugang; Wang, Guiling; Zheng, Yiqun

2018-06-01

We assessed the sensitivity of 10-m wind speed to land surface schemes (LSSs) and the processes affecting wind speed in China during the summer of 2003 using the ARWv3 mesoscale model. The derived hydrodynamic equation, which directly reflects the effects of the processes that drive changes in the full wind speed, shows that the convection term CON (the advection effect) plays the smallest role; thus, the summer 10-m wind speed is largely dominated by the pressure gradient (PRE) and the diffusion (DFN) terms, and the equation shows that both terms are highly sensitive to the choice of LSS within the studied subareas (i.e., Northwest China, East China, and the Tibetan Plateau). For example, Northwest China had the largest DFN, with a PRE four times that of CON and the highest sensitivity of PRE to the choice of LSS, as indicated by a difference index value of 63%. Moreover, we suggest that two types of mechanisms, direct and indirect effects, affect the 10-m wind speed. Through their simulated surface fluxes (mainly the sensible heat flux), the different LSSs directly provide different amounts of heat to the surface air at local scales, which influences atmospheric stratification and the characteristics of downward momentum transport. Meanwhile, through the indirect effect, the LSS-induced changes in surface fluxes can significantly modify the distributions of the temperature and pressure fields in the lower atmosphere over larger scales. These changes alter the thermal and geostrophic winds, respectively, as well as the 10-m wind speed. Due to the differences in land properties and climates, the indirect effect (e.g., PRE) can be greater than the direct effect (e.g., DFN).

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.

Regional-Scale Modeling at NASA Goddard Space Flight Center

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Adler, R.; Baker, D.; Braun, S.; Chou, M.-D.; Jasinski, M. F.; Jia, Y.; Kakar, R.; Karyampudi, M.; Lang, S.

2003-01-01

Over the past decade, the Goddard Mesoscale Modeling and Dynamics Group has used a popular regional scale model, MM5, to study precipitation processes. Our group is making contributions to the MM5 by incorporating the following physical and numerical packages: improved Goddard cloud processes, a land processes model (Parameterization for Land-Atmosphere-Cloud Exchange - PLACE), efficient but sophisticated radiative processes, conservation of hydrometeor mass (water budget), four-dimensional data assimilation for rainfall, and better computational methods for trace gas transport. At NASA Goddard, the MM5 has been used to study: (1) the impact of initial conditions, assimilation of satellite-derived rainfall, and cumulus parameterizations on rapidly intensifying oceanic cyclones, hurricanes and typhoons, (2) the dynamic and thermodynamic processes associated with the development of narrow cold frontal rainbands, (3) regional climate and water cycles, (4) the impact of vertical transport by clouds and lightning on trace gas distributiodproduction associated with South and North American mesoscale convective systems, (5) the development of a westerly wind burst (WWB) that occurred during the TOGA COARE and the diurnal variation of precipitation in the tropics, (6) a Florida sea breeze convective event and a Mid-US flood event using a sophisticated land surface model, (7) the influence of soil heterogeneity on land surface energy balance in the southwest GCIP region, (8) explicit simulations (with 1.33 to 4 km horizontal resolution) of hurricanes Bob (1991) and Bonnie (1998), (9) a heavy precipitation event over Taiwan, and (10) to make real time forecasts for a major NASA field program. In this paper, the modifications and simulated cases will be described and discussed.

Interplay between river dynamics and international borders: the Hirmand River between Iran and Afghanistan

NASA Astrophysics Data System (ADS)

Yousefi, Saleh; Keesstra, Saskia; Pourghasemi, Hamid Reza; Surian, Nicola; Mirzaee, Somayeh

2017-04-01

Fluvial dynamics in riverine borders can play an important role in political relationships between countries. Rivers move and evolve under the influence of natural processes and external drivers (e.g. land use change in river catchments). The Hirmand River is an important riverine border between Iran and Afghanistan. The present study shows the evolution and lateral shifting of the Hirmand River along the common international border (25.6 km) over a period of 6 decades (1955-2015). Seven data series of aerial photos, topographic maps and Landsat images were used to identify the land cover and morphological changes in the study reach. The land cover has changed dramatically on both sides of the border during the last 6 decades, especially in the Afghan part. Overall, 49% of all land surface changed its cover type, especially the area of agriculture and residential land contributed to that, with an increase in surface area of about 4931 ha and 561 ha, respectively. On the other hand, the natural cover and water bodies decreased to 38 % and 63 %, respectively. The impact of these land use changes on the morphological evolution of Hirmand River was investigated in 5 sub-reaches. We found an average decrease of the active channel width of 53% during 60 years and the average River Network Change Index for the whole study reach during 60 years was -1.25 m/yr. Deposition and narrowing turned out to be the main processes occurring within the study reach. Furthermore, due to natural riverine processes the Hirmand River has moved towards Afghanistan (37 m on average) and lateral shifting was found to be up to 1900 m in some sections.

A Study of Heavy Precipitation Events in Taiwan During 10-13 August, 1994. Part 2; Mesoscale Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei Kuo; Chen, C.-S.; Jia, Y.; Baker, D.; Lang, S.; Wetzel, P.; Lau, W. K.-M.

2001-01-01

Several heavy precipitation episodes occurred over Taiwan from August 10 to 13, 1994. Precipitation patterns and characteristics are quite different between the precipitation events that occurred from August 10 and I I and from August 12 and 13. In Part I (Chen et al. 2001), the environmental situation and precipitation characteristics are analyzed using the EC/TOGA data, ground-based radar data, surface rainfall patterns, surface wind data, and upper air soundings. In this study (Part II), the Penn State/NCAR Mesoscale Model (MM5) is used to study the precipitation characteristics of these heavy precipitation events. Various physical processes (schemes) developed at NASA Goddard Space Flight Center (i.e., cloud microphysics scheme, radiative transfer model, and land-soil-vegetation surface model) have recently implemented into the MM5. These physical packages are described in the paper, Two way interactive nested grids are used with horizontal resolutions of 45, 15 and 5 km. The model results indicated that Cloud physics, land surface and radiation processes generally do not change the location (horizontal distribution) of heavy precipitation. The Goddard 3-class ice scheme produced more rainfall than the 2-class scheme. The Goddard multi-broad-band radiative transfer model reduced precipitation compared to a one-broad band (emissivity) radiation model. The Goddard land-soil-vegetation surface model also reduce the rainfall compared to a simple surface model in which the surface temperature is computed from a Surface energy budget following the "force-re store" method. However, model runs including all Goddard physical processes enhanced precipitation significantly for both cases. The results from these runs are in better agreement with observations. Despite improved simulations using different physical schemes, there are still some deficiencies in the model simulations. Some potential problems are discussed. Sensitivity tests (removing either terrain or radiative processes) are performed to identify the physical processes that determine the precipitation patterns and characteristics for heavy rainfall events. These sensitivity tests indicated that terrain can play a major role in determining the exact location for both precipitation events. The terrain can also play a major role in determining the intensity of precipitation for both events. However, it has a large impact on one event but a smaller one on the other. The radiative processes are also important for determining, the precipitation patterns for one case but. not the other. The radiative processes can also effect the total rainfall for both cases to different extents.

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.

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.

Geomorphic Processes and Remote Sensing Signatures of Alluvial Fans in the Kun Lun Mountains, China

NASA Technical Reports Server (NTRS)

Farr, Tom G.; Chadwick, Oliver A.

1996-01-01

The timing of alluvial deposition in arid and semiarid areas is tied to land-surface instability caused by regional climate changes. The distribution pattern of dated deposits provides maps of regional land-surface response to past climate change. Sensitivity to differences in surface roughness and composition makes remote sensing techniques useful for regional mapping of alluvial deposits. Radar images from the Spaceborne Radar Laboratory and visible wavelength images from the French SPOT satellite were used to determine remote sensing signatures of alluvial fan units for an area in the Kun Lun Mountains of northwestern China. These data were combined with field observations to compare surface processes and their effects on remote sensing signatures in northwestern China and the southwestern United States. Geomorphic processes affecting alluvial fans in the two areas include aeolian deposition, desert varnish, and fluvial dissection. However, salt weathering is a much more important process in the Kun Lun than in the southwestern United States. This slows the formation of desert varnish and prevents desert pavement from forming. Thus the Kun Lun signatures are characteristic of the dominance of salt weathering, while signatures from the southwestern United States are characteristic of the dominance of desert varnish and pavement processes. Remote sensing signatures are consistent enough in these two regions to be used for mapping fan units over large areas.

Simulating land-atmosphere feedbacks and response to widespread forest disturbance: The role of lower boundary configuration and dynamic water table in meteorological modeling

NASA Astrophysics Data System (ADS)

Forrester, M.; Maxwell, R. M.; Bearup, L. A.; Gochis, D.

2017-12-01

Numerical meteorological models are frequently used to diagnose land-atmosphere interactions and predict large-scale response to extreme or hazardous events, including widespread land disturbance or perturbations to near-surface moisture. However, few atmospheric modeling platforms consider the impact that dynamic groundwater storage, specifically 3D subsurface flow, has on land-atmosphere interactions. In this study, we use the Weather Research and Forecasting (WRF) mesoscale meteorological model to identify ecohydrologic and land-atmosphere feedbacks to disturbance by the mountain pine beetle (MPB) over the Colorado Headwaters region. Disturbance simulations are applied to WRF with various lower boundary configurations: Including default Noah land surface model soil moisture representation; a version of WRF coupled to ParFlow (PF), an integrated groundwater-surface water model that resolves variably saturated flow in the subsurface; and WRF coupled to PF in a static water table version, simulating only vertical and no lateral subsurface flow. Our results agree with previous literature showing MPB-induced reductions in canopy transpiration in all lower boundary scenarios, as well as energy repartitioning, higher water tables, and higher planetary boundary layer over infested regions. Simulations show that expanding from local to watershed scale results in significant damping of MPB signal as unforested and unimpacted regions are added; and, while deforestation appears to have secondary feedbacks to planetary boundary layer and convection, these slight perturbations to cumulative summer precipitation are insignificant in the context of ensemble methodologies. Notably, the results suggest that groundwater representation in atmospheric modeling affects the response intensity of a land disturbance event. In the WRF-PF case, energy and atmospheric processes are more sensitive to disturbance in regions with higher water tables. Also, when dynamic subsurface hydrology is removed, WRF simulates a greater response to MPB at the land-atmosphere interface, including greater changes to daytime skin temperature, Bowen ratio and near-surface humidity. These findings highlight lower boundary representations in computational meteorology and numerical land-atmosphere modeling.

Towards a better understanding of flood generation and surface water inundation mechanisms using NASA remote sensing data products

NASA Astrophysics Data System (ADS)

Lucey, J.; Reager, J. T., II; Lopez, S. R.

2017-12-01

Floods annually cause several weather-related fatalities and financial losses. According to NOAA and FEMA, there were 43 deaths and 18 billion dollars paid out in flood insurance policies during 2005. The goal of this work is to improve flood prediction and flood risk assessment by creating a general model of predictability of extreme runoff generation using various NASA products. Using satellite-based flood inundation observations, we can relate surface water formation processes to changes in other hydrological variables, such as precipitation, storage and soil moisture, and understand how runoff generation response to these forcings is modulated by local topography and land cover. Since it is known that a flood event would cause an abnormal increase in surface water, we examine these underlying physical relationships in comparison with the Dartmouth Flood Observatory archive of historic flood events globally. Using ground water storage observations (GRACE), precipitation (TRMM or GPCP), land use (MODIS), elevation (SRTM) and surface inundation levels (SWAMPS), an assessment of geological and climate conditions can be performed for any location around the world. This project utilizes multiple linear regression analysis evaluating the relationship between surface water inundation, total water storage anomalies and precipitation values, grouped by average slope or land use, to determine their statistical relationships and influences on inundation data. This research demonstrates the potential benefits of using global data products for early flood prediction and will improve our understanding of runoff generation processes.

Assimilation of Satellite-Derived Precipitation into the Regional Atmospheric Model System (RAMS): Its Impacts on the Weather and Hydrology in the Southwest United States

NASA Astrophysics Data System (ADS)

Yi, H.; Gao, X.; Sorooshian, S.

2002-05-01

As one aspect of the study of interactions between the atmosphere, vegetation, soil, and hydrology, there has been on going efforts to assimilate soil moisture data using coupled and uncoupled land surface-atmosphere hydrology models. The assimilation of soil moisture is expected to have influence due to its vital function in regulating runoff, partitioning latent and sensible heat, and through determining groundwater recharge. Soil moisture can provides long-term memory or persistence of the surface boundary condition, influencing large-scale atmospheric circulation over subsequent intervals. Now that the application of satellite remote sensing has become obvious to provide input parameters associated with land surface processes to the numerical models, this study utilizes remotely sensed precipitation data, PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) to assimilate soil moisture and other soil surface characteristics. Compared to the other earlier modeling experiments of seasonal or interannual temporal scale in continental or global spatial scale, this study investigates short term predictability in regional scale with the southwest United States as a study area, which has unique metrological and geographical features that provide special difficulties for mesoscale modeling. Research objectives are to assimilate the PERSIANN precipitation data into the mesoscale model for model initialization, examine the influence and memory of model precipitation errors on the land surface and atmospheric processes, and thereby study the short term predictability of meteorology and hydrology in the Southwest United States.

Impact of Land Model Depth on Long Term Climate Variability and Change.

NASA Astrophysics Data System (ADS)

Gonzalez-Rouco, J. F.; García-Bustamante, E.; Hagemann, S.; Lorentz, S.; Jungclaus, J.; de Vrese, P.; Melo, C.; Navarro, J.; Steinert, N.

2017-12-01

The available evidence indicates that the simulation of subsurface thermodynamics in current General Circulation Models (GCMs) is not accurate enough due to the land-surface model imposing a zero heat flux boundary condition that is too close to the surface. Shallow land model components distort the amplitude and phase of the heat propagation in the subsurface with implications for energy storage and land-air interactions. Off line land surface model experiments forced with GCM climate change simulations and comparison with borehole temperature profiles indicate there is a large reduction of the energy storage of the soil using the typical shallow land models included in most GCMs. However, the impact of increasing the depth of the soil model in `on-line' GCM simulations of climate variability or climate change has not yet been systematically explored. The JSBACH land surface model has been used in stand alone mode, driven by outputs of the MPIESM to assess the impacts of progressively increasing the depth of the soil model. In a first stage, preindustrial control simulations are developed increasing the lower depth of the zero flux bottom boundary condition placed for temperature at the base of the fifth model layer (9.83 m) down to 294.6 m (layer 9), thus allowing for the bottom layers to reach equilibrium. Starting from piControl conditions, historical and scenario simulations have been performed since 1850 yr. The impact of increasing depths on the subsurface layer temperatures is analysed as well as the amounts of energy involved. This is done also considering permafrost processes (freezing and thawing). An evaluation on the influence of deepening the bottom boundary on the simulation of low frequency variability and temperature trends is provided.

Development of a modular streamflow model to quantify runoff contributions from different land uses in tropical urban environments using Genetic Programming

NASA Astrophysics Data System (ADS)

Meshgi, Ali; Schmitter, Petra; Chui, Ting Fong May; Babovic, Vladan

2015-06-01

The decrease of pervious areas during urbanization has severely altered the hydrological cycle, diminishing infiltration and therefore sub-surface flows during rainfall events, and further increasing peak discharges in urban drainage infrastructure. Designing appropriate waster sensitive infrastructure that reduces peak discharges requires a better understanding of land use specific contributions towards surface and sub-surface processes. However, to date, such understanding in tropical urban environments is still limited. On the other hand, the rainfall-runoff process in tropical urban systems experiences a high degree of non-linearity and heterogeneity. Therefore, this study used Genetic Programming to establish a physically interpretable modular model consisting of two sub-models: (i) a baseflow module and (ii) a quick flow module to simulate the two hydrograph flow components. The relationship between the input variables in the model (i.e. meteorological data and catchment initial conditions) and its overall structure can be explained in terms of catchment hydrological processes. Therefore, the model is a partial greying of what is often a black-box approach in catchment modelling. The model was further generalized to the sub-catchments of the main catchment, extending the potential for more widespread applications. Subsequently, this study used the modular model to predict both flow components of events as well as time series, and applied optimization techniques to estimate the contributions of various land uses (i.e. impervious, steep grassland, grassland on mild slope, mixed grasses and trees and relatively natural vegetation) towards baseflow and quickflow in tropical urban systems. The sub-catchment containing the highest portion of impervious surfaces (40% of the area) contributed the least towards the baseflow (6.3%) while the sub-catchment covered with 87% of relatively natural vegetation contributed the most (34.9%). The results from the quickflow module revealed average runoff coefficients between 0.12 and 0.80 for the various land uses and decreased from impervious (0.80), grass on steep slopes (0.56), grass on mild slopes (0.48), mixed grasses and trees (0.42) to relatively natural vegetation (0.12). The established modular model, reflecting the driving hydrological processes, enables the quantification of land use specific contributions towards the baseflow and quickflow components. This quantification facilitates the integration of water sensitive urban infrastructure for the sustainable development of water in tropical megacities.

Land Use and Land Cover (LULC) Change Detection in Islamabad and its Comparison with Capital Development Authority (CDA) 2006 Master Plan

NASA Astrophysics Data System (ADS)

Hasaan, Zahra

2016-07-01

Remote sensing is very useful for the production of land use and land cover statistics which can be beneficial to determine the distribution of land uses. Using remote sensing techniques to develop land use classification mapping is a convenient and detailed way to improve the selection of areas designed to agricultural, urban and/or industrial areas of a region. In Islamabad city and surrounding the land use has been changing, every day new developments (urban, industrial, commercial and agricultural) are emerging leading to decrease in vegetation cover. The purpose of this work was to develop the land use of Islamabad and its surrounding area that is an important natural resource. For this work the eCognition Developer 64 computer software was used to develop a land use classification using SPOT 5 image of year 2012. For image processing object-based classification technique was used and important land use features i.e. Vegetation cover, barren land, impervious surface, built up area and water bodies were extracted on the basis of object variation and compared the results with the CDA Master Plan. The great increase was found in built-up area and impervious surface area. On the other hand vegetation cover and barren area followed a declining trend. Accuracy assessment of classification yielded 92% accuracies of the final land cover land use maps. In addition these improved land cover/land use maps which are produced by remote sensing technique of class definition, meet the growing need of legend standardization.

Constraining the Surface Energy Balance of Snow in Complex Terrain

NASA Astrophysics Data System (ADS)

Lapo, Karl E.

Physically-based snow models form the basis of our understanding of current and future water and energy cycles, especially in mountainous terrain. These models are poorly constrained and widely diverge from each other, demonstrating a poor understanding of the surface energy balance. This research aims to improve our understanding of the surface energy balance in regions of complex terrain by improving our confidence in existing observations and improving our knowledge of remotely sensed irradiances (Chapter 1), critically analyzing the representation of boundary layer physics within land models (Chapter 2), and utilizing relatively novel observations to in the diagnoses of model performance (Chapter 3). This research has improved the understanding of the literal and metaphorical boundary between the atmosphere and land surface. Solar irradiances are difficult to observe in regions of complex terrain, as observations are subject to harsh conditions not found in other environments. Quality control methods were developed to handle these unique conditions. These quality control methods facilitated an analysis of estimated solar irradiances over mountainous environments. Errors in the estimated solar irradiance are caused by misrepresenting the effect of clouds over regions of topography and regularly exceed the range of observational uncertainty (up to 80Wm -2) in all regions examined. Uncertainty in the solar irradiance estimates were especially pronounced when averaging over high-elevation basins, with monthly differences between estimates up to 80Wm-2. These findings can inform the selection of a method for estimating the solar irradiance and suggest several avenues of future research for improving existing methods. Further research probed the relationship between the land surface and atmosphere as it pertains to the stable boundary layers that commonly form over snow-covered surfaces. Stable conditions are difficult to represent, especially for low wind speed values and coupled land-atmosphere models have difficulty representing these processes. We developed a new method analyzing turbulent fluxes at the land surface that relies on using the observed surface temperature, which we called the offline turbulence method. We used this method to test a number of stability schemes as they are implemented within land models. Stability schemes can cause small biases in the simulated sensible heat flux, but these are caused by compensating errors, as no single method was able to accurately reproduce the observed distribution of the sensible heat flux. We described how these turbulence schemes perform within different turbulence regimes, particularly noting the difficulty representing turbulence during conditions with faster wind speeds and the transition between weak and strong wind turbulence regimes. Heterogeneity in the horizontal distribution of surface temperature associated with different land surface types likely explains some of the missing physics within land models and is manifested as counter-gradient fluxes in observations. The coupling of land and atmospheric models needs further attention, as we highlight processes that are missing. Expanding on the utility of surface temperature, Ts, in model evaluations, we demonstrated the utility of using surface temperature in snow models evaluations. Ts is the diagnostic variable of the modeled surface energy balance within physically-based models and is an ideal supplement to traditional evaluation techniques. We demonstrated how modeling decisions affect Ts, specifically testing the impact of vertical layer structure, thermal conductivity, and stability corrections in addition to the effect of uncertainty in forcing data on simulated Ts. The internal modeling decisions had minimal impacts relative to uncertainty in the forcing data. Uncertainty in downwelling longwave was found to have the largest impact on simulated Ts. Using Ts, we demonstrated how various errors in the forcing data can be identified, noting that uncertainty in downwelling longwave and wind are the easiest to identify due to their effect on night time minimum Ts.

