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Sample records for global land surface

  1. Mycorrhizal fungi and global land surface models?

    NASA Astrophysics Data System (ADS)

    Brzostek, E. R.; Fisher, J. B.; Shi, M.; Phillips, R.

    2013-12-01

    In the current generation of Land Surface Models (LSMs), the representation of coupled carbon (C) and nutrient cycles does not account for allocation of C by plants to mycorrhizal fungi in exchange for limiting nutrients. Given that the amount of C transferred to mycorrhizae can exceed 20% of net primary production (NPP), mycorrhizae can supply over half of the nitrogen (N) needed to support NPP, and that large majority of plants form associations with mycorrhizae; integrating these mechanisms into LSMs may significantly alter our understanding of the role of the terrestrial biosphere in mitigating climate change. Here, we present results from the integration of a mycorrhizal framework into a cutting-edge global plant nitrogen model -- Fixation & Uptake of Nitrogen (FUN; Fisher et al., 2010) -- that can be coupled into existing LSMs. In this mycorrhizal framework, the C cost of N acquisition varies as a function of mycorrhizal type with: (1) plants that support arbuscular mycorrhizae (AM) benefiting when N is plentiful and (2) plants that support ectomycorrhizae (ECM) benefiting when N is limiting. At the plot scale (15 x 15m), the My-FUN model improved predictions of retranslocation, N uptake, and the amount of C transferred into the soil relative to the base model across 45 plots that vary in mycorrhizal type in Indiana, USA. At the ecosystem scale, when we coupled this new framework into the Community Land Model (CLM-CN), the model estimated lower C uptake than the base model and more accurately predicted C uptake at the Morgan Monroe State Forest AmeriFlux site. These results suggest that the inclusion of a mycorrhizal framework into LSMs will enhance our ability to predict feedbacks between global change and the terrestrial biosphere.

  2. The international surface temperature initiative's global land surface databank

    NASA Astrophysics Data System (ADS)

    Lawrimore, J. H.; Rennie, J.; Gambi de Almeida, W.; Christy, J.; Flannery, M.; Gleason, B.; Klein-Tank, A.; Mhanda, A.; Ishihara, K.; Lister, D.; Menne, M. J.; Razuvaev, V.; Renom, M.; Rusticucci, M.; Tandy, J.; Thorne, P. W.; Worley, S.

    2013-09-01

    The International Surface Temperature Initiative (ISTI) consists of an end-to-end process for land surface air temperature analyses. The foundation is the establishment of a global land surface Databank. This builds upon the groundbreaking efforts of scientists in the 1980s and 1990s. While using many of their principles, a primary aim is to improve aspects including data provenance, version control, openness and transparency, temporal and spatial coverage, and improved methods for merging disparate sources. The initial focus is on daily and monthly timescales. A Databank Working Group is focused on establishing Stage-0 (original observation forms) through Stage-3 data (merged dataset without quality control). More than 35 sources of data have already been added and efforts have now turned to development of the initial version of the merged dataset. Methods have been established for ensuring to the extent possible the provenance of all data from the point of observation through all intermediate steps to final archive and access. Databank submission procedures were designed to make the process of contributing data as easy as possible. All data are provided openly and without charge. We encourage the use of these data and feedback from interested users.

  3. Global scale hydrology - Advances in land surface modeling

    SciTech Connect

    Wood, E.F. )

    1991-01-01

    Research into global scale hydrology is an expanding area that includes researchers from the meteorology, climatology, ecology and hydrology communities. This paper reviews research in this area carried out in the United States during the last IUGG quadrennial period of 1987-1990. The review covers the representation of land-surface hydrologic processes for general circulation models (GCMs), sensitivity analysis of these representations on global hydrologic fields like precipitation, regional studies of climate that have global hydrologic implications, recent field studies and experiments whose aims are the improved understanding of land surface-atmospheric interactions, and the use of remotely sensed data for the further understanding of the spatial variability of surface hydrologic processes that are important at regional and global climate scales. 76 refs.

  4. Results from Global Land-Surface Data Assimilation Methods

    NASA Technical Reports Server (NTRS)

    Radakovich, Jon D.; Houser, Paul R.; daSilva, Arlindo; Bosilovich, Michael G.; Einaudi, Franco (Technical Monitor)

    2001-01-01

    Realistic representation of the land surface is crucial in global climate modeling (GCM). Recently, the Mosaic land-surface Model (LSM) has been driven off-line using GEOS DAS (Goddard Earth Observing System Data Assimilation System) atmospheric forcing, forming the Off-line Land-surface Global Assimilation (OLGA) system. This system provides a computationally efficient test bed for land surface data assimilation. Here, we validate the OLGA simulation of surface processes and the assimilation of ISCCP surface temperatures. Another component of this study as the incorporation of the Physical-space Statistical Analysis System (PSAS) into OLGA, in order to assimilate surface temperature observations from the International Satellite Cloud Climatology Project (ISCCP). To counteract the subsequent forcing of the analyzed skin temperature back to the initial state following the analysis. incremental bias correction (IBC) was included in the assimilation. The IBC scheme effectively removed the time mean bias, but did not remove him in the mean diurnal cycle. Therefore, a diurnal him correction (DBC) scheme was developed, where the time-dependent bias was modeled with a sine wave parameterization. In addition, quality control of the ISCCP data and anisotropic temperature correction were implemented in PSAS. Preliminary results showed a substantial impact from the inclusion of PSAS and DBC that was visible in the surface meteorology fields and energy budget. Also, the monthly mean diurnal cycle from the experiment closely matched the diurnal cycle from the observations.

  5. Results From Global Land-surface Data Assimilation Methods

    NASA Astrophysics Data System (ADS)

    Radakovich, J. D.; Houser, P. R.; da Silva, A.; Bosilovich, M. G.

    2001-05-01

    Realistic representation of the land surface is crucial in global climate modeling (GCM). Recently, the Mosaic land-surface Model (LSM) has been driven off-line using GEOS DAS (Goddard Earth Observing System Data Assimilation System) atmospheric forcing, forming the Off-line Land-surface Global Assimilation (OLGA) system. This system provides a computationally efficient test bed for land surface data assimilation. Here, we validate the OLGA simulation of surface processes and the assimilation of ISCCP surface temperatures. Another component of this study was the incorporation of the Physical-space Statistical Analysis System (PSAS) into OLGA, in order to assimilate surface temperature observations from the International Satellite Cloud Climatology Project (ISCCP). To counteract the subsequent forcing of the analyzed skin temperature back to the initial state following the analysis, incremental bias correction (IBC) was included in the assimilation. The IBC scheme effectively removed the time mean bias, but did not remove bias in the mean diurnal cycle. Therefore, a diurnal bias correction (DBC) scheme was developed, where the time-dependent bias was modeled with a sine wave parameterization. In addition, quality control of the ISCCP data and anisotropic temperature correction were implemented in PSAS. Preliminary results showed a substantial impact from the inclusion of PSAS and DBC that was visible in the surface meteorology fields and energy budget. Also, the monthly mean diurnal cycle from the experiment closely matched the diurnal cycle from the observations.

  6. 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.

  7. Global Land Surface Emissivity Retrieved From Satellite Ultraspectral IR Measurements

    NASA Technical Reports Server (NTRS)

    Zhou, D. K.; Larar, A. M.; Liu, Xu; Smith, W. L.; Strow, L. L.; Yang, Ping; Schlussel, P.; Calbet, X.

    2011-01-01

    Ultraspectral resolution infrared (IR) radiances obtained from nadir observations provide information about the atmosphere, surface, aerosols, and clouds. Surface spectral emissivity (SSE) and surface skin temperature from current and future operational satellites can and will reveal critical information about the Earth s ecosystem and land-surface-type properties, which might be utilized as a means of long-term monitoring of the Earth s environment and global climate change. In this study, fast radiative transfer models applied to the atmosphere under all weather conditions are used for atmospheric profile and surface or cloud parameter retrieval from ultraspectral and/or hyperspectral spaceborne IR soundings. An inversion scheme, dealing with cloudy as well as cloud-free radiances observed with ultraspectral IR sounders, has been developed to simultaneously retrieve atmospheric thermodynamic and surface or cloud microphysical parameters. This inversion scheme has been applied to the Infrared Atmospheric Sounding Interferometer (IASI). Rapidly produced SSE is initially evaluated through quality control checks on the retrievals of other impacted surface and atmospheric parameters. Initial validation of retrieved emissivity spectra is conducted with Namib and Kalahari desert laboratory measurements. Seasonal products of global land SSE and surface skin temperature retrieved with IASI are presented to demonstrate seasonal variation of SSE.

  8. Global Land Surface Emissivity Retrieved From Satellite Ultraspectral IR Measurements

    NASA Technical Reports Server (NTRS)

    Zhou, D. K.; Larar, A. M.; Liu, Xu; Smith, W. L.; Strow, L. L.; Yang, Ping; Schlussel, P.; Calbet, X.

    2011-01-01

    Ultraspectral resolution infrared (IR) radiances obtained from nadir observations provide information about the atmosphere, surface, aerosols, and clouds. Surface spectral emissivity (SSE) and surface skin temperature from current and future operational satellites can and will reveal critical information about the Earth s ecosystem and land-surface-type properties, which might be utilized as a means of long-term monitoring of the Earth s environment and global climate change. In this study, fast radiative transfer models applied to the atmosphere under all weather conditions are used for atmospheric profile and surface or cloud parameter retrieval from ultraspectral and/or hyperspectral spaceborne IR soundings. An inversion scheme, dealing with cloudy as well as cloud-free radiances observed with ultraspectral IR sounders, has been developed to simultaneously retrieve atmospheric thermodynamic and surface or cloud microphysical parameters. This inversion scheme has been applied to the Infrared Atmospheric Sounding Interferometer (IASI). Rapidly produced SSE is initially evaluated through quality control checks on the retrievals of other impacted surface and atmospheric parameters. Initial validation of retrieved emissivity spectra is conducted with Namib and Kalahari desert laboratory measurements. Seasonal products of global land SSE and surface skin temperature retrieved with IASI are presented to demonstrate seasonal variation of SSE.

  9. Forest biomass allometry in global land surface models

    NASA Astrophysics Data System (ADS)

    Wolf, Adam; Ciais, Philippe; Bellassen, Valentin; Delbart, Nicolas; Field, Christopher B.; Berry, Joseph A.

    2011-09-01

    A number of global land surface models simulate photosynthesis, respiration, and disturbance, important flows in the carbon cycle that are widely tested against flux towers and CO2 concentration gradients. The resulting forest biomass is examined in this paper for its resemblance to realistic stands, which are characterized using allometric theory. The simulated biomass pools largely do not conform to widely observed allometry, particularly for young stands. The best performing models had an explicit treatment of stand-thinning processes, which brought the slope of the allometry of these models closer to observations. Additionally, models that had relatively shorter wood turnover times performed were generally closer to observed allometries. The discrepancy between the pool distribution between models and data suggests estimates of NEE have biases when integrated over the long term, as compared to observed biomass data, and could therefore compromise long-term predictions of land carbon sources and sinks. We think that this presents a practical obstacle for improving models by informing them better with data. The approach taken in this paper, examining biomass pools allometrically, offers a simple approach to improving the characteristic behaviors of global models with the relatively sparse data that is available globally by forest inventory.

  10. Global Intercomparison of 12 Land Surface Heat Flux Estimates

    NASA Technical Reports Server (NTRS)

    Jimenez, C.; Prigent, C.; Mueller, B.; Seneviratne, S. I.; McCabe, M. F.; Wood, E. F.; Rossow, W. B.; Balsamo, G.; Betts, A. K.; Dirmeyer, P. A.; hide

    2011-01-01

    A global intercomparison of 12 monthly mean land surface heat flux products for the period 1993-1995 is presented. The intercomparison includes some of the first emerging global satellite-based products (developed at Paris Observatory, Max Planck Institute for Biogeochemistry, University of California Berkeley, University of Maryland, and Princeton University) and examples of fluxes produced by reanalyses (ERA-Interim, MERRA, NCEP-DOE) and off-line land surface models (GSWP-2, GLDAS CLM/ Mosaic/Noah). An intercomparison of the global latent heat flux (Q(sub le)) annual means shows a spread of approx 20 W/sq m (all-product global average of approx 45 W/sq m). A similar spread is observed for the sensible (Q(sub h)) and net radiative (R(sub n)) fluxes. In general, the products correlate well with each other, helped by the large seasonal variability and common forcing data for some of the products. Expected spatial distributions related to the major climatic regimes and geographical features are reproduced by all products. Nevertheless, large Q(sub le)and Q(sub h) absolute differences are also observed. The fluxes were spatially averaged for 10 vegetation classes. The larger Q(sub le) differences were observed for the rain forest but, when normalized by mean fluxes, the differences were comparable to other classes. In general, the correlations between Q(sub le) and R(sub n) were higher for the satellite-based products compared with the reanalyses and off-line models. The fluxes were also averaged for 10 selected basins. The seasonality was generally well captured by all products, but large differences in the flux partitioning were observed for some products and basins.

  11. Global Intercomparison of 12 Land Surface Heat Flux Estimates

    NASA Technical Reports Server (NTRS)

    Jimenez, C.; Prigent, C.; Mueller, B.; Seneviratne, S. I.; McCabe, M. F.; Wood, E. F.; Rossow, W. B.; Balsamo, G.; Betts, A. K.; Dirmeyer, P. A.; Fisher, J. B.; Jung, M.; Kanamitsu, M.; Reichle, R. H.; Reichstein, M.; Rodell, M.; Sheffield, J.; Tu, K.; Wang, K.

    2011-01-01

    A global intercomparison of 12 monthly mean land surface heat flux products for the period 1993-1995 is presented. The intercomparison includes some of the first emerging global satellite-based products (developed at Paris Observatory, Max Planck Institute for Biogeochemistry, University of California Berkeley, University of Maryland, and Princeton University) and examples of fluxes produced by reanalyses (ERA-Interim, MERRA, NCEP-DOE) and off-line land surface models (GSWP-2, GLDAS CLM/ Mosaic/Noah). An intercomparison of the global latent heat flux (Q(sub le)) annual means shows a spread of approx 20 W/sq m (all-product global average of approx 45 W/sq m). A similar spread is observed for the sensible (Q(sub h)) and net radiative (R(sub n)) fluxes. In general, the products correlate well with each other, helped by the large seasonal variability and common forcing data for some of the products. Expected spatial distributions related to the major climatic regimes and geographical features are reproduced by all products. Nevertheless, large Q(sub le)and Q(sub h) absolute differences are also observed. The fluxes were spatially averaged for 10 vegetation classes. The larger Q(sub le) differences were observed for the rain forest but, when normalized by mean fluxes, the differences were comparable to other classes. In general, the correlations between Q(sub le) and R(sub n) were higher for the satellite-based products compared with the reanalyses and off-line models. The fluxes were also averaged for 10 selected basins. The seasonality was generally well captured by all products, but large differences in the flux partitioning were observed for some products and basins.

  12. Mapping the global depth to bedrock for land surface modeling

    NASA Astrophysics Data System (ADS)

    Shangguan, Wei; Hengl, Tomislav; Mendes de Jesus, Jorge; Yuan, Hua; Dai, Yongjiu

    2017-03-01

    Depth to bedrock serves as the lower boundary of land surface models, which controls hydrologic and biogeochemical processes. This paper presents a framework for global estimation of depth to bedrock (DTB). Observations were extracted from a global compilation of soil profile data (ca. 1,30,000 locations) and borehole data (ca. 1.6 million locations). Additional pseudo-observations generated by expert knowledge were added to fill in large sampling gaps. The model training points were then overlaid on a stack of 155 covariates including DEM-based hydrological and morphological derivatives, lithologic units, MODIS surface reflectance bands and vegetation indices derived from the MODIS land products. Global spatial prediction models were developed using random forest and Gradient Boosting Tree algorithms. The final predictions were generated at the spatial resolution of 250 m as an ensemble prediction of the two independently fitted models. The 10-fold cross-validation shows that the models explain 59% for absolute DTB and 34% for censored DTB (depths deep than 200 cm are predicted as 200 cm). The model for occurrence of R horizon (bedrock) within 200 cm does a good job. Visual comparisons of predictions in the study areas where more detailed maps of depth to bedrock exist show that there is a general match with spatial patterns from similar local studies. Limitation of the data set and extrapolation in data spare areas should not be ignored in applications. To improve accuracy of spatial prediction, more borehole drilling logs will need to be added to supplement the existing training points in under-represented areas.

  13. An Open and Transparent Databank of Global Land Surface Temperature

    NASA Astrophysics Data System (ADS)

    Rennie, J.; Thorne, P.; Lawrimore, J. H.; Gleason, B.; Menne, M. J.; Williams, C.

    2013-12-01

    The International Surface Temperature Initiative (ISTI) consists of an effort to create an end-to-end process for land surface air temperature analyses. The foundation of this process is the establishment of a global land surface databank. The databank builds upon the groundbreaking efforts of scientists who led efforts to construct global land surface datasets in the 1980's and 1990's. A primary aim of the databank is to improve aspects including data provenance, version control, temporal and spatial coverage, and improved methods for bringing dozens of source data together into an integrated dataset. The databank consists of multiple stages, with each successive stage providing a higher level of processing, quality and integration. Currently more than 50 sources of data have been added to the databank. An automated algorithm has been developed that merges these sources into one complete dataset by removing duplicate station records, identifying two or more station records that can be merged into a single record, and incorporating new and unique stations. The program runs iteratively through all the sources which are ordered based upon criteria established by the ISTI. The highest preferred source, known as the target, runs through all the candidate sources, calculating station comparisons that are acceptable for merging. The process is probabilistic in approach, and the final fate of a candidate station is based upon metadata matching and data equivalence criteria. If there is not enough information, the station is withheld for further investigation. The algorithm has been validated using a pseudo-source of stations with a known time of observation bias, and correct matches have been made nearly 95% of the time. The final product, endorsed and recommended by ISTI, contains over 30,000 stations, however slight changes in the algorithm can perturb results. Subjective decisions, such as the ordering of the sources, or changing metadata and data matching thresholds

  14. The influence of global sea surface temperature variability on the large-scale land surface temperature

    NASA Astrophysics Data System (ADS)

    Tyrrell, Nicholas L.; Dommenget, Dietmar; Frauen, Claudia; Wales, Scott; Rezny, Mike

    2015-04-01

    In global warming scenarios, global land surface temperatures () warm with greater amplitude than sea surface temperatures (SSTs), leading to a land/sea warming contrast even in equilibrium. Similarly, the interannual variability of is larger than the covariant interannual SST variability, leading to a land/sea contrast in natural variability. This work investigates the land/sea contrast in natural variability based on global observations, coupled general circulation model simulations and idealised atmospheric general circulation model simulations with different SST forcings. The land/sea temperature contrast in interannual variability is found to exist in observations and models to a varying extent in global, tropical and extra-tropical bands. There is agreement between models and observations in the tropics but not the extra-tropics. Causality in the land-sea relationship is explored with modelling experiments forced with prescribed SSTs, where an amplification of the imposed SST variability is seen over land. The amplification of to tropical SST anomalies is due to the enhanced upper level atmospheric warming that corresponds with tropical moist convection over oceans leading to upper level temperature variations that are larger in amplitude than the source SST anomalies. This mechanism is similar to that proposed for explaining the equilibrium global warming land/sea warming contrast. The link of the to the dominant mode of tropical and global interannual climate variability, the El Niño Southern Oscillation (ENSO), is found to be an indirect and delayed connection. ENSO SST variability affects the oceans outside the tropical Pacific, which in turn leads to a further, amplified and delayed response of.

  15. 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.; hide

    2013-01-01

    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 (approx. 2 m or less) commercial satellite data (Quickbird and Worldview2) available to us through the unclassified

  16. 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

  17. Land Surface Phenology from MODIS: Characterization of the Collection 5 Global Land Cover Dynamics Product

    NASA Technical Reports Server (NTRS)

    Ganguly, Sangram; Friedl, Mark A.; Tan, Bin; Zhang, Xiaoyang; Verma, Manish

    2010-01-01

    Information related to land surface phenology is important for a variety of applications. For example, phenology is widely used as a diagnostic of ecosystem response to global change. In addition, phenology influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. Increasingly, the importance of phenology for studies of habitat and biodiversity is also being recognized. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, remote sensing provides the only way to observe and monitor phenology over large scales and at regular intervals. The MODIS Global Land Cover Dynamics Product was developed to support investigations that require regional to global scale information related to spatiotemporal dynamics in land surface phenology. Here we describe the Collection 5 version of this product, which represents a substantial refinement relative to the Collection 4 product. This new version provides information related to land surface phenology at higher spatial resolution than Collection 4 (500-m vs. 1-km), and is based on 8-day instead of 16-day input data. The paper presents a brief overview of the algorithm, followed by an assessment of the product. To this end, we present (1) a comparison of results from Collection 5 versus Collection 4 for selected MODIS tiles that span a range of climate and ecological conditions, (2) a characterization of interannual variation in Collections 4 and 5 data for North America from 2001 to 2006, and (3) a comparison of Collection 5 results against ground observations for two forest sites in the northeastern United States. Results show that the Collection 5 product is qualitatively similar to Collection 4. However, Collection 5 has fewer missing values outside of regions with persistent cloud cover and atmospheric aerosols. Interannual variability in Collection 5 is consistent with expected ranges of

  18. 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

  19. Surface Temperature Assimilation in the Global Land Data Assimilation System (GLDAS)

    NASA Technical Reports Server (NTRS)

    Bosilovich, Michael G.; Radakovich, Jon D.; daSilva, Arlindo; Houser, Paul R.; Atlas, Robert M. (Technical Monitor)

    2002-01-01

    The Global Land Data Assimilation System (GLDAS) is a global land parameterization that uses prescribed meteorology as forcing in order to determine regular gridded land surface states (temperature and moisture) and other properties (e.g. water and heat fluxes). In the present experiment, the assimilation of surface skin temperature is incorporated into the land parameterizations. The meteorological forcing was derived from the Goddard Earth Observing System (GEOS-3) Data Assimilation System (DAS) for the full year of 1998 GLDAS can use several land parameterizations, but here we use the Mosaic land surface model and the Common Land Model (CLM). TOVS surface temperature observations are assimilated into GLDAS. The TOVS observations are less frequent that observations used in previous experiments (ISCCP). The purpose of this presentation is to evaluate the impact of the TOVS assimilation on both Mosaic and CLM. We will especially consider the impact of coarse temporal observations on the assimilation and bias correction.

  20. Surface Temperature Assimilation in the Global Land Data Assimilation System (GLDAS)

    NASA Technical Reports Server (NTRS)

    Bosilovich, Michael G.; Radakovich, Jon D.; daSilva, Arlindo; Houser, Paul R.; Atlas, Robert M. (Technical Monitor)

    2002-01-01

    The Global Land Data Assimilation System (GLDAS) is a global land parameterization that uses prescribed meteorology as forcing in order to determine regular gridded land surface states (temperature and moisture) and other properties (e.g. water and heat fluxes). In the present experiment, the assimilation of surface skin temperature is incorporated into the land parameterizations. The meteorological forcing was derived from the Goddard Earth Observing System (GEOS-3) Data Assimilation System (DAS) for the full year of 1998 GLDAS can use several land parameterizations, but here we use the Mosaic land surface model and the Common Land Model (CLM). TOVS surface temperature observations are assimilated into GLDAS. The TOVS observations are less frequent that observations used in previous experiments (ISCCP). The purpose of this presentation is to evaluate the impact of the TOVS assimilation on both Mosaic and CLM. We will especially consider the impact of coarse temporal observations on the assimilation and bias correction.

  1. Forcing a Global, Offline Land Surface Modeling System with Observation-Based Fields

    NASA Technical Reports Server (NTRS)

    Rodell, Matthew; Houser, Paul R.; Jambor, U.; Gottschalck, J.; Radakovich, J.; Arsenault, K.; Meng, C.-J.; Mitchell, K. E.

    2002-01-01

    The Global Land Data Assimilation System (GLDAS) drives multiple uncoupled land surface models in order to produce optimal output fields of surface states in near-real time, globally, at 1/4 degree spatial resolution. These fields are then made available for coupled atmospheric model initialization and further research. One of the unique aspects of GLDAS is its ability to ingest both modeled and observation-derived forcing for running global scale land surface models. This paper compares results of runs forced by modeled and observed precipitation and shortwave radiation fields. Differences are examined and the impact of the observations on model skill is assessed.

  2. Global climate sensitivity to land surface change: The Mid Holocene revisited

    NASA Astrophysics Data System (ADS)

    Diffenbaugh, Noah S.; Sloan, Lisa C.

    2002-05-01

    Land surface forcing of global climate has been shown both for anthropogenic and non-anthropogenic changes in land surface distribution. Because validation of global climate models (GCMs) is dependent upon the use of accurate boundary conditions, and because changes in land surface distribution have been shown to have effects on climate in areas remote from those changes, we have tested the sensitivity of a GCM to a global Mid Holocene vegetation distribution reconstructed from the fossil record, a first for a 6 ka GCM run. Here we demonstrate that large areas of the globe show statistically significant temperature sensitivity to these land surface changes and that the magnitude of the vegetation forcing is equal to the magnitude of 6 ka orbital forcing, emphasizing the importance of accurate land surface distribution for both model validation and future climate prediction.

  3. Deriving New Topography-based Global Datasets for Land Surface Modeling

    NASA Astrophysics Data System (ADS)

    Tesfa, T. K.; Leung, L. R.

    2015-12-01

    Topography exerts a major control on land surface processes through its influence on atmospheric forcing, soil and vegetation properties, network topology and drainage area. Land surface spatial structure that captures spatial heterogeneity influenced by topography is expected to improve representation of land surface processes in land surface models. For example, land surface modeling using subbasins instead of regular grids as computational units has demonstrated improved scalability of simulated runoff and streamflow processes. In this study, a local classification method is applied to derive a new land surface spatial structure defined by further dividing subbasins into subgrid units based on elevation, topographic slope and aspect to take advantage of the emergent patterns and scaling properties of atmospheric, hydrologic, and vegetation processes in land surface models. For this purpose, a more consistent 90 meter resolution global surface elevation data has been developed by blending elevation data obtained from various sources. Taking the advantage of natural hydrologic connectivity of watersheds, new subbasin-based river routing and reservoir dependency datasets are being developed to improve representation of the managed hydrologic systems in the Community Land Model.

  4. The effects of land surface process perturbations in a global ensemble forecast system

    NASA Astrophysics Data System (ADS)

    Deng, Guo; Zhu, Yuejian; Gong, Jiandong; Chen, Dehui; Wobus, Richard; Zhang, Zhe

    2016-10-01

    Atmospheric variability is driven not only by internal dynamics, but also by external forcing, such as soil states, SST, snow, sea-ice cover, and so on. To investigate the forecast uncertainties and effects of land surface processes on numerical weather prediction, we added modules to perturb soil moisture and soil temperature into NCEP's Global Ensemble Forecast System (GEFS), and compared the results of a set of experiments involving different configurations of land surface and atmospheric perturbation. It was found that uncertainties in different soil layers varied due to the multiple timescales of interactions between land surface and atmospheric processes. Perturbations of the soil moisture and soil temperature at the land surface changed sensible and latent heat flux obviously, as compared to the less or indirect land surface perturbation experiment from the day-to-day forecasts. Soil state perturbations led to greater variation in surface heat fluxes that transferred to the upper troposphere, thus reflecting interactions and the response to atmospheric external forcing. Various verification scores were calculated in this study. The results indicated that taking the uncertainties of land surface processes into account in GEFS could contribute a slight improvement in forecast skill in terms of resolution and reliability, a noticeable reduction in forecast error, as well as an increase in ensemble spread in an under-dispersive system. This paper provides a preliminary evaluation of the effects of land surface processes on predictability. Further research using more complex and suitable methods is needed to fully explore our understanding in this area.

  5. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

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

  7. 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

  8. Deriving global parameter estimates for the Noah land surface model using FLUXNET and machine learning

    NASA Astrophysics Data System (ADS)

    Chaney, Nathaniel W.; Herman, Jonathan D.; Ek, Michael B.; Wood, Eric F.

    2016-11-01

    With their origins in numerical weather prediction and climate modeling, land surface models aim to accurately partition the surface energy balance. An overlooked challenge in these schemes is the role of model parameter uncertainty, particularly at unmonitored sites. This study provides global parameter estimates for the Noah land surface model using 85 eddy covariance sites in the global FLUXNET network. The at-site parameters are first calibrated using a Latin Hypercube-based ensemble of the most sensitive parameters, determined by the Sobol method, to be the minimum stomatal resistance (rs,min), the Zilitinkevich empirical constant (Czil), and the bare soil evaporation exponent (fxexp). Calibration leads to an increase in the mean Kling-Gupta Efficiency performance metric from 0.54 to 0.71. These calibrated parameter sets are then related to local environmental characteristics using the Extra-Trees machine learning algorithm. The fitted Extra-Trees model is used to map the optimal parameter sets over the globe at a 5 km spatial resolution. The leave-one-out cross validation of the mapped parameters using the Noah land surface model suggests that there is the potential to skillfully relate calibrated model parameter sets to local environmental characteristics. The results demonstrate the potential to use FLUXNET to tune the parameterizations of surface fluxes in land surface models and to provide improved parameter estimates over the globe.

  9. The land surface-atmosphere interaction: A review based on observational and global modeling perspectives

    NASA Astrophysics Data System (ADS)

    Betts, Alan K.; Ball, John H.; Beljaars, Anton C. M.; Miller, Martin J.; Viterbo, Pedro A.

    1996-03-01

    This review discusses the land-surface-atmosphere interaction using observations from two North American field experiments (First International Satellite Land Surface Climatology Project Field Experiment (FIFE) and Boreal Ecosystem Atmosphere Study (BOREAS)) and the application of research data to the improvement of land surface and boundary layer parameterizations in the European Centre for Medium-Range Weather Forecast (ECMWF) global forecast model. Using field data, we discuss some of the diurnal and seasonal feedback loops controlling the net surface radiation and its partition into the surface sensible and latent heat fluxes and the ground heat flux. We consider the impact on the boundary layer evolution and show the changes in the diurnal cycle with soil moisture in midsummer. We contrast the surface energy budget over the tropical oceans with that over both dry and wet land surfaces in summer. Results from a new ECMWF model with four predicted soil layers illustrate the interaction between the soil moisture reservoir, evaporation and precipitation on different timescales and space scales. An analysis of an ensemble of 30-day integrations for July 1993 (the month of the Mississippi flood) showed a large sensitivity of the monthly precipitation pattern (and amount) to different initial soil moisture conditions. Short-range forecasts with old and new land surface and boundary layer schemes showed that the new scheme produced much better precipitation forecasts for the central United States because of a more realistic thermodynamic structure, which in turn resulted from improved evaporation in an area that is about 1-day upstream. The results suggest that some predictability exists in the extended range as a result of the memory of the soil moisture reservoir. We also discuss briefly the problem of soil moisture initialization in a global forecast model and summarize recent experience with nudging of soil moisture at ECMWF and improvements in the surface energy

  10. Codominant water control on global interannual variability and trends in land surface phenology and greenness.

    PubMed

    Forkel, Matthias; Migliavacca, Mirco; Thonicke, Kirsten; Reichstein, Markus; Schaphoff, Sibyll; Weber, Ulrich; Carvalhais, Nuno

    2015-09-01

    Identifying the relative importance of climatic and other environmental controls on the interannual variability and trends in global land surface phenology and greenness is challenging. Firstly, quantifications of land surface phenology and greenness dynamics are impaired by differences between satellite data sets and phenology detection methods. Secondly, dynamic global vegetation models (DGVMs) that can be used to diagnose controls still reveal structural limitations and contrasting sensitivities to environmental drivers. Thus, we assessed the performance of a new developed phenology module within the LPJmL (Lund-Potsdam-Jena managed Lands) DGVM with a comprehensive ensemble of three satellite data sets of vegetation greenness and ten phenology detection methods, thereby thoroughly accounting for observational uncertainties. The improved and tested model allows us quantifying the relative importance of environmental controls on interannual variability and trends of land surface phenology and greenness at regional and global scales. We found that start of growing season interannual variability and trends are in addition to cold temperature mainly controlled by incoming radiation and water availability in temperate and boreal forests. Warming-induced prolongations of the growing season in high latitudes are dampened by a limited availability of light. For peak greenness, interannual variability and trends are dominantly controlled by water availability and land-use and land-cover change (LULCC) in all regions. Stronger greening trends in boreal forests of Siberia than in North America are associated with a stronger increase in water availability from melting permafrost soils. Our findings emphasize that in addition to cold temperatures, water availability is a codominant control for start of growing season and peak greenness trends at the global scale.

  11. A framework for global diurnally-resolved observations of Land Surface Temperature

    NASA Astrophysics Data System (ADS)

    Ghent, Darren; Remedios, John

    2014-05-01

    Land surface temperature (LST) is the radiative skin temperature of the land, and is one of the key parameters in the physics of land-surface processes on regional and global scales. Being a key boundary condition in land surface models, which determine the surface to atmosphere fluxes of heat, water and carbon; thus influencing cloud cover, precipitation and atmospheric chemistry predictions within Global models, the requirement for global diurnal observations of LST is well founded. Earth Observation satellites offer an opportunity to obtain global coverage of LST, with the appropriate exploitation of data from multiple instruments providing a capacity to resolve the diurnal cycle on a global scale. Here we present a framework for the production of global, diurnally resolved, data sets for LST which is a key request from users of LST data. We will show how the sampling of both geostationary and low earth orbit data sets could conceptually be employed to build combined, multi-sensor, pole-to-pole data sets. Although global averages already exist for individual instruments and merging of geostationary based LST is already being addressed operationally (Freitas, et al., 2013), there are still a number of important challenges to overcome. In this presentation, we will consider three of the issues still open in LST remote sensing: 1) the consistency amongst retrievals; 2) the clear-sky bias and its quantification; and 3) merging methods and the propagation of uncertainties. For example, the combined use of both geostationary earth orbit (GEO) and low earth orbit (LEO) data, and both infra-red and microwave data are relatively unexplored but are necessary to make the most progress. Hence this study will suggest what is state-of-the-art and how considerable advances can be made, accounting also for recent improvements in techniques and data quality. The GlobTemperature initiative under the Data User Element of ESA's 4th Earth Observation Envelope Programme (2013

  12. A framework for global diurnally-resolved observations of Land Surface Temperature

    NASA Astrophysics Data System (ADS)

    Ghent, D.; Remedios, J.; Pinnock, S.

    2013-12-01

    Land surface temperature (LST) is the radiative skin temperature of the land, and is one of the key parameters in the physics of land-surface processes on regional and global scales. Being a key boundary condition in land surface models, which determine the surface to atmosphere fluxes of heat, water and carbon; thus influencing cloud cover, precipitation and atmospheric chemistry predictions within Global models, the requirement for global diurnal observations of LST is well founded. Earth Observation satellites offer an opportunity to obtain global coverage of LST, with the appropriate exploitation of data from multiple instruments providing a capacity to resolve the diurnal cycle on a global scale. Here we present a framework for the production of global, diurnally resolved, data sets for LST which is a key request from users of LST data. We will show how the sampling of both geostationary and low earth orbit data sets could conceptually be employed to build combined, multi-sensor, pole-to-pole data sets. Although global averages already exist for individual instruments and merging of geostationary based LST is already being addressed operationally (Freitas, et al., 2013), there are still a number of important challenges to overcome. In this presentation, we will consider three of the issues still open in LST remote sensing: 1) the consistency amongst retrievals; 2) the clear-sky bias and its quantification; and 3) merging methods and the propagation of uncertainties. For example, the combined use of both geostationary earth orbit (GEO) and low earth orbit (LEO) data, and both infra-red and microwave data are relatively unexplored but are necessary to make the most progress. Hence this study will suggest what is state-of-the-art and how considerable advances can be made, accounting also for recent improvements in techniques and data quality. The GlobTemperature initiative under the Data User Element of ESA's 4th Earth Observation Envelope Programme (2013

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

    NASA Astrophysics Data System (ADS)

    Liang, S.

    2015-12-01

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

  14. Comparisons of global land surface seasonality and phenology derived from AVHRR, MODIS, and VIIRS data

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaoyang; Liu, Lingling; Yan, Dong

    2017-06-01

    Land surface seasonality has been widely investigated from satellite observations for monitoring the dynamics of terrestrial ecosystems in response to climate change. A great deal of efforts has focused on the characterization of interannual variation and long-term trends of vegetation phenological metrics derived from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data across regional and global scales. Recently, Visible Infrared Imaging Radiometer Suite (VIIRS) data have become available for the detections of global land surface phenology. These data sets provide us a potential opportunity to generate a consistent long-term climate data record of land surface phenology. However, to bridge the multiple-sensor-based phenology measurements, we need to understand their consistency and discrepancy across various geographical and ecological regions. To this end, we collected daily AVHRR, MODIS, and VIIRS data ( 5 km) globally, compared their temporal trajectories of two band enhanced vegetation index (EVI2) during 2013 and 2014, examined their discrepancy of phenology retrievals, and explored the influence of EVI2 data quality from the three satellite sensors on phenology detections. The results revealed the similarity and discrepancy of EVI2 time series and land surface phenology retrievals globally. Specifically, EVI2 time series from VIIRS and MODIS observations were similar with some discrepancies mainly arising from unsystematic impact factors. In contrast, VIIRS EVI2 was systematically higher than AVHRR EVI2, in which their differences could be greatly reduced by intersensor calibration. Further, the quality of EVI2 time series among AVHRR, MODIS, and VIIRS varied largely across the globe, which was generally better in Northern Hemisphere than in Southern Hemisphere. Their differences in EVI2 data quality led to the inconsistencies in the detections of phenological dates. On average, the absolute

  15. Land Surface Water and Energy Estimates in the Global MERRA-2 Reanalysis

    NASA Astrophysics Data System (ADS)

    Reichle, R. H.; Draper, C. S.; Liu, Q.; Koster, R. D.; Mahanama, S. P. P.; De Lannoy, G. J. M.; Girotto, M.

    2015-12-01

    Multi-decadal reanalysis datasets have been widely used to study the global terrestrial water and energy cycles. The driving component of the land surface water budget is the incoming precipitation forcing, which was traditionally generated by the atmospheric general circulation model component of the reanalysis system following the assimilation of atmospheric temperature and humidity observations. The recent CFSR and MERRA-2 reanalysis products, however, essentially use precipitation observations from satellites and/or gauges to force the land surface. This presentation first reviews the approach by which the precipitation observations are introduced in MERRA-2, which relies on a mix of (i) model-generated precipitation at high-latitudes, (ii) a pentad, 2.5 degree satellite product from the NOAA Climate Prediction Center (CPC) over Africa, and (iii) a daily, 0.5 degree, gauge-based CPC precipitation product elsewhere. This approach represents an evolution of the method used in the land-only MERRA-Land reanalysis. Next, the precipitation climatologies and the resulting land surface conditions are evaluated regionally and for the reanalysis time period (1980-present) against available independent observations. MERRA-2 provides generally improved land surface conditions when compared to MERRA, its predecessor. Improvements include enhanced estimates of soil moisture, terrestrial water storage, runoff, screen-level temperature and turbulent fluxes, with MERRA-2 skill metrics generally similar to those of MERRA-Land. But MERRA-2 also suffers from adverse spin-up effects in soil moisture conditions at very high latitudes because of model precipitation bias in this region.

  16. A global, 30-m resolution land-surface water body dataset for 2000

    NASA Astrophysics Data System (ADS)

    Feng, M.; Sexton, J. O.; Huang, C.; Song, D. X.; Song, X. P.; Channan, S.; Townshend, J. R.

    2014-12-01

    Inland surface water is essential to terrestrial ecosystems and human civilization. The distribution of surface water in space and its change over time are related to many agricultural, environmental and ecological issues, and are important factors that must be considered in human socioeconomic development. Accurate mapping of surface water is essential for both scientific research and policy-driven applications. Satellite-based remote sensing provides snapshots of Earth's surface and can be used as the main input for water mapping, especially in large areas. Global water areas have been mapped with coarse resolution remotely sensed data (e.g., the Moderate Resolution Imaging Spectroradiometer (MODIS)). However, most inland rivers and water bodies, as well as their changes, are too small to map at such coarse resolutions. Landsat TM (Thematic Mapper) and ETM+ (Enhanced Thematic Mapper Plus) imagery has a 30m spatial resolution and provides decades of records (~40 years). Since 2008, the opening of the Landsat archive, coupled with relatively lower costs associated with computing and data storage, has made comprehensive study of the dynamic changes of surface water over large even global areas more feasible. Although Landsat images have been used for regional and even global water mapping, the method can hardly be automated due to the difficulties on distinguishing inland surface water with variant degrees of impurities and mixing of soil background with only Landsat data. The spectral similarities to other land cover types, e.g., shadow and glacier remnants, also cause misidentification. We have developed a probabilistic based automatic approach for mapping inland surface water bodies. Landsat surface reflectance in multiple bands, derived water indices, and data from other sources are integrated to maximize the ability of identifying water without human interference. The approach has been implemented with open-source libraries to facilitate processing large

  17. A global assessment of the local impacts of land cover changes on the surface energy budget

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

    Biophysical effects of land use and land cover change (LULCC) on climate have received less attention than biogeochemical effects. Yet, their impact is potentially more perceptible because the effect is almost immediate at local scales. Biophysical effects depend on the specific LULCC transition, and can change in sign and magnitude across space and time. Spatially explicit assessments are therefore required to describe these phenomena. Whilst accurately characterising these local biophysical effects using Land Surface Models (LSMs) can be problematic given the strong modelling assumptions that must be made, satellite remote sensing instruments operationally measure several of the key energy fluxes at high temporal and spatial resolution across the entire planet. We leverage this synoptic property of remote sensing to develop a methodology capable of isolating the biophysical signal of potential vegetation transitions at local scale. Because mapping LULCC accurately at global scale is notoriously challenging, and because many potential transitions may not yet have occurred in various places, the approach relies on trading space for time over a moving window as a surrogate for monitoring real change. The result is a global dataset with a spatial resolution of 1° indicating the potential change in all terms of the surface energy balance (excepting the soil heat flux) for all transitions amongst 7 different plant functional types that are widely used by the land surface modelling community. This dataset will serve three main purposes: (1) to derive a data-driven diagnostic of the local biophysical effects of LULCC on the surface energy budget and local climate; (2) to provide a benchmark to assess model performances; and (3) to develop guidelines for the monitoring, reporting and verification of climate mitigation and adaptation plans that account for land biophysical impacts on climate.

  18. Sensitivity of global tropical climate to land surface processes: Mean state and interannual variability

    SciTech Connect

    Ma, Hsi-Yen; Xiao, Heng; Mechoso, C. R.; Xue, Yongkang

    2013-03-01

    This study examines the sensitivity of global tropical climate to land surface processes (LSP) using an atmospheric general circulation model both uncoupled (with prescribed SSTs) and coupled to an oceanic general circulation model. The emphasis is on the interactive soil moisture and vegetation biophysical processes, which have first order influence on the surface energy and water budgets. The sensitivity to those processes is represented by the differences between model simulations, in which two land surface schemes are considered: 1) a simple land scheme that specifies surface albedo and soil moisture availability, and 2) the Simplified Simple Biosphere Model (SSiB), which allows for consideration of interactive soil moisture and vegetation biophysical process. Observational datasets are also employed to assess the reality of model-revealed sensitivity. The mean state sensitivity to different LSP is stronger in the coupled mode, especially in the tropical Pacific. Furthermore, seasonal cycle of SSTs in the equatorial Pacific, as well as ENSO frequency, amplitude, and locking to the seasonal cycle of SSTs are significantly modified and more realistic with SSiB. This outstanding sensitivity of the atmosphere-ocean system develops through changes in the intensity of equatorial Pacific trades modified by convection over land. Our results further demonstrate that the direct impact of land-atmosphere interactions on the tropical climate is modified by feedbacks associated with perturbed oceanic conditions ("indirect effect" of LSP). The magnitude of such indirect effect is strong enough to suggest that comprehensive studies on the importance of LSP on the global climate have to be made in a system that allows for atmosphere-ocean interactions.

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

    NASA Astrophysics Data System (ADS)

    Chen, Xuelong; Su, Bob

    2017-04-01

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

  20. Evaluation and Validation of Global Land Surface Products Derived from Landsat, MODIS, and VIIRS

    NASA Technical Reports Server (NTRS)

    Roman, Miguel O.

    2012-01-01

    Data at medium and coarse resolution from the Landsat, MODIS, and VIIRS instruments provide crucial and indispensable time-series for the land component of the study of global change. This talk will be divided into two main sections. In the first part, a summary of the status of the processing, archiving, and early (Launch +6 months) on-orbit evaluation of the VIIRS Land Environmental Data Records (EDRs), will be presented. In the second part, results from an uncertainty analysis of MODIS- and Landsat-based albedo retrievals, based on collocated comparisons with tower and airborne multiangular measurements collected at the Cloud and Radiation Testbed (CART) site during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC'07), will be discussed.

  1. The Contribution of Reservoirs to Global Land Surface Water Storage Variations

    SciTech Connect

    Zhou, Tian; Nijssen, Bart; Gao, Huilin; Lettenmaier, Dennis P.

    2016-12-21

    Man-made reservoirs play a key role in the terrestrial water system. They alter water fluxes at the land surface and impact surface water storage through water management regulations for diverse purposes such as irrigation, municipal water supply, hydropower generation, and flood control. Although most developed countries have established sophisticated observing systems for many variables in the land surface water cycle, long-term and consistent records of reservoir storage are much more limited and not always shared. Furthermore, most land surface hydrological models do not represent the effects of water management activities. Here, the contribution of reservoirs to seasonal water storage variations is investigated using a large-scale water management model to simulate the effects of reservoir management at basin and continental scales. The model was run from 1948 to 2010 at a spatial resolution of 0.258 latitude–longitude. A total of 166 of the largest reservoirs in the world with a total capacity of about 3900 km3 (nearly 60%of the globally integrated reservoir capacity) were simulated. The global reservoir storage time series reflects the massive expansion of global reservoir capacity; over 30 000 reservoirs have been constructed during the past half century, with a mean absolute interannual storage variation of 89 km3. The results indicate that the average reservoir-induced seasonal storage variation is nearly 700 km3 or about 10%of the global reservoir storage. For some river basins, such as the Yellow River, seasonal reservoir storage variations can be as large as 72%of combined snow water equivalent and soil moisture storage.

  2. Global fields of soil moisture and land surface evapotranspiration derived from observed precipitation and surface air temperature

    NASA Technical Reports Server (NTRS)

    Mintz, Y.; Walker, G. K.

    1993-01-01

    The global fields of normal monthly soil moisture and land surface evapotranspiration are derived with a simple water budget model that has precipitation and potential evapotranspiration as inputs. The precipitation is observed and the potential evapotranspiration is derived from the observed surface air temperature with the empirical regression equation of Thornthwaite (1954). It is shown that at locations where the net surface radiation flux has been measured, the potential evapotranspiration given by the Thornthwaite equation is in good agreement with those obtained with the radiation-based formulations of Priestley and Taylor (1972), Penman (1948), and Budyko (1956-1974), and this provides the justification for the use of the Thornthwaite equation. After deriving the global fields of soil moisture and evapotranspiration, the assumption is made that the potential evapotranspiration given by the Thornthwaite equation and by the Priestley-Taylor equation will everywhere be about the same; the inverse of the Priestley-Taylor equation is used to obtain the normal monthly global fields of net surface radiation flux minus ground heat storage. This and the derived evapotranspiration are then used in the equation for energy conservation at the surface of the earth to obtain the global fields of normal monthly sensible heat flux from the land surface to the atmosphere.

  3. Global fields of soil moisture and land surface evapotranspiration derived from observed precipitation and surface air temperature

    NASA Technical Reports Server (NTRS)

    Mintz, Y.; Walker, G. K.

    1993-01-01

    The global fields of normal monthly soil moisture and land surface evapotranspiration are derived with a simple water budget model that has precipitation and potential evapotranspiration as inputs. The precipitation is observed and the potential evapotranspiration is derived from the observed surface air temperature with the empirical regression equation of Thornthwaite (1954). It is shown that at locations where the net surface radiation flux has been measured, the potential evapotranspiration given by the Thornthwaite equation is in good agreement with those obtained with the radiation-based formulations of Priestley and Taylor (1972), Penman (1948), and Budyko (1956-1974), and this provides the justification for the use of the Thornthwaite equation. After deriving the global fields of soil moisture and evapotranspiration, the assumption is made that the potential evapotranspiration given by the Thornthwaite equation and by the Priestley-Taylor equation will everywhere be about the same; the inverse of the Priestley-Taylor equation is used to obtain the normal monthly global fields of net surface radiation flux minus ground heat storage. This and the derived evapotranspiration are then used in the equation for energy conservation at the surface of the earth to obtain the global fields of normal monthly sensible heat flux from the land surface to the atmosphere.

  4. Mapping 2000 2010 Impervious Surface Change in India Using Global Land Survey Landsat Data

    NASA Technical Reports Server (NTRS)

    Wang, Panshi; Huang, Chengquan; Brown De Colstoun, Eric C.

    2017-01-01

    Understanding and monitoring the environmental impacts of global urbanization requires better urban datasets. Continuous field impervious surface change (ISC) mapping using Landsat data is an effective way to quantify spatiotemporal dynamics of urbanization. It is well acknowledged that Landsat-based estimation of impervious surface is subject to seasonal and phenological variations. The overall goal of this paper is to map 200-02010 ISC for India using Global Land Survey datasets and training data only available for 2010. To this end, a method was developed that could transfer the regression tree model developed for mapping 2010 impervious surface to 2000 using an iterative training and prediction (ITP) approach An independent validation dataset was also developed using Google Earth imagery. Based on the reference ISC from the validation dataset, the RMSE of predicted ISC was estimated to be 18.4%. At 95% confidence, the total estimated ISC for India between 2000 and 2010 is 2274.62 +/- 7.84 sq km.

  5. Global biogeophysical interactions between historical deforestation and climate through land surface albedo and interactive ocean

    NASA Astrophysics Data System (ADS)

    Wang, Ye

    2017-02-01

    Deforestation is expanding and accelerating into the remaining areas of undisturbed forest, and the quality of the remaining forests is declining today. Assessing the climatic impacts of deforestation can help to rectify this alarming situation. In this paper, how historical deforestation may affect global climate through interactive ocean and surface albedo is examined using an Earth system model of intermediate complexity (EMIC). Control and anomaly integrations are performed for 1000 years. In the anomaly case, cropland is significantly expanded since AD 1700. The response of climate in deforested areas is not uniform between the regions. In the background of a global cooling of 0.08 °C occurring with cooler surface air above 0.4 °C across 30° N to 75° N from March to September, the surface albedo increase has a global cooling effect in response to global-scale replacement of forests by cropland, especially over northern mid-high latitudes. The northern mid-latitude (30° N-60° N) suffers a prominent cooling in June, suggesting that this area is most sensitive to cropland expansion through surface albedo. Most regions show a consistent trend between the overall cooling in response to historical deforestation and its resulting cooling due to surface albedo anomaly. Furthermore, the effect of the interactive ocean on shaping the climate response to deforestation is greater than that of prescribed SSTs in most years with a maximum spread of 0.05 °C. This difference is more prominent after year 1800 than that before due to the more marked deforestation. These findings show the importance of the land cover change and the land surface albedo, stressing the necessity to analyze other biogeophysical processes of deforestation using interactive ocean.

  6. Global Land Information System

    USGS Publications Warehouse

    ,

    1999-01-01

    The Global Land Information System (GLIS) is a World Wide Web-based query tool developed by the U.S. Geological Survey (USGS) to provide data and information about the Earth's land surface. Examples of holdings available through the GLIS include cartographic data, topographic data, soils data, aerial photographs, and satellite images from various agencies and cooperators located around the world. Both hard copy and digital data collections are represented in the GLIS, and preview images are available for millions of the products in the system.

  7. Simulating global and local surface temperature changes due to Holocene anthropogenic land cover change

    NASA Astrophysics Data System (ADS)

    He, Feng; Vavrus, Steve J.; Kutzbach, John E.; Ruddiman, William F.; Kaplan, Jed O.; Krumhardt, Kristen M.

    2014-01-01

    Surface albedo changes from anthropogenic land cover change (ALCC) represent the second largest negative radiative forcing behind aerosol during the industrial era. Using a new reconstruction of ALCC during the Holocene era by Kaplan et al. (2011), we quantify the local and global temperature response induced by Holocene ALCC in the Community Climate System Model, version 4. We find that Holocene ALCC causes a global cooling of 0.17°C due to the biogeophysical effects of land-atmosphere exchange of momentum, moisture, and radiative and heat fluxes. On the global scale, the biogeochemical effects of Holocene ALCC from carbon emissions dominate the biogeophysical effects by causing 0.9°C global warming. The net effects of Holocene ALCC amount to a global warming of 0.73°C during the preindustrial era, which is comparable to the ~0.8°C warming during industrial times. On local to regional scales, such as parts of Europe, North America, and Asia, the biogeophysical effects of Holocene ALCC are significant and comparable to the biogeochemical effect.

  8. A Global Database of Land Surface Parameters at 1-km Resolution in Meteorological and Climate Models.

    NASA Astrophysics Data System (ADS)

    Masson, Valéry; Champeaux, Jean-Louis; Chauvin, Fabrice; Meriguet, Christelle; Lacaze, Roselyne

    2003-05-01

    Ecoclimap, a new complete surface parameter global dataset at a 1-km resolution, is presented. It is intended to be used to initialize the soil-vegetation-atmosphere transfer schemes (SVATs) in meteorological and climate models (at all horizontal scales). The database supports the `tile' approach, which is utilized by an increasing number of SVATs. Two hundred and fifteen ecosystems representing areas of homogeneous vegetation are derived by combining existing land cover maps and climate maps, in addition to using Advanced Very High Resolution Radiometer (AVHRR) satellite data. Then, all surface parameters are derived for each of these ecosystems using lookup tables with the annual cycle of the leaf area index (LAI) being constrained by the AVHRR information. The resulting LAI is validated against a large amount of in situ ground observations, and it is also compared to LAI derived from the International Satellite Land Surface Climatology Project (ISLSCP-2) database and the Polarization and Directionality of the Earth's Reflectance (POLDER) satellite. The comparison shows that this new LAI both reproduces values coherent at large scales with other datasets, and includes the high spatial variations owing to the input land cover data at a 1-km resolution. In terms of climate modeling studies, the use of this new database is shown to improve the surface climatology of the ARPEGE climate model.

  9. Global land surface evaporation trend during the past half century: Corroboration by Clausius-Clapeyron scaling

    NASA Astrophysics Data System (ADS)

    Brutsaert, Wilfried

    2017-08-01

    Analyses of satellite data mainly over the world's ocean surfaces have shown that during 1986-2006 global average values of atmospheric water vapor, precipitation and evaporation have increased at a relative rate of 0.0013a-1 ; this is roughly in accordance with the Clausius-Clapeyron equation for the average temperature trend during this period, and amounts to 0.065K-1 at the average temperature of T =14∘ C . Application of this concept over the world's land surfaces yields an average global evaporation trend during the past half century of around 0.4 to 0.5 mm a-2 ; this confirms the values obtained in previous studies with totally different methods.

  10. Hyperresolution Global Land Surface Modeling: Meeting a Grand Challenge for Monitoring Earth's Terrestrial Water

    NASA Technical Reports Server (NTRS)

    Wood, Eric F.; Roundy, Joshua K.; Troy, Tara J.; van Beek, L. P. H.; Bierkens, Marc F. P.; 4 Blyth, Eleanor; de Roo, Ad; Doell. Petra; Ek, Mike; Famiglietti, James; hide

    2011-01-01

    Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (approx.10-100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface-subsurface interactions due to fine-scale topography and vegetation; improved representation of land-atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 10(exp 9) unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a grand challenge to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

  11. Hyperresolution Global Land Surface Modeling: Meeting a Grand Challenge for Monitoring Earth's Terrestrial Water

    NASA Technical Reports Server (NTRS)

    Wood, Eric F.; Roundy, Joshua K.; Troy, Tara J.; van Beek, L. P. H.; Bierkens, Marc F. P.; 4 Blyth, Eleanor; de Roo, Ad; Doell. Petra; Ek, Mike; Famiglietti, James; Gochis, David; van de Giesen, Nick; Houser, Paul; Jaffe, Peter R.; Kollet, Stefan; Lehner, Bernhard; Lettenmaier, Dennis P.; Peters-Lidard, Christa; Sivpalan, Murugesu; Sheffield, Justin; Wade, Andrew; Whitehead, Paul

    2011-01-01

    Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (approx.10-100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface-subsurface interactions due to fine-scale topography and vegetation; improved representation of land-atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 10(exp 9) unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a grand challenge to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

  12. Trends in ERS and Envisat (A)ATSR Global Land Surface Temperature Data Since 1991

    NASA Astrophysics Data System (ADS)

    Kogler, Christian; Pinnock, Simon; Arino, Olivier; Casadio, Stefano; Corlett, Gary; Prata, Fred; Bras, Teresa

    2010-12-01

    Land surface temperature (LST) is a key parameter in the physical study of atmosphere-land interactions as well as for global warming and climate change monitoring on a longer timescale. The main tool to obtain LST as such a key parameter at global scale with different spatial and temporal resolutions is remote sensing. To retrieve highly accurate LSTs, measured radiances at the sensor have to be corrected for emissivity, atmospheric effects and contaminating clouds. This study is based on LST data provided by the Along-Track Scanning Radiometer (ATSR) and the Advanced ATSR (AATSR) on board the three ESA satellites ERS-1, ERS-2 and ENVISAT. The analysis covers data from August 1991 up to December 2009 and contains detailed investigations on global as well as on regional scale with a temporal resolution of one month, outlining problems and restrictions within the time series due to cloud contamination and failing cloud detection tests. It is demonstrated that trends, for cooling as well as for warming, rather show trends in cloud contamination, than real trends in LST.

