How to Get Data from NOAA Environmental Satellites: An Overview of Operations, Products, Access and Archive

Science.gov (United States)

Donoho, N.; Graumann, A.; McNamara, D. P.

2015-12-01

In this presentation we will highlight access and availability of NOAA satellite data for near real time (NRT) and retrospective product users. The presentation includes an overview of the current fleet of NOAA satellites and methods of data distribution and access to hundreds of imagery and products offered by the Environmental Satellite Processing Center (ESPC) and the Comprehensive Large Array-data Stewardship System (CLASS). In particular, emphasis on the various levels of services for current and past observations will be presented. The National Environmental Satellite, Data, and Information Service (NESDIS) is dedicated to providing timely access to global environmental data from satellites and other sources. In special cases, users are authorized direct access to NESDIS data distribution systems for environmental satellite data and products. Other means of access include publicly available distribution services such as the Global Telecommunication System (GTS), NOAA satellite direct broadcast services and various NOAA websites and ftp servers, including CLASS. CLASS is NOAA's information technology system designed to support long-term, secure preservation and standards-based access to environmental data collections and information. The National Centers for Environmental Information (NCEI) is responsible for the ingest, quality control, stewardship, archival and access to data and science information. This work will also show the latest technology improvements, enterprise approach and future plans for distribution of exponentially increasing data volumes from future NOAA missions. A primer on access to NOAA operational satellite products and services is available at http://www.ospo.noaa.gov/Organization/About/access.html. Access to post-operational satellite data and assorted products is available at http://www.class.noaa.gov

MALIBU: A High Spatial Resolution Multi-Angle Imaging Unmanned Airborne System to Validate Satellite-derived BRDF/Albedo Products

Science.gov (United States)

Wang, Z.; Roman, M. O.; Pahlevan, N.; Stachura, M.; McCorkel, J.; Bland, G.; Schaaf, C.

2016-12-01

Albedo is a key climate forcing variable that governs the absorption of incoming solar radiation and its ultimate transfer to the atmosphere. Albedo contributes significant uncertainties in the simulation of climate changes; and as such, it is defined by the Global Climate Observing System (GCOS) as a terrestrial essential climate variable (ECV) required by global and regional climate and biogeochemical models. NASA's Goddard Space Flight Center's Multi AngLe Imaging Bidirectional Reflectance Distribution Function small-UAS (MALIBU) is part of a series of pathfinder missions to develop enhanced multi-angular remote sensing techniques using small Unmanned Aircraft Systems (sUAS). The MALIBU instrument package includes two multispectral imagers oriented at two different viewing geometries (i.e., port and starboard sides) capture vegetation optical properties and structural characteristics. This is achieved by analyzing the surface reflectance anisotropy signal (i.e., BRDF shape) obtained from the combination of surface reflectance from different view-illumination angles and spectral channels. Satellite measures of surface albedo from MODIS, VIIRS, and Landsat have been evaluated by comparison with spatially representative albedometer data from sparsely distributed flux towers at fixed heights. However, the mismatch between the footprint of ground measurements and the satellite footprint challenges efforts at validation, especially for heterogeneous landscapes. The BRDF (Bidirectional Reflectance Distribution Function) models of surface anisotropy have only been evaluated with airborne BRDF data over a very few locations. The MALIBU platform that acquires extremely high resolution sub-meter measures of surface anisotropy and surface albedo, can thus serve as an important source of reference data to enable global land product validation efforts, and resolve the errors and uncertainties in the various existing products generated by NASA and its national and

CHAOS-2-a geomagnetic field model derived from one decade of continuous satellite data

DEFF Research Database (Denmark)

Olsen, Nils; Mandea, M.; Sabaka, T.J.

2009-01-01

We have derived a model of the near-Earth's magnetic field using more than 10 yr of high-precision geomagnetic measurements from the three satellites Orsted, CHAMP and SAC-C. This model is an update of the two previous models, CHAOS (Olsen et al. 2006) and xCHAOS (Olsen & Mandea 2008). Data...... by minimizing the second time derivative of the squared magnetic field intensity at the core-mantle boundary. The CHAOS-2 model describes rapid time changes, as monitored by the ground magnetic observatories, much better than its predecessors....

Building a satellite climate diagnostics data base for real-time climate monitoring

International Nuclear Information System (INIS)

Ropelewski, C.F.

1991-01-01

The paper discusses the development of a data base, the Satellite Climate Diagnostic Data Base (SCDDB), for real time operational climate monitoring utilizing current satellite data. Special attention is given to the satellite-derived quantities useful for monitoring global climate changes, the requirements of SCDDB, and the use of conventional meteorological data and model assimilated data in developing the SCDDB. Examples of prototype SCDDB products are presented. 10 refs

Satellite-derived land covers for runoff estimation using SCS-CN method in Chen-You-Lan Watershed, Taiwan

Science.gov (United States)

Zhang, Wen-Yan; Lin, Chao-Yuan

2017-04-01

The Soil Conservation Service Curve Number (SCS-CN) method, which was originally developed by the USDA Natural Resources Conservation Service, is widely used to estimate direct runoff volume from rainfall. The runoff Curve Number (CN) parameter is based on the hydrologic soil group and land use factors. In Taiwan, the national land use maps were interpreted from aerial photos in 1995 and 2008. Rapid updating of post-disaster land use map is limited due to the high cost of production, so the classification of satellite images is the alternative method to obtain the land use map. In this study, Normalized Difference Vegetation Index (NDVI) in Chen-You-Lan Watershed was derived from dry and wet season of Landsat imageries during 2003 - 2008. Land covers were interpreted from mean value and standard deviation of NDVI and were categorized into 4 groups i.e. forest, grassland, agriculture and bare land. Then, the runoff volume of typhoon events during 2005 - 2009 were estimated using SCS-CN method and verified with the measured runoff data. The result showed that the model efficiency coefficient is 90.77%. Therefore, estimating runoff by using the land cover map classified from satellite images is practicable.

Comparison of the characteristic energy of precipitating electrons derived from ground-based and DMSP satellite data

Directory of Open Access Journals (Sweden)

M. Ashrafi

2005-01-01

Full Text Available Energy maps are important for ionosphere-magnetosphere coupling studies, because quantitative determination of field-aligned currents requires knowledge of the conductances and their spatial gradients. By combining imaging riometer absorption and all-sky auroral optical data it is possible to produce high temporal and spatial resolution maps of the Maxwellian characteristic energy of precipitating electrons within a 240240 common field of view. These data have been calibrated by inverting EISCAT electron density profiles into equivalent energy spectra. In this paper energy maps produced by ground-based instruments (optical and riometer are compared with DMSP satellite data during geomagnetic conjunctions. For the period 1995-2002, twelve satellite passes over the ground-based instruments' field of view for the cloud-free conditions have been considered. Four of the satellite conjunctions occurred during moderate geomagnetic, steady-state conditions and without any ion precipitation. In these cases with Maxwellian satellite spectra, there is 71% agreement between the characteristic energies derived from the satellite and the ground-based energy map method.

Comparison of the characteristic energy of precipitating electrons derived from ground-based and DMSP satellite data

Directory of Open Access Journals (Sweden)

M. Ashrafi

2005-01-01

Full Text Available Energy maps are important for ionosphere-magnetosphere coupling studies, because quantitative determination of field-aligned currents requires knowledge of the conductances and their spatial gradients. By combining imaging riometer absorption and all-sky auroral optical data it is possible to produce high temporal and spatial resolution maps of the Maxwellian characteristic energy of precipitating electrons within a 240240 common field of view. These data have been calibrated by inverting EISCAT electron density profiles into equivalent energy spectra. In this paper energy maps produced by ground-based instruments (optical and riometer are compared with DMSP satellite data during geomagnetic conjunctions. For the period 1995-2002, twelve satellite passes over the ground-based instruments' field of view for the cloud-free conditions have been considered. Four of the satellite conjunctions occurred during moderate geomagnetic, steady-state conditions and without any ion precipitation. In these cases with Maxwellian satellite spectra, there is 71% agreement between the characteristic energies derived from the satellite and the ground-based energy map method.

Estimation of absorbed photosynthetically active radiation and vegetation net production efficiency using satellite data

International Nuclear Information System (INIS)

Hanan, N.P.; Prince, S.D.; Begue, A.

1995-01-01

The amount of photosynthetically active radiation (PAR) absorbed by green vegetation is an important determinant of photosynthesis and growth. Methods for the estimation of fractional absorption of PAR (iff PAR ) for areas greater than 1 km 2 using satellite data are discussed, and are applied to sites in the Sahel that have a sparse herb layer and tree cover of less than 5%. Using harvest measurements of seasonal net production, net production efficiencies are calculated. Variation in estimates of seasonal PAR absorption (APAR) caused by the atmospheric correction method and relationship between surface reflectances and iff PAR is considered. The use of maximum value composites of satellite NDVI to reduce the effect of the atmosphere is shown to produce inaccurate APAR estimates. In this data set, however, atmospheric correction using average optical depths was found to give good approximations of the fully corrected data. A simulation of canopy radiative transfer using the SAIL model was used to derive a relationship between canopy NDVI and iff PAR . Seasonal APAR estimates assuming a 1:1 relationship between iff PAR and NDVI overestimated the SAIL modeled results by up to 260%. The use of a modified 1:1 relationship, where iff PAR was assumed to be linearly related to NDVI scaled between minimum (soil) and maximum (infinite canopy) values, underestimated the SAIL modeled results by up to 35%. Estimated net production efficiencies (ϵ n , dry matter per unit APAR) fell in the range 0.12–1.61 g MJ −1 for above ground production, and in the range 0.16–1.88 g MJ −1 for total production. Sites with lower rainfall had reduced efficiencies, probably caused by physiological constraints on photosynthesis during dry conditions. (author)

Site-level evaluation of satellite-based global terrestrial gross primary production and net primary production monitoring.

Science.gov (United States)

David P. Turner; William D. Ritts; Warren B. Cohen; Thomas K. Maeirsperger; Stith T. Gower; Al A. Kirschbaum; Steve W. Runnings; Maosheng Zhaos; Steven C. Wofsy; Allison L. Dunn; Beverly E. Law; John L. Campbell; Walter C. Oechel; Hyo Jung Kwon; Tilden P. Meyers; Eric E. Small; Shirley A. Kurc; John A. Gamon

2005-01-01

Operational monitoring of global terrestrial gross primary production (GPP) and net primary production (NPP) is now underway using imagery from the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Evaluation of MODIS GPP and NPP products will require site-level studies across a range of biomes, with close attention to numerous scaling...

An evolutionary framework for the Jovian and Saturnian satellites

International Nuclear Information System (INIS)

Stevenson, R.J.

1987-01-01

The position of the satellite within the protonebula, the influence of the parent planet, particularly the relative effects of tidal (gravitational) as opposed to radiogenic (internal) heat generating processes, as well as the type of ice, exert a control on the evolutionary histories of the Jovian and Saturnian satellites. The landscapes of the moons are modified by surface deformational processes (tectonic activity derived from within the body) and externally derived cratering. The geological history of the Galilean satellites is deduced from surface stratigraphic successions of geological units. Io and Europa, with crater-free surfaces, are tectonically more advanced than crater-saturated Callisto. Two thermal-drive models are proposed based on: an expression for externally derived gravitational influences between two bodies; and internal heat generation via radiogenic decay (expressed by surface area/volume ratio). Both parameters, for the Galilean satellites, are plotted against an inferred product of tectonic processes - the age of the surface terrain. From these diagrams, the tectonic evolutionary state of the more distant Saturnian system are predicted. These moons are fitted into an evolutionary framework for the Solar System. 34 refs.; 4 figs.; 2 tabs

Use of Real Time Satellite Infrared and Ocean Color to Produce Ocean Products

Science.gov (United States)

Roffer, M. A.; Muller-Karger, F. E.; Westhaver, D.; Gawlikowski, G.; Upton, M.; Hall, C.

2014-12-01

Real-time data products derived from infrared and ocean color satellites are useful for several types of users around the world. Highly relevant applications include recreational and commercial fisheries, commercial towing vessel and other maritime and navigation operations, and other scientific and applied marine research. Uses of the data include developing sampling strategies for research programs, tracking of water masses and ocean fronts, optimizing ship routes, evaluating water quality conditions (coastal, estuarine, oceanic), and developing fisheries and essential fish habitat indices. Important considerations for users are data access and delivery mechanisms, and data formats. At this time, the data are being generated in formats increasingly available on mobile computing platforms, and are delivered through popular interfaces including social media (Facebook, Linkedin, Twitter and others), Google Earth and other online Geographical Information Systems, or are simply distributed via subscription by email. We review 30 years of applications and describe how we develop customized products and delivery mechanisms working directly with users. We review benefits and issues of access to government databases (NOAA, NASA, ESA), standard data products, and the conversion to tailored products for our users. We discuss advantages of different product formats and of the platforms used to display and to manipulate the data.

SeaWiFS Technical Report Series. Volume 42; Satellite Primary Productivity Data and Algorithm Development: A Science Plan for Mission to Planet Earth

Science.gov (United States)

Falkowski, Paul G.; Behrenfeld, Michael J.; Esaias, Wayne E.; Balch, William; Campbell, Janet W.; Iverson, Richard L.; Kiefer, Dale A.; Morel, Andre; Yoder, James A.; Hooker, Stanford B. (Editor);

Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

Science.gov (United States)

Albergel, Clément; Munier, Simon; Leroux, Delphine Jennifer; Dewaele, Hélène; Fairbairn, David; Lavinia Barbu, Alina; Gelati, Emiliano; Dorigo, Wouter; Faroux, Stéphanie; Meurey, Catherine; Le Moigne, Patrick; Decharme, Bertrand; Mahfouf, Jean-Francois; Calvet, Jean-Christophe

2017-10-01

the assimilation impact is conducted using (i) agricultural statistics over France, (ii) river discharge observations, (iii) satellite-derived estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM) project and (iv) spatially gridded observation-based estimates of upscaled gross primary production and evapotranspiration from the FLUXNET network. Comparisons with those four datasets highlight neutral to highly positive improvement.

Comparison of Satellite Rainfall Estimates and Rain Gauge Measurements in Italy, and Impact on Landslide Modeling

Directory of Open Access Journals (Sweden)

Mauro Rossi

2017-12-01

Full Text Available Landslides can be triggered by intense or prolonged rainfall. Rain gauge measurements are commonly used to predict landslides even if satellite rainfall estimates are available. Recent research focuses on the comparison of satellite estimates and gauge measurements. The rain gauge data from the Italian network (collected in the system database “Verifica Rischio Frana”, VRF are compared with the National Aeronautics and Space Administration (NASA Tropical Rainfall Measuring Mission (TRMM products. For the purpose, we couple point gauge and satellite rainfall estimates at individual grid cells, evaluating the correlation between gauge and satellite data in different morpho-climatological conditions. We then analyze the statistical distributions of both rainfall data types and the rainfall events derived from them. Results show that satellite data underestimates ground data, with the largest differences in mountainous areas. Power-law models, are more appropriate to correlate gauge and satellite data. The gauge and satellite-based products exhibit different statistical distributions and the rainfall events derived from them differ. In conclusion, satellite rainfall cannot be directly compared with ground data, requiring local investigation to account for specific morpho-climatological settings. Results suggest that satellite data can be used for forecasting landslides, only performing a local scaling between satellite and ground data.

Validating GPM-based Multi-satellite IMERG Products Over South Korea

Science.gov (United States)

Wang, J.; Petersen, W. A.; Wolff, D. B.; Ryu, G. H.

2017-12-01

Accurate precipitation estimates derived from space-borne satellite measurements are critical for a wide variety of applications such as water budget studies, and prevention or mitigation of natural hazards caused by extreme precipitation events. This study validates the near-real-time Early Run, Late Run and the research-quality Final Run Integrated Multi-Satellite Retrievals for GPM (IMERG) using Korean Quantitative Precipitation Estimation (QPE). The Korean QPE data are at a 1-hour temporal resolution and 1-km by 1-km spatial resolution, and were developed by Korea Meteorological Administration (KMA) from a Real-time ADjusted Radar-AWS (Automatic Weather Station) Rainrate (RAD-RAR) system utilizing eleven radars over the Republic of Korea. The validation is conducted by comparing Version-04A IMERG (Early, Late and Final Runs) with Korean QPE over the area (124.5E-130.5E, 32.5N-39N) at various spatial and temporal scales during March 2014 through November 2016. The comparisons demonstrate the reasonably good ability of Version-04A IMERG products in estimating precipitation over South Korea's complex topography that consists mainly of hills and mountains, as well as large coastal plains. Based on this data, the Early Run, Late Run and Final Run IMERG precipitation estimates higher than 0.1mm h-1 are about 20.1%, 7.5% and 6.1% higher than Korean QPE at 0.1o and 1-hour resolutions. Detailed comparison results are available at https://wallops-prf.gsfc.nasa.gov/KoreanQPE.V04/index.html

Production process for advanced space satellite system cables/interconnects.

Energy Technology Data Exchange (ETDEWEB)

Mendoza, Luis A.

2007-12-01

This production process was generated for the satellite system program cables/interconnects group, which in essences had no well defined production process. The driver for the development of a formalized process was based on the set backs, problem areas, challenges, and need improvements faced from within the program at Sandia National Laboratories. In addition, the formal production process was developed from the Master's program of Engineering Management for New Mexico Institute of Mining and Technology in Socorro New Mexico and submitted as a thesis to meet the institute's graduating requirements.

Capabilities and uncertainties of aircraft measurements for the validation of satellite precipitation products – a virtual case study

Directory of Open Access Journals (Sweden)

Andrea Lammert

2015-08-01

Full Text Available Remote sensing sensors on board of research aircraft provide detailed measurements of clouds and precipitation which can be used as reference data to validate satellite products. Such satellite derived precipitation data using passive microwave radiometers with a resolution of typically 50×50km2$50\\times50\\,\\text{km}^2$ stands against high spatial and temporal resolved airborne measurements, but only along a chosen line. This paper focuses on analysis on the uncertainty arising from the different spatial resolution and coverage. Therefore we use a perfect model approach, with a high resolved forecast model yielding perfect virtual aircraft and satellite observations. The mean precipitation and standard deviation per satellite box were estimated with a Gaussian approach. The comparison of the mean values shows a high correlation of 0.92, but a very wide spread. As criterion to define good agreement between satellite mean and reference, we choose a deviation of one standard deviation of the virtual aircraft as threshold. Considering flight tracks in the range of 50 km (one overflight, the perfect agreement of satellite and aircraft observations is only detected in 65 % of the cases. To increase this low reliability the precipitation distributions of the virtual aircraft were fitted by a gamma density function. Using the same quality criterion, the usage of gamma density fit yields an improvement of the Aircraft reliability up to 80 %.

Assessment of Satellite-Derived Surface Reflectances by NASA's CAR Airborne Radiometer over Railroad Valley, Nevada

Science.gov (United States)

Kharbouche, Said; Muller, Jan-Peter; Gatebe, Charles K.; Scanlon, Tracy; Banks, Andrew C.

2017-01-01

CAR (Cloud Absorption Radiometer) is a multi-angular and multi-spectral airborne radiometer instrument, whose radiometric and geometric characteristics are well calibrated and adjusted before and after each flight campaign. CAR was built by NASA (National Aeronautics and Space Administration) in 1984. On 16 May 2008, a CAR flight campaign took place over the well-known calibration and validation site of Railroad Valley in Nevada (38.504 deg N, 115.692 deg W).The campaign coincided with the overpasses of several key EO (Earth Observation) satellites such as Landsat-7, Envisat and Terra. Thus, there are nearly simultaneous measurements from these satellites and the CAR airborne sensor over the same calibration site. The CAR spectral bands are close to those of most EO satellites. CAR has the ability to cover the whole range of azimuth view angles and a variety of zenith angles depending on altitude and, as a consequence, the biases seen between satellite and CAR measurements due to both unmatched spectral bands and unmatched angles can be significantly reduced. A comparison is presented here between CARs land surface reflectance (BRF or Bidirectional Reflectance Factor) with those derived from Terra/MODIS (MOD09 and MAIAC), Terra/MISR, Envisat/MERIS and Landsat-7. In this study, we utilized CAR data from low altitude flights (approx. 180 m above the surface) in order to minimize the effects of the atmosphere on these measurements and then obtain a valuable ground-truth data set of surface reflectance. Furthermore, this study shows that differences between measurements caused by surface heterogeneity can be tolerated, thanks to the high homogeneity of the study site on the one hand, and on the other hand, to the spatial sampling and the large number of CAR samples. These results demonstrate that satellite BRF measurements over this site are in good agreement with CAR with variable biases across different spectral bands. This is most likely due to residual aerosol

Systematical estimation of GPM-based global satellite mapping of precipitation products over China

Science.gov (United States)

Zhao, Haigen; Yang, Bogang; Yang, Shengtian; Huang, Yingchun; Dong, Guotao; Bai, Juan; Wang, Zhiwei

2018-03-01

As the Global Precipitation Measurement (GPM) Core Observatory satellite continues its mission, new version 6 products for Global Satellite Mapping of Precipitation (GSMaP) have been released. However, few studies have systematically evaluated the GSMaP products over mainland China. This study quantitatively evaluated three GPM-based GSMaP version 6 precipitation products for China and eight subregions referring to the Chinese daily Precipitation Analysis Product (CPAP). The GSMaP products included near-real-time (GSMaP_NRT), microwave-infrared reanalyzed (GSMaP_MVK), and gauge-adjusted (GSMaP_Gau) data. Additionally, the gauge-adjusted Integrated Multi-Satellite Retrievals for Global Precipitation Measurement Mission (IMERG_Gau) was also assessed and compared with GSMaP_Gau. The analyses of the selected daily products were carried out at spatiotemporal resolutions of 1/4° for the period of March 2014 to December 2015 in consideration of the resolution of CPAP and the consistency of the coverage periods of the satellite products. The results indicated that GSMaP_MVK and GSMaP_NRT performed comparably and underdetected light rainfall events (Pearson linear correlation coefficient (CC), fractional standard error (FSE), and root-mean-square error (RMSE) metrics during the summer. Compared with GSMaP_NRT and GSMaP_MVK, GSMaP_Gau possessed significantly improved metrics over mainland China and the eight subregions and performed better in terms of CC, RMSE, and FSE but underestimated precipitation to a greater degree than IMERG_Gau. As a quantitative assessment of the GPM-era GSMaP products, these validation results will supply helpful references for both end users and algorithm developers. However, the study findings need to be confirmed over a longer future study period when the longer-period IMERG retrospectively-processed data are available.