Modeling surface energy fluxes from a patchwork of fields with different soils and crops

NASA Astrophysics Data System (ADS)

Klein, Christian; Thieme, Christoph; Heinlein, Florian; Priesack, Eckart

2017-04-01

Agroecosystems are a dominant terrestrial land-use on planet earth and cover about 36% of the ice-free surface (12% pasture, 26% agriculture) [Foley2011]. Within this land use type, management practices vary strongly due to climate, cultural preferences, degree of industrialization, soil properties, crop rotations, field sizes, degree of land use sustainability, water availability, sowing and harvest dates, tillage, etc. These management practices influence abiotic environmental factors like water flow and heat transport within the ecosystem leading to changes of land surface fluxes. The relevance of vegetation (e.g. crops), ground cover, and soil properties to the moisture and energy exchanges between the land surface and the atmosphere is well known [McPherson 2007], but the impact of vegetation growth dynamics on energy fluxes is only partly understood [Gayler et al. 2014]. Thus, the structure of turbulence and the albedo evolve during the cropping period and large variations of heat can be measured on the field scale [Aubinet2012]. One issue of local distributed mixture of different land use is the measurement process which makes it challenging to evaluate simulations. Unfortunately, for meteorological flux-measurements like the Flux-Gradient or the Eddy Covariance (EC) method, comparability with simulations only exists in the ideal case, where fields have to be completely uniform in land use and flat within the reach of the footprint. Then a model with one specific land use would have the same underlying source area as the measurement. An elegant method to avoid the shortcoming of grid cell resolution is the so called mixed approach, which was recently implemented into the ecosystem model framework Expert-N [Biernath et al. 2013]. The aim of this study was to analyze the impact of the characteristics of five managed field plots, planted with winter wheat, potato and maize on the near surface soil moistures and on the near surface energy flux exchanges of the soil-plant-atmosphere interface. The simulated energy fluxes were compared with eddy flux tower measurements between the respective fields at the research farm Scheyern, North-West of Munich, Germany. These simulations were done by coupling the ecosystem model Expert-N to an analytical footprint model [Mauder & Foken 2011] . The coupled model system has the ability to calculate the mixing ratio of the surface energy fluxes at the flux tower position. The approach accounts for the temporarily and spatially changing contributions of the patchwork of environmental land surface conditions (land use, management, soil properties) which influence the energy flux tower measurements due to the footprint dynamics. The statistical evaluation between simulation and measurements showed that the mixed approach improved the comparability in most cases. Furthermore, the management impact on single patches can be clearly detected, both in the measurements and the simulation. We conclude that reasonable simulations of energy and matter fluxes can be obtained if the heterogeneity of the land surfaces is taken into account.

The Land Use Model Intercomparison Project (LUMIP) Contribution to CMIP6: Rationale and Experimental Design

NASA Astrophysics Data System (ADS)

Lawrence, D. M.; Hurtt, G. C.; Arneth, A.; Brovkin, V.; Calvin, K. V.; Jones, A. D.; Jones, C.; Lawrence, P.; De Noblet-Ducoudré, N.; Pongratz, J.; Seneviratne, S. I.; Shevliakova, E.

2016-12-01

Human land-use activities have resulted in large changes to the Earth surface, with resulting implications for climate. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the questions: (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy and (3) Are there regional land-management strategies with promise to help mitigate against climate change? LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. Foci will include separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land-use, the unique impacts of land-cover change versus land management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent that CO2 fertilization is modulated by past and future land use. LUMIP involves three sets of activities: (1) development of an updated and expanded historical and future land-use dataset, (2) an experimental protocol for LUMIP experiments, and (3) definition of metrics that quantify model performance with respect to LULCC. LUMIP experiments are designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate. LUMIP also includes simulations that allow quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. We will present the experimental protocol in detail, explain the rationale, outlines plans for analysis, and describe a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types).

Using SMAP to identify structural errors in hydrologic models

NASA Astrophysics Data System (ADS)

Crow, W. T.; Reichle, R. H.; Chen, F.; Xia, Y.; Liu, Q.

2017-12-01

Despite decades of effort, and the development of progressively more complex models, there continues to be underlying uncertainty regarding the representation of basic water and energy balance processes in land surface models. Soil moisture occupies a central conceptual position between atmosphere forcing of the land surface and resulting surface water fluxes. As such, direct observations of soil moisture are potentially of great value for identifying and correcting fundamental structural problems affecting these models. However, to date, this potential has not yet been realized using satellite-based retrieval products. Using soil moisture data sets produced by the NASA Soil Moisture Active/Passive mission, this presentation will explore the use of the remotely-sensed soil moisture data products as a constraint to reject certain types of surface runoff parameterizations within a land surface model. Results will demonstrate that the precision of the SMAP Level 4 Surface and Root-Zone soil moisture product allows for the robust sampling of correlation statistics describing the true strength of the relationship between pre-storm soil moisture and subsequent storm-scale runoff efficiency (i.e., total storm flow divided by total rainfall both in units of depth). For a set of 16 basins located in the South-Central United States, we will use these sampled correlations to demonstrate that so-called "infiltration-excess" runoff parameterizations under predict the importance of pre-storm soil moisture for determining storm-scale runoff efficiency. To conclude, we will discuss prospects for leveraging this insight to improve short-term hydrologic forecasting and additional avenues for SMAP soil moisture products to provide process-level insight for hydrologic modelers.

Application of LANDSAT-2 data to the implementation and enforcement of the Pennsylvania Surface Mining Conservation and Reclamation Act

NASA Technical Reports Server (NTRS)

Russell, O. R. (Principal Investigator); Nichols, D. A.; Anderson, R.

1977-01-01

The author has identified the following significant results. Evaluation of LANDSAT imagery indicates severe limitations in its utility for surface mine land studies. Image stripping resulting from unequal detector response on satellite degrades the image quality to the extent that images of scales larger than 1:125,000 are of limited value for manual interpretation. Computer processing of LANDSAT data to improve image quality is essential; the removal of scanline stripping and enhancement of mine land reflectance data combined with color composite printing permits useful photographic enlargements to approximately 1:60,000.

Himalayan Glacier Disasters: Changing Geomorphological Process Landscape, or a Changing Human Landscape?

NASA Astrophysics Data System (ADS)

Kargel, J. S.; Leonard, G. J.

2012-12-01

Recent deadly glacier-related disasters in the Himalayan-Karakoram region—the Attabad landslide and formation of glacier meltwater-fed Lake Gojal, the Gayari ice avalanche/landslide and burial of a Pakistani Army base, and the Seti River outburst disaster—beg the question of whether disasters may be on the rise. Science is not yet ready to offer a full answer, but it is an important one to resolve, because future land-use planning and mitigative measures may be affected. Natural disasters have been commonplace throughout the long human history of the Himalaya-Karakoram region. The broad outlines of the changing natural process, natural hazard, and risk environment may be established. The risk is rising rapidly primarily due to increased human presence in these once-forbidding mountains. Risk is shifting also because climate change is modifying the land surface process system. Rapidly changing glaciers cause a destabilization of the landscape. Glaciers are fundamentally a mestastable phenomenon put in motion by the high gravitational potential energies of the components of glacial systems: snow, ice, water, and debris. Any change in the climate-land-glacier system MUST result in a change in the land process system, with hazards and risks rising or falling or changing location or type. Most commonly, glacier-related disasters include a natural process cascade; as the factors affecting land surface processes and the frequency or magnitude of any one of the elements of the process cascade changes, the net hazard and risk to people changes. Otherwise similar glaciers and glacierized basins have differing sets of hazardous conditions and processes depending on whether the glacier is stable, advancing or retreating. The consequences for the overall risk to people will depend on the details of a specific glacier near a particular village or bridge or railroad. One size does not fit all. Generalizations about trends in natural hazards as related to climate change impacts on glaciers are possible, but any particular locality may buck the general trends. Hence, climate change is affecting the natural process, natural hazard, and human risk environment. However, changing glaciers exhibit a montage of different response behaviors, so the natural hazards and shifting hazards are also a montage. Overwhelmingly, changing land use has the largest impact on the natural hazard and risk environment. We will take recent examples of natural disasters--using both remote sensing data and field data-- and discuss how changing climate, the changing cryosphere, and changing human relationships to the land in Himalayan realms may have contributed to or altered those events.

A novel assessment of the role of land-use and land-cover change in the global carbon cycle, using a new Dynamic Global Vegetation Model version of the CABLE land surface model

NASA Astrophysics Data System (ADS)

Haverd, Vanessa; Smith, Benjamin; Nieradzik, Lars; Briggs, Peter; Canadell, Josep

2017-04-01

In recent decades, terrestrial ecosystems have sequestered around 1.2 PgC y-1, an amount equivalent to 20% of fossil-fuel emissions. This land carbon flux is the net result of the impact of changing climate and CO2 on ecosystem productivity (CO2-climate driven land sink ) and deforestation, harvest and secondary forest regrowth (the land-use change (LUC) flux). The future trajectory of the land carbon flux is highly dependent upon the contributions of these processes to the net flux. However their contributions are highly uncertain, in part because the CO2-climate driven land sink and LUC components are often estimated independently, when in fact they are coupled. We provide a novel assessment of global land carbon fluxes (1800-2015) that integrates land-use effects with the effects of changing climate and CO2 on ecosystem productivity. For this, we use a new land-use enabled Dynamic Global Vegetation Model (DGVM) version of the CABLE land surface model, suitable for use in attributing changes in terrestrial carbon balance, and in predicting changes in vegetation cover and associated effects on land-atmosphere exchange. In this model, land-use-change is driven by prescribed gross land-use transitions and harvest areas, which are converted to changes in land-use area and transfer of carbon between pools (soil, litter, biomass, harvested wood products and cleared wood pools). A novel aspect is the treatment of secondary woody vegetation via the coupling between the land-use module and the POP (Populations Order Physiology) module for woody demography and disturbance-mediated landscape heterogeneity. Land-use transitions to and from secondary forest tiles modify the patch age distribution within secondary-vegetated tiles, in turn affecting biomass accumulation and turnover rates and hence the magnitude of the secondary forest sink. The resulting secondary forest patch age distribution also influences the magnitude of the secondary forest harvest and clearance fluxes, with oldest patches (high biomass) being preferentially harvested, and youngest patches (low biomass) being preferentially cleared. Our results, which agree well with the net land flux derived from the global carbon budget, are used for a process-attribution of the land carbon sink. Use of multiple constraints provides confidence in our process-attribution: we use observation-based data sets to evaluate predictions of global spatial distributions of vegetation cover, evaporation, gross primary production, biomass and soil carbon; interannual variability of the global terrestrial carbon sink; forest allometric relations and age-effects on net primary production.

Micro-topographic hydrologic variability due to vegetation acclimation under climate change

NASA Astrophysics Data System (ADS)

Le, P. V.; Kumar, P.

2012-12-01

Land surface micro-topography and vegetation cover have fundamental effects on the land-atmosphere interactions. The altered temperature and precipitation variability associated with climate change will affect the water and energy processes both directly and that mediated through vegetation. Since climate change induces vegetation acclimation that leads to shifts in evapotranspiration and heat fluxes, it further modifies microclimate and near-surface hydrological processes. In this study, we investigate the impacts of vegetation acclimation to climate change on micro-topographic hydrologic variability. The ability to accurately predict these impacts requires the simultaneous considerations of biochemical, ecophysiological and hydrological processes. A multilayer canopy-root-soil system model coupled with a conjunctive surface-subsurface flow model is used to capture the acclimatory responses and analyze the changes in dynamics of structure and connectivity of micro-topographic storage and in magnitudes of runoff. The study is performed using Light Detection and Ranging (LiDAR) topographic data in the Birds Point-New Madrid floodway in Missouri, U.S.A. The result indicates that both climate change and its associated vegetation acclimation play critical roles in altering the micro-topographic hydrological responses.

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).

Sustainable land cover and terrain modification to enhance convection and precipitation in the arid region of the United Arab Emirates

NASA Astrophysics Data System (ADS)

Wulfmeyer, V.; Branch, O.; Adebabseh, A.; Temimi, M.

2017-12-01

Irrigated plantations and modified terrain can provide a sustainable means of enhancing convective rainfall in arid regions like the United Arab Emirates, or UAE, and can be used to aid ongoing cloud seeding operations through the geographic-localization of seedable cloud formation. The first method, the planting of vast irrigated plantations of hardy desert shrubs, can lead to wind convergence and vertical mixing through increased roughness and modified radiative balances. When upper-air atmospheric instability is present, these phenomena can initiate convection. The second method, increasing the elevation of moderate-sized mountains, is based on the correlation between elevation and the number of summertime convection initiation events observed in the mountains of the UAE and Oman. This augmentation of existing orographic features should therefore increase the likelihood and geographic range of convection initiation events. High-resolution simulations provide a powerful means of assessing the likely impacts of land surface modifications. Previous convection-permitting simulations have yielded some evidential support for these hypotheses, but higher resolutions down to 1 km provide more detail regarding convective processes and land surface representation. Using seasonal simulations with the WRF-NOAHMP land-atmosphere model at a 2.5 km resolution, we identify frequent zones of convergence and atmospheric instability in the UAE and select interesting cases. Using these results, as well as an agricultural feasibility study, we identify optimal plantation positions within the UAE. We then run realistic plantation scenarios for single case studies at 1 km resolution. Using the same cases, we simulate the impact of augmenting mountain elevations on convective processes, with the augmentation being achieved through GIS-based modification of the terrain data. For both methods, we assess the impacts quantitatively and qualitatively, and assess key processes and dependencies. If we can demonstrate that convective rainfall would be enhanced through feasible agricultural and engineering methods, then land surface-based weather modification deserves serious consideration as a solution for water scarcity and anthropogenic climate change.

Gray Wave of the Great Transformation: A Satellite View of Urbanization, Climate Change, and Food Security

NASA Technical Reports Server (NTRS)

Imhoff, Marc Lee; Kamiell, Arnon Menahem

2010-01-01

Land cover change driven by human activity is profoundly affecting Earth's natural systems with impacts ranging from a loss of biological diversity to changes in regional and global climate. This change has been so pervasive and progressed so rapidly, compared to natural processes, scientists refer to it as "the great transformation". Urbanization or the 'gray wave' of land transformation is being increasingly recognized as an important process in global climate change. A hallmark of our success as a species, large urban conglomerates do in fact alter the land surface so profoundly that both local climate and the basic ecology of the landscape are affected in ways that have consequences to human health and economic well-being. Fortunately we have incredible new tools for planning and developing urban places that are both enjoyable and sustainable. A suite of Earth observing satellites is making it possible to study the interactions between urbanization, biological processes, and weather and climate. Using these Earth Observatories we are learning how urban heat islands form and potentially ameliorate them, how urbanization can affect rainfall, pollution, and surface water recharge at the local level and climate and food security globally.

Retrieval of the Land Surface Reflectance for Landsat-8 and Sentinel-2 and its validation.

NASA Astrophysics Data System (ADS)

Roger, J. C.; Vermote, E.; Skakun, S.; Franch, B.; Holben, B. N.; Justice, C. O.

2017-12-01

The land surface reflectance is a fundamental climate data record at the basis of the derivation of other climate data records (Albedo, LAI/Fpar, Vegetation indices) and a key parameter in the understanding of the land-surface-climate processes. For 25 years, Vermote and al. develop atmospheric corrections methods to define a land surface reflectance product for various satellites (AVHRR, MODIS, VIIRS…). This presentation highlights the algorithms developed both for Landsant-8 and Sentinel-2. We also emphasize the validation of the "Land surface reflectance" satellite products, which is a very important step to be done. For that purpose, we compared the surface reflectance products to a reference determined by using the accurate radiative transfer code 6S and very detailed measurements of the atmosphere obtained over the AERONET network (which allows to test for a large range of aerosol characteristics); formers being important inputs for atmospheric corrections. However, the application of this method necessitates the definition of a very detailed protocol for the use of AERONET data especially as far as size distribution and absorption are concerned, so that alternative validation methods or protocols could be compared. We describe here the protocol we have been working on based on our experience with the AERONET data and its application to Landsat-8 and Sentinel-2). We also derive a detailed error budget in relation to this approach. For a mean loaded atmosphere, t550 less than 0.25, the maximum uncertainty is 0.0025 corresponding to a relative uncertainty (in the RED channels): U < 1% for rsurf > 0.10, and 1% < U <2% for 0.10 >rsurf > 0.04.

Impacts of regional land-grab on regional hydroclimate in southeastern Africa via modeling and remote sensing

NASA Astrophysics Data System (ADS)

Maksimowicz, M.; Masarik, M. T.; Brandt, J.; Flores, A. N.

2017-12-01

Land use/land cover (LULC) change directly impacts the partitioning of surface mass and energy fluxes. Regional-scale weather and climate are potentially altered by LULC if the resultant changes in partitioning of surface energy fluxes are significant enough to induce changes in the evolution of the planetary boundary layer and its interaction with the atmosphere above. Dynamics of land use, particularly those related to the social dimensions of the Earth System, are often simplified or not represented in regional land-atmosphere models or Earth System Models. This study explores the role of LULC change on a regional hydroclimate system, focusing on potential hydroclimate changes arising from timber harvesting due to a land grab boom in Mozambique. We also focus more narrowly at quantifying regional impacts on Gorongosa National Park, a nationally important economic and biodiversity resource in southeastern Africa. After nationalizing all land in 1975 after Mozambique gained independence, complex social processes, including an extended low intensity conflict civil war and economic hardships, led to an escalation of land use rights grants to foreign governments. Between 2004 and 2009, large tracts of land were requested for timber. Here we use existing tree cover loss datasets to more accurately represent land cover within a regional weather model. LULC in a region encompassing Gorongosa is updated at three instances between 2001 and 2014 using a tree cover loss dataset. We use these derived LULC datasets to inform lower boundary conditions in the Weather Research and Forecasting (WRF) model. To quantify potential hydrometeorological changes arising from land use change, we performed a factorial-like experiment by mixing input LULC maps and atmospheric forcing data from before, during, and after the land grab. Results suggest that the land grab has impacted microclimate parameters in a significant way via direct and indirect impacts on land-atmosphere interactions. Results of this study suggest that LULC change arising from regional social dynamics are a potentially understudied, yet important human process to capture in both regional reanalyses and climate change projections.

Land-Atmosphere Interactions in Cold Environments (LATICE): The role of Atmosphere - Biosphere - Cryosphere - Hydrosphere interactions in a changing climate

NASA Astrophysics Data System (ADS)

Burkhart, J. F.; Tallaksen, L. M.; Stordal, F.; Berntsen, T.; Westermann, S.; Kristjansson, J. E.; Etzelmuller, B.; Hagen, J. O.; Schuler, T.; Hamran, S. E.; Lande, T. S.; Bryn, A.

