WorldWideScience

Sample records for satellite land-surface climatology

  1. Land surface skin temperature climatology: benefitting from the strengths of satellite observations

    International Nuclear Information System (INIS)

    Jin Menglin; Dickinson, Robert E

    2010-01-01

    Surface skin temperature observations (T skin ), as obtained by satellite remote sensing, provide useful climatological information of high spatial resolution and global coverage that enhances the traditional ground observations of surface air temperature (T air ) and so, reveal new information about land surface characteristics. This letter analyzes nine years of moderate-resolution imaging spectroradiometer (MODIS) skin temperature observations to present monthly skin temperature diurnal, seasonal, and inter-annual variations at a 0.05 deg. latitude/longitude grid over the global land surface and combines these measurements with other MODIS-based variables in an effort to understand the physical mechanisms responsible for T skin variations. In particular, skin temperature variations are found to be closely related to vegetation cover, clouds, and water vapor, but to differ from 2 m surface T air in terms of both physical meaning and magnitude. Therefore, the two temperatures (T skin and T air ) are complementary in their contribution of valuable information to the study of climate change.

  2. Synthesis of results obtained within the framework of international satellite land surface climatology projects. Final report

    International Nuclear Information System (INIS)

    Bolle, H.J.; Katergiannakis, U.; Billing, H.; Koslowsky, D.; Langer, I.; Tonn, W.

    1993-01-01

    In large-scale field experiments, methods were validated with whose aid characteristics of the terrestrial surfaces can be derived from satellite data; these characteristics are required for the exploration of the global change. The report gives an overview. The following topics are treated: Problems of calibration of satellite sensors; the geographical matching of ground observations to the satellite measurements; necessary corrections; dimensional integration of the data up to the dimensions of raster grids of global climate models. The report discusses in detail in what manner the remote exploration data can be connected with information on the terrestrial surfaces, in particular with energy balances. Few experiments only have been executed up to now within the framework of land surface climatology; however, they contributed a great deal to the better understanding of linking satellite data with terrestrial surface processes. If one wants to apply the elaborated methods globally wants, one needs, however, complex algorithms as well as - at least for the time being - constant quality control in the different landscape regions of the earth. (orig.) [de

  3. An Overview of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE)

    Science.gov (United States)

    Sellers, P. J.; Hall, F. G.; Asrar, G.; Strebel, D. E.; Murphy, R. E.

    1992-11-01

    In the summer of 1983 a group of scientists working in the fields of meteorology, biology, and remote sensing met to discuss methods for modeling and observing land-surface—atmosphere interactions on regional and global scales. They concluded, first, that the existing climate models contained poor representations of the processes controlling the exchanges of energy, water, heat, and carbon between the land surface and the atmosphere and, second, that satellite remote sensing had been underutilized as a means of specifying global fields of the governing biophysical parameters. Accordingly, a multiscale, multidisciplinary experiment, FIFE, was initiated to address these two issues. The objectives of FIFE were specified as follows: (1) Upscale integration of models: The experiment was designed to test the soil-plant-atmosphere models developed by biometeorologists for small-scale applications (millimeters to meters) and to develop methods to apply them at the larger scales (kilometers) appropriate to atmospheric models and satellite remote sensing. (2) Application of satellite remote sensing: Even if the first goal were achieved to yield a "perfect" model of vegetation-atmosphere exchanges, it would have very limited applications without a global observing system for initialization and validation. As a result, the experiment was tasked with exploring methods for using satellite data to quantify important biophysical states and rates for model input. The experiment was centered on a 15 × 15 km grassland site near Manhattan, Kansas. This area became the focus for an extended monitoring program of satellite, meteorological, biophysical, and hydrological data acquisition from early 1987 through October 1989 and a series of 12- to 20-day intensive field campaigns (IFCs), four in 1987 and one in 1989. During the IFCs the fluxes of heat, moisture, carbon dioxide, and radiation were measured with surface and airborne equipment in coordination with measurements of surface

  4. Data rescue of NASA First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) aerial observations

    Science.gov (United States)

    Santhana Vannan, S. K.; Boyer, A.; Deb, D.; Beaty, T.; Wei, Y.; Wei, Z.

    2017-12-01

    The Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) for biogeochemical dynamics is one of the NASA Earth Observing System Data and Information System (EOSDIS) data centers. ORNL DAAC (https://daac.ornl.gov) is responsible for data archival, product development and distribution, and user support for biogeochemical and ecological data and models. In particular, ORNL DAAC has been providing data management support for NASA's terrestrial ecology field campaign programs for the last several decades. Field campaigns combine ground, aircraft, and satellite-based measurements in specific ecosystems over multi-year time periods. The data collected during NASA field campaigns are archived at the ORNL DAAC (https://daac.ornl.gov/get_data/). This paper describes the effort of the ORNL DAAC team for data rescue of a First ISLSCP Field Experiment (FIFE) dataset containing airborne and satellite data observations from the 1980s. The data collected during the FIFE campaign contain high resolution aerial imageries collected over Kansas. The data rescue workflow was prepared to test for successful recovery of the data from a CD-ROM and to ensure that the data are usable and preserved for the future. The imageries contain spectral reflectance data that can be used as a historical benchmark to examine climatological and ecological changes in the Kansas region since the 1980s. Below are the key steps taken to convert the files to modern standards. Decompress the imageries using custom compression software provided with the data. The compression algorithm created for MS-DOS in 1980s had to be set up to run on modern computer systems. Decompressed files were geo-referenced by using metadata information stored in separate compressed header files. Standardized file names were applied (File names and details were described in separate readme documents). Image files were converted to GeoTIFF format with embedded georeferencing information. Leverage Open Geospatial

  5. Egypt satellite images for land surface characterization

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    images used for mapping the vegetation cover types and other land cover types in Egypt. The mapping ranges from 1 km resolution to 30 m resolution. The aim is to provide satellite image mapping with land surface characteristics relevant for roughness mapping.......Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...

  6. All-weather Land Surface Temperature Estimation from Satellite Data

    Science.gov (United States)

    Zhou, J.; Zhang, X.

    2017-12-01

    Satellite remote sensing, including the thermal infrared (TIR) and passive microwave (MW), provides the possibility to observe LST at large scales. For better modeling the land surface processes with high temporal resolutions, all-weather LST from satellite data is desirable. However, estimation of all-weather LST faces great challenges. On the one hand, TIR remote sensing is limited to clear-sky situations; this drawback reduces its usefulness under cloudy conditions considerably, especially in regions with frequent and/or permanent clouds. On the other hand, MW remote sensing suffers from much greater thermal sampling depth (TSD) and coarser spatial resolution than TIR; thus, MW LST is generally lower than TIR LST, especially at daytime. Two case studies addressing the challenges mentioned previously are presented here. The first study is for the development of a novel thermal sampling depth correction method (TSDC) to estimate the MW LST over barren land; this second study is for the development of a feasible method to merge the TIR and MW LSTs by addressing the coarse resolution of the latter one. In the first study, the core of the TSDC method is a new formulation of the passive microwave radiation balance equation, which allows linking bulk MW radiation to the soil temperature at a specific depth, i.e. the representative temperature: this temperature is then converted to LST through an adapted soil heat conduction equation. The TSDC method is applied to the 6.9 GHz channel in vertical polarization of AMSR-E. Evaluation shows that LST estimated by the TSDC method agrees well with the MODIS LST. Validation is based on in-situ LSTs measured at the Gobabeb site in western Namibia. The results demonstrate the high accuracy of the TSDC method: it yields a root-mean squared error (RMSE) of 2 K and ignorable systematic error over barren land. In the second study, the method consists of two core processes: (1) estimation of MW LST from MW brightness temperature and (2

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

    Science.gov (United States)

    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

  8. A global satellite assisted precipitation climatology

    Science.gov (United States)

    Funk, Christopher C.; Verdin, Andrew P.; Michaelsen, Joel C.; Pedreros, Diego; Husak, Gregory J.; Peterson, P.

    2015-01-01

    Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high resolution (0.05°) global precipitation climatologies that perform reasonably well in data sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate

  9. Advancing land surface model development with satellite-based Earth observations

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Mukesh Singh Boori

    2016-12-01

    Full Text Available 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.

  11. LAND SURFACE TEMPERATURES ESTIMATED ON GROUNDOBSERVED DATA AND SATELLITE IMAGES, DURING THE VEGETATION PERIOD IN THE OLTENIA PLAIN

    Directory of Open Access Journals (Sweden)

    ONŢEL IRINA

    2015-03-01

    Full Text Available The purpose of this study is to analyze the land surface temperatures by using climatological and remote sensing data during the vegetation period in the Oltenia Plain. The data used in this study refer both to climatological data (namely monthly and seasonal air and soil temperatures, and to remote sensing data delivered by MODIS Land Surface Temperature (LST, with a spatial resolution of 1 km. The analyzed period spans from 2000 to 2013 and the vegetation period considered is April-September. As main results, there were observed four years with high temperatures, namely 2000 (20.4oC-air T, 24.6oC soil T, and 26oC LST, 2003 (20.2oC air T, 23.9oC soil T and 24.5oC LST, 2007 (20.5oC air T, 24.3oC soil T and 25oC LST and 2012 (21.3oC air T, 25.7oC soil T and 26.5oC LST. The correlations between air temperature, soil temperature and LST were statisticaly significant. The diference between air temperature and soil temperature values ranked within 3-4oC, while the difference between soil temperature and land surface temperature obtained from MODIS images was about 0.8oC. Spatially, the highest temperatures were recorded on the Leu-Rotunda Field, the Caracal Plain and the Nedeia Field, and pretty high variations of observed temperatures seemed to depend on vegetation cover. The MODIS images represent one of the most important types of satellite data available for free, which can be successfully used in determining the climatic parameters and can help to predict the changes in plant activity, due to weather phenomena.

  12. Rain detection over land surfaces using passive microwave satellite data

    NARCIS (Netherlands)

    Bauer, P.; Burose, D.; Schulz, J.

    2002-01-01

    An algorithm is presented for the detection of surface rainfall using passive microwave measurements by satellite radiometers. The technique consists of a two-stage approach to distinguish precipitation signatures from other effects: (1) Contributions from slowly varying parameters (surface type and

  13. Advancing land surface model development with satellite-based Earth observations

    Science.gov (United States)

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

    2017-04-01

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

  14. Analysing Regional Land Surface Temperature Changes by Satellite Data, a Case Study of Zonguldak, Turkey

    Science.gov (United States)

    Sekertekin, A.; Kutoglu, S.; Kaya, S.; Marangoz, A. M.

    2014-12-01

    In recent years, climate change is one of the most important problems that the ecological system of the world has been encountering. Global warming and climate change have been studied frequently by all disciplines all over the world and Geomatics Engineering also contributes to such studies by means of remote sensing, global positioning system etc. Monitoring Land Surface Temperature (LST) via remote sensing satellites is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and there are lots of algorithms to obtain LST by remote sensing techniques. The most commonly used algorithms are split-window algorithm, temperature/emissivity separation method, mono-window algorithm and single channel method. Generally three algorithms are used to obtain LST by using Landsat 5 TM data. These algorithms are radiative transfer equation method, single channel method and mono-window algorithm. Radiative transfer equation method is not applicable because during the satellite pass, atmospheric parameters must be measured in-situ. In this research, mono window algorithm was implemented to Landsat 5 TM image. Besides, meteorological data such as humidity and temperature are used in the algorithm. Acquisition date of the image is 28.08.2011 and our study area is Zonguldak, Turkey. High resolution images are used to investigate the relationships between LST and land cover type. As a result of these analyses, area with vegetation cover has approximately 5 ºC lower temperature than the city center and arid land. Because different surface properties like reinforced concrete construction, green zones and sandbank are all together in city center, LST differs about 10 ºC in the city center. The temperature around some places in thermal power plant region Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature because of land cover structure. Thanks to this

  15. Global Drought Monitoring and Forecasting based on Satellite Data and Land Surface Modeling

    Science.gov (United States)

    Sheffield, J.; Lobell, D. B.; Wood, E. F.

    2010-12-01

    Monitoring drought globally is challenging because of the lack of dense in-situ hydrologic data in many regions. In particular, soil moisture measurements are absent in many regions and in real time. This is especially problematic for developing regions such as Africa where water information is arguably most needed, but virtually non-existent on the ground. With the emergence of remote sensing estimates of all components of the water cycle there is now the potential to monitor the full terrestrial water cycle from space to give global coverage and provide the basis for drought monitoring. These estimates include microwave-infrared merged precipitation retrievals, evapotranspiration based on satellite radiation, temperature and vegetation data, gravity recovery measurements of changes in water storage, microwave based retrievals of soil moisture and altimetry based estimates of lake levels and river flows. However, many challenges remain in using these data, especially due to biases in individual satellite retrieved components, their incomplete sampling in time and space, and their failure to provide budget closure in concert. A potential way forward is to use modeling to provide a framework to merge these disparate sources of information to give physically consistent and spatially and temporally continuous estimates of the water cycle and drought. Here we present results from our experimental global water cycle monitor and its African drought monitor counterpart (http://hydrology.princeton.edu/monitor). The system relies heavily on satellite data to drive the Variable Infiltration Capacity (VIC) land surface model to provide near real-time estimates of precipitation, evapotranspiraiton, soil moisture, snow pack and streamflow. Drought is defined in terms of anomalies of soil moisture and other hydrologic variables relative to a long-term (1950-2000) climatology. We present some examples of recent droughts and how they are identified by the system, including

  16. Monitoring Multidecadal satellite earth observation of soil moisture products through land surface reanalysis

    NARCIS (Netherlands)

    Albergel, C.; Dorigo, W.; Balsamo, G.; Sabatar, J; de Rosnay, P.; Isaksen, I; Brocca, L; de Jeu, R.A.M.; Wagner, W.

    2013-01-01

    Soil moisture from ERA-Land, a revised version of the land surface components of the European Centre for Medium-Range Weather Forecasts Interim reanalysis (ERA-Interim), is used to monitor at a global scale the consistency of a new microwave based multi-satellite surface soil moisture date set

  17. Improving evapotranspiration in a land surface model using biophysical variables derived from MSG/SEVIRI satellite

    Directory of Open Access Journals (Sweden)

    N. Ghilain

    2012-08-01

    Full Text Available Monitoring evapotranspiration over land is highly dependent on the surface state and vegetation dynamics. Data from spaceborn platforms are desirable to complement estimations from land surface models. The success of daily evapotranspiration monitoring at continental scale relies on the availability, quality and continuity of such data. The biophysical variables derived from SEVIRI on board the geostationary satellite Meteosat Second Generation (MSG and distributed by the Satellite Application Facility on Land surface Analysis (LSA-SAF are particularly interesting for such applications, as they aimed at providing continuous and consistent daily time series in near-real time over Africa, Europe and South America. In this paper, we compare them to monthly vegetation parameters from a database commonly used in numerical weather predictions (ECOCLIMAP-I, showing the benefits of the new daily products in detecting the spatial and temporal (seasonal and inter-annual variability of the vegetation, especially relevant over Africa. We propose a method to handle Leaf Area Index (LAI and Fractional Vegetation Cover (FVC products for evapotranspiration monitoring with a land surface model at 3–5 km spatial resolution. The method is conceived to be applicable for near-real time processes at continental scale and relies on the use of a land cover map. We assess the impact of using LSA-SAF biophysical variables compared to ECOCLIMAP-I on evapotranspiration estimated by the land surface model H-TESSEL. Comparison with in-situ observations in Europe and Africa shows an improved estimation of the evapotranspiration, especially in semi-arid climates. Finally, the impact on the land surface modelled evapotranspiration is compared over a north–south transect with a large gradient of vegetation and climate in Western Africa using LSA-SAF radiation forcing derived from remote sensing. Differences are highlighted. An evaluation against remote sensing derived land

  18. Integrating satellite retrieved leaf chlorophyll into land surface models for constraining simulations of water and carbon fluxes

    KAUST Repository

    Houborg, Rasmus; Cescatti, Alessandro; Gitelson, Anatoly A.

    2013-01-01

    variability exists. Satellite remote sensing can support modeling efforts by offering distributed information on important land surface characteristics, which would be very difficult to obtain otherwise. This study investigates the utility of satellite based

  19. Modeling directional effects in land surface temperature derived from geostationary satellite data

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander

    This PhD-thesis investigates the directional effects in land surface temperature (LST) estimates from the SEVIRI sensor onboard the Meteosat Second Generation (MSG) satellites. The directional effects are caused by the land surface structure (i.e. tree size and shape) interacting with the changing...... sun-target-sensor geometry. The directional effects occur because the different surface components, e.g. tree canopies and bare soil surfaces, will in many cases have significantly different temperatures. Depending on the viewing angle, different fractions of each of the components will be viewed...... by the sensor. This is further complicated by temperature differences between the sunlit and shaded parts of each of the components, controlled by the exposure of the components to direct sunlight. As the SEVIRI sensor is onboard a geostationary platform, the viewing geometry is fixed (for each pixel), while...

  20. NORSEWInD satellite wind climatology

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete; Mouche, Alexis

    The EU-NORSEWInD project www.norsewind.eu has taken place from August 2008 to July 2012 (4 years). NORSEWInD is short for Northern Seas Wind Index database. In the project ocean surface wind observations from space have been retrieved, processed and analysed. The overall aim of the work...... is to provide new offshore wind climatology map for the entire area of interest based on satellite remote sensing. This has been based on Synthetic Aperture Radar (SAR) from Envisat ASAR using 9000 scenes re-processed with ECMWF wind direction and CMOD-IFR. The number of overlapping samples range from 450...... in the Irish Sea to more than 1200 in most of the Baltic Sea. Wind resource statistics include maps at 2 km spatial resolution of mean wind speed, Weibull A and k, and energy density at 10 m above sea level. Uncertainty estimates on the number of available samples for each of the four parameters are presented...

  1. FLDAS Noah Land Surface Model L4 Monthly Climatology 0.1 x 0.1 degree for Eastern Africa (MERRA-2 and CHIRPS) V001 (FLDAS_NOAH01_C_EA_MC) at GES DISC

    Data.gov (United States)

    National Aeronautics and Space Administration — The monthly climatology data set contains a series of land surface parameters simulated from the Noah 3.3 model in the Famine Early Warning Systems Network (FEWS...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2010-01-01

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

  4. ANALYSING THE EFFECTS OF DIFFERENT LAND COVER TYPES ON LAND SURFACE TEMPERATURE USING SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    A. Şekertekin

    2015-12-01

    Full Text Available Monitoring Land Surface Temperature (LST via remote sensing images is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and it also helps us to understand the behavior of urban heat islands. There are lots of algorithms to obtain LST by remote sensing techniques. The most commonly used algorithms are split-window algorithm, temperature/emissivity separation method, mono-window algorithm and single channel method. In this research, mono window algorithm was implemented to Landsat 5 TM image acquired on 28.08.2011. Besides, meteorological data such as humidity and temperature are used in the algorithm. Moreover, high resolution Geoeye-1 and Worldview-2 images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. As a result of the analyses, area with vegetation cover has approximately 5 ºC lower temperatures than the city center and arid land., LST values change about 10 ºC in the city center because of different surface properties such as reinforced concrete construction, green zones and sandbank. The temperature around some places in thermal power plant region (ÇATES and ZETES Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure.

  5. Analysing the Effects of Different Land Cover Types on Land Surface Temperature Using Satellite Data

    Science.gov (United States)

    Şekertekin, A.; Kutoglu, Ş. H.; Kaya, S.; Marangoz, A. M.

    2015-12-01

    Monitoring Land Surface Temperature (LST) via remote sensing images is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and it also helps us to understand the behavior of urban heat islands. There are lots of algorithms to obtain LST by remote sensing techniques. The most commonly used algorithms are split-window algorithm, temperature/emissivity separation method, mono-window algorithm and single channel method. In this research, mono window algorithm was implemented to Landsat 5 TM image acquired on 28.08.2011. Besides, meteorological data such as humidity and temperature are used in the algorithm. Moreover, high resolution Geoeye-1 and Worldview-2 images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. As a result of the analyses, area with vegetation cover has approximately 5 ºC lower temperatures than the city center and arid land., LST values change about 10 ºC in the city center because of different surface properties such as reinforced concrete construction, green zones and sandbank. The temperature around some places in thermal power plant region (ÇATES and ZETES) Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure.

  6. Evaluation of Land Surface Temperature Operationally Retrieved from Korean Geostationary Satellite (COMS Data

    Directory of Open Access Journals (Sweden)

    A-Ra Cho

    2013-08-01

    Full Text Available We evaluated the precision of land surface temperature (LST operationally retrieved from the Korean multipurpose geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS. The split-window (SW-type retrieval algorithm was developed through radiative transfer model simulations under various atmospheric profiles, satellite zenith angles, surface emissivity values and surface lapse rate conditions using Moderate Resolution Atmospheric Transmission version 4 (MODTRAN4. The estimation capabilities of the COMS SW (CSW LST algorithm were evaluated for various impacting factors, and the retrieval accuracy of COMS LST data was evaluated with collocated Moderate Resolution Imaging Spectroradiometer (MODIS LST data. The surface emissivity values for two SW channels were generated using a vegetation cover method. The CSW algorithm estimated the LST distribution reasonably well (averaged bias = 0.00 K, Root Mean Square Error (RMSE = 1.41 K, correlation coefficient = 0.99; however, the estimation capabilities of the CSW algorithm were significantly impacted by large brightness temperature differences and surface lapse rates. The CSW algorithm reproduced spatiotemporal variations of LST comparing well to MODIS LST data, irrespective of what month or time of day the data were collected from. The one-year evaluation results with MODIS LST data showed that the annual mean bias, RMSE and correlation coefficient for the CSW algorithm were −1.009 K, 2.613 K and 0.988, respectively.

  7. Satellite Estimation of Daily Land Surface Water Vapor Pressure Deficit from AMSR- E

    Science.gov (United States)

    Jones, L. A.; Kimball, J. S.; McDonald, K. C.; Chan, S. K.; Njoku, E. G.; Oechel, W. C.

    2007-12-01

    Vapor pressure deficit (VPD) is a key variable for monitoring land surface water and energy exchanges, and estimating plant water stress. Multi-frequency day/night brightness temperatures from the Advanced Microwave Scanning Radiometer on EOS Aqua (AMSR-E) were used to estimate daily minimum and average near surface (2 m) air temperatures across a North American boreal-Arctic transect. A simple method for determining daily mean VPD (Pa) from AMSR-E air temperature retrievals was developed and validated against observations across a regional network of eight study sites ranging from boreal grassland and forest to arctic tundra. The method assumes that the dew point and minimum daily air temperatures tend to equilibrate in areas with low night time temperatures and relatively moist conditions. This assumption was tested by comparing the VPD algorithm results derived from site daily temperature observations against results derived from AMSR-E retrieved temperatures alone. An error analysis was conducted to determine the amount of error introduced in VPD estimates given known levels of error in satellite retrieved temperatures. Results indicate that the assumption generally holds for the high latitude study sites except for arid locations in mid-summer. VPD estimates using the method with AMSR-E retrieved temperatures compare favorably with site observations. The method can be applied to land surface temperature retrievals from any sensor with day and night surface or near-surface thermal measurements and shows potential for inferring near-surface wetness conditions where dense vegetation may hinder surface soil moisture retrievals from low-frequency microwave sensors. This work was carried out at The University of Montana, at San Diego State University, and at the Jet Propulsion Laboratory, California Institute of Technology, under contract to the National Aeronautics and Space Administration.

  8. Comparing land surface phenology derived from satellite and GPS network microwave remote sensing.

    Science.gov (United States)

    Jones, Matthew O; Kimball, John S; Small, Eric E; Larson, Kristine M

    2014-08-01

    The land surface phenology (LSP) start of season (SOS) metric signals the seasonal onset of vegetation activity, including canopy growth and associated increases in land-atmosphere water, energy and carbon (CO2) exchanges influencing weather and climate variability. The vegetation optical depth (VOD) parameter determined from satellite passive microwave remote sensing provides for global LSP monitoring that is sensitive to changes in vegetation canopy water content and biomass, and insensitive to atmosphere and solar illumination constraints. Direct field measures of canopy water content and biomass changes desired for LSP validation are generally lacking due to the prohibitive costs of maintaining regional monitoring networks. Alternatively, a normalized microwave reflectance index (NMRI) derived from GPS base station measurements is sensitive to daily vegetation water content changes and may provide for effective microwave LSP validation. We compared multiyear (2007-2011) NMRI and satellite VOD records at over 300 GPS sites in North America, and their derived SOS metrics for a subset of 24 homogenous land cover sites to investigate VOD and NMRI correspondence, and potential NMRI utility for LSP validation. Significant correlations (P<0.05) were found at 276 of 305 sites (90.5 %), with generally favorable correspondence in the resulting SOS metrics (r (2)=0.73, P<0.001, RMSE=36.8 days). This study is the first attempt to compare satellite microwave LSP metrics to a GPS network derived reflectance index and highlights both the utility and limitations of the NMRI data for LSP validation, including spatial scale discrepancies between local NMRI measurements and relatively coarse satellite VOD retrievals.

  9. Derivation and evaluation of land surface temperature from the geostationary operational environmental satellite series

    Science.gov (United States)

    Fang, Li

    The Geostationary Operational Environmental Satellites (GOES) have been continuously monitoring the earth surface since 1970, providing valuable and intensive data from a very broad range of wavelengths, day and night. The National Oceanic and Atmospheric Administration's (NOAA's) National Environmental Satellite, Data, and Information Service (NESDIS) is currently operating GOES-15 and GOES-13. The design of the GOES series is now heading to the 4 th generation. GOES-R, as a representative of the new generation of the GOES series, is scheduled to be launched in 2015 with higher spatial and temporal resolution images and full-time soundings. These frequent observations provided by GOES Image make them attractive for deriving information on the diurnal land surface temperature (LST) cycle and diurnal temperature range (DTR). These parameters are of great value for research on the Earth's diurnal variability and climate change. Accurate derivation of satellite-based LSTs from thermal infrared data has long been an interesting and challenging research area. To better support the research on climate change, the generation of consistent GOES LST products for both GOES-East and GOES-West from operational dataset as well as historical archive is in great demand. The derivation of GOES LST products and the evaluation of proposed retrieval methods are two major objectives of this study. Literature relevant to satellite-based LST retrieval techniques was reviewed. Specifically, the evolution of two LST algorithm families and LST retrieval methods for geostationary satellites were summarized in this dissertation. Literature relevant to the evaluation of satellite-based LSTs was also reviewed. All the existing methods are a valuable reference to develop the GOES LST product. The primary objective of this dissertation is the development of models for deriving consistent GOES LSTs with high spatial and high temporal coverage. Proper LST retrieval algorithms were studied

  10. Hurricane Satellite (HURSAT) from International Satellite Cloud Climatology Project (ISCCP) B1, Version 6

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Hurricane Satellite (HURSAT) from derived International Satellite Cloud Climatology Project (ISCCP) B1 observations of tropical cyclones worldwide. The B1 data...

  11. Satellite-derived land surface parameters for mesoscale modelling of the Mexico City basin

    Directory of Open Access Journals (Sweden)

    B. de Foy

    2006-01-01

    Full Text Available Mesoscale meteorological modelling is an important tool to help understand air pollution and heat island effects in urban areas. Accurate wind simulations are difficult to obtain in areas of weak synoptic forcing. Local factors have a dominant role in the circulation and include land surface parameters and their interaction with the atmosphere. This paper examines an episode during the MCMA-2003 field campaign held in the Mexico City Metropolitan Area (MCMA in April of 2003. Because the episode has weak synoptic forcing, there is the potential for the surface heat budget to influence the local meteorology. High resolution satellite observations are used to specify the land use, vegetation fraction, albedo and surface temperature in the MM5 model. Making use of these readily available data leads to improved meteorological simulations in the MCMA, both for the wind circulation patterns and the urban heat island. Replacing values previously obtained from land-use tables with actual measurements removes the number of unknowns in the model and increases the accuracy of the energy budget. In addition to improving the understanding of local meteorology, this sets the stage for the use of advanced urban modules.

  12. Estimation of Global Vegetation Productivity from Global LAnd Surface Satellite Data

    Directory of Open Access Journals (Sweden)

    Tao Yu

    2018-02-01

    Full Text Available Accurately estimating vegetation productivity is important in research on terrestrial ecosystems, carbon cycles and climate change. Eight-day gross primary production (GPP and annual net primary production (NPP are contained in MODerate Resolution Imaging Spectroradiometer (MODIS products (MOD17, which are considered the first operational datasets for monitoring global vegetation productivity. However, the cloud-contaminated MODIS leaf area index (LAI and Fraction of Photosynthetically Active Radiation (FPAR retrievals may introduce some considerable errors to MODIS GPP and NPP products. In this paper, global eight-day GPP and eight-day NPP were first estimated based on Global LAnd Surface Satellite (GLASS LAI and FPAR products. Then, GPP and NPP estimates were validated by FLUXNET GPP data and BigFoot NPP data and were compared with MODIS GPP and NPP products. Compared with MODIS GPP, a time series showed that estimated GLASS GPP in our study was more temporally continuous and spatially complete with smoother trajectories. Validated with FLUXNET GPP and BigFoot NPP, we demonstrated that estimated GLASS GPP and NPP achieved higher precision for most vegetation types.

  13. Variations in global land surface phenology: a comparison of satellite optical and passive microwave data

    Science.gov (United States)

    Tong, X.; Tian, F.; Brandt, M.; Zhang, W.; Liu, Y.; Fensholt, R.

    2017-12-01

    Changes in vegetation phenological events are among the most sensitive biological responses to climate change. In last decades, facilitating by satellite remote sensing techniques, land surface phenology (LSP) have been monitored at global scale using proxy approaches as tracking the temporal change of a satellite-derived vegetation index. However, the existing global assessments of changes in LSP are all established on the basis of leaf phenology using NDVI derived from optical sensors, being responsive to vegetation canopy cover and greenness. Instead, the vegetation optical depth (VOD) parameter from passive microwave sensors, which is sensitive to the aboveground vegetation water content by including as well the woody components in the observations, provides an alternative, independent and comprehensive means for global vegetation phenology monitoring. We used the unique long-term global VOD record available for the period 1992-2012 to monitoring the dynamics of LSP metrics (length of season, start of season and end of season) in comparison with the dynamics of LSP metrics derived from the latest GIMMS NDVI3G V1. We evaluated the differences in the linear trends of LSP metrics between two datasets. Currently, our results suggest that the level of seasonality variation of vegetation water content is less than the vegetation greenness. We found significant phenological changes in vegetation water content in African woodlands, where has been reported with little leaf phenological change regardless of the delays in rainfall onset. Therefore, VOD might allow us to detect temporal shifts in the timing difference of vegetation water storage vs. leaf emergence and to see if some ecophysiological thresholds seem to be reached, that could cause species turnover as climate change-driven alterations to the African monsoon proceed.

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

    Science.gov (United States)

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

    2017-12-01

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

  15. Land surface temperature distribution and development for green open space in Medan city using imagery-based satellite Landsat 8

    Science.gov (United States)

    Sulistiyono, N.; Basyuni, M.; Slamet, B.

    2018-03-01

    Green open space (GOS) is one of the requirements where a city is comfortable to stay. GOS might reduce land surface temperature (LST) and air pollution. Medan is one of the biggest towns in Indonesia that experienced rapid development. However, the early development tends to neglect the GOS existence for the city. The objective of the study is to determine the distribution of land surface temperature and the relationship between the normalized difference vegetation index (NDVI) and the priority of GOS development in Medan City using imagery-based satellite Landsat 8. The method approached to correlate the distribution of land surface temperature derived from the value of digital number band 10 with the NDVI which was from the ratio of groups five and four on satellite images of Landsat 8. The results showed that the distribution of land surface temperature in the Medan City in 2016 ranged 20.57 - 33.83 °C. The relationship between the distribution of LST distribution with NDVI was reversed with a negative correlation of -0.543 (sig 0,000). The direction of GOS in Medan City is therefore developed on the allocation of LST and divided into three priority classes namely first priority class had 5,119.71 ha, the second priority consisted of 16,935.76 ha, and third priority of 6,118.50 ha.

  16. Climatology 2011: An MLS and Sonde Derived Ozone Climatology for Satellite Retrieval Algorithms

    Science.gov (United States)

    McPeters, Richard D.; Labow, Gordon J.

    2012-01-01

    The ozone climatology used as the a priori for the version 8 Solar Backscatter Ultraviolet (SBUV) retrieval algorithms has been updated. The Microwave Limb Sounder (MLS) instrument on Aura has excellent latitude coverage and measures ozone daily from the upper troposphere to the lower mesosphere. The new climatology consists of monthly average ozone profiles for ten degree latitude zones covering pressure altitudes from 0 to 65 km. The climatology was formed by combining data from Aura MLS (2004-2010) with data from balloon sondes (1988-2010). Ozone below 8 km (below 12 km at high latitudes) is based on balloons sondes, while ozone above 16 km (21 km at high latitudes) is based on MLS measurements. Sonde and MLS data are blended in the transition region. Ozone accuracy in the upper troposphere is greatly improved because of the near uniform coverage by Aura MLS, while the addition of a large number of balloon sonde measurements improves the accuracy in the lower troposphere, in the tropics and southern hemisphere in particular. The addition of MLS data also improves the accuracy of climatology in the upper stratosphere and lower mesosphere. The revised climatology has been used for the latest reprocessing of SBUV and TOMS satellite ozone data.

  17. Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

    Science.gov (United States)

    Reichle, Rolf H.; De Lannoy, Gabrielle J. M.

    2012-01-01

    The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters

  18. Land Surface Temperature- Comparing Data from Polar Orbiting and Geostationary Satellites

    Science.gov (United States)

    Comyn-Platt, E.; Remedios, J. J.; Good, E. J.; Ghent, D.; Saunders, R.

    2012-04-01

    Land Surface Temperature (LST) is a vital parameter in Earth climate science, driving long-wave radiation exchanges that control the surface energy budget and carbon fluxes, which are important factors in Numerical Weather Prediction (NWP) and the monitoring of climate change. Satellites offer a convenient way to observe LST consistently and regularly over large areas. A comparison between LST retrieved from a Geostationary Instrument, the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), and a Polar Orbiting Instrument, the Advanced Along Track Scanning Radiometer (AATSR) is presented. Both sensors offer differing benefits. AATSR offers superior precision and spatial resolution with global coverage but given its sun-synchronous platform only observes at two local times, ~10am and ~10pm. SEVIRI provides the high-temporal resolution (every 15 minutes) required for observing diurnal variability of surface temperatures but given its geostationary platform has a poorer resolution, 3km at nadir, which declines at higher latitudes. A number of retrieval methods are applied to the raw satellite data: First order coefficient based algorithms provided on an operational basis by the LandSAF (for SEVIRI) and the University of Leicester (for AATSR); Second order coefficient based algorithms put forward by the University of Valencia; and an optimal estimation method using the 1DVar software provided by the NWP SAF. Optimal estimation is an iterative technique based upon inverse theory, thus is very useful for expanding into data assimilation systems. The retrievals are assessed and compared on both a fine scale using in-situ data from recognised validation sites and on a broad scale using two 100x100 regions such that biases can be better understood. Overall, the importance of LST lies in monitoring daily temperature extremes, e.g. for estimating permafrost thawing depth or risk of crop damage due to frost, hence the ideal dataset would use a combination of observations

  19. Impacts of Satellite-Based Snow Albedo Assimilation on Offline and Coupled Land Surface Model Simulations.

    Directory of Open Access Journals (Sweden)

    Tao Wang

    Full Text Available Seasonal snow cover in the Northern Hemisphere is the largest component of the terrestrial cryosphere and plays a major role in the climate system through strong positive feedbacks related to albedo. The snow-albedo feedback is invoked as an important cause for the polar amplification of ongoing and projected climate change, and its parameterization across models is an important source of uncertainty in climate simulations. Here, instead of developing a physical snow albedo scheme, we use a direct insertion approach to assimilate satellite-based surface albedo during the snow season (hereafter as snow albedo assimilation into the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms and assess the influences of such assimilation on offline and coupled simulations. Our results have shown that snow albedo assimilation in both ORCHIDEE and ORCHIDEE-LMDZ (a general circulation model of Laboratoire de Météorologie Dynamique improve the simulation accuracy of mean seasonal (October throughout May snow water equivalent over the region north of 40 degrees. The sensitivity of snow water equivalent to snow albedo assimilation is more pronounced in the coupled simulation than the offline simulation since the feedback of albedo on air temperature is allowed in ORCHIDEE-LMDZ. We have also shown that simulations of air temperature at 2 meters in ORCHIDEE-LMDZ due to snow albedo assimilation are significantly improved during the spring in particular over the eastern Siberia region. This is a result of the fact that high amounts of shortwave radiation during the spring can maximize its snow albedo feedback, which is also supported by the finding that the spatial sensitivity of temperature change to albedo change is much larger during the spring than during the autumn and winter. In addition, the radiative forcing at the top of the atmosphere induced by snow albedo assimilation during the spring is estimated to be -2.50 W m-2, the

  20. Integrating satellite retrieved leaf chlorophyll into land surface models for constraining simulations of water and carbon fluxes

    KAUST Repository

    Houborg, Rasmus

    2013-07-01

    In terrestrial biosphere models, key biochemical controls on carbon uptake by vegetation canopies are typically assigned fixed literature-based values for broad categories of vegetation types although in reality significant spatial and temporal variability exists. Satellite remote sensing can support modeling efforts by offering distributed information on important land surface characteristics, which would be very difficult to obtain otherwise. This study investigates the utility of satellite based retrievals of leaf chlorophyll for estimating leaf photosynthetic capacity and for constraining model simulations of water and carbon fluxes. © 2013 IEEE.

  1. Observational and Dynamical Wave Climatologies. VOS vs Satellite Data

    Science.gov (United States)

    Grigorieva, Victoria; Badulin, Sergei; Chernyshova, Anna

    2013-04-01

    The understanding physics of wind-driven waves is crucially important for fundamental science and practical applications. This is why experimental efforts are targeted at both getting reliable information on sea state and elaborating effective tools of the sea wave forecasting. The global Visual Wave Observations and satellite data from the GLOBWAVE project of the European Space Agency are analyzed in the context of these two viewpoints. Within the first "observational" aspect we re-analyze conventional climatologies of all basic wave parameters for the last decades [5]. An alternative "dynamical" climatology is introduced as a tool of prediction of dynamical features of sea waves on global scales. The features of wave dynamics are studied in terms of one-parametric dependencies of wave heights on wave periods following the theoretical concept of self-similar wind-driven seas [3, 1, 4] and recently proposed approach to analysis of Voluntary Observing Ship (VOS) data [2]. Traditional "observational" climatologies based on VOS and satellite data collections demonstrate extremely consistent pictures for significant wave heights and dominant periods. On the other hand, collocated satellite and VOS data show significant differences in wave heights, wind speeds and, especially, in wave periods. Uncertainties of visual wave observations can explain these differences only partially. We see the key reason of this inconsistency in the methods of satellite data processing which are based on formal application of data interpolation methods rather than on up-to-date physics of wind-driven waves. The problem is considered within the alternative climatology approach where dynamical criteria of wave height-to-period linkage are used for retrieving wave periods and constructing physically consistent dynamical climatology. The key dynamical parameter - exponent R of one-parametric dependence Hs ~ TR shows dramatically less pronounced latitudinal dependence as compared to observed Hs

  2. A satellite and model based flood inundation climatology of Australia

    Science.gov (United States)

    Schumann, G.; Andreadis, K.; Castillo, C. J.

    2013-12-01

    To date there is no coherent and consistent database on observed or simulated flood event inundation and magnitude at large scales (continental to global). The only compiled data set showing a consistent history of flood inundation area and extent at a near global scale is provided by the MODIS-based Dartmouth Flood Observatory. However, MODIS satellite imagery is only available from 2000 and is hampered by a number of issues associated with flood mapping using optical images (e.g. classification algorithms, cloud cover, vegetation). Here, we present for the first time a proof-of-concept study in which we employ a computationally efficient 2-D hydrodynamic model (LISFLOOD-FP) complemented with a sub-grid channel formulation to generate a complete flood inundation climatology of the past 40 years (1973-2012) for the entire Australian continent. The model was built completely from freely available SRTM-derived data, including channel widths, bank heights and floodplain topography, which was corrected for vegetation canopy height using a global ICESat canopy dataset. Channel hydraulics were resolved using actual channel data and bathymetry was estimated within the model using hydraulic geometry. On the floodplain, the model simulated the flow paths and inundation variables at a 1 km resolution. The developed model was run over a period of 40 years and a floodplain inundation climatology was generated and compared to satellite flood event observations. Our proof-of-concept study demonstrates that this type of model can reliably simulate past flood events with reasonable accuracies both in time and space. The Australian model was forced with both observed flow climatology and VIC-simulated flows in order to assess the feasibility of a model-based flood inundation climatology at the global scale.

  3. Linking Satellite Derived Land Surface Temperature with Cholera: A Case Study for South Sudan

    Science.gov (United States)

    Aldaach, H. S. V.; Jutla, A.; Akanda, A. S.; Colwell, R. R.

    2014-12-01

    A sudden onset of cholera in South Sudan, in April 2014 in Northern Bari in Juba town resulted in more than 400 cholera cases after four weeks of initial outbreak with a case of fatality rate of CFR 5.4%. The total number of reported cholera cases for the period of April to July, 2014 were 5,141 including 114 deaths. With the limited efficacy of cholera vaccines, it is necessary to develop mechanisms to predict cholera occurrence and thereafter devise intervention strategies for mitigating impacts of the disease. Hydroclimatic processes, primarily precipitation and air temperature are related to epidemic and episodic outbreak of cholera. However, due to coarse resolution of both datasets, it is not possible to precisely locate the geographical location of disease. Here, using Land Surface Temperature (LST) from MODIS sensors, we have developed an algorithm to identify regions susceptible for cholera. Conditions for occurrence of cholera were detectable at least one month in advance in South Sudan and were statistically sensitive to hydroclimatic anomalies of land surface and air temperature, and precipitation. Our results indicate significant spatial and temporal averaging required to infer usable information from LST over South Sudan. Preliminary results that geographically location of cholera outbreak was identifiable within 1km resolution of the LST data.

  4. A Satellite-Derived Climatological Analysis of Urban Heat Island over Shanghai during 2000–2013

    Directory of Open Access Journals (Sweden)

    Weijiao Huang

    2017-06-01

    Full Text Available The urban heat island is generally conducted based on ground observations of air temperature and remotely sensing of land surface temperature (LST. Satellite remotely sensed LST has the advantages of global coverage and consistent periodicity, which overcomes the weakness of ground observations related to sparse distributions and costs. For human related studies and urban climatology, canopy layer urban heat island (CUHI based on air temperatures is extremely important. This study has employed remote sensing methodology to produce monthly CUHI climatology maps during the period 2000–2013, revealing the spatiotemporal characteristics of daytime and nighttime CUHI during this period of rapid urbanization in Shanghai. Using stepwise linear regression, daytime and nighttime air temperatures at the four overpass times of Terra/Aqua were estimated based on time series of Terra/Aqua-MODIS LST and other auxiliary variables including enhanced vegetation index, normalized difference water index, solar zenith angle and distance to coast. The validation results indicate that the models produced an accuracy of 1.6–2.6 °C RMSE for the four overpass times of Terra/Aqua. The models based on Terra LST showed higher accuracy than those based on Aqua LST, and nighttime air temperature estimation had higher accuracy than daytime. The seasonal analysis shows daytime CUHI is strongest in summer and weakest in winter, while nighttime CUHI is weakest in summer and strongest in autumn. The annual mean daytime CUHI during 2000–2013 is 1.0 and 2.2 °C for Terra and Aqua overpass, respectively. The annual mean nighttime CUHI is about 1.0 °C for both Terra and Aqua overpass. The resultant CUHI climatology maps provide a spatiotemporal quantification of CUHI with emphasis on temperature gradients. This study has provided information of relevance to urban planners and environmental managers for assessing and monitoring urban thermal environments which are constantly

  5. Land Surface Data Assimilation

    Science.gov (United States)

    Houser, P. R.

    2012-12-01

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

  6. Estimation of land surface temperature based on satellite image data. Paper no. IGEC-1-117

    International Nuclear Information System (INIS)

    Torii, S.; Yano, T.; Iino, N.

    2005-01-01

    The aim of the present study is to predict a ground surface temperature (GST) of Kagoshima Prefecture in Kyushu Island, Japan, by using LANDSAT-5/TM and NOAA-11/AVHRR digital data. Image processing procedure is employed to aid in evaluating GST, in which the thermal images of AVHRR bands 4 and 5 are analysed. Emphasis is placed on the prediction accuracy of the existing atmospheric correlation equations taking the atmospheric attenuation effect into account, which are proposed by Tamba et. al., Bates and Diaz, and Sakkaida and Kawamura. It is disclosed that (I) the factor of the zenith angle need to be taken into account when the accurate GST is evaluated by using the atmospheric correction equations, (ii) that of Sakaida and Kawamura has better accuracy, (iii) LANDSAT-5/TM data contains a very high resolution level of the land, the estimated land surface temperature is higher than the measured value, and (iv) improved accuracy of the surface temperature is achieved if LANDSAT-5/TM data are used together with NOAA-11/AVHRR. (author)

  7. Agriculture pest and disease risk maps considering MSG satellite data and land surface temperature

    Science.gov (United States)

    Marques da Silva, J. R.; Damásio, C. V.; Sousa, A. M. O.; Bugalho, L.; Pessanha, L.; Quaresma, P.

    2015-06-01

    Pest risk maps for agricultural use are usually constructed from data obtained from in-situ meteorological weather stations, which are relatively sparsely distributed and are often quite expensive to install and difficult to maintain. This leads to the creation of maps with relatively low spatial resolution, which are very much dependent on interpolation methodologies. Considering that agricultural applications typically require a more detailed scale analysis than has traditionally been available, remote sensing technology can offer better monitoring at increasing spatial and temporal resolutions, thereby, improving pest management results and reducing costs. This article uses ground temperature, or land surface temperature (LST), data distributed by EUMETSAT/LSASAF (with a spatial resolution of 3 × 3 km (nadir resolution) and a revisiting time of 15 min) to generate one of the most commonly used parameters in pest modeling and monitoring: "thermal integral over air temperature (accumulated degree-days)". The results show a clear association between the accumulated LST values over a threshold and the accumulated values computed from meteorological stations over the same threshold (specific to a particular tomato pest). The results are very promising and enable the production of risk maps for agricultural pests with a degree of spatial and temporal detail that is difficult to achieve using in-situ meteorological stations.

  8. Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research

    Science.gov (United States)

    Maxwell, S.K.; Meliker, J.R.; Goovaerts, P.

    2010-01-01

    In recent years, geographic information systems (GIS) have increasingly been used for reconstructing individual-level exposures to environmental contaminants in epidemiological research. Remotely sensed data can be useful in creating space-time models of environmental measures. The primary advantage of using remotely sensed data is that it allows for study at the local scale (e.g., residential level) without requiring expensive, time-consuming monitoring campaigns. The purpose of our study was to identify how land surface remotely sensed data are currently being used to study the relationship between cancer and environmental contaminants, focusing primarily on agricultural chemical exposure assessment applications. We present the results of a comprehensive literature review of epidemiological research where remotely sensed imagery or land cover maps derived from remotely sensed imagery were applied. We also discuss the strengths and limitations of the most commonly used imagery data (aerial photographs and Landsat satellite imagery) and land cover maps.

  9. Assessing the Regional/Diurnal Bias between Satellite Retrievals and GEOS-5/MERRA Model Estimates of Land Surface Temperature

    Science.gov (United States)

    Scarino, B. R.; Smith, W. L., Jr.; Minnis, P.; Bedka, K. M.

    2017-12-01

    Atmospheric models rely on high-accuracy, high-resolution initial radiometric and surface conditions for better short-term meteorological forecasts, as well as improved evaluation of global climate models. Continuous remote sensing of the Earth's energy budget, as conducted by the Clouds and Earth's Radiant Energy System (CERES) project, allows for near-realtime evaluation of cloud and surface radiation properties. It is unfortunately common for there to be bias between atmospheric/surface radiation models and Earth-observations. For example, satellite-observed surface skin temperature (Ts), an important parameter for characterizing the energy exchange at the ground/water-atmosphere interface, can be biased due to atmospheric adjustment assumptions and anisotropy effects. Similarly, models are potentially biased by errors in initial conditions and regional forcing assumptions, which can be mitigated through assimilation with true measurements. As such, when frequent, broad-coverage, and accurate retrievals of satellite Ts are available, important insights into model estimates of Ts can be gained. The Satellite ClOud and Radiation Property retrieval System (SatCORPS) employs a single-channel thermal-infrared method to produce anisotropy-corrected Ts over clear-sky land and ocean surfaces from data taken by geostationary Earth orbit (GEO) satellite imagers. Regional and diurnal changes in model land surface temperature (LST) performance can be assessed owing to the somewhat continuous measurements of the LST offered by GEO satellites - measurements which are accurate to within 0.2 K. A seasonal, hourly comparison of satellite-observed LST with the NASA Goddard Earth Observing System Version 5 (GEOS-5) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA) LST estimates is conducted to reveal regional and diurnal biases. This assessment is an important first step for evaluating the effectiveness of Ts assimilation, as well for determining the

  10. Quantifying Uncertainty in Satellite-Retrieved Land Surface Temperature from Cloud Detection Errors

    Directory of Open Access Journals (Sweden)

    Claire E. Bulgin

    2018-04-01

    Full Text Available Clouds remain one of the largest sources of uncertainty in remote sensing of surface temperature in the infrared, but this uncertainty has not generally been quantified. We present a new approach to do so, applied here to the Advanced Along-Track Scanning Radiometer (AATSR. We use an ensemble of cloud masks based on independent methodologies to investigate the magnitude of cloud detection uncertainties in area-average Land Surface Temperature (LST retrieval. We find that at a grid resolution of 625 km 2 (commensurate with a 0.25 ∘ grid size at the tropics, cloud detection uncertainties are positively correlated with cloud-cover fraction in the cell and are larger during the day than at night. Daytime cloud detection uncertainties range between 2.5 K for clear-sky fractions of 10–20% and 1.03 K for clear-sky fractions of 90–100%. Corresponding night-time uncertainties are 1.6 K and 0.38 K, respectively. Cloud detection uncertainty shows a weaker positive correlation with the number of biomes present within a grid cell, used as a measure of heterogeneity in the background against which the cloud detection must operate (e.g., surface temperature, emissivity and reflectance. Uncertainty due to cloud detection errors is strongly dependent on the dominant land cover classification. We find cloud detection uncertainties of a magnitude of 1.95 K over permanent snow and ice, 1.2 K over open forest, 0.9–1 K over bare soils and 0.09 K over mosaic cropland, for a standardised clear-sky fraction of 74.2%. As the uncertainties arising from cloud detection errors are of a significant magnitude for many surface types and spatially heterogeneous where land classification varies rapidly, LST data producers are encouraged to quantify cloud-related uncertainties in gridded products.

  11. Hydrological Modelling and data assimilation of Satellite Snow Cover Area using a Land Surface Model, VIC

    Directory of Open Access Journals (Sweden)

    S. Naha

    2016-06-01

    Full Text Available The snow cover plays an important role in Himalayan region as it contributes a useful amount to the river discharge. So, besides estimating rainfall runoff, proper assessment of snowmelt runoff for efficient management and water resources planning is also required. A Land Surface Model, VIC (Variable Infiltration Capacity is used at a high resolution grid size of 1 km. Beas river basin up to Thalot in North West Himalayas (NWH have been selected as the study area. At first model setup is done and VIC has been run in its energy balance mode. The fluxes obtained from VIC has been routed to simulate the discharge for the time period of (2003-2006. Data Assimilation is done for the year 2006 and the techniques of Data Assimilation considered in this study are Direct Insertion (D.I and Ensemble Kalman Filter (EnKF that uses observations of snow covered area (SCA to update hydrologic model states. The meteorological forcings were taken from 0.5 deg. resolution VIC global forcing data from 1979-2006 with daily maximum temperature, minimum temperature from Climate Research unit (CRU, rainfall from daily variability of NCEP and wind speed from NCEP-NCAR analysis as main inputs and Indian Meteorological Department (IMD data of 0.25 °. NBSSLUP soil map and land use land cover map of ISRO-GBP project for year 2014 were used for generating the soil parameters and vegetation parameters respectively. The threshold temperature i.e. the minimum rain temperature is -0.5°C and maximum snow temperature is about +0.5°C at which VIC can generate snow fluxes. Hydrological simulations were done using both NCEP and IMD based meteorological Forcing datasets, but very few snow fluxes were obtained using IMD data met forcing, whereas NCEP based met forcing has given significantly better snow fluxes throughout the simulation years as the temperature resolution as given by IMD data is 0.5°C and rainfall resolution of 0.25°C. The simulated discharge has been validated

  12. LEAST SQUARE APPROACH FOR ESTIMATING OF LAND SURFACE TEMPERATURE FROM LANDSAT-8 SATELLITE DATA USING RADIATIVE TRANSFER EQUATION

    Directory of Open Access Journals (Sweden)

    Y. Jouybari-Moghaddam

    2017-09-01

    Full Text Available Land Surface Temperature (LST is one of the significant variables measured by remotely sensed data, and it is applied in many environmental and Geoscience studies. The main aim of this study is to develop an algorithm to retrieve the LST from Landsat-8 satellite data using Radiative Transfer Equation (RTE. However, LST can be retrieved from RTE, but, since the RTE has two unknown parameters including LST and surface emissivity, estimating LST from RTE is an under the determined problem. In this study, in order to solve this problem, an approach is proposed an equation set includes two RTE based on Landsat-8 thermal bands (i.e.: band 10 and 11 and two additional equations based on the relation between the Normalized Difference Vegetation Index (NDVI and emissivity of Landsat-8 thermal bands by using simulated data for Landsat-8 bands. The iterative least square approach was used for solving the equation set. The LST derived from proposed algorithm is evaluated by the simulated dataset, built up by MODTRAN. The result shows the Root Mean Squared Error (RMSE is less than 1.18°K. Therefore; the proposed algorithm can be a suitable and robust method to retrieve the LST from Landsat-8 satellite data.

  13. Least Square Approach for Estimating of Land Surface Temperature from LANDSAT-8 Satellite Data Using Radiative Transfer Equation

    Science.gov (United States)

    Jouybari-Moghaddam, Y.; Saradjian, M. R.; Forati, A. M.

    2017-09-01

    Land Surface Temperature (LST) is one of the significant variables measured by remotely sensed data, and it is applied in many environmental and Geoscience studies. The main aim of this study is to develop an algorithm to retrieve the LST from Landsat-8 satellite data using Radiative Transfer Equation (RTE). However, LST can be retrieved from RTE, but, since the RTE has two unknown parameters including LST and surface emissivity, estimating LST from RTE is an under the determined problem. In this study, in order to solve this problem, an approach is proposed an equation set includes two RTE based on Landsat-8 thermal bands (i.e.: band 10 and 11) and two additional equations based on the relation between the Normalized Difference Vegetation Index (NDVI) and emissivity of Landsat-8 thermal bands by using simulated data for Landsat-8 bands. The iterative least square approach was used for solving the equation set. The LST derived from proposed algorithm is evaluated by the simulated dataset, built up by MODTRAN. The result shows the Root Mean Squared Error (RMSE) is less than 1.18°K. Therefore; the proposed algorithm can be a suitable and robust method to retrieve the LST from Landsat-8 satellite data.

  14. Normalization and calibration of geostationary satellite radiances for the International Satellite Cloud Climatology Project

    Science.gov (United States)

    Desormeaux, Yves; Rossow, William B.; Brest, Christopher L.; Campbell, G. G.

    1993-01-01

    Procedures are described for normalizing the radiometric calibration of image radiances obtained from geostationary weather satellites that contributed data to the International Satellite Cloud Climatology Project. The key step is comparison of coincident and collocated measurements made by each satellite and the concurrent AVHRR on the 'afternoon' NOAA polar-orbiting weather satellite at the same viewing geometry. The results of this comparison allow transfer of the AVHRR absolute calibration, which has been established over the whole series, to the radiometers on the geostationary satellites. Results are given for Meteosat-2, 3, and 4, for GOES-5, 6, and 7, for GMS-2, 3, and 4 and for Insat-1B. The relative stability of the calibrations of these radiance data is estimated to be within +/- 3 percent; the uncertainty of the absolute calibrations is estimated to be less than 10 percent. The remaining uncertainties are at least two times smaller than for the original radiance data.

  15. Downscaling Satellite Land Surface Temperatures in Urban Regions for Surface Energy Balance Study and Heat Index Development

    Science.gov (United States)

    Norouzi, H.; Bah, A.; Prakash, S.; Nouri, N.; Blake, R.

    2017-12-01

    A great percentage of the world's population reside in urban areas that are exposed to the threats of global and regional climate changes and associated extreme weather events. Among them, urban heat islands have significant health and economic impacts due to higher thermal gradients of impermeable surfaces in urban regions compared to their surrounding rural areas. Therefore, accurate characterization of the surface energy balance in urban regions are required to predict these extreme events. High spatial resolution Land surface temperature (LST) in the scale of street level in the cities can provide wealth of information to study surface energy balance and eventually providing a reliable heat index. In this study, we estimate high-resolution LST maps using combination of LandSat 8 and infrared based satellite products such as Moderate Resolution Imaging Spectroradiometer (MODIS) and newly launched Geostationary Operational Environmental Satellite-R Series (GOES-R). Landsat 8 provides higher spatial resolution (30 m) estimates of skin temperature every 16 days. However, MODIS and GOES-R have lower spatial resolution (1km and 4km respectively) with much higher temporal resolution. Several statistical downscaling methods were investigated to provide high spatiotemporal LST maps in urban regions. The results reveal that statistical methods such as Principal Component Analysis (PCA) can provide reliable estimations of LST downscaling with 2K accuracy. Other methods also were tried including aggregating (up-scaling) the high-resolution data to a coarse one to examine the limitations and to build the model. Additionally, we deployed flux towers over distinct materials such as concrete, asphalt, and rooftops in New York City to monitor the sensible and latent heat fluxes through eddy covariance method. To account for the incoming and outgoing radiation, a 4-component radiometer is used that can observe both incoming and outgoing longwave and shortwave radiation. This

  16. Using Satellite Data and Land Surface Models to Monitor and Forecast Drought Conditions in Africa and Middle East

    Science.gov (United States)

    Arsenault, K. R.; Shukla, S.; Getirana, A.; Peters-Lidard, C. D.; Kumar, S.; McNally, A.; Zaitchik, B. F.; Badr, H. S.; Funk, C. C.; Koster, R. D.; Narapusetty, B.; Jung, H. C.; Roningen, J. M.

    2017-12-01

    Drought and water scarcity are among the important issues facing several regions within Africa and the Middle East. In addition, these regions typically have sparse ground-based data networks, where sometimes remotely sensed observations may be the only data available. Long-term satellite records can help with determining historic and current drought conditions. In recent years, several new satellites have come on-line that monitor different hydrological variables, including soil moisture and terrestrial water storage. Though these recent data records may be considered too short for the use in identifying major droughts, they do provide additional information that can better characterize where water deficits may occur. We utilize recent satellite data records of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) and the European Space Agency's Advanced Scatterometer (ASCAT) soil moisture retrievals. Combining these records with land surface models (LSMs), NASA's Catchment and the Noah Multi-Physics (MP), is aimed at improving the land model states and initialization for seasonal drought forecasts. The LSMs' total runoff is routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics, which can provide an additional means of validation against in situ streamflow data. The NASA Land Information System (LIS) software framework drives the LSMs and HyMAP and also supports the capability to assimilate these satellite retrievals, such as soil moisture and TWS. The LSMs are driven for 30+ years with NASA's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS/UCSB Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) rainfall dataset. The seasonal water deficit forecasts are generated using downscaled and bias-corrected versions of NASA's Goddard Earth Observing System Model (GEOS-5), and NOAA's Climate Forecast System (CFSv2) forecasts

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

    Science.gov (United States)

    Cak, A. D.