A climate index derived from satellite measured spectral infrared radiation. Ph.D. Thesis

Science.gov (United States)

Abel, M. D.; Fox, S. K.

1982-01-01

The vertical infrared radiative emitting structure (VIRES) climate index, based on radiative transfer theory and derived from the spectral radiances typically used to retrieve temperature profiles, is introduced. It is assumed that clouds and climate are closely related and a change in one will result in a change in the other. The index is a function of the cloud, temperature, and moisture distributions. It is more accurately retrieved from satellite data than is cloudiness per se. The VIRES index is based upon the shape and relative magnitude of the broadband weighting function of the infrared radiative transfer equation. The broadband weighting curves are retrieved from simulated satellite infrared sounder data (spectral radiances). The retrieval procedure is described and the error error sensitivities of the method investigated. Index measuring options and possible applications of the VIRES index are proposed.

Validation of satellite-derived tropical cyclone heat potential with in situ observations in the North Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

Nagamani, P.V.; Ali, M.M.; Goni, G.J.; Dinezio, P.N.; Pezzullo, J.C.; UdayaBhaskar, T.V.S.; Gopalakrishna, V.V.; Nisha, K.

validation with in situ estimations for quantification of their reliability and consistency. Once the validation has been carried out, the satellite-derived TCHP values with their improved tempo- ral and spatial properties can be conveniently used...

Satellite precipitation estimation over the Tibetan Plateau

Science.gov (United States)

Porcu, F.; Gjoka, U.

2012-04-01

Precipitation characteristics over the Tibetan Plateau are very little known, given the scarcity of reliable and widely distributed ground observation, thus the satellite approach is a valuable choice for large scale precipitation analysis and hydrological cycle studies. However,the satellite perspective undergoes various shortcomings at the different wavelengths used in atmospheric remote sensing. In the microwave spectrum often the high soil emissivity masks or hides the atmospheric signal upwelling from light-moderate precipitation layers, while low and relatively thin precipitating clouds are not well detected in the visible-infrared, because of their low contrast with cold and bright (if snow covered) background. In this work an IR-based, statistical rainfall estimation technique is trained and applied over the Tibetan Plateau hydrological basin to retrive precipitation intensity at different spatial and temporal scales. The technique is based on a simple artificial neural network scheme trained with two supervised training sets assembled for monsoon season and for the rest of the year. For the monsoon season (estimated from June to September), the ground radar precipitation data for few case studies are used to build the training set: four days in summer 2009 are considered. For the rest of the year, CloudSat-CPR derived snowfall rate has been used as reference precipitation data, following the Kulie and Bennartz (2009) algorithm. METEOSAT-7 infrared channels radiance (at 6.7 and 11 micometers) and derived local variability features (such as local standard deviation and local average) are used as input and the actual rainrate is obtained as output for each satellite slot, every 30 minutes on the satellite grid. The satellite rainrate maps for three years (2008-2010) are computed and compared with available global precipitation products (such as C-MORPH and TMPA products) and with other techniques applied to the Plateau area: similarities and differences are

Camera derived vegetation greenness index as proxy for gross primary production in a low Arctic wetland area

DEFF Research Database (Denmark)

Westergaard-Nielsen, Andreas; Lund, Magnus; Hansen, Birger Ulf

2013-01-01

vegetation index (NDVI) product derived from the WorldView-2 satellite. An object-based classification based on a bi-temporal image composite was used to classify the study area into heath, copse, fen, and bedrock. Temporal evolution of vegetation greenness was evaluated and modeled with double sigmoid...... and GPP (R-2 = 0.85, p remote Arctic regions....... (C) 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved....

Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model

Science.gov (United States)

Laiolo, P.; Gabellani, S.; Campo, L.; Silvestro, F.; Delogu, F.; Rudari, R.; Pulvirenti, L.; Boni, G.; Fascetti, F.; Pierdicca, N.; Crapolicchio, R.; Hasenauer, S.; Puca, S.

2016-06-01

The reliable estimation of hydrological variables in space and time is of fundamental importance in operational hydrology to improve the flood predictions and hydrological cycle description. Nowadays remotely sensed data can offer a chance to improve hydrological models especially in environments with scarce ground based data. The aim of this work is to update the state variables of a physically based, distributed and continuous hydrological model using four different satellite-derived data (three soil moisture products and a land surface temperature measurement) and one soil moisture analysis to evaluate, even with a non optimal technique, the impact on the hydrological cycle. The experiments were carried out for a small catchment, in the northern part of Italy, for the period July 2012-June 2013. The products were pre-processed according to their own characteristics and then they were assimilated into the model using a simple nudging technique. The benefits on the model predictions of discharge were tested against observations. The analysis showed a general improvement of the model discharge predictions, even with a simple assimilation technique, for all the assimilation experiments; the Nash-Sutcliffe model efficiency coefficient was increased from 0.6 (relative to the model without assimilation) to 0.7, moreover, errors on discharge were reduced up to the 10%. An added value to the model was found in the rainfall season (autumn): all the assimilation experiments reduced the errors up to the 20%. This demonstrated that discharge prediction of a distributed hydrological model, which works at fine scale resolution in a small basin, can be improved with the assimilation of coarse-scale satellite-derived data.

Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

International Nuclear Information System (INIS)

Boresjoe Bronge, Laine

2004-03-01

Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given

Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

Energy Technology Data Exchange (ETDEWEB)

Boresjoe Bronge, Laine [SwedPower AB, Stockholm (Sweden)

2004-03-01

Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given.

Northern South China Sea Surface Circulation and its Variability Derived by Combining Satellite Altimetry and Surface Drifter Data

Directory of Open Access Journals (Sweden)

N. Peter Benny

2015-01-01

Full Text Available The present study analyses the mean and seasonal mesoscale surface circulation of the Northern South China Sea (NSCS and determines the influence of El Niño/SouthernNiño/Southern Oscillation (ENSO. High resolution Eulerian velocity field is derived by combining the available satellite tracked surface drifter data with satellite altimetry during 1993 - 2012. The wind driven current is computed employing the weekly ocean surface mean wind fields derived from the scatterometers on board ERS 1/2, QuikSCAT and ASCAT. The derived mean velocity field exhibits strong boundary currents and broad zonal flow across NSCS. The anomalous field is quite strong in the southern part and the Seasonal circulation clearly depicts the monsoonal forcing. Eddy Kinetic Energy (EKE distribution and its spatial and temporal structures are determined employing Empirical Orthogonal Function (EOF analysis. The ENSO influence on NSCS surface circulation has been analyzed using monthly absolute geostrophic velocity fields during 1996 - 1999.

Developing Information Services and Tools to Access and Evaluate Data Quality in Global Satellite-based Precipitation Products

Science.gov (United States)

Liu, Z.; Shie, C. L.; Meyer, D. J.

2017-12-01

Global satellite-based precipitation products have been widely used in research and applications around the world. Compared to ground-based observations, satellite-based measurements provide precipitation data on a global scale, especially in remote continents and over oceans. Over the years, satellite-based precipitation products have evolved from single sensor and single algorithm to multi-sensors and multi-algorithms. As a result, many satellite-based precipitation products have been enhanced such as spatial and temporal coverages. With inclusion of ground-based measurements, biases of satellite-based precipitation products have been significantly reduced. However, data quality issues still exist and can be caused by many factors such as observations, satellite platform anomaly, algorithms, production, calibration, validation, data services, etc. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to NASA global precipitation product archives including the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), as well as other global and regional precipitation products. Precipitation is one of the top downloaded and accessed parameters in the GES DISC data archive. Meanwhile, users want to easily locate and obtain data quality information at regional and global scales to better understand how precipitation products perform and how reliable they are. As data service providers, it is necessary to provide an easy access to data quality information, however, such information normally is not available, and when it is available, it is not in one place and difficult to locate. In this presentation, we will present challenges and activities at the GES DISC to address precipitation data quality issues.

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.

Validation of Satellite-Derived Sea Surface Temperatures for Waters around Taiwan

Directory of Open Access Journals (Sweden)

Ming-An Lee

2005-01-01

Full Text Available In order to validate the Advanced Very High Resolution Radiometer (AVHRR-derived sea surface temperatures (SST of the waters around Taiwan, we generated a match-up data set of 961 pairs, which included in situ SSTs and concurrent AVHRR measurements for the period of 1998 to 2002. Availability of cloud-free images, i.e., images with more than 85% of cloud-free area in their coverage, was about 2.23% of all AVHRR images during the study period. The range of in situ SSTs was from _ to _ The satellite derived-SSTs through MCSST and NLSST algorithms were linearly related to the in situ SSTs with correlation coefficients of 0.985 and 0.98, respectively. The MCSSTs and NLSSTs had small biases of 0.009 _ and 0.256 _ with root mean square deviations of 0.64 _ and 0.801 _ respectively, therefore the AVHRR-based MCSSTs and NLSSTs had high accuracy in the seas around Taiwan.

Improved Satellite-based Photosysnthetically Active Radiation (PAR) for Air Quality Studies

Science.gov (United States)

Pour Biazar, A.; McNider, R. T.; Cohan, D. S.; White, A.; Zhang, R.; Dornblaser, B.; Doty, K.; Wu, Y.; Estes, M. J.

2015-12-01

One of the challenges in understanding the air quality over forested regions has been the uncertainties in estimating the biogenic hydrocarbon emissions. Biogenic volatile organic compounds, BVOCs, play a critical role in atmospheric chemistry, particularly in ozone and particulate matter (PM) formation. In southeastern United States, BVOCs (mostly as isoprene) are the dominant summertime source of reactive hydrocarbon. Despite significant efforts in improving BVOC estimates, the errors in emission inventories remain a concern. Since BVOC emissions are particularly sensitive to the available photosynthetically active radiation (PAR), model errors in PAR result in large errors in emission estimates. Thus, utilization of satellite observations to estimate PAR can help in reducing emission uncertainties. Satellite-based PAR estimates rely on the technique used to derive insolation from satellite visible brightness measurements. In this study we evaluate several insolation products against surface pyranometer observations and offer a bias correction to generate a more accurate PAR product. The improved PAR product is then used in biogenic emission estimates. The improved biogenic emission estimates are compared to the emission inventories over Texas and used in air quality simulation over the period of August-September 2013 (NASA's Discover-AQ field campaign). A series of sensitivity simulations will be performed and evaluated against Discover-AQ observations to test the impact of satellite-derived PAR on air quality simulations.

Evaluating Terra MODIS Satellite Sensor Data Products for Maize ...

African Journals Online (AJOL)

Evaluating Terra MODIS Satellite Sensor Data Products for Maize Yield Estimation in South Africa. C Frost, N Thiebaut, T Newby. Abstract. The Free State Province of the Republic of South Africa contains some of the most important maize-producing areas in South Africa. For this reason this province has also been selected ...

Comparison of precision orbit derived density estimates for CHAMP and GRACE satellites

Science.gov (United States)

Fattig, Eric Dale

Current atmospheric density models cannot adequately represent the density variations observed by satellites in Low Earth Orbit (LEO). Using an optimal orbit determination process, precision orbit ephemerides (POE) are used as measurement data to generate corrections to density values obtained from existing atmospheric models. Densities obtained using these corrections are then compared to density data derived from the onboard accelerometers of satellites, specifically the CHAMP and GRACE satellites. This comparison takes two forms, cross correlation analysis and root mean square analysis. The densities obtained from the POE method are nearly always superior to the empirical models, both in matching the trends observed by the accelerometer (cross correlation), and the magnitudes of the accelerometer derived density (root mean square). In addition, this method consistently produces better results than those achieved by the High Accuracy Satellite Drag Model (HASDM). For satellites orbiting Earth that pass through Earth's upper atmosphere, drag is the primary source of uncertainty in orbit determination and prediction. Variations in density, which are often not modeled or are inaccurately modeled, cause difficulty in properly calculating the drag acting on a satellite. These density variations are the result of many factors; however, the Sun is the main driver in upper atmospheric density changes. The Sun influences the densities in Earth's atmosphere through solar heating of the atmosphere, as well as through geomagnetic heating resulting from the solar wind. Data are examined for fourteen hour time spans between November 2004 and July 2009 for both the CHAMP and GRACE satellites. This data spans all available levels of solar and geomagnetic activity, which does not include data in the elevated and high solar activity bins due to the nature of the solar cycle. Density solutions are generated from corrections to five different baseline atmospheric models, as well as

Estimating Advective Near-surface Currents from Ocean Color Satellite Images

Science.gov (United States)

2015-01-01

on the SuomiNational Polar-Orbiting Partner- ship (S- NPP ) satellite. The GOCI is the world’s first geostationary orbit satellite sensor over the...radiance Lwn at several wave - lengths. These spectral Lwn channels are used to derive several in- water bio-optical properties (Lee, Carder, & Arnone...the same surface flow, it is the inter-product similarities, instead of the differences, that are more likely to stand for the surface advection. If

Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

Directory of Open Access Journals (Sweden)

C. Albergel

2017-10-01

�comprehensive evaluation of the assimilation impact is conducted using (i agricultural statistics over France, (ii river discharge observations, (iii satellite-derived estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM project and (iv spatially gridded observation-based estimates of upscaled gross primary production and evapotranspiration from the FLUXNET network. Comparisons with those four datasets highlight neutral to highly positive improvement.

Measurement-based perturbation theory and differential equation parameter estimation with applications to satellite gravimetry

Science.gov (United States)

Xu, Peiliang

2018-06-01

The numerical integration method has been routinely used by major institutions worldwide, for example, NASA Goddard Space Flight Center and German Research Center for Geosciences (GFZ), to produce global gravitational models from satellite tracking measurements of CHAMP and/or GRACE types. Such Earth's gravitational products have found widest possible multidisciplinary applications in Earth Sciences. The method is essentially implemented by solving the differential equations of the partial derivatives of the orbit of a satellite with respect to the unknown harmonic coefficients under the conditions of zero initial values. From the mathematical and statistical point of view, satellite gravimetry from satellite tracking is essentially the problem of estimating unknown parameters in the Newton's nonlinear differential equations from satellite tracking measurements. We prove that zero initial values for the partial derivatives are incorrect mathematically and not permitted physically. The numerical integration method, as currently implemented and used in mathematics and statistics, chemistry and physics, and satellite gravimetry, is groundless, mathematically and physically. Given the Newton's nonlinear governing differential equations of satellite motion with unknown equation parameters and unknown initial conditions, we develop three methods to derive new local solutions around a nominal reference orbit, which are linked to measurements to estimate the unknown corrections to approximate values of the unknown parameters and the unknown initial conditions. Bearing in mind that satellite orbits can now be tracked almost continuously at unprecedented accuracy, we propose the measurement-based perturbation theory and derive global uniformly convergent solutions to the Newton's nonlinear governing differential equations of satellite motion for the next generation of global gravitational models. Since the solutions are global uniformly convergent, theoretically speaking

On the reliable use of satellite-derived surface water products for global flood monitoring

Science.gov (United States)

Hirpa, F. A.; Revilla-Romero, B.; Thielen, J.; Salamon, P.; Brakenridge, R.; Pappenberger, F.; de Groeve, T.

2015-12-01

Early flood warning and real-time monitoring systems play a key role in flood risk reduction and disaster response management. To this end, real-time flood forecasting and satellite-based detection systems have been developed at global scale. However, due to the limited availability of up-to-date ground observations, the reliability of these systems for real-time applications have not been assessed in large parts of the globe. In this study, we performed comparative evaluations of the commonly used satellite-based global flood detections and operational flood forecasting system using 10 major flood cases reported over three years (2012-2014). Specially, we assessed the flood detection capabilities of the near real-time global flood maps from the Global Flood Detection System (GFDS), and from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the operational forecasts from the Global Flood Awareness System (GloFAS) for the major flood events recorded in global flood databases. We present the evaluation results of the global flood detection and forecasting systems in terms of correctly indicating the reported flood events and highlight the exiting limitations of each system. Finally, we propose possible ways forward to improve the reliability of large scale flood monitoring tools.

Merging thermal and microwave satellite observations for a high-resolution soil moisture data product

Science.gov (United States)

Many societal applications of soil moisture data products require high spatial resolution and numerical accuracy. Current thermal geostationary satellite sensors (GOES Imager and GOES-R ABI) could produce 2-16km resolution soil moisture proxy data. Passive microwave satellite radiometers (e.g. AMSR...

Resolving traceability issues of product derivation for software product lines

OpenAIRE

Abid, Saad bin

2009-01-01

peer-reviewed Dealing with traceability management issues during model based product derivation in large complex industrial SPL is error prone due to the lack of tool support. As a result traceability management between connected models emerges as an important research topic. In this position paper, we discuss research challenges as scenarios from developed example product line and give recommendations on resolving traceability issues during product derivation. We also discuss initial idea...

Comparison of Cloud Properties from CALIPSO-CloudSat and Geostationary Satellite Data

Science.gov (United States)

Nguyen, L.; Minnis, P.; Chang, F.; Winker, D.; Sun-Mack, S.; Spangenberg, D.; Austin, R.

2007-01-01

Cloud properties are being derived in near-real time from geostationary satellite imager data for a variety of weather and climate applications and research. Assessment of the uncertainties in each of the derived cloud parameters is essential for confident use of the products. Determination of cloud amount, cloud top height, and cloud layering is especially important for using these real -time products for applications such as aircraft icing condition diagnosis and numerical weather prediction model assimilation. Furthermore, the distribution of clouds as a function of altitude has become a central component of efforts to evaluate climate model cloud simulations. Validation of those parameters has been difficult except over limited areas where ground-based active sensors, such as cloud radars or lidars, have been available on a regular basis. Retrievals of cloud properties are sensitive to the surface background, time of day, and the clouds themselves. Thus, it is essential to assess the geostationary satellite retrievals over a variety of locations. The availability of cloud radar data from CloudSat and lidar data from CALIPSO make it possible to perform those assessments over each geostationary domain at 0130 and 1330 LT. In this paper, CloudSat and CALIPSO data are matched with contemporaneous Geostationary Operational Environmental Satellite (GOES), Multi-functional Transport Satellite (MTSAT), and Meteosat-8 data. Unlike comparisons with cloud products derived from A-Train imagers, this study considers comparisons of nadir active sensor data with off-nadir retrievals. These matched data are used to determine the uncertainties in cloud-top heights and cloud amounts derived from the geostationary satellite data using the Clouds and the Earth s Radiant Energy System (CERES) cloud retrieval algorithms. The CERES multi-layer cloud detection method is also evaluated to determine its accuracy and limitations in the off-nadir mode. The results will be useful for

Merged/integrated Bathymetric Data Derived from Multibeam Sonar, LiDAR, and Satellite-derived Bathymetry

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with derived bathymetry from alternate sources to provide a GIS layer with expanded spatial coverage. Integrated products...

Estimation of PV energy production based on satellite data

Science.gov (United States)

Mazurek, G.

2015-09-01

Photovoltaic (PV) technology is an attractive source of power for systems without connection to power grid. Because of seasonal variations of solar radiation, design of such a power system requires careful analysis in order to provide required reliability. In this paper we present results of three-year measurements of experimental PV system located in Poland and based on polycrystalline silicon module. Irradiation values calculated from results of ground measurements have been compared with data from solar radiation databases employ calculations from of satellite observations. Good convergence level of both data sources has been shown, especially during summer. When satellite data from the same time period is available, yearly and monthly production of PV energy can be calculated with 2% and 5% accuracy, respectively. However, monthly production during winter seems to be overestimated, especially in January. Results of this work may be helpful in forecasting performance of similar PV systems in Central Europe and allow to make more precise forecasts of PV system performance than based only on tables with long time averaged values.