  13. Assessing the Influence of Human Activities on Global Water Resources Using an Advanced Land Surface Model

    NASA Astrophysics Data System (ADS)

    Pokhrel, Y.; Hanasaki, N.; Koirala, S.; Kanae, S.; Oki, T.

    2010-12-01

    In order to examine the impact of human intervention on the global hydrological cycle, a Land Surface Model was enhanced with schemes to assess the anthropogenic disturbance on the natural water flow at the global scale. Four different schemes namely; reservoir operation, crop growth, environmental flow, and anthropogenic water withdrawal modules from a state-of-the-art global water resources assessment model called H08 were integrated into an offline version of LSM, Minimal Advance Treatment of Surface Interaction and Runoff (MATSIRO). MATSIRO represents majority of the hydrological processes of water and energy exchange between the land surface and the atmosphere on a physical basis and is designed to be coupled with GCM. The integrated model presented here thus has the capability to simulate both natural and anthropogenic flows of water globally at a spatial resolution of 1°x1°, considering dam operation, domestic, industrial and agricultural water withdrawals and environmental flow requirements. The model can also be coupled with climate models to assess the impact of human activities on the climate system. A simple groundwater scheme was also incorporated and the model can be used to assess the change in water table due to groundwater pumping for irrigation. The model was validated by comparing simulated soil moisture, river discharge and Terrestrial Water Storage Anomaly (TWSA) with observations. The model performs well in simulating TWSA as compared to GRACE observation in different river basins ranging from very wet to very dry. Soil moisture cannot be validated globally because of the lack of validation datasets. For Illinois region, where long term soil moisture observations are available, the model captures the seasonal variation quite well. The simulated global potential irrigation demand is about 1100km3/year, which is within the range of previously published estimates based on various water balance models and LSMs. The model has an advanced option

  14. Assessment of the consistency among global microwave land surface emissivity products

    NASA Astrophysics Data System (ADS)

    Norouzi, H.; Temimi, M.; Prigent, C.; Turk, J.; Khanbilvardi, R.; Tian, Y.; Furuzawa, F.; Masunaga, H.

    2014-09-01

    The goal of this work is to inter-compare a number of global land surface emissivity products over various land-cover conditions to assess their consistency. Ultimately, the discrepancies between the studied emissivity products will help interpreting the divergences among numerical weather prediction models in which land emissivity is a key surface boundary parameter. The intercompared retrieved land emissivity products were generated over five-year period (2003-2007) using observations from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), Special Sensor Microwave Imager (SSM/I), The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Windsat. First, all products were reprocessed in the same projection and spatial resolution as they were generated from sensors with various configurations. Then, the mean value and standard deviations of monthly emissivity values were calculated for each product to assess the spatial distribution of the consistencies/inconsistencies among the products across the globe. The emissivity values from four products were also compared to soil moisture estimates and satellite-based vegetation index to assess their sensitivities to the changes in land surface conditions. Results show that systematic differences among products exist and variation of emissivities at each product has similar frequency dependency at any land cover type. Monthly means of emissivity values from AMSR-E in the vertical and horizontal polarizations seem to be systematically lower across various land cover condition which may be attributed to the 1.30 a.m./p.m. overpass time of the sensor and possibly a residual skin temperature effect in the product. The standard deviation of the analysed products was the lowest (less than 0.01) in rain forest regions for all products and the highest in northern latitudes, above 0.04 for AMSR-E and SSM/I and around 0.03 for WindSat. Despite differences in absolute emissivity estimates

  15. Simulating global and local surface temperature changes due to Holocene anthropogenic land cover change

    NASA Astrophysics Data System (ADS)

    He, F.; Vavrus, S. J.; Kutzbach, J. E.; Ruddiman, W. F.; Kaplan, J. O.; Krumhardt, K. M.

    2015-12-01

    Surface albedo changes from anthropogenic land cover change (ALCC) represent the second-largest negative radiative forcing behind aerosol during the industrial era. Using a new reconstruction of ALCC during the Holocene era by Kaplan et al. [2011], we quantify the local and global temperature response induced by Holocene ALCC in the Community Climate System Model, version 4 (CCSM4). With 1-degree resolution of the CCSM4 slab-ocean model,we find that Holocene ALCC cause a global cooling of 0.17 °C due to the biogeophysical effects of land-atmosphere exchange of momentum, moisture, radiative and heat fluxes. On the global scale, the biogeochemical effects of Holocene ALCC from carbon emissions dominate the biogeophysical effects by causing 0.9 °C global warming. The net effects of Holocene ALCC amount to a global warming of 0.73 °C during the pre-industrial era, which is comparable to the ~0.8 °C warming during industrial times. On local to regional scales, such as parts of Europe, North America and Asia, the biogeophysical effects of Holocene ALCC are significant and comparable to the biogeochemical effect. The lack of ocean dynamics in the 1° CCSM4 slab-ocean simulations could underestimate the climate sensitivity because of the lack of feedbacks from ocean heat transport [Kutzbach et al., 2013; Manabe and Bryan, 1985]. In 1° CCSM4 fully coupled simulations, the climate sensitivity is ~65% larger than the 1° CCSM4 slab-ocean simulations during the Holocene (5.3 °C versus 3.2 °C) [Kutzbach et al., 2013]. With this greater climate sensitivity, the biogeochemical effects of Holocene ALCC could have caused a global warming of ~1.5 °C, and the net biogeophysical and biogeochemical effects of Holocene ALCC could cause a global warming of 1.2 °C during the preindustrial era in our simulations, which is 50% higher than the global warming of ~0.8 °C during industrial times.

  16. A gridded global data set of soil, intact regolith, and sedimentary deposit thicknesses for regional and global land surface modeling

    DOE PAGES

    Pelletier, Jon D.; Broxton, Patrick D.; Hazenberg, Pieter; ...

    2016-01-22

    Earth’s terrestrial near-subsurface environment can be divided into relatively porous layers of soil, intact regolith, and sedimentary deposits above unweathered bedrock. Variations in the thicknesses of these layers control the hydrologic and biogeochemical responses of landscapes. Currently, Earth System Models approximate the thickness of these relatively permeable layers above bedrock as uniform globally, despite the fact that their thicknesses vary systematically with topography, climate, and geology. To meet the need for more realistic input data for models, we developed a high-resolution gridded global data set of the average thicknesses of soil, intact regolith, and sedimentary deposits within each 30 arcsecmore » (~ 1 km) pixel using the best available data for topography, climate, and geology as input. Our data set partitions the global land surface into upland hillslope, upland valley bottom, and lowland landscape components and uses models optimized for each landform type to estimate the thicknesses of each subsurface layer. On hillslopes, the data set is calibrated and validated using independent data sets of measured soil thicknesses from the U.S. and Europe and on lowlands using depth to bedrock observations from groundwater wells in the U.S. As a result, we anticipate that the data set will prove useful as an input to regional and global hydrological and ecosystems models.« less

  17. Assessment of the consistency among global microwave land surface emissivity products

    NASA Astrophysics Data System (ADS)

    Norouzi, H.; Temimi, M.; Prigent, C.; Turk, J.; Khanbilvardi, R.; Tian, Y.; Furuzawa, F. A.; Masunaga, H.

    2015-03-01

    The goal of this work is to intercompare four global land surface emissivity products over various land-cover conditions to assess their consistency. The intercompared land emissivity products were generated over a 5-year period (2003-2007) using observations from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), the Special Sensor Microwave Imager (SSM/I), the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), and WindSat. First, all products were reprocessed in the same projection and spatial resolution as they were generated from sensors with various configurations. Then, the mean value and standard deviations of monthly emissivity values were calculated for each product to assess the spatial distribution of the consistencies/inconsistencies among the products across the globe. The emissivity products were also compared to soil moisture estimates and a satellite-based vegetation index to assess their sensitivities to changes in land surface conditions. Results show the existence of systematic differences among the products. Also, it was noticed that emissivity values in each product have similar frequency dependency over different land-cover types. Monthly means of emissivity values from AMSR-E in the vertical and horizontal polarizations seem to be systematically lower than the rest of the products across various land-cover conditions which may be attributed to the 01:30/13:30 LT overpass time of the sensor and possibly a residual skin temperature effect in the product. The standard deviation of the analyzed products was lowest (less than 0.01) in rain forest regions for all products and highest at northern latitudes, above 0.04 for AMSR-E and SSM/I and around 0.03 for WindSat. Despite differences in absolute emissivity estimates, all products were similarly sensitive to changes in soil moisture and vegetation. The correlation between the emissivity polarization differences and normalized difference vegetation index

  18. 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

  19. SYNOPTIC GLOBAL REMOTE SENSING OF LAND SURFACE VEGETATION: OVERVIEW OF DAILY DATA QUALITY, CHALLENGES, AND OPPORTUNITIES

    NASA Astrophysics Data System (ADS)

    Barreto-Munoz, A.; Didan, K.

    2009-12-01

    Continuous acquisition of global satellite imagery over the years has contributed to the creation of a long data record from AVHRR, MODIS, TM, SPOT VGT, and other sensors. These records account now for 30+ years, and as the archive grows, it becomes an invaluable source of data for many environmental related studies dealing with trends and changes from local to global scale. Synoptic global remote sensing provides a multitude of land surface state variables and serves as a major foundation for global change research. However, these records are inhibited with problems that need to be accounted for in order to understand the limits and improve the science results derived from these records. The presence of clouds, aerosols, spatial gaps, variable viewing geometry, inconsistent atmosphere corrections, multiple reprocessing, and different sensors characteristics, makes it difficult to obtain frequently high quality data everywhere and every time. Moreover, these issues are location and season dependent making it even more difficult to construct the consistent time series required to study change over time. To evaluate these records, we analyzed 30+ years (1981 to 1999 and 2000 to 2009) of daily global land surface measurements (CMG resolution) from AVHRR (N07, N09, N11 and N14) and MODIS (AQUA and TERRA, Collection 5, C5). We stratified the data based on land cover, latitudinal zone, and season and we examined the daily data quality, including cloud persistence, aerosol loads, data gaps, and an index of reliability that measures how likely an observation is acceptable for research. The aim was to generate aggregate maps of cloud distribution, aerosol levels distribution, and data reliability distribution in both time and space. This information was then converted into an uncertainty measure at the pixel level that indicates how suspect or significant a result could potentially be, depending on its location and season and consequently what geographic locations and times

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

    NASA Astrophysics Data System (ADS)

    Cuntz, M.; Haverd, V.

    2013-12-01

    Transfer of energy and moisture in frozen soil, and hence the active layer depth, are strongly influenced by the soil freezing curve which specifies liquid moisture content as a function of temperature. However, the curve is typically not represented in global land surface models, with less physically-based approximations being used instead. In this work, we develop a physically accurate model of soil freeze-thaw processes, suitable for use in a global land surface scheme. We incorporated soil freeze-thaw processes into an existing detailed model for the transfer of heat, liquid water and water vapor in soils, including isotope diagnostics - Soil-Litter-Iso (SLI, Haverd & Cuntz 2010), which has been used successfully for water and carbon balances of the Australian continent (Haverd et al. 2013). A unique feature of SLI is that fluxes of energy and moisture are coupled using a single system of linear equations. The extension to include freeze-thaw processes and snow maintains this elegant coupling, requiring only coefficients in the linear equations to be modified. No impedance factor for hydraulic conductivity is needed because of the formulation by matric flux potential rather than pressure head. Iterations are avoided which results in the same computational speed as without freezing. The extended model is evaluated extensively in stand-alone mode (against theoretical predictions, lab experiments and field data) and as part of the CABLE global land surface scheme. SLI accurately solves the classical Stefan problem of a homogeneous medium undergoing a phase change. The model also accurately reproduces the freezing front, which is observed in laboratory experiments (Hansson et al. 2004). SLI was further tested against observations at a permafrost site in Tibet (Weismüller et al. 2011). It reproduces seasonal thawing and freezing of the active layer to within 3 K of the observed soil temperature and to within 10% of the observed volumetric liquid soil moisture

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

    NASA Astrophysics Data System (ADS)

    Cuntz, Matthias; Haverd, Vanessa

    2014-05-01

    Transfer of energy and moisture in frozen soil, and hence the active layer depth, are strongly influenced by the soil freezing curve which specifies liquid moisture content as a function of temperature. However, the curve is typically not represented in global land surface models, with less physically-based approximations being used instead. In this work, we develop a physically accurate model of soil freeze-thaw processes, suitable for use in a global land surface scheme. We incorporated soil freeze-thaw processes into an existing detailed model for the transfer of heat, liquid water and water vapor in soils, including isotope diagnostics - Soil-Litter-Iso (SLI, Haverd & Cuntz 2010), which has been used successfully for water and carbon balances of the Australian continent (Haverd et al. 2013). A unique feature of SLI is that fluxes of energy and moisture are coupled using a single system of linear equations. The extension to include freeze-thaw processes and snow maintains this elegant coupling, requiring only coefficients in the linear equations to be modified. No impedance factor for hydraulic conductivity is needed because of the formulation by matric flux potential rather than pressure head. Iterations are avoided which results in the same computational speed as without freezing. The extended model is evaluated extensively in stand-alone mode (against theoretical predictions, lab experiments and field data) and as part of the CABLE global land surface scheme. SLI accurately solves the classical Stefan problem of a homogeneous medium undergoing a phase change. The model also accurately reproduces the freezing front, which is observed in laboratory experiments (Hansson et al. 2004). SLI was further tested against observations at a permafrost site in Tibet (Weismüller et al. 2011). It reproduces seasonal thawing and freezing of the active layer to within 3 K of the observed soil temperature and to within 10% of the observed volumetric liquid soil moisture

  2. Global land surface albedo maps from MODIS using the Google Earth Engine

    NASA Astrophysics Data System (ADS)

    Mitraka, Zina; Benas, Nikolaos; Gorelick, Noel; Chrysoulakis, Nektarios

    2016-04-01

    The land surface albedo (LSA) is a critical physical variable, which influences the Earth's climate by affecting the energy budget and distribution in the Earth-atmosphere system. Its role is highly significant in both global and local scales; hence, LSA measurements provide a quantitative means for better constraining global and regional scale climate modelling efforts. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, on board NASA's Terra and Aqua platforms, provides the parameters needed for the computation of LSA on an 8-day temporal scale and a variety of spatial scales (ranging between 0.5 - 5 km). This dataset was used here for the LSA estimation and its changes over the study area at 0.5 km spatial resolution. More specifically, the MODIS albedo product was used, which includes both the directional-hemispherical surface reflectance (black-sky albedo) and the bi-hemispherical surface reflectance (white-sky albedo). The LSA was estimated for the whole globe on an 8-day basis for the whole time period covered by MODIS acquisitions (i.e. 2000 until today). To estimate LSA from black-sky and white-sky albedos, the fraction of the diffused radiation is needed, a function of the Aerosol Optical Thickness (AOT). Required AOT information was acquired from the MODIS AOT product at 1̊ × 1̊ spatial resolution. Since LSA also depends on solar zenith angle (SZA), 8-day mean LSA values were computed as averages of corresponding LSA values for representative SZAs covering the 24-hour day. The estimated LSA was analysed in terms of both spatial and seasonal characteristics, while LSA changes during the period examined were assessed. All computation were performed using the Google Earth Engine (GEE). The GEE provided access to all the MODIS products needed for the analysis without the need of searching or downloading. Moreover, the combination of MODIS products in both temporal and spatial terms was fast and effecting using the GEE API (Application

  3. The effect of GCM biases on global runoff simulations of a land surface model

    NASA Astrophysics Data System (ADS)

    Papadimitriou, Lamprini V.; Koutroulis, Aristeidis G.; Grillakis, Manolis G.; Tsanis, Ioannis K.

    2017-09-01

    Global climate model (GCM) outputs feature systematic biases that render them unsuitable for direct use by impact models, especially for hydrological studies. To deal with this issue, many bias correction techniques have been developed to adjust the modelled variables against observations, focusing mainly on precipitation and temperature. However, most state-of-the-art hydrological models require more forcing variables, in addition to precipitation and temperature, such as radiation, humidity, air pressure, and wind speed. The biases in these additional variables can hinder hydrological simulations, but the effect of the bias of each variable is unexplored. Here we examine the effect of GCM biases on historical runoff simulations for each forcing variable individually, using the JULES land surface model set up at the global scale. Based on the quantified effect, we assess which variables should be included in bias correction procedures. To this end, a partial correction bias assessment experiment is conducted, to test the effect of the biases of six climate variables from a set of three GCMs. The effect of the bias of each climate variable individually is quantified by comparing the changes in simulated runoff that correspond to the bias of each tested variable. A methodology for the classification of the effect of biases in four effect categories (ECs), based on the magnitude and sensitivity of runoff changes, is developed and applied. Our results show that, while globally the largest changes in modelled runoff are caused by precipitation and temperature biases, there are regions where runoff is substantially affected by and/or more sensitive to radiation and humidity. Global maps of bias ECs reveal the regions mostly affected by the bias of each variable. Based on our findings, for global-scale applications, bias correction of radiation and humidity, in addition to that of precipitation and temperature, is advised. Finer spatial-scale information is also provided

  4. Incorporation of groundwater pumping in a global Land Surface Model with the representation of human impacts

    NASA Astrophysics Data System (ADS)

    Pokhrel, Yadu N.; Koirala, Sujan; Yeh, Pat J.-F.; Hanasaki, Naota; Longuevergne, Laurent; Kanae, Shinjiro; Oki, Taikan

    2015-01-01

    Observations indicate that groundwater levels are declining in many regions around the world. Simulating such depletion of groundwater at the global scale still remains a challenge because most global Land Surface Models (LSMs) lack the physical representation of groundwater dynamics in general and well pumping in particular. Here we present an integrated hydrologic model, which explicitly simulates groundwater dynamics and pumping within a global LSM that also accounts for human activities such as irrigation and reservoir operation. The model is used to simulate global water fluxes and storages with a particular focus on groundwater withdrawal and depletion in the High Plains Aquifer (HPA) and Central Valley Aquifer (CVA). Simulated global groundwater withdrawal and depletion for the year 2000 are 570 and 330 km3 yr-1, respectively; the depletion agrees better with observations than our previous model result without groundwater representation, but may still contain certain uncertainties and is on the higher side of other estimates. Groundwater withdrawals from the HPA and CVA are ˜22 and ˜9 km3 yr-1, respectively, which are also consistent with the observations of ˜24 and ˜13 km3 yr-1. The model simulates a significant decline in total terrestrial water storage in both regions as caused mainly by groundwater storage depletion. Groundwater table declined by ˜14 cm yr-1 in the HPA during 2003-2010; the rate is even higher (˜71 cm yr-1) in the CVA. These results demonstrate the potential of the developed model to study the dynamic relationship between human water use, groundwater storage, and the entire hydrologic cycle.

  5. Global Assessment of Land Surface Temperature From Geostationary Satellites and Model Estimates

    NASA Technical Reports Server (NTRS)

    Reichle, Rolf H.; Liu, Q.; Minnis, P.; daSilva, A. M., Jr.; Palikonda, R.; Yost, C. R.

    2012-01-01

    Land surface (or 'skin') temperature (LST) lies at the heart of the surface energy balance and is a key variable in weather and climate models. In this research we compare two global and independent data sets: (i) LST retrievals from five geostationary satellites generated at the NASA Langley Research Center (LaRC) and (ii) LST estimates from the quasi-operational NASA GEOS-5 global modeling and assimilation system. The objective is to thoroughly understand both data sets and their systematic differences in preparation for the assimilation of the LaRC LST retrievals into GEOS-5. As expected, mean differences (MD) and root-mean-square differences (RMSD) between modeled and retrieved LST vary tremendously by region and time of day. Typical (absolute) MD values range from 1-3 K in Northern Hemisphere mid-latitude regions to near 10 K in regions where modeled clouds are unrealistic, for example in north-eastern Argentina, Uruguay, Paraguay, and southern Brazil. Typically, model estimates of LST are higher than satellite retrievals during the night and lower during the day. RMSD values range from 1-3 K during the night to 2-5 K during the day, but are larger over the 50-120 W longitude band where the LST retrievals are derived from the FY2E platform

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  8. The Development and Validation of a New Land Surface Model for Regional and Global Climate Modeling

    NASA Astrophysics Data System (ADS)

    Lynch-Stieglitz, Marc

    1995-11-01

    A new land-surface scheme intended for use in mesoscale and global climate models has been developed and validated. The ground scheme consists of 6 soil layers. Diffusion and a modified tipping bucket model govern heat and water flow respectively. A 3 layer snow model has been incorporated into a modified BEST vegetation scheme. TOPMODEL equations and Digital Elevation Model data are used to generate baseflow which supports lowland saturated zones. Soil moisture heterogeneity represented by saturated lowlands subsequently impacts watershed evapotranspiration, the partitioning of surface fluxes, and the development of the storm hydrograph. Five years of meteorological and hydrological data from the Sleepers river watershed located in the eastern highlands of Vermont where winter snow cover is significant were then used to drive and validate the new scheme. Site validation data were sufficient to evaluate model performance with regard to various aspects of the watershed water balance, including snowpack growth/ablation, the spring snowmelt hydrograph, storm hydrographs, and the seasonal development of watershed evapotranspiration and soil moisture. By including topographic effects, not only are the main spring hydrographs and individual storm hydrographs adequately resolved, but the mechanisms generating runoff are consistent with current views of hydrologic processes. The seasonal movement of the mean water table depth and the saturated area of the watershed are consistent with site data and the overall model hydroclimatology, including the surface fluxes, seems reasonable.

  9. 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.

  10. 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.

  11. Variability of basin scale water resources indicators derived from global hydrological and land surface models

    NASA Astrophysics Data System (ADS)

    Werner, Micha; Blyth, Eleanor; Schellekens, Jaap

    2016-04-01

    Global hydrological and land-surface models are becoming increasingly available, and as the resolution of these improves, as well how hydrological processes are represented, so does their potential. These offer consistent datasets at the global scale, which can be used to establish water balances and derive policy relevant indicators in medium to large basins, including those that are poorly gauged. However, differences in model structure, model parameterisation, and model forcing may result in quite different indicator values being derived, depending on the model used. In this paper we explore indicators developed using four land surface models (LSM) and five global hydrological models (GHM). Results from these models have been made available through the Earth2Observe project, a recent research initiative funded by the European Union 7th Research Framework. All models have a resolution of 0.5 arc degrees, and are forced using the same WATCH-ERA-Interim (WFDEI) meteorological re-analysis data at a daily time step for the 32 year period from 1979 to 2012. We explore three water resources indicators; an aridity index, a simplified water exploitation index; and an indicator that calculates the frequency of occurrence of root zone stress. We compare indicators derived over selected areas/basins in Europe, Colombia, Southern Africa, the Indian Subcontinent and Australia/New Zealand. The hydrological fluxes calculated show quite significant differences between the nine models, despite the common forcing dataset, with these differences reflected in the indicators subsequently derived. The results show that the variability between models is related to the different climates types, with that variability quite logically depending largely on the availability of water. Patterns are also found in the type of models that dominate different parts of the distribution of the indicator values, with LSM models providing lower values, and GHM models providing higher values in some

  12. Global and Regional Surface Albedo Changes due to Land Use Transformation: an Anthropogenic Source for Climate Change

    NASA Astrophysics Data System (ADS)

    Monier, E.; Wharton, S.; Laabs, B.; Reck, R.

    2005-12-01

    For the past decades, cropland area has been slowly increasing while forests and woodlands diminished, leading to consequent changes in land use resulting from human behavior. Besides, desertification directly affects millions of people around the world and not a single year goes by without new reports of ice melting. More than being an economic issue, land use transformation can prove to have altered the energy balance, and therefore the climate, through surface albedo changes over the past decades. Each land category has its own surface albedo, defined as its solar back scatter and being only a function of the radiation field incident on it and the properties of the land category itself. Using a global surface albedo model (Hummel and Reck, 1979), involving 49 different types of surfaces for each quarter of the year, January-March, April-June, July-September and October-December, surface albedo maps are computed from land usage maps for the 1970s and 1990s. Regional changes in the surface albedo can cause variation in the energy budget of the earth-atmosphere system, specifically in the tropospheric distribution of temperature, and therefore can be an anthropogenic source for climate change at a global scale. Many feedbacks and teleconnections can be found between surface albedo, cloud coverage and CO2 fluxes leading to a potentially unstable energy budget system. In order to fully comprehend climate change, a extensive review on that system and its foundations is expected to be released in 2006.

  13. Improving HJ-1B IRS land surface temperature product using ASTER global emissivity database

    NASA Astrophysics Data System (ADS)

    Li, H.; Hu, T.; Meng, X.; Yongming, D.; Cao, B.; Liu, Q.

    2015-12-01

    Land surface temperature (LST) is a key parameter for hydrological, meteorological, climatological and environmental studies. Currently many operational LST products have been generated using European and American satellite data, i.e., the Advanced Very High Resolution Radiometer (AVHRR), Advanced Along-Track Scanning Radiometer (AATSR) and Moderate Resolution Imaging Spectroradiometer (MODIS). However, few LST product has been produced using Chinese satellite data. Thus, the objective of this study is to generate reliable LST product using Chinese HJ-1B satellite data. The HJ-1B satellite of China, were launched on September 6, 2008, which are used for disaster and environment monitoring. IRS (Infrared Scanner) is one of the key instruments onboard HJ-1B satellite, it can scan the earth every four days, has four spectral bands ranging from the near-infrared to thermal infrared bands (band 1 0.75 - 1.10μm, band 2 1.55-1.75μm, MIR band 3 3.50 - 3.90μm, band 4 10.5-12.5μm) with 720 km swath. It scans ±29° from nadir and the spatial resolution for band1-3 is 150m and 300m for band4. In this study, a single-channel parametric model (SC-PM) algorithm were used to produce 300m LST product from HJ-1B IRS data. The NCEP atmospheric profiles and a parametric model were used for atmospheric correction. In order to improve the accuracy of the land surface emissivity (LSE), the 1km ASTER Global Emissivity Database (GED) and self-developed 5-day 1km vegetation cover product were used for estimating the LSE based on the Vegetation Cover Method. Two years of HJ-1B IRS LST product in Heihe River basin (Gansu province, China) from June 2012 to June 2014 were generated. The LST products were evaluated against ground observations in an arid area of northwest China during the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) experiment. Four barren surface sites and ten vegetated sites were chosen for the evaluation. The results show that the developed HJ-1B IRS

  14. Relating Nimbus-7 37 GHz data to global land-surface evaporation, primary productivity and the atmospheric CO2 concentration

    NASA Technical Reports Server (NTRS)

    Choudhury, B. J.

    1988-01-01

    Global observations at 37 GHz by the Nimbus-7 SMMR are related to zonal variations of land surface evaporation and primary productivity, as well as to temporal variations of atmospheric CO2 concentration. The temporal variation of CO2 concentration and the zonal variations of evaporation and primary productivity are shown to be highly correlated with the satellite sensor data. The potential usefulness of the 37-GHz data for global biospheric and climate studies is noted.

  15. Relating Nimbus-7 37 GHz data to global land-surface evaporation, primary productivity and the atmospheric CO2 concentration

    NASA Technical Reports Server (NTRS)

    Choudhury, B. J.

    1988-01-01

    Global observations at 37 GHz by the Nimbus-7 SMMR are related to zonal variations of land surface evaporation and primary productivity, as well as to temporal variations of atmospheric CO2 concentration. The temporal variation of CO2 concentration and the zonal variations of evaporation and primary productivity are shown to be highly correlated with the satellite sensor data. The potential usefulness of the 37-GHz data for global biospheric and climate studies is noted.

  16. An enhanced VIIRS aerosol optical thickness (AOT) retrieval algorithm over land using a global surface reflectance ratio database

    NASA Astrophysics Data System (ADS)

    Zhang, Hai; Kondragunta, Shobha; Laszlo, Istvan; Liu, Hongqing; Remer, Lorraine A.; Huang, Jingfeng; Superczynski, Stephen; Ciren, Pubu

    2016-09-01

    The Visible/Infrared Imager Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite has been retrieving aerosol optical thickness (AOT), operationally and globally, over ocean and land since shortly after S-NPP launch in 2011. However, the current operational VIIRS AOT retrieval algorithm over land has two limitations in its assumptions for land surfaces: (1) it only retrieves AOT over the dark surfaces and (2) it assumes that the global surface reflectance ratios between VIIRS bands are constants. In this work, we develop a surface reflectance ratio database over land with a spatial resolution 0.1° × 0.1° using 2 years of VIIRS top of atmosphere reflectances. We enhance the current operational VIIRS AOT retrieval algorithm by applying the surface reflectance ratio database in the algorithm. The enhanced algorithm is able to retrieve AOT over both dark and bright surfaces. Over bright surfaces, the VIIRS AOT retrievals from the enhanced algorithm have a correlation of 0.79, mean bias of -0.008, and standard deviation (STD) of error of 0.139 when compared against the ground-based observations at the global AERONET (Aerosol Robotic Network) sites. Over dark surfaces, the VIIRS AOT retrievals using the surface reflectance ratio database improve the root-mean-square error from 0.150 to 0.123. The use of the surface reflectance ratio database also increases the data coverage of more than 20% over dark surfaces. The AOT retrievals over bright surfaces are comparable to MODIS Deep Blue AOT retrievals.

  17. The recent hiatus in global warming of the land surface: Scale-dependent breakpoint occurrences in space and time

    NASA Astrophysics Data System (ADS)

    Ying, Lingxiao; Shen, Zehao; Piao, Shilong

    2015-08-01

    The spatial and temporal variability of the recent land warming hiatus have seldom been explored, despite their importance for understanding the mechanisms underlying the phenomenon. In this study, we applied piecewise linear regression to investigate the spatiotemporal patterns of the breakpoint time of warming over 40 years (1974-2013). Our results showed that at the global scale, mean annual temperature (MAT) over the land increased significantly until 2005 and that the warming trend then stalled. However, the breakpoint time of the warming varied greatly among different seasons and continents. We found no statistically significant breakpoint in MAT over the Northern Hemisphere, but MAT over the Southern Hemisphere showed a significant breakpoint (P < 0.001) in 1979. At the seasonal scale, only the winter season (December-January-February) showed a statistically significant breakpoint in global land temperature. The other seasons showed continuous increasing temperature during the whole study period. Our study examined the recent global warming hiatus on the land surface using an area-weighted summary of a scale-dependent phenomenon with substantial spatiotemporal heterogeneity and revealed the winter cooling in the Northern Hemisphere low-middle latitudes in 1999-2008 as the major contributor to the global warming hiatus on land surface in 2005. This result highlights the importance of using a statistical method to identify the timing of climate phase change. A better understanding of the processes behind the spatiotemporal patterns of local-scale breakpoint occurrences in land surface temperature would shed new light on the mechanisms of the recent global warming hiatus.

  18. Global Land Information System (GLIS)

    USGS Publications Warehouse

    ,

    1992-01-01

    The Global Land Information System (GLIS) is an interactive computer system developed by the U.S. Geological Survey (USGS) for scientists seeking sources of information about the Earth's land surfaces. GLIS contains "metadata," that is, descriptive information about data sets. Through GLIS, scientists can evaluate data sets, determine their availability, and place online requests for products. GLIS is more, however, than a mere list of products. It offers online samples of earth science data that may be ordered through the system.

  19. A Modeling Approach to Global Land Surface Monitoring with Low Resolution Satellite Imaging

    NASA Technical Reports Server (NTRS)

    Hlavka, Christine A.; Dungan, Jennifer; Livingston, Gerry P.; Gore, Warren J. (Technical Monitor)

    1998-01-01

    The effects of changing land use/land cover on global climate and ecosystems due to greenhouse gas emissions and changing energy and nutrient exchange rates are being addressed by federal programs such as NASA's Mission to Planet Earth (MTPE) and by international efforts such as the International Geosphere-Biosphere Program (IGBP). The quantification of these effects depends on accurate estimates of the global extent of critical land cover types such as fire scars in tropical savannas and ponds in Arctic tundra. To address the requirement for accurate areal estimates, methods for producing regional to global maps with satellite imagery are being developed. The only practical way to produce maps over large regions of the globe is with data of coarse spatial resolution, such as Advanced Very High Resolution Radiometer (AVHRR) weather satellite imagery at 1.1 km resolution or European Remote-Sensing Satellite (ERS) radar imagery at 100 m resolution. The accuracy of pixel counts as areal estimates is in doubt, especially for highly fragmented cover types such as fire scars and ponds. Efforts to improve areal estimates from coarse resolution maps have involved regression of apparent area from coarse data versus that from fine resolution in sample areas, but it has proven difficult to acquire sufficient fine scale data to develop the regression. A method for computing accurate estimates from coarse resolution maps using little or no fine data is therefore needed.

  20. Global Flood Response Using Satellite Rainfall Information Coupled with Land Surface and Routing Models

    NASA Astrophysics Data System (ADS)

    Adler, R. F.; Wu, H.

    2016-12-01

    The Global Flood Monitoring System (GFMS) (http://flood.umd.edu) has been developed and used in recent years to provide real-time flood detection, streamflow estimates and inundation calculations for most of the globe. The GFMS is driven by satellite-based precipitation, with the accuracy of the flood estimates being primarily dependent on the accuracy of the precipitation analyses and the land surface and routing models used. The routing calculations are done at both 12 km and 1 km resolution. Users of GFMS results include international and national flood response organizations. The devastating floods in October 2015 in South Carolina are analyzed indicating that the GFMS estimated streamflow is accurate and useful indicating significant flooding in the upstream basins. Further downstream the GFMS streamflow underestimates due to the presence of dams which are not accounted for in GFMS. Other examples are given for Yemen and Somalia and for Sri Lanka and southern India. A forecast flood event associated with a typhoon hitting Taiwan is also examined. One-kilometer resolution inundation mapping from GFMS holds the promise of highly useful information for flood disaster response. The algorithm is briefly described and examples are shown for recent cases where inundation estimates available from optical and Synthetic Aperture Radar (SAR) satellite sensors are available. For a case of significant flooding in Texas in May and June along the Brazos River the GFMS calculated streamflow compares favorably with the observed. Available Landsat-based (May 28) and MODIS-based (June 2) inundation analyses from U. of Colorado shows generally good agreement with the GFMS inundation calculation in most of the area where skies were clear and the optical techniques could be applied. The GFMS provides very useful disaster response information on a timely basis. However, there is still significant room for improvement, including improved precipitation information from NASA's Global

  1. Mapping the land surface for global atmosphere-biosphere models: Toward continuous distributions of vegetation's functional properties

    NASA Astrophysics Data System (ADS)

    Defries, Ruth S.; Field, Christopher B.; Fung, Inez; Justice, Christopher O.; Los, Sietse; Matson, Pamela A.; Matthews, Elaine; Mooney, Harold A.; Potter, Christopher S.; Prentice, Katharine; Sellers, Piers J.; Townshend, John R. G.; Tucker, Compton J.; Ustin, Susan L.; Vitousek, Peter M.

    1995-10-01

    Global land surface characteristics are important boundary conditions for global models that describe exchanges of water, energy, and carbon dioxide between the atmosphere and biosphere. Existing data sets of global land cover are based on classification schemes that characterize each grid cell as a discrete vegetation type. Consequently, parameter fields derived from these data sets are dependent on the particular scheme and the number of vegetation types it includes. The functional controls on exchanges of water, energy, and carbon dioxide between the atmosphere and biosphere are now well enough understood that it is increasingly feasible to model these exchanges using a small number of vegetation characteristics that either are related to or closely related to the functional controls. Ideally, these characteristics would be mapped as continuous distributions to capture mixtures and gradients in vegetation within the cell size of the model. While such an approach makes it more difficult to build models from detailed observations at a small number of sites, it increases the potential for capturing functionally important variation within, as well as between, vegetation types. Globally, the vegetation characteristics that appear to be most important in controlling fluxes of water, energy, and carbon dioxide include (1) growth form (tree, shrub, herb), (2) seasonality of woody vegetation (deciduous, evergreen), (3) leaf type (broadleaf, coniferous), (4) photosynthetic pathway of nonwoody vegetation (C3, C4), (5) longevity (annual, perennial), and (6) type and intensity of disturbance (e.g., cultivation, fire history). Many of these characteristics can be obtained through remote sensing, though some require ground-based information. The minimum number and the identity of the required land surface characteristics almost certainly vary with the intended objective, but the philosophy of driving models with continuous distributions of a small number of land surface

  2. Modelling the angular effects on satellite retrieved LST at global scale using a land surface classification

    NASA Astrophysics Data System (ADS)

    Ermida, Sofia; DaCamara, Carlos C.; Trigo, Isabel F.; Pires, Ana C.; Ghent, Darren

    2017-04-01

    Land Surface Temperature (LST) is a key climatological variable and a diagnostic parameter of land surface conditions. Remote sensing constitutes the most effective method to observe LST over large areas and on a regular basis. Although LST estimation from remote sensing instruments operating in the Infrared (IR) is widely used and has been performed for nearly 3 decades, there is still a list of open issues. One of these is the LST dependence on viewing and illumination geometry. This effect introduces significant discrepancies among LST estimations from different sensors, overlapping in space and time, that are not related to uncertainties in the methodologies or input data used. Furthermore, these directional effects deviate LST products from an ideally defined LST, which should represent to the ensemble of directional radiometric temperature of all surface elements within the FOV. Angular effects on LST are here conveniently estimated by means of a kernel model of the surface thermal emission, which describes the angular dependence of LST as a function of viewing and illumination geometry. The model is calibrated using LST data as provided by a wide range of sensors to optimize spatial coverage, namely: 1) a LEO sensor - the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board NASA's TERRA and AQUA; and 2) 3 GEO sensors - the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board EUMETSAT's Meteosat Second Generation (MSG), the Japanese Meteorological Imager (JAMI) on-board the Japanese Meteorological Association (JMA) Multifunction Transport SATellite (MTSAT-2), and NASA's Geostationary Operational Environmental Satellites (GOES). As shown in our previous feasibility studies the sampling of illumination and view angles has a high impact on the obtained model parameters. This impact may be mitigated when the sampling size is increased by aggregating pixels with similar surface conditions. Here we propose a methodology where land surface is

  3. Implementing the Remotely Sensed Evaporative Stress Index Globally Using MODIS Day/Night Land-surface Temperatures

    NASA Astrophysics Data System (ADS)

    Anderson, M. C.; Hain, C.; Otkin, J.

    2014-12-01

    The utility and reliability of standard meteorological drought indices based on measurements of precipitation is limited by the spatial distribution and quality of currently available rainfall data. Furthermore, precipitation-based indices only reflect one component of the surface hydrologic cycle, and cannot readily capture non-precipitation based moisture inputs to the land-surface system (e.g., irrigation, shallow groundwater tables) that may temper drought impacts or variable rates of water consumption across a landscape. As global drought monitoring exercises, such as the Global Drought Information System, continue to expand, a need for tools that complement precipitation-based indicators will also grow. Here we describe a global implementation of the remotely sensed Evaporative Stress Index (ESI) based on anomalies in actual-to-reference evapotranspiration (ET) ratio. For ESI implementations to date, actual ET has been derived via energy balance using the morning land-surface temperature (LST) rise observed with geostationary satellites. In comparison with vegetation indices, LST is a fast-response variable, with the potential for providing early warning of crop stress reflected in increasing canopy temperatures. Our initial work has mainly focused on regional implementations of ESI (e.g., North America, Brazil, Africa) and a global ESI product has not been yet been evaluated. As the global constellation of geostationary sensors continue to mature, some limitations still exist which hamper an implementation of ESI using only geostationary LST. Therefore, a new regression-based methodology which uses twice-daily observations of LST from polar orbiting sensors (such as the Moderate Resolution Imaging Spectrometer - MODIS and the Visible Infrared Imaging Radiometer Suite - VIIRS) has been developed to estimate mid-morning LST needed for ESI from a single sensor. This new global ESI dataset will be evaluated over the 2000-2014 time period against currently used

  4. Global land-surface primary productivity based upon Nimbus-7 37 GHz data

    NASA Technical Reports Server (NTRS)

    Choudhury, B. J.

    1988-01-01

    Accumulation and renewal of organic matter as quantified through net primary productivity (NPP) is considered a very major function of the biosphere, and its estimation is crucial in understanding the carbon cycle. A physically-based model relating NPP to the difference of vertically and horizontally polarized brightness temperatures (Delta T) observed at 37 GHz frequency of the scanning multichannel microwave radiometer on board the Nimbus-7 satellite is used for fitting areally averaged values of NPP and Delta T for five biomes. The land-surface NPP within 80 deg N to 55 deg S is then calculated using the Delta T data and compared with other estimates.

  5. Global land-surface primary productivity based upon Nimbus-7 37 GHz data

    NASA Technical Reports Server (NTRS)

    Choudhury, B. J.

    1988-01-01

    Accumulation and renewal of organic matter as quantified through net primary productivity (NPP) is considered a very major function of the biosphere, and its estimation is crucial in understanding the carbon cycle. A physically-based model relating NPP to the difference of vertically and horizontally polarized brightness temperatures (Delta T) observed at 37 GHz frequency of the scanning multichannel microwave radiometer on board the Nimbus-7 satellite is used for fitting areally averaged values of NPP and Delta T for five biomes. The land-surface NPP within 80 deg N to 55 deg S is then calculated using the Delta T data and compared with other estimates.

  6. Evaluating biases in simulated land surface albedo from CMIP5 global climate models

    NASA Astrophysics Data System (ADS)

    Li, Yue; Wang, Tao; Zeng, Zhenzhong; Peng, Shushi; Lian, Xu; Piao, Shilong

    2016-06-01

    Land surface albedo is a key parameter affecting energy balance and near-surface climate. In this study, we used satellite data to evaluate simulated surface albedo in 37 models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). There was a systematic overestimation in the simulated seasonal cycle of albedo with the highest bias occurring during the Northern Hemisphere's winter months. The bias in surface albedo during the snow-covered season was classified into that in snow cover fraction (SCF) and albedo contrast (β1). There was a general overestimation of β1 due to the simulated snow-covered albedo being brighter than the observed value; negative biases in SCF were not always related to negative albedo biases, highlighting the need for realistic representation of snow-covered albedo in models. In addition, models with a lower leaf area index (LAI) tend to produce a higher surface albedo over the boreal forests during the winter, which emphasizes the necessity of improving LAI simulations in CMIP5 models. Insolation weighting showed that spring albedo biases were of greater importance for climate. The removal of albedo biases is expected to improve temperature simulations particularly over high-elevation regions.

  7. Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

    NASA Technical Reports Server (NTRS)

    Pokhrel, Yadu N.; Hanasaki, Naota; Wada, Yoshihide; Kim, Hyungjun

    2016-01-01

    The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.

  8. Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

    NASA Technical Reports Server (NTRS)

    Pokhrel, Yadu N.; Hanasaki, Naota; Wada, Yoshihide; Kim, Hyungjun

    2016-01-01

    The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.

  9. Analysis of land cover change and rainfall on the global land surface water coverage database for 1987-2015

    NASA Astrophysics Data System (ADS)

    Li, X.; Takeuchi, W.

    2016-06-01

    In this paper, taking into account population density of the world, major river basin was delineated continent wise all over the world using HYDRO1k data. Then, monthly rainfall change from the year 1981 to 2014 and daily LSWC (Land surface water coverage) change from 1987 to 2015 based on each major river basin was computed and compared with each other. A good agreement was found between LSWC pattern and rainfall pattern, showing a seasonal variation characteristic in each year. However, it could be seen that rainfall is not the only factor that bring about change in LSWC. Also, it was found that the change of urban area is very strong. Especially in Yangtze basin, from 2000 to 2012, the urban changed from 0.07% to 0.83%. Moreover, the proportion of cropland increased significantly, especially in Ganges basin increased by 57.64%, grew to nearly 70% from 1992 to 2012. Besides, the trend of consistent growth was showed both in cropland and LSWC. It is indicated that the widespread expansion of cropland may bring about LSWC increasing.

  10. Global water balances reconstructed by multi-model offline simulations of land surface models under GSWP3 (Invited)

    NASA Astrophysics Data System (ADS)

    Oki, T.; KIM, H.; Ferguson, C. R.; Dirmeyer, P.; Seneviratne, S. I.

    2013-12-01

    As the climate warms, the frequency and severity of flood and drought events is projected to increase. Understanding the role that the land surface will play in reinforcing or diminishing these extremes at regional scales will become critical. In fact, the current development path from atmospheric (GCM) to coupled atmosphere-ocean (AOGCM) to fully-coupled dynamic earth system models (ESMs) has brought new awareness to the climate modeling community of the abundance of uncertainty in land surface parameterizations. One way to test the representativeness of a land surface scheme is to do so in off-line (uncoupled) mode with controlled, high quality meteorological forcing. When multiple land schemes are run in-parallel (with the same forcing data), an inter-comparison of their outputs can provide the basis for model confidence estimates and future model refinements. In 2003, the Global Soil Wetness Project Phase 2 (GSWP2) provided the first global multi-model analysis of land surface state variables and fluxes. It spanned the decade of 1986-1995. While it was state-of-the art at the time, physical schemes have since been enhanced, a number of additional processes and components in the water-energy-eco-systems nexus can now be simulated, , and the availability of global, long-term observationally-based datasets that can be used for forcing and validating models has grown. Today, the data exists to support century-scale off-line experiments. The ongoing follow-on to GSWP2, named GSWP3, capitalizes on these new feasibilities and model functionalities. The project's cornerstone is its century-scale (1901-2010), 3-hourly, 0.5° meteorological forcing dataset that has been dynamically downscaled from the Twentieth Century Reanalysis and bias-corrected using monthly Climate Research Unit (CRU) temperature and Global Precipitation Climatology Centre (GPCC) precipitation data. However, GSWP3 also has an important long-term future climate component that spans the 21st century

  11. A multi-layer land surface energy budget model for implicit coupling with global atmospheric simulations

    NASA Astrophysics Data System (ADS)

    Ryder, J.; Polcher, J.; Peylin, P.; Ottlé, C.; Chen, Y.; van Gorsel, E.; Haverd, V.; McGrath, M. J.; Naudts, K.; Otto, J.; Valade, A.; Luyssaert, S.

    2016-01-01

    In Earth system modelling, a description of the energy budget of the vegetated surface layer is fundamental as it determines the meteorological conditions in the planetary boundary layer and as such contributes to the atmospheric conditions and its circulation. The energy budget in most Earth system models has been based on a big-leaf approach, with averaging schemes that represent in-canopy processes. Furthermore, to be stable, that is to say, over large time steps and without large iterations, a surface layer model should be capable of implicit coupling to the atmospheric model. Surface models with large time steps, however, have difficulties in reproducing consistently the energy balance in field observations. Here we outline a newly developed numerical model for energy budget simulation, as a component of the land surface model ORCHIDEE-CAN (Organising Carbon and Hydrology In Dynamic Ecosystems - CANopy). This new model implements techniques from single-site canopy models in a practical way. It includes representation of in-canopy transport, a multi-layer long-wave radiation budget, height-specific calculation of aerodynamic and stomatal conductance, and interaction with the bare-soil flux within the canopy space. Significantly, it avoids iterations over the height of the canopy and so maintains implicit coupling to the atmospheric model LMDz (Laboratoire de Météorologie Dynamique Zoomed model). As a first test, the model is evaluated against data from both an intensive measurement campaign and longer-term eddy-covariance measurements for the intensively studied Eucalyptus stand at Tumbarumba, Australia. The model performs well in replicating both diurnal and annual cycles of energy and water fluxes, as well as the vertical gradients of temperature and of sensible heat fluxes.

  12. The Global Land Information System

    NASA Astrophysics Data System (ADS)

    Oleson, Lyndon R.

    1993-08-01

    The Global Land Information System (GLIS) is an interactive computer system being developed by the U.S. Geological Survey for scientists seeking data pertaining to the Earth's land surface that can be used in global change studies. GLIS contains descriptive information on a variety of regional, continental, and global land data sets. The interactive query services of GLIS allow scientists to assess the potential utility of data sets, determine their availability, and place online requests for data products. In addition to the text-based query services, GLIS offers a number of graphical aids to users accessing the system through one of the supported graphical user interfaces, such as the PG-GLIS package developed for IBM-compatible personal computers. These services include interative specification of geographic search areas, geographic coverage plots, and online digital image browse capabilities. Access to GLIS is provided through either wide-area network or dial-up interfaces. A prototype of the system became operational in June 1991, and full operational status is expected by September 1992. In addition to continued data set expansion, 1992 development plans include the enhancement of data query and visualization services and the addition of a graphical user interface for UNIX workstations.

  13. A multi-layer land surface energy budget model for implicit coupling with global atmospheric simulations

    NASA Astrophysics Data System (ADS)

    Ryder, J.; Polcher, J.; Peylin, P.; Ottlé, C.; Chen, Y.; van Gorsel, E.; Haverd, V.; McGrath, M. J.; Naudts, K.; Otto, J.; Valade, A.; Luyssaert, S.

    2014-12-01

    In Earth system modelling, a description of the energy budget of the vegetated surface layer is fundamental as it determines the meteorological conditions in the planetary boundary layer and as such contributes to the atmospheric conditions and its circulation. The energy budget in most Earth system models has long been based on a "big-leaf approach", with averaging schemes that represent in-canopy processes. Such models have difficulties in reproducing consistently the energy balance in field observations. We here outline a newly developed numerical model for energy budget simulation, as a component of the land surface model ORCHIDEE-CAN (Organising Carbon and Hydrology In Dynamic Ecosystems - CANopy). This new model implements techniques from single-site canopy models in a practical way. It includes representation of in-canopy transport, a multilayer longwave radiation budget, height-specific calculation of aerodynamic and stomatal conductance, and interaction with the bare soil flux within the canopy space. Significantly, it avoids iterations over the height of tha canopy and so maintains implicit coupling to the atmospheric model LMDz. As a first test, the model is evaluated against data from both an intensive measurement campaign and longer term eddy covariance measurements for the intensively studied Eucalyptus stand at Tumbarumba, Australia. The model performs well in replicating both diurnal and annual cycles of fluxes, as well as the gradients of sensible heat fluxes. However, the model overestimates sensible heat flux against an underestimate of the radiation budget. Improved performance is expected through the implementation of a more detailed calculation of stand albedo and a more up-to-date stomatal conductance calculation.

  14. Quantifying the effect of lichen and bryophyte cover on permafrost soil within a global land surface model

    NASA Astrophysics Data System (ADS)

    Porada, Philipp; Ekici, Altug; Beer, Christian

    2016-04-01

    Vegetation near the surface, such as bryophytes and lichens, has an insulating effect on the soil at high latitudes and it can therefore protect permafrost conditions. Warming due to climate change, however, may change the average surface coverage of bryophytes and lichens. This can result in permafrost thawing associated with a release of soil carbon to the atmosphere, which may lead to a positive feedback on atmospheric CO2. Thus, it is important to predict how the bryophyte and lichen cover at high latitudes will react to environmental change. However, current global land surface models so far contain mostly empirical approaches to represent bryophytes and lichens, which makes it impractical to predict their future state and function. For this reason, we integrate a process-based model of bryophyte and lichen growth into the global land surface model JSBACH. We explicitly represent dynamic thermal properties of the bryophyte and lichen cover and their relation to climate. Subsequently, we compare simulations with and without bryophyte and lichen cover to quantify the insulating effect. We estimate an annual average cooling effect of the bryophyte and lichen cover of 2.7 K on topsoil temperature for the northern high latitudes under current climate. Locally, the cooling may reach up to 5.7 K. Moreover, we show that neglecting dynamic properties of the bryophyte and lichen cover by using a simple, empirical scheme only results in an average cooling of around 0.5 K. This suggests that bryophytes and lichens have a significant impact on soil temperature in high-latitude ecosystems and also that a process-based description of their thermal properties is necessary for a realistic representation of the cooling effect.

  15. Analysis of Multiple Precipitation Products and Preliminary Assessment of Their Impact on Global Land Data Assimilation System (GLDAS) Land Surface States

    NASA Technical Reports Server (NTRS)

    Gottschalck, Jon; Meng, Jesse; Rodel, Matt; Houser, paul

    2005-01-01

    Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. NASA's Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type). Precipitation is arguably the most important input to LSMs. Many precipitation datasets have been produced using satellite and rain gauge observations and weather forecast models. In this study, seven different global precipitation datasets were evaluated over the United States, where dense rain gauge networks contribute to reliable precipitation maps. We then used the seven datasets as inputs to GLDAS simulations, so that we could diagnose their impacts on output stocks and fluxes of water. In terms of totals, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) had the closest agreement with the US rain gauge dataset for all seasons except winter. The CMAP precipitation was also the most closely correlated in time with the rain gauge data during spring, fall, and winter, while the satellitebased estimates performed best in summer. The GLDAS simulations revealed that modeled soil moisture is highly

  16. Analysis of Multiple Precipitation Products and Preliminary Assessment of Their Impact on Global Land Data Assimilation System (GLDAS) Land Surface States

    NASA Technical Reports Server (NTRS)

    Gottschalck, Jon; Meng, Jesse; Rodel, Matt; Houser, paul

    2005-01-01

    Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. NASA's Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type). Precipitation is arguably the most important input to LSMs. Many precipitation datasets have been produced using satellite and rain gauge observations and weather forecast models. In this study, seven different global precipitation datasets were evaluated over the United States, where dense rain gauge networks contribute to reliable precipitation maps. We then used the seven datasets as inputs to GLDAS simulations, so that we could diagnose their impacts on output stocks and fluxes of water. In terms of totals, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) had the closest agreement with the US rain gauge dataset for all seasons except winter. The CMAP precipitation was also the most closely correlated in time with the rain gauge data during spring, fall, and winter, while the satellitebased estimates performed best in summer. The GLDAS simulations revealed that modeled soil moisture is highly

  17. Global Land Use History: A New Synthesis

    NASA Astrophysics Data System (ADS)

    Ellis, E. C.

    2011-12-01

    Human use of land has transformed the terrestrial biosphere, causing global changes in ecosystems, landscapes, biogeochemistry, climate, and biodiversity. This global transformation is commonly described as recent in human-environment history. Interdisciplinary paleo and historical data reconstructions and global land use and land cover modeling challenge this view, indicating that human use of land has been extensive and sustained for millennia, and may represent more of a recovery than an acceleration of land use in this century and beyond. Here we present a new global synthesis of recent scientific work on the emergence, history, and future of land use as a global force transforming the Earth system. Central to this synthesis is early human use of fire to engineer ecosystems and other systemic changes in land use dynamics, which together explain how relatively small human populations may have caused widespread and profound ecological changes early in the Holocene, while the largest human populations in history are associated with forests recovery across large regions. While quantitative global models of Holocene and even contemporary land use are still at early stage of development, improved land use histories and models that incorporate land change processes offer a more spatially detailed and accurate view of our planet's history, with a biosphere and perhaps even climate long ago affected by humans. The implicit view from the Anthropocene that humans have reached a historical moment in which "wild nature" is threatened is thus challenged by a view that humans are ancestral shapers and permanent stewards of Earth's terrestrial surface. Land use intensification processes have long sustained human interactions with the terrestrial biosphere, and they continue to evolve as populations grow and urbanize. While these processes are rapidly shifting from their historic patterns in both scale and type, integrative land use and land cover models that incorporate

  18. A global climate model (GENESIS) with a land-surface transfer scheme (LSX). Part II: CO{sub 2} sensitivity

    SciTech Connect

    Thompson, S.L.; Pollard, D.

    1995-05-01

    The sensitivity of the equilibrium climate to doubled atmospheric CO{sub 2} is investigated using the GENESIS global climate model version 1.02. The atmospheric general circulation model is a heavily modified version of the NCAR CCM1 and is coupled to a multicanopy lane-surface model (LSX); multilayer models of soil, snow, and sea ice; and a slab ocean mixed layer. Features that are relatively new in CO{sub 2} sensitivity studies include explicit subgrid convective plumes, PBL mixing, a diurnal cycle, a complex land-surface model, sea ice dynamics, and semi-Lagrangian transport of water vapor. The global annual surface-air warming in the model is 2.1{degrees}C, with global precipitation increasing by 3.3%. Over most land areas, most of the changes in precipitation are insignificant at the 5% level compared to interannual variability. Decreases in soil moisture in summer are not as large as in most previous models and only occur poleward of {approximately}55{degrees} in Siberia, northern CAnada, and Alaska. Sea ice area in September recedes by 62% in the Artic and by 43% in the Antarctic. The area of Northern Hemispheric permafrost decreases by 48%, while the the total area of Northern hemispheric snowcover in January decreases by 48%, while the total area of Northern Hemispheric snowcover in January decreases by on 13%. The effects of several modifications to the model physics are described. Replacing LSX and the multilayer soil with a single-layer bucket model causes little change to CO{sub 2} sensitivities on global scales, and the regions of summer drying in northern high latitudes are reproduced, although with somewhat greater amplitude. Compared to convective adjustment, penetrative plume convection increases the tropical Hadley Cell response but decreases the global warming slightly by 0.1{degrees} to 0.3{degrees}, contrary to several previous GCM studies in which penetrative convection was associated with greater CO{sub 2} warming. 60 refs., 20 figs., 3 tabs.