2015-12-01

Climate change is impacting the high latitudes more rapidly and significantly than any other region of the Earth because of feedback processes between the atmosphere and the underlying surface. A warmer climate has already led to thawing of permafrost, reducing snow cover and a longer growing season; changes, which in turn influence the atmospheric circulation and the hydrological cycle. Still, many studies rely on one-way coupling between the atmosphere and the land surface, thereby neglecting important interactions and feedbacks. The observation, understanding and prediction of such processes from local to regional and global scales, represent a major scientific challenge that requires multidisciplinary scientific effort. The successful integration of earth observations (remote and in-situ data) and model development requires a harmonized research effort between earth system scientists, modelers and the developers of technologies and sensors. LATICE, which is recognized as a priority research area by the Faculty of Mathematics and Natural Sciences at the University of Oslo, aims to advance the knowledge base concerning land atmosphere interactions and their role in controlling climate variability and climate change at high northern latitudes. The consortium consists of an interdisciplinary team of experts from the atmospheric and terrestrial (hydrosphere, cryosphere and biosphere) research groups, together with key expertise on earth observations and novel sensor technologies. LATICE addresses critical knowledge gaps in the current climate assessment capacity through: Improving parameterizations of processes in earth system models controlling the interactions and feedbacks between the land (snow, ice, permafrost, soil and vegetation) and the atmosphere at high latitudes, including the boreal, alpine and artic zone. Assessing the influence of climate and land cover changes on water and energy fluxes. Integrating remote earth observations with in-situ data and suitable models to allow studies of finer-scale processes governing land-atmosphere interactions. Addressing observational challenges through the development of novel observational products and networks.

Biomarker Production and Preservation on Europa

NASA Astrophysics Data System (ADS)

Buffo, J.; Schmidt, B. E.

2017-12-01

Future landing site selection and sampling techniques for Europa will concentrate on locations of high potential biomarker preservation, however it is unclear what the best targets might be. On Europa, the scenario is quite unlike the depositional surface environments of terrestrial planets we've studied thus far-Europa's surface is passively communicating with putative habitable niches below that extend throughout the ice shell, ocean and sea floor. In this work, I approach biomarker production and preservation on Europa based by considering the many hypotheses that govern the its habitability, the processes that occur within the sea floor, ocean, and ice and exchange between them, and the geologic hypotheses for the formation of its various surfaces to establish, what journey through the planet a biomarker might take to arrive, if possible, at the surface where it is accessible to near-term landed missions. The goal of this project is to construct a simple model through which to consider the context for sampled material that will provide us with the ability to identify limitations in our intuition, understanding of the Europan system, our current hypotheses and data, and provide a road map for developing both areas for new research and identifying technology gaps that we must overcome before we can confidently select a landing site or analyze a sample from the near surface of Europa. I first consider the nature of the environment, i.e. at the sea floor interface, the ocean, or ocean-ice interface, in order to establish what the likely "biomarker" could be and then trace its path through the system: downwelling through the shell, mixing through the ocean, and pathways to the surface. Importantly, many models exist for the production of Europa's surface and subsurface geology that could affect the integrity of a putative biomarker. Often we modulate such considerations as a function of the time-scales over which the geologic process occurs, however such processes will also vary in transportation efficiency, and how any ice and water is incorporated into the ice shell. I will also comment on synergies between the upcoming JUICE and Europa Clipper missions, a putative landed mission, and how these missions could provide invaluable data that allows us to get beneath Europa's icy skin in relatively short order.

Quantifying the Terrestrial Surface Energy Fluxes Using Remotely-Sensed Satellite Data

NASA Astrophysics Data System (ADS)

Siemann, Amanda Lynn

The dynamics of the energy fluxes between the land surface and the atmosphere drive local and regional climate and are paramount to understand the past, present, and future changes in climate. Although global reanalysis datasets, land surface models (LSMs), and climate models estimate these fluxes by simulating the physical processes involved, they merely simulate our current understanding of these processes. Global estimates of the terrestrial, surface energy fluxes based on observations allow us to capture the dynamics of the full climate system. Remotely-sensed satellite data is the source of observations of the land surface which provide the widest spatial coverage. Although net radiation and latent heat flux global, terrestrial, surface estimates based on remotely-sensed satellite data have progressed, comparable sensible heat data products and ground heat flux products have not progressed at this scale. Our primary objective is quantifying and understanding the terrestrial energy fluxes at the Earth's surface using remotely-sensed satellite data with consistent development among all energy budget components [through the land surface temperature (LST) and input meteorology], including validation of these products against in-situ data, uncertainty assessments, and long-term trend analysis. The turbulent fluxes are constrained by the available energy using the Bowen ratio of the un-constrained products to ensure energy budget closure. All final products are within uncertainty ranges of literature values, globally. When validated against the in-situ estimates, the sensible heat flux estimates using the CFSR air temperature and constrained with the products using the MODIS albedo produce estimates closest to the FLUXNET in-situ observations. Poor performance over South America is consistent with the largest uncertainties in the energy budget. From 1984-2007, the longwave upward flux increase due to the LST increase drives the net radiation decrease, and the decrease in the available energy balances the decrease in the sensible heat flux. These datasets are useful for benchmarking climate models and LSM output at the global annual scale and the regional scale subject to the regional uncertainties and performance. Future work should improve the input data, particularly the temperature gradient and Zilitinkevich empirical constant, to reduce uncertainties.

Estimating changes to groundwater discharge temperature under altered climate conditions

NASA Astrophysics Data System (ADS)

Manga, M.; Burns, E. R.; Zhu, Y.; Zhan, H.; Williams, C. F.; Ingebritsen, S.; Dunham, J.

2017-12-01

Changes in groundwater temperature resulting from climate-driven boundary conditions (recharge and land surface temperature) can be evaluated using new analytical solutions of the groundwater heat transport equation. These steady-state solutions account for land-surface boundary conditions, hydrology, and geothermal and viscous heating, and can be used to identify the key physical processes that control thermal responses of groundwater-fed ecosystems to climate change, in particular (1) groundwater recharge rate and temperature and (2) land-surface temperature transmitted through the vadose zone. Also, existing transient solutions of conduction are compared with a new solution for advective transport of heat to estimate the timing of groundwater-discharge response to changes in recharge and land surface temperature. As an example, the new solutions are applied to the volcanic Medicine Lake highlands, California, USA, and associated Fall River Springs complexes that host groundwater-dependent ecosystems. In this system, high-elevation groundwater temperatures are strongly affected only by recharge conditions, but as the vadose zone thins away from the highlands, changes to the average annual land surface temperature will also influence groundwater temperatures. Transient response to temperature change depends on both the conductive timescale and the rate at which recharge delivers heat. Most of the thermal response of groundwater at high elevations will occur within 20 years of a shift in recharge temperatures, but the lower-elevation Fall River Springs will respond more slowly, with about half of the conductive response occurring within the first 20 years and about half of the advective response to higher recharge temperatures occurring in approximately 60 years.

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Department

NASA Technical Reports Server (NTRS)

Case. Jonathan; Mungai, John; Sakwa, Vincent; Kabuchanga, Eric; Zavodsky, Bradley T.; Limaye, Ashutosh S.

2014-01-01

Flooding and drought are two key forecasting challenges for the Kenya Meteorological Department (KMD). Atmospheric processes leading to excessive precipitation and/or prolonged drought can be quite sensitive to the state of the land surface, which interacts with the boundary layer of the atmosphere providing a source of heat and moisture. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface within weakly-sheared environments, such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in numerical weather prediction models. Enhanced regional modeling capabilities have the potential to improve forecast guidance in support of daily operations and high-end events over east Africa. KMD currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Nonhydrostatic Mesoscale Model (NMM) dynamical core. They make use of the National Oceanic and Atmospheric Administration / National Weather Service Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the WRF-NMM model runs on a 7-km regional grid over eastern Africa. Two organizations at the National Aeronautics and Space Administration Marshall Space Flight Center in Huntsville, AL, SERVIR and the Short-term Prediction Research and Transition (SPoRT) Center, have established a working partnership with KMD for enhancing its regional modeling capabilities. To accomplish this goal, SPoRT and SERVIR will provide experimental land surface initialization datasets and model verification capabilities to KMD. To produce a land-surface initialization more consistent with the resolution of the KMD-WRF runs, the NASA Land Information System (LIS) will be run at a comparable resolution to provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Additionally, real-time green vegetation fraction data from the Visible Infrared Imaging Radiometer Suite will be incorporated into the KMD-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service. Finally, model verification capabilities will be transitioned to KMD using the Model Evaluation Tools (MET) package, in order to quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. The transition of these MET tools will enable KMD to monitor model forecast accuracy in near real time. This presentation will highlight preliminary verification results of WRF runs over east Africa using the LIS land surface initialization.

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

NASA Astrophysics Data System (ADS)

Jiao, Yang; Lei, Huimin; Yang, Dawen; Huang, Maoyi; Liu, Dengfeng; Yuan, Xing

2017-08-01

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of eco-hydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965-1969) from -0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010-2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

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

Jiao, Yang; Lei, Huimin; Yang, Dawen

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of ecohydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of themore » Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965–1969) from 0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010–2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.« less

Principles in Remote Sensing of Aerosol from MODIS Over Land and Ocean

NASA Technical Reports Server (NTRS)

Remer, L. A.; Kaufman, Y. J.; Tanre, D.; Chu, D. A.

1999-01-01

The well-calibrated spectral radiances measured by MODIS will be processed to retrieve daily aerosol properties that include optical thickness and mass loading over land and optical thickness, the mean particle size of the dominant mode and the ratio between aerosol modes over ocean. In addition, after launch, aerosol single scattering albedo will be calculated as an experimental product. The retrieval process over land is based on a dark target method that identifies appropriate targets in the mid-IR channels and uses an empirical relationship found between the mid-ER and the visible channels to estimate surface reflectance in the visible from the mid-HZ reflectance measured by satellite. The method employs new aerosol models for industrial, smoke and dust aerosol. The process for retrieving aerosol over the ocean makes use of the wide spectral band from 0.55-2.13 microns and a look-up table constructed from combinations of five accumulation modes and five coarse modes. Both the over land and over ocean algorithms have been validated with satellite and airborne radiance measurements. We estimate that MODIS will be able to measure aerosol optical thickness (t) to within 0.05 +/- 0.2t over land and to within 0.05 +/- 0.05t over ocean. Much of the earth's surface is located far from aerosol sources and experience very low aerosol optical thickness. Will the accuracy expected from MODIS retrievals be sufficient to measure the global aerosol direct and indirect forcing? We are attempting to answer this question using global model results and cloud climatology.

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.

Using WEED to simulate the global wetland distribution in a ESM

NASA Astrophysics Data System (ADS)

Stacke, Tobias; Hagemann, Stefan

2016-04-01

Lakes and wetlands are an important land surface feature. In terms of hydrology, they regulate river discharge, mitigate flood events and constitute a significant surface water storage. Considering physical processes, they link the surface water and energy balances by altering the separation of incoming energy into sensible and latent heat fluxes. Finally, they impact biogeochemical processes and may act as carbon sinks or sources. Most global hydrology and climate models regard wetland extent and properties as constant in time. However, to study interactions between wetlands and different states of climate, it is necessary to implement surface water bodies (thereafter referred to as wetlands) with dynamical behavior into these models. Besides an improved representation of geophysical feedbacks between wetlands, land surface and atmosphere, a dynamical wetland scheme could also provide estimates of soil wetness as input for biogeochemical models, which are used to compute methane production in wetlands. Recently, a model for the representation of wetland extent dynamics (WEED) was developed as part of the hydrology model (MPI-HM) of the Max-Planck-Institute for Meteorology (MPI-M). The WEED scheme computes wetland extent in agreement with the range of observations for the high northern latitudes. It simulates a realistic seasonal cycle which shows sensitivity to northern snow-melt as well as rainy seasons in the tropics. Furthermore, flood peaks in river discharge are mitigated. However, the WEED scheme overestimates wetland extent in the Tropics which might be related to the MPI-HM's simplified potential evapotranspiration computation. In order to overcome this limitation, the WEED scheme is implemented into the MPI-M's land surface model JSBACH. Thus, not only its effect on water fluxes can be investigated but also its impact on the energy cycle, which is not included in the MPI-HM. Furthermore, it will be possible to analyze the physical effects of wetlands in a coupled land-atmosphere simulation. First simulations with JSBACH-WEED show results similar to the MPI-HM simulations. As the next step, the scheme is modified to account for energy cycle relevant issues such as the dynamical alteration of surface albedo as well as the allocation of appropriate thermal properties to the wetlands. In our presentation, we will give an overview on the functionality of the WEED scheme and the effect of wetlands in coupled land-atmosphere simulations.

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.

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.

Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS

PubMed Central

Wang, De-Cai; Zhang, Gan-Lin; Zhao, Ming-Song; Pan, Xian-Zhang; Zhao, Yu-Guo; Li, De-Cheng; Macmillan, Bob

2015-01-01

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data. PMID:26090852

Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS.

PubMed

Wang, De-Cai; Zhang, Gan-Lin; Zhao, Ming-Song; Pan, Xian-Zhang; Zhao, Yu-Guo; Li, De-Cheng; Macmillan, Bob

2015-01-01

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data.

Physically Accurate Soil Freeze-Thaw Processes in a Global Land Surface Scheme

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Haverd, Vanessa

2018-01-01

The model Soil-Litter-Iso (SLI) calculates coupled heat and water transport in soil. It was recently implemented into the Australian land surface model CABLE, which is the land component of the Australian Community Climate and Earth System Simulator (ACCESS). Here we extended SLI to include accurate freeze-thaw processes in the soil and snow. SLI provides thence an implicit solution of the energy and water balances of soil and snow as a standalone model and within CABLE. The enhanced SLI was tested extensively against theoretical formulations, laboratory experiments, field data, and satellite retrievals. The model performed well for all experiments at wide-ranging temporal and spatial scales. SLI melts snow faster at the end of the cold season compared to observations though because there is no subgrid variability within SLI given by the implicit, coupled solution of energy and water. Combined CABLE-SLI shows very realistic dynamics and extent of permafrost on the Northern hemisphere. It illustrated, however, also the limits of possible comparisons between large-scale land surface models and local permafrost observations. CABLE-SLI exhibits the same patterns of snow depth and snow water equivalent on the Northern hemisphere compared to satellite-derived observations but quantitative comparisons depend largely on the given meteorological input fields. Further extension of CABLE-SLI with depth-dependence of soil carbon will allow realistic projections of the development of permafrost and frozen carbon stocks in a changing climate.

A new MRI land surface model HAL

NASA Astrophysics Data System (ADS)

Hosaka, M.

2011-12-01

A land surface model HAL is newly developed for MRI-ESM1. It is used for the CMIP simulations. HAL consists of three submodels: SiByl (vegetation), SNOWA (snow) and SOILA (soil) in the current version. It also contains a land coupler LCUP which connects some submodels and an atmospheric model. The vegetation submodel SiByl has surface vegetation processes similar to JMA/SiB (Sato et al. 1987, Hirai et al. 2007). SiByl has 2 vegetation layers (canopy and grass) and calculates heat, moisture, and momentum fluxes between the land surface and the atmosphere. The snow submodel SNOWA can have any number of snow layers and the maximum value is set to 8 for the CMIP5 experiments. Temperature, SWE, density, grain size and the aerosol deposition contents of each layer are predicted. The snow properties including the grain size are predicted due to snow metamorphism processes (Niwano et al., 2011), and the snow albedo is diagnosed from the aerosol mixing ratio, the snow properties and the temperature (Aoki et al., 2011). The soil submodel SOILA can also have any number of soil layers, and is composed of 14 soil layers in the CMIP5 experiments. The temperature of each layer is predicted by solving heat conduction equations. The soil moisture is predicted by solving the Darcy equation, in which hydraulic conductivity depends on the soil moisture. The land coupler LCUP is designed to enable the complicated constructions of the submidels. HAL can include some competing submodels (precise and detailed ones, and simpler ones), and they can run at the same simulations. LCUP enables a 2-step model validation, in which we compare the results of the detailed submodels with the in-situ observation directly at the 1st step, and follows the comparison between them and those of the simpler ones at the 2nd step. When the performances of the detailed ones are good, we can improve the simpler ones by using the detailed ones as reference models.

30 CFR 769.13 - Contents of petitions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Contents of petitions. 769.13 Section 769.13 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR AREAS UNSUITABLE FOR MINING PETITION PROCESS FOR DESIGNATION OF FEDERAL LANDS AS UNSUITABLE FOR ALL OR CERTAIN TYPES OF SURFACE COAL MINING OPERATIONS...

Emerging ecological datasets with application for modeling North American dust emissions

NASA Astrophysics Data System (ADS)

McCord, S.; Stauffer, N. G.; Garman, S.; Webb, N.

2017-12-01

In 2011 the US Bureau of Land Management (BLM) established the Assessment, Inventory and Monitoring (AIM) program to monitor the condition of BLM land and to provide data to support evidence-based management of multi-use public lands. The monitoring program shares core data collection methods with the Natural Resources Conservation Service's (NRCS) National Resources Inventory (NRI), implemented on private lands nationally. Combined, the two programs have sampled >30,000 locations since 2003 to provide vegetation composition, vegetation canopy height, the size distribution of inter-canopy gaps, soil texture and crusting information on rangelands and pasture lands across North America. The BLM implements AIM on more than 247.3 million acres of land across the western US, encompassing major dust source regions of the Chihuahuan, Sonoran, Mojave and Great Basin deserts, the Colorado Plateau, and potential high-latitude dust sources in Alaska. The AIM data are publicly available and can be used to support modeling of land surface and boundary-layer processes, including dust emission. While understanding US dust source regions and emission processes has been of national interest since the 1930s Dust Bowl, most attention has been directed to the croplands of the Great Plains and emission hot spots like Owens Lake, California. The magnitude, spatial extent and temporal dynamics of dust emissions from western dust source areas remain highly uncertain. Here, we use ensemble modeling with empirical and physically-based dust emission schemes applied to AIM monitoring data to assess regional-scale patterns of aeolian sediment mass fluxes and dust emissions. The analysis enables connections to be made between dust emission rates at source and other indicators of ecosystem function at the landscape scale. Emerging ecological datasets like AIM provide new opportunities to evaluate aeolian sediment transport responses to land surface conditions, potential interactions with disturbances (e.g., fire) and ecological change (e.g., invasive species), and the impacts of anthropogenic land use and land cover change.

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.

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.

2011-01-01

The Land Information System (LIS; http://lis.gsfc.nasa.gov) is a flexible land surface modeling framework that has been developed 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. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected as a co-winner of NASA?s 2005 Software of the Year award.LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has e volved from two earlier efforts -- North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations.In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins". LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling be enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation, who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs.LIS has also recently been demonstrated for multi-model data assimilation using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature.Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation.Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems

Influence of high-latitude warming and land-use changes in the early 20th century northern Eurasian CO2 sink

NASA Astrophysics Data System (ADS)

Bastos, Ana; Peregon, Anna; Gani, Érico A.; Khudyaev, Sergey; Yue, Chao; Li, Wei; Gouveia, Célia M.; Ciais, Philippe

2018-06-01

While the global carbon budget (GCB) is relatively well constrained over the last decades of the 20th century [1], observations and reconstructions of atmospheric CO2 growth rate present large discrepancies during the earlier periods [2]. The large uncertainty in GCB has been attributed to the land biosphere, although it is not clear whether the gaps between observations and reconstructions are mainly because land-surface models (LSMs) underestimate inter-annual to decadal variability in natural ecosystems, or due to inaccuracies in land-use change reconstructions. As Eurasia encompasses about 15% of the terrestrial surface, 20% of the global soil organic carbon pool and constitutes a large CO2 sink, we evaluate the potential contribution of natural and human-driven processes to induce large anomalies in the biospheric CO2 fluxes in the early 20th century. We use an LSM specifically developed for high-latitudes, that correctly simulates Eurasian C-stocks and fluxes from observational records [3], in order to evaluate the sensitivity of the Eurasian sink to the strong high-latitude warming occurring between 1930 and 1950. We show that the LSM with improved high-latitude phenology, hydrology and soil processes, contrary to the group of LSMs in [2], is able to represent enhanced vegetation growth linked to boreal spring warming, consistent with tree-ring time-series [4]. By compiling a dataset of annual agricultural area in the Former Soviet Union that better reflects changes in cropland area linked with socio-economic fluctuations during the early 20th century, we show that land-abadonment during periods of crisis and war may result in reduced CO2 emissions from land-use change (44%–78% lower) detectable at decadal time-scales. Our study points to key processes that may need to be improved in LSMs and LUC datasets in order to better represent decadal variability in the land CO2 sink, and to better constrain the GCB during the pre-observational record.