Estimates of lightning NOx production from GOME satellite observations

Directory of Open Access Journals (Sweden)

K. F. Boersma

2005-01-01

Full Text Available Tropospheric NO2 column retrievals from the Global Ozone Monitoring Experiment (GOME satellite spectrometer are used to quantify the source strength and 3-D distribution of lightning produced nitrogen oxides (NOx=NO+NO2. A sharp increase of NO2 is observed at convective cloud tops with increasing cloud top height, consistent with a power-law behaviour with power 5±2. Convective production of clouds with the same cloud height are found to produce NO2 with a ratio 1.6/1 for continents compared to oceans. This relation between cloud properties and NO2 is used to construct a 10:30 local time global lightning NO2 production map for 1997. An extensive statistical comparison is conducted to investigate the capability of the TM3 chemistry transport model to reproduce observed patterns of lightning NO2 in time and space. This comparison uses the averaging kernel to relate modelled profiles of NO2 to observed NO2 columns. It exploits a masking scheme to minimise the interference of other NOx sources on the observed total columns. Simulations are performed with two lightning parameterizations, one relating convective preciptation (CP scheme to lightning flash distributions, and the other relating the fifth power of the cloud top height (H5 scheme to lightning distributions. The satellite-retrieved NO2 fields show significant correlations with the simulated lightning contribution to the NO2 concentrations for both parameterizations. Over tropical continents modelled lightning NO2 shows remarkable quantitative agreement with observations. Over the oceans however, the two model lightning parameterizations overestimate the retrieved NO2 attributed to lightning. Possible explanations for these overestimations are discussed. The ratio between satellite-retrieved NO2 and modelled lightning NO2 is used to rescale the original modelled lightning NOx production. Eight estimates of the lightning NOx production in 1997 are obtained from spatial and temporal

An Innovative Metric to Evaluate Satellite Precipitation's Spatial Distribution

Science.gov (United States)

Liu, H.; Chu, W.; Gao, X.; Sorooshian, S.

2011-12-01

Thanks to its capability to cover the mountains, where ground measurement instruments cannot reach, satellites provide a good means of estimating precipitation over mountainous regions. In regions with complex terrains, accurate information on high-resolution spatial distribution of precipitation is critical for many important issues, such as flood/landslide warning, reservoir operation, water system planning, etc. Therefore, in order to be useful in many practical applications, satellite precipitation products should possess high quality in characterizing spatial distribution. However, most existing validation metrics, which are based on point/grid comparison using simple statistics, cannot effectively measure satellite's skill of capturing the spatial patterns of precipitation fields. This deficiency results from the fact that point/grid-wised comparison does not take into account of the spatial coherence of precipitation fields. Furth more, another weakness of many metrics is that they can barely provide information on why satellite products perform well or poor. Motivated by our recent findings of the consistent spatial patterns of the precipitation field over the western U.S., we developed a new metric utilizing EOF analysis and Shannon entropy. The metric can be derived through two steps: 1) capture the dominant spatial patterns of precipitation fields from both satellite products and reference data through EOF analysis, and 2) compute the similarities between the corresponding dominant patterns using mutual information measurement defined with Shannon entropy. Instead of individual point/grid, the new metric treat the entire precipitation field simultaneously, naturally taking advantage of spatial dependence. Since the dominant spatial patterns are shaped by physical processes, the new metric can shed light on why satellite product can or cannot capture the spatial patterns. For demonstration, a experiment was carried out to evaluate a satellite

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tutuila Island, American Samoa, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Rose Atoll, American Samoa, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry were...

How robust are in situ observations for validating satellite-derived albedo over the dark zone of the Greenland Ice Sheet?

Science.gov (United States)

Ryan, J.; Hubbard, A., II; Irvine-Fynn, T. D.; Doyle, S. H.; Cook, J.; Stibal, M.; Smith, L. C.; Box, J. E.

2017-12-01

Calibration and validation of satellite-derived ice sheet albedo data require high-quality, in situ measurements commonly acquired by up and down facing pyranometers mounted on automated weather stations (AWS). However, direct comparison between ground and satellite-derived albedo can only be justified when the measured surface is homogeneous at the length-scale of both satellite pixel and in situ footprint. We used digital imagery acquired by an unmanned aerial vehicle to evaluate point-to-pixel albedo comparisons across the western, ablating margin of the Greenland Ice Sheet. Our results reveal that in situ measurements overestimate albedo by up to 0.10 at the end of the melt season because the ground footprints of AWS-mounted pyranometers are insufficient to capture the spatial heterogeneity of the ice surface as it progressively ablates and darkens. Statistical analysis of 21 AWS across the entire Greenland Ice Sheet reveals that almost half suffer from this bias, including some AWS located within the wet snow zone.

Error estimates for near-Real-Time Satellite Soil Moisture as Derived from the Land Parameter Retrieval Model

NARCIS (Netherlands)

Parinussa, R.M.; Meesters, A.G.C.A.; Liu, Y.Y.; Dorigo, W.; Wagner, W.; de Jeu, R.A.M.

2011-01-01

A time-efficient solution to estimate the error of satellite surface soil moisture from the land parameter retrieval model is presented. The errors are estimated using an analytical solution for soil moisture retrievals from this radiative-transfer-based model that derives soil moisture from

Underway Sampling of Marine Inherent Optical Properties on the Tara Oceans Expedition as a Novel Resource for Ocean Color Satellite Data Product Validation

Science.gov (United States)

Werdell, P. Jeremy; Proctor, Christopher W.; Boss, Emmanuel; Leeuw, Thomas; Ouhssain, Mustapha

2013-01-01

Developing and validating data records from operational ocean color satellite instruments requires substantial volumes of high quality in situ data. In the absence of broad, institutionally supported field programs, organizations such as the NASA Ocean Biology Processing Group seek opportunistic datasets for use in their operational satellite calibration and validation activities. The publicly available, global biogeochemical dataset collected as part of the two and a half year Tara Oceans expedition provides one such opportunity. We showed how the inline measurements of hyperspectral absorption and attenuation coefficients collected onboard the R/V Tara can be used to evaluate near-surface estimates of chlorophyll-a, spectral particulate backscattering coefficients, particulate organic carbon, and particle size classes derived from the NASA Moderate Resolution Imaging Spectroradiometer onboard Aqua (MODISA). The predominant strength of such flow-through measurements is their sampling rate-the 375 days of measurements resulted in 165 viable MODISA-to-in situ match-ups, compared to 13 from discrete water sampling. While the need to apply bio-optical models to estimate biogeochemical quantities of interest from spectroscopy remains a weakness, we demonstrated how discrete samples can be used in combination with flow-through measurements to create data records of sufficient quality to conduct first order evaluations of satellite-derived data products. Given an emerging agency desire to rapidly evaluate new satellite missions, our results have significant implications on how calibration and validation teams for these missions will be constructed.

Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Baker Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

The relationship of field burn severity measures to satellite-derived Burned Area Reflectance Classification (BARC) maps

Science.gov (United States)

Andrew Hudak; Penelope Morgan; Carter Stone; Pete Robichaud; Terrie Jain; Jess Clark

2004-01-01

Preliminary results are presented from ongoing research on spatial variability of fire effects on soils and vegetation from the Black Mountain Two and Cooney Ridge wildfires, which burned in western Montana during the 2003 fire season. Extensive field fractional cover data were sampled to assess the efficacy of quantitative satellite image-derived indicators of burn...

On the assimilation of satellite derived soil moisture in numerical weather prediction models

Science.gov (United States)

Drusch, M.

2006-12-01

Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.

Preparing for Automated Derivation of Products in a Software Product Line

National Research Council Canada - National Science Library

McGregor, John D

2005-01-01

... to bring a product to market, or through other production improvements. Business goals such as these make automated product derivation an appealing strategy to a software product line organization...

Modelling ocean-colour-derived chlorophyll a

Directory of Open Access Journals (Sweden)

S. Dutkiewicz

2018-01-01

Full Text Available This article provides a proof of concept for using a biogeochemical/ecosystem/optical model with a radiative transfer component as a laboratory to explore aspects of ocean colour. We focus here on the satellite ocean colour chlorophyll a (Chl a product provided by the often-used blue/green reflectance ratio algorithm. The model produces output that can be compared directly to the real-world ocean colour remotely sensed reflectance. This model output can then be used to produce an ocean colour satellite-like Chl a product using an algorithm linking the blue versus green reflectance similar to that used for the real world. Given that the model includes complete knowledge of the (model water constituents, optics and reflectance, we can explore uncertainties and their causes in this proxy for Chl a (called derived Chl a in this paper. We compare the derived Chl a to the actual model Chl a field. In the model we find that the mean absolute bias due to the algorithm is 22 % between derived and actual Chl a. The real-world algorithm is found using concurrent in situ measurement of Chl a and radiometry. We ask whether increased in situ measurements to train the algorithm would improve the algorithm, and find a mixed result. There is a global overall improvement, but at the expense of some regions, especially in lower latitudes where the biases increase. Not surprisingly, we find that region-specific algorithms provide a significant improvement, at least in the annual mean. However, in the model, we find that no matter how the algorithm coefficients are found there can be a temporal mismatch between the derived Chl a and the actual Chl a. These mismatches stem from temporal decoupling between Chl a and other optically important water constituents (such as coloured dissolved organic matter and detrital matter. The degree of decoupling differs regionally and over time. For example, in many highly seasonal regions, the timing of initiation

Satellite Data Support for the ARM Climate Research Facility, 8/01/2009 - 7/31/2015

Energy Technology Data Exchange (ETDEWEB)

Minnis, Patrick [NASA Langley Research Center, Hampton, VA (United States); Khaiyer, Mandana M [Science Systems and Applications, Inc., Hampton, VA (United States)

2015-10-06

This report summarizes the support provided by NASA Langley Research for the DOE ARM Program in the form of cloud and radiation products derived from satellite imager data for the period between 8/01/09 through 7/31/15. Cloud properties such as cloud amount, height, and optical depth as well as outgoing longwave and shortwave broadband radiative fluxes were derived from geostationary and low-earth orbiting satellite imager radiance measurements for domains encompassing ARM permanent sites and field campaigns during the performance period. Datasets provided and documents produced are listed.

Mosaic of bathymetry derived from multispectral World View-2 satellite imagery of Sarigan Island, Territory of Territory of Mariana, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Agrihan Island, Territory of Mariana, USA (NODC Accession 0126914)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multispectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

Solar resources and power potential mapping in Vietnam using satellite-derived and GIS-based information

International Nuclear Information System (INIS)

Polo, J.; Bernardos, A.; Navarro, A.A.; Fernandez-Peruchena, C.M.; Ramírez, L.; Guisado, María V.; Martínez, S.

2015-01-01

Highlights: • Satellite-based, reanalysis data and measurements are combined for solar mapping. • Plant output modeling for PV and CSP results in simple expressions of solar potential. • Solar resource, solar potential are used in a GIS for determine technical solar potential. • Solar resource and potential maps of Vietnam are presented. - Abstract: The present paper presents maps of the solar resources in Vietnam and of the solar potential for concentrating solar power (CSP) and for grid-connected photovoltaic (PV) technology. The mapping of solar radiation components has been calculated from satellite-derived data combined with solar radiation derived from sunshine duration and other additional sources of information based on reanalysis for several atmospheric and meteorological parameters involved. Two scenarios have been selected for the study of the solar potential: CSP Parabolic Trough of 50 MWe and grid-connected Flat Plate PV plant of around 1 MWe. For each selected scenario plant performance simulations have been computed for developing simple expressions that allow the estimation of the solar potential from the annual solar irradiation and the latitude of every site in Vietnam. Finally, Geographic Information Systems (GIS) have been used for combining the solar potential with the land availability according each scenario to deliver the technical solar potential maps of Vietnam

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.

How consistent are global long-term satellite LAI products in terms of interannual variability and trend?

Science.gov (United States)

Jiang, C.; Ryu, Y.; Fang, H.

2016-12-01

Proper usage of global satellite LAI products requires comprehensive evaluation. To address this issue, the Committee on Earth Observation Satellites (CEOS) Land Product Validation (LPV) subgroup proposed a four-stage validation hierarchy. During the past decade, great efforts have been made following this validation framework, mainly focused on absolute magnitude, seasonal trajectory, and spatial pattern of those global satellite LAI products. However, interannual variability and trends of global satellite LAI products have been investigated marginally. Targeting on this gap, we made an intercomparison between seven global satellite LAI datasets, including four short-term ones: MODIS C5, MODIS C6, GEOV1, MERIS, and three long-term products ones: LAI3g, GLASS, and GLOBMAP. We calculated global annual LAI time series for each dataset, among which we found substantial differences. During the overlapped period (2003 - 2011), MODIS C5, GLASS and GLOBMAP have positive correlation (r > 0.6) between each other, while MODIS C6, GEOV1, MERIS, and LAI3g are highly consistent (r > 0.7) in interannual variations. However, the previous three datasets show negative trends, all of which use MODIS C5 reflectance data, whereas the latter four show positive trends, using MODIS C6, SPOT/VGT, ENVISAT/MERIS, and NOAA/AVHRR, respectively. During the pre-MODIS era (1982 - 1999), the three AVHRR-based datasets (LAI3g, GLASS and GLOBMAP) agree well (r > 0.7), yet all of them show oscillation related with NOAA platform changes. In addition, both GLASS and GLOBMAP show clear cut-points around 2000 when they move from AVHRR to MODIS. Such inconsistency is also visible for GEOV1, which uses SPOT-4 and SPOT-5 before and after 2002. We further investigate the map-to-map deviations among these products. This study highlights that continuous sensor calibration and cross calibration are essential to obtain reliable global LAI time series.

Product derivation in software product families : a case study

NARCIS (Netherlands)

Deelstra, S; Sinnema, M; Bosch, J

2005-01-01

From our experience with several organizations that employ software product families, we have learned that, contrary to popular belief, deriving individual products from shared software assets is a time-consuming and expensive activity. In this paper we therefore present a study that investigated

ASSESSMENT OF SATELLITE PRECIPITATION PRODUCTS IN THE PHILIPPINE ARCHIPELAGO

Directory of Open Access Journals (Sweden)

M. D. Ramos

2016-06-01

Full Text Available Precipitation is the most important weather parameter in the Philippines. Made up of more than 7100 islands, the Philippine archipelago is an agricultural country that depends on rain-fed crops. Located in the western rim of the North West Pacific Ocean, this tropical island country is very vulnerable to tropical cyclones that lead to severe flooding events. Recently, satellite-based precipitation estimates have improved significantly and can serve as alternatives to ground-based observations. These data can be used to fill data gaps not only for climatic studies, but can also be utilized for disaster risk reduction and management activities. This study characterized the statistical errors of daily precipitation from four satellite-based rainfall products from (1 the Tropical Rainfall Measuring Mission (TRMM, (2 the CPC Morphing technique (CMORPH of NOAA and (3 the Global Satellite Mapping of Precipitation (GSMAP and (4 Precipitation Estimation from Remotely Sensed information using Artificial Neural Networks (PERSIANN. Precipitation data were compared to 52 synoptic weather stations located all over the Philippines. Results show GSMAP to have over all lower bias and CMORPH with lowest Mean Absolute Error (MAE and Root Mean Square Error (RMSE. In addition, a dichotomous rainfall test reveals GSMAP and CMORPH have low Proportion Correct (PC for convective and stratiform rainclouds, respectively. TRMM consistently showed high PC for almost all raincloud types. Moreover, all four satellite precipitation showed high Correct Negatives (CN values for the north-western part of the country during the North-East monsoon and spring monsoonal transition periods.

Assessment of Satellite Precipitation Products in the Philippine Archipelago

Science.gov (United States)

Ramos, M. D.; Tendencia, E.; Espana, K.; Sabido, J.; Bagtasa, G.

2016-06-01

Precipitation is the most important weather parameter in the Philippines. Made up of more than 7100 islands, the Philippine archipelago is an agricultural country that depends on rain-fed crops. Located in the western rim of the North West Pacific Ocean, this tropical island country is very vulnerable to tropical cyclones that lead to severe flooding events. Recently, satellite-based precipitation estimates have improved significantly and can serve as alternatives to ground-based observations. These data can be used to fill data gaps not only for climatic studies, but can also be utilized for disaster risk reduction and management activities. This study characterized the statistical errors of daily precipitation from four satellite-based rainfall products from (1) the Tropical Rainfall Measuring Mission (TRMM), (2) the CPC Morphing technique (CMORPH) of NOAA and (3) the Global Satellite Mapping of Precipitation (GSMAP) and (4) Precipitation Estimation from Remotely Sensed information using Artificial Neural Networks (PERSIANN). Precipitation data were compared to 52 synoptic weather stations located all over the Philippines. Results show GSMAP to have over all lower bias and CMORPH with lowest Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). In addition, a dichotomous rainfall test reveals GSMAP and CMORPH have low Proportion Correct (PC) for convective and stratiform rainclouds, respectively. TRMM consistently showed high PC for almost all raincloud types. Moreover, all four satellite precipitation showed high Correct Negatives (CN) values for the north-western part of the country during the North-East monsoon and spring monsoonal transition periods.

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

OpenAIRE

Ayehu, Getachew Tesfaye; Tadesse, Tsegaye; Gessesse, Berhan; Dinku, Tufa

2018-01-01

Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor) ground observations) or through...

Evaluation of Latent Heat Flux Fields from Satellites and Models during SEMAPHORE.

Science.gov (United States)

Bourras, Denis; Liu, W. Timothy; Eymard, Laurence; Tang, Wenqing

2003-02-01

Latent heat fluxes were derived from satellite observations in the region of Structure des Echanges Mer-Atmosphère, Propriétés des Hétérogénéités Océaniques: Recherche Expérimentale (SEMAPHORE), which was conducted near the Azores islands in the North Atlantic Ocean in autumn of 1993. The satellite fluxes were compared with output fields of two atmospheric circulation models and in situ measurements. The rms error of the instantaneous satellite fluxes is between 35 and 40 W m-2 and the bias is 60-85 W m-2. The large bias is mainly attributed to a bias in satellite-derived atmospheric humidity and is related to the particular shape of the vertical humidity profiles during SEMAPHORE. The bias in humidity implies that the range of estimated fluxes is smaller than the range of ship fluxes, by 34%-38%. The rms errors for fluxes from models are 30-35 W m-2, and the biases are smaller than the biases in satellite fluxes (14-18 W m-2). Two case studies suggest that the satellites detect horizontal gradients of wind speed and specific humidity if the magnitude of the gradients exceeds a detection threshold, which is 1.27 g kg-1 (100 km)-1 for specific humidity and between 0.35 and 0.82 m s-1 (30 km)-1 for wind speed. In contrast, the accuracy of the spatial gradients of bulk variables from models always varies as a function of the location and number of assimilated observations. A comparison between monthly fluxes from satellites and models reveals that satellite-derived flux anomaly fields are consistent with reanalyzed fields, whereas operational model products lack part of the mesoscale structures present in the satellite fields.

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...

Satellite Monitoring of Ash and Sulphur Dioxide for the mitigation of Aviation Hazards: Part II. Validation of satellite-derived Volcanic Sulphur Dioxide Levels.

Science.gov (United States)

Koukouli, MariLiza; Balis, Dimitris; Dimopoulos, Spiros; Clarisse, Lieven; Carboni, Elisa; Hedelt, Pascal; Spinetti, Claudia; Theys, Nicolas; Tampellini, Lucia; Zehner, Claus

2014-05-01

The eruption of the Icelandic volcano Eyjafjallajökull in the spring of 2010 turned the attention of both the public and the scientific community to the susceptibility of the European airspace to the outflows of large volcanic eruptions. The ash-rich plume from Eyjafjallajökull drifted towards Europe and caused major disruptions of European air traffic for several weeks affecting the everyday life of millions of people and with a strong economic impact. This unparalleled situation revealed limitations in the decision making process due to the lack of information on the tolerance to ash of commercial aircraft engines as well as limitations in the ash monitoring and prediction capabilities. The European Space Agency project Satellite Monitoring of Ash and Sulphur Dioxide for the mitigation of Aviation Hazards, was introduced to facilitate the development of an optimal End-to-End System for Volcanic Ash Plume Monitoring and Prediction. This system is based on comprehensive satellite-derived ash plume and sulphur dioxide [SO2] level estimates, as well as a widespread validation using supplementary satellite, aircraft and ground-based measurements. The validation of volcanic SO2 levels extracted from the sensors GOME-2/MetopA and IASI/MetopA are shown here with emphasis on the total column observed right before, during and after the Eyjafjallajökull 2010 eruptions. Co-located ground-based Brewer Spectrophotometer data extracted from the World Ozone and Ultraviolet Radiation Data Centre, WOUDC, were compared to the different satellite estimates. The findings are presented at length, alongside a comprehensive discussion of future scenarios.

CDDIS_GNSS_products_erp

Data.gov (United States)

National Aeronautics and Space Administration — Earth Rotation Parameters (ERPs) derived from analysis of Global Navigation Satellite System (GNSS) data. These products are the generated by analysis centers in...

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)

Evaluation of Satellite and Model Precipitation Products Over Turkey

Science.gov (United States)

Yilmaz, M. T.; Amjad, M.

2017-12-01

Satellite-based remote sensing, gauge stations, and models are the three major platforms to acquire precipitation dataset. Among them satellites and models have the advantage of retrieving spatially and temporally continuous and consistent datasets, while the uncertainty estimates of these retrievals are often required for many hydrological studies to understand the source and the magnitude of the uncertainty in hydrological response parameters. In this study, satellite and model precipitation data products are validated over various temporal scales (daily, 3-daily, 7-daily, 10-daily and monthly) using in-situ measured precipitation observations from a network of 733 gauges from all over the Turkey. Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 version 7 and European Center of Medium-Range Weather Forecast (ECMWF) model estimates (daily, 3-daily, 7-daily and 10-daily accumulated forecast) are used in this study. Retrievals are evaluated for their mean and standard deviation and their accuracies are evaluated via bias, root mean square error, error standard deviation and correlation coefficient statistics. Intensity vs frequency analysis and some contingency table statistics like percent correct, probability of detection, false alarm ratio and critical success index are determined using daily time-series. Both ECMWF forecasts and TRMM observations, on average, overestimate the precipitation compared to gauge estimates; wet biases are 10.26 mm/month and 8.65 mm/month, respectively for ECMWF and TRMM. RMSE values of ECMWF forecasts and TRMM estimates are 39.69 mm/month and 41.55 mm/month, respectively. Monthly correlations between Gauges-ECMWF, Gauges-TRMM and ECMWF-TRMM are 0.76, 0.73 and 0.81, respectively. The model and the satellite error statistics are further compared against the gauges error statistics based on inverse distance weighting (IWD) analysis. Both the model and satellite data have less IWD errors (14

Satellite observation of particulate organic carbon dynamics in ...