  19. Quantification and attribution of errors in the simulated annual gross primary production and latent heat fluxes by two global land surface models

    NASA Astrophysics Data System (ADS)

    Li, Jianduo; Wang, Ying-Ping; Duan, Qingyun; Lu, Xingjie; Pak, Bernard; Wiltshire, Andy; Robertson, Eddy; Ziehn, Tilo

    2016-09-01

    Differences in the predicted carbon and water fluxes by different global land models have been quite large and have not decreased over the last two decades. Quantification and attribution of the uncertainties of global land surface models are important for improving the performance of global land surface models, and are the foci of this study. Here we quantified the model errors by comparing the simulated monthly global gross primary productivity (GPP) and latent heat flux (LE) by two global land surface models with the model-data products of global GPP and LE from 1982 to 2005. By analyzing model parameter sensitivities within their ranges, we identified about 2-11 most sensitive model parameters that have strong influences on the simulated GPP or LE by two global land models, and found that the sensitivities of the same parameters are different among the plant functional types (PFT). Using parameter ensemble simulations, we found that 15%-60% of the model errors were reduced by tuning only a few (<4) most sensitive parameters for most PFTs, and that the reduction in model errors varied spatially within a PFT or among different PFTs. Our study shows that future model improvement should optimize key model parameters, particularly those parameters relating to leaf area index, maximum carboxylation rate, and stomatal conductance.

  20. Differentiating the role of land surface variability and cloudiness variability on global energy transport within the atmosphere and oceans

    NASA Technical Reports Server (NTRS)

    Smith, Eric A.

    1993-01-01

    The following provides the final report on NASA IDP Project NAGW-1840 'Differentiating the Role of Land Surface Variability on Global Energy Transport within the Atmosphere and Oceans'. The project was designed to investigate the role of regional perturbations in the earth radiation budget on atmospheric and oceanic energy transports on an interannual basis. We proposed a modeling strategy based on an entropy extremum principle that could be used to separate the transports into oceanic and atmospheric components so as to better understand the effects of regional perturbations at the distinct atmospheric and oceanic time scales. The original focus was to consider the maintenance and year-to-year modulation of a large-scale, low-latitude North African-West Pacific Ocean net radiation dipole, which we had detected in the Nimbus 6 and 7 record of earth radiation budget measurements, and which necessitated significant cross-meridional energy transports to maintain global equilibrium. In addition, perturbations in the radiation balance term were to be partitioned into cloud-induced and surface-induced components to better understand the feedbacks between clouds and surface boundary conditions on interannual variability of the radiation balance.

  1. Optimal estimation of areal values of near-land-surface temperatures for testing global and local spatio-temporal trends

    NASA Astrophysics Data System (ADS)

    Wang, Hong; Pardo-Igúzquiza, Eulogio; Dowd, Peter A.; Yang, Yongguo

    2017-09-01

    This paper provides a solution to the problem of estimating the mean value of near-land-surface temperature over a relatively large area (here, by way of example, applied to mainland Spain covering an area of around half a million square kilometres) from a limited number of weather stations covering a non-representative (biased) range of altitudes. As evidence mounts for altitude-dependent global warming, this bias is a significant problem when temperatures at high altitudes are under-represented. We correct this bias by using altitude as a secondary variable and using a novel clustering method for identifying geographical regions (clusters) that maximize the correlation between altitude and mean temperature. In addition, the paper provides an improved regression kriging estimator, which is optimally determined by the cluster analysis. The optimal areal values of near-land-surface temperature are used to generate time series of areal temperature averages in order to assess regional changes in temperature trends. The methodology is applied to records of annual mean temperatures over the period 1950-2011 across mainland Spain. The robust non-parametric Theil-Sen method is used to test for temperature trends in the regional temperature time series. Our analysis shows that, over the 62-year period of the study, 78% of mainland Spain has had a statistically significant increase in annual mean temperature.

  2. A new integrated and homogenized global monthly land surface air temperature dataset for the period since 1900

    NASA Astrophysics Data System (ADS)

    Xu, Wenhui; Li, Qingxiang; Jones, Phil; Wang, Xiaolan L.; Trewin, Blair; Yang, Su; Zhu, Chen; Zhai, Panmao; Wang, Jinfeng; Vincent, Lucie; Dai, Aiguo; Gao, Yun; Ding, Yihui

    2017-06-01

    A new dataset of integrated and homogenized monthly surface air temperature over global land for the period since 1900 [China Meteorological Administration global Land Surface Air Temperature (CMA-LSAT)] is developed. In total, 14 sources have been collected and integrated into the newly developed dataset, including three global (CRUTEM4, GHCN, and BEST), three regional and eight national sources. Duplicate stations are identified, and those with the higher priority are chosen or spliced. Then, a consistency test and a climate outlier test are conducted to ensure that each station series is quality controlled. Next, two steps are adopted to assure the homogeneity of the station series: (1) homogenized station series in existing national datasets (by National Meteorological Services) are directly integrated into the dataset without any changes (50% of all stations), and (2) the inhomogeneities are detected and adjusted for in the remaining data series using a penalized maximal t test (50% of all stations). Based on the dataset, we re-assess the temperature changes in global and regional areas compared with GHCN-V3 and CRUTEM4, as well as the temperature changes during the three periods of 1900-2014, 1979-2014 and 1998-2014. The best estimates of warming trends and there 95% confidence ranges for 1900-2014 are approximately 0.102 ± 0.006 °C/decade for the whole year, and 0.104 ± 0.009, 0.112 ± 0.007, 0.090 ± 0.006, and 0.092 ± 0.007 °C/decade for the DJF (December, January, February), MAM, JJA, and SON seasons, respectively. MAM saw the most significant warming trend in both 1900-2014 and 1979-2014. For an even shorter and more recent period (1998-2014), MAM, JJA and SON show similar warming trends, while DJF shows opposite trends. The results show that the ability of CMA-LAST for describing the global temperature changes is similar with other existing products, while there are some differences when describing regional temperature changes.

  3. Long term global scale root zone soil moisture monitoring at ECMWF using a surface-only land data assimilation system

    NASA Astrophysics Data System (ADS)

    Albergel, Clement; de Rosnay, Patricia; Balsamo, Gianpaolo; Dutra, Emanuel; Kral, Tomas; Munoz-Sabater, Joaquin; Isaksen, Lars; Boussetta, Souhail; Massari, Christian; Brocca, Luca

    2015-04-01

    In the framework of the H-SAF (Satellite Application Facility on Support to Operational Hydrology and Water Management) project of EUMETSAT, ECMWF is developing a re-analysis of soil moisture that will cover 1992-2014 and will make use of satellite derived surface soil moisture (SSM) from ERS-1&2, ASCAT. This study presents the first steps toward the conception of this long term global scale root zone soil moisture; a surface-only Land Data Assimilation System (so-LDAS) able to ingest satellite-derived SSM observations is tested at global scale to increase prediction accuracy for surface and root zone soil moisture. The so-LDAS is defined as an offline sequential data assimilation system (simplified Extended Kalman Filter) based on a Land Surface Model (HTESSEL) uncoupled with the atmosphere, it is driven by ERA-Interim observations based atmospheric forcing. Its impact is assessed over 2010-2013 (1) using local in situ measurements of surface and root zone soil moisture and (2) at a basin scale initialising an event based Rainfall-Runoff hydrological model. Additionally to an open loop experiment (OL no analysis) three data assimilation experiments are used with different specification of the error matrices. The first one (Asc1) has been set up to test the so-LDAS with a soil moisture standard deviation of σb=0.01 m3m-3 for the first three layers of soil analysed and σo=0.02 m3m-3 for ASCAT SSM. σb was then doubled (Asc2) and σo set to 0.05 m3m-3 to be more consistent with satellite derived SSM errors deduced from previous independent studies. In a third experiment (Asc3), σo is set to 0.05 m3m-3, σb, is set to 0.1 × (wfc - wwilt), where wfc and wwilt are the volumetric water content at field capacity and at permanent wilting point, which depend on soil texture.

  4. Comparison of Total Water Storage Anomalies from Global Hydrologic and Land Surface Models and New GRACE Satellite Solutions

    NASA Astrophysics Data System (ADS)

    Scanlon, B. R.; Zhang, Z.; Sun, A.; Save, H.; Mueller Schmied, H.; Wada, Y.; Doll, P. M.; Eisner, S.

    2016-12-01

    There is Increasing interest in global hydrology based on modeling and remote sensing, highlighting the need to compare output from modeling and remote sensing approaches. Here we evaluate simulated terrestrial Total Water Storage anomalies (TWSA) from global hydrologic models (GHMs: WGHM and PRC-GLOBWB) and global land surface models (LSMs, such as GLDAS NOAH, MOSAIC, VIC, and CLM) using newly released GRACE mascons solutions from the Univ. of Texas Center for Space Research. The comparisons are based on monthly TWS anomalies over 13 years (April 2002 - April 2015) for 176 basins globally. Performance metrics include scatter plots of simulated and GRACE observed TWSA by basin with median slopes for different models indicating bias, correlations (shape and timing of TWS time series), and variability ratio (standard deviation of model TWSA/std. dev. GRACE observed TWSA), with optimal values of 1 indicating perfect agreement. The GRACE data were also disaggregated into long-term trends and seasonal amplitudes. Modeled TWS anomalies are biased low by 20 - 30% relative to GRACE TWSA with similar bias levels for basins in different size classes but greater bias with increasing basin aridity. Discrepancies between models and GRACE TWSA are greatest for long-term trends in TWSA with 60 - 95% underestimation of GRACE TWSA by models. There is good agreement in seasonal amplitudes from models and GRACE (< 10-30% bias in models). Comparing times series of modeled and GRACE TWSA time series shows good agreement, with median correlation coefficients ranging from 0.7 - 0.8 but much lower correlation coefficients in arid settings (range: 0.4 - 0.7). The variability ratios are > 0.9 for models with little impact of basin size or climate for most models. These comparisons highlight reliable model performance in terms of seasonal amplitudes in TWSA and underestimation of long-term trends in TWSA and in arid basins.

  5. Global scale estimation of land surface heat fluxes from space: current status, opportunities and future direction

    USDA-ARS?s Scientific Manuscript database

    While considerable progress has been made in the development of global flux products from space, there remain a number of issues that either limit the application of these data to their fullest extent, or provide an inherent constraint on the accuracy achievable. This is particularly true when using...

  6. Global evaluation of gross primary productivity in the JULES land surface model v3.4.1

    NASA Astrophysics Data System (ADS)

    Slevin, Darren; Tett, Simon F. B.; Exbrayat, Jean-François; Bloom, A. Anthony; Williams, Mathew

    2017-07-01

    This study evaluates the ability of the JULES land surface model (LSM) to simulate gross primary productivity (GPP) on regional and global scales for 2001-2010. Model simulations, performed at various spatial resolutions and driven with a variety of meteorological datasets (WFDEI-GPCC, WFDEI-CRU and PRINCETON), were compared to the MODIS GPP product, spatially gridded estimates of upscaled GPP from the FLUXNET network (FLUXNET-MTE) and the CARDAMOM terrestrial carbon cycle analysis. Firstly, when JULES was driven with the WFDEI-GPCC dataset (at 0. 5° × 0. 5° spatial resolution), the annual average global GPP simulated by JULES for 2001-2010 was higher than the observation-based estimates (MODIS and FLUXNET-MTE), by 25 and 8 %, respectively, and CARDAMOM estimates by 23 %. JULES was able to simulate the standard deviation of monthly GPP fluxes compared to CARDAMOM and the observation-based estimates on global scales. Secondly, GPP simulated by JULES for various biomes (forests, grasslands and shrubs) on global and regional scales were compared. Differences among JULES, MODIS, FLUXNET-MTE and CARDAMOM on global scales were due to differences in simulated GPP in the tropics. Thirdly, it was shown that spatial resolution (0. 5° × 0. 5°, 1° × 1° and 2° × 2°) had little impact on simulated GPP on these large scales, with global GPP ranging from 140 to 142 PgC year-1. Finally, the sensitivity of JULES to meteorological driving data, a major source of model uncertainty, was examined. Estimates of annual average global GPP were higher when JULES was driven with the PRINCETON meteorological dataset than when driven with the WFDEI-GPCC dataset by 3 PgC year-1. On regional scales, differences between the two were observed, with the WFDEI-GPCC-driven model simulations estimating higher GPP in the tropics (5° N-5° S) and the PRINCETON-driven model simulations estimating higher GPP in the extratropics (30-60° N).

  7. Use of satellite remote sensing to evaluate an integrated global land surface hydrology - routing - water resources management model

    NASA Astrophysics Data System (ADS)

    Voisin, N.; Huang, M.; Li, H.; Leung, L.

    2013-12-01

    An integrated model has been developed to advance our understanding of the interactions between human activities, terrestrial system and water cycle, and to evaluate how system interactions will be affected by a changing climate at the regional and global scales. The integrated model consists of a land surface hydrology model (LSM) with crop and irrigation modules, a routing model and a water resources management model (WM). The modeling system has shown reasonable performance at the regional and subregional scales over the Columbia River Basin and Upper Midwest in the USA. The overall and individual components of integrated system were validated by evaluating both regulated and natural flows, reservoir storage and water supply with respect to observations. In this presentation, the first application of this system at the global scale is discussed. The overall system is evaluated with respect to GRDC observed regulated flow. The terrestrial hydrologic simulations are evaluated against GRACE and MODIS products, and data-model or observed naturalized flow where available. In addition, the reservoir model is evaluated with respect to satellite altimetry data from the US Department of Agriculture and French Space Agency (Centre National D'Etudes Spatial CNES). Although the reservoir model is not tuned specifically for each observed regulated flow, we investigate potential bias and discuss on the cascade of errors from the atmospheric model forcing, into the LSM down to WM over major reservoirs throughout the world for different hydro-climatic conditions and reservoir characteristics.

  8. Impact of fire on global land surface air temperature and energy budget for the 20th century due to changes within ecosystems

    DOE PAGES

    Li, Fang; Lawrence, David M.; Bond-Lamberty, Ben

    2017-04-03

    Fire is a global phenomenon and tightly interacts with the biosphere and climate. This study provides the first quantitative assessment of fire’s influence on the global land air temperature during the 20th century through its impact on terrestrial ecosystems. We quantify the impact of fire by comparing 20th century fire-on and fire-off simulations with the Community Earth System Model (CESM) as the model platform. Here, results show that fire-induced changes in terrestrial ecosystems increased global land surface air temperature by 0.04 °C. Such changes significantly warmed the tropical savannas and southern Asia mainly by reducing latent heat flux, but cooledmore » Southeast China by enhancing the East Asian winter monsoon. 20% of the early 20th century global land warming can be attributed to fire-induced changes in terrestrial ecosystems, providing a new mechanism for explaining the poorly-understood climate change.« less

  9. Optimising the prognostic leaf phenology of a land surface model at a global scale: perspectives and challenges

    NASA Astrophysics Data System (ADS)

    MacBean, Natasha; Maignan, Fabienne; Peylin, Philippe; Bacour, Cédric

    2014-05-01

    Leaf phenology is a critical component of the coupled soil-vegetation-atmosphere system as it directly controls the spatial and temporal variability of the surface carbon, water and energy fluxes. The length of the growing season governs the net amount of carbon that is assimilated and released through photosynthesis and autotrophic respiration, as well as affecting the surface energy balance and hydrology through changing albedo, surface roughness and evapotranspiration, which in turn regulate the land surface temperature and moisture conditions. These provide a strong constraint on atmospheric boundary layer conditions and circulation, with possible important long-term impacts on the climate. A recent study (Richardson et al., 2012) showed that there is bias in the growing season length (GSL) predicted by many Land Surface Models (LSMs) when compared to observations. However, prior to parameter optimisation it is unclear whether the model-data misfit is the result of inaccurate parameter values or model structural error. Here satellite-derived NDVI data are used to constrain the phenology parameters in the ORCHIDEE LSM. A 4D-variational multi-site data assimilation system is used to optimise parameters that directly control the leaf phenology models of all natural deciduous PFTs in ORCHIDEE. The resultant parameter vectors are validated both temporally and spatially, both at site and global scales. The ability of the satellite data to improve the seasonal C fluxes is evaluated with in situ net CO2 fluxes and atmospheric CO2 data, and the improvement in the inter-annual variability of the GSL is discussed. The impact of the optimisations on the coupled water and energy budgets is also examined. Technical issues are also addressed, including the ability of the multi-site DA system to retrieve PFT-generic parameter vectors at a global scale, the difficulty of finding a unique parameter vector, especially for parameters involved in threshold responses, and the issue

  10. Global Drought Information System: Influence of Differences in Land Surface Model Dynamics on Drought Monitoring

    NASA Astrophysics Data System (ADS)

    Nijssen, B.; Shukla, S.; Mo, K. C.; Lettenmaier, D. P.

    2014-12-01

    Real-time drought monitoring enables a proactive drought management approach that can lead to timely actions to mitigate the losses due to a drought event. In recent years, the availability of long-term, high quality, satellite and reanalysis based datasets of atmospheric forcings, combined with the development of state-of-the-art hydrologic models have made real-time global drought monitoring feasible. Hydrologic models are invaluable tools for global drought monitoring given the scarcity of long-term moisture observations (e.g. soil moisture, streamflow). However, as valuable as they are for drought monitoring, characteristics of a drought event (i.e. onset, severity and persistence) as estimated by a hydrologic model depend on the model's parameters (e.g. soil and vegetation parameters) and its inherent dynamics that guide the partition of precipitation into evapotranspiration and runoff. One approach to account for the differences in drought estimates due to differences in model dynamics is to use multiple hydrologic models. Each hydrologic model is forced with the same atmospheric forcings to simulate moisture conditions which are converted into objective drought indicators (e.g. soil moisture percentile) with respect to the model's own climatology and then those estimates are combined to provide a multimodel based drought estimates. The University of Washington's Global Drought Information System (GDIS) developed in 2013, is one such prototype drought monitoring system. This system uses the VIC, NOAH and Catchment models. In this presentation we investigate how the differences in the dynamics of the models used in UW's GDIS, influence the drought monitoring estimates. Specifically we answer following questions: 1.What is the level of uncertainties in drought onset, severity and persistence as estimated by different hydrologic models? 2. How do the uncertainties vary spatially and seasonally? 3. What are the sources of the uncertainties?

  11. Monitoring global land surface using Nimbus-7 37 GHz data - Theory and examples

    NASA Technical Reports Server (NTRS)

    Choudhury, Bhaskar J.

    1989-01-01

    Simplified radiative transfer models for 37 GHz brightness temperatures are developed and applied to observations taken with the Nimbus-7 scanning multichannel microwave radiometer. It is found that, as the vegetation density increases, polarization difference decreases. The polarization difference also decreases with increasing surface roughness. Empirical relations are established between the satellite observations and annual rainfall over Africa and Australia, primary productivity, and actual evaporation. Color-coded maps of primary productivity and evaporation are presented.

  12. Evaluation of the global MODIS 30 arc-second spatially and temporally complete snow-free land surface albedo and reflectance anisotropy dataset

    NASA Astrophysics Data System (ADS)

    Sun, Qingsong; Wang, Zhuosen; Li, Zhan; Erb, Angela; Schaaf, Crystal B.

    2017-06-01

    Land surface albedo is an essential variable for surface energy and climate modeling as it describes the proportion of incident solar radiant flux that is reflected from the Earth's surface. To capture the temporal variability and spatial heterogeneity of the land surface, satellite remote sensing must be used to monitor albedo accurately at a global scale. However, large data gaps caused by cloud or ephemeral snow have slowed the adoption of satellite albedo products by the climate modeling community. To address the needs of this community, we used a number of temporal and spatial gap-filling strategies to improve the spatial and temporal coverage of the global land surface MODIS BRDF, albedo and NBAR products. A rigorous evaluation of the gap-filled values shows good agreement with original high quality data (RMSE = 0.027 for the NIR band albedo, 0.020 for the red band albedo). This global snow-free and cloud-free MODIS BRDF and albedo dataset (established from 2001 to 2015) offers unique opportunities to monitor and assess the impact of the changes on the Earth's land surface.

  13. Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982-2010

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

    2014-05-01

    Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examined across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and GSL varied considerably during 1982-2010 across the globe. Generally, the interannual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative GSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3

  14. 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

  15. Anticipating land surface change.

    PubMed

    Streeter, Richard; Dugmore, Andrew J

    2013-04-09

    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.

  16. Global land and water grabbing.

    PubMed

    Rulli, Maria Cristina; Saviori, Antonio; D'Odorico, Paolo

    2013-01-15

    Societal pressure on the global land and freshwater resources is increasing as a result of the rising food demand by the growing human population, dietary changes, and the enhancement of biofuel production induced by the rising oil prices and recent changes in United States and European Union bioethanol policies. Many countries and corporations have started to acquire relatively inexpensive and productive agricultural land located in foreign countries, as evidenced by the dramatic increase in the number of transnational land deals between 2005 and 2009. Often known as "land grabbing," this phenomenon is associated with an appropriation of freshwater resources that has never been assessed before. Here we gather land-grabbing data from multiple sources and use a hydrological model to determine the associated rates of freshwater grabbing. We find that land and water grabbing are occurring at alarming rates in all continents except Antarctica. The per capita volume of grabbed water often exceeds the water requirements for a balanced diet and would be sufficient to improve food security and abate malnourishment in the grabbed countries. It is found that about 0.31 × 10(12) m(3) · y(-1) of green water (i.e., rainwater) and up to 0.14 × 10(12) m(3) · y(-1) of blue water (i.e., irrigation water) are appropriated globally for crop and livestock production in 47 × 10(6) ha of grabbed land worldwide (i.e., in 90% of the reported global grabbed land).

  17. Global land and water grabbing

    PubMed Central

    Rulli, Maria Cristina; Saviori, Antonio; D’Odorico, Paolo

    2013-01-01

    Societal pressure on the global land and freshwater resources is increasing as a result of the rising food demand by the growing human population, dietary changes, and the enhancement of biofuel production induced by the rising oil prices and recent changes in United States and European Union bioethanol policies. Many countries and corporations have started to acquire relatively inexpensive and productive agricultural land located in foreign countries, as evidenced by the dramatic increase in the number of transnational land deals between 2005 and 2009. Often known as “land grabbing,” this phenomenon is associated with an appropriation of freshwater resources that has never been assessed before. Here we gather land-grabbing data from multiple sources and use a hydrological model to determine the associated rates of freshwater grabbing. We find that land and water grabbing are occurring at alarming rates in all continents except Antarctica. The per capita volume of grabbed water often exceeds the water requirements for a balanced diet and would be sufficient to improve food security and abate malnourishment in the grabbed countries. It is found that about 0.31 × 1012 m3⋅y−1 of green water (i.e., rainwater) and up to 0.14 × 1012 m3⋅y−1 of blue water (i.e., irrigation water) are appropriated globally for crop and livestock production in 47 × 106 ha of grabbed land worldwide (i.e., in 90% of the reported global grabbed land). PMID:23284174

  18. Real-Time Global Flood Estimation Using Satellite-Based Precipitation and a Coupled Land Surface and Routing Model

    NASA Technical Reports Server (NTRS)

    Wu, Huan; Adler, Robert F.; Tian, Yudong; Huffman, George J.; Li, Hongyi; Wang, JianJian

    2014-01-01

    A widely used land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood monitoring parameters for the latitude band 50 deg. N - 50 deg. S at relatively high spatial (approximately 12 km) and temporal (3 hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Evaluation results are slightly better for the research-quality input and significantly better for longer duration events (3 day events versus 1 day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is approximately 0.9 and the false alarm ratio is approximately 0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30 deg. S - 30 deg. N) gives positive daily Nash-Sutcliffe Coefficients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. There were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.

  19. Real-time global flood estimation using satellite-based precipitation and a coupled land surface and routing model

    SciTech Connect

    Wu, Huan; Adler, Robert F.; Tian, Yudong; Huffman, George J.; Li, Hongyi; Wang, JianJian

    2014-03-01

    A widely used land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood monitoring parameters for the latitude band 50°N–50°S at relatively high spatial (~12 km) and temporal (3 hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Evaluation results are slightly better for the research-quality input and significantly better for longer duration events (3 day events versus 1 day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is ~0.9 and the false alarm ratio is ~0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30°S–30°N) gives positive daily Nash-Sutcliffe Coefficients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. Finally, there were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.

  20. Interannual Variations and Trends in Global Land Surface Phenology Derived from Enhanced Vegetation Index During 1982-2010

    NASA Technical Reports Server (NTRS)

    Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

    2014-01-01

    Land swiace phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstmted to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This srudy detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examIned across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and OSL varied considerably during 1982-2010 across the globe. Generally, the interarmual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative OSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3

  1. A Quasi-Global Approach to Improve Day-Time Satellite Surface Soil Moisture Anomalies through the Land Surface Temperature Input

    NASA Technical Reports Server (NTRS)

    Parinussa, Robert M.; de Jeu, Richard A. M.; van Der Schalie, Robin; Crow, Wade T.; Lei, Fangni; Holmes, Thomas R. H.

    2016-01-01

    Passive microwave observations from various spaceborne sensors have been linked to the soil moisture of the Earth's surface layer. A new generation of passive microwave sensors are dedicated to retrieving this variable and make observations in the single theoretically optimal L-band frequency (1-2 GHz). Previous generations of passive microwave sensors made observations in a range of higher frequencies, allowing for simultaneous estimation of additional variables required for solving the radiative transfer equation. One of these additional variables is land surface temperature, which plays a unique role in the radiative transfer equation and has an influence on the final quality of retrieved soil moisture anomalies. This study presents an optimization procedure for soil moisture retrievals through a quasi-global precipitation-based verification technique, the so-called Rvalue metric. Various land surface temperature scenarios were evaluated in which biases were added to an existing linear regression, specifically focusing on improving the skills to capture the temporal variability of soil moisture. We focus on the relative quality of the day-time (01:30 pm) observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), as these are theoretically most challenging due to the thermal equilibrium theory, and existing studies indicate that larger improvements are possible for these observations compared to their night-time (01:30 am) equivalent. Soil moisture data used in this study were retrieved through the Land Parameter Retrieval Model (LPRM), and in line with theory, both satellite paths show a unique and distinct degradation as a function of vegetation density. Both the ascending (01:30 pm) and descending (01:30 am) paths of the publicly available and widely used AMSR-E LPRM soil moisture products were used for benchmarking purposes. Several scenarios were employed in which the land surface temperature input for the radiative

  2. Dynamic Land Surface Classifcations using Microwave Frequencies

    NASA Astrophysics Data System (ADS)

    Jackson, H.; Tian, Y.; Peters-Lidard, C. D.; Harrison, K. W.

    2014-12-01

    Land surface emissivity in microwave frequencies is critical to the remote sensing of soil moisture, precipitation, and vegetation. Different land surfaces have different spectral signatures in the microwave portions of the electromagnetic spectrum. Their spatial and temporal behaviors are also highly variable. These properties are yet not well understood in microwave frequencies, despite their capability in detecting water-related variables in the atmosphere and land surface. A classification scheme was developed to stratify the Earth's land surfaces based on their seasonally dynamic microwave signatures. An unsupervised clustering approach was used identify and distinguish data groupings along two microwave based indicies. Land surface data clusters were mapped to determine their spatial relationships to known land cover groupings. Differences in land surface clusters were analyzed in their spatial consistency and their direction and magnitude of land surface change. It was found that vegetation and topography were the predominant contributors to change between seasons. Land surface extremes of sandy desert and closed canopy tropical forest displayed minimal intra-annual variability while transitional zones, such as the Sahel and North American temperate forests, exhibited the most variability. Distinct microwave signatures varied between seasons along a latittudinal gradient. Overall variability in land surface types increased at high lattitudes. This classification will help inform research studies maniputlating the microwave frequencies of the electromagnetic spectrum to better characterize land surface dynamics, and will be very useful in the validation of radiative transfer models and quantification of uncertainty in global precipitation monitoring.

  3. Impact of fire on global land surface air temperature and energy budget for the 20th century due to changes within ecosystems

    NASA Astrophysics Data System (ADS)

    Li, Fang; Lawrence, David M.; Bond-Lamberty, Ben

    2017-04-01

    Fire is a global phenomenon and tightly interacts with the biosphere and climate. This study provides the first quantitative assessment and understanding of fire’s influence on the global annual land surface air temperature and energy budget through its impact on terrestrial ecosystems. Fire impacts are quantified by comparing fire-on and fire-off simulations with the Community Earth System Model (CESM). Results show that, for the 20th century average, fire-induced changes in terrestrial ecosystems significantly increase global land annual mean surface air temperature by 0.18 °C, decrease surface net radiation and latent heat flux by 1.08 W m-2 and 0.99 W m-2, respectively, and have limited influence on sensible heat flux (-0.11 W m-2) and ground heat flux (+0.02 W m-2). Fire impacts are most clearly seen in the tropical savannas. Our analyses suggest that fire increases surface air temperature predominantly by reducing latent heat flux, mainly due to fire-induced damage to the vegetation canopy, and decreases net radiation primarily because fire-induced surface warming significantly increases upward surface longwave radiation. This study provides an integrated estimate of fire and induced changes in ecosystems, climate, and energy budget at a global scale, and emphasizes the importance of a consistent and integrated understanding of fire effects.

  4. Global Land Carbon Uptake from Trait Distributions

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  5. A quasi-global approach to improve day-time satellite surface soil moisture anomalies through land surface temperature input

    USDA-ARS?s Scientific Manuscript database

    Passive microwave observations from various space borne sensors have been linked to soil moisture of the Earth’s surface layer. The new generation passive microwave sensors are dedicated to retrieving this variable and make observations in the single, theoretically optimal L-band frequency (1-2 GHz)...

  6. Impact of model developments on present and future simulations of permafrost in a global land-surface model

    NASA Astrophysics Data System (ADS)

    Chadburn, S. E.; Burke, E. J.; Essery, R. L. H.; Boike, J.; Langer, M.; Heikenfeld, M.; Cox, P. M.; Friedlingstein, P.

    2015-03-01

    There is a large amount of organic carbon stored in permafrost in the northern high latitudes, which may become vulnerable to microbial decomposition under future climate warming. In order to estimate this potential carbon-climate feedback it is necessary to correctly simulate the physical dynamics of permafrost within global Earth System Models (ESMs) and to determine the rate at which it will thaw. Additional new processes within JULES, the land surface scheme of the UK ESM (UKESM), include a representation of organic soils, moss and bedrock, and a modification to the snow scheme. The impact of a higher vertical soil resolution and deeper soil column is also considered. Evaluation against a large group of sites shows the annual cycle of soil temperatures is approximately 25 % too large in the standard JULES version, but this error is corrected by the model improvements, in particular by deeper soil, organic soils, moss and the modified snow scheme. Comparing with active layer monitoring sites shows that the active layer is on average just over 1 m too deep in the standard model version, and this bias is reduced by 70 cm in the improved version. Increasing the soil vertical resolution allows the full range of active layer depths to be simulated, where by contrast with a poorly resolved soil, at least 50% of the permafrost area has a maximum thaw depth at the centre of the bottom soil layer. Thus all the model modifications are seen to improve the permafrost simulations. Historical permafrost area corresponds fairly well to observations in all simulations, covering an area between 14-19 million km2. Simulations under two future climate scenarios show a reduced sensitivity of permafrost degradation to temperature, with the near-surface permafrost lost per degree of warming reduced from 1.5 million km2 °C-1 in the standard version of JULES to between 1.1 and 1.2 million km2 °C-1 in the new model version. However, the near-surface permafrost area is still projected

  7. Impact of model developments on present and future simulations of permafrost in a global land-surface model

    NASA Astrophysics Data System (ADS)

    Chadburn, S. E.; Burke, E. J.; Essery, R. L. H.; Boike, J.; Langer, M.; Heikenfeld, M.; Cox, P. M.; Friedlingstein, P.

    2015-08-01

    There is a large amount of organic carbon stored in permafrost in the northern high latitudes, which may become vulnerable to microbial decomposition under future climate warming. In order to estimate this potential carbon-climate feedback it is necessary to correctly simulate the physical dynamics of permafrost within global Earth system models (ESMs) and to determine the rate at which it will thaw. Additional new processes within JULES, the land-surface scheme of the UK ESM (UKESM), include a representation of organic soils, moss and bedrock and a modification to the snow scheme; the sensitivity of permafrost to these new developments is investigated in this study. The impact of a higher vertical soil resolution and deeper soil column is also considered. Evaluation against a large group of sites shows the annual cycle of soil temperatures is approximately 25 % too large in the standard JULES version, but this error is corrected by the model improvements, in particular by deeper soil, organic soils, moss and the modified snow scheme. A comparison with active layer monitoring sites shows that the active layer is on average just over 1 m too deep in the standard model version, and this bias is reduced by 70 cm in the improved version. Increasing the soil vertical resolution allows the full range of active layer depths to be simulated; by contrast, with a poorly resolved soil at least 50 % of the permafrost area has a maximum thaw depth at the centre of the bottom soil layer. Thus all the model modifications are seen to improve the permafrost simulations. Historical permafrost area corresponds fairly well to observations in all simulations, covering an area between 14 and 19 million km2. Simulations under two future climate scenarios show a reduced sensitivity of permafrost degradation to temperature, with the near-surface permafrost loss per degree of warming reduced from 1.5 million km2 °C-1 in the standard version of JULES to between 1.1 and 1.2 million km2 °C-1

  8. Global Consequences of Land Use

    NASA Astrophysics Data System (ADS)

    Foley, Jonathan A.; DeFries, Ruth; Asner, Gregory P.; Barford, Carol; Bonan, Gordon; Carpenter, Stephen R.; Chapin, F. Stuart; Coe, Michael T.; Daily, Gretchen C.; Gibbs, Holly K.; Helkowski, Joseph H.; Holloway, Tracey; Howard, Erica A.; Kucharik, Christopher J.; Monfreda, Chad; Patz, Jonathan A.; Prentice, I. Colin; Ramankutty, Navin; Snyder, Peter K.

    2005-07-01

    Land use has generally been considered a local environmental issue, but it is becoming a force of global importance. Worldwide changes to forests, farmlands, waterways, and air are being driven by the need to provide food, fiber, water, and shelter to more than six billion people. Global croplands, pastures, plantations, and urban areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity. Such changes in land use have enabled humans to appropriate an increasing share of the planet's resources, but they also potentially undermine the capacity of ecosystems to sustain food production, maintain freshwater and forest resources, regulate climate and air quality, and ameliorate infectious diseases. We face the challenge of managing trade-offs between immediate human needs and maintaining the capacity of the biosphere to provide goods and services in the long term.

  9. A framework for high-resolution global forecasts of the impacts of climatic and land use changes on Earth surface processes

    NASA Astrophysics Data System (ADS)

    Pelletier, J. D.; Russell, J. L.; McGuire, L.

    2016-12-01

    The Earth System Modeling (ESM) community has been very effective at forecasting primary climatic and land-use change forcing variables, but "downstream" scientific communities (principally hydrologists, ecologists, and geomorphologists) have arguably been less effective at translating available ESM-derived forecasts into assessments of the changes that are likely to occur in the rates of Earth surface processes and the probabilities of Earth surface hazards including floods, debris flows, soil erosion, and dust storms. In this talk I propose a framework for forecasting changes in surface process rates and natural hazard probabilities. This framework uses global, gridded reanalysis data (1980-present) for primary climatic and land use change forcing variables (e.g., precipitation, soil moisture, land cover, and wind speed) to calibrate and validate geomorphic models that are applied globally within a High Performance Computing (HPC) environment. Ensemble ESM forecasts (from the present to 2100) of primary climatic and land use change forcing variables are then used to forecast changes in the rates of geomorphic processes and hazard probabilities. We demonstrate this framework using wind erosion and dust storms as examples. However, the framework is general and is designed for application to a wide variety of geomorphic processes and hazards. We address the challenges with this approach, such as downscaling reanalysis and ESM model output to the scales necessary to resolve the spatial and temporal variations in the driving and resisting forces necessary for accurate forecasts. We also address the variability among forecasts obtained using different ESM model forecasts. The results highlight the nonlinear, threshold nature of many geomorphic processes and hazards and the resulting sensitivity of forecasts to differences in ESM forecasts of the primary climatic and land use change variables.

  10. Operating The Copernicus Global Land Service

    NASA Astrophysics Data System (ADS)

    Smets, B.; Lacaze, R.; Freitas, S. C.; Jann, A.; Calvet, J.-C.; Camacho, F.; Baret, F.; Paulik, C.; d'Andrimont, R.; Tansey, K.; Verger, A.

    2013-12-01

    From 1st January 2013, the Copernicus Global Land Service is operational, providing continuously a set of biophysical variables describing the vegetation conditions, the energy budget at the continental surface and the water cycle over the whole globe. Essential Climate Variables like the Leaf Area Index (LAI), the Fraction of PAR absorbed by the vegetation (FAPAR), the surface albedo, the Land Surface Temperature, the soil moisture, the burnt areas, the areas of water bodies, and additional vegetation indices, dry matter productivity and TOC reflectance, are generated every hour, every day or every 10 days on a reliable and automatic basis from Earth Observation satellite data. The service and its products are continuously checked on technical and scientific quality. In view of service continuity, the existing retrieval methodologies are being adapted to new sensors (e.g. Proba-V and the Sentinels), taking the benefit of the increased resolution.

  11. Land surface interaction

    NASA Technical Reports Server (NTRS)

    Dickinson, Robert E.

    1992-01-01

    The topics covered include the following: land and climate modeling; sensitivity studies; the process of a land model; model-specific parameterizations; water stress; within-canopy resistances; partial vegetation; canopy temperature; and present experience with a land model coupled to a general circulation model.

  12. Protocol for Validation of the Land Surface Reflectance Fundamental Climate Data Record using AERONET: Application to the Global MODIS and VIIRS Data Records

    NASA Astrophysics Data System (ADS)

    Roger, J. C.; Vermote, E.; Holben, B. N.

    2014-12-01

    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. It is essential that a careful validation of its uncertainties is performed on a global and continuous basis. One approach is the direct comparison of this product with ground measurements but that approach presents several issues related to scale, the episodic nature of ground measurements and the global representativeness. An alternative is to compare the surface reflectance product to reference reflectance determined from Top of atmosphere reflectance corrected using accurate radiative transfer code and very detailed measurements of the atmosphere obtained over the AERONET sites (Vermote and al, 2014, RSE) 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. This paper describes the protocol we have been working on based on our experience with the AERONET data and its application to the MODIS and VIIRS record.

  13. A description of the global land-surface precipitation data products of the Global Precipitation Climatology Centre with sample applications including centennial (trend) analysis from 1901-present

    NASA Astrophysics Data System (ADS)

    Becker, A.; Finger, P.; Meyer-Christoffer, A.; Rudolf, B.; Schamm, K.; Schneider, U.; Ziese, M.

    2013-02-01

    The availability of highly accessible and reliable monthly gridded data sets of global land-surface precipitation is a need that was already identified in the mid-1980s when there was a complete lack of globally homogeneous gauge-based precipitation analyses. Since 1989, the Global Precipitation Climatology Centre (GPCC) has built up its unique capacity to assemble, quality assure, and analyse rain gauge data gathered from all over the world. The resulting database has exceeded 200 yr in temporal coverage and has acquired data from more than 85 000 stations worldwide. Based on this database, this paper provides the reference publication for the four globally gridded monthly precipitation products of the GPCC, covering a 111-yr analysis period from 1901-present. As required for a reference publication, the content of the product portfolio, as well as the underlying methodologies to process and interpolate are detailed. Moreover, we provide information on the systematic and statistical errors associated with the data products. Finally, sample applications provide potential users of GPCC data products with suitable advice on capabilities and constraints of the gridded data sets. In doing so, the capabilities to access El Niño-Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO) sensitive precipitation regions and to perform trend analyses across the past 110 yr are demonstrated. The four gridded products, i.e. the Climatology (CLIM) V2011, the Full Data Reanalysis (FD) V6, the Monitoring Product (MP) V4, and the First Guess Product (FG), are publicly available on easily accessible latitude/longitude grids encoded in zipped clear text ASCII files for subsequent visualization and download through the GPCC download gate hosted on ftp://ftp.dwd.de/pub/data/gpcc/html/download_gate.html by the Deutscher Wetterdienst (DWD), Offenbach, Germany. Depending on the product, four (0

  14. A description of the global land-surface precipitation data products of the Global Precipitation Climatology Centre with sample applications including centennial (trend) analysis from 1901-present

    NASA Astrophysics Data System (ADS)

    Becker, A.; Finger, P.; Meyer-Christoffer, A.; Rudolf, B.; Schamm, K.; Schneider, U.; Ziese, M.

    2012-09-01

    The availability of highly accessible and reliable monthly gridded data sets of the global land-surface precipitation is a need that has already been identified in the mid-80s when there was a complete lack of a globally homogeneous gauge based precipitation analysis. Since 1989 the Global Precipitation Climatology Centre (GPCC) has built up a unique capacity to assemble, quality assure, and analyse rain gauge data gathered from all over the world. The resulting data base has exceeded 200 yr in temporal coverage and has acquired data from more than 85 000 stations world-wide. This paper provides the reference publication for the four globally gridded monthly precipitation products of the GPCC covering a 111-yr analysis period from 1901-present, processed from this data base. As required for a reference publication, the content of the product portfolio, as well as the underlying methodologies to process and interpolate are detailed. Moreover, we provide information on the systematic and statistical errors associated with the data products. Finally, sample applications provide potential users of GPCC data products with suitable advice on capabilities and constraints of the gridded data sets. In doing so, the capabilities to access ENSO and NAO sensitive precipitation regions and to perform trend analysis across the past 110 yr are demonstrated. The four gridded products, i.e. the Climatology V2011 (CLIM), the Full Data Reanalysis (FD) V6, the Monitoring Product (MP) V4, and the First Guess Product (FG) are public available on easy accessible latitude longitude grids encoded in zipped clear text ASCII files for subsequent visualization and download through the GPCC download gate hosted on ftp://ftp.dwd.de/pub/data/gpcc/html/download_gate.html by the Deutscher Wetterdienst (DWD), Offenbach, Germany. Depending on the product four (0.25°, 0.5°, 1.0°, 2.5° for CLIM), three (0.5°, 1.0

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  16. Challenges in Global Land Use/Land Cover Change Modeling

    NASA Astrophysics Data System (ADS)

    Clarke, K. C.

    2011-12-01

    For the purposes of projecting and anticipating human-induced land use change at the global scale, much work remains in the systematic mapping and modeling of world-wide land uses and their related dynamics. In particular, research has focused on tropical deforestation, loss of prime agricultural land, loss of wild land and open space, and the spread of urbanization. Fifteen years of experience in modeling land use and land cover change at the regional and city level with the cellular automata model SLEUTH, including cross city and regional comparisons, has led to an ability to comment on the challenges and constraints that apply to global level land use change modeling. Some issues are common to other modeling domains, such as scaling, earth geometry, and model coupling. Others relate to geographical scaling of human activity, while some are issues of data fusion and international interoperability. Grid computing now offers the prospect of global land use change simulation. This presentation summarizes what barriers face global scale land use modeling, but also highlights the benefits of such modeling activity on global change research. An approach to converting land use maps and forecasts into environmental impact measurements is proposed. Using such an approach means that multitemporal mapping, often using remotely sensed sources, and forecasting can also yield results showing the overall and disaggregated status of the environment.

  17. Using reactive transport codes to provide mechanistic biogeochemistry representations in global land surface models: CLM-PFLOTRAN 1.0

    NASA Astrophysics Data System (ADS)

    Tang, G.; Yuan, F.; Bisht, G.; Hammond, G. E.; Lichtner, P. C.; Kumar, J.; Mills, R. T.; Xu, X.; Andre, B.; Hoffman, F. M.; Painter, S. L.; Thornton, P. E.

    2015-12-01

    We explore coupling to a configurable subsurface reactive transport code as a flexible and extensible approach to biogeochemistry in land surface models; our goal is to facilitate testing of alternative models and incorporation of new understanding. A reaction network with the CLM-CN decomposition, nitrification, denitrification, and plant uptake is used as an example. We implement the reactions in the open-source PFLOTRAN code, coupled with the Community Land Model (CLM), and test at Arctic, temperate, and tropical sites. To make the reaction network designed for use in explicit time stepping in CLM compatible with the implicit time stepping used in PFLOTRAN, the Monod substrate rate-limiting function with a residual concentration is used to represent the limitation of nitrogen availability on plant uptake and immobilization. To achieve accurate, efficient, and robust numerical solutions, care needs to be taken to use scaling, clipping, or log transformation to avoid negative concentrations during the Newton iterations. With a tight relative update tolerance to avoid false convergence, an accurate solution can be achieved with about 50 % more computing time than CLM in point mode site simulations using either the scaling or clipping methods. The log transformation method takes 60-100 % more computing time than CLM. The computing time increases slightly for clipping and scaling; it increases substantially for log transformation for half saturation decrease from 10-3 to 10-9 mol m-3, which normally results in decreasing nitrogen concentrations. The frequent occurrence of very low concentrations (e.g. below nanomolar) can increase the computing time for clipping or scaling by about 20 %; computing time can be doubled for log transformation. Caution needs to be taken in choosing the appropriate scaling factor because a small value caused by a negative update to a small concentration may diminish the update and result in false convergence even with very tight relative

  18. Using reactive transport codes to provide mechanistic biogeochemistry representations in global land surface models: CLM-PFLOTRAN 1.0

    DOE PAGES

    Tang, G.; Yuan, F.; Bisht, G.; ...

    2015-12-17

    We explore coupling to a configurable subsurface reactive transport code as a flexible and extensible approach to biogeochemistry in land surface models; our goal is to facilitate testing of alternative models and incorporation of new understanding. A reaction network with the CLM-CN decomposition, nitrification, denitrification, and plant uptake is used as an example. We implement the reactions in the open-source PFLOTRAN code, coupled with the Community Land Model (CLM), and test at Arctic, temperate, and tropical sites. To make the reaction network designed for use in explicit time stepping in CLM compatible with the implicit time stepping used in PFLOTRAN,more » the Monod substrate rate-limiting function with a residual concentration is used to represent the limitation of nitrogen availability on plant uptake and immobilization. To achieve accurate, efficient, and robust numerical solutions, care needs to be taken to use scaling, clipping, or log transformation to avoid negative concentrations during the Newton iterations. With a tight relative update tolerance to avoid false convergence, an accurate solution can be achieved with about 50 % more computing time than CLM in point mode site simulations using either the scaling or clipping methods. The log transformation method takes 60–100 % more computing time than CLM. The computing time increases slightly for clipping and scaling; it increases substantially for log transformation for half saturation decrease from 10−3 to 10−9 mol m−3, which normally results in decreasing nitrogen concentrations. The frequent occurrence of very low concentrations (e.g. below nanomolar) can increase the computing time for clipping or scaling by about 20 %; computing time can be doubled for log transformation. Caution needs to be taken in choosing the appropriate scaling factor because a small value caused by a negative update to a small concentration may diminish the update and result in false convergence even with very

  19. 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

  20. Landsat: A Global Land-Imaging Project

    USGS Publications Warehouse

    Headley, Rachel

    2010-01-01

    Across nearly four decades since 1972, Landsat satellites continuously have acquired space-based images of the Earth's land surface, coastal shallows, and coral reefs. The Landsat Program, a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), was established to routinely gather land imagery from space; consequently, NASA develops remote-sensing instruments and spacecraft, then launches and validates the satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground-data reception, archiving, product generation, and distribution. The result of this program is a visible, long-term record of natural and human-induced changes on the global landscape.

  1. Landsat: a global land-imaging mission

    USGS Publications Warehouse

    ,

    2012-01-01

    Across four decades since 1972, Landsat satellites have continuously acquired space-based images of the Earth's land surface, coastal shallows, and coral reefs. The Landsat Program, a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), was established to routinely gather land imagery from space. NASA develops remote-sensing instruments and spacecraft, then launches and validates the performance of the instruments and satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground reception, data archiving, product generation, and distribution. The result of this program is a long-term record of natural and human induced changes on the global landscape.

  2. Landsat: A global land-imaging mission

    USGS Publications Warehouse

    ,

    2012-01-01

    Across four decades since 1972, Landsat satellites have continuously acquired space-based images of the Earth's land surface, coastal shallows, and coral reefs. The Landsat Program, a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), was established to routinely gather land imagery from space. NASA develops remote-sensing instruments and spacecraft, then launches and validates the performance of the instruments and satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground reception, data archiving, product generation, and distribution. The result of this program is a long-term record of natural and human induced changes on the global landscape.

  3. Landsat: a global land imaging program

    USGS Publications Warehouse

    Byrnes, Raymond A.

    2012-01-01

    Landsat satellites have continuously acquired space-based images of the Earth's land surface, coastal shallows, and coral reefs across four decades. The Landsat Program, a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), was established to routinely gather land imagery from space. In practice, NASA develops remote-sensing instruments and spacecraft, launches satellites, and validates their performance. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground-data reception, archiving, product generation, and distribution. The result of this program is a visible, long-term record of natural and human-induced changes on the global landscape.

  4. An improved characterization of the land surface heterogeneity over Africa for use in Land Surface Models

    NASA Astrophysics Data System (ADS)

    Kaptue, A.; Roujean, J.; Begue, A.; Faroux, S.; Boone, A.; Hanan, N. P.; Prihodko, L.

    2011-12-01

    Information related to land surface is immensely important to global change science. For example land surface changes can alter regional climate through its effects on fluxes of water, energy and carbon. In the past decades, data sources and methodologies for characterizing land surface heterogeneity (e.g. land cover, leaf area index, fractional vegetation cover, bare soil and vegetation albedos) from remote sensing have evolved rapidly. The double ECOCLIMAP database - constituted by a land cover map and land surface variables and derived from AVHRR observations acquired between April 1992 and March 1993 - was developed to support investigations that require information related to spatio-temporal dynamics of land surface. Here we describe ECOCLIMAP-II, a new characterization of the land surface heterogeneity based on the latest generation of sensors, which represents an update of the ECOCLIMAP-I database over Africa. Owing to the many features of the MODIS sensors (a better accurate in spatial resolution and spectral information compared to the AVHRR sensor), a variety of methods have been developed for an extended period of 8 years (2000 to 2007) to strengthen consistency between land surface variables as required by the meteorological and ecological communities. The relative accuracy (or performance) quality of ECOCLIMAP-II was assessed (i.e. by comparison with other global datasets). Results illustrate a substantial refinement. For instance, the fractional vegetation cover resulting in a root mean square error of 34% instead of 64% in comparison with the original version of ECOCLIMAP. These new datasets have been implemented in land surface models (LSM) to investigate the sensitivity of energy, water and carbon fluxes to the land surface heterogeneity over the Sahel.

  5. MISR Level 3 Land Surface and Aerosol Versioning

    Atmospheric Science Data Center

    2016-11-04

      MISR Level 3 Land Surface and Aerosol Versioning Component Global Land Surface Product (CGLS) and Component Global Aerosol Product (CGAS) - ... fields for netCDF files (even though there is only one time value). This was a change requested by data product users to integrate better ...

  6. Updated global soil map for the Weather Research and Forecasting model and soil moisture initialization for the Noah land surface model

    NASA Astrophysics Data System (ADS)

    DY, C. Y.; Fung, J. C. H.

    2016-08-01

    A meteorological model requires accurate initial conditions and boundary conditions to obtain realistic numerical weather predictions. The land surface controls the surface heat and moisture exchanges, which can be determined by the physical properties of the soil and soil state variables, subsequently exerting an effect on the boundary layer meteorology. The initial and boundary conditions of soil moisture are currently obtained via National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data, which are collected operationally in 1° by 1° resolutions every 6 h. Another input to the model is the soil map generated by the Food and Agriculture Organization of the United Nations - United Nations Educational, Scientific and Cultural Organization (FAO-UNESCO) soil database, which combines several soil surveys from around the world. Both soil moisture from the FNL analysis data and the default soil map lack accuracy and feature coarse resolutions, particularly for certain areas of China. In this study, we update the global soil map with data from Beijing Normal University in 1 km by 1 km grids and propose an alternative method of soil moisture initialization. Simulations of the Weather Research and Forecasting model show that spinning-up the soil moisture improves near-surface temperature and relative humidity prediction using different types of soil moisture initialization. Explanations of that improvement and improvement of the planetary boundary layer height in performing process analysis are provided.

  7. Next generation of global land cover characterization, mapping, and monitoring

    NASA Astrophysics Data System (ADS)

    Giri, C.; Pengra, B.; Long, J.; Loveland, T. R.

    2013-12-01

    Land cover change is increasingly affecting the biophysics, biogeochemistry, and biogeography of the Earth's surface and the atmosphere, with far-reaching consequences to human well-being. However, our scientific understanding of the distribution and dynamics of land cover and land cover change (LCLCC) is limited. Previous global land cover assessments performed using coarse spatial resolution (300 m-1 km) satellite data did not provide enough thematic detail or change information for global change studies and for resource management. High resolution (˜30 m) land cover characterization and monitoring is needed that permits detection of land change at the scale of most human activity and offers the increased flexibility of environmental model parameterization needed for global change studies. However, there are a number of challenges to overcome before producing such data sets including unavailability of consistent global coverage of satellite data, sheer volume of data, unavailability of timely and accurate training and validation data, difficulties in preparing image mosaics, and high performance computing requirements. Integration of remote sensing and information technology is needed for process automation and high-performance computing needs. Recent developments in these areas have created an opportunity for operational high resolution land cover mapping, and monitoring of the world. Here, we report and discuss these advancements and opportunities in producing the next generations of global land cover characterization, mapping, and monitoring at 30-m spatial resolution primarily in the context of United States, Group on Earth Observations Global 30 m land cover initiative (UGLC).

  8. GLORI (GLObal navigation satellite system Reflectometry Instrument): A New Airborne GNSS-R receiver for land surface applications

    NASA Astrophysics Data System (ADS)

    Motte, Erwan; Zribi, Mehrez; Fanise, Pascal

    2015-04-01

    GLORI (GLObal navigation satellite system Reflectometry Instrument) is a new receiver dedicated to the airborne measurement of surface parameters such as soil moisture and biomass above ground and sea state (wave height and direction) above oceans. The instrument is based on the PARIS concept [Martin-Neira, 1993] using both the direct and surface-reflected L-band signals from the GPS constellation as a multistatic radar source. The receiver is based on one up-looking and one down-looking dual polarization hemispherical active antennas feeding a low-cost 4-channel SDR direct down-conversion receiver tuned to the GPS L1 frequency. The raw measurements are sampled at 16.368MHz and stored as 2-bit, IQ binary files. In post-processing, GPS acquisition and tracking are performed on the direct up-looking signal while the down-looking signal is processed blindly using tracking parameters from the direct signal. The obtained direct and reflected code-correlation waveforms are the basic observables for geophysical parameters inversion. The instrument was designed to be installed aboard the ATR42 experimental aircraft from the French SAFIRE fleet as a permanent payload. The long term goal of the project is to provide real-time continuous surface information for every flight performed. The aircraft records attitude information through its Inertial Measurement Unit and a commercial GPS receiver records additional information such as estimated doppler and code phase, receiver location, satellites azimuth and elevation. A series of test flights were performed over both the Toulouse and Gulf of Lion (Mediterranean Sea) regions during the period 17-21 Nov 2014 together with the KuROS radar [Hauser et al., 2014]. Using processing methods from the literature [Egido et al., 2014], preliminary results demonstrate the instrument sensitivity to both ground and ocean surface parameters estimation. A dedicated scientific flight campaign is planned at the end of second quarter 2015 with

  9. Ongoing Development of NASA's Global Land Data Assimilation System

    NASA Technical Reports Server (NTRS)

    Rodell, Matthew; Kato, Hiroko; Zaitchik, Ben

    2008-01-01

    NASA's Global Land Data Assimilation System (GLDAS) produces global fields of land surface states (e.g., soil moisture and temperature) and fluxes (e.g., latent heat flux and runoff) by driving offline land surface models with observation-based inputs, using the Land Information System (LIS) software. Since production began in 2001, GLDAS has supported more than 100 scientific investigations and applications. Some examples are GEWEX and NASA Energy and Water Cycle Study (NEWS) global water and energy budget analyses, interpretations of hydrologic data derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and forecast model initiation studies at NOAA and NASA. At the same time, the GLDAS team has continued improve results through the development of new modeling and data assimilation techniques. Here we describe several recent and ongoing innovations. These include global implementation of a runoff routing procedure, GRACE data assimilation, advanced snow cover assimilation, and irrigation modeling.