    2017-12-01

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

  18. Climatology

    International Nuclear Information System (INIS)

    Schoenwiese, C.D.

    1994-01-01

    Climatology is an important field of continuing interest in nearly all fields of science and beyond. In view of this interdisciplinary role, the textbook gives an accurate and intelligible introduction to the fundamentals and modern aspects of general climatology. It covers the basic concepts of climate elements, the physical processes, atmospheric circulation and further components of the ''climate system'' (ocean, ice, continents), as well as an explanation of the observed field characteristics of the climate, problems of climate modelling fundamentals of bioclimatology, and, last but not least, key aspects of climate history and anthropogenic effects on climate. (orig.) [de

  19. Climatology of GPS signal loss observed by Swarm satellites

    Directory of Open Access Journals (Sweden)

    C. Xiong

    2018-04-01

    Full Text Available By using 3-year global positioning system (GPS measurements from December 2013 to November 2016, we provide in this study a detailed survey on the climatology of the GPS signal loss of Swarm onboard receivers. Our results show that the GPS signal losses prefer to occur at both low latitudes between ±5 and ±20° magnetic latitude (MLAT and high latitudes above 60° MLAT in both hemispheres. These events at all latitudes are observed mainly during equinoxes and December solstice months, while totally absent during June solstice months. At low latitudes the GPS signal losses are caused by the equatorial plasma irregularities shortly after sunset, and at high latitude they are also highly related to the large density gradients associated with ionospheric irregularities. Additionally, the high-latitude events are more often observed in the Southern Hemisphere, occurring mainly at the cusp region and along nightside auroral latitudes. The signal losses mainly happen for those GPS rays with elevation angles less than 20°, and more commonly occur when the line of sight between GPS and Swarm satellites is aligned with the shell structure of plasma irregularities. Our results also confirm that the capability of the Swarm receiver has been improved after the bandwidth of the phase-locked loop (PLL widened, but the updates cannot radically avoid the interruption in tracking GPS satellites caused by the ionospheric plasma irregularities. Additionally, after the PLL bandwidth increased larger than 0.5 Hz, some unexpected signal losses are observed even at middle latitudes, which are not related to the ionospheric plasma irregularities. Our results suggest that rather than 1.0 Hz, a PLL bandwidth of 0.5 Hz is a more suitable value for the Swarm receiver.

  20. Climatology of GPS signal loss observed by Swarm satellites

    Science.gov (United States)

    Xiong, Chao; Stolle, Claudia; Park, Jaeheung

    2018-04-01

    By using 3-year global positioning system (GPS) measurements from December 2013 to November 2016, we provide in this study a detailed survey on the climatology of the GPS signal loss of Swarm onboard receivers. Our results show that the GPS signal losses prefer to occur at both low latitudes between ±5 and ±20° magnetic latitude (MLAT) and high latitudes above 60° MLAT in both hemispheres. These events at all latitudes are observed mainly during equinoxes and December solstice months, while totally absent during June solstice months. At low latitudes the GPS signal losses are caused by the equatorial plasma irregularities shortly after sunset, and at high latitude they are also highly related to the large density gradients associated with ionospheric irregularities. Additionally, the high-latitude events are more often observed in the Southern Hemisphere, occurring mainly at the cusp region and along nightside auroral latitudes. The signal losses mainly happen for those GPS rays with elevation angles less than 20°, and more commonly occur when the line of sight between GPS and Swarm satellites is aligned with the shell structure of plasma irregularities. Our results also confirm that the capability of the Swarm receiver has been improved after the bandwidth of the phase-locked loop (PLL) widened, but the updates cannot radically avoid the interruption in tracking GPS satellites caused by the ionospheric plasma irregularities. Additionally, after the PLL bandwidth increased larger than 0.5 Hz, some unexpected signal losses are observed even at middle latitudes, which are not related to the ionospheric plasma irregularities. Our results suggest that rather than 1.0 Hz, a PLL bandwidth of 0.5 Hz is a more suitable value for the Swarm receiver.

  1. Estimation of the Land Surface Temperature over the Tibetan Plateau by Using Chinese FY-2C Geostationary Satellite Data.

    Science.gov (United States)

    Hu, Yuanyuan; Zhong, Lei; Ma, Yaoming; Zou, Mijun; Xu, Kepiao; Huang, Ziyu; Feng, Lu

    2018-01-28

    During the process of land-atmosphere interaction, one of the essential parameters is the land surface temperature (LST). The LST has high temporal variability, especially in its diurnal cycle, which cannot be acquired by polar-orbiting satellites. Therefore, it is of great practical significance to retrieve LST data using geostationary satellites. According to the data of FengYun 2C (FY-2C) satellite and the measurements from the Enhanced Observing Period (CEOP) of the Asia-Australia Monsoon Project (CAMP) on the Tibetan Plateau (CAMP/Tibet), a regression approach was utilized in this research to optimize the split window algorithm (SWA). The thermal infrared data obtained by the Chinese geostationary satellite FY-2C over the Tibetan Plateau (TP) was used to estimate the hourly LST time series. To decrease the effects of cloud, the 10-day composite hourly LST data were obtained through the approach of maximal value composite (MVC). The derived LST was used to compare with the product of MODIS LST and was also validated by the field observation. The results show that the LST retrieved through the optimized SWA and in situ data has a better consistency (with correlation coefficient (R), mean absolute error (MAE), mean bias (MB), and root mean square error (RMSE) values of 0.987, 1.91 K, 0.83 K and 2.26 K, respectively) than that derived from Becker and Li's SWA and MODIS LST product, which means that the modified SWA can be applied to achieve plateau-scale LST. The diurnal variation of the LST and the hourly time series of the LST over the Tibetan Plateau were also obtained. The diurnal range of LST was found to be clearly affected by the influence of the thawing and freezing process of soil and the summer monsoon evolution. The comparison between the seasonal and diurnal variations of LST at four typical underlying surfaces over the TP indicate that the variation of LST is closely connected with the underlying surface types as well. The diurnal variation of LST is

  2. The role of land surface fluxes in Saudi-KAU AGCM: Temperature climatology over the Arabian Peninsula for the period 1981-2010

    Science.gov (United States)

    Ashfaqur Rahman, M.; Almazroui, Mansour; Nazrul Islam, M.; O'Brien, Enda; Yousef, Ahmed Elsayed

    2018-02-01

    A new version of the Community Land Model (CLM) was introduced to the Saudi King Abdulaziz University Atmospheric Global Climate Model (Saudi-KAU AGCM) for better land surface component representation, and so to enhance climate simulation. CLM replaced the original land surface model (LSM) in Saudi-KAU AGCM, with the aim of simulating more accurate land surface fluxes globally, but especially over the Arabian Peninsula. To evaluate the performance of Saudi-KAU AGCM, simulations were completed with CLM and LSM for the period 1981-2010. In comparison with LSM, CLM generates surface air temperature values that are closer to National Centre for Environmental Prediction (NCEP) observations. The global annual averages of land surface air temperature are 9.51, 9.52, and 9.57 °C for NCEP, CLM, and LSM respectively, although the same atmospheric radiative and surface forcing from Saudi-KAU AGCM are provided to both LSM and CLM at every time step. The better temperature simulations when using CLM can be attributed to the more comprehensive plant functional type and hierarchical tile approach to the land cover type in CLM, along with better parameterization of upward land surface fluxes compared to LSM. At global scale, CLM exhibits smaller annual and seasonal mean biases of temperature with respect to NCEP data. Moreover, at regional scale, CLM demonstrates reasonable seasonal and annual mean temperature over the Arabian Peninsula as compared to the Climatic Research Unit (CRU) data. Finally, CLM generated better matches to single point-wise observations of surface air temperature and surface fluxes for some case studies.

  3. International Satellite Cloud Climatology Project (ISCCP) Climate Data Record, H-Series

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The International Satellite Cloud Climatology Project (ISCCP) focuses on the distribution and variation of cloud radiative properties to improve the understanding of...

  4. Does quality control matter? Surface urban heat island intensity variations estimated by satellite-derived land surface temperature products

    Science.gov (United States)

    Lai, Jiameng; Zhan, Wenfeng; Huang, Fan; Quan, Jinling; Hu, Leiqiu; Gao, Lun; Ju, Weimin

    2018-05-01

    The temporally regular and spatially comprehensive monitoring of surface urban heat islands (SUHIs) have been extremely difficult, until the advent of satellite-based land surface temperature (LST) products. However, these LST products have relatively higher errors compared to in situ measurements. This has resulted in comparatively inaccurate estimations of SUHI indicators and, consequently, may have distorted interpretations of SUHIs. Although reports have shown that LST qualities are important for SUHI interpretations, systematic investigations of the response of SUHI indicators to LST qualities across cities with dissimilar bioclimates are rare. To address this issue, we chose eighty-six major cities across mainland China and analyzed SUHI intensity (SUHII) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) LST data. The LST-based SUHII differences due to inclusion or exclusion of MODIS quality control (QC) flags (i.e., ΔSUHII) were evaluated. Our major findings included, but are not limited to, the following four aspects: (1) SUHIIs can be significantly impacted by MODIS QC flags, and the associated QC-induced ΔSUHIIs generally accounted for 24.3% (29.9%) of the total SUHII value during the day (night); (2) the ΔSUHIIs differed between seasons, with considerable differences between transitional (spring and autumn) and extreme (summer and winter) seasons; (3) significant discrepancies also appeared among cities located in northern and southern regions, with northern cities often possessing higher annual mean ΔSUHIIs. The internal variations of ΔSUHIIs within individual cities also showed high heterogeneity, with ΔSUHII variations that generally exceeded 5.0 K (3.0 K) in northern (southern) cities; (4) ΔSUHIIs were negatively related to SUHIIs and cloud cover percentages (mostly in transitional seasons). No significant relationship was found in the extreme seasons. Our findings highlight the need to be extremely cautious when using LST

  5. Impact of highway construction on land surface energy balance and local climate derived from LANDSAT satellite data.

    Science.gov (United States)

    Nedbal, Václav; Brom, Jakub

    2018-08-15

    Extensive construction of highways has a major impact on the landscape and its structure. They can also influence local climate and heat fluxes in the surrounding area. After the removal of vegetation due to highway construction, the amount of solar radiation energy used for plant evapotranspiration (latent heat flux) decreases, bringing about an increase in landscape surface temperature, changing the local climate and increasing surface run-off. In this study, we evaluated the impact of the D8 highway construction (Central Bohemia, Czech Republic) on the distribution of solar radiation energy into the various heat fluxes (latent, sensible and ground heat flux) and related surface functional parameters (surface temperature and surface wetness). The aim was to describe the severity of the impact and the distance from the actual highway in which it can be observed. LANDSAT multispectral satellite images and field meteorological measurements were used to calculate surface functional parameters and heat balance before and during the highway construction. Construction of a four-lane highway can influence the heat balance of the landscape surface as far as 90m in the perpendicular direction from the highway axis, i.e. up to 75m perpendicular from its edge. During a summer day, the decrease in evapotranspired water can reach up to 43.7m 3 per highway kilometre. This means a reduced cooling effect, expressed as the decrease in latent heat flux, by an average of 29.7MWh per day per highway kilometre and its surroundings. The loss of the cooling ability of the land surface by evaporation can lead to a rise in surface temperature by as much as 7°C. Thus, the results indicate the impact of extensive line constructions on the local climate. Copyright © 2018 Elsevier B.V. All rights reserved.

  6. Correction of sub-pixel topographical effects on land surface albedo retrieved from geostationary satellite (FengYun-2D) observations

    International Nuclear Information System (INIS)

    Roupioz, L; Nerry, F; Jia, L; Menenti, M

    2014-01-01

    The Qinghai-Tibetan Plateau is characterised by a very strong relief which affects albedo retrieval from satellite data. The objective of this study is to highlight the effects of sub-pixel topography and to account for those effects when retrieving land surface albedo from geostationary satellite FengYun-2D (FY-2D) data with 1.25km spatial resolution using the high spatial resolution (30 m) data of the Digital Elevation Model (DEM) from ASTER. The methodology integrates the effects of sub-pixel topography on the estimation of the total irradiance received at the surface, allowing the computation of the topographically corrected surface reflectance. Furthermore, surface albedo is estimated by applying the parametric BRDF (Bidirectional Reflectance Distribution Function) model called RPV (Rahman-Pinty-Verstraete) to the terrain corrected surface reflectance. The results, evaluated against ground measurements collected over several experimental sites on the Qinghai-Tibetan Plateau, document the advantage of integrating the sub-pixel topography effects in the land surface reflectance at 1km resolution to estimate the land surface albedo. The results obtained after using sub-pixel topographic correction are compared with the ones obtained after using pixel level topographic correction. The preliminary results imply that, in highly rugged terrain, the sub-pixel topography correction method gives more accurate results. The pixel level correction tends to overestimate surface albedo

  7. Recent Trends of the Tropical Hydrological Cycle Inferred from Global Precipitation Climatology Project and International Satellite Cloud Climatology Project data

    Science.gov (United States)

    Zhou, Y. P.; Xu, Kuan-Man; Sud, Y. C.; Betts, A. K.

    2011-01-01

    Scores of modeling studies have shown that increasing greenhouse gases in the atmosphere impact the global hydrologic cycle; however, disagreements on regional scales are large, and thus the simulated trends of such impacts, even for regions as large as the tropics, remain uncertain. The present investigation attempts to examine such trends in the observations using satellite data products comprising Global Precipitation Climatology Project precipitation and International Satellite Cloud Climatology Project cloud and radiation. Specifically, evolving trends of the tropical hydrological cycle over the last 20-30 years were identified and analyzed. The results show (1) intensification of tropical precipitation in the rising regions of the Walker and Hadley circulations and weakening over the sinking regions of the associated overturning circulation; (2) poleward shift of the subtropical dry zones (up to 2deg/decade in June-July-August (JJA) in the Northern Hemisphere and 0.3-0.7deg/decade in June-July-August and September-October-November in the Southern Hemisphere) consistent with an overall broadening of the Hadley circulation; and (3) significant poleward migration (0.9-1.7deg/decade) of cloud boundaries of Hadley cell and plausible narrowing of the high cloudiness in the Intertropical Convergence Zone region in some seasons. These results support findings of some of the previous studies that showed strengthening of the tropical hydrological cycle and expansion of the Hadley cell that are potentially related to the recent global warming trends.

  8. Retrieval of land surface temperature (LST) from landsat TM6 and TIRS data by single channel radiative transfer algorithm using satellite and ground-based inputs

    Science.gov (United States)

    Chatterjee, R. S.; Singh, Narendra; Thapa, Shailaja; Sharma, Dravneeta; Kumar, Dheeraj

    2017-06-01

    The present study proposes land surface temperature (LST) retrieval from satellite-based thermal IR data by single channel radiative transfer algorithm using atmospheric correction parameters derived from satellite-based and in-situ data and land surface emissivity (LSE) derived by a hybrid LSE model. For example, atmospheric transmittance (τ) was derived from Terra MODIS spectral radiance in atmospheric window and absorption bands, whereas the atmospheric path radiance and sky radiance were estimated using satellite- and ground-based in-situ solar radiation, geographic location and observation conditions. The hybrid LSE model which is coupled with ground-based emissivity measurements is more versatile than the previous LSE models and yields improved emissivity values by knowledge-based approach. It uses NDVI-based and NDVI Threshold method (NDVITHM) based algorithms and field-measured emissivity values. The model is applicable for dense vegetation cover, mixed vegetation cover, bare earth including coal mining related land surface classes. The study was conducted in a coalfield of India badly affected by coal fire for decades. In a coal fire affected coalfield, LST would provide precise temperature difference between thermally anomalous coal fire pixels and background pixels to facilitate coal fire detection and monitoring. The derived LST products of the present study were compared with radiant temperature images across some of the prominent coal fire locations in the study area by graphical means and by some standard mathematical dispersion coefficients such as coefficient of variation, coefficient of quartile deviation, coefficient of quartile deviation for 3rd quartile vs. maximum temperature, coefficient of mean deviation (about median) indicating significant increase in the temperature difference among the pixels. The average temperature slope between adjacent pixels, which increases the potential of coal fire pixel detection from background pixels, is

  9. TransCom satellite intercomparison experiment: construction of a bias corrected atmospheric CO2 climatology

    NARCIS (Netherlands)

    Saito, R.; Houweling, S.; Patra, P. K.; Belikov, D.; Lokupitiya, R.; Niwa, Y.; Chevallier, F.; Saeki, T.; Maksyutov, S.

    2011-01-01

    A model-based three-dimensional (3-D) climatology of atmospheric CO2 concentrations has been constructed for the analysis of satellite observations, as a priori information in retrieval calculations, and for preliminary evaluation of remote sensing products. The locations of ground-based instruments

  10. Hydrological land surface modelling

    DEFF Research Database (Denmark)

    Ridler, Marc-Etienne Francois

    Recent advances in integrated hydrological and soil-vegetation-atmosphere transfer (SVAT) modelling have led to improved water resource management practices, greater crop production, and better flood forecasting systems. However, uncertainty is inherent in all numerical models ultimately leading...... temperature are explored in a multi-objective calibration experiment to optimize the parameters in a SVAT model in the Sahel. The two satellite derived variables were effective at constraining most land-surface and soil parameters. A data assimilation framework is developed and implemented with an integrated...... and disaster management. The objective of this study is to develop and investigate methods to reduce hydrological model uncertainty by using supplementary data sources. The data is used either for model calibration or for model updating using data assimilation. Satellite estimates of soil moisture and surface...

  11. Analysing the advantages of high temporal resolution geostationary MSG SEVIRI data compared to Polar operational environmental satellite data for land surface monitoring in Africa

    DEFF Research Database (Denmark)

    Fensholt, Rasmus; Anyamba, Assaf; Huber Gharib, Silvia

    2011-01-01

    Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth’s natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which often...... is obscured by frequent and persistent cloud cover creating large gaps in time series measurements. The launch of the Meteosat Second Generation (MSG) satellite into geostationary orbit has opened new opportunities for land surface monitoring. The Spinning Enhanced Visible and Infrared Imager (SEVIRI...... affected by droughts and floods in 2008 caused by periods of abnormally low and high rainfall, respectively. Based on the effectiveness of monitoring these events from Earth Observation (EO) data the current analyses show that the new generation of geostationary remote sensing data can provide higher...

  12. Multi-satellite climatologies of fundamental atmospheric variables from Radio Occulation and their validation

    International Nuclear Information System (INIS)

    Pirscher, B.

    2010-01-01

    Monitoring of global climate change requires high quality observations not only on the Earths surface but also in the free atmosphere. Global Positioning System (GPS) Radio Occultation (RO) observations are known to have the potential to deliver very accurate, precise, and long-term stable measurements between about 8 km and 30 km altitude.This thesis investigates the suitability of RO observations to serve as climate benchmark record by validating the consistency of RO data provided by different satellites. The main focus lies on systematic differences of RO climatologies, originating from different data processing, data quality, spatio-temporal sampling, and particular orbit characteristics. Data of six RO satellite missions (including one multi-satellite constellation) are analyzed. Largest disagreements of RO climatologies are observed when comparing data provided by different processing centers. Mean absolute temperature differences between 8 km and 30 km altitude amount to 0.5 K, while climate time series of temperature changes agree much closer.Utilizing RO data from the same data center and considering space-temporal sampling yields remarkable consistency of temperature climatologies with mean differences being smaller than 0.1 K. Disagreements are found to be largest at 35 km, where they exceed 0.2 K. This results from different data quality and its utilization within the processing scheme. Climatologies, which are derived from data with the same quality agree to within 0.02 K also at high altitudes. The measurements local time, which depends on the satellites orbit, has a minor but clearly understandable influence on differences in RO climatologies. The results underline the utility of RO data for long-term monitoring of the global climate. (author) [de

  13. Analysing the Advantages of High Temporal Resolution Geostationary MSG SEVIRI Data Compared to Polar Operational Environmental Satellite Data for Land Surface Monitoring in Africa

    Science.gov (United States)

    Fensholt, R.; Anyamba, A.; Huber, S.; Proud, S. R.; Tucker, C. J.; Small, J.; Pak, E.; Rasmussen, M. O.; Sandholt, I.; Shisanya, C.

    2011-01-01

    Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth s natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which often is obscured by frequent and persistent cloud cover creating large gaps in time series measurements. The launch of the Meteosat Second Generation (MSG) satellite into geostationary orbit has opened new opportunities for land surface monitoring. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on-board MSG with an imaging capability every 15 minutes which is substantially greater than any temporal resolution that can be obtained from existing polar operational environmental satellites (POES) systems currently in use for environmental monitoring. Different areas of the African continent were affected by droughts and floods in 2008 caused by periods of abnormally low and high rainfall, respectively. Based on the effectiveness of monitoring these events from Earth Observation (EO) data the current analyses show that the new generation of geostationary remote sensing data can provide higher temporal resolution cloud-free (less than 5 days) measurements of the environment as compared to existing POES systems. SEVIRI MSG 5-day continental scale composites will enable rapid assessment of environmental conditions and improved early warning of disasters for the African continent such as flooding or droughts. The high temporal resolution geostationary data will complement existing higher spatial resolution polar-orbiting satellite data for various dynamic environmental and natural resource applications of terrestrial ecosystems.

  14. Evaluation of Land Surface Models in Reproducing Satellite-Derived LAI over the High-Latitude Northern Hemisphere. Part I: Uncoupled DGVMs

    Directory of Open Access Journals (Sweden)

    Ning Zeng

    2013-10-01

    Full Text Available Leaf Area Index (LAI represents the total surface area of leaves above a unit area of ground and is a key variable in any vegetation model, as well as in climate models. New high resolution LAI satellite data is now available covering a period of several decades. This provides a unique opportunity to validate LAI estimates from multiple vegetation models. The objective of this paper is to compare new, satellite-derived LAI measurements with modeled output for the Northern Hemisphere. We compare monthly LAI output from eight land surface models from the TRENDY compendium with satellite data from an Artificial Neural Network (ANN from the latest version (third generation of GIMMS AVHRR NDVI data over the period 1986–2005. Our results show that all the models overestimate the mean LAI, particularly over the boreal forest. We also find that seven out of the eight models overestimate the length of the active vegetation-growing season, mostly due to a late dormancy as a result of a late summer phenology. Finally, we find that the models report a much larger positive trend in LAI over this period than the satellite observations suggest, which translates into a higher trend in the growing season length. These results highlight the need to incorporate a larger number of more accurate plant functional types in all models and, in particular, to improve the phenology of deciduous trees.

  15. Assessing regional crop water demand using a satellite-based combination equation with a land surface temperature componen

    DEFF Research Database (Denmark)

    Moyano, Carmen; Garcia, Monica; Tornos, Lucia

    2015-01-01

    -sequence spanning for more than a decade (2002-2013). The thermal-PT-JPL model was forced with vegetation, albedo, reflectance and temperature products from the Moderate-resolution Imaging Spectroradiometer (MODIS) from both Aqua and Terra satellites. The study region, B-XII Irrigation District of the Lower...

  16. Two-Layer Variable Infiltration Capacity Land Surface Representation for General Circulation Models

    Science.gov (United States)

    Xu, L.

    1994-01-01

    A simple two-layer variable infiltration capacity (VIC-2L) land surface model suitable for incorporation in general circulation models (GCMs) is described. The model consists of a two-layer characterization of the soil within a GCM grid cell, and uses an aerodynamic representation of latent and sensible heat fluxes at the land surface. The effects of GCM spatial subgrid variability of soil moisture and a hydrologically realistic runoff mechanism are represented in the soil layers. The model was tested using long-term hydrologic and climatalogical data for Kings Creek, Kansas to estimate and validate the hydrological parameters. Surface flux data from three First International Satellite Land Surface Climatology Project Field Experiments (FIFE) intensive field compaigns in the summer and fall of 1987 in central Kansas, and from the Anglo-Brazilian Amazonian Climate Observation Study (ABRACOS) in Brazil were used to validate the mode-simulated surface energy fluxes and surface temperature.

  17. Generalized Split-Window Algorithm for Estimate of Land Surface Temperature from Chinese Geostationary FengYun Meteorological Satellite (FY-2C Data

    Directory of Open Access Journals (Sweden)

    Jun Xia

    2008-02-01

    Full Text Available On the basis of the radiative transfer theory, this paper addressed the estimate ofLand Surface Temperature (LST from the Chinese first operational geostationarymeteorological satellite-FengYun-2C (FY-2C data in two thermal infrared channels (IR1,10.3-11.3 μ m and IR2, 11.5-12.5 μ m , using the Generalized Split-Window (GSWalgorithm proposed by Wan and Dozier (1996. The coefficients in the GSW algorithmcorresponding to a series of overlapping ranging of the mean emissivity, the atmosphericWater Vapor Content (WVC, and the LST were derived using a statistical regressionmethod from the numerical values simulated with an accurate atmospheric radiativetransfer model MODTRAN 4 over a wide range of atmospheric and surface conditions.The simulation analysis showed that the LST could be estimated by the GSW algorithmwith the Root Mean Square Error (RMSE less than 1 K for the sub-ranges with theViewing Zenith Angle (VZA less than 30° or for the sub-rangs with VZA less than 60°and the atmospheric WVC less than 3.5 g/cm2 provided that the Land Surface Emissivities(LSEs are known. In order to determine the range for the optimum coefficients of theGSW algorithm, the LSEs could be derived from the data in MODIS channels 31 and 32 provided by MODIS/Terra LST product MOD11B1, or be estimated either according tothe land surface classification or using the method proposed by Jiang et al. (2006; and theWVC could be obtained from MODIS total precipitable water product MOD05, or beretrieved using Li et al.’ method (2003. The sensitivity and error analyses in term of theuncertainty of the LSE and WVC as well as the instrumental noise were performed. Inaddition, in order to compare the different formulations of the split-window algorithms,several recently proposed split-window algorithms were used to estimate the LST with thesame simulated FY-2C data. The result of the intercomparsion showed that most of thealgorithms give

  18. Modelling Angular Dependencies in Land Surface Temperatures From the SEVIRI Instrument onboard the Geostationary Meteosat Second Generation Satellites

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander; Pinheiro, AC; Proud, Simon Richard

    2010-01-01

    on vegetation structure and viewing and illumination geometry. Despite this, these effects are not considered in current operational LST products from neither polar-orbiting nor geostationary satellites. In this paper, we simulate the angular dependence that can be expected when estimating LST with the viewing...... geometry of the geostationary Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager sensor across the African continent and compare it to a normalized view geometry. We use the modified geometric projection model that estimates the scene thermal infrared radiance from a surface covered...

  19. Estimating carbon flux phenology with satellite-derived land surface phenology and climate drivers for different biomes: a synthesis of AmeriFlux observations.

    Directory of Open Access Journals (Sweden)

    Wenquan Zhu

    Full Text Available Carbon Flux Phenology (CFP can affect the interannual variation in Net Ecosystem Exchange (NEE of carbon between terrestrial ecosystems and the atmosphere. In this study, we proposed a methodology to estimate CFP metrics with satellite-derived Land Surface Phenology (LSP metrics and climate drivers for 4 biomes (i.e., deciduous broadleaf forest, evergreen needleleaf forest, grasslands and croplands, using 159 site-years of NEE and climate data from 32 AmeriFlux sites and MODIS vegetation index time-series data. LSP metrics combined with optimal climate drivers can explain the variability in Start of Carbon Uptake (SCU by more than 70% and End of Carbon Uptake (ECU by more than 60%. The Root Mean Square Error (RMSE of the estimations was within 8.5 days for both SCU and ECU. The estimation performance for this methodology was primarily dependent on the optimal combination of the LSP retrieval methods, the explanatory climate drivers, the biome types, and the specific CFP metric. This methodology has a potential for allowing extrapolation of CFP metrics for biomes with a distinct and detectable seasonal cycle over large areas, based on synoptic multi-temporal optical satellite data and climate data.

  20. Using satellite data on meteorological and vegetation characteristics and soil surface humidity in the Land Surface Model for the vast territory of agricultural destination

    Science.gov (United States)

    Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Vasilenko, Eugene; Volkova, Elena; Kukharsky, Alexander

    2017-04-01

    The model of water and heat exchange between vegetation covered territory and atmosphere (LSM, Land Surface Model) for vegetation season has been developed to calculate soil water content, evapotranspiration, infiltration of water into the soil, vertical latent and sensible heat fluxes and other water and heat balances components as well as soil surface and vegetation cover temperatures and depth distributions of moisture and temperature. The LSM is suited for utilizing satellite-derived estimates of precipitation, land surface temperature and vegetation characteristics and soil surface humidity for each pixel. Vegetation and meteorological characteristics being the model parameters and input variables, correspondingly, have been estimated by ground observations and thematic processing measurement data of scanning radiometers AVHRR/NOAA, SEVIRI/Meteosat-9, -10 (MSG-2, -3) and MSU-MR/Meteor-M № 2. Values of soil surface humidity has been calculated from remote sensing data of scatterometers ASCAT/MetOp-A, -B. The case study has been carried out for the territory of part of the agricultural Central Black Earth Region of European Russia with area of 227300 km2 located in the forest-steppe zone for years 2012-2015 vegetation seasons. The main objectives of the study have been: - to built estimates of precipitation, land surface temperatures (LST) and vegetation characteristics from MSU-MR measurement data using the refined technologies (including algorithms and programs) of thematic processing satellite information matured on AVHRR and SEVIRI data. All technologies have been adapted to the area of interest; - to investigate the possibility of utilizing satellite-derived estimates of values above in the LSM including verification of obtained estimates and development of procedure of their inputting into the model. From the AVHRR data there have been built the estimates of precipitation, three types of LST: land skin temperature Tsg, air temperature at a level of

  1. A European satellite-derived UV climatology available for impact studies

    International Nuclear Information System (INIS)

    Verdebout, J.

    2004-01-01

    This paper presents a satellite-derived climatology of the surface UV radiation, intended to support impact studies on the environment and human health. As of today, the dataset covers the period from 1 January 1984 to 31 August 2003, with daily dose maps covering Europe with a spatial resolution of 0.05 deg.. A comparison between the modelled erythemal daily dose and measurements in Ispra yields an r.m.s value with a relative difference of 29% and a bias of 3%. The seemingly large dispersion is, however, due to a restricted number of days for which the relative difference is very high. The climatological dataset documents systematic patterns in the geographical distribution of the surface UV radiation due to cloudiness, altitude and snow. It also shows a large year-to-year variability in monthly doses of up to ±50% in spring and ±30% in summer. (authors)

  2. Advantages of Using Microwave Satellite Soil Moisture over Gridded Precipitation Products and Land Surface Model Output in Assessing Regional Vegetation Water Availability and Growth Dynamics for a Lateral Inflow Receiving Landscape

    NARCIS (Netherlands)

    Chen, T.; McVicar, T.R.; Wang, G.J.; Chen, X.; de Jeu, R.A.M.; Liu, Y.; Shen, H.; Zhang, F.; Dolman, A.J.

    2016-01-01

    To improve the understanding of water-vegetation relationships, direct comparative studies assessing the utility of satellite remotely sensed soil moisture, gridded precipitation products, and land surface model output are needed. A case study was investigated for a water-limited, lateral inflow

  3. Utilization of satellite remote sensing data on land surface characteristics in water and heat balance component modeling for vegetation covered territories

    Science.gov (United States)

    Muzylev, Eugene; Uspensky, Alexander; Startseva, Zoya; Volkova, Elena; Kukharsky, Alexander; Uspensky, Sergey

    2010-05-01

    The model of vertical water and heat transfer in the "soil-vegetation-atmosphere" system (SVAT) for vegetation covered territory has been developed, allowing assimilating satellite remote sensing data on land surface condition as well as accounting for heterogeneities of vegetation and meteorological characteristics. The model provides the calculation of water and heat balance components (such as evapotranspiration Ev, soil water content W, sensible and latent heat fluxes and others ) as well as vertical soil moisture and temperature distributions, temperatures of soil surface and foliage, land surface brightness temperature for any time interval within vegetation season. To describe the landscape diversity soil constants and leaf area index LAI, vegetation cover fraction B, and other vegetation characteristics are used. All these values are considered to be the model parameters. Territory of Kursk region with square about 15 thousands km2 situated in the Black Earth zone of Central Russia was chosen for investigation. Satellite-derived estimates of land surface characteristics have been constructed under cloud-free condition basing AVHRR/NOAA, MODIS/EOS Terra and EOS Aqua, SEVIRI/Meteosat-8, -9 data. The developed technologies of AVHRR data thematic processing have been refined providing the retrieval of surface skin brightness temperature Tsg, air foliage temperature Ta, efficient surface temperature Ts.eff and emissivity E, as well as derivation of vegetation index NDVI, B, and LAI. The linear regression estimators for Tsg, Ta and LAI have been built using representative training samples for 2003-2009 vegetation seasons. The updated software package has been applied for AVHRR data thematic processing to generate named remote sensing products for various dates of the above vegetation seasons. The error statistics of Ta, Ts.eff and Тsg derivation has been investigated for various samples using comparison with in-situ measurements that has given RMS errors in the

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

    Science.gov (United States)

    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

  5. A spatiotemporal analysis of the relationship between near-surface air temperature and satellite land surface temperatures using 17 years of data from the ATSR series

    Science.gov (United States)

    Good, Elizabeth J.; Ghent, Darren J.; Bulgin, Claire E.; Remedios, John J.

    2017-09-01

    The relationship between satellite land surface temperature (LST) and ground-based observations of 2 m air temperature (T2m) is characterized in space and time using >17 years of data. The analysis uses a new monthly LST climate data record (CDR) based on the Along-Track Scanning Radiometer series, which has been produced within the European Space Agency GlobTemperature project (http://www.globtemperature.info/). Global LST-T2m differences are analyzed with respect to location, land cover, vegetation fraction, and elevation, all of which are found to be important influencing factors. LSTnight ( 10 P.M. local solar time, clear-sky only) is found to be closely coupled with minimum T2m (Tmin, all-sky) and the two temperatures generally consistent to within ±5°C (global median LSTnight-Tmin = 1.8°C, interquartile range = 3.8°C). The LSTday ( 10 A.M. local solar time, clear-sky only)-maximum T2m (Tmax, all-sky) variability is higher (global median LSTday-Tmax = -0.1°C, interquartile range = 8.1°C) because LST is strongly influenced by insolation and surface regime. Correlations for both temperature pairs are typically >0.9 outside of the tropics. The monthly global and regional anomaly time series of LST and T2m—which are completely independent data sets—compare remarkably well. The correlation between the data sets is 0.9 for the globe with 90% of the CDR anomalies falling within the T2m 95% confidence limits. The results presented in this study present a justification for increasing use of satellite LST data in climate and weather science, both as an independent variable, and to augment T2m data acquired at meteorological stations.

  6. Climatologies from satellite measurements: the impact of orbital sampling on the standard error of the mean

    Directory of Open Access Journals (Sweden)

    M. Toohey

    2013-04-01

    Full Text Available Climatologies of atmospheric observations are often produced by binning measurements according to latitude and calculating zonal means. The uncertainty in these climatological means is characterised by the standard error of the mean (SEM. However, the usual estimator of the SEM, i.e., the sample standard deviation divided by the square root of the sample size, holds only for uncorrelated randomly sampled measurements. Measurements of the atmospheric state along a satellite orbit cannot always be considered as independent because (a the time-space interval between two nearest observations is often smaller than the typical scale of variations in the atmospheric state, and (b the regular time-space sampling pattern of a satellite instrument strongly deviates from random sampling. We have developed a numerical experiment where global chemical fields from a chemistry climate model are sampled according to real sampling patterns of satellite-borne instruments. As case studies, the model fields are sampled using sampling patterns of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS and Atmospheric Chemistry Experiment Fourier-Transform Spectrometer (ACE-FTS satellite instruments. Through an iterative subsampling technique, and by incorporating information on the random errors of the MIPAS and ACE-FTS measurements, we produce empirical estimates of the standard error of monthly mean zonal mean model O3 in 5° latitude bins. We find that generally the classic SEM estimator is a conservative estimate of the SEM, i.e., the empirical SEM is often less than or approximately equal to the classic estimate. Exceptions occur only when natural variability is larger than the random measurement error, and specifically in instances where the zonal sampling distribution shows non-uniformity with a similar zonal structure as variations in the sampled field, leading to maximum sensitivity to arbitrary phase shifts between the sample distribution and

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

    Science.gov (United States)

    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

  8. Lightning climatology over Jakarta, Indonesia, based on long-term surface operational, satellite, and campaign observations

    Science.gov (United States)

    Mori, Shuichi; Wu, Peiming; Yamanaka, Manabu D.; Hattori, Miki; Hamada, Jun-Ichi; Arbain, Ardhi A.; Lestari, Sopia; Sulistyowati, Reni; Syamsudin, Fadli

    2016-04-01

    Lightning frequency over Indonesian Maritime Continent (MC) is quite high (Petersen and Rutledge 2001, Christian et al. 2003, Takayabu 2006, etc). In particular, Bogor (south of Jakarta, west Jawa) had 322 days of lightning in one year (Guinness Book in 1988). Lightning causes serious damage on nature and society over the MC; forest fore, power outage, inrush/surge currents on many kinds of electronics. Lightning climatology and meso-scale characteristics of thunderstorm over the MC, in particular over Jakarta, where social damage is quite serious, were examined. We made Statistical analysis of lightning and thunderstorm based on TRMM Lightning Image Sensor (LIS) and Global Satellite Mapping of Precipitation (GSMaP) together with long-term operational surface observation data (SYNOP) in terms of diurnal, intraseasonal, monsoonal, and interannual variations. In addition, we carried out a campaign observation in February 2015 in Bogor to obtain meso-scale structure and dynamics of thunderstorm over Jakarta to focus on graupel and other ice phase particles inside by using an X-band dual-polarimetric (DP) radar. Recently, Virts et al. (2013a, b) showed comprehensive lightning climatology based on the World Wide Lightning Location Network (WWLLN). However, they also reported problems with its detection efficiency (Japan Society for the Promotion of Science (JSPS) KAKENHI (Grants-in-Aid for Scientific Research) grant number 25350515 and the Japan Aerospace Exploration Agency (JAXA) 7th Research Announcement (RA).

  9. Meteosat SEVIRI Fire Radiative Power (FRP) products from the Land Surface Analysis Satellite Applications Facility (LSA SAF) - Part 1: Algorithms, product contents and analysis

    Science.gov (United States)

    Wooster, M. J.; Roberts, G.; Freeborn, P. H.; Xu, W.; Govaerts, Y.; Beeby, R.; He, J.; Lattanzio, A.; Mullen, R.

    2015-06-01

    Characterising changes in landscape scale fire activity at very high temporal resolution is best achieved using thermal observations of actively burning fires made from geostationary Earth observation (EO) satellites. Over the last decade or more, a series of research and/or operational "active fire" products have been developed from these types of geostationary observations, often with the aim of supporting the generation of data related to biomass burning fuel consumption and trace gas and aerosol emission fields. The Fire Radiative Power (FRP) products generated by the Land Surface Analysis Satellite Applications Facility (LSA SAF) from data collected by the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) are one such set of products, and are freely available in both near real-time and archived form. Every 15 min, the algorithms used to generate these products identify and map the location of new SEVIRI observations containing actively burning fires, and characterise their individual rates of radiative energy release (fire radiative power; FRP) that is believed proportional to rates of biomass consumption and smoke emission. The FRP-PIXEL product contains the highest spatial resolution FRP dataset, delivered for all of Europe, northern and southern Africa, and part of South America at a spatial resolution of 3 km (decreasing away from the west African sub-satellite point) at the full 15 min temporal resolution. The FRP-GRID product is an hourly summary of the FRP-PIXEL data, produced at a 5° grid cell size and including simple bias adjustments for meteorological cloud cover and for the regional underestimation of FRP caused, primarily, by the non-detection of low FRP fire pixels at SEVIRI's relatively coarse pixel size. Here we describe the enhanced geostationary Fire Thermal Anomaly (FTA) algorithm used to detect the SEVIRI active fire pixels, and detail methods used to deliver atmospherically corrected FRP information

  10. The International Satellite Cloud Climatology Project H-Series climate data record product

    Science.gov (United States)

    Young, Alisa H.; Knapp, Kenneth R.; Inamdar, Anand; Hankins, William; Rossow, William B.

    2018-03-01

    This paper describes the new global long-term International Satellite Cloud Climatology Project (ISCCP) H-series climate data record (CDR). The H-series data contain a suite of level 2 and 3 products for monitoring the distribution and variation of cloud and surface properties to better understand the effects of clouds on climate, the radiation budget, and the global hydrologic cycle. This product is currently available for public use and is derived from both geostationary and polar-orbiting satellite imaging radiometers with common visible and infrared (IR) channels. The H-series data currently span July 1983 to December 2009 with plans for continued production to extend the record to the present with regular updates. The H-series data are the longest combined geostationary and polar orbiter satellite-based CDR of cloud properties. Access to the data is provided in network common data form (netCDF) and archived by NOAA's National Centers for Environmental Information (NCEI) under the satellite Climate Data Record Program (https://doi.org/10.7289/V5QZ281S" target="_blank">https://doi.org/10.7289/V5QZ281S). The basic characteristics, history, and evolution of the dataset are presented herein with particular emphasis on and discussion of product changes between the H-series and the widely used predecessor D-series product which also spans from July 1983 through December 2009. Key refinements included in the ISCCP H-series CDR are based on improved quality control measures, modified ancillary inputs, higher spatial resolution input and output products, calibration refinements, and updated documentation and metadata to bring the H-series product into compliance with existing standards for climate data records.

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

    Science.gov (United States)

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

    2013-01-01

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

  12. Towards a climatology of tropical cyclone morphometric structures using a newly standardized passive microwave satellite dataset

    Science.gov (United States)

    Cossuth, J.; Hart, R. E.

    2013-12-01

    storm's rainband and eyewall organization. Ultimately, this project develops a consistent climatology of TC structures using a new database of research-quality historical TC satellite microwave observations. Not only can such data sets more accurately study TC structural evolution, but they may facilitate automated TC intensity estimates and provide methods to enhance current operational and research products, such as at the NRL TC webpage (http://www.nrlmry.navy.mil/TC.html). The process of developing the dataset and possible objective definitions of TC structures using passive microwave imagery will be described, with preliminary results suggesting new methods to identify TC structures that may interrogate and expand upon physical and dynamical theories. Structural metrics such as threshold analysis of the outlines of the TC shape as well as methods to diagnose the inner-core size, completion, and magnitude will be introduced.

  13. Ungulate Reproductive Parameters Track Satellite Observations of Plant Phenology across Latitude and Climatological Regimes.

    Directory of Open Access Journals (Sweden)

    David C Stoner

    Full Text Available The effect of climatically-driven plant phenology on mammalian reproduction is one key to predicting species-specific demographic responses to climate change. Large ungulates face their greatest energetic demands from the later stages of pregnancy through weaning, and so in seasonal environments parturition dates should match periods of high primary productivity. Interannual variation in weather influences the quality and timing of forage availability, which can influence neonatal survival. Here, we evaluated macro-scale patterns in reproductive performance of a widely distributed ungulate (mule deer, Odocoileus hemionus across contrasting climatological regimes using satellite-derived indices of primary productivity and plant phenology over eight degrees of latitude (890 km in the American Southwest. The dataset comprised > 180,000 animal observations taken from 54 populations over eight years (2004-2011. Regionally, both the start and peak of growing season ("Start" and "Peak", respectively are negatively and significantly correlated with latitude, an unusual pattern stemming from a change in the dominance of spring snowmelt in the north to the influence of the North American Monsoon in the south. Corresponding to the timing and variation in both the Start and Peak, mule deer reproduction was latest, lowest, and most variable at lower latitudes where plant phenology is timed to the onset of monsoonal moisture. Parturition dates closely tracked the growing season across space, lagging behind the Start and preceding the Peak by 27 and 23 days, respectively. Mean juvenile production increased, and variation decreased, with increasing latitude. Temporally, juvenile production was best predicted by primary productivity during summer, which encompassed late pregnancy, parturition, and early lactation. Our findings offer a parsimonious explanation of two key reproductive parameters in ungulate demography, timing of parturition and mean annual

  14. GRACILE: a comprehensive climatology of atmospheric gravity wave parameters based on satellite limb soundings

    Directory of Open Access Journals (Sweden)

    M. Ern

    2018-04-01

    Full Text Available Gravity waves are one of the main drivers of atmospheric dynamics. The spatial resolution of most global atmospheric models, however, is too coarse to properly resolve the small scales of gravity waves, which range from tens to a few thousand kilometers horizontally, and from below 1 km to tens of kilometers vertically. Gravity wave source processes involve even smaller scales. Therefore, general circulation models (GCMs and chemistry climate models (CCMs usually parametrize the effect of gravity waves on the global circulation. These parametrizations are very simplified. For this reason, comparisons with global observations of gravity waves are needed for an improvement of parametrizations and an alleviation of model biases. We present a gravity wave climatology based on atmospheric infrared limb emissions observed by satellite (GRACILE. GRACILE is a global data set of gravity wave distributions observed in the stratosphere and the mesosphere by the infrared limb sounding satellite instruments High Resolution Dynamics Limb Sounder (HIRDLS and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER. Typical distributions (zonal averages and global maps of gravity wave vertical wavelengths and along-track horizontal wavenumbers are provided, as well as gravity wave temperature variances, potential energies and absolute momentum fluxes. This global data set captures the typical seasonal variations of these parameters, as well as their spatial variations. The GRACILE data set is suitable for scientific studies, and it can serve for comparison with other instruments (ground-based, airborne, or other satellite instruments and for comparison with gravity wave distributions, both resolved and parametrized, in GCMs and CCMs. The GRACILE data set is available as supplementary data at https://doi.org/10.1594/PANGAEA.879658.

  15. GRACILE: a comprehensive climatology of atmospheric gravity wave parameters based on satellite limb soundings

    Science.gov (United States)

    Ern, Manfred; Trinh, Quang Thai; Preusse, Peter; Gille, John C.; Mlynczak, Martin G.; Russell, James M., III; Riese, Martin

    2018-04-01

    Gravity waves are one of the main drivers of atmospheric dynamics. The spatial resolution of most global atmospheric models, however, is too coarse to properly resolve the small scales of gravity waves, which range from tens to a few thousand kilometers horizontally, and from below 1 km to tens of kilometers vertically. Gravity wave source processes involve even smaller scales. Therefore, general circulation models (GCMs) and chemistry climate models (CCMs) usually parametrize the effect of gravity waves on the global circulation. These parametrizations are very simplified. For this reason, comparisons with global observations of gravity waves are needed for an improvement of parametrizations and an alleviation of model biases. We present a gravity wave climatology based on atmospheric infrared limb emissions observed by satellite (GRACILE). GRACILE is a global data set of gravity wave distributions observed in the stratosphere and the mesosphere by the infrared limb sounding satellite instruments High Resolution Dynamics Limb Sounder (HIRDLS) and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER). Typical distributions (zonal averages and global maps) of gravity wave vertical wavelengths and along-track horizontal wavenumbers are provided, as well as gravity wave temperature variances, potential energies and absolute momentum fluxes. This global data set captures the typical seasonal variations of these parameters, as well as their spatial variations. The GRACILE data set is suitable for scientific studies, and it can serve for comparison with other instruments (ground-based, airborne, or other satellite instruments) and for comparison with gravity wave distributions, both resolved and parametrized, in GCMs and CCMs. The GRACILE data set is available as supplementary data at https://doi.org/10.1594/PANGAEA.879658" target="_blank">https://doi.org/10.1594/PANGAEA.879658.

  16. The greening of the McGill Paleoclimate Model. Part I: Improved land surface scheme with vegetation dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yi; Mysak, Lawrence A.; Wang, Zhaomin [McGill University, Department of Atmospheric and Oceanic Sciences, Global Environmental and Climate Change Centre (GEC3), Montreal, QC (Canada); Brovkin, Victor [Potsdam Institute for Climate Impact Research (PIK), Potsdam (Germany)

    2005-04-01

    The formulation of a new land surface scheme (LSS) with vegetation dynamics for coupling to the McGill Paleoclimate Model (MPM) is presented. This LSS has the following notable improvements over the old version: (1) parameterization of deciduous and evergreen trees by using the model's climatology and the output of the dynamic global vegetation model, VECODE (Brovkin et al. in Ecological Modelling 101:251-261 (1997), Global Biogeochemical Cycles 16(4):1139, (2002)); (2) parameterization of tree leaf budburst and leaf drop by using the model's climatology; (3) parameterization of the seasonal cycle of the grass leaf area index; (4) parameterization of the seasonal cycle of tree leaf area index by using the time-dependent growth of the leaves; (5) calculation of land surface albedo by using vegetation-related parameters, snow depth and the model's climatology. The results show considerable improvement of the model's simulation of the present-day climate as compared with that simulated in the original physically-based MPM. In particular, the strong seasonality of terrestrial vegetation and the associated land surface albedo variations are in good agreement with several satellite observations of these quantities. The application of this new version of the MPM (the ''green'' MPM) to Holocene millennial-scale climate changes is described in a companion paper, Part II. (orig.)

  17. Alpine cloud climatology using long-term NOAA-AVHRR satellite data

    Energy Technology Data Exchange (ETDEWEB)

    Kaestner, M.; Kriebel, K.T.

    2000-07-01

    Three different climates have been identified by our evaluation of AVHRR (advanced very high resolution radiometer) data using APOLLO (AVHRR processing scheme over land, clouds and ocean) for a five-years cloud climatology of the Alpine region. The cloud cover data from four layers were spatially averaged in boxes of 15 km by 14 km. The study area only comprises 540 km by 560 km, but contains regions with moderate, Alpine and Mediterranean climate. Data from the period July 1989 until December 1996 have been considered. The temporal resolution is one scene per day, the early afternoon pass, yielding monthly means of satellite derived cloud coverages 5% to 10% above the daily mean compared to conventional surface observation. At nonvegetated sites the cloudiness is sometimes significantly overestimated. Averaging high resolution cloud data seems to be superior to low resolution measurements of cloud properties and averaging is favourable in topographical homogeneous regions only. The annual course of cloud cover reveals typical regional features as foehn or temporal singularities as the so-called Christmas thaw. The cloud cover maps in spatially high resolution show local luff/lee features which outline the orography. Less cloud cover is found over the Alps than over the forelands in winter, an accumulation of thick cirrus is found over the High Alps and an accumulation of thin cirrus north of the Alps. (orig.)

  18. Contributions of Tropical Cyclones to the North Atlantic Climatological Rainfall as Observed from Satellites

    Science.gov (United States)

    Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.; Einaudi, Franco (Technical Monitor)

    2000-01-01

    The tropical cyclone rainfall climatology study that was performed for the North Pacific was extended to the North Atlantic. Similar to the North Pacific tropical cyclone study, mean monthly rainfall within 444 km of the center of the North Atlantic tropical cyclones (i.e., that reached storm stage and greater) was estimated from passive microwave satellite observations during, an eleven year period. These satellite-observed rainfall estimates were used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the North Atlantic total rainfall during, June-November when tropical cyclones were most abundant. The main results from this study indicate: 1) that tropical cyclones contribute, respectively, 4%, 3%, and 4% to the western, eastern, and entire North Atlantic; 2) similar to that observed in the North Pacific, the maximum in North Atlantic tropical cyclone rainfall is approximately 5 - 10 deg poleward (depending on longitude) of the maximum non-tropical cyclone rainfall; 3) tropical cyclones contribute regionally a maximum of 30% of the total rainfall 'northeast of Puerto Rico, within a region near 15 deg N 55 deg W, and off the west coast of Africa; 4) there is no lag between the months with maximum tropical cyclone rainfall and non-tropical cyclone rainfall in the western North Atlantic, while in the eastern North Atlantic, maximum tropical cyclone rainfall precedes maximum non-tropical cyclone rainfall; 5) like the North Pacific, North Atlantic tropical cyclones Of hurricane intensity generate the greatest amount of rainfall in the higher latitudes; and 6) warm ENSO events inhibit tropical cyclone rainfall.

  19. Associating Land Surface Temperature Retrieved From Satellite and Unmanned Aerial Vehicle Data With Urban Cover and Topography in Aburrá Valley

    Science.gov (United States)

    Guzmán, G.; Hoyos Ortiz, C. D.

    2017-12-01

    Urban heat island effect commonly refers to temperature differences between urban areas and their countrysides due to urbanization. These temperature differences are evident at surface, and within the canopy and the boundary layer. This effect is heterogeneous within the city, and responds to urban morphology, prevailing materials, amount of vegetation, among others, which are also important in the urban balance of energy. In order to study the relationship between land surface temperature (LST) and urban coverage over Aburrá Valley, which is a narrow valley locate at tropical Andes in northern South America, Landsat 8 mission products of LST, density of vegetation (normalized difference vegetation index, NDVI), and a proxy of soil humidity are derived and used. The results are analyzed from the point of view of dominant urban form and settlement density at scale of neighborhoods, and also from potential downward solar radiation received at the surface. Besides, specific sites were chosen to obtain LST from thermal imaging using an unmanned aerial vehicle to characterize micro-scale patterns and to validate Landast retrievals. Direct relationships between LST, NDVI, soil humidity, and duration of insolation are found, showing the impact of the current spatial distribution of land uses on surface temperature over Aburrá Valley. In general, the highest temperatures correspond to neighborhoods with large, flat-topped buildings in commercial and industrial areas, and low-rise building in residential areas with scarce vegetation, all on the valley bottom. Landsat images are in the morning for the Aburrá Valley, for that reason the coldest temperatures are prevalent at certain orientation of the hillslope, according with the amount of radiation received from sunrise to time of data.

  20. Correcting satellite-based precipitation products through SMOS soil moisture data assimilation in two land-surface models of different complexity: API and SURFEX

    Science.gov (United States)

    Real-time rainfall accumulation estimates at the global scale is useful for many applications. However, the real-time versions of satellite-based rainfall products are known to contain errors relative to real rainfall observed in situ. Recent studies have demonstrated how information about rainfall ...

  1. A bare ground evaporation revision in the ECMWF land-surface scheme: evaluation of its impact using ground soil moisture and satellite microwave data

    Directory of Open Access Journals (Sweden)

    C. Albergel

    2012-10-01

    Full Text Available In situ soil moisture data from 122 stations across the United States are used to evaluate the impact of a new bare ground evaporation formulation at ECMWF. In November 2010, the bare ground evaporation used in ECMWF's operational Integrated Forecasting System (IFS was enhanced by adopting a lower stress threshold than for the vegetation, allowing a higher evaporation. It results in more realistic soil moisture values when compared to in situ data, particularly over dry areas. Use was made of the operational IFS and offline experiments for the evaluation. The latter are based on a fixed version of the IFS and make it possible to assess the impact of a single modification, while the operational analysis is based on a continuous effort to improve the analysis and modelling systems, resulting in frequent updates (a few times a year. Considering the field sites with a fraction of bare ground greater than 0.2, the root mean square difference (RMSD of soil moisture is shown to decrease from 0.118 m3 m−3 to 0.087 m3 m−3 when using the new formulation in offline experiments, and from 0.110 m3 m−3 to 0.088 m3 m−3 in operations. It also improves correlations. Additionally, the impact of the new formulation on the terrestrial microwave emission at a global scale is investigated. Realistic and dynamically consistent fields of brightness temperature as a function of the land surface conditions are required for the assimilation of the SMOS data. Brightness temperature simulated from surface fields from two offline experiments with the Community Microwave Emission Modelling (CMEM platform present monthly mean differences up to 7 K. Offline experiments with the new formulation present drier soil moisture, hence simulated brightness temperature with its surface fields are larger. They are also closer to SMOS remotely sensed brightness temperature.

  2. A Spatio-Temporal Analysis of the Relationship Between Near-Surface Air Temperature and Satellite Land Surface Temperatures Using 17 Years of Data from the ATSR Series

    Science.gov (United States)

    Ghent, D.; Good, E.; Bulgin, C.; Remedios, J. J.

    2017-12-01

    Surface temperatures (ST) over land have traditionally been measured at weather stations. There are many parts of the globe with very few stations, e.g. across much of Africa, leading to gaps in ST datasets, affecting our understanding of how ST is changing, and the impacts of extreme events. Satellites can provide global ST data but these observations represent how hot the land ST (LST; including the uppermost parts of e.g. trees, buildings) is to touch, whereas stations measure the air temperature just above the surface (T2m). Satellite LST data may only be available in cloud-free conditions and data records are frequently climate studies. In this study, the relationship between clear-sky satellite LST and all-sky T2m is characterised in space and time using >17 years of data. The analysis uses a new monthly LST climate data record (CDR) based on the Along-Track Scanning Radiometer (ATSR) series, which has been produced within the European Space Agency GlobTemperature project. The results demonstrate the dependency of the global LST-T2m differences on location, land cover, vegetation and elevation. LSTnight ( 10 pm local solar time) is found to be closely coupled with minimum T2m (Tmin) and the two temperatures generally consistent to within ±5 °C (global median LSTnight- Tmin= 1.8 °C, interquartile range = 3.8 °C). The LSTday ( 10 am local time)-maximum T2m (Tmax) variability is higher because LST is strongly influenced by insolation and surface regime (global median LSTday-Tmax= -0.1 °C, interquartile range = 8.1 °C). Correlations for both temperature pairs are typically >0.9 outside of the tropics. A crucial aspect of this study is a comparison between the monthly global anomaly time series of LST and CRUTEM4 T2m. The time series agree remarkably well, with a correlation of 0.9 and 90% of the CDR anomalies falling within the T2m 95% confidence limits (see figure). This analysis provides independent verification of the 1995-2012 T2m anomaly time series

  3. Improving Frozen Precipitation Density Estimation in Land Surface Modeling

    Science.gov (United States)

    Sparrow, K.; Fall, G. M.

    2017-12-01

    The Office of Water Prediction (OWP) produces high-value water supply and flood risk planning information through the use of operational land surface modeling. Improvements in diagnosing frozen precipitation density will benefit the NWS's meteorological and hydrological services by refining estimates of a significant and vital input into land surface models. A current common practice for handling the density of snow accumulation in a land surface model is to use a standard 10:1 snow-to-liquid-equivalent ratio (SLR). Our research findings suggest the possibility of a more skillful approach for assessing the spatial variability of precipitation density. We developed a 30-year SLR climatology for the coterminous US from version 3.22 of the Daily Global Historical Climatology Network - Daily (GHCN-D) dataset. Our methods followed the approach described by Baxter (2005) to estimate mean climatological SLR values at GHCN-D sites in the US, Canada, and Mexico for the years 1986-2015. In addition to the Baxter criteria, the following refinements were made: tests were performed to eliminate SLR outliers and frequent reports of SLR = 10, a linear SLR vs. elevation trend was fitted to station SLR mean values to remove the elevation trend from the data, and detrended SLR residuals were interpolated using ordinary kriging with a spherical semivariogram model. The elevation values of each station were based on the GMTED 2010 digital elevation model and the elevation trend in the data was established via linear least squares approximation. The ordinary kriging procedure was used to interpolate the data into gridded climatological SLR estimates for each calendar month at a 0.125 degree resolution. To assess the skill of this climatology, we compared estimates from our SLR climatology with observations from the GHCN-D dataset to consider the potential use of this climatology as a first guess of frozen precipitation density in an operational land surface model. The difference in

  4. Goddard Satellite-Based Surface Turbulent Fluxes Climatology, Yearly Grid V3

    Data.gov (United States)

    National Aeronautics and Space Administration — These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-3 Dataset recently produced through a MEaSUREs funded project led by Dr. Chung-Lin Shie...

  5. Goddard Satellite-Based Surface Turbulent Fluxes Climatology, Seasonal Grid V3

    Data.gov (United States)

    National Aeronautics and Space Administration — These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-3 Dataset recently produced through a MEaSUREs funded project led by Dr. Chung-Lin Shie...