Science.gov (United States)

Particulate organic carbon (POC) plays an important role in coastal carbon cycling and the formation of hypoxia. Yet, coastal POC dynamics are often poorly understood due to a lack of long-term POC observations and the complexity of coastal hydrodynamic and biogeochemical processes that influence POC sources and sinks. Using field observations and satellite ocean color products, we developed a nw multiple regression algorithm to estimate POC on the Louisiana Continental Shelf (LCS) from satellite observations. The algorithm had reliable performance with mean relative error (MRE) of ?40% and root mean square error (RMSE) of ?50% for MODIS and SeaWiFS images for POC ranging between ?80 and ?1200 mg m23, and showed similar performance for a large estuary (Mobile Bay). Substantial spatiotemporal variability in the satellite-derived POC was observed on the LCS, with high POC found on the inner shelf (satellite data with carefully developed algorithms can greatly increase

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.

Deriving the effect of wind speed on clean marine aerosol optical properties using the A-Train satellites

Directory of Open Access Journals (Sweden)

V. P. Kiliyanpilakkil

2011-11-01

showed a tendency toward leveling off, asymptotically approaching value of 0.15. The conclusions of this study regarding the aerosol extinction vs. wind speed relationship may have been influenced by the constant lidar ratio used for CALIPSO-derived AOD₅₃₂. Nevertheless, active satellite sensor used in this study that allows separation of maritime wind induced component of AOD from the total AOD over the ocean could lead to improvements in optical properties of sea spray aerosols and their production mechanisms.

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Palmyra Atoll, Pacific Remote Island Area, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

JPSS Preparations at the Satellite Proving Ground for Marine, Precipitation, and Satellite Analysis

Science.gov (United States)

Folmer, Michael J.; Berndt, E.; Clark, J.; Orrison, A.; Kibler, J.; Sienkiewicz, J.; Nelson, J.; Goldberg, M.; Sjoberg, W.

2016-01-01

The ocean prediction center at the national hurricane center's tropical analysis and forecast Branch, the Weather Prediction center and the Satellite analysis branch of NESDIS make up the Satellite Proving Ground for Marine, Precipitation and Satellite Analysis. These centers had early exposure to JPSS products using the S-NPP Satellite that was launched in 2011. Forecasters continue to evaluate new products in anticipation for the launch of JPSS-1 sometime in 2017.

Monitoring Cyanobacteria with Satellites Webinar

Science.gov (United States)

real-world satellite applications can quantify cyanobacterial harmful algal blooms and related water quality parameters. Provisional satellite derived cyanobacteria data and different software tools are available to state environmental and health agencies.

Hurricane Satellite (HURSAT) Microwave (MW)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Hurricane Satellite (HURSAT) from Microwave (MW) observations of tropical cyclones worldwide data consist of raw satellite observations. The data derive from the...

A Comparative Study on Satellite- and Model-Based Crop Phenology in West Africa

Directory of Open Access Journals (Sweden)

Elodie Vintrou

2014-02-01

Full Text Available Crop phenology is essential for evaluating crop production in the food insecure regions of West Africa. The aim of the paper is to study whether satellite observation of plant phenology are consistent with ground knowledge of crop cycles as expressed in agro-simulations. We used phenological variables from a MODIS Land Cover Dynamics (MCD12Q2 product and examined whether they reproduced the spatio-temporal variability of crop phenological stages in Southern Mali. Furthermore, a validated cereal crop growth model for this region, SARRA-H (System for Regional Analysis of Agro-Climatic Risks, provided precise agronomic information. Remotely-sensed green-up, maturity, senescence and dormancy MODIS dates were extracted for areas previously identified as crops and were compared with simulated leaf area indices (LAI temporal profiles generated using the SARRA-H crop model, which considered the main cropping practices. We studied both spatial (eight sites throughout South Mali during 2007 and temporal (two sites from 2002 to 2008 differences between simulated crop cycles and determined how the differences were indicated in satellite-derived phenometrics. The spatial comparison of the phenological indicator observations and simulations showed mainly that (i the satellite-derived start-of-season (SOS was detected approximately 30 days before the model-derived SOS; and (ii the satellite-derived end-of-season (EOS was typically detected 40 days after the model-derived EOS. Studying the inter-annual difference, we verified that the mean bias was globally consistent for different climatic conditions. Therefore, the land cover dynamics derived from the MODIS time series can reproduce the spatial and temporal variability of different start-of-season and end-of-season crop species. In particular, we recommend simultaneously using start-of-season phenometrics with crop models for yield forecasting to complement commonly used climate data and provide a better

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

NARCIS (Netherlands)

Tote, C.; Patricio, D.; Boogaard, H.L.; Wijngaart, van der R.; Tarnavsky, E.; Funk, C.

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and

Impact of the assimilation of satellite soil moisture and LST on the hydrological cycle

Science.gov (United States)

Laiolo, Paola; Gabellani, Simone; Delogu, Fabio; Silvestro, Francesco; Rudari, Roberto; Campo, Lorenzo; Boni, Giorgio

2014-05-01

The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce ground based data. The aim of this work is to investigate the impacts on the performances of a distributed hydrological model (Continuum) of the assimilation of satellite-derived soil moisture products and Land Surface (LST). In this work three different soil moisture (SM) products, derived by ASCAT sensor, are used. These data are provided by the EUMETSAT's H-SAF (Satellite Application Facility on Support to Operational Hydrology and Water Management) program. The considered soil moisture products are: large scale surface soil moisture (SM OBS 1 - H07), small scale surface soil moisture (SM OBS 2 - H08) and profile index in the roots region (SM DAS 2 - H14). These data are compared with soil moisture estimated by Continuum model on the Orba catchment (800 km2), in the northern part of Italy, for the period July 2012-June 2013. Different assimilation experiments have been performed. The first experiment consists in the assimilation of the SM products by using a simple Nudging technique; the second one is the assimilation of only LST data, derived from MSG satellite, and the third is the assimilation of both SM products and LST. The benefits on the model predictions of discharge, LST and soil moisture dynamics were tested.

A Novel Approach for Forecasting Crop Production and Yield Using Remotely Sensed Satellite Images

Science.gov (United States)

Singh, R. K.; Budde, M. E.; Senay, G. B.; Rowland, J.

2017-12-01

Forecasting crop production in advance of crop harvest plays a significant role in drought impact management, improved food security, stabilizing food grain market prices, and poverty reduction. This becomes essential, particularly in Sub-Saharan Africa, where agriculture is a critical source of livelihoods, but lacks good quality agricultural statistical data. With increasing availability of low cost satellite data, faster computing power, and development of modeling algorithms, remotely sensed images are becoming a common source for deriving information for agricultural, drought, and water management. Many researchers have shown that the Normalized Difference Vegetation Index (NDVI), based on red and near-infrared reflectance, can be effectively used for estimating crop production and yield. Similarly, crop production and yield have been closely related to evapotranspiration (ET) also as there are strong linkages between production/yield and transpiration based on plant physiology. Thus, we combined NDVI and ET information from remotely sensed images for estimating total production and crop yield prior to crop harvest for Niger and Burkina Faso in West Africa. We identified the optimum time (dekads 23-29) for cumulating NDVI and ET and developed a new algorithm for estimating crop production and yield. We used the crop data from 2003 to 2008 to calibrate our model and the data from 2009 to 2013 for validation. Our results showed that total crop production can be estimated within 5% of actual production (R2 = 0.98) about 30-45 days before end of the harvest season. This novel approach can be operationalized to provide a valuable tool to decision makers for better drought impact management in drought-prone regions of the world.

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.

Satellite-Based Derivation of High-Resolution Forest Information Layers for Operational Forest Management

Directory of Open Access Journals (Sweden)

Johannes Stoffels

2015-06-01

Full Text Available A key factor for operational forest management and forest monitoring is the availability of up-to-date spatial information on the state of forest resources. Earth observation can provide valuable contributions to these information needs. The German federal state of Rhineland-Palatinate transferred its inherited forest information system to a new architecture that is better able to serve the needs of centralized inventory and planning services, down to the level of forest districts. During this process, a spatially adaptive classification approach was developed to derive high-resolution forest information layers (e.g., forest type, tree species distribution, development stages based on multi-temporal satellite data. This study covers the application of the developed approach to a regional scale (federal state level and the further adaptation of the design to meet the information needs of the state forest service. The results confirm that the operational requirements for mapping accuracy can, in principle, be fulfilled. However, the state-wide mapping experiment also revealed that the ability to meet the required level of accuracy is largely dependent on the availability of satellite observations within the optimum phenological time-windows.

Assessment of satellite rainfall products over the Andean plateau

Science.gov (United States)

Satgé, Frédéric; Bonnet, Marie-Paule; Gosset, Marielle; Molina, Jorge; Hernan Yuque Lima, Wilson; Pillco Zolá, Ramiro; Timouk, Franck; Garnier, Jérémie

2016-01-01

Nine satellite rainfall estimations (SREs) were evaluated for the first time over the South American Andean plateau watershed by comparison with rain gauge data acquired between 2005 and 2007. The comparisons were carried out at the annual, monthly and daily time steps. All SREs reproduce the salient pattern of the annual rain field, with a marked north-south gradient and a lighter east-west gradient. However, the intensity of the gradient differs among SREs: it is well marked in the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 (TMPA-3B42), Precipitation Estimation from remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Global Satellite Mapping of Precipitation (GSMaP) products, and it is smoothed out in the Climate prediction center MORPHing (CMORPH) products. Another interesting difference among products is the contrast in rainfall amounts between the water surfaces (Lake Titicaca) and the surrounding land. Some products (TMPA-3B42, PERSIANN and GSMaP) show a contradictory rainfall deficit over Lake Titicaca, which may be due to the emissivity contrast between the lake and the surrounding lands and warm rain cloud processes. An analysis differentiating coastal Lake Titicaca from inland pixels confirmed this trend. The raw or Real Time (RT) products have strong biases over the study region. These biases are strongly positive for PERSIANN (above 90%), moderately positive for TMPA-3B42 (28%), strongly negative for CMORPH (- 42%) and moderately negative for GSMaP (- 18%). The biases are associated with a deformation of the rain rate frequency distribution: GSMaP underestimates the proportion of rainfall events for all rain rates; CMORPH overestimates the proportion of rain rates below 2 mm day- 1; and the other products tend to overestimate the proportion of moderate to high rain rates. These biases are greatly reduced by the gauge adjustment in the TMPA-3B42, PERSIANN and CMORPH products, whereas a

Characterization of the variability of the South Pacific Convergence Zone using satellite and reanalysis wind product

Science.gov (United States)

Lee, T.; Kidwell, A. N.; Jo, Y. H.; Yan, X. H.

2016-02-01

The variability of the South Pacific Convergence Zone (SPCZ) is evaluated using ocean surface wind products derived from the QuickSCAT satellite scatterometer for the period of 1999-2009and ERA-Interim atmospheric reanalysis for the period of 1981-2014. From these products, indices were developed to represent the SPCZ strength, area, and centroid location. Excellent agreement is found between the indices derived from the two wind products during the QuikSCAT period in terms of the spatio-temporal structures of the SPCZ. The longer ERA-Interim product is then used to study the variations of SPCZ properties on intraseasonal, seasonal, interannual, and decadal time scales. The SPCZ strength, area, and centroid latitude have a dominant seasonal cycle. In contrast, the SPCZ centroid longitude is dominated by intraseasonal variability due to the influence by the Madden-Julian Oscillation. The SPCZ indices are all correlated with El Niño-Southern Oscillation indices. Interannual and intraseasonal variations of SPCZ strength during strong El Niño are approximately twice as large as the respective seasonal variations. SPCZ strength depends more on the intensity of El Niño rather than the central- vs. eastern-Pacific type. The change from positive to negative Pacific Decadal Oscillation phase around 1999 results in a westward shift of the SPCZ centroid longitude, much smaller interannual swing in centroid latitude, and a decrease in SPCZ area. This study improves the understanding of the variations of the SPCZ on multiple time scales and reveals the variations of SPCZ strength not reported previously. The diagnostics analyses can be used to evaluate climate models.

A new CM SAF Solar Surface Radiation Climate Data Set derived from Meteosat Satellite Observations

Science.gov (United States)

Trentmann, J.; Mueller, R. W.; Pfeifroth, U.; Träger-Chatterjee, C.; Cremer, R.

2014-12-01

The incoming surface solar radiation has been defined as an essential climate variable by GCOS. It is mandatory to monitor this part of the earth's energy balance, and thus gain insights on the state and variability of the climate system. In addition, data sets of the surface solar radiation have received increased attention over the recent years as an important source of information for the planning of solar energy applications. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) is deriving surface solar radiation from geostationary and polar-orbiting satellite instruments. While CM SAF is focusing on the generation of high-quality long-term climate data records, also operationally data is provided in short time latency within 8 weeks. Here we present SARAH (Solar Surface Radiation Dataset - Heliosat), i.e. the new CM SAF Solar Surface Radiation data set based on Meteosat satellite observations. SARAH provides instantaneous, daily- and monthly-averaged data of the effective cloud albedo (CAL), the direct normalized solar radiation (DNI) and the solar irradiance (SIS) from 1983 to 2013 for the full view of the Meteosat satellite (i.e, Europe, Africa, parts of South America, and the Atlantic ocean). The data sets are generated with a high spatial resolution of 0.05 deg allowing for detailed regional studies, and are available in netcdf-format at no cost without restrictions at www.cmsaf.eu. We provide an overview of the data sets, including a validation against reference measurements from the BSRN and GEBA surface station networks.

Using GIS data and satellite derived irradiance to optimize siting of PV installations in Switzerland

Science.gov (United States)

Kahl, Annelen; Nguyen, Viet-Anh; Bartlett, Stuart; Sossan, Fabrizio; Lehning, Michael

2016-04-01

For a successful distribution strategy of PV installations, it does not suffice to choose the locations with highest annual total irradiance. Attention needs to be given to spatial correlation patterns of insolation to avoid large system-wide variations, which can cause extended deficits in supply or might even damage the electrical network. One alternative goal instead is to seek configurations that provide the smoothest energy production, with the most reliable and predictable supply. Our work investigates several scenarios, each pursuing a different strategy for a future renewable Switzerland without nuclear power. Based on an estimate for necessary installed capacity for solar power [Bartlett, 2015] we first use heuristics to pre-select realistic placements for PV installations. Then we apply optimization methods to find a subset of locations that provides the best possible combined electricity production. For the first part of the selection process, we use a DEM to exclude high elevation zones which would be difficult to access and which are prone to natural hazards. Then we use land surface cover information to find all zones with potential roof area, deemed suitable for installation of solar panels. The optimization employs Principal Component Analysis of satellite derived irradiance data (Surface Incoming Shortwave Radiation (SIS), based on Meteosat Second Generation sensors) to incorporate a spatial aspect into the selection process that does not simply maximize annual total production but rather provides the most robust supply, by combining regions with anti-correlated cloud cover patterns. Depending on the initial assumptions and constraints, the resulting distribution schemes for PV installations vary with respect to required surface area, annual total and lowest short-term production, and illustrate how important it is to clearly define priorities and policies for a future renewable Switzerland.

Spatially Explicit Estimation of Optimal Light Use Efficiency for Improved Satellite Data Driven Ecosystem Productivity Modeling

Science.gov (United States)

Madani, N.; Kimball, J. S.; Running, S. W.

2014-12-01

Remote sensing based light use efficiency (LUE) models, including the MODIS (MODerate resolution Imaging Spectroradiometer) MOD17 algorithm are commonly used for regional estimation and monitoring of vegetation gross primary production (GPP) and photosynthetic carbon (CO2) uptake. A common model assumption is that plants in a biome matrix operate at their photosynthetic capacity under optimal climatic conditions. A prescribed biome maximum light use efficiency parameter defines the maximum photosynthetic carbon conversion rate under prevailing climate conditions and is a large source of model uncertainty. Here, we used tower (FLUXNET) eddy covariance measurement based carbon flux data for estimating optimal LUE (LUEopt) over a North American domain. LUEopt was first estimated using tower observed daily carbon fluxes, meteorology and satellite (MODIS) observed fraction of photosynthetically active radiation (FPAR). LUEopt was then spatially interpolated over the domain using empirical models derived from independent geospatial data including global plant traits, surface soil moisture, terrain aspect, land cover type and percent tree cover. The derived LUEopt maps were then used as primary inputs to the MOD17 LUE algorithm for regional GPP estimation; these results were evaluated against tower observations and alternate MOD17 GPP estimates determined using Biome-specific LUEopt constants. Estimated LUEopt shows large spatial variability within and among different land cover classes indicated from a sparse North American tower network. Leaf nitrogen content and soil moisture are two important factors explaining LUEopt spatial variability. GPP estimated from spatially explicit LUEopt inputs shows significantly improved model accuracy against independent tower observations (R2 = 0.76; Mean RMSE plant trait information can explain spatial heterogeneity in LUEopt, leading to improved GPP estimates from satellite based LUE models.

Evaluation of NWP-based Satellite Precipitation Error Correction with Near-Real-Time Model Products and Flood-inducing Storms

Science.gov (United States)

Zhang, X.; Anagnostou, E. N.; Schwartz, C. S.

2017-12-01

Satellite precipitation products tend to have significant biases over complex terrain. Our research investigates a statistical approach for satellite precipitation adjustment based solely on numerical weather simulations. This approach has been evaluated in two mid-latitude (Zhang et al. 2013*1, Zhang et al. 2016*2) and three topical mountainous regions by using the WRF model to adjust two high-resolution satellite products i) National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center morphing technique (CMORPH) and ii) Global Satellite Mapping of Precipitation (GSMaP). Results show the adjustment effectively reduces the satellite underestimation of high rain rates, which provides a solid proof-of-concept for continuing research of NWP-based satellite correction. In this study we investigate the feasibility of using NCAR Real-time Ensemble Forecasts*3 for adjusting near-real-time satellite precipitation datasets over complex terrain areas in the Continental United States (CONUS) such as Olympic Peninsula, California coastal mountain ranges, Rocky Mountains and South Appalachians. The research will focus on flood-inducing storms occurred from May 2015 to December 2016 and four satellite precipitation products (CMORPH, GSMaP, PERSIANN-CCS and IMERG). The error correction performance evaluation will be based on comparisons against the gauge-adjusted Stage IV precipitation data. *1 Zhang, Xinxuan, et al. "Using NWP simulations in satellite rainfall estimation of heavy precipitation events over mountainous areas." Journal of Hydrometeorology 14.6 (2013): 1844-1858. *2 Zhang, Xinxuan, et al. "Hydrologic Evaluation of NWP-Adjusted CMORPH Estimates of Hurricane-Induced Precipitation in the Southern Appalachians." Journal of Hydrometeorology 17.4 (2016): 1087-1099. *3 Schwartz, Craig S., et al. "NCAR's experimental real-time convection-allowing ensemble prediction system." Weather and Forecasting 30.6 (2015): 1645-1654.

Providing Access and Visualization to Global Cloud Properties from GEO Satellites

Science.gov (United States)

Chee, T.; Nguyen, L.; Minnis, P.; Spangenberg, D.; Palikonda, R.; Ayers, J. K.

2015-12-01

Providing public access to cloud macro and microphysical properties is a key concern for the NASA Langley Research Center Cloud and Radiation Group. This work describes a tool and method that allows end users to easily browse and access cloud information that is otherwise difficult to acquire and manipulate. The core of the tool is an application-programming interface that is made available to the public. One goal of the tool is to provide a demonstration to end users so that they can use the dynamically generated imagery as an input into their own work flows for both image generation and cloud product requisition. This project builds upon NASA Langley Cloud and Radiation Group's experience with making real-time and historical satellite cloud product imagery accessible and easily searchable. As we see the increasing use of virtual supply chains that provide additional value at each link there is value in making satellite derived cloud product information available through a simple access method as well as allowing users to browse and view that imagery as they need rather than in a manner most convenient for the data provider. Using the Open Geospatial Consortium's Web Processing Service as our access method, we describe a system that uses a hybrid local and cloud based parallel processing system that can return both satellite imagery and cloud product imagery as well as the binary data used to generate them in multiple formats. The images and cloud products are sourced from multiple satellites and also "merged" datasets created by temporally and spatially matching satellite sensors. Finally, the tool and API allow users to access information that spans the time ranges that our group has information available. In the case of satellite imagery, the temporal range can span the entire lifetime of the sensor.