  10. Ongoing Development of NASA's Global Land Data Assimilation System

    NASA Technical Reports Server (NTRS)

    Rodell, Matthew; Kato, Hiroko; Zaitchik, Ben

    2008-01-01

    NASA's Global Land Data Assimilation System (GLDAS) produces global fields of land surface states (e.g., soil moisture and temperature) and fluxes (e.g., latent heat flux and runoff) by driving offline land surface models with observation-based inputs, using the Land Information System (LIS) software. Since production began in 2001, GLDAS has supported more than 100 scientific investigations and applications. Some examples are GEWEX and NASA Energy and Water Cycle Study (NEWS) global water and energy budget analyses, interpretations of hydrologic data derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and forecast model initiation studies at NOAA and NASA. At the same time, the GLDAS team has continued improve results through the development of new modeling and data assimilation techniques. Here we describe several recent and ongoing innovations. These include global implementation of a runoff routing procedure, GRACE data assimilation, advanced snow cover assimilation, and irrigation modeling.

  11. The CEOS constellation for land surface imaging

    USGS Publications Warehouse

    Bailey, G.B.; Berger, M.; Jeanjean, H.; Gallo, K.P.

    2007-01-01

    A constellation of satellites that routinely and frequently images the Earth's land surface in consistently calibrated wavelengths from the visible through the microwave and in spatial detail that ranges from sub-meter to hundreds of meters would offer enormous potential benefits to society. A well-designed and effectively operated land surface imaging satellite constellation could have great positive impact not only on the quality of life for citizens of all nations, but also on mankind's very ability to sustain life as we know it on this planet long into the future. The primary objective of the Committee on Earth Observation Satellites (CEOS) Land Surface Imaging (LSI) Constellation is to define standards (or guidelines) that describe optimal future LSI Constellation capabilities, characteristics, and practices. Standards defined for a LSI Constellation will be based on a thorough understanding of user requirements, and they will address at least three fundamental areas of the systems comprising a Land Surface Imaging Constellation: the space segments, the ground segments, and relevant policies and plans. Studies conducted by the LSI Constellation Study Team also will address current and shorter-term problems and issues facing the land remote sensing community today, such as seeking ways to work more cooperatively in the operation of existing land surface imaging systems and helping to accomplish tangible benefits to society through application of land surface image data acquired by existing systems. 2007 LSI Constellation studies are designed to establish initial international agreements, develop preliminary standards for a mid-resolution land surface imaging constellation, and contribute data to a global forest assessment.

  12. Land-atmosphere feedbacks amplify aridity increase over land under global warming

    NASA Astrophysics Data System (ADS)

    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, P. C. D.

    2016-09-01

    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.

  13. Prognostic land surface albedo from a dynamic global vegetation model clumped canopy radiative transfer scheme and satellite-derived geographic forest heights

    NASA Astrophysics Data System (ADS)

    Kiang, N. Y.; Yang, W.; Ni-Meister, W.; Aleinov, I. D.; Jonas, J.

    2014-12-01

    Vegetation cover was introduced into general circulations models (GCMs) in the 1980's to account for the effect of land surface albedo and water vapor conductance on the Earth's climate. Schemes assigning canopy albedoes by broad biome type have been superceded in 1990's by canopy radiative transfer schemes for homogeneous canopies obeying Beer's Law extinction as a function of leaf area index (LAI). Leaf albedo and often canopy height are prescribed by plant functional type (PFT). It is recognized that this approach does not effectively describe geographic variation in the radiative transfer of vegetated cover, particularly for mixed and sparse canopies. GCM-coupled dynamic global vegetation models (DGVMs) have retained these simple canopy representations, with little further evaluation of their albedos. With the emergence lidar-derived canopy vertical structure data, DGVM modelers are now revisiting albedo simulation. We present preliminary prognostic global land surface albedo produced by the Ent Terrestrial Biosphere Model (TBM), a DGVM coupled to the NASA Goddard Institute for Space Studies (GISS) GCM. The Ent TBM is a next generation DGVM designed to incorporate variation in canopy heights, and mixed and sparse canopies. For such dynamically varying canopy structure, it uses the Analytical Clumped Two-Stream (ACTS) canopy radiative transfer model, which is derived from gap probability theory for canopies of tree cohorts with ellipsoidal crowns, and accounts for soil, snow, and bare stems. We have developed a first-order global vegetation structure data set (GVSD), which gives a year of satellite-derived geographic variation in canopy height, maximum canopy leaf area, and seasonal LAI. Combined with Ent allometric relations, this data set provides population density and foliage clumping within crowns. We compare the Ent prognostic albedoes to those of the previous GISS GCM scheme, and to satellite estimates. The impact of albedo differences on surface

  14. Global Surface Temperature Change

    NASA Astrophysics Data System (ADS)

    Hansen, J.; Ruedy, R.; Sato, M.; Lo, K.

    2010-12-01

    We update the Goddard Institute for Space Studies (GISS) analysis of global surface temperature change, compare alternative analyses, and address questions about perception and reality of global warming. Satellite-observed night lights are used to identify measurement stations located in extreme darkness and adjust temperature trends of urban and periurban stations for nonclimatic factors, verifying that urban effects on analyzed global change are small. Because the GISS analysis combines available sea surface temperature records with meteorological station measurements, we test alternative choices for the ocean data, showing that global temperature change is sensitive to estimated temperature change in polar regions where observations are limited. We use simple 12 month (and n × 12) running means to improve the information content in our temperature graphs. Contrary to a popular misconception, the rate of warming has not declined. Global temperature is rising as fast in the past decade as in the prior 2 decades, despite year-to-year fluctuations associated with the El Niño-La Niña cycle of tropical ocean temperature. Record high global 12 month running mean temperature for the period with instrumental data was reached in 2010.

  15. Towards a global land subsidence map

    NASA Astrophysics Data System (ADS)

    Erkens, Gilles; Sutanudjaja, Edwin

    2015-04-01

    Human activities have intensified large and growing global groundwater depletion problems. Groundwater depletion under cities in delta regions or river valleys is in many cases leading to significant land subsidence, causing damage to infrastructure and increases in the risk of flooding. Yet, a global land subsidence map is not available. Such map is crucial to raise global awareness of land subsidence. Land subsidence is costly (probably in the order of billions of dollars annually). One of the most prominent causes for land subsidence is excessive groundwater extraction for domestic, agricultural and industrial use. For instance, the Vietnamese Mekong Delta sinks on average 1.6 cm/yr, attributed to groundwater extraction. Crucially, in many coastal mega-cities, land subsidence is accelerated by ongoing urbanization. In Jakarta land subsidence is up to 20 cm/yr. With ongoing economic development and related increased demands for water, the expectation is that land subsidence rates and areas affected will accelerate and expand in the near future. A global land subsidence map would not only locate current land subsidence hotspots but also help to identify future sinking areas under different socio-economic development scenarios. A global hydrological model, PCR-GLOBWB, serves as the starting point. The hydrological model includes a global simulation of spatio-temporal groundwater head dynamics under abstractions for the period 1960-2100. The hydrological model is coupled to a land subsidence module, iMOD-SUB-CR, which is an extension of the MOD-FLOW SUB-WT module developed by the USGS. The required subsurface information is unavailable at this time, but will be approached by using different scenarios of subsurface build-up. The outcomes will be compared to measured or modeled land level lowering in well-known damaging case study areas, such as Jakarta and the Vietnamese Mekong Delta, as well as in well-known recovering areas, such as Venice and Tokyo, which have

  16. Oscillations in land surface hydrological cycle

    NASA Astrophysics Data System (ADS)

    Labat, D.

    2006-02-01

    Hydrological cycle is the perpetual movement of water throughout the various component of the global Earth's system. Focusing on the land surface component of this cycle, the determination of the succession of dry and humid periods is of high importance with respect to water resources management but also with respect to global geochemical cycles. This knowledge requires a specified estimation of recent fluctuations of the land surface cycle at continental and global scales. Our approach leans towards a new estimation of freshwater discharge to oceans from 1875 to 1994 as recently proposed by Labat et al. [Labat, D., Goddéris, Y., Probst, JL, Guyot, JL, 2004. Evidence for global runoff increase related to climate warming. Advances in Water Resources, 631-642]. Wavelet analyses of the annual freshwater discharge time series reveal an intermittent multiannual variability (4- to 8-y, 14- to 16-y and 20- to 25-y fluctuations) and a persistent multidecadal 30- to 40-y variability. Continent by continent, reasonable relationships between land-water cycle oscillations and climate forcing (such as ENSO, NAO or sea surface temperature) are proposed even though if such relationships or correlations remain very complex. The high intermittency of interannual oscillations and the existence of persistent multidecadal fluctuations make prediction difficult for medium-term variability of droughts and high-flows, but lead to a more optimistic diagnostic for long-term fluctuations prediction.

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

    NASA Astrophysics Data System (ADS)

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

    2017-08-01

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

  18. The global land rush and climate change

    NASA Astrophysics Data System (ADS)

    Davis, Kyle Frankel; Rulli, Maria Cristina; D'Odorico, Paolo

    2015-08-01

    Climate change poses a serious global challenge in the face of rapidly increasing human demand for energy and food. A recent phenomenon in which climate change may play an important role is the acquisition of large tracts of land in the developing world by governments and corporations. In the target countries, where land is relatively inexpensive, the potential to increase crop yields is generally high and property rights are often poorly defined. By acquiring land, investors can realize large profits and countries can substantially alter the land and water resources under their control, thereby changing their outlook for meeting future demand. While the drivers, actors, and impacts involved with land deals have received substantial attention in the literature, we propose that climate change plays an important yet underappreciated role, both through its direct effects on agricultural production and through its influence on mitigative or adaptive policy decisions. Drawing from various literature sources as well as a new global database on reported land deals, we trace the evolution of the global land rush and highlight prominent examples in which the role of climate change is evident. We find that climate change—both historical and anticipated—interacts substantially with drivers of land acquisitions, having important implications for the resilience of communities in targeted areas. As a result of this synthesis, we ultimately contend that considerations of climate change should be integrated into future policy decisions relating to the large-scale land acquisitions.

  19. Benchmarking global land surface models in CMIP5: analysis of ecosystem water use efficiency (WUE) and Budyko framework

    NASA Astrophysics Data System (ADS)

    Li, Longhui

    2015-04-01

    Twelve Earth System Models (ESMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated in terms of ecosystem water use efficiency (WUE) and Budyko framework. Simulated values of GPP and ET from ESMs were validated against with FLUXNET measurements, and the slope of linear regression between the measurement and the model ranged from 0.24 in CanESM2 to 0.8 in GISS-E2 for GPP, and from 0.51 to 0.86 for ET. The performances of 12 ESMs in simulating ET are generally better than GPP. Compared with flux-tower-based estimates by Jung et al. [Journal of Geophysical Research 116 (2011) G00J07] (JU11), all ESMs could capture the latitudinal variations of GPP and ET, but the majority of models extremely overestimated GPP and ET, particularly around the equator. The 12 ESMs showed much larger variations in latitudinal WUE. 4 of 12 ESMs predicted global annual GPP of higher than 150 Pg C year-1, and the other 8 ESMs predicted global GPP with ±15% error of the JU11 GPP. In contrast, all EMSs predicted moderate bias for global ET. The coefficient of variation (CV) of ET (0.11) is significantly less than that of GPP (0.25). More than half of 12 ESMs generally comply with the Budyko framework but some models deviated much. Spatial analysis of error in GPP and ET indicated that model results largely differ among models at different regions. This study suggested that the estimate of ET was much better than GPP. Incorporating the convergence of WUE and the Budyko framework into ESMs as constraints in the next round of CMIP scheme is expected to decrease the uncertainties of carbon and water fluxes estimates.

  20. Land surface Verification Toolkit (LVT)

    NASA Technical Reports Server (NTRS)

    Kumar, Sujay V.

    2017-01-01

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

  1. A NEW LAND-SURFACE MODEL IN MM5

    EPA Science Inventory

    There has recently been a general realization that more sophisticated modeling of land-surface processes can be important for mesoscale meteorology models. Land-surface models (LSMs) have long been important components in global-scale climate models because of their more compl...

  2. A NEW LAND-SURFACE MODEL IN MM5

    EPA Science Inventory

    There has recently been a general realization that more sophisticated modeling of land-surface processes can be important for mesoscale meteorology models. Land-surface models (LSMs) have long been important components in global-scale climate models because of their more compl...

  3. Climate Effects of Global Land Cover Change

    SciTech Connect

    Gibbard, S G; Caldeira, K; Bala, G; Phillips, T; Wickett, M

    2005-08-24

    There are two competing effects of global land cover change on climate: an albedo effect which leads to heating when changing from grass/croplands to forest, and an evapotranspiration effect which tends to produce cooling. It is not clear which effect would dominate in a global land cover change scenario. We have performed coupled land/ocean/atmosphere simulations of global land cover change using the NCAR CAM3 atmospheric general circulation model. We find that replacement of current vegetation by trees on a global basis would lead to a global annual mean warming of 1.6 C, nearly 75% of the warming produced under a doubled CO{sub 2} concentration, while global replacement by grasslands would result in a cooling of 0.4 C. These results suggest that more research is necessary before forest carbon storage should be deployed as a mitigation strategy for global warming. In particular, high latitude forests probably have a net warming effect on the Earth's climate.

  4. Land Surface Emission Modeling to Support Physical Precipitation Retrievals

    NASA Technical Reports Server (NTRS)

    Peters-Lidard, Christina D.; Harrison, Kenneth; Kumar, Sujay; Ferraro, Ralph; Skofronick-Jackson, Gail

    2010-01-01

    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.

  5. Next generation of global land cover characterization, mapping, and monitoring

    USGS Publications Warehouse

    Giri, Chandra; Pengra, Bruce; Long, J.; Loveland, Thomas R.

    2013-01-01

    Land cover change is increasingly affecting the biophysics, biogeochemistry, and biogeography of the Earth's surface and the atmosphere, with far-reaching consequences to human well-being. However, our scientific understanding of the distribution and dynamics of land cover and land cover change (LCLCC) is limited. Previous global land cover assessments performed using coarse spatial resolution (300 m–1 km) satellite data did not provide enough thematic detail or change information for global change studies and for resource management. High resolution (∼30 m) land cover characterization and monitoring is needed that permits detection of land change at the scale of most human activity and offers the increased flexibility of environmental model parameterization needed for global change studies. However, there are a number of challenges to overcome before producing such data sets including unavailability of consistent global coverage of satellite data, sheer volume of data, unavailability of timely and accurate training and validation data, difficulties in preparing image mosaics, and high performance computing requirements. Integration of remote sensing and information technology is needed for process automation and high-performance computing needs. Recent developments in these areas have created an opportunity for operational high resolution land cover mapping, and monitoring of the world. Here, we report and discuss these advancements and opportunities in producing the next generations of global land cover characterization, mapping, and monitoring at 30-m spatial resolution primarily in the context of United States, Group on Earth Observations Global 30 m land cover initiative (UGLC).

  6. A Meta-Analysis of Global Urban Land Expansion

    PubMed Central

    Seto, Karen C.; Fragkias, Michail; Güneralp, Burak; Reilly, Michael K.

    2011-01-01

    The conversion of Earth's land surface to urban uses is one of the most irreversible human impacts on the global biosphere. It drives the loss of farmland, affects local climate, fragments habitats, and threatens biodiversity. Here we present a meta-analysis of 326 studies that have used remotely sensed images to map urban land conversion. We report a worldwide observed increase in urban land area of 58,000 km2 from 1970 to 2000. India, China, and Africa have experienced the highest rates of urban land expansion, and the largest change in total urban extent has occurred in North America. Across all regions and for all three decades, urban land expansion rates are higher than or equal to urban population growth rates, suggesting that urban growth is becoming more expansive than compact. Annual growth in GDP per capita drives approximately half of the observed urban land expansion in China but only moderately affects urban expansion in India and Africa, where urban land expansion is driven more by urban population growth. In high income countries, rates of urban land expansion are slower and increasingly related to GDP growth. However, in North America, population growth contributes more to urban expansion than it does in Europe. Much of the observed variation in urban expansion was not captured by either population, GDP, or other variables in the model. This suggests that contemporary urban expansion is related to a variety of factors difficult to observe comprehensively at the global level, including international capital flows, the informal economy, land use policy, and generalized transport costs. Using the results from the global model, we develop forecasts for new urban land cover using SRES Scenarios. Our results show that by 2030, global urban land cover will increase between 430,000 km2 and 12,568,000 km2, with an estimate of 1,527,000 km2 more likely. PMID:21876770

  7. Predicting the response of the Amazon rainforest to persistent drought conditions under current and future climates: a major challenge for global land surface models

    NASA Astrophysics Data System (ADS)

    Joetzjer, E.; Delire, C.; Douville, H.; Ciais, P.; Decharme, B.; Fisher, R.; Christoffersen, B.; Calvet, J. C.; da Costa, A. C. L.; Ferreira, L. V.; Meir, P.

    2014-12-01

    While a majority of global climate models project drier and longer dry seasons over the Amazon under higher CO2 levels, large uncertainties surround the response of vegetation to persistent droughts in both present-day and future climates. We propose a detailed evaluation of the ability of the ISBACC (Interaction Soil-Biosphere-Atmosphere Carbon Cycle) land surface model to capture drought effects on both water and carbon budgets, comparing fluxes and stocks at two recent throughfall exclusion (TFE) experiments performed in the Amazon. We also explore the model sensitivity to different water stress functions (WSFs) and to an idealized increase in CO2 concentration and/or temperature. In spite of a reasonable soil moisture simulation, ISBACC struggles to correctly simulate the vegetation response to TFE whose amplitude and timing is highly sensitive to the WSF. Under higher CO2 concentrations, the increased water-use efficiency (WUE) mitigates the sensitivity of ISBACC to drought. While one of the proposed WSF formulations improves the response of most ISBACC fluxes, except respiration, a parameterization of drought-induced tree mortality is missing for an accurate estimate of the vegetation response. Also, a better mechanistic understanding of the forest responses to drought under a warmer climate and higher CO2 concentration is clearly needed.

  8. Predicting the response of the Amazon rainforest to persistent drought conditions under current and future climates: a major challenge for global land surface models

    NASA Astrophysics Data System (ADS)

    Joetzjer, E.; Delire, C.; Douville, H.; Ciais, P.; Decharme, B.; Fisher, R.; Christoffersen, B.; Calvet, J. C.; da Costa, A. C. L.; Ferreira, L. V.; Meir, P.

    2014-08-01

    While a majority of Global Climate Models project dryer and longer dry seasons over the Amazon under higher CO2 levels, large uncertainties surround the response of vegetation to persistent droughts in both present-day and future climates. We propose a detailed evaluation of the ability of the ISBACC Land Surface Model to capture drought effects on both water and carbon budgets, comparing fluxes and stocks at two recent ThroughFall Exclusion (TFE) experiments performed in the Amazon. We also explore the model sensitivity to different Water Stress Function (WSF) and to an idealized increase in CO2 concentration and/or temperature. In spite of a reasonable soil moisture simulation, ISBACC struggles to correctly simulate the vegetation response to TFE whose amplitude and timing is highly sensitive to the WSF. Under higher CO2 concentration, the increased Water Use Efficiency (WUE) mitigates the ISBACC's sensitivity to drought. While one of the proposed WSF formulation improves the response of most ISBACC fluxes, except respiration, a parameterization of drought-induced tree mortality is missing for an accurate estimate of the vegetation response. Also, a better mechanistic understanding of the forest responses to drought under a warmer climate and higher CO2 concentration is clearly needed.

  9. Land cover mapping of North and Central America—Global Land Cover 2000

    USGS Publications Warehouse

    Latifovic, Rasim; Zhu, Zhi-Liang

    2004-01-01

    The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

  10. Land-related global habitability science issues

    NASA Technical Reports Server (NTRS)

    1983-01-01

    The scientific investigation of the viewpoint of the biosphere that living organisms and their physical and chemical environment are bound, inseparable parts of one set of closely coupled global processes of the global biogeochemical system, life and life support cycles, is discussed as one of the major scientific challenges of the next decade by building from understanding land processes to interdisciplinary, holistic studies of biospheric dynamics including human impacts.

  11. Phoenix Landing Site Indicated on Global View

    NASA Technical Reports Server (NTRS)

    2008-01-01

    NASA's Phoenix Mars Mission landed at 68.2 degrees north latitude, 234.2 degrees east longitude. The far-northern location of the site is indicated on this global view from the Mars Orbiter Camera on NASA's Mars Global Surveyor.

    The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by JPL, Pasadena, Calif. Spacecraft development was by Lockheed Martin Space Systems, Denver.

  12. Relative roles of differential SST warming, uniform SST warming and land surface warming in determining the Walker circulation changes under global warming

    NASA Astrophysics Data System (ADS)

    Zhang, Lei; Li, Tim

    2017-02-01

    Most of CMIP5 models projected a weakened Walker circulation in tropical Pacific, but what causes such change is still an open question. By conducting idealized numerical simulations separating the effects of the spatially uniform sea surface temperature (SST) warming, extra land surface warming and differential SST warming, we demonstrate that the weakening of the Walker circulation is attributed to the western North Pacific (WNP) monsoon and South America land effects. The effect of the uniform SST warming is through so-called "richest-get-richer" mechanism. In response to a uniform surface warming, the WNP monsoon is enhanced by competing moisture with other large-scale convective branches. The strengthened WNP monsoon further induces surface westerlies in the equatorial western-central Pacific, weakening the Walker circulation. The increase of the greenhouse gases leads to a larger land surface warming than ocean surface. As a result, a greater thermal contrast occurs between American Continent and equatorial Pacific. The so-induced zonal pressure gradient anomaly forces low-level westerly anomalies over the equatorial eastern Pacific and weakens the Walker circulation. The differential SST warming also plays a role in driving low-level westerly anomalies over tropical Pacific. But such an effect involves a positive air-sea feedback that amplifies the weakening of both east-west SST gradient and Pacific trade winds.

  13. Relative roles of differential SST warming, uniform SST warming and land surface warming in determining the Walker circulation changes under global warming

    NASA Astrophysics Data System (ADS)

    Zhang, Lei; Li, Tim

    2016-04-01

    Most of CMIP5 models projected a weakened Walker circulation in tropical Pacific, but what causes such change is still an open question. By conducting idealized numerical simulations separating the effects of the spatially uniform sea surface temperature (SST) warming, extra land surface warming and differential SST warming, we demonstrate that the weakening of the Walker circulation is attributed to the western North Pacific (WNP) monsoon and South America land effects. The effect of the uniform SST warming is through so-called "richest-get-richer" mechanism. In response to a uniform surface warming, the WNP monsoon is enhanced by competing moisture with other large-scale convective branches. The strengthened WNP monsoon further induces surface westerlies in the equatorial western-central Pacific, weakening the Walker circulation. The increase of the greenhouse gases leads to a larger land surface warming than ocean surface. As a result, a greater thermal contrast occurs between American Continent and equatorial Pacific. The so-induced zonal pressure gradient anomaly forces low-level westerly anomalies over the equatorial eastern Pacific and weakens the Walker circulation. The differential SST warming also plays a role in driving low-level westerly anomalies over tropical Pacific. But such an effect involves a positive air-sea feedback that amplifies the weakening of both east-west SST gradient and Pacific trade winds.

  14. Coupled land surface/hydrologic/atmospheric models

    NASA Technical Reports Server (NTRS)

    Pielke, Roger; Steyaert, Lou; Arritt, Ray; Lahtakia, Mercedes; Smith, Chris; Ziegler, Conrad; Soong, Su Tzai; Avissar, Roni; Wetzel, Peter; Sellers, Piers

    1993-01-01

    The topics covered include the following: prototype land cover characteristics data base for the conterminous United States; surface evapotranspiration effects on cumulus convection and implications for mesoscale models; the use of complex treatment of surface hydrology and thermodynamics within a mesoscale model and some related issues; initialization of soil-water content for regional-scale atmospheric prediction models; impact of surface properties on dryline and MCS evolution; a numerical simulation of heavy precipitation over the complex topography of California; representing mesoscale fluxes induced by landscape discontinuities in global climate models; emphasizing the role of subgrid-scale heterogeneity in surface-air interaction; and problems with modeling and measuring biosphere-atmosphere exchanges of energy, water, and carbon on large scales.

  15. Magnitude and variability of land evaporation and its components at the global scale

    USDA-ARS?s Scientific Manuscript database

    A physics-based methodology is applied to estimate global land-surface evaporation from multi-satellite observations. GLEAM (Global Land-surface Evaporation: the Amsterdam Methodology) combines a wide range of remotely sensed observations within a Priestley and Taylor-based framework. Daily actual e...

  16. 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

  17. Numerical modeling and remote sensing of global water management systems: Applications for land surface modeling, satellite missions, and sustainable water resources

    NASA Astrophysics Data System (ADS)

    Solander, Kurt C.

    The ability to accurately quantify water storages and fluxes in water management systems through observations or models is of increasing importance due to the expected impacts from climate change and population growth worldwide. Here, I describe three innovative techniques developed to better understand this problem. First, a model was created to represent reservoir storage and outflow with the objective of integration into a Land Surface Model (LSM) to simulate the impacts of reservoir management on the climate system. Given this goal, storage capacity represented the lone model input required that is not already available to an LSM user. Model parameterization was linked to air temperature to allow future simulations to adapt to a changing climate, making it the first such model to mimic the potential response of a reservoir operator to climate change. Second, spatial and temporal error properties of future NASA Surface Water and Ocean Topography (SWOT) satellite reservoir operations were quantified. This work invoked the use of the SWOTsim instrument simulator, which was run over a number of synthetic and actual reservoirs so the resulting error properties could be extrapolated to the global scale. The results provide eventual users of SWOT data with a blueprint of expected reservoir error properties so such characteristics can be determined a priori for a reservoir given knowledge about its topology and anticipated repeat orbit pass over its location. Finally, data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission was used in conjunction with in-situ water use records to evaluate sustainable water use at the two-digit HUC basin scale over the contiguous United States. Results indicate that the least sustainable water management region is centered in the southwest, where consumptive water use exceeded water availability by over 100% on average for some of these basins. This work represents the first attempt at evaluating sustainable

  18. Development of an Independent Global Land Cover Validation Dataset

    NASA Astrophysics Data System (ADS)

    Sulla-Menashe, D. J.; Olofsson, P.; Woodcock, C. E.; Holden, C.; Metcalfe, M.; Friedl, M. A.; Stehman, S. V.; Herold, M.; Giri, C.

    2012-12-01

    Accurate information related to the global distribution and dynamics in global land cover is critical for a large number of global change science questions. A growing number of land cover products have been produced at regional to global scales, but the uncertainty in these products and the relative strengths and weaknesses among available products are poorly characterized. To address this limitation we are compiling a database of high spatial resolution imagery to support international land cover validation studies. Validation sites were selected based on a probability sample, and may therefore be used to estimate statistically defensible accuracy statistics and associated standard errors. Validation site locations were identified using a stratified random design based on 21 strata derived from an intersection of Koppen climate classes and a population density layer. In this way, the two major sources of global variation in land cover (climate and human activity) are explicitly included in the stratification scheme. At each site we are acquiring high spatial resolution (< 1-m) satellite imagery for 5-km x 5-km blocks. The response design uses an object-oriented hierarchical legend that is compatible with the UN FAO Land Cover Classification System. Using this response design, we are classifying each site using a semi-automated algorithm that blends image segmentation with a supervised RandomForest classification algorithm. In the long run, the validation site database is designed to support international efforts to validate land cover products. To illustrate, we use the site database to validate the MODIS Collection 4 Land Cover product, providing a prototype for validating the VIIRS Surface Type Intermediate Product scheduled to start operational production early in 2013. As part of our analysis we evaluate sources of error in coarse resolution products including semantic issues related to the class definitions, mixed pixels, and poor spectral separation between

  19. The global land Cryosphere Radiative Effect during the MODIS era

    NASA Astrophysics Data System (ADS)

    Singh, D.; Flanner, M. G.; Perket, J.

    2015-07-01

    Cryosphere Radiative Effect (CrRE) is the instantaneous influence of snow- and ice-cover on Earth's top of atmosphere (TOA) solar energy budget. Here, we apply measurements from the Moderate Resolution Imaging Spectrometer (MODIS), combined with microwave retrievals of snow presence and radiative kernels produced from 4 different models, to derive CrRE over global land during 2001-2013. We estimate global annual mean land CrRE during this period of -2.6 W m-2, with variations from -2.2 to -3.0 W m-2 resulting from use of different kernels, and variations of -2.4 to -2.6 W m-2 resulting from different algorithmic determinations of snow presence and surface albedo. Slightly more than half of the global land CrRE originates from perennial snow on Antarctica, whereas the majority of the Northern Hemisphere effect originates from seasonal snow. Consequently, the Northern Hemisphere land CrRE peaks at -6.0 W m-2 in April, whereas the Southern Hemisphere effect more closely follows the austral insolation cycle, peaking in December. Mountain glaciers resolved in 0.05° MODIS data contribute about -0.037 W m-2 (1.4 %) of the global effect, with the majority (94 %) of this contribution originating from the Himalayas. Inter-annual trends in the global annual mean land CrRE are not statistically significant during the MODIS era, but trends are positive (less negative) over large areas of Northern Asia, especially during spring, and slightly negative over Antarctica, possibly due to increased snowfall. During a common overlap period of 2001-2008, our MODIS estimates of the Northern Hemisphere land CrRE are about 18 % smaller (less negative) than previous estimates derived from coarse-resolution AVHRR data, though inter-annual variations are well correlated (r = 0.78), indicating that these data are useful in determining longer term trends in land CrRE.

  20. 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

  1. Exploring Dynamics of Land surface-Subsurface Coupling Under Change

    NASA Astrophysics Data System (ADS)

    Ajami, Hoori; McCabe, Matthew F.; Evans, Jason P.

    2013-04-01

    The degree of land surface-subsurface coupling is controlled by complex interactions between the atmosphere, land surface condition and subsurface hydrologic characteristics. Global climate models project increases in temperature and changes in precipitation rates and patterns which in turn alter terrestrial water and energy budgets impacting water resources. However, the degree of land surface-subsurface coupling under scenarios of land cover and climate change has not been fully explored. In this study, we used an integrated groundwater-surface water-land surface model (ParFlow.CLM) across a semi-arid catchment located in the central west New South Wales, Australia to assess variability in water and energy fluxes under historic condition and scenarios of climate and land cover change. The Baldry hydrological observatory situated in a topographically flat terrain has the area of 2 km2 and contains two distinct land cover types of pasture and a regenerated Eucalyptus forest. High resolution groundwater level measurements in the site reveal differences in groundwater connectivity in wet versus dry periods in pasture and Eucalyptus forest for the historic condition. Using downscaled climate forcing obtained from a regional climate model for eastern Australia, the degree of land surface-subsurface coupling within the catchment was examined under various scenarios of climate and changes in land cover types. It is expected that a fully integrated hydrologic model like ParFlow.CLM improve predictions in land-atmospheric feedback processes under changes in hydrologic conditions.

  2. Open and reproducible global land use classification

    NASA Astrophysics Data System (ADS)

    Nüst, Daniel; Václavík, Tomáš; Pross, Benjamin

    2015-04-01

    Researchers led by the Helmholtz Centre for Environmental research (UFZ) developed a new world map of land use systems based on over 30 diverse indicators (http://geoportal.glues.geo.tu-dresden.de/stories/landsystemarchetypes.html) of land use intensity, climate and environmental and socioeconomic factors. They identified twelve land system archetypes (LSA) using a data-driven classification algorithm (self-organizing maps) to assess global impacts of land use on the environment, and found unexpected similarities across global regions. We present how the algorithm behind this analysis can be published as an executable web process using 52°North WPS4R (https://wiki.52north.org/bin/view/Geostatistics/WPS4R) within the GLUES project (http://modul-a.nachhaltiges-landmanagement.de/en/scientific-coordination-glues/). WPS4R is an open source collaboration platform for researchers, analysts and software developers to publish R scripts (http://www.r-project.org/) as a geo-enabled OGC Web Processing Service (WPS) process. The interoperable interface to call the geoprocess allows both reproducibility of the analysis and integration of user data without knowledge about web services or classification algorithms. The open platform allows everybody to replicate the analysis in their own environments. The LSA WPS process has several input parameters, which can be changed via a simple web interface. The input parameters are used to configure both the WPS environment and the LSA algorithm itself. The encapsulation as a web process allows integration of non-public datasets, while at the same time the publication requires a well-defined documentation of the analysis. We demonstrate this platform specifically to domain scientists and show how reproducibility and open source publication of analyses can be enhanced. We also discuss future extensions of the reproducible land use classification, such as the possibility for users to enter their own areas of interest to the system and

  3. Enso effects on land surface-biosphere-atmosphere interactions: A global study from satellite remote sensing and NCEP/NCAR reanalysis data

    NASA Astrophysics Data System (ADS)

    Bartholomew, Henry D.

    Two mechanisms are examined to reveal the impact of El Nino-Southern Oscillation (ENSO) on land surface, biosphere, and atmosphere interactions. One mechanism is large-scale dynamics---namely, changes in circulation patterns and the jet stream. Another mechanism is local land cover effects, in particular, vegetation and skin temperature. Non-lag and lag correlation coefficients between Nino 3 indices derived from sea-surface temperature (SST) anomalies and land surface variables from satellite based moderate resolution imaging spectroradiometer (MODIS) data, as well as National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis data are analyzed for 2001-2010. Strong positive correlations between January Nino 3 indices and both air temperature (Tair) skin temperature (Tskin) occur over the northwest United States, western Canada, and southern Alaska, suggesting that an El Nino event is associated with warmer winter temperatures over these regions, consistent with previous studies. In addition, strong negative correlations exist over central and northern Europe in January, meaning colder than normal winters, with positive correlations over central Siberia meaning warmer than normal winters. Despite the different physical meanings between Tair and T skin, the general response to ENSO is the same. Furthermore, satellite observations of Tskin provide more rich information and higher spatial resolution than NCEP/NCAR Reanalysis data.

  4. Global land use change, economic globalization, and the looming land scarcity

    PubMed Central

    Lambin, Eric F.; Meyfroidt, Patrick

    2011-01-01

    A central challenge for sustainability is how to preserve forest ecosystems and the services that they provide us while enhancing food production. This challenge for developing countries confronts the force of economic globalization, which seeks cropland that is shrinking in availability and triggers deforestation. Four mechanisms—the displacement, rebound, cascade, and remittance effects—that are amplified by economic globalization accelerate land conversion. A few developing countries have managed a land use transition over the recent decades that simultaneously increased their forest cover and agricultural production. These countries have relied on various mixes of agricultural intensification, land use zoning, forest protection, increased reliance on imported food and wood products, the creation of off-farm jobs, foreign capital investments, and remittances. Sound policies and innovations can therefore reconcile forest preservation with food production. Globalization can be harnessed to increase land use efficiency rather than leading to uncontrolled land use expansion. To do so, land systems should be understood and modeled as open systems with large flows of goods, people, and capital that connect local land use with global-scale factors. PMID:21321211

  5. Global land use change, economic globalization, and the looming land scarcity.

    PubMed

    Lambin, Eric F; Meyfroidt, Patrick

    2011-03-01

    A central challenge for sustainability is how to preserve forest ecosystems and the services that they provide us while enhancing food production. This challenge for developing countries confronts the force of economic globalization, which seeks cropland that is shrinking in availability and triggers deforestation. Four mechanisms-the displacement, rebound, cascade, and remittance effects-that are amplified by economic globalization accelerate land conversion. A few developing countries have managed a land use transition over the recent decades that simultaneously increased their forest cover and agricultural production. These countries have relied on various mixes of agricultural intensification, land use zoning, forest protection, increased reliance on imported food and wood products, the creation of off-farm jobs, foreign capital investments, and remittances. Sound policies and innovations can therefore reconcile forest preservation with food production. Globalization can be harnessed to increase land use efficiency rather than leading to uncontrolled land use expansion. To do so, land systems should be understood and modeled as open systems with large flows of goods, people, and capital that connect local land use with global-scale factors.

  6. 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.

  7. 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.

  8. The Land Surface Temperature Impact to Land Cover Types

    NASA Astrophysics Data System (ADS)

    Ibrahim, I.; Abu Samah, A.; Fauzi, R.; Noor, N. M.

    2016-06-01

    Land cover type is an important signature that is usually used to understand the interaction between the ground surfaces with the local temperature. Various land cover types such as high density built up areas, vegetation, bare land and water bodies are areas where heat signature are measured using remote sensing image. The aim of this study is to analyse the impact of land surface temperature on land cover types. The objectives are 1) to analyse the mean temperature for each land cover types and 2) to analyse the relationship of temperature variation within land cover types: built up area, green area, forest, water bodies and bare land. The method used in this research was supervised classification for land cover map and mono window algorithm for land surface temperature (LST) extraction. The statistical analysis of post hoc Tukey test was used on an image captured on five available images. A pixel-based change detection was applied to the temperature and land cover images. The result of post hoc Tukey test for the images showed that these land cover types: built up-green, built up-forest, built up-water bodies have caused significant difference in the temperature variation. However, built up-bare land did not show significant impact at p<0.05. These findings show that green areas appears to have a lower temperature difference, which is between 2° to 3° Celsius compared to urban areas. The findings also show that the average temperature and the built up percentage has a moderate correlation with R2 = 0.53. The environmental implications of these interactions can provide some insights for future land use planning in the region.

  9. Land cover change or land-use intensification: simulating land system change with a global-scale land change model.

    PubMed

    van Asselen, Sanneke; Verburg, Peter H

    2013-12-01

    Land-use change is both a cause and consequence of many biophysical and socioeconomic changes. The CLUMondo model provides an innovative approach for global land-use change modeling to support integrated assessments. Demands for goods and services are, in the model, supplied by a variety of land systems that are characterized by their land cover mosaic, the agricultural management intensity, and livestock. Land system changes are simulated by the model, driven by regional demand for goods and influenced by local factors that either constrain or promote land system conversion. A characteristic of the new model is the endogenous simulation of intensification of agricultural management versus expansion of arable land, and urban versus rural settlements expansion based on land availability in the neighborhood of the location. Model results for the OECD Environmental Outlook scenario show that allocation of increased agricultural production by either management intensification or area expansion varies both among and within world regions, providing useful insight into the land sparing versus land sharing debate. The land system approach allows the inclusion of different types of demand for goods and services from the land system as a driving factor of land system change. Simulation results are compared to observed changes over the 1970-2000 period and projections of other global and regional land change models.

  10. Development of a Physically Based Land Surface Emissivity for TMI

    NASA Astrophysics Data System (ADS)

    Turk, F. J.; Li, L.; Haddad, Z.

    2010-12-01

    Over-land precipitation retrieval using active or passive microwave spaceborne measurements requires accurate estimates of the radiometric signature of the surface to constrain the rainfall solutions. Such measurements are a vital part of the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Mission (GPM). For a passive microwave (PMW) radiometer, the radiometric signature is the land surface emissivity, which is characterized by uncertainties introduced by temporal variations of temperature, soil moisture and vegetation water content. Because no such characterization of the surface signature is available at microwave frequencies above L-band, current PMW land rainfall algorithms rely upon scattering-induced signatures at high frequencies (≥ 85 GHz) and are empirical in nature. Typically, not only is it difficult to quantify the spatial and temporal variability of the surface characteristics that are due to the rain itself, one would also need to know how the surface signature under the rain differs from the signature in neighboring clear areas. Therefore, an improved assessment of the surface emissivities are crucial if one is to make better use of emission-based channels (< 85 GHz) over land for TRMM and future GPM algorithms. In principle, accurate estimates of surface characteristics require accurate knowledge of land surface parameters including surface type, soil moisture and vegetation water content, and the forward modeling to convert land surface parameters to rain-affected surface emissivity. We demonstrate an adaptation of the land surface forward and inverse models that were developed for the AMSR-E and WindSat radiometers, to construct dynamic land surface emissivity datasets for use in physically-based precipitation retrievals over land. TRMM’s long life provides ample data to examine the surface properties under a wide range of environmental conditions, seasons, rain events, etc., and provides the means to examine the

  11. Land Cover / Climate Interaction at Global and Regional Scales

    NASA Astrophysics Data System (ADS)

    Xue, Y.

    2014-12-01

    Land cover and climate interact at regional and global scales through biophysical, biogeochemical, and ecological processes. Land cover change (LCC) affects regional climate through impacts on surface albedo and surface net radiation, on the partitioning of available energy between sensible and latent heat fluxes, on the atmospheric heating, moisture flux convergence and circulation, and the partitioning of rainfall between evaporation and runoff. Meanwhile, the climate variability and change also affect the LCC. Based on historical anthropogenic land cover change data from 1948-2005, numerical experiments that were designed to test its impact using general circulation models indicate that the LCC enhances the global warming in past half century. This is because after land degradation, reduction of evaporation is dominant, leading to surface warming. The reduction of net radiation due to high surface albedo plays a secondary role. Meanwhile, its impact on the regional monsoon is significant. The produced monsoon rainfall anomaly is not only limited within the land degradation area but extend to much large area through its interaction with the atmospheric circulations. The warming climate and climate variability also affect the vegetation distribution. For instance, with a coupled biophysical and dynamic vegetation model forced by the observed meteorological data, the North America leaf area index (LAI) shows an increasing trend after the 1970s in responding to warming. Meanwhile, the effects of the severe drought during 1987-1992 and the last decade in the southwestern U.S. on vegetation are also evident from the simulated and satellite-derived LAIs. The land covers in some parts of North America also show substantial changes. Evaluations of these simulations using satellite data are crucial. The critical issues in applying satellite data for LCC studies are also discussed.

  12. Modeling of global surface air temperature

    NASA Astrophysics Data System (ADS)

    Gusakova, M. A.; Karlin, L. N.

    2012-04-01

    A model to assess a number of factors, such as total solar irradiance, albedo, greenhouse gases and water vapor, affecting climate change has been developed on the basis of Earth's radiation balance principle. To develop the model solar energy transformation in the atmosphere was investigated. It's a common knowledge, that part of the incoming radiation is reflected into space from the atmosphere, land and water surfaces, and another part is absorbed by the Earth's surface. Some part of outdoing terrestrial radiation is retained in the atmosphere by greenhouse gases (carbon dioxide, methane, nitrous oxide) and water vapor. Making use of the regression analysis a correlation between concentration of greenhouse gases, water vapor and global surface air temperature was obtained which, it is turn, made it possible to develop the proposed model. The model showed that even smallest fluctuations of total solar irradiance intensify both positive and negative feedback which give rise to considerable changes in global surface air temperature. The model was used both to reconstruct the global surface air temperature for the 1981-2005 period and to predict global surface air temperature until 2030. The reconstructions of global surface air temperature for 1981-2005 showed the models validity. The model makes it possible to assess contribution of the factors listed above in climate change.

  13. Global Land Ice Measurements from Space

    NASA Technical Reports Server (NTRS)

    Scharfen, Gregory R.; Troisi, Vincent J.; Barry, Roger G.

    2004-01-01

    The NSIDC at the University of Colorado has successfully completed the tasks outlined in its proposal 0999.08.1216B, the 'Global Land Ice Measurements from Space' grant funded by NASA under NAG5-9722. The Global Land Ice Measurements from Space (GLIMS) grant reported on here is one of the first completed elements of the overall GLIMS project that continues with separate funding from NASA, the United States Geological Survey (USGS), and internationally by many national agencies and universities. The primary goals of GLIMS are to survey significant numbers of the world's 160,000 glaciers with data collected by the ASTER (Advanced Spaceborne Thermal Emission and reflection Radiometer) instrument aboard the EOS Terra spacecraft, and Landsat ETM+ (Enhanced Thematic Mapper Plus) and to make these data available to users in a common and easily usable format. GLIMS participants include: NSIDC as developer of the GLIMS database, USGS Flagstaff as the GLIMS Coordination Center, USGS EROS Data Center (EDC) as the archive for satellite imagery used in GLIMS analyses (NASA funding for GLIMS also includes the Flagstaff group and EDC through the related ASTER Science Team and Land Processes Distributed Active Archive Center [LP DAAC] activities), and approximately twenty two Regional Centers (RCs). RCs are funded by the national agencies of participating countries to analyze satellite imagery for a specified set of glaciological parameters and provide the results to NSIDC for archive and distribution to the public.

  14. A global dataset of crowdsourced land cover and land use reference data.

    PubMed

    Fritz, Steffen; See, Linda; Perger, Christoph; McCallum, Ian; Schill, Christian; Schepaschenko, Dmitry; Duerauer, Martina; Karner, Mathias; Dresel, Christopher; Laso-Bayas, Juan-Carlos; Lesiv, Myroslava; Moorthy, Inian; Salk, Carl F; Danylo, Olha; Sturn, Tobias; Albrecht, Franziska; You, Liangzhi; Kraxner, Florian; Obersteiner, Michael

    2017-06-13

    Global land cover is an essential climate variable and a key biophysical driver for earth system models. While remote sensing technology, particularly satellites, have played a key role in providing land cover datasets, large discrepancies have been noted among the available products. Global land use is typically more difficult to map and in many cases cannot be remotely sensed. In-situ or ground-based data and high resolution imagery are thus an important requirement for producing accurate land cover and land use datasets and this is precisely what is lacking. Here we describe the global land cover and land use reference data derived from the Geo-Wiki crowdsourcing platform via four campaigns. These global datasets provide information on human impact, land cover disagreement, wilderness and land cover and land use. Hence, they are relevant for the scientific community that requires reference data for global satellite-derived products, as well as those interested in monitoring global terrestrial ecosystems in general.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  16. Global cloud climatology from surface observations

    SciTech Connect

    Warren, S.

    1995-09-01

    Surface weather observations from stations on land and ships in the ocean are used to obtain the global distribution, at 5{sup o}x5{sup o} latitude-longitude resolution, of total cloud cover and the average amounts of the different cloud types: cumulus, cumulonimbus, stratus, stratocumulus, nimbostratus, altostratus, altocumulus, cirrus, cirrostratus, cirrocumulus, and fog. Diurnal and seasonal variations are derived, as well as interannual variations and multi-year trends. 3 refs., 3 figs.

  17. Understanding the global land-use marketplace

    NASA Astrophysics Data System (ADS)

    Belward, Alan

    2013-04-01

    Over 7 billion humans inhabit Earth and our population increases by more than a hundred per minute. Satisfying the resource demands of seven-plus billion people whilst sustaining the Earth System is a delicate balancing act. We need to balance resource use with regenerative capacity and this balance must avoid tipping points beyond which return and recovery are impossible. Tipping points in the physical, biogeochemical and ecological components of the Earth System have all been proposed - adding the global land-use marketplace to such a list may not be obvious but it undeniably deserves attention. The land is where most humans live most of the time. It meets most food, fuel, freshwater and fibre requirements and shapes Earth's climate. As land is essentially a finite resource this leads to intense competition. Monetizing land resources is nothing new. Choice of agricultural practice has long been governed in part by economics. But in recent years monetization has extended to include new dimensions such as carbon trading and biodiversity offsetting. Our land-use marketplace now has to optimise food, fibre and fuel production whilst maintaining and enhancing land's role as a carbon sink, a hydrologic reservoir and a support for biological diversity. International (and national) environmental policies aim to find a balance between such competing uses. These policies call for accurate, accountable and timely evidence concerning how, when and where land resources are changing. In 2013 the European Space Agency will launch the first of the Copernicus programme's Earth Observing Sentinel satellites. These technologically advanced systems are matched to data acquisition and processing strategies that should provide scientific evidence concerning the land on an unprecedented scale. This paper provides one vision of how Earth science will benefit from the Sentinels and their associated services and how this science will subsequently inform and shape policies, especially

  18. Towards monitoring land-cover and land-use changes at a global scale: the global land survey 2005

    USGS Publications Warehouse

    Gutman, G.; Byrnes, Raymond A.; Masek, J.; Covington, S.; Justice, C.; Franks, S.; Headley, Rachel

    2008-01-01

    Land cover is a critical component of the Earth system, infl uencing land-atmosphere interactions, greenhouse gas fl uxes, ecosystem health, and availability of food, fi ber, and energy for human populations. The recent Integrated Global Observations of Land (IGOL) report calls for the generation of maps documenting global land cover at resolutions between 10m and 30m at least every fi ve years (Townshend et al., in press). Moreover, despite 35 years of Landsat observations, there has not been a unifi ed global analysis of land-cover trends nor has there been a global assessment of land-cover change at Landsat-like resolution. Since the 1990s, the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) have supported development of data sets based on global Landsat observations (Tucker et al., 2004). These land survey data sets, usually referred to as GeoCover ™, provide global, orthorectifi ed, typically cloud-free Landsat imagery centered on the years 1975, 1990, and 2000, with a preference for leaf-on conditions. Collectively, these data sets provided a consistent set of observations to assess land-cover changes at a decadal scale. These data are freely available via the Internet from the USGS Center for Earth Resources Observation and Science (EROS) (see http://earthexplorer.usgs.gov or http://glovis.usgs.gov). This has resulted in unprecedented downloads of data, which are widely used in scientifi c studies of land-cover change (e.g., Boone et al., 2007; Harris et al., 2005; Hilbert, 2006; Huang et al. 2007; Jantz et al., 2005, Kim et al., 2007; Leimgruber, 2005; Masek et al., 2006). NASA and USGS are continuing to support land-cover change research through the development of GLS2005 - an additional global Landsat assessment circa 20051 . Going beyond the earlier initiatives, this data set will establish a baseline for monitoring changes on a 5-year interval and will pave the way toward continuous global land

  19. Towards monitoring land-cover and land-use changes at a global scale: the global land survey 2005

    USGS Publications Warehouse

    Gutman, G.; Byrnes, Raymond A.; Masek, J.; Covington, S.; Justice, C.; Franks, S.; Headley, Rachel

    2008-01-01

    Land cover is a critical component of the Earth system, infl uencing land-atmosphere interactions, greenhouse gas fl uxes, ecosystem health, and availability of food, fi ber, and energy for human populations. The recent Integrated Global Observations of Land (IGOL) report calls for the generation of maps documenting global land cover at resolutions between 10m and 30m at least every fi ve years (Townshend et al., in press). Moreover, despite 35 years of Landsat observations, there has not been a unifi ed global analysis of land-cover trends nor has there been a global assessment of land-cover change at Landsat-like resolution. Since the 1990s, the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) have supported development of data sets based on global Landsat observations (Tucker et al., 2004). These land survey data sets, usually referred to as GeoCover ™, provide global, orthorectifi ed, typically cloud-free Landsat imagery centered on the years 1975, 1990, and 2000, with a preference for leaf-on conditions. Collectively, these data sets provided a consistent set of observations to assess land-cover changes at a decadal scale. These data are freely available via the Internet from the USGS Center for Earth Resources Observation and Science (EROS) (see http://earthexplorer.usgs.gov or http://glovis.usgs.gov). This has resulted in unprecedented downloads of data, which are widely used in scientifi c studies of land-cover change (e.g., Boone et al., 2007; Harris et al., 2005; Hilbert, 2006; Huang et al. 2007; Jantz et al., 2005, Kim et al., 2007; Leimgruber, 2005; Masek et al., 2006). NASA and USGS are continuing to support land-cover change research through the development of GLS2005 - an additional global Landsat assessment circa 20051 . Going beyond the earlier initiatives, this data set will establish a baseline for monitoring changes on a 5-year interval and will pave the way toward continuous global land

  20. New land surface digital elevation model covers the Earth

    USGS Publications Warehouse

    Gesch, Dean B.; Verdin, Kristine L.; Greenlee, Susan K.

    1999-01-01

    Land surface elevation around the world is reaching new heights—as far as its description and measurement goes. A new global digital elevation model (DEM) is being cited as a significant improvement in the quality of topographic data available for Earth science studies.Land surface elevation is one of the Earth's most fundamental geophysical properties, but the accuracy and detail with which it has been measured and described globally have been insufficient for many large-area studies. The new model, developed at the U.S. Geological Survey's (USGS) EROS Data Center (EDC), has changed all that.

  1. Towards Monitoring Satellite Land Surface Temperature Production

    NASA Astrophysics Data System (ADS)

    Yu, P.; Yu, Y.; Liu, Y.; Wang, Z.; Zhang, X.

    2014-12-01

    Land surface temperature (LST) is of fundamental importance to the net radiation budget at the Earth surface and to monitoring the state of crops and vegetation, as well as an important indicator of both the greenhouse effect and the energy flux between the atmosphere and the land. Since its launch on October 28, 2011, the Suomi National Polar-orbiting Partnership (S-NPP) satellite has been continuously providing data for LST production; intensive validation and calibration of the LST data have been conducted since then. To better monitor the performance of the S-NPP LST product and evaluate different retrieval algorithms for potential improvement, a near-real-time monitoring system has been developed and implemented. The system serves as a tool for both the routine monitoring and the deep-dive researches. It currently consists of two major components: the global cross-satellite LST comparisons between S-NPP/VIIRS and MODIS/AQUA, and the LST validation with respect to in-situ observations from SURFRAD network. Results about cross-satellite comparisons, satellite-in situ LST validation, and evaluation of different retrieval algorithms are routinely generated and published through an FTP server of the system ftp. The results indicate that LST from the S-NPP is comparable to that from MODIS. A few case studies using this tool will be analyzed and presented.

  2. Analysis of Anomaly in Land Surface Temperature Using MODIS Products

    NASA Astrophysics Data System (ADS)

    Yorozu, K.; Kodama, T.; Kim, S.; Tachikawa, Y.; Shiiba, M.

    2011-12-01

    Atmosphere-land surface interaction plays a dominant role on the hydrologic cycle. Atmospheric phenomena cause variation of land surface state and land surface state can affect on atmosphereic conditions. Widely-known article related in atmospheric-land interaction was published by Koster et al. in 2004. The context of this article is that seasonal anomaly in soil moisture or soil surface temperature can affect summer precipitation generation and other atmospheric processes especially in middle North America, Sahel and south Asia. From not only above example but other previous research works, it is assumed that anomaly of surface state has a key factor. To investigate atmospheric-land surface interaction, it is necessary to analyze anomaly field in land surface state. In this study, soil surface temperature should be focused because it can be globally and continuously observed by satellite launched sensor. To land surface temperature product, MOD11C1 and MYD11C1 products which are kinds of MODIS products are applied. Both of them have 0.05 degree spatial resolution and daily temporal resolution. The difference of them is launched satellite, MOD11C1 is Terra and MYD11C1 is Aqua. MOD11C1 covers the latter of 2000 to present and MYD11C1 covers the early 2002 to present. There are unrealistic values on provided products even if daily product was already calibrated or corrected. For pre-analyzing, daily data is aggregated into 8-days data to remove irregular values for stable analysis. It was found that there are spatial and temporal distribution of 10-years average and standard deviation for each 8-days term. In order to point out extreme anomaly in land surface temperature, standard score for each 8-days term is applied. From the analysis of standard score, it is found there are large anomaly in land surface temperature around north China plain in early April 2005 and around Bangladesh in early May 2009.

  3. Development of High Resolution Land Surface Parameters for the Community Land Model

    SciTech Connect

    Ke, Yinghai; Leung, Lai-Yung R.; Huang, Maoyi; Coleman, Andre M.; Li, Hongyi; Wigmosta, Mark S.

    2012-11-06

    There is a growing need for high-resolution land surface parameters as land surface models are being applied at increasingly higher spatial resolution offline as well as in regional and global models. The default land surface parameters for the most recent version of the Community Land Model (i.e. CLM 4.0) are at 0.5° or coarser resolutions, released with the Community Earth System Model (CESM). Plant Functional Types (PFTs), vegetation properties such as Leaf Area Index (LAI), Stem Area Index (SAI), and non-vegetated land covers were developed using remotely sensed datasets retrieved in late 1990’s and the beginning of this century. In this study, we developed new land surface parameters for CLM 4.0, specifically PFTs, LAI, SAI and non-vegetated land cover composition, at 0.05° resolution globally based on the most recent MODIS land cover and improved MODIS LAI products. Compared to the current CLM 4.0 parameters, the new parameters produced a decreased coverage by bare soil and trees, but an increased coverage by shrub, grass, and cropland. The new parameters result in a decrease in global seasonal LAI, with the biggest decrease in boreal forests; however, the new parameters also show a large increase in LAI in tropical forest. Differences between the new and the current parameters are mainly caused by changes in the sources of remotely sensed data and the representation of land cover in the source data. Advantages and disadvantages of each dataset were discussed in order to provide guidance on the use of the data. The new high-resolution land surface parameters have been used in a coupled land-atmosphere model (WRF-CLM) applied to the western U.S. to demonstrate their use in high-resolution modeling. A remapping method from the latitude/longitude grid of the CLM data to the WRF grids with map projection was also demonstrated. Future work will include global offline CLM simulations to examine the impacts of source data resolution and subsequent land parameter

  4. Land surface hydrology in the cloud land surface interaction campaign (CLASIC)

    USDA-ARS?s Scientific Manuscript database

    A fundamental objective of the Cloud Land Surface Interaction Campaign (CLASIC) was to contribute to our understanding of the interactions between the atmosphere and the land surface. It has been observed that land surface characteristics influence the timing and evolution of cumulus convection. The...

  5. Correcting for Atmospheric Spatial Variability When Estimating Surface Fluxes from Remotely Sensed Land Surface Data

    USDA-ARS?s Scientific Manuscript database

    Efforts to monitor the terrestrial water cycle require accurate estimates of evapotranspiration over the global land area. Flux towers provide valuable site-level data, but their collective footprints cover only a very small fraction of the land surface. Satellite remote sensing instruments, on th...