Uncertainty Quantification and Regional Sensitivity Analysis of Snow-related Parameters in the Canadian LAnd Surface Scheme (CLASS)

NASA Astrophysics Data System (ADS)

Badawy, B.; Fletcher, C. G.

2017-12-01

The parameterization of snow processes in land surface models is an important source of uncertainty in climate simulations. Quantifying the importance of snow-related parameters, and their uncertainties, may therefore lead to better understanding and quantification of uncertainty within integrated earth system models. However, quantifying the uncertainty arising from parameterized snow processes is challenging due to the high-dimensional parameter space, poor observational constraints, and parameter interaction. In this study, we investigate the sensitivity of the land simulation to uncertainty in snow microphysical parameters in the Canadian LAnd Surface Scheme (CLASS) using an uncertainty quantification (UQ) approach. A set of training cases (n=400) from CLASS is used to sample each parameter across its full range of empirical uncertainty, as determined from available observations and expert elicitation. A statistical learning model using support vector regression (SVR) is then constructed from the training data (CLASS output variables) to efficiently emulate the dynamical CLASS simulations over a much larger (n=220) set of cases. This approach is used to constrain the plausible range for each parameter using a skill score, and to identify the parameters with largest influence on the land simulation in CLASS at global and regional scales, using a random forest (RF) permutation importance algorithm. Preliminary sensitivity tests indicate that snow albedo refreshment threshold and the limiting snow depth, below which bare patches begin to appear, have the highest impact on snow output variables. The results also show a considerable reduction of the plausible ranges of the parameters values and hence reducing their uncertainty ranges, which can lead to a significant reduction of the model uncertainty. The implementation and results of this study will be presented and discussed in details.

Towards a Near Real-Time Satellite-Based Flux Monitoring System for the MENA Region

NASA Astrophysics Data System (ADS)

Ershadi, A.; Houborg, R.; McCabe, M. F.; Anderson, M. C.; Hain, C.

2013-12-01

Satellite remote sensing has the potential to offer spatially and temporally distributed information on land surface characteristics, which may be used as inputs and constraints for estimating land surface fluxes of carbon, water and energy. Enhanced satellite-based monitoring systems for aiding local water resource assessments and agricultural management activities are particularly needed for the Middle East and North Africa (MENA) region. The MENA region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. To address these issues, an integrated modeling approach for near real-time monitoring of land surface states and fluxes at fine spatio-temporal scales over the MENA region is presented. This approach is based on synergistic application of multiple sensors and wavebands in the visible to shortwave infrared and thermal infrared (TIR) domain. The multi-scale flux mapping and monitoring system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and multi-sensor remotely sensed data from polar orbiting (e.g. Landsat and MODerate resolution Imaging Spectroradiometer (MODIS)) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate time-continuous (i.e. daily) estimates of field-scale water, energy and carbon fluxes. Within this modeling system, TIR satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and a detailed soil surface characterization (i.e. for prognostic modeling of soil transport processes). The STARFM fusion methodology blends aspects of high frequency (spatially coarse) and spatially fine resolution sensors and is applied directly to flux output fields to facilitate daily mapping of fluxes at sub-field scales. A complete processing infrastructure to automatically ingest and pre-process all required input data and to execute the integrated modeling system for near real-time agricultural monitoring purposes over targeted MENA sites is being developed, and initial results from this concerted effort will be discussed.

Combining super-ensembles and statistical emulation to improve a regional climate and vegetation model

NASA Astrophysics Data System (ADS)

Hawkins, L. R.; Rupp, D. E.; Li, S.; Sarah, S.; McNeall, D. J.; Mote, P.; Betts, R. A.; Wallom, D.

2017-12-01

Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land-atmosphere feedback strengths.

Non-radiative processes dominate land surface signals in the climate system

NASA Astrophysics Data System (ADS)

Bright, R. M.; Davin, E.; O'Halloran, T. L.; Pongratz, J.; Zhao, K.; Cescatti, A.

2016-12-01

Perturbations to the surface energy budget linked to land cover/land management changes (LCMC) are rarely included in land-climate assessments although they have long been recognized as important drivers of local climate change. At local scales, climate forcings from LCMC depend strongly on changes to surface energy redistribution by various non-radiative mechanisms, dampening or even outweighing the local radiative effect of an albedo change. The extent to which these mechanisms are locally relevant for different types of LCMC across the world remains largely unquantified. Here, we combine extensive records of remote sensing and in-situ observations to quantify local forcings for nine common real-world LCMC perturbations, identifying their underlying physical mechanisms and analyzing their spatial patterns at the global scale. We find that throughout the densely populated regions, non-radiative forcings dominate the local surface temperature response in 8 of 9 LCMC scenarios. Further, the observed local response to re-/afforestation is an annual cooling in all regions south of the upper conterminous United States, Western Europe, and Indo-China. Given that the global response to re-/afforestation in these regions is likely a cooling, projects here can be seen as attractive mitigation measures. Our results - gridded to a 1° x 1° resolution - can be directly used to evaluate climate models or compute indicators providing a more comprehensive picture of the trade-offs between local and global climate forcings linked to land sector projects and policies.

Ordovician ash geochemistry and the establishment of land plants

PubMed Central

2012-01-01

The colonization of the terrestrial environment by land plants transformed the planetary surface and its biota, and shifted the balance of Earth’s biomass from the subsurface towards the surface. However there was a long delay between the formation of palaeosols (soils) on the land surface and the key stage of plant colonization. The record of palaeosols, and their colonization by fungi and lichens extends well back into the Precambrian. While these early soils provided a potential substrate, they were generally leached of nutrients as part of the weathering process. In contrast, volcanic ash falls provide a geochemically favourable substrate that is both nutrient-rich and has high water retention, making them good hosts to land plants. An anomalously extensive system of volcanic arcs generated unprecedented volumes of lava and volcanic ash (tuff) during the Ordovician. The earliest, mid-Ordovician, records of plant spores coincide with these widespread volcanic deposits, suggesting the possibility of a genetic relationship. The ash constituted a global environment of nutrient-laden, water-saturated soil that could be exploited to maximum advantage by the evolving anchoring systems of land plants. The rapid and pervasive inoculation of modern volcanic ash by plant spores, and symbiotic nitrogen-fixing fungi, suggests that the Ordovician ash must have received a substantial load of the earliest spores and their chemistry favoured plant development. In particular, high phosphorus levels in ash were favourable to plant growth. This may have allowed photosynthesizers to diversify and enlarge, and transform the surface of the planet. PMID:22925460

Geometric-Optical Modeling of Directional Thermal Radiance for Improvement of Land Surface Temperature Retrievals from MODIS, ASTER, and Landsat-7 Instruments

NASA Technical Reports Server (NTRS)

Li, Xiaowen; Friedl, Mark; Strahler, Alan

2002-01-01

The general objectives of this project were to improve understanding of the directional emittance properties of land surfaces in the thermal infrared (TIR) region of the electro-magnetic spectrum. To accomplish these objectives our research emphasized a combination of theoretical model development and empirical studies designed to improve land surface temperature (LST) retrievals from space-borne remote sensing instruments. Following the proposal, the main tasks for this project were to: (1) Participate in field campaigns; (2) Acquire and process field, aircraft, and ancillary data; (3) Develop and refine models of LST emission; (4) Develop algorithms for LST retrieval; and (5) Explore LST retrieval methods for use in energy balance models. In general all of these objectives were addressed, and for the most part achieved. The main results from this project are described in the publications arising from this effort. We summarize our efforts related to each of the objectives.

Understanding the life cycle surface land requirements of natural gas-fired electricity

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

Jordaan, Sarah M.; Heath, Garvin A.; Macknick, Jordan

The surface land use of fossil fuel acquisition and utilization has not been well characterized, inhibiting consistent comparisons of different electricity generation technologies. We present a method for robust estimation of the life cycle land use of electricity generated from natural gas through a case study that includes inventories of infrastructure, satellite imagery and well-level production. Approximately 500 sites in the Barnett Shale of Texas were sampled across five life cycle stages (production, gathering, processing, transmission and power generation). Total land use (0.62 m 2 MWh -1, 95% confidence intervals +/-0.01 m 2 MWh -1) was dominated by midstream infrastructure,more » particularly pipelines (74%). These results were sensitive to power plant heat rate (85-190% of the base case), facility lifetime (89-169%), number of wells per site (16-100%), well lifetime (92-154%) and pipeline right of way (58-142%). When replicated for other gas-producing regions and different fuels, our approach offers a route to enable empirically grounded comparisons of the land footprint of energy choices.« less

Understanding the life cycle surface land requirements of natural gas-fired electricity

DOE PAGES

Jordaan, Sarah M.; Heath, Garvin A.; Macknick, Jordan; ...

2017-10-02

The surface land use of fossil fuel acquisition and utilization has not been well characterized, inhibiting consistent comparisons of different electricity generation technologies. We present a method for robust estimation of the life cycle land use of electricity generated from natural gas through a case study that includes inventories of infrastructure, satellite imagery and well-level production. Approximately 500 sites in the Barnett Shale of Texas were sampled across five life cycle stages (production, gathering, processing, transmission and power generation). Total land use (0.62 m 2 MWh -1, 95% confidence intervals +/-0.01 m 2 MWh -1) was dominated by midstream infrastructure,more » particularly pipelines (74%). These results were sensitive to power plant heat rate (85-190% of the base case), facility lifetime (89-169%), number of wells per site (16-100%), well lifetime (92-154%) and pipeline right of way (58-142%). When replicated for other gas-producing regions and different fuels, our approach offers a route to enable empirically grounded comparisons of the land footprint of energy choices.« less

Western rangelands: overgrazed and undermanaged

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

Sheridan, D.

1981-05-01

Overgrazing and poor management of the western arid lands causes desertification as the levels of water tables and surface waters drop, top soil and surface waters become more saline, soil erodes, and native vegetation disappears. This process had led to severe desertification in an estimated 1.1 million square miles and very severe desertification on 10,500 square miles in the US. The three areas in the very severe category occur in the Navajo Indian reservation in Arizona and New Mexico and on either side of El Paso, Texas. All were subjected to overgrazing. Government policies have only recently tried to bringmore » public land grazing in line with the land's carrying capacity by focusing on long-term productivity. The Public Rangelands Improvement Act of 1978 authorizes better management and multiple use of public lands, but the Bureau of Land Management has not established an effective monitoring system to ensure its implementation or to overcome political constraints against reducing livestock. Ranchers disagree with the assessments made by scientists and support vegetation modification instead of grazing allotments. 58 references, 7 figures. (DCK)« less

Understanding the life cycle surface land requirements of natural gas-fired electricity

NASA Astrophysics Data System (ADS)

Jordaan, Sarah M.; Heath, Garvin A.; Macknick, Jordan; Bush, Brian W.; Mohammadi, Ehsan; Ben-Horin, Dan; Urrea, Victoria; Marceau, Danielle

2017-10-01

The surface land use of fossil fuel acquisition and utilization has not been well characterized, inhibiting consistent comparisons of different electricity generation technologies. Here we present a method for robust estimation of the life cycle land use of electricity generated from natural gas through a case study that includes inventories of infrastructure, satellite imagery and well-level production. Approximately 500 sites in the Barnett Shale of Texas were sampled across five life cycle stages (production, gathering, processing, transmission and power generation). Total land use (0.62 m2 MWh-1, 95% confidence intervals ±0.01 m2 MWh-1) was dominated by midstream infrastructure, particularly pipelines (74%). Our results were sensitive to power plant heat rate (85-190% of the base case), facility lifetime (89-169%), number of wells per site (16-100%), well lifetime (92-154%) and pipeline right of way (58-142%). When replicated for other gas-producing regions and different fuels, our approach offers a route to enable empirically grounded comparisons of the land footprint of energy choices.

Mössbauer spectroscopy on Mars: goethite in the Columbia Hills at Gusev crater

NASA Astrophysics Data System (ADS)

Klingelhöfer, G.; Degrave, E.; Morris, R. V.; van Alboom, A.; de Resende, V. G.; de Souza, P. A.; Rodionov, D.; Schröder, C.; Ming, D. W.; Yen, A.

2005-11-01

In January 2004 the USA space agency NASA landed two rovers on the surface of Mars, both carrying the Mainz Mössbauer spectrometer MIMOS II. The instrument on the Mars-Exploration-Rover (MER) Spirit analyzed soils and rocks on the plains and in the Columbia Hills of Gusev crater landing site on Mars. The surface material in the plains have an olivine basaltic signature [1, 5] suggesting physical rather than chemical weathering processes present in the plains. The Mössbauer signature for the Columbia Hills surface material is very different ranging from nearly unaltered material to highly altered material. Some of the rocks, in particular a rock named Clovis, contain a significant amount of the Fe oxyhydroxide goethite, α-FeOOH, which is mineralogical evidence for aqueous processes because it is formed only under aqueous conditions. In this paper we describe the analysis of these data using hyperfine field distributions (HFD) and discuss the results in comparison to terrestrial analogues.

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.

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.

Improved representations of coupled soil–canopy processes in the CABLE land surface model (Subversion revision 3432)

DOE PAGES

Haverd, Vanessa; Cuntz, Matthias; Nieradzik, Lars P.; ...

2016-09-07

CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. While CABLE performs well in comparison with other land surface models, results are impacted by decoupling of transpiration and photosynthesis fluxes under drying soil conditions, often leading to implausibly high water use efficiencies. Here, we present a solution to this problem, ensuring that modelled transpiration is always consistent with modelled photosynthesis, while introducing a parsimonious single-parameter drought response function which is coupled to root water uptake. We further improve CABLE's simulation of coupled soil–canopy processes by introducing an alternative hydrology model with amore » physically accurate representation of coupled energy and water fluxes at the soil–air interface, including a more realistic formulation of transfer under atmospherically stable conditions within the canopy and in the presence of leaf litter. The effects of these model developments are assessed using data from 18 stations from the global eddy covariance FLUXNET database, selected to span a large climatic range. Here, marked improvements are demonstrated, with root mean squared errors for monthly latent heat fluxes and water use efficiencies being reduced by 40 %. Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.« less

Reclamation of mined lands in the western coal region

USGS Publications Warehouse

Narten, Perry F.; Litner, S.F.; Allingham, J.W.; Foster, Lee; Larsen, D.M.; McWreath, H.C.

1983-01-01

In 1978, a group of scientists from several Federal agencies examined reclamation work at 22 coal mines in seven western States. The results of these examinations were not used to derive quantitative predictions of the outcome of reclamation work but rather to determine the general requirements for revegetation success. Locally, reclamation efforts are affected by climate, especially precipitation; the landform of the restored surface; the nature of the overburden material; the nature of the surface soil; and the natural ecological system. The goals of reclamation efforts are now broader than ever. Regulations call not only for reducing the steepness of the final surface and establishing a cover of mostly perennial native vegetation, but for restoring the land for specific land uses, achieving diversity both in types of plants and in number of species, and reintroduction of biological and ecological processes. If specific sites are monitored over a long enough period of time, quantitative predictions of success for individual mines may be possible, and such predictions can be included in environmental impact statements to help in the decision-making process. The results of this study indicate that current reclamation objectives can be met when the reclamation effort is designed on the basis of site-specific needs and when existing technology is used.

Using Landsat Surface Reflectance Data as a Reference Target for Multiswath Hyperspectral Data Collected Over Mixed Agricultural Rangeland Areas

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

McCann, Cooper; Repasky, Kevin S.; Morin, Mikindra

Low-cost flight-based hyperspectral imaging systems have the potential to provide important information for ecosystem and environmental studies as well as aide in land management. To realize this potential, methods must be developed to provide large-area surface reflectance data allowing for temporal data sets at the mesoscale. This paper describes a bootstrap method of producing a large-area, radiometrically referenced hyperspectral data set using the Landsat surface reflectance (LaSRC) data product as a reference target. The bootstrap method uses standard hyperspectral processing techniques that are extended to remove uneven illumination conditions between flight passes, allowing for radiometrically self-consistent data after mosaicking. Throughmore » selective spectral and spatial resampling, LaSRC data are used as a radiometric reference target. Advantages of the bootstrap method include the need for minimal site access, no ancillary instrumentation, and automated data processing. Data from two hyperspectral flights over the same managed agricultural and unmanaged range land covering approximately 5.8 km 2 acquired on June 21, 2014 and June 24, 2015 are presented. As a result, data from a flight over agricultural land collected on June 6, 2016 are compared with concurrently collected ground-based reflectance spectra as a means of validation.« less

Documentation of a deep percolation model for estimating ground-water recharge

USGS Publications Warehouse

Bauer, H.H.; Vaccaro, J.J.

1987-01-01

A deep percolation model, which operates on a daily basis, was developed to estimate long-term average groundwater recharge from precipitation. It has been designed primarily to simulate recharge in large areas with variable weather, soils, and land uses, but it can also be used at any scale. The physical and mathematical concepts of the deep percolation model, its subroutines and data requirements, and input data sequence and formats are documented. The physical processes simulated are soil moisture accumulation, evaporation from bare soil, plant transpiration, surface water runoff, snow accumulation and melt, and accumulation and evaporation of intercepted precipitation. The minimum data sets for the operation of the model are daily values of precipitation and maximum and minimum air temperature, soil thickness and available water capacity, soil texture, and land use. Long-term average annual precipitation, actual daily stream discharge, monthly estimates of base flow, Soil Conservation Service surface runoff curve numbers, land surface altitude-slope-aspect, and temperature lapse rates are optional. The program is written in the FORTRAN 77 language with no enhancements and should run on most computer systems without modifications. Documentation has been prepared so that program modifications may be made for inclusions of additional physical processes or deletion of ones not considered important. (Author 's abstract)

Using Landsat Surface Reflectance Data as a Reference Target for Multiswath Hyperspectral Data Collected Over Mixed Agricultural Rangeland Areas

DOE PAGES

McCann, Cooper; Repasky, Kevin S.; Morin, Mikindra; ...

2017-07-25

Low-cost flight-based hyperspectral imaging systems have the potential to provide important information for ecosystem and environmental studies as well as aide in land management. To realize this potential, methods must be developed to provide large-area surface reflectance data allowing for temporal data sets at the mesoscale. This paper describes a bootstrap method of producing a large-area, radiometrically referenced hyperspectral data set using the Landsat surface reflectance (LaSRC) data product as a reference target. The bootstrap method uses standard hyperspectral processing techniques that are extended to remove uneven illumination conditions between flight passes, allowing for radiometrically self-consistent data after mosaicking. Throughmore » selective spectral and spatial resampling, LaSRC data are used as a radiometric reference target. Advantages of the bootstrap method include the need for minimal site access, no ancillary instrumentation, and automated data processing. Data from two hyperspectral flights over the same managed agricultural and unmanaged range land covering approximately 5.8 km 2 acquired on June 21, 2014 and June 24, 2015 are presented. As a result, data from a flight over agricultural land collected on June 6, 2016 are compared with concurrently collected ground-based reflectance spectra as a means of validation.« less

Improved representations of coupled soil–canopy processes in the CABLE land surface model (Subversion revision 3432)

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

Haverd, Vanessa; Cuntz, Matthias; Nieradzik, Lars P.

CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. While CABLE performs well in comparison with other land surface models, results are impacted by decoupling of transpiration and photosynthesis fluxes under drying soil conditions, often leading to implausibly high water use efficiencies. Here, we present a solution to this problem, ensuring that modelled transpiration is always consistent with modelled photosynthesis, while introducing a parsimonious single-parameter drought response function which is coupled to root water uptake. We further improve CABLE's simulation of coupled soil–canopy processes by introducing an alternative hydrology model with amore » physically accurate representation of coupled energy and water fluxes at the soil–air interface, including a more realistic formulation of transfer under atmospherically stable conditions within the canopy and in the presence of leaf litter. The effects of these model developments are assessed using data from 18 stations from the global eddy covariance FLUXNET database, selected to span a large climatic range. Here, marked improvements are demonstrated, with root mean squared errors for monthly latent heat fluxes and water use efficiencies being reduced by 40 %. Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.« less

Improved representations of coupled soil-canopy processes in the CABLE land surface model (Subversion revision 3432)

NASA Astrophysics Data System (ADS)

Haverd, Vanessa; Cuntz, Matthias; Nieradzik, Lars P.; Harman, Ian N.