Asian Dust Weather Categorization with Satellite and Surface Observations

Science.gov (United States)

Lin, Tang-Huang; Hsu, N. Christina; Tsay, Si-Chee; Huang, Shih-Jen

2011-01-01

This study categorizes various dust weather types by means of satellite remote sensing over central Asia. Airborne dust particles can be identified by satellite remote sensing because of the different optical properties exhibited by coarse and fine particles (i.e. varying particle sizes). If a correlation can be established between the retrieved aerosol optical properties and surface visibility, the intensity of dust weather can be more effectively and consistently discerned using satellite rather than surface observations. In this article, datasets consisting of collocated products from Moderate Resolution Imaging Spectroradiometer Aqua and surface measurements are analysed. The results indicate an exponential relationship between the surface visibility and the satellite-retrieved aerosol optical depth, which is subsequently used to categorize the dust weather. The satellite-derived spatial frequency distributions in the dust weather types are consistent with China s weather station reports during 2003, indicating that dust weather classification using satellite data is highly feasible. Although the period during the springtime from 2004 to 2007 may be not sufficient for statistical significance, our results reveal an increasing tendency in both intensity and frequency of dust weather over central Asia during this time period.

Error Analysis of Satellite Precipitation-Driven Modeling of Flood Events in Complex Alpine Terrain

Directory of Open Access Journals (Sweden)

Yiwen Mei

2016-03-01

Full Text Available The error in satellite precipitation-driven complex terrain flood simulations is characterized in this study for eight different global satellite products and 128 flood events over the Eastern Italian Alps. The flood events are grouped according to two flood types: rain floods and flash floods. The satellite precipitation products and runoff simulations are evaluated based on systematic and random error metrics applied on the matched event pairs and basin-scale event properties (i.e., rainfall and runoff cumulative depth and time series shape. Overall, error characteristics exhibit dependency on the flood type. Generally, timing of the event precipitation mass center and dispersion of the time series derived from satellite precipitation exhibits good agreement with the reference; the cumulative depth is mostly underestimated. The study shows a dampening effect in both systematic and random error components of the satellite-driven hydrograph relative to the satellite-retrieved hyetograph. The systematic error in shape of the time series shows a significant dampening effect. The random error dampening effect is less pronounced for the flash flood events and the rain flood events with a high runoff coefficient. This event-based analysis of the satellite precipitation error propagation in flood modeling sheds light on the application of satellite precipitation in mountain flood hydrology.

Satellite Earth observation data to identify climate and anthropogenic pressures on Bucharest periurban forests

Energy Technology Data Exchange (ETDEWEB)

Zoran, Maria; Savastru, Roxana; Savastru, Dan [National Institute of R& D for Optoelectronics, MG5 Bucharest-Magurele, 077125 Romania (Romania); Dida, Adrian [University Transylvania of Brasov, Brasov (Romania)

2016-03-25

Satellite Earth observation data in the visible and near-infrared (VNIR) wavelengths represent a useful source of information for forest systems monitoring through derived biogeophysical parameters (vegetation index, leaf area index, canopy cover, fraction of absorbed photosynthetically active radiation, chlorophyll content, net primary production, canopy water stress, etc.). Use of satellite remote sensing data to assess forest spatio-temporal changes due to climatic or anthropogenic stressors is an excellent example of the value of multispectral and multitemporal observations. Fusion technique was applied to time-series multispectral and multitemporal satellite imagery (NOAA AVHRR, MODIS Terra/Aqua, Landsat ETM and IKONOS satellite data) for periurban forest areas Cernica-Branesti, placed in the neighboring of Bucharest town, Romania, over 2002-2014 period.

Satellite Earth observation data to identify climate and anthropogenic pressures on Bucharest periurban forests

International Nuclear Information System (INIS)

Zoran, Maria; Savastru, Roxana; Savastru, Dan; Dida, Adrian

2016-01-01

Satellite Earth observation data in the visible and near-infrared (VNIR) wavelengths represent a useful source of information for forest systems monitoring through derived biogeophysical parameters (vegetation index, leaf area index, canopy cover, fraction of absorbed photosynthetically active radiation, chlorophyll content, net primary production, canopy water stress, etc.). Use of satellite remote sensing data to assess forest spatio-temporal changes due to climatic or anthropogenic stressors is an excellent example of the value of multispectral and multitemporal observations. Fusion technique was applied to time-series multispectral and multitemporal satellite imagery (NOAA AVHRR, MODIS Terra/Aqua, Landsat ETM and IKONOS satellite data) for periurban forest areas Cernica-Branesti, placed in the neighboring of Bucharest town, Romania, over 2002-2014 period.

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Sarigan Island, Territory of Mariana, USA.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Rota Island, Territory of Mariana, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

Comparison of cloud top heights derived from FY-2 meteorological satellites with heights derived from ground-based millimeter wavelength cloud radar

Science.gov (United States)

Wang, Zhe; Wang, Zhenhui; Cao, Xiaozhong; Tao, Fa

2018-01-01

Clouds are currently observed by both ground-based and satellite remote sensing techniques. Each technique has its own strengths and weaknesses depending on the observation method, instrument performance and the methods used for retrieval. It is important to study synergistic cloud measurements to improve the reliability of the observations and to verify the different techniques. The FY-2 geostationary orbiting meteorological satellites continuously observe the sky over China. Their cloud top temperature product can be processed to retrieve the cloud top height (CTH). The ground-based millimeter wavelength cloud radar can acquire information about the vertical structure of clouds-such as the cloud base height (CBH), CTH and the cloud thickness-and can continuously monitor changes in the vertical profiles of clouds. The CTHs were retrieved using both cloud top temperature data from the FY-2 satellites and the cloud radar reflectivity data for the same time period (June 2015 to May 2016) and the resulting datasets were compared in order to evaluate the accuracy of CTH retrievals using FY-2 satellites. The results show that the concordance rate of cloud detection between the two datasets was 78.1%. Higher consistencies were obtained for thicker clouds with larger echo intensity and for more continuous clouds. The average difference in the CTH between the two techniques was 1.46 km. The difference in CTH between low- and mid-level clouds was less than that for high-level clouds. An attenuation threshold of the cloud radar for rainfall was 0.2 mm/min; a rainfall intensity below this threshold had no effect on the CTH. The satellite CTH can be used to compensate for the attenuation error in the cloud radar data.

A new model of Earth's radial conductivity structure derived from over 10 yr of satellite and observatory magnetic data

DEFF Research Database (Denmark)

Püthe, Christoph; Kuvshinov, Alexey; Khan, Amir

2015-01-01

We present a newmodel of the radial (1-D) conductivity structure of Earth's mantle. This model is derived frommore than 10 yr of magnetic measurements from the satellites ørsted, CHAMP, SAC-C and the Swarm trio as well as the global network of geomagnetic observatories. After removal of core...

Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002-2012)

Science.gov (United States)

Prat, O. P.; Nelson, B. R.

2015-04-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over the contiguous United States (CONUS) for the period 2002-2012. This comparison effort includes satellite multi-sensor data sets (bias-adjusted TMPA 3B42, near-real-time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation data sets are compared with surface observations from the Global Historical Climatology Network-Daily (GHCN-D) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (±6%). However, differences at the RFC are more important in particular for near-real-time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near-real-time counterpart 3B42RT. However, large biases remained for 3B42 over the western USA for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in. day-1) over the Pacific Northwest. Furthermore, the conditional analysis and a contingency analysis conducted illustrated the challenge in retrieving extreme precipitation from remote sensing estimates.

Mosaic of bathymetry derived from multispectral World View-2 satellite imagery of Ni'ihau Island, Territory of the Main Hawaiian Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

A model of Earth’s magnetic field derived from 2 years of Swarm satellite constellation data

DEFF Research Database (Denmark)

Olsen, Nils; Finlay, Chris; Kotsiaros, Stavros

2016-01-01

More than 2 years of magnetic field data taken by the three-satellite constellation mission Swarm are used to derive a model of Earth’s magnetic field and its time variation. This model is called SIFMplus. In addition to the magnetic field observations provided by each of the three Swarm satellites...... the North–South gradient. The SIFMplus model provides a description of the static lithospheric field that is very similar to models determined from CHAMP data, up to at least spherical harmonic degree n=75. Also the core field part of SIFMplus, with a quadratic time dependence for n≤6 and a linear time...... with the model of the core, lithospheric and large-scale magnetospheric fields, a magnetic potential that depends on quasi-dipole latitude and magnetic local time....

Effects of assimilating precipitation zones derived from satellite and lightning data on numerical simulations of tropical-like Mediterranean storms

Science.gov (United States)

Fita, L.; Romero, R.; Luque, A.; Ramis, C.

2009-08-01

The scarcity of meteorological observations in maritime areas is a well-known problem that can be an important limitation in the study of different phenomena. Tropical-like storms or medicanes developed over the Mediterranean sea are intense storms with some similarities to the tropical ones. Although they do not reach the hurricane intensity, their potential for damage is very high, due to the densely populated Mediterranean coastal regions. In this study, the two notable cases of medicane development which occurred in the western Mediterranean basin in September 1996 and October 2003, are considered. The capability of mesoscale numerical models to simulate general aspects of such a phenomena has been previously shown. With the aim of improving the numerical results, an adjustment of the humidity vertical profiles in MM5 simulations is performed by means of satellite derived precipitation. Convective and stratiform precipitation types obtained from satellite images are used to individually adjust the profiles. Lightning hits are employed to identify convective grid points. The adjustment of the vertical humidity profiles is carried out in the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses used as initial conditions for the simulations. Analyses nudging to ECMWF analyses and to the satellite-based humidity-corrected version of these analyses has also been applied using Four Dimensional Data Assimilation (FDDA). An additional adjustment is applied as observation nudging of satellite/lightning information at different time and spatial resolutions. Statistical parameters are proposed and tested as an objective way to intercompare satellite-derived and simulated trajectories. Simulations of medicanes exhibit a strong sensitivity to vertical humidity profiles. Trajectories of the storms are improved or worsened by using FDDA. A case dependence is obtained on the characteristics of the humidity-corrected medicanes. FDDA sensitivity on temporal and

Effects of assimilating precipitation zones derived from satellite and lightning data on numerical simulations of tropical-like Mediterranean storms

Directory of Open Access Journals (Sweden)

L. Fita

2009-08-01

Full Text Available The scarcity of meteorological observations in maritime areas is a well-known problem that can be an important limitation in the study of different phenomena. Tropical-like storms or medicanes developed over the Mediterranean sea are intense storms with some similarities to the tropical ones. Although they do not reach the hurricane intensity, their potential for damage is very high, due to the densely populated Mediterranean coastal regions. In this study, the two notable cases of medicane development which occurred in the western Mediterranean basin in September 1996 and October 2003, are considered. The capability of mesoscale numerical models to simulate general aspects of such a phenomena has been previously shown. With the aim of improving the numerical results, an adjustment of the humidity vertical profiles in MM5 simulations is performed by means of satellite derived precipitation. Convective and stratiform precipitation types obtained from satellite images are used to individually adjust the profiles. Lightning hits are employed to identify convective grid points. The adjustment of the vertical humidity profiles is carried out in the European Centre for Medium-Range Weather Forecasts (ECMWF analyses used as initial conditions for the simulations. Analyses nudging to ECMWF analyses and to the satellite-based humidity-corrected version of these analyses has also been applied using Four Dimensional Data Assimilation (FDDA. An additional adjustment is applied as observation nudging of satellite/lightning information at different time and spatial resolutions. Statistical parameters are proposed and tested as an objective way to intercompare satellite-derived and simulated trajectories. Simulations of medicanes exhibit a strong sensitivity to vertical humidity profiles. Trajectories of the storms are improved or worsened by using FDDA. A case dependence is obtained on the characteristics of the humidity-corrected medicanes. FDDA sensitivity

Effects of assimilating precipitation zones derived from satellite and lightning data on numerical simulations of tropical-like Mediterranean storms

Energy Technology Data Exchange (ETDEWEB)

Fita, L.; Romero, R.; Luque, A.; Ramis, C. [Univ. de les Illes Balears, Palma de Mallorca (Spain). Grup de Meteorologia

2009-07-01

The scarcity of meteorological observations in maritime areas is a well-known problem that can be an important limitation in the study of different phenomena. Tropical-like storms or medicanes developed over the Mediterranean sea are intense storms with some similarities to the tropical ones. Although they do not reach the hurricane intensity, their potential for damage is very high, due to the densely populated Mediterranean coastal regions. In this study, the two notable cases of medicane development which occurred in the western Mediterranean basin in September 1996 and October 2003, are considered. The capability of mesoscale numerical models to simulate general aspects of such a phenomena has been previously shown. With the aim of improving the numerical results, an adjustment of the humidity vertical profiles in MM5 simulations is performed by means of satellite derived precipitation. Convective and stratiform precipitation types obtained from satellite images are used to individually adjust the profiles. Lightning hits are employed to identify convective grid points. The adjustment of the vertical humidity profiles is carried out in the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses used as initial conditions for the simulations. Analyses nudging to ECMWF analyses and to the satellite-based humidity-corrected version of these analyses has also been applied using Four Dimensional Data Assimilation (FDDA). An additional adjustment is applied as observation nudging of satellite/lightning information at different time and spatial resolutions. Statistical parameters are proposed and tested as an objective way to intercompare satellite-derived and simulated trajectories. Simulations of medicanes exhibit a strong sensitivity to vertical humidity profiles. Trajectories of the storms are improved or worsened by using FDDA. A case dependence is obtained on the characteristics of the humidity-corrected medicanes. FDDA sensitivity on temporal and

Preliminary hard and soft bottom seafloor substrate map derived from an supervised classification of bathymetry derived from multispectral World View-2 satellite imagery of Ni'ihau Island, Territory of Main Hawaiian Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary hard and soft seafloor substrate map derived from a supervised classification from multispectral World View-2 satellite imagery of Ni'ihau Island,...

Satellite Derived Water Quality Observations Are Related to River Discharge and Nitrogen Loads in Pensacola Bay, Florida

OpenAIRE

John C. Lehrter; John C. Lehrter; Chengfeng Le

2017-01-01

Relationships between satellite-derived water quality variables and river discharges, concentrations and loads of nutrients, organic carbon, and sediments were investigated over a 9-year period (2003–2011) in Pensacola Bay, Florida, USA. These analyses were conducted to better understand which river forcing factors were the primary drivers of estuarine variability in several water quality variables. Remote sensing reflectance time-series data were retrieved from the MEdium Resolution Imaging ...

Evaluating Satellite Products for Precipitation Estimation in Mountain Regions: A Case Study for Nepal

Directory of Open Access Journals (Sweden)

Tarendra Lakhankar

2013-08-01

Full Text Available Precipitation in mountain regions is often highly variable and poorly observed, limiting abilities to manage water resource challenges. Here, we evaluate remote sensing and ground station-based gridded precipitation products over Nepal against weather station precipitation observations on a monthly timescale. We find that the Tropical Rainfall Measuring Mission (TRMM 3B-43 precipitation product exhibits little mean bias and reasonable skill in giving precipitation over Nepal. Compared to station observations, the TRMM precipitation product showed an overall Nash-Sutcliffe efficiency of 0.49, which is similar to the skill of the gridded station-based product Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE. The other satellite precipitation products considered (Global Satellite Mapping of Precipitation (GSMaP, the Climate Prediction Center Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS were less skillful, as judged by Nash-Sutcliffe efficiency, and, on average, substantially underestimated precipitation compared to station observations, despite their, in some cases, higher nominal spatial resolution compared to TRMM. None of the products fully captured the dependence of mean precipitation on elevation seen in the station observations. Overall, the TRMM product is promising for use in water resources applications.

Advanced Satellite-Derived Wind Observations, Assimilation, and Targeting Strategies during TCS-08 for Developing Improved Operational Analysis and Prediction of Western Pacific Tropical Cyclones

Science.gov (United States)

2013-09-30

TC structure evolve up to landfall or extratropical transition. In particular, winds derived from geostationary satellites have been shown to be an... extratropical transition, it is clear that a dedicated research effort is needed to optimize the satellite data processing strategies, assimilation, and...applications to better understand the behavior of the near- storm environmental flow fields during these evolutionary TC stages. To our knowledge, this

JPSS Preparations at the Satellite Proving Ground for Marine, Precipitation, and Satellite Analysis

Science.gov (United States)

Folmer, M. J.; Berndt, E.; Clark, J.; Orrison, A.; Kibler, J.; Sienkiewicz, J. M.; Nelson, J. A., Jr.; Goldberg, M.

2016-12-01

The National Oceanic and Atmospheric Administration (NOAA) Satellite Proving Ground (PG) for Marine, Precipitation, and Satellite Analysis (MPS) has been demonstrating and evaluating Suomi National Polar-orbiting Partnership (S-NPP) products along with other polar-orbiting satellite platforms in preparation for the Joint Polar Satellite System - 1 (JPSS-1) launch in March 2017. The first S-NPP imagery was made available to the MPS PG during the evolution of Hurricane Sandy in October 2012 and has since been popular in operations. Since this event the MPS PG Satellite Liaison has been working with forecasters on ways to integrate single-channel and multispectral imagery from the Visible Infrared Imaging Radiometer Suite (VIIRS), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Advanced Very High Resolution Radiometer (AVHRR)into operations to complement numerical weather prediction and geostationary satellite savvy National Weather Service (NWS) National Centers. Additional unique products have been introduced to operations to address specific forecast challenges, including the Cooperative Institute for Research in the Atmosphere (CIRA) Layered Precipitable Water, the National Environmental Satellite, Data, and Information Service (NESDIS) Snowfall Rate product, NOAA Unique Combined Atmospheric Processing System (NUCAPS) Soundings, ozone products from the Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS), and Infrared Atmospheric Sounding Interferometer (IASI). In addition, new satellite domains have been created to provide forecasters at the NWS Ocean Prediction Center and Weather Prediction Center with better quality imagery at high latitudes. This has led to research projects that are addressing forecast challenges such as tropical to extratropical transition and explosive cyclogenesis. This presentation will provide examples of how the MPS PG has been introducing and integrating

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Ofu and Olosega Islands, Territory of American Samoa, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multipectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

Detecting weather radar clutter using satellite-based nowcasting products

DEFF Research Database (Denmark)

Jensen, Thomas B.S.; Gill, Rashpal S.; Overgaard, Søren

2006-01-01

This contribution presents the initial results from experiments with detection of weather radar clutter by information fusion with satellite based nowcasting products. Previous studies using information fusion of weather radar data and first generation Meteosat imagery have shown promising results...... for the detecting and removal of clutter. Naturally, the improved spatio-temporal resolution of the Meteosat Second Generation sensors, coupled with its increased number of spectral bands, is expected to yield even better detection accuracies. Weather radar data from three C-band Doppler weather radars...... Application Facility' of EUMETSAT and is based on multispectral images from the SEVIRI sensor of the Meteosat-8 platform. Of special interest is the 'Precipitating Clouds' product, which uses the spectral information coupled with surface temperatures from Numerical Weather Predictions to assign probabilities...

Evaluation of the Performance of Three Satellite Precipitation Products over Africa

Directory of Open Access Journals (Sweden)

Aleix Serrat-Capdevila

2016-10-01

Full Text Available We present an evaluation of daily estimates from three near real-time quasi-global Satellite Precipitation Products—Tropical Rainfall Measuring Mission (TRMM Multi-satellite Precipitation Analysis (TMPA, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, and Climate Prediction Center (CPC Morphing Technique (CMORPH—over the African continent, using the Global Precipitation Climatology Project one Degree Day (GPCP-1dd as a reference dataset for years 2001 to 2013. Different types of errors are characterized for each season as a function of spatial classifications (latitudinal bands, climatic zones and topography and in relationship with the main rain-producing mechanisms in the continent: the Intertropical Convergence Zone (ITCZ and the East African Monsoon. A bias correction of the satellite estimates is applied using a probability density function (pdf matching approach, with a bias analysis as a function of rain intensity, season and latitude. The effects of bias correction on different error terms are analyzed, showing an almost elimination of the mean and variance terms in most of the cases. While raw estimates of TMPA show higher efficiency, all products have similar efficiencies after bias correction. PERSIANN consistently shows the smallest median errors when it correctly detects precipitation events. The areas with smallest relative errors and other performance measures follow the position of the ITCZ oscillating seasonally over the equator, illustrating the close relationship between satellite estimates and rainfall regime.

Merging of airborne gravity and gravity derived from satellite altimetry: Test cases along the coast of greenland

DEFF Research Database (Denmark)

Olesen, Arne Vestergaard; Andersen, Ole Baltazar; Tscherning, C.C.

2002-01-01

for the use of gravity data especially, when computing geoid models in coastal regions. The presence of reliable marine gravity data for independent control offers an opportunity to study procedures for the merging of airborne and satellite data around Greenland. Two different merging techniques, both based......The National Survey and Cadastre - Denmark (KMS) has for several years produced gravity anomaly maps over the oceans derived from satellite altimetry. During the last four years, KMS has also conducted airborne gravity surveys along the coast of Greenland dedicated to complement the existing...... onshore gravity coverage and fill in new data in the very-near coastal area, where altimetry data may contain gross errors. The airborne surveys extend from the coastline to approximately 100 km offshore, along 6000 km of coastline. An adequate merging of these different data sources is important...

Satellite Image Classification of Building Damages Using Airborne and Satellite Image Samples in a Deep Learning Approach

Science.gov (United States)

Duarte, D.; Nex, F.; Kerle, N.; Vosselman, G.