  6. Climatology and Interannual Variability of Quasi-Global Intense Precipitation Using Satellite Observations

    Science.gov (United States)

    Ricko, Martina; Adler, Robert F.; Huffman, George J.

    2016-01-01

    Climatology and variations of recent mean and intense precipitation over a near-global (50 deg. S 50 deg. N) domain on a monthly and annual time scale are analyzed. Data used to derive daily precipitation to examine the effects of spatial and temporal coverage of intense precipitation are from the current Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 version 7 precipitation product, with high spatial and temporal resolution during 1998 - 2013. Intense precipitation is defined by several different parameters, such as a 95th percentile threshold of daily precipitation, a mean precipitation that exceeds that percentile, or a fixed threshold of daily precipitation value [e.g., 25 and 50 mm day(exp -1)]. All parameters are used to identify the main characteristics of spatial and temporal variation of intense precipitation. High correlations between examined parameters are observed, especially between climatological monthly mean precipitation and intense precipitation, over both tropical land and ocean. Among the various parameters examined, the one best characterizing intense rainfall is a fraction of daily precipitation Great than or equal to 25 mm day(exp. -1), defined as a ratio between the intense precipitation above the used threshold and mean precipitation. Regions that experience an increase in mean precipitation likely experience a similar increase in intense precipitation, especially during the El Nino Southern Oscillation (ENSO) events. Improved knowledge of this intense precipitation regime and its strong connection to mean precipitation given by the fraction parameter can be used for monitoring of intense rainfall and its intensity on a global to regional scale.

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

    Science.gov (United States)

    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.

  8. Contribution of Tropical Cyclones to the North Pacific Climatological Rainfall as Observed from Satellites.

    Science.gov (United States)

    Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.

    2000-10-01

    Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations for an 11-yr period. These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and interannual distribution of the North Pacific Ocean total rainfall during June-November when tropical cyclones are most important.To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from passive microwave satellite observations within 444-km radius of the center of those North Pacific tropical cyclones that reached storm stage and greater. These rain-rate observations are converted to monthly rainfall amounts and then compared with those for nontropical cyclone systems.The main results of this study indicate that 1) tropical cyclones contribute 7% of the rainfall to the entire domain of the North Pacific during the tropical cyclone season and 12%, 3%, and 4% when the study area is limited to, respectively, the western, central, and eastern third of the ocean; 2) the maximum tropical cyclone rainfall is poleward (5°-10° latitude depending on longitude) of the maximum nontropical cyclone rainfall; 3) tropical cyclones contribute a maximum of 30% northeast of the Philippine Islands and 40% off the lower Baja California coast; 4) in the western North Pacific, the tropical cyclone rainfall lags the total rainfall by approximately two months and shows seasonal latitudinal variation following the Intertropical Convergence Zone; and 5) in general, tropical cyclone rainfall is enhanced during the El Niño years by warm SSTs in the eastern North Pacific and by the monsoon trough in the western and central North Pacific.

  9. Variations in Upper-Level Water Vapor Transport Diagnosed from Climatological Satellite Data

    Science.gov (United States)

    Lerner, Jeffrey A; Jedlovee, Gary J.; Atkinson, Robert J.

    1998-01-01

    GOES-7 VAS measurements during the Pathfinder period (1987-88) have been analysed to reveal seasonal and interannual variations in moisture transport. Long term measurements of quality winds and humidity from satellite estimates show superior benefit in diagnosing middle and upper tropospheric large scale climate variations such as ENSO events and direct circulation systems such as the Hadley Cell. A water Vapor Transport Index (WVTI) has been developed to diagnose preferred regions of strong moisture transport and to gauge the seasonal and interannual intensities detected in the GOES viewing area. Second-order variables that may be derived from GOES winds will be also discussed on the poster.

  10. The retrieval of land surface albedo in rugged terrain

    NARCIS (Netherlands)

    Gao, B.; Jia, L.; Menenti, M.

    2012-01-01

    Land surface albedo may be derived from the satellite data through the estimation of a bidirectional reflectance distribution function (BRDF) model and angular integration. However many BRDF models do not consider explicitly the topography. In rugged terrain, the topography influences the observed

  11. A calibrated, high-resolution goes satellite solar insolation product for a climatology of Florida evapotranspiration

    Science.gov (United States)

    Paech, S.J.; Mecikalski, J.R.; Sumner, D.M.; Pathak, C.S.; Wu, Q.; Islam, S.; Sangoyomi, T.

    2009-01-01

    Estimates of incoming solar radiation (insolation) from Geostationary Operational Environmental Satellite observations have been produced for the state of Florida over a 10-year period (1995-2004). These insolation estimates were developed into well-calibrated half-hourly and daily integrated solar insolation fields over the state at 2 km resolution, in addition to a 2-week running minimum surface albedo product. Model results of the daily integrated insolation were compared with ground-based pyranometers, and as a result, the entire dataset was calibrated. This calibration was accomplished through a three-step process: (1) comparison with ground-based pyranometer measurements on clear (noncloudy) reference days, (2) correcting for a bias related to cloudiness, and (3) deriving a monthly bias correction factor. Precalibration results indicated good model performance, with a station-averaged model error of 2.2 MJ m-2/day (13%). Calibration reduced errors to 1.7 MJ m -2/day (10%), and also removed temporal-related, seasonal-related, and satellite sensor-related biases. The calibrated insolation dataset will subsequently be used by state of Florida Water Management Districts to produce statewide, 2-km resolution maps of estimated daily reference and potential evapotranspiration for water management-related activities. ?? 2009 American Water Resources Association.

  12. Response to Toward Unified Satellite Climatology of Aerosol Properties. 3; MODIS versus MISR versus AERONET

    Science.gov (United States)

    Kahn, Ralph A.; Garay, Michael J.; Nelson, David L.; Levy, Robert C.; Bull, Michael A.; Diner, David J.; Martonchik, John V.; Hansen, Earl G.; Remer, Lorraine A.; Tanre, Didler

    2010-01-01

    A recent paper by Mishchenko et al. compares near-coincident MISR, MODIS, and AERONET aerosol optical depth (AOD), and gives a much less favorable impression of the utility of the satellite products than that presented by the instrument teams and other groups. We trace the reasons for the differing pictures to whether known and previously documented limitations of the products are taken into account in the assessments. Specifically, the analysis approaches differ primarily in (1) the treatment of outliers, (2) the application of absolute vs. relative criteria for testing agreement, and (3) the ways in which seasonally varying spatial distributions of coincident retrievals are taken into account. Mishchenko et al. also do not distinguish between observational sampling differences and retrieval algorithm error. We assess the implications of the different analysis approaches, and cite examples demonstrating how the MISR and MODIS aerosol products have been applied successfully to a range of scientific investigations.

  13. Satellite, climatological, and theoretical inputs for modeling of the diurnal cycle of fire emissions

    Science.gov (United States)

    Hyer, E. J.; Reid, J. S.; Schmidt, C. C.; Giglio, L.; Prins, E.

    2009-12-01

    The diurnal cycle of fire activity is crucial for accurate simulation of atmospheric effects of fire emissions, especially at finer spatial and temporal scales. Estimating diurnal variability in emissions is also a critical problem for construction of emissions estimates from multiple sensors with variable coverage patterns. An optimal diurnal emissions estimate will use as much information as possible from satellite fire observations, compensate known biases in those observations, and use detailed theoretical models of the diurnal cycle to fill in missing information. As part of ongoing improvements to the Fire Location and Monitoring of Burning Emissions (FLAMBE) fire monitoring system, we evaluated several different methods of integrating observations with different temporal sampling. We used geostationary fire detections from WF_ABBA, fire detection data from MODIS, empirical diurnal cycles from TRMM, and simple theoretical diurnal curves based on surface heating. Our experiments integrated these data in different combinations to estimate the diurnal cycles of emissions for each location and time. Hourly emissions estimates derived using these methods were tested using an aerosol transport model. We present results of this comparison, and discuss the implications of our results for the broader problem of multi-sensor data fusion in fire emissions modeling.

  14. Remote sensing of land surface temperature: The directional viewing effect

    International Nuclear Information System (INIS)

    Smith, J.A.; Schmugge, T.J.; Ballard, J.R. Jr.

    1997-01-01

    Land Surface Temperature (LST) is an important parameter in understanding global environmental change because it controls many of the underlying processes in the energy budget at the surface and heat and water transport between the surface and the atmosphere. The measurement of LST at a variety of spatial and temporal scales and extension to global coverage requires remote sensing means to achieve these goals. Land surface temperature and emissivity products are currently being derived from satellite and aircraft remote sensing data using a variety of techniques to correct for atmospheric effects. Implicit in the commonly employed approaches is the assumption of isotropy in directional thermal infrared exitance. The theoretical analyses indicate angular variations in apparent infrared temperature will typically yield land surface temperature errors ranging from 1 to 4 C unless corrective measures are applied

  15. Land surface sensitivity of mesoscale convective systems

    Science.gov (United States)

    Tournay, Robert C.

    Mesoscale convective systems (MCSs) are important contributors to the hydrologic cycle in many regions of the world as well as major sources of severe weather. MCSs continue to challenge forecasters and researchers alike, arising from difficulties in understanding system initiation, propagation, and demise. One distinct type of MCS is that formed from individual convective cells initiated primarily by daytime heating over high terrain. This work is aimed at improving our understanding of the land surface sensitivity of this class of MCS in the contiguous United States. First, a climatology of mesoscale convective systems originating in the Rocky Mountains and adjacent high plains from Wyoming southward to New Mexico is developed through a combination of objective and subjective methods. This class of MCS is most important, in terms of total warm season precipitation, in the 500 to 1300m elevations of the Great Plains (GP) to the east in eastern Colorado to central Nebraska and northwest Kansas. Examining MCSs by longevity, short lasting MCSs (15 hrs) reveals that longer lasting systems tend to form further south and have a longer track with a more southerly track. The environment into which the MCS is moving showed differences across commonly used variables in convection forecasting, with some variables showing more favorable conditions throughout (convective inhibition, 0-6 km shear and 250 hPa wind speed) ahead of longer lasting MCSs. Other variables, such as convective available potential energy, showed improving conditions through time for longer lasting MCSs. Some variables showed no difference across longevity of MCS (precipitable water and large-scale vertical motion). From subsets of this MCS climatology, three regions of origin were chosen based on the presence of ridgelines extending eastward from the Rocky Mountains known to be foci for convection initiation and subsequent MCS formation: Southern Wyoming (Cheyenne Ridge), Colorado (Palmer divide) and

  16. Modelling land surface - atmosphere interactions

    DEFF Research Database (Denmark)

    Rasmussen, Søren Højmark

    representation of groundwater in the hydrological model is found to important and this imply resolving the small river valleys. Because, the important shallow groundwater is found in the river valleys. If the model does not represent the shallow groundwater then the area mean surface flux calculation......The study is investigates modelling of land surface – atmosphere interactions in context of fully coupled climatehydrological model. With a special focus of under what condition a fully coupled model system is needed. Regional climate model inter-comparison projects as ENSEMBLES have shown bias...... by the hydrological model is found to be insensitive to model resolution. Furthermore, this study highlights the effect of bias precipitation by regional climate model and it implications for hydrological modelling....

  17. Land surface Verification Toolkit (LVT)

    Science.gov (United States)

    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.

  18. On the sensitivity of Land Surface Temperature estimates in arid irrigated lands using MODTRAN

    KAUST Repository

    Rosas, Jorge; Houborg, Rasmus; McCabe, Matthew

    2015-01-01

    Land surface temperature (LST) derived from thermal infrared (TIR) satellite data has been reliably used as a remote indicator of evapotranspiration (ET) and surface moisture status. However, in order to retrieve the ET with an accuracy approaching

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  1. Using high-resolution satellite aerosol optical depth to estimate daily PM2.5 geographical distribution in Mexico City

    OpenAIRE

    Just, Allan C.; Wright, Robert O.; Schwartz, Joel; Coull, Brent A.; Baccarelli, Andrea A.; Tellez-Rojo, Martha María; Moody, Emily; Wang, Yujie; Lyapustin, Alexei; Kloog, Itai

    2015-01-01

    Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to...

  2. Estimation of daily minimum land surface air temperature using MODIS data in southern Iran

    Science.gov (United States)

    Didari, Shohreh; Norouzi, Hamidreza; Zand-Parsa, Shahrokh; Khanbilvardi, Reza

    2017-11-01

    Land surface air temperature (LSAT) is a key variable in agricultural, climatological, hydrological, and environmental studies. Many of their processes are affected by LSAT at about 5 cm from the ground surface (LSAT5cm). Most of the previous studies tried to find statistical models to estimate LSAT at 2 m height (LSAT2m) which is considered as a standardized height, and there is not enough study for LSAT5cm estimation models. Accurate measurements of LSAT5cm are generally acquired from meteorological stations, which are sparse in remote areas. Nonetheless, remote sensing data by providing rather extensive spatial coverage can complement the spatiotemporal shortcomings of meteorological stations. The main objective of this study was to find a statistical model from the previous day to accurately estimate spatial daily minimum LSAT5cm, which is very important in agricultural frost, in Fars province in southern Iran. Land surface temperature (LST) data were obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua and Terra satellites at daytime and nighttime periods with normalized difference vegetation index (NDVI) data. These data along with geometric temperature and elevation information were used in a stepwise linear model to estimate minimum LSAT5cm during 2003-2011. The results revealed that utilization of MODIS Aqua nighttime data of previous day provides the most applicable and accurate model. According to the validation results, the accuracy of the proposed model was suitable during 2012 (root mean square difference ( RMSD) = 3.07 °C, {R}_{adj}^2 = 87 %). The model underestimated (overestimated) high (low) minimum LSAT5cm. The accuracy of estimation in the winter time was found to be lower than the other seasons ( RMSD = 3.55 °C), and in summer and winter, the errors were larger than in the remaining seasons.

  3. Afforestation in China cools local land surface temperature

    OpenAIRE

    Peng, Shu-Shi; Piao, Shilong; Zeng, Zhenzhong; Ciais, Philippe; Zhou, Liming; Li, Laurent Z. X.; Myneni, Ranga B.; Yin, Yi; Zeng, Hui

    2014-01-01

    International audience; China has the largest afforested area in the world (~62 million hectares in 2008), and these forests are carbon sinks. The climatic effect of these new forests depends on how radiant and turbulent energy fluxes over these plantations modify surface temperature. For instance, a lower albedo may cause warming, which negates the climatic benefits of carbon sequestration. Here, we used satellite measurements of land surface temperature (LST) from planted forests and adjace...

  4. Extreme Maximum Land Surface Temperatures.

    Science.gov (United States)

    Garratt, J. R.

    1992-09-01

    There are numerous reports in the literature of observations of land surface temperatures. Some of these, almost all made in situ, reveal maximum values in the 50°-70°C range, with a few, made in desert regions, near 80°C. Consideration of a simplified form of the surface energy balance equation, utilizing likely upper values of absorbed shortwave flux (1000 W m2) and screen air temperature (55°C), that surface temperatures in the vicinity of 90°-100°C may occur for dry, darkish soils of low thermal conductivity (0.1-0.2 W m1 K1). Numerical simulations confirm this and suggest that temperature gradients in the first few centimeters of soil may reach 0.5°-1°C mm1 under these extreme conditions. The study bears upon the intrinsic interest of identifying extreme maximum temperatures and yields interesting information regarding the comfort zone of animals (including man).

  5. Galactic cosmic ray and El Nino Southern Oscillation trends in International Satellite Cloud Climatology Project D2 low-cloud properties

    DEFF Research Database (Denmark)

    Marsh, N.; Svensmark, Henrik

    2003-01-01

    [1] The recently reported correlation between clouds and galactic cosmic rays (GCR) implies the existence of a previously unknown process linking solar variability and climate. An analysis of the interannual variability of International Satellite Cloud Climatology Project D2 (ISCCP-D2) low-cloud...... a strong correlation with GCR, which suggests that low-cloud properties observed in these regions are less likely to be contaminated from overlying cloud. The GCR-low cloud correlation cannot easily be explained by internal climate processes, changes in direct solar forcing, or UV-ozone interactions...... properties over the period July 1983 to August 1994 suggests that low clouds are statistically related to two processes, (1) GCR and (2) El Nino-Southern Oscillation (ENSO), with GCR explaining a greater percentage of the total variance. Areas where satellites have an unobstructed view of low cloud possess...

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

    Science.gov (United States)

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

    2017-04-01

    Land surface models (LSM) are widely applied as supporting tools for policy-relevant assessment of climate change and its impact on terrestrial ecosystems, yet knowledge of their performance skills in representing the sensitivity of biophysical processes to changes in vegetation density is still limited. This is particularly relevant in light of the substantial impacts on regional climate associated with the changes in leaf area index (LAI) following the observed global greening. Benchmarking LSMs on the sensitivity of the simulated processes to vegetation density is essential to reduce their uncertainty and improve the representation of these effects. Here we present a novel benchmark system to assess model capacity in reproducing land surface-atmosphere energy exchanges modulated by vegetation density. Through a collaborative effort of different modeling groups, a consistent set of land surface energy fluxes and LAI dynamics has been generated from multiple LSMs, including JSBACH, JULES, ORCHIDEE, CLM4.5 and LPJ-GUESS. Relationships of interannual variations of modeled surface fluxes to LAI changes have been analyzed at global scale across different climatological gradients and compared with satellite-based products. A set of scoring metrics has been used to assess the overall model performances and a detailed analysis in the climate space has been provided to diagnose possible model errors associated to background conditions. Results have enabled us to identify model-specific strengths and deficiencies. An overall best performing model does not emerge from the analyses. However, the comparison with other models that work better under certain metrics and conditions indicates that improvements are expected to be potentially achievable. A general amplification of the biophysical processes mediated by vegetation is found across the different land surface schemes. Grasslands are characterized by an underestimated year-to-year variability of LAI in cold climates

  7. Evaluating the Impacts of NASA/SPoRT Daily Greenness Vegetation Fraction on Land Surface Model and Numerical Weather Forecasts

    Science.gov (United States)

    Bell, Jordan R.; Case, Jonathan L.; Molthan, Andrew L.

    2011-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center develops new products and techniques that can be used in operational meteorology. The majority of these products are derived from NASA polar-orbiting satellite imagery from the Earth Observing System (EOS) platforms. One such product is a Greenness Vegetation Fraction (GVF) dataset, which is produced from Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the new SPoRT-MODIS GVF dataset on land surface models apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. The second phase of the project is to examine the impacts of the SPoRT GVF dataset on NWP using the Weather Research and Forecasting (WRF) model. Two separate WRF model simulations were made for individual severe weather case days using the NCEP GVF (control) and SPoRT GVF (experimental), with all other model parameters remaining the same. Based on the sensitivity results in these case studies, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and lower direct surface heating, which typically resulted in lower (higher) predicted 2-m temperatures (2-m dewpoint temperatures). The opposite was true

  8. Impact of Vegetation Cover Fraction Parameterization schemes on Land Surface Temperature Simulation in the Tibetan Plateau

    Science.gov (United States)

    Lv, M.; Li, C.; Lu, H.; Yang, K.; Chen, Y.

    2017-12-01

    The parameterization of vegetation cover fraction (VCF) is an important component of land surface models. This paper investigates the impacts of three VCF parameterization schemes on land surface temperature (LST) simulation by the Common Land Model (CoLM) in the Tibetan Plateau (TP). The first scheme is a simple land cover (LC) based method; the second one is based on remote sensing observation (hereafter named as RNVCF) , in which multi-year climatology VCFs is derived from Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI (Normalized Difference Vegetation Index); the third VCF parameterization scheme derives VCF from the LAI simulated by LSM and clump index at every model time step (hereafter named as SMVCF). Simulated land surface temperature(LST) and soil temperature by CoLM with three VCF parameterization schemes were evaluated by using satellite LST observation and in situ soil temperature observation, respectively, during the period of 2010 to 2013. The comparison against MODIS Aqua LST indicates that (1) CTL produces large biases for both four seasons in early afternoon (about 13:30, local solar time), while the mean bias in spring reach to 12.14K; (2) RNVCF and SMVCF reduce the mean bias significantly, especially in spring as such reduce is about 6.5K. Surface soil temperature observed at 5 cm depth from three soil moisture and temperature monitoring networks is also employed to assess the skill of three VCF schemes. The three networks, crossing TP from West to East, have different climate and vegetation conditions. In the Ngari network, located in the Western TP with an arid climate, there are not obvious differences among three schemes. In Naqu network, located in central TP with a semi-arid climate condition, CTL shows a severe overestimates (12.1 K), but such overestimations can be reduced by 79% by RNVCF and 87% by SMVCF. In the third humid network (Maqu in eastern TP), CoLM performs similar to Naqu. However, at both Naqu and Maqu networks

  9. Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

    Science.gov (United States)

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

    2012-01-01

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

  10. Seasonal evaluation of the land surface sheme HTESSEL against remote sensing derived energy fluxes of the Transdanubian regions in Hungary

    NARCIS (Netherlands)

    Wipfler, E.L.; Metselaar, K.; Dam, van J.C.; Feddes, R.A.; Meijgaard, van E.; Ulft, van L.H.; Hurk, van den B.; Zwart, S.J.; Bastiaanssen, W.G.M.

    2011-01-01

    The skill of the land surface model HTESSEL is assessed to reproduce evaporation in response to land surface characteristics and atmospheric forcing, both being spatially variable. Evaporation estimates for the 2005 growing season are inferred from satellite observations of the Western part of

  11. Detecting geothermal anomalies and evaluating LST geothermal component by combining thermal remote sensing time series and land surface model data

    NARCIS (Netherlands)

    Romaguera, M.; Vaughan, R. G.; Ettema, J.; Izquierdo-Verdiguier, E.; Hecker, C. A.; van der Meer, F. D.

    This paper explores for the first time the possibilities to use two land surface temperature (LST) time series of different origins (geostationary Meteosat Second Generation satellite data and Noah land surface modelling, LSM), to detect geothermal anomalies and extract the geothermal component of

  12. Detecting geothermal anomalies and evaluating LST geothermal component by combining thermal remote sensing time series and land surface model data

    NARCIS (Netherlands)

    Romaguera, M.; Vaughan, R. G.; Ettema, J.; Izquierdo-Verdiguier, E.; Hecker, C. A.; van der Meer, F. D.

    2017-01-01

    This paper explores for the first time the possibilities to use two land surface temperature (LST) time series of different origins (geostationary Meteosat Second Generation satellite data and Noah land surface modelling, LSM), to detect geothermal anomalies and extract the geothermal component of

  13. Evaluating the Impacts of NASA/SPoRT Daily Greenness Vegetation Fraction on Land Surface Model and Numerical Weather Forecasts

    Science.gov (United States)

    Bell, Jordan R.; Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.

    2012-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the SPoRT-MODIS GVF dataset on a land surface model (LSM) apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. In the West, higher latent heat fluxes prevailed, which enhanced the rates of evapotranspiration and soil moisture depletion in the LSM. By late Summer and Autumn, both the average sensible and latent heat fluxes increased in the West as a result of the more rapid soil drying and higher coverage of GVF. The impacts of the SPoRT GVF dataset on NWP was also examined for a single severe weather case study using the Weather Research and Forecasting (WRF) model. Two separate coupled LIS/WRF model simulations were made for the 17 July 2010 severe weather event in the Upper Midwest using the NCEP and SPoRT GVFs, with all other model parameters remaining the same. Based on the sensitivity results, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and

  14. Validation of Land Surface Temperature from Sentinel-3

    Science.gov (United States)

    Ghent, D.

    2017-12-01

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

  15. Climate Impacts of Fire-Induced Land-Surface Changes

    Science.gov (United States)

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

    2017-12-01

    One of the consequences of wildfires is the changes in land-surface properties such as removal of vegetation. This will change local and regional climate through modifying the land-air heat and water fluxes. This study investigates mechanism by developing and a parameterization of fire-induced land-surface property changes and applying it to modeling of the climate impacts of large wildfires in the United States. Satellite remote sensing was used to quantitatively evaluate the land-surface changes from large fires provided from the Monitoring Trends in Burning Severity (MTBS) dataset. It was found that the changes in land-surface properties induced by fires are very complex, depending on vegetation type and coverage, climate type, season and time after fires. The changes in LAI are remarkable only if the actual values meet a threshold. Large albedo changes occur in winter for fires in cool climate regions. The signs are opposite between the first post-fire year and the following years. Summer day-time temperature increases after fires, while nigh-time temperature changes in various patterns. The changes are larger in forested lands than shrub / grassland lands. In the parameterization scheme, the detected post-fire changes are decomposed into trends using natural exponential functions and fluctuations of periodic variations with the amplitudes also determined by natural exponential functions. The final algorithm is a combination of the trends, periods, and amplitude functions. This scheme is used with Earth system models to simulate the local and regional climate effects of wildfires.

  16. ECOCLIMAP-II/Europe: a twofold database of ecosystems and surface parameters at 1-km resolution based on satellite information for use in land surface, meteorological and climate models

    Science.gov (United States)

    Faroux, S.; Kaptué Tchuenté, A. T.; Roujean, J.-L.; Masson, V.; Martin, E.; Le Moigne, P.

    2012-11-01

    The overall objective of the present study is to introduce the new ECOCLIMAP-II database for Europe, which is an upgrade for this region of the former initiative, ECOCLIMAP-I, already implemented at global scale. The ECOCLIMAP programme is a dual database at 1-km resolution that includes an ecosystem classification and a coherent set of land surface parameters that are primarily mandatory in meteorological modelling (notably leaf area index and albedo). Hence, the aim of this innovative physiography is to enhance the quality of initialisation and impose some surface attributes within the scope of weather forecasting and climate related studies. The strategy for implementing ECOCLIMAP-II is to depart from prevalent land cover products such as CLC2000 (Corine Land Cover) and GLC2000 (Global Land Cover) by splitting existing classes into new classes that possess a better regional character by virtue of the climatic environment (latitude, proximity to the sea, topography). The leaf area index (LAI) from MODIS and NDVI from SPOT/Vegetation yield the two proxy variables that were considered here in order to perform a multi-year trimmed analysis between 1999 and 2005 using the K-means method. Further, meteorological applications require each land cover type to appear as a partition of fractions of 4 main surface types or tiles (nature, water bodies, sea, urban areas) and, inside the nature tile, fractions of 12 Plant Functional Types (PFTs) representing generic vegetation types - principally broadleaf forest, needleleaf forest, C3 and C4 crops, grassland and bare land - as incorporated by the SVAT model ISBA developed at Météo France. This landscape division also forms the cornerstone of a validation exercise. The new ECOCLIMAP-II can be verified with auxiliary land cover products at very fine and coarse resolutions by means of versatile land occupation nomenclatures.

  17. ECOCLIMAP-II/Europe: a twofold database of ecosystems and surface parameters at 1 km resolution based on satellite information for use in land surface, meteorological and climate models

    Science.gov (United States)

    Faroux, S.; Kaptué Tchuenté, A. T.; Roujean, J.-L.; Masson, V.; Martin, E.; Le Moigne, P.

    2013-04-01

    The overall objective of the present study is to introduce the new ECOCLIMAP-II database for Europe, which is an upgrade for this region of the former initiative, ECOCLIMAP-I, already implemented at global scale. The ECOCLIMAP programme is a dual database at 1 km resolution that includes an ecosystem classification and a coherent set of land surface parameters that are primarily mandatory in meteorological modelling (notably leaf area index and albedo). Hence, the aim of this innovative physiography is to enhance the quality of initialisation and impose some surface attributes within the scope of weather forecasting and climate related studies. The strategy for implementing ECOCLIMAP-II is to depart from prevalent land cover products such as CLC2000 (Corine Land Cover) and GLC2000 (Global Land Cover) by splitting existing classes into new classes that possess a better regional character by virtue of the climatic environment (latitude, proximity to the sea, topography). The leaf area index (LAI) from MODIS and normalized difference vegetation index (NDVI) from SPOT/Vegetation (a global monitoring system of vegetation) yield the two proxy variables that were considered here in order to perform a multi-year trimmed analysis between 1999 and 2005 using the K-means method. Further, meteorological applications require each land cover type to appear as a partition of fractions of 4 main surface types or tiles (nature, water bodies, sea, urban areas) and, inside the nature tile, fractions of 12 plant functional types (PFTs) representing generic vegetation types - principally broadleaf forest, needleleaf forest, C3 and C4 crops, grassland and bare land - as incorporated by the SVAT model ISBA (Interactions Surface Biosphere Atmosphere) developed at Météo France. This landscape division also forms the cornerstone of a validation exercise. The new ECOCLIMAP-II can be verified with auxiliary land cover products at very fine and coarse resolutions by means of versatile land

  18. Tropical Rainfall Analysis Using TRMM in Combination With Other Satellite Gauge Data: Comparison with Global Precipitation Climatology Project (GPCP) Results

    Science.gov (United States)

    Adler, Robert F.; Huffman, George J.; Bolvin, David; Nelkin, Eric; Curtis, Scott

    1999-01-01

    This paper describes recent results of using Tropical Rainfall Measuring Mission (TRMM) information as the key calibration tool in a merged analysis on a 1 deg x 1 deg latitude/longitude monthly scale based on multiple satellite sources and raingauge analysis. The procedure used to produce the GPCP data set is a stepwise approach which first combines the satellite low-orbit microwave and geosynchronous IR observations into a "multi-satellite" product and than merges that result with the raingauge analysis. Preliminary results produced with the still-stabilizing TRMM algorithms indicate that TRMM shows tighter spatial gradients in tropical rain maxima with higher peaks in the center of the maxima. The TRMM analyses will be used to evaluate the evolution of the 1998 ENSO variations, again in comparison with the GPCP analyses.

  19. Remote sensing of land surface phenology

    Science.gov (United States)

    Meier, G.A.; Brown, Jesslyn 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.

  20. The esa earth explorer land surface processes and interactions mission

    Science.gov (United States)

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

    2017-11-01

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

  1. A satellite-based climatology (1989-2012) of lake surface water temperature from AVHRR 1-km for Central European water bodies

    Science.gov (United States)

    Riffler, Michael; Wunderle, Stefan

    2013-04-01

    The temperature of lakes is an important parameter for lake ecosystems influencing the speed of physio-chemical reactions, the concentration of dissolved gazes (e.g. oxygen), and vertical mixing. Even small temperature changes might have irreversible effects on the lacustrine system due to the high specific heat capacity of water. These effects could alter the quality of lake water depending on parameters like lake size and volume. Numerous studies mention lake water temperature as an indicator of climate change and in the Global Climate Observing System (GCOS) requirements it is listed as an essential climate variable. In contrast to in situ observations, satellite imagery offers the possibility to derive spatial patterns of lake surface water temperature (LSWT) and their variability. Moreover, although for some European lakes long in situ time series are available, the temperatures of many lakes are not measured or only on a non-regular basis making these observations insufficient for climate monitoring. However, only few satellite sensors offer the possibility to analyze time series which cover more than 20 years. The Advanced Very High Resolution Radiometer (AVHRR) is among these and has been flown on the National Oceanic and Atmospheric Administration (NOAA) Polar Operational Environmental Satellites (POES) and on the Meteorological Operational Satellites (MetOp) from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) as a heritage instrument for almost 35 years. It will be carried on for at least ten more years finally offering a unique opportunity for satellite-based climate studies. Herein we present the results from a study initiated by the Swiss GCOS office to generate a satellite-based LSWT climatology for the pre-alpine water bodies in Switzerland. It relies on the extensive AVHRR 1-km data record (1985-2012) of the Remote Sensing Research Group at the University of Bern (RSGB) and has been derived from the AVHRR/2

  2. A Satellite-Based Surface Radiation Climatology Derived by Combining Climate Data Records and Near-Real-Time Data

    Directory of Open Access Journals (Sweden)

    Bodo Ahrens

    2013-09-01

    Full Text Available This study presents a method for adjusting long-term climate data records (CDRs for the integrated use with near-real-time data using the example of surface incoming solar irradiance (SIS. Recently, a 23-year long (1983–2005 continuous SIS CDR has been generated based on the visible channel (0.45–1 μm of the MVIRI radiometers onboard the geostationary Meteosat First Generation Platform. The CDR is available from the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF. Here, it is assessed whether a homogeneous extension of the SIS CDR to the present is possible with operationally generated surface radiation data provided by CM SAF using the SEVIRI and GERB instruments onboard the Meteosat Second Generation satellites. Three extended CM SAF SIS CDR versions consisting of MVIRI-derived SIS (1983–2005 and three different SIS products derived from the SEVIRI and GERB instruments onboard the MSG satellites (2006 onwards were tested. A procedure to detect shift inhomogeneities in the extended data record (1983–present was applied that combines the Standard Normal Homogeneity Test (SNHT and a penalized maximal T-test with visual inspection. Shift detection was done by comparing the SIS time series with the ground stations mean, in accordance with statistical significance. Several stations of the Baseline Surface Radiation Network (BSRN and about 50 stations of the Global Energy Balance Archive (GEBA over Europe were used as the ground-based reference. The analysis indicates several breaks in the data record between 1987 and 1994 probably due to artefacts in the raw data and instrument failures. After 2005 the MVIRI radiometer was replaced by the narrow-band SEVIRI and the broadband GERB radiometers and a new retrieval algorithm was applied. This induces significant challenges for the homogenisation across the satellite generations. Homogenisation is performed by applying a mean-shift correction depending on the shift size of

  3. Physically plausible prescription of land surface model soil moisture

    Science.gov (United States)

    Hauser, Mathias; Orth, René; Thiery, Wim; Seneviratne, Sonia

    2016-04-01

    Land surface hydrology is an important control of surface weather and climate, especially under extreme dry or wet conditions where it can amplify heat waves or floods, respectively. Prescribing soil moisture in land surface models is a valuable technique to investigate this link between hydrology and climate. It has been used for example to assess the influence of soil moisture on temperature variability, mean and extremes (Seneviratne et al. 2006, 2013, Lorenz et al., 2015). However, perturbing the soil moisture content artificially can lead to a violation of the energy and water balances. Here we present a new method for prescribing soil moisture which ensures water and energy balance closure by using only water from runoff and a reservoir term. If water is available, the method prevents soil moisture decrease below climatological values. Results from simulations with the Community Land Model (CLM) indicate that our new method allows to avoid soil moisture deficits in many regions of the world. We show the influence of the irrigation-supported soil moisture content on mean and extreme temperatures and contrast our findings with that of earlier studies. Additionally, we will assess how long into the 21st century the new method will be able to maintain present-day climatological soil moisture levels for different regions. Lorenz, R., Argüeso, D., Donat, M.G., Pitman, A.J., den Hurk, B.V., Berg, A., Lawrence, D.M., Chéruy, F., Ducharne, A., Hagemann, S. and Meier, A., 2015. Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble. Journal of Geophysical Research: Atmospheres. Seneviratne, S.I., Lüthi, D., Litschi, M. and Schär, C., 2006. Land-atmosphere coupling and climate change in Europe. Nature, 443(7108), pp.205-209. Seneviratne, S.I., Wilhelm, M., Stanelle, T., Hurk, B., Hagemann, S., Berg, A., Cheruy, F., Higgins, M.E., Meier, A., Brovkin, V. and Claussen, M., 2013. Impact of soil moisture

  4. THE EFFECT OF LAND USE CHANGE ON LAND SURFACE TEMPERATURE IN THE NETHERLANDS

    Directory of Open Access Journals (Sweden)

    S. Youneszadeh

    2015-12-01

    Full Text Available The Netherlands is a small country with a relatively large population which experienced a rapid rate of land use changes from 2000 to 2008 years due to the industrialization and population increase. Land use change is especially related to the urban expansion and open agriculture reduction due to the enhanced economic growth. This research reports an investigation into the application of remote sensing and geographical information system (GIS in combination with statistical methods to provide a quantitative information on the effect of land use change on the land surface temperature. In this study, remote sensing techniques were used to retrieve the land surface temperature (LST by using the MODIS Terra (MOD11A2 Satellite imagery product. As land use change alters the thermal environment, the land surface temperature (LST could be a proper change indicator to show the thermal changes in relation with land use changes. The Geographical information system was further applied to extract the mean yearly land surface temperature (LST for each land use type and each province in the 2003, 2006 and 2008 years, by using the zonal statistic techniques. The results show that, the inland water and offshore area has the highest night land surface temperature (LST. Furthermore, the Zued (South-Holland province has the highest night LST value in the 2003, 2006 and 2008 years. The result of this research will be helpful tool for urban planners and environmental scientists by providing the critical information about the land surface temperature.

  5. Land-surface modelling in hydrological perspective

    DEFF Research Database (Denmark)

    Overgaard, Jesper; Rosbjerg, Dan; Butts, M.B.

    2006-01-01

    The purpose of this paper is to provide a review of the different types of energy-based land-surface models (LSMs) and discuss some of the new possibilities that will arise when energy-based LSMs are combined with distributed hydrological modelling. We choose to focus on energy-based approaches......, and the difficulties inherent in various evaluation procedures are presented. Finally, the dynamic coupling of hydrological and atmospheric models is explored, and the perspectives of such efforts are discussed......., because in comparison to the traditional potential evapotranspiration models, these approaches allow for a stronger link to remote sensing and atmospheric modelling. New opportunities for evaluation of distributed land-surface models through application of remote sensing are discussed in detail...

  6. The impact of climatic and non-climatic factors on land surface temperature in southwestern Romania

    Science.gov (United States)

    Roşca, Cristina Florina; Harpa, Gabriela Victoria; Croitoru, Adina-Eliza; Herbel, Ioana; Imbroane, Alexandru Mircea; Burada, Doina Cristina

    2017-11-01

    Land surface temperature is one of the most important parameters related to global warming. It depends mainly on soil type, discontinuous vegetation cover, or lack of precipitation. The main purpose of this paper is to investigate the relationship between high LST, synoptic conditions and air masses trajectories, vegetation cover, and soil type in one of the driest region in Romania. In order to calculate the land surface temperature and normalized difference vegetation index, five satellite images of LANDSAT missions 5 and 7, covering a period of 26 years (1986-2011), were selected, all of them collected in the month of June. The areas with low vegetation density were derived from normalized difference vegetation index, while soil types have been extracted from Corine Land Cover database. HYSPLIT application was employed to identify the air masses origin based on their backward trajectories for each of the five study cases. Pearson, logarithmic, and quadratic correlations were used to detect the relationships between land surface temperature and observed ground temperatures, as well as between land surface temperature and normalized difference vegetation index. The most important findings are: strong correlation between land surface temperature derived from satellite images and maximum ground temperature recorded in a weather station located in the area, as well as between areas with land surface temperature equal to or higher than 40.0 °C and those with lack of vegetation; the sandy soils are the most prone to high land surface temperature and lack of vegetation, followed by the chernozems and brown soils; extremely severe drought events may occur in the region.

  7. Downscaling of Aircraft, Landsat, and MODIS-bases Land Surface Temperature Images with Support Vector Machines

    Science.gov (United States)

    High spatial resolution Land Surface Temperature (LST) images are required to estimate evapotranspiration (ET) at a field scale for irrigation scheduling purposes. Satellite sensors such as Landsat 5 Thematic Mapper (TM) and Moderate Resolution Imaging Spectroradiometer (MODIS) can offer images at s...

  8. Identification of soil erosion land surfaces by Landsat data analysis and processing

    International Nuclear Information System (INIS)

    Lo Curzio, S.

    2009-01-01

    In this paper, we outline the typical relationship between the spectral reflectance of aileron's on newly-formed land surfaces and the geo morphological features of the land surfaces at issue. These latter represent the products of superficial erosional processes due to the action of the gravity and/or water; thus, such land surfaces are highly representative of the strong soil degradation occurring in a wide area located on the boundary between Molise and Puglia regions (Southern Italy). The results of this study have been reported on thematic maps; on such maps, the detected erosional land surfaces have been mapped on the basis of their typical spectral signature. The study has been performed using Landsat satellite imagery data which have been then validated by means of field survey data. The satellite data have been processed using remote sensing techniques, such as: false colour composite, contrast stretching, principal component analysis and decorrelation stretching. The study has permitted to produce, in a relatively short time and at low expense, a map of the eroded land surfaces. Such a result represents a first and fundamental step in evaluating and monitoring the erosional processes in the study area [it

  9. Climatology of the Occurrence Rate and Amplitudes of Local Time Distinguished Equatorial Plasma Depletions Observed by Swarm Satellite

    Science.gov (United States)

    Wan, Xin; Xiong, Chao; Rodriguez-Zuluaga, Juan; Kervalishvili, Guram N.; Stolle, Claudia; Wang, Hui

    2018-04-01

    In this study, we developed an autodetection technique for the equatorial plasma depletions (EPDs) and their occurrence and depletion amplitudes based on in situ electron density measurements gathered by Swarm A satellite. For the first time, comparisons are made among the detected EPDs and their amplitudes with the loss of Global Positioning System (GPS) signal of receivers onboard Swarm A, and the Swarm Level-2 product, Ionospheric Bubble Index (IBI). It has been found that the highest rate of EPD occurrence takes place generally between 2200 and 0000 magnetic local time (MLT), in agreement with the IBI. However, the largest amplitudes of EPD are detected earlier at about 1900-2100 MLT. This coincides with the moment of higher background electron density and the largest occurrence of GPS signal loss. From a longitudinal perspective, the higher depletion amplitude is always witnessed in spatial bins with higher background electron density. At most longitudes, the occurrence rate of postmidnight EPDs is reduced compared to premidnight ones; while more postmidnight EPDs are observed at African longitudes. CHAMP observations confirm this point regardless of high or low solar activity condition. Further by comparing with previous studies and the plasma vertical drift velocity from ROCSAT-1, we suggest that while the F region vertical plasma drift plays a key role in dominating the occurrence of EPDs during premidnight hours, the postmidnight EPDs are the combined results from the continuing of former EPDs and newborn EPDs, especially during June solstice. And these newborn EPDs during postmidnight hours seem to be less related to the plasma vertical drift.

  10. Analytical Retrieval of Global Land Surface Emissivity Maps at AMSR-E passive microwave frequencies

    Science.gov (United States)

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

    2009-12-01

    Land emissivity is a crucial boundary condition in Numerical Weather Prediction (NWP) modeling. Land emissivity is also a key indicator of land surface and subsurface properties. The objective of this study, supported by NOAA-NESDIS, is to develop global land emissivity maps using AMSR-E passive microwave measurements along with several ancillary data. The International Satellite Cloud Climatology Project (ISCCP) database has been used to obtain several inputs for the proposed approach such as land surface temperature, cloud mask and atmosphere profile. The Community Radiative Transfer Model (CRTM) has been used to estimate upwelling and downwelling atmospheric contributions. Although it is well known that correction of the atmospheric effect on brightness temperature is required at higher frequencies (over 19 GHz), our preliminary results have shown that a correction at 10.7 GHz is also necessary over specific areas. The proposed approach is based on three main steps. First, all necessary data have been collected and processed. Second, a global cloud free composite of AMSR-E data and corresponding ancillary images is created. Finally, monthly composting of emissivity maps has been performed. AMSR-E frequencies at 6.9, 10.7, 18.7, 36.5 and 89.0 GHz have been used to retrieve the emissivity. Water vapor information obtained from ISCCP (TOVS data) was used to calculate upwelling, downwelling temperatures and atmospheric transmission in order to assess the consistency of those derived from the CRTM model. The frequent land surface temperature (LST) determination (8 times a day) in the ISCCP database has allowed us to assess the diurnal cycle effect on emissivity retrieval. Differences in magnitude and phase between thermal temperature and low frequencies microwave brightness temperature have been noticed. These differences seem to vary in space and time. They also depend on soil texture and thermal inertia. The proposed methodology accounts for these factors and

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    2007-05-01

    The spatially distributed application of a land surface model (LSM) over a region of interest requires the application of similarly distributed precipitation fields that can be derived from various sources, including surface gauge networks, surface-based radar, and orbital platforms. The spatial variability of precipitation influences the spatial organization of soil temperature and moisture states and, consequently, the spatial variability of land- atmosphere fluxes. The accuracy of spatially-distributed precipitation fields can contribute significantly to the uncertainty of model-based hydrological states and fluxes at the land surface. Collaborations between the Air Force Weather Agency (AFWA), NASA, and Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS-based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and

  13. Estimation of land surface temperature of Kaduna metropolis ...

    African Journals Online (AJOL)

    Estimation of land surface temperature of Kaduna metropolis, Nigeria using landsat images. Isa Zaharaddeen, Ibrahim I. Baba, Ayuba Zachariah. Abstract. Understanding the spatial variation of Land Surface Temperature (LST), will be helpful in urban micro climate studies. This study estimates the land surface temperature ...

  14. Communicating why land surface heterogeneity matters

    Science.gov (United States)

    Tague, C.; Burke, W.; Bart, R. R.; Turpin, E.; Wood, T.; Gordon, D.

    2017-12-01

    As hydrologic scientists, we know that land surface heterogeneity can have nuanced and sometimes dramatic impacts on the water cycle. Land surface characteristics, including the structure and composition of vegetation and soil storage and drainage properties, alter how incoming precipitation is translated into streamflow and evapotranspiration. Land surface heterogeneity can explain why this partitioning of incoming precipitation cannot always be computed by a simple water budget calculation. We also know that land surface characteristics are dynamic - vegetation grows and changes with fire, disease and human actions and these changes will alter the partitioning of water - how much so, however depends itself on other site characteristics - soil water storage and the timing and magnitude of precipitation. This complex impact of space-time dynamics on the water cycle is something we need to effectively communicate to non-experts. For example, we may want to explain why sometimes forest management practices increase water availability but sometimes they don't - or why the impacts of urbanization or fire are location specific. If we do not communicate these dependencies we risk over-simplifying and eroding scientific credibility when observed effects don't match simple generalizations. On the other hand excessive detail can overwhelm and disengage audiences. So how do we help different communities public, private landowners, other scientists, NGOs, governments to better understand the role of space-time heterogeneity. To address this issue, we present some results from ongoing work that looks at the impact of fuel treatment of forest ecohydrology. This work stem from a collaboration between an ecohydrologic modeling team, social-scientists, a visual artist and compute graphics students. We use a coupled model, validated with field measurements, to show why spatial heterogeneity matters for understanding the impact of fuel treatments on the water cycle for the Sierra

  15. A novel tropopause-related climatology of ozone profiles

    NARCIS (Netherlands)

    Sofieva, V.F.; Tamminen, J.; Kyrola, E.; Mielonen, T.; Veefkind, J.P.; Hassler, B.; Bodeker, G.E.

    2014-01-01

    A new ozone climatology, based on ozonesonde and satellite measurements, spanning the altitude region between the earth's surface and ~60 km is presented (TpO3 climatology). This climatology is novel in that the ozone profiles are categorized according to calendar month, latitude and local

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

    Science.gov (United States)

    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.

  17. Land surface Verification Toolkit (LVT) - a generalized framework for land surface model evaluation

    Science.gov (United States)

    Kumar, S. V.; Peters-Lidard, C. D.; Santanello, J.; Harrison, K.; Liu, Y.; Shaw, M.

    2012-06-01

    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 supports hydrological data products from non-LIS environments as well. 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. Characterization of Land Surfaces with Satellite-borne Sensor

    Science.gov (United States)

    Qiao, Y.

    Hot groundwater is a kind of valuable natural resources to be explored utilized. Shanxi Province, located in the eastern Loess Plateau of China, is rich in geothermal resources, most of which was found in irrigation well drilling or geological survey. Basic study is weak. Now new developed Remote Sensing technique provides geothermal study with an advanced way. Air-RS information of thermal infrared and dada from thermal channel of Meteorological Landset AVHRR has been used widely. A thermal infrared channel (TM6) was installed in the U.S. second Landset, Its resolving power of space is as high as 120m, 10 times more than one of AVHRR. A Landset earth recourses launched by China and Brazil (CBERS-1) in 1999, including a spectrum of thermal infrared. It is paid a great interested and attention to survey geothermal resources using thermal infrared. This article is a brief introduction of finding hot groundwater with on the bases of differences of thermal radiation of objects reflected by thermal infrared in the Landset, and treated with HIS colors changes. This study provides an advanced way widely used to exploit hot groundwater and to promote the development of tourism and geothermal medical in China.

  19. Land surface water cycles observed with satellite sensors

    Science.gov (United States)

    Nghiem, Son V.; Njoku, E. G.; Brakenridge, G. R.; Kim, Y.

    2005-01-01

    Acceleration of the global water cycle may lead to increased global precipitation, faster evaporation and a consequent exacerbation of hydrologic extreme. In the U.S. national assessment of the potential consequences of climate variability and change, two GCMs (CGCM1 and HadCM2) show a large increase in precipitation in the future over the southwestern U.S. particularly during winter (Felzer and Heard, 1999). Increased precipitation potentially has important impacts on agricultural and water use in the southeast U.S. (Hatch et al., 1999) and in the central Great Plains (Nielsen, 1997). A hurricane model predicts a 40% precipitation increase for severe hurricanes affecting southeastern Florida, which provokes substantially greater flooding that could negate most of the benefits of present water-management practices in this basin (Gutowski et al., 1994). Thus, it is important to observe the hydroclimate on a continuous longterm basis to address the question of increased precipitation in the enhanced water cycle.

  20. Mapping the global land surface using 1 km AVHRR data

    Science.gov (United States)

    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.

  1. Improving Land Surface Temperature Retrievals over Mountainous Regions

    Directory of Open Access Journals (Sweden)

    Virgílio A. Bento

    2017-01-01

    Full Text Available Algorithms for Land Surface Temperature (LST retrieval from infrared measurements are usually sensitive to the amount of water vapor present in the atmosphere. The Satellite Application Facilities on Climate Monitoring and Land Surface Analysis (CM SAF and LSA SAF are currently compiling a 25 year LST Climate data record (CDR, which uses water vapor information from ERA-Int reanalysis. However, its relatively coarse spatial resolution may lead to systematic errors in the humidity profiles with implications in LST, particularly over mountainous areas. The present study compares LST estimated with three different retrieval algorithms: a radiative transfer-based physical mono-window (PMW, a statistical mono-window (SMW, and a generalized split-windows (GSW. The algorithms were tested over the Alpine region using ERA-Int reanalysis data and relied on the finer spatial scale Consortium for Small-Scale Modelling (COSMO model data as a reference. Two methods were developed to correct ERA-Int water vapor misestimation: (1 an exponential parametrization of total precipitable water (TPW appropriate for SMW/GSW; and (2 a level reduction method to be used in PMW. When ERA-Int TPW was used, the algorithm missed the right TPW class in 87% of the cases. When the exponential parametrization was used, the missing class rate decreased to 9%, and when the level reduction method was applied, the LST corrections went up to 1.7 K over the study region. Overall, the correction for pixel orography in TPW leads to corrections in LST estimations, which are relevant to ensure that long-term LST records meet climate requirements, particularly over mountainous regions.

  2. Large-scale Validation of AMIP II Land-surface Simulations: Preliminary Results for Ten Models

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, T J; Henderson-Sellers, A; Irannejad, P; McGuffie, K; Zhang, H

    2005-12-01

    This report summarizes initial findings of a large-scale validation of the land-surface simulations of ten atmospheric general circulation models that are entries in phase II of the Atmospheric Model Intercomparison Project (AMIP II). This validation is conducted by AMIP Diagnostic Subproject 12 on Land-surface Processes and Parameterizations, which is focusing on putative relationships between the continental climate simulations and the associated models' land-surface schemes. The selected models typify the diversity of representations of land-surface climate that are currently implemented by the global modeling community. The current dearth of global-scale terrestrial observations makes exacting validation of AMIP II continental simulations impractical. Thus, selected land-surface processes of the models are compared with several alternative validation data sets, which include merged in-situ/satellite products, climate reanalyses, and off-line simulations of land-surface schemes that are driven by observed forcings. The aggregated spatio-temporal differences between each simulated process and a chosen reference data set then are quantified by means of root-mean-square error statistics; the differences among alternative validation data sets are similarly quantified as an estimate of the current observational uncertainty in the selected land-surface process. Examples of these metrics are displayed for land-surface air temperature, precipitation, and the latent and sensible heat fluxes. It is found that the simulations of surface air temperature, when aggregated over all land and seasons, agree most closely with the chosen reference data, while the simulations of precipitation agree least. In the latter case, there also is considerable inter-model scatter in the error statistics, with the reanalyses estimates of precipitation resembling the AMIP II simulations more than to the chosen reference data. In aggregate, the simulations of land-surface latent and

  3. Land-surface initialisation improves seasonal climate prediction skill for maize yield forecast.

    Science.gov (United States)

    Ceglar, Andrej; Toreti, Andrea; Prodhomme, Chloe; Zampieri, Matteo; Turco, Marco; Doblas-Reyes, Francisco J

    2018-01-22

    Seasonal crop yield forecasting represents an important source of information to maintain market stability, minimise socio-economic impacts of crop losses and guarantee humanitarian food assistance, while it fosters the use of climate information favouring adaptation strategies. As climate variability and extremes have significant influence on agricultural production, the early prediction of severe weather events and unfavourable conditions can contribute to the mitigation of adverse effects. Seasonal climate forecasts provide additional value for agricultural applications in several regions of the world. However, they currently play a very limited role in supporting agricultural decisions in Europe, mainly due to the poor skill of relevant surface variables. Here we show how a combined stress index (CSI), considering both drought and heat stress in summer, can predict maize yield in Europe and how land-surface initialised seasonal climate forecasts can be used to predict it. The CSI explains on average nearly 53% of the inter-annual maize yield variability under observed climate conditions and shows how concurrent heat stress and drought events have influenced recent yield anomalies. Seasonal climate forecast initialised with realistic land-surface achieves better (and marginally useful) skill in predicting the CSI than with climatological land-surface initialisation in south-eastern Europe, part of central Europe, France and Italy.

  4. Experimental use of Land Surface Models in the La Plata Basin

    Science.gov (United States)

    Goncalves, L.; de Mattos, J. Z.; Sapucci, L. F.; Herdies, D. L.; Berbery, E. H.

    2009-12-01

    Soil moisture is a key variable that controls the partitioning between sensible and latent heat flux, and under favorable conditions, it can modulate precipitation. The overlying boundary layer can be affected by soil moisture anomalies when persisting for an enough period of time. Several studies have shown the influence of surface processes in the South American atmospheric circulation and precipitation patterns. However the absence of a comprehensive observation network over that region represents a disadvantage for determining and quantifying memory and coupling between the land surface and the atmosphere. The La Plata Basin (LPB) in southeastern South America is recognized as an area of great importance for the economic and social development of several countries. Vast areas of this basin have experienced changes in land cover conditions due to the expansion of the agriculture (replacing natural vegetation), but also due to changes in crop types. This work presents results from an ensemble of four land surface models (Noah, CLM, MOSAIC and SiB2) used for climatic characterization of the past 30 years of soil moisture and temperature over the LPB. The Modern Era Retrospective-Analysis for Research and Applications (MERRA), from NASA’s Global Modeling and Assimilation Office (GMAO) was downscaled to be used to force the land surface models at 10Km, 3-hourly resolutions. Two sets of runs were made for this study: first, the LSMs were forced using reanalysis data to characterize the climatological states at coarse resolution, and second, the models were run using South American LDAS forcing fields from 2000 until present at higher resolution. The resulting spread among the different models was used as a measure of uncertainty in the initial states. In particular, the surface states derived from the Noah model were rescaled and used as initial conditions for atmospheric model simulations using the coupled ETA/Noah models. The control run was performed using

  5. Internal Physical Features of a Land Surface Model Employing a Tangent Linear Model

    Science.gov (United States)

    Yang, Runhua; Cohn, Stephen E.; daSilva, Arlindo; Joiner, Joanna; Houser, Paul R.

    1997-01-01

    variables are predicted imperfectly due to inherent uncertainties in the modeling process, our study suggests how satellite observations can be combined with the model, through land surface data assimilation, to improve their prediction.

  6. A new MRI land surface model HAL

    Science.gov (United States)

    Hosaka, M.

    2011-12-01

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

  7. ENVISAT Land Surface Processes. Phase 2

    Science.gov (United States)

    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

  8. The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements

    KAUST Repository

    Niu, Guo-Yue

    2011-06-24

    This first paper of the two-part series describes the objectives of the community efforts in improving the Noah land surface model (LSM), documents, through mathematical formulations, the augmented conceptual realism in biophysical and hydrological processes, and introduces a framework for multiple options to parameterize selected processes (Noah-MP). The Noah-MP\\'s performance is evaluated at various local sites using high temporal frequency data sets, and results show the advantages of using multiple optional schemes to interpret the differences in modeling simulations. The second paper focuses on ensemble evaluations with long-term regional (basin) and global scale data sets. The enhanced conceptual realism includes (1) the vegetation canopy energy balance, (2) the layered snowpack, (3) frozen soil and infiltration, (4) soil moisture-groundwater interaction and related runoff production, and (5) vegetation phenology. Sample local-scale validations are conducted over the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) site, the W3 catchment of Sleepers River, Vermont, and a French snow observation site. Noah-MP shows apparent improvements in reproducing surface fluxes, skin temperature over dry periods, snow water equivalent (SWE), snow depth, and runoff over Noah LSM version 3.0. Noah-MP improves the SWE simulations due to more accurate simulations of the diurnal variations of the snow skin temperature, which is critical for computing available energy for melting. Noah-MP also improves the simulation of runoff peaks and timing by introducing a more permeable frozen soil and more accurate simulation of snowmelt. We also demonstrate that Noah-MP is an effective research tool by which modeling results for a given process can be interpreted through multiple optional parameterization schemes in the same model framework. Copyright © 2011 by the American Geophysical Union.

  9. Estimating surface turbulent heat fluxes from land surface temperature and soil moisture using the particle batch smoother

    Science.gov (United States)

    Lu, Yang; Dong, Jianzhi; Steele-Dunne, Susan; van de Giesen, Nick

    2016-04-01

    This study is focused on estimating surface sensible and latent heat fluxes from land surface temperature (LST) time series and soil moisture observations. Surface turbulent heat fluxes interact with the overlying atmosphere and play a crucial role in meteorology, hydrology and other climate-related fields, but in-situ measurements are costly and difficult. It has been demonstrated that the time series of LST contains information of energy partitioning and that surface turbulent heat fluxes can be determined from assimilation of LST. These studies are mainly based on two assumptions: (1) a monthly value of bulk heat transfer coefficient under neutral conditions (CHN) which scales the sum of the fluxes, and (2) an evaporation fraction (EF) which stays constant during the near-peak hours of the day. Previous studies have applied variational and ensemble approaches to this problem. Here the newly developed particle batch smoother (PBS) algorithm is adopted to test its capability in this application. The PBS can be seen as an extension of the standard particle filter (PF) in which the states and parameters within a fix window are updated in a batch using all observations in the window. The aim of this study is two-fold. First, the PBS is used to assimilate only LST time series into the force-restore model to estimate fluxes. Second, a simple soil water transfer scheme is introduced to evaluate the benefit of assimilating soil moisture observations simultaneously. The experiments are implemented using the First ISLSCP (International Satellite Land Surface Climatology Project) (FIFE) data. It is shown that the restored LST time series using PBS agrees very well with observations, and that assimilating LST significantly improved the flux estimation at both daily and half-hourly time scales. When soil moisture is introduced to further constrain EF, the accuracy of estimated EF is greatly improved. Furthermore, the RMSEs of retrieved fluxes are effectively reduced at both

  10. Derivation of Land Surface Albedo at High Resolution by Combining HJ-1A/B Reflectance Observations with MODIS BRDF Products

    Directory of Open Access Journals (Sweden)

    Bo Gao

    2014-09-01

    Full Text Available Land surface albedo is an essential parameter for monitoring global/regional climate and land surface energy balance. Although many studies have been conducted on global or regional land surface albedo using various remote sensing data over the past few decades, land surface albedo product with a high spatio–temporal resolution is currently very scarce. This paper proposes a method for deriving land surface albedo with a high spatio–temporal resolution (space: 30 m and time: 2–4 days. The proposed method works by combining the land surface reflectance data at 30 m spatial resolution obtained from the charge-coupled devices in the Huanjing-1A and -1B (HJ-1A/B satellites with the Moderate Resolution Imaging Spectroradiometer (MODIS land surface bidirectional reflectance distribution function (BRDF parameters product (MCD43A1, which is at a spatial resolution of 500 m. First, the land surface BRDF parameters for HJ-1A/B land surface reflectance with a spatial–temporal resolutions of 30 m and 2–4 day are calculated on the basis of the prior knowledge from the MODIS BRDF product; then, the calculated high resolution BRDF parameters are integrated over the illuminating/viewing hemisphere to produce the white- and black-sky albedos at 30 m resolution. These results form the basis for the final land surface albedo derivation by accounting for the proportion of direct and diffuse solar radiation arriving at the ground. The albedo retrieved by this novel method is compared with MODIS land surface albedo products, as well as with ground measurements. The results show that the derived land surface albedo during the growing season of 2012 generally achieved a mean absolute accuracy of ±0.044, and a root mean square error of 0.039, confirming the effectiveness of the newly proposed method.