2016-09-01

CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. While CABLE performs well in comparison with other land surface models, results are impacted by decoupling of transpiration and photosynthesis fluxes under drying soil conditions, often leading to implausibly high water use efficiencies. Here, we present a solution to this problem, ensuring that modelled transpiration is always consistent with modelled photosynthesis, while introducing a parsimonious single-parameter drought response function which is coupled to root water uptake. We further improve CABLE's simulation of coupled soil-canopy processes by introducing an alternative hydrology model with a physically accurate representation of coupled energy and water fluxes at the soil-air interface, including a more realistic formulation of transfer under atmospherically stable conditions within the canopy and in the presence of leaf litter. The effects of these model developments are assessed using data from 18 stations from the global eddy covariance FLUXNET database, selected to span a large climatic range. Marked improvements are demonstrated, with root mean squared errors for monthly latent heat fluxes and water use efficiencies being reduced by 40 %. Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.

Uncertainties in estimates of fAPAR for photosynthesis (fAPARPSN) in tropical, Arctic/boreal, coastal, and wetland-dominant regions when approximated with fAPARcanopy and NDVI

NASA Astrophysics Data System (ADS)

Zhang, Q.; Yao, T.

2016-12-01

The climate is affected by the land surface through regulating the exchange of mass and energy with the atmosphere. The energy that reaches the land surface has three pathways: (1) reflected into atmosphere; (2) absorbed for photosynthesis; and (3) discarded as latent and sensible heat or emitted as fluorescence. Vegetation removes CO2 from the atmosphere during the process of photosynthesis, but also releases CO2 back into the atmosphere through the process of respiration. The complex set of vegetation-soil-atmosphere interactions requires that a realistic land-surface parameterization be included in any climate model or general circulation model (GCM) to accurately simulate canopy photosynthesis and stomatal conductance.We retrieve fraction of PAR absorbed by chlorophyll (fAPARchl) with an advanced canopy-leaf-soil-snow-water coupled radiative transfer model. Most ecological models and land-surface models that simulate vegetation GPP with remote sensing data utilize fraction of PAR absorbed by the whole canopy (fAPARcanopy). However, only the PAR absorbed by chlorophyll is potentially available for photosynthesis since the PAR absorbed by non-photosynthetic vegetation section (NPV) of the canopy is not used for photosynthesis. Therefore, fAPARchl (rather than fAPARcanopy) should be utilized to estimate fAPAR for photosynthesis (fAPARPSN), and thus in GPP simulation. Globally selected sites include those sites in tropical, Arctic/boreal, coastal, and wetland-dominant regions. The fAPARchl and fAPARcanopy products for a surrounding area 50 km x 50 km of each site are mapped. The fAPARchl is utilized to estimate GPP, and compared to tower flux GPP for validation. The GPP estimation performance with fAPARchl is also compared with the GPP estimation performance with MOD15A2 FPAR. The fAPARchl product is further implemented into ecological models and land-surface models to simulate vegetation GPP. NDVI is the other proxy of fAPARPSN in GPP estimation. We quantify the uncertainties in estimates of fAPARPSN when approximated with fAPARcanopy and NDVI. The uncertainties are significant and vary spatially, temporally, and with plant functional types.

Land surface energy budget during dry spells: global CMIP5 AMIP simulations vs. satellite observations

NASA Astrophysics Data System (ADS)

Gallego-Elvira, Belen; Taylor, Christopher M.; Harris, Phil P.; Ghent, Darren; Folwell, Sonja S.

2015-04-01

During extended periods without rain (dry spells), the soil can dry out due to vegetation transpiration and soil evaporation. At some point in this drying cycle, land surface conditions change from energy-limited to water-limited evapotranspiration, and this is accompanied by an increase of the ground and overlying air temperatures. Regionally, the characteristics of this transition determine the influence of soil moisture on air temperature and rainfall. Global Climate Models (GCMs) disagree on where and how strongly the surface energy budget is limited by soil moisture. Flux tower observations are improving our understanding of these dry down processes, but typical heterogeneous landscapes are too sparsely sampled to ascertain a representative regional response. Alternatively, satellite observations of land surface temperature (LST) provide indirect information about the surface energy partition at 1km resolution globally. In our study, we analyse how well the dry spell dynamics of LST are represented by GCMs across the globe. We use a spatially and temporally aggregated diagnostic to describe the composite response of LST during surface dry down in rain-free periods in distinct climatic regions. The diagnostic is derived from daytime MODIS-Terra LST observations and bias-corrected meteorological re-analyses, and compared against the outputs of historical climate simulations of seven models running the CMIP5 AMIP experiment. Dry spell events are stratified by antecedent precipitation, land cover type and geographic regions to assess the sensitivity of surface warming rates to soil moisture levels at the onset of a dry spell for different surface and climatic zones. In a number of drought-prone hot spot regions, we find important differences in simulated dry spell behaviour, both between models, and compared to observations. These model biases are likely to compromise seasonal forecasts and future climate projections.

Ground displacements caused by aquifer-system water-level variations observed using interferometric synthetic aperture radar near Albuquerque, New Mexico

USGS Publications Warehouse

Heywood, Charles E.; Galloway, Devin L.; Stork, Sylvia V.

2002-01-01

Six synthetic aperture radar (SAR) images were processed to form five unwrapped interferometric (InSAR) images of the greater metropolitan area in the Albuquerque Basin. Most interference patterns in the images were caused by range displacements resulting from changes in land-surface elevation. Loci of land- surface elevation changes correlate with changes in aquifer-system water levels and largely result from the elastic response of the aquifer-system skeletal material to changes in pore-fluid pressure. The magnitude of the observed land-surface subsidence and rebound suggests that aquifer-system deformation resulting from ground-water withdrawals in the Albuquerque area has probably remained in the elastic (recoverable) range from July 1993 through September 1999. Evidence of inelastic (permanent) land subsidence in the Rio Rancho area exists, but its relation to compaction of the aquifer system is inconclusive because of insufficient water-level data. Patterns of elastic deformation in both Albuquerque and Rio Rancho suggest that intrabasin faults impede ground- water-pressure diffusion at seasonal time scales and that these faults are probably important in controlling patterns of regional ground-water flow.

Impact of a regional drought on terrestrial carbon fluxes and atmospheric carbon: results from a coupled carbon cycle model

NASA Astrophysics Data System (ADS)

Lee, E.; Koster, R. D.; Ott, L. E.; Weir, B.; Mahanama, S. P. P.; Chang, Y.; Zeng, F.

2017-12-01

Understanding the underlying processes that control the carbon cycle is key to predicting future global change. Much of the uncertainty in the magnitude and variability of the atmospheric carbon dioxide (CO2) stems from uncertainty in terrestrial carbon fluxes. Budget-based analyses show that such fluxes exhibit substantial interannual variability, but the relative impacts of temperature and moisture variations on regional and global scales are poorly understood. Here we investigate the impact of a regional drought on terrestrial carbon fluxes and CO2 mixing ratios over North America using the NASA Goddard Earth Observing System (GEOS) Model. Two 48-member ensembles of NASA GEOS-5 simulations with fully coupled land and atmosphere carbon components are performed - a control ensemble and an ensemble with an artificially imposed dry land surface anomaly for three months (April-June) over the lower Mississippi River Valley. Comparison of the results using the ensemble approach allows a direct quantification of the impact of the regional drought on local and proximate carbon exchange at the land surface via the carbon-water feedback processes.

The Urban Heat Island Impact in Consideration of Spatial Pattern of Urban Landscape and Structure

NASA Astrophysics Data System (ADS)

Kim, J.; Lee, D. K.; Jeong, W.; Sung, S.; Park, J.

2015-12-01

Preceding study has established a clear relationship between land surface temperature and area of land covers. However, only few studies have specifically examined the effects of spatial patterns of land covers and urban structure. To examine how much the local climate is affected by the spatial pattern in highly urbanized city, we investigated the correlation between land surface temperature and spatial patterns of land covers. In the analysis of correlation, we categorized urban structure to four different land uses: Apartment residential area, low rise residential area, industrial area and central business district. Through this study, we aims to examine the types of residential structure and land cover pattern for reducing urban heat island and sustainable development. Based on land surface temperature, we investigated the phenomenon of urban heat island through using the data of remote sensing. This study focused on Daegu in Korea. This city, one of the hottest city in Korea has basin form. We used high-resolution land cover data and land surface temperature by using Landsat8 satellite image to examine 100 randomly selected sample sites of 884.15km2 (1)In each land use, we quantified several landscape-levels and class-level landscape metrics for the sample study sites. (2)In addition, we measured the land surface temperature in 3 year hot summer seasons (July to September). Then, we investigated the pattern of land surface temperature for each land use through Ecognition package. (3)We deducted the Pearson correlation coefficients between land surface temperature and each landscape metrics. (4)We analyzed the variance among the four land uses. (5)Using linear regression, we determined land surface temperature model for each land use. (6)Through this analysis, we aims to examine the best pattern of land cover and artificial structure for reducing urban heat island effect in highly urbanized city. The results of linear regression showed that proportional land cover of grass, tree, water and impervious surfaces well explained the temperature in apartment residential areas. In contrast, the changes in the pattern of water, grass, tree and impervious surfaces were the best to determine the temperature in low rise residential area, central business district and industrial area.

Estimation of Transpiration and Water Use Efficiency Using Satellite and Field Observations

NASA Technical Reports Server (NTRS)

Choudhury, Bhaskar J.; Quick, B. E.

2003-01-01

Structure and function of terrestrial plant communities bring about intimate relations between water, energy, and carbon exchange between land surface and atmosphere. Total evaporation, which is the sum of transpiration, soil evaporation and evaporation of intercepted water, couples water and energy balance equations. The rate of transpiration, which is the major fraction of total evaporation over most of the terrestrial land surface, is linked to the rate of carbon accumulation because functioning of stomata is optimized by both of these processes. Thus, quantifying the spatial and temporal variations of the transpiration efficiency (which is defined as the ratio of the rate of carbon accumulation and transpiration), and water use efficiency (defined as the ratio of the rate of carbon accumulation and total evaporation), and evaluation of modeling results against observations, are of significant importance in developing a better understanding of land surface processes. An approach has been developed for quantifying spatial and temporal variations of transpiration, and water-use efficiency based on biophysical process-based models, satellite and field observations. Calculations have been done using concurrent meteorological data derived from satellite observations and four dimensional data assimilation for four consecutive years (1987-1990) over an agricultural area in the Northern Great Plains of the US, and compared with field observations within and outside the study area. The paper provides substantive new information about interannual variation, particularly the effect of drought, on the efficiency values at a regional scale.

Modelling evapotranspiration during precipitation deficits: Identifying critical processes in a land surface model

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

Ukkola, Anna M.; Pitman, Andy J.; Decker, Mark

Surface fluxes from land surface models (LSMs) have traditionally been evaluated against monthly, seasonal or annual mean states. The limited ability of LSMs to reproduce observed evaporative fluxes under water-stressed conditions has been previously noted, but very few studies have systematically evaluated these models during rainfall deficits. We evaluated latent heat fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLE) LSM across 20 flux tower sites at sub-annual to inter-annual timescales, in particular focusing on model performance during seasonal-scale rainfall deficits. The importance of key model processes in capturing the latent heat flux was explored by employing alternative representations of hydrology, leafmore » area index, soil properties and stomatal conductance. We found that the representation of hydrological processes was critical for capturing observed declines in latent heat during rainfall deficits. By contrast, the effects of soil properties, LAI and stomatal conductance were highly site-specific. Whilst the standard model performs reasonably well at annual scales as measured by common metrics, it grossly underestimates latent heat during rainfall deficits. A new version of CABLE, with a more physically consistent representation of hydrology, captures the variation in the latent heat flux during seasonal-scale rainfall deficits better than earlier versions, but remaining biases point to future research needs. Lastly, our results highlight the importance of evaluating LSMs under water-stressed conditions and across multiple plant functional types and climate regimes.« less

Modelling evapotranspiration during precipitation deficits: Identifying critical processes in a land surface model

DOE PAGES

Ukkola, Anna M.; Pitman, Andy J.; Decker, Mark; ...

2016-06-21

Surface fluxes from land surface models (LSMs) have traditionally been evaluated against monthly, seasonal or annual mean states. The limited ability of LSMs to reproduce observed evaporative fluxes under water-stressed conditions has been previously noted, but very few studies have systematically evaluated these models during rainfall deficits. We evaluated latent heat fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLE) LSM across 20 flux tower sites at sub-annual to inter-annual timescales, in particular focusing on model performance during seasonal-scale rainfall deficits. The importance of key model processes in capturing the latent heat flux was explored by employing alternative representations of hydrology, leafmore » area index, soil properties and stomatal conductance. We found that the representation of hydrological processes was critical for capturing observed declines in latent heat during rainfall deficits. By contrast, the effects of soil properties, LAI and stomatal conductance were highly site-specific. Whilst the standard model performs reasonably well at annual scales as measured by common metrics, it grossly underestimates latent heat during rainfall deficits. A new version of CABLE, with a more physically consistent representation of hydrology, captures the variation in the latent heat flux during seasonal-scale rainfall deficits better than earlier versions, but remaining biases point to future research needs. Lastly, our results highlight the importance of evaluating LSMs under water-stressed conditions and across multiple plant functional types and climate regimes.« less

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.

Digital mapping of the Mars Pathfinder landing site: Design, acquisition, and derivation of cartographic products for science applications

USGS Publications Warehouse

Gaddis, L.R.; Kirk, R.L.; Johnson, J. R.; Soderblom, L.A.; Ward, A.W.; Barrett, J.; Becker, K.; Decker, T.; Blue, J.; Cook, D.; Eliason, E.; Hare, T.; Howington-Kraus, E.; Isbell, C.; Lee, E.M.; Redding, B.; Sucharski, R.; Sucharski, T.; Smith, P.H.; Britt, D.T.

1999-01-01

The Imager for Mars Pathfinder (IMP) acquired more than 16,000 images and provided panoramic views of the surface of Mars at the Mars Pathfinder landing site in Ares Vallis. This paper describes the stereoscopic, multispectral IMP imaging sequences and focuses on their use for digital mapping of the landing site and for deriving cartographic products to support science applications of these data. Two-dimensional cartographic processing of IMP data, as performed via techniques and specialized software developed for ISIS (the U.S.Geological Survey image processing software package), is emphasized. Cartographic processing of IMP data includes ingestion, radiometric correction, establishment of geometric control, coregistration of multiple bands, reprojection, and mosaicking. Photogrammetric processing, an integral part of this cartographic work which utilizes the three-dimensional character of the IMP data, supplements standard processing with geometric control and topographic information [Kirk et al., this issue]. Both cartographic and photogrammetric processing are required for producing seamless image mosaics and for coregistering the multispectral IMP data. Final, controlled IMP cartographic products include spectral cubes, panoramic (360?? azimuthal coverage) and planimetric (top view) maps, and topographic data, to be archived on four CD-ROM volumes. Uncontrolled and semicontrolled versions of these products were used to support geologic characterization of the landing site during the nominal and extended missions. Controlled products have allowed determination of the topography of the landing site and environs out to ???60 m, and these data have been used to unravel the history of large- and small-scale geologic processes which shaped the observed landing site. We conclude by summarizing several lessons learned from cartographic processing of IMP data. Copyright 1999 by the American Geophysical Union.

Modelling the effect of urbanization on the transmission of an infectious disease.

PubMed

Zhang, Ping; Atkinson, Peter M

2008-01-01

This paper models the impact of urbanization on infectious disease transmission by integrating a CA land use development model, population projection matrix model and CA epidemic model in S-Plus. The innovative feature of this model lies in both its explicit treatment of spatial land use development, demographic changes, infectious disease transmission and their combination in a dynamic, stochastic model. Heuristically-defined transition rules in cellular automata (CA) were used to capture the processes of both land use development with urban sprawl and infectious disease transmission. A population surface model and dwelling distribution surface were used to bridge the gap between urbanization and infectious disease transmission. A case study is presented involving modelling influenza transmission in Southampton, a dynamically evolving city in the UK. The simulation results for Southampton over a 30-year period show that the pattern of the average number of infection cases per day can depend on land use and demographic changes. The modelling framework presents a useful tool that may be of use in planning applications.

Simulation Experiment on Landing Site Selection Using a Simple Geometric Approach

NASA Astrophysics Data System (ADS)

Zhao, W.; Tong, X.; Xie, H.; Jin, Y.; Liu, S.; Wu, D.; Liu, X.; Guo, L.; Zhou, Q.

2017-07-01

Safe landing is an important part of the planetary exploration mission. Even fine scale terrain hazards (such as rocks, small craters, steep slopes, which would not be accurately detected from orbital reconnaissance) could also pose a serious risk on planetary lander or rover and scientific instruments on-board it. In this paper, a simple geometric approach on planetary landing hazard detection and safe landing site selection is proposed. In order to achieve full implementation of this algorithm, two easy-to-compute metrics are presented for extracting the terrain slope and roughness information. Unlike conventional methods which must do the robust plane fitting and elevation interpolation for DEM generation, in this work, hazards is identified through the processing directly on LiDAR point cloud. For safe landing site selection, a Generalized Voronoi Diagram is constructed. Based on the idea of maximum empty circle, the safest landing site can be determined. In this algorithm, hazards are treated as general polygons, without special simplification (e.g. regarding hazards as discrete circles or ellipses). So using the aforementioned method to process hazards is more conforming to the real planetary exploration scenario. For validating the approach mentioned above, a simulated planetary terrain model was constructed using volcanic ash with rocks in indoor environment. A commercial laser scanner mounted on a rail was used to scan the terrain surface at different hanging positions. The results demonstrate that fairly hazard detection capability and reasonable site selection was obtained compared with conventional method, yet less computational time and less memory usage was consumed. Hence, it is a feasible candidate approach for future precision landing selection on planetary surface.

Towards a high resolution, integrated hydrology model of North America.

NASA Astrophysics Data System (ADS)

Maxwell, R. M.; Condon, L. E.

2015-12-01

Recent studies demonstrate feedbacks between groundwater dynamics, overland flow, land surface and vegetation processes, and atmospheric boundary layer development that significantly affect local and regional climate across a range of climatic conditions. Furthermore, the type and distribution of vegetation cover alters land-atmosphere water and energy fluxes, as well as runoff generation and overland flow processes. These interactions can result in significant feedbacks on local and regional climate. In mountainous regions, recent research has shown that spatial and temporal variability in annual evapotranspiration, and thus water budgets, is strongly dependent on lateral groundwater flow; however, the full effects of these feedbacks across varied terrain (e.g. from plains to mountains) are not well understood. Here, we present a high-resolution, integrated hydrology model that covers much of continental North America and encompasses the Mississippi and Colorado watersheds. The model is run in a fully-transient manner at hourly temporal resolution incorporating fully-coupled land energy states and fluxes with integrated surface and subsurface hydrology. Connections are seen between hydrologic variables (such as water table depth) and land energy fluxes (such as latent heat) and spatial and temporal scaling is shown to span many orders of magnitude. Using these transient simulations as a proof of concept, we present a vision for future integrated simulation capabilities.

ICESat Contributions to Understanding Coastal Processes

NASA Astrophysics Data System (ADS)

Urban, T. J.; Schutz, B. E.; Neuenschwander, A. L.

2006-12-01

ICESat (Ice, Cloud, and land Elevation Satellite) has been obtaining global elevation measurements of the Earth since 2003. These data have shed new light in unprecedented detail over ice, land and ocean surfaces. In particular, coastal altimetry including transitions from land to water and back benefit from ICESat's small footprint (~70 m diameter), high resolution (40 Hz and 170 m spot separation), and high precision (3 cm over non-vegetated surfaces). ICESat data support a wide variety of interdisciplinary investigations incorporating other data such as GRACE, GPS, SRTM, InSAR, Landsat, radar altimetry (TOPEX/Jason/Envisat), airborne LIDAR, and tide gauges. This paper provides an introduction to the potential capabilities of using ICESat coastal data in cooperative efforts. Several examples of coastal topography and change detection are shown, including the Texas-Louisiana Gulf Coast and the Mississippi Delta.

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.

Comparing atmosphere-land surface feedbacks from models within the tropics (CALM). Part 1: Evaluation of CMIP5 GCMs to simulate the land surface-atmosphere feedback

NASA Astrophysics Data System (ADS)

Williams, C.; Allan, R.; Kniveton, D.