  6. Documenting Biophysical Activities on Land Surfaces

    NASA Astrophysics Data System (ADS)

    Gobron, N.; Pinty, B.; Melin, F.; Taberner, M.; Verstraete, M. M.; Widlowski, J.

    2002-12-01

    The biophysical activities on land surfaces have been documented from spectral measurements made in space for decades. These estimates often were derived from the Normalized Difference Vegetation Index, which is simple to compute but very sensitive to perturbations and prone to yield misleading or erroneous results. Advances in the understanding of radiation transfer and availability of higher performance instruments have lead to the development of a new generation of geophysical products poised to provide reliable, accurate information on the state and evolution of terrestrial environments. Specifically, a series of optimized algorithms have been developed to estimate the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) for various instruments. Such an approach allows the synergistic use of FAPAR products derived from different sensors and the construction of global FAPAR time series independent from the life time of these specific sensors. The outline of the methodology will be summarized and the results from an application conducted with SeaWiFS data will be presented.

  7. Improving distributed hydrologic modeling and global land cover data

    NASA Astrophysics Data System (ADS)

    Broxton, Patrick

    Distributed models of the land surface are essential for global climate models because of the importance of land-atmosphere exchanges of water, energy, momentum. They are also used for high resolution hydrologic simulation because of the need to capture non-linear responses to spatially variable inputs. Continued improvements to these models, and the data which they use, is especially important given ongoing changes in climate and land cover. In hydrologic models, important aspects are sometimes neglected due to the need to simplify the models for operational simulation. For example, operational flash flood models do not consider the role of snow and are often lumped (i.e. do not discretize a watershed into multiple units, and so do not fully consider the effect of intense, localized rainstorms). To address this deficiency, an overland flow model is coupled with a subsurface flow model to create a distributed flash flood forecasting system that can simulate flash floods that involve rain on snow. The model is intended for operational use, and there are extensive algorithms to incorporate high-resolution hydrometeorologic data, to assist in the calibration of the models, and to run the model in real time. A second study, which is designed to improve snow simulation in forested environments, demonstrates the importance of explicitly representing a near canopy environment in snow models, instead of only representing open and canopy covered areas (i.e. with % canopy fraction), as is often done. Our modeling, which uses canopy structure information from Aerial Laser Survey Mapping at 1 meter resolution, suggests that areas near trees have more net snow water input than surrounding areas because of the lack of snow interception, shading by the trees, and the effects of wind. In addition, the greatest discrepancy between our model simulations that explicitly represent forest structure and those that do not occur in areas with more canopy edges. In addition, two value

  8. Global land cover mapping using Earth observation satellite data: Recent progresses and challenges

    NASA Astrophysics Data System (ADS)

    Ban, Yifang; Gong, Peng; Giri, Chandra

    2015-05-01

    Land cover is an important variable for many studies involving the Earth surface, such as climate, food security, hydrology, soil erosion, atmospheric quality, conservation biology, and plant functioning. Land cover not only changes with human caused land use changes, but also changes with nature. Therefore, the state of land cover is highly dynamic. In winter snow shields underneath various other land cover types in higher latitudes. Floods may persist for a long period in a year over low land areas in the tropical and subtropical regions. Forest maybe burnt or clear cut in a few days and changes to bare land. Within several months, the coverage of crops may vary from bare land to nearly 100% crops and then back to bare land following harvest. The highly dynamic nature of land cover creates a challenge in mapping and monitoring which remains to be adequately addressed. As economic globalization continues to intensify, there is an increasing trend of land cover/land use change, environmental pollution, land degradation, biodiversity loss at the global scale, timely and reliable information on global land cover and its changes is urgently needed to mitigate the negative impact of global environment change.

  9. The global land and ocean mean energy balance

    NASA Astrophysics Data System (ADS)

    Wild, Martin; Folini, Doris

    2016-04-01

    land, and 16 and 100 Wm-2 over oceans, for sensible and latent heat fluxes, respectively. Estimated uncertainties are on the order of 10 and 5 Wm-2 for most surface and TOA fluxes, respectively. Combining these surface budgets with satellite-determined TOA budgets (CERES-EBAF) results in an atmospheric solar absorption of 77 and 82 Wm-2 and a net atmospheric thermal emission of -165 and -190 Wm-2 over land and oceans, respectively. We further revisit the global mean energy balance by combining the area weighed land and ocean mean budgets. This study is published in: Wild, M., Folini, D., Hakuba, M., Schär, C., Seneviratne, S.I., Kato, S., Rutan, D., Ammann, C., Wood, E.F., and König-Langlo, G., 2015: The energy balance over land and oceans: An assessment based on direct observations and CMIP5 climate models. Clim. Dyn., Dyn., 44, 3393-3429, doi: 10.1007/s00382-014-2430-z.

  10. 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.

  11. Global land use data for integrated assessment modeling

    SciTech Connect

    Ramankutty, Navin

    2005-12-12

    Changes in land use and land cover have been one of the major drivers of global change over the last three centuries. Detailed spatially-explicit data sets characterizing these historical land cover changes are now emerging. By synthesizing remotely-sensed land cover classification data sets with historical land use census data, our research group has developed comprehensive databases of historical land use and land cover change. Moreover, we are building estimates of the land suitability for agriculture to predict the constraints on future land use. In this project, we have interacted with the Global Trade and Analysis Project (GTAP) at Purdue University, to adapt our land use data for use with the GTAP database, a baseline database widely used by the integrated assessment modeling community. Moreover, we have developed an interactive website for providing these newly emerging land use data products for the integrated assessment (IA) community and to the climate modeling community.

  12. Conceptual Problems in Land Surface Data Assimilation

    NASA Technical Reports Server (NTRS)

    Reichle, Rolf

    2012-01-01

    A land data assimilation system (LDAS) merges observations (or satellite 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, several conceptual problems can interfere with realizing the potential improvements from data assimilation. Of particular concern is the frequent mismatch between the assimilated observations and the land surface model variables of interest. The seminar will discuss recent research with the ensemble-based NASA GEOS-S LDAS to address various aspects of this mismatch. These aspects include (i) the assimilation of coarse-scale observations into higher-resolution land surface models, (ii) the partitioning of satellite observations (such as TWS retrievals) into their constituent water cycle components, (iii) the forward modeling of microwave brightness temperatures over land for radiance-based land surface data aSSimilation, and (iv) the selection of the most relevant types of observations for the analysis of a specific water cycle variable (such as root zone soil moisture). At its core, the solution to the above 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.

  13. Historical Landsat data comparisons: illustrations of land surface change

    USGS Publications Warehouse

    Cross, Matthew D.

    1990-01-01

    This booklet provides an overview of the Landsat program and shows the application of the data to monitor changes occurring on the surface of the Earth. To show changes that have taken place within the last 20 years or less, image pairs were constructed from the Landsat multispectral scanner (MSS) and thematic mapper (TM) sensors. Landsat MSS data provide a historical global record of the land surface from the early 1970's to present. Landsat TM data provide land surface information from the early 1980's to present.

  14. Joint variability of global runoff and global sea surface temperatures

    USGS Publications Warehouse

    McCabe, G.J.; Wolock, D.M.

    2008-01-01

    Global land surface runoff and sea surface temperatures (SST) are analyzed to identify the primary modes of variability of these hydroclimatic data for the period 1905-2002. A monthly water-balance model first is used with global monthly temperature and precipitation data to compute time series of annual gridded runoff for the analysis period. The annual runoff time series data are combined with gridded annual sea surface temperature data, and the combined dataset is subjected to a principal components analysis (PCA) to identify the primary modes of variability. The first three components from the PCA explain 29% of the total variability in the combined runoff/SST dataset. The first component explains 15% of the total variance and primarily represents long-term trends in the data. The long-term trends in SSTs are evident as warming in all of the oceans. The associated long-term trends in runoff suggest increasing flows for parts of North America, South America, Eurasia, and Australia; decreasing runoff is most notable in western Africa. The second principal component explains 9% of the total variance and reflects variability of the El Ni??o-Southern Oscillation (ENSO) and its associated influence on global annual runoff patterns. The third component explains 5% of the total variance and indicates a response of global annual runoff to variability in North Aflantic SSTs. The association between runoff and North Atlantic SSTs may explain an apparent steplike change in runoff that occurred around 1970 for a number of continental regions.

  15. Land-surface influences on weather and climate

    NASA Technical Reports Server (NTRS)

    Baer, F.; Mintz, Y.

    1984-01-01

    Land-surface influences on weather and climate are reviewed. The interrelationship of vegetation, evapotranspiration, atmospheric circulation, and climate is discussed. Global precipitation, soil moisture, the seasonal water cycle, heat transfer, and atmospheric temperature are among the parameters considered in the context of a general biosphere model.

  16. Applications of Land Surface Temperature from Microwave Observations

    USDA-ARS?s Scientific Manuscript database

    Land surface temperature (LST) is a key input for physically-based retrieval algorithms of hydrological states and fluxes. Yet, it remains a poorly constrained parameter for global scale studies. The main two observational methods to remotely measure T are based on thermal infrared (TIR) observation...

  17. Exploration of scaling effects on coarse resolution land surface phenology

    USDA-ARS?s Scientific Manuscript database

    A great number of land surface phenoloy (LSP) data have been produced from various coarse resolution satellite datasets and detection algorithms across regional and global scales. Unlike field- measured phenological events which are quantitatively defined with clear biophysical meaning, current LSP ...

  18. The Potential Radiative Forcing of Global Land Use and Land Cover Change Activities

    NASA Astrophysics Data System (ADS)

    Ward, D. S.; Mahowald, N. M.; Kloster, S.

    2014-12-01

    Given the expected increase in pressure on land resources over the next century, there is a need to understand the total impacts of activities associated with land use and land cover change (LULCC). Here we quantify these impacts using the radiative forcing metric, including forcings from changes in long-lived greenhouse gases, tropospheric ozone, aerosol effects, and land surface albedo. We estimate radiative forcings from the different agents for historical LULCC and for six future projections using simulations from the National Center for Atmospheric Research Community Land Model and Community Atmosphere Models and additional offline analyses. When all forcing agents are considered together we show that 45% (+30%, -20%) of the present-day (2010) anthropogenic radiative forcing can be attributed to LULCC. Changes in the emission of non-CO2 greenhouse gases and aerosols from LULCC enhance the total LULCC radiative forcing by a factor of 2 to 3 with respect to the forcing from CO2 alone. In contrast, the non-CO2 forcings from fossil fuel burning are roughly neutral, due largely to the negative (cooling) impact of aerosols from these sources. We partition the global LULCC radiative forcing into three major sources: direct modification of land cover (e.g. deforestation), agricultural activities, and fire regime changes. Contributions from deforestation and agriculture are roughly equal in the present day, while changes to wildfire activity impose a small negative forcing globally. In 2100, deforestation activities comprise the majority of the LULCC radiative forcing for all projections except one (Representative Concentration Pathway (RCP) 4.5). This suggests that realistic scenarios of future forest area change are essential for projecting the contribution of LULCC to climate change. However, the commonly used RCP land cover change projections all include decreases in global deforestation rates over the next 85 years. To place an upper bound on the potential

  19. Cross comparisons of land surface process descriptions in land surface models using multiple sources of data

    NASA Astrophysics Data System (ADS)

    Park, Gi Hyeon

    2006-12-01

    Land surface-atmospheric interactions influence climate and weather varying spatial scales from local to mesoscale, and even to global. This dissertation deals with several topics: (1) evaluation of various sources of incoming solar radiations, (2) evaluation of land surface process descriptions in the land surface models in both basin-scale and point scale offline model simulations, and (3) inverse estimation of radiation components using net radiation and other meteorological variables. Incoming solar radiations from various sources were evaluated. This study identified the two sources of errors in the North American Data Assimilation system (NLDAS) solar radiation: One is related to bias inherited from the ETA Data Assimilation System (EDAS) during 2001 and 2003, and the other is software error at NESDIS operational system during 2002. Land surface processes are treated quite differently in the land surface models used in this study. Over the state of Oklahoma, Common Land Model 2.1 (CLM2.1) estimates more evaporation but less transpiration than the Variable Infiltration Capacity (VIC3L) model. This is due to the difference in the runoff algorithm, which results in more infiltration down to the soil layer and then providing more available water to plant roots in VIC3L. CLM2.1 overestimates ground heat flux in Point scale simulation. CoLM, which employs two stream radiative transfer scheme, shows better agreements to adjusted ground observations (using Bowen-ration closure method) in offline simulations than CLM2.1. CoLM, in addition, shows various model behaviors depending on vegetation cover types. Inverse radiation estimation methods were developed and evaluated at four AmeriFlux sites. Analysis of observed radiations showed a triangle shape relationship among net radiation, net solar radiation and cloud factor (defined in this study). Clear-sky downward longwave radiation is needed to be calibrated for each site. SCE-UA method was used to calibrate an

  20. Do Increasingly Globalized Land Systems Promote or Undermine Sustainability?

    NASA Astrophysics Data System (ADS)

    Munroe, D. K.

    2015-12-01

    Scholars are now studying land systems in a global context using such concepts as "telecoupling." Research to date has recognized that local land systems may be undermined by globalization, and local people displaced. The land change community emphasizes the ways in which local people make decisions about natural resources given the opportunities and constraints that globalization presents. This talk will present a summary of current land systems science research in agribusiness, global trade and financial institutions, highlighting key ways in which sustainability measures can capture the effects of these actors and activities.

  1. Global characterization of surface soil moisture drydowns

    NASA Astrophysics Data System (ADS)

    McColl, Kaighin A.; Wang, Wei; Peng, Bin; Akbar, Ruzbeh; Short Gianotti, Daniel J.; Lu, Hui; Pan, Ming; Entekhabi, Dara

    2017-04-01

    Loss terms in the land water budget (including drainage, runoff, and evapotranspiration) are encoded in the shape of soil moisture "drydowns": the soil moisture time series directly following a precipitation event, during which the infiltration input is zero. The rate at which drydowns occur—here characterized by the exponential decay time scale τ—is directly related to the shape of the loss function and is a key characteristic of global weather and climate models. In this study, we use 1 year of surface soil moisture observations from NASA's Soil Moisture Active Passive mission to characterize τ globally. Consistent with physical reasoning, the observations show that τ is lower in regions with sandier soils, and in regions that are more arid. To our knowledge, these are the first global estimates of τ—based on observations alone—at scales relevant to weather and climate models.

  2. Land-surface processes and monsoon climate system

    NASA Astrophysics Data System (ADS)

    Xue, Yongkang; De Sales, Fernando; Lau, William; Boone, Arron; Mechoso, Carlos

    2015-04-01

    Yongkang Xue, F. De Sales, B. Lau, A. Boone, C. R. Mechoso Differential thermal heating of land and ocean and heat release into the atmosphere are important factors that determine the onset, strength, duration and spatial distribution of large-scale monsoons. A global and seasonal assessment of land surface process (LSP) effects on the monsoon system has been made based on general circulation models (GCM) coupled to different benchmark land models, which physically represent either comprehensive, or partial, or minimal LSP representations. Observed precipitation is applied as constrain and differences in simulation error are used to assess the effect of the LSP with different complexity. The AGCM results indicate that the land/atmosphere interaction has substantial impact on global water cycle, while the monsoon regions have had strongest impact at intraseasonal to decadal scales. Among monsoon regions, West Africa, South Asia, East Asia, and Amazon regions have largest impact while some monsoon regions have less impact due to strong air/sea interactions and narrow land mass there. LSP reduces the annual precipitation error by 58% over global monsoon regions, about 35% observed precipitation. The partial LSP effect (excluding soil moisture and vegetation albedo) reduces annual precipitation error over monsoon region that equals to about 13% of observed precipitation. The LSP affects the monsoon evolution through different mechanisms at different scales. It affects the surface energy balance and energy partitioning in latent and sensible heat, the atmospheric heating rate, and general circulation. The LSP effects have also been assessed in the land use land cover change experiment. Based on recently compiled global land-use data from 1948-2005, the GCM simulation results indicate the degradation in Mexico, West Africa, south and East Asia and South America produce substantial precipitation anomalies, some of which are consistent with observed regional precipitation

  3. Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data

    USGS Publications Warehouse

    Loveland, T.R.; Reed, B.C.; Brown, J.F.; Ohlen, D.O.; Zhu, Z.; Yang, L.; Merchant, J.W.

    2000-01-01

    Researchers from the U.S. Geological Survey, University of Nebraska-Lincoln and the European Commission's Joint Research Centre, Ispra, Italy produced a 1 km resolution global land cover characteristics database for use in a wide range of continental-to global-scale environmental studies. This database provides a unique view of the broad patterns of the biogeographical and ecoclimatic diversity of the global land surface, and presents a detailed interpretation of the extent of human development. The project was carried out as an International Geosphere-Biosphere Programme, Data and Information Systems (IGBP-DIS) initiative. The IGBP DISCover global land cover product is an integral component of the global land cover database. DISCover includes 17 general land cover classes defined to meet the needs of IGBP core science projects. A formal accuracy assessment of the DISCover data layer will be completed in 1998. The 1 km global land cover database was developed through a continent-by-continent unsupervised classification of 1 km monthly Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) composites covering 1992-1993. Extensive post-classification stratification was necessary to resolve spectral/temporal confusion between disparate land cover types. The complete global database consists of 961 seasonal land cover regions that capture patterns of land cover, seasonality and relative primary productivity. The seasonal land cover regions were aggregated to produce seven separate land cover data sets used for global environmental modelling and assessment. The data sets include IGBP DISCover, U.S. Geological Survey Anderson System, Simple Biosphere Model, Simple Biosphere Model 2, Biosphere-Atmosphere Transfer Scheme, Olson Ecosystems and Running Global Remote Sensing Land Cover. The database also includes all digital sources that were used in the classification. The complete database can be sourced from the website: http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html.

  4. Reforestation of surface mines on lands of VICC Land Company

    Treesearch

    Thomas F. Evans

    1980-01-01

    This Virginia coal company's surface mined lands show an adequate stocking of tree seedlings in terms of number per acre, but the distribution of seedlings has been affected by past reclamation practices. Natural reseeding has been an important contributor to the present seedling stock.

  5. The COSMO-CLM 4.8 regional climate model coupled to regional ocean, land surface and global earth system models using OASIS3-MCT: description and performance

    NASA Astrophysics Data System (ADS)

    Will, Andreas; Akhtar, Naveed; Brauch, Jennifer; Breil, Marcus; Davin, Edouard; Ho-Hagemann, Ha T. M.; Maisonnave, Eric; Thürkow, Markus; Weiher, Stefan

    2017-04-01

    We developed a coupled regional climate system model based on the CCLM regional climate model. Within this model system, using OASIS3-MCT as a coupler, CCLM can be coupled to two land surface models (the Community Land Model (CLM) and VEG3D), the NEMO-MED12 regional ocean model for the Mediterranean Sea, two ocean models for the North and Baltic seas (NEMO-NORDIC and TRIMNP+CICE) and the MPI-ESM Earth system model.We first present the different model components and the unified OASIS3-MCT interface which handles all couplings in a consistent way, minimising the model source code modifications and defining the physical and numerical aspects of the couplings. We also address specific coupling issues like the handling of different domains, multiple usage of the MCT library and exchange of 3-D fields.We analyse and compare the computational performance of the different couplings based on real-case simulations over Europe. The usage of the LUCIA tool implemented in OASIS3-MCT enables the quantification of the contributions of the coupled components to the overall coupling cost. These individual contributions are (1) cost of the model(s) coupled, (2) direct cost of coupling including horizontal interpolation and communication between the components, (3) load imbalance, (4) cost of different usage of processors by CCLM in coupled and stand-alone mode and (5) residual cost including i.a. CCLM additional computations.Finally a procedure for finding an optimum processor configuration for each of the couplings was developed considering the time to solution, computing cost and parallel efficiency of the simulation. The optimum configurations are presented for sequential, concurrent and mixed (sequential+concurrent) coupling layouts. The procedure applied can be regarded as independent of the specific coupling layout and coupling details.We found that the direct cost of coupling, i.e. communications and horizontal interpolation, in OASIS3-MCT remains below 7 % of the CCLM stand

  6. Improving land surface emissivty parameter for land surface models using portable FTIR and remote sensing observation in Taklimakan Desert

    NASA Astrophysics Data System (ADS)

    Liu, Yongqiang; Mamtimin, Ali; He, Qing

    2014-05-01

    Because land surface emissivity (ɛ) has not been reliably measured, global climate model (GCM) land surface schemes conventionally set this parameter as simply assumption, for example, 1 as in the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) model, 0.96 for soil and wetland in the Global and Regional Assimilation and Prediction System (GRAPES) Common Land Model (CoLM). This is the so-called emissivity assumption. Accurate broadband emissivity data are needed as model inputs to better simulate the land surface climate. It is demonstrated in this paper that the assumption of the emissivity induces errors in modeling the surface energy budget over Taklimakan Desert where ɛ is far smaller than original value. One feasible solution to this problem is to apply the accurate broadband emissivity into land surface models. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has routinely measured spectral emissivities in six thermal infrared bands. The empirical regression equations have been developed in this study to convert these spectral emissivities to broadband emissivity required by land surface models. In order to calibrate the regression equations, using a portable Fourier Transform infrared (FTIR) spectrometer instrument, crossing Taklimakan Desert along with highway from north to south, to measure the accurate broadband emissivity. The observed emissivity data show broadband ɛ around 0.89-0.92. To examine the impact of improved ɛ to radiative energy redistribution, simulation studies were conducted using offline CoLM. The results illustrate that large impacts of surface ɛ occur over desert, with changes up in surface skin temperature, as well as evident changes in sensible heat fluxes. Keywords: Taklimakan Desert, surface broadband emissivity, Fourier Transform infrared spectrometer, MODIS, CoLM

  7. Global Impact of Land Use on Soil Carbon Storage

    NASA Astrophysics Data System (ADS)

    Sanderman, J.; Hengl, T.; Fiske, G. J.; Cheney, E.

    2016-12-01

    Land use and land cover change has resulted in substantial losses of carbon from soils globally. This historic loss in soil organic carbon now represents a significant climate mitigation opportunity. Current estimates of the potential soil organic carbon (SOC) sink strength generally come from simplistic bookkeeping calculations that have been disaggregated to at best the continental scale. Others have taken a modeling approach whereby agroecosystem models have been run using alternative management practices to estimate SOC sequestration potential. A third approach which is adopted here is to use a data-driven spatial modeling approach whereby measured SOC stocks from minimally distrubed regions are projected across the highly managed regions of the world. The International Soil Reference and Information Center (www.isric.org) curates the largest repository of spatially explicit soil data which now includes data from over 150,000 soil profiles globally. From this dataset, we have masked out data from profiles collected from used parts of the globe. Then SOC stocks were related to factors which are known to control SOC storage using machine learning algorithms. Spatially continuous data layers included climate, topography, lithology and potential vegetation class. The trained machine learning algorithms were then used to project potential SOC stocks across the entire global land surface at a resolution of 1 km. In addition to an assessment of model performance in the development stage, an independent test set of over 400 paired-plot (native v. agricultural) measurements of SOC stocks within major agricultural regions was collected to help validate model output. Land area with the largest carbon debit and thus the greatest potential of SOC storage was revealed by comparison of this potential SOC map with a map of actual SOC values (SoilGrids250m) that was produced using a consistent spatial modeling approach.

  8. Impacts on the Hydrological Cycle of Counteracting Global Warming with Albedo Changes over Oceans or Land

    NASA Astrophysics Data System (ADS)

    Bala, G.; Caldeira, K.; Nemani, R. R.; Cao, L.; Ban-Weiss, G. A.; Shin, H.

    2010-12-01

    Solar Radiation Management (SRM) "geoengineering" proposals to completely offset global mean temperature increases by reducing the amount of absorbed sunlight nearly uniformly over land and oceans (e.g. stratospheric injection of aerosols) are expected to slow the global water cycle and reduce runoff over land. However, proposed countering of global warming by increasing the albedo of marine clouds or painting the roof white would reduce surface solar radiation either over the oceans or land. Here, we analyze the response of temperature and the hydrological cycle to either increased reflection over the oceans or decreased reflection over land using an atmospheric general circulation model coupled to a mixed layer ocean model. When cloud droplets are reduced in size over all oceans uniformly to offset the temperature increase from a doubling of atmospheric CO2, the global-mean precipitation and evaporation decreases by about 1.3% but runoff over land increases by 7.5% primarily due to increases over tropical land. In the model, more reflective marine clouds cool the atmospheric column over ocean. The result is a sinking motion over oceans and upward motion over land. We attribute the increased runoff over land to this increased upward motion over land when marine clouds are made more reflective. Qualitatively similar results are obtained when reflection from land areas is reduced indicating that increased reflection from land surface could result in reduced precipitation and runoff over land. Our results suggest that offsetting mean global warming by reducing marine cloud droplet size will lead to wetter continents, and large scale increase in land surface albedo could lead to drying of the continents.

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

    USDA-ARS?s Scientific Manuscript database

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

  10. Effective UV surface albedo of seasonally snow-covered lands

    NASA Astrophysics Data System (ADS)

    Tanskanen, A.; Manninen, T.

    2007-05-01

    At ultraviolet wavelengths the albedo of most natural surfaces is small with the striking exception of snow and ice. Therefore, snow cover is a major challenge for various applications based on radiative transfer modelling. The aim of this work was to determine the characteristic effective UV range surface albedo of various land cover types when covered by snow. First we selected 1 by 1 degree sample regions that met three criteria: the sample region contained dominantly subpixels of only one land cover type according to the 8 km global land cover classification product from the University of Maryland; the average slope of the sample region was less than 2 degrees according to the USGS's HYDRO1K slope data; the sample region had snow cover in March according to the NSIDC Northern Hemisphere weekly snow cover data. Next we generated 1 by 1 degree gridded 360 nm surface albedo data from the Nimbus-7 TOMS Lambertian equivalent reflectivity data, and used them to construct characteristic effective surface albedo distributions for each land cover type. The resulting distributions showed that each land cover type experiences a characteristic range of surface albedo values when covered by snow. The result is explained by the vegetation that extends upward beyond the snow cover and masks the bright snow covered surface.

  11. Effective UV surface albedo of seasonally snow-covered lands

    NASA Astrophysics Data System (ADS)

    Tanskanen, A.; Manninen, T.

    2007-02-01

    At ultraviolet wavelengths the albedo of most natural surfaces is small with the striking exception of snow and ice. Therefore, snow cover is a major challenge for various applications based on radiative transfer modelling. The aim of this work was to determine the characteristic effective UV range surface albedo of various land cover types when covered by snow. First we selected 1 by 1 degree sample regions that met three criteria: the sample region contained dominantly subpixels of only one land cover type according to the 8 km global land cover classification product from the University of Maryland; the average slope of the sample region was less than 2 degrees according to the USGS's HYDRO1K slope data; the sample region had snow cover in March according to the NSIDC Northern Hemisphere weekly snow cover data. Next we generated 1 by 1 degree gridded 360 nm surface albedo data from the Nimbus-7 TOMS Lambertian equivalent reflectivity data, and used them to construct characteristic effective surface albedo distributions for each land cover type. The resulting distributions showed that each land cover type experiences a characteristic range of surface albedo values when covered by snow. The result is explained by the vegetation that extends upward beyond the snow cover and masks the bright snow covered surface.

  12. Observations of Land Surface Variability Using Passive Microwave Sensing

    NASA Technical Reports Server (NTRS)

    Njoku, Eni G.

    1999-01-01

    Understanding the global variability of land surface wetness (soil moisture), skin temperature, and related surface fluxes of heat and moisture is key to assessing the importance of the land surface in influencing climate. The feasibility of producing model estimates of these quantities is being studied as part of the International Satellite Land Surface Climatology Project (ISLSCP) Global Soil Wetness Project (GSWP). In the GSWP approach, meteorological observations and analyses are used to drive global circulation models. Satellite measurements can provide independent estimates of key land surface parameters that are needed for initializing and validating the climate models and for monitoring long-term change. Satellite observations of the land surface can also be assimilated into soil models to estimate moisture in the root zone. In our research, passive microwave satellite data recorded during 1978-1987 from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) are being used to examine spatial and temporal trends in surface soil moisture, vegetation, and temperature. These data include observations at C and X bands (6.6 and 10.7 GHz), which are not available on the current Special Sensor Microwave/Imager (SSM/I) and are precursors to data that will become available from the Advanced Microwave Scanning Radiometer (AMSR) on Advanced Earth Observing Satellite (ADEOS-II) and Earth Observing System (EOS) PM1 in the year 2000. A chart shows a time-series of SMMR-derived surface temperature, T-e and surface soil moisture M, retrieved on a 0.5 deg x 0.5 deg grid and further averaged over a 4 deg x 10 deg study region in the African Sahel. Also shown are National Center for Environmental Prediction (NCEP) model outputs of surface temperature, T-sfc, and soil wetness, Soil-w. The variables have been scaled to have similar dynamic ranges on the plots. The NCEP data from the NCEP Reanalysis Project are monthly averages on a 2.5 deg x 2.5 deg grid averaged over

  13. The Copernicus Global Land Service: present and future

    NASA Astrophysics Data System (ADS)

    Lacaze, Roselyne; Smets, Bruno; Trigo, Isabel; Calvet, Jean-Christophe; Jann, Alexander; Camacho, Fernando; Baret, Frédéric; Kidd, Richard; Defourny, Pierre; Tansey, Kevin; Pacholczyk, Philippe; Balsamo, Gianpaolo; Szintai, Balazs

    2013-04-01

    From 1st January 2013, the Copernicus Global Land Service is operational, providing continuously to European, African and International users a set of biophysical variables describing the vegetation conditions, the energy budget at the continental surface and the water cycle over the whole globe at one kilometer resolution. These generic products can serve numerous applications such as agriculture and food security monitoring, weather forecast, climate change impact studies, water, forest and natural resources management. The Copernicus Global Land Service is built on the achievements of the BioPar component of the FP7 geoland2 project. Essential Climate Variables like the Leaf Area Index (LAI), the Fraction of PAR absorbed by the vegetation (FAPAR), the surface albedo, the Land Surface Temperature, the soil moisture, the burnt areas, the areas of water bodies, and additional vegetation indices, are generated every hour, every day or every 10 days on a reliable and automatic basis from Earth Observation satellite data. Beside this timely production, the available historical archives have been processed, using the same innovative algorithms, to get consistent time series as long as possible. As an example, more than 30 years of LAI and FAPAR relying on NOAA/AVHRR sensors (from 1981 to 2000) and SPOT/VGT sensors (from 1999 to the present) are now available. All products are accessible, free of charge and after registration, at the following address: http://www.geoland2.eu/core-mapping-services/biopar.html. Documentation describing the physical methodologies, the technical properties of products, and the results of validation exercises can also be downloaded. In view of service continuity, research and development are performed on two parallel ways. On one hand, the existing retrieval methodologies will be adapted to new input data sets (e.g. Proba-V and Sentinel-3 at 1km resolution) that will be used in replacement of current sensor (SPOT/VGT) which reached the end

  14. Land-surface processes and monsoon climate system

    NASA Astrophysics Data System (ADS)

    Xue, Y.

    2014-12-01

    Differential thermal heating of land and ocean and heat release into the atmosphere are important factors that determine the onset, strength, duration and spatial distribution of large-scale monsoons. A global and seasonal assessment of land surface process (LSP) effects on the monsoon system has been made based on general circulation models (GCM) coupled to different benchmark land models, which physically represent either comprehensive, or partial, or minimal LSP representations. Observed precipitation is applied as constrain and differences in simulation error are used to assess the effect of the LSP with different complexity. The AGCM results indicate that the land/atmosphere interaction has substantial impact on global water cycle, while the monsoon regions have had strongest impact at intraseasonal to decadal scales. Among monsoon regions, West Africa, South Asia, East Asia, and Amazon regions have largest impact while some monsoon regions have less impact due to strong air/sea interactions and narrow land mass. LSP reduces the annual precipitation error by 58% over global monsoon regions, about 35% observed precipitation. The partial LSP effect (excluding soil moisture and vegetation albedo) reduces annual precipitation error over monsoon region that equals to about 13% of observed precipitation. It has also been suggested that LSP contribute to the abrupt jump in latitude of the East Asian monsoon as well as general circulation turning in some monsoon regions in its early stages. The LSP effects have also been assessed in the land use land cover change experiment. Based on recently compiled global land-use data from 1948-2005, the GCM simulation results indicate the degradation in Mexico, West Africa, south and East Asia and South America produce substantial precipitation anomalies, some of which are consistent with observed regional precipitation anomalies. More comprehensive studies with multi-models are imperatively necessary.

  15. Revising Hydrology of a Land Surface Model

    NASA Astrophysics Data System (ADS)

    Le Vine, Nataliya; Butler, Adrian; McIntyre, Neil; Jackson, Christopher

    2015-04-01

    Land Surface Models (LSMs) are key elements in guiding adaptation to the changing water cycle and the starting points to develop a global hyper-resolution model of the terrestrial water, energy and biogeochemical cycles. However, before this potential is realised, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. An important limitation is the simplistic or non-existent representation of the deep subsurface in LSMs; and another is the lack of connection of LSM parameterisations to relevant hydrological information. In this context, the paper uses a case study of the JULES (Joint UK Land Environmental Simulator) LSM applied to the Kennet region in Southern England. The paper explores the assumptions behind JULES hydrology, adapts the model structure and optimises the coupling with the ZOOMQ3D regional groundwater model. The analysis illustrates how three types of information can be used to improve the model's hydrology: a) observations, b) regionalized information, and c) information from an independent physics-based model. It is found that: 1) coupling to the groundwater model allows realistic simulation of streamflows; 2) a simple dynamic lower boundary improves upon JULES' stationary unit gradient condition; 3) a 1D vertical flow in the unsaturated zone is sufficient; however there is benefit in introducing a simple dual soil moisture retention curve; 4) regionalized information can be used to describe soil spatial heterogeneity. It is concluded that relatively simple refinements to the hydrology of JULES and its parameterisation method can provide a substantial step forward in realising its potential as a high-resolution multi-purpose model.

  16. Land use for animal production in global change studies: Defining and characterizing a framework.

    PubMed

    Phelps, Leanne N; Kaplan, Jed O

    2017-11-01

    Land use for animal production influences the earth system in a variety of ways, including local-scale modification to biodiversity, soils, and nutrient cycling; regional changes in albedo and hydrology; and global-scale changes in greenhouse gas and aerosol concentrations. Pasture is furthermore the single most extensive form of land cover, currently comprising about 22-26% of the earth's ice-free land surface. Despite the importance and variable expressions of animal production, distinctions among different systems are effectively absent from studies of land use and land cover change. This deficiency is improving; however, livestock production system classifications are rarely applied in this context, and the most popular global land cover inventories still present only a single, usually poorly defined category of "pasture" or "rangeland" with no characterization of land use. There is a marked lack of bottom-up, evidence-based methodology, creating a pressing need to incorporate cross-disciplinary evidence of past and present animal production systems into global change studies. Here, we present a framework, modified from existing livestock production systems, that is rooted in sociocultural, socioeconomic, and ecological contexts. The framework defines and characterizes the range of land usage pertaining to animal production, and is suitable for application in land use inventories and scenarios, land cover modeling, and studies on sustainable land use in the past, present, and future. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

  17. Modeling Land Surface Phenology Using Earthlight

    NASA Astrophysics Data System (ADS)

    Henebry, G. M.

    2005-12-01

    Microwave radiometers have long been used in earth observation, but the coarse spatial resolution of the data has discouraged its use in investigations of the vegetated land surface. The Advanced Microwave Scanning Radiometer (AMSR-E) on the Aqua satellite acquires multifrequency observations twice daily (1:30 and 13:30). From these brightness temperatures come two data products relevant to land surface phenology: soil moisture and vegetation water content. Although the nominal spatial resolution of these products is coarse (25 km), the fine temporal sampling allows characterization of the diel variation in surface moisture as contained in the uppermost soil layer and bound in the vegetation canopy. The ephermal dynamics of surficial soil moisture are difficult to validate due to the scale discrepancy between the 625 sq km coverage of a single pixel and the sparse network of weather stations. In contrast, canopy dynamics are more readily validated using finer spatial resolution data products and/or ecoregionalizations. For sites in the North American Great Plains and Northern Eurasia dominated by herbaceous vegetation, I will present land surface phenologies modeled using emitted earthlight and compare them with land surface phenologies modeled using reflected sunlight. I will also explore whether some key climate modes have a significant effect on the microwave-retrieved land surface phenologies.

  18. 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.

  19. Influence of land-surface evapotranspiration on the earth's climate

    NASA Technical Reports Server (NTRS)

    Shukla, J.; Mintz, Y.

    1982-01-01

    Land-surface evapotranspiration is shown to strongly influence global fields of rainfall, temperature and motion by calculations using a numerical model of the atmosphere, confirming the general belief in the importance of evapotranspiration-producing surface vegetation for the earth's climate. The current version of the Goddard Laboratory atmospheric general circulation model is used in the present experiment, in which conservation equations for mass, momentum, moisture and energy are expressed in finite-difference form for a spherical grid to calculate (1) surface pressure field evolution, and (2) the wind, temperature, and water vapor fields at nine levels between the surface and a 20 km height.

  20. Spatial assessment of land surface temperature and land use/land cover in Langkawi Island

    NASA Astrophysics Data System (ADS)

    Abu Bakar, Suzana Binti; Pradhan, Biswajeet; Salihu Lay, Usman; Abdullahi, Saleh

    2016-06-01

    This study investigates the relationship between Land Surface Temperature and Land Use/Land Cover in Langkawi Island by using Normalized Difference Vegetation Index (NDVI), Normalized Difference Build-Up Index (NDBI) and Modified Normalized Difference Water Index (MNDWI) qualitatively by using Landsat 7 ETM+ and Landsat 8 (OLI/TIRS) over the period 2002 and 2015. Pixel-based classifiers Maximum Likelihood (MLC) and Support Vector Machine (SVM), has been performed to prepare the Land Use/ Land Cover map (LU/LC) and the result shows that Support Vector Machine (SVM) achieved maximum accuracy with 90% and 90.46% compared to Maximum Likelihood (MLC) classifier with 86.62% and 86.98% respectively. The result revealed that as the impervious surface (built-up /roads) increases, the surface temperature of the area increased. However, land surface temperature decreased in the vegetated areas. Based from the linear regression between LST and NDVI, NDBI and MNDWI, these indices can be used as an indicator to monitor the impact of Land Use/Land Cover on Land Surface Temperature.

  1. Global land-water nexus: Agricultural land and freshwater use embodied in worldwide supply chains.

    PubMed

    Chen, B; Han, M Y; Peng, K; Zhou, S L; Shao, L; Wu, X F; Wei, W D; Liu, S Y; Li, Z; Li, J S; Chen, G Q

    2017-09-21

    As agricultural land and freshwater inextricably interrelate and interact with each other, the conventional water and land policy in "silos" should give way to nexus thinking when formulating the land and water management strategies. This study constructs a systems multi-regional input-output (MRIO) model to expound global land-water nexus by simultaneously tracking agricultural land and freshwater use flows along the global supply chains. Furthermore, land productivity and irrigation water requirements of 160 crops in different regions are investigated to reflect the land-water linkage. Results show that developed economies (e.g., USA and Japan) and major large developing economies (e.g., mainland China and India) are the overriding drivers of agricultural land and freshwater use globally. In general, significant net transfers of these two resources are identified from resource-rich and less-developed economies to resource-poor and more-developed economies. For some crops, blue water productivity is inversely related to land productivity, indicating that irrigation water consumption is sometimes at odds with land use. The results could stimulus international cooperation for sustainable land and freshwater management targeting on original suppliers and final consumers along the global supply chains. Moreover, crop-specific land-water linkage could provide insights for trade-off decisions on minimizing the environmental impacts on local land and water resources. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Human Land-Use Practices Lead to Global Long-Term Increases in Photosynthetic Capacity

    NASA Technical Reports Server (NTRS)

    Mueller, Thomas; Tucker, Compton J.; Dressler, Gunnar; Pinzon, Jorge E.; Leimgruber, Peter; Dubayah, Ralph O.; Hurtt, George C.; Boehning-Gaese, Katrin; Fagan, William F.

    2014-01-01

    Long-term trends in photosynthetic capacity measured with the satellite-derived Normalized Difference Vegetation Index (NDVI) are usually associated with climate change. Human impacts on the global land surface are typically not accounted for. Here, we provide the first global analysis quantifying the effect of the earth's human footprint on NDVI trends. Globally, more than 20% of the variability in NDVI trends was explained by anthropogenic factors such as land use, nitrogen fertilization, and irrigation. Intensely used land classes, such as villages, showed the greatest rates of increase in NDVI, more than twice than those of forests. These findings reveal that factors beyond climate influence global long-term trends in NDVI and suggest that global climate change models and analyses of primary productivity should incorporate land use effects.

  3. Upscaling and downscaling of land surface fluxes with surface temperature

    USDA-ARS?s Scientific Manuscript database

    Land surface temperature (LST) is a key surface boundary condition that is significantly correlated to surface flux partitioning between latent and sensible heat. The spatial and temporal variation in LST is driven by radiation, wind, vegetation cover and roughness as well as soil moisture status ...

  4. Spatial modeling of agricultural land use change at global scale

    NASA Astrophysics Data System (ADS)

    Meiyappan, P.; Dalton, M.; O'Neill, B. C.; Jain, A. K.

    2014-11-01

    Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns. We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling

  5. 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.

  6. Operational 333m Biophysical Products of the Copernicus Global Land Service for Agriculture Monitoring

    NASA Astrophysics Data System (ADS)

    Lacaze, R.; Smets, B.; Baret, F.; Weiss, M.; Ramon, D.; Montersleet, B.; Wandrebeck, L.; Calvet, J.-C.; Roujean, J.-L.; Camacho, F.

    2015-04-01

    The Copernicus Global Land service provides continuously a set of bio-geophysical variables describing, over the whole globe, the vegetation dynamic, the energy budget at the continental surface and some components of the water cycle. These generic products serve numerous applications including agriculture and food security monitoring. The portfolio of the Copernicus Global Land service contains Essential Climate Variables like the Leaf Area Index (LAI), the Fraction of PAR absorbed by the vegetation (FAPAR), the surface albedo, the Land Surface Temperature, the soil moisture, the burnt areas, the areas of water bodies, and additional vegetation indices. They are generated every hour, every day or every 10 days on a reliable automatic basis from Earth Observation satellite data. Beside this timely production, the available historical archives have been processed, using the same innovative algorithms, to get consistent time series as long as possible. All products are accessible, free of charge after registration through FTP/HTTP (land.copernicus.eu/global/>http://land.copernicus.eu/global/) and through the GEONETCast satellite distribution system. The evolution of the service towards the operations at 333m resolution is partly supported by the FP7/ImagineS project which focuses on the retrieval of LAI, FAPAR, fraction of vegetation cover and surface albedo from PROBA-V sensor data. The paper presents the innovations of the 333m biophysical products, make an overview of their current status, and introduce the next steps of the evolution of the Copernicus Global Land service.

  7. Land surface processes/land cover change (LCC) and the Tibetan Plateau climate

    NASA Astrophysics Data System (ADS)

    Xue, Y.; Li, Q.; de Sales, F.; Vasic, R.; Song, G.

    2010-12-01

    The Tibetan Plateau (TP) is a key region of land-atmosphere interactions with severe eco-environment degradation. A GCM land/atmosphere interaction study indicates that the land surface processes has substantial impact on TP water cycle, contributing 46% and 53% of annual precipitation for TP and East Asian, respectively, with strong land impacts during the spring and summer (Xue et al., 2010). For East Asia, the land effect during the fall is also strong. Using the NCEP GCM/SSiB, a preliminarily assessment of possible impact of LCC on the TP regional summer circulation and precipitation has been conducted. Two existing vegetation maps with very different land cover conditions over the TP, one with bare ground and one with grassland over the central TP and needleleaf evergreen trees in the southeastern derived from satellite-derived data, are tested and produce clearer climate signals due to land cover change. It shows that LCC from vegetated land to bare ground decreases radiation absorbed by the surface and results in weaker surface thermal effects, which leads to lower sensible heat flux as well as weaker vertical ascending motion, low-layer cyclonic, upper-level anticyclonic, and summer monsoon circulation in large scale. These changes in circulation cause a decrease in the precipitation in the southeastern TP. This spatial characteristics are consistent with the statistical relationship between satellite products and observed precipitation. Meanwhile, the results also show that through affecting the meridional circulation cells, the land disturbance in TP could have substantial impact on the global circulation.

  8. Remote sensing of land surface phenology

    USGS Publications Warehouse

    Meier, G.A.; Brown, J.F.

    2014-01-01

    Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program produces annually, nine phenology indicator variables at 250 m and 1,000 m resolution for the contiguous U.S. The 12 year archive is available at http://phenology.cr.usgs.gov/index.php.

  9. A Land System representation for global assessments and land-use modeling.

    PubMed

    van Asselen, Sanneke; Verburg, Peter H

    2012-10-01

    Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land-use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human-environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi-)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land-use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land-change models that include the human drivers of land change are best parameterized at sub-global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions. © 2012 Blackwell Publishing Ltd.

  10. Advanced microwave forward model for the land surface data assimilation

    NASA Astrophysics Data System (ADS)

    Park, Chang-Hwan; Pause, Marion; Gayler, Sebastian; Wollschlaeger, Ute; Jackson, Thomas J.; LeDrew, Ellsworth; Behrendt, Andreas; Wulfmeyer, Volker

    2015-04-01

    From local to global scales, microwave remote-sensing techniques can provide temporally and spatially highly resolved observations of land surface properties including soil moisture and temperature as well as the state of vegetation. These variables are critical for agricultural productivity and water resource management. Furthermore, having accurate information of these variables allows us to improve the performances of numerical weather forecasts and climate prediction models. However, it is challenging to translate a measured brightness temperature into the multiple land surface properties because of the inherent inversion problem. In this study, we introduce a novel forward model for microwave remote sensing to resolve this inversion problem and to close the gap between land surface modeling and observations. It is composed of the Noah-MP land surface model as well as new models for the dielectric mixing and the radiative transfer. For developing a realistic forward operator, the land surface model must simulate soil and vegetation processes properly. The Noah-MP land surface model provides an excellent starting point because it contains already a sophisticated soil texture and land cover data set. Soil moisture transport is derived using the Richards equation in combination with a set of soil hydraulic parameters. Vegetation properties are considered using several photosynthesis models with different complexity. The energy balance is closed for the top soil and the vegetation layers. The energy flux becomes more realistic due to including not only the volumetric ratio of land surface properties but also their surface fraction as sub-grid scale information (semitile approach). Dielectric constant is the fundamental link to quantify the land surface properties. Our physical based new dielectric-mixing model is superior to previous calibration and semi-empirical approaches. Furthermore, owing to the consideration of the oversaturated surface dielectric behaviour

  11. Global assessment of the economics of land degradation and improvement

    NASA Astrophysics Data System (ADS)

    Nkonya, Ephraim

    2017-04-01

    Land degradation—defined by the Millennium Ecosystem Assessment report as the long-term loss of ecosystems services—is a global problem, negatively affecting the livelihoods and food security of billions of people. Intensifying efforts, mobilizing more investments and strengthening the policy commitment for addressing land degradation at the global level needs to be supported by a careful evaluation of the costs and benefits of action versus costs of inaction against land degradation. Consistent with the definition of land degradation, we adopt the Total Economic Value (TEV) approach to determine the costs of land degradation and use remote sensing data and global statistical databases in our analysis. The results show that the annual costs of land degradation due to land use and land cover change (LUCC) are about US231 billion per year or about 0.41 % of the global GDP of US56.49 trillion in 2007. Contrary to past global land degradation assessment studies, land degradation is severe in both tropical and temperate countries. However, the losses from LUCC are especially high in Sub-Saharan Africa, which accounts for 26 % of the total global costs of land degradation due to LUCC. However, the local tangible losses (mainly provisioning services) account only for 46 % of the total cost of land degradation and the rest of the cost is due to the losses of ecosystem services (ES) accruable largely to beneficiaries other than the local land users. These external ES losses include carbon sequestration, biodiversity, genetic information and cultural services. This implies that the global community bears the largest cost of land degradation, which suggests that efforts to address land degradation should be done bearing in mind that the global community,as a whole, incurs larger losses than the local communities experiencing land degradation. The cost of soil fertility mining due to using land degrading management practices on maize, rice and wheat is estimated to be

  12. 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.

    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.

  13. Soft Landing of Complex Molecules on Surfaces *

    NASA Astrophysics Data System (ADS)

    Johnson, Grant E.; Hu, Qichi; Laskin, Julia

    2011-07-01

    Soft and reactive landing of mass-selected ions onto surfaces has become a topic of substantial interest due to its promising potential for the highly controlled preparation of materials. For example, there are possible applications in the production of peptide and protein microarrays for use in high-throughput screening, protein separation and conformational enrichment of peptides, redox protein characterization, thin-film production, and the preparation of catalysts through deposition of clusters and organometallic complexes. Soft landing overcomes many of the limitations associated with conventional thin-film production techniques and offers unprecedented selectivity and specificity of preparation of deposited species. This review discusses the fundamental aspects of soft and reactive landing of mass-selected ions on surfaces that pertain to applications of these techniques in biomaterials, molecular electronics, catalysis, and interfacial chemistry.

  14. Emulation of Land-Surface Models

    NASA Astrophysics Data System (ADS)

    Massoud, E. C.; Vrugt, J. A.

    2016-12-01

    Land surface models (LSMs) such as the Community Land Model (CLM) simulate the governing processes and interactions of the biogeochemical, hydrologic and the energy cycle at the land surface. LSMs are particularly useful for analysis of the impacts of environmental change on terrestrial ecosystems and the feedback of those changes on the atmosphere and the climate. Most LSMs are CPU-intensive and contain many hundreds of parameters whose values are site specific. This makes it rather difficult to calibrate LSMs against observations of the model output. In this paper, we use emulation techniques to create a surrogate model of a LSM. This surrogate model approximates closely the output of the LSM, but at a drastically reduced CPU-cost of just a few seconds. We then use this emulator to quantify model parameter uncertainty using Bayesian inference. The maximum-aposteriori density solution is then used in the original LSM and compared against the default parameterization for different sites.

  15. A new map of global ecological land units—An ecophysiographic stratification approach

    USGS Publications Warehouse

    Sayre, Roger; Dangermond, Jack; Frye, Charlie; Vaughan, Randy; Aniello, Peter; Breyer, Sean; Cribbs, Douglas; Hopkins, Dabney; Nauman, Richard; Derrenbacher, William; Wright, Dawn; Brown, Clint; Convis, Charles; Smith, Jonathan H.; Benson, Laurence; Van Sistine, Darren; Warner, Harumi; Cress, Jill Janene; Danielson, Jeffrey J.; Hamann, Sharon L.; Cecere, Thomas; Reddy, Ashwan D.; Burton, Devon; Grosse, Andrea; True, Diane; Metzger, Marc; Hartmann, Jens; Moosdorf, Nils; Durr, Hans; Paganini, Marc; Defourny, Pierre; Arino, Olivier; Maynard, Simone; Anderson, Mark; Comer, Patrick

    2014-01-01

    In response to the need and an intergovernmental commission for a high resolution and data-derived global ecosystem map, land surface elements of global ecological pattern were characterized in an ecophysiographic stratification of the planet. The stratification produced 3,923 terrestrial ecological land units (ELUs) at a base resolution of 250 meters. The ELUs were derived from data on land surface features in a three step approach. The first step involved acquiring or developing four global raster datalayers representing the primary components of ecosystem structure: bioclimate, landform, lithology, and land cover. These datasets generally represent the most accurate, current, globally comprehensive, and finest spatial and thematic resolution data available for each of the four inputs. The second step involved a spatial combination of the four inputs into a single, new integrated raster dataset where every cell represents a combination of values from the bioclimate, landforms, lithology, and land cover datalayers. This foundational global raster datalayer, called ecological facets (EFs), contains 47,650 unique combinations of the four inputs. The third step involved an aggregation of the EFs into the 3,923 ELUs. This subdivision of the Earth’s surface into relatively fine, ecological land areas is designed to be useful for various types of ecosystem research and management applications, including assessments of climate change impacts to ecosystems, economic and non-economic valuation of ecosystem services, and conservation planning.

  16. Land System Science: between global challenges and local realities☆

    PubMed Central

    Verburg, Peter H; Erb, Karl-Heinz; Mertz, Ole; Espindola, Giovana

    2013-01-01

    This issue of Current Opinion in Environmental Sustainability provides an overview of recent advances in Land System Science while at the same time setting the research agenda for the Land System Science community. Land System Science is not just representing land system changes as either a driver or a consequence of global environmental change. Land systems also offer solutions to global change through adaptation and mitigation and can play a key role in achieving a sustainable future earth. The special issue assembles 14 articles that entail different perspectives on land systems and their dynamics, synthesizing current knowledge, highlighting currently under-researched topics, exploring scientific frontiers and suggesting ways ahead, integrating a plethora of scientific disciplines. PMID:24851141

  17. An analysis of IGBP global land-cover characterization process

    USGS Publications Warehouse

    Loveland, Thomas R.; Zhu, Zhiliang; Ohlen, Donald O.; Brown, Jesslyn F.; Reed, Bradley C.; Yang, Limin

    1999-01-01

    The international Geosphere Biosphere Programme (IGBP) has called for the development of improved global land-cover data for use in increasingly sophisticated global environmental models. To meet this need, the staff of the U.S. Geological Survey and the University of Nebraska-Lincoln developed and applied a global land-cover characterization methodology using 1992-1993 1-km resolution Advanced Very High Resolution Radiometer (AVHRR) and other spatial data. The methodology, based on unsupervised classification with extensive postclassification refinement, yielded a multi-layer database consisting of eight land-cover data sets, descriptive attributes, and source data. An independent IGBP accuracy assessment reports a global accuracy of 73.5 percent, and continental results vary from 63 percent to 83 percent. Although data quality, methodology, interpreter performance, and logistics affected the results, significant problems were associated with the relationship between AVHRR data and fine-scale, spectrally similar land-cover patterns in complex natural or disturbed landscapes.

  18. LandScan 2007 High Resolution Global Population Data Set

    SciTech Connect

    2008-01-01

    The LandScan data set is a worldwide population database compiled on a 30" x 30" latitude/longitude grid. Census counts (at sub-national level) were apportioned to each grid cell based on likelihood coefficients, which are based on proximity to roads, slope, land cover, nighttime lights, and other data sets. LandScan 2001 has been developed as part of Oak Ridge National Laboratory (ORNL) Global Population Project for estimating ambient population risk.

  19. LandScan 2008 High Resolution Global Population Data Set

    SciTech Connect

    2009-01-01

    The LandScan data set is a worldwide population database compiled on a 30" x 30" latitude/longitude grid. Census counts (at sub-national level) were apportioned to each grid cell based on likelihood coefficients, which are based on proximity to roads, slope, land cover, nighttime lights, and other data sets. LandScan 2001 has been developed as part of Oak Ridge National Laboratory (ORNL) Global Population Project for estimating ambient population risk.

  20. LandScan 2009 High Resolution Global Population Data Set

    SciTech Connect

    2009-07-01

    The LandScan data set is a worldwide population database compiled on a 30" x 30" latitude/longitude grid. Census counts (at sub-national level) were apportioned to each grid cell based on likelihood coefficients, which are based on proximity to roads, slope, land cover, nighttime lights, and other data sets. LandScan 2001 has been developed as part of Oak Ridge National Laboratory (ORNL) Global Population Project for estimating ambient population risk.

  1. LandScan 2010 High Resolution Global Population Data Set

    SciTech Connect

    2010-07-01

    The LandScan data set is a worldwide population database compiled on a 30" x 30" latitude/longitude grid. Census counts (at sub-national level) were apportioned to each grid cell based on likelihood coefficients, which are based on proximity to roads, slope, land cover, nighttime lights, and other data sets. LandScan 2001 has been developed as part of Oak Ridge National Laboratory (ORNL) Global Population Project for estimating ambient population risk.

  2. LandScan 2013 High Resolution Global Population Data Set

    SciTech Connect

    2014-07-01

    The LandScan data set is a worldwide population database compiled on a 30"x30" latitude/longitude grid. Census counts (at sub-national level) were apportioned to each grid cell based on likelihood coefficients, which are based on land cover, slope, road proximity, high-resolution imagery, and other data sets. The LandScan data set was developed as part of Oak Ridge National Laboratory (ORNL) Global Population Project for estimating ambient populations at risk.

  3. LandScan 2011 High Resolution Global Population Data Set

    SciTech Connect

    2012-11-19

    The LandScan data set is a worldwide population database compiled on a 30" x 30" latitude/longitude grid. Census counts (at sub-national level) were apportioned to each grid cell based on likelihood coefficients, which are based on proximity to roads, slope, land cover, nighttime lights, and other data sets. LandScan 2001 has been developed as part of Oak Ridge National Laboratory (ORNL) Global Population Project for estimating ambient population risk.

  4. Recent Development on the NOAA's Global Surface Temperature Dataset

    NASA Astrophysics Data System (ADS)

    Zhang, H. M.; Huang, B.; Boyer, T.; Lawrimore, J. H.; Menne, M. J.; Rennie, J.