2018-05-01

The localization and detailed assessment of damaged buildings after a disastrous event is of utmost importance to guide response operations, recovery tasks or for insurance purposes. Several remote sensing platforms and sensors are currently used for the manual detection of building damages. However, there is an overall interest in the use of automated methods to perform this task, regardless of the used platform. Owing to its synoptic coverage and predictable availability, satellite imagery is currently used as input for the identification of building damages by the International Charter, as well as the Copernicus Emergency Management Service for the production of damage grading and reference maps. Recently proposed methods to perform image classification of building damages rely on convolutional neural networks (CNN). These are usually trained with only satellite image samples in a binary classification problem, however the number of samples derived from these images is often limited, affecting the quality of the classification results. The use of up/down-sampling image samples during the training of a CNN, has demonstrated to improve several image recognition tasks in remote sensing. However, it is currently unclear if this multi resolution information can also be captured from images with different spatial resolutions like satellite and airborne imagery (from both manned and unmanned platforms). In this paper, a CNN framework using residual connections and dilated convolutions is used considering both manned and unmanned aerial image samples to perform the satellite image classification of building damages. Three network configurations, trained with multi-resolution image samples are compared against two benchmark networks where only satellite image samples are used. Combining feature maps generated from airborne and satellite image samples, and refining these using only the satellite image samples, improved nearly 4 % the overall satellite image

Stem-cell-derived products: an FDA update.

Science.gov (United States)

Moos, Malcolm

2008-12-01

The therapeutic potential of products derived from stem cells of various types has prompted increasing research and development and public attention. Initiation of human clinical trials in the not-too-distant future is now a realistic possibility. It is, therefore, important to weigh the potential benefits against known, theoretical and totally unsuspected risks in light of current knowledge to ensure that subjects participating in these trials are afforded the most reasonable balance possible between potential risks and potential benefits. There are no apparent differences in fundamental, qualitative biological characteristics between stem-cell-derived products and other cellular therapies regulated by the United States Food and Drug Administration (FDA). Existing authorities can, therefore, be applied. Nevertheless, these products do have properties that require careful evaluation.

LAI, FAPAR and FCOVER products derived from AVHRR long time series: principles and evaluation

Science.gov (United States)

Verger, A.; Baret, F.; Weiss, M.; Lacaze, R.; Makhmara, H.; Pacholczyk, P.; Smets, B.; Kandasamy, S.; Vermote, E.

2012-04-01

Continuous and long term global monitoring of the terrestrial biosphere has draught an intense interest in the recent years in the context of climate and global change. Developing methodologies for generating historical data records from data collected with different satellite sensors over the past three decades by taking benefits from the improvements identified in the processing of the new generation sensors is a new central issue in remote sensing community. In this context, the Bio-geophysical Parameters (BioPar) service within Geoland2 project (http://www.geoland2.eu) aims at developing pre-operational infrastructures for providing global land products both in near real time and off-line mode with long time series. In this contribution, we describe the principles of the GEOLAND algorithm for generating long term datasets of three key biophysical variables, leaf area index (LAI), Fraction of Absorbed Photosynthetic Active Radiation (FAPAR) and cover fraction (FCOVER), that play a key role in several processes, including photosynthesis, respiration and transpiration. LAI, FAPAR and FCOVER are produced globally from AVHRR Long Term Data Record (LTDR) for the 1981-2000 period at 0.05° spatial resolution and 10 days temporal sampling frequency. The proposed algorithm aims to ensure robustness of the derived long time series and consistency with the ones developed in the recent years, and particularly with GEOLAND products derived from VEGETATION sensor. The approach is based on the capacity of neural networks to learn a particular biophysical product (GEOLAND) from reflectances from another sensor (AVHRR normalized reflectances in the red and near infrared bands). Outliers due to possible cloud contamination or residual atmospheric correction are iteratively eliminated. Prior information based on the climatology is used to get more robust estimates. A specific gap filing and smoothing procedure was applied to generate continuous and smooth time series of decadal

Animal derived products may conflict with religious patients' beliefs.

Science.gov (United States)

Eriksson, Axelina; Burcharth, Jakob; Rosenberg, Jacob

2013-12-01

Implants and drugs with animal and human derived content are widely used in medicine and surgery, but information regarding ingredients is rarely obtainable by health practitioners. A religious perspective concerning the use of animal and human derived drug ingredients has not thoroughly been investigated. The purpose of this study was to clarify which parts of the medical and surgical treatments offered in western world-hospitals that conflicts with believers of major religions. Religious and spiritual leaders of the six largest religions worldwide (18 branches) were contacted. A standardised questionnaire was sent out regarding their position on the use of human and animal derived products in medical and surgical treatments. Of the 18 contacted religious branches, 10 replied representing the 6 largest religions worldwide. Hindus and Sikhs did not approve of the use of bovine or porcine derived products, and Muslims did not accept the use of porcine derived drugs, dressings or implants. Christians (including Jehovah's Witnesses), Jews and Buddhists accepted the use of all animal and human derived products. However, all religions accepted the use of all these products in case of an emergency and only if alternatives were not available. The views here suggest that religious codes conflict with some treatment regimens. It is crucial to obtain informed consent from patients for the use of drugs and implants with animal or human derived content. However, information on the origin of ingredients in drugs is not always available to health practitioners.

Some European capabilities in satellite cinema exhibition

Science.gov (United States)

Bock, Wolfgang

1990-08-01

The likely performance envelope and architecture for satellite cinema systems are derived from simple practical assumptions. A case is made for possible transatlantic cooperation towards establishing a satellite cinema standard.

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

Science.gov (United States)

Tesfaye Ayehu, Getachew; Tadesse, Tsegaye; Gessesse, Berhan; Dinku, Tufa

2018-04-01

Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor) ground observations) or through integrating with rain gauge measurements. In this study, the potential of a newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall product has been evaluated in comparison to rain gauge data over the Upper Blue Nile basin in Ethiopia for the period of 2000 to 2015. In addition, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT 3) and the African Rainfall Climatology (ARC 2) products have been used as a benchmark and compared with CHIRPS. From the overall analysis at dekadal (10 days) and monthly temporal scale, CHIRPS exhibited better performance in comparison to TAMSAT 3 and ARC 2 products. An evaluation based on categorical/volumetric and continuous statistics indicated that CHIRPS has the greatest skills in detecting rainfall events (POD = 0.99, 1.00) and measure of volumetric rainfall (VHI = 1.00, 1.00), the highest correlation coefficients (r = 0.81, 0.88), better bias values (0.96, 0.96), and the lowest RMSE (28.45 mm dekad-1, 59.03 mm month-1) than TAMSAT 3 and ARC 2 products at dekadal and monthly analysis, respectively. CHIRPS overestimates the frequency of rainfall occurrence (up to 31 % at dekadal scale), although the volume of rainfall recorded during those events was very small. Indeed, TAMSAT 3 has shown a comparable performance with that of the CHIRPS product, mainly with regard to bias. The ARC 2 product was found to have the weakest performance underestimating rain gauge observed rainfall by

The ecology of malaria--as seen from Earth-observation satellites.

Science.gov (United States)

Thomson, M C; Connor, S J; Milligan, P J; Flasse, S P

1996-06-01

Data from sensors on board geostationary and polar-orbiting, meteorological satellites (Meteosat and NOAA series) are routinely obtained free, via local reception systems, in an increasing number of African countries. Data collected by these satellites are processed to produce proxy ecological variables which have been extensively investigated for monitoring changes in the distribution and condition of different natural resources, including rainfall and vegetation state. How these data products (once incorporated, along with other data, into a geographical information system) could contribute to the goals of monitoring patterns of malaria transmission, predicting epidemics and planning control strategies is the subject of the present review. By way of illustration, an analysis of two of these products, normalized difference vegetation index (NVDI) and cold-cloud duration (CCD), is given in conjunction with epidemiological and entomological data from The Gambia, a country where extensive studies on malaria transmission have been undertaken in recent years. Preliminary results indicate that even simple analysis of proxy ecological variables derived from satellite data can indicate variation in environmental factors affecting malaria-transmission indices. However, it is important to note that the associations observed will vary depending on the local ecology, season and species of vector. Whilst further quantitative research is required to validate the relationship between satellite-data products and malaria-transmission indices, this approach offers a means by which detailed knowledge of the underlying spatial and temporal variation in the environment can be incorporated into a decision-support system for malaria control.

A lithospheric magnetic field model derived from the Swarm satellite magnetic field measurements

Science.gov (United States)

Hulot, G.; Thebault, E.; Vigneron, P.

2015-12-01

The Swarm constellation of satellites was launched in November 2013 and has since then delivered high quality scalar and vector magnetic field measurements. A consortium of several research institutions was selected by the European Space Agency (ESA) to provide a number of scientific products which will be made available to the scientific community. Within this framework, specific tools were tailor-made to better extract the magnetic signal emanating from Earth's the lithospheric. These tools rely on the scalar gradient measured by the lower pair of Swarm satellites and rely on a regional modeling scheme that is more sensitive to small spatial scales and weak signals than the standard spherical harmonic modeling. In this presentation, we report on various activities related to data analysis and processing. We assess the efficiency of this dedicated chain for modeling the lithospheric magnetic field using more than one year of measurements, and finally discuss refinements that are continuously implemented in order to further improve the robustness and the spatial resolution of the lithospheric field model.

Statistical properties of entropy production derived from fluctuation theorems

International Nuclear Information System (INIS)

Merhav, Neri; Kafri, Yariv

2010-01-01

Several implications of well-known fluctuation theorems, on the statistical properties of entropy production, are studied using various approaches. We begin by deriving a tight lower bound on the variance of the entropy production for a given mean of this random variable. It is shown that the Evans–Searles fluctuation theorem alone imposes a significant lower bound on the variance only when the mean entropy production is very small. It is then nonetheless demonstrated that upon incorporating additional information concerning the entropy production, this lower bound can be significantly improved, so as to capture extensivity properties. Another important aspect of the fluctuation properties of the entropy production is the relationship between the mean and the variance, on the one hand, and the probability of the event where the entropy production is negative, on the other hand. Accordingly, we derive upper and lower bounds on this probability in terms of the mean and the variance. These bounds are tighter than previous bounds that can be found in the literature. Moreover, they are tight in the sense that there exist probability distributions, satisfying the Evans–Searles fluctuation theorem, that achieve them with equality. Finally, we present a general method for generating a wide class of inequalities that must be satisfied by the entropy production. We use this method to derive several new inequalities that go beyond the standard derivation of the second law

Electricity derivative markets: Investment valuation, production planning and hedging

International Nuclear Information System (INIS)

Naesaekkaelae, E.

2005-01-01

This thesis studies electricity derivative markets from a view point of an electricity producer. The traditionally used asset pricing methods, based on the no arbitrage principle, are extended to take into account electricity specific features: the non storability of electricity and the variability in the load process. The sources of uncertainty include electricity forward curve, prices of resources used to generate electricity, and the size of the future production. Also the effects of competitors' actions are considered. The thesis illustrates how the information in the derivative prices can be used in investment and production planning. In addition, the use of derivatives as a tool to stabilize electricity dependent cash flows is considered. The results indicate that the information about future electricity prices and their uncertainty, obtained from derivative markets, is important in investment analysis and production planning. (orig.)

Electricity derivative markets: Investment valuation, production planning and hedging

Energy Technology Data Exchange (ETDEWEB)

Naesaekkaelae, E.

2005-07-01

This thesis studies electricity derivative markets from a view point of an electricity producer. The traditionally used asset pricing methods, based on the no arbitrage principle, are extended to take into account electricity specific features: the non storability of electricity and the variability in the load process. The sources of uncertainty include electricity forward curve, prices of resources used to generate electricity, and the size of the future production. Also the effects of competitors' actions are considered. The thesis illustrates how the information in the derivative prices can be used in investment and production planning. In addition, the use of derivatives as a tool to stabilize electricity dependent cash flows is considered. The results indicate that the information about future electricity prices and their uncertainty, obtained from derivative markets, is important in investment analysis and production planning. (orig.)

Initial results of centralized autonomous orbit determination of the new-generation BDS satellites with inter-satellite link measurements

Science.gov (United States)

Tang, Chengpan; Hu, Xiaogong; Zhou, Shanshi; Liu, Li; Pan, Junyang; Chen, Liucheng; Guo, Rui; Zhu, Lingfeng; Hu, Guangming; Li, Xiaojie; He, Feng; Chang, Zhiqiao

2018-01-01

Autonomous orbit determination is the ability of navigation satellites to estimate the orbit parameters on-board using inter-satellite link (ISL) measurements. This study mainly focuses on data processing of the ISL measurements as a new measurement type and its application on the centralized autonomous orbit determination of the new-generation Beidou navigation satellite system satellites for the first time. The ISL measurements are dual one-way measurements that follow a time division multiple access (TDMA) structure. The ranging error of the ISL measurements is less than 0.25 ns. This paper proposes a derivation approach to the satellite clock offsets and the geometric distances from TDMA dual one-way measurements without a loss of accuracy. The derived clock offsets are used for time synchronization, and the derived geometry distances are used for autonomous orbit determination. The clock offsets from the ISL measurements are consistent with the L-band two-way satellite, and time-frequency transfer clock measurements and the detrended residuals vary within 0.5 ns. The centralized autonomous orbit determination is conducted in a batch mode on a ground-capable server for the feasibility study. Constant hardware delays are present in the geometric distances and become the largest source of error in the autonomous orbit determination. Therefore, the hardware delays are estimated simultaneously with the satellite orbits. To avoid uncertainties in the constellation orientation, a ground anchor station that "observes" the satellites with on-board ISL payloads is introduced into the orbit determination. The root-mean-square values of orbit determination residuals are within 10.0 cm, and the standard deviation of the estimated ISL hardware delays is within 0.2 ns. The accuracy of the autonomous orbits is evaluated by analysis of overlap comparison and the satellite laser ranging (SLR) residuals and is compared with the accuracy of the L-band orbits. The results indicate

Particle production in higher derivative theory

Indian Academy of Sciences (India)

Lemaitre–Robertson–Walker cosmological model during the early stages of the universe is analysed in the framework of higher derivative theory. The universe has been considered as an open thermodynamic system where particle production ...

Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

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.

TOGA COARE Satellite data summaries available on the World Wide Web

Science.gov (United States)

Chen, S. S.; Houze, R. A., Jr.; Mapes, B. E.; Brodzick, S. R.; Yutler, S. E.

1995-01-01

Satellite data summary images and analysis plots from the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE), which were initially prepared in the field at the Honiara Operations Center, are now available on the Internet via World Wide Web browsers such as Mosaic. These satellite data summaries consist of products derived from the Japanese Geosynchronous Meteorological Satellite IR data: a time-size series of the distribution of contiguous cold cloudiness areas, weekly percent high cloudiness (PHC) maps, and a five-month time-longitudinal diagram illustrating the zonal motion of large areas of cold cloudiness. The weekly PHC maps are overlaid with weekly mean 850-hPa wind calculated from the European Centre for Medium-Range Weather Forecasts (ECMWF) global analysis field and can be viewed as an animation loop. These satellite summaries provide an overview of spatial and temporal variabilities of the cloud population and a large-scale context for studies concerning specific processes of various components of TOGA COARE.

Calibration of GOES-derived solar radiation data using a distributed network of surface measurements in Florida, USA

Science.gov (United States)

Sumner, David M.; Pathak, Chandra S.; Mecikalski, John R.; Paech, Simon J.; Wu, Qinglong; Sangoyomi, Taiye; Babcock, Roger W.; Walton, Raymond

2008-01-01

Solar radiation data are critically important for the estimation of evapotranspiration. Analysis of visible-channel data derived from Geostationary Operational Environmental Satellites (GOES) using radiative transfer modeling has been used to produce spatially- and temporally-distributed datasets of solar radiation. An extensive network of (pyranometer) surface measurements of solar radiation in the State of Florida has allowed refined calibration of a GOES-derived daily integrated radiation data product. This refinement of radiation data allowed for corrections of satellite sensor drift, satellite generational change, and consideration of the highly-variable cloudy conditions that are typical of Florida. To aid in calibration of a GOES-derived radiation product, solar radiation data for the period 1995–2004 from 58 field stations that are located throughout the State were compiled. The GOES radiation product was calibrated by way of a three-step process: 1) comparison with ground-based pyranometer measurements on clear reference days, 2) correcting for a bias related to cloud cover, and 3) deriving month-by-month bias correction factors. Pre-calibration results indicated good model performance, with a station-averaged model error of 2.2 MJ m–2 day–1 (13 percent). Calibration reduced errors to 1.7 MJ m–2 day–1 (10 percent) and also removed time- and cloudiness-related biases. The final dataset has been used to produce Statewide evapotranspiration estimates.

Migration to Earth Observation Satellite Product Dissemination System at JAXA

Science.gov (United States)

Ikehata, Y.; Matsunaga, M.

2017-12-01

JAXA released "G-Portal" as a portal web site for search and deliver data of Earth observation satellites in February 2013. G-Portal handles ten satellites data; GPM, TRMM, Aqua, ADEOS-II, ALOS (search only), ALOS-2 (search only), MOS-1, MOS-1b, ERS-1 and JERS-1 and archives 5.17 million products and 14 million catalogues in total. Users can search those products/catalogues in GUI web search and catalogue interface(CSW/Opensearch). In this fiscal year, we will replace this to "Next G-Portal" and has been doing integration, test and migrations. New G-Portal will treat data of satellites planned to be launched in the future in addition to those handled by G - Portal. At system architecture perspective, G-Portal adopted "cluster system" for its redundancy, so we must replace the servers into those with higher specifications when we improve its performance ("scale up approach"). This requests a lot of cost in every improvement. To avoid this, Next G-Portal adopts "scale out" system: load balancing interfaces, distributed file system, distributed data bases. (We reported in AGU fall meeting 2015(IN23D-1748).) At customer usability perspective, G-Portal provides complicated interface: "step by step" web design, randomly generated URLs, sftp (needs anomaly tcp port). Customers complained about the interfaces and the support team had been tired from answering them. To solve this problem, Next G-Portal adopts simple interfaces: "1 page" web design, RESTful URL, and Normal FTP. (We reported in AGU fall meeting 2016(IN23B-1778).) Furthermore, Next G-Portal must merge GCOM-W data dissemination system to be terminated in the next March as well as the current G-Portal. This might arrise some difficulties, since the current G-Portal and GCOM-W data dissemination systems are quite different from Next G-Portal. The presentation reports the knowledge obtained from the process of merging those systems.

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Baker Island, Pacific Remote Island Areas, Central Pacific.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...

Modeling gross primary production of agro-forestry ecosystems by assimilation of satellite-derived information in a process-based model.

Science.gov (United States)

Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther

2009-01-01

In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.

Modeling Gross Primary Production of Agro-Forestry Ecosystems by Assimilation of Satellite-Derived Information in a Process-Based Model

Directory of Open Access Journals (Sweden)

Guenther Seufert

2009-02-01

Full Text Available In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC with the aims of i improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.

Evaluating the hydrological consistency of satellite based water cycle components

KAUST Repository

Lopez Valencia, Oliver Miguel

2016-06-15

Advances in multi-satellite based observations of the earth system have provided the capacity to retrieve information across a wide-range of land surface hydrological components and provided an opportunity to characterize terrestrial processes from a completely new perspective. Given the spatial advantage that space-based observations offer, several regional-to-global scale products have been developed, offering insights into the multi-scale behaviour and variability of hydrological states and fluxes. However, one of the key challenges in the use of satellite-based products is characterizing the degree to which they provide realistic and representative estimates of the underlying retrieval: that is, how accurate are the hydrological components derived from satellite observations? The challenge is intrinsically linked to issues of scale, since the availability of high-quality in-situ data is limited, and even where it does exist, is generally not commensurate to the resolution of the satellite observation. Basin-scale studies have shown considerable variability in achieving water budget closure with any degree of accuracy using satellite estimates of the water cycle. In order to assess the suitability of this type of approach for evaluating hydrological observations, it makes sense to first test it over environments with restricted hydrological inputs, before applying it to more hydrological complex basins. Here we explore the concept of hydrological consistency, i.e. the physical considerations that the water budget impose on the hydrologic fluxes and states to be temporally and spatially linked, to evaluate the reproduction of a set of large-scale evaporation (E) products by using a combination of satellite rainfall (P) and Gravity Recovery and Climate Experiment (GRACE) observations of storage change, focusing on arid and semi-arid environments, where the hydrological flows can be more realistically described. Our results indicate no persistent hydrological

Scale up of proteoliposome derived Cochleate production.

Science.gov (United States)

Zayas, Caridad; Bracho, Gustavo; Lastre, Miriam; González, Domingo; Gil, Danay; Acevedo, Reinaldo; del Campo, Judith; Taboada, Carlos; Solís, Rosa L; Barberá, Ramón; Pérez, Oliver

2006-04-12

Cochleate are highly stable structures with promising immunological features. Cochleate structures are usually obtaining from commercial lipids. Proteoliposome derived Cochleate are derived from an outer membrane vesicles of Neisseria meningitidis B. Previously, we obtained Cochleates using dialysis procedures. In order to increase the production process, we used a crossflow system (CFS) that allows easy scale up to obtain large batches in an aseptic environment. The raw material and solutions used in the production process are already approved for human application. This work demonstrates that CFS is very efficient process to obtain Cochleate structures with a yield of more than 80% and the immunogenicity comparable to that obtained by dialysis membrane.