2012-04-01

Man-made transformations to the environment, and in particular the land surface, are having a large impact on the distribution (in both time and space) of rainfall, upon which all life is reliant. From global changes in the composition of the atmosphere, through the emission of greenhouse gases and aerosols, to more localised land use and land cover changes due to an expanding population with an increasing ecological footprint, human activity has a considerable impact on the processes controlling rainfall. This is of particular importance for environmentally vulnerable regions such as many of those in the tropics. Here, widespread poverty, an extensive disease burden and pockets of political instability has resulted in a low resilience and limited adaptative capacity to climate related shocks and stresses. Recently, the 5th Climate Modelling Intercomparison Project (CMIP5) has run a number of state-of-the-art climate models using various present-day and future emission scenarios of greenhouse gases, and therefore provides an unprecedented amount of simulated model data. This paper presents the results of the first stage of a larger project, aiming to further our understanding of how the interactions between tropical rainfall and the land surface are represented in some of the latest climate model simulations. Focusing on precipitation, soil moisture and near-surface temperature, this paper compares the data from all of these models, as well as blended observational-satellite data, to see how the interactions between rainfall and the land surface differs (or agrees) between the models and reality. Firstly, in an analysis of the processes from the "observed" data, the results suggest a strong positive relationship between precipitation and soil moisture at both daily and seasonal timescales. There is a weaker and negative relationship between precipitation and temperature, and likewise between soil moisture and temperature. For all variables, the correlations are stronger at the seasonal timescale. These results also suggest that there are "hotspots" of high linear gradients between precipitation and soil moisture, corresponding to regions experiencing heavy rainfall. Secondly, in a comparison of these relationships across all available models, preliminary results suggest that there is high variability in the ability of the models to reproduce the observed correlations between precipitation and soil moisture. All models show weaker correlations than in the observed at daily timescales. Finally, one of the models (namely HadGEM2-ES, from the UK Met Office Hadley Centre) will be focused upon as an example case study. Here, preliminary findings suggest a difference between the model and the observations in the timings of the correlations, with the model showing the highest positive correlations when precipitation leads soil moisture by one day.

An Investigation of the Influence of Urban Areas on Rainfall Using a Cloud-Mesoscale Model and the TRMM Satellite

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Starr, David O'C (Technical Monitor)

2001-01-01

A recent paper by Shepherd and Pierce (conditionally accepted to Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. A convective-mesoscale model with extensive land-surface processes is employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. Early analysis suggests that urban surface roughness (through turbulence and low-level convergence) may control timing and initial location of UHI-induced convection. The magnitude of the heat island appears to be closely linked to the total rainfall amount with minor impact on timing and location. The physical size of the city may predominantly impact on the location of UHI-induced rainfall anomaly. The UHI factor parameter space will be thoroughly investigated with respect to their effects on rainfall amount, location, and timing. This study extends prior numerical investigations of the impact of urban surfaces on meteorological processes, particularly rainfall development. The work also contains several novel aspects, including the application of a high-resolution (less than I km) cloud-mesoscale model to investigate urban-induce rainfall process; investigation of thermal magnitude of the UHI on rainfall process; and investigation of UHI physical size on rainfall processes.

The Central Valley Hydrologic Model

NASA Astrophysics Data System (ADS)

Faunt, C.; Belitz, K.; Hanson, R. T.

2009-12-01

Historically, California’s Central Valley has been one of the most productive agricultural regions in the world. The Central Valley also is rapidly becoming an important area for California’s expanding urban population. In response to this competition for water, a number of water-related issues have gained prominence: conjunctive use, artificial recharge, hydrologic implications of land-use change, subsidence, and effects of climate variability. To provide information to stakeholders addressing these issues, the USGS made a detailed assessment of the Central Valley aquifer system that includes the present status of water resources and how these resources have changed over time. The principal product of this assessment is a tool, referred to as the Central Valley Hydrologic Model (CVHM), that simulates surface-water flows, groundwater flows, and land subsidence in response to stresses from human uses and from climate variability throughout the entire Central Valley. The CVHM utilizes MODFLOW combined with a new tool called “Farm Process” to simulate groundwater and surface-water flow, irrigated agriculture, land subsidence, and other key processes in the Central Valley on a monthly basis. This model was discretized horizontally into 20,000 1-mi2 cells and vertically into 10 layers ranging in thickness from 50 feet at the land surface to 750 feet at depth. A texture model constructed by using data from more than 8,500 drillers’ logs was used to estimate hydraulic properties. Unmetered pumpage and surface-water deliveries for 21 water-balance regions were simulated with the Farm Process. Model results indicate that human activities, predominately surface-water deliveries and groundwater pumping for irrigated agriculture, have dramatically influenced the hydrology of the Central Valley. These human activities have increased flow though the aquifer system by about a factor of six compared to pre-development conditions. The simulated hydrology reflects spatial and temporal variability in climate, land-use changes, and available surface-water deliveries. For example, the droughts of 1976-77 and 1987-92 led to reduced streamflow and surface-water deliveries and increased evapotranspiration and groundwater pumpage throughout most of the valley, resulting in a decrease in groundwater storage. Since the mid-1990s, annual surface-water deliveries generally have exceeded groundwater pumpage, resulting in an increase or no change in groundwater storage throughout most of the valley. However, groundwater is still being removed from storage during most years in the southern part of the Central Valley. The CVHM is designed to be coupled with Global Climate Models to forecast the potential supply of surface-water deliveries, demand for groundwater pumpage, potential subsidence, and changes in groundwater storage in response to different climate-change scenarios. The detailed database on texture properties coupled with CVHM's ability to simulate the combined effects of recharge and discharge make CVHM particularly useful for assessing water-management plans, such as conjunctive water use, conservation of agriculture land, and land-use change. In the future, the CVHM could be used in conjunction with optimization models to help evaluate water-management alternatives to effectively utilize the available water resources.

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).

Development of an Impervious-Surface Database for the Little Blackwater River Watershed, Dorchester County, Maryland

USGS Publications Warehouse

Milheim, Lesley E.; Jones, John W.; Barlow, Roger A.

2007-01-01

Many agricultural and forested areas in proximity to National Wildlife Refuges (NWR) are under increasing economic pressure for commercial or residential development. The upper portion of the Little Blackwater River watershed - a 27 square mile area within largely low-lying Dorchester County, Maryland, on the eastern shore of the Chesapeake Bay - is important to the U.S. Fish and Wildlife Service (USFWS) because it flows toward the Blackwater National Wildlife Refuge (BNWR), and developmental impacts of areas upstream from the BNWR are unknown. One of the primary concerns for the Refuge is how storm-water runoff may affect living resources downstream. The Egypt Road project (fig. 1), for which approximately 600 residential units have been approved, has the potential to markedly change the land use and land cover on the west bank of the Little Blackwater River. In an effort to limit anticipated impacts, the Maryland Department of Natural Resources (Maryland DNR) recently decided to purchase some of the lands previously slated for development. Local topography, a high water table (typically 1 foot or less below the land surface), and hydric soils present a challenge for the best management of storm-water flow from developed surfaces. A spatial data coordination group was formed by the Dorchester County Soil and Conservation District to collect data to aid decisionmakers in watershed management and on the possible impacts of development on this watershed. Determination of streamflow combined with land cover and impervious-surface baselines will allow linking of hydrologic and geologic factors that influence the land surface. This baseline information will help planners, refuge managers, and developers discuss issues and formulate best management practices to mitigate development impacts on the refuge. In consultation with the Eastern Region Geospatial Information Office, the dataset selected to be that baseline land cover source was the June-July 2005 National Agricultural Imagery Program (NAIP) 1-meter resolution orthoimagery of Maryland. This publicly available, statewide dataset provided imagery corresponding to the closest in time to the installation of a U.S. Geological Survey (USGS) Water Resources Discipline gaging station on the Little Blackwater River. It also captures land cover status just before major residential development occurs. This document describes the process used to create a database of impervious surfaces for the Little Blackwater watershed.

GEONEX: Land Monitoring From a New Generation of Geostationary Satellite Sensors

NASA Technical Reports Server (NTRS)

Nemani, Ramakrishna; Lyapustin, Alexei; Wang, Weile; Wang, Yujie; Hashimoto, Hirofumi; Li, Shuang; Ganguly, Sangram; Michaelis, Andrew; Higuchi, Atsushi; Takaneka, Hideaki;

GEONEX: Land monitoring from a new generation of geostationary satellite sensors

NASA Astrophysics Data System (ADS)

Nemani, R. R.; Lyapustin, A.; Wang, W.; Ganguly, S.; Wang, Y.; Michaelis, A.; Hashimoto, H.; Li, S.; Higuchi, A.; Huete, A. R.; Yeom, J. M.; camacho De Coca, F.; Lee, T. J.; Takenaka, H.

2017-12-01

The latest generation of geostationary satellites carry sensors such as ABI (Advanced Baseline Imager on GOES-16) and the AHI (Advanced Himawari Imager on Himawari) that closely mimic the spatial and spectral characteristics of Earth Observing System flagship MODIS for monitoring land surface conditions. More importantly they provide observations at 5-15 minute intervals. Such high frequency data offer exciting possibilities for producing robust estimates of land surface conditions by overcoming cloud cover, enabling studies of diurnally varying local-to-regional biosphere-atmosphere interactions, and operational decision-making in agriculture, forestry and disaster management. But the data come with challenges that need special attention. For instance, geostationary data feature changing sun angle at constant view for each pixel, which is reciprocal to sun-synchronous observations, and thus require careful adaptation of EOS algorithms. Our goal is to produce a set of land surface products from geostationary sensors by leveraging NASA's investments in EOS algorithms and in the data/compute facility NEX. The land surface variables of interest include atmospherically corrected surface reflectances, snow cover, vegetation indices and leaf area index (LAI)/fraction of photosynthetically absorbed radiation (FPAR), as well as land surface temperature and fires. In order to get ready to produce operational products over the US from GOES-16 starting 2018, we have utilized 18 months of data from Himawari AHI over Australia to test the production pipeline and the performance of various algorithms for our initial tests. The end-to-end processing pipeline consists of a suite of modules to (a) perform calibration and automatic georeference correction of the AHI L1b data, (b) adopt the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to produce surface spectral reflectances along with compositing schemes and QA, and (c) modify relevant EOS retrieval algorithms (e.g., LAI and FPAR, GPP, etc.) for subsequent science product generation. Initial evaluation of Himawari AHI products against standard MODIS products indicate general agreement, suggesting that data from geostationary sensors can augment low earth orbit (LEO) satellite observations.

Heterogeneity and scaling land-atmospheric water and energy fluxes in climate systems

NASA Technical Reports Server (NTRS)

Wood, Eric F.

1993-01-01

The effects of small-scale heterogeneity in land surface characteristics on the large-scale fluxes of water and energy in land-atmosphere system has become a central focus of many of the climatology research experiments. The acquisition of high resolution land surface data through remote sensing and intensive land-climatology field experiments (like HAPEX and FIFE) has provided data to investigate the interactions between microscale land-atmosphere interactions and macroscale models. One essential research question is how to account for the small scale heterogeneities and whether 'effective' parameters can be used in the macroscale models. To address this question of scaling, three modeling experiments were performed and are reviewed in the paper. The first is concerned with the aggregation of parameters and inputs for a terrestrial water and energy balance model. The second experiment analyzed the scaling behavior of hydrologic responses during rain events and between rain events. The third experiment compared the hydrologic responses from distributed models with a lumped model that uses spatially constant inputs and parameters. The results show that the patterns of small scale variations can be represented statistically if the scale is larger than a representative elementary area scale, which appears to be about 2 - 3 times the correlation length of the process. For natural catchments this appears to be about 1 - 2 sq km. The results concerning distributed versus lumped representations are more complicated. For conditions when the processes are nonlinear, then lumping results in biases; otherwise a one-dimensional model based on 'equivalent' parameters provides quite good results. Further research is needed to fully understand these conditions.

Global Impacts of Long-Term Land Cover Changes Within China's Densely Populated Rural Regions

NASA Astrophysics Data System (ADS)

Ellis, E. C.

2006-12-01

Long-term changes in land cover are usually investigated in terms of large-scale change processes such as urban expansion, deforestation and land conversion to agriculture. Yet China's densely populated agricultural regions, which cover more than 2 million square kilometers of Monsoon Asia, have been transformed profoundly over the past fifty years by fine-scale changes in land cover caused by unprecedented changes in population, technology and social conditions. Using a regional sampling and upscaling design coupled with high-resolution landscape change measurements at five field sites, we investigated long-term changes in land cover and ecological processes, circa 1945 to 2002, within and across China's densely populated agricultural regions. As expected, the construction of buildings and roads increased impervious surface area over time, but the total net increase was surprising, being similar in magnitude to the total current extent of China's cities. Agricultural land area declined over the same period, while tree cover increased, by about 10%, driven by tree planting and regrowth around new buildings, the introduction of perennial agriculture, improved forestry, and declines in annual crop cultivation. Though changes in impervious surface areas were closely related to changes in population density, long-term changes in agricultural land and tree cover were unrelated to populated density and required explanation by more complex models with strong regional and biophysical components. Moreover, most of these changes occurred primarily at fine spatial scales (< 30 m), under the threshold for conventional global and regional land cover change measurements. Given that these changes in built structures and vegetation cover have the potential to contribute substantially to regional and global changes in biogeochemistry, hydrology, and land-atmosphere interactions, future investigations of these changes and their impacts across Monsoon Asia would benefit from models that incorporate fine-scale landscape structure and its changes over time.

Hydrologic Remote Sensing and Land Surface Data Assimilation.

PubMed

Moradkhani, Hamid

2008-05-06

Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear updating rule and assumption of jointly normal distribution of errors in state variables and observation.

Incorporating human-water dynamics in a hyper-resolution land surface model

NASA Astrophysics Data System (ADS)

Vergopolan, N.; Chaney, N.; Wanders, N.; Sheffield, J.; Wood, E. F.

2017-12-01

The increasing demand for water, energy, and food is leading to unsustainable groundwater and surface water exploitation. As a result, the human interactions with the environment, through alteration of land and water resources dynamics, need to be reflected in hydrologic and land surface models (LSMs). Advancements in representing human-water dynamics still leave challenges related to the lack of water use data, water allocation algorithms, and modeling scales. This leads to an over-simplistic representation of human water use in large-scale models; this is in turn leads to an inability to capture extreme events signatures and to provide reliable information at stakeholder-level spatial scales. The emergence of hyper-resolution models allows one to address these challenges by simulating the hydrological processes and interactions with the human impacts at field scales. We integrated human-water dynamics into HydroBlocks - a hyper-resolution, field-scale resolving LSM. HydroBlocks explicitly solves the field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs); and its HRU-based model parallelization allows computationally efficient long-term simulations as well as ensemble predictions. The implemented human-water dynamics include groundwater and surface water abstraction to meet agricultural, domestic and industrial water demands. Furthermore, a supply-demand water allocation scheme based on relative costs helps to determine sectoral water use requirements and tradeoffs. A set of HydroBlocks simulations over the Midwest United States (daily, at 30-m spatial resolution for 30 years) are used to quantify the irrigation impacts on water availability. The model captures large reductions in total soil moisture and water table levels, as well as spatiotemporal changes in evapotranspiration and runoff peaks, with their intensity related to the adopted water management strategy. By incorporating human-water dynamics in a hyper-resolution LSM this work allows for progress on hydrological monitoring and predictions, as well as drought preparedness and water impact assessments at relevant decision-making scales.

Examining Environmental Gradients with satellite data in permafrost regions - the current state of the ESA GlobPermafrost initative

NASA Astrophysics Data System (ADS)

Grosse, G.; Bartsch, A.; Kääb, A.; Westermann, S.; Strozzi, T.; Wiesmann, A.; Duguay, C. R.; Seifert, F. M.; Obu, J.; Nitze, I.; Heim, B.; Haas, A.; Widhalm, B.

2017-12-01

Permafrost cannot be directly detected from space, but many surface features of permafrost terrains and typical periglacial landforms are observable with a variety of EO sensors ranging from very high to medium resolution at various wavelengths. In addition, landscape dynamics associated with permafrost changes and geophysical variables relevant for characterizing the state of permafrost, such as land surface temperature or freeze-thaw state can be observed with spaceborne Earth Observation. Suitable regions to examine environmental gradients across the Arctic have been defined in a community white paper (Bartsch et al. 2014, hdl:10013/epic.45648.d001). These transects have been revised and adjusted within the DUE GlobPermafrost initiative of the European Space Agency. The ESA DUE GlobPermafrost project develops, validates and implements Earth Observation (EO) products to support research communities and international organisations in their work on better understanding permafrost characteristics and dynamics. Prototype product cases will cover different aspects of permafrost by integrating in situ measurements of subsurface and surface properties, Earth Observation, and modelling to provide a better understanding of permafrost today. The project will extend local process and permafrost monitoring to broader spatial domains, support permafrost distribution modelling, and help to implement permafrost landscape and feature mapping in a GIS framework. It will also complement active layer and thermal observing networks. Both lowland (latitudinal) and mountain (altitudinal) permafrost issues are addressed. The status of the Permafrost Information System and first results will be presented. Prototypes of GlobPermafrost datasets include: Modelled mean annual ground temperature by use of land surface temperature and snow water equivalent from satellites Land surface characterization including shrub height, land cover and parameters related to surface roughness Trends from Landsat time-series over selected transects For selected sites: subsidence, ground fast lake ice, land surface features and rock glacier monitoring

Scalability of grid- and subbasin-based land surface modeling approaches for hydrologic simulations

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

Tesfa, Teklu K.; Ruby Leung, L.; Huang, Maoyi

2014-03-27

This paper investigates the relative merits of grid- and subbasin-based land surface modeling approaches for hydrologic simulations, with a focus on their scalability (i.e., abilities to perform consistently across a range of spatial resolutions) in simulating runoff generation. Simulations produced by the grid- and subbasin-based configurations of the Community Land Model (CLM) are compared at four spatial resolutions (0.125o, 0.25o, 0.5o and 1o) over the topographically diverse region of the U.S. Pacific Northwest. Using the 0.125o resolution simulation as the “reference”, statistical skill metrics are calculated and compared across simulations at 0.25o, 0.5o and 1o spatial resolutions of each modelingmore » approach at basin and topographic region levels. Results suggest significant scalability advantage for the subbasin-based approach compared to the grid-based approach for runoff generation. Basin level annual average relative errors of surface runoff at 0.25o, 0.5o, and 1o compared to 0.125o are 3%, 4%, and 6% for the subbasin-based configuration and 4%, 7%, and 11% for the grid-based configuration, respectively. The scalability advantages of the subbasin-based approach are more pronounced during winter/spring and over mountainous regions. The source of runoff scalability is found to be related to the scalability of major meteorological and land surface parameters of runoff generation. More specifically, the subbasin-based approach is more consistent across spatial scales than the grid-based approach in snowfall/rainfall partitioning, which is related to air temperature and surface elevation. Scalability of a topographic parameter used in the runoff parameterization also contributes to improved scalability of the rain driven saturated surface runoff component, particularly during winter. Hence this study demonstrates the importance of spatial structure for multi-scale modeling of hydrological processes, with implications to surface heat fluxes in coupled land-atmosphere modeling.« less

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.

Rosetta Lander - Philae: preparations for landing on comet 67P/Churyumov-Gerasimenko

NASA Astrophysics Data System (ADS)

Ulamec, S.; Biele, J.; Jurado, E.; Gaudon, P.; Geurts, K.

2013-12-01

Rosetta is a Cornerstone Mission of the ESA Horizon 2000 programme. It is going to rendezvous with comet 67P/Churyumov-Gerasimenko after a ten year cruise and will study both its nucleus and coma with an orbiting spacecraft as well as with a Lander, Philae, that has been designed to land softly on the comet nucleus. Aboard Philae, a payload consisting of ten scientific instruments will perform in-situ studies of the cometary material. Philae will be separated from the mother spacecraft from a dedicated delivery trajectory. It then descends, ballistically, to the surface of the comet, stabilized with an internal flywheel. At touch-down anchoring harpoons will be fired and a damping mechanism within the landing gear will provide the lander from re-bouncing. Currently the characteristics of the nucleus of the comet are hardly known. Mapping with the orbiter cameras (shape, slopes, surface roughness) and essential measurements like gravity field, state of rotation or outgassing parameters can only be performed after arrival of the main spacecraft, between May and October 2014. These data will be used for selecting a landing site and defining the detailed landing strategy. Landing is foreseen for November 2014 at a heliocentric distance of 3 AU. The paper describes the Rosetta Lander system and its payload, but emphasizes on the preparations for landing, the landing site selection process and the planned operational timeline.