    2016-12-01

    Global Surface Temperature (GST) is one of the most widely used indicators for climate trend and extreme analyses. A widely used GST dataset is the NOAA merged land-ocean surface temperature dataset known as NOAAGlobalTemp (formerly MLOST). The NOAAGlobalTemp had recently been updated from version 3.5.4 to version 4. The update includes a significant improvement in the ocean surface component (Extended Reconstructed Sea Surface Temperature or ERSST, from version 3b to version 4) which resulted in an increased temperature trends in recent decades. Since then, advancements in both the ocean component (ERSST) and land component (GHCN-Monthly) have been made, including the inclusion of Argo float SSTs and expanded EOT modes in ERSST, and the use of ISTI databank in GHCN-Monthly. In this presentation, we describe the impact of those improvements on the merged global temperature dataset, in terms of global trends and other aspects.

  5. Monitoring global monthly mean surface temperatures

    SciTech Connect

    Trenberth, K.E.; Hurrell, J.W. ); Christy, J.R. )

    1992-12-01

    An assessment is made of how well the monthly mean surface temperatures for the decade of the 1980s are known. The sources of noise in the data, the numbers of observations, and the spatial coverage are appraised for comparison with the climate signal, and different analyzed results are compared to see how reproducible they are. The data are further evaluated by comparing anomalies of near-global monthly mean surface temperatures with those of global satellite channel 2 microwave sounding unit (MSU) temperatures for 144 months from 1979 to 1990. Very distincitve patterns are seen in the correlation coefficients, which range from high (> 0.8) over the extratropical continents of the Northern Hemisphere, to moderate ([approximately] 0.5) over tropical and subtropical land areas, to very low over the southern oceans and tropical western Pacific. The physical difference between the two temperature measurements is one factor in these patterns. The correlation coefficient is a measure of the signal-to-noise ratio, and largest values are found where the climate signal is largest, but the spatial variation in the inherent noise in the surface observations over the oceans is the other major factor in accounting for the pattern. 42 refs., 12 figs., 4 tab.

  6. Food Footprints: Global diet preferences and the land required to sustain them

    NASA Astrophysics Data System (ADS)

    Cassidy, E. S.; Gerber, J. S.; Foley, J. A.

    2011-12-01

    Agricultural land occupies approximately 4.9 billion hectares of the earth's surface. The amount of land that is required to feed a person differs globally, however, dependent mainly on diet. Diets dense in grain-fed animal protein require more land than plant-based diets in order to supply the same quantity of calories and protein. As the world's population becomes more affluent, more animal products will be demanded of the food system. In this presentation, I will discuss how diet preferences differ globally and how these preferences translate to the amount of cropland needed to sustain them.

  7. Effects of land use and land cover change on global ozone air quality in the mid-21st century

    NASA Astrophysics Data System (ADS)

    Wong, A. Y. H.; Tai, A. P. K.; Geddes, J.

    2016-12-01

    Over the coming century, processes such as cropland expansion are projected to substantially alter global land use patterns, while the simultaneous changes in CO2 concentration are also expected to influence vegetation growth. The resulting changes in global land cover and land use (LCLU) have the potential to greatly influence atmospheric composition, but the magnitudes and even the signs of impacts are still highly uncertain due to the complex interactions between climate, CO2, air pollutants and vegetation, with substantial ramifications for the accuracy of future air quality projections. In this study, we use a one-way coupled land-atmosphere modeling framework to investigate how future LCLU changes will affect ozone air quality under two future scenarios of anthropogenic land use changes (RCP4.5 and RCP8.5). We first use the fractional coverage of different plant functional types (PFTs) and PFT-specific leaf area index (LAI) to characterize a land cover for the present day and for a future that considers anthropogenic land use change only. We then use CLM (Community Land Model) to simulate the evolution of the land cover from 2000 to 2050 under the simultaneous influence of CO2 on vegetation variables (e.g., LAI, stomatal conductance, biogenic emissions). The results are then fed into the GEOS-Chem chemical transport model with a novel land cover harmonization scheme to investigate their individual and combined effects on atmospheric chemistry.We show that different projected scenarios for cropland expansion and reforestation can lead to drastically different responses of surface ozone to land use change alone under RCP4.5 and RCP8.5 by year 2050. Surface ozone is projected to increase by up to 4 ppbv under RCP4.5 but decrease by up to 3 ppbv under RCP8.5 over North America, South America and Africa. In China, both land use scenarios produce large decreases in surface ozone (by up to 8 ppbv for RCP4.5 and 6 ppbv for RCP8.5). While the changes in isoprene

  8. 25 CFR 214.14 - Use of surface lands.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 25 Indians 1 2010-04-01 2010-04-01 false Use of surface lands. 214.14 Section 214.14 Indians... LANDS, OKLAHOMA, FOR MINING, EXCEPT OIL AND GAS § 214.14 Use of surface lands. (a) Lessees may use so much of the surface of the leased land as shall be reasonably necessary for the prospecting and mining...

  9. 25 CFR 214.14 - Use of surface lands.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 25 Indians 1 2011-04-01 2011-04-01 false Use of surface lands. 214.14 Section 214.14 Indians... LANDS, OKLAHOMA, FOR MINING, EXCEPT OIL AND GAS § 214.14 Use of surface lands. (a) Lessees may use so much of the surface of the leased land as shall be reasonably necessary for the prospecting and mining...

  10. 25 CFR 214.14 - Use of surface lands.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 25 Indians 1 2013-04-01 2013-04-01 false Use of surface lands. 214.14 Section 214.14 Indians... LANDS, OKLAHOMA, FOR MINING, EXCEPT OIL AND GAS § 214.14 Use of surface lands. (a) Lessees may use so much of the surface of the leased land as shall be reasonably necessary for the prospecting and mining...

  11. 25 CFR 214.14 - Use of surface lands.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 25 Indians 1 2014-04-01 2014-04-01 false Use of surface lands. 214.14 Section 214.14 Indians... LANDS, OKLAHOMA, FOR MINING, EXCEPT OIL AND GAS § 214.14 Use of surface lands. (a) Lessees may use so much of the surface of the leased land as shall be reasonably necessary for the prospecting and mining...

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

    NASA Astrophysics Data System (ADS)

    Byrne, M.; O'Gorman, P. A.

    2016-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  14. Identifying Land Use and Land-Use Changes (LULUC): A Global LULUC Matrix.

    PubMed

    De Rosa, Michele; Vestergaard Odgaard, Mette; Staunstrup, Jan K; Trydeman Knudsen, Marie; Hermansen, John Erik

    2017-07-18

    Land use and land-use changes (LULUC) information is essential to determine the environmental impacts of anthropogenic land-use and conversion. However, existing data sets are either local-scale or they quantify land occupation per land-use type rather than providing information on land-use changes. Here we combined the strengths of the remotely sensed MODIS land cover data set and FAOSTAT land-use data to obtain a database including a collection of 231 country-specific LULUC matrixes, as suggested by the IPCC. We produced two versions of each matrix: version 1, identifying forestland based on canopy cover criteria; version 2, distinguishing primary, secondary, planted forests and permanent crops. The outcome was a first country-based, consistent set of spatially explicit LULUC matrixes. The database facilitates a more holistic assessment of land-use changes, quantifying changes that occur between land classes from 2001 to 2012, providing crucial information for assessing environmental impacts caused by LULUC. The data allow global-scale land-use change analyses, requiring a distinction between land types based not only on land cover but also on land uses. The spatially explicit data set may also serve as a starting point for further studies aiming at determining the drivers of land-use change supported by spatial statistical modeling.

  15. Multidecadal climate variability of global lands and oceans

    USGS Publications Warehouse

    McCabe, G.J.; Palecki, M.A.

    2006-01-01

    Principal components analysis (PCA) and singular value decomposition (SVD) are used to identify the primary modes of decadal and multidecadal variability in annual global Palmer Drought Severity Index (PDSI) values and sea-surface temperature (SSTs). The PDSI and SST data for 1925-2003 were detrended and smoothed (with a 10-year moving average) to isolate the decadal and multidecadal variability. The first two principal components (PCs) of the PDSI PCA explained almost 38% of the decadal and multidecadal variance in the detrended and smoothed global annual PDSI data. The first two PCs of detrended and smoothed global annual SSTs explained nearly 56% of the decadal variability in global SSTs. The PDSI PCs and the SST PCs are directly correlated in a pairwise fashion. The first PDSI and SST PCs reflect variability of the detrended and smoothed annual Pacific Decadal Oscillation (PDO), as well as detrended and smoothed annual Indian Ocean SSTs. The second set of PCs is strongly associated with the Atlantic Multidecadal Oscillation (AMO). The SVD analysis of the cross-covariance of the PDSI and SST data confirmed the close link between the PDSI and SST modes of decadal and multidecadal variation and provided a verification of the PCA results. These findings indicate that the major modes of multidecadal variations in SSTs and land-surface climate conditions are highly interrelated through a small number of spatially complex but slowly varying teleconnections. Therefore, these relations may be adaptable to providing improved baseline conditions for seasonal climate forecasting. Published in 2006 by John Wiley & Sons, Ltd.

  16. Ecorestoration model for surface mined lands

    SciTech Connect

    Soni, P.; Vasistha, H.B.; Kumar, O.

    1990-12-31

    Surface mining for minerals creates vast stretches of derelict lands which are, technically speaking, areas of {open_quotes}no value{close_quotes} from economic, social and aesthetic points of view. Problems due to surface mining are manifold, e.g. deforestation, soil erosion, pollution of water, air, noise, etc..., and depletion of nutrients. This paper discusses the ecorestoration model developed by the authors for restoring surface mined lands in one of the most fragile ecological regions of the country. Use of ecologically suitable native species of grasses, shrubs, and trees for restoration leads to stabilization of overburden dumps in a short span of five to six years. At the same time, the model stimulates ecological succession of flora and fauna, helps water pollution control and is capable of generating socioeconomic return in terms of fuel, fodder, fibre, etc.

  17. 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

  18. Upscaling and Downscaling of Land Surface Fluxes with Surface Temperature

    NASA Astrophysics Data System (ADS)

    Kustas, W. P.; Anderson, M. C.; Hain, C.; Albertson, J. D.; Gao, F.; Yang, Y.

    2015-12-01

    Land surface temperature (LST) is a key surface boundary condition that is significantly correlated to surface flux partitioning between latent and sensible heat. The spatial and temporal variation in LST is driven by radiation, wind, vegetation cover and roughness as well as soil moisture status in the surface and root zone. Data from airborne and satellite-based platforms provide LST from ~10 km to sub meter resolutions. A land surface scheme called the Two-Source Energy Balance (TSEB) model has been incorporated into a multi-scale regional modeling system ALEXI (Atmosphere Land Exchange Inverse) and a disaggregation scheme (DisALEXI) using higher resolution LST. Results with this modeling system indicates that it can be applied over heterogeneous land surfaces and estimate reliable surface fluxes with minimal in situ information. Consequently, this modeling system allows for scaling energy fluxes from subfield to regional scales in regions with little ground data. In addition, the TSEB scheme has been incorporated into a large Eddy Simulation (LES) model for investigating dynamic interactions between variations in the land surface state reflected in the spatial pattern in LST and the lower atmospheric air properties affecting energy exchange. An overview of research results on scaling of fluxes and interactions with the lower atmosphere from the subfield level to regional scales using the TSEB, ALEX/DisALEX and the LES-TSEB approaches will be presented. Some unresolved issues in the use of LST at different spatial resolutions for estimating surface energy balance and upscaling fluxes, particularly evapotranspiration, will be discussed.

  19. Climate change impacts on global rainfed agricultural land availability

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Cai, X.

    2010-12-01

    Global rainfed agricultural land availability can be subject to significant changes in both magnitude and spatial distribution due to climate change. We assess the possible changes using current and projected climate data from thirteen general circulation models (GCMs) under two emission scenarios, A1B & B1, together with global databases on land, including soil properties and slope. Two ensemble methods with the set of GCMs, Simple Average Method (SAM) and Root Mean Square Error Ensemble Method (RMSEMM), are employed to abate uncertainty involved in global GCM projections for assembling regional climate. Fuzzy logic, which handles land classification in an approximate yet efficient way, is adopted to estimate the land suitability through empirically determined membership functions and fuzzy rules chosen through a learning process based on remote sensed crop land products. Land suitability under five scenarios, which include the present-climate baseline scenario and four projected scenarios, A1B-SAM, A1B-RMSEMM, B1-SAM, and B1-RMSEMM, are assessed for both global and seven important agricultural regions in the world, Africa, China, India, Europe (excluding Russia), Russia, South America, and U.S. It is found that countries at the high latitudes of north hemisphere are more likely to benefit from climate change with respect to agricultural land availability; while countries at mid- and low latitudes may suffer different levels of loss of potential arable land. Expansions of the gross potential arable land are likely to occur in regions at the north high latitudes, including Russia, North China and U.S., while land shrinking can be expected in South America, Africa, India and Europe. Although the greatest potential for agricultural expansion lies in Africa and South America, with current cultivated land accounting for 20% and 13% respectively of the net potential arable land, negative effects from climate change may decline the potential. In summary, climate change

  20. Customer-oriented Data Formats and Services for Global Land Data Assimilation System (GLDAS) Products at the NASA GES DISC

    NASA Technical Reports Server (NTRS)

    Fang, Hongliang; Beaudoing, Hiroko; Rodell, Matthew; Teng, BIll; Vollmer, Bruce

    2008-01-01

    The Global Land Data Assimilation System (GLDAS) is generating a series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) products simulated by four land surface Models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information Services Center (HDISC), a component of NASA Goddard Earth Sciences Data and Information Services Center (GESDISC).

  1. The Project for Intercomparison of Land-surface Parameterization Schemes

    NASA Technical Reports Server (NTRS)

    Henderson-Sellers, A.; Yang, Z.-L.; Dickinson, R. E.

    1993-01-01

    The Project for Intercomparison of Land-surface Parameterization Schemes (PILPS) is described and the first stage science plan outlined. PILPS is a project designed to improve the parameterization of the continental surface, especially the hydrological, energy, momentum, and carbon exchanges with the atmosphere. The PILPS Science Plan incorporates enhanced documentation, comparison, and validation of continental surface parameterization schemes by community participation. Potential participants include code developers, code users, and those who can provide datasets for validation and who have expertise of value in this exercise. PILPS is an important activity because existing intercomparisons, although piecemeal, demonstrate that there are significant differences in the formulation of individual processes in the available land surface schemes. These differences are comparable to other recognized differences among current global climate models such as cloud and convection parameterizations. It is also clear that too few sensitivity studies have been undertaken with the result that there is not yet enough information to indicate which simplifications or omissions are important for the near-surface continental climate, hydrology, and biogeochemistry. PILPS emphasizes sensitivity studies with and intercomparisons of existing land surface codes and the development of areally extensive datasets for their testing and validation.

  2. Land surface processes and Sahel climate

    NASA Astrophysics Data System (ADS)

    Nicholson, Sharon

    2000-02-01

    This paper examines the question of land surface-atmosphere interactions in the West African Sahel and their role in the interannual variability of rainfall. In the Sahel, mean rainfall decreased by 25-40% between 1931-1960 and 1968-1997; every year in the 1950s was wet, and nearly every year since 1970 has been anomalously dry. Thus the intensity and multiyear persistence of drought conditions are unusual and perhaps unique features of Sahel climate. This article presents arguments for the role of land surface feedback in producing these features and reviews research relevant to land surface processes in the region, such as results from the 1992 Hydrologic Atmospheric Pilot Experiment (HAPEX)-Sahel experiment and recent studies on aerosols and on the issue of desertification in the region, a factor implicated by some as a cause of the changes in rainfall. Included also is a summary of evidence of feedback on meteorological processes, presented from both model results and observations. The reviewed studies demonstrate numerous ways in which the state of the land surface can influence interactions with the atmosphere. Surface hydrology essentially acts to delay and prolong the effects of meteorological drought. Each evaporative component of the surface water balance has its own timescale, with the presence of vegetation affecting the process both by delaying and prolonging the return of soil moisture to the atmosphere but at the same time accelerating the process through the evaporation of canopy-intercepted water. Hence the vegetation structure, including rooting depth, can modulate the land-atmosphere interaction. Such processes take on particular significance in the Sahel, where there is a high degree of recycling of atmospheric moisture and where the meteorological processes from the scale of boundary layer development to mesoscale disturbance generation are strongly influenced by moisture. Simple models of these feedback processes and their various timescales

  3. Global land cover mapping: a review and uncertainty analysis

    USGS Publications Warehouse

    Congalton, Russell G.; Gu, Jianyu; Yadav, Kamini; Thenkabail, Prasad S.; Ozdogan, Mutlu

    2014-01-01

    Given the advances in remotely sensed imagery and associated technologies, several global land cover maps have been produced in recent times including IGBP DISCover, UMD Land Cover, Global Land Cover 2000 and GlobCover 2009. However, the utility of these maps for specific applications has often been hampered due to considerable amounts of uncertainties and inconsistencies. A thorough review of these global land cover projects including evaluating the sources of error and uncertainty is prudent and enlightening. Therefore, this paper describes our work in which we compared, summarized and conducted an uncertainty analysis of the four global land cover mapping projects using an error budget approach. The results showed that the classification scheme and the validation methodology had the highest error contribution and implementation priority. A comparison of the classification schemes showed that there are many inconsistencies between the definitions of the map classes. This is especially true for the mixed type classes for which thresholds vary for the attributes/discriminators used in the classification process. Examination of these four global mapping projects provided quite a few important lessons for the future global mapping projects including the need for clear and uniform definitions of the classification scheme and an efficient, practical, and valid design of the accuracy assessment.

  4. Global Land Survey Impervious Mapping Project Web Site

    NASA Technical Reports Server (NTRS)

    DeColstoun, Eric Brown; Phillips, Jacqueline

    2014-01-01

    The Global Land Survey Impervious Mapping Project (GLS-IMP) aims to produce the first global maps of impervious cover at the 30m spatial resolution of Landsat. The project uses Global Land Survey (GLS) Landsat data as its base but incorporates training data generated from very high resolution commercial satellite data and using a Hierarchical segmentation program called Hseg. The web site contains general project information, a high level description of the science, examples of input and output data, as well as links to other relevant projects.

  5. Land system architecture: Using land systems to adapt and mitigate global environmental change

    SciTech Connect

    Turner, B.L.; Janetos, Anthony C.; Verbug, Peter H.; Murray, Alan T.

    2013-04-01

    Land systems (mosaics of land use and cover) are human environment systems, the changes in which drive and respond to local to global environmental changes, climate to macro-economy (Foley et al., 2005). Changes in land systems have been the principal proximate cause in the loss of habitats and biota globally, long contributed to atmospheric greenhouse gases, and hypothesized to have triggered climate changes in the early Holocene (Ruddiman, 2003). Land use, foremost agriculture, is the largest source of biologically active nitrogen to the atmosphere, critical to sources and sinks of carbon, and a major component in the hydrologic cycle (e.g., Bouwman et al., 2011). Changes in land systems also affect regional climate (Feddema et al., 2005; Pielke, 2005), ecosystem functions, and the array of ecosystem services they provide. Land systems, therefore, are a central feature of how humankind manages its relationship with nature-intended or not, or whether this relationship proceeds sustainably or not.

  6. The global distribution and dynamics of surface soil moisture

    NASA Astrophysics Data System (ADS)

    McColl, Kaighin A.; Alemohammad, Seyed Hamed; Akbar, Ruzbeh; Konings, Alexandra G.; Yueh, Simon; Entekhabi, Dara

    2017-01-01

    Surface soil moisture has a direct impact on food security, human health and ecosystem function. It also plays a key role in the climate system, and the development and persistence of extreme weather events such as droughts, floods and heatwaves. However, sparse and uneven observations have made it difficult to quantify the global distribution and dynamics of surface soil moisture. Here we introduce a metric of soil moisture memory and use a full year of global observations from NASA's Soil Moisture Active Passive mission to show that surface soil moisture--a storage believed to make up less than 0.001% of the global freshwater budget by volume, and equivalent to an, on average, 8-mm thin layer of water covering all land surfaces--plays a significant role in the water cycle. Specifically, we find that surface soil moisture retains a median 14% of precipitation falling on land after three days. Furthermore, the retained fraction of the surface soil moisture storage after three days is highest over arid regions, and in regions where drainage to groundwater storage is lowest. We conclude that lower groundwater storage in these regions is due not only to lower precipitation, but also to the complex partitioning of the water cycle by the surface soil moisture storage layer at the land surface.

  7. Does surface roughness dominate biophysical forcing of land use and land cover change in the eastern United States?

    NASA Astrophysics Data System (ADS)

    Burakowski, E. A.; Tawfik, A. B.; Ouimette, A.; Lepine, L. C.; Ollinger, S. V.; Bonan, G. B.; Zarzycki, C. M.; Novick, K. A.

    2016-12-01

    Changes in land use, land cover, or both promote changes in surface temperature that can amplify or dampen long-term trends driven by natural and anthropogenic climate change by modifying the surface energy budget, primarily through differences in albedo, evapotranspiration, and aerodynamic roughness. Recent advances in variable resolution global models provide the tools necessary to investigate local and global impacts of land use and land cover change by embedding a high-resolution grid over areas of interest in a seamless and computationally efficient manner. Here, we used two eddy covariance tower clusters in the Eastern US (University of New Hampshire UNH and Duke Forest) to validate simulation of surface energy fluxes and properties by the uncoupled Community Land Model (PTCLM4.5) and coupled land-atmosphere Variable-Resolution Community Earth System Model (VR-CESM1.3). Surface energy fluxes and properties are generally well captured by the models for grassland sites, however forested sites tend to underestimate latent heat and overestimate sensible heat flux. Surface roughness emerged as the dominant biophysical forcing factor affecting surface temperature in the eastern United States, generally leading to warmer nighttime temperatures and cooler daytime temperatures. However, the sign and magnitude of the roughness effect on surface temperature was highly sensitive to the calculation of aerodynamic resistance to heat transfer.

  8. An examination of methods for estimating land surface microwave emissivity

    NASA Astrophysics Data System (ADS)

    Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; You, Yalei; Ringerud, Sarah; Kumar, Sujay; Turk, F. Joseph

    2015-11-01

    Land surface emissivity is a critical variable for the passive microwave-based remote sensing of the land and atmosphere. Driven by the Global Precipitation Measurement mission, we implemented and evaluated a variety of approaches for quantitative estimation of land surface emissivity and its variability, within a well-defined common framework. These approaches fall into three classes: physical modeling, statistical modeling, and a hybrid of physical and statistical modeling. Every approach is subject to evaluation against retrieved emissivity over a large area in the Southern Great Plains for a period of 2 years. Physical modeling, based on two radiative transfer models coupled to a land surface modeling framework, produced reasonable estimates, with channel- and polarization-dependent errors. Calibration of these models with historical data substantially improved their performance at lower frequencies. The statistical method was tested with five different regression models, and each of them consistently outperformed physical models by about 50%. The best statistical model had an average error of 0.9-2.1%. These statistical models were slightly improved when empirical orthogonal function analysis was incorporated in the emissivity data. The hybrid approach produced errors between the uncalibrated and calibrated physical model errors. In addition to their predictive performance, other aspects of each approach's strengths and weaknesses are discussed.

  9. "Global warming, continental drying? Interpreting projected aridity changes over land under climate change"

    NASA Astrophysics Data System (ADS)

    Berg, Alexis

    2017-04-01

    In recent years, a number of studies have suggested that, as climate warms, the land surface will globally become more arid. Such results usually rely on drought or aridity diagnostics, such as the Palmer Drought Severity Index or the Aridity Index (ratio of precipitation over potential evapotranspiration, PET), applied to climate model projections of surface climate. From a global perspective, the projected widespread drying of the land surface is generally interpreted as the result of the dominant, ubiquitous warming-induced PET increase, which overwhelms the slight overall precipitation increase projected over land. However, several lines of evidence, based on (paleo)observations and climate model projections, raise questions regarding this interpretation of terrestrial climate change. In this talk, I will review elements of the literature supporting these different perspectives, and will present recent results based on CMIP5 climate model projections regarding changes in aridity over land that shed some light on this discussion. Central to the interpretation of projected land aridity changes is the understanding of projected PET trends over land and their link with changes in other variables of the terrestrial water cycle (ET, soil moisture) and surface climate in the context of the coupled land-atmosphere system.

  10. Coupling a Reactive Transport Code with a Global Land Surface Model for Mechanistic Biogeochemistry Representation: 1. Addressing the Challenge of Nonnegativity

    DOE PAGES

    Tang, Guoping; Yuan, Fengming; Bisht, Gautam; ...

    2016-01-01

    Reactive transport codes (e.g., PFLOTRAN) are increasingly used to improve the representation of biogeochemical processes in terrestrial ecosystem models (e.g., the Community Land Model, CLM). As CLM and PFLOTRAN use explicit and implicit time stepping, implementation of CLM biogeochemical reactions in PFLOTRAN can result in negative concentration, which is not physical and can cause numerical instability and errors. The objective of this work is to address the nonnegativity challenge to obtain accurate, efficient, and robust solutions. We illustrate the implementation of a reaction network with the CLM-CN decomposition, nitrification, denitrification, and plant nitrogen uptake reactions and test the implementation atmore » arctic, temperate, and tropical sites. We examine use of scaling back the update during each iteration (SU), log transformation (LT), and downregulating the reaction rate to account for reactant availability limitation to enforce nonnegativity. Both SU and LT guarantee nonnegativity but with implications. When a very small scaling factor occurs due to either consumption or numerical overshoot, and the iterations are deemed converged because of too small an update, SU can introduce excessive numerical error. LT involves multiplication of the Jacobian matrix by the concentration vector, which increases the condition number, decreases the time step size, and increases the computational cost. Neither SU nor SE prevents zero concentration. When the concentration is close to machine precision or 0, a small positive update stops all reactions for SU, and LT can fail due to a singular Jacobian matrix. The consumption rate has to be downregulated such that the solution to the mathematical representation is positive. A first-order rate downregulates consumption and is nonnegative, and adding a residual concentration makes it positive. For zero-order rate or when the reaction rate is not a function of a reactant, representing the availability limitation

  11. MODIS Global Sea Surface Temperature

    NASA Technical Reports Server (NTRS)

    2002-01-01

    Every day the Moderate-resolution Imaging Spectroradiometer (MODIS) measures sea surface temperature over the entire globe with high accuracy. This false-color image shows a one-month composite for May 2001. Red and yellow indicates warmer temperatures, green is an intermediate value, while blues and then purples are progressively colder values. The new MODIS sea surface temperature product will be particularly useful in studies of temperature anomalies, such as El Nino, as well as research into how air-sea interactions drive changes in weather and climate patterns. In the high resolution image, notice the amazing detail in some of the regional current patterns. For instance, notice the cold water currents that move from Antarctica northward along South America's west coast. These cold, deep waters upwell along an equatorial swath around and to the west of the Galapagos Islands. Note the warm, wide currents of the Gulf Stream moving up the United States' east coast, carrying Caribbean warmth toward Newfoundland and across the Atlantic toward Western Europe. Note the warm tongue of water extending from Africa's east coast to well south of the Cape of Good Hope. MODIS was launched in December 1999 aboard NASA's Terra satellite. For more details on this and other MODIS data products, please see NASA Unveils Spectacular Suite of New Global Data Products from MODIS. Image courtesy MODIS Ocean Group, NASA GSFC, and the University of Miami

  12. MODIS Global Sea Surface Temperature

    NASA Technical Reports Server (NTRS)

    2002-01-01

    Every day the Moderate-resolution Imaging Spectroradiometer (MODIS) measures sea surface temperature over the entire globe with high accuracy. This false-color image shows a one-month composite for May 2001. Red and yellow indicates warmer temperatures, green is an intermediate value, while blues and then purples are progressively colder values. The new MODIS sea surface temperature product will be particularly useful in studies of temperature anomalies, such as El Nino, as well as research into how air-sea interactions drive changes in weather and climate patterns. In the high resolution image, notice the amazing detail in some of the regional current patterns. For instance, notice the cold water currents that move from Antarctica northward along South America's west coast. These cold, deep waters upwell along an equatorial swath around and to the west of the Galapagos Islands. Note the warm, wide currents of the Gulf Stream moving up the United States' east coast, carrying Caribbean warmth toward Newfoundland and across the Atlantic toward Western Europe. Note the warm tongue of water extending from Africa's east coast to well south of the Cape of Good Hope. MODIS was launched in December 1999 aboard NASA's Terra satellite. For more details on this and other MODIS data products, please see NASA Unveils Spectacular Suite of New Global Data Products from MODIS. Image courtesy MODIS Ocean Group, NASA GSFC, and the University of Miami

  13. Atmosphere-only GCM (ACCESS1.0) simulations with prescribed land surface temperatures

    NASA Astrophysics Data System (ADS)

    Ackerley, Duncan; Dommenget, Dietmar

    2016-06-01

    General circulation models (GCMs) are valuable tools for understanding how the global ocean-atmosphere-land surface system interacts and are routinely evaluated relative to observational data sets. Conversely, observational data sets can also be used to constrain GCMs in order to identify systematic errors in their simulated climates. One such example is to prescribe sea surface temperatures (SSTs) such that 70 % of the Earth's surface temperature field is observationally constrained (known as an Atmospheric Model Intercomparison Project, AMIP, simulation). Nevertheless, in such simulations, land surface temperatures are typically allowed to vary freely, and therefore any errors that develop over the land may affect the global circulation. In this study therefore, a method for prescribing the land surface temperatures within a GCM (the Australian Community Climate and Earth System Simulator, ACCESS) is presented. Simulations with this prescribed land surface temperature model produce a mean climate state that is comparable to a simulation with freely varying land temperatures; for example, the diurnal cycle of tropical convection is maintained. The model is then developed further to incorporate a selection of "proof of concept" sensitivity experiments where the land surface temperatures are changed globally and regionally. The resulting changes to the global circulation in these sensitivity experiments are found to be consistent with other idealized model experiments described in the wider scientific literature. Finally, a list of other potential applications is described at the end of the study to highlight the usefulness of such a model to the scientific community.

  14. Modeling the relationship between land use and surface water quality.

    PubMed

    Tong, Susanna T Y; Chen, Wenli

    2002-12-01

    It is widely known that watershed hydrology is dependent on many factors, including land use, climate, and soil conditions. But the relative impacts of different types of land use on the surface water are yet to be ascertained and quantified. This research attempted to use a comprehensive approach to examine the hydrologic effects of land use at both a regional and a local scale. Statistical and spatial analyses were employed to examine the statistical and spatial relationships of land use and the flow and water quality in receiving waters on a regional scale in the State of Ohio. Besides, a widely accepted watershed-based water quality assessment tool, the Better Assessment Science Integrating Point and Nonpoint Sources (BASINS), was adopted to model the plausible effects of land use on water quality in a local watershed in the East Fork Little Miami River Basin. The results from the statistical analyses revealed that there was a significant relationship between land use and in-stream water quality, especially for nitrogen, phosphorus and Fecal coliform. The geographic information systems (GIS) spatial analyses identified the watersheds that have high levels of contaminants and percentages of agricultural and urban lands. Furthermore, the hydrologic and water quality modeling showed that agricultural and impervious urban lands produced a much higher level of nitrogen and phosphorus than other land surfaces. From this research, it seems that the approach adopted in this study is comprehensive, covering both the regional and local scales. It also reveals that BASINS is a very useful and reliable tool, capable of characterizing the flow and water quality conditions for the study area under different watershed scales. With little modification, these models should be able to adapt to other watersheds or to simulate other contaminants. They also can be used to study the plausible impacts of global environmental change. In addition, the information on the hydrologic

  15. Influence of Land-Surface Roughness on Atmospheric Circulation and Rainfall: A Sensitivity Study with a GCM

    NASA Technical Reports Server (NTRS)

    Sud, Y. C.; Shukla, J.; Mintz, Y.

    1985-01-01

    The sensitivity of atmospheric circulation to the surface roughness of land was studied. The study suggests that land-surface roughness is an important parameter. It is concluded that future simulations of weather and climate should be made with global circulation models that include a suitable parameterization of the vegetation on land.

  16. Modeling Global Change in Local Places: Capturing Global Change and Local Impacts in a Global Land System Change Model

    NASA Astrophysics Data System (ADS)

    Verburg, P.; Eitelberg, D.; Ornetsmueller, C.; van Vliet, J.

    2015-12-01

    Global land use models are driven by demands for food and urban space. However, at the same time many transitions in land use and land cover are driven by societal changes and the demand for a wide range of landscape functions or ecosystem services, including the conservation of biodiversity, regulation of climate and floods, and recreation. Some of these demands lead to tele-connected land use change through the transport of good and services, others are place-based and shape the local realities of land system change. Most current land use change models focus on land cover changes alone and ignore the importance of changes in land management and landscape configuration that affect climate, biodiversity and the provisioning of ecosystem services. This talk will present an alternative approach to global land use modelling based on the simulation of changes in land systems in response to a wide set of ecosystem service demands. Simulations at global scale illustrate that accounting for demands for livestock products, carbon sequestration and biological conservation (following the Aichi targets) leads to different outcomes of land change models and allows the identification of synergies between carbon and biodiversity targets. An application in Laos indicates the complex transitions in land systems and landscapes that occur upon the transition from shifting cultivation to permanent agriculture and tree-crop plantations. We discuss the implications of such land system representations for Earth system modelling.

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  18. MEaSUREs Land Surface Temperature from GOES Satellites

    NASA Astrophysics Data System (ADS)

    Pinker, Rachel T.; Chen, Wen; Ma, Yingtao; Islam, Tanvir; Borbas, Eva; Hain, Chris; Hulley, Glynn; Hook, Simon

    2017-04-01

    Information on Land Surface Temperature (LST) can be generated from observations made from satellites in low Earth orbit (LEO) such as MODIS and ASTER and by sensors in geostationary Earth orbit (GEO) such as GOES. Under a project titled: "A Unified and Coherent Land Surface Temperature and Emissivity Earth System Data Record for Earth Science" led by Jet Propulsion Laboratory, an effort is underway to develop long term consistent information from both such systems. In this presentation we will describe an effort to derive LST information from GOES satellites. Results will be presented from two approaches: 1) based on regression developed from a wide range of simulations using MODTRAN, SeeBor Version 5.0 global atmospheric profiles and the CAMEL (Combined ASTER and MODIS Emissivity for Land) product based on the standard University of Wisconsin 5 km emissivity values (UWIREMIS) and the ASTER Global Emissivity Database (GED) product; 2) RTTOV radiative transfer model driven with MERRA-2 reanalysis fields. We will present results of evaluation of these two methods against various products, such as MOD11, and ground observations for the five year period of (2004-2008).

  19. Use of AMSR-E microwave satellite data for land surface characteristics and snow cover variation.

    PubMed

    Boori, Mukesh Singh; Ferraro, Ralph R; Choudhary, Komal; Kupriyanov, Alexander

    2016-12-01

    This data article contains data related to the research article entitled "Global land cover classification based on microwave polarization and gradient ratio (MPGR)" [1] and "Microwave polarization and gradient ratio (MPGR) for global land surface phenology" [2]. This data article presents land surface characteristics and snow cover variation information from sensors like EOS Advanced Microwave Scanning Radiometer (AMSR-E). This data article use the HDF Explorer, Matlab, and ArcGIS software to process the pixel latitude, longitude, snow water equivalent (SWE), digital elevation model (DEM) and Brightness Temperature (BT) information from AMSR-E satellite data to provide land surface characteristics and snow cover variation data in all-weather condition at any time. This data information is useful to discriminate different land surface cover types and snow cover variation, which is turn, will help to improve monitoring of weather, climate and natural disasters.

  20. Global land cover products tailored to the needs of the climate modeling community - Land Cover project of the ESA Climate Change Initiative

    NASA Astrophysics Data System (ADS)

    Bontemps, S.; Defourny, P.; Radoux, J.; Kalogirou, V.; Arino, O.

    2012-04-01

    Improving the systematic observation of land cover, as an Essential Climate Variable, will support the United Framework Convention on Climate Change effort to reduce the uncertainties in our understanding of the climate system and to better cope with climate change. The Land Cover project of the ESA Climate Change Initiative aims at contributing to this effort by providing new global land cover products tailored to the expectations of the climate modeling community. During the first three months of the project, consultation mechanisms were established with this community to identify its specific requirements in terms of satellite-based global land cover products. This assessment highlighted specific needs in terms of land cover characterization, accuracy of products, as well as stability and consistency, needs that are currently not met or even addressed. Based on this outcome, the project revisits the current land cover representation and mapping approaches. First, the stable and dynamic components of land cover are distinguished. The stable component refers to the set of land surface features that remains stable over time and thus defines the land cover independently of any sources of temporary or natural variability. Conversely, the dynamic component is directly related to this temporary or natural variability that can induce some variation in land observation over time but without changing the land cover state in its essence (e.g. flood, snow on forest, etc.). Second, the project focuses on the possibility to generate such stable global land cover maps. Previous projects, like GlobCover and MODIS Land Cover, have indeed shown that products' stability is a key issue. In delivering successive global products derived from the same sensor, they highlighted the existence of spurious year-to-year variability in land cover labels, which were not associated with land cover change but with phenology, disturbances or landscape heterogeneity. An innovative land cover

  1. Timescales of Land Surface Evapotranspiration Response

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

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

  2. Land cover change impacts on surface ozone: an observation-based study

    NASA Astrophysics Data System (ADS)

    Zhang, Yi; Lin, Jintai

    2016-04-01

    Ozone air quality is a critical global environmental issue. Although it is clear that industrialization and urbanization has increased surface ozone through enhanced emissions of its precursors, much less is known about the role of changes in land cover and land use. Human activities have substantially altered the global land cover and land use through agriculture, urbanization, deforestation, and afforestation. Changes in Land cover and land use affect the ozone levels by altering soil emissions of nitrogen oxides (NOx), biogenic emissions of volatile organic compounds (VOCs), and dry deposition of ozone itself. This study performs a series of experiments with a chemical transport model based on satellite observation of land types to analyze the influences of changes in land cover/land use and their impact on surface ozone concentration. Our results indicate that land cover change explains 1-2 ppbv of summertime surface ozone increase in the Western United States and 1-6 ppbv of increase in Southern China between 2001 and 2012. This is largely driven by enhanced isoprene emissions and soil NOx emissions. It is also found that land cover change itself elevates summertime surface zone in Canadian coniferous forests by up to 4 ppbv mainly through substantial decreases in ozone dry deposition associated with increased vegetation density in a warmer climate.

  3. The generation of China land surface datasets for CLM

    NASA Astrophysics Data System (ADS)

    Li, Haiying; Peng, Hongchun; Li, Xin; Veroustraete, Frank

    2005-10-01

    Community land model or common land model (CLM) describes the exchange of the fluxes of energy, mass and momentum between the earth's surface and the planetary boundary layer. This model is used to simulate the environmental changes in China. Hence, it requires a complete parameters field of the land surface. The present paper focuses on making the surface datasets of CLM in China. In the present paper, vegetation was divided into 39 Plant Function Types (PFTs) of China from its classification map. The land surface datasets were created using vegetation type, five land cover types (lake, wetland, glacier, urban and vegetated), monthly maximum Normalized Difference Vegetation Index (NDVI) derived from SPOT_VGT data and soil properties data. The percentages of glacier, lake and wetland were derived from their own vector maps of China. The fractional coverage of PFTs was derived from China vegetation map. Time-independent vegetation biophysical parameters, such as canopy top and bottom heights and other vegetation parameters related to photosynthesis, were based on the values documented in literatures. The soil color dataset was derived from landuse and vegetation data based on their correspondent relationship. The soil texture (clay%, sand% and silt%) came from global dataset. Time-dependent vegetation biophysical parameters, such as leaf area index(LAI) and fractional absorbed photosynthetically active radiation(FPAR), were calculated from one year of NDVI monthly maximum value composites for the China region based on equations given in Sellers et al. (1996a,b) and Los et al. (2000). The resolution of these datasets for CLM is 1km.

  4. Estimating the Mean Annual Surface Air Temperature at Armagh Observatory, Northern Ireland, and the Global Land-Ocean Temperature Index for Sunspot Cycle 24, the Current Ongoing Sunspot Cycle

    NASA Technical Reports Server (NTRS)

    Wilson, Robert M.

    2013-01-01

    surface air temperature (ASAT) and the Global Land-Ocean Temperature Index (GLOTI) in relation to SSN and the SC in order to determine their likely values during SC24. Hence, it may provide insight as to whether solar forcing of global temperature is now lessening as a contributor to global warming, thereby indicating a possible cooling in the near term immediate future that potentially could ameliorate the effect of increased anthropogenic warming.

  5. The reliability of global and hemispheric surface temperature records

    NASA Astrophysics Data System (ADS)

    Jones, Philip

    2016-03-01

    The purpose of this review article is to discuss the development and associated estimation of uncertainties in the global and hemispheric surface temperature records. The review begins by detailing the groups that produce surface temperature datasets. After discussing the reasons for similarities and differences between the various products, the main issues that must be addressed when deriving accurate estimates, particularly for hemispheric and global averages, are then considered. These issues are discussed in the order of their importance for temperature records at these spatial scales: biases in SST data, particularly before the 1940s; the exposure of land-based thermometers before the development of louvred screens in the late 19th century; and urbanization effects in some regions in recent decades. The homogeneity of land-based records is also discussed; however, at these large scales it is relatively unimportant. The article concludes by illustrating hemispheric and global temperature records from the four groups that produce series in near-real time.

  6. Desertification, land use, and the transformation of global drylands

    USGS Publications Warehouse

    Bestelmeyer, Brandon T.; Okin, Gregory S.; Duniway, Michael C.; Archer, Steven R.; Sayre, Nathan F.; Williamson, Jebediah C.; Herrick, Jeffrey E.

    2015-01-01

    Desertification is an escalating concern in global drylands, yet assessments to guide management and policy responses are limited by ambiguity concerning the definition of “desertification” and what processes are involved. To improve clarity, we propose that assessments of desertification and land transformation be placed within a state change–land-use change (SC–LUC) framework. This framework considers desertification as state changes occurring within the context of particular land uses (eg rangeland, cropland) that interact with land-use change. State changes that can be readily reversed are distinguished from regime shifts, which are state changes involving persistent alterations to vegetation or soil properties. Pressures driving the transformation of rangelands to other types of land uses may be low, fluctuating, or high, and may influence and be influenced by state change. We discuss how the SC–LUC perspective can guide more effective assessment of desertification and management of drylands.

  7. Understanding Land-Atmosphere Interaction in the NCEP Global Forecast System

    NASA Astrophysics Data System (ADS)

    Zheng, W.; Ek, M. B.; Mitchell, K.

    2016-12-01

    The accurate representation of land-atmosphere processes and interactions in numerical models is regarded as the key for improving numerical weather and climate prediction and a challenging task owing to the multiplicity of the related physical processes and their complex interactions. In this presentation, the National Centers for Environmental Prediction (NCEP) global single column model (SCM) coupled with Noah land surface model (LSM) was used to explore the land-atmosphere processes and interactions with the approaches of Diurnal Land/Atmosphere Coupling Experiment (DICE) and GEWEX Atmospheric Boundary Layer Study (GABLS) 4. The NCEP SCM has 64 vertical levels, and the physical package includes a non-local mixing scheme with stratocumulus-top-driven turbulence mixing. The Noah LSM includes one-layer snow scheme. The performance of boundary layer, surface fluxes and surface fields is investigated. Results from these experiments will be presented.

  8. Recent advances in land data assimilation at the NASA Global Modeling and Assimilation Office

    USDA-ARS?s Scientific Manuscript database

    Research in land surface data assimilation has grown rapidly over the last decade. We provide a brief overview of key research contributions by the NASA Global Modeling and Assimilation Office (GMAO). The GMAO contributions primarily include the continued development and application of the Ensembl...

  9. The potential of land management to decrease global warming from climate change

    NASA Astrophysics Data System (ADS)

    Mayer, A.; Hausfather, Z.; Jones, A. D.; Silver, W. L.

    2016-12-01

    Recent evidence suggests that negative emissions (i.e. sequestration) is critical to slow climate change (IPCC, 2013; Gasser et al, 2015). Agricultural (crop and grazing) lands have the potential to act as a significant carbon sink. These ecosystems cover a significant proportion of the global land surface, and are largely degraded with regard to soil carbon due to previous management practices (Bai et al, 2008). However, few studies have examined the required scale of land management interventions that would be required to make a significant contribution to a portfolio of efforts aimed at limiting anthropogenic influences on global mean temperature. To address this, we modelled the quantitative effect of a range of soil carbon sequestration rates on global temperature to 2100. Results showed that by assuming a baseline emissions scenario outlined in RCP 2.6, the sequestration of an additional 0.7 Pg C per year through improved agricultural land management practices would produce a reduction of 0.1 degrees C from predicted global temperatures by the year 2100. We also compiled previous estimates of global carbon sequestration potential of agricultural soils to compare with our theoretical prediction to determine whether carbon sequestration through existing land management practices has potential to significantly reduce global temperatures. Assuming long-term soil carbon uptake, the combined potential of agricultural land management-based mitigation approaches exceeded 0.25 degrees C warming reduction by the year 2100. However, results were highly sensitive to potential carbon saturation, defined as the maximum threshold for carbon storage in soil. Our results suggest that current land management technologies and available land area exist and could make a measureable impact on warming reduction. Results also highlighted potential carbon saturation as a key gap in knowledge.

  10. Derived Land Surface Emissivity From Suomi NPP CrIS

    NASA Technical Reports Server (NTRS)

    Zhou, Daniel K.; Larar, Allen M.; Liu, Xu

    2012-01-01

    Presented here is the land surface IR spectral emissivity retrieved from the Cross-track Infrared Sounder (CrIS) measurements. The CrIS is aboard the Suomi National Polar-orbiting Partnership (NPP) satellite launched on October 28, 2011. We describe the retrieval algorithm, demonstrate the surface emissivity retrieved with CrIS measurements, and inter-comparison with the Infrared Atmospheric Sounding Interferometer (IASI) emissivity. We also demonstrate that surface emissivity from satellite measurements can be used in assistance of monitoring global surface climate change, as a long-term measurement of IASI and CrIS will be provided by the series of EUMETSAT MetOp and US Joint Polar Satellite System (JPSS) satellites. Monthly mean surface properties are produced using last 5-year IASI measurements. A temporal variation indicates seasonal diversity and El Nino/La Nina effects not only shown on the water but also on the land. Surface spectral emissivity and skin temperature from current and future operational satellites can be utilized as a means of long-term monitoring of the Earth's environment. CrIS spectral emissivity are retrieved and compared with IASI. The difference is small and could be within expected retrieval error; however it is under investigation.

  11. GLEAM version 3: Global Land Evaporation Datasets and Model

    NASA Astrophysics Data System (ADS)

    Martens, B.; Miralles, D. G.; Lievens, H.; van der Schalie, R.; de Jeu, R.; Fernandez-Prieto, D.; Verhoest, N.

    2015-12-01

    Terrestrial evaporation links energy, water and carbon cycles over land and is therefore a key variable of the climate system. However, the global-scale magnitude and variability of the flux, and the sensitivity of the underlying physical process to changes in environmental factors, are still poorly understood due to limitations in in situ measurements. As a result, several methods have risen to estimate global patterns of land evaporation from satellite observations. However, these algorithms generally differ in their approach to model evaporation, resulting in large differences in their estimates. One of these methods is GLEAM, the Global Land Evaporation: the Amsterdam Methodology. GLEAM estimates terrestrial evaporation based on daily satellite observations of meteorological variables, vegetation characteristics and soil moisture. Since the publication of the first version of the algorithm (2011), the model has been widely applied to analyse trends in the water cycle and land-atmospheric feedbacks during extreme hydrometeorological events. A third version of the GLEAM global datasets is foreseen by the end of 2015. Given the relevance of having a continuous and reliable record of global-scale evaporation estimates for climate and hydrological research, the establishment of an online data portal to host these data to the public is also foreseen. In this new release of the GLEAM datasets, different components of the model have been updated, with the most significant change being the revision of the data assimilation algorithm. In this presentation, we will highlight the most important changes of the methodology and present three new GLEAM datasets and their validation against in situ observations and an alternative dataset of terrestrial evaporation (ERA-Land). Results of the validation exercise indicate that the magnitude and the spatiotemporal variability of the modelled evaporation agree reasonably well with the estimates of ERA-Land and the in situ

  12. Contextualizing the global relevance of local land change observations

    NASA Astrophysics Data System (ADS)

    Magliocca, N. R.; Ellis, E. C.; Oates, T.; Schmill, M.

    2014-02-01

    To understand global changes in the Earth system, scientists must generalize globally from observations made locally and regionally. In land change science (LCS), local field-based observations are costly and time consuming, and generally obtained by researchers working at disparate local and regional case-study sites chosen for different reasons. As a result, global synthesis efforts in LCS tend to be based on non-statistical inferences subject to geographic biases stemming from data limitations and fragmentation. Thus, a fundamental challenge is the production of generalized knowledge that links evidence of the causes and consequences of local land change to global patterns and vice versa. The GLOBE system was designed to meet this challenge. GLOBE aims to transform global change science by enabling new scientific workflows based on statistically robust, globally relevant integration of local and regional observations using an online social-computational and geovisualization system. Consistent with the goals of Digital Earth, GLOBE has the capability to assess the global relevance of local case-study findings within the context of over 50 global biophysical, land-use, climate, and socio-economic datasets. We demonstrate the implementation of one such assessment - a representativeness analysis - with a recently published meta-study of changes in swidden agriculture in tropical forests. The analysis provides a standardized indicator to judge the global representativeness of the trends reported in the meta-study, and a geovisualization is presented that highlights areas for which sampling efforts can be reduced and those in need of further study. GLOBE will enable researchers and institutions to rapidly share, compare, and synthesize local and regional studies within the global context, as well as contributing to the larger goal of creating a Digital Earth.

  13. 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

    2017-06-01

    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.

  14. 25 CFR 226.19 - Use of surface of land.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 25 Indians 1 2010-04-01 2010-04-01 false Use of surface of land. 226.19 Section 226.19 Indians... LANDS FOR OIL AND GAS MINING Operations § 226.19 Use of surface of land. (a) Lessee or his/her authorized representative shall have the right to use so much of the surface of the land within the...

  15. 25 CFR 226.19 - Use of surface of land.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 25 Indians 1 2013-04-01 2013-04-01 false Use of surface of land. 226.19 Section 226.19 Indians... LANDS FOR OIL AND GAS MINING Operations § 226.19 Use of surface of land. (a) Lessee or his/her authorized representative shall have the right to use so much of the surface of the land within the Osage...

  16. Relative Efficiency of Surface Energy Budgets Over Different Land Covers

    NASA Astrophysics Data System (ADS)

    Yang, Jiachuan

    The partitioning of available solar energy into different fluxes at the Earth's surface is important in determining different physical processes, such as turbulent transport, subsurface hydrology, land-atmospheric interactions, etc. Direct measurements of these turbulent fluxes were carried out using eddy-covariance (EC) towers. However, the distribution of EC towers is sparse due to relatively high cost and practical difficulties in logistics and deployment. As a result, data is temporally and spatially limited and is inadequate to be used for researches at large scales, such as regional and global climate modeling. Besides field measurements, an alternative way is to estimate turbulent fluxes based on the intrinsic relations between surface energy budget components, largely through thermodynamic equilibrium. These relations, referred as relative efficiency, have been included in several models to estimate the magnitude of turbulent fluxes in surface energy budgets such as latent heat and sensible heat. In this study, three theoretical models based on the lumped heat transfer model, the linear stability analysis and the maximum entropy principle respectively, were investigated. Model predictions of relative efficiencies were compared with turbulent flux data over different land covers, viz. lake, grassland and suburban surfaces. Similar results were observed over lake and suburban surface but significant deviation is found over vegetation surface. The relative efficiency of outgoing longwave radiation is found to be orders of magnitude deviated from theoretic predictions. Meanwhile, results show that energy partitioning process is influenced by the surface water availability to a great extent. The study provides insight into what property is determining energy partitioning process over different land covers and gives suggestion for future models.

  17. Spatially Complete Surface Albedo Data Sets: Value-Added Products Derived from Terra MODIS Land Products

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

    Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent observations of diffuse bihemispherical (white-sky) and direct beam directional hemispherical (black-sky ) land surface albedo included in the MOD43B3 product from MODIS instruments aboard NASA's Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal characteristics. Cloud and seasonal snow cover, however, curtail retrievals to approximately half the global land surfaces on an annual equal-angle basis, precluding MOD43B3 albedo products from direct inclusion in some research projects and production environments.

  18. Spatially Complete Surface Albedo Data Sets: Value-Added Products Derived from Terra MODIS Land Products

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

    Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent observations of diffuse bihemispherical (white-sky) and direct beam directional hemispherical (black-sky ) land surface albedo included in the MOD43B3 product from MODIS instruments aboard NASA's Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal characteristics. Cloud and seasonal snow cover, however, curtail retrievals to approximately half the global land surfaces on an annual equal-angle basis, precluding MOD43B3 albedo products from direct inclusion in some research projects and production environments.

  19. Terrestrial Ecosystems - Land Surface Forms of the Conterminous United States

    USGS Publications Warehouse

    Cress, Jill J.; Sayre, Roger G.; Comer, Patrick; Warner, Harumi

    2009-01-01

    As part of an effort to map terrestrial ecosystems, the U.S. Geological Survey has generated land surface form classes to be used in creating maps depicting standardized, terrestrial ecosystem models for the conterminous United States, using an ecosystems classification developed by NatureServe . A biophysical stratification approach, developed for South America and now being implemented globally, was used to model the ecosystem distributions. Since land surface forms strongly influence the differentiation and distribution of terrestrial ecosystems, they are one of the key input layers in this biophysical stratification. After extensive investigation into various land surface form mapping methodologies, the decision was made to use the methodology developed by the Missouri Resource Assessment Partnership (MoRAP). MoRAP made modifications to Hammond's land surface form classification, which allowed the use of 30-meter source data and a 1-km2 window for analyzing the data cell and its surrounding cells (neighborhood analysis). While Hammond's methodology was based on three topographic variables, slope, local relief, and profile type, MoRAP's methodology uses only slope and local relief. Using the MoRAP method, slope is classified as gently sloping when more than 50 percent of the area in a 1-km2 neighborhood has slope less than 8 percent, otherwise the area is considered moderately sloping. Local relief, which is the difference between the maximum and minimum elevation in a neighborhood, is classified into five groups: 0-15 m, 16-30 m, 31-90 m, 91-150 m, and >150 m. The land surface form classes are derived by combining slope and local relief to create eight landform classes: flat plains (gently sloping and local relief = 90 m), low hills (not gently sloping and local relief = 150 m). However, in the USGS application of the MoRAP methodology, an additional local relief group was used (> 400 m) to capture additional local topographic variation. As a result, low

  20. Toward Transfer Functions for Land Surface Phenologies

    NASA Astrophysics Data System (ADS)

    Henebry, G. M.

    2010-12-01

    A key problem in projecting future landscapes is simulating the associated land surface phenologies (or LSPs). A recent study of land surface models concluded that the representations of crop phenologies among the models diverged sufficiently to impede a useful intercomparison of simulation results from their associated climate models. Grassland phenologies are far more complicated than cropland phenologies due to multiple forcing factors, photosynthetic pathways (C3 vs C4), and spatial heterogeneities in both resource availabilities and land management practices. Furthermore, many tallgrass species (such as switchgrass) are widely distributed across temperature, but not moisture, gradients, resulting in significant ecotypic variation across the species' geographic range. Thus, how feasible is "transplanting" tallgrass LSPs across isotherms—but along isohyets—to simulate a shift in cultivation from maize-soy to switchgrass? Prior work has shown a quadratic model can provide a parsimonious link between a Normalized Difference Vegetation Index (or NDVI) time series and thermal time, measured in terms of accumulated growing degree-days (or AGDD). Moreover, the thermal time to peak NDVI (or TTP) is a simple function of the parameter coefficients of fitted model. I fitted quadratic models to MODIS NDVI and weather station data at multiple sites across the Northern Great Plains over ten growing seasons, 2000-2009. There is a strong latitudinal gradient in TTP that results in part from a quasi-linear gradient in accumulated daylight hours (or ADH) between 30 and 50 degrees north. However, AGDD improves upon ADH by providing sensitivity to the variability of growing season weather. In the quadratic parameter coefficients there is a geographic pattern apparent as a function of TTP, although it is more variable at shorter TTPs. Using these patterns, an LSP transfer function was implemented along a latitudinal transect to simulate switchgrass cultivation in areas now

  1. ENVISAT Land Surface Processes. Phase 2

    NASA Technical Reports Server (NTRS)

    vandenHurk, B. J. J. M.; Su, Z.; Verhoef, W.; Menenti, M.; Li, Z.-L.; Wan, Z.; Moene, A. F.; Roerink, G.; Jia, I.