  11. Evaluation of satellite-retrieved extreme precipitation using gauge observations

    Science.gov (United States)

    Lockhoff, M.; Zolina, O.; Simmer, C.; Schulz, J.

    2012-04-01

    Precipitation extremes have already been intensively studied employing rain gauge datasets. Their main advantage is that they represent a direct measurement with a relatively high temporal coverage. Their main limitation however is their poor spatial coverage and thus a low representativeness in many parts of the world. In contrast, satellites can provide global coverage and there are meanwhile data sets available that are on one hand long enough to be used for extreme value analysis and that have on the other hand the necessary spatial and temporal resolution to capture extremes. However, satellite observations provide only an indirect mean to determine precipitation and there are many potential observational and methodological weaknesses in particular over land surfaces that may constitute doubts concerning their usability for the analysis of precipitation extremes. By comparing basic climatological metrics of precipitation (totals, intensities, number of wet days) as well as respective characteristics of PDFs, absolute and relative extremes of satellite and observational data this paper aims at assessing to which extent satellite products are suitable for analysing extreme precipitation events. In a first step the assessment focuses on Europe taking into consideration various satellite products available, e.g. data sets provided by the Global Precipitation Climatology Project (GPCP). First results indicate that satellite-based estimates do not only represent the monthly averaged precipitation very similar to rain gauge estimates but they also capture the day-to-day occurrence fairly well. Larger differences can be found though when looking at the corresponding intensities.

  12. [An operational remote sensing algorithm of land surface evapotranspiration based on NOAA PAL dataset].

    Science.gov (United States)

    Hou, Ying-Yu; He, Yan-Bo; Wang, Jian-Lin; Tian, Guo-Liang

    2009-10-01

    Based on the time series 10-day composite NOAA Pathfinder AVHRR Land (PAL) dataset (8 km x 8 km), and by using land surface energy balance equation and "VI-Ts" (vegetation index-land surface temperature) method, a new algorithm of land surface evapotranspiration (ET) was constructed. This new algorithm did not need the support from meteorological observation data, and all of its parameters and variables were directly inversed or derived from remote sensing data. A widely accepted ET model of remote sensing, i. e., SEBS model, was chosen to validate the new algorithm. The validation test showed that both the ET and its seasonal variation trend estimated by SEBS model and our new algorithm accorded well, suggesting that the ET estimated from the new algorithm was reliable, being able to reflect the actual land surface ET. The new ET algorithm of remote sensing was practical and operational, which offered a new approach to study the spatiotemporal variation of ET in continental scale and global scale based on the long-term time series satellite remote sensing images.

  13. Characterizing Land Surface Anisotropic Reflectance over Rugged Terrain: A Review of Concepts and Recent Developments

    Directory of Open Access Journals (Sweden)

    Jianguang Wen

    2018-02-01

    Full Text Available Rugged terrain, including mountains, hills, and some high lands are typical land surfaces around the world. As a physical parameter for characterizing the anisotropic reflectance of the land surface, the importance of the bidirectional reflectance distribution function (BRDF has been gradually recognized in the remote sensing community, and great efforts have been dedicated to build BRDF models over various terrain types. However, on rugged terrain, the topography intensely affects the shape and magnitude of the BRDF and creates challenges in modeling the BRDF. In this paper, after a brief introduction of the theoretical background of the BRDF over rugged terrain, the status of estimating land surface BRDF properties over rugged terrain is comprehensively reviewed from a historical perspective and summarized in two categories: BRDFs describing solo slopes and those describing composite slopes. The discussion focuses on land surface reflectance retrieval over mountainous areas, the difference in solo slope and composite slope BRDF models, and suggested future research to improve the accuracy of BRDFs derived with remote sensing satellites.

  14. Climatology of the oceanography in the northern South China Sea Shelf-sea (NoSoCS) and adjacent waters: Observations from satellite remote sensing

    Science.gov (United States)

    Pan, X.; Wong, G. T.; Tai, J.; Ho, T.

    2013-12-01

    By using the observations from multiple satellite sensors, the climatology of the oceanography, including the surface wind vector, sea surface temperature (SST), surface chlorophyll a concentration (Chl_a), and vertically integrated net primary production (PPeu), in the northern South China Sea Shelf-sea (NoSoCS) and adjacent waters is evaluated. Regional and sub-regional mechanisms in driving the coastal processes, which influence the spatial and temporal distributional patterns in water component, are assessed. Seasonal vertical convective mixing by wind and surface heating/cooling is the primary force in driving the annual changes in SST and Chl_a in the open South China Sea (SCS), in which highly negative correlation coefficients between Chl_a and SST and moderately positive correlation coefficients between Chl_a and wind speed are found. Together, the seasonal variations in SST and wind speed account for about 80% of the seasonal variation in Chl_a. In the NoSoCS as a whole, however, the contribution is reduced to about 40%, primarily due to the effect of the Pearl River plume. A tongue of water extending eastward from the mouth of the River into the middle shelf with positive correlation coefficients between Chl_a and SST and around zero or slightly negative correlation coefficients between Chl_a and wind is the most striking feature in the NoSoCS. The westward and eastward propagations of the Pearl River plume are both very small during the northeast monsoonal season, driven primarily by the Coriolis effect. The abrupt increase in the areal coverage of the River plume, which is much more pronounced in the eastward propagation, between June and August can be attributed to the prevailing southwest monsoon as well as the annual peak of the river flow. Coastal upwelling is another sub-regional phenomenon in the NoSoCS. The upwelling at the shelf edge off the Taiwan Bank may be characterized by its elevated Chl_a. Its areal coverage and average Chl_a do not vary

  15. Daily monitoring of the land surface of the Earth

    Science.gov (United States)

    Mascaro, J.

    2016-12-01

    Planet is an integrated aerospace and data analytics company that operates the largest fleet of Earth-imaging satellites. With more than 140 cube-sats successfully launched to date, Planet is now collecting approximately 10 million square kilometers of imagery per day (3-5m per pixel, in red, green, blue and near infrared spectral bands). By early 2017, Planet's constellation will image the entire land surface of the Earth on a daily basis. Due to investments in cloud storage and computing, approximately 75% of imagery collected is available to Planet's partners within 24 hours of capture through an Application Program Interface. This unique dataset has enormous applications for monitoring the status of Earth's natural ecosystems, as well as human settlements and agricultural welfare. Through our Ambassadors Program, Planet has made data available for researchers in areas as disparate as human rights monitoring in refugee camps, to assessments of the impact of hydroelectric installations, to tracking illegal gold mining in Amazon forests, to assessing the status of the cryosphere. Here, we share early results from Planet's research partner network, including enhanced spatial and temporal resolution of NDVI data for agricultural health in Saudi Arabia, computation of rates of illegal deforestation in Southern Peru, estimates of tropical forest carbon stocks based on data integration with active sensors, and estimates of glacial flow rates. We synthesize the potentially enormous research and scientific value of Planet's persistent monitoring capability, and discuss methods by which the data will be disseminated into the scientific community.

  16. The CEOS-Land Surface Imaging Constellation Portal for GEOSS: A resource for land surface imaging system information and data access

    Science.gov (United States)

    Holm, Thomas; Gallo, Kevin P.; Bailey, Bryan

    2010-01-01

    The Committee on Earth Observation Satellites is an international group that coordinates civil space-borne observations of the Earth, and provides the space component of the Global Earth Observing System of Systems (GEOSS). The CEOS Virtual Constellations concept was implemented in an effort to engage and coordinate disparate Earth observing programs of CEOS member agencies and ultimately facilitate their contribution in supplying the space-based observations required to satisfy the requirements of the GEOSS. The CEOS initially established Study Teams for four prototype constellations that included precipitation, land surface imaging, ocean surface topography, and atmospheric composition. The basic mission of the Land Surface Imaging (LSI) Constellation [1] is to promote the efficient, effective, and comprehensive collection, distribution, and application of space-acquired image data of the global land surface, especially to meet societal needs of the global population, such as those addressed by the nine Group on Earth Observations (GEO) Societal Benefit Areas (SBAs) of agriculture, biodiversity, climate, disasters, ecosystems, energy, health, water, and weather. The LSI Constellation Portal is the result of an effort to address important goals within the LSI Constellation mission and provide resources to assist in planning for future space missions that might further contribute to meeting those goals.

  17. Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balances

    Science.gov (United States)

    Tang, G.; Bartlein, P. J.

    2012-08-01

    Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM) simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i) modify a DGVM for simulating land surface water balances; (ii) evaluate the modified model in simulating actual evapotranspiration (ET), soil moisture, and surface runoff at regional or watershed scales; and (iii) gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH) model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ) DGVM. To evaluate the model we ran LH using historical (1981-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981-2006 (R2 > 0.46, p 0.52). The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences day method for snowmelt computation, the addition of the solar radiation effect on snowmelt enabled LH to better simulate monthly stream flow in winter and early spring for rivers located at mid-to-high latitudes. In addition, LH

  18. Enhancing the representation of subgrid land surface characteristics in land surface models

    Directory of Open Access Journals (Sweden)

    Y. Ke

    2013-09-01

    Full Text Available Land surface heterogeneity has long been recognized as important to represent in the land surface models. In most existing land surface models, the spatial variability of surface cover is represented as subgrid composition of multiple surface cover types, although subgrid topography also has major controls on surface processes. In this study, we developed a new subgrid classification method (SGC that accounts for variability of both topography and vegetation cover. Each model grid cell was represented with a variable number of elevation classes and each elevation class was further described by a variable number of vegetation types optimized for each model grid given a predetermined total number of land response units (LRUs. The subgrid structure of the Community Land Model (CLM was used to illustrate the newly developed method in this study. Although the new method increases the computational burden in the model simulation compared to the CLM subgrid vegetation representation, it greatly reduced the variations of elevation within each subgrid class and is able to explain at least 80% of the total subgrid plant functional types (PFTs. 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 (SGC1: M elevation bands–N PFTs method; SGC2: N PFTs–M elevation bands method. Implemented at five model resolutions (0.1°, 0.25°, 0.5°, 1.0°and 2.0° with three maximum-allowed total number of LRUs (i.e., NLRU of 24, 18 and 12 over North America (NA, the new method yielded more computationally efficient subgrid representation compared to SGC1 and SGC2, particularly at coarser model resolutions and moderate computational intensity (NLRU = 18. It also explained the most PFTs and elevation variability that is more homogeneously distributed spatially. The SGC method will be implemented in CLM over the NA continent to assess its impacts on

  19. Land surface phenology of Northeast China during 2000-2015: temporal changes and relationships with climate changes.

    Science.gov (United States)

    Zhang, Yue; Li, Lin; Wang, Hongbin; Zhang, Yao; Wang, Naijia; Chen, Junpeng

    2017-10-01

    As an important crop growing area, Northeast China (NEC) plays a vital role in China's food security, which has been severely affected by climate change in recent years. Vegetation phenology in this region is sensitive to climate change, and currently, the relationship between the phenology of NEC and climate change remains unclear. In this study, we used a satellite-derived normalized difference vegetation index (NDVI) to obtain the temporal patterns of the land surface phenology in NEC from 2000 to 2015 and validated the results using ground phenology observations. We then explored the relationships among land surface phenology, temperature, precipitation, and sunshine hours for relevant periods. Our results showed that the NEC experienced great phenological changes in terms of spatial heterogeneity during 2000-2015. The spatial patterns of land surface phenology mainly changed with altitude and land cover type. In most regions of NEC, the start date of land surface phenology had advanced by approximately 1.0 days year -1 , and the length of land surface phenology had been prolonged by approximately 1.0 days year -1 except for the needle-leaf and cropland areas, due to the warm conditions. We found that a distinct inter-annual variation in land surface phenology related to climate variables, even if some areas presented non-significant trends. Land surface phenology was coupled with climate variables and distinct responses at different combinations of temperature, precipitation, sunshine hours, altitude, and anthropogenic influence. These findings suggest that remote sensing and our phenology extracting methods hold great potential for helping to understand how land surface phenology is sensitive to global climate change.

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Science.gov (United States)

    Santanello, J. A.; Kumar, S.; Peters-Lidard, C. D.; Harrison, K. W.; Zhou, S.

    2012-12-01

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

  2. Effect of water table dynamics on land surface hydrologic memory

    Science.gov (United States)

    Lo, Min-Hui; Famiglietti, James S.

    2010-11-01

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

  3. Derivation of Land Surface Temperature for Landsat-8 TIRS Using a Split Window Algorithm

    Directory of Open Access Journals (Sweden)

    Offer Rozenstein

    2014-03-01

    Full Text Available Land surface temperature (LST is one of the most important variables measured by satellite remote sensing. Public domain data are available from the newly operational Landsat-8 Thermal Infrared Sensor (TIRS. This paper presents an adjustment of the split window algorithm (SWA for TIRS that uses atmospheric transmittance and land surface emissivity (LSE as inputs. Various alternatives for estimating these SWA inputs are reviewed, and a sensitivity analysis of the SWA to misestimating the input parameters is performed. The accuracy of the current development was assessed using simulated Modtran data. The root mean square error (RMSE of the simulated LST was calculated as 0.93 °C. This SWA development is leading to progress in the determination of LST by Landsat-8 TIRS.

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

    Science.gov (United States)

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

    2017-12-01

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

  5. Satellites

    International Nuclear Information System (INIS)

    Burns, J.A.; Matthews, M.S.

    1986-01-01

    The present work is based on a conference: Natural Satellites, Colloquium 77 of the IAU, held at Cornell University from July 5 to 9, 1983. Attention is given to the background and origins of satellites, protosatellite swarms, the tectonics of icy satellites, the physical characteristics of satellite surfaces, and the interactions of planetary magnetospheres with icy satellite surfaces. Other topics include the surface composition of natural satellites, the cratering of planetary satellites, the moon, Io, and Europa. Consideration is also given to Ganymede and Callisto, the satellites of Saturn, small satellites, satellites of Uranus and Neptune, and the Pluto-Charon system

  6. estimation of land surface temperature of kaduna metropolis, nigeria

    African Journals Online (AJOL)

    Zaharaddeen et. al

    Land surface temperature can provide noteworthy information about the surface ... modelling the surface energy balance (Kalma, et al., 2008; ... Landsat, in addition some of the Landsat data have cloud cover and ..... The Impact Of Urban.

  7. Impact of high resolution land surface initialization in Indian summer ...

    Indian Academy of Sciences (India)

    The direct impact of high resolution land surface initialization on the forecast bias in a regional climate model in recent years ... surface initialization using a regional climate model. ...... ization of the snow field in a cloud model; J. Clim. Appl.

  8. ENHANCED MODELING OF REMOTELY SENSED ANNUAL LAND SURFACE TEMPERATURE CYCLE

    Directory of Open Access Journals (Sweden)

    Z. Zou

    2017-09-01

    Full Text Available Satellite thermal remote sensing provides access to acquire large-scale Land surface temperature (LST data, but also generates missing and abnormal values resulting from non-clear-sky conditions. Given this limitation, Annual Temperature Cycle (ATC model was employed to reconstruct the continuous daily LST data over a year. The original model ATCO used harmonic functions, but the dramatic changes of the real LST caused by the weather changes remained unclear due to the smooth sine curve. Using Aqua/MODIS LST products, NDVI and meteorological data, we proposed enhanced model ATCE based on ATCO to describe the fluctuation and compared their performances for the Yangtze River Delta region of China. The results demonstrated that, the overall root mean square errors (RMSEs of the ATCE was lower than ATCO, and the improved accuracy of daytime was better than that of night, with the errors decreased by 0.64 K and 0.36 K, respectively. The improvements of accuracies varied with different land cover types: the forest, grassland and built-up areas improved larger than water. And the spatial heterogeneity was observed for performance of ATC model: the RMSEs of built-up area, forest and grassland were around 3.0 K in the daytime, while the water attained 2.27 K; at night, the accuracies of all types significantly increased to similar RMSEs level about 2 K. By comparing the differences between LSTs simulated by two models in different seasons, it was found that the differences were smaller in the spring and autumn, while larger in the summer and winter.

  9. A Multisensor Approach to Global Retrievals of Land Surface Albedo

    Directory of Open Access Journals (Sweden)

    Aku Riihelä

    2018-05-01

    Full Text Available Satellite-based retrievals offer the most cost-effective way to comprehensively map the surface albedo of the Earth, a key variable for understanding the dynamics of radiative energy interactions in the atmosphere-surface system. Surface albedo retrievals have commonly been designed separately for each different spaceborne optical imager. Here, we introduce a novel type of processing framework that combines the data from two polar-orbiting optical imager families, the Advanced Very High-Resolution Radiometer (AVHRR and Moderate Resolution Imaging Spectroradiometer (MODIS. The goal of the paper is to demonstrate that multisensor albedo retrievals can provide a significant reduction in the sampling time required for a robust and comprehensive surface albedo retrieval, without a major degradation in retrieval accuracy, as compared to state-of-the-art single-sensor retrievals. We evaluated the multisensor retrievals against reference in situ albedo measurements and compare them with existing datasets. The results show that global land surface albedo retrievals with a sampling period of 10 days can offer near-complete spatial coverage, with a retrieval bias mostly comparable to existing single sensor datasets, except for bright surfaces (deserts and snow where the retrieval framework shows degraded performance because of atmospheric correction design compromises. A level difference is found between the single sensor datasets and the demonstrator developed here, pointing towards a need for further work in the atmospheric correction, particularly over bright surfaces, and inter-sensor radiance homogenization. The introduced framework is expandable to include other sensors in the future.

  10. New dynamic NNORSY ozone profile climatology

    Science.gov (United States)

    Kaifel, A. K.; Felder, M.; Declercq, C.; Lambert, J.-C.

    2012-01-01

    Climatological ozone profile data are widely used as a-priori information for total ozone using DOAS type retrievals as well as for ozone profile retrieval using optimal estimation, for data assimilation or evaluation of 3-D chemistry-transport models and a lot of other applications in atmospheric sciences and remote sensing. For most applications it is important that the climatology represents not only long term mean values but also the links between ozone and dynamic input parameters. These dynamic input parameters should be easily accessible from auxiliary datasets or easily measureable, and obviously should have a high correlation with ozone. For ozone profile these parameters are mainly total ozone column and temperature profile data. This was the outcome of a user consultation carried out in the framework of developing a new, dynamic ozone profile climatology. The new ozone profile climatology is based on the Neural Network Ozone Retrieval System (NNORSY) widely used for ozone profile retrieval from UV and IR satellite sounder data. NNORSY allows implicit modelling of any non-linear correspondence between input parameters (predictors) and ozone profile target vector. This paper presents the approach, setup and validation of a new family of ozone profile climatologies with static as well as dynamic input parameters (total ozone and temperature profile). The neural network training relies on ozone profile measurement data of well known quality provided by ground based (ozonesondes) and satellite based (SAGE II, HALOE, and POAM-III) measurements over the years 1995-2007. In total, four different combinations (modes) for input parameters (date, geolocation, total ozone column and temperature profile) are available. The geophysical validation spans from pole to pole using independent ozonesonde, lidar and satellite data (ACE-FTS, AURA-MLS) for individual and time series comparisons as well as for analysing the vertical and meridian structure of different modes of

  11. The impact of implementing the bare essentials of surface transfer land surface scheme into the BMRC GCM

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Z.L. [Univ. of Arizona, Tucson, AZ (United States); Pitman, A.J. [Macquarie Univ., Sydney (Australia); McAvaney, B. [Bureau of Meterology Research Centre, Melbourne (Australia)] [and others

    1995-07-01

    This study describes the first order impacts of incorporating a complex land-surface scheme, the bare essentials of surface transfer (BEST), into the Australian Bureau of Meteorology Research Centre (BMRC) global atmospheric general circulation model (GCM). Land seasonal climatologies averaged over the last six years of integrations after equilibrium from the GCM with BEST and without BEST (the control) are compared. The modeled results are evaluated with comprehensive sources of data, including the layer-cloud climatologies project (ISCCP) data from 1983 to 1991 and the surface-observed global data of Warrent et al., a five-year climatology of surface albedo estimated from earth radiation budget experiment (ERBE) top-of-the-atmosphere (TOA) radiative fluxes, global grid point datasets of precipitation, and the climatological analyses of surface evaporation and albedo. Emphasis is placed on the surface evaluation of simulations of land-surface conditions such as surface roughness, surface albedo and the surface wetness factor, and on their effects on surface evaporation, precipitation, layer-cloud and surface temperature. The improvements due to the inclusion of BEST are: a realistic geographical distribution of surface roughness, a decrease in surface albedo over areas with seasonal snow cover, an an increase in surface albedo over snow-free land. The simulated reduction in surface evaporation due, in part, to the bio-physical control of vegetation, is also consistent with the previous studies. Since the control climate has a dry bias, the overall simulations from the GCM with BEST are degraded, except for significant improvements for the northern winter hemisphere because of the realistic vegetation-masking effects. The implications of our results for synergistic developments of other aspects of model parameterization schemes such as boundary layer dynamics, clouds, convection and rainfall are discussed. 82 refs., 9 figs., 3 tabs.

  12. Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balance

    Science.gov (United States)

    Tang, G.; Bartlein, P. J.

    2012-01-01

    Water balance models of simple structure are easier to grasp and more clearly connect cause and effect than models of complex structure. Such models are essential for studying large spatial scale land surface water balance in the context of climate and land cover change, both natural and anthropogenic. This study aims to (i) develop a large spatial scale water balance model by modifying a dynamic global vegetation model (DGVM), and (ii) test the model's performance in simulating actual evapotranspiration (ET), soil moisture and surface runoff for the coterminous United States (US). Toward these ends, we first introduced development of the "LPJ-Hydrology" (LH) model by incorporating satellite-based land covers into the Lund-Potsdam-Jena (LPJ) DGVM instead of dynamically simulating them. We then ran LH using historical (1982-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells. The simulated ET, soil moisture and surface runoff were compared to existing sets of observed or simulated data for the US. The results indicated that LH captures well the variation of monthly actual ET (R2 = 0.61, p 0.46, p 0.52) with observed values over the years 1982-2006, respectively. The modeled spatial patterns of annual ET and surface runoff are in accordance with previously published data. Compared to its predecessor, LH simulates better monthly stream flow in winter and early spring by incorporating effects of solar radiation on snowmelt. Overall, this study proves the feasibility of incorporating satellite-based land-covers into a DGVM for simulating large spatial scale land surface water balance. LH developed in this study should be a useful tool for studying effects of climate and land cover change on land surface hydrology at large spatial scales.

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

    Science.gov (United States)

    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.

  14. Global Land Surface Temperature From the Along-Track Scanning Radiometers

    Science.gov (United States)

    Ghent, D. J.; Corlett, G. K.; Göttsche, F.-M.; Remedios, J. J.

    2017-11-01

    The Leicester Along-Track Scanning Radiometer (ATSR) and Sea and Land Surface Temperature Radiometer (SLSTR) Processor for LAnd Surface Temperature (LASPLAST) provides global land surface temperature (LST) products from thermal infrared radiance data. In this paper, the state-of-the-art version of LASPLAST, as deployed in the GlobTemperature project, is described and applied to data from the Advanced Along-Track Scanning Radiometer (AATSR). The LASPLAST retrieval formulation for LST is a nadir-only, two-channel, split-window algorithm, based on biome classification, fractional vegetation, and across-track water vapor dependences. It incorporates globally robust retrieval coefficients derived using highly sampled atmosphere profiles. LASPLAST benefits from appropriate spatial resolution auxiliary information and a new probabilistic-based cloud flagging algorithm. For the first time for a satellite-derived LST product, pixel-level uncertainties characterized in terms of random, locally correlated, and systematic components are provided. The new GlobTemperature GT_ATS_2P Version 1.0 product has been validated for 1 year of AATSR data (2009) against in situ measurements acquired from "gold standard reference" stations: Gobabeb, Namibia, and Evora, Portugal; seven Surface Radiation Budget stations, and the Atmospheric Radiation Measurement station at Southern Great Plains. These data show average absolute biases for the GT_ATS_2P Version 1.0 product of 1.00 K in the daytime and 1.08 K in the nighttime. The improvements in data provenance including better accuracy, fully traceable retrieval coefficients, quantified uncertainty, and more detailed information in the new harmonized format of the GT_ATS_2P product will allow for more significant exploitation of the historical LST data record from the ATSRs and a valuable near-real-time service from the Sea and Land Surface Temperature Radiometers (SLSTRs).

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

    Science.gov (United States)

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

    2017-12-01

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

  16. Intercomparison of Satellite Derived Gravity Time Series with Inferred Gravity Time Series from TOPEX/POSEIDON Sea Surface Heights and Climatological Model Output

    Science.gov (United States)

    Cox, C.; Au, A.; Klosko, S.; Chao, B.; Smith, David E. (Technical Monitor)

    2001-01-01

    The upcoming GRACE mission promises to open a window on details of the global mass budget that will have remarkable clarity, but it will not directly answer the question of what the state of the Earth's mass budget is over the critical last quarter of the 20th century. To address that problem we must draw upon existing technologies such as SLR, DORIS, and GPS, and climate modeling runs in order to improve our understanding. Analysis of long-period geopotential changes based on SLR and DORIS tracking has shown that addition of post 1996 satellite tracking data has a significant impact on the recovered zonal rates and long-period tides. Interannual effects such as those causing the post 1996 anomalies must be better characterized before refined estimates of the decadal period changes in the geopotential can be derived from the historical database of satellite tracking. A possible cause of this anomaly is variations in ocean mass distribution, perhaps associated with the recent large El Nino/La Nina. In this study, a low-degree spherical harmonic gravity time series derived from satellite tracking is compared with a TOPEX/POSEIDON-derived sea surface height time series. Corrections for atmospheric mass effects, continental hydrology, snowfall accumulation, and ocean steric model predictions will be considered.

  17. The influence of land surface parameters on energy flux densities derived from remote sensing data

    Energy Technology Data Exchange (ETDEWEB)

    Tittebrand, A.; Schwiebus, A. [Inst. for Hydrology und Meteorology, TU Dresden (Germany); Berger, F.H. [Observatory Lindenberg, German Weather Service, Lindenberg (Germany)

    2005-04-01

    Knowledge of the vegetation properties surface reflectance, normalised difference vegetation index (NDVI) and leaf area index (LAI) are essential for the determination of the heat and water fluxes between terrestrial ecosystems and the atmosphere. Remote sensing data can be used to derive spatial estimates of the required surface properties. The determination of land surface parameters and their influence on radiant and energy flux densities is investigated with data of different remote sensing systems. Sensitivity studies show the importance of correctly derived land surface properties to estimate the key quantity of the hydrological cycle, the evapotranspiration (L.E), most exactly. In addition to variable parameters like LAI or NDVI there are also parameters which are can not be inferred from satellite data but needed for the Penman-Monteith approach. Fixed values are assumed for these variables because they have little influence on L.E. Data of Landsat-7 ETM+ and NOAA-16 AVHRR are used to show results in different spatial resolution. The satellite derived results are compared with ground truth data provided by the Observatory Lindenberg of the German Weather Service. (orig.)

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

    Science.gov (United States)

    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.

  19. An Estimation of Land Surface Temperatures from Landsat ETM+ ...

    African Journals Online (AJOL)

    Dr-Adeline

    Keywords: Urban growth, urban heat Island, land surface temperatures, ... climate from the resulting increase in LST can impact on the development of ... were not available (due to high cloud cover) in a given season, 2011 images ..... Sailor, D.J. and H. Fan, 2002: Modeling the diurnal variability of effective albedo for cities.

  20. Land surface and climate parameters and malaria features in Vietnam

    Science.gov (United States)

    Liou, Y. A.; Anh, N. K.

    2017-12-01

    Land surface parameters may affect local microclimate, which in turn alters the development of mosquito habitats and transmission risks (soil-vegetation-atmosphere-vector borne diseases). Forest malaria is a chromic issue in Southeast Asian countries, in particular, such as Vietnam (in 1991, approximate 2 million cases and 4,646 deaths were reported (https://sites.path.org)). Vietnam has lowlands, sub-tropical high humidity, and dense forests, resulting in wide-scale distribution and high biting rate of mosquitos in Vietnam, becoming a challenging and out of control scenario, especially in Vietnamese Central Highland region. It is known that Vietnam's economy mainly relies on agriculture and malaria is commonly associated with poverty. There is a strong demand to investigate the relationship between land surface parameters (land cover, soil moisture, land surface temperature, etc.) and climatic variables (precipitation, humidity, evapotranspiration, etc.) in association with malaria distribution. GIS and remote sensing have been proven their powerful potentials in supporting environmental and health studies. The objective of this study aims to analyze physical attributes of land surface and climate parameters and their links with malaria features. The outcomes are expected to illustrate how remotely sensed data has been utilized in geohealth applications, surveillance, and health risk mapping. In addition, a platform with promising possibilities of allowing disease early-warning systems with citizen participation will be proposed.

  1. Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balances

    Directory of Open Access Journals (Sweden)

    G. Tang

    2012-08-01

    Full Text Available Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i modify a DGVM for simulating land surface water balances; (ii evaluate the modified model in simulating actual evapotranspiration (ET, soil moisture, and surface runoff at regional or watershed scales; and (iii gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ DGVM. To evaluate the model we ran LH using historical (1981–2006 climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981–2006 (R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficient > 0.52. The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences < 15% with observed values for these rivers. Compared to a degree-day method for snowmelt computation, the addition of the solar radiation effect on snowmelt

  2. The Global Climatology Network Precipitation data

    International Nuclear Information System (INIS)

    Peterson, T.C.; Easterling, D.R.; Eischeid, J.K.

    1993-01-01

    Several years ago, in response to growing concern about global climate change, the US National Climatic Data Center and the Carbon Dioxide Information Analysis Center undertook an effort to create a baseline global land surface climate data set called the Global Historical Climatology Network (GHCN, Vose et al., 1992). GHCN was created by merging several large existing climate data sets into one data base. Fifteen separate data sets went into the creation of the GHCN version 1.0. GHCN version 1.0 was released in 1992. It has 7,533 precipitation stations, but the number of stations varies with time. A slight majority (55%) have records in excess of 50 years, and a significant proportion (13%) have records in excess of 100 years. The longest period of record for any given station is 291 years (1697--1987 for Kew, United Kingdom)

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

    Science.gov (United States)

    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.

  4. Object-based Dimensionality Reduction in Land Surface Phenology Classification

    Directory of Open Access Journals (Sweden)

    Brian E. Bunker

    2016-11-01

    Full Text Available Unsupervised classification or clustering of multi-decadal land surface phenology provides a spatio-temporal synopsis of natural and agricultural vegetation response to environmental variability and anthropogenic activities. Notwithstanding the detailed temporal information available in calibrated bi-monthly normalized difference vegetation index (NDVI and comparable time series, typical pre-classification workflows average a pixel’s bi-monthly index within the larger multi-decadal time series. While this process is one practical way to reduce the dimensionality of time series with many hundreds of image epochs, it effectively dampens temporal variation from both intra and inter-annual observations related to land surface phenology. Through a novel application of object-based segmentation aimed at spatial (not temporal dimensionality reduction, all 294 image epochs from a Moderate Resolution Imaging Spectroradiometer (MODIS bi-monthly NDVI time series covering the northern Fertile Crescent were retained (in homogenous landscape units as unsupervised classification inputs. Given the inherent challenges of in situ or manual image interpretation of land surface phenology classes, a cluster validation approach based on transformed divergence enabled comparison between traditional and novel techniques. Improved intra-annual contrast was clearly manifest in rain-fed agriculture and inter-annual trajectories showed increased cluster cohesion, reducing the overall number of classes identified in the Fertile Crescent study area from 24 to 10. Given careful segmentation parameters, this spatial dimensionality reduction technique augments the value of unsupervised learning to generate homogeneous land surface phenology units. By combining recent scalable computational approaches to image segmentation, future work can pursue new global land surface phenology products based on the high temporal resolution signatures of vegetation index time series.

  5. Preliminary Monthly Climatological Summaries

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary Local Climatological Data, recorded since 1970 on Weather Burean Form 1030 and then National Weather Service Form F-6. The preliminary climate data pages...

  6. Reference Climatological Stations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Reference Climatological Stations (RCS) network represents the first effort by NOAA to create and maintain a nationwide network of stations located only in areas...

  7. OW Levitus Climatology

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The dataset consists of global temperature and salinity climatologies with a spatial resolution of 1x1 degree, and consists of 19 levels (surface - 5000m). It was...

  8. Climatological Data National Summary

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The CDNS was published from 1950 - 1980. Monthly and annual editions contain summarized climatological information from the following publications: Local...

  9. Historical Climatology Series

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Historical Climatology Series (HCS) is a set of climate-related publications published by NOAA's National Climatic Data Center beginning in 1978. HCS is...

  10. Evaluation of Satellite-Based Precipitation Products from IMERG V04A and V03D, CMORPH and TMPA with Gauged Rainfall in Three Climatologic Zones in China

    Directory of Open Access Journals (Sweden)

    Guanghua Wei

    2017-12-01

    Full Text Available A critical evaluation of the newly released precipitation data set is very important for both the end users and data developers. Meanwhile, the evaluation may provide a benchmark for the product’s continued development and future improvement. To these ends, the four precipitation estimates including IMERG (the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement V04A, IMERG V03D, CMORPH (the Climate Prediction Center Morphing technique-CRT and TRMM (the Tropical Rainfall Measuring Mission 3B42 are systematically evaluated against the gauge precipitation estimates at multiple spatiotemporal scales from 1 June 2014 to 30 November 2015 over three different topographic and climatic watersheds in China. Meanwhile, the statistical methods are utilized to quantize the performance of the four satellite-based precipitation estimates. The results show that: (1 over the Tibetan Plateau cold region, among all products, IMERG V04A underestimates precipitation with the largest RB (−46.98% during the study period and the similar results are seen at the seasonal scale. However, IMERG V03D demonstrates the best performance according to RB (7.46%, RMSE (0.44 mm/day and RRMSE (28.37%. Except for in summer, TRMM 3B42 perform better than CMORPH according to RMSEs, RRMSEs and Rs; (2 within the semi-humid Huaihe River Basin, IMERG V04A has a slight advantage over the other three satellite-based precipitation products with the lowest RMSE (0.32 mm/day during the evaluation period and followed by IMERG V03D, TRMM 3B42 and CMORPH orderly; (3 over the arid/semi-arid Weihe River Basin, in comparison with the other three products, TRMM 3B42 demonstrates the best performance with the lowest RMSE (0.1 mm/day, RRMSE (8.44% and highest R (0.92 during the study period. Meanwhile, IMERG V03D perform better than IMERG V04A according all the statistical indicators; (4 in winter, IMERG V04A and IMERG V03D tend to underestimate the total precipitation

  11. Climatological determinants of woody cover in Africa.

    Science.gov (United States)

    Good, Stephen P; Caylor, Kelly K

    2011-03-22

    Determining the factors that influence the distribution of woody vegetation cover and resolving the sensitivity of woody vegetation cover to shifts in environmental forcing are critical steps necessary to predict continental-scale responses of dryland ecosystems to climate change. We use a 6-year satellite data record of fractional woody vegetation cover and an 11-year daily precipitation record to investigate the climatological controls on woody vegetation cover across the African continent. We find that-as opposed to a relationship with only mean annual rainfall-the upper limit of fractional woody vegetation cover is strongly influenced by both the quantity and intensity of rainfall events. Using a set of statistics derived from the seasonal distribution of rainfall, we show that areas with similar seasonal rainfall totals have higher fractional woody cover if the local rainfall climatology consists of frequent, less intense precipitation events. Based on these observations, we develop a generalized response surface between rainfall climatology and maximum woody vegetation cover across the African continent. The normalized local gradient of this response surface is used as an estimator of ecosystem vegetation sensitivity to climatological variation. A comparison between predicted climate sensitivity patterns and observed shifts in both rainfall and vegetation during 2009 reveals both the importance of rainfall climatology in governing how ecosystems respond to interannual fluctuations in climate and the utility of our framework as a means to forecast continental-scale patterns of vegetation shifts in response to future climate change.

  12. Characterization of land surface energy fluxes in a tropical lowland rice paddy

    Science.gov (United States)

    Chatterjee, Dibyendu; Tripathi, Rahul; Chatterjee, Sumanta; Debnath, Manish; Shahid, Mohammad; Bhattacharyya, Pratap; Swain, Chinmaya Kumar; Tripathy, Rojalin; Bhattacharya, Bimal K.; Nayak, Amaresh Kumar

    2018-04-01

    A field experiment was conducted in 2015 to study the land surface energy fluxes from tropical lowland rice paddy in eastern India with an objective to determine the mass, momentum, and energy exchange rates between rice paddies and the atmosphere. All the land surface energy fluxes were measured by eddy covariance (EC) system (make Campbell Scientific) in dry season (DS, 1-125 Julian days), dry fallow (DF, 126-181 Julian days), wet season (WS, 182-324 Julian days), and wet fallow (WF, 325-365 Julian days). The rice was cultivated in dry season (January-May) and wet season (July-November) in low wet lands and the ground is kept fallow during the remainder of the year. Results showed that albedo varied from 0.09 to 0.24 and showed positive value from morning 6:00 h until evening 18:00 h. Mean soil temperature (T g) was highest in DF, while the skin temperature (T s) was highest in WS. Average Bowen ratio (B) ranged from 0.21 to 0.64 and large variation in B was observed during the fallow periods as compared to the cropping seasons. The magnitude of aerodynamic, canopy, and climatological resistances increased with the progress of cropping season and their magnitudes decreased during the end of both cropping seasons and found minimum during the fallow periods. At a constant vapor pressure deficit (VPD) at 0.16, 0.18, 0.15, and 0.43 kPa, latent heat flux (LE) initially increased, but later it tended to level off with an increase in VPD. The actual evapotranspiration (ETa) during both the cropping seasons was higher than the fallow period. This study can be used as a source of default values for many land surface energy fluxes which are required in various meteorological or air-quality models for rice paddies. A larger imbalance of energy was observed during the wet season as the energy is stored and perhaps advected in the fresh water.

  13. HadISDH: an updateable land surface specific humidity product for climate monitoring

    Directory of Open Access Journals (Sweden)

    K. M. Willett

    2013-03-01

    Full Text Available HadISDH is a near-global land surface specific humidity monitoring product providing monthly means from 1973 onwards over large-scale grids. Presented herein to 2012, annual updates are anticipated. HadISDH is an update to the land component of HadCRUH, utilising the global high-resolution land surface station product HadISD as a basis. HadISD, in turn, uses an updated version of NOAA's Integrated Surface Database. Intensive automated quality control has been undertaken at the individual observation level, as part of HadISD processing. The data have been subsequently run through the pairwise homogenisation algorithm developed for NCDC's US Historical Climatology Network monthly temperature product. For the first time, uncertainty estimates are provided at the grid-box spatial scale and monthly timescale. HadISDH is in good agreement with existing land surface humidity products in periods of overlap, and with both land air and sea surface temperature estimates. Widespread moistening is shown over the 1973–2012 period. The largest moistening signals are over the tropics with drying over the subtropics, supporting other evidence of an intensified hydrological cycle over recent years. Moistening is detectable with high (95% confidence over large-scale averages for the globe, Northern Hemisphere and tropics, with trends of 0.089 (0.080 to 0.098 g kg−1 per decade, 0.086 (0.075 to 0.097 g kg−1 per decade and 0.133 (0.119 to 0.148 g kg−1 per decade, respectively. These changes are outside the uncertainty range for the large-scale average which is dominated by the spatial coverage component; station and grid-box sampling uncertainty is essentially negligible on large scales. A very small moistening (0.013 (−0.005 to 0.031 g kg−1 per decade is found in the Southern Hemisphere, but it is not significantly different from zero and uncertainty is large. When globally averaged, 1998 is the moistest year since monitoring began in 1973, closely

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

    Science.gov (United States)

    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

  15. Estimating Daily Global Evapotranspiration Using Penman–Monteith Equation and Remotely Sensed Land Surface Temperature

    Directory of Open Access Journals (Sweden)

    Roozbeh Raoufi

    2017-11-01

    Full Text Available Daily evapotranspiration (ET is modeled globally for the period 2000–2013 based on the Penman–Monteith equation with radiation and vapor pressures derived using remotely sensed Land Surface Temperature (LST from the MODerate resolution Imaging Spectroradiometer (MODIS on the Aqua and Terra satellites. The ET for a given land area is based on four surface conditions: wet/dry and vegetated/non-vegetated. For each, the ET resistance terms are based on land cover, leaf area index (LAI and literature values. The vegetated/non-vegetated fractions of the land surface are estimated using land cover, LAI, a simplified version of the Beer–Lambert law for describing light transition through vegetation and newly derived light extension coefficients for each MODIS land cover type. The wet/dry fractions of the land surface are nonlinear functions of LST derived humidity calibrated using in-situ ET measurements. Results are compared to in-situ measurements (average of the root mean squared errors and mean absolute errors for 39 sites are 0.81 mm day−1 and 0.59 mm day−1, respectively and the MODIS ET product, MOD16, (mean bias during 2001–2013 is −0.2 mm day−1. Although the mean global difference between MOD16 and ET estimates is only 0.2 mm day−1, local temperature derived vapor pressures are the likely contributor to differences, especially in energy and water limited regions. The intended application for the presented model is simulating ET based on long-term climate forecasts (e.g., using only minimum, maximum and mean daily or monthly temperatures.

  16. Water Balance in the Amazon Basin from a Land Surface Model Ensemble

    Science.gov (United States)

    Getirana, Augusto C. V.; Dutra, Emanuel; Guimberteau, Matthieu; Kam, Jonghun; Li, Hong-Yi; Decharme, Bertrand; Zhang, Zhengqiu; Ducharne, Agnes; Boone, Aaron; Balsamo, Gianpaolo; hide

    2014-01-01

    Despite recent advances in land surfacemodeling and remote sensing, estimates of the global water budget are still fairly uncertain. This study aims to evaluate the water budget of the Amazon basin based on several state-ofthe- art land surface model (LSM) outputs. Water budget variables (terrestrial water storage TWS, evapotranspiration ET, surface runoff R, and base flow B) are evaluated at the basin scale using both remote sensing and in situ data. Meteorological forcings at a 3-hourly time step and 18 spatial resolution were used to run 14 LSMs. Precipitation datasets that have been rescaled to matchmonthly Global Precipitation Climatology Project (GPCP) andGlobal Precipitation Climatology Centre (GPCC) datasets and the daily Hydrologie du Bassin de l'Amazone (HYBAM) dataset were used to perform three experiments. The Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme was forced with R and B and simulated discharges are compared against observations at 165 gauges. Simulated ET and TWS are compared against FLUXNET and MOD16A2 evapotranspiration datasets andGravity Recovery and ClimateExperiment (GRACE)TWSestimates in two subcatchments of main tributaries (Madeira and Negro Rivers).At the basin scale, simulated ET ranges from 2.39 to 3.26 mm day(exp -1) and a low spatial correlation between ET and precipitation indicates that evapotranspiration does not depend on water availability over most of the basin. Results also show that other simulated water budget components vary significantly as a function of both the LSM and precipitation dataset, but simulated TWS generally agrees with GRACE estimates at the basin scale. The best water budget simulations resulted from experiments using HYBAM, mostly explained by a denser rainfall gauge network and the rescaling at a finer temporal scale.

  17. How you cannot find rain with changes in land surface temperature

    Science.gov (United States)

    Wanders, Niko

    2017-04-01

    Estimating precipitation from space-born sensors is valuable source of observation in poorly-gauged regions. For example, hydrological modelling and monitoring greatly benefits from the increased near-real time data availability for improved accuracy in the simulations of water resources. As is true for all satellite product, precipitation estimated from space are far from perfect and scientist have used many techniques to improve their accuracy. In this study, I tried to improve the space-born precipitation estimates by using remotely sensed soil moisture to observe sudden increases in soil wetness as a result of precipitation. After a month of massaging the data and applied methodology I realized that the gain was very marginal and I was drilling a dry hole. Driven by these disappointing results I tried some random other satellite products to see if they showed correlation with the precipitation signal. There I found a causality that I had not expected at the start of this study, linking land surface temperature to precipitation. It seemed that using changes in land surface temperature strongly correlated with precipitation totals, driven by a cooling of the soil as a result of increase wetness. This link could not only be modelled, but more surprisingly it could be observed from space and used to improve the satellite precipitation estimates. The reduction in the precipitation uncertainty was far better than for any of the three soil moisture products, contrary to what one might expect. This was far from the anticipated result but it showed me that sometimes you should think out of the box and not only use observations for their intended purpose. This experience has motivated me to not only use the obvious observation or method and try techniques and methods from other disciplines to see if we can improve our understanding of the hydrological cycle.

  18. SGP Cloud and Land Surface Interaction Campaign (CLASIC): Measurement Platforms

    Energy Technology Data Exchange (ETDEWEB)

    MA Miller; R Avissar; LK Berg; SA Edgerton; ML Fischer; TJ Jackson; B. Kustas; PJ Lamb; G McFarquhar; Q Min; B Schmid; MS Torn; DD Tuner

    2007-06-01

    The Cloud and Land Surface Interaction Campaign (CLASIC) will be conducted from June 8 to June 30, 2007, at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site. Data will be collected using eight aircraft equipped with a variety of specialized sensors, four specially instrumented surface sites, and two prototype surface radar systems. The architecture of CLASIC includes a high-altitude surveillance aircraft and enhanced vertical thermodynamic and wind profile measurements that will characterize the synoptic scale structure of the clouds and the land surface within the ACRF SGP site. Mesoscale and microscale structures will be sampled with a variety of aircraft, surface, and radar observations. An overview of the measurement platforms that will be used during the CLASIC are described in this report. The coordination of measurements, especially as it relates to aircraft flight plans, will be discussed in the CLASIC Implementation Plan.

  19. NASA GLDAS Evapotranspiration Data and Climatology

    Science.gov (United States)

    Rui, Hualan; Beaudoing, Hiroko Kato; Teng, William L.; Vollmer, Bruce; Rodell, Matthew

    2012-01-01

    Evapotranspiration (ET) is the water lost to the atmosphere by evaporation and transpiration. ET is a shared component in the energy and water budget, therefore, a critical variable for global energy and water cycle and climate change studies. However, direct ET measurements and data acquisition are difficult and expensive, especially at the global level. Therefore, modeling is one common alternative for estimating ET. With the goal to generate optimal fields of land surface states and fluxes, the Global Land Data Assimilation System (GLDAS) has been generating quality-controlled, spatially and temporally consistent, terrestrial hydrologic data, including ET and other variables that affect evaporation and transpiration, such as temperature, precipitation, humidity, wind, soil moisture, heat flux, and solar radiation. This poster presents the long-term ET climatology (mean and monthly), derived from the 61-year GLDAS-2 monthly 1.0 deg x 1.0 deg. NOAH model Experiment-1 data, and describes the basic characteristics of spatial and seasonal variations of the climatology. The time series of GLDAS-2 precipitation and radiation, and ET are also discussed to show the improvement of GLDAS-2 forcing data and model output over those from GLDAS-1.

  20. Land-surface modelling in hydrological perspective ? a review

    OpenAIRE

    Overgaard , J.; Rosbjerg , D.; Butts , M. B.

    2006-01-01

    International audience; The purpose of this paper is to provide a review of the different types of energy-based land-surface models (LSMs) and discuss some of the new possibilities that will arise when energy-based LSMs are combined with distributed hydrological modelling. We choose to focus on energy-based approaches, because in comparison to the traditional potential evapotranspiration models, these approaches allow for a stronger link to remote sensing and atmospheric modelling. New opport...

  1. Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area, Turkey

    Directory of Open Access Journals (Sweden)

    Osman Orhan

    2014-01-01

    Full Text Available The main purpose of this paper is to investigate multitemporal land surface temperature (LST changes by using satellite remote sensing data. The study included a real-time field work performed during the overpass of Landsat-5 satellite on 21/08/2011 over Salt Lake, Turkey. Normalized vegetation index (NDVI, vegetation condition index (VCI, and temperature vegetation index (TVX were used for evaluating drought impact over the region between 1984 and 2011. In the image processing step, geometric and radiometric correction procedures were conducted to make satellite remote sensing data comparable with in situ measurements carried out using thermal infrared thermometer supported by hand-held GPS. The results showed that real-time ground and satellite remote sensing data were in good agreement with correlation coefficient (R2 values of 0.90. The remotely sensed and treated satellite images and resulting thematic indices maps showed that dramatic land surface temperature changes occurred (about 2∘C in the Salt Lake Basin area during the 28-year period (1984–2011. Analysis of air temperature data also showed increases at a rate of 1.5–2∘C during the same period. Intensification of irrigated agriculture particularly in the southern basin was also detected. The use of water supplies, especially groundwater, should be controlled considering particularly summer drought impacts on the basin.

  2. Regional seasonal warming anomalies and land-surface feedbacks

    Science.gov (United States)

    Coffel, E.; Horton, R. M.

    2017-12-01

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

  3. On the predictability of land surface fluxes from meteorological variables

    Science.gov (United States)

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

    2018-01-01

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

  4. Generation and Evaluation of a Global Land Surface Phenology Product from Suomi-NPP VIIRS Observations

    Science.gov (United States)

    Zhang, X.; Liu, L.; Yan, D.; Moon, M.; Liu, Y.; Henebry, G. M.; Friedl, M. A.; Schaaf, C.

    2017-12-01

    Land surface phenology (LSP) datasets have been produced from a variety of coarse spatial resolution satellite observations at both regional and global scales and spanning different time periods since 1982. However, the LSP product generated from NASA's MODerate Resolution Imaging Spectroradiometer (MODIS) data at a spatial resolution of 500m, which is termed Land Cover Dynamics (MCD12Q2), is the only global product operationally produced and freely accessible at annual time steps from 2001. Because MODIS instrument is aging and will be replaced by the Visible Infrared Imaging Radiometer Suite (VIIRS), this research focuses on the generation and evaluation of a global LSP product from Suomi-NPP VIIRS time series observations that provide continuity with the MCD12Q2 product. Specifically, we generate 500m VIIRS global LSP data using daily VIIRS Nadir BRDF (bidirectional reflectance distribution function)-Adjusted reflectances (NBAR) in combination with land surface temperature, snow cover, and land cover type as inputs. The product provides twelve phenological metrics (seven phenological dates and five phenological greenness magnitudes), along with six quality metrics characterizing the confidence and quality associated with phenology retrievals at each pixel. In this paper, we describe the input data and algorithms used to produce this new product, and investigate the impact of VIIRS data time series quality on phenology detections across various climate regimes and ecosystems. As part of our analysis, the VIIRS LSP is evaluated using PhenoCam imagery in North America and Asia, and using higher spatial resolution satellite observations from Landsat 8 over an agricultural area in the central USA. We also explore the impact of high frequency cloud cover on the VIIRS LSP product by comparing with phenology detected from the Advanced Himawari Imager (AHI) onboard Himawari-8. AHI is a new geostationary sensor that observes land surface every 10 minutes, which increases

  5. Evaluating the use of sharpened land surface temperature for daily evapotranspiration estimation over irrigated crops in arid lands

    KAUST Repository

    Rosas, Jorge

    2014-12-01

    Satellite remote sensing provides data on land surface characteristics, useful for mapping land surface energy fluxes and evapotranspiration (ET). Land-surface temperature (LST) derived from thermal infrared (TIR) satellite data has been reliably used as a remote indicator of ET and surface moisture status. However, TIR imagery usually operates at a coarser resolution than that of shortwave sensors on the same satellite platform, making it sometimes unsuitable for monitoring of field-scale crop conditions. This study applies the data mining sharpener (DMS; Gao et al., 2012) technique to data from the Moderate Resolution Imaging Spectroradiometer (MODIS), which sharpens the 1 km thermal data down to the resolution of the optical data (250-500 m) based on functional LST and reflectance relationships established using a flexible regression tree approach. The DMS approach adopted here has been enhanced/refined for application over irrigated farming areas located in harsh desert environments in Saudi Arabia. The sharpened LST data is input to an integrated modeling system that uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI) in conjunction with model reanalysis data and remotely sensed data from polar orbiting (MODIS) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate daily estimates of evapotranspiration. Results are evaluated against available flux tower observations over irrigated maize near Riyadh in Saudi Arabia. Successful monitoring of field-scale changes in surface fluxes are of importance towards an efficient water use in areas where fresh water resources are scarce and poorly monitored. Gao, F.; Kustas, W.P.; Anderson, M.C. A Data Mining Approach for Sharpening Thermal Satellite Imagery over Land. Remote Sens. 2012, 4, 3287-3319.

  6. Estimation of surface air temperature over central and eastern Eurasia from MODIS land surface temperature

    International Nuclear Information System (INIS)

    Shen Suhung; Leptoukh, Gregory G

    2011-01-01

    Surface air temperature (T a ) is a critical variable in the energy and water cycle of the Earth–atmosphere system and is a key input element for hydrology and land surface models. This is a preliminary study to evaluate estimation of T a from satellite remotely sensed land surface temperature (T s ) by using MODIS-Terra data over two Eurasia regions: northern China and fUSSR. High correlations are observed in both regions between station-measured T a and MODIS T s . The relationships between the maximum T a and daytime T s depend significantly on land cover types, but the minimum T a and nighttime T s have little dependence on the land cover types. The largest difference between maximum T a and daytime T s appears over the barren and sparsely vegetated area during the summer time. Using a linear regression method, the daily maximum T a were estimated from 1 km resolution MODIS T s under clear-sky conditions with coefficients calculated based on land cover types, while the minimum T a were estimated without considering land cover types. The uncertainty, mean absolute error (MAE), of the estimated maximum T a varies from 2.4 °C over closed shrublands to 3.2 °C over grasslands, and the MAE of the estimated minimum T a is about 3.0 °C.

  7. Investigating Land Surface Temperature Changes Using Landsat Data in Konya, Turkey

    Directory of Open Access Journals (Sweden)

    O. Orhan

    2016-06-01

    Full Text Available The main purpose of this paper is to investigate multi-temporal land surface temperature (LST and Normalized Difference Vegetation Index (NDVI changes of Konya in Turkey using remotely sensed data. Konya is located in the semi-arid central Anatolian region of Turkey and hosts many important wetland sites including Salt Lake. Six images taken by Landsat-5 TM and Landsat 8- OLI satellites were used as the basic data source. These raw images were taken in 1984, 2011 and 2014 intended as long-term and short-term. Firstly, those raw images was corrected radiometric and geometrically within the scope of project. Three mosaic images were obtained by using the full-frame images of Landsat-5 TM / 8- OLI which had been already transformed comparison each other. Then, Land Surface Temperature (LST, Normalized Difference Vegetation Index (NDVI maps have been produced to determine the dimension of the drought. The obtained results showed that surface temperature rates in the basin increased about 5°C between 1984 and 2014 as long periods, increased about 2-3°C between 2011and 2014 as short periods. Meteorological data supports the increase in temperature.

  8. Changes in Land Surface Water Dynamics since the 1990s and Relation to Population Pressure

    Science.gov (United States)

    Prigent, C.; Papa, F.; Aires, F.; Jimenez, C.; Rossow, W. B.; Matthews, E.

    2012-01-01

    We developed a remote sensing approach based on multi-satellite observations, which provides an unprecedented estimate of monthly distribution and area of land-surface open water over the whole globe. Results for 1993 to 2007 exhibit a large seasonal and inter-annual variability of the inundation extent with an overall decline in global average maximum inundated area of 6% during the fifteen-year period, primarily in tropical and subtropical South America and South Asia. The largest declines of open water are found where large increases in population have occurred over the last two decades, suggesting a global scale effect of human activities on continental surface freshwater: denser population can impact local hydrology by reducing freshwater extent, by draining marshes and wetlands, and by increasing water withdrawals. Citation: Prigent, C., F. Papa, F. Aires, C. Jimenez, W. B. Rossow, and E. Matthews (2012), Changes in land surface water dynamics since the 1990s and relation to population pressure, in section 4, insisting on the potential applications of the wetland dataset.

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

    Science.gov (United States)

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

    2007-12-01

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

  10. Climatological determinants of woody cover in Africa

    OpenAIRE

    Good, Stephen P.; Caylor, Kelly K.

    2011-01-01

    Determining the factors that influence the distribution of woody vegetation cover and resolving the sensitivity of woody vegetation cover to shifts in environmental forcing are critical steps necessary to predict continental-scale responses of dryland ecosystems to climate change. We use a 6-year satellite data record of fractional woody vegetation cover and an 11-year daily precipitation record to investigate the climatological controls on woody vegetation cover across the African continent....

  11. 4.4 Development of a 30-Year Soil Moisture Climatology for Situational Awareness and Public Health Applications

    Science.gov (United States)

    Case, Jonathan L.; Zavodsky, Bradley T.; White, Kristopher D.; Bell, Jesse E.

    2015-01-01

    This paper provided a brief background on the work being done at NASA SPoRT and the CDC to create a soil moisture climatology over the CONUS at high spatial resolution, and to provide a valuable source of soil moisture information to the CDC for monitoring conditions that could favor the development of Valley Fever. The soil moisture climatology has multi-faceted applications for both the NOAA/NWS situational awareness in the areas of drought and flooding, and for the Public Health community. SPoRT plans to increase its interaction with the drought monitoring and Public Health communities by enhancing this testbed soil moisture anomaly product. This soil moisture climatology run will also serve as a foundation for upgrading the real-time (currently southeastern CONUS) SPoRT-LIS to a full CONUS domain based on LIS version 7 and incorporating real-time GVF data from the Suomi-NPP Visible Infrared Imaging Radiometer Suite (Vargas et al. 2013) into LIS-Noah. The upgraded SPoRT-LIS run will serve as a testbed proof-of-concept of a higher-resolution NLDAS-2 modeling member. The climatology run will be extended to near real-time using the NLDAS-2 meteorological forcing from 2011 to present. The fixed 1981-2010 climatology shall provide the soil moisture "normals" for the production of real-time soil moisture anomalies. SPoRT also envisions a web-mapping type of service in which an end-user could put in a request for either an historical or real-time soil moisture anomaly graph for a specified county (as exemplified by Figure 2) and/or for local and regional maps of soil moisture proxy percentiles. Finally, SPoRT seeks to assimilate satellite soil moisture data from the current Soil Moisture Ocean Salinity (SMOS; Blankenship et al. 2014) and the recently-launched NASA Soil Moisture Active Passive (SMAP; Entekhabi et al. 2010) missions, using the EnKF capability within LIS. The 9-km combined active radar and passive microwave retrieval product from SMAP (Das et al. 2011

  12. Relation between seasonally detrended shortwave infrared reflectance data and land surface moisture in semi-arid Sahel

    DEFF Research Database (Denmark)

    Olsen, Jørgen Lundegaard; Ceccato, Pietro; Proud, Simon Richard

    2013-01-01

    in vegetation moisture status, and is compared to detrended time series of the Normalized Difference Vegetation Index (NDVI). It was found that when plant available water is low, the SIWSI anomalies increase over time, while the NDVI anomalies decrease over time, but less systematically. Therefore SIWSI may......In the Sudano-Sahelian areas of Africa droughts can have serious impacts on natural resources, and therefore land surface moisture is an important factor. Insufficient conventional sites for monitoring land surface moisture make the use of Earth Observation data for this purpose a key issue...... Second Generation (MSG) satellite. We focused on responses in surface reflectance to soil- and surface moisture for bare soil and early to mid- growing season. A method for implementing detrended time series of the Shortwave Infrared Water Stress Index (SIWSI) is examined for detecting variations...