Trajectory-based change detection for automated characterization of forest disturbance dynamics

Treesearch

Robert E. Kennedy; Warren B. Cohen; Todd A. Schroeder

2007-01-01

Satellite sensors are well suited to monitoring changes on the Earth's surface through provision of consistent and repeatable measurements at a spatial scale appropriate for many processes causing change on the land surface. Here, we describe and test a new conceptual approach to change detection of forests using a dense temporal stack of Landsat Thematic Mapper (...

ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation

NASA Astrophysics Data System (ADS)

Guimberteau, Matthieu; Zhu, Dan; Maignan, Fabienne; Huang, Ye; Yue, Chao; Dantec-Nédélec, Sarah; Ottlé, Catherine; Jornet-Puig, Albert; Bastos, Ana; Laurent, Pierre; Goll, Daniel; Bowring, Simon; Chang, Jinfeng; Guenet, Bertrand; Tifafi, Marwa; Peng, Shushi; Krinner, Gerhard; Ducharne, Agnès; Wang, Fuxing; Wang, Tao; Wang, Xuhui; Wang, Yilong; Yin, Zun; Lauerwald, Ronny; Joetzjer, Emilie; Qiu, Chunjing; Kim, Hyungjun; Ciais, Philippe

2018-01-01

The high-latitude regions of the Northern Hemisphere are a nexus for the interaction between land surface physical properties and their exchange of carbon and energy with the atmosphere. At these latitudes, two carbon pools of planetary significance - those of the permanently frozen soils (permafrost), and of the great expanse of boreal forest - are vulnerable to destabilization in the face of currently observed climatic warming, the speed and intensity of which are expected to increase with time. Improved projections of future Arctic and boreal ecosystem transformation require improved land surface models that integrate processes specific to these cold biomes. To this end, this study lays out relevant new parameterizations in the ORCHIDEE-MICT land surface model. These describe the interactions between soil carbon, soil temperature and hydrology, and their resulting feedbacks on water and CO2 fluxes, in addition to a recently developed fire module. Outputs from ORCHIDEE-MICT, when forced by two climate input datasets, are extensively evaluated against (i) temperature gradients between the atmosphere and deep soils, (ii) the hydrological components comprising the water balance of the largest high-latitude basins, and (iii) CO2 flux and carbon stock observations. The model performance is good with respect to empirical data, despite a simulated excessive plant water stress and a positive land surface temperature bias. In addition, acute model sensitivity to the choice of input forcing data suggests that the calibration of model parameters is strongly forcing-dependent. Overall, we suggest that this new model design is at the forefront of current efforts to reliably estimate future perturbations to the high-latitude terrestrial environment.

Calibration, navigation, and registration of MAMS data for FIFE

NASA Technical Reports Server (NTRS)

Jedlovec, G. J.; Atkinson, R. J.

1993-01-01

The International Satellite Land Surface Climatology Project (ISLSCP) was conducted to study the interaction of the atmosphere with the land surface and the research problems associated with the interpretation of satellite data over the Earth's land surface. The experimental objectives of the First ISLSCP Field Experiment (FIFE) were the simultaneous acquisition of satellite, atmospheric, and surface data and to use these data to understand the processes controlling energy/mass exchange at the surface. The experiment site is a 15 x 15 km area southeast of Manhattan, Kansas, intersected by Interstate 70 and Kansas highway 177. The Konza Prairie portion is 5 x 5 km and is a controlled experiment site consisting primarily of native tall grass prairie vegetation. The remainder of the site is grazing and farm land with trees along creek beds that are scattered over the area. Airborne multispectral imagery from the Multispectral Atmospheric Mapping Sensor (MAMS) was collected over this region on two days during Intensive Field Campaign-1 (1FC-1) to study the time and space variability of remotely-sensed geophysical parameters. These datasets consist of multiple overflights covering about a 60-min period during late morning on June 4, 1987 and shortly after dark on the following day. Image data from each overpass were calibrated and Earth located with respect to each other using aircraft inertial navigation system parameters and ground control points. These were the first MAMS flights made with 10-bit thermal data.

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.

Characterization of Air and Ground Temperature Relationships within the CMIP5 Historical and Future Climate Simulations

NASA Astrophysics Data System (ADS)

García-García, A.; Cuesta-Valero, F. J.; Beltrami, H.; Smerdon, J. E.

2017-12-01

The relationships between air and ground surface temperatures across North America are examined in the historical and future projection simulations from 32 General Circulation Models (GCMs) included in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The covariability between surface air (2 m) and ground surface temperatures (10 cm) is affected by simulated snow cover, vegetation cover and precipitation through changes in soil moisture at the surface. At high latitudes, the differences between air and ground surface temperatures, for all CMIP5 simulations, are related to the insulating effect of snow cover and soil freezing phenomena. At low latitudes, the differences between the two temperatures, for the majority of simulations, are inversely proportional to leaf area index and precipitation, likely due to induced-changes in latent and sensible heat fluxes at the ground surface. Our results show that the transport of energy across the air-ground interface differs from observations and among GCM simulations, by amounts that depend on the components of the land-surface models that they include. The large variability among GCMs and the marked dependency of the results on the choice of the land-surface model, illustrate the need for improving the representation of processes controlling the coupling of the lower atmosphere and the land surface in GCMs as a means of reducing the variability in their representation of weather and climate phenomena, with potentially important implications for positive climate feedbacks such as permafrost and soil carbon stability.

High-Resolution Specification of the Land and Ocean Surface for Improving Regional Mesoscale Model Predictions

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Lazarus, Steven M.; Splitt, Michael E.; Crosson, William L.; Lapenta, William M.; Jedlovec, Gary J.; Peters-Lidard, Christa D.

2008-01-01

The exchange of energy and moisture between the Earth's surface and the atmospheric boundary layer plays a critical role in many meteorological processes. High-resolution, accurate representations of surface properties such as sea-surface temperature (SST), soil temperature and moisture content, ground fluxes, and vegetation are necessary to better understand the Earth-atmosphere interactions and improve numerical predictions of sensible weather. The NASA Short-term Prediction Research and Transition (SPoRT) Center has been conducting separate studies to examine the impacts of high-resolution land-surface initialization data from the Goddard Space Flight Center Land Information System (LIS) on subsequent WRF forecasts, as well as the influence of initializing WRF with SST composites derived from the MODIS instrument. This current project addresses the combined impacts of using high-resolution lower boundary data over both land (LIS data) and water (MODIS SSTs) on the subsequent daily WRF forecasts over Florida during May 2004. For this experiment, the WRF model is configured to run on a nested domain with 9- km and 3-kin grid spacing, centered on the Florida peninsula and adjacent coastal waters of the Gulf of Mexico and Atlantic Ocean. A control configuration of WRF is established to take all initial condition data from the NCEP Eta model. Meanwhile, two WRF experimental runs are configured to use high-resolution initialization data from (1) LIS land-surface data only, and (2) a combination of LIS data and high-resolution MODIS SST composites. The experiment involves running 24-hour simulations of the control WRF configuration, the MS-initialized WRF, and the LIS+MODIS-initialized WRF daily for the entire month of May 2004. All atmospheric data for initial and boundary conditions for the Control, LIS, and LIS+MODIS runs come from the NCEP Eta model on a 40-km grid. Verification statistics are generated at land surface observation sites and buoys, and the impacts of the high-resolution lower boundary data on the development and evolution of mesoscale circulations such as sea and land breezes are examined, This paper will present the results of these WRF modeling experiments using LIS and MODIS lower boundary datasets over the Florida peninsula during May 2004.

Comparing SMAP to Macro-scale and Hyper-resolution Land Surface Models over Continental U. S.

NASA Astrophysics Data System (ADS)

Pan, Ming; Cai, Xitian; Chaney, Nathaniel; Wood, Eric

2016-04-01

SMAP sensors collect moisture information in top soil at the spatial resolution of ~40 km (radiometer) and ~1 to 3 km (radar, before its failure in July 2015). Such information is extremely valuable for understanding various terrestrial hydrologic processes and their implications on human life. At the same time, soil moisture is a joint consequence of numerous physical processes (precipitation, temperature, radiation, topography, crop/vegetation dynamics, soil properties, etc.) that happen at a wide range of scales from tens of kilometers down to tens of meters. Therefore, a full and thorough analysis/exploration of SMAP data products calls for investigations at multiple spatial scales - from regional, to catchment, and to field scales. Here we first compare the SMAP retrievals to the Variable Infiltration Capacity (VIC) macro-scale land surface model simulations over the continental U. S. region at 3 km resolution. The forcing inputs to the model are merged/downscaled from a suite of best available data products including the NLDAS-2 forcing, Stage IV and Stage II precipitation, GOES Surface and Insolation Products, and fine elevation data. The near real time VIC simulation is intended to provide a source of large scale comparisons at the active sensor resolution. Beyond the VIC model scale, we perform comparisons at 30 m resolution against the recently developed HydroBloks hyper-resolution land surface model over several densely gauged USDA experimental watersheds. Comparisons are also made against in-situ point-scale observations from various SMAP Cal/Val and field campaign sites.

Advancements in medium and high resolution Earth observation for land-surface imaging: Evolutions, future trends and contributions to sustainable development

NASA Astrophysics Data System (ADS)

Ouma, Yashon O.

2016-01-01

Technologies for imaging the surface of the Earth, through satellite based Earth observations (EO) have enormously evolved over the past 50 years. The trends are likely to evolve further as the user community increases and their awareness and demands for EO data also increases. In this review paper, a development trend on EO imaging systems is presented with the objective of deriving the evolving patterns for the EO user community. From the review and analysis of medium-to-high resolution EO-based land-surface sensor missions, it is observed that there is a predictive pattern in the EO evolution trends such that every 10-15 years, more sophisticated EO imaging systems with application specific capabilities are seen to emerge. Such new systems, as determined in this review, are likely to comprise of agile and small payload-mass EO land surface imaging satellites with the ability for high velocity data transmission and huge volumes of spatial, spectral, temporal and radiometric resolution data. This availability of data will magnify the phenomenon of ;Big Data; in Earth observation. Because of the ;Big Data; issue, new computing and processing platforms such as telegeoprocessing and grid-computing are expected to be incorporated in EO data processing and distribution networks. In general, it is observed that the demand for EO is growing exponentially as the application and cost-benefits are being recognized in support of resource management.

Evaluation of different field methods for measuring soil water infiltration

NASA Astrophysics Data System (ADS)

Pla-Sentís, Ildefonso; Fonseca, Francisco

2010-05-01

Soil infiltrability, together with rainfall characteristics, is the most important hydrological parameter for the evaluation and diagnosis of the soil water balance and soil moisture regime. Those balances and regimes are the main regulating factors of the on site water supply to plants and other soil organisms and of other important processes like runoff, surface and mass erosion, drainage, etc, affecting sedimentation, flooding, soil and water pollution, water supply for different purposes (population, agriculture, industries, hydroelectricity), etc. Therefore the direct measurement of water infiltration rates or its indirect deduction from other soil characteristics or properties has become indispensable for the evaluation and modelling of the previously mentioned processes. Indirect deductions from other soil characteristics measured under laboratory conditions in the same soils, or in other soils, through the so called "pedo-transfer" functions, have demonstrated to be of limited value in most of the cases. Direct "in situ" field evaluations have to be preferred in any case. In this contribution we present the results of past experiences in the measurement of soil water infiltration rates in many different soils and land conditions, and their use for deducing soil water balances under variable climates. There are also presented and discussed recent results obtained in comparing different methods, using double and single ring infiltrometers, rainfall simulators, and disc permeameters, of different sizes, in soils with very contrasting surface and profile characteristics and conditions, including stony soils and very sloping lands. It is concluded that there are not methods universally applicable to any soil and land condition, and that in many cases the results are significantly influenced by the way we use a particular method or instrument, and by the alterations in the soil conditions by the land management, but also due to the manipulation of the surface soil before and during the measurement. Due to the commonly found high variability, natural or induced by land management, of the soil surface and subsurface hydrological properties, and to the limitations imposed by the requirements of water for the measurements, there is proposed a simple and handy method, which do not use high volumes of water, adaptable to very different soil and land conditions, and that allow many repeated measurements with acceptable accuracy for most of the purposes. References Pla, I., 1997. A soil water balance model for monitoring soil erosion processes and effects on steep lands in the tropics. Soil Technology. 11(1):17-30. Elsevier Pla, I., 2006. Hydrological approach for assessing desertification processes in the Mediterranean region. In W.G. Kepner et al. (Editors), Desertification in the Mediterranean Region. A Security Issue. 579-600 Springer. Heidelberg (Germany) Reynolds W.D., B.T. Bowman, R.R. Brunke, C.F. Drury and C.S. Tan. 2000. Comparison of Tension Infiltrometer, Pressure Infiltrometer, and Soil Core Estimates of Saturated Hydraulic Conductivity . Soil Science Society of America Journal 64:478-484 Segal, E., S.A.Bradford, P. Shouse; N. Lazarovich, and D. Corwin. 2008. Integration of Hard and Soft Data to Characterize Field-Scale Hydraulic Properties for Flow and Transport Studies. Vadose Zone J 7:878-889 Young, E. 1991. Infiltration measurements, a review. Hydrological processes 5: 309-320.

MODIS land data at the EROS data center DAAC

USGS Publications Warehouse

Jenkerson, Calli B.; Reed, B.C.

2001-01-01

The US Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center (EDC) in Sioux Falls, SD, USA, is the primary national archive for land processes data and one of the National Aeronautics and Space Administration's (NASA) Distributed Active Archive Centers (DAAC) for the Earth Observing System (EOS). One of EDC's functions as a DAAC is the archival and distribution of Moderate Resolution Spectroradiometer (MODIS) Land Data collected from the Earth Observing System (EOS) satellite Terra. More than 500,000 publicly available MODIS land data granules totaling 25 Terabytes (Tb) are currently stored in the EDC archive. This collection is managed, archived, and distributed by EOS Data and Information System (EOSDIS) Core System (ECS) at EDC. EDC User Services support the use of MODIS Land data, which include land surface reflectance/albedo, temperature/emissivity, vegetation characteristics, and land cover, by responding to user inquiries, constructing user information sites on the EDC web page, and presenting MODIS materials worldwide.

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 ...

Applications of Future NASA Decadal Missions for Observing Earth's Land and Water Processes

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey C.; Hook, Simon; Brown, Molly E.; Tzortziou, Maria A.; Carroll, Mark; Escobar, Vanessa M.; Omar, Ali

2013-01-01

Misson Objective: To collect altimetry data of the Earth's surface optimized to measure ice sheet elevation change and sea ice thickness, while also generating an estimate of global vegetation biomass.

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.

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.

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.

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Kumar, Sujay V.; Santanello, Joseph A., Jr.; Reichle, Rolf H.

2009-01-01

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters- Lidard et al.,2007) is a flexible land surface modeling framework that has been developed 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. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected ase co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations. In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins,". As described in Kumar et al., 2007, and demonstrated in Case et al., 2008, and Santanello et al., 2009, LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling the enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation as described in Peters-Lidard et al. (2008) and Santanello et al. (2007), who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs. LIS has also recently been demonstrated for multi-model data assimilation (Kumar et al., 2008) using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature. Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation. Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeoroogical modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems.

Sensitivity of Precipitation in Coupled Land-Atmosphere Models

NASA Technical Reports Server (NTRS)

Neelin, David; Zeng, N.; Suarez, M.; Koster, R.

2004-01-01

The project objective was to understand mechanisms by which atmosphere-land-ocean processes impact precipitation in the mean climate and interannual variations, focusing on tropical and subtropical regions. A combination of modeling tools was used: an intermediate complexity land-atmosphere model developed at UCLA known as the QTCM and the NASA Seasonal-to-Interannual Prediction Program general circulation model (NSIPP GCM). The intermediate complexity model was used to develop hypotheses regarding the physical mechanisms and theory for the interplay of large-scale dynamics, convective heating, cloud radiative effects and land surface feedbacks. The theoretical developments were to be confronted with diagnostics from the more complex GCM to validate or modify the theory.

Land-use and land-cover scenarios and spatial modeling at the regional scale

USGS Publications Warehouse

Sohl, Terry L.; Sleeter, Benjamin M.

2012-01-01

Land-use and land-cover (LULC) change has altered a large part of the earth's surface. Scenarios of potential future LULC change are required in order to better manage potential impacts on biodiversity, carbon fluxes, climate change, hydrology, and many other ecological processes. The U.S. Geological Survey is analyzing potential future LULC change in the United States, using an approach based on scenario construction and spatially explicit modeling. Similar modeling techniques are being used to produce historical LULC maps from 1940 to present. With the combination of backcast and forecast LULC data, the USGS is providing consistent LULC data for historical, current, and future time frames to support a variety of research applications.

The role of groundwater in hydrological processes and memory

NASA Astrophysics Data System (ADS)

Lo, Min-Hui

The interactions between soil moisture and groundwater play important roles in controlling Earth's climate, by changing the terrestrial water cycle. However, most contemporary land surface models (LSMs) used for climate modeling lack any representation of groundwater aquifers. In this dissertation, the effects of water table dynamics on the National Center for Atmospheric Research (NCAR) Community Land Model (CLM) and Community Atmosphere Model (CAM) hydrology and land-atmosphere simulations are investigated. First, a simple, lumped unconfined aquifer model is incorporated into the CLM, in which the water table is interactively coupled to the soil moisture through groundwater recharge fluxes. The recent availability of GRACE water storage data provides a unique opportunity to constrain LSMs simulations of terrestrial hydrology. A multi-objective calibration framework using GRACE and streamflow data is developed. This approach improves parameter estimation and reduces the uncertainty of water table simulations in the CLM. Next, experiments are conducted with the off-line CLM to explore the effects of groundwater on land surface memory. Results show that feedbacks of groundwater on land surface memory can be positive, negative, or neutral depending on water table dynamics. The CAM-CLM is further utilized to investigate the effects of water table dynamics on spatial-temporal variations of precipitation. Results indicate that groundwater can increase short-term (seasonal) and long-term (interannual) memory of precipitation for some regions with suitable groundwater table depth. Finally, lower tropospheric water vapor is increased due to the presence of groundwater in the model. However, the impact of groundwater on the spatial distribution of precipitation is not globally homogeneous. In the boreal summer, tropical land regions show a positive (negative) anomaly over the Northern (Southern) Hemisphere. The increased tropical precipitation follows the climatology of the convective zone rather than that of evapotranspiration. In contrast, evapotranspiration is the major contribution to the increased precipitation in the transition climatic zone (e.g., Central North America), where the land and atmosphere are strongly coupled. This dissertation reveals the highly nonlinear responses of precipitation and soil moisture to the groundwater representation in the model, and also underscores the importance of subsurface hydrological memory processes in the climate system.

A Catchment-Based Approach to Modeling Land Surface Processes in a GCM. Part 2; Parameter Estimation and Model Demonstration

NASA Technical Reports Server (NTRS)

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

2000-01-01

The viability of a new catchment-based land surface model (LSM) developed for use with general circulation models is demonstrated. First, simple empirical functions -- tractable enough for operational use in the LSM -- are established that faithfully capture the control of topography on the subgrid variability of soil moisture and the surface water budget, as predicted by theory. Next, the full LSM is evaluated offline. Using forcing and validation datasets developed for PILPS Phase 2c, the minimally calibrated model is shown to reproduce observed evaporation and runoff fluxes successfully in the Red-Arkansas River Basin. A complementary idealized study that employs the range of topographic variability seen over North America demonstrates that the simulated surface water budget does vary strongly with topography, which can, by itself, induce variations in annual evaporation as high as 20%.

Towards a high resolution, integrated hydrology model of North America: Diagnosis of feedbacks between groundwater and land energy fluxes at continental scales.