A methodology for calibration of hyperspectral and multispectral satellite data in coastal areas

Science.gov (United States)

Pennucci, Giuliana; Fargion, Giulietta; Alvarez, Alberto; Trees, Charles; Arnone, Robert

2012-06-01

The objective of this work is to determine the location(s) in any given oceanic area during different temporal periods where in situ sampling for Calibration/Validation (Cal/Val) provides the best capability to retrieve accurate radiometric and derived product data (lowest uncertainties). We present a method to merge satellite imagery with in situ measurements, to determine the best in situ sampling strategy suitable for satellite Cal/Val and to evaluate the present in situ locations through uncertainty indices. This analysis is required to determine if the present in situ sites are adequate for assessing uncertainty and where additional sites and ship programs should be located to improve Calibration/Validation (Cal/Val) procedures. Our methodology uses satellite acquisitions to build a covariance matrix encoding the spatial-temporal variability of the area of interest. The covariance matrix is used in a Bayesian framework to merge satellite and in situ data providing a product with lower uncertainty. The best in situ location for Cal/Val is then identified by using a design principle (A-optimum design) that looks for minimizing the estimated variance of the merged products. Satellite products investigated in this study include Ocean Color water leaving radiance, chlorophyll, and inherent and apparent optical properties (retrieved from MODIS and VIIRS). In situ measurements are obtained from systems operated on fixed deployment platforms (e.g., sites of the Ocean Color component of the AErosol RObotic NETwork- AERONET-OC), moorings (e.g, Marine Optical Buoy-MOBY), ships or autonomous vehicles (such as Autonomous Underwater Vehicles and/or Gliders).

Assessment of the Latest GPM-Era High-Resolution Satellite Precipitation Products by Comparison with Observation Gauge Data over the Chinese Mainland

Directory of Open Access Journals (Sweden)

Shaowei Ning

2016-10-01

Full Text Available The Global Precipitation Mission (GPM Core Observatory that was launched on 27 February 2014 ushered in a new era for estimating precipitation from satellites. Based on their high spatial–temporal resolution and near global coverage, satellite-based precipitation products have been applied in many research fields. The goal of this study was to quantitatively compare two of the latest GPM-era satellite precipitation products (GPM IMERG and GSMap-Gauge Ver. 6 with a network of 840 precipitation gauges over the Chinese mainland. Direct comparisons of satellite-based precipitation products with rain gauge observations over a 20 month period from April 2014 to November 2015 at 0.1° and daily/monthly resolutions showed the following results: Both of the products were capable of capturing the overall spatial pattern of the 20 month mean daily precipitation, which was characterized by a decreasing trend from the southeast to the northwest. GPM IMERG overestimated precipitation by approximately 0.09 mm/day while GSMap-Gauge Ver. 6 underestimated precipitation by −0.04 mm/day. The two satellite-based precipitation products performed better over wet southern regions than over dry northern regions. They also showed better performance in summer than in winter. In terms of mean error, root mean square error, correlation coefficient, and probability of detection, GSMap-Gauge was better able to estimate precipitation and had more stable quality results than GPM IMERG on both daily and monthly scales. GPM IMERG was more sensitive to conditions of no rain or light rainfall and demonstrated good capability of capturing the behavior of extreme precipitation events. Overall, the results revealed some limitations of these two latest satellite-based precipitation products when used over the Chinese mainland, helping to characterize some of the error features in these datasets for potential users.

Hierarchical Satellite-based Approach to Global Monitoring of Crop Condition and Food Production

Science.gov (United States)

Zheng, Y.; Wu, B.; Gommes, R.; Zhang, M.; Zhang, N.; Zeng, H.; Zou, W.; Yan, N.

2014-12-01

The assessment of global food security goes beyond the mere estimate of crop production: It needs to take into account the spatial and temporal patterns of food availability, as well as physical and economic access. Accurate and timely information is essential to both food producers and consumers. Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, such as FY-2/3A, HJ-1 CCD, CropWatch has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The new monitoring approach adopts a hierarchical system covering four spatial levels of detail: global (sixty-five Monitoring and Reporting Units, MRU), seven major production zones (MPZ), thirty-one key countries (including China) and "sub- countries." The thirty-one countries encompass more that 80% of both global exports and production of four major crops (maize, rice, soybean and wheat). The methodology resorts to climatic and remote sensing indicators at different scales, using the integrated information to assess global, regional, and national (as well as sub-national) crop environmental condition, crop condition, drought, production, and agricultural trends. The climatic indicators for rainfall, temperature, photosynthetically active radiation (PAR) as well as potential biomass are first analysed at global scale to describe overall crop growing conditions. At MPZ scale, the key indicators pay more attention to crops and include Vegetation health index (VHI), Vegetation condition index (VCI), Cropped arable land fraction (CALF) as well as Cropping intensity (CI). Together, they characterise agricultural patterns, farming intensity and stress. CropWatch carries out detailed crop condition analyses for thirty one individual countries at the national scale with a comprehensive array of variables and indicators. The Normalized difference vegetation index (NDVI), cropped areas and crop condition are

Open Source GIS Connectors to NASA GES DISC Satellite Data

Science.gov (United States)

Kempler, Steve; Pham, Long; Yang, Wenli

2014-01-01

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) houses a suite of high spatiotemporal resolution GIS data including satellite-derived and modeled precipitation, air quality, and land surface parameter data. The data are valuable to various GIS research and applications at regional, continental, and global scales. On the other hand, many GIS users, especially those from the ArcGIS community, have difficulties in obtaining, importing, and using our data due to factors such as the variety of data products, the complexity of satellite remote sensing data, and the data encoding formats. We introduce a simple open source ArcGIS data connector that significantly simplifies the access and use of GES DISC data in ArcGIS.

Mosaic of 2m bathymetry derived from multispectral IKONOS World View-2 satellite imagery of Swains Island, Territory of American Samoa, South Pacific, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

Contribution of Multi-GNSS Constellation to SLR-Derived Terrestrial Reference Frame

Science.gov (United States)

Sośnica, K.; Bury, G.; Zajdel, R.

2018-03-01

All satellites of new Global Navigation Satellite Systems (GNSS) are equipped with laser retroreflectors dedicated to Satellite Laser Ranging (SLR). This paper demonstrates the contribution of SLR tracking of multi-GNSS constellations to the improved SLR-derived reference frame and scientific products. We show a solution strategy with estimating satellite orbits, SLR station coordinates, geocenter coordinates, and Earth rotation parameters using SLR observations to 2 Laser Geodynamics Satellites (LAGEOS) and 55 GNSS satellites: 1 GPS, 31 Globalnaya Navigatsionnaya Sputnikovaya Sistema, 18 Galileo, 3 BeiDou Inclined Geosynchronous Orbit, 1 BeiDou Medium Earth Orbit, and 1 Quasi-Zenith Satellite System satellite for the period 2014.0-2017.4. Due to a substantial number of GNSS observations, the number of weekly solutions for some SLR stations, for example, Arkhyz, Komsomolsk, Altay, and Brasilia, is larger up to 41% in the combined LAGEOS + GNSS solution when compared to the LAGEOS-only solution. The SLR observations to GNSS can transfer the orientation of the reference frame from GNSS to SLR solutions. As a result, the SLR-derived pole coordinates and length-of-day estimates become more consistent with GNSS microwave-based results. The root-mean-square errors of length-of-day are reduced from 122.5 μs/d to 43.0 μs/d, whereas mean offsets are reduced from -81.6 μs/d to 0.5 μs/d in LAGEOS only and in the combined LAGEOS + GNSS solutions, respectively.

SatelliteDL: a Toolkit for Analysis of Heterogeneous Satellite Datasets

Science.gov (United States)

Galloy, M. D.; Fillmore, D.

2014-12-01

SatelliteDL is an IDL toolkit for the analysis of satellite Earth observations from a diverse set of platforms and sensors. The core function of the toolkit is the spatial and temporal alignment of satellite swath and geostationary data. The design features an abstraction layer that allows for easy inclusion of new datasets in a modular way. Our overarching objective is to create utilities that automate the mundane aspects of satellite data analysis, are extensible and maintainable, and do not place limitations on the analysis itself. IDL has a powerful suite of statistical and visualization tools that can be used in conjunction with SatelliteDL. Toward this end we have constructed SatelliteDL to include (1) HTML and LaTeX API document generation,(2) a unit test framework,(3) automatic message and error logs,(4) HTML and LaTeX plot and table generation, and(5) several real world examples with bundled datasets available for download. For ease of use, datasets, variables and optional workflows may be specified in a flexible format configuration file. Configuration statements may specify, for example, a region and date range, and the creation of images, plots and statistical summary tables for a long list of variables. SatelliteDL enforces data provenance; all data should be traceable and reproducible. The output NetCDF file metadata holds a complete history of the original datasets and their transformations, and a method exists to reconstruct a configuration file from this information. Release 0.1.0 distributes with ingest methods for GOES, MODIS, VIIRS and CERES radiance data (L1) as well as select 2D atmosphere products (L2) such as aerosol and cloud (MODIS and VIIRS) and radiant flux (CERES). Future releases will provide ingest methods for ocean and land surface products, gridded and time averaged datasets (L3 Daily, Monthly and Yearly), and support for 3D products such as temperature and water vapor profiles. Emphasis will be on NPP Sensor, Environmental and

A WebGIS system on the base of satellite data processing system for marine application

Science.gov (United States)

Gong, Fang; Wang, Difeng; Huang, Haiqing; Chen, Jianyu

2007-10-01

From 2002 to 2004, a satellite data processing system for marine application had been built up in State Key Laboratory of Satellite Ocean Environment Dynamics (Second Institute of Oceanography, State Oceanic Administration). The system received satellite data from TERRA, AQUA, NOAA-12/15/16/17/18, FY-1D and automatically generated Level3 products and Level4 products(products of single orbit and merged multi-orbits products) deriving from Level0 data, which is controlled by an operational control sub-system. Currently, the products created by this system play an important role in the marine environment monitoring, disaster monitoring and researches. Now a distribution platform has been developed on this foundation, namely WebGIS system for querying and browsing of oceanic remote sensing data. This system is based upon large database system-Oracle. We made use of the space database engine of ArcSDE and other middleware to perform database operation in addition. J2EE frame was adopted as development model, and Oracle 9.2 DBMS as database background and server. Simply using standard browsers(such as IE6.0), users can visit and browse the public service information that provided by system, including browsing for oceanic remote sensing data, and enlarge, contract, move, renew, traveling, further data inquiry, attribution search and data download etc. The system is still under test now. Founding of such a system will become an important distribution platform of Chinese satellite oceanic environment products of special topic and category (including Sea surface temperature, Concentration of chlorophyll, and so on), for the exaltation of satellite products' utilization and promoting the data share and the research of the oceanic remote sensing platform.

Retrieval of daily gross primary production over Europe and Africa from an ensemble of SEVIRI/MSG products

Science.gov (United States)

Martínez, B.; Sanchez-Ruiz, S.; Gilabert, M. A.; Moreno, A.; Campos-Taberner, M.; García-Haro, F. J.; Trigo, I. F.; Aurela, M.; Brümmer, C.; Carrara, A.; De Ligne, A.; Gianelle, D.; Grünwald, T.; Limousin, J. M.; Lohila, A.; Mammarella, I.; Sottocornola, M.; Steinbrecher, R.; Tagesson, T.

2018-03-01

The main goal of this paper is to derive a method for a daily gross primary production (GPP) product over Europe and Africa taking the full advantage of the SEVIRI/MSG satellite products from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) sensors delivered from the Satellite Application Facility for Land Surface Analysis (LSA SAF) system. Special attention is paid to model the daily GPP response from an optimized Montheith's light use efficiency model under dry conditions by controlling water shortage limitations from the actual evapotranspiration and the potential evapotranspiration (PET). The PET was parameterized using the mean daily air temperature at 2 m (Ta) from ERA-Interim data. The GPP product (MSG GPP) was produced for 2012 and assessed by direct site-level comparison with GPP from eddy covariance data (EC GPP). MSG GPP presents relative bias errors lower than 40% for the most forest vegetation types with a high agreement (r > 0.7) when compared with EC GPP. For drylands, MSG GPP reproduces the seasonal variations related to water limitation in a good agreement with site level GPP estimates (RMSE = 2.11 g m-2 day-1; MBE = -0.63 g m-2 day-1), especially for the dry season. A consistency analysis against other GPP satellite products (MOD17A2 and FLUXCOM) reveals a high consistency among products (RMSD Africa. The major GPP disagreement arises over moist biomes in central Africa (RMSD > 3.0 g m-2 day-1) and over dry biomes with MSG GPP estimates lower than FLUXCOM (MBD up to -3.0 g m-2 day-1). This newly derived product has the potential for analysing spatial patterns and temporal dynamics of GPP at the MSG spatial resolutions on a daily basis allowing to better capture the GPP dynamics and magnitude.

NESDIS Blended Total Precipitable Water (TPW) Products

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The blended Total Precipitable Water (TPW) product is derived from multiple sensors/satellites. The Percentage of TPW normal (PCT), or TPW anomaly, shows the...

The ESA climate change initiative: Satellite data records for essential climate variables

DEFF Research Database (Denmark)

Hollmann, R.; Merchant, C.J.; Saunders, R.

2013-01-01

The European Space Agency (ESA) has launched the Climate Change Initiative (CCI) to provide satellite-based climate data records (CDRs) that meet the challenging requirements of the climate community. The aim is to realize the full potential of the long-term Earth observation (EO) archives...... that both ESA and third parties have established. This includes aspects of producing a CDR, which involve data acquisition, calibration, algorithm development, validation, maintenance, and provision of the data to the climate research community. The CCI is consistent with several international efforts...... targeting the generation of satellite derived climate data records. One focus of the CCI is to provide products for climate modelers who increasingly use satellite data to initialize, constrain, and validate models on a wide range of space and time scales....

Operational surface UV radiation product from GOME-2 and AVHRR/3 data

OpenAIRE

J. Kujanpää; N. Kalakoski

2015-01-01

The surface ultraviolet (UV) radiation product, version 1.20, generated operationally in the framework of the Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M SAF) of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) is described. The product is based on the total ozone column derived from the measurements of the second Global Ozone Monitoring Experiment (GOME-2) instrument aboard EUMETSA...

Impact analysis of satellite rainfall products on flow simulations in the Magdalena River Basin, Colombia

Directory of Open Access Journals (Sweden)

Amr Elgamal

2017-02-01

Full Text Available The Magdalena River is the most important river in Colombia in terms of economic activities and is home to about 77% of the country’s population. The river faces water resources allocation challenges, which require reliable hydrological assessments. However, hydrological analysis and model simulations are hampered by insufficient and uncertain knowledge of the actual rainfall fields. In this research the reliability of groundbased measurements, different satellite products of rainfall and their combinations are tested for their impact on the discharge simulations of the Magdalena River. Two different satellite rainfall products from the Tropical Rainfall Measuring Mission (TRMM, have been compared and merged with the ground-based measurements and their impact on the Magdalena river flows quantified using the Representative Elementary Watershed (REW distributed hydrological model.

Precipitation Analysis at Fine Time Scales Using Multiple Satellites: Real-time and Research Products and Applications

Science.gov (United States)

Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold

2004-01-01

Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) in 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25" latitude-longitude resolution over the latitude range from 5O"N-5O0S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, including: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

Directory of Open Access Journals (Sweden)

G. T. Ayehu

2018-04-01

Full Text Available Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor ground observations or through integrating with rain gauge measurements. In this study, the potential of a newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS rainfall product has been evaluated in comparison to rain gauge data over the Upper Blue Nile basin in Ethiopia for the period of 2000 to 2015. In addition, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT 3 and the African Rainfall Climatology (ARC 2 products have been used as a benchmark and compared with CHIRPS. From the overall analysis at dekadal (10 days and monthly temporal scale, CHIRPS exhibited better performance in comparison to TAMSAT 3 and ARC 2 products. An evaluation based on categorical/volumetric and continuous statistics indicated that CHIRPS has the greatest skills in detecting rainfall events (POD  =  0.99, 1.00 and measure of volumetric rainfall (VHI  =  1.00, 1.00, the highest correlation coefficients (r =  0.81, 0.88, better bias values (0.96, 0.96, and the lowest RMSE (28.45 mm dekad−1, 59.03 mm month−1 than TAMSAT 3 and ARC 2 products at dekadal and monthly analysis, respectively. CHIRPS overestimates the frequency of rainfall occurrence (up to 31 % at dekadal scale, although the volume of rainfall recorded during those events was very small. Indeed, TAMSAT 3 has shown a comparable performance with that of the CHIRPS product, mainly with regard to bias. The ARC 2 product was found to have the weakest performance

Assessing concentration uncertainty estimates from passive microwave sea ice products

Science.gov (United States)

Meier, W.; Brucker, L.; Miller, J. A.

2017-12-01

Sea ice concentration is an essential climate variable and passive microwave derived estimates of concentration are one of the longest satellite-derived climate records. However, until recently uncertainty estimates were not provided. Numerous validation studies provided insight into general error characteristics, but the studies have found that concentration error varied greatly depending on sea ice conditions. Thus, an uncertainty estimate from each observation is desired, particularly for initialization, assimilation, and validation of models. Here we investigate three sea ice products that include an uncertainty for each concentration estimate: the NASA Team 2 algorithm product, the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI-SAF) product, and the NOAA/NSIDC Climate Data Record (CDR) product. Each product estimates uncertainty with a completely different approach. The NASA Team 2 product derives uncertainty internally from the algorithm method itself. The OSI-SAF uses atmospheric reanalysis fields and a radiative transfer model. The CDR uses spatial variability from two algorithms. Each approach has merits and limitations. Here we evaluate the uncertainty estimates by comparing the passive microwave concentration products with fields derived from the NOAA VIIRS sensor. The results show that the relationship between the product uncertainty estimates and the concentration error (relative to VIIRS) is complex. This may be due to the sea ice conditions, the uncertainty methods, as well as the spatial and temporal variability of the passive microwave and VIIRS products.

Harmonizing estimates of forest land area from national-level forest inventory and satellite imagery

Science.gov (United States)

Bonnie Ruefenacht; Mark D. Nelson; Mark Finco

2009-01-01

Estimates of forest land area are derived both from national-level forest inventories and satellite image-based map products. These estimates can differ substantially within subregional extents (e.g., states or provinces) primarily due to differences in definitions of forest land between inventory- and image-based approaches. We present a geospatial modeling approach...

Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

CALIBRATION/VALIDATION OF LANDSAT-DERIVED OCEAN COLOUR PRODUCTS IN BOSTON HARBOUR

Directory of Open Access Journals (Sweden)

N. Pahlevan

2016-06-01

Full Text Available The Landsat data archive provides a unique opportunity to investigate the long-term evolution of coastal ecosystems at fine spatial scales that cannot be resolved by ocean colour (OC satellite sensors. Recognizing Landsat’s limitations in applications over coastal waters, we have launched a series of field campaigns in Boston Harbor and Massachusetts Bay (MA, USA to validate OC products derived from Landsat-8. We will provide a preliminary demonstration on the calibration/validation of the existing OC algorithms (atmospheric correction and in-water optical properties to enhance monitoring efforts in Boston Harbor. To do so, Landsat optical images were first compared against ocean colour products over high-latitude regions. The in situ cruise data, including optical data (remote sensing reflectance and water samples were analyzed to obtain insights into the optical and biogeochemical properties of near-surface waters. Along with the cruise data, three buoys were deployed in three locations across the Harbor to complement our database of concentrations of chlorophyll a, total suspended solids (TSS, and absorption of colour dissolved organic matter (CDOM. The data collected during the first year of the project are used to develop and/or tune OC algorithms. The data will be combined with historic field data to map in-water constituents back to the early 1990’s. This paper presents preliminary analysis of some of the data collected under Landsat-8 overpasses.

Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

Determining Optimal New Generation Satellite Derived Metrics for Accurate C3 and C4 Grass Species Aboveground Biomass Estimation in South Africa

Directory of Open Access Journals (Sweden)

Cletah Shoko

2018-04-01

Full Text Available While satellite data has proved to be a powerful tool in estimating C3 and C4 grass species Aboveground Biomass (AGB, finding an appropriate sensor that can accurately characterize the inherent variations remains a challenge. This limitation has hampered the remote sensing community from continuously and precisely monitoring their productivity. This study assessed the potential of a Sentinel 2 MultiSpectral Instrument, Landsat 8 Operational Land Imager, and WorldView-2 sensors, with improved earth imaging characteristics, in estimating C3 and C4 grasses AGB in the Cathedral Peak, South Africa. Overall, all sensors have shown considerable potential in estimating species AGB; with the use of different combinations of the derived spectral bands and vegetation indices producing better accuracies. However, WorldView-2 derived variables yielded better predictive accuracies (R2 ranging between 0.71 and 0.83; RMSEs between 6.92% and 9.84%, followed by Sentinel 2, with R2 between 0.60 and 0.79; and an RMSE 7.66% and 14.66%. Comparatively, Landsat 8 yielded weaker estimates, with R2 ranging between 0.52 and 0.71 and high RMSEs ranging between 9.07% and 19.88%. In addition, spectral bands located within the red edge (e.g., centered at 0.705 and 0.745 µm for Sentinel 2, SWIR, and NIR, as well as the derived indices, were found to be very important in predicting C3 and C4 AGB from the three sensors. The competence of these bands, especially of the free-available Landsat 8 and Sentinel 2 dataset, was also confirmed from the fusion of the datasets. Most importantly, the three sensors managed to capture and show the spatial variations in AGB for the target C3 and C4 grassland area. This work therefore provides a new horizon and a fundamental step towards C3 and C4 grass productivity monitoring for carbon accounting, forage mapping, and modelling the influence of environmental changes on their productivity.

Atmospheric correction using near-infrared bands for satellite ocean color data processing in the turbid western Pacific region.