  13. SAFARI 2000 AVHRR-derived Land Surface Temperature Maps, Africa, 1995-2000

    Data.gov (United States)

    National Aeronautics and Space Administration — Land Surface Temperature (LST) is a key indicator of land surface states, and can provide information on surface-atmosphere heat and mass fluxes, vegetation water...

  14. SAFARI 2000 AVHRR-derived Land Surface Temperature Maps, Africa, 1995-2000

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: Land Surface Temperature (LST) is a key indicator of land surface states, and can provide information on surface-atmosphere heat and mass fluxes,...

  15. Land Surface Model (LSM 1.0) for Ecological, Hydrological, Atmospheric Studies

    Data.gov (United States)

    National Aeronautics and Space Administration — The NCAR LSM 1.0 is a land surface model developed to examine biogeophysical and biogeochemical land-atmosphere interactions, especially the effects of land surfaces...

  16. Hydro-climatology

    DEFF Research Database (Denmark)

    The hydro-climatological approach of this volume illustrates the scientific and practical value of considering hydrological phenomena and processes in a climate context to improve understanding of controls, process interaction, and past and future variability/change. Contributions deal with under......The hydro-climatological approach of this volume illustrates the scientific and practical value of considering hydrological phenomena and processes in a climate context to improve understanding of controls, process interaction, and past and future variability/change. Contributions deal...... considered. The interdisciplinary approach reveals information and perspective that go beyond the study of cli ate and hydro gy alone...

  17. Subsurface temperature estimation from climatology and satellite SST for the sea around Korean Peninsula 1Bong-Guk, Kim, 1Yang-Ki, Cho, 1Bong-Gwan, Kim, 1Young-Gi, Kim, 1Ji-Hoon, Jung 1School of Earth and Environmental Sciences, Seoul National University

    Science.gov (United States)

    Kim, Bong-Guk; Cho, Yang-Ki; Kim, Bong-Gwan; Kim, Young-Gi; Jung, Ji-Hoon

    2015-04-01

    Subsurface temperature plays an important role in determining heat contents in the upper ocean which are crucial in long-term and short-term weather systems. Furthermore, subsurface temperature affects significantly ocean ecology. In this study, a simple and practical algorithm has proposed. If we assume that subsurface temperature changes are proportional to surface heating or cooling, subsurface temperature at each depth (Sub_temp) can be estimated as follows PIC whereiis depth index, Clm_temp is temperature from climatology, dif0 is temperature difference between satellite and climatology in the surface, and ratio is ratio of temperature variability in each depth to surface temperature variability. Subsurface temperatures using this algorithm from climatology (WOA2013) and satellite SST (OSTIA) where calculated in the sea around Korean peninsula. Validation result with in-situ observation data show good agreement in the upper 50 m layer with RMSE (root mean square error) less than 2 K. The RMSE is smallest with less than 1 K in winter when surface mixed layer is thick, and largest with about 2~3 K in summer when surface mixed layer is shallow. The strong thermocline and large variability of the mixed layer depth might result in large RMSE in summer. Applying of mixed layer depth information for the algorithm may improve subsurface temperature estimation in summer. Spatial-temporal details on the improvement and its causes will be discussed.

  18. A review on remotely sensed land surface temperature anomaly as an earthquake precursor

    Science.gov (United States)

    Bhardwaj, Anshuman; Singh, Shaktiman; Sam, Lydia; Joshi, P. K.; Bhardwaj, Akanksha; Martín-Torres, F. Javier; Kumar, Rajesh

    2017-12-01

    The low predictability of earthquakes and the high uncertainty associated with their forecasts make earthquakes one of the worst natural calamities, capable of causing instant loss of life and property. Here, we discuss the studies reporting the observed anomalies in the satellite-derived Land Surface Temperature (LST) before an earthquake. We compile the conclusions of these studies and evaluate the use of remotely sensed LST anomalies as precursors of earthquakes. The arrival times and the amplitudes of the anomalies vary widely, thus making it difficult to consider them as universal markers to issue earthquake warnings. Based on the randomness in the observations of these precursors, we support employing a global-scale monitoring system to detect statistically robust anomalous geophysical signals prior to earthquakes before considering them as definite precursors.

  19. Advancements in Modelling of Land Surface Energy Fluxes with Remote Sensing at Different Spatial Scales

    DEFF Research Database (Denmark)

    Guzinski, Radoslaw

    uxes, such as sensible heat ux, ground heat ux and net radiation, are also necessary. While it is possible to measure those uxes with ground-based instruments at local scales, at region scales they usually need to be modelled or estimated with the help of satellite remote sensing data. Even though...... to increase the spatial resolution of the reliable DTD-modelled fluxes from 1 km to 30 m. Furthermore, synergies between remote sensing based models and distributed hydrological models were studied with the aim of improving spatial performance of the hydrological models through incorporation of remote sensing...... of this study was to look at, and improve, various approaches for modelling the land-surface energy uxes at different spatial scales. The work was done using physically-based Two-Source Energy Balance (TSEB) approach as well as semi-empirical \\Triangle" approach. The TSEB-based approach was the main focus...

  20. Developing first time-series of land surface temperature from AATSR with uncertainty estimates

    Science.gov (United States)

    Ghent, Darren; Remedios, John

    2013-04-01

    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. Earth Observation satellites provide the opportunity to obtain global coverage of LST approximately every 3 days or less. One such source of satellite retrieved LST has been the Advanced Along-Track Scanning Radiometer (AATSR); with LST retrieval being implemented in the AATSR Instrument Processing Facility in March 2004. Here we present first regional and global time-series of LST data from AATSR with estimates of uncertainty. Mean changes in temperature over the last decade will be discussed along with regional patterns. Although time-series across all three ATSR missions have previously been constructed (Kogler et al., 2012), the use of low resolution auxiliary data in the retrieval algorithm and non-optimal cloud masking resulted in time-series artefacts. As such, considerable ESA supported development has been carried out on the AATSR data to address these concerns. This includes the integration of high resolution auxiliary data into the retrieval algorithm and subsequent generation of coefficients and tuning parameters, plus the development of an improved cloud mask based on the simulation of clear sky conditions from radiance transfer modelling (Ghent et al., in prep.). Any inference on this LST record is though of limited value without the accompaniment of an uncertainty estimate; wherein the Joint Committee for Guides in Metrology quote an uncertainty as "a parameter associated with the result of a measurement that characterizes the dispersion of the values that could reasonably be attributed to the measurand that is the value of the particular quantity to be measured". Furthermore, pixel level uncertainty fields are a mandatory requirement in the on-going preparation of the LST product for the upcoming Sea and Land Surface Temperature (SLSTR) instrument on-board Sentinel-3

  1. Soil Structure - A Neglected Component of Land-Surface Models

    Science.gov (United States)

    Fatichi, S.; Or, D.; Walko, R. L.; Vereecken, H.; Kollet, S. J.; Young, M.; Ghezzehei, T. A.; Hengl, T.; Agam, N.; Avissar, R.

    2017-12-01

    Soil structure is largely absent in most standard sampling and measurements and in the subsequent parameterization of soil hydraulic properties deduced from soil maps and used in Earth System Models. The apparent omission propagates into the pedotransfer functions that deduce parameters of soil hydraulic properties primarily from soil textural information. Such simple parameterization is an essential ingredient in the practical application of any land surface model. Despite the critical role of soil structure (biopores formed by decaying roots, aggregates, etc.) in defining soil hydraulic functions, only a few studies have attempted to incorporate soil structure into models. They mostly looked at the effects on preferential flow and solute transport pathways at the soil profile scale; yet, the role of soil structure in mediating large-scale fluxes remains understudied. Here, we focus on rectifying this gap and demonstrating potential impacts on surface and subsurface fluxes and system wide eco-hydrologic responses. The study proposes a systematic way for correcting the soil water retention and hydraulic conductivity functions—accounting for soil-structure—with major implications for near saturated hydraulic conductivity. Modification to the basic soil hydraulic parameterization is assumed as a function of biological activity summarized by Gross Primary Production. A land-surface model with dynamic vegetation is used to carry out numerical simulations with and without the role of soil-structure for 20 locations characterized by different climates and biomes across the globe. Including soil structure affects considerably the partition between infiltration and runoff and consequently leakage at the base of the soil profile (recharge). In several locations characterized by wet climates, a few hundreds of mm per year of surface runoff become deep-recharge accounting for soil-structure. Changes in energy fluxes, total evapotranspiration and vegetation productivity

  2. Teaching Climatology and Meterology

    OpenAIRE

    Waddington, Shelagh B.

    1997-01-01

    Climatology and meteorology are often regarded as very difficult to teach by teachers and very hard to learn by students. This paper presents simple practical exercises which will enable teachers to make the topic of greater interest and easier for students to understand some of the basic ideas.

  3. General Climatology 3

    Science.gov (United States)

    Hartmann, Dennis L.

    General Climatology 3 is volume 3 of the series World Survey of Climatology, which consists of 15 volumes containing review articles on a broad range of topics. General Climatology 3 contains four chapters: ‘Human Bioclimatology,’ ‘Agricultural Climatology,’ ‘City Climate,’ and ‘Technical Climatology.’ Each of these chapters will be briefly described here.‘Human Bioclimatology,’ the first chapter, was authored by E. Flach and provides a survey of the effects on the human organism of the physical conditions at the earth's surface. It contains four main sections. A section entitled ‘Light and Life’ deals with the effects of solar radiation on man and contains much interesting information on the response of the human eye and human skin to radiation at various frequencies. ‘Air and Life’ discusses the composition of air and its effect on human health and performance, including discussions of the effects of altitude, aerosols, and noxious trace gases. ‘Temperature and Life’ discusses how the body responds to temperature and how it maintains its heat budget under the variety of conditions to which it falls subject and considerable discussion is given to objective ways to characterize air conditions that give an accurate measure of their impact on the body. This discussion leads naturally into the final section, ‘Bioclimatological Evaluation Systems,’ which addresses the problem of how to classify a particular site according to its overall suitability to human habitation.

  4. A factorial assessment of the sensitivity of the BATS land-surface parameterization scheme. [BATS (Biosphere-Atmosphere Transfer Scheme)

    Energy Technology Data Exchange (ETDEWEB)

    Henderson-Sellers, A. (Macquarie Univ., North Ryde, New South Wales (Australia))

    1993-02-01

    Land-surface schemes developed for incorporation into global climate models include parameterizations that are not yet fully validated and depend upon the specification of a large (20-50) number of ecological and soil parameters, the values of which are not yet well known. There are two methods of investigating the sensitivity of a land-surface scheme to prescribed values: simple one-at-a-time changes or factorial experiments. Factorial experiments offer information about interactions between parameters and are thus a more powerful tool. Here the results of a suite of factorial experiments are reported. These are designed (i) to illustrate the usefulness of this methodology and (ii) to identify factors important to the performance of complex land-surface schemes. The Biosphere-Atmosphere Transfer Scheme (BATS) is used and its sensitivity is considered (a) to prescribed ecological and soil parameters and (b) to atmospheric forcing used in the off-line tests undertaken. Results indicate that the most important atmospheric forcings are mean monthly temperature and the interaction between mean monthly temperature and total monthly precipitation, although fractional cloudiness and other parameters are also important. The most important ecological parameters are vegetation roughness length, soil porosity, and a factor describing the sensitivity of the stomatal resistance of vegetation to the amount of photosynthetically active solar radiation and, to a lesser extent, soil and vegetation albedos. Two-factor interactions including vegetation roughness length are more important than many of the 23 specified single factors. The results of factorial sensitivity experiments such as these could form the basis for intercomparison of land-surface parameterization schemes and for field experiments and satellite-based observation programs aimed at improving evaluation of important parameters.

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

    Science.gov (United States)

    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.

  6. Estimation of Surface Air Temperature Over Central and Eastern Eurasia from MODIS Land Surface Temperature

    Science.gov (United States)

    Shen, Suhung; Leptoukh, Gregory G.

    2011-01-01

    Surface air temperature (T(sub a)) is a critical variable in the energy and water cycle of the Earth.atmosphere system and is a key input element for hydrology and land surface models. This is a preliminary study to evaluate estimation of T(sub a) from satellite remotely sensed land surface temperature (T(sub s)) by using MODIS-Terra data over two Eurasia regions: northern China and fUSSR. High correlations are observed in both regions between station-measured T(sub a) and MODIS T(sub s). The relationships between the maximum T(sub a) and daytime T(sub s) depend significantly on land cover types, but the minimum T(sub a) and nighttime T(sub s) have little dependence on the land cover types. The largest difference between maximum T(sub a) and daytime T(sub s) appears over the barren and sparsely vegetated area during the summer time. Using a linear regression method, the daily maximum T(sub a) were estimated from 1 km resolution MODIS T(sub s) under clear-sky conditions with coefficients calculated based on land cover types, while the minimum T(sub a) were estimated without considering land cover types. The uncertainty, mean absolute error (MAE), of the estimated maximum T(sub a) varies from 2.4 C over closed shrublands to 3.2 C over grasslands, and the MAE of the estimated minimum Ta is about 3.0 C.

  7. Urbanization Process and Variation of Energy Budget of Land Surfaces

    Directory of Open Access Journals (Sweden)

    Ciro Gardi

    2007-06-01

    Full Text Available Urban areas are increasing at a rate much higher than human population growth in many part of the world; actually more than 73 towns in the world are larger than 1000 km2. The European Environmental Agency indicates an urban area average growth rate, over the last 20 years, of 20%. The urbanization process, and the consequent soil sealing, determines not only the losses of the ecological functions of the soil, but also a variation of the energy budget of land surfaces, that affect the microclimatic conditions (heat islands. The alteration of the energy budget are determined by the variations of albedo and roughness of surfaces, but especially by the net losses of evapotranspirating areas. In the present research we have assessed the variation of Parma territory energy budget, induced by the change in land use over the last 122 years. The urban area increase between 1881 and 2003 was 535%.

  8. A global data set of land-surface parameters

    International Nuclear Information System (INIS)

    Claussen, M.; Lohmann, U.; Roeckner, E.; Schulzweida, U.

    1994-01-01

    A global data set of land surface parameters is provided for the climate model ECHAM developed at the Max-Planck-Institut fuer Meteorologie in Hamburg. These parameters are: background (surface) albedo α, surface roughness length z 0y , leaf area index LAI, fractional vegetation cover or vegetation ratio c y , and forest ratio c F . The global set of surface parameters is constructed by allocating parameters to major exosystem complexes of Olson et al. (1983). The global distribution of ecosystem complexes is given at a resolution of 0.5 0 x 0.5 0 . The latter data are compatible with the vegetation types used in the BIOME model of Prentice et al. (1992) which is a potential candidate of an interactive submodel within a comprehensive model of the climate system. (orig.)

  9. Development and evaluation of climatologically-downscaled AFWA AGRMET precipitation products over the continental U.S.

    Science.gov (United States)

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

    2008-05-01

    Collaborations between the Air Force Weather Agency (AFWA), the Hydrological Sciences Branch at NASA-GSFC, and the PRISM Group at Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS- based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and near-real-time simulations in regions of interest. This work focuses on value added to the AGRMET precipitation product by the inclusion of high-quality climatological information on a monthly time scale. The AGRMET method uses microwave-based satellite precipitation estimates from various polar-orbiting platforms (NOAA POES and DMSP), infrared-based estimates from geostationary platforms (GOES, METEOSAT, etc.), related cloud analysis products, and surface gauge observations in a complex and hierarchical blending process. Results from processing of the legacy AGRMET precipitation

  10. Hydrologic Remote Sensing and Land Surface Data Assimilation

    Directory of Open Access Journals (Sweden)

    Hamid Moradkhani

    2008-05-01

    Full Text Available Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface–atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF and Particle filter (PF, for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law and could be a strong alternative to EnKF which is subject to some

  11. Hydrologic Remote Sensing and Land Surface Data Assimilation.

    Science.gov (United States)

    Moradkhani, Hamid

    2008-05-06

    Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear

  12. Land surface temperature downscaling using random forest regression: primary result and sensitivity analysis

    Science.gov (United States)

    Pan, Xin; Cao, Chen; Yang, Yingbao; Li, Xiaolong; Shan, Liangliang; Zhu, Xi

    2018-04-01

    The land surface temperature (LST) derived from thermal infrared satellite images is a meaningful variable in many remote sensing applications. However, at present, the spatial resolution of the satellite thermal infrared remote sensing sensor is coarser, which cannot meet the needs. In this study, LST image was downscaled by a random forest model between LST and multiple predictors in an arid region with an oasis-desert ecotone. The proposed downscaling approach was evaluated using LST derived from the MODIS LST product of Zhangye City in Heihe Basin. The primary result of LST downscaling has been shown that the distribution of downscaled LST matched with that of the ecosystem of oasis and desert. By the way of sensitivity analysis, the most sensitive factors to LST downscaling were modified normalized difference water index (MNDWI)/normalized multi-band drought index (NMDI), soil adjusted vegetation index (SAVI)/ shortwave infrared reflectance (SWIR)/normalized difference vegetation index (NDVI), normalized difference building index (NDBI)/SAVI and SWIR/NDBI/MNDWI/NDWI for the region of water, vegetation, building and desert, with LST variation (at most) of 0.20/-0.22 K, 0.92/0.62/0.46 K, 0.28/-0.29 K and 3.87/-1.53/-0.64/-0.25 K in the situation of +/-0.02 predictor perturbances, respectively.

  13. Monitoring of Land-Surface Deformation in the Karamay Oilfield, Xinjiang, China, Using SAR Interferometry

    Directory of Open Access Journals (Sweden)

    Yusupujiang Aimaiti

    2017-07-01

    Full Text Available Synthetic Aperture Radar (SAR interferometry is a technique that provides high-resolution measurements of the ground displacement associated with various geophysical processes. To investigate the land-surface deformation in Karamay, a typical oil-producing city in the Xinjiang Uyghur Autonomous Region, China, Advanced Land Observing Satellite (ALOS Phased Array L-band Synthetic Aperture Radar (PALSAR data were acquired for the period from 2007 to 2009, and a two-pass differential SAR interferometry (D-InSAR process was applied. The experimental results showed that two sites in the north-eastern part of the city exhibit a clear indication of land deformation. For a further evaluation of the D-InSAR result, the Persistent Scatterer (PS and Small Baseline Subset (SBAS-InSAR techniques were applied for 21 time series Environmental Satellite (ENVISAT C-band Advanced Synthetic Aperture Radar (ASAR data from 2003 to 2010. The comparison between the D-InSAR and SBAS-InSAR measurements had better agreement than that from the PS-InSAR measurement. The maximum deformation rate attributed to subsurface water injection for the period from 2003 to 2010 was up to approximately 33 mm/year in the line of sight (LOS direction. The interferometric phase change from November 2007 to June 2010 showed a clear deformation pattern, and the rebound center has been expanding in scale and increasing in quantity.

  14. Comparison of Sensible Heat Flux from Eddy Covariance and Scintillometer over different land surface conditions

    Science.gov (United States)

    Zeweldi, D. A.; Gebremichael, M.; Summis, T.; Wang, J.; Miller, D.

    2008-12-01

    The large source of uncertainty in satellite-based evapotranspiration algorithm results from the estimation of sensible heat flux H. Traditionally eddy covariance sensors, and recently large-aperture scintillometers, have been used as ground truth to evaluate satellite-based H estimates. The two methods rely on different physical measurement principles, and represent different foot print sizes. In New Mexico, we conducted a field campaign during summer 2008 to compare H estimates obtained from the eddy covariance and scintillometer methods. During this field campaign, we installed sonic anemometers; one propeller eddy covariance (OPEC) equipped with net radiometer and soil heat flux sensors; large aperture scintillometer (LAS); and weather station consisting of wind speed, direction and radiation sensors over three different experimental areas consisting of different roughness conditions (desert, irrigated area and lake). Our results show the similarities and differences in H estimates obtained from these various methods over the different land surface conditions. Further, our results show that the H estimates obtained from the LAS agree with those obtained from the eddy covariance method when high frequency thermocouple temperature, instead of the typical weather station temperature measurements, is used in the LAS analysis.

  15. A climatology of visible surface reflectance spectra

    International Nuclear Information System (INIS)

    Zoogman, Peter; Liu, Xiong; Chance, Kelly; Sun, Qingsong; Schaaf, Crystal; Mahr, Tobias; Wagner, Thomas

    2016-01-01

    We present a high spectral resolution climatology of visible surface reflectance as a function of wavelength for use in satellite measurements of ozone and other atmospheric species. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument is planned to measure backscattered solar radiation in the 290–740 nm range, including the ultraviolet and visible Chappuis ozone bands. Observation in the weak Chappuis band takes advantage of the relative transparency of the atmosphere in the visible to achieve sensitivity to near-surface ozone. However, due to the weakness of the ozone absorption features this measurement is more sensitive to errors in visible surface reflectance, which is highly variable. We utilize reflectance measurements of individual plant, man-made, and other surface types to calculate the primary modes of variability of visible surface reflectance at a high spectral resolution, comparable to that of TEMPO (0.6 nm). Using the Moderate-resolution Imaging Spectroradiometer (MODIS) Bidirection Reflectance Distribution Function (BRDF)/albedo product and our derived primary modes we construct a high spatial resolution climatology of wavelength-dependent surface reflectance over all viewing scenes and geometries. The Global Ozone Monitoring Experiment–2 (GOME-2) Lambertian Equivalent Reflectance (LER) product provides complementary information over water and snow scenes. Preliminary results using this approach in multispectral ultraviolet+visible ozone retrievals from the GOME-2 instrument show significant improvement to the fitting residuals over vegetated scenes. - Highlights: • Our goals was visible surface reflectance for satellite trace gas measurements. • Captured the range of surface reflectance spectra through EOF analysis. • Used satellite surface reflectance products for each given scene to anchor EOFs. • Generated a climatology of time/geometry dependent surface reflectance spectra. • Demonstrated potential to

  16. Global Precipitation Climatology Project (GPCP) Climate Data Record (CDR), Version 2.3 (Monthly)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Precipitation Climatology Project (GPCP) consists of monthly satellite-gauge and associated precipitation error estimates and covers the period January...

  17. Long Term Validation of Land Surface Temperature Retrieved from MSG/SEVIRI with Continuous in-Situ Measurements in Africa

    Directory of Open Access Journals (Sweden)

    Frank-M. Göttsche

    2016-05-01

    Full Text Available Since 2005, the Land Surface Analysis Satellite Application Facility (LSA SAF operationally retrieves Land Surface Temperature (LST for the Spinning Enhanced Visible and Infrared Imager (SEVIRI on board Meteosat Second Generation (MSG. The high temporal resolution of the Meteosat satellites and their long term availability since 1977 make their data highly valuable for climate studies. In order to ensure that the LSA SAF LST product continuously meets its target accuracy of 2 °C, it is validated with in-situ measurements from four dedicated LST validation stations. Three stations are located in highly homogenous areas in Africa (semiarid bush, desert, and Kalahari semi-desert and typically provide thousands of monthly match-ups with LSA SAF LST, which are used to perform seasonally resolved validations. An uncertainty analysis performed for desert station Gobabeb yielded an estimate of total in-situ LST uncertainty of 0.8 ± 0.12 °C. Ignoring rainy seasons, the results for the period 2009–2014 show that LSA SAF LST consistently meets its target accuracy: the highest mean root-mean-square error (RMSE for LSA SAF LST over the African stations was 1.6 °C while mean absolute bias was 0.1 °C. Nighttime and daytime biases were up to 0.7 °C but had opposite signs: when evaluated together, these partially compensated each other.

  18. Interdependencies of Arctic land surface processes: A uniquely sensitive environment

    Science.gov (United States)

    Bowling, L. C.

    2007-12-01

    The circumpolar arctic drainage basin is composed of several distinct ecoregions including steppe grassland and cropland, boreal forest and tundra. Land surface hydrology throughout this diverse region shares several unique features such as dramatic seasonal runoff differences controlled by snowmelt and ice break-up; the storage of significant portions of annual precipitation as snow and in lakes and wetlands; and the effects of ephemeral and permanently frozen soils. These arctic land processes are delicately balanced with the climate and are therefore important indicators of change. The litany of recently-detected changes in the Arctic includes changes in snow precipitation, trends and seasonal shifts in river discharge, increases and decreases in the extent of surface water, and warming soil temperatures. Although not unique to the arctic, increasing anthropogenic pressures represent an additional element of change in the form of resource extraction, fire threat and reservoir construction. The interdependence of the physical, biological and social systems mean that changes in primary indicators have large implications for land cover, animal populations and the regional carbon balance, all of which have the potential to feed back and induce further change. In fact, the complex relationships between the hydrological processes that make the Artic unique also render observed historical change difficult to interpret and predict, leading to conflicting explanations. For example, a decrease in snow accumulation may provide less insulation to the underlying soil resulting in greater frost development and increased spring runoff. Similarly, melting permafrost and ground ice may lead to ground subsidence and increased surface saturation and methane production, while more complete thaw may enhance drainage and result in drier soil conditions. The threshold nature of phase change around the freezing point makes the system especially sensitive to change. In addition, spatial

  19. Comparing soil moisture memory in satellite observations and models

    Science.gov (United States)

    Stacke, Tobias; Hagemann, Stefan; Loew, Alexander

    2013-04-01

    A major obstacle to a correct parametrization of soil processes in large scale global land surface models is the lack of long term soil moisture observations for large parts of the globe. Currently, a compilation of soil moisture data derived from a range of satellites is released by the ESA Climate Change Initiative (ECV_SM). Comprising the period from 1978 until 2010, it provides the opportunity to compute climatological relevant statistics on a quasi-global scale and to compare these to the output of climate models. Our study is focused on the investigation of soil moisture memory in satellite observations and models. As a proxy for memory we compute the autocorrelation length (ACL) of the available satellite data and the uppermost soil layer of the models. Additional to the ECV_SM data, AMSR-E soil moisture is used as observational estimate. Simulated soil moisture fields are taken from ERA-Interim reanalysis and generated with the land surface model JSBACH, which was driven with quasi-observational meteorological forcing data. The satellite data show ACLs between one week and one month for the greater part of the land surface while the models simulate a longer memory of up to two months. Some pattern are similar in models and observations, e.g. a longer memory in the Sahel Zone and the Arabian Peninsula, but the models are not able to reproduce regions with a very short ACL of just a few days. If the long term seasonality is subtracted from the data the memory is strongly shortened, indicating the importance of seasonal variations for the memory in most regions. Furthermore, we analyze the change of soil moisture memory in the different soil layers of the models to investigate to which extent the surface soil moisture includes information about the whole soil column. A first analysis reveals that the ACL is increasing for deeper layers. However, its increase is stronger in the soil moisture anomaly than in its absolute values and the first even exceeds the

  20. Situational Lightning Climatologies

    Science.gov (United States)

    Bauman, William; Crawford, Winifred

    2010-01-01

    Research has revealed distinct spatial and temporal distributions of lightning occurrence that are strongly influenced by large-scale atmospheric flow regimes. It was believed there were two flow systems, but it has been discovered that actually there are seven distinct flow regimes. The Applied Meteorology Unit (AMU) has recalculated the lightning climatologies for the Shuttle Landing Facility (SLF), and the eight airfields in the National Weather Service in Melbourne (NWS MLB) County Warning Area (CWA) using individual lightning strike data to improve the accuracy of the climatologies. The software determines the location of each CG lightning strike with 5-, 10-, 20-, and 30-nmi (.9.3-, 18.5-, 37-, 55.6-km) radii from each airfield. Each CG lightning strike is binned at 1-, 3-, and 6-hour intervals at each specified radius. The software merges the CG lightning strike time intervals and distance with each wind flow regime and creates probability statistics for each time interval, radii, and flow regime, and stratifies them by month and warm season. The AMU also updated the graphical user interface (GUI) with the new data.

  1. Eight Year Climatologies from Observational (AIRS) and Model (MERRA) Data

    Science.gov (United States)

    Hearty, Thomas; Savtchenko, Andrey; Won, Young-In; Theobalk, Mike; Vollmer, Bruce; Manning, Evan; Smith, Peter; Ostrenga, Dana; Leptoukh, Greg

    2010-01-01

    We examine climatologies derived from eight years of temperature, water vapor, cloud, and trace gas observations made by the Atmospheric Infrared Sounder (AIRS) instrument flying on the Aqua satellite and compare them to similar climatologies constructed with data from a global assimilation model, the Modern Era Retrospective-Analysis for Research and Applications (MERRA). We use the AIRS climatologies to examine anomalies and trends in the AIRS data record. Since sampling can be an issue for infrared satellites in low earth orbit, we also use the MERRA data to examine the AIRS sampling biases. By sampling the MERRA data at the AIRS space-time locations both with and without the AIRS quality control we estimate the sampling bias of the AIRS climatology and the atmospheric conditions where AIRS has a lower sampling rate. While the AIRS temperature and water vapor sampling biases are small at low latitudes, they can be more than a few degrees in temperature or 10 percent in water vapor at higher latitudes. The largest sampling biases are over desert. The AIRS and MERRA data are available from the Goddard Earth Sciences Data and Information Services Center (GES DISC). The AIRS climatologies we used are available for analysis with the GIOVANNI data exploration tool. (see, http://disc.gsfc.nasa.gov).

  2. Land surface cleanup of plutonium at the Nevada Test Site

    International Nuclear Information System (INIS)

    Ebeling, L.L.; Evans, R.B.; Walsh, E.J.

    1991-01-01

    The Nevada Test Site (NTS) covers approximately 3300 km 2 of high desert and is located approximately 100 km northwest of Las Vegas, Nevada. Soil contaminated by plutonium exists on the NTS and surrounding areas from safety tests conducted in the 1950s and 1960s. About 150 curies of contamination have been measured over 1200 hectares of land surface. Most contamination is found in the top 5 cm of soil but may be found deep as 25 cm. The cost of conventional removal and disposal of the full soil volume has been estimated at over $500,000,000. This study is directed toward minimizing the volume of waste which must be further processed and disposed of by precisely controlling soil removal depth. The following soil removal machines were demonstrated at the NTS: (1) a CMI Corporation Model PR-500FL pavement profiler, (2) a CMI Corporation Model Tr-225B trimmer reclaimer, (3) a Caterpillar Model 623 elevating scraper equipped with laser depth control, (4) a Caterpillar Model 14G motor grader equipped with laser depth control, (5) a Caterpillar Model 637 auger scraper, and (6) a XCR Series Guzzler vacuum truck. 5 refs., 5 figs

  3. Modeling land-surface/atmosphere dynamics for CHAMMP

    International Nuclear Information System (INIS)

    Gutowski, W.J. Jr.

    1993-01-01

    Project progress is described on a DOE CHAMP project to model the land-surface/atmosphere coupling in a heterogeneous environment. This work is a collaboration between scientists at Iowa State University and the University of New Hampshire. Work has proceeded in two areas: baseline model coupling and data base development for model validation. The core model elements (land model, atmosphere model) have been ported to the Principal Investigator's computing system and baseline coupling has commenced. The initial target data base is the set of observations from the FIFE field campaign, which is in the process of being acquired. For the remainder of the project period, additional data from the region surrounding the FIFE site and from other field campaigns will be acquired to determine how to best extrapolate results from the initial target region to the rest of the globe. In addition, variants of the coupled model will be used to perform experiments examining resolution requirements and coupling strategies for land-atmosphere coupling in a heterogeneous environment

  4. Downscaling Coarse Actual ET Data Using Land Surface Resistance

    Science.gov (United States)

    Shen, T.

    2017-12-01

    This study proposed a new approach of downscaling ETWATCH 1km actual evapotranspiration (ET) product to a spatial resolution of 30m using land surface resistance that simulated mainly from monthly Landsat8 data and Jarvis method, which combined the benefits of both high temporal resolution of ETWATCH product and fine spatial resolution of Landsat8. The driving factor, surface resistance (Rs), was chosen for the reason that could reflect the transfer ability of vapor flow over canopy. Combined resistance Rs both upon canopy conditions, atmospheric factors and available water content of soil, which remains stable inside one ETWATCH pixel (1km). In this research, we used ETWATCH 1km ten-day actual ET product from April to October in a total of twenty-one images and monthly 30 meters cloud-free NDVI of 2013 (two images from HJ as a substitute due to cloud contamination) combined meteorological indicators for downscaling. A good agreement and correlation were obtained between the downscaled data and three flux sites observation in the middle reach of Heihe basin. The downscaling results show good consistency with the original ETWATCH 1km data both temporal and spatial scale over different land cover types with R2 ranged from 0.8 to 0.98. Besides, downscaled result captured the progression of vegetation transpiration well. This study proved the practicability of new downscaling method in the water resource management.

  5. Land-Surface-Atmosphere Coupling in Observations and Models

    Directory of Open Access Journals (Sweden)

    Alan K Betts

    2009-07-01

    Full Text Available The diurnal cycle and the daily mean at the land-surface result from the coupling of many physical processes. The framework of this review is largely conceptual; looking for relationships and information in the coupling of processes in models and observations. Starting from the surface energy balance, the role of the surface and cloud albedos in the shortwave and longwave fluxes is discussed. A long-wave radiative scaling of the diurnal temperature range and the night-time boundary layer is summarized. Several aspects of the local surface energy partition are presented: the role of soilwater availability and clouds; vector methods for understanding mixed layer evolution, and the coupling between surface and boundary layer that determines the lifting condensation level. Moving to larger scales, evaporation-precipitation feedback in models is discussed; and the coupling of column water vapor, clouds and precipitation to vertical motion and moisture convergence over the Amazon. The final topic is a comparison of the ratio of surface shortwave cloud forcing to the diabatic precipitation forcing of the atmosphere in ERA-40 with observations.

  6. Online Global Land Surface Temperature Estimation from Landsat

    Directory of Open Access Journals (Sweden)

    David Parastatidis

    2017-11-01

    Full Text Available This study explores the estimation of land surface temperature (LST for the globe from Landsat 5, 7 and 8 thermal infrared sensors, using different surface emissivity sources. A single channel algorithm is used for consistency among the estimated LST products, whereas the option of using emissivity from different sources provides flexibility for the algorithm’s implementation to any area of interest. The Google Earth Engine (GEE, an advanced earth science data and analysis platform, allows the estimation of LST products for the globe, covering the time period from 1984 to present. To evaluate the method, the estimated LST products were compared against two reference datasets: (a LST products derived from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer, as higher-level products based on the temperature-emissivity separation approach; (b Landsat LST data that have been independently produced, using different approaches. An overall RMSE (root mean square error of 1.52 °C was observed and it was confirmed that the accuracy of the LST product is dependent on the emissivity; different emissivity sources provided different LST accuracies, depending on the surface cover. The LST products, for the full Landsat 5, 7 and 8 archives, are estimated “on-the-fly” and are available on-line via a web application.

  7. Reliable low precision simulations in land surface models

    Science.gov (United States)

    Dawson, Andrew; Düben, Peter D.; MacLeod, David A.; Palmer, Tim N.

    2017-12-01

    Weather and climate models must continue to increase in both resolution and complexity in order that forecasts become more accurate and reliable. Moving to lower numerical precision may be an essential tool for coping with the demand for ever increasing model complexity in addition to increasing computing resources. However, there have been some concerns in the weather and climate modelling community over the suitability of lower precision for climate models, particularly for representing processes that change very slowly over long time-scales. These processes are difficult to represent using low precision due to time increments being systematically rounded to zero. Idealised simulations are used to demonstrate that a model of deep soil heat diffusion that fails when run in single precision can be modified to work correctly using low precision, by splitting up the model into a small higher precision part and a low precision part. This strategy retains the computational benefits of reduced precision whilst preserving accuracy. This same technique is also applied to a full complexity land surface model, resulting in rounding errors that are significantly smaller than initial condition and parameter uncertainties. Although lower precision will present some problems for the weather and climate modelling community, many of the problems can likely be overcome using a straightforward and physically motivated application of reduced precision.

  8. Effects of Seasonal Land Surface Conditions on Hydrometeorological Dynamics in South-western North America

    Science.gov (United States)

    2015-09-21

    rain gauges to measure precipitation , and 1 internal mini-flume to measure runoff . 9 Fig. 8. Processed fluxes measured at the two eddy...SECURITY CLASSIFICATION OF: Arid and semiarid landscapes in regions with seasonal precipitation experience dramatic changes that alter land surface...semiarid landscapes in regions with seasonal precipitation experience dramatic changes that alter land surface conditions, including soil moisture

  9. On Diffusive Climatological Models.

    Science.gov (United States)

    Griffel, D. H.; Drazin, P. G.

    1981-11-01

    A simple, zonally and annually averaged, energy-balance climatological model with diffusive heat transport and nonlinear albedo feedback is solved numerically. Some parameters of the model are varied, one by one, to find the resultant effects on the steady solution representing the climate. In particular, the outward radiation flux, the insulation distribution and the albedo parameterization are varied. We have found an accurate yet simple analytic expression for the mean annual insolation as a function of latitude and the obliquity of the Earth's rotation axis; this has enabled us to consider the effects of the oscillation of the obliquity. We have used a continuous albedo function which fits the observed values; it considerably reduces the sensitivity of the model. Climatic cycles, calculated by solving the time-dependent equation when parameters change slowly and periodically, are compared qualitatively with paleoclimatic records.

  10. Estonian total ozone climatology

    Directory of Open Access Journals (Sweden)

    K. Eerme

    Full Text Available The climatological characteristics of total ozone over Estonia based on the Total Ozone Mapping Spectrometer (TOMS data are discussed. The mean annual cycle during 1979–2000 for the site at 58.3° N and 26.5° E is compiled. The available ground-level data interpolated before TOMS, have been used for trend detection. During the last two decades, the quasi-biennial oscillation (QBO corrected systematic decrease of total ozone from February–April was 3 ± 2.6% per decade. Before 1980, a spring decrease was not detectable. No decreasing trend was found in either the late autumn ozone minimum or in the summer total ozone. The QBO related signal in the spring total ozone has an amplitude of ± 20 DU and phase lag of 20 months. Between 1987–1992, the lagged covariance between the Singapore wind and the studied total ozone was weak. The spring (April–May and summer (June–August total ozone have the best correlation (coefficient 0.7 in the yearly cycle. The correlation between the May and August total ozone is higher than the one between the other summer months. Seasonal power spectra of the total ozone variance show preferred periods with an over 95% significance level. Since 1986, during the winter/spring, the contribution period of 32 days prevails instead of the earlier dominating 26 days. The spectral densities of the periods from 4 days to 2 weeks exhibit high interannual variability.

    Key words. Atmospheric composition and structure (middle atmosphere – composition and chemistry; volcanic effects – Meteorology and atmospheric dynamics (climatology

  11. Downscaling Meteosat Land Surface Temperature over a Heterogeneous Landscape Using a Data Assimilation Approach

    Directory of Open Access Journals (Sweden)

    Rihab Mechri

    2016-07-01

    Full Text Available A wide range of environmental applications require the monitoring of land surface temperature (LST at frequent intervals and fine spatial resolutions, but these conditions are not offered nowadays by the available space sensors. To overcome these shortcomings, LST downscaling methods have been developed to derive higher resolution LST from the available satellite data. This research concerns the application of a data assimilation (DA downscaling approach, the genetic particle smoother (GPS, to disaggregate Meteosat 8 LST time series (3 km × 5 km at finer spatial resolutions. The methodology was applied over the Crau-Camargue region in Southeastern France for seven months in 2009. The evaluation of the downscaled LSTs has been performed at a moderate resolution using a set of coincident clear-sky MODIS LST images from Aqua and Terra platforms (1 km × 1 km and at a higher resolution using Landsat 7 data (60 m × 60 m. The performance of the downscaling has been assessed in terms of reduction of the biases and the root mean square errors (RMSE compared to prior model-simulated LSTs. The results showed that GPS allows downscaling the Meteosat LST product from 3 × 5 km2 to 1 × 1 km2 scales with a RMSE less than 2.7 K. Finer scale downscaling at Landsat 7 resolution showed larger errors (RMSE around 5 K explained by land cover errors and inter-calibration issues between sensors. Further methodology improvements are finally suggested.

  12. A critical assessment of the JULES land surface model hydrology for humid tropical environments

    Science.gov (United States)

    Zulkafli, Z.; Buytaert, W.; Onof, C.; Lavado, W.; Guyot, J. L.

    2013-03-01

    Global land surface models (LSMs) such as the Joint UK Land Environment Simulator (JULES) are originally developed to provide surface boundary conditions for climate models. They are increasingly used for hydrological simulation, for instance to simulate the impacts of land use changes and other perturbations on the water cycle. This study investigates how well such models represent the major hydrological fluxes at the relevant spatial and temporal scales - an important question for reliable model applications in poorly understood, data-scarce environments. The JULES-LSM is implemented in a 360 000 km2 humid tropical mountain basin of the Peruvian Andes-Amazon at 12-km grid resolution, forced with daily satellite and climate reanalysis data. The simulations are evaluated using conventional discharge-based evaluation methods, and by further comparing the magnitude and internal variability of the basin surface fluxes such as evapotranspiration, throughfall, and surface and subsurface runoff of the model with those observed in similar environments elsewhere. We find reasonably positive model efficiencies and high correlations between the simulated and observed streamflows, but high root-mean-square errors affecting the performance in smaller, upper sub-basins. We attribute this to errors in the water balance and JULES-LSM's inability to model baseflow. We also found a tendency to under-represent the high evapotranspiration rates of the region. We conclude that strategies to improve the representation of tropical systems to be (1) addressing errors in the forcing and (2) incorporating local wetland and regional floodplain in the subsurface representation.

  13. Landsat and Local Land Surface Temperatures in a Heterogeneous Terrain Compared to MODIS Values

    Directory of Open Access Journals (Sweden)

    Gemma Simó

    2016-10-01

    Full Text Available Land Surface Temperature (LST as provided by remote sensing onboard satellites is a key parameter for a number of applications in Earth System studies, such as numerical modelling or regional estimation of surface energy and water fluxes. In the case of Moderate Resolution Imaging Spectroradiometer (MODIS onboard Terra or Aqua, pixels have resolutions near 1 km 2 , LST values being an average of the real subpixel variability of LST, which can be significant for heterogeneous terrain. Here, we use Landsat 7 LST decametre-scale fields to evaluate the temporal and spatial variability at the kilometre scale and compare the resulting average values to those provided by MODIS for the same observation time, for the very heterogeneous Campus of the University of the Balearic Islands (Mallorca, Western Mediterranean, with an area of about 1 km 2 , for a period between 2014 and 2016. Variations of LST between 10 and 20 K are often found at the sub-kilometre scale. In addition, MODIS values are compared to the ground truth for one point in the Campus, as obtained from a four-component net radiometer, and a bias of 3.2 K was found in addition to a Root Mean Square Error (RMSE of 4.2 K. An indication of a more elaborated local measurement strategy in the Campus is given, using an array of radiometers distributed in the area.

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

    Science.gov (United States)

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

    2016-05-01

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

  15. Long term, non-anthropogenic groundwater storage changes simulated by a global land surface model

    Science.gov (United States)

    Li, B.; Rodell, M.; Sheffield, J.; Wood, E. F.

    2017-12-01

    Groundwater is crucial for meeting agricultural, industrial and municipal water needs, especially in arid, semi-arid and drought impacted regions. Yet, knowledge on groundwater response to climate variability is not well understood due to lack of systematic and continuous in situ measurements. In this study, we investigate global non-anthropogenic groundwater storage variations with a land surface model driven by a 67-year (1948-204) meteorological forcing data set. Model estimates were evaluated using in situ groundwater data from the central and northeastern U.S. and terrestrial water storage derived from the Gravity Recovery and Climate Experiment (GRACE) satellites and found to be reasonable. Empirical orthogonal function (EOF) analysis was employed to examine modes of variability of groundwater storage and their relationship with atmospheric effects such as precipitation and evapotranspiration. The result shows that the leading mode in global groundwater storage reflects the influence of the El Niño Southern Oscillation (ENSO). Consistent with the EOF analysis, global total groundwater storage reflected the low frequency variability of ENSO and decreased significantly over 1948-2014 while global ET and precipitation did not exhibit statistically significant trends. This study suggests that while precipitation and ET are the primary drivers of climate related groundwater variability, changes in other forcing fields than precipitation and temperature are also important because of their influence on ET. We discuss the need to improve model physics and to continuously validate model estimates and forcing data for future studies.

  16. Mapping the global depth to bedrock for land surface modelling

    Science.gov (United States)

    Shangguan, W.; Hengl, T.; Yuan, H.; Dai, Y. J.; Zhang, S.

    2017-12-01

    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. 130,000 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 surfacee reflectance bands and vegetation indices derived from the MODIS land products. Global spatial prediction models were developed using random forests and Gradient Boosting Tree algorithms. The final predictions were generated at the spatial resolution of 250m 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.

  17. Atmospheric teleconnection influence on North American land surface phenology

    Science.gov (United States)

    Dannenberg, Matthew P.; Wise, Erika K.; Janko, Mark; Hwang, Taehee; Kolby Smith, W.

    2018-03-01

    Short-term forecasts of vegetation activity are currently not well constrained due largely to our lack of understanding of coupled climate-vegetation dynamics mediated by complex interactions between atmospheric teleconnection patterns. Using ecoregion-scale estimates of North American vegetation activity inferred from remote sensing (1982-2015), we examined seasonal and spatial relationships between land surface phenology and the atmospheric components of five teleconnection patterns over the tropical Pacific, north Pacific, and north Atlantic. Using a set of regression experiments, we also tested for interactions among these teleconnection patterns and assessed predictability of vegetation activity solely based on knowledge of atmospheric teleconnection indices. Autumn-to-winter composites of the Southern Oscillation Index (SOI) were strongly correlated with start of growing season timing, especially in the Pacific Northwest. The two leading modes of north Pacific variability (the Pacific-North American, PNA, and West Pacific patterns) were significantly correlated with start of growing season timing across much of southern Canada and the upper Great Lakes. Regression models based on these Pacific teleconnections were skillful predictors of spring phenology across an east-west swath of temperate and boreal North America, between 40°N-60°N. While the North Atlantic Oscillation (NAO) was not strongly correlated with start of growing season timing on its own, we found compelling evidence of widespread NAO-SOI and NAO-PNA interaction effects. These results suggest that knowledge of atmospheric conditions over the Pacific and Atlantic Oceans increases the predictability of North American spring phenology. A more robust consideration of the complexity of the atmospheric circulation system, including interactions across multiple ocean basins, is an important step towards accurate forecasts of vegetation activity.

  18. Land surface cleanup of plutonium at the Nevada Test Site

    International Nuclear Information System (INIS)

    Ebeling, L.L.; Evans, R.B.; Walsh, E.J.

    1991-01-01

    The Nevada Test Site (NTS) covers approximately 3300 km 2 of high desert and is located approximately 100 km northwest of Las Vegas, Nevada. Soil contaminated by plutonium exists on the NTS and surrounding areas from safety tests conducted in the 1950s and 1960s. About 150 curies of contamination have been measured over 1200 hectares of land surface. Most contamination is found in the top 5 cm of soil but may be found as deep as 25 cm. The cost of conventional removal and disposal of the full soil volume has been estimated at over $500,000,000. This study is directed toward minimizing the volume of waste which must be further processed and disposed of by precisely controlling soil removal depth. The following soil removal machines were demonstrated at the NTS: (1) a CMI Corporation Model PR-500FL pavement profiler, (2) a CMI Corporation Model TR-225B trimmer reclaimer, (3) a Caterpillar Model 623 elevating scraper equipped with laser depth control, (4) a Caterpillar Model 14G motor grader equipped with laser depth control, (5) a Caterpillar Model 637 auger scraper, and (6) a XCR Series Guzzler vacuum truck. The most effective removal technique tested was the pavement profiler, which provided for dust control and precisely removed thin layers of soil. Soil removal with the motor grader and paddle scraper generated unacceptable dust levels, even after the soil was extensively watered. The vacuum truck was ineffective because of its limited intake volume which is a function of its small intake size, its weak intake force, and the tendency of its filters to clog

  19. The Global Precipitation Climatology Project (GPCP) Combined Precipitation Dataset

    Science.gov (United States)

    Huffman, George J.; Adler, Robert F.; Arkin, Philip; Chang, Alfred; Ferraro, Ralph; Gruber, Arnold; Janowiak, John; McNab, Alan; Rudolf, Bruno; Schneider, Udo

    1997-01-01

    The Global Precipitation Climatology Project (GPCP) has released the GPCP Version 1 Combined Precipitation Data Set, a global, monthly precipitation dataset covering the period July 1987 through December 1995. The primary product in the dataset is a merged analysis incorporating precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit -satellite infrared data, and rain gauge observations. The dataset also contains the individual input fields, a combination of the microwave and infrared satellite estimates, and error estimates for each field. The data are provided on 2.5 deg x 2.5 deg latitude-longitude global grids. Preliminary analyses show general agreement with prior studies of global precipitation and extends prior studies of El Nino-Southern Oscillation precipitation patterns. At the regional scale there are systematic differences with standard climatologies.

  20. Reconnoitering the effect of shallow groundwater on land surface temperature and surface energy balance using MODIS and SEBS

    Directory of Open Access Journals (Sweden)

    F. Alkhaier

    2012-07-01

    Full Text Available The possibility of observing shallow groundwater depth and areal extent using satellite measurements can support groundwater models and vast irrigation systems management. Moreover, these measurements can help to include the effect of shallow groundwater on surface energy balance within land surface models and climate studies, which broadens the methods that yield more reliable and informative results. To examine the capacity of MODIS in detecting the effect of shallow groundwater on land surface temperature and the surface energy balance in an area within Al-Balikh River basin in northern Syria, we studied the interrelationship between in-situ measured water table depths and land surface temperatures measured by MODIS. We, also, used the Surface Energy Balance System (SEBS to calculate surface energy fluxes, evaporative fraction and daily evaporation, and inspected their relationships with water table depths. We found out that the daytime temperature increased while the nighttime temperature decreased when the depth of the water table increased. And, when the water table depth increased, net radiation, latent and ground heat fluxes, evaporative fraction and daily evaporation decreased, while sensible heat flux increased. This concords with the findings of a companion paper (Alkhaier et al., 2012. The observed clear relationships were the result of meeting both conditions that were concluded in the companion paper, i.e. high potential evaporation and big contrast in day-night temperature. Moreover, the prevailing conditions in this study area helped SEBS to yield accurate estimates. Under bare soil conditions and under the prevailing weather conditions, we conclude that MODIS is suitable for detecting the effect of shallow groundwater because it has proper imaging times and adequate sensor accuracy; nevertheless, its coarse spatial resolution is disadvantageous.

  1. The Morphology, Dynamics and Potential Hotspots of Land Surface Temperature at a Local Scale in Urban Areas

    Directory of Open Access Journals (Sweden)

    Jiong Wang

    2015-12-01

    Full Text Available Current characterization of the Urban Heat Island (UHI remains insufficient to support the effective mitigation and adaptation of increasing temperatures in urban areas. Planning and design strategies are restricted to the investigation of temperature anomalies at a city scale. By focusing on Land Surface Temperature of Wuhan, China, this research examines the temperature variations locally where mitigation and adaptation would be more feasible. It shows how local temperature anomalies can be identified morphologically. Technically, the MODerate-resolution Imaging Spectroradiometer satellite image products are used. They are first considered as noisy observations of the latent temperature patterns. The continuous latent patterns of the temperature are then recovered from these discrete observations by using the non-parametric Multi-Task Gaussian Process Modeling. The Multi-Scale Shape Index is then applied in the area of focus to extract the local morphological features. A triplet of shape, curvedness and temperature is formed as the criteria to extract local heat islands. The behavior of the local heat islands can thus be quantified morphologically. The places with critical deformations are identified as hotpots. The hotspots with certain yearly behavior are further associated with land surface composition to determine effective mitigation and adaptation strategies. This research can assist in the temperature and planning field on two levels: (1 the local land surface temperature patterns are characterized by decomposing the variations into fundamental deformation modes to allow a process-based understanding of the dynamics; and (2 the characterization at local scale conforms to planning and design conventions where mitigation and adaptation strategies are supposed to be more practical. The weaknesses and limitations of the study are addressed in the closing section.

  2. Effect of land model ensemble versus coupled model ensemble on the simulation of precipitation climatology and variability

    Science.gov (United States)

    Wei, Jiangfeng; Dirmeyer, Paul A.; Yang, Zong-Liang; Chen, Haishan

    2017-10-01

    Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.

  3. Black Sea impact on its west-coast land surface temperature

    Science.gov (United States)

    Cheval, Sorin; Constantin, Sorin

    2018-03-01

    This study investigates the Black Sea influence on the thermal characteristics of its western hinterland based on satellite imagery acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS). The marine impact on the land surface temperature (LST) values is detected at daily, seasonal and annual time scales, and a strong linkage with the land cover is demonstrated. The remote sensing products used within the study supply LST data with complete areal coverage during clear sky conditions at 1-km spatial resolution, which is appropriate for climate studies. The sea influence is significant up to 4-5 km, by daytime, while the nighttime influence is very strong in the first 1-2 km, and it gradually decreases westward. Excepting the winter, the daytime temperature increases towards the plateau with the distance from the sea, e.g. with a gradient of 0.9 °C/km in the first 5 km in spring or with 0.7 °C/km in summer. By nighttime, the sea water usually remains warmer than the contiguous land triggering higher LST values in the immediate proximity of the coastline in all seasons, e.g. mean summer LST is 19.0 °C for the 1-km buffer, 16.6 °C for the 5-km buffer and 16.0 °C for the 10-km buffer. The results confirm a strong relationship between the land cover and thermal regime in the western hinterland of the Black Sea coast. The satellite-derived LST and air temperature values recorded at the meteorological stations are highly correlated for similar locations, but the marine influence propagates differently, pledging for distinct analysis. Identified anomalies in the general observed trends are investigated in correlation with sea surface temperature dynamics in the coastal area.

  4. Cloud Tolerance of Remote-Sensing Technologies to Measure Land Surface Temperature

    Science.gov (United States)

    Holmes, Thomas R. H.; Hain, Christopher R.; Anderson, Martha C.; Crow, Wade T.

    2016-01-01

    Conventional methods to estimate land surface temperature (LST) from space rely on the thermal infrared(TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave(MW) observations. The MW-LST product is informed by six polar-orbiting satellites to create a global record with up to eight observations per day for each 0.25resolution grid box. For days with sufficient observations, a continuous diurnal temperature cycle (DTC) was fitted. The main characteristics of the DTC were scaled to match those of a geostationary TIR-LST product. This paper tests the cloud tolerance of the MW-LST product. In particular, we demonstrate its stable performance with respect to flux tower observation sites (four in Europe and nine in the United States), over a range of cloudiness conditions up to heavily overcast skies. The results show that TIR based LST has slightly better performance than MW-LST for clear-sky observations but suffers an increasing negative bias as cloud cover increases. This negative bias is caused by incomplete masking of cloud-covered areas within the TIR scene that affects many applications of TIR-LST. In contrast, for MW-LST we find no direct impact of clouds on its accuracy and bias. MW-LST can therefore be used to improve TIR cloud screening. Moreover, the ability to provide LST estimates for cloud-covered surfaces can help expand current clear-sky-only satellite retrieval products to all-weather applications.

  5. On the sensitivity of Land Surface Temperature estimates in arid irrigated lands using MODTRAN

    KAUST Repository

    Rosas, Jorge

    2015-11-29

    Land surface temperature (LST) derived from thermal infrared (TIR) satellite data has been reliably used as a remote indicator of evapotranspiration (ET) and surface moisture status. However, in order to retrieve the ET with an accuracy approaching 10%, LST should be retrieved to within 1 ◦C or better, disregarding other elements of uncertainty. The removal of atmospheric effects is key towards achieving a precise estimation of LST and it requires detailed information on water vapor. The Thermal Infrared Sensor (TIRS) onboard Landsat 8 captures data in two long wave thermal bands with 100-meter resolution. However, the US Geological Survey has reported a calibration problem of TIRS bands caused by stray light, resulting in a higher bias in one of its two bands (4% in band 11, 2% in band 10). Therefore, split-window algorithms for the estimation of LST might not be reliable. Our work will focus on the impact of using different atmospheric profiles (e.g. weather prediction models, satellite) for the estimation of LST derived from MODTRAN by using one of the TIRS bands onboard Landsat 8 (band 10). Sites with in-situ measurements of LST are used as evaluation sources. Comparisons between the measured LST and LST derived based on different atmospheric profile inputs to MODTRAN are carried out from 2 Landsat-overpass days (DOY 153 and 160 2015). Preliminary results show a mean absolute error of around 3 ◦C between in-situ and estimated LST over two different crops (alfalfa and carrot) and bare soil.

  6. Study of land surface temperature and spectral emissivity using multi ...

    Indian Academy of Sciences (India)

    tral emissivities over a hard rock terrain using multi-sensor satellite data. The study area, of .... Georeferenced MODIS level 1B data (bands 31 and. 32) and Landsat ETM+ data .... the optical properties of the atmosphere. In the present study ...

  7. Seasonal evaluation of the land surface scheme HTESSEL against remote sensing derived energy fluxes of the Transdanubian region in Hungary

    Directory of Open Access Journals (Sweden)

    E. L. Wipfler

    2011-04-01

    Full Text Available The skill of the land surface model HTESSEL is assessed to reproduce evaporation in response to land surface characteristics and atmospheric forcing, both being spatially variable. Evaporation estimates for the 2005 growing season are inferred from satellite observations of the Western part of Hungary and compared to model outcomes. Atmospheric forcings are obtained from a hindcast run with the Regional Climate Model RACMO2. Although HTESSEL slightly underpredicts the seasonal evaporative fraction as compared to satellite estimates, the mean, 10th and 90th percentile of this variable are of the same magnitude as the satellite observations. The initial water as stored in the soil and snow layer does not have a significant effect on the statistical properties of the evaporative fraction. However, the spatial distribution of the initial soil and snow water significantly affects the spatial distribution of the calculated evaporative fraction and the models ability to reproduce evaporation correctly in low precipitation areas in the considered region. HTESSEL performs weaker in dryer areas. In Western Hungary these areas are situated in the Danube valley, which is partly covered by irrigated cropland and which also may be affected by shallow groundwater. Incorporating (lateral groundwater flow and irrigation, processes that are not included now, may improve HTESSELs ability to predict evaporation correctly. Evaluation of the model skills using other test areas and larger evaluation periods is needed to confirm the results.

    Based on earlier sensitivity analysis, the effect of a number of modifications to HTESSEL has been assessed. A more physically based reduction function for dry soils has been introduced, the soil depth is made variable and the effect of swallow groundwater included. However, the combined modification does not lead to a significantly improved performance of HTESSEL.