NASA Astrophysics Data System (ADS)

Maxwell, Reed; Condon, Laura

2016-04-01

Recent studies demonstrate feedbacks between groundwater dynamics, overland flow, land surface and vegetation processes, and atmospheric boundary layer development that significantly affect local and regional climate across a range of climatic conditions. Furthermore, the type and distribution of vegetation cover alters land-atmosphere water and energy fluxes, as well as runoff generation and overland flow processes. These interactions can result in significant feedbacks on local and regional climate. In mountainous regions, recent research has shown that spatial and temporal variability in annual evapotranspiration, and thus water budgets, is strongly dependent on lateral groundwater flow; however, the full effects of these feedbacks across varied terrain (e.g. from plains to mountains) are not well understood. Here, we present a high-resolution, integrated hydrology model that covers much of continental North America and encompasses the Mississippi and Colorado watersheds. The model is run in a fully-transient manner at hourly temporal resolution incorporating fully-coupled land energy states and fluxes with integrated surface and subsurface hydrology. Connections are seen between hydrologic variables (such as water table depth) and land energy fluxes (such as latent heat) and spatial and temporal scaling is shown to span many orders of magnitude. Model results suggest that partitioning of plant transpiration to bare soil evaporation is a function of water table depth and later groundwater flow. Using these transient simulations as a proof of concept, we present a vision for future integrated simulation capabilities.

LAI is the major cause of divergence in CO2 fertilization effect in land surface models

NASA Astrophysics Data System (ADS)

Li, Q.; Luo, Y.; Lu, X.; Wang, Y.; Huang, X.; Lin, G., Sr.

2017-12-01

Concentration-carbon feedback (β), also called CO2 fertilization effect, is an important feedback between terrestrial ecosystems and atmosphere to alleviate global climate change. However, models participating in C4MIP and CMIP5 predicted diverse CO2 fertilization effects under future CO2 inceasing scenarios. Hence identifing the key processes dominating the divergence of β in land surface models is of significance. We calculated CO2 fertilization effects from leaf level, canopy gross productivity level, net ecosystem productivity level and ecosystem carbon stock level in Community Atmosphere Biosphere Land Exchange (CABLE) model. Our results identified LAI is the key factor dominating the divergence of β among C3 plants in CABLE model. Saturation of the ecosystem productivity to increasing CO2 is not only regulated by leaf-level response, but also the response of LAI to increasing CO2. The greatest variation among C3 plants at ecosystem level suggests that other processes such as different allocation patterns and soil carbon dynamics of various vegetation types are also responsible for the divergence. Our results indicate that processes regarding to LAI need to be better calibrated according to experiments and observations in order to better represent the response of ecosystem productivity to increasing CO2.

Evaluation Of The MODIS-VIIRS Land Surface Reflectance Fundamental Climate Data Record.

NASA Astrophysics Data System (ADS)

Roger, J. C.; Vermote, E.; Skakun, S.; Murphy, E.; Holben, B. N.; Justice, C. O.

2016-12-01

The land surface reflectance is a fundamental climate data record at the basis of the derivation of other climate data records (Albedo, LAI/Fpar, Vegetation indices) and has been recognized as a key parameter in the understanding of the land-surface-climate processes. Here, we present the validation of the Land surface reflectance used for MODIS and VIIRS data. This methodology uses the 6SV Code and data from the AERONET network. The first part was to define a protocol to use the AERONET data. To correctly take into account the aerosol model, we used the aerosol microphysical properties provided by the AERONET network including size-distribution (%Cf, %Cc, rf, rc, σr, σc), complex refractive indices and sphericity. Over the 670 available AERONET sites, we selected 230 sites with sufficient data. To be useful for validation, the aerosol model should be readily available anytime, which is rarely the case. We then used regressions for each microphysical parameter using the aerosol optical thickness at 440nm and the Angström coefficient as parameters. Comparisons with the AERONET dataset give good APU (Accuracy-Precision-Uncertainties) for each parameter. The second part of the study relies on the theoretical land surface retrieval. We generated TOA synthetic data using aerosol models from AERONET and determined APU on the surface reflectance retrieval while applying the MODIS and VIRRS Atmospheric correction software. Over 250 AERONET sites, the global uncertainties are for MODIS band 1 (red) is always lower than 0.0015 (when surface reflectance is > 0.04). This very good result shows the validity of our reference. Then, we used this reference for validating the MODIS and VIIRS surface reflectance products. The overall accuracy clearly reaches specifications. Finally, we will present an error budget of the surface reflectance retrieval. Indeed, to better understand how to improve the methodology, we defined an exhaustive error budget. We included all inputs i.e. sensor, calibration, aerosol properties, atmospheric conditions… This latter work provides a lot of information, such as the aerosol optical thickness obviously drives the uncertainties of the retrieval, the absorption and the volume concentration of the fine aerosol mode have an important impact as well…

Visualizing Airborne and Satellite Imagery

NASA Technical Reports Server (NTRS)

Bierwirth, Victoria A.

2011-01-01

Remote sensing is a process able to provide information about Earth to better understand Earth's processes and assist in monitoring Earth's resources. The Cloud Absorption Radiometer (CAR) is one remote sensing instrument dedicated to the cause of collecting data on anthropogenic influences on Earth as well as assisting scientists in understanding land-surface and atmospheric interactions. Landsat is a satellite program dedicated to collecting repetitive coverage of the continental Earth surfaces in seven regions of the electromagnetic spectrum. Combining these two aircraft and satellite remote sensing instruments will provide a detailed and comprehensive data collection able to provide influential information and improve predictions of changes in the future. This project acquired, interpreted, and created composite images from satellite data acquired from Landsat 4-5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper plus (ETM+). Landsat images were processed for areas covered by CAR during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCT AS), Cloud and Land Surface Interaction Campaign (CLASIC), Intercontinental Chemical Transport Experiment-Phase B (INTEXB), and Southern African Regional Science Initiative (SAFARI) 2000 missions. The acquisition of Landsat data will provide supplemental information to assist in visualizing and interpreting airborne and satellite imagery.

Heat Capacity Mapping Mission (HCMM) thermal surface water mapping and its correlation to LANDSAT. [Lake Anna, Virginia

NASA Technical Reports Server (NTRS)

Colvocoresses, A. P. (Principal Investigator)

1980-01-01

Graphics are presented which show HCMM mapped water-surface temperature in Lake Anna, a 13,000 dendrically-shaped lake which provides cooling for a nuclear power plant in Virginia. The HCMM digital data, produced by NASA were processed by NOAA/NESS into image and line-printer form. A LANDSAT image of the lake illustrates the relationship between MSS band 7 data and the HCMM data as processed by the NASA image processing facility which transforms the data to the same distortion-free hotline oblique Mercator projection. Spatial correlation of the two images is relatively simple by either digital or analog means and the HCMM image has a potential accuracy approaching the 80 m of the original LANDSAT data. While it is difficult to get readings that are not diluted by radiation from cooler adjacent land areas in narrow portions of the lake, digital data indicated by the line-printer display five different temperatures for open-water areas. Where the water surface response was not diluted by land areas, the temperature difference recorded by HCMM corresponds to in situ readings with rsme on the order of 1 C.

Antarctic Temperature Extremes from MODIS Land Surface Temperatures: New Processing Methods Reveal Data Quality Puzzles

NASA Astrophysics Data System (ADS)

Grant, G.; Gallaher, D. W.

2017-12-01

New methods for processing massive remotely sensed datasets are used to evaluate Antarctic land surface temperature (LST) extremes. Data from the MODIS/Terra sensor (Collection 6) provides a twice-daily look at Antarctic LSTs over a 17 year period, at a higher spatiotemporal resolution than past studies. Using a data condensation process that creates databases of anomalous values, our processes create statistical images of Antarctic LSTs. In general, the results find few significant trends in extremes; however, they do reveal a puzzling picture of inconsistent cloud detection and possible systemic errors, perhaps due to viewing geometry. Cloud discrimination shows a distinct jump in clear-sky detections starting in 2011, and LSTs around the South Pole exhibit a circular cooling pattern, which may also be related to cloud contamination. Possible root causes are discussed. Ongoing investigations seek to determine whether the results are a natural phenomenon or, as seems likely, the results of sensor degradation or processing artefacts. If the unusual LST patterns or cloud detection discontinuities are natural, they point to new, interesting processes on the Antarctic continent. If the data artefacts are artificial, MODIS LST users should be alerted to the potential issues.

Microphysics in Multi-scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2012-01-01

Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.

Urban Expansion Modeling Approach Based on Multi-Agent System and Cellular Automata

NASA Astrophysics Data System (ADS)

Zeng, Y. N.; Yu, M. M.; Li, S. N.

2018-04-01

Urban expansion is a land-use change process that transforms non-urban land into urban land. This process results in the loss of natural vegetation and increase in impervious surfaces. Urban expansion also alters the hydrologic cycling, atmospheric circulation, and nutrient cycling processes and generates enormous environmental and social impacts. Urban expansion monitoring and modeling are crucial to understanding urban expansion process, mechanism, and its environmental impacts, and predicting urban expansion in future scenarios. Therefore, it is important to study urban expansion monitoring and modeling approaches. We proposed to simulate urban expansion by combining CA and MAS model. The proposed urban expansion model based on MSA and CA was applied to a case study area of Changsha-Zhuzhou-Xiangtan urban agglomeration, China. The results show that this model can capture urban expansion with good adaptability. The Kappa coefficient of the simulation results is 0.75, which indicated that the combination of MAS and CA offered the better simulation result.

Human Mars Landing Site and Impacts on Mars Surface Operations

NASA Technical Reports Server (NTRS)

Bussey, Ben; Hoffman, Stephen J.

2016-01-01

NASA has begun a process to identify and discuss candidate locations where humans could land, live and work on the Martian surface. These locations are referred to as Exploration Zones (EZs). Given current mission concepts, an EZ is a collection of Regions of Interest (ROIs) that are located within approximately 100 kilometers of a centralized landing site. ROIs are areas that are relevant for scientific investigation and/or development/maturation of capabilities and resources necessary for a sustainable human presence. The EZ also contains a landing site and a habitation site that will be used by multiple human crews during missions to explore and utilize the ROIs within the EZ. These candidate EZs will be used by NASA as part of a multi-year process of determining where and how humans could explore Mars. In the near term this process includes: (a) identifying locations that would maximize the potential science return from future human exploration missions, (b) identifying locations with the potential for resources required to support humans, (c) developing concepts and engineering systems needed by future human crews to conduct operations within an EZ, and (d) identifying key characteristics of the proposed candidate EZs that cannot be evaluated using existing data sets, thus helping to define precursor measurements needed in advance of human missions. Existing and future robotic spacecraft will be tasked to gather data from specific Mars surface sites within the representative EZs to support these NASA activities. The proposed paper will describe NASA's initial steps for identifying and evaluating candidate EZs and ROIs. This includes plans for the "First Landing Site/Exploration Zone Workshop for Human Missions to the Surface of Mars" to be held in October 2015 at which proposals for EZs and ROIs will be presented and discussed. It will also include a discussion of how these considerations are (or will be) taken into account as future robotic Mars missions are defined and developed. One or more representative EZs, drawn from similar previous studies involving Mars sites, will be used in the proposed paper to illustrate the process NASA envisions for gathering additional data from robotic precursor missions to assist in making a final selection of an EZ for human crews as well as the steps likely to occur during the buildup of a habitation site. Examples of the systems and operations likely to be used by human crews, assisted by robotic vehicles, to explore the scientific ROIs as well as developing the resource ROIs within the example EZs will be discussed.

Enhancing Europa surface characterization with ice penetrating radar: A Comparative study in Antarctica

NASA Astrophysics Data System (ADS)

Curra, C.; Arnold, E.; Karwoski, B.; Grima, C.; Schroeder, D. M.; Young, D. A.; Blankenship, D. D.

2013-12-01

The shape and composition of the surface of Europa result from multiple processes, most of them involving direct and indirect interactions between the liquid and solid phases of its outer water layer. The surface ice composition is likely to reflect the material exchanged with the sub-glacial ocean and potentially holds signatures of organic compounds that could demonstrate the ability of the icy moon to sustain life. Therefore, the most likely targets for in-situ landing missions are primarily located in complex terrains disrupted by exchange mechanisms with the ocean/lenses of sub-glacial liquid water. Any landing site selection process to ensure a safe delivery of a future lander, will then have to confidently characterize its surface roughness. We evaluate the capability of an ice-penetrating radar to characterize the roughness using a statistical method applied to the surface echoes. Our approach is to compare radar-derived data with nadir-imagery and laser altimetry simultaneously acquired on an airborne platform over Marie Byrd Land, West Antarctica, during the 2012-13 GIMBLE survey. The radar is the High-Capability Radar Sounder 2 (HiCARS 2, 60 MHz) system operated by the University of Texas Institute for Geophysics (UTIG), with specifications similar to the Ice Penetrating Radar (IPR) of the Europa Clipper project. Surface textures as seen by simultaneously collected nadir imagery are manually classified, allowing individual contrast stretching for better identification. We identified crevasse fields, blue ice patches, and families of wind-blown patterns. Homogeneity/heterogeneity of the textures has also been an important classification criterion. The various textures are geolocated and compared to the evolution and amplitude of laser-derived and radar-derived roughness. Similarities and discrepancies between these three datasets are illustrated and analyzed to qualitatively constrain radar sensitivity to the surface textures. The result allows for a first insight and discussion into how to interpret statistically-inverted radar data from an icy planetary surface.

Video Guidance, Landing, and Imaging system (VGLIS) for space missions

NASA Technical Reports Server (NTRS)

Schappell, R. T.; Knickerbocker, R. L.; Tietz, J. C.; Grant, C.; Flemming, J. C.

1975-01-01

The feasibility of an autonomous video guidance system that is capable of observing a planetary surface during terminal descent and selecting the most acceptable landing site was demonstrated. The system was breadboarded and "flown" on a physical simulator consisting of a control panel and monitor, a dynamic simulator, and a PDP-9 computer. The breadboard VGLIS consisted of an image dissector camera and the appropriate processing logic. Results are reported.

Development of a Land Use Database for the Little Blackwater Watershed, Dorchester County, Maryland

USGS Publications Warehouse

Milheim, Lesley E.; Jones, John W.; Barlow, Roger A.

2007-01-01

Many agricultural and forested areas in proximity to National Wildlife Refuges (NWR) are under increasing economic pressure to develop lands for commercial or residential development. The upper portion of the Little Blackwater River watershed - a 27 square mile area within largely low-lying Dorchester County, Maryland, on the eastern shore of the Chesapeake Bay - is important to the U.S. Fish and Wildlife Service (USFWS) because it flows toward the Blackwater National Wildlife Refuge (BNWR), and developmental impacts of areas upstream from the BNWR are unknown. One of the primary concerns for the refuge is how storm-water runoff may affect living resources downstream. The Egypt Road project (fig. 1), for which approximately 600 residential units have been approved, has the potential to markedly change the land use and land cover on the west bank of the Little Blackwater River. In an effort to limit anticipated impacts, the Maryland Department of Natural Resources (Maryland DNR) recently decided to purchase some of the lands previously slated for development. Local topography, a high water table (typically 1 foot or less below the land surface), and hydric soils present a challenge for the best management of storm-water flow from developed surfaces. A spatial data coordination group was formed by the Dorchester County Soil and Conservation District to collect data to aid decisionmakers in watershed management and on the possible impacts of development on this watershed. Determination of streamflow combined with land cover and impervious-surface baselines will allow linking of hydrologic and geologic factors that influence the land surface. This baseline information will help planners, refuge managers, and developers discuss issues and formulate best management practices to mitigate development impacts on the refuge. In consultation with the Eastern Region Geospatial Information Office, the dataset selected to be that baseline land cover source was the June-July 2005 National Agricultural Imagery Program (NAIP) 1-meter resolution orthoimagery of Maryland. This publicly available, statewide dataset provided imagery corresponding to the closest in time to the installation of a U.S. Geological Survey (USGS) Water Resources Discipline gaging station on the Little Blackwater River. It also captures land cover status just before major residential development occurs. This document describes the process used to create a land use database for the Little Blackwater watershed.

APPLICATION OF A NEW LAND-SURFACE, DRY DEPOSITION, AND PBL MODEL IN THE MODELS-3 COMMUNITY MULTI-SCALE AIR QUALITY (CMAQ) MODEL SYSTEM

EPA Science Inventory

Like most air quality modeling systems, CMAQ divides the treatment of meteorological and chemical/transport processes into separate models run sequentially. A potential drawback to this approach is that it creates the illusion that these processes are minimally interdependent an...

Reactor Meltdown: Critical Zone Processes In Siliciclastics Unlikely To Be Directly Transferable To Carbonates

NASA Astrophysics Data System (ADS)

Gulley, J. D.; Cohen, M. J.; Kramer, M. G.; Martin, J. B.; Graham, W. D.

2013-12-01

Carbonate terrains cover 20% of Earth's ice-free land and are modified through interactions between rocks, water and biota that couple ecosystems processes to weathering reactions within the critical zone. Weathering in carbonate systems differs from the Critical Zone Reactor model developed for siliciclastic systems because reactions in siliciclastic critical zones largely consist of incongruent weathering (e.g., feldspar to secondary clay minerals) that typically occur in the soil zone within a few meters of the land surface. These incongruent reactions create regolith, which is removed by physical transport mechanisms that drive landscape denudation. In contrast, carbonate critical zones are mostly composed of homogeneous and soluble minerals, which dissolve congruently with the weathering products exported in solution, limiting regolith in the soil mantle to small amounts of insoluble residues. These reactions can extend to depths greater than 2 km below the surface. As water at the land surface drains preferentially through vertical joints and horizontal bedding planes of the carbonate critical zones, it is 'charged' with biologically-derived carbon dioxide, which decreases pH, dissolves carbonate rock, and enlarges subsurface flowpaths through feedbacks between flow and dissolution. Caves are extreme end products of this process and are key morphological features of carbonate critical zones. Caves link surface processes to the deep subsurface and serve as efficient delivery agents for oxygen, carbon and nutrients to zones within the critical zone that are deficient in all three, interrupting vertical and horizontal chemical gradients that would exist if caves were not present. We present select data from air and water-filled caves in the upper Floridan aquifer, Florida, USA, that demonstrate how caves, acting as very large preferential flow paths, alter processes in carbonate relative to siliciclastic critical zones. While caves represent an extreme end member of hydraulic and chemical heterogeneity that has no direct counterpart siliciclastic systems, these large voids provide easily accessible laboratories to investigate processes in carbonate critical zones, and how they differ from standard siliciclastic models of critical zones.

Contrastive Analysis of Meteorological Element Effect Simulated by parameterization schemes Land Surface Process of Noah and CLM4 over the Yellow River Source Region

NASA Astrophysics Data System (ADS)

Zhang, Y.; Wen, X.

2017-12-01

The Yellow River source region is situated in the northeast Tibetan Plateau, which is considered as a global climate change hot-spot and one of the most sensitive areas in terms of response to global warming in view of its fragile ecosystem. This region plays an irreplaceable role for downstream water supply of The Yellow River because of its unique topography and variable climate. The water energy cycle processes of the Yellow River source Region from July to September in 2015 were simulated by using the WRF mesoscale numerical model. The two groups respectively used Noah and CLM4 parameterization schemes of land surface process. Based on the observation data of GLDAS data set, ground automatic weather station and Zoige plateau wetland ecosystem research station, the simulated values of near surface meteorological elements and surface energy parameters of two different schemes were compared. The results showed that the daily variations about meteorological factors in Zoige station in September were simulated quite well by the model. The correlation coefficient between the simulated temperature and humidity of the CLM scheme were 0.88 and 0.83, the RMSE were 1.94 ° and 9.97%, and the deviation Bias were 0.04 ° and 3.30%, which was closer to the observation data than the Noah scheme. The correlation coefficients of net radiation, surface heat flux, upward short wave and upward longwave radiation were respectively 0.86, 0.81, 0.84 and 0.88, which corresponded better than the observation data. The sensible heat flux and latent heat flux distribution of the Noah scheme corresponded quite well to GLDAS. the distribution and magnitude of 2m relative humidity and soil moisture were closer to surface observation data because the CLM scheme described the photosynthesis and evapotranspiration of land surface vegetation more rationally. The simulating abilities of precipitation and downward longwave radiation need to be improved. This study provides a theoretical basis for the numerical simulation of water energy cycle in the source region over the Yellow River basin.