    2002-01-01

    This is a progress report of the 2nd phase of the project ENVISAT- Land Surface Processes, which has a 3-year scope. In this project, preparative research is carried out aiming at the retrieval of land surface characteristics from the ENVISAT sensors MERIS and AATSR, for assimilation into a system for Numerical Weather Prediction (NWP). Where in the 1st phase a number of first shot experiments were carried out (aiming at gaining experience with the retrievals and data assimilation procedures), the current 2nd phase has put more emphasis on the assessment and improvement of the quality of the retrieved products. The forthcoming phase will be devoted mainly to the data assimilation experiments and the assessment of the added value of the future ENVISAT products for NWP forecast skill. Referring to the retrieval of albedo, leaf area index and atmospheric corrections, preliminary radiative transfer calculations have been carried out that should enable the retrieval of these parameters once AATSR and MERIS data become available. However, much of this work is still to be carried out. An essential part of work in this area is the design and implementation of software that enables an efficient use of MODTRAN(sub 4) radiative transfer code, and during the current project phase familiarization with these new components has been achieved. Significant progress has been made with the retrieval of component temperatures from directional ATSR-images, and the calculation of surface turbulent heat fluxes from these data. The impact of vegetation cover on the retrieved component temperatures appears manageable, and preliminary comparison of foliage temperature to air temperatures were encouraging. The calculation of surface fluxes using the SEBI concept,which includes a detailed model of the surface roughness ratio, appeared to give results that were in reasonable agreement with local measurements with scintillometer devices. The specification of the atmospheric boundary conditions

  2. ENVISAT Land Surface Processes. Phase 2

    NASA Technical Reports Server (NTRS)

    vandenHurk, B. J. J. M.; Su, Z.; Verhoef, W.; Menenti, M.; Li, Z.-L.; Wan, Z.; Moene, A. F.; Roerink, G.; Jia, I.

    2002-01-01

    This is a progress report of the 2nd phase of the project ENVISAT- Land Surface Processes, which has a 3-year scope. In this project, preparative research is carried out aiming at the retrieval of land surface characteristics from the ENVISAT sensors MERIS and AATSR, for assimilation into a system for Numerical Weather Prediction (NWP). Where in the 1st phase a number of first shot experiments were carried out (aiming at gaining experience with the retrievals and data assimilation procedures), the current 2nd phase has put more emphasis on the assessment and improvement of the quality of the retrieved products. The forthcoming phase will be devoted mainly to the data assimilation experiments and the assessment of the added value of the future ENVISAT products for NWP forecast skill. Referring to the retrieval of albedo, leaf area index and atmospheric corrections, preliminary radiative transfer calculations have been carried out that should enable the retrieval of these parameters once AATSR and MERIS data become available. However, much of this work is still to be carried out. An essential part of work in this area is the design and implementation of software that enables an efficient use of MODTRAN(sub 4) radiative transfer code, and during the current project phase familiarization with these new components has been achieved. Significant progress has been made with the retrieval of component temperatures from directional ATSR-images, and the calculation of surface turbulent heat fluxes from these data. The impact of vegetation cover on the retrieved component temperatures appears manageable, and preliminary comparison of foliage temperature to air temperatures were encouraging. The calculation of surface fluxes using the SEBI concept,which includes a detailed model of the surface roughness ratio, appeared to give results that were in reasonable agreement with local measurements with scintillometer devices. The specification of the atmospheric boundary conditions

  3. NOAA AVHRR Land Surface Albedo Algorithm Development

    NASA Technical Reports Server (NTRS)

    Toll, D. L.; Shirey, D.; Kimes, D. S.

    1997-01-01

    The primary objective of this research is to develop a surface albedo model for the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR). The primary test site is the Konza prairie, Kansas (U.S.A.), used by the International Satellite Land Surface Climatology Project (ISLSCP) in the First ISLSCP Field Experiment (FIFE). In this research, high spectral resolution field spectrometer data was analyzed to simulate AVHRR wavebands and to derive surface albedos. Development of a surface albedo algorithm was completed by analysing a combination of satellite, field spectrometer, and ancillary data. Estimated albedos from the field spectrometer data were compared to reference albedos derived using pyranometer data. Variations from surface anisotropy of reflected solar radiation were found to be the most significant albedo-related error. Additional error or sensitivity came from estimation of a shortwave mid-IR reflectance (1.3-4.0 micro-m) using the AVHRR red and near-IR bands. Errors caused by the use of AVHRR spectral reflectance to estimate both a total visible (0.4-0.7 micro-m) and near-IR (0.7-1.3 micro-m) reflectance were small. The solar spectral integration, using the derived ultraviolet, visible, near-IR and SW mid-IR reflectivities, was not sensitive to many clear-sky changes in atmospheric properties and illumination conditions.

  4. Contributions of projected land use to global radiative forcing ascribed to local sources

    NASA Astrophysics Data System (ADS)

    Ward, D. S.; Mahowald, N. M.; Kloster, S.

    2013-12-01

    With global demand for food expected to dramatically increase and put additional pressures on natural lands, there is a need to understand the environmental impacts of land use and land cover change (LULCC). Previous studies have shown that the magnitude and even the sign of the radiative forcing (RF) of biogeophysical effects from LULCC depends on the latitude and forest ecology of the disturbed region. Here we ascribe the contributions to the global RF by land-use related anthropogenic activities to their local sources, organized on a grid of 1.9 degrees latitude by 2.5 degrees longitude. We use RF estimates for the year 2100, using five future LULCC projections, computed from simulations with the National Center for Atmospheric Research Community Land Model and Community Atmosphere Models and additional offline analyses. Our definition of the LULCC RF includes changes to terrestrial carbon storage, methane and nitrous oxide emissions, atmospheric chemistry, aerosol emissions, and surface albedo. We ascribe the RF to gridded locations based on LULCC-related emissions of relevant trace gases and aerosols, including emissions from fires. We find that the largest contributions to the global RF in year 2100 from LULCC originate in the tropics for all future scenarios. In fact, LULCC is the largest tropical source of anthropogenic RF. The LULCC RF in the tropics is dominated by emissions of CO2 from deforestation and methane emissions from livestock and soils. Land surface albedo change is rarely the dominant forcing agent in any of the future LULCC projections, at any location. By combining the five future scenarios we find that deforested area at a specific tropical location can be used to predict the contribution to global RF from LULCC at that location (the relationship does not hold as well in the extratropics). This information could support global efforts like REDD (Reducing Emissions from Deforestation and Forest Degradation), that aim to reduce greenhouse gas

  5. A comparative analysis of the Global Land Cover 2000 and MODIS land cover data sets

    USGS Publications Warehouse

    Giri, C.; Zhu, Z.; Reed, B.

    2005-01-01

    Accurate and up-to-date global land cover data sets are necessary for various global change research studies including climate change, biodiversity conservation, ecosystem assessment, and environmental modeling. In recent years, substantial advancement has been achieved in generating such data products. Yet, we are far from producing geospatially consistent high-quality data at an operational level. We compared the recently available Global Land Cover 2000 (GLC-2000) and MODerate resolution Imaging Spectrometer (MODIS) global land cover data to evaluate the similarities and differences in methodologies and results, and to identify areas of spatial agreement and disagreement. These two global land cover data sets were prepared using different data sources, classification systems, and methodologies, but using the same spatial resolution (i.e., 1 km) satellite data. Our analysis shows a general agreement at the class aggregate level except for savannas/shrublands, and wetlands. The disagreement, however, increases when comparing detailed land cover classes. Similarly, percent agreement between the two data sets was found to be highly variable among biomes. The identified areas of spatial agreement and disagreement will be useful for both data producers and users. Data producers may use the areas of spatial agreement for training area selection and pay special attention to areas of disagreement for further improvement in future land cover characterization and mapping. Users can conveniently use the findings in the areas of agreement, whereas users might need to verify the informaiton in the areas of disagreement with the help of secondary information. Learning from past experience and building on the existing infrastructure (e.g., regional networks), further research is necessary to (1) reduce ambiguity in land cover definitions, (2) increase availability of improved spatial, spectral, radiometric, and geometric resolution satellite data, and (3) develop advanced

  6. A blended land emissivity product from the Inter-Comparison of different Land Surface Emissivity Estimates

    NASA Astrophysics Data System (ADS)

    Norouzi, H.; Temimi, M.; Khanbilvardi, R.

    2012-12-01

    Passive microwave observations are routinely used to estimate rain rate, cloud liquid water, and total precipitable water. In order to have accurate estimations from microwave, the contribution of the surface should be accounted for. Over land, due to the complex interaction between the microwave signal and the soil surface, retrieval of land surface emissivity and other surface and subsurface parameters is not straightforward. Several microwave emissivity products from various microwave sensors have been proposed. However, lack of ground truth measurements makes the validation of these products difficult. This study aims to inter-compare several available emissivity products over land and ultimately proposes a unique blended product that overcomes the flaws of each individual product. The selected products are based on observations from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), the Special Sensor Microwave Imager (SSM/I), the Advanced Microwave Sounding unit (AMSU), and the Special Sensor Microwave Imager/Sounder (SSMIS). In retrieval of emissivities from these sensors different methods and ancillary data have been used. Some inherent discrepancies between the selected products can be introduced by as the difference in geometry in terms of incident angle, spectral response, and the foot print size which can affect the estimations. Moreover, ancillary data especially skin temperature and cloud mask cover can cause significant discrepancies between various estimations. The time series and correlation between emissivity maps are explored to assess the consistency of emissivity variations with geophysical variable such as snow, precipitation and drought. Preliminary results reveal that inconsistency between products varies based on land cover type due to penetration depth effect and ancillary data. Six years of estimations are employed in this research study, and a global blended emissivity estimations based on all product with minimal discrepancies

  7. 25 CFR 214.14 - Use of surface lands.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 25 Indians 1 2012-04-01 2011-04-01 true Use of surface lands. 214.14 Section 214.14 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR ENERGY AND MINERALS LEASING OF OSAGE RESERVATION LANDS, OKLAHOMA, FOR MINING, EXCEPT OIL AND GAS § 214.14 Use of surface lands. (a) Lessees may use so much of the...

  8. Global change pressures on soils from land use and management.

    PubMed

    Smith, Pete; House, Joanna I; Bustamante, Mercedes; Sobocká, Jaroslava; Harper, Richard; Pan, Genxing; West, Paul C; Clark, Joanna M; Adhya, Tapan; Rumpel, Cornelia; Paustian, Keith; Kuikman, Peter; Cotrufo, M Francesca; Elliott, Jane A; McDowell, Richard; Griffiths, Robert I; Asakawa, Susumu; Bondeau, Alberte; Jain, Atul K; Meersmans, Jeroen; Pugh, Thomas A M

    2016-03-01

    Soils are subject to varying degrees of direct or indirect human disturbance, constituting a major global change driver. Factoring out natural from direct and indirect human influence is not always straightforward, but some human activities have clear impacts. These include land-use change, land management and land degradation (erosion, compaction, sealing and salinization). The intensity of land use also exerts a great impact on soils, and soils are also subject to indirect impacts arising from human activity, such as acid deposition (sulphur and nitrogen) and heavy metal pollution. In this critical review, we report the state-of-the-art understanding of these global change pressures on soils, identify knowledge gaps and research challenges and highlight actions and policies to minimize adverse environmental impacts arising from these global change drivers. Soils are central to considerations of what constitutes sustainable intensification. Therefore, ensuring that vulnerable and high environmental value soils are considered when protecting important habitats and ecosystems, will help to reduce the pressure on land from global change drivers. To ensure that soils are protected as part of wider environmental efforts, a global soil resilience programme should be considered, to monitor, recover or sustain soil fertility and function, and to enhance the ecosystem services provided by soils. Soils cannot, and should not, be considered in isolation of the ecosystems that they underpin and vice versa. The role of soils in supporting ecosystems and natural capital needs greater recognition. The lasting legacy of the International Year of Soils in 2015 should be to put soils at the centre of policy supporting environmental protection and sustainable development. © 2015 John Wiley & Sons Ltd.

  9. Global modeling of land water and energy balances. Part II: Land-characteristic contributions to spatial variability

    USGS Publications Warehouse

    Milly, P.C.D.; Shmakin, A.B.

    2002-01-01

    Land water and energy balances vary around the globe because of variations in amount and temporal distribution of water and energy supplies and because of variations in land characteristics. The former control (water and energy supplies) explains much more variance in water and energy balances than the latter (land characteristics). A largely untested hypothesis underlying most global models of land water and energy balance is the assumption that parameter values based on estimated geographic distributions of soil and vegetation characteristics improve the performance of the models relative to the use of globally constant land parameters. This hypothesis is tested here through an evaluation of the improvement in performance of one land model associated with the introduction of geographic information on land characteristics. The capability of the model to reproduce annual runoff ratios of large river basins, with and without information on the global distribution of albedo, rooting depth, and stomatal resistance, is assessed. To allow a fair comparison, the model is calibrated in both cases by adjusting globally constant scale factors for snow-free albedo, non-water-stressed bulk stomatal resistance, and critical root density (which is used to determine effective root-zone depth). The test is made in stand-alone mode, that is, using prescribed radiative and atmospheric forcing. Model performance is evaluated by comparing modeled runoff ratios with observed runoff ratios for a set of basins where precipitation biases have been shown to be minimal. The withholding of information on global variations in these parameters leads to a significant degradation of the capability of the model to simulate the annual runoff ratio. An additional set of optimization experiments, in which the parameters are examined individually, reveals that the stomatal resistance is, by far, the parameter among these three whose spatial variations add the most predictive power to the model in

  10. Recent decline in the global land evapotranspiration trend due to limited moisture supply.

    PubMed

    Jung, Martin; Reichstein, Markus; Ciais, Philippe; Seneviratne, Sonia I; Sheffield, Justin; Goulden, Michael L; Bonan, Gordon; Cescatti, Alessandro; Chen, Jiquan; de Jeu, Richard; Dolman, A Johannes; Eugster, Werner; Gerten, Dieter; Gianelle, Damiano; Gobron, Nadine; Heinke, Jens; Kimball, John; Law, Beverly E; Montagnani, Leonardo; Mu, Qiaozhen; Mueller, Brigitte; Oleson, Keith; Papale, Dario; Richardson, Andrew D; Roupsard, Olivier; Running, Steve; Tomelleri, Enrico; Viovy, Nicolas; Weber, Ulrich; Williams, Christopher; Wood, Eric; Zaehle, Sönke; Zhang, Ke

    2010-10-21

    More than half of the solar energy absorbed by land surfaces is currently used to evaporate water. Climate change is expected to intensify the hydrological cycle and to alter evapotranspiration, with implications for ecosystem services and feedback to regional and global climate. Evapotranspiration changes may already be under way, but direct observational constraints are lacking at the global scale. Until such evidence is available, changes in the water cycle on land−a key diagnostic criterion of the effects of climate change and variability−remain uncertain. Here we provide a data-driven estimate of global land evapotranspiration from 1982 to 2008, compiled using a global monitoring network, meteorological and remote-sensing observations, and a machine-learning algorithm. In addition, we have assessed evapotranspiration variations over the same time period using an ensemble of process-based land-surface models. Our results suggest that global annual evapotranspiration increased on average by 7.1 ± 1.0 millimetres per year per decade from 1982 to 1997. After that, coincident with the last major El Niño event in 1998, the global evapotranspiration increase seems to have ceased until 2008. This change was driven primarily by moisture limitation in the Southern Hemisphere, particularly Africa and Australia. In these regions, microwave satellite observations indicate that soil moisture decreased from 1998 to 2008. Hence, increasing soil-moisture limitations on evapotranspiration largely explain the recent decline of the global land-evapotranspiration trend. Whether the changing behaviour of evapotranspiration is representative of natural climate variability or reflects a more permanent reorganization of the land water cycle is a key question for earth system science.

  11. Modification of growing-season surface temperature records in the northern great plains due to land-use transformation: verification of modelling results and implication for global climate change

    NASA Astrophysics Data System (ADS)

    Mahmood, Rezaul; Hubbard, Kenneth G.; Carlson, Christy

    2004-03-01

    Land-use and land-cover change can modify near-surface atmospheric condition. Mesoscale modelling studies have shown that modification in land use affects near-surface soil moisture storage and energy balance. Such a study in the Great Plains showed that changes in land use from natural grass to irrigated agriculture enhanced soil water storage in the root zone and increased latent energy flux. This increase in latent energy flux would correspond to a decrease in sensible heat flux and, therefore, modify near-surface temperature records. To verify this deduction, we have investigated the changes in the historical near-surface temperature records in Nebraska, USA. We have analysed the long-term mean monthly maximum, minimum, and monthly mean air temperature data from five irrigated and five non-irrigated sites. The cooperative weather observation (coop) network is the source of the data. We have found that there is a clear trend in decreasing mean maximum and average temperature data for irrigated sites. For example, York, NE, reports that the mean maximum growing season temperature is decreasing at the rate -0.01°C year-1. The results from non-irrigated sites indicated an increasing trend for the same parameters. The data from Halsey, NE, indicate a +0.01°C year-1 increase in this century. In addition, we have conducted similar analyses of temperature data for the National Climatic Data Center's Historical Climatic Network data set for the same locations. The results are similar to that obtained with the coop data set. Further investigation of dew-point temperature records for irrigated and non-irrigated sites also show an increasing and decreasing trend respectively. Therefore, we conclude that the land-use change in the Great Plains has modified near-surface temperature records.

  12. 25 CFR 226.19 - Use of surface of land.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... LANDS FOR OIL AND GAS MINING Operations § 226.19 Use of surface of land. (a) Lessee or his/her... originally drilled under the currently lease. A drilling site shall be held to the minimum area essential for...

  13. Accessing Recent Trend of Land Surface Temperature from Satellite Observations

    NASA Technical Reports Server (NTRS)

    Shen, Suhung; Leptoukh, Gregory G.; Romanov, Peter

    2011-01-01

    Land surface temperature (Ts) is an important element to measure the state of terrestrial ecosystems and to study surface energy budgets. In support of the land cover/land use change-related international program MAIRS (Monsoon Asia Integrated Regional Study), we have collected global monthly Ts measured by MODIS since the beginning of the missions. The MODIS Ts time series have approximately 11 years of data from Terra since 2000 and approximately 9 years of data from Aqua since 2002, which makes possible to study the recent climate, such as trend. In this study, monthly climatology from two platforms are calculated and compared with that from AIRS. The spatial patterns of Ts trends are accessed, focusing on the Eurasia region. Furthermore, MODIS Ts trends are compared with those from AIRS and NASA's atmospheric assimilation model, MERRA (Modern Era Retrospective-analysis for Research and Applications). The preliminary results indicate that the recent 8-year Ts trend shows an oscillation-type spatial variation over Eurasia. The pattern is consistent for data from MODIS, AIRS, and MERRA, with the positive center over Eastern Europe, and the negative center over Central Siberia. The calculated climatology and anomaly of MODIS Ts will be integrated into the online visualization system, Giovanni, at NASA GES DISC for easy use by scientists and general public.

  14. 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).

  15. 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).

  16. Accessing Recent Trend of Land Surface Temperature from Satellite Observations

    NASA Astrophysics Data System (ADS)

    Shen, S.; Leptoukh, G. G.; Romanov, P.

    2011-12-01

    Land surface temperature (LST) is an important element to measure the state of the terrestrial ecosystems and to study the surface energy budgets. In support of the land cover/land use change related international program MAIRS (Monsoon Asia Integrated Regional Study), we have collected the global monthly LST measured by MODIS since the beginning of the missions. The MODIS LST time series have ~11 years of data from Terra since 2000 and ~9 years of data from Aqua since 2002, which makes possible to study the recent climate, such as trend and variability. In this study, monthly climatology from two satellite platforms are calculated and compared. The spatial patterns of LST trends are accessed, focusing on the Asian Monsoon region. Furthermore, the MODIS LST trends are compared with the skin temperature trend from the NASA's atmospheric assimilation model, MERRA (MODERN ERA RETROSPECTIVE-ANALYSIS FOR RESEARCH AND APPLICATIONS), which has longer data record since 1979. The calculated climatology and anomaly of MODIS LST will be integrated into the online visualization system, Giovanni, at NASA GES DISC for easy access and use by scientists and general public.

  17. CEOS Land Surface Imaging Constellation Mid-Resolution Optical Guidelines

    NASA Technical Reports Server (NTRS)

    Keyes, Jennifer P.; Killough, B.

    2011-01-01

    The LSI community of users is large and varied. To reach all these users as well as potential instrument contributors this document has been organized by measurement parameters of interest such as Leaf Area Index and Land Surface Temperature. These measurement parameters and the data presented in this document are drawn from multiple sources, listed at the end of the document, although the two primary ones are "The Space-Based Global Observing System in 2010 (GOS-2010)" that was compiled for the World Meteorological Organization (WMO) by Bizzarro Bizzarri, and the CEOS Missions, Instruments, and Measurements online database (CEOS MIM). For each measurement parameter the following topics will be discussed: (1) measurement description, (2) applications, (3) measurement spectral bands, and (4) example instruments and mission information. The description of each measurement parameter starts with a definition and includes a graphic displaying the relationships to four general land surface imaging user communities: vegetation, water, earth, and geo-hazards, since the LSI community of users is large and varied. The vegetation community uses LSI data to assess factors related to topics such as agriculture, forest management, crop type, chlorophyll, vegetation land cover, and leaf or canopy differences. The water community analyzes snow and lake cover, water properties such as clarity, and body of water delineation. The earth community focuses on minerals, soils, and sediments. The geo-hazards community is designed to address and aid in emergencies such as volcanic eruptions, forest fires, and large-scale damaging weather-related events.

  18. Sub-grid Representation of Snow in Land Surface Models

    NASA Astrophysics Data System (ADS)

    Ganji, Arman; Sushama, Laxmi

    2017-04-01

    Snow depth and fraction in high-latitude landscapes play a key role in defining surface energy and moisture relationships. In light of the role that snow plays in influencing various processes, it is important that the land surface schemes used in weather and climate models accurately represent the spatial variation of snow depth and cover. In this paper, a new sub-grid snow parameterization is proposed for the Canadian Land Surface Scheme (CLASS), which is used in the Canadian regional and global climate models. The sub-grid scheme takes into account elevation, slope and aspect variations within a grid cell and uses a clustering approach to classify sub-grid cells based on elevation, slope and aspect values into groups. The impact of these modifications on the regional hydrology is assessed by comparing two offline simulations, performed with the original and modified versions of CLASS, driven by atmospheric forcing data from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA-Interim), for the 1970-2013 period, over a northwest Canadian domain. Results suggest higher Snow Water Equivalent (SWE) in the simulation with modified CLASS compared to the original version. Also, the simulated SWE using the modified CLASS is in better agreement to SNODAS. Furthermore, the results show that the magnitude of streamflows is improved in the modified model. This study thus demonstrates the added value of sub-grid snow parameterization, as reflected in the realistic simulation of surface hydrologic variables.

  19. Evaluation of global stream flow routing based on gridded run-off fluxes of Global Land Data Assimilation System (GLDAS)

    NASA Astrophysics Data System (ADS)

    Shrestha, R. K.; Xia, Y.; Meng, J.; Dirmeyer, P.; Ek, M. B.

    2014-12-01

    The current Global Land Data Assimilation System (GLDAS) project provides detailed estimates of energy fluxes and water budget, with currently planned upgrades including improved Land Surface Model (LSM) physics, enhanced global meteorological forcing data sets, more robust soil moisture initialization, updated model specific parameter sets and an advanced snow data assimilation scheme. Because of these advancements made in the GLDAS experiment, the spatio-temporal variability of hydrologic fluxes is expected to be as good as other key land-surface fluxes. Gridded surface runoff from GLDAS experiment provides a unique opportunity to implement flow routing along the network of river system. In this experiment, we add stream flow routing in the GLDAS and investigate the stream flow variability using a computationally expensive cell-to-cell (C2C) routing scheme and a simpler source-to-sink (S2S) routing scheme. Appropriate parameterization of C2C is difficult, but it can use a detailed set of parameters, which provide an opportunity to develop a robust and realistic flow routing. On the other hand, the S2S offers simplified and computationally efficient routing solution but it needs periodic adjustments to its parameters. We will present a comparative analysis of these routing experiments, which may be useful for hydrologic estimations in data scarce regions as well as to establish an operational global stream flow prediction system.

  20. Nitrogen Dynamics are a Key Factor in Explaining Global Land Carbon Sink

    NASA Astrophysics Data System (ADS)

    Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.; Ciais, P.; Schaefer, K. M.; King, A. W.; Wei, Y.; Cook, R. B.; Fisher, J. B.; Hayes, D. J.; Huang, M.; Ito, A.; Jain, A. K.; Lei, H.; Lu, C.; Maignan, F.; Mao, J.; Parazoo, N.; Peng, S.; Poulter, B.; Ricciuto, D. M.; Shi, X.; Tian, H.; Wang, W.; Zeng, N.; Zhao, F.

    2015-12-01

    The terrestrial carbon cycle plays a critical role in regulating the amount of anthropogenic emissions that remain in the atmosphere. Yet, land-atmosphere carbon dynamics are one of the largest sources of uncertainty in projections of future climate. Reducing this uncertainty requires understanding the relative role of various drivers to land carbon uptake. We use an ensemble of land surface models to quantify the influence of climate, land use history, atmospheric CO2, and nitrogen deposition on the strength of the net land sink over the past 110 years. Each model can be thought of as one realization of terrestrial carbon cycling and the factors most important in controlling land sink strength. Using a series of sensitivity simulations, we identify the dominant drivers to the net land sink that emerge consistently across models, both globally and regionally. We find that the relative importance of external forcing factors on the strength of net land carbon uptake varies considerably across models and depends strongly on whether nitrogen cycling is explicitly simulated. Models without a nitrogen cycle estimate cumulative land carbon uptake (since 1959) that is 3 times greater (93.3 ± 84.1 PgC) than global mass balance constraints (34.6 ± 41.6 PgC). Surprisingly, the greatest impacts are seen in the tropics, where coupled carbon-nitrogen cycle models estimate CO2 fertilization and climate affects that are ~60% weaker than models without a nitrogen cycle. The results highlight the importance of model structure on the inferred sensitivity of land carbon uptake to external forcing factors. The range in sensitivity across models is important for future climate projections since the differences in the processes that explain trends in net land sink strength between models with and without nitrogen dynamics can lead to very different future trajectories of atmospheric CO2 and thus climate.

  1. Global land and water grabbing for food and bioenergy

    NASA Astrophysics Data System (ADS)

    Rulli, M. C.; D'Odorico, P.

    2014-12-01

    The increasing demand for food, fibers and biofuels, the consequently escalating prices of agricultural products, and the uncertainty of international food markets have recently drawn the attention of governments and corporations toward investments in productive agricultural land, mostly in developing countries. Since 2000 more than 37 million hectares of arable land have been purchased or leased by foreign investors worldwide. The targeted regions are typically located in areas where crop yields are relatively low because of lack of modern technology. It is expected that in the long run large scale investments in agriculture and the consequent development of commercial farming will bring the technology required to close the existing crop yield gaps. Recently, a number of studies and reports have documented the process of foreign land acquisition, while the associated appropriation of land based resources (e.g., water and crops) has remained poorly investigated. The amount of food this land can produce and the number of people it could feed still needs to be quantified. It is also unclear to what extent the acquired land will be used to for biofuel production and the role played by U.S. and E.U. bioenergy policies as drivers of the ongoing land rush. The environmental impacts of these investments in agriculture require adequate investigation. Here we provide a global quantitative assessment of the rates of water and crop appropriation potentially associated with large scale land acquisitions. We evaluate the associated impacts on the food and energy security of both target and investors' countries, and highlight the societal and environmental implications of the land rush phenomenon.

  2. Assimilation of Surface Temperature in Land Surface Models

    NASA Technical Reports Server (NTRS)

    Lakshmi, Venkataraman

    1998-01-01

    Hydrological models have been calibrated and validated using catchment streamflows. However, using a point measurement does not guarantee correct spatial distribution of model computed heat fluxes, soil moisture and surface temperatures. With the advent of satellites in the late 70s, surface temperature is being measured two to four times a day from various satellite sensors and different platforms. The purpose of this paper is to demonstrate use of satellite surface temperature in (a) validation of model computed surface temperatures and (b) assimilation of satellite surface temperatures into a hydrological model in order to improve the prediction accuracy of soil moistures and heat fluxes. The assimilation is carried out by comparing the satellite and the model produced surface temperatures and setting the "true"temperature midway between the two values. Based on this "true" surface temperature, the physical relationships of water and energy balance are used to reset the other variables. This is a case of nudging the water and energy balance variables so that they are consistent with each other and the true" surface temperature. The potential of this assimilation scheme is demonstrated in the form of various experiments that highlight the various aspects. This study is carried over the Red-Arkansas basin in the southern United States (a 5 deg X 10 deg area) over a time period of a year (August 1987 - July 1988). The land surface hydrological model is run on an hourly time step. The results show that satellite surface temperature assimilation improves the accuracy of the computed surface soil moisture remarkably.

  3. Modeling, Calibration, and Sensitivity Analysis of Coupled Land-Surface Models

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Gupta, H. V.; Bastidas, L. A.; Sorooshian, S.

    2002-12-01

    To better understand various land-surface hydrological processes, it is desirable and pressing to extend land-surface modeling from off-line modes to coupled modes to explore the significance of various land surface-atmospheric interactions in regulating the energy and water balance of the hydrologic cycle. While it is extremely difficult to directly test the parameterizations of a global climate model due to the complexity, a locally coupled single-column model provides a favorable environment for investigations into the complicated interactions between the land surface and the overlying atmosphere. In this research, the off-line NCAR LSM and the coupled NCAR Single-column Community Climate Model (NCAR SCCM) are used. Extensive efforts have been focused on the impacts that the coupling of the two systems may have on the sensitivities of the land-surface model to both land-surface parameters and land-surface parameterizations. Additional efforts are directed to the comparisons of results from off-line and coupled calibration experiments using the optimization algorithm MOCOM-UA and IOP data sets from the Atmosphere Radiation Measurement-Cloud and Radiation Testbed (ARM-CART) project. Possibilities of calibrating some atmospheric parameters in the coupled model are also explored. Preliminary results show that the parameterization of surface energy and water balance is crucial in coupled systems and that the land-atmosphere coupling can significantly affect the estimations of land-surface parameters. In addition, it has been found that solar radiation and precipitation play an extremely important role in a coupled land-surface model by dominating the two-way interactions within the coupled system. This study will also enable us to investigate into the feasibility of applying the parameter estimation methods used for point-validations of LSM over grid-boxes in a coupled environment, and facilitate following studies on the effects that a coupled environment would have

  4. Recent data and information system initiatives for remotely sensed measurements of the land surface

    SciTech Connect

    Justice, C.O.; Maiden, M.E.; Rasool, S.I.; Bailey, G.B.; Strebel, D.E.; Tarpley, J.D.

    1995-01-01

    As part of the International Satellite Land Satellite Climatology Program (ISLSCP) Workshop on Remote Sensing of the Land Surface for Studies of Global Change, five invited presentations were given on recent data initiatives relevant to the ISLSCP community. The presentations are summarized in this paper along with some observations by the authors on data systems for the land sciences community. The invited presentations are by no means all inclusive but were selected as examples of current data activities, representing a range of topics associated with data for land sciences including: the generation of global and local scale data sets, the reworking of historical data sets, new data initiatives and some programmatic aspects of land data base development. This paper serves to provide information on these data initiatives and to air some of the issues concerning land science data systems that were raised at the meeting.

  5. Global land-use change hidden behind nickel consumption.

    PubMed

    Nakajima, Kenichi; Nansai, Keisuke; Matsubae, Kazuyo; Tomita, Makoto; Takayanagi, Wataru; Nagasaka, Tetsuya

    2017-05-15

    Economic growth is associated with a rapid rise in the use of natural resources within the economy, and has potential environmental impacts at local and/or global scales. In today's globalized economy, each country has indirect flows supporting its economic activities, and natural resource consumption through supply chains influences environmental impacts far removed from the place of consumption. One way to control environmental impacts associated with consumption of natural resources is to identify the consumption of natural resources and the associated environmental impacts through the global supply chain. In this study, we used a global link input-output model (GLIO, a hybrid multiregional input-output model) to detect the linkages between national nickel consumption and mining-associated global land-use changes. We focused on nickel, whose global demand has risen rapidly in recent years, as a case study. The estimated area of land-use change around the world caused by nickel mining in 2005 was 1.9km(2), and that induced by Japanese final demand for nickel was 0.38km(2). Our modeling also revealed that the areas of greatest land-use change associated with nickel mining were concentrated in only a few countries and regions far removed from the place of consumption. For example, 57.7% of the world's land-use changes caused by nickel mining were concentrated in five countries in 2005: Australia, 13.7%; Russia, 12.9%; Indonesia, 12.5%; New Caledonia, 10.4%; and Colombia, 8.2%. The mining-associated land-use change induced by Japanese final demand accounted for 19.5% of the total area affected by land-use change caused by nickel mining. The top three countries accounted for 70.6% (Indonesia: 47.0%, New Caledonia: 16.0%, and Australia: 7.7%), and the top five accounted for 82.4% (the Philippines: 7.5%, and Canada: 4.3%, in addition to the top three countries and regions). Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  6. Assessment Of The Impact Of ESA CCI Land Cover Information For Global Climate Model Simulations

    NASA Astrophysics Data System (ADS)

    Khlystova, Iryna G.; Loew, A.; Hangemann, S.; Defourny, P.; Brockmann, C.; Bontemps, S.

    2013-12-01

    Addressing the issues of climate change, the European Space Agency has recently initiated the Global Monitoring of an Essential Climate Variables program (ESA Climate Change Initiative). The main objective is to realize the full potential of the long-term global Earth Observation archives that ESA has established over the last thirty years. Due to well organized data access and transparency for the data quality, as well as long-term scientific and technical support, the provided datasets have become very attractive for the use in Earth System Modeling. The Max Plank Institute for Meteorology is contributing to the ESA CCI via the Climate Modeler User Group (CMUG) activities and is responsible for providing a modeler perspective on the Land Cover and Fire Essential Climate Variables. The new ESA land cover ECV has recently released a new global 300-m land cover dataset. This dataset is supported by an interactive tool which allows flexible horizontal re-scaling and conversion from currently accepted satellite specific land classes to the model- specific Plant Functional Types (PFT) categorization. Such a dataset is an ideal starting point for the generation of the land cover information for the initialization of model cover fractions. In this presentation, we show how the usage of this new dataset affects the model performance, comparing it to the standard model set-up, in terms of energy and water fluxes. To do so, we performed a number of offline land-system simulations with original standard JSBACH land cover information and with the new ESA CCI land cover product. We have analyzed the impact of land cover on a simulated surface albedo, temperature and energy fluxes as well as on the biomass load and fire carbon emissions.

  7. Multispectral imaging contributions to global land ice measurements from space

    USGS Publications Warehouse

    Kargel, J.S.; Abrams, M.J.; Bishop, M.P.; Bush, A.; Hamilton, G.; Jiskoot, H.; Kaab, Andreas; Kieffer, H.H.; Lee, E.M.; Paul, F.; Rau, F.; Raup, B.; Shroder, J.F.; Soltesz, D.; Stainforth, D.; Stearns, L.; Wessels, R.

    2005-01-01

    Global Land Ice Measurements from Space (GLIMS) is an international consortium established to acquire satellite images of the world's glaciers, analyse them for glacier extent and changes, and assess change data for causes and implications for people and the environment. Although GLIMS is making use of multiple remote-sensing systems, ASTER (Advanced Spaceborne Thermal Emission and reflection Radiometer) is optimized for many needed observations, including mapping of glacier boundaries and material facies, and tracking of surface dynamics, such as flow vector fields and supraglacial lake development. Software development by GLIMS is geared toward mapping clean-ice and debris-covered glaciers; terrain classification emphasizing snow, ice, water, and admixtures of ice with rock debris; multitemporal change analysis; visualization of images and derived data; and interpretation and archiving of derived data. A global glacier database has been designed at the National Snow and Ice Data Center (NSIDC, Boulder, Colorado); parameters are compatible with and expanded from those of the World Glacier Inventory (WGI). These technology efforts are summarized here, but will be presented in detail elsewhere. Our presentation here pertains to one broad question: How can ASTER and other satellite multispectral data be used to map, monitor, and characterize the state and dynamics of glaciers and to understand their responses to 20th and 21st century climate change? Our sampled results are not yet glaciologically or climatically representative. Our early results, while indicating complexity, are generally consistent with the glaciology community's conclusion that climate change is spurring glacier responses around the world (mainly retreat). Whether individual glaciers are advancing or retreating, the aggregate average of glacier change must be climatic in origin, as nonclimatic variations average out. We have discerned regional spatial patterns in glaciological response behavior

  8. MEaSUREs Land Surface Temperature from GOES satellites

    NASA Astrophysics Data System (ADS)

    Pinker, Rachel T.; Ma, Yingtao; Chen, Wen; Hulley, Glynn; Borbas, Eva; Hain, Chris; Hook, Simon

    2016-04-01

    Information on Land Surface Temperature (LST) can be generated from observations made from satellites in low Earth orbit (LEO) such as MODIS and ASTER and by sensors in geostationary Earth orbit (GEO) such as GOES. Both observations have unique advantages, however, when combined, introduced are challenges related to inhomogeneity of the resulting information. NASA has identified a major need for developing long-term, consistent, and calibrated data and products that are consistent across multiple missions and satellite sensors. Under a project titled: "A Unified and Coherent Land Surface Temperature and Emissivity Earth System Data Record (ESDR) for Earth Science" led by Jet Propulsion Laboratory, such an effort is underway. In this presentation we will describe part of that effort, dealing with the generation of an approach to derive LST information from the GOES satellites from 2000 and onward. Since implementation of the well-established split window approach is not possible after mid-2003 (will be possible again after the launch of GOES-R in October of 2016), there is a need to focus on retrievals from a single thermal channel in order to provide continuity in the LST record. The methodology development requires the generation of consistently calibrated GOES observations, identification of clear sky radiances, and development of retrieval algorithms that benefit from most recent advances in related fields that provide auxiliary information required for driving the inference schemes. Results will be presented from two approaches. One is based on a regression approach that utilizes a wide range of simulations using MODTRAN, SeeBor Version 5.0 global atmospheric profiles and. The second approach uses MERRA-2 reanalysis fields with the RTTOV radiative transfer model approach to derive LST from the LEO satellites, adjusted for the GEO characteristics. The advantage of this latter approach is in the consistency between this retrieval approaches and those used at JPL

  9. Idealized Land-sea Warming Contrast Experiments with Two Global Circulation Models: Preliminary results

    NASA Astrophysics Data System (ADS)

    Kim, J. E. E.; Lee, J. L.; Hong, S. Y.

    2014-12-01

    Simulations of warming climates with climate models have pointed out that land surface temperatures will increase more rapidly than sea surface temperature (SST), which is known as the "land-sea warming contrast". We investigate the response of a zonally symmetric atmosphere to robust land-sea surface warming contrast using two global circulation models (GCMs): Non-hydrostatic Icosahedral Model (NIM) and Global and Regional Integrated Model system (GRIMs). NIM is a Finite-volume icosahedral model developed as a next-generation operational model at National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA ESRL). Full model physics were taken from Model for Prediction Across Scales (MPAS) physics suite. GRIMs is a spectral model which has been developed in Korea (Hong et al., 2013, APJAS). It has flexibility for selection of comparable physics options with NIM. Two sets of experiments are designed: one is the control experiment with zonally-symmetric distributions with maxima at the equator and varying off-equatorial temperature gradients on ocean and land. The other experiment will impose the land/sea warming ratio of 1.5. Since two models can be set up with identical physics parameterizations, general consensus on responses and model-dependent feedback can be suggested.

  10. The Cloud and Land Surface Interaction Campaign (CLASIC)

    NASA Astrophysics Data System (ADS)

    Miller, M. A.

    2008-05-01

    The consequences of increasing greenhouse gas concentrations on the Earth's climate system are evaluated using Global Climate Models, which must accurately simulate the complex array of mechanisms and feedbacks in the climate system and predict how they will operate in the future. A significant challenge for these models is the representation of cumulus convection, which is an important component of the water and energy budget of the planet and plays a key role in the hydrologic cycle. The role of cumulus convection in the water budget is particularly important in semi-arid regions and in regions with significant agricultural interests. In situations where the synoptic scale forcing is weak and the surface is sufficiently moist, continental cumulus convection may be strongly modulated by land surface conditions, while at the same time influencing the land surface itself through rain-induced changes in soil moisture and through its impact on photosynthesis. Many of the properties of the land surface that likely influence the development and evolution of cumulus convection can be altered by human activities such as urban development and agriculture. The Cloud and Land Surface Interaction Campaign (CLASIC) was conducted in the Southern Great Plains of the United States during June 2007. A principal goal of the experiment was to examine these interactions when shallow convection was the dominant cloud type across the SGP domain. The experiment was lead by the Department of Energy's (DOE's) Atmospheric Radiation Measurement (ARM) Program and held at the ARM Southern Great Plains (SGP) Climate Research Facility. Additional support was provided by the National Aeronautics and Space Administration and the United States Department of Agriculture. A multiple scale observation approach was used during CLASIC. Large scale forcing was quantified using enhanced radiosonde observations within the SGP site in conjunction with the National Oceanic and Atmospheric Administration

  11. Venus - Global surface radio emissivity

    NASA Technical Reports Server (NTRS)

    Ford, P. G.; Pettengill, G. H.

    1983-01-01

    Observations of thermal radio emission from the surface of Venus, made by the Pioneer Venus radar mapper at a wavelength of 17 cm, show variations that are dominated by changes in surface emissivity. The regions of lowest emissivity (0.54 + or - 0.05 for the highland areas of Aphrodite Terra and Theia Mons) correspond closely to regions of high radar reflectivity reported earlier. These results support the inference of inclusions of material with high electrical conductivity in the surface rock of these areas.

  12. Sentinel-3 for the Copernicus Global Land Service: Monitoring the Continental Ecosystems at Global Scale

    NASA Astrophysics Data System (ADS)

    Lacaze, R.; Smets, B.; Calvet, J.-C.; Camacho, F.; Tansey, K.; Baret, F.; Ramon, D.; Montersleet, B.; Roujean, J.-L.; Wandrebeck, L.; Swinnen, E.; Freitas, S.; Paulik, C.; Jann, A.

    2015-12-01

    The Copernicus Global Land service provides continuously bio-geophysical variables describing, over the whole globe, the vegetation dynamic, the energy budget at the continental surface and some components of the water cycle. Some of these variables were derived from SPOT/VGT, and are now based upon the PROBA-V data. The evolution of the service towards a production at 333m resolution is prepared, using PROBA-V data, in the FP7/ImagineS project focusing on the LAI, FAPAR, FCover, normalized TOC reflectance and Albedo. The next major evolution of the service will be the exploitation of the Sentinel-3 data: for the continuity of 1km and 333m resolution production, jointly with the PROBA-V data; for the evolution of the service, jointly with Sentinel-2 data, to set-up a high resolution monitoring service. For that, timeliness, for NRT production, spatial coverage for a daily global monitoring, and the consistency, for a joint use of multi-mission data, are mandatory.

  13. Estimation of Land Surface States and Fluxes using a Land Surface Model Considering Different Irrigation Systems

    NASA Astrophysics Data System (ADS)

    Chun, J. A.; Zaitchik, B. F.; Evans, J. P.; Beaudoing, H. K.

    2012-12-01

    Food security can be improved by increasing the extent of agricultural land or by increasing agricultural productivity, including through intensive management such as irrigation. The objectives of this study were to incorporate practical irrigation schemes into land surface models of the NASA Land Information System (LIS) and to apply the tool to estimate the impact of irrigation on land surface states and fluxes—including evapotranspiration, soil moisture, and runoff—in the Murray-Darling basin in Australia. Here we present results obtained using Noah Land Surface Model v3.2 within LIS without simulated irrigation (IR0) and with three irrigation simulation routines: flood irrigation (IR1), drip irrigation (IR2), and sprinkler irrigation (IR3). Moderate Resolution Imaging Spectrometer (MODIS) vegetation index was used to define crop growing seasons. Simulations were performed for a full year (July 2002 to June 2003) and evaluated against hydrologic flux estimates obtained in previous studies. Irrigation amounts during the growing season (August 2002 to March 2003) were simulated as 104.6, 24.6, and 188.1 GL for IR1, IR2, and IR3, respectively. These preliminary results showed water use efficiency from a drip irrigation scheme would be highest and lowest from a sprinkler irrigation scheme, with a highly optimized version of flood irrigation falling in between. Irrigation water contributed to a combination of increased evapotranspiration, runoff, and soil moisture storage in the irrigation simulations relative to IR0. Implications for water management applications and for further model development will be discussed.

  14. Global surface temperature changes since the 1850s

    SciTech Connect

    Jones, P.D.

    1996-12-31

    Temperature data from land and marine areas form the basis for many studies of climatic variations on local, regional and hemispheric scales, and the global mean temperature is a fundamental measure of the state of the climate system. In this paper it is shown that the surface temperature of the globe has warmed by about 0.5{degrees}C since the mid-nineteenth century. This is an important part of the evidence in the {open_quote}global warming{close_quote} debate. How certain are we about the magnitude of the warming? Where has it been greatest? In this paper, these and related issues will be addressed.

  15. Land Cover Applications, Landscape Dynamics, and Global Change

    USGS Publications Warehouse

    Tieszen, Larry L.

    2007-01-01

    The Land Cover Applications, Landscape Dynamics, and Global Change project at U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) seeks to integrate remote sensing and simulation models to better understand and seek solutions to national and global issues. Modeling processes related to population impacts, natural resource management, climate change, invasive species, land use changes, energy development, and climate mitigation all pose significant scientific opportunities. The project activities use remotely sensed data to support spatial monitoring, provide sensitivity analyses across landscapes and large regions, and make the data and results available on the Internet with data access and distribution, decision support systems, and on-line modeling. Applications support sustainable natural resource use, carbon cycle science, biodiversity conservation, climate change mitigation, and robust simulation modeling approaches that evaluate ecosystem and landscape dynamics.

  16. Compression of the Global Land 1-km AVHRR dataset

    USGS Publications Warehouse

    Kess, B. L.; Steinwand, D.R.; Reichenbach, S.E.

    1996-01-01

    Large datasets, such as the Global Land 1-km Advanced Very High Resolution Radiometer (AVHRR) Data Set (Eidenshink and Faundeen 1994), require compression methods that provide efficient storage and quick access to portions of the data. A method of lossless compression is described that provides multiresolution decompression within geographic subwindows of multi-spectral, global, 1-km, AVHRR images. The compression algorithm segments each image into blocks and compresses each block in a hierarchical format. Users can access the data by specifying either a geographic subwindow or the whole image and a resolution (1,2,4, 8, or 16 km). The Global Land 1-km AVHRR data are presented in the Interrupted Goode's Homolosine map projection. These images contain masked regions for non-land areas which comprise 80 per cent of the image. A quadtree algorithm is used to compress the masked regions. The compressed region data are stored separately from the compressed land data. Results show that the masked regions compress to 0·143 per cent of the bytes they occupy in the test image and the land areas are compressed to 33·2 per cent of their original size. The entire image is compressed hierarchically to 6·72 per cent of the original image size, reducing the data from 9·05 gigabytes to 623 megabytes. These results are compared to the first order entropy of the residual image produced with lossless Joint Photographic Experts Group predictors. Compression results are also given for Lempel-Ziv-Welch (LZW) and LZ77, the algorithms used by UNIX compress and GZIP respectively. In addition to providing multiresolution decompression of geographic subwindows of the data, the hierarchical approach and the use of quadtrees for storing the masked regions gives a marked improvement over these popular methods.

  17. Human land-use-driven reduction of forest volatiles cools global climate

    NASA Astrophysics Data System (ADS)

    Unger, Nadine

    2014-10-01

    Human conversion of forest ecosystems to agriculture is a major driver of global change. Conventionally, the impacts of the historical cropland expansion on Earth’s radiation balance have been quantified through two opposing effects: the release of stored carbon to the atmosphere as CO2 (warming) versus the increase in surface albedo (cooling). Changing forest cover has a third effect on the global radiation balance by altering emissions of biogenic volatile organic compounds (BVOCs) that control the loadings of multiple warming and cooling climate pollutants: tropospheric ozone (O3), methane (CH4) and aerosols. Although human land cover change has dominated BVOC emission variability over the past century, the net effect on global climate has not been quantified. Here, I show that the effects of the global cropland expansion between the 1850s and 2000s on BVOC emissions and atmospheric chemistry have imposed an additional net global radiative impact of -0.11 +/- 0.17 W m-2 (cooling). This magnitude is comparable to that of the surface albedo and land carbon release effects. I conclude that atmospheric chemistry must be considered in climate impact assessments of anthropogenic land cover change and in forestry for climate protection strategies.

  18. Enhancing the Representation of Subgrid Land Surface Characteristics in Land Surface Models

    SciTech Connect

    Ke, Yinghai; Leung, Lai-Yung R.; Huang, Maoyi; Li, Hongyi

    2013-09-27

    Land surface heterogeneity has long been recognized and increasingly incorporated in the land surface modelling. In most existing land surface models, the spatial variability of surface cover is represented as subgrid composition of multiple surface cover types. In this study, we developed a new subgrid classification method (SGC) that accounts for the topographic variability of the vegetation cover. Each model grid cell was represented with a number of elevation classes and each elevation class was further described by a number of vegetation types. The numbers of elevation classes and vegetation types were variable and optimized for each model grid so that the spatial variability of both elevation and vegetation can be reasonably explained given a pre-determined total number of classes. The subgrid structure of the Community Land Model (CLM) was used as an example to illustrate the newly developed method in this study. With similar computational burden as the current subgrid vegetation representation in CLM, the new method is able to explain at least 80% of the total subgrid PFTs and greatly reduced the variations of elevation within each subgrid class compared to the baseline method where a single elevation class is assigned to each subgrid PFT. The new method was also evaluated against two other subgrid methods (SGC1 and SGC2) that assigned fixed numbers of elevation and vegetation classes for each model grid with different perspectives of surface cover classification. Implemented at five model resolutions (0.1°, 0.25°, 0.5°, 1.0° and 2.0°) with three maximum-allowed total number of classes N_class of 24, 18 and 12 representing different computational burdens over the North America (NA) continent, the new method showed variable performances compared to the SGC1 and SGC2 methods. However, the advantage of the SGC method over the other two methods clearly emerged at coarser model resolutions and with moderate computational intensity (N_class = 18) as it

  19. Global priorities for national carnivore conservation under land use change

    PubMed Central

    Di Minin, Enrico; Slotow, Rob; Hunter, Luke T. B.; Montesino Pouzols, Federico; Toivonen, Tuuli; Verburg, Peter H.; Leader-Williams, Nigel; Petracca, Lisanne; Moilanen, Atte

    2016-01-01

    Mammalian carnivores have suffered the biggest range contraction among all biodiversity and are particularly vulnerable to habitat loss and fragmentation. Therefore, we identified priority areas for the conservation of mammalian carnivores, while accounting for species-specific requirements for connectivity and expected agricultural and urban expansion. While prioritizing for carnivores only, we were also able to test their effectiveness as surrogates for 23,110 species of amphibians, birds, mammals and reptiles and 867 terrestrial ecoregions. We then assessed the risks to carnivore conservation within each country that makes a contribution to global carnivore conservation. We found that land use change will potentially lead to important range losses, particularly amongst already threatened carnivore species. In addition, the 17% of land targeted for protection under the Aichi Target 11 was found to be inadequate to conserve carnivores under expected land use change. Our results also highlight that land use change will decrease the effectiveness of carnivores to protect other threatened species, especially threatened amphibians. In addition, the risk of human-carnivore conflict is potentially high in countries where we identified spatial priorities for their conservation. As meeting the global biodiversity target will be inadequate for carnivore protection, innovative interventions are needed to conserve carnivores outside protected areas to compliment any proposed expansion of the protected area network. PMID:27034197

  20. Global priorities for national carnivore conservation under land use change.

    PubMed

    Di Minin, Enrico; Slotow, Rob; Hunter, Luke T B; Montesino Pouzols, Federico; Toivonen, Tuuli; Verburg, Peter H; Leader-Williams, Nigel; Petracca, Lisanne; Moilanen, Atte

    2016-04-01

    Mammalian carnivores have suffered the biggest range contraction among all biodiversity and are particularly vulnerable to habitat loss and fragmentation. Therefore, we identified priority areas for the conservation of mammalian carnivores, while accounting for species-specific requirements for connectivity and expected agricultural and urban expansion. While prioritizing for carnivores only, we were also able to test their effectiveness as surrogates for 23,110 species of amphibians, birds, mammals and reptiles and 867 terrestrial ecoregions. We then assessed the risks to carnivore conservation within each country that makes a contribution to global carnivore conservation. We found that land use change will potentially lead to important range losses, particularly amongst already threatened carnivore species. In addition, the 17% of land targeted for protection under the Aichi Target 11 was found to be inadequate to conserve carnivores under expected land use change. Our results also highlight that land use change will decrease the effectiveness of carnivores to protect other threatened species, especially threatened amphibians. In addition, the risk of human-carnivore conflict is potentially high in countries where we identified spatial priorities for their conservation. As meeting the global biodiversity target will be inadequate for carnivore protection, innovative interventions are needed to conserve carnivores outside protected areas to compliment any proposed expansion of the protected area network.

  1. Global Landing Site Access Using Atmospheric Skip Trajectories

    NASA Technical Reports Server (NTRS)

    Bryant, Lee

    2002-01-01

    Mars direct entry, without going into orbit, does not provide global access to all landing site latitudes. Latitudes accessible via direct entry trajectories consist of a ring around the backside of the planet, centered about V infinity. Landing sites outside this ring can be achieved using a modified approach trajectory entering the atmosphere over the South Pole "aerocapture fashion" that will skip out to an altitude above the atmosphere and then re-enter the atmosphere a second time and continue to toward the North Pole. The first aerocapture maneuver is aligned to provide an exit orbit that contains the desired landing site with an apoapsis computed to provide proper ranging for the second entry. A powered maneuver is utilized during the exoatmospheric phase to remove altitude and flight path deviations due to uncertainties in the atmosphere occurring during the first entry. Three guidance schemes are required for global landing site access analysis. Aerocapture guidance was used for the first atmospheric entry, Shuttle Powered Explicit Guidance was used for the exoatmospheric maneuver, and Apollo Derived Entry Guidance was used for the second atmospheric entry. An altimeter to update the onboard navigation state after the first atmospheric entry, was required to remove accumulated deadreckoning navigation errors and achieve reasonable range errors at chute deploy.

  2. Characterizing the relationship between land use land cover change and land surface temperature

    NASA Astrophysics Data System (ADS)

    Tran, Duy X.; Pla, Filiberto; Latorre-Carmona, Pedro; Myint, Soe W.; Caetano, Mario; Kieu, Hoan V.

    2017-02-01

    Exploring changes in land use land cover (LULC) to understand the urban heat island (UHI) effect is valuable for both communities and local governments in cities in developing countries, where urbanization and industrialization often take place rapidly but where coherent planning and control policies have not been applied. This work aims at determining and analyzing the relationship between LULC change and land surface temperature (LST) patterns in the context of urbanization. We first explore the relationship between LST and vegetation, man-made features, and cropland using normalized vegetation, and built-up indices within each LULC type. Afterwards, we assess the impacts of LULC change and urbanization in UHI using hot spot analysis (Getis-Ord Gi∗ statistics) and urban landscape analysis. Finally, we propose a model applying non-parametric regression to estimate future urban climate patterns using predicted land cover and land use change. Results from this work provide an effective methodology for UHI characterization, showing that (a) LST depends on a nonlinear way of LULC types; (b) hotspot analysis using Getis Ord Gi∗ statistics allows to analyze the LST pattern change through time; (c) UHI is influenced by both urban landscape and urban development type; (d) LST pattern forecast and UHI effect examination can be done by the proposed model using nonlinear regression and simulated LULC change scenarios. We chose an inner city area of Hanoi as a case-study, a small and flat plain area where LULC change is significant due to urbanization and industrialization. The methodology presented in this paper can be broadly applied in other cities which exhibit a similar dynamic growth. Our findings can represent an useful tool for policy makers and the community awareness by providing a scientific basis for sustainable urban planning and management.

  3. 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

  4. Processing techniques for global land 1-km AVHRR data

    USGS Publications Warehouse

    Eidenshink, Jeffery C.; Steinwand, Daniel R.; Wivell, Charles E.; Hollaren, Douglas M.; Meyer, David

    1993-01-01

    The U.S. Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center (EDC) in cooperation with several international science organizations has developed techniques for processing daily Advanced Very High Resolution Radiometer (AVHRR) 1-km data of the entire global land surface. These techniques include orbital stitching, geometric rectification, radiometric calibration, and atmospheric correction. An orbital stitching algorithm was developed to combine consecutive observations acquired along an orbit by ground receiving stations into contiguous half-orbital segments. The geometric rectification process uses an AVHRR satellite model that contains modules for forward mapping, forward terrain correction, and inverse mapping with terrain correction. The correction is accomplished by using the hydrologic features coastlines and lakes from the Digital Chart of the World. These features are rasterized into the satellite projection and are matched to the AVHRR imagery using binary edge correlation techniques. The resulting coefficients are related to six attitude correction parameters: roll, roll rate, pitch, pitch rate, yaw, and altitude. The image can then be precision corrected to a variety of map projections and user-selected image frames. Because the AVHRR lacks onboard calibration for the optical wavelengths, a series of time-variant calibration coefficients derived from vicarious calibration methods and are used to model the degradation profile of the instruments. Reducing atmospheric effects on AVHRR data is important. A method has been develop that will remove the effects of molecular scattering and absorption from clear sky observations, using climatological measurements of ozone. Other methods to remove the effects of water vapor and aerosols are being investigated.