  8. Land Surface Microwave Emissivities Derived from AMSR-E and MODIS Measurements with Advanced Quality Control

    Science.gov (United States)

    Moncet, Jean-Luc; Liang, Pan; Galantowicz, John F.; Lipton, Alan E.; Uymin, Gennady; Prigent, Catherine; Grassotti, Christopher

    2011-01-01

    A microwave emissivity database has been developed with data from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and with ancillary land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same Aqua spacecraft. The primary intended application of the database is to provide surface emissivity constraints in atmospheric and surface property retrieval or assimilation. An additional application is to serve as a dynamic indicator of land surface properties relevant to climate change monitoring. The precision of the emissivity data is estimated to be significantly better than in prior databases from other sensors due to the precise collocation with high-quality MODIS LST data and due to the quality control features of our data analysis system. The accuracy of the emissivities in deserts and semi-arid regions is enhanced by applying, in those regions, a version of the emissivity retrieval algorithm that accounts for the penetration of microwave radiation through dry soil with diurnally varying vertical temperature gradients. These results suggest that this penetration effect is more widespread and more significant to interpretation of passive microwave measurements than had been previously established. Emissivity coverage in areas where persistent cloudiness interferes with the availability of MODIS LST data is achieved using a classification-based method to spread emissivity data from less-cloudy areas that have similar microwave surface properties. Evaluations and analyses of the emissivity products over homogeneous snow-free areas are presented, including application to retrieval of soil temperature profiles. Spatial inhomogeneities are the largest in the vicinity of large water bodies due to the large water/land emissivity contrast and give rise to large apparent temporal variability in the retrieved emissivities when satellite footprint locations vary over time. This issue will be dealt with in the future by

  9. A One-Source Approach for Estimating Land Surface Heat Fluxes Using Remotely Sensed Land Surface Temperature

    Directory of Open Access Journals (Sweden)

    Yongmin Yang

    2017-01-01

    Full Text Available The partitioning of available energy between sensible heat and latent heat is important for precise water resources planning and management in the context of global climate change. Land surface temperature (LST is a key variable in energy balance process and remotely sensed LST is widely used for estimating surface heat fluxes at regional scale. However, the inequality between LST and aerodynamic surface temperature (Taero poses a great challenge for regional heat fluxes estimation in one-source energy balance models. To address this issue, we proposed a One-Source Model for Land (OSML to estimate regional surface heat fluxes without requirements for empirical extra resistance, roughness parameterization and wind velocity. The proposed OSML employs both conceptual VFC/LST trapezoid model and the electrical analog formula of sensible heat flux (H to analytically estimate the radiometric-convective resistance (rae via a quartic equation. To evaluate the performance of OSML, the model was applied to the Soil Moisture-Atmosphere Coupling Experiment (SMACEX in United States and the Multi-Scale Observation Experiment on Evapotranspiration (MUSOEXE in China, using remotely sensed retrievals as auxiliary data sets at regional scale. Validated against tower-based surface fluxes observations, the root mean square deviation (RMSD of H and latent heat flux (LE from OSML are 34.5 W/m2 and 46.5 W/m2 at SMACEX site and 50.1 W/m2 and 67.0 W/m2 at MUSOEXE site. The performance of OSML is very comparable to other published studies. In addition, the proposed OSML model demonstrates similar skills of predicting surface heat fluxes in comparison to SEBS (Surface Energy Balance System. Since OSML does not require specification of aerodynamic surface characteristics, roughness parameterization and meteorological conditions with high spatial variation such as wind speed, this proposed method shows high potential for routinely acquisition of latent heat flux estimation

  10. High Resolution Land Surface Modeling over the NEF Basin in the Chilean Patagonia

    Science.gov (United States)

    Somos-Valenzuela, M. A.

    2017-12-01

    Stakeholders and policy makers perceive that water and climate change adaptation are among the most vulnerable issues that need to be addressed. Therefore, there is a need not only from the scientific community but also from the society to use integrated methodologies that link advances in climatology with hydrology to provide data that helps us to provide adaptation strategies. The Andes and the Chilean-Argentinean Patagonia have been steadily warming up to 0.5 Celsius degrees per decades at the same time that precipitation is decreasing by 10 to 12 % per decade. In the future is expected that these trends will continue which will have impacts in the annual water budget. The Chilean Patagonia has brought a lot of attention during last decade because two hydroelectric project seek to build dams in one of the most pristine environments in the world. Also, in the Baker River basin a series of Glacier Lakes Outburst Flood have occurred which is perceived as an undeniable consequence of the effects of climate change in the glacier system. Major attention is mainly situated in the impact of climate change in glaciers contribution to sea level rise, GLOF studies given the numerous supra glacier lakes that are forming, and the study of stream flow point observation. The objectives of this research are: 1) Study the historical trends of precipitation, temperature, land cover changes and streamflow available in the Baker Basin; 2) Use a couple glacier model with a land surface model to predict the evolution of glaciers and their effects in the water availability. To address these objectives, I will analyze trends in hydro meteorology observations and correlation with trends in Land Cover Changes. Use the WRF-hydro framework to generate data in a small watershed that will allow to calibrate a high resolution hydro glaciology model to understand the partition between glaciered and non-glaciered runoff. The parameters estimated in the small domain could have the potential to

  11. Comparison of land surface humidity between observations and CMIP5 models

    Science.gov (United States)

    Dunn, Robert J. H.; Willett, Kate M.; Ciavarella, Andrew; Stott, Peter A.

    2017-08-01

    We compare the latest observational land surface humidity dataset, HadISDH, with the latest generation of climate models extracted from the CMIP5 archive and the ERA-Interim reanalysis over the period 1973 to present. The globally averaged behaviour of HadISDH and ERA-Interim are very similar in both humidity measures and air temperature, on decadal and interannual timescales. The global average relative humidity shows a gradual increase from 1973 to 2000, followed by a steep decline in recent years. The observed specific humidity shows a steady increase in the global average during the early period but in the later period it remains approximately constant. None of the CMIP5 models or experiments capture the observed behaviour of the relative or specific humidity over the entire study period. When using an atmosphere-only model, driven by observed sea surface temperatures and radiative forcing changes, the behaviour of regional average temperature and specific humidity are better captured, but there is little improvement in the relative humidity. Comparing the observed climatologies with those from historical model runs shows that the models are generally cooler everywhere, are drier and less saturated in the tropics and extra-tropics, and have comparable moisture levels but are more saturated in the high latitudes. The spatial pattern of linear trends is relatively similar between the models and HadISDH for temperature and specific humidity, but there are large differences for relative humidity, with less moistening shown in the models over the tropics and very little at high latitudes. The observed drying in mid-latitudes is present at a much lower magnitude in the CMIP5 models. Relationships between temperature and humidity anomalies (T-q and T-rh) show good agreement for specific humidity between models and observations, and between the models themselves, but much poorer for relative humidity. The T-q correlation from the models is more steeply positive than

  12. Detection of open water dynamics with ENVISAT ASAR in support of land surface modelling at high latitudes

    Directory of Open Access Journals (Sweden)

    A. Bartsch

    2012-02-01

    Full Text Available Wetlands are generally accepted as being the largest but least well quantified single source of methane (CH4. The extent of wetland or inundation is a key factor controlling methane emissions, both in nature and in the parameterisations used in large-scale land surface and climate models. Satellite-derived datasets of wetland extent are available on the global scale, but the resolution is rather coarse (>25 km. The purpose of the present study is to assess the capability of active microwave sensors to derive inundation dynamics for use in land surface and climate models of the boreal and tundra environments. The focus is on synthetic aperture radar (SAR operating in C-band since, among microwave systems, it has comparably high spatial resolution and data availability, and long-term continuity is expected.

    C-band data from ENVISAT ASAR (Advanced SAR operating in wide swath mode (150 m resolution were investigated and an automated detection procedure for deriving open water fraction has been developed. More than 4000 samples (single acquisitions tiled onto 0.5° grid cells have been analysed for July and August in 2007 and 2008 for a study region in Western Siberia. Simple classification algorithms were applied and found to be robust when the water surface was smooth. Modification of input parameters results in differences below 1 % open water fraction. The major issue to address was the frequent occurrence of waves due to wind and precipitation, which reduces the separability of the water class from other land cover classes. Statistical measures of the backscatter distribution were applied in order to retrieve suitable classification data. The Pearson correlation between each sample dataset and a location specific representation of the bimodal distribution was used. On average only 40 % of acquisitions allow a separation of the open water class. Although satellite data are available every 2–3 days over the Western Siberian

  13. Challenges and opportunities in land surface modelling of savanna ecosystems

    Directory of Open Access Journals (Sweden)

    R. Whitley

    2017-10-01

    Full Text Available The savanna complex is a highly diverse global biome that occurs within the seasonally dry tropical to sub-tropical equatorial latitudes and are structurally and functionally distinct from grasslands and forests. Savannas are open-canopy environments that encompass a broad demographic continuum, often characterised by a changing dominance between C3-tree and C4-grass vegetation, where frequent environmental disturbances such as fire modulates the balance between ephemeral and perennial life forms. Climate change is projected to result in significant changes to the savanna floristic structure, with increases to woody biomass expected through CO2 fertilisation in mesic savannas and increased tree mortality expected through increased rainfall interannual variability in xeric savannas. The complex interaction between vegetation and climate that occurs in savannas has traditionally challenged terrestrial biosphere models (TBMs, which aim to simulate the interaction between the atmosphere and the land surface to predict responses of vegetation to changing in environmental forcing. In this review, we examine whether TBMs are able to adequately represent savanna fluxes and what implications potential deficiencies may have for climate change projection scenarios that rely on these models. We start by highlighting the defining characteristic traits and behaviours of savannas, how these differ across continents and how this information is (or is not represented in the structural framework of many TBMs. We highlight three dynamic processes that we believe directly affect the water use and productivity of the savanna system: phenology, root-water access and fire dynamics. Following this, we discuss how these processes are represented in many current-generation TBMs and whether they are suitable for simulating savanna fluxes.Finally, we give an overview of how eddy-covariance observations in combination with other data sources can be used in model

  14. Recent trends (2003-2013) of land surface heat fluxes on the southern side of the central Himalayas, Nepal

    Science.gov (United States)

    Amatya, Pukar Man; Ma, Yaoming; Han, Cunbo; Wang, Binbin; Devkota, Lochan Prasad

    2015-12-01

    Novice efforts have been made in order to study the regional distribution of land surface heat fluxes on the southern side of the central Himalayas utilizing high-resolution remotely sensed products, but these have been on instantaneous scale. In this study the Surface Energy Balance System model is used to obtain annual averaged maps of the land surface heat fluxes for 11 years (2003-2013) and study their annual trends on the central Himalayan region. The maps were derived at 5 km resolution using monthly input products ranging from satellite derived to Global Land Data Assimilation System meteorological data. It was found that the net radiation flux is increasing as a result of decreasing precipitation (drier environment). The sensible heat flux did not change much except for the northwestern High Himalaya and High Mountains. In northwestern High Himalaya sensible heat flux is decreasing because of decrease in wind speed, ground-air temperature difference, and increase in winter precipitation, whereas in High Mountains it is increasing due to increase in ground-air temperature difference and high rate of deforestation. The latent heat flux has an overall increasing trend with increase more pronounced in the lower regions compared to high elevated regions. It has been reported that precipitation is decreasing with altitude in this region. Therefore, the increasing trend in latent heat flux can be attributed to increase in net radiation flux under persistent forest cover and irrigation land used for agriculture.

  15. THE EFFECTS OF BUILT-UP AND GREEN AREAS ON THE LAND SURFACE TEMPERATURE OF THE KUALA LUMPUR CITY

    Directory of Open Access Journals (Sweden)

    N. A. Isa

    2017-10-01

    Full Text Available A common consequence of rapid and uncontrollable urbanization is Urban Heat Island (UHI. It occurs due to the negligence on climate behaviour which degrades the quality of urban climate condition. Recently, addressing urban climate in urban planning through mapping has received worldwide attention. Therefore, the need to identify the significant factors is a must. This study aims to analyse the relationships between Land Surface Temperature (LST and two urban parameters namely built-up and green areas. Geographical Information System (GIS and remote sensing techniques were used to prepare the necessary data layers required for this study. The built-up and the green areas were extracted from Landsat 8 satellite images either using the Normalized Difference Built-Up Index (NDBI, Normalized Difference Vegetation Index (NDVI or Modified Normalize Difference Water Index (MNDWI algorithms, while the mono-window algorithm was used to retrieve the Land Surface Temperature (LST. Correlation analysis and Multi-Linear Regression (MLR model were applied to quantitatively analyse the effects of the urban parameters. From the study, it was found that the two urban parameters have significant effects on the LST of Kuala Lumpur City. The built-up areas have greater influence on the LST as compared to the green areas. The built-up areas tend to increase the LST while green areas especially the densely vegetated areas help to reduce the LST within an urban areas. Future studies should focus on improving existing urban climatic model by including other urban parameters.

  16. An Improved Single-Channel Method to Retrieve Land Surface Temperature from the Landsat-8 Thermal Band

    Directory of Open Access Journals (Sweden)

    Jordi Cristóbal

    2018-03-01

    Full Text Available Land surface temperature (LST is one of the sources of input data for modeling land surface processes. The Landsat satellite series is the only operational mission with more than 30 years of archived thermal infrared imagery from which we can retrieve LST. Unfortunately, stray light artifacts were observed in Landsat-8 TIRS data, mostly affecting Band 11, currently making the split-window technique impractical for retrieving surface temperature without requiring atmospheric data. In this study, a single-channel methodology to retrieve surface temperature from Landsat TM and ETM+ was improved to retrieve LST from Landsat-8 TIRS Band 10 using near-surface air temperature (Ta and integrated atmospheric column water vapor (w as input data. This improved methodology was parameterized and successfully evaluated with simulated data from a global and robust radiosonde database and validated with in situ data from four flux tower sites under different types of vegetation and snow cover in 44 Landsat-8 scenes. Evaluation results using simulated data showed that the inclusion of Ta together with w within a single-channel scheme improves LST retrieval, yielding lower errors and less bias than models based only on w. The new proposed LST retrieval model, developed with both w and Ta, yielded overall errors on the order of 1 K and a bias of −0.5 K validated against in situ data, providing a better performance than other models parameterized using w and Ta or only w models that yielded higher error and bias.

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

    Science.gov (United States)

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

    2018-06-01

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

  18. A Method for Retrieving Daily Land Surface Albedo from Space at 30-m Resolution

    Directory of Open Access Journals (Sweden)

    Bo Gao

    2015-08-01

    Full Text Available Land surface albedo data with high spatio-temporal resolution are increasingly important for scientific studies addressing spatially and/or temporally small-scale phenomena, such as urban heat islands and urban land surface energy balance. Our previous study derived albedo data with 2–4-day and 30-m temporal and spatial resolution that have better spatio-temporal resolution than existing albedo data, but do not completely satisfy the requirements for monitoring high-frequency land surface changes at the small scale. Downscaling technology provides a chance to further improve the albedo data spatio-temporal resolution and accuracy. This paper introduces a method that combines downscaling technology for land surface reflectance with an empirical method of deriving land surface albedo. Firstly, downscaling daily MODIS land surface reflectance data (MOD09GA from 500 m to 30 m on the basis of HJ-1A/B BRDF data with 2–4-day and 30-m temporal and spatial resolution is performed: this is the key step in the improved method. Subsequently, the daily 30-m land surface albedo data are derived by an empirical method combining prior knowledge of the MODIS BRDF product and the downscaled daily 30-m reflectance. Validation of albedo data obtained using the proposed method shows that the new method has both improved spatio-temporal resolution and good accuracy (a total absolute accuracy of 0.022 and a total root mean squared error at six sites of 0.028.

  19. Advances in tourism climatology

    Energy Technology Data Exchange (ETDEWEB)

    Matzarakis, A.; Freitas, C.R. de; Scott, D. (eds.)

    2004-11-01

    This publication grew out of the Second International Workshop of the International Society of Biometeorology, Commission on Climate Tourism and Recreation (ISB-CCTR) that took place at the Orthodox Academy of Crete in Kolimbari, Greece, 8-11 June 2004. The aim of the meeting was to (a) bring together a selection of researchers and tourism experts to review the current state of knowledge of tourism and recreation climatology and (b) explore possibilities for future research and the role of the ISB-CCTR in this. A total of 40 delegates attended the June 2004 ISB-CCTR Workshop. Their fields of expertise included biometeorology, bioclimatology, thermal comfort and heat balance modelling, tourism marketing and planning, urban and landscape planning, architecture, climate change, emission reduction and climate change impact assessment. Participants came from universities and research institutions in Australia, Austria, Canada, Croatia, France, Germany, Greece, Hungary, Italy, the Netherlands, New Zealand, Portugal, Slovenia, United Kingdom and United States of America. Business conducted at the Workshop was divided between five sessions: assessment of climatic resources; climate change; health; weather, sports and risk forecasts; and behaviour and perception. However, the content of this publication is organised so that it reflects the new perspectives and methods that have evolved since the ISB-CCTR was established. (orig.)

  20. Global Synoptic Climatology Network (GSCN)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Dataset DSI-9290 is the result of a joint effort to create a Global Synoptic Climatology Network among the Meteorological Service of Canada (Downsview, Ontario and...

  1. Local Climatological Data (LCD) Publication

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Local Climatological Data (LCD) contains summaries from major airport weather stations that include a daily account of temperature extremes, degree days,...

  2. Temperature sensitivity to the land-surface model in MM5 climate simulations over the Iberian Peninsula

    Energy Technology Data Exchange (ETDEWEB)

    Jerez, Sonia; Montavez, Juan P.; Gomez-Navarro, Juan J.; Jimenez-Guerrero, Pedro [Dept. de Fisica, Univ. de Murcia (Spain); Jimenez, Jose M.; Gonzalez-Rouco, Jesus F. [Dept. de Astrofisica y CC. de la Atmosfera, Univ. Complutense de Madrid (Spain)

    2010-06-15

    Three different Land Surface Models have been used in three high resolution climate simulations performed with the mesoscale model MM5 over the Iberian Peninsula. The main difference among them lies in the soil moisture treatment, which is dynamically modelled by only two of them (Noah and Pleim and Xiu models), while in the simplest model (Simple Five-Layers) it is fixed to climatological values. The simulated period covers 1958-2002, using the ERA40 reanalysis data as driving conditions. Focusing on near-surface air temperature, this work evaluates the skill of each simulation in reproducing mean values and temporal variability, by comparing the simulations with observed temperature series. When the simplest simulation was analyzed, the greatest discrepances were observed for the summer season, when both, the mean values and the temporal variability of the temperature series, were badly underestimated. These weaknesses are largely overcome in the other two simulations (performed by coupling a more advanced soil model to MM5), and there was greater concordance between the simulated and observed spatial patterns. The influence of a dynamic soil moisture parameterization and, therefore, a more realistic simulation of the latent and sensible heat fluxes between the land and the atmosphere, helps to explain these results. (orig.)

  3. Towards a public, standardized, diagnostic benchmarking system for land surface models

    Directory of Open Access Journals (Sweden)

    G. Abramowitz

    2012-06-01

    Full Text Available This work examines different conceptions of land surface model benchmarking and the importance of internationally standardized evaluation experiments that specify data sets, variables, metrics and model resolutions. It additionally demonstrates how essential the definition of a priori expectations of model performance can be, based on the complexity of a model and the amount of information being provided to it, and gives an example of how these expectations might be quantified. Finally, the Protocol for the Analysis of Land Surface models (PALS is introduced – a free, online land surface model benchmarking application that is structured to meet both of these goals.

  4. Assessing the influence of groundwater and land surface scheme in the modelling of land surface-atmosphere feedbacks over the FIFE area in Kansas, USA

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl; Højmark Rasmussen, Søren; Drews, Martin

    2016-01-01

    The land surface-atmosphere interaction is described differently in large scale surface schemes of regional climate models and small scale spatially distributed hydrological models. In particular, the hydrological models include the influence of shallow groundwater on evapotranspiration during dry...... by HIRHAM simulated precipitation. The last two simulations include iv) a standard HIRHAM simulation, and v) a fully coupled HIRHAM-MIKE SHE simulation locally replacing the land surface scheme by MIKE SHE for the FIFE area, while HIRHAM in standard configuration is used for the remaining model area...

  5. NLDAS Noah Land Surface Model L4 Hourly 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation...

  6. MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day (MYD21A1D.006). A new suite of MODIS Land Surface Temperature (LST) and...

  7. MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night (MOD21A1N.006). A new suite of MODIS Land Surface Temperature (LST) and...

  8. MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Aqua Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Night (MYD21A1N.006). A new suite of MODIS Land Surface Temperature (LST) and...

  9. MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Terra Land Surface Temperature/3-Band Emissivity Daily L3 Global 1km SIN Grid Day (MOD21A1D.006). A new suite of MODIS Land Surface Temperature (LST) and...

  10. NLDAS Noah Land Surface Model L4 Monthly 0.125 x 0.125 degree V002

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation...

  11. Evaluation of MODIS Land Surface Temperature with In Situ Snow Surface Temperature from CREST-SAFE

    Science.gov (United States)

    Perez Diaz, C. L.; Lakhankar, T.; Romanov, P.; Munoz, J.; Khanbilvardi, R.; Yu, Y.

    2016-12-01

    This paper presents the procedure and results of a temperature-based validation approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) product provided by the National Aeronautics and Space Administration (NASA) Terra and Aqua Earth Observing System satellites using in situ LST observations recorded at the Cooperative Remote Sensing Science and Technology Center - Snow Analysis and Field Experiment (CREST-SAFE) during the years of 2013 (January-April) and 2014 (February-April). A total of 314 day and night clear-sky thermal images, acquired by the Terra and Aqua satellites, were processed and compared to ground-truth data from CREST-SAFE with a frequency of one measurement every 3 min. Additionally, this investigation incorporated supplementary analyses using meteorological CREST-SAFE in situ variables (i.e. wind speed, cloud cover, incoming solar radiation) to study their effects on in situ snow surface temperature (T-skin) and T-air. Furthermore, a single pixel (1km2) and several spatially averaged pixels were used for satellite LST validation by increasing the MODIS window size to 5x5, 9x9, and 25x25 windows for comparison. Several trends in the MODIS LST data were observed, including the underestimation of daytime values and nighttime values. Results indicate that, although all the data sets (Terra and Aqua, diurnal and nocturnal) showed high correlation with ground measurements, day values yielded slightly higher accuracy ( 1°C), both suggesting that MODIS LST retrievals are reliable for similar land cover classes and atmospheric conditions. Results from the CREST-SAFE in situ variables' analyses indicate that T-air is commonly higher than T-skin, and that a lack of cloud cover results in: lower T-skin and higher T-air minus T-skin difference (T-diff). Additionally, the study revealed that T-diff is inversely proportional to cloud cover, wind speed, and incoming solar radiation. Increasing the MODIS window size

  12. Frost Monitoring and Forecasting Using MODIS Land Surface Temperature Data and a Numerical Weather Prediction Model Forecasts for Eastern Africa

    Science.gov (United States)

    Kabuchanga, Eric; Flores, Africa; Malaso, Susan; Mungai, John; Sakwa, Vincent; Shaka, Ayub; Limaye, Ashutosh

    2014-01-01

    Frost is a major challenge across Eastern Africa, severely impacting agricultural farms. Frost damages have wide ranging economic implications on tea and coffee farms, which represent a major economic sector. Early monitoring and forecasting will enable farmers to take preventive actions to minimize the losses. Although clearly important, timely information on when to protect crops from freezing is relatively limited. MODIS Land Surface Temperature (LST) data, derived from NASA's Terra and Aqua satellites, and 72-hr weather forecasts from the Kenya Meteorological Service's operational Weather Research Forecast model are enabling the Regional Center for Mapping of Resources for Development (RCMRD) and the Tea Research Foundation of Kenya to provide timely information to farmers in the region. This presentation will highlight an ongoing collaboration among the Kenya Meteorological Service, RCMRD, and the Tea Research Foundation of Kenya to identify frost events and provide farmers with potential frost forecasts in Eastern Africa.

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

    Science.gov (United States)

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

    2016-04-01

    The interactions between land surface and climate are complex. Climate changes can affect ecosystem structure and functions, by altering photosynthesis and productivity or inducing thermal and hydric stresses on plant species. These changes then impact socio-economic systems, through e.g., lower farming or forestry incomes. Ultimately, it can lead to permanent changes in land use structure, especially when associated with other non-climatic factors, such as urbanization pressure. These interactions and changes have feedbacks on the climate systems, in terms of changing: (1) surface properties (albedo, roughness, evapotranspiration, etc.) and (2) greenhouse gas emissions (mainly CO2, CH4, N2O). In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), we aim at improving regional climate model projections at the decennial scale over Belgium and Western Europe by combining high-resolution models of climate, land surface dynamics and socio-economic processes. The land surface dynamics (LSD) module is composed of a dynamic vegetation model (CARAIB) calculating the productivity and growth of natural and managed vegetation, and an agent-based model (CRAFTY), determining the shifts in land use and land cover. This up-scaled LSD module is made consistent with the surface scheme of the regional climate model (RCM: ALARO) to allow simulations of the RCM with a fully dynamic land surface for the recent past and the period 2000-2030. In this contribution, we analyze the results of the first simulations performed with the CARAIB dynamic vegetation model over Belgium at a resolution of 1km. This analysis is performed at the species level, using a set of 17 species for natural vegetation (trees and grasses) and 10 crops, especially designed to represent the Belgian vegetation. The CARAIB model is forced with surface atmospheric variables derived from the monthly global CRU climatology or ALARO outputs

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

    Science.gov (United States)

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

    2017-12-01

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

  15. Retrieval of Land Surface Temperature over the Heihe River Basin Using HJ-1B Thermal Infrared Data

    Directory of Open Access Journals (Sweden)

    Xiaoying Ouyang

    2014-12-01

    Full Text Available The reliable estimation of spatially distributed Land Surface Temperature (LST is useful for monitoring regional land surface heat fluxes. A single-channel method is developed to derive the LST over the Heihe River Basin in China using data from the infrared sensor (IRS onboard the Chinese “Environmental and Disaster Monitoring and Forecasting with a Small Satellite Constellation” (HJ-1B for short for one of the satellites, with ancillary water vapor information from Moderate Resolution Imaging Spectroradiometer (MODIS products (MOD05 and in situ automatic sun tracking photometer CE318 data for the first time. In situ LST data for the period from mid-June to mid-September 2012 were acquired from automatic meteorological stations (AMS that are part of Heihe Watershed Allied Telemetry Experimental Research (HiWATER project. MOD05-based LST and CE318-based LST are compared with in situ measurements at 16 AMS sites with land cover types of vegetable, maize and orchards. The results show that the use of the MOD05 product could achieve a comparable accuracy in LST retrieval with that achieved using the CE318 data. The largest difference between the MOD05-based LST and CE318-based LST is 0.84 K throughout the study period over the Heihe River Basin. The standard deviation (STD, root mean square error (RMSE, and correlation coefficient (R of HJ-1B/IRS vs. the in situ measurements are 2.45 K, 2.78 K, and 0.67, respectively, whereas those for the MODIS 1 km LST product vs. the in situ measurements are 4.07 K, 2.98 K, and 0.79, respectively. The spatial pattern of the HJ-1B/LST over the study area in the Heihe River Basin generally agreed well with the MODIS 1 km LST product and contained more detailed spatial textures.

  16. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 2 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  17. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 3 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Land Surface Temperature Databank contains monthly timescale mean, maximum, and minimum temperature for approximately 40,000 stations globally. It was...

  18. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 2 Daily

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  19. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 1 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  20. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 1 Daily

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  1. Optimal use of land surface temperature data to detect changes in tropical forest cover

    Science.gov (United States)

    Van Leeuwen, T. T.; Frank, A. J.; Jin, Y.; Smyth, P.; Goulden, M.; van der Werf, G.; Randerson, J. T.

    2011-12-01

    Rapid and accurate assessment of global forest cover change is needed to focus conservation efforts and to better understand how deforestation is contributing to the build up of atmospheric CO2. Here we examined different ways to use remotely sensed land surface temperature (LST) to detect changes in tropical forest cover. In our analysis we used monthly 0.05×0.05 degree Terra MODerate Resolution Imaging Spectroradiometer (MODIS) observations of LST and PRODES (Program for the Estimation of Deforestation in the Brazilian Amazon) estimates of forest cover change. We also compared MODIS LST observations with an independent estimate of forest cover loss derived from MODIS and Landsat observations. Our study domain of approximately 10×10 degree included most of the Brazilian state of Mato Grosso. For optimal use of LST data to detect changes in tropical forest cover in our study area, we found that using data sampled during the end of the dry season (~1-2 months after minimum monthly precipitation) had the greatest predictive skill. During this part of the year, precipitation was low, surface humidity was at a minimum, and the difference between day and night LST was the largest. We used this information to develop a simple temporal sampling algorithm appropriate for use in pan-tropical deforestation classifiers. Combined with the normalized difference vegetation index (NDVI), a logistic regression model using day-night LST did moderately well at predicting forest cover change. Annual changes in day-night LST difference decreased during 2006-2009 relative to 2001-2005 in many regions within the Amazon, providing independent confirmation of lower deforestation levels during the latter part of this decade as reported by PRODES. The use of day-night LST differences may be particularly valuable for use with satellites that do not have spectral bands that allow for the estimation of NDVI or other vegetation indices.

  2. Multi-site evaluation of the JULES land surface model using global and local data

    Directory of Open Access Journals (Sweden)

    D. Slevin

    2015-02-01

    Full Text Available This study evaluates the ability of the JULES land surface model (LSM to simulate photosynthesis using local and global data sets at 12 FLUXNET sites. Model parameters include site-specific (local values for each flux tower site and the default parameters used in the Hadley Centre Global Environmental Model (HadGEM climate model. Firstly, gross primary productivity (GPP estimates from driving JULES with data derived from local site measurements were compared to observations from the FLUXNET network. When using local data, the model is biased with total annual GPP underestimated by 16% across all sites compared to observations. Secondly, GPP estimates from driving JULES with data derived from global parameter and atmospheric reanalysis (on scales of 100 km or so were compared to FLUXNET observations. It was found that model performance decreases further, with total annual GPP underestimated by 30% across all sites compared to observations. When JULES was driven using local parameters and global meteorological data, it was shown that global data could be used in place of FLUXNET data with a 7% reduction in total annual simulated GPP. Thirdly, the global meteorological data sets, WFDEI and PRINCETON, were compared to local data to find that the WFDEI data set more closely matches the local meteorological measurements (FLUXNET. Finally, the JULES phenology model was tested by comparing results from simulations using the default phenology model to those forced with the remote sensing product MODIS leaf area index (LAI. Forcing the model with daily satellite LAI results in only small improvements in predicted GPP at a small number of sites, compared to using the default phenology model.

  3. Mapping Surface Heat Fluxes by Assimilating SMAP Soil Moisture and GOES Land Surface Temperature Data

    Science.gov (United States)

    Lu, Yang; Steele-Dunne, Susan C.; Farhadi, Leila; van de Giesen, Nick

    2017-12-01

    Surface heat fluxes play a crucial role in the surface energy and water balance. In situ measurements are costly and difficult, and large-scale flux mapping is hindered by surface heterogeneity. Previous studies have demonstrated that surface heat fluxes can be estimated by assimilating land surface temperature (LST) and soil moisture to determine two key parameters: a neutral bulk heat transfer coefficient (CHN) and an evaporative fraction (EF). Here a methodology is proposed to estimate surface heat fluxes by assimilating Soil Moisture Active Passive (SMAP) soil moisture data and Geostationary Operational Environmental Satellite (GOES) LST data into a dual-source (DS) model using a hybrid particle assimilation strategy. SMAP soil moisture data are assimilated using a particle filter (PF), and GOES LST data are assimilated using an adaptive particle batch smoother (APBS) to account for the large gap in the spatial and temporal resolution. The methodology is implemented in an area in the U.S. Southern Great Plains. Assessment against in situ observations suggests that soil moisture and LST estimates are in better agreement with observations after assimilation. The RMSD for 30 min (daytime) flux estimates is reduced by 6.3% (8.7%) and 31.6% (37%) for H and LE on average. Comparison against a LST-only and a soil moisture-only assimilation case suggests that despite the coarse resolution, assimilating SMAP soil moisture data is not only beneficial but also crucial for successful and robust flux estimation, particularly when the uncertainties in the model estimates are large.

  4. MEDOKADS - A 20 Year's Daily AVHRR Data Series for Analysis of Land Surface Properties

    Science.gov (United States)

    Koslowsky, D.; Billing, H.; Bolle, H.-J.

    2009-04-01

    To derive primary data products from raw AVHRR data, like spectral reflectances or temperatures, it is necessary to correct for sensor degradation and changing hardware specifications, to re-sample the data into a grid of equal pixel size, to perform geographical registration, cloud-screening and normalization for illumination and observation geometry. A data set which resulted from the application of these corrections is the top of the atmosphere Mediterranean Extended One-Km AVHRR Data Set (MEDOKADS) which now covers a period of 20 years. To study land surface processes, the obtained spectral data have to be combined, radiometric corrections for atmospheric effects, emissivity corrections in the case of temperature measurements have to be applied, and the variable over-flight times have to be accounted for. By application of complex evaluation schemes then higher level products are generated, like vegetation indices, surface albedo, and surface energy fluxes. The ultimate goal is to provide the users community with problem-related information. This includes the quantification of changes and the determination of trends. Methods and tools to reach this goal as well as their limitations are discussed. To validate the data, extended field measurements have been performed in which the scaling between local ground measurements and large scale satellite data play a major role. A major problem remains the application of atmospheric corrections because of the not well known variable aerosol content. The supervision of the quality of the derived information leads to the concept of anchor stations at which surface and atmospheric properties should permanently be measured.

  5. Cloud-enabled large-scale land surface model simulations with the NASA Land Information System

    Science.gov (United States)

    Duffy, D.; Vaughan, G.; Clark, M. P.; Peters-Lidard, C. D.; Nijssen, B.; Nearing, G. S.; Rheingrover, S.; Kumar, S.; Geiger, J. V.

    2017-12-01

    Developed by the Hydrological Sciences Laboratory at NASA Goddard Space Flight Center (GSFC), the Land Information System (LIS) is a high-performance software framework for terrestrial hydrology modeling and data assimilation. LIS provides the ability to integrate satellite and ground-based observational products and advanced modeling algorithms to extract land surface states and fluxes. Through a partnership with the National Center for Atmospheric Research (NCAR) and the University of Washington, the LIS model is currently being extended to include the Structure for Unifying Multiple Modeling Alternatives (SUMMA). With the addition of SUMMA in LIS, meaningful simulations containing a large multi-model ensemble will be enabled and can provide advanced probabilistic continental-domain modeling capabilities at spatial scales relevant for water managers. The resulting LIS/SUMMA application framework is difficult for non-experts to install due to the large amount of dependencies on specific versions of operating systems, libraries, and compilers. This has created a significant barrier to entry for domain scientists that are interested in using the software on their own systems or in the cloud. In addition, the requirement to support multiple run time environments across the LIS community has created a significant burden on the NASA team. To overcome these challenges, LIS/SUMMA has been deployed using Linux containers, which allows for an entire software package along with all dependences to be installed within a working runtime environment, and Kubernetes, which orchestrates the deployment of a cluster of containers. Within a cloud environment, users can now easily create a cluster of virtual machines and run large-scale LIS/SUMMA simulations. Installations that have taken weeks and months can now be performed in minutes of time. This presentation will discuss the steps required to create a cloud-enabled large-scale simulation, present examples of its use, and

  6. Evaluation of coarse scale land surface remote sensing albedo product over rugged terrain

    Science.gov (United States)

    Wen, J.; Xinwen, L.; You, D.; Dou, B.

    2017-12-01

    Satellite derived Land surface albedo is an essential climate variable which controls the earth energy budget and it can be used in applications such as climate change, hydrology, and numerical weather prediction. The accuracy and uncertainty of surface albedo products should be evaluated with a reliable reference truth data prior to applications. And more literatures investigated the validation methods about the albedo validation in a flat or homogenous surface. However, the albedo performance over rugged terrain is still unknow due to the validation method limited. A multi-validation strategy is implemented to give a comprehensive albedo validation, which will involve the high resolution albedo processing, high resolution albedo validation based on in situ albedo, and the method to upscale the high resolution albedo to a coarse scale albedo. Among them, the high resolution albedo generation and the upscale method is the core step for the coarse scale albedo validation. In this paper, the high resolution albedo is generated by Angular Bin algorithm. And a albedo upscale method over rugged terrain is developed to obtain the coarse scale albedo truth. The in situ albedo located 40 sites in mountain area are selected globally to validate the high resolution albedo, and then upscaled to the coarse scale albedo by the upscale method. This paper takes MODIS and GLASS albedo product as a example, and the prelimarily results show the RMSE of MODIS and GLASS albedo product over rugged terrain are 0.047 and 0.057, respectively under the RMSE with 0.036 of high resolution albedo.

  7. Land surface temperature as potential indicator of burn severity in forest Mediterranean ecosystems

    Science.gov (United States)

    Quintano, C.; Fernández-Manso, A.; Calvo, L.; Marcos, E.; Valbuena, L.

    2015-04-01

    Forest fires are one of the most important causes of environmental alteration in Mediterranean countries. Discrimination of different degrees of burn severity is critical for improving management of fire-affected areas. This paper aims to evaluate the usefulness of land surface temperature (LST) as potential indicator of burn severity. We used a large convention-dominated wildfire, which occurred on 19-21 September, 2012 in Northwestern Spain. From this area, a 1-year series of six LST images were generated from Landsat 7 Enhanced Thematic Mapper (ETM+) data using a single channel algorithm. Further, the Composite Burn Index (CBI) was measured in 111 field plots to identify the burn severity level (low, moderate, and high). Evaluation of the potential relationship between post-fire LST and ground measured CBI was performed by both correlation analysis and regression models. Correlation coefficients were higher in the immediate post-fire LST images, but decreased during the fall of 2012 and increased again with a second maximum value in summer, 2013. A linear regression model between post-fire LST and CBI allowed us to represent spatially predicted CBI (R-squaredadj > 85%). After performing an analysis of variance (ANOVA) between post-fire LST and CBI, a Fisher's least significant difference test determined that two burn severity levels (low-moderate and high) could be statistically distinguished. The identification of such burn severity levels is sufficient and useful to forest managers. We conclude that summer post-fire LST from moderate resolution satellite data may be considered as a valuable indicator of burn severity for large fires in Mediterranean forest ecosytems.

  8. Monitoring arid-land groundwater abstraction through optimization of a land surface model with remote sensing-based evaporation

    KAUST Repository

    Lopez Valencia, Oliver Miguel

    2018-02-01

    The increase in irrigated agriculture in Saudi Arabia is having a large impact on its limited groundwater resources. While large-scale water storage changes can be estimated using satellite data, monitoring groundwater abstraction rates is largely non-existent at either farm or regional level, so water management decisions remain ill-informed. Although determining water use from space at high spatiotemporal resolutions remains challenging, a number of approaches have shown promise, particularly in the retrieval of crop water use via evaporation. Apart from satellite-based estimates, land surface models offer a continuous spatial-temporal evolution of full land-atmosphere water and energy exchanges. In this study, we first examine recent trends in terrestrial water storage depletion within the Arabian Peninsula and explore its relation to increased agricultural activity in the region using satellite data. Next, we evaluate a number of large-scale remote sensing-based evaporation models, giving insight into the challenges of evaporation retrieval in arid environments. Finally, we present a novel method aimed to retrieve groundwater abstraction rates used in irrigated fields by constraining a land surface model with remote sensing-based evaporation observations. The approach is used to reproduce reported irrigation rates over 41 center-pivot irrigation fields presenting a range of crop dynamics over the course of one year. The results of this application are promising, with mean absolute errors below 3 mm:day-1, bias of -1.6 mm:day-1, and a first rough estimate of total annual abstractions of 65.8 Mm3 (close to the estimated value using reported farm data, 69.42 Mm3). However, further efforts to address the overestimation of bare soil evaporation in the model are required. The uneven coverage of satellite data within the study site allowed us to evaluate its impact on the optimization, with a better match between observed and obtained irrigation rates on fields with

  9. Status of Land Surface Temperature Product Development at NOAA/NESDIS/STAR for JPSS and GOES-R Missions

    Science.gov (United States)

    Yu, Yunyue; Liu, yuling; yu, peng; Casiszar, Ivan; Zhou, Lihang

    2016-04-01

    Land surface temperature (LST) is of fundamental importance to many aspects of the geosciences, e.g., net radiation budget at the Earth surface, monitoring state of crops and vegetation, as well as an important indicator of both the greenhouse effect and the physics of land-surface processes at local through global scales. Satellite LST measurements provide unique data sources for regional and global coverage in fairly good temporal, spatial resolution and time span. Therefore, LST is one of baseline products in both JPSS and GOES-R satellite missions. The Center for SaTellite Applications and Research (STAR) of NOAA/NESDIS is responsible for developing high quality LST products for a variety of satellite missions including JPSS and GOES-R. The JPSS LST data, which is produced for each swath of observations, has reached its beta, provisional and validated stage 1 status in October 2013, May 2014, and December 2015, respectively. A routine validation and monitoring toolkit has been developed and its results are available through a public web site. Our validation results against the U.S. SURFRAD ground stations show that uncertainty of the VIIRS LST is less than 2.35K (vs. the JPSS mission requirement of 2.5K). Improvement of the JPSS LST product is on-going, which counts surface emissive variation explicitly in retrieval algorithm. Further, a gridded daily global LST product will be available by end of 2016. In terms of the GOES-R LST product, we have evaluated the retrieval algorithm using SEVIRI and AHI data as proxies. The evaluation results show that the accuracy of GOES-R LST is expected to be less than 2.30K (GOES-R mission requirement). The validation toolkit developed for JPSS mission will be extended and applicable for the GOES-R mission as well. A detailed Readiness, Implementation and Management Plan (RIMP) of GOES-R LST beta and provisional validation has been developed for the GOES-R launch that is scheduled in October 2016.

  10. Quantifying the Uncertainty in High Spatial and Temporal Resolution Synthetic Land Surface Reflectance at Pixel Level Using Ground-Based Measurements

    Science.gov (United States)

    Kong, J.; Ryu, Y.

    2017-12-01

    Algorithms for fusing high temporal frequency and high spatial resolution satellite images are widely used to develop dense time-series land surface observations. While many studies have revealed that the synthesized frequent high spatial resolution images could be successfully applied in vegetation mapping and monitoring, validation and correction of fused images have not been focused than its importance. To evaluate the precision of fused image in pixel level, in-situ reflectance measurements which could account for the pixel-level heterogeneity are necessary. In this study, the synthetic images of land surface reflectance were predicted by the coarse high-frequency images acquired from MODIS and high spatial resolution images from Landsat-8 OLI using the Flexible Spatiotemporal Data Fusion (FSDAF). Ground-based reflectance was measured by JAZ Spectrometer (Ocean Optics, Dunedin, FL, USA) on rice paddy during five main growth stages in Cheorwon-gun, Republic of Korea, where the landscape heterogeneity changes through the growing season. After analyzing the spatial heterogeneity and seasonal variation of land surface reflectance based on the ground measurements, the uncertainties of the fused images were quantified at pixel level. Finally, this relationship was applied to correct the fused reflectance images and build the seasonal time series of rice paddy surface reflectance. This dataset could be significant for rice planting area extraction, phenological stages detection, and variables estimation.

  11. Comparison of two perturbation methods to estimate the land surface modeling uncertainty

    Science.gov (United States)

    Su, H.; Houser, P.; Tian, Y.; Kumar, S.; Geiger, J.; Belvedere, D.

    2007-12-01

    In land surface modeling, it is almost impossible to simulate the land surface processes without any error because the earth system is highly complex and the physics of the land processes has not yet been understood sufficiently. In most cases, people want to know not only the model output but also the uncertainty in the modeling, to estimate how reliable the modeling is. Ensemble perturbation is an effective way to estimate the uncertainty in land surface modeling, since land surface models are highly nonlinear which makes the analytical approach not applicable in this estimation. The ideal perturbation noise is zero mean Gaussian distribution, however, this requirement can't be satisfied if the perturbed variables in land surface model have physical boundaries because part of the perturbation noises has to be removed to feed the land surface models properly. Two different perturbation methods are employed in our study to investigate their impact on quantifying land surface modeling uncertainty base on the Land Information System (LIS) framework developed by NASA/GSFC land team. One perturbation method is the built-in algorithm named "STATIC" in LIS version 5; the other is a new perturbation algorithm which was recently developed to minimize the overall bias in the perturbation by incorporating additional information from the whole time series for the perturbed variable. The statistical properties of the perturbation noise generated by the two different algorithms are investigated thoroughly by using a large ensemble size on a NASA supercomputer and then the corresponding uncertainty estimates based on the two perturbation methods are compared. Their further impacts on data assimilation are also discussed. Finally, an optimal perturbation method is suggested.

  12. The Goddard Snow Radiance Assimilation Project: An Integrated Snow Radiance and Snow Physics Modeling Framework for Snow/cold Land Surface Modeling

    Science.gov (United States)

    Kim, E.; Tedesco, M.; Reichle, R.; Choudhury, B.; Peters-Lidard C.; Foster, J.; Hall, D.; Riggs, G.

    2006-01-01

    Microwave-based retrievals of snow parameters from satellite observations have a long heritage and have so far been generated primarily by regression-based empirical "inversion" methods based on snapshots in time. Direct assimilation of microwave radiance into physical land surface models can be used to avoid errors associated with such retrieval/inversion methods, instead utilizing more straightforward forward models and temporal information. This approach has been used for years for atmospheric parameters by the operational weather forecasting community with great success. Recent developments in forward radiative transfer modeling, physical land surface modeling, and land data assimilation are converging to allow the assembly of an integrated framework for snow/cold lands modeling and radiance assimilation. The objective of the Goddard snow radiance assimilation project is to develop such a framework and explore its capabilities. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. In fact, multiple models are available for each element enabling optimization to match the needs of a particular study. Together these form a modular and flexible framework for self-consistent, physically-based remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster. Capabilities for assimilation of snow retrieval products are already under development for LIS. We will describe plans to add radiance-based assimilation capabilities. Plans for validation activities using field measurements will also be discussed.

  13. U.S. Local Climatological Data (LCD)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Local Climatological Data (LCD) are summaries of climatological conditions from airport and other prominent weather stations managed by NWS, FAA, and DOD. The...

  14. Inclusion of Solar Elevation Angle in Land Surface Albedo Parameterization Over Bare Soil Surface.

    Science.gov (United States)

    Zheng, Zhiyuan; Wei, Zhigang; Wen, Zhiping; Dong, Wenjie; Li, Zhenchao; Wen, Xiaohang; Zhu, Xian; Ji, Dong; Chen, Chen; Yan, Dongdong

    2017-12-01

    Land surface albedo is a significant parameter for maintaining a balance in surface energy. It is also an important parameter of bare soil surface albedo for developing land surface process models that accurately reflect diurnal variation characteristics and the mechanism behind the solar spectral radiation albedo on bare soil surfaces and for understanding the relationships between climate factors and spectral radiation albedo. Using a data set of field observations, we conducted experiments to analyze the variation characteristics of land surface solar spectral radiation and the corresponding albedo over a typical Gobi bare soil underlying surface and to investigate the relationships between the land surface solar spectral radiation albedo, solar elevation angle, and soil moisture. Based on both solar elevation angle and soil moisture measurements simultaneously, we propose a new two-factor parameterization scheme for spectral radiation albedo over bare soil underlying surfaces. The results of numerical simulation experiments show that the new parameterization scheme can more accurately depict the diurnal variation characteristics of bare soil surface albedo than the previous schemes. Solar elevation angle is one of the most important factors for parameterizing bare soil surface albedo and must be considered in the parameterization scheme, especially in arid and semiarid areas with low soil moisture content. This study reveals the characteristics and mechanism of the diurnal variation of bare soil surface solar spectral radiation albedo and is helpful in developing land surface process models, weather models, and climate models.

  15. Active Learning in Introductory Climatology.

    Science.gov (United States)

    Dewey, Kenneth F.; Meyer, Steven J.

    2000-01-01

    Introduces a software package available for the climatology curriculum that determines possible climatic events according to a long-term climate history. Describes the integration of the software into the curriculum and presents examples of active learning. (Contains 19 references.) (YDS)

  16. Estimation and Validation of Land Surface Temperatures from Chinese Second-Generation Polar-Orbit FY-3A VIRR Data

    Directory of Open Access Journals (Sweden)

    Bo-Hui Tang

    2015-03-01

    Full Text Available This work estimated and validated the land surface temperature (LST from thermal-infrared Channels 4 (10.8 µm and 5 (12.0 µm of the Visible and Infrared Radiometer (VIRR onboard the second-generation Chinese polar-orbiting FengYun-3A (FY-3A meteorological satellite. The LST, mean emissivity and atmospheric water vapor content (WVC were divided into several tractable sub-ranges with little overlap to improve the fitting accuracy. The experimental results showed that the root mean square errors (RMSEs were proportional to the viewing zenith angles (VZAs and WVC. The RMSEs were below 1.0 K for VZA sub-ranges less than 30° or for VZA sub-ranges less than 60° and WVC less than 3.5 g/cm2, provided that the land surface emissivities were known. A preliminary validation using independently simulated data showed that the estimated LSTs were quite consistent with the actual inputs, with a maximum RMSE below 1 K for all VZAs. An inter-comparison using the Moderate Resolution Imaging Spectroradiometer (MODIS-derived LST product MOD11_L2 showed that the minimum RMSE was 1.68 K for grass, and the maximum RMSE was 3.59 K for barren or sparsely vegetated surfaces. In situ measurements at the Hailar field site in northeastern China from October, 2013, to September, 2014, were used to validate the proposed method. The result showed that the RMSE between the LSTs calculated from the ground measurements and derived from the VIRR data was 1.82 K.

  17. Land surface temperature as an indicator of the unsaturated zone thickness: A remote sensing approach in the Atacama Desert.

    Science.gov (United States)

    Urqueta, Harry; Jódar, Jorge; Herrera, Christian; Wilke, Hans-G; Medina, Agustín; Urrutia, Javier; Custodio, Emilio; Rodríguez, Jazna

    2018-01-15

    Land surface temperature (LST) seems to be related to the temperature of shallow aquifers and the unsaturated zone thickness (∆Z uz ). That relationship is valid when the study area fulfils certain characteristics: a) there should be no downward moisture fluxes in an unsaturated zone, b) the soil composition in terms of both, the different horizon materials and their corresponding thermal and hydraulic properties, must be as homogeneous and isotropic as possible, c) flat and regular topography, and d) steady state groundwater temperature with a spatially homogeneous temperature distribution. A night time Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image and temperature field measurements are used to test the validity of the relationship between LST and ∆Z uz at the Pampa del Tamarugal, which is located in the Atacama Desert (Chile) and meets the above required conditions. The results indicate that there is a relation between the land surface temperature and the unsaturated zone thickness in the study area. Moreover, the field measurements of soil temperature indicate that shallow aquifers dampen both the daily and the seasonal amplitude of the temperature oscillation generated by the local climate conditions. Despite empirically observing the relationship between the LST and ∆Z uz in the study zone, such a relationship cannot be applied to directly estimate ∆Z uz using temperatures from nighttime thermal satellite images. To this end, it is necessary to consider the soil thermal properties, the soil surface roughness and the unseen water and moisture fluxes (e.g., capillarity and evaporation) that typically occur in the subsurface. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Analyzing land surface temperature variations during Fogo Island (Cape Verde) 2014-2015 eruption with Landsat 8 images

    Science.gov (United States)

    Vieira, D.; Teodoro, A.; Gomes, A.

    2016-10-01

    Land Surface Temperature (LST) is an important parameter related to land surface processes that changes continuously through time. Assessing its dynamics during a volcanic eruption has both environmental and socio-economical interest. Lava flows and other volcanic materials produced and deposited throughout an eruption transform the landscape, contributing to its heterogeneity and altering LST measurements. This paper aims to assess variations of satellite-derived LST and to detect patterns during the latest Fogo Island (Cape Verde) eruption, extending from November 2014 through February 2015. LST data was obtained through four processed Landsat 8 images, focused on the caldera where Pico do Fogo volcano sits. QGIS' plugin Semi-Automatic Classification was used in order to apply atmospheric corrections and radiometric calibrations. The algorithm used to retrieve LST values is a single-channel method, in which emissivity values are known. The absence of in situ measurements is compensated by the use of MODIS sensor-derived LST data, used to compare with Landsat retrieved measurements. LST data analysis shows as expected that the highest LST values are located inside the caldera. High temperature values were also founded on the south-facing flank of the caldera. Although spatial patterns observed on the retrieved data remained roughly the same during the time period considered, temperature values changed throughout the area and over time, as it was also expected. LST values followed the eruption dynamic experiencing a growth followed by a decline. Moreover, it seems possible to recognize areas affected by lava flows of previous eruptions, due to well-defined LST spatial patterns.

  19. Upper-soil moisture inter-comparison from SMOS's products and land surface models over the Iberian Peninsula

    Science.gov (United States)

    Polcher, Jan; Barella-Ortiz, Anaïs; Aires, Filipe; Balsamo, Gianpaolo; Gelati, Emiliano; Rodríguez-Fernández, Nemesio

    2015-04-01

    Soil moisture is a key state variable of the hydrological cycle. It conditions runoff, infiltration and evaporation over continental surfaces, and is key for forecasting droughts and floods. It plays thus an important role in surface-atmosphere interactions. Surface Soil Moisture (SSM) can be measured by in situ measurements, by satellite observations or modelled using land surface models. As a complementary tool, data assimilation can be used to combine both modelling and satellite observations. The work presented here is an inter-comparison of retrieved and modelled SSM data, for the 2010 - 2012 period, over the Iberian Peninsula. The region has been chosen because its vegetation cover is not very dense and includes strong contrasts in the rainfall regimes and thus a diversity of behaviours for SSM. Furthermore this semi-arid region is strongly dependent on a good management of its water resources. Satellite observations correspond to the Soil Moisture and Ocean Salinity (SMOS) retrievals: the L2 product from an optimal interpolation retrieval, and 3 other products using Neural Network retrievals with different input information: SMOS time indexes, purely SMOS data, or addition of the European Advanced Scaterometer (ASCAT) backscattering, and the Moderate-Resolution Imaging Spectrometer (MODIS) surface temperature information. The modelled soil moistures have been taken from the ORCHIDEE (ORganising Carbon and Hydrology In Dynamic EcosystEms) and the HTESSEL (Hydrology-Tiled ECMWF Scheme for Surface Exchanges over Land) land surface models. Both models are forced with the same atmospheric conditions (as part of the Earth2Observe FP7 project) over the period but they represent the surface soil moisture with very different degrees of complexity. ORCHIDEE has 5 levels in the top 5 centimetres of soil while in HTESSEL this variable is part of the top soil moisture level. The two types of SMOS retrievals are compared to the model outputs in their spatial and temporal

  20. Improving weather predictability by including land-surface model parameter uncertainty

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Pappenberger, Florian

    2016-04-01

    The land surface forms an important component of Earth system models and interacts nonlinearly with other parts such as ocean and atmosphere. To capture the complex and heterogenous hydrology of the land surface, land surface models include a large number of parameters impacting the coupling to other components of the Earth system model. Focusing on ECMWF's land-surface model HTESSEL we present in this study a comprehensive parameter sensitivity evaluation using multiple observational datasets in Europe. We select 6 poorly constrained effective parameters (surface runoff effective depth, skin conductivity, minimum stomatal resistance, maximum interception, soil moisture stress function shape, total soil depth) and explore their sensitivity to model outputs such as soil moisture, evapotranspiration and runoff using uncoupled simulations and coupled seasonal forecasts. Additionally we investigate the possibility to construct ensembles from the multiple land surface parameters. In the uncoupled runs we find that minimum stomatal resistance and total soil depth have the most influence on model performance. Forecast skill scores are moreover sensitive to the same parameters as HTESSEL performance in the uncoupled analysis. We demonstrate the robustness of our findings by comparing multiple best performing parameter sets and multiple randomly chosen parameter sets. We find better temperature and precipitation forecast skill with the best-performing parameter perturbations demonstrating representativeness of model performance across uncoupled (and hence less computationally demanding) and coupled settings. Finally, we construct ensemble forecasts from ensemble members derived with different best-performing parameterizations of HTESSEL. This incorporation of parameter uncertainty in the ensemble generation yields an increase in forecast skill, even beyond the skill of the default system. Orth, R., E. Dutra, and F. Pappenberger, 2016: Improving weather predictability by

  1. Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment

    Science.gov (United States)

    Bindlish, Rajat; Jackson, Thomas; Cosh, Michael; Zhao, Tianjie; O'Neil, Peggy

    2015-01-01

    Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = -0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.

  2. Land Surface Process and Air Quality Research and Applications at MSFC

    Science.gov (United States)

    Quattrochi, Dale; Khan, Maudood

    2007-01-01

    This viewgraph presentation provides an overview of land surface process and air quality research at MSFC including atmospheric modeling and ongoing research whose objective is to undertake a comprehensive spatiotemporal analysis of the effects of accurate land surface characterization on atmospheric modeling results, and public health applications. Land use maps as well as 10 meter air temperature, surface wind, PBL mean difference heights, NOx, ozone, and O3+NO2 plots as well as spatial growth model outputs are included. Emissions and general air quality modeling are also discussed.

  3. Climatology of lightning in the Czech Republic

    Science.gov (United States)

    Novák, Petr; Kyznarová, Hana

    2011-06-01

    The Czech Hydrometeorological Institute (CHMI) has utilized lightning data from the Central European Lightning Detection Network (CELDN) since 1999. The CELDN primarily focuses on the detection of cloud-to-ground (CG) lightning but intra-cloud (IC) lightning detection is also available. Lightning detection is used by the CHMI forecasters as an additional source to radar and satellite data for nowcasting of severe storms. Lightning data are also quantitatively used in automatic nowcasting applications. The quality of lightning data can be evaluated using their climatological characteristics. Climatological characteristics are also useful for defining decision thresholds that are valuable for human forecasters as well as for automatic nowcasting applications. The seven-year period from 2002 to 2008, which had relatively even-quality lightning data, was used to calculate the spatial and temporal distributions of lightning. The monthly number of CG strokes varies depending on the season. The highest number of CG strokes occurs during summer, with more than 20 days of at least five detected CG strokes on the Czech Republic territory in June and July. The least number of CG stokes occurs in winter, with less than three days per month having at least five detected CG stokes. The mean diurnal distribution of CG strokes peaks between 1500 and 1600 UTC and reaches a minimum between 0500 and 0800 UTC. The average spatial distribution of CG strokes shows sharp local maxima corresponding with the locations of the TV broadcast towers. The average spatial distribution of CG flash density, calculated on a 20 × 20 km grid, shows the maximum (3.23 flashes km - 2 year - 1 ) in the western part of Czech Republic and the minimum (0.92 flashes km - 2 year - 1 ) in the south-southeast of the Czech Republic. In addition, lightning characteristics related to the identified convective cells, such as distribution of the lightning stroke rates or relation to the radar derived by Vertically

  4. Vicarious Calibration of sUAS Microbolometer Temperature Imagery for Estimation of Radiometric Land Surface Temperature

    Directory of Open Access Journals (Sweden)

    Alfonso Torres-Rua

    2017-06-01

    Full Text Available In recent years, the availability of lightweight microbolometer thermal cameras compatible with small unmanned aerial systems (sUAS has allowed their use in diverse scientific and management activities that require sub-meter pixel resolution. Nevertheless, as with sensors already used in temperature remote sensing (e.g., Landsat satellites, a radiance atmospheric correction is necessary to estimate land surface temperature. This is because atmospheric conditions at any sUAS flight elevation will have an adverse impact on the image accuracy, derived calculations, and study replicability using the microbolometer technology. This study presents a vicarious calibration methodology (sUAS-specific, time-specific, flight-specific, and sensor-specific for sUAS temperature imagery traceable back to NIST-standards and current atmospheric correction methods. For this methodology, a three-year data collection campaign with a sUAS called “AggieAir”, developed at Utah State University, was performed for vineyards near Lodi, California, for flights conducted at different times (early morning, Landsat overpass, and mid-afternoon” and seasonal conditions. From the results of this study, it was found that, despite the spectral response of microbolometer cameras (7.0 to 14.0 μm, it was possible to account for the effects of atmospheric and sUAS operational conditions, regardless of time and weather, to acquire accurate surface temperature data. In addition, it was found that the main atmospheric correction parameters (transmissivity and atmospheric radiance significantly varied over the course of a day. These parameters fluctuated the most in early morning and partially stabilized in Landsat overpass and in mid-afternoon times. In terms of accuracy, estimated atmospheric correction parameters presented adequate statistics (confidence bounds under ±0.1 for transmissivity and ±1.2 W/m2/sr/um for atmospheric radiance, with a range of RMSE below 1.0 W/m2/sr

  5. Impacts of Wildfires on Land Surface Phenology of Western US Forests

    Science.gov (United States)

    Wang, J.; Zhang, X.

    2017-12-01

    Land surface phenology (LSP) characterizes seasonal dynamics of vegetation communities within a satellite pixel. The temporal variation of LSP has been widely associated with recent global climate change. However, few studies have focused on the influence of land disturbance, such as wildfire, on LSP variations, which is particularly true at a continental scale. Wildfire has increased in size and severity in the western United States (US) during last few decades. To explore wildfire impacts on LSP in the western US forest, we analyzed the start of growing season (SOS) integrated from the entire forest area, the burned area, and the unburned area, respectively. Specifically, SOS was derived from time series of daily MODIS surface reflectance product at 250 m using a hybrid piecewise logistic detection model. The annual burn perimeters during 2000-2014 were obtained from Monitoring Trends in Burn Severity maps to study the wildfire effect on the SOS in the subsequent years (2001-2015). The wildfire effect was analyzed at three levels: the entire western US, Environmental Protection Agency's Level III ecoregions, and states. Results show that wildfires basically advance SOS but have diverse effects with different regions and years. Comparing SOS in the burned areas with that in surrounding unburned areas from 2001-2015, it was found that the SOS shift was -3.4 days (-: earlier; +: later) on average in the western US forests, and varied from -16.1 to 13.1 days across ecoregions and from -11.4 to 4.3 days across states. Because of the small proportion of annual burned areas (SOS shift in the burned areas had limited influences on the overall SOS, which caused shifts of -0.06 days over the entire western US, from -0.2 to 0.2 days across ecoregions, and -0.06 to 0.13 days across states. Overall, this study demonstrates that wildfires strongly impact SOS at local areas although the effect in the large region is relatively limited.

  6. Assimilation of the ESA CCI Soil Moisture ACTIVE and PASSIVE Product into the SURFEX Land Surface Model using the Ensemble Transform Kalman Filter

    Science.gov (United States)

    Blyverket, J.; Hamer, P.; Bertino, L.; Lahoz, W. A.

    2017-12-01

    The European Space Agency Climate Change Initiative for soil moisture (ESA CCI SM) was initiated in 2012 for a period of six years, the objective for this period was to produce the most complete and consistent global soil moisture data record based on both active and passive sensors. The ESA CCI SM products consist of three surface soil moisture datasets: The ACTIVE product and the PASSIVE product were created by fusing scatterometer and radiometer soil moisture data, respectively. The COMBINED product is a blended product based on the former two datasets. In this study we assimilate globally both the ACTIVE and PASSIVE product at a 25 km spatial resolution. The different satellite platforms have different overpass times, an observation is mapped to the hours 00.00, 06.00, 12.00 or 18.00 if it falls within a 3 hour window centred at these times. We use the SURFEX land surface model with the ISBA diffusion scheme for the soil hydrology. For the assimilation routine we apply the Ensemble Transform Kalman Filter (ETKF). The land surface model is driven by perturbed MERRA-2 atmospheric forcing data, which has a temporal resolution of one hour and is mapped to the SURFEX model grid. Bias between the land surface model and the ESA CCI product is removed by cumulative distribution function (CDF) matching. This work is a step towards creating a global root zone soil moisture product from the most comprehensive satellite surface soil moisture product available. As a first step we consider the period from 2010 - 2016. This allows for comparison against other global root zone soil moisture products (SMAP Level 4, which is independent of the ESA CCI SM product).

  7. Assimilation of SMOS Brightness Temperatures or Soil Moisture Retrievals into a Land Surface Model

    Science.gov (United States)

    De Lannoy, Gabrielle J. M.; Reichle, Rolf H.

    2016-01-01

    Three different data products from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated separately into the Goddard Earth Observing System Model, version 5 (GEOS-5) to improve estimates of surface and root-zone soil moisture. The first product consists of multi-angle, dual-polarization brightness temperature (Tb) observations at the bottom of the atmosphere extracted from Level 1 data. The second product is a derived SMOS Tb product that mimics the data at a 40 degree incidence angle from the Soil Moisture Active Passive (SMAP) mission. The third product is the operational SMOS Level 2 surface soil moisture (SM) retrieval product. The assimilation system uses a spatially distributed ensemble Kalman filter (EnKF) with seasonally varying climatological bias mitigation for Tb assimilation, whereas a time-invariant cumulative density function matching is used for SM retrieval assimilation. All assimilation experiments improve the soil moisture estimates compared to model-only simulations in terms of unbiased root-mean-square differences and anomaly correlations during the period from 1 July 2010 to 1 May 2015 and for 187 sites across the US. Especially in areas where the satellite data are most sensitive to surface soil moisture, large skill improvements (e.g., an increase in the anomaly correlation by 0.1) are found in the surface soil moisture. The domain-average surface and root-zone skill metrics are similar among the various assimilation experiments, but large differences in skill are found locally. The observation-minus-forecast residuals and analysis increments reveal large differences in how the observations add value in the Tb and SM retrieval assimilation systems. The distinct patterns of these diagnostics in the two systems reflect observation and model errors patterns that are not well captured in the assigned EnKF error parameters. Consequently, a localized optimization of the EnKF error parameters is needed to further improve Tb or SM retrieval

  8. Derivation of Land Surface Albedo at High Resolution by Combining HJ-1A/B Reflectance Observations with MODIS BRDF Products

    NARCIS (Netherlands)

    Gao, B.; Jia, L.; Wang, T.X.

    2014-01-01

    Land surface albedo is an essential parameter for monitoring global/regional climate and land surface energy balance. Although many studies have been conducted on global or regional land surface albedo using various remote sensing data over the past few decades, land surface albedo product with a

  9. Advancements in medium and high resolution Earth observation for land-surface imaging: Evolutions, future trends and contributions to sustainable development

    Science.gov (United States)

    Ouma, Yashon O.

    2016-01-01

    Technologies for imaging the surface of the Earth, through satellite based Earth observations (EO) have enormously evolved over the past 50 years. The trends are likely to evolve further as the user community increases and their awareness and demands for EO data also increases. In this review paper, a development trend on EO imaging systems is presented with the objective of deriving the evolving patterns for the EO user community. From the review and analysis of medium-to-high resolution EO-based land-surface sensor missions, it is observed that there is a predictive pattern in the EO evolution trends such that every 10-15 years, more sophisticated EO imaging systems with application specific capabilities are seen to emerge. Such new systems, as determined in this review, are likely to comprise of agile and small payload-mass EO land surface imaging satellites with the ability for high velocity data transmission and huge volumes of spatial, spectral, temporal and radiometric resolution data. This availability of data will magnify the phenomenon of ;Big Data; in Earth observation. Because of the ;Big Data; issue, new computing and processing platforms such as telegeoprocessing and grid-computing are expected to be incorporated in EO data processing and distribution networks. In general, it is observed that the demand for EO is growing exponentially as the application and cost-benefits are being recognized in support of resource management.

  10. Selection of soil hydraulic properties in a land surface model using remotely-sensed soil moisture and surface temperature

    Science.gov (United States)

    Shellito, P. J.; Small, E. E.; Gutmann, E. D.

    2013-12-01

    Synoptic-scale weather is heavily influenced by latent and sensible heating from the land surface. The partitioning of available energy between these two fluxes as well as the distribution of moisture throughout the soil column is controlled by a unique set of soil hydraulic properties (SHPs) at every location. Weather prediction systems, which use coupled land surface and atmospheric models in their forecasts, must therefore be parameterized with estimates of SHPs. Currently, land surface models (LSMs) obtain SHP values by assuming a correlation exists between SHPs and the soil type, which the USDA maps in 12 classes. This method is spurious because texture is only one control of many that affects SHPs. Alternatively, SHPs can be obtained by calibrating them within the framework of an LSM. Because remotely-sensed data have the potential for continent-wide application, there is a critical need to understand their specific role in calibration efforts and the extent to which such calibrated SHPs can improve model simulations. This study focuses on SHP calibration with soil moisture content (SMC) and land surface temperature (Ts), data that are available from the SMOS and MODIS satellite missions, respectively. The scientific goals of this study are: (1) What is the model performance tradeoff between weighting SMC and Ts differently during the calibration process? (2) What can the tradeoff between calibration using in-situ and remotely-sensed SMC reveal about SHP scaling? (3) How are these relationships influenced by climatic regime and vegetation type? (4) To what extent can calibrated SHPs improve model performance over that of texture-based SHPs? Model calibrations are carried out within the framework of the Noah LSM using the Shuffled Complex Evolution Metropolis (SCEM-UA) algorithm in five different climatic regimes. At each site, a five-dimensional parameter space of SHPs is searched to find the location that minimizes the difference between observed and

  11. Inferring CO2 Fluxes from OCO-2 for Assimilation into Land Surface Models to Calculate Net Ecosystem Exchange

    Science.gov (United States)

    Prouty, R.; Radov, A.; Halem, M.; Nearing, G. S.

    2016-12-01

    Investigations of mid to high latitude atmospheric CO2 show a growing seasonal amplitude. Land surface models poorly predict net ecosystem exchange (NEE) and are unable to substantiate these sporadic observations. An investigation of how the biosphere has reacted to changes in atmospheric CO2 is essential to our understanding of potential climate-vegetation feedbacks. A global, seasonal investigation of CO2-flux is then necessary in order to assimilate into land surface models for improving the prediction of annual NEE. The Atmospheric Radiation Measurement program (ARM) of DOE collects CO2-flux measurements (in addition to CO2 concentration and various other meteorological quantities) at several towers located around the globe at half hour temporal frequencies. CO2-fluxes are calculated via the eddy covariance technique, which utilizes CO2-densities and wind velocities to calculate CO2-fluxes. The global coverage of CO2 concentrations as provided by the Orbiting Carbon Observatory (OCO-2) provide satellite-derived CO2 concentrations all over the globe. A framework relating the satellite-inferred CO2 concentrations collocated with the ground-based ARM as well as Ameriflux stations would enable calculations of CO2-fluxes far from the station sites around the entire globe. Regression techniques utilizing deep-learning neural networks may provide such a framework. Additionally, meteorological reanalysis allows for the replacement of the ARM multivariable meteorological variables needed to infer the CO2-fluxes. We present the results of inferring CO2-fluxes from OCO-2 CO2 concentrations for a two year period, Sept. 2014- Sept. 2016 at the ARM station located near Oklahoma City. A feed-forward neural network (FFNN) is used to infer relationships between the following data sets: F([ARM CO2-density], [ARM Meteorological Data]) = [ARM CO2-Flux] F([OCO-2 CO2-density],[ARM Meteorological Data]) = [ARM CO2-Flux] F([ARM CO2-density],[Meteorological Reanalysis]) = [ARM CO2-Flux

  12. Land Surface Temperature Retrieval from MODIS Data by Integrating Regression Models and the Genetic Algorithm in an Arid Region

    Directory of Open Access Journals (Sweden)

    Ji Zhou

    2014-06-01

    Full Text Available The land surface temperature (LST is one of the most important parameters of surface-atmosphere interactions. Methods for retrieving LSTs from satellite remote sensing data are beneficial for modeling hydrological, ecological, agricultural and meteorological processes on Earth’s surface. Many split-window (SW algorithms, which can be applied to satellite sensors with two adjacent thermal channels located in the atmospheric window between 10 μm and 12 μm, require auxiliary atmospheric parameters (e.g., water vapor content. In this research, the Heihe River basin, which is one of the most arid regions in China, is selected as the study area. The Moderate-resolution Imaging Spectroradiometer (MODIS is selected as a test case. The Global Data Assimilation System (GDAS atmospheric profiles of the study area are used to generate the training dataset through radiative transfer simulation. Significant correlations between the atmospheric upwelling radiance in MODIS channel 31 and the other three atmospheric parameters, including the transmittance in channel 31 and the transmittance and upwelling radiance in channel 32, are trained based on the simulation dataset and formulated with three regression models. Next, the genetic algorithm is used to estimate the LST. Validations of the RM-GA method are based on the simulation dataset generated from in situ measured radiosonde profiles and GDAS atmospheric profiles, the in situ measured LSTs, and a pair of daytime and nighttime MOD11A1 products in the study area. The results demonstrate that RM-GA has a good ability to estimate the LSTs directly from the MODIS data without any auxiliary atmospheric parameters. Although this research is for local application in the Heihe River basin, the findings and proposed method can easily be extended to other satellite sensors and regions with arid climates and high elevations.

  13. The Plumbing of Land Surface Models: Is Poor Performance a Result of Methodology or Data Quality?

    Science.gov (United States)

    Haughton, Ned; Abramowitz, Gab; Pitman, Andy J.; Or, Dani; Best, Martin J.; Johnson, Helen R.; Balsamo, Gianpaolo; Boone, Aaron; Cuntz, Matthais; Decharme, Bertrand; hide

    2016-01-01

    The PALS Land sUrface Model Benchmarking Evaluation pRoject (PLUMBER) illustrated the value of prescribing a priori performance targets in model intercomparisons. It showed that the performance of turbulent energy flux predictions from different land surface models, at a broad range of flux tower sites using common evaluation metrics, was on average worse than relatively simple empirical models. For sensible heat fluxes, all land surface models were outperformed by a linear regression against downward shortwave radiation. For latent heat flux, all land surface models were outperformed by a regression against downward shortwave, surface air temperature and relative humidity. These results are explored here in greater detail and possible causes are investigated. We examine whether particular metrics or sites unduly influence the collated results, whether results change according to time-scale aggregation and whether a lack of energy conservation in fluxtower data gives the empirical models an unfair advantage in the intercomparison. We demonstrate that energy conservation in the observational data is not responsible for these results. We also show that the partitioning between sensible and latent heat fluxes in LSMs, rather than the calculation of available energy, is the cause of the original findings. Finally, we present evidence suggesting that the nature of this partitioning problem is likely shared among all contributing LSMs. While we do not find a single candidate explanation forwhy land surface models perform poorly relative to empirical benchmarks in PLUMBER, we do exclude multiple possible explanations and provide guidance on where future research should focus.

  14. Heat waves measured with MODIS land surface temperature data predict changes in avian community structure

    Science.gov (United States)

    Thomas P. Albright; Anna M. Pidgeon; Chadwick D. Rittenhouse; Murray K. Clayton; Curtis H. Flather; Patrick D. Culbert; Volker C. Radeloff

    2011-01-01

    Heat waves are expected to become more frequent and severe as climate changes, with unknown consequences for biodiversity. We sought to identify ecologically-relevant broad-scale indicators of heat waves based on MODIS land surface temperature (LST) and interpolated air temperature data and assess their associations with avian community structure. Specifically, we...

  15. Multi-sensor remote sensing parameterization of heat fluxes over heterogeneous land surfaces

    NARCIS (Netherlands)

    Faivre, R.D.

    2014-01-01

    The parameterization of heat transfer by remote sensing, and based on SEBS scheme for turbulent heat fluxes retrieval, already proved to be very convenient for estimating evapotranspiration (ET) over homogeneous land surfaces. However, the use of such a method over heterogeneous landscapes (e.g.

  16. Microclimatic models. Estimation of components of the energy balance over land surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Heikinheimo, M.; Venaelaeinen, A.; Tourula, T. [Finnish Meteorological Inst., Helsinki (Finland). Air Quality Dept.

    1996-12-31

    Climates at regional scale are strongly dependent on the interaction between atmosphere and its lower boundary, the oceans and the land surface mosaic. Land surfaces influence climate through their albedo, and the aerodynamic roughness, the processes of the biosphere and many soil hydrological properties; all these factors vary considerably geographically. Land surfaces receive a certain portion of the solar irradiance depending on the cloudiness, atmospheric transparency and surface albedo. Short-wave solar irradiance is the source of the heat energy exchange at the earth`s surface and also regulates many biological processes, e.g. photosynthesis. Methods for estimating solar irradiance, atmospheric transparency and surface albedo were reviewed during the course of this project. The solar energy at earth`s surface is consumed for heating the soil and the lower atmosphere. Where moisture is available, evaporation is one of the key components of the surface energy balance, because the conversion of liquid water into water vapour consumes heat. The evaporation process was studied by carrying out field experiments and testing parameterisation for a cultivated agricultural surface and for lakes. The micrometeorological study over lakes was carried out as part of the international `Northern Hemisphere Climatic Processes Experiment` (NOPEX/BAHC) in Sweden. These studies have been aimed at a better understanding of the energy exchange processes of the earth`s surface-atmosphere boundary for a more accurate and realistic parameterisation of the land surface in atmospheric models

  17. Cloud tolerance of remote sensing technologies to measure land surface temperature

    Science.gov (United States)

    Conventional means to estimate land surface temperature (LST) from space relies on the thermal infrared (TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave (MW) obse...

  18. Impacts of Climate Change and Land use Changes on Land Surface Radiation and Energy Budgets

    Science.gov (United States)

    Land surface radiation and energy budgets are critical to address a variety of scientific and application issues related to climate trends, weather predictions, hydrologic and biogeophysical modeling, and the monitoring of ecosystem health and agricultural crops. This is an introductory paper to t...

  19. Study of Volcanic Activity at Different Time Scales Using Hypertemporal Land Surface Temperature Data

    NARCIS (Netherlands)

    Pavlidou, Efthymia; Hecker, Chris; van der Werff, Harald; van der Meijder, Mark

    2017-01-01

    We apply a method for detecting subtle spatiotemporal signal fluctuations to monitor volcanic activity. Whereas midwave infrared data are commonly used for volcanic hot spot detection, our approach utilizes hypertemporal longwave infrared-based land surface temperature (LST) data. Using LST data of

  20. Microclimatic models. Estimation of components of the energy balance over land surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Heikinheimo, M; Venaelaeinen, A; Tourula, T [Finnish Meteorological Inst., Helsinki (Finland). Air Quality Dept.

    1997-12-31

    Climates at regional scale are strongly dependent on the interaction between atmosphere and its lower boundary, the oceans and the land surface mosaic. Land surfaces influence climate through their albedo, and the aerodynamic roughness, the processes of the biosphere and many soil hydrological properties; all these factors vary considerably geographically. Land surfaces receive a certain portion of the solar irradiance depending on the cloudiness, atmospheric transparency and surface albedo. Short-wave solar irradiance is the source of the heat energy exchange at the earth`s surface and also regulates many biological processes, e.g. photosynthesis. Methods for estimating solar irradiance, atmospheric transparency and surface albedo were reviewed during the course of this project. The solar energy at earth`s surface is consumed for heating the soil and the lower atmosphere. Where moisture is available, evaporation is one of the key components of the surface energy balance, because the conversion of liquid water into water vapour consumes heat. The evaporation process was studied by carrying out field experiments and testing parameterisation for a cultivated agricultural surface and for lakes. The micrometeorological study over lakes was carried out as part of the international `Northern Hemisphere Climatic Processes Experiment` (NOPEX/BAHC) in Sweden. These studies have been aimed at a better understanding of the energy exchange processes of the earth`s surface-atmosphere boundary for a more accurate and realistic parameterisation of the land surface in atmospheric models

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

    Science.gov (United States)

    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.

  2. Modelling land surface fluxes of CO2 in response to climate change and nitrogen deposition

    DEFF Research Database (Denmark)

    Hansen, Kristina; Ambelas Skjøth, Carsten; Geels, Camilla

    Climate change, land use variations, and impacts of atmospheric nitrogen (N) deposition represent uncertainties for the prediction of future greenhouse gas exchange between land surfaces and the atmosphere as the mechanisms describing nutritional effects are not well developed in climate...... climate feedback mechanisms of CO2 between changes in management, land use practise, and climate change....

  3. Northern Alaskan land surface response to reduced Arctic sea ice extent

    Energy Technology Data Exchange (ETDEWEB)

    Higgins, Matthew E. [University of Colorado, Cooperative Institute for Research in Environmental Sciences, Boulder, CO (United States); Cassano, John J. [University of Colorado, Cooperative Institute for Research in Environmental Sciences, Department of Atmospheric and Oceanic Sciences, Boulder, CO (United States)

    2012-05-15

    With Arctic sea ice extent at near-record lows, an improved understanding of the relationship between sea ice and the land surface is warranted. We examine the land surface response to changing sea ice by first conducting a simulation using the Community Atmospheric Model version 3.1 with end of the twenty-first century sea ice extent. This future atmospheric response is then used to force the Weather and Research Forecasting Model version 3.1 to examine the terrestrial land surface response at high resolution over the North Slope of Alaska. Similar control simulations with twentieth century sea ice projections are also performed, and in both simulations only sea ice extent is altered. In the future sea ice extent experiment, atmospheric temperature increases significantly due to increases in latent and sensible heat flux, particularly in the winter season. Precipitation and snow pack increase significantly, and the increased snow pack contributes to warmer soil temperatures for most seasons by insulating the land surface. In the summer, however, soil temperatures are reduced due to increased albedo. Despite warmer near-surface atmospheric temperatures, it is found that spring melt is delayed throughout much of the North Slope due to the increased snow pack, and the growing season length is shortened. (orig.)

  4. Calibration of a distributed hydrology and land surface model using energy flux measurements

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl; Refsgaard, Jens Christian; Jensen, Karsten H.

    2016-01-01

    In this study we develop and test a calibration approach on a spatially distributed groundwater-surface water catchment model (MIKE SHE) coupled to a land surface model component with particular focus on the water and energy fluxes. The model is calibrated against time series of eddy flux measure...

  5. An Improved Method For Retrieving Land Surface Albedo Over Rugged Terrain

    NARCIS (Netherlands)

    Gao, B.; Jia, L.; Menenti, M.

    2014-01-01

    Land surface albedo is a very important parameter, which can be derived from a bidirectional reflectance distribution function (BRDF) model with angular integration of BRDF in a particular distribution of downward solar irradiance. The Algorithm for MODIS Bidirectional Reflectance Anisotropic of

  6. Using High-Resolution Satellite Aerosol Optical Depth To Estimate Daily PM2.5 Geographical Distribution in Mexico City.

    Science.gov (United States)

    Just, Allan C; Wright, Robert O; Schwartz, Joel; Coull, Brent A; Baccarelli, Andrea A; Tellez-Rojo, Martha María; Moody, Emily; Wang, Yujie; Lyapustin, Alexei; Kloog, Itai

    2015-07-21

    Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to the Mexico City area, a region with higher PM2.5 than most U.S. and European urban areas. Using a novel 1 km resolution AOD product from the MODIS instrument, we constructed daily predictions across the greater Mexico City area for 2004-2014. We calibrated the association of AOD to PM2.5 daily using municipal ground monitors, land use, and meteorological features. Predictions used spatial and temporal smoothing to estimate AOD when satellite data were missing. Our model performed well, resulting in an out-of-sample cross-validation R(2) of 0.724. Cross-validated root-mean-squared prediction error (RMSPE) of the model was 5.55 μg/m(3). This novel model reconstructs long- and short-term spatially resolved exposure to PM2.5 for epidemiological studies in Mexico City.

  7. Towards scale-independent land-surface flux estimates in Noah-MP

    Science.gov (United States)

    Thober, Stephan; Mizukami, Naoki; Samaniego, Luis; Attinger, Sabine; Clark, Martyn; Cuntz, Matthias

    2017-04-01

    Land-surface models use a variety of process representations to calculate terrestrial energy, water and biogeochemical fluxes. These process descriptions are usually derived from point measurements which are, in turn, scaled to much larger resolutions ranging from 1 km in catchment hydrology to 100 km in climate modelling. Both, hydrologic and climate models are nowadays run on different spatial resolutions, using the exactly same land surface representations. A fundamental criterion for the physical consistency of land-surface simulations across scales is that a flux estimated over a given area is independent of the spatial model resolution (i.e., the flux-matching criterion). The Noah-MP land surface model considers only one soil and land cover type per model grid cell without any representation of their subgrid variability, implying a weak flux-matching. A fractional approach simulates the subgrid variability but it requires a higher computational demand than using effective parameters and it is used only for land cover in current land surface schemes. A promising approach to derive scale-independent parameters is the Multiscale Parameter Regionalization (MPR) technique, which consists of two steps: first, it applies transfer functions directly to high-resolution data (such as 100 m soil maps) to derive high-resolution model parameter fields, acknowledging the full subgrid variability. Second, it upscales these high-resolution parameter fields to the model resolution by using appropriate upscaling operators. MPR has shown to improve substantially the scalability of the mesoscale Hydrologic Models mHM (Samaniego et al., 2010 WRR). Here, we apply the MPR technique to the Noah-MP land-surface model for a large sample of basins distributed across the contiguous USA. Specifically, we evaluate the flux-matching criterion for several hydrologic fluxes such as evapotranspiration and drainage at scales ranging from 3 km to 48 km. We investigate the impact of different

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2014-11-01

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

  10. Towards an Improved Represenation of Reservoirs and Water Management in a Land Surface-Hydrology Model

    Science.gov (United States)

    Yassin, F.; Anis, M. R.; Razavi, S.; Wheater, H. S.

    2017-12-01

    Water management through reservoirs, diversions, and irrigation have significantly changed river flow regimes and basin-wide energy and water balance cycles. Failure to represent these effects limits the performance of land surface-hydrology models not only for streamflow prediction but also for the estimation of soil moisture, evapotranspiration, and feedbacks to the atmosphere. Despite recent research to improve the representation of water management in land surface models, there remains a need to develop improved modeling approaches that work in complex and highly regulated basins such as the 406,000 km2 Saskatchewan River Basin (SaskRB). A particular challenge for regional and global application is a lack of local information on reservoir operational management. To this end, we implemented a reservoir operation, water abstraction, and irrigation algorithm in the MESH land surface-hydrology model and tested it over the SaskRB. MESH is Environment Canada's Land Surface-hydrology modeling system that couples Canadian Land Surface Scheme (CLASS) with hydrological routing model. The implemented reservoir algorithm uses an inflow-outflow relationship that accounts for the physical characteristics of reservoirs (e.g., storage-area-elevation relationships) and includes simplified operational characteristics based on local information (e.g., monthly target volume and release under limited, normal, and flood storage zone). The irrigation algorithm uses the difference between actual and potential evapotranspiration to estimate irrigation water demand. This irrigation demand is supplied from the neighboring reservoirs/diversion in the river system. We calibrated the model enabled with the new reservoir and irrigation modules in a multi-objective optimization setting. Results showed that the reservoir and irrigation modules significantly improved the MESH model performance in generating streamflow and evapotranspiration across the SaskRB and that this our approach provides

  11. Stable water isotope simulation by current land-surface schemes:Results of IPILPS phase 1

    Energy Technology Data Exchange (ETDEWEB)

    Henderson-Sellers, A.; Fischer, M.; Aleinov, I.; McGuffie, K.; Riley, W.J.; Schmidt, G.A.; Sturm, K.; Yoshimura, K.; Irannejad, P.

    2005-10-31

    Phase 1 of isotopes in the Project for Intercomparison of Land-surface Parameterization Schemes (iPILPS) compares the simulation of two stable water isotopologues ({sup 1}H{sub 2} {sup 18}O and {sup 1}H{sup 2}H{sup 16}O) at the land-atmosphere interface. The simulations are off-line, with forcing from an isotopically enabled regional model for three locations selected to offer contrasting climates and ecotypes: an evergreen tropical forest, a sclerophyll eucalypt forest and a mixed deciduous wood. Here we report on the experimental framework, the quality control undertaken on the simulation results and the method of intercomparisons employed. The small number of available isotopically-enabled land-surface schemes (ILSSs) limits the drawing of strong conclusions but, despite this, there is shown to be benefit in undertaking this type of isotopic intercomparison. Although validation of isotopic simulations at the land surface must await more, and much more complete, observational campaigns, we find that the empirically-based Craig-Gordon parameterization (of isotopic fractionation during evaporation) gives adequately realistic isotopic simulations when incorporated in a wide range of land-surface codes. By introducing two new tools for understanding isotopic variability from the land surface, the Isotope Transfer Function and the iPILPS plot, we show that different hydrological parameterizations cause very different isotopic responses. We show that ILSS-simulated isotopic equilibrium is independent of the total water and energy budget (with respect to both equilibration time and state), but interestingly the partitioning of available energy and water is a function of the models' complexity.

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

    Science.gov (United States)

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

    2017-12-01

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

  13. An assessment of the land surface emissivity in the 8 - 12 micrometer window determined from ASTER and MODIS data

    Science.gov (United States)

    Schmugge, T.; Hulley, G.; Hook, S.

    2009-04-01

    The land surface emissivity is often overlooked when considering surface properties that effect the energy balance. However, knowledge of the emissivity in the window region is important for determining the longwave radiation balance and its subsequent effect on surface temperature. The net longwave radiation (NLR) is strongly affected by the difference between the temperature of the emitting surface and the sky brightness temperature, this difference will be the greatest in the window region. Outside the window region any changes in the emitted radiation by emissivity variability are mostly compensated for by changes in the reflected sky brightness. The emissivity variability is typically greatest in arid regions where the exposed soil and rock surfaces display the widest range of emissivity. For example, the dune regions of North Africa have emissivities of 0.7 or less in the 8 to 9 micrometer wavelength band due to the quartz sands of the region, which can produce changes in NLR of more than 10 w/m*m compared to assuming a constant emissivity. The errors in retrievals of atmospheric temperature and moisture profiles from hyperspectral infrared radiances, such as those from the Atmospheric Infrared Sounder (AIRS) on the NASA Aqua satellite result from using constant or inaccurate surface emissivities, particularly over arid and semi-arid regions here the variation in emissivity is large, both spatially and spectrally. The multispectral thermal infrared data obtained from the Advanced Spaceborne Thermal Emission and Reflection (ASTER) radiometer and MODerate resolution Imaging Spectrometer (MODIS) sensors on NASA's Terra satellite have been shown to be of good quality and provide a unique new tool for studying the emissivity of the land surface. ASTER has 5 channels in the 8 to 12 micrometer waveband with 90 m spatial resolution, when the data are combined with the Temperature Emissivity Separation (TES) algorithm the surface emissivity over this wavelength region

  14. MODIS/Aqua Land Surface Temperature/3-Band Emissivity 8-Day L3 Global 1km SIN Grid V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Aqua Land Surface Temperature/3-Band Emissivity 8-Day L3 Global 1km SIN Grid (MYD21A2.006). A new suite of MODIS Land Surface Temperature (LST) and Emissivity...

  15. MODIS/Terra Land Surface Temperature/3-Band Emissivity 8-Day L3 Global 1km SIN Grid V006

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS/Terra Land Surface Temperature/3-Band Emissivity 8-Day L3 Global 1km SIN Grid (MOD21A2.006). A new suite of MODIS Land Surface Temperature (LST) and Emissivity...

  16. State-dependent errors in a land surface model across biomes inferred from eddy covariance observations on multiple timescales

    NARCIS (Netherlands)

    Wang, T.; Brender, P.; Ciais, P.; Piao, S.; Mahecha, M.D.; Chevallier, F.; Reichstein, M.; Ottle, C.; Maignan, F.; Arain, A.; Bohrer, G.; Cescatti, A.; Kiely, G.; Law, B.E.; Lutz, M.; Montagnani, L.; Moors, E.J.

    2012-01-01

    Characterization of state-dependent model biases in land surface models can highlight model deficiencies, and provide new insights into model development. In this study, artificial neural networks (ANNs) are used to estimate the state-dependent biases of a land surface model (ORCHIDEE: ORganising

  17. Estimation of Daily Air Temperature Based on MODIS Land Surface Temperature Products over the Corn Belt in the US

    Directory of Open Access Journals (Sweden)

    Linglin Zeng

    2015-01-01

    Full Text Available Air temperature (Ta is a key input in a wide range of agroclimatic applications. Moderate Resolution Imaging Spectroradiometer (MODIS Ts (Land Surface Temperature (LST products are widely used to estimate daily Ta. However, only daytime LST (Ts-day or nighttime LST (Ts-night data have been used to estimate Tmax/Tmin (daily maximum or minimum air temperature, respectively. The relationship between Tmax and Ts-night, and the one between Tmin and Ts-day has not been studied. In this study, both the ability of Ts-night data to estimate Tmax and the ability of Ts-day data to estimate Tmin were tested and studied in the Corn Belt during the growing season (May–September from 2008 to 2012, using MODIS daily LST products from both Terra and Aqua. The results show that using Ts-night for estimating Tmax could result in a higher accuracy than using Ts-day for a similar estimate. Combining Ts-day and Ts-night, the estimation of Tmax was improved by 0.19–1.85, 0.37–1.12 and 0.26–0.93 °C for crops, deciduous forest and developed areas, respectively, when compared with using only Ts-day or Ts-night data. The main factors influencing the Ta estimation errors spatially and temporally were analyzed and discussed, such as satellite overpassing time, air masses, irrigation, etc.

  18. Flood Simulations and Uncertainty Analysis for the Pearl River Basin Using the Coupled Land Surface and Hydrological Model System

    Directory of Open Access Journals (Sweden)

    Yongnan Zhu

    2017-06-01

    Full Text Available The performances of hydrological simulations for the Pearl River Basin in China were analysed using the Coupled Land Surface and Hydrological Model System (CLHMS. Three datasets, including East Asia (EA, high-resolution gauge satellite-merged China Merged Precipitation Analysis (CMPA-Daily, and the Asian Precipitation Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE daily precipitation were used to drive the CLHMS model to simulate daily hydrological processes from 1998 to 2006. The results indicate that the precipitation data was the most important source of uncertainty in the hydrological simulation. The simulated streamflow driven by the CMPA-Daily agreed well with observations, with a Pearson correlation coefficient (PMC greater than 0.70 and an index of agreement (IOA similarity coefficient greater than 0.82 at Liuzhou, Shijiao, and Wuzhou Stations. Comparison of the Nash-Sutcliffe efficiency coefficient (NSE shows that the peak flow simulation ability of CLHMS driven with the CMPA-Daily rainfall is relatively superior to that with the EA and APHRODITE datasets. The simulation results for the high-flow periods in 1998 and 2005 indicate that the CLHMS is promising for its future application in the flood simulation and prediction.

  19. TRMM-Based Lightning Climatology

    Science.gov (United States)

    Cecil, Daniel J.; Buechler, Dennis E.; Blakeslee, Richard J.

    2011-01-01

    Gridded climatologies of total lightning flash rates seen by the spaceborne Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) have been updated. OTD collected data from May 1995 to March 2000. LIS data (equatorward of about 38 deg) has been added for 1998-2010. Flash counts from each instrument are scaled by the best available estimates of detection efficiency. The long LIS record makes the merged climatology most robust in the tropics and subtropics, while the high latitude data is entirely from OTD. The mean global flash rate from the merged climatology is 46 flashes per second. The peak annual flash rate at 0.5 deg scale is 160 fl/square km/yr in eastern Congo. The peak monthly average flash rate at 2.5 scale is 18 fl/square km/mo, from early April to early May in the Brahmaputra Valley of far eastern India. Lightning decreases in this region during the monsoon season, but increases further north and west. A monthly average peak from early August to early September in northern Pakistan also exceeds any monthly averages from Africa, despite central Africa having the greatest yearly average. Most continental regions away from the equator have an annual cycle with lightning flash rates peaking in late spring or summer. The main exceptions are India and southeast Asia, with springtime peaks in April and May. For landmasses near the equator, flash rates peak near the equinoxes. For many oceanic regions, the peak flash rates occur in autumn. This is particularly noticeable for the Mediterranean and North Atlantic. Landmasses have a strong diurnal cycle of lightning, with flash rates generally peaking between 3-5 pm local solar time. The central United States flash rates peak later, in late evening or early night. Flash rates peak after midnight in northern Argentina. These regions are known for large, intense, long-lived mesoscale convective systems.

  20. WRF Simulation over the Eastern Africa by use of Land Surface Initialization

    Science.gov (United States)

    Sakwa, V. N.; Case, J.; Limaye, A. S.; Zavodsky, B.; Kabuchanga, E. S.; Mungai, J.

    2014-12-01

    The East Africa region experiences severe weather events associated with hazards of varying magnitude. It receives heavy precipitation which leads to wide spread flooding and lack of sufficient rainfall in some parts results into drought. Cases of flooding and drought are two key forecasting challenges for the Kenya Meteorological Service (KMS). The source of heat and moisture depends on the state of the land surface which interacts with the boundary layer of the atmosphere to produce excessive precipitation or lack of it that leads to severe drought. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface within weakly-sheared environments, such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in numerical weather prediction models. Improved modeling capabilities within the region have the potential to enhance forecast guidance in support of daily operations and high-impact weather over East Africa. KMS currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Non-hydrostatic Mesoscale Model (NMM) dynamical core. They make use of the National Oceanic and Atmospheric Administration / National Weather Service Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the WRF-NMM model runs on a 7-km regional grid over Eastern Africa.SPoRT and SERVIR provide land surface initialization datasets and model verification tool. The NASA Land Information System (LIS) provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Model verification is done using the Model Evaluation Tools (MET) package, in order

  1. 2-way coupling the hydrological land surface model PROMET with the regional climate model MM5

    Directory of Open Access Journals (Sweden)

    F. Zabel

    2013-05-01

    Full Text Available Most land surface hydrological models (LSHMs consider land surface processes (e.g. soil–plant–atmosphere interactions, lateral water flows, snow and ice in a spatially detailed manner. The atmosphere is considered as exogenous driver, neglecting feedbacks between the land surface and the atmosphere. On the other hand, regional climate models (RCMs generally simulate land surface processes through coarse descriptions and spatial scales but include land–atmosphere interactions. What is the impact of the differently applied model physics and spatial resolution of LSHMs on the performance of RCMs? What feedback effects are induced by different land surface models? This study analyses the impact of replacing the land surface module (LSM within an RCM with a high resolution LSHM. A 2-way coupling approach was applied using the LSHM PROMET (1 × 1 km2 and the atmospheric part of the RCM MM5 (45 × 45 km2. The scaling interface SCALMET is used for down- and upscaling the linear and non-linear fluxes between the model scales. The change in the atmospheric response by MM5 using the LSHM is analysed, and its quality is compared to observations of temperature and precipitation for a 4 yr period from 1996 to 1999 for the Upper Danube catchment. By substituting the Noah-LSM with PROMET, simulated non-bias-corrected near-surface air temperature improves for annual, monthly and daily courses when compared to measurements from 277 meteorological weather stations within the Upper Danube catchment. The mean annual bias was improved from −0.85 to −0.13 K. In particular, the improved afternoon heating from May to September is caused by increased sensible heat flux and decreased latent heat flux as well as more incoming solar radiation in the fully coupled PROMET/MM5 in comparison to the NOAH/MM5 simulation. Triggered by the LSM replacement, precipitation overall is reduced; however simulated precipitation amounts are still of high uncertainty, both

  2. A Global Ozone Climatology from Ozone Soundings via Trajectory Mapping: A Stratospheric Perspective

    Science.gov (United States)

    Liu, J. J.; Tarasick, D. W.; Fioletov, V. E.; McLinden, C.; Zhao, T.; Gong, S.; Sioris, G.; Jin, J. J.; Liu, G.; Moeini, O.

    2013-01-01

    This study explores a domain-filling trajectory approach to generate a global ozone climatology from sparse ozonesonde data. Global ozone soundings of 51,898 profiles at 116 stations over 44 years (1965-2008) are used, from which forward and backward trajectories are performed for 4 days, driven by a set of meteorological reanalysis data. Ozone mixing ratios of each sounding from the surface to 26 km altitude are assigned to the entire path along the trajectory. The resulting global ozone climatology is archived monthly for five decades from the 1960s to the 2000s with grids of 5 degree 5 degree 1 km (latitude, longitude, and altitude). It is also archived yearly from 1965 to 2008. This climatology is validated at 20 ozonesonde stations by comparing the actual ozone sounding profile with that found through the trajectories, using the ozone soundings at all the stations except one being tested. The two sets of profiles are in good agreement, both individually with correlation coefficients between 0.975 and 0.998 and root mean square (RMS) differences of 87 to 482 ppbv, and overall with a correlation coefficient of 0.991 and an RMS of 224 ppbv. The ozone climatology is also compared with two sets of satellite data, from the Satellite Aerosol and Gas Experiment (SAGE) and the Optical Spectrography and InfraRed Imager System (OSIRIS). Overall, the ozone climatology compares well with SAGE and OSIRIS data by both seasonal and zonal means. The mean difference is generally under 20 above 15 km. The comparison is better in the northern hemisphere, where there are more ozonesonde stations, than in the southern hemisphere; it is also better in the middle and high latitudes than in the tropics, where assimilated winds are imperfect in some regions. This ozone climatology can capture known features in the stratosphere, as well as seasonal and decadal variations of these features. Furthermore, it provides a wealth of detail about longitudinal variations in the stratosphere such

  3. Los Alamos Climatology 2016 Update

    Energy Technology Data Exchange (ETDEWEB)

    Bruggeman, David Alan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-02-10

    The Los Alamos National Laboratory (LANL or the Laboratory) operates a meteorology monitoring network to support LANL emergency response, engineering designs, environmental compliance, environmental assessments, safety evaluations, weather forecasting, environmental monitoring, research programs, and environmental restoration. Weather data has been collected in Los Alamos since 1910. Bowen (1990) provided climate statistics (temperature and precipitation) for the 1961– 1990 averaging period, and included other analyses (e.g., wind and relative humidity) based on the available station locations and time periods. This report provides an update to the 1990 publication Los Alamos Climatology (Bowen 1990).

  4. Towards a long-term Science Exploitation Plan for the Sea and Land Surface Temperature Radiometer on Sentinel-3 and the Along-Track Scanning Radiometers

    Science.gov (United States)

    Remedios, John J.; Llewellyn-Jones, David

    2014-05-01

    The Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel-3 is the latest satellite instrument in a series of dual-angle optical and thermal sensors, the Along-Track Scanning Radiometers (ATSRs). Operating on Sentinel-3, the SLSTR has a number of significant improvements compared to the original ATSRs including wider swaths for nadir and dual angles, emphasis on all surface temperature domains, dedicated fire channels and additional cloud channels. The SLSTR therefore provides some excellent opportunities to extend science undertaken with the ATSRs whilst also providing long-term data sets to investigate climate change. The European Space Agency, together with the Department of Energy and Climate Change, sponsored the production of an Exploitation Plan for the ATSRs. In the last year, this been extended to cover the SLSTR also. The plan enables UK and European member states to plan activities related to SLSTR in a long-term context. Covering climate change, oceanography, land surface, atmosphere and cryosphere science, particular attention is paid to the exploitation of long-term data sets. In the case of SLSTR, relevant products include sea, land, lake and ice surface temperatures; aerosols and clouds; fires and gas flares; land surface reflectances. In this presentation, the SLSTR and ATSR science Exploitation Plan will be outlined with emphasis on SLSTR science opportunities, on appropriate co-ordinating mechanisms and on example implementation plans. Particular attention will be paid to the challenges of linking ATSR records with SLSTR to provide consistent long-term data sets, and on the international context of such data sets. The exploitation plan approach to science may prove relevant and useful for other Sentinel instruments.

  5. Advancing of Land Surface Temperature Retrieval Using Extreme Learning Machine and Spatio-Temporal Adaptive Data Fusion Algorithm

    Directory of Open Access Journals (Sweden)

    Yang Bai

    2015-04-01

    Full Text Available As a critical variable to characterize the biophysical processes in ecological environment, and as a key indicator in the surface energy balance, evapotranspiration and urban heat islands, Land Surface Temperature (LST retrieved from Thermal Infra-Red (TIR images at both high temporal and spatial resolution is in urgent need. However, due to the limitations of the existing satellite sensors, there is no earth observation which can obtain TIR at detailed spatial- and temporal-resolution simultaneously. Thus, several attempts of image fusion by blending the TIR data from high temporal resolution sensor with data from high spatial resolution sensor have been studied. This paper presents a novel data fusion method by integrating image fusion and spatio-temporal fusion techniques, for deriving LST datasets at 30 m spatial resolution from daily MODIS image and Landsat ETM+ images. The Landsat ETM+ TIR data were firstly enhanced based on extreme learning machine (ELM algorithm using neural network regression model, from 60 m to 30 m resolution. Then, the MODIS LST and enhanced Landsat ETM+ TIR data were fused by Spatio-temporal Adaptive Data Fusion Algorithm for Temperature mapping (SADFAT in order to derive high resolution synthetic data. The synthetic images were evaluated for both testing and simulated satellite images. The average difference (AD and absolute average difference (AAD are smaller than 1.7 K, where the correlation coefficient (CC and root-mean-square error (RMSE are 0.755 and 1.824, respectively, showing that the proposed method enhances the spatial resolution of the predicted LST images and preserves the spectral information at the same time.

  6. The Impact of Model and Rainfall Forcing Errors on Characterizing Soil Moisture Uncertainty in Land Surface Modeling

    Science.gov (United States)

    Maggioni, V.; Anagnostou, E. N.; Reichle, R. H.

    2013-01-01

    The contribution of rainfall forcing errors relative to model (structural and parameter) uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM), forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from satellite rainfall products. The ensemble satellite rain fields are propagated through CLSM to produce soil moisture ensembles. Errors in CLSM are modeled with two different approaches: either by perturbing model parameters (representing model parameter uncertainty) or by adding randomly generated noise (representing model structure and parameter uncertainty) to the model prognostic variables. Our findings highlight that the method currently used in the NASA GEOS-5 Land Data Assimilation System to perturb CLSM variables poorly describes the uncertainty in the predicted soil moisture, even when combined with rainfall model perturbations. On the other hand, by adding model parameter perturbations to rainfall forcing perturbations, a better characterization of uncertainty in soil moisture simulations is observed. Specifically, an analysis of the rank histograms shows that the most consistent ensemble of soil moisture is obtained by combining rainfall and model parameter perturbations. When rainfall forcing and model prognostic perturbations are added, the rank histogram shows a U-shape at the domain average scale, which corresponds to a lack of variability in the forecast ensemble. The more accurate estimation of the soil moisture prediction uncertainty obtained by combining rainfall and parameter perturbations is encouraging for the application of this approach in ensemble data assimilation systems.

  7. Evaluation of root water uptake in the ISBA-A-gs land surface model using agricultural yield statistics over France

    Science.gov (United States)

    Canal, N.; Calvet, J.-C.; Decharme, B.; Carrer, D.; Lafont, S.; Pigeon, G.

    2014-12-01

    The simulation of root water uptake in land surface models is affected by large uncertainties. The difficulty in mapping soil depth and in describing the capacity of plants to develop a rooting system is a major obstacle to the simulation of the terrestrial water cycle and to the representation of the impacts of drought. In this study, long time series of agricultural statistics are used to evaluate and constrain root water uptake models. The inter-annual variability of cereal grain yield and permanent grassland dry matter yield is simulated over France by the Interactions between Soil, Biosphere and Atmosphere, CO2-reactive (ISBA-A-gs) generic land surface model (LSM). The two soil profile schemes available in the model are used to simulate the above-ground biomass (Bag) of cereals and grasslands: a two-layer force-restore (FR-2L) bulk reservoir model and a multi-layer diffusion (DIF) model. The DIF model is implemented with or without deep soil layers below the root zone. The evaluation of the various root water uptake models is achieved by using the French agricultural statistics of Agreste over the 1994-2010 period at 45 cropland and 48 grassland départements, for a range of rooting depths. The number of départements where the simulated annual maximum Bag presents a significant correlation with the yield observations is used as a metric to benchmark the root water uptake models. Significant correlations (p value neutral impact of the most refined versions of the model is found with respect to the simplified soil hydrology scheme. This shows that efforts should be made in future studies to reduce other sources of uncertainty, e.g. by using a more detailed soil and root density profile description together with satellite vegetation products. It is found that modelling additional subroot-zone base flow soil layers does not improve (and may even degrade) the representation of the inter-annual variability of the vegetation above-ground biomass. These results are

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

    Science.gov (United States)

    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

  9. Detecting geothermal anomalies and evaluating LST geothermal component by combining thermal remote sensing time series and land surface model data

    Science.gov (United States)

    Romaguera, Mireia; Vaughan, R. Greg; Ettema, J.; Izquierdo-Verdiguier, E.; Hecker, C. A.; van der Meer, F.D.

    2018-01-01

    This paper explores for the first time the possibilities to use two land surface temperature (LST) time series of different origins (geostationary Meteosat Second Generation satellite data and Noah land surface modelling, LSM), to detect geothermal anomalies and extract the geothermal component of LST, the LSTgt. We hypothesize that in geothermal areas the LSM time series will underestimate the LST as compared to the remote sensing data, since the former does not account for the geothermal component in its model.In order to extract LSTgt, two approaches of different nature (physical based and data mining) were developed and tested in an area of about 560 × 560 km2 centered at the Kenyan Rift. Pre-dawn data in the study area during the first 45 days of 2012 were analyzed.The results show consistent spatial and temporal LSTgt patterns between the two approaches, and systematic differences of about 2 K. A geothermal area map from surface studies was used to assess LSTgt inside and outside the geothermal boundaries. Spatial means were found to be higher inside the geothermal limits, as well as the relative frequency of occurrence of high LSTgt. Results further show that areas with strong topography can result in anomalously high LSTgt values (false positives), which suggests the need for a slope and aspect correction in the inputs to achieve realistic results in those areas. The uncertainty analysis indicates that large uncertainties of the input parameters may limit detection of LSTgt anomalies. To validate the approaches, higher spatial resolution images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data over the Olkaria geothermal field were used. An established method to estimate radiant geothermal flux was applied providing values between 9 and 24 W/m2 in the geothermal area, which coincides with the LSTgt flux rates obtained with the proposed approaches.The proposed approaches are a first step in estimating LSTgt

  10. The NEWS Water Cycle Climatology

    Science.gov (United States)

    Rodell, M.; Beaudoing, H. K.; L'Ecuyer, T.; Olson, W. S.

    2012-12-01

    NASA's Energy and Water Cycle Study (NEWS) program fosters collaborative research towards improved quantification and prediction of water and energy cycle consequences of climate change. In order to measure change, it is first necessary to describe current conditions. The goal of the first phase of the NEWS Water and Energy Cycle Climatology project was to develop "state of the global water cycle" and "state of the global energy cycle" assessments based on data from modern ground and space based observing systems and data integrating models. The project was a multi-institutional collaboration with more than 20 active contributors. This presentation will describe the results of the water cycle component of the first phase of the project, which include seasonal (monthly) climatologies of water fluxes over land, ocean, and atmosphere at continental and ocean basin scales. The requirement of closure of the water budget (i.e., mass conservation) at various scales was exploited to constrain the flux estimates via an optimization approach that will also be described. Further, error assessments were included with the input datasets, and we examine these in relation to inferred uncertainty in the optimized flux estimates in order to gauge our current ability to close the water budget within an expected uncertainty range.

  11. The NEWS Water Cycle Climatology

    Science.gov (United States)

    Rodell, Matthew; Beaudoing, Hiroko Kato; L'Ecuyer, Tristan; William, Olson

    2012-01-01

    NASA's Energy and Water Cycle Study (NEWS) program fosters collaborative research towards improved quantification and prediction of water and energy cycle consequences of climate change. In order to measure change, it is first necessary to describe current conditions. The goal of the first phase of the NEWS Water and Energy Cycle Climatology project was to develop "state of the global water cycle" and "state of the global energy cycle" assessments based on data from modern ground and space based observing systems and data integrating models. The project was a multi-institutional collaboration with more than 20 active contributors. This presentation will describe the results of the water cycle component of the first phase of the project, which include seasonal (monthly) climatologies of water fluxes over land, ocean, and atmosphere at continental and ocean basin scales. The requirement of closure of the water budget (i.e., mass conservation) at various scales was exploited to constrain the flux estimates via an optimization approach that will also be described. Further, error assessments were included with the input datasets, and we examine these in relation to inferred uncertainty in the optimized flux estimates in order to gauge our current ability to close the water budget within an expected uncertainty range.

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

    Science.gov (United States)

    Molthan, Andrew; Burks, Jason; Bell, Jordan

    2016-01-01

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

  13. Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach

    CSIR Research Space (South Africa)

    Marshall, M

    2013-03-01

    Full Text Available , latent energy (LE: ET energy equivalent) during the rainy season is the primary regulator after solar forcing of energy balance seasonal variability, the strength of which changes signifi- cantly across land cover types (Ramier et al., 2009). At inter... Table 1. Acronyms and their definitions in order of appearance. Acronym Definition ET Evapotranspiration LE Latent Heat LSM Land Surface Model NDVI Normalized Difference Vegetation Index PET Potential Evapotranspiration AMMA African Monsoon...

  14. Impact of dynamic vegetation phenology on the simulated pan-Arctic land surface state

    Science.gov (United States)

    Teufel, Bernardo; Sushama, Laxmi; Arora, Vivek K.; Verseghy, Diana

    2018-03-01

    The pan-Arctic land surface is undergoing rapid changes in a warming climate, with near-surface permafrost projected to degrade significantly during the twenty-first century. Vegetation-related feedbacks have the potential to influence the rate of degradation of permafrost. In this study, the impact of dynamic phenology on the pan-Arctic land surface state, particularly near-surface permafrost, for the 1961-2100 period, is assessed by comparing two simulations of the Canadian Land Surface Scheme (CLASS)—one with dynamic phenology, modelled using the Canadian Terrestrial Ecosystem Model (CTEM), and the other with prescribed phenology. These simulations are forced by atmospheric data from a transient climate change simulation of the 5th generation Canadian Regional Climate Model (CRCM5) for the Representative Concentration Pathway 8.5 (RCP8.5). Comparison of the CLASS coupled to CTEM simulation to available observational estimates of plant area index, spatial distribution of permafrost and active layer thickness suggests that the model captures reasonably well the overall distribution of vegetation and permafrost. It is shown that the most important impact of dynamic phenology on the land surface occurs through albedo and it is demonstrated for the first time that vegetation control on albedo during late spring and early summer has the highest potential to impact the degradation of permafrost. While both simulations show extensive near-surface permafrost degradation by the end of the twenty-first century, the strong projected response of vegetation to climate warming and increasing CO2 concentrations in the coupled simulation results in accelerated permafrost degradation in the northernmost continuous permafrost regions.

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

    Science.gov (United States)

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

    2015-12-01

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

  16. Coupling a groundwater model with a land surface model to improve water and energy cycle simulation

    Directory of Open Access Journals (Sweden)

    W. Tian

    2012-12-01

    Full Text Available Water and energy cycles interact, making these two processes closely related. Land surface models (LSMs can describe the water and energy cycles on the land surface, but their description of the subsurface water processes is oversimplified, and lateral groundwater flow is ignored. Groundwater models (GWMs describe the dynamic movement of the subsurface water well, but they cannot depict the physical mechanisms of the evapotranspiration (ET process in detail. In this study, a coupled model of groundwater flow with a simple biosphere (GWSiB is developed based on the full coupling of a typical land surface model (SiB2 and a 3-D variably saturated groundwater model (AquiferFlow. In this coupled model, the infiltration, ET and energy transfer are simulated by SiB2 using the soil moisture results from the groundwater flow model. The infiltration and ET results are applied iteratively to drive the groundwater flow model. After the coupled model is built, a sensitivity test is first performed, and the effect of the groundwater depth and the hydraulic conductivity parameters on the ET are analyzed. The coupled model is then validated using measurements from two stations located in shallow and deep groundwater depth zones. Finally, the coupled model is applied to data from the middle reach of the Heihe River basin in the northwest of China to test the regional simulation capabilities of the model.

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

    Science.gov (United States)

    Li, Bailing; Rodell, Matthew; Zaitchik, Benjamin F.; Reichle, Rolf H.; Koster, Randal D.; van Dam, Tonie M.

    2012-01-01

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

  18. Towards an improved Land Surface Phenology mapping using a new MODIS product: A case study of Bavarian Forest National Park

    Science.gov (United States)

    Misra, Gourav; Buras, Allan; Asam, Sarah; Menzel, Annette

    2017-04-01

    State Ministry of the Environment and Consumer Protection. References: 1. Fisher, J.I.; Mustard, J.F. Cross-scalar satellite phenology from ground, Landsat, and MODIS data. Remote Sens. Environ. 2007, 109, 261-273. 2. Misra, G.; Buras, A.; Menzel, A. Effects of Different Methods on the Comparison be-tween Land Surface and Ground Phenology—A Methodological Case Study from South-Western Germany. Remote Sens. 2016, 8, 753. 3. Asam, S.; Callegari, M.; Fiore, G.; Matiu, M.; De Gregorio, L.; Jacob, A.; Staab, J.; Men-zel, A.; Notarnicola, C. Analysis of spatiotemporal variations of climate, snow cover and plant phenology over the Alps. 2017 (in preparation). 4. Stöckli, R.; Rutishauser, T.; Dragoni, D.; O'Keefe, J.; Thornton, P. E.; Jolly, M.; Lu, L.; Denning, A. S. Remote sensing data assimilation for a prognostic phenology model. Journal of Geophysical Research: Biogeosciences. 2008, 113.

  19. Estimating Climatological Bias Errors for the Global Precipitation Climatology Project (GPCP)

    Science.gov (United States)

    Adler, Robert; Gu, Guojun; Huffman, George

    2012-01-01

    A procedure is described to estimate bias errors for mean precipitation by using multiple estimates from different algorithms, satellite sources, and merged products. The Global Precipitation Climatology Project (GPCP) monthly product is used as a base precipitation estimate, with other input products included when they are within +/- 50% of the GPCP estimates on a zonal-mean basis (ocean and land separately). The standard deviation s of the included products is then taken to be the estimated systematic, or bias, error. The results allow one to examine monthly climatologies and the annual climatology, producing maps of estimated bias errors, zonal-mean errors, and estimated errors over large areas such as ocean and land for both the tropics and the globe. For ocean areas, where there is the largest question as to absolute magnitude of precipitation, the analysis shows spatial variations in the estimated bias errors, indicating areas where one should have more or less confidence in the mean precipitation estimates. In the tropics, relative bias error estimates (s/m, where m is the mean precipitation) over the eastern Pacific Ocean are as large as 20%, as compared with 10%-15% in the western Pacific part of the ITCZ. An examination of latitudinal differences over ocean clearly shows an increase in estimated bias error at higher latitudes, reaching up to 50%. Over land, the error estimates also locate regions of potential problems in the tropics and larger cold-season errors at high latitudes that are due to snow. An empirical technique to area average the gridded errors (s) is described that allows one to make error estimates for arbitrary areas and for the tropics and the globe (land and ocean separately, and combined). Over the tropics this calculation leads to a relative error estimate for tropical land and ocean combined of 7%, which is considered to be an upper bound because of the lack of sign-of-the-error canceling when integrating over different areas with a

  20. National Satellite Land Remote Sensing Data Archive

    Science.gov (United States)

    Faundeen, John L.; Kelly, Francis P.; Holm, Thomas M.; Nolt, Jenna E.

    2013-01-01

    The National Satellite Land Remote Sensing Data Archive (NSLRSDA) resides at the U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center. Through the Land Remote Sensing Policy Act of 1992, the U.S. Congress directed the Department of the Interior (DOI) to establish a permanent Government archive containing satellite remote sensing data of the Earth's land surface and to make this data easily accessible and readily available. This unique DOI/USGS archive provides a comprehensive, permanent, and impartial observational record of the planet's land surface obtained throughout more than five decades of satellite remote sensing. Satellite-derived data and information products are primary sources used to detect and understand changes such as deforestation, desertification, agricultural crop vigor, water quality, invasive plant species, and certain natural hazards such as flood extent and wildfire scars.