  5. Estimation of Croplands in West Africa using Global Land Cover and Land Use Datasets: Preliminary Results

    NASA Astrophysics Data System (ADS)

    Adhikari, P.; de Beurs, K.

    2013-12-01

    Africa is vulnerable to the effects of global climate change resulting in reduced agricultural production and worsening food security. Studies show that Africa has the lowest cereal yield compared to other regions of the world. The situation is particularly dire in East, Central and West Africa. Despite their low cereal yield, the population of East, Central and West Africa has doubled between 1980 and 2007. Furthermore, West Africa has a history of severe and long droughts which have occasionally caused widespread famine. To understand how global climate change and land cover change have impacted crop production (yield) it is important to estimate croplands in the region. The objective of this study is to compare ten publicly available land cover and land use datasets, covering different time periods, to estimate croplands in West Africa. The land cover and land use data sets used cover the period from early 1990s to 2010. Preliminary results show a high variability in cropland estimates. For example, in Benin, the estimated cropland area varies from 2.5 to 21% of the total area, while it varies from 3 to 8% in Niger. Datasets with a finer resolution (≤ 1,000 m) have consistently estimated comparable cropland areas across all countries. Several categorical verification statistics such as probability of detection (POD), false alarm ratio (FAR) and critical success index are also used to analyze the correspondence between estimated and observed cropland pixels at the scales of 1 Km and 10 Km.

  6. Improving land surface models with FLUXNET data

    NASA Astrophysics Data System (ADS)

    Williams, M.; Richardson, A. D.; Reichstein, M.; Stoy, P. C.; Peylin, P.; Verbeeck, H.; Carvalhais, N.; Jung, M.; Hollinger, D. Y.; Kattge, J.; Leuning, R.; Luo, Y.; Tomelleri, E.; Trudinger, C. M.; Wang, Y.-P.

    2009-07-01

    There is a growing consensus that land surface models (LSMs) that simulate terrestrial biosphere exchanges of matter and energy must be better constrained with data to quantify and address their uncertainties. FLUXNET, an international network of sites that measure the land surface exchanges of carbon, water and energy using the eddy covariance technique, is a prime source of data for model improvement. Here we outline a multi-stage process for "fusing" (i.e. linking) LSMs with FLUXNET data to generate better models with quantifiable uncertainty. First, we describe FLUXNET data availability, and its random and systematic biases. We then introduce methods for assessing LSM model runs against FLUXNET observations in temporal and spatial domains. These assessments are a prelude to more formal model-data fusion (MDF). MDF links model to data, based on error weightings. In theory, MDF produces optimal analyses of the modelled system, but there are practical problems. We first discuss how to set model errors and initial conditions. In both cases incorrect assumptions will affect the outcome of the MDF. We then review the problem of equifinality, whereby multiple combinations of parameters can produce similar model output. Fusing multiple independent and orthogonal data provides a means to limit equifinality. We then show how parameter probability density functions (PDFs) from MDF can be used to interpret model validity, and to propagate errors into model outputs. Posterior parameter distributions are a useful way to assess the success of MDF, combined with a determination of whether model residuals are Gaussian. If the MDF scheme provides evidence for temporal variation in parameters, then that is indicative of a critical missing dynamic process. A comparison of parameter PDFs generated with the same model from multiple FLUXNET sites can provide insights into the concept and validity of plant functional types (PFT) - we would expect similar parameter estimates among

  7. Improving land surface models with FLUXNET data

    NASA Astrophysics Data System (ADS)

    Williams, M.; Richardson, A. D.; Reichstein, M.; Stoy, P. C.; Peylin, P.; Verbeeck, H.; Carvalhais, N.; Jung, M.; Hollinger, D. Y.; Kattge, J.; Leuning, R.; Luo, Y.; Tomelleri, E.; Trudinger, C.; Wang, Y.-P.

    2009-03-01

    There is a growing consensus that land surface models (LSMs) that simulate terrestrial biosphere exchanges of matter and energy must be better constrained with data to quantify and address their uncertainties. FLUXNET, an international network of sites that measure the land surface exchanges of carbon, water and energy using the eddy covariance technique, is a prime source of data for model improvement. Here we outline a multi-stage process for fusing LSMs with FLUXNET data to generate better models with quantifiable uncertainty. First, we describe FLUXNET data availability, and its random and systematic biases. We then introduce methods for assessing LSM model runs against FLUXNET observations in temporal and spatial domains. These assessments are a prelude to more formal model-data fusion (MDF). MDF links model to data, based on error weightings. In theory, MDF produces optimal analyses of the modelled system, but there are practical problems. We first discuss how to set model errors and initial conditions. In both cases incorrect assumptions will affect the outcome of the MDF. We then review the problem of equifinality, whereby multiple combinations of parameters can produce similar model output. Fusing multiple independent data provides a means to limit equifinality. We then show how parameter probability density functions (PDFs) from MDF can be used to interpret model process validity, and to propagate errors into model outputs. Posterior parameter distributions are a useful way to assess the success of MDF, combined with a determination of whether model residuals are Gaussian. If the MDF scheme provides evidence for temporal variation in parameters, then that is indicative of a critical missing dynamic process. A comparison of parameter PDFs generated with the same model from multiple FLUXNET sites can provide insights into the concept and validity of plant functional types (PFT) - we would expect similar parameter estimates among sites sharing a single PFT

  8. Divergent surface and total soil moisture projections under global warming

    USGS Publications Warehouse

    Berg, Alexis; Sheffield, Justin; Milly, Paul C.D.

    2017-01-01

    Land aridity has been projected to increase with global warming. Such projections are mostly based on off-line aridity and drought metrics applied to climate model outputs but also are supported by climate-model projections of decreased surface soil moisture. Here we comprehensively analyze soil moisture projections from the Coupled Model Intercomparison Project phase 5, including surface, total, and layer-by-layer soil moisture. We identify a robust vertical gradient of projected mean soil moisture changes, with more negative changes near the surface. Some regions of the northern middle to high latitudes exhibit negative annual surface changes but positive total changes. We interpret this behavior in the context of seasonal changes in the surface water budget. This vertical pattern implies that the extensive drying predicted by off-line drought metrics, while consistent with the projected decline in surface soil moisture, will tend to overestimate (negatively) changes in total soil water availability.

  9. Land surface dynamics monitoring using microwave passive satellite sensors

    NASA Astrophysics Data System (ADS)

    Guijarro, Lizbeth Noemi

    Soil moisture, surface temperature and vegetation are variables that play an important role in our environment. There is growing demand for accurate estimation of these geophysical parameters for the research of global climate models (GCMs), weather, hydrological and flooding models, and for the application to agricultural assessment, land cover change, and a wide variety of other uses that meet the needs for the study of our environment. The different studies covered in this dissertation evaluate the capabilities and limitations of microwave passive sensors to monitor land surface dynamics. The first study evaluates the 19 GHz channel of the SSM/I instrument with a radiative transfer model and in situ datasets from the Illinois stations and the Oklahoma Mesonet to retrieve land surface temperature and surface soil moisture. The surface temperatures were retrieved with an average error of 5 K and the soil moisture with an average error of 6%. The results show that the 19 GHz channel can be used to qualitatively predict the spatial and temporal variability of surface soil moisture and surface temperature at regional scales. In the second study, in situ observations were compared with sensor observations to evaluate aspects of low and high spatial resolution at multiple frequencies with data collected from the Southern Great Plains Experiment (SGP99). The results showed that the sensitivity to soil moisture at each frequency is a function of wavelength and amount of vegetation. The results confirmed that L-band is more optimal for soil moisture, but each sensor can provide soil moisture information if the vegetation water content is low. The spatial variability of the emissivities reveals that resolution suffers considerably at higher frequencies. The third study evaluates C- and X-bands of the AMSR-E instrument. In situ datasets from the Soil Moisture Experiments (SMEX03) in South Central Georgia were utilized to validate the AMSR-E soil moisture product and to

  10. Global Surface Temperature Change and Uncertainties Since 1861

    NASA Technical Reports Server (NTRS)

    Shen, Samuel S. P.; Lau, William K. M. (Technical Monitor)

    2002-01-01

    The objective of this talk is to analyze the warming trend and its uncertainties of the global and hemi-spheric surface temperatures. By the method of statistical optimal averaging scheme, the land surface air temperature and sea surface temperature observational data are used to compute the spatial average annual mean surface air temperature. The optimal averaging method is derived from the minimization of the mean square error between the true and estimated averages and uses the empirical orthogonal functions. The method can accurately estimate the errors of the spatial average due to observational gaps and random measurement errors. In addition, quantified are three independent uncertainty factors: urbanization, change of the in situ observational practices and sea surface temperature data corrections. Based on these uncertainties, the best linear fit to annual global surface temperature gives an increase of 0.61 +/- 0.16 C between 1861 and 2000. This lecture will also touch the topics on the impact of global change on nature and environment. as well as the latest assessment methods for the attributions of global change.

  11. Global Surface Temperature Change and Uncertainties Since 1861

    NASA Technical Reports Server (NTRS)

    Shen, Samuel S. P.; Lau, William K. M. (Technical Monitor)

    2002-01-01

    The objective of this talk is to analyze the warming trend and its uncertainties of the global and hemi-spheric surface temperatures. By the method of statistical optimal averaging scheme, the land surface air temperature and sea surface temperature observational data are used to compute the spatial average annual mean surface air temperature. The optimal averaging method is derived from the minimization of the mean square error between the true and estimated averages and uses the empirical orthogonal functions. The method can accurately estimate the errors of the spatial average due to observational gaps and random measurement errors. In addition, quantified are three independent uncertainty factors: urbanization, change of the in situ observational practices and sea surface temperature data corrections. Based on these uncertainties, the best linear fit to annual global surface temperature gives an increase of 0.61 +/- 0.16 C between 1861 and 2000. This lecture will also touch the topics on the impact of global change on nature and environment. as well as the latest assessment methods for the attributions of global change.

  12. Application of the global Land-Potential Knowledge System (LandPKS) mobile apps to land degradation, restoration and climate change adaptation

    USDA-ARS?s Scientific Manuscript database

    Combatting land degradation, promoting restoration and adapting to climate change all require an understanding of land potential. A global Land-Potential Knowledge System (LandPKS) is being developed that will address many of these limitations using an open source approach designed to allow anyone w...

  13. Clear sky visibility has decreased over land globally from 1973 to 2007.

    PubMed

    Wang, Kaicun; Dickinson, Robert E; Liang, Shunlin

    2009-03-13

    Visibility in the clear sky is reduced by the presence of aerosols, whose types and concentrations have a large impact on the amount of solar radiation that reaches Earth's surface. Here we establish a global climatology of inverse visibilities over land from 1973 to 2007 and interpret it in terms of changes in aerosol optical depth and the consequent impacts on incident solar radiation. The aerosol contribution to "global dimming," first reported in terms of strong decreases in measured incident solar radiation up to the mid-1980s, has monotonically increased over the period analyzed. Since that time, visibility has increased over Europe, consistent with reported European "brightening," but has decreased substantially over south and east Asia, South America, Australia, and Africa, resulting in net global dimming over land.

  14. The impact of land data assimilation on global river discharge predictions

    NASA Astrophysics Data System (ADS)

    Zsoter, Ervin; Cloke, Hannah; Smith, Paul; Emerton, Rebecca; Muñoz-Sabater, Joaquín; Pappenberger, Florian

    2017-04-01

    Operational probabilistic flood forecasts have become common in supporting decision-making processes and providing a platform to risk reduction. The Global Flood Awareness System (GloFAS) is one of the few global scale applications that currently exist. GloFAS is developed by the Joint Research Centre of the European Commission (JRC) and the European Centre for Medium-Range Weather Forecasts (ECMWF) with the support of national authorities and research institutions. It couples state-of-the art weather forecasts with a hydrological model to produce daily ensemble forecasts of river discharge with a forecast horizon of 30 days across a global river network. In GloFAS the real time streamflow forecasts are compared with climatological simulations to detect the severity of any high flow situations. In the current configuration, runoff produced "offline", where the ECMWF land-surface model (HTESSEL) is forced with atmospheric conditions from ERA Interim reanalysis, and runoff produced operationally in coupled mode with land data assimilation, are both used. This inhomogeneity of the application of land data assimilation in different parts of the GloFAS system can cause significant differences in river discharge and therefore limit the reliability of the flood severity information determined by comparing the real time forecasts to the historical discharge. In this study we evaluate the potential impact of the land data assimilation on discharge forecasting in the global context. The analysis is based on the new ERA5 climate reanalysis dataset covering the period 1979 to present and developed through the Copernicus Climate Change Service (C3S). ERA5 is the 5th major global reanalysis produced by ECMWF, following FGGE, ERA-15, ERA-40 and ERA-Interim. This version consists of a high resolution reanalysis dataset (31 km), and additionally includes information on uncertainties based on 10 ensemble members at 62 km horizontal resolution. ERA5 is currently in production and the

  15. Forest transitions, trade, and the global displacement of land use.

    PubMed

    Meyfroidt, Patrick; Rudel, Thomas K; Lambin, Eric F

    2010-12-07

    Reducing tropical deforestation is an international priority, given its impacts on carbon emissions and biodiversity. We examined whether recent forest transitions--a shift from net deforestation to net reforestation--involved a geographic displacement of forest clearing across countries through trade in agricultural and forest products. In most of the seven developing countries that recently experienced a forest transition, displacement of land use abroad accompanied local reforestation. Additional global land-use change embodied in their net wood trade offset 74% of their total reforested area. Because the reforesting countries continued to export more agricultural goods than they imported, this net displacement offset 22% of their total reforested area when both agriculture and forestry sectors are included. However, this net displacement increased to 52% during the last 5 y. These countries thus have contributed to a net global reforestation and/or decrease in the pressure on forests, but this global environmental benefit has been shrinking during recent years. The net decrease in the pressure on forests does not account for differences in their ecological quality. Assessments of the impacts of international policies aimed at reducing global deforestation should integrate international trade in agricultural and forest commodities.

  16. Forest transitions, trade, and the global displacement of land use

    PubMed Central

    Meyfroidt, Patrick; Rudel, Thomas K.; Lambin, Eric F.

    2010-01-01

    Reducing tropical deforestation is an international priority, given its impacts on carbon emissions and biodiversity. We examined whether recent forest transitions—a shift from net deforestation to net reforestation—involved a geographic displacement of forest clearing across countries through trade in agricultural and forest products. In most of the seven developing countries that recently experienced a forest transition, displacement of land use abroad accompanied local reforestation. Additional global land-use change embodied in their net wood trade offset 74% of their total reforested area. Because the reforesting countries continued to export more agricultural goods than they imported, this net displacement offset 22% of their total reforested area when both agriculture and forestry sectors are included. However, this net displacement increased to 52% during the last 5 y. These countries thus have contributed to a net global reforestation and/or decrease in the pressure on forests, but this global environmental benefit has been shrinking during recent years. The net decrease in the pressure on forests does not account for differences in their ecological quality. Assessments of the impacts of international policies aimed at reducing global deforestation should integrate international trade in agricultural and forest commodities. PMID:21078977

  17. 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

  18. Global climate change, land management, and biosolids application to semiarid grasslands

    SciTech Connect

    Loftin, S.R.

    1995-12-31

    Global climate change combined with improper land management, including over-grazing, can lead to a severe reduction in plant cover and soil productivity. This process is especially common in arid and semiarid regions with sparse vegetation cover. New and innovative methods of land management are needed to restore and maintain these ecosystems in a productive and sustainable state. Research conducted in New Mexico on the Rio Puerco Resource Area and the Sevilleta National Wildlife Refuge has shown that biosolids (municipal sewage sludge) application to semiarid grasslands can increase soil nutrient availability, increase plant cover and productivity, and decrease surface runoff and soil erosion without harming environmental quality.

  19. CARBON SEQUESTRATION ON SURFACE MINE LANDS

    SciTech Connect

    Donald H. Graves; Christopher Barton; Richard Sweigard; Richard Warner

    2003-10-30

    The 2002-2003 Department of Energy plantings amounted to 164 acres containing 111,520 tree seedlings in eastern and western Kentucky. Data gathered on these trees included an inventory to determine survival of all planted species. A sub-sample of seedlings was selected to assess the height and diameter of individual species of seedlings established. Additional efforts involved collection of soil sample and litter samples, analysis of herbaceous ground cover from vegetation clip plots and leaf area on each tree species, and development of tissue collections. All areas were sampled for penetration resistance, penetration depth (or depth to refusal), and bulk density at various depths. Rain fall events and flow rates were recorded. The water quality of runoff samples involved the determination of total and settleable solids and particle size distribution. A study was initiated that will focus on the colonization of small mammals from forest edges to various areas located on reclaimed surface mines. This effort will provide a better understanding of the role small mammals and birds have in the establishment of plant communities on mine lands that will be useful in developing and improving reclamation techniques.

  20. Land surface evaporation: Measurement and parameterization

    SciTech Connect

    Schmugge, T.; Andre, J.C.

    1991-01-01

    This book, which largely addresses issues suggested by its title, is based on papers presented at a workshop at Banyuls, France. This is one of the better books of its type. There is a strong emphasis on the role of land-surface evaporation in connection to the atmospheric and hydrological components of the climate system. The chapters are all well written and complement each other over a wide range of topics. Strong editing is evident, however, the individual chapters have not been closely integrated beyond adequate cross referencing. A variety of subject matter common to many of the chapters is briefly but redundantly introduced in several individual chapters rather than treated with enough explanation in one place for a beginning student to learn it. This was particularly evident in the various cursory introductions to the Monin-Obukhov similarity theory scattered throughout the book. Also, it is easy to find technical terms that go undefined-for example, mesoscale alpha and beta. Thus, the audience that will be served is advanced graduate students and professional who are looking for good general reviews of the current status of the materials treated.

  1. Ground surface temperature simulation for different land covers

    NASA Astrophysics Data System (ADS)

    Herb, William R.; Janke, Ben; Mohseni, Omid; Stefan, Heinz G.

    2008-07-01

    SummaryA model for predicting temperature time series for dry and wet land surfaces is described, as part of a larger project to assess the impact of urban development on the temperature of surface runoff and coldwater streams. Surface heat transfer processes on impervious and pervious land surfaces were investigated for both dry and wet weather periods. The surface heat transfer equations were combined with a numerical approximation of the 1-D unsteady heat diffusion equation to calculate pavement and soil temperature profiles to a depth of 10 m. Equations to predict the magnitude of the radiative, convective, conductive and evaporative heat fluxes at a dry or wet surface, using standard climate data as input, were developed. A model for the effect of plant canopies on surface heat transfer was included for vegetated land surfaces. Given suitable climate data, the model can simulate the land surface and sub-surface temperatures continuously throughout a six month time period or for a single rainfall event. Land surface temperatures have been successfully simulated for pavements, bare soil, short and tall grass, a forest, and two agricultural crops (corn and soybeans). The simulations were run for three different locations in US, and different years as imposed by the availability of measured soil temperature and climate data. To clarify the effect of land use on surface temperatures, the calibrated coefficients for each land use and the same soil coefficients were used to simulate surface temperatures for a six year climate data set from Albertville, MN. Asphalt and concrete give the highest surface temperatures, as expected, while vegetated surfaces gave the lowest. Bare soil gives surface temperatures that lie between those for pavements and plant-covered surfaces. The soil temperature model predicts hourly surface temperatures of bare soil and pavement with root-mean-square errors (RMSEs) of 1-2 °C, and hourly surface temperatures of vegetation-covered surfaces

  2. Climate and the equilibrium state of land surface hydrology parameterizations

    NASA Technical Reports Server (NTRS)

    Entekhabi, Dara; Eagleson, Peter S.

    1991-01-01

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

  3. Advancing land surface model development with satellite-based Earth observations

    NASA Astrophysics Data System (ADS)

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

    2017-05-01

    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 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.

  4. 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.

  5. Revisiting the global surface energy budgets with maximum-entropy-production model of surface heat fluxes

    NASA Astrophysics Data System (ADS)

    Huang, Shih-Yu; Deng, Yi; Wang, Jingfeng

    2016-10-01

    The maximum-entropy-production (MEP) model of surface heat fluxes, based on contemporary non-equilibrium thermodynamics, information theory, and atmospheric turbulence theory, is used to re-estimate the global surface heat fluxes. The MEP model predicted surface fluxes automatically balance the surface energy budgets at all time and space scales without the explicit use of near-surface temperature and moisture gradient, wind speed and surface roughness data. The new MEP-based global annual mean fluxes over the land surface, using input data of surface radiation, temperature data from National Aeronautics and Space Administration-Clouds and the Earth's Radiant Energy System (NASA CERES) supplemented by surface specific humidity data from the Modern-Era Retrospective Analysis for Research and Applications (MERRA), agree closely with previous estimates. The new estimate of ocean evaporation, not using the MERRA reanalysis data as model inputs, is lower than previous estimates, while the new estimate of ocean sensible heat flux is higher than previously reported. The MEP model also produces the first global map of ocean surface heat flux that is not available from existing global reanalysis products.

  6. Revisiting the global surface energy budgets with maximum-entropy-production model of surface heat fluxes

    NASA Astrophysics Data System (ADS)

    Huang, Shih-Yu; Deng, Yi; Wang, Jingfeng

    2017-09-01

    The maximum-entropy-production (MEP) model of surface heat fluxes, based on contemporary non-equilibrium thermodynamics, information theory, and atmospheric turbulence theory, is used to re-estimate the global surface heat fluxes. The MEP model predicted surface fluxes automatically balance the surface energy budgets at all time and space scales without the explicit use of near-surface temperature and moisture gradient, wind speed and surface roughness data. The new MEP-based global annual mean fluxes over the land surface, using input data of surface radiation, temperature data from National Aeronautics and Space Administration-Clouds and the Earth's Radiant Energy System (NASA CERES) supplemented by surface specific humidity data from the Modern-Era Retrospective Analysis for Research and Applications (MERRA), agree closely with previous estimates. The new estimate of ocean evaporation, not using the MERRA reanalysis data as model inputs, is lower than previous estimates, while the new estimate of ocean sensible heat flux is higher than previously reported. The MEP model also produces the first global map of ocean surface heat flux that is not available from existing global reanalysis products.

  7. Reforesting unused surface mined lands by replanting with native trees

    Treesearch

    Patrick N. Angel; James A. Burger; Carl E. Zipper; Scott Eggerud

    2012-01-01

    More than 600,000 ha (1.5 million ac) of mostly forested land in the Appalachian region were surface mined for coal under the Surface Mining Control and Reclamation Act. Today, these lands are largely unmanaged and covered with persistent herbaceous species, such as fescue (Festuca spp.) and sericea lespedeza (Lespedeza cuneata [Dum. Cours.] G. Don,) and a mix of...

  8. Comparative analyses of measured evapotranspiration for various land surfaces

    Treesearch

    Suat Irmak

    2016-01-01

    There is a significant lack of continuously measured ET data for multiple land surfaces in the same area to be able to make comparisons of water use rates of different agroecosystems. This research presentation will provide continuous evapotranspiration and other surface energy balance variables measured above multiple land use and management practices.

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

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

    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, 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. Overall the local method

  10. 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

  11. Large-Scale Validation of AMIP2 Land-Surface Simulations

    SciTech Connect

    Phillips, T J

    2003-02-04

    Diagnostic Subproject 12 (DSP 12) on Land-surface Processes and Parameterizations is one of several AMIP-related efforts to analyze the effectiveness of current climate models in simulating continental processes. DSP 12's particular objectives are (1) to validate large-scale AMIP2 continental simulations against available global reference data sets; (2) to verify continental energy/moisture conservation and diagnose related land-surface processes in the AMIP2 models; and (3) to formulate hypotheses on putative connections between AMIP2 simulation performance and the complexities of the respective land-surface schemes (LSSs) that might be tested by further numerical experimentation. This paper outlines DSP 12's large-scale validation work, while companion papers by Henderson-Sellers et al., Irannejad et al., and Zhang et al. briefly present our analysis of other facets of AMIP2 land-surface simulations.

  12. Carbon Sequestration on Surface Mine Lands

    SciTech Connect

    Donald Graves; Christopher Barton; Richard Sweigard; Richard Warner; Carmen Agouridis

    2006-03-31

    Since the implementation of the federal Surface Mining Control and Reclamation Act of 1977 (SMCRA) in May of 1978, many opportunities have been lost for the reforestation of surface mines in the eastern United States. Research has shown that excessive compaction of spoil material in the backfilling and grading process is the biggest impediment to the establishment of productive forests as a post-mining land use (Ashby, 1998, Burger et al., 1994, Graves et al., 2000). Stability of mine sites was a prominent concern among regulators and mine operators in the years immediately following the implementation of SMCRA. These concerns resulted in the highly compacted, flatly graded, and consequently unproductive spoils of the early post-SMCRA era. However, there is nothing in the regulations that requires mine sites to be overly compacted as long as stability is achieved. It has been cultural barriers and not regulatory barriers that have contributed to the failure of reforestation efforts under the federal law over the past 27 years. Efforts to change the perception that the federal law and regulations impede effective reforestation techniques and interfere with bond release must be implemented. Demonstration of techniques that lead to the successful reforestation of surface mines is one such method that can be used to change perceptions and protect the forest ecosystems that were indigenous to these areas prior to mining. The University of Kentucky initiated a large-scale reforestation effort to address regulatory and cultural impediments to forest reclamation in 2003. During the three years of this project 383,000 trees were planted on over 556 acres in different physiographic areas of Kentucky (Table 1, Figure 1). Species used for the project were similar to those that existed on the sites before mining was initiated (Table 2). A monitoring program was undertaken to evaluate growth and survival of the planted species as a function of spoil characteristics and

  13. Intercomparison of Land Surface Remote Sensing Products From Various Sensors.

    NASA Astrophysics Data System (ADS)

    Gobron, N.; Pinty, B.; Mélin, F.; Taberner, M.; Verstraete, M.; Widlowski, J.

    2003-12-01

    The biophysical activities on land surfaces are documented from spectral measurements made in space. Advances in the understanding of radiation transfer and availability of higher performance instruments have lead to the development of a new generation of geophysical products able to provide reliable, accurate information on the state and evolution of terrestrial environments. Specifically, a series of optimized algorithms have been developed to estimate the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) for various instruments. Such an approach allows the synergistic use of FAPAR products derived from different sensors and the construction of global FAPAR time series independent from the life time of these specific sensors. The outline of the methodology will be summarized and the preliminary results of an inter-comparison exercise conducted with SeaWiFS, MERIS(ENVISAT), MISR(Terra) and MODIS(Terra) products will be presented.

  14. Land water storage variability over West Africa estimated by Gravity Recovery and Climate Experiment (GRACE) and land surface models

    NASA Astrophysics Data System (ADS)

    Grippa, M.; Kergoat, L.; Frappart, F.; Araud, Q.; Boone, A.; de Rosnay, P.; Lemoine, J.-M.; Gascoin, S.; Balsamo, G.; Ottlé, C.; Decharme, B.; Saux-Picart, S.; Ramillien, G.

    2011-05-01

    Land water storage plays a fundamental role in the West African water cycle and has an important impact on climate and on the natural resources of this region. However, measurements of land water storage are scarce at regional and global scales and especially in poorly instrumented endorheic regions, such as most of the Sahel, where little useful information can be derived from river flow measurements and basin water budgets. The Gravity Recovery and Climate Experiment (GRACE) satellite mission provides an accurate measurement of the terrestrial gravity field variations from which land water storage variations can be derived. However, their retrieval is not straightforward, and different methods are employed, which results in different water storage GRACE products. On the other hand, water storage can be estimated by land surface modeling forced with observed or satellite-based boundary conditions, but such estimates can be highly model dependent. In this study, land water storage by six GRACE products and soil moisture estimations by nine land surface models (run within the framework of the African Monsoon Multidisciplinary Analysis Land Surface Intercomparison Project (ALMIP)) are evaluated over West Africa, with a particular focus on the Sahelian area. The water storage spatial distribution, including zonal transects, its seasonal cycle, and its and interannual variability, are analyzed for the years 2003-2007. Despite the nonnegligible differences among the various GRACE products and among the different models, a generally good agreement between satellite and model estimates is found over the West Africa study region. In particular, GRACE data are shown to reproduce well the water storage interannual variability over the Sahel for the 5 year study period. The comparison between satellite estimates and ALMIP results leads to the identification of processes needing improvement in the land surface models. In particular, our results point out the importance of

  15. Monitoring multi-decadal satellite earth observation of soil moisture using era-land global land water resources dataset

    NASA Astrophysics Data System (ADS)

    Albergel, Clement; Dorigo, Wouter; Balsamo, Gianpaolo; de Rosnay, Patricia; Muñoz-Sabater, Joaquin; Isaksen, Lars; Brocca, Luca; de Jeu, Richard; Wagner, Wolfgang

    2014-05-01

    It has been widely recognized that soil moisture is one of the main drivers of the water, energy and carbon cycles. It is a crucial variable for Numerical Weather Prediction (NWP) and climate projections because it plays a key role in hydro-meteorological processes. A good representation of soil moisture conditions can help improving the forecasting of precipitation, temperature, droughts and floods. For many applications global or continental scale soil moisture maps are needed. As a consequence, a signi?cant amount of studies have been conducted to obtain such information. For that purpose, land surface modeling, remote sensing techniques or a combination of both through Land Data Assimilation Systems are used. Assessing the quality of these products is required and for instance, the release of a new -long term- harmonized soil moisture product (SM-MW hereafter) from remote sensing within the framework of the European Space Agency's Water Cycle Multi-mission Observation Strategy (WACMOS) and Climate Change Initiative (CCI) projects in 2012 (more information at http://www.esa-soilmoisture-cci.org/) triggered several evaluation activities. The typical validation approach for model and satellite based data products is to compare them to in situ observations. However the evaluation of soil moisture products using ground measurements is not trivial. Even if in the recent years huge efforts were made to make such observations available in contrasting biomes and climate conditions, long term and large scale ground measurements networks are still sparse. Additionally, different networks will present different characteristics (e.g. measurement methods, installation depths and modes, calibration techniques, measurement interval, and temporal and spatial coverage). Finally using in situ measurements, the quality of retrieved soil moisture can be accurately assessed for the locations of the stations. That is why it is of interest to conceive new validation methods

  16. Global effects of land use on local terrestrial biodiversity.

    PubMed

    Newbold, Tim; Hudson, Lawrence N; Hill, Samantha L L; Contu, Sara; Lysenko, Igor; Senior, Rebecca A; Börger, Luca; Bennett, Dominic J; Choimes, Argyrios; Collen, Ben; Day, Julie; De Palma, Adriana; Díaz, Sandra; Echeverria-Londoño, Susy; Edgar, Melanie J; Feldman, Anat; Garon, Morgan; Harrison, Michelle L K; Alhusseini, Tamera; Ingram, Daniel J; Itescu, Yuval; Kattge, Jens; Kemp, Victoria; Kirkpatrick, Lucinda; Kleyer, Michael; Correia, David Laginha Pinto; Martin, Callum D; Meiri, Shai; Novosolov, Maria; Pan, Yuan; Phillips, Helen R P; Purves, Drew W; Robinson, Alexandra; Simpson, Jake; Tuck, Sean L; Weiher, Evan; White, Hannah J; Ewers, Robert M; Mace, Georgina M; Scharlemann, Jörn P W; Purvis, Andy

    2015-04-02

    Human activities, especially conversion and degradation of habitats, are causing global biodiversity declines. How local ecological assemblages are responding is less clear--a concern given their importance for many ecosystem functions and services. We analysed a terrestrial assemblage database of unprecedented geographic and taxonomic coverage to quantify local biodiversity responses to land use and related changes. Here we show that in the worst-affected habitats, these pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%. We estimate that, globally, these pressures have already slightly reduced average within-sample richness (by 13.6%), total abundance (10.7%) and rarefaction-based richness (8.1%), with changes showing marked spatial variation. Rapid further losses are predicted under a business-as-usual land-use scenario; within-sample richness is projected to fall by a further 3.4% globally by 2100, with losses concentrated in biodiverse but economically poor countries. Strong mitigation can deliver much more positive biodiversity changes (up to a 1.9% average increase) that are less strongly related to countries' socioeconomic status.

  17. Global effects of land use on local terrestrial biodiversity

    NASA Astrophysics Data System (ADS)

    Newbold, Tim; Hudson, Lawrence N.; Hill, Samantha L. L.; Contu, Sara; Lysenko, Igor; Senior, Rebecca A.; Börger, Luca; Bennett, Dominic J.; Choimes, Argyrios; Collen, Ben; Day, Julie; de Palma, Adriana; Díaz, Sandra; Echeverria-Londoño, Susy; Edgar, Melanie J.; Feldman, Anat; Garon, Morgan; Harrison, Michelle L. K.; Alhusseini, Tamera; Ingram, Daniel J.; Itescu, Yuval; Kattge, Jens; Kemp, Victoria; Kirkpatrick, Lucinda; Kleyer, Michael; Correia, David Laginha Pinto; Martin, Callum D.; Meiri, Shai; Novosolov, Maria; Pan, Yuan; Phillips, Helen R. P.; Purves, Drew W.; Robinson, Alexandra; Simpson, Jake; Tuck, Sean L.; Weiher, Evan; White, Hannah J.; Ewers, Robert M.; Mace, Georgina M.; Scharlemann, Jörn P. W.; Purvis, Andy

    2015-04-01

    Human activities, especially conversion and degradation of habitats, are causing global biodiversity declines. How local ecological assemblages are responding is less clear--a concern given their importance for many ecosystem functions and services. We analysed a terrestrial assemblage database of unprecedented geographic and taxonomic coverage to quantify local biodiversity responses to land use and related changes. Here we show that in the worst-affected habitats, these pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%. We estimate that, globally, these pressures have already slightly reduced average within-sample richness (by 13.6%), total abundance (10.7%) and rarefaction-based richness (8.1%), with changes showing marked spatial variation. Rapid further losses are predicted under a business-as-usual land-use scenario; within-sample richness is projected to fall by a further 3.4% globally by 2100, with losses concentrated in biodiverse but economically poor countries. Strong mitigation can deliver much more positive biodiversity changes (up to a 1.9% average increase) that are less strongly related to countries' socioeconomic status.

  18. Self-regulation in land plant and global climate interactions

    NASA Astrophysics Data System (ADS)

    Morel, V.; dePolo, P.; Matsumoto, K.

    2013-12-01

    The interactions between land plants and climate have long been recognized. As global climate change occurs, there is a necessity to understand the sensitivity of vegetation and the surrounding physical environment to these changes. In this study, we use MESMO-2E, an earth system model of intermediate complexity, to investigate the response of climate and land plants to changes in the optimal growth conditions of the plants (temperature and ambient carbon dioxide level). In an initial set of sensitivity experiments, the amount of carbon stored in vegetation, and consequently the air temperature, were reduced as the climate changed from pre-industrial to glacial conditions. As the optimal temperature and carbon dioxide levels were changed to be similar to that of the glacial environment, an increase in carbon vegetation and air temperature was observed, suggesting a self-regulation mechanism. Results of further sensitivity experiments that work to identify the self-regulation mechanism will be presented.

  19. REGIONAL AND GLOBAL PATTERNS OF POPULATION, LAND USE AND LAND COVER CHANGE: AN OVERVIEW OF STRESSORS AND IMPACTS

    EPA Science Inventory

    This paper provides an overview of land use and land cover (LULC) change and regional to global patterns of that change and responses. Human activities now dominate the Earth's global ecosystem and LULC change is one of the most pervasive and influential activities. LULC change a...

  20. REGIONAL AND GLOBAL PATTERNS OF POPULATION, LAND USE AND LAND COVER CHANGE: AN OVERVIEW OF STRESSORS AND IMPACTS

    EPA Science Inventory

    This paper provides an overview of land use and land cover (LULC) change and regional to global patterns of that change and responses. Human activities now dominate the Earth's global ecosystem and LULC change is one of the most pervasive and influential activities. LULC change a...

  1. Assessment of uncertainties in global land cover products for hydro-climate modeling in India

    NASA Astrophysics Data System (ADS)

    Madhusoodhanan, C. G.; Sreeja, K. G.; Eldho, T. I.

    2017-02-01

    Earth's land cover (LC) has significant influence on land-atmospheric processes and affects the climate at multiple scales. There are multiple global LC (GLC) data sets which are yet to be evaluated for uncertainties and their propagation into the simulation of land surface fluxes (LSFs) in land surface/climate modeling. The present study assesses the uncertainties in seven GLC products with reference to a regional data set for the simulation of LSFs in India using a macro-scale land surface model. There is considerable overestimation of the extent of croplands in most of the GLCs. The uncertainties in LCs exert significant bias in the simulation of the LSFs of actual evapotranspiration (ETa), latent heat (LE), and sensible heat (H) fluxes. Uncertainty propagation in LSFs is proportional to the bias in cropping intensity under rainfed condition. The high underrepresentation of cropland area in the UMd data set results in highest bias in LSFs whereas the least cropland bias in Globland30 leads to least bias. Irrigation has higher potential to alter the LSFs than uncertainties related to LC especially in regions with large area under irrigation like India. The changes in LSFs are higher in arid/semiarid regions with medium irrigation intensity than in subhumid regions with high irrigation intensity. This has significant implications for the country's future irrigation expansion plans in the arid/semiarid regions. The study also emphasizes the need for focused efforts to quantify the uncertainties from varying irrigation intensities in the next generation CMIP6 experiments.

  2. Simulation of land-atmosphere gaseous exchange using a coupled land surface-biogeochemical model

    NASA Astrophysics Data System (ADS)

    Gu, C.; Riley, W. J.; Perez, T. J.; Pan, L.

    2009-12-01

    It is important to develop and evaluate biogeochemical models that on the one hand represent vegetation and soil dynamics and on the other hand provide energy and water fluxes in a temporal resolution suitable for biogeochemical processes. In this study, we present a consistent coupling between a common land surface model (CLM3.0) and a recently developed biogeochemical model (TOUGHREACT-N). The model TOUGHREACT-N (TR-N) is one of the few process-based models that simulate green house gases fluxes by using an implicit scheme to solve the diffusion equations governing soil heat and water fluxes. By coupling with CLM3.0, we have significantly improved TR-N by including realistic representations of surface water, energy, and momentum exchanges, through the use of improved formulations for soil evaporation, plant transpiration, vegetation growth, and plant nitrogen uptake embedded in CLM3.0. The coupled CLMTR-N model is a first step for a full coupling of land surface and biogeochemical processes. The model is evaluated with measurements of soil temperature, soil water content, and N2O and N2 gaseous emission data from fallow, corn, and forest sites in Venezuela. The results demonstrate that the CLMTR-N model simulates realistic diurnal variation of soil temperature, soil water content, and N gaseous fluxes. For example, mean differences between predicted and observed midday near-surface soil water content were 8, 11, and 4 % in July, August, and September. The sensitivity of the biogeochemical processes and resulting N emissions to variation in environmental drivers is high, which indicates the need to calculate biogeochemical processes in, at least, two hourly time steps using dynamically updated (rather than daily averaged) soil environmental conditions. The development in CLMTR-N of such a complex representation of processes will allow us to characterize relevant processes and simplifications appropriate for regional to global-scale coupled biogeochemical and

  3. Decadal modulation of global surface temperature by internal climate variability

    NASA Astrophysics Data System (ADS)

    Dai, Aiguo; Fyfe, John C.; Xie, Shang-Ping; Dai, Xingang

    2015-06-01

    Despite a steady increase in atmospheric greenhouse gases (GHGs), global-mean surface temperature (T) has shown no discernible warming since about 2000, in sharp contrast to model simulations, which on average project strong warming. The recent slowdown in observed surface warming has been attributed to decadal cooling in the tropical Pacific, intensifying trade winds, changes in El Niño activity, increasing volcanic activity and decreasing solar irradiance. Earlier periods of arrested warming have been observed but received much less attention than the recent period, and their causes are poorly understood. Here we analyse observed and model-simulated global T fields to quantify the contributions of internal climate variability (ICV) to decadal changes in global-mean T since 1920. We show that the Interdecadal Pacific Oscillation (IPO) has been associated with large T anomalies over both ocean and land. Combined with another leading mode of ICV, the IPO explains most of the difference between observed and model-simulated rates of decadal change in global-mean T since 1920, and particularly over the so-called `hiatus' period since about 2000. We conclude that ICV, mainly through the IPO, was largely responsible for the recent slowdown, as well as for earlier slowdowns and accelerations in global-mean T since 1920, with preferred spatial patterns different from those associated with GHG-induced warming or aerosol-induced cooling. Recent history suggests that the IPO could reverse course and lead to accelerated global warming in the coming decades.

  4. Decadal Modulation of Global Surface Temperature By Internal Climate Variability

    NASA Astrophysics Data System (ADS)

    Dai, A.; Fyfe, J. C.; Xie, S. P.; Dai, X.

    2014-12-01

    Despite a steady increase in atmospheric greenhouse gases (GHGs), global-mean surface temperature (T) has shown no discernable warming since about 2000, in sharp contrast to model simulations which on average project strong warming. The recent slowdown in observed surface warming has been attributed to decadal cooling in the tropical Pacific, intensifying trade winds, changes in El Niño activity, increasing volcanic activity and decreasing solar irradiance. Earlier periods of arrested warming have been observed but received much less attention than the recent period, and their causes are poorly understood. Here we analyze observed and model-simulated global T fields to quantify the contributions of internal climate variability (ICV) to decadal changes in global-mean T since 1920. We show that the Inter-decadal Pacific Oscillation (IPO) has been associated with large T anomalies over both ocean and land since 1920. Combined with another leading mode of ICV, the IPO explains most of the difference between observed and model-simulated rates of decadal change in global-mean T since 1920, and particularly over the so-called "hiatus" period since about 2000. We conclude that ICV, mainly through the IPO, was largely responsible for the recent slowdown, as well as for earlier slowdowns and accelerations in global-mean T since 1920, with preferred spatial patterns different from GHG-induced warming. Recent history suggests that the IPO could reverse course and lead to accelerated global warming in the coming decades.

  5. The Second Phase of the Global Land Atmosphere Coupling Experiment (GLACE-2): Impact of Land Initialization on Subseasonal Forecasts

    NASA Technical Reports Server (NTRS)

    Koster, Randal; Mahanama, Sarith

    2012-01-01

    The recently-completed second phase of the Global Land-Atmosphere Coupling Experiment (GLACE-2) focused on quantifying, for boreal summer, the subseasonal (out to two months) forecast skill for precipitation and air temperature that can be derived from the realistic initialization of land surface states, notably soil moisture. An overview of the multi-institutional numerical experiment is described, along with a determination and characterization of multi-model "consensus" skill. The models show modest but significant land-derived skill in predicting air temperatures out to two months, especially where the rain gauge network is dense. Given that precipitation is the chief driver of soil moisture, and thereby assuming that rain gauge density is a reasonable proxy for the adequacy of the observational network contributing to soil moisture initialization, this result indeed highlights the potential contribution of enhanced observations to prediction. Land-derived precipitation forecast skill is much weaker than that for air temperature. The skill for predicting air temperature, and to some extent precipitation, increases with the magnitude of the initial soil moisture anomaly. GLACE-2 results are examined further to provide insight into the asymmetric impacts of wet and dry soil moisture initialization on skill.

  6. The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations

    NASA Astrophysics Data System (ADS)

    Walters, David; Boutle, Ian; Brooks, Malcolm; Melvin, Thomas; Stratton, Rachel; Vosper, Simon; Wells, Helen; Williams, Keith; Wood, Nigel; Allen, Thomas; Bushell, Andrew; Copsey, Dan; Earnshaw, Paul; Edwards, John; Gross, Markus; Hardiman, Steven; Harris, Chris; Heming, Julian; Klingaman, Nicholas; Levine, Richard; Manners, James; Martin, Gill; Milton, Sean; Mittermaier, Marion; Morcrette, Cyril; Riddick, Thomas; Roberts, Malcolm; Sanchez, Claudio; Selwood, Paul; Stirling, Alison; Smith, Chris; Suri, Dan; Tennant, Warren; Vidale, Pier Luigi; Wilkinson, Jonathan; Willett, Martin; Woolnough, Steve; Xavier, Prince

    2017-04-01

    We describe Global Atmosphere 6.0 and Global Land 6.0 (GA6.0/GL6.0): the latest science configurations of the Met Office Unified Model and JULES (Joint UK Land Environment Simulator) land surface model developed for use across all timescales. Global Atmosphere 6.0 includes the ENDGame (Even Newer Dynamics for General atmospheric modelling of the environment) dynamical core, which significantly increases mid-latitude variability improving a known model bias. Alongside developments of the model's physical parametrisations, ENDGame also increases variability in the tropics, which leads to an improved representation of tropical cyclones and other tropical phenomena. Further developments of the atmospheric and land surface parametrisations improve other aspects of model performance, including the forecasting of surface weather phenomena. We also describe GA6.1/GL6.1, which includes a small number of long-standing differences from our main trunk configurations that we continue to require for operational global weather prediction. Since July 2014, GA6.1/GL6.1 has been used by the Met Office for operational global numerical weather prediction, whilst GA6.0/GL6.0 was implemented in its remaining global prediction systems over the following year.

  7. Determination of Land Surface Temperature and Soil Moisture From Trmm/tmi Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Wen, J.; Su, Z.

    An analytical algorithm for determination of land surface temperature and soil mois- ture from Tropical Rainfall Measuring Mission/Microwave Imager (TRMM/TMI) re- mote sensing data is developed in this study. Error analyses illustrate that uncer- tainty of the involved parameters will not give serious errors in determination of land surface temperature and soil Fresnel reflectivity. With the proposed algorithm and TRMM/TMI remote sensing data collected during Global Energy and Water Experi- ment (GEWEX) Asian Monsoon Experiment in Tibet (GAME/Tibet) Intensive Obser- vation Period (IOP'98) field campaign in 1998, the regional and temporal distributions of the land surface temperature and volumetric soil moisture are estimated over the central Tibetan plateau area. To validate the proposed method, the ground measured surface temperature and soil volumetric moisture are compared to TRMM/TMI de- rived land surface temperature and soil Fresnel reflectivity respectively. The result shows that estimated surface temperature is in good agreement with ground mea- surements, their difference and correlation coefficient are 0.52+-2.41 K and 0.81. A quasi-linear relationship exists between the estimated Fresnel reflectivity and ground measured volumetric soil moisture with a correlation coefficient 0.82. The land sur- face characteristics can also be clearly identified from the regional distribution of the estimated land surface temperature, the mountainous area and water bodies give a very lower surface temperature while the river basin shows a higher surface temper- ature compared to the mountainous area. The southeastern part of the selected area has lower soil moisture, while the river basin exhibits high soil moisture values. It is therefore concluded that the proposed method is successful for the retrieval of land surface temperature and soil moisture using TRMM/TMI data. Keywords: TRMM/TMI, brightness temperature, land surface emperature, soil mois- ture and Tibetan

  8. Improving the representation of agricultural management in land surface models

    NASA Astrophysics Data System (ADS)

    Sacks, William J.

    To gain a better understanding of processes affecting crop yield, as well as two-way feedbacks between agricultural management and climate, a number of groups have recently incorporated croplands into regional and global land surface models. However, many aspects of agricultural management are still treated in a rudimentary way in these models. For my doctoral research, I have aimed to improve the representation of two key agricultural processes in land surface models: crop phenology and irrigation. In addition, I have investigated the effects of these processes on both crop yields and climate. First, I assembled a dataset of global crop planting and harvesting dates for nineteen crops. I also investigated climatic and non-climatic factors that drive planting date decisions around the world. Second, I investigated trends and variability in crop planting dates and development progress across the U.S. I showed a trend to earlier planting of corn and soybeans, along with a trend to a longer crop growth period, and particularly a lengthening reproductive period in corn. In addition, I showed that growing degree days are a good predictor of the length of the vegetative period in corn, but less so for the reproductive period. Third, I used these observed trends along with the Agro-IBIS model to explore the implications of changes in crop phenology for both crop yields and fluxes of water and energy. I estimated that the trend to longer-season corn cultivars over the last three decades can account for 26% of the observed yield trend in the U.S. In addition, I found that earlier planting and longer-season cultivars shift the seasonality of water and energy fluxes, and have a small effect on annual-average fluxes. Finally, I investigated the effects of irrigation on climate, finding that this effect is significant in some large regions of the globe. Although the global-average temperature change was small, the large regional changes are important for both crop yields and

  9. Water security, global change and land-atmosphere feedbacks.

    PubMed

    Dadson, Simon; Acreman, Michael; Harding, Richard

    2013-11-13

    Understanding the competing pressures on water resources requires a detailed knowledge of the future water balance under uncertain environmental change. The need for a robust, scientifically rigorous evidence base for effective policy planning and practice has never been greater. Environmental change includes, but is not limited to, climate change; it also includes land-use and land-cover change, including deforestation for agriculture, and occurs alongside changes in anthropogenic interventions that are used in natural resource management such as the regulation of river flows using dams, which can have impacts that frequently exceed those arising in the natural system. In this paper, we examine the role that land surface models can play in providing a robust scientific basis for making resource management decisions against a background of environmental change. We provide some perspectives on recent developments in modelling in land surface hydrology. Among the range of current land surface and hydrology models, there is a large range of variability, which indicates that the specification and parametrization of several basic processes in the models can be improved. Key areas that require improvement in order to address hydrological applications include (i) the representation of groundwater in models, particularly at the scales relevant to land surface modelling, (ii) the representation of human interventions such as dams and irrigation in the hydrological system, (iii) the quantification and communication of uncertainty, and (iv) improved understanding of the impact on water resources availability of multiple use through treatment, recycling and return flows (and the balance of consumptive and conservative uses). Through a series of examples, we demonstrate that changes in water use could have important reciprocal impacts on climate over a wide area. The effects of water management decisions on climate feedbacks are only beginning to be investigated-they are

  10. The Trajectories and Impacts of Land Use and Land Cover Change: A Global Synthesis

    NASA Astrophysics Data System (ADS)

    Mustard, J. F.; Fisher, T. R.; Prince, S. D.; Soja, A. J.; Elmore, A. J.

    2001-12-01

    We have summarized the trajectories of land cover and land use change (LCLUC) and the resulting impacts through a synthesis of results from studies encompassing a wide range of environments. While the specific changes and impacts are in some ways unique to each environment, we have nevertheless identified some general principles that seem to apply across all regions. The LCLUC trajectory of a particular landscape under influence by human actions begins with the transition from conditions dominated by natural vegetation to a frontier state. Land use activities in a frontier state are centered primarily around resource extraction and development of infrastructure such as roads or ports. Under the proper conditions (e.g. soils, climate), the frontier state gives way to an agricultural landscape by further conversion of natural vegetation to agriculture and management of cleared land for agriculture. The maximum extent of this conversion is a function of local biophysical and socio-economic factors. For example conversion of arid lands may be limited by water availability, access to capital for development of water resources and access to markets for the products. Given the appropriate conditions (e.g. economic and social policy, generation of wealth), LCLUC evolves as large settlements and industrialization develop in concert with high land prices and agricultural intensification. In some cases (e.g., New England, Appalachia), economic conditions (e.g., better land for agriculture elsewhere) may result in reversion of agriculture to natural vegetation. The last stage in LCLUC is conversion of agriculture to residential and suburban environments (e.g., Baltimore/Washington corridor). Examination of global land cover indicates that every stage is currently present, with areas like the Eastern United States and Western Europe as examples of regions having experienced all stages, while parts of the Amazon basin, Siberia, and Africa are moving through the frontier

  11. The use of hyperspectral / directional data in land surface process models

    NASA Astrophysics Data System (ADS)

    Mauser, W.; Schneider, K.; Bach, H.

    2002-06-01

    The presentation analyses the role of land surface parameters, in particular those, which can be derived from hyperspectral/directional remote sensing data, for land surface process models. Land surface process models are used to understand and predict the dominant cycles of energy, water, carbon, nutrients and humans on the plant on the local, regional and global scale. They address environmental issues of great importance like the carbon budget and the availability and quality of water as a basis for life. Land surface process models use land surface parameters to characterize the properties of the land surface and to solve the underlying physically based models. Among these parameters are vegetation type, leaf area index (LAI), fraction of absorbed photosynthetically active solar radiation, biomass, soilmoisture or chlorophyll-content. The main characteristics of the cycles on the land surface are complexity as well as large temporal dynamics and spatial heterogeneity on all considered scales. Conventional, state of the art modelling of land surface processes usually derive the temporal and spatial distribution of the parameters involved from interpolation of point measurements, which either leads to large errors or creates prohibitive sampling efforts. Recently land surface process models have learned to treat spatial processes in a spatial way and are now prepared to digest spatially explicit input information e.g. from remote sensing soruces. Remote Sensing data and especially hyperspectral/directional data can be used to derive land surface parameters. Their main advantage for land surface process modelling is, that they can implicitly measure the temporal dynamics and spatial heterogeneity of the reflection of the land surface. Parameter models convert the directional reflectance spectra into spatial fields of land surface parameter values. They in turn can be used as spatially distributed inputs to the process models. In the classical approach (and usually

  12. Modeling global distribution of agricultural insecticides in surface waters.

    PubMed

    Ippolito, Alessio; Kattwinkel, Mira; Rasmussen, Jes J; Schäfer, Ralf B; Fornaroli, Riccardo; Liess, Matthias

    2015-03-01

    Agricultural insecticides constitute a major driver of animal biodiversity loss in freshwater ecosystems. However, the global extent of their effects and the spatial extent of exposure remain largely unknown. We applied a spatially explicit model to estimate the potential for agricultural insecticide runoff into streams. Water bodies within 40% of the global land surface were at risk of insecticide runoff. We separated the influence of natural factors and variables under human control determining insecticide runoff. In the northern hemisphere, insecticide runoff presented a latitudinal gradient mainly driven by insecticide application rate; in the southern hemisphere, a combination of daily rainfall intensity, terrain slope, agricultural intensity and insecticide application rate determined the process. The model predicted the upper limit of observed insecticide exposure measured in water bodies (n = 82) in five different countries reasonably well. The study provides a global map of hotspots for insecticide contamination guiding future freshwater management and conservation efforts. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. Inversing grided land surface carbon fluxes focusing on Asia region

    NASA Astrophysics Data System (ADS)

    Zhang, Huifang

    2013-04-01

    With the global carbon budget research carrying out, there is a growing scientific and political interest to better understand terrestrial carbon cycle at global and regional scales. Asia, contributed one of the largest uncertainties to global carbon budget, needs further more investigation and study. The contribution of Asia to the global carbon cycle is characterized by its high fossil fuel emissions due to economic booming and demand steep rising in energy, a rapidly increasing land cover change or degradation caused by population explosion and crop land expansion, a fast forest recovering in virtue of forest afforestation in the past 20 years. These unique characteristics force the exchange of terrestrial carbon more heterogeneous in Asian continent, and lead the Asian carbon balance research's implementation more difficult. In view of the Asian net ecosystem exchange (NEE) of carbon characteristics, we used a state-of-the-art CO2 data assimilation system called CarbonTraker to estimate NEE of CO2 in Asia for every week during the years 2000-2009. This approach includes the following three steps: (1) the atmospheric transport model (TM5) used in the data assimilation system was nested to be 1x1 degree grid in Asian area while globally at 2x3 degree resolution; (2) the number of CO2 observation sites was expend with 22 in Asia (including CONTRAIL and NOAA's CO2 measurement); and (3) two different prior flux products were used to estimate uncertainty ranges. We find the Asian terrestrial biosphere absorbed about 1.89 PgC (1 petagram=1015 g) per year averaged over the period studied, partly offsetting the estimated 3.87 PgC/yr release by fossil fuel burning and cement manufacturing. The estimated sink is located mainly in the boreal Asia, while the temperate Asia and the tropical Asia are a week sink and a very small source, respectively. The results also show that the surface fluxes produced by the CarbonTracker system were reasonably consistent with the recent

  14. A new global mascon solution focused on land ice evolution

    NASA Astrophysics Data System (ADS)

    Luthcke, S. B.; Sabaka, T. J.; Rowlands, D. D.; McCarthy, J. J.; Loomis, B.; Arendt, A. A.

    2011-12-01

    A new global mascon solution has been developed with 1-arc-degree spatial and 10-day temporal sampling. The global mascons are estimated directly from the reduction of 8 years of GRACE K-band range-rate data. Temporal and anisotropic spatial constraints have been applied for land, ocean and ice regions. The solution construction and tuning is focused towards the Greenland and Antarctic ice sheets (GIS and AIS) as well as glaciers (e.g. Gulf of Alaska mountain glaciers) and ice caps. Details of the solution development will be discussed, including the mascon parameter definitions, and tuning of constraints. Results will be presented, exploring the spatial and temporal variability of the ice sheets and glacier regions. A detailed error analysis will be discussed, including solution dependence on iteration, constraints, forward modeling, and multi-technique comparisons. We also investigate the fundamental temporal and spatial resolution of the solution and the spatial correlation of ice sheet inter-annual change.

  15. 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