  1. Spatiotemporal Variability of Land Surface Phenology in China from 2001–2014

    Directory of Open Access Journals (Sweden)

    Zhaohui Luo

    2017-01-01

    Full Text Available Land surface phenology is a highly sensitive and simple indicator of vegetation dynamics and climate change. However, few studies on spatiotemporal distribution patterns and trends in land surface phenology across different climate and vegetation types in China have been conducted since 2000, a period during which China has experienced remarkably strong El Niño events. In addition, even fewer studies have focused on changes of the end of season (EOS and length of season (LOS despite their importance. In this study, we used four methods to reconstruct Moderate Resolution Imaging Spectroradiometer (MODIS Enhanced Vegetation Index (EVI dataset and chose the best smoothing result to estimate land surface phenology. Then, the phenophase trends were analyzed via the Mann-Kendall method. We aimed to assess whether trends in land surface phenology have continued since 2000 in China at both national and regional levels. We also sought to determine whether trends in land surface phenology in subtropical or high altitude areas are the same as those observed in high latitude areas and whether those trends are uniform among different vegetation types. The result indicated that the start of season (SOS was progressively delayed with increasing latitude and altitude. In contrast, EOS exhibited an opposite trend in its spatial distribution, and LOS showed clear spatial patterns over this region that decreased from south to north and from east to west at a national scale. The trend of SOS was advanced at a national level, while the trend in Southern China and the Tibetan Plateau was opposite to that in Northern China. The transaction zone of the SOS within Northern China and Southern China occurred approximately between 31.4°N and 35.2°N. The trend in EOS and LOS were delayed and extended, respectively, at both national and regional levels except that of LOS in the Tibetan Plateau, which was shortened by delayed SOS onset more than by delayed EOS onset. The

  2. Estimation of Key Parameters of the Coupled Energy and Water Model by Assimilating Land Surface Data

    Science.gov (United States)

    Abdolghafoorian, A.; Farhadi, L.

    2017-12-01

    Accurate estimation of land surface heat and moisture fluxes, as well as root zone soil moisture, is crucial in various hydrological, meteorological, and agricultural applications. Field measurements of these fluxes are costly and cannot be readily scaled to large areas relevant to weather and climate studies. Therefore, there is a need for techniques to make quantitative estimates of heat and moisture fluxes using land surface state observations that are widely available from remote sensing across a range of scale. In this work, we applies the variational data assimilation approach to estimate land surface fluxes and soil moisture profile from the implicit information contained Land Surface Temperature (LST) and Soil Moisture (SM) (hereafter the VDA model). The VDA model is focused on the estimation of three key parameters: 1- neutral bulk heat transfer coefficient (CHN), 2- evaporative fraction from soil and canopy (EF), and 3- saturated hydraulic conductivity (Ksat). CHN and EF regulate the partitioning of available energy between sensible and latent heat fluxes. Ksat is one of the main parameters used in determining infiltration, runoff, groundwater recharge, and in simulating hydrological processes. In this study, a system of coupled parsimonious energy and water model will constrain the estimation of three unknown parameters in the VDA model. The profile of SM (LST) at multiple depths is estimated using moisture diffusion (heat diffusion) equation. In this study, the uncertainties of retrieved unknown parameters and fluxes are estimated from the inverse of Hesian matrix of cost function which is computed using the Lagrangian methodology. Analysis of uncertainty provides valuable information about the accuracy of estimated parameters and their correlation and guide the formulation of a well-posed estimation problem. The results of proposed algorithm are validated with a series of experiments using a synthetic data set generated by the simultaneous heat and

  3. Transitioning Enhanced Land Surface Initialization and Model Verification Capabilities to the Kenya Meteorological Department (KMD)

    Science.gov (United States)

    Case, Jonathan L.; Mungai, John; Sakwa, Vincent; Zavodsky, Bradley T.; Srikishen, Jayanthi; Limaye, Ashutosh; Blankenship, Clay B.

    2016-01-01

    Flooding, severe weather, and drought are key forecasting challenges for the Kenya Meteorological Department (KMD), based in Nairobi, Kenya. Atmospheric processes leading to convection, excessive precipitation and/or prolonged drought can be strongly influenced by land cover, vegetation, and soil moisture content, especially during anomalous conditions and dry/wet seasonal transitions. It is thus important to represent accurately land surface state variables (green vegetation fraction, soil moisture, and soil temperature) in Numerical Weather Prediction (NWP) models. The NASA SERVIR and the Short-term Prediction Research and Transition (SPoRT) programs in Huntsville, AL have established a working partnership with KMD to enhance its regional modeling capabilities. SPoRT and SERVIR are providing experimental land surface initialization datasets and model verification capabilities for capacity building at KMD. To support its forecasting operations, KMD is running experimental configurations of the Weather Research and Forecasting (WRF; Skamarock et al. 2008) model on a 12-km/4-km nested regional domain over eastern Africa, incorporating the land surface datasets provided by NASA SPoRT and SERVIR. SPoRT, SERVIR, and KMD participated in two training sessions in March 2014 and June 2015 to foster the collaboration and use of unique land surface datasets and model verification capabilities. Enhanced regional modeling capabilities have the potential to improve guidance in support of daily operations and high-impact weather and climate outlooks over Eastern Africa. For enhanced land-surface initialization, the NASA Land Information System (LIS) is run over Eastern Africa at 3-km resolution, providing real-time land surface initialization data in place of interpolated global model soil moisture and temperature data available at coarser resolutions. Additionally, real-time green vegetation fraction (GVF) composites from the Suomi-NPP VIIRS instrument is being incorporated

  4. Climatology and Impact of Convection on the Tropical Tropopause Layer

    Science.gov (United States)

    Robertson, Franklin; Pittman, Jasna

    2007-01-01

    Water vapor plays an important role in controlling the radiative balance and the chemical composition of the Tropical Tropopause Layer (TTL). Mechanisms ranging from slow transport and dehydration under thermodynamic equilibrium conditions to fast transport in convection have been proposed as regulators of the amount of water vapor in this layer. However,.details of these mechanisms and their relative importance remain poorly understood, The recently completed Tropical Composition, Cloud, and Climate Coupling (TC4) campaign had the opportunity to sample the.TTL over the Eastern Tropical Pacific using ground-based, airborne, and spaceborne instruments. The main goal of this study is to provide the climatological context for this campaign of deep and overshooting convective activity using various satellite observations collected during the summertime. We use the Microwave Humidity Sensor (MRS) aboard the NOAA-18 satellite to investigate the horizontal extent.and the frequency of convection reaching and penetrating into the TTL. We use the Moderate Resolution I1l1aging Spectroradiometer (MODIS) aboard the Aqua satellite to investigate the frequency distribution of daytime cirrus clouds. We use the Tropical Rainfall Measuring Mission(TRMM) and CloudSat to investigate the vertical structure and distribution of hydrometeors in the convective cells, In addition to cloud measurements; we investigate the impact that convection has on the concentration of radiatively important gases such as water vapor and ozone in the TTL by examining satellite measurement obtained from the Microwave Limb Sounder(MLS) aboard the Aura satellite.

  5. Climatological features of blocking anticyclones

    International Nuclear Information System (INIS)

    Lupo, A.R.; Smith, P.J.; Oglesby, R.J.

    1994-01-01

    Several climatological studies have been previously performed using large observational data sets (i.e., 10 years or longer) in order to determine the predominant characteristics of blocking anticyclones, including favored development regions, duration, preferred seasonal occurrence, and frequency of occurrence. These studies have shown that blocking anticyclones occur most frequently from October to April over the eastern Atlantic and Pacific oceans downstream from both the North American and Asian continental regions and the storm track regions to the east of these continents. Some studies have also revealed the presence of a third region block formation in western Russia near 40 degrees E which is associated with another storm track region over the Mediterranean and western Asia

  6. Intercomparison of Satellite Dust Retrieval Products over the West African Sahara During the Fennec Campaign in June 2011

    Science.gov (United States)

    Banks, J.R.; Brindley, H. E.; Flamant, C.; Garay, M. J.; Hsu, N. C.; Kalashnikova, O. V.; Klueser, L.; Sayer, A. M.

    2013-01-01

    Dust retrievals over the Sahara Desert during June 2011 from the IASI, MISR, MODIS, and SEVIRI satellite instruments are compared against each other in order to understand the strengths and weaknesses of each retrieval approach. Particular attention is paid to the effects of meteorological conditions, land surface properties, and the magnitude of the dust loading. The period of study corresponds to the time of the first Fennec intensive measurement campaign, which provides new ground-based and aircraft measurements of the dust characteristics and loading. Validation using ground-based AERONET sunphotometer data indicate that of the satellite instruments, SEVIRI is most able to retrieve dust during optically thick dust events, whereas IASI and MODIS perform better at low dust loadings. This may significantly affect observations of dust emission and the mean dust climatology. MISR and MODIS are least sensitive to variations in meteorological conditions, while SEVIRI tends to overestimate the aerosol optical depth (AOD) under moist conditions (with a bias against AERONET of 0.31), especially at low dust loadings where the AODproperties on the retrievals is also investigated. Over elevated surfaces IASI retrieves AODs which are most consistent with AERONET observations, while the AODs retrieved by MODIS tend to be biased low. In contrast, over the least emissive surfaces IASI significantly underestimates the AOD (with a bias of -0.41), while MISR and SEVIRI show closest agreement.

  7. NLDAS Noah Land Surface Model L4 Hourly 0.125 x 0.125 degree V002 (NLDAS_NOAH0125_H) at GES DISC

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation...

  8. CMIP5 land surface models systematically underestimate inter-annual variability of net ecosystem exchange in semi-arid southwestern North America.

    Science.gov (United States)

    MacBean, N.; Scott, R. L.; Biederman, J. A.; Vuichard, N.; Hudson, A.; Barnes, M.; Fox, A. M.; Smith, W. K.; Peylin, P. P.; Maignan, F.; Moore, D. J.

    2017-12-01

    Recent studies based on analysis of atmospheric CO2 inversions, satellite data and terrestrial biosphere model simulations have suggested that semi-arid ecosystems play a dominant role in the interannual variability and long-term trend in the global carbon sink. These studies have largely cited the response of vegetation activity to changing moisture availability as the primary mechanism of variability. However, some land surface models (LSMs) used in these studies have performed poorly in comparison to satellite-based observations of vegetation dynamics in semi-arid regions. Further analysis is therefore needed to ensure semi-arid carbon cycle processes are well represented in global scale LSMs before we can fully establish their contribution to the global carbon cycle. In this study, we evaluated annual net ecosystem exchange (NEE) simulated by CMIP5 land surface models using observations from 20 Ameriflux sites across semi-arid southwestern North America. We found that CMIP5 models systematically underestimate the magnitude and sign of NEE inter-annual variability; therefore, the true role of semi-arid regions in the global carbon cycle may be even more important than previously thought. To diagnose the factors responsible for this bias, we used the ORCHIDEE LSM to test different climate forcing data, prescribed vegetation fractions and model structures. Climate and prescribed vegetation do contribute to uncertainty in annual NEE simulations, but the bias is primarily caused by incorrect timing and magnitude of peak gross carbon fluxes. Modifications to the hydrology scheme improved simulations of soil moisture in comparison to data. This in turn improved the seasonal cycle of carbon uptake due to a more realistic limitation on photosynthesis during water stress. However, the peak fluxes are still too low, and phenology is poorly represented for desert shrubs and grasses. We provide suggestions on model developments needed to tackle these issues in the future.

  9. NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Temperature (LST) Environmental Data Record (EDR) from IDPS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of Land Surface Temperature (LST) from the Visible Infrared Imaging Radiometer Suite...

  10. MODIS/Aqua Land Surface Temperature/Emissivity 8-Day L3 Global 0.05Deg CMG V041

    Data.gov (United States)

    National Aeronautics and Space Administration — The MYD11C2.041 dataset was decommissioned as of March 1, 2018. Users are encouraged to use Version 6 of MODIS/Aqua Land Surface Temperature and Emissivity Daily L3...

  11. GLDAS Noah Land Surface Model L4 3 Hourly 1.0 x 1.0 degree Subsetted V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains a series of land surface parameters simulated from the Noah 2.7.1 model in the Global Land Data Assimilation System (GLDAS). The data are in...

  12. Measurements of land surface features using an airborne laser altimeter: the HAPEX-Sahel experiment

    International Nuclear Information System (INIS)

    Ritchie, J.C.; Menenti, M.; Weltz, M.A.

    1997-01-01

    An airborne laser profiling altimeter was used to measure surface features and properties of the landscape during the HAPEX-Sahel Experiment in Niger, Africa in September 1992. The laser altimeter makes 4000 measurements per second with a vertical resolution of 5 cm. Airborne laser and detailed field measurements of vegetation heights had similar average heights and frequency distribution. Laser transects were used to estimate land surface topography, gully and channel morphology, and vegetation properties ( height, cover and distribution). Land surface changes related to soil erosion and channel development were measured. For 1 km laser transects over tiger bush communities, the maximum vegetation height was between 4-5 and 6-5 m, with an average height of 21 m. Distances between the centre of rows of tiger bush vegetation averaged 100 m. For two laser transects, ground cover for tiger bush was estimated to be 225 and 301 per cent for vegetation greater than 0-5m tall and 190 and 25-8 per cent for vegetation greater than 10m tall. These values are similar to published values for tiger bush. Vegetation cover for 14 and 18 km transects was estimated to be 4 per cent for vegetation greater than 0-5 m tall. These cover values agree within 1-2 per cent with published data for short transects (⩾ 100 m) for the area. The laser altimeter provided quick and accurate measurements for evaluating changes in land surface features. Such information provides a basis for understanding land degradation and a basis for management plans to rehabilitate the landscape. (author)

  13. An Algorithm for Retrieving Land Surface Temperatures Using VIIRS Data in Combination with Multi-Sensors

    Science.gov (United States)

    Xia, Lang; Mao, Kebiao; Ma, Ying; Zhao, Fen; Jiang, Lipeng; Shen, Xinyi; Qin, Zhihao

    2014-01-01

    A practical algorithm was proposed to retrieve land surface temperature (LST) from Visible Infrared Imager Radiometer Suite (VIIRS) data in mid-latitude regions. The key parameter transmittance is generally computed from water vapor content, while water vapor channel is absent in VIIRS data. In order to overcome this shortcoming, the water vapor content was obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) data in this study. The analyses on the estimation errors of vapor content and emissivity indicate that when the water vapor errors are within the range of ±0.5 g/cm2, the mean retrieval error of the present algorithm is 0.634 K; while the land surface emissivity errors range from −0.005 to +0.005, the mean retrieval error is less than 1.0 K. Validation with the standard atmospheric simulation shows the average LST retrieval error for the twenty-three land types is 0.734 K, with a standard deviation value of 0.575 K. The comparison between the ground station LST data indicates the retrieval mean accuracy is −0.395 K, and the standard deviation value is 1.490 K in the regions with vegetation and water cover. Besides, the retrieval results of the test data have also been compared with the results measured by the National Oceanic and Atmospheric Administration (NOAA) VIIRS LST products, and the results indicate that 82.63% of the difference values are within the range of −1 to 1 K, and 17.37% of the difference values are within the range of ±2 to ±1 K. In a conclusion, with the advantages of multi-sensors taken fully exploited, more accurate results can be achieved in the retrieval of land surface temperature. PMID:25397919

  14. Hyper-Resolution Global Land Surface Model at Regional-to-Local Scales with observed Groundwater data assimilation

    OpenAIRE

    Singh, Raj Shekhar

    2014-01-01

    Modeling groundwater is challenging: it is not readily visible and is difficult to measure, with limited sets of observations available. Even though groundwater models can reproduce water table and head variations, considerable drift in modeled land surface states can nonetheless result from partially known geologic structure, errors in the input forcing fields, and imperfect Land Surface Model (LSM) parameterizations. These models frequently have biased results that are very different from o...

  15. Urban percent impervious surface and its relationship with land surface temperature in Yantai City, China

    International Nuclear Information System (INIS)

    Yu, Xinyang; Lu, Changhe

    2014-01-01

    This study investigated percent impervious surface area (PISA) extracted by a four-endmember normalized spectral mixture analysis (NSMA) method and evaluated the reliability of PISA as an indicator of land surface temperature (LST). Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) images for Yantai city, eastern China obtained from USGS were used as the main data source. The results demonstrated that four-endmember NSMA method performed better than the typical three-endmember one, and there was a strong linear relationship between LST and PISA for the two images, which suggest percent impervious surface area provides an alternative parameter for analyzing LST quantitatively in urban areas

  16. Understanding Changes in Modeled Land Surface Characteristics Prior to Lightning-Initiated Holdover Fire Breakout

    Science.gov (United States)

    Schultz, Christopher J.; Case, Jonathan L.; Hain, Christopher R.; White, Kristopher; Wachter, J. Brent; Nauslar, Nicholas; MacNamara, Brittany

    2018-01-01

    Lightning initiated wildfires are only 16% of the total number of wildfires within the United States, but account for 56% of the acreage burned. One of the challenges with lightning-initiated wildfires is their ability to "holdover" which means smolder for up to 2+ weeks before breaking out into a full fledged fire. This work helps characterize the percentage of holdover events due to lightning, and helps quantify changes in the land surface characteristics to help understand trends in soil moisture and vegetation stress that potentially contribute to the fire breaking out into a full wildfire.

  17. Underground black-coal mining and its impact on the land surface

    International Nuclear Information System (INIS)

    Pollmann, H.J.; Wilke, F.L.

    1994-01-01

    This book wants to describe the special requirements and consequences resulting from natural conditions at the deposit as well as from decisions and processes of mining operations. On this basis it should be possible to assess the degree to which the impact of mining on defined areas of the land surface can be influenced with reasonable effort. Furthermore, the consequences from conditions governing mining activities for the planning and realization of mining operations and their impact and the granting of permissions and approvals on the part of the mining authorities are discussed. (HS) [de

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

    Science.gov (United States)

    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

  19. Modeling large-scale human alteration of land surface hydrology and climate

    Science.gov (United States)

    Pokhrel, Yadu N.; Felfelani, Farshid; Shin, Sanghoon; Yamada, Tomohito J.; Satoh, Yusuke

    2017-12-01

    Rapidly expanding human activities have profoundly affected various biophysical and biogeochemical processes of the Earth system over a broad range of scales, and freshwater systems are now amongst the most extensively altered ecosystems. In this study, we examine the human-induced changes in land surface water and energy balances and the associated climate impacts using a coupled hydrological-climate model framework which also simulates the impacts of human activities on the water cycle. We present three sets of analyses using the results from two model versions—one with and the other without considering human activities; both versions are run in offline and coupled mode resulting in a series of four experiments in total. First, we examine climate and human-induced changes in regional water balance focusing on the widely debated issue of the desiccation of the Aral Sea in central Asia. Then, we discuss the changes in surface temperature as a result of changes in land surface energy balance due to irrigation over global and regional scales. Finally, we examine the global and regional climate impacts of increased atmospheric water vapor content due to irrigation. Results indicate that the direct anthropogenic alteration of river flow in the Aral Sea basin resulted in the loss of 510 km3 of water during the latter half of the twentieth century which explains about half of the total loss of water from the sea. Results of irrigation-induced changes in surface energy balance suggest a significant surface cooling of up to 3.3 K over 1° grids in highly irrigated areas but a negligible change in land surface temperature when averaged over sufficiently large global regions. Results from the coupled model indicate a substantial change in 2 m air temperature and outgoing longwave radiation due to irrigation, highlighting the non-local (regional and global) implications of irrigation. These results provide important insights on the direct human alteration of land surface

  20. Reply to comment by Ma and Zhang on "Rescaling the complementary relationship for land surface evaporation"

    Science.gov (United States)

    Crago, Richard; Qualls, Russell; Szilagyi, Jozsef; Huntington, Justin

    2017-07-01

    Ma and Zhang (2017) note a concern they have with our rescaled Complementary Relationship (CR) for land surface evaporation when daily average wind speeds are very low (perhaps less than 1 m/s). We discuss conditions and specific formulations that lead to this concern, but ultimately argue that under these conditions, a key assumption behind the CR itself may not be satisfied at the daily time scale. Thus, careful consideration of the reliability of the CR is needed when wind speeds are very low.

  1. Convective climatology over the southwest U.S. and Mexico from passive microwave and infrared data

    Science.gov (United States)

    Negri, Andrew J.; Howard, Kenneth W.; Keehn, Peter R.; Maddox, Robert A.; Adler, Robert F.

    1992-01-01

    Passive microwave data from the Special Sensor Microwave Imager (SSM/I) were used to estimate the amount of rainfall in the June-August season for the regions of the southwest U.S. and Mexico, and the results are compared to rain-gauge observations and to IR climatologies of Maddox et al. (1992), using both the hourly IR data and IR data sampled at the time of the overpass of the SSM/I. A comparison of the microwave climatology with monthly rainfall measured by the climatological gage network over several states of western Mexico resulted in a 0.63 correlation and a large (482 mm) bias, due to sampling and the incongruity of rain gages and satellite estimates. A comparison between the IR and microwave data showed that the IR tended toward higher percentages along the coast compared to the microwave.

  2. Impact of Soil Moisture Assimilation on Land Surface Model Spin-Up and Coupled LandAtmosphere Prediction

    Science.gov (United States)

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

    2016-01-01

    Advances in satellite monitoring of the terrestrial water cycle have led to a concerted effort to assimilate soil moisture observations from various platforms into offline land surface models (LSMs). One principal but still open question is that of the ability of land data assimilation (LDA) to improve LSM initial conditions for coupled short-term weather prediction. In this study, the impact of assimilating Advanced Microwave Scanning Radiometer for EOS (AMSR-E) soil moisture retrievals on coupled WRF Model forecasts is examined during the summers of dry (2006) and wet (2007) surface conditions in the southern Great Plains. LDA is carried out using NASAs Land Information System (LIS) and the Noah LSM through an ensemble Kalman filter (EnKF) approach. The impacts of LDA on the 1) soil moisture and soil temperature initial conditions for WRF, 2) land-atmosphere coupling characteristics, and 3) ambient weather of the coupled LIS-WRF simulations are then assessed. Results show that impacts of soil moisture LDA during the spin-up can significantly modify LSM states and fluxes, depending on regime and season. Results also indicate that the use of seasonal cumulative distribution functions (CDFs) is more advantageous compared to the traditional annual CDF bias correction strategies. LDA performs consistently regardless of atmospheric forcing applied, with greater improvements seen when using coarser, global forcing products. Downstream impacts on coupled simulations vary according to the strength of the LDA impact at the initialization, where significant modifications to the soil moisture flux- PBL-ambient weather process chain are observed. Overall, this study demonstrates potential for future, higher-resolution soil moisture assimilation applications in weather and climate research.

  3. The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins

    KAUST Repository

    Yang, Zong-Liang

    2011-06-24

    The augmented Noah land surface model described in the first part of the two-part series was evaluated here over global river basins. Across various climate zones, global-scale tests can reveal a model\\'s weaknesses and strengths that a local-scale testing cannot. In addition, global-scale tests are more challenging than local- and catchment-scale tests. Given constant model parameters (e. g., runoff parameters) across global river basins, global-scale tests are more stringent. We assessed model performance against various satellite and ground-based observations over global river basins through six experiments that mimic a transition from the original Noah LSM to the fully augmented version. The model shows transitional improvements in modeling runoff, soil moisture, snow, and skin temperature, despite considerable increase in computational time by the fully augmented Noah-MP version compared to the original Noah LSM. The dynamic vegetation model favorably captures seasonal and spatial variability of leaf area index and green vegetation fraction. We also conducted 36 ensemble experiments with 36 combinations of optional schemes for runoff, leaf dynamics, stomatal resistance, and the β factor. Runoff schemes play a dominant and different role in controlling soil moisture and its relationship with evapotranspiration compared to ecological processes such as β the factor, vegetation dynamics, and stomatal resistance. The 36-member ensemble mean of runoff performs better than any single member over the world\\'s 50 largest river basins, suggesting a great potential of land-based ensemble simulations for climate prediction. Copyright © 2011 by the American Geophysical Union.

  4. Estimation of Land Surface Temperature through Blending MODIS and AMSR-E Data with the Bayesian Maximum Entropy Method

    Directory of Open Access Journals (Sweden)

    Xiaokang Kou

    2016-01-01

    Full Text Available Land surface temperature (LST plays a major role in the study of surface energy balances. Remote sensing techniques provide ways to monitor LST at large scales. However, due to atmospheric influences, significant missing data exist in LST products retrieved from satellite thermal infrared (TIR remotely sensed data. Although passive microwaves (PMWs are able to overcome these atmospheric influences while estimating LST, the data are constrained by low spatial resolution. In this study, to obtain complete and high-quality LST data, the Bayesian Maximum Entropy (BME method was introduced to merge 0.01° and 0.25° LSTs inversed from MODIS and AMSR-E data, respectively. The result showed that the missing LSTs in cloudy pixels were filled completely, and the availability of merged LSTs reaches 100%. Because the depths of LST and soil temperature measurements are different, before validating the merged LST, the station measurements were calibrated with an empirical equation between MODIS LST and 0~5 cm soil temperatures. The results showed that the accuracy of merged LSTs increased with the increasing quantity of utilized data, and as the availability of utilized data increased from 25.2% to 91.4%, the RMSEs of the merged data decreased from 4.53 °C to 2.31 °C. In addition, compared with the filling gap method in which MODIS LST gaps were filled with AMSR-E LST directly, the merged LSTs from the BME method showed better spatial continuity. The different penetration depths of TIR and PMWs may influence fusion performance and still require further studies.

  5. Effects of post-fire wood management strategies on vegetation recovery and land surface temperature (LST) estimated from Landsat images

    Science.gov (United States)

    Vlassova, Lidia; Pérez-Cabello, Fernando

    2016-02-01

    The study contributes remote sensing data to the discussion about effects of post-fire wood management strategies on forest regeneration. Land surface temperature (LST) and Normalized Differenced Vegetation Index (NDVI), estimated from Landsat-8 images are used as indicators of Pinus halepensis ecosystem recovery after 2008 fire in areas of three post-fire treatments: (1) salvage logging with wood extraction from the site on skidders in suspended position (SL); (2) snag shredding in situ leaving wood debris in place (SS) performed two years after the event; and (3) non-intervention control areas (CL) where all snags were left standing. Six years after the fire NDVI values ∼0.5 estimated from satellite images and field radiometry indicate considerable vegetation recovery due to efficient regeneration traits developed by the dominant plant species. However, two years after management activities in part of the burnt area, the effect of SL and SS on ecosystem recovery is observed in terms of both LST and NDVI. Statistically significant differences are detected between the intervened areas (SL and SS) and control areas of non-intervention (CL); no difference is registered between zones of different intervention types (SL and SS). CL areas are on average 1 °C cooler and 10% greener than those corresponding to either SL or SS, because of the beneficial effects of burnt wood residuals, which favor forest recovery through (i) enhanced nutrient cycling in soils, (ii) avoidance of soil surface disturbance and mechanical damage of seedlings typical to the managed areas, and (iii) ameliorated microclimate. The results of the study show that in fire-resilient ecosystems, such as P. halepensis forests, NDVI is higher and LST is lower in areas with no management intervention, being an indication of more favorable conditions for vegetation regeneration.

  6. The investigation of spatiotemporal variations of land surface temperature based on land use changes using NDVI in southwest of Iran

    Science.gov (United States)

    Fathizad, Hassan; Tazeh, Mahdi; Kalantari, Saeideh; Shojaei, Saeed

    2017-10-01

    Land use changes can bring about changes in land surface temperature (LST) which is influenced by climatic conditions and physical characteristics of the land surface. In this study, spatiotemporal variations of land surface temperature have been investigated in the desert area of Dasht-e-Abbas, Ilam, based on a variety of land use changes. The investigated periods for the study include 1990, 2000 and 2010 using Landsat image data. First, in mapping land use we used the Fuzzy ARTMAP Neural Network Classification method followed by determination of the NDVI Index to estimate land surface temperature. The results show an increase in LST in areas where degradation, land use and land cover changes have occurred. In 1990, 2000 and 2010, the average land surface temperature of the Fair Rangelands was 26.72 °C, 30.06 °C and 30.95 °C, respectively. This rangeland has been reduced by about 5%. For poor rangelands, the average LSTs were 26.95, 32.83 and 34.49 Cº, respectively which had a 18% reduction. In 1990, 2000 and 2010, the average land surface temperatures of agricultural lands were 24.31 °C, 27.87 °C and 28.61 °C, respectively which has been an increasing trend. The reason can be attributed to changes in cropping patterns of the study area.

  7. Introduction to Global Urban Climatology

    Science.gov (United States)

    Varquez, A. C. G.; Kanda, M.; Kawano, N.; Darmanto, N. S.; Dong, Y.

    2016-12-01

    Urban heat island (UHI) is a widely investigated phenomenon in the field of urban climate characterized by the warming of urban areas relative to its surrounding rural environs. Being able to understand the mechanism behind the UHI formation of a city and distinguish its impact from that of global climate change is indispensable when identifying adaptation and mitigation strategies. However, the lack of UHI studies many cities especially for developing countries makes it difficult to generalize the mechanism for UHI formation. Thus, there is an impending demand for studies that focus on the simultaneous analyses of UHI and its trends throughout the world. Hence, we propose a subfield of urban climatology, called "global urban climatology" (GUC), which mainly focuses on the uniform understanding of urban climates across all cities, globally. By using globally applicable methodologies to quantify and compare urban heat islands of cities with diverse backgrounds, including their geography, climate, socio-demography, and other factors, a universal understanding of the mechanisms underlying the formation of the phenomenon can be established. The implementation of GUC involves the use of globally acquired historical observation networks, gridded meteorological parameters from climate models, global geographic information system datasets; the construction of a distributed urban parameter database; and the development of techniques necessary to model the urban climate. Research under GUC can be categorized into three approaches. The collaborative approach (1st) relies on the collection of data from micro-scale experiments conducted worldwide with the aid or development of professional social networking platforms; the analytical approach (2nd) relies on the use of global weather station datasets and their corresponding objectively analysed global outputs; and the numerical approach (3rd) relies on the global estimation of high-resolution urban-representative parameters as

  8. Developing MODIS-based cloud climatologies to aid species distribution modeling and conservation activities

    Directory of Open Access Journals (Sweden)

    Michael William Douglas

    2016-10-01

    Full Text Available WorldClim (Hijmans et al. 2005 has been the de-facto source of basic climatological analyses for most species distribution modeling research and conservation science applications because of its global coverage and fine (<1 km spatial resolution.  However, it has been recognized since its development that there are limitations in data-poor regions, especially with regard to the precipitation analyses.  Here we describe procedures to develop a satellite-based daytime cloudiness climatology that better reflects the variations in vegetation cover in many regions of the globe than do the WorldClim precipitation products.  Moderate Resolution Imaging Spectroradiometer (MODIS imagery from the National Aeronautics and Space Administration (NASA Terra and Aqua sun-synchronous satellites have recently been used to develop multi-year climatologies of cloudiness.  Several procedures exist for developing such climatologies.  We first discuss a simple procedure that uses brightness thresholds to identify clouds.  We compare these results with those from a more complex procedure: the MODIS Cloud Mask product, recently averaged into climatological products by Wilson and Jetz (2016.  We discuss advantages and limitations of both approaches.  We also speculate on further work that will be needed to improve the usefulness of these MODIS-based climatologies of cloudiness. Despite limitations of current MODIS-based climatology products, they have the potential to greatly improve our understanding of the distribution of biota across the globe.  We show examples from oceanic islands and arid coastlines in the subtropics and tropics where the MODIS products should be of special value in predicting the observed vegetation cover.  Some important applications of reliable climatologies based on MODIS imagery products will include 1 helping to restore long-degraded cloud-impacted environments; 2 improving estimations of the spatial distribution of cloud

  9. Climatological Implications of Deep-Rooting in Water-Limited Ecosystems

    Science.gov (United States)

    Amenu, G. G.; Kumar, P.

    2005-12-01

    In vegetated ecosystems, plants are the primary channels that connect the soil with the atmosphere (through water, energy, carbon, and nutrient cycles), with plant roots controlling the below-ground dynamics. Recently, several observational evidences are emerging which suggests the existence of plant roots much deeper in the soil/rock profile than the depth usually perceived in existing hydroclimatological and hydroecological models. In this study, using land surface model, we assess the effects of vegetation deep-rooting on (a) moisture and temperature redistribution in the soil profile, (b) energy flux partitioning at the land surface, and (c) net primary productivity of vegetated ecosystems. Three sites characterized by different vegetation, soil, and climate (all located in arid to sub-humid regions of the United States) were studied. The sites include the Mogollon Rim in Arizona, the Edwards Plateau in Texas, and the Southern Piedmont in Georgia. Soil depths of up to 10 m are investigated. Results of this modeling effort and its implications for climatological modeling will be presented.

  10. International Satellite Cloud Climatology Project, D-Series (Superseded)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — ISCCP D-Series has been superseded by a newer version. Users should not use ISCCP D-Series except in rare cases (e.g., when reproducing previous studies that used...

  11. Ozone climatology over western Mediterranean Sea

    International Nuclear Information System (INIS)

    Pibiri, G.; Randaccio, P.; Serra, A.; Sollai, A.

    1984-01-01

    A preliminary climatology of atmospheric ozone over Western Mediterranean Sea is given by analysis of the upper observations of O 3 carried out at Cagliari-Elmas station from 1968 to 1976. Some peculiarities are here illustrated and discussed

  12. Global Daily Climatology Network: Kazakhstan subset

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset is a compilation of in situ daily meteorological observations for Kazakhstan within the framework of joint efforts to create Global Daily Climatology...

  13. Northeast Pacific Regional Climatology (NCEI Accession 0163799)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Northeast Pacific (NEP) new regional climatology is derived from the NCEI World Ocean Database archive of temperature and salinity and covers a time period from...

  14. Northwest Atlantic Regional Climatology (NCEI Accession 0155889)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — To provide an improved oceanographic foundation and reference for multi-disciplinary studies of the Northwest Atlantic Ocean, NCEI Regional Climatology Team...

  15. U.S. Annual Climatological Summaries

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Annual Climatological Summary contains historical monthly and annual summaries for over 8000 U.S. locations. Observing stations are located in the United States of...

  16. Quality Controlled Local Climatological Data (QCLCD) Publication

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quality Controlled Local Climatological Data (QCLCD) contains summaries from major airport weather stations that include a daily account of temperature extremes,...

  17. Climatology of the Savannah River Plant site

    International Nuclear Information System (INIS)

    Hoel, D.D.

    1984-06-01

    This document contains information on the climatological characteristics of the SRP site, as well as information on relative concentrations and deposition for specific radionuclides. 42 references, 42 figures, 45 tables

  18. Derivation of Land Surface Albedo at High Resolution by Combining HJ-1A/B Reflectance Observations with MODIS BRDF Products

    OpenAIRE

    Gao, Bo; Jia, Li; Wang, Tianxing

    2014-01-01

    Land surface albedo is an essential parameter for monitoring global/regional climate and land surface energy balance. Although many studies have been conducted on global or regional land surface albedo using various remote sensing data over the past few decades, land surface albedo product with a high spatio-temporal resolution is currently very scarce. This paper proposes a method for deriving land surface albedo with a high spatio-temporal resolution (space: 30 m and time: 2-4 days). The pr...

  19. SPATIAL AND TEMPORAL VARIATION OF LAND SURFACE TEMPERATURE IN FUJIAN PROVINCE FROM 2001 TO 2015

    Directory of Open Access Journals (Sweden)

    Y. Li

    2018-04-01

    Full Text Available Land surface temperature (LST is an essential parameter in the physics of land surface processes. The spatiotemporal variations of LST on the Fujian province were studied using AQUA Moderate Resolution Imaging Spectroradiometer LST data. Considering the data gaps in remotely sensed LST products caused by cloud contamination, the Savitzky-Golay (S-G filter method was used to eliminate the influence of cloud cover and to describe the periodical signals of LST. Observed air temperature data from 27 weather stations were employed to evaluate the fitting performance of the S-G filter method. Results indicate that S-G can effectively fit the LST time series and remove the influence of cloud cover. Based on the S-G-derived result, Spatial and temporal Variations of LST in Fujian province from 2001 to 2015 are analysed through slope analysis. The results show that: 1 the spatial distribution of annual mean LST generally exhibits consistency with altitude in the study area and the average of LST was much higher in the east than in the west. 2 The annual mean temperature of LST declines slightly among 15 years in Fujian. 3 Slope analysis reflects the spatial distribution characteristics of LST changing trend in Fujian.Improvement areas of LST are mainly concentrated in the urban areas of Fujian, especially in the eastern urban areas. Apparent descent areas are mainly distributed in the area of Zhangzhou and eastern mountain area.

  20. Globalland30 Mapping Capacity of Land Surface Water in Thessaly, Greece

    Directory of Open Access Journals (Sweden)

    Ioannis Manakos

    2014-12-01

    Full Text Available The National Geomatics Center of China (NGCC produced Global Land Cover (GlobalLand30 maps with 30 m spatial resolution for the years 2000 and 2009–2010, responding to the need for harmonized, accurate, and high-resolution global land cover data. This study aims to assess the mapping accuracy of the land surface water layer of GlobalLand30 for 2009–2010. A representative Mediterranean region, situated in Greece, is considered as the case study area, with 2009 as the reference year. The assessment is realized through an object-based comparison of the GlobalLand30 water layer with the ground truth and visually interpreted data from the Hellenic Cadastre fine spatial resolution (0.5 m orthophoto map layer. GlobCover 2009, GlobCorine 2009, and GLCNMO 2008 corresponding thematic layers are utilized to show and quantify the progress brought along with the increment of the spatial resolution, from 500 m to 300 m and finally to 30 m with the newly produced GlobalLand30 maps. GlobalLand30 detected land surface water areas show a 91.9% overlap with the reference data, while the coarser resolution products are restricted to lower accuracies. Validation is extended to the drainage network elements, i.e., rivers and streams, where GlobalLand30 outperforms the other global map products, as well.

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

    Science.gov (United States)

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

    2015-10-01

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

  2. Spatial and Temporal Variation of Land Surface Temperature in Fujian Province from 2001 TO 2015

    Science.gov (United States)

    Li, Y.; Wang, X.; Ding, Z.

    2018-04-01

    Land surface temperature (LST) is an essential parameter in the physics of land surface processes. The spatiotemporal variations of LST on the Fujian province were studied using AQUA Moderate Resolution Imaging Spectroradiometer LST data. Considering the data gaps in remotely sensed LST products caused by cloud contamination, the Savitzky-Golay (S-G) filter method was used to eliminate the influence of cloud cover and to describe the periodical signals of LST. Observed air temperature data from 27 weather stations were employed to evaluate the fitting performance of the S-G filter method. Results indicate that S-G can effectively fit the LST time series and remove the influence of cloud cover. Based on the S-G-derived result, Spatial and temporal Variations of LST in Fujian province from 2001 to 2015 are analysed through slope analysis. The results show that: 1) the spatial distribution of annual mean LST generally exhibits consistency with altitude in the study area and the average of LST was much higher in the east than in the west. 2) The annual mean temperature of LST declines slightly among 15 years in Fujian. 3) Slope analysis reflects the spatial distribution characteristics of LST changing trend in Fujian.Improvement areas of LST are mainly concentrated in the urban areas of Fujian, especially in the eastern urban areas. Apparent descent areas are mainly distributed in the area of Zhangzhou and eastern mountain area.

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

    Science.gov (United States)

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

    2018-01-12

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

  4. Quantitative estimation of land surface evapotranspiration in Taiwan based on MODIS data

    Directory of Open Access Journals (Sweden)

    Che-sheng Zhan

    2011-09-01

    Full Text Available Land surface evapotranspiration (ET determines the local and regional water-heat balances. Accurate estimation of regional surface ET provides a scientific basis for the formulation and implementation of water conservation programs. This study set up a table of the momentum roughness length and zero-plane displacement related with land cover and an empirical relationship between land surface temperature and air temperature. A revised quantitative remote sensing ET model, the SEBS-Taiwan model, was developed. Based on Moderate Resolution Imaging Spectroradiometer (MODIS data, SEBS-Taiwan was used to simulate and evaluate the typical actual daily ET values in different seasons of 2002 and 2003 in Taiwan. SEBS-Taiwan generally performed well and could accurately simulate the actual daily ET. The simulated daily ET values matched the observed values satisfactorily. The results indicate that the net regional solar radiation, evaporation ratio, and surface ET values for the whole area of Taiwan are larger in summer than in spring, and larger in autumn than in winter. The results also show that the regional average daily ET values of 2002 are a little higher than those of 2003. Through analysis of the ET values from different types of land cover, we found that forest has the largest ET value, while water areas, bare land, and urban areas have the lowest ET values. Generally, the Northern Taiwan area, including Ilan County, Nantou County, and Hualien County, has higher ET values, while other cities, such as Chiayi, Taichung, and Tainan, have lower ET values.

  5. High-resolution Continental Scale Land Surface Model incorporating Land-water Management in United States

    Science.gov (United States)

    Shin, S.; Pokhrel, Y. N.

    2016-12-01

    Land surface models have been used to assess water resources sustainability under changing Earth environment and increasing human water needs. Overwhelming observational records indicate that human activities have ubiquitous and pertinent effects on the hydrologic cycle; however, they have been crudely represented in large scale land surface models. In this study, we enhance an integrated continental-scale land hydrology model named Leaf-Hydro-Flood to better represent land-water management. The model is implemented at high resolution (5km grids) over the continental US. Surface water and groundwater are withdrawn based on actual practices. Newly added irrigation, water diversion, and dam operation schemes allow better simulations of stream flows, evapotranspiration, and infiltration. Results of various hydrologic fluxes and stores from two sets of simulation (one with and the other without human activities) are compared over a range of river basin and aquifer scales. The improved simulations of land hydrology have potential to build consistent modeling framework for human-water-climate interactions.

  6. Determination of Optimum Viewing Angles for the Angular Normalization of Land Surface Temperature over Vegetated Surface

    Directory of Open Access Journals (Sweden)

    Huazhong Ren

    2015-03-01

    Full Text Available Multi-angular observation of land surface thermal radiation is considered to be a promising method of performing the angular normalization of land surface temperature (LST retrieved from remote sensing data. This paper focuses on an investigation of the minimum requirements of viewing angles to perform such normalizations on LST. The normally kernel-driven bi-directional reflectance distribution function (BRDF is first extended to the thermal infrared (TIR domain as TIR-BRDF model, and its uncertainty is shown to be less than 0.3 K when used to fit the hemispheric directional thermal radiation. A local optimum three-angle combination is found and verified using the TIR-BRDF model based on two patterns: the single-point pattern and the linear-array pattern. The TIR-BRDF is applied to an airborne multi-angular dataset to retrieve LST at nadir (Te-nadir from different viewing directions, and the results show that this model can obtain reliable Te-nadir from 3 to 4 directional observations with large angle intervals, thus corresponding to large temperature angular variations. The Te-nadir is generally larger than temperature of the slant direction, with a difference of approximately 0.5~2.0 K for vegetated pixels and up to several Kelvins for non-vegetated pixels. The findings of this paper will facilitate the future development of multi-angular thermal infrared sensors.

  7. Biomes computed from simulated climatologies

    Energy Technology Data Exchange (ETDEWEB)

    Claussen, M.; Esch, M. [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany)

    1994-01-01

    The biome model of Prentice et al. is used to predict global patterns of potential natural plant formations, or biomes, from climatologies simulated by ECHAM, a model used for climate simulations at the Max-Planck-Institut fuer Meteorologie. This study undertaken in order to show the advantage of this biome model in diagnosing the performance of a climate model and assessing effects of past and future climate changes predicted by a climate model. Good overall agreement is found between global patterns of biomes computed from observed and simulated data of present climate. But there are also major discrepancies indicated by a difference in biomes in Australia, in the Kalahari Desert, and in the Middle West of North America. These discrepancies can be traced back to in simulated rainfall as well as summer or winter temperatures. Global patterns of biomes computed from an ice age simulation reveal that North America, Europe, and Siberia should have been covered largely by tundra and taiga, whereas only small differences are for the tropical rain forests. A potential northeast shift of biomes is expected from a simulation with enhanced CO{sub 2} concentration according to the IPCC Scenario A. Little change is seen in the tropical rain forest and the Sahara. Since the biome model used is not capable of predicting chances in vegetation patterns due to a rapid climate change, the latter simulation to be taken as a prediction of chances in conditions favourable for the existence of certain biomes, not as a reduction of a future distribution of biomes. 15 refs., 8 figs., 2 tabs.

  8. Biomes computed from simulated climatologies

    Energy Technology Data Exchange (ETDEWEB)

    Claussen, W.; Esch, M.

    1992-09-01

    The biome model of Prentice et al. is used to predict global patterns of potential natural plant formations, or biomes, from climatologies simulated by ECHAM, a model used for climate simulations at the Max-Planck-Institut fuer Meteorologie. This study is undertaken in order to show the advantage of this biome model in comprehensively diagnosing the performance of a climate model and assessing effects of past and future climate changes predicted by a climate model. Good overall agreement is found between global patterns of biomes computed from observed and simulated data of present climate. But there are also major discrepancies indicated by a difference in biomes in Australia, in the Kalahari Desert, and in the Middle West of North America. These discrepancies can be traced back to failures in simulated rain fall as well as summer or winter temperatures. Global patterns of biomes computed from an ice age simulation reveal that North America, Europe, and Siberia should have been covered largely by tundra and taiga, whereas only small differences are seen for the tropical rain forests. A potential North-East shift of biomes is expected from a simulation with enhanced CO{sub 2} concentration according to the IPCC Scenario A. Little change is seen in the tropical rain forest and the Sahara. Since the biome model used is not capable of predicting changes in vegetation patterns due to a rapid climate change, the latter simulation has to be taken as a prediction of changes in conditions favorable for the existence of certain biomes, not as a prediction of a future distribution of biomes. (orig.).

  9. Coherence of land surface layout as intangible environmental resource (Vooremaa landscape protection area, Estonia

    Directory of Open Access Journals (Sweden)

    Oleksandr Karasov

    2017-09-01

    Full Text Available Vooremaa Landscape Protection Area provides a specimen of native Estonian agricultural lands, alternating with picturesque moraine lakes. The overall visual environment within this area was basically changed by glacial agents and, hereafter, by cultural activities, such as crop farming. Topography consists of about 100 drumlins (some of them are cultivated, as well as depressions, filled with lakes and covered by forests and grasslands. A rich combination of the mentioned factors determined the study area selection. There was accepted, that the harmony, or pleasing organization of distinguishable units of visual environment (with no attention to their colours or textures, but regarding their geographical meaning only, depends on the system effect: the more complexity of the overall system exceeds the algebraic sum of the complexity of its components, the more its organization does. In this way, some developments of information theory could be applied to the analysis of visual environment (from top view, similarly to the analysis of the text (considering units of land relief, land cover, and land cover relief, or a land surface in total, as the symbols of some alphabet, and their diversity within the floating circle – as words, consisting of the symbols. Since mentioned notions of organization and harmony are frequently implied in the concept of landscape coherence, the latter term was used as a fixed and well-known one in the landscape and environmental aesthetics. Hartley’s formula was used to compute the coherence of the land surface layout and the respective regionalization within the study area and surroundings. The effectiveness of the proposed method for representation of visual harmony was non-rigorously verified with transect of Google Street View panoramic photo series, while everyone is welcomed to use the Google Street View to compare the presented results with his own conclusions. There was found, that the proposed index

  10. Reconstruction of gap-free time series satellite observations of land surface temperature to model spectral soil thermal admittance

    NARCIS (Netherlands)

    Ghafarian Malamiri, H.R.

    2015-01-01

    The soil thermal properties (soil thermal conductivity, soil heat capacity and soil diffusivity) are the main parameters in the applications that need quantitative information on soil heat transfer. Conventionally, these properties are either measured in situ or estimated by semi-empirical models

  11. [Spatial pattern of land surface dead combustible fuel load in Huzhong forest area in Great Xing'an Mountains].

    Science.gov (United States)

    Liu, Zhi-Hua; Chang, Yu; Chen, Hong-Wei; Zhou, Rui; Jing, Guo-Zhi; Zhang, Hong-Xin; Zhang, Chang-Meng

    2008-03-01

    By using geo-statistics and based on time-lag classification standard, a comparative study was made on the land surface dead combustible fuels in Huzhong forest area in Great Xing'an Mountains. The results indicated that the first level land surface dead combustible fuel, i. e., 1 h time-lag dead fuel, presented stronger spatial auto-correlation, with an average of 762.35 g x m(-2) and contributing to 55.54% of the total load. Its determining factors were species composition and stand age. The second and third levels land surface dead combustible fuel, i. e., 10 h and 100 h time-lag dead fuels, had a sum of 610.26 g x m(-2), and presented weaker spatial auto-correlation than 1 h time-lag dead fuel. Their determining factor was the disturbance history of forest stand. The complexity and heterogeneity of the factors determining the quality and quantity of forest land surface dead combustible fuels were the main reasons for the relatively inaccurate interpolation. However, the utilization of field survey data coupled with geo-statistics could easily and accurately interpolate the spatial pattern of forest land surface dead combustible fuel loads, and indirectly provide a practical basis for forest management.

  12. Quality assurance of in-situ measurements of land surface albedo: A model-based approach

    Science.gov (United States)

    Adams, Jennifer; Gobron, Nadine; Widlowski, Jean-Luc; Mio, Corrado

    2016-04-01

    This paper presents the development of a model-based framework for assessing the quality of in-situ measurements of albedo used to validate land surface albedo products. Using a 3D Monte Carlo Ray Tracing (MCRT) radiative transfer model, a quality assurance framework is built based on simulated field measurements of albedo within complex 3D canopies and under various illumination scenarios. This method provides an unbiased approach in assessing the quality of field measurements, and is also able to trace the contributions of two main sources of uncertainty in field-measurements of albedo; those resulting from 1) the field measurement protocol, such as height or placement of field measurement within the canopy, and 2) intrinsic factors of the 3D canopy under specific illumination characteristics considered, such as the canopy structure and landscape heterogeneity, tree heights, ecosystem type and season.

  13. Improvement of a land surface model for accurate prediction of surface energy and water balances

    International Nuclear Information System (INIS)

    Katata, Genki

    2009-02-01

    In order to predict energy and water balances between the biosphere and atmosphere accurately, sophisticated schemes to calculate evaporation and adsorption processes in the soil and cloud (fog) water deposition on vegetation were implemented in the one-dimensional atmosphere-soil-vegetation model including CO 2 exchange process (SOLVEG2). Performance tests in arid areas showed that the above schemes have a significant effect on surface energy and water balances. The framework of the above schemes incorporated in the SOLVEG2 and instruction for running the model are documented. With further modifications of the model to implement the carbon exchanges between the vegetation and soil, deposition processes of materials on the land surface, vegetation stress-growth-dynamics etc., the model is suited to evaluate an effect of environmental loads to ecosystems by atmospheric pollutants and radioactive substances under climate changes such as global warming and drought. (author)

  14. Spatial Modeling of Urban Vegetation and Land Surface Temperature: A Case Study of Beijing

    Directory of Open Access Journals (Sweden)

    Chudong Huang

    2015-07-01

    Full Text Available The coupling relationship between urban vegetation and land surface temperature (LST has been heatedly debated in a variety of environmental studies. This paper studies the urban vegetation information and LST by utilizing a series of remote sensing imagery covering the period from 1990 to 2007. Their coupling relationship is analyzed, in order to provide the basis for ecological planning and environment protection. The results show that the normalized difference vegetation index (NDVI, urban vegetation abundance (UVA and urban forest abundance (UFA are negatively correlated with LST, which means that both urban vegetation and urban forest are capable in decreasing LST. The apparent influence of urban vegetation and urban forest on LST varies with the spatial resolution of the imagery, and peaks at the resolutions ranging from 90 m to 120 m.

  15. Simulating carbon exchange using a regional atmospheric model coupled to an advanced land-surface model

    International Nuclear Information System (INIS)

    Ter Maat, H.W.; Hutjes, R.W.A.; Miglietta, F.; Gioli, B.; Bosveld, F.C.; Vermeulen, A.T.; Fritsch, H.

    2010-08-01

    This paper is a case study to investigate what the main controlling factors are that determine atmospheric carbon dioxide content for a region in the centre of The Netherlands. We use the Regional Atmospheric Modelling System (RAMS), coupled with a land surface scheme simulating carbon, heat and momentum fluxes (SWAPS-C), and including also submodels for urban and marine fluxes, which in principle should include the dominant mechanisms and should be able to capture the relevant dynamics of the system. To validate the model, observations are used that were taken during an intensive observational campaign in central Netherlands in summer 2002. These include flux-tower observations and aircraft observations of vertical profiles and spatial fluxes of various variables.

  16. Land Surface Temperature Differences within Local Climate Zones, Based on Two Central European Cities

    Czech Academy of Sciences Publication Activity Database

    Geletič, Jan; Lehnert, M.; Dobrovolný, Petr

    2016-01-01

    Roč. 8, č. 10 (2016), č. článku 788. ISSN 2072-4292 R&D Projects: GA MŠk(CZ) LO1415 Grant - others:UrbanAdapt(XE) EHP-CZ02-OV-1-036-2015 Program:CZ02 Biodiverzita a ekosystémové služby / Monitorování a integrované plánování a kontrola v životním prostředí/ Adaptace na změnu klimatu Institutional support: RVO:67179843 Keywords : land surface temperature * local climate zones * ASTER * LANDSAT * analysis of variance * Prague * Brno * Czech Republic Subject RIV: EH - Ecology, Behaviour Impact factor: 3.244, year: 2016

  17. Development of an Aerosol Opacity Retrieval Algorithm for Use with Multi-Angle Land Surface Images

    Science.gov (United States)

    Diner, D.; Paradise, S.; Martonchik, J.

    1994-01-01

    In 1998, the Multi-angle Imaging SpectroRadiometer (MISR) will fly aboard the EOS-AM1 spacecraft. MISR will enable unique methods for retrieving the properties of atmospheric aerosols, by providing global imagery of the Earth at nine viewing angles in four visible and near-IR spectral bands. As part of the MISR algorithm development, theoretical methods of analyzing multi-angle, multi-spectral data are being tested using images acquired by the airborne Advanced Solid-State Array Spectroradiometer (ASAS). In this paper we derive a method to be used over land surfaces for retrieving the change in opacity between spectral bands, which can then be used in conjunction with an aerosol model to derive a bound on absolute opacity.

  18. GEOEPIDERM – AN ECOLOGICAL CONCEPT THAT INTEGRATES SOIL COVER WITH ASSOCIATED LAND SURFACE COMPONENTS

    Directory of Open Access Journals (Sweden)

    I. Munteanu

    2008-10-01

    Full Text Available Based on the new concept of the “Epiderm of the Earth” introduced by the 2006 edition of the WRB-SR, the idea of “geoepiderm” has been developed. Besides its holistic meaning, by including both soil and non-soil materials found in the first 2 meters of the land surface, the term “geoepiderm” has a strong ecological sense, by suggesting similarity with the skin of the living organisms, as such, this concept is fully concordant with that of “Gaia” (Living Earth developed by James Lovelock. According to the main pedo-ecological characteristics of the soil and not soil coverings from the earth surface, ten kinds (classes of ‘geoepiderms” have been identified:1 – Protoderma (Entiderma– the primitive (emerging geoepiderm (mainly non-soil materials; five main subtypes: a Regoderma, b Leptoderma, c Areniderma, d Fluviderma and e Gleyoderma, were identified;2 – Cryoderma (Geliderma – geoepiderm of cold, mainly artic and subartic, regions with mean annual soil temperature <00C (often with perennial frozen subsoil - permafrost:3 – Arididerma – geoepiderm of arid regions and salt affected lands with limited or scarce available moisture; two subtypes: a Desertiderma, b Saliderma4 – Inceptiderma (or Juvenilederma – with 2 subtypes: a Cambiderma – a young (incipiently developed geoepiderm and b Andiderma, geoepiderm developed in volcanic materials;5 – Euderma – nutrient rich geoepiderm with two main subtypes: a Cherniderma (or Molliderma and b Luviderma (or Alfiderma;6 – Oligoderma – geoepiderm with low macro-nutrient and weatherable minerals content with 2 subtypes: a Podziderma (or Spodiderma and b Acriderma (or Ultiderma;7 – Ferriderma (Oxiderma or Senilederma – geoepiderm strongly weathered and with iron and aluminium hydroxides enrichment and low weatherable minerals reserve;8 – Vertiderma (Contractilederma – Contractile geoepiderm, developed from swelling clays;9 – Histoderma (Organiderma

  19. Using Land Surface Phenology to Detect Land Use Change in the Northern Great Plains

    Science.gov (United States)

    Nguyen, L. H.; Henebry, G. M.

    2017-12-01

    The Northern Great Plains of the US have been undergoing many types of land cover / land use change over the past two decades, including expansion of irrigation, conversion of grassland to cropland, biofuels production, urbanization, and fossil fuel mining. Much of the literature on these changes has relied on post-classification change detection based on a limited number of observations per year. Here we demonstrate an approach to characterize land dynamics through land surface phenology (LSP) by synergistic use of image time series at two scales. Our study areas include regions of interest (ROIs) across the Northern Great Plains located within Landsat path overlap zones to boost the number of valid observations (free of clouds or snow) each year. We first compute accumulated growing degree-days (AGDD) from MODIS 8-day composites of land surface temperature (MOD11A2 and MYD11A2). Using Landsat Collection 1 surface reflectance-derived vegetation indices (NDVI, EVI), we then fit at each pixel a downward convex quadratic model linking the vegetation index to each year's progression of AGDD. This quadratic equation exhibits linearity in a mathematical sense; thus, the fitted models can be linearly mixed and unmixed using a set of LSP endmembers (defined by the fitted parameter coefficients of the quadratic model) that represent "pure" land cover types with distinct seasonal patterns found within the region, such as winter wheat, spring wheat, maize, soybean, sunflower, hay/pasture/grassland, developed/built-up, among others. Information about land cover corresponding to each endmember are provided by the NLCD (National Land Cover Dataset) and CDL (Cropland Data Layer). We use linear unmixing to estimate the likely proportion of each LSP endmember within particular areas stratified by latitude. By tracking the proportions over the 2001-2011 period, we can quantify various types of land transitions in the Northern Great Plains.

  20. Calibration of an integrated land surface process and radiobrightness (LSP/R) model during summertime

    Science.gov (United States)

    Judge, Jasmeet; England, Anthony W.; Metcalfe, John R.; McNichol, David; Goodison, Barry E.

    2008-01-01

    In this study, a soil vegetation and atmosphere transfer (SVAT) model was linked with a microwave emission model to simulate microwave signatures for different terrain during summertime, when the energy and moisture fluxes at the land surface are strong. The integrated model, land surface process/radiobrightness (LSP/R), was forced with weather and initial conditions observed during a field experiment. It simulated the fluxes and brightness temperatures for bare soil and brome grass in the Northern Great Plains. The model estimates of soil temperature and moisture profiles and terrain brightness temperatures were compared with the observed values. Overall, the LSP model provides realistic estimates of soil moisture and temperature profiles to be used with a microwave model. The maximum mean differences and standard deviations between the modeled and the observed temperatures (canopy and soil) were 2.6 K and 6.8 K, respectively; those for the volumetric soil moisture were 0.9% and 1.5%, respectively. Brightness temperatures at 19 GHz matched well with the observations for bare soil, when a rough surface model was incorporated indicating reduced dielectric sensitivity to soil moisture by surface roughness. The brightness temperatures of the brome grass matched well with the observations indicating that a simple emission model was sufficient to simulate accurate brightness temperatures for grass typical of that region and surface roughness was not a significant issue for grass-covered soil at 19 GHz. Such integrated SVAT-microwave models allow for direct assimilation of microwave observations and can also be used to understand sensitivity of microwave signatures to changes in weather forcings and soil conditions for different terrain types.