Science.gov (United States)

Wang, Menghua; Shi, Wei; Jiang, Lide

2012-01-16

A regional near-infrared (NIR) ocean normalized water-leaving radiance (nL(w)(λ)) model is proposed for atmospheric correction for ocean color data processing in the western Pacific region, including the Bohai Sea, Yellow Sea, and East China Sea. Our motivation for this work is to derive ocean color products in the highly turbid western Pacific region using the Geostationary Ocean Color Imager (GOCI) onboard South Korean Communication, Ocean, and Meteorological Satellite (COMS). GOCI has eight spectral bands from 412 to 865 nm but does not have shortwave infrared (SWIR) bands that are needed for satellite ocean color remote sensing in the turbid ocean region. Based on a regional empirical relationship between the NIR nL(w)(λ) and diffuse attenuation coefficient at 490 nm (K(d)(490)), which is derived from the long-term measurements with the Moderate-resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, an iterative scheme with the NIR-based atmospheric correction algorithm has been developed. Results from MODIS-Aqua measurements show that ocean color products in the region derived from the new proposed NIR-corrected atmospheric correction algorithm match well with those from the SWIR atmospheric correction algorithm. Thus, the proposed new atmospheric correction method provides an alternative for ocean color data processing for GOCI (and other ocean color satellite sensors without SWIR bands) in the turbid ocean regions of the Bohai Sea, Yellow Sea, and East China Sea, although the SWIR-based atmospheric correction approach is still much preferred. The proposed atmospheric correction methodology can also be applied to other turbid coastal regions.

Satellite-Derived Photic Depth on the Great Barrier Reef: Spatio-Temporal Patterns of Water Clarity

Directory of Open Access Journals (Sweden)

Scarla Weeks

2012-11-01

Full Text Available Detecting changes to the transparency of the water column is critical for understanding the responses of marine organisms, such as corals, to light availability. Long-term patterns in water transparency determine geographical and depth distributions, while acute reductions cause short-term stress, potentially mortality and may increase the organisms’ vulnerability to other environmental stressors. Here, we investigated the optimal, operational algorithm for light attenuation through the water column across the scale of the Great Barrier Reef (GBR, Australia. We implemented and tested a quasi-analytical algorithm to determine the photic depth in GBR waters and matched regional Secchi depth (ZSD data to MODIS-Aqua (2002–2010 and SeaWiFS (1997–2010 satellite data. The results of the in situ ZSD/satellite data matchup showed a simple bias offset between the in situ and satellite retrievals. Using a Type II linear regression of log-transformed satellite and in situ data, we estimated ZSD and implemented the validated ZSD algorithm to generate a decadal satellite time series (2002–2012 for the GBR. Water clarity varied significantly in space and time. Seasonal effects were distinct, with lower values during the austral summer, most likely due to river runoff and increased vertical mixing, and a decline in water clarity between 2008–2012, reflecting a prevailing La Niña weather pattern. The decline in water clarity was most pronounced in the inshore area, where a significant decrease in mean inner shelf ZSD of 2.1 m (from 8.3 m to 6.2 m occurred over the decade. Empirical Orthogonal Function Analysis determined the dominance of Mode 1 (51.3%, with the greatest variation in water clarity along the mid-shelf, reflecting the strong influence of oceanic intrusions on the spatio-temporal patterns of water clarity. The newly developed photic depth product has many potential applications for the GBR from water quality monitoring to analyses of

Estimating crop net primary production using inventory data and MODIS-derived parameters

Energy Technology Data Exchange (ETDEWEB)

Bandaru, Varaprasad; West, Tristram O.; Ricciuto, Daniel M.; Izaurralde, Roberto C.

2013-06-03

National estimates of spatially-resolved cropland net primary production (NPP) are needed for diagnostic and prognostic modeling of carbon sources, sinks, and net carbon flux. Cropland NPP estimates that correspond with existing cropland cover maps are needed to drive biogeochemical models at the local scale and over national and continental extents. Existing satellite-based NPP products tend to underestimate NPP on croplands. A new Agricultural Inventory-based Light Use Efficiency (AgI-LUE) framework was developed to estimate individual crop biophysical parameters for use in estimating crop-specific NPP. The method is documented here and evaluated for corn and soybean crops in Iowa and Illinois in years 2006 and 2007. The method includes a crop-specific enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), shortwave radiation data estimated using Mountain Climate Simulator (MTCLIM) algorithm and crop-specific LUE per county. The combined aforementioned variables were used to generate spatially-resolved, crop-specific NPP that correspond to the Cropland Data Layer (CDL) land cover product. The modeling framework represented well the gradient of NPP across Iowa and Illinois, and also well represented the difference in NPP between years 2006 and 2007. Average corn and soybean NPP from AgI-LUE was 980 g C m-2 yr-1 and 420 g C m-2 yr-1, respectively. This was 2.4 and 1.1 times higher, respectively, for corn and soybean compared to the MOD17A3 NPP product. Estimated gross primary productivity (GPP) derived from AgI-LUE were in close agreement with eddy flux tower estimates. The combination of new inputs and improved datasets enabled the development of spatially explicit and reliable NPP estimates for individual crops over large regional extents.

Evaluation of multiple satellite evaporation products in two dryland regions using GRACE

KAUST Repository

Lopez, Oliver

2015-12-01

Remote sensing has become a valuable tool for monitoring the water cycle variables in areas that lack the availability of ground-based measurements. Integrating multiple remote sensing-based estimates of evaporation, precipitation, and the terrestrial water storage changes with local measurements of streamflow into a consistent estimate of the regional water budget is a challenge, due to the scale mismatch among the retrieved variables. Evapotranspiration, including soil evaporation, interception losses and canopy transpiration, has received special focus in a number of recent studies that aim to provide global or regional estimates of evaporation at regular time intervals using a variety of remote sensing input. In arid and semi-arid regions, modeling of evaporation is particularly challenging due to the relatively high role of the soil evaporation component in these regions and the variable nature of rainfall events that drive the evaporation process. In this study, we explore the hydrological consistency of remote sensing products in terms of water budget closure and the correlation among spatial patterns of precipitation (P), evaporation (E) and terrestrial water storage, using P-E as a surrogate of water storage changes, with special attention to the evaporation component. The analysis is undertaken within two dryland regions that have presented recent significant changes in climatology (Murray-Darling Basin in Australia) and water storage (the Saq aquifer in northern Saudi Arabia). Water storage changes were derived from the Gravity Recovery and Climate Experiment (GRACE) spherical harmonic (SH) coefficients. Six remote sensing-based evaporation estimates were subtracted from the Global Precipitation Climatology Project (GPCP)-based precipitation estimates and were compared with GRACE-derived water storage changes. Our results suggest that it is not possible to close the water balance by using satellite data alone, even when adopting a spherical harmonic

A prototype method for diagnosing high ice water content probability using satellite imager data

Science.gov (United States)

Yost, Christopher R.; Bedka, Kristopher M.; Minnis, Patrick; Nguyen, Louis; Strapp, J. Walter; Palikonda, Rabindra; Khlopenkov, Konstantin; Spangenberg, Douglas; Smith, William L., Jr.; Protat, Alain; Delanoe, Julien

2018-03-01

Recent studies have found that ingestion of high mass concentrations of ice particles in regions of deep convective storms, with radar reflectivity considered safe for aircraft penetration, can adversely impact aircraft engine performance. Previous aviation industry studies have used the term high ice water content (HIWC) to define such conditions. Three airborne field campaigns were conducted in 2014 and 2015 to better understand how HIWC is distributed in deep convection, both as a function of altitude and proximity to convective updraft regions, and to facilitate development of new methods for detecting HIWC conditions, in addition to many other research and regulatory goals. This paper describes a prototype method for detecting HIWC conditions using geostationary (GEO) satellite imager data coupled with in situ total water content (TWC) observations collected during the flight campaigns. Three satellite-derived parameters were determined to be most useful for determining HIWC probability: (1) the horizontal proximity of the aircraft to the nearest overshooting convective updraft or textured anvil cloud, (2) tropopause-relative infrared brightness temperature, and (3) daytime-only cloud optical depth. Statistical fits between collocated TWC and GEO satellite parameters were used to determine the membership functions for the fuzzy logic derivation of HIWC probability. The products were demonstrated using data from several campaign flights and validated using a subset of the satellite-aircraft collocation database. The daytime HIWC probability was found to agree quite well with TWC time trends and identified extreme TWC events with high probability. Discrimination of HIWC was more challenging at night with IR-only information. The products show the greatest capability for discriminating TWC ≥ 0.5 g m-3. Product validation remains challenging due to vertical TWC uncertainties and the typically coarse spatio-temporal resolution of the GEO data.

How Satellites Have Contributed to Building a Weather Ready Nation

Science.gov (United States)

Lapenta, W.

2017-12-01

NOAA's primary mission since its inception has been to reduce the loss of life and property, as well as disruptions from, high impact weather and water-related events. In recent years, significant societal losses resulting even from well forecast extreme events have shifted attention from the forecast alone toward ensuring societal response is equal to the risks that exist for communities, businesses and the public. The responses relate to decisions ranging from coastal communities planning years in advance to mitigate impacts from rising sea level, to immediate lifesaving decisions such as a family seeking adequate shelter during a tornado warning. NOAA is committed to building a "Weather-Ready Nation" where communities are prepared for and respond appropriately to these events. The Weather-Ready Nation (WRN) strategic priority is building community resilience in the face of increasing vulnerability to extreme weather, water, climate and environmental threats. To build a Weather-Ready Nation, NOAA is enhancing Impact-Based Decision Support Services (IDSS), transitioning science and technology advances into forecast operations, applying social science research to improve the communication and usefulness of information, and expanding its dissemination efforts to achieve far-reaching readiness, responsiveness and resilience. These four components of Weather-Ready Nation are helping ensure NOAA data, products and services are fully utilized to minimize societal impacts from extreme events. Satellite data and satellite products have been important elements of the national Weather Service (NWS) operations for more than 40 years. When one examines the uses of satellite data specific to the internal forecast and warning operations of NWS, two main applications are evident. The first is the use of satellite data in numerical weather prediction models; the second is the use of satellite imagery and derived products for mesoscale and short-range weather warning and

Initializing numerical weather prediction models with satellite-derived surface soil moisture: Data assimilation experiments with ECMWF's Integrated Forecast System and the TMI soil moisture data set

Science.gov (United States)

Drusch, M.

2007-02-01

Satellite-derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analyzed from the modeled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. For this study, three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been performed for the 2-month period of June and July 2002: a control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating TMI (TRMM Microwave Imager) derived soil moisture over the southern United States. In this experimental run the satellite-derived soil moisture product is introduced through a nudging scheme using 6-hourly increments. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analyzed in the nudging experiment is the most accurate estimate when compared against in situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage.

Poverty, health and satellite-derived vegetation indices: their inter-spatial relationship in West Africa

Science.gov (United States)

Sedda, Luigi; Tatem, Andrew J.; Morley, David W.; Atkinson, Peter M.; Wardrop, Nicola A.; Pezzulo, Carla; Sorichetta, Alessandro; Kuleszo, Joanna; Rogers, David J.

2015-01-01

Background Previous analyses have shown the individual correlations between poverty, health and satellite-derived vegetation indices such as the normalized difference vegetation index (NDVI). However, generally these analyses did not explore the statistical interconnections between poverty, health outcomes and NDVI. Methods In this research aspatial methods (principal component analysis) and spatial models (variography, factorial kriging and cokriging) were applied to investigate the correlations and spatial relationships between intensity of poverty, health (expressed as child mortality and undernutrition), and NDVI for a large area of West Africa. Results This research showed that the intensity of poverty (and hence child mortality and nutrition) varies inversely with NDVI. From the spatial point-of-view, similarities in the spatial variation of intensity of poverty and NDVI were found. Conclusions These results highlight the utility of satellite-based metrics for poverty models including health and ecological components and, in general for large scale analysis, estimation and optimisation of multidimensional poverty metrics. However, it also stresses the need for further studies on the causes of the association between NDVI, health and poverty. Once these relationships are confirmed and better understood, the presence of this ecological component in poverty metrics has the potential to facilitate the analysis of the impacts of climate change on the rural populations afflicted by poverty and child mortality. PMID:25733559

JPSS Products, Applications and Training

Science.gov (United States)

Torres, J. R.; Connell, B. H.; Miller, S. D.

2017-12-01

The Joint Polar Satellite System (JPSS) is a new generation polar-orbiting operational environmental satellite system that will monitor the weather and environment around the globe. JPSS will provide technological and scientific improvements in environmental monitoring via high resolution satellite imagery and derived products that stand to improve weather forecasting capabilities for National Weather Service (NWS) forecasters and complement operational Geostationary satellites. JPSS will consist of four satellites, JPSS-1 through JPSS-4, where JPSS-1 is due to launch in Fall 2017. A predecessor, prototype and operational risk-reduction for JPSS is the Suomi-National Polar-orbiting Partnership (S-NPP) satellite, launched on 28 October 2011. The following instruments on-board S-NPP will also be hosted on JPSS-1: Visible Infrared Imaging Radiometer Suite (VIIRS), Cross-track Infrared Sounder (CrIS), Advanced Technology Microwave Sounder (ATMS), Ozone Mapping and Profiler Suite (OMPS) and the Clouds and Earth's Radiant Energy System (CERES). JPSS-1 instruments will provide satellite imagery, products and applications to users. The applications include detecting water and ice clouds, snow, sea surface temperatures, fog, fire, severe weather, vegetation health, aerosols, and sensing reflected lunar and emitted visible-wavelength light during the nighttime via the Day/Night Band (DNB) sensor included on VIIRS. Currently, there are only a few polar products that are operational for forecasters, however, more products will become available in the near future via Advanced Weather Interactive Processing System-II (AWIPS-II)-a forecasting analysis software package that forecasters can use to analyze meteorological data. To complement the polar products an wealth of training materials are currently in development. Denoted as the Satellite Foundational Course for JPSS (SatFC-J), this training will benefit NWS forecasters to utilize satellite data in their forecasts and daily

Intercomparison of phenological transition dates derived from the PhenoCam Dataset V1.0 and MODIS satellite remote sensing.

Science.gov (United States)

Richardson, Andrew D; Hufkens, Koen; Milliman, Tom; Frolking, Steve

2018-04-09

Phenology is a valuable diagnostic of ecosystem health, and has applications to environmental monitoring and management. Here, we conduct an intercomparison analysis using phenological transition dates derived from near-surface PhenoCam imagery and MODIS satellite remote sensing. We used approximately 600 site-years of data, from 128 camera sites covering a wide range of vegetation types and climate zones. During both "greenness rising" and "greenness falling" transition phases, we found generally good agreement between PhenoCam and MODIS transition dates for agricultural, deciduous forest, and grassland sites, provided that the vegetation in the camera field of view was representative of the broader landscape. The correlation between PhenoCam and MODIS transition dates was poor for evergreen forest sites. We discuss potential reasons (including sub-pixel spatial heterogeneity, flexibility of the transition date extraction method, vegetation index sensitivity in evergreen systems, and PhenoCam geolocation uncertainty) for varying agreement between time series of vegetation indices derived from PhenoCam and MODIS imagery. This analysis increases our confidence in the ability of satellite remote sensing to accurately characterize seasonal dynamics in a range of ecosystems, and provides a basis for interpreting those dynamics in the context of tangible phenological changes occurring on the ground.

A Novel Strategy Using Factor Graphs and the Sum-Product Algorithm for Satellite Broadcast Scheduling Problems

Science.gov (United States)

Chen, Jung-Chieh

This paper presents a low complexity algorithmic framework for finding a broadcasting schedule in a low-altitude satellite system, i. e., the satellite broadcast scheduling (SBS) problem, based on the recent modeling and computational methodology of factor graphs. Inspired by the huge success of the low density parity check (LDPC) codes in the field of error control coding, in this paper, we transform the SBS problem into an LDPC-like problem through a factor graph instead of using the conventional neural network approaches to solve the SBS problem. Based on a factor graph framework, the soft-information, describing the probability that each satellite will broadcast information to a terminal at a specific time slot, is exchanged among the local processing in the proposed framework via the sum-product algorithm to iteratively optimize the satellite broadcasting schedule. Numerical results show that the proposed approach not only can obtain optimal solution but also enjoys the low complexity suitable for integral-circuit implementation.

Whey-derived valuable products obtained by microbial fermentation.

Science.gov (United States)

Pescuma, Micaela; de Valdez, Graciela Font; Mozzi, Fernanda

2015-08-01

Whey, the main by-product of the cheese industry, is considered as an important pollutant due to its high chemical and biological oxygen demand. Whey, often considered as waste, has high nutritional value and can be used to obtain value-added products, although some of them need expensive enzymatic synthesis. An economical alternative to transform whey into valuable products is through bacterial or yeast fermentations and by accumulation during algae growth. Fermentative processes can be applied either to produce individual compounds or to formulate new foods and beverages. In the first case, a considerable amount of research has been directed to obtain biofuels able to replace those derived from petrol. In addition, the possibility of replacing petrol-derived plastics by biodegradable polymers synthesized during bacterial fermentation of whey has been sought. Further, the ability of different organisms to produce metabolites commonly used in the food and pharmaceutical industries (i.e., lactic acid, lactobionic acid, polysaccharides, etc.) using whey as growth substrate has been studied. On the other hand, new low-cost functional whey-based foods and beverages leveraging the high nutritional quality of whey have been formulated, highlighting the health-promoting effects of fermented whey-derived products. This review aims to gather the multiple uses of whey as sustainable raw material for the production of individual compounds, foods, and beverages by microbial fermentation. This is the first work to give an overview on the microbial transformation of whey as raw material into a large repertoire of industrially relevant foods and products.

Evaluation of high-resolution satellite precipitation products with surface rain gauge observations from Laohahe Basin in northern China

Directory of Open Access Journals (Sweden)

Shan-hu Jiang

2010-12-01

Full Text Available Three high-resolution satellite precipitation products, the Tropical Rainfall Measuring Mission (TRMM standard precipitation products 3B42V6 and 3B42RT and the Climate Precipitation Center's (CPC morphing technique precipitation product (CMORPH, were evaluated against surface rain gauge observations from the Laohahe Basin in northern China. Widely used statistical validation indices and categorical statistics were adopted. The evaluations were performed at multiple time scales, ranging from daily to yearly, for the years from 2003 to 2008. The results show that all three satellite precipitation products perform very well in detecting the occurrence of precipitation events, but there are some different biases in the amount of precipitation. 3B42V6, which has a bias of 21%, fits best with the surface rain gauge observations at both daily and monthly scales, while the biases of 3B42RT and CMORPH, with values of 81% and 67%, respectively, are much higher than a normal receivable threshold. The quality of the satellite precipitation products also shows monthly and yearly variation: 3B42RT has a large positive bias in the cold season from September to April, while CMORPH has a large positive bias in the warm season from May to August, and they all attained their best values in 2006 (with 10%, 50%, and −5% biases for 3B42V6, 3B42RT, and CMORPH, respectively. Our evaluation shows that, for the Laohahe Basin, 3B42V6 has the best correspondence with the surface observations, and CMORPH performs much better than 3B42RT. The large errors of 3B42RT and CMORPH remind us of the need for new improvements to satellite precipitation retrieval algorithms or feasible bias adjusting methods.

On the performance of satellite precipitation products in riverine flood modeling: A review

Science.gov (United States)

Maggioni, Viviana; Massari, Christian

2018-03-01

This work is meant to summarize lessons learned on using satellite precipitation products for riverine flood modeling and to propose future directions in this field of research. Firstly, the most common satellite precipitation products (SPPs) during the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM) eras are reviewed. Secondly, we discuss the main errors and uncertainty sources in these datasets that have the potential to affect streamflow and runoff model simulations. Thirdly, past studies that focused on using SPPs for predicting streamflow and runoff are analyzed. As the impact of floods depends not only on the characteristics of the flood itself, but also on the characteristics of the region (population density, land use, geophysical and climatic factors), a regional analysis is required to assess the performance of hydrologic models in monitoring and predicting floods. The performance of SPP-forced hydrological models was shown to largely depend on several factors, including precipitation type, seasonality, hydrological model formulation, topography. Across several basins around the world, the bias in SPPs was recognized as a major issue and bias correction methods of different complexity were shown to significantly reduce streamflow errors. Model re-calibration was also raised as a viable option to improve SPP-forced streamflow simulations, but caution is necessary when recalibrating models with SPP, which may result in unrealistic parameter values. From a general standpoint, there is significant potential for using satellite observations in flood forecasting, but the performance of SPP in hydrological modeling is still inadequate for operational purposes.

Tumorigenicity studies for human pluripotent stem cell-derived products.

Science.gov (United States)

Kuroda, Takuya; Yasuda, Satoshi; Sato, Yoji

2013-01-01

Human pluripotent stem cells (hPSCs), i.e. human embryonic stem cells and human induced pluripotent stem cells, are able to self-renew and differentiate into multiple cell types. Because of these abilities, numerous attempts have been made to utilize hPSCs in regenerative medicine/cell therapy. hPSCs are, however, also tumorigenic, that is, they can give rise to the progressive growth of tumor nodules in immunologically unresponsive animals. Therefore, assessing and managing the tumorigenicity of all final products is essential in order to prevent ectopic tissue formation, tumor development, and/or malignant transformation elicited by residual pluripotent stem cells after implantation. No detailed guideline for the tumorigenicity testing of hPSC-derived products has yet been issued for regenerative medicine/cell therapy, despite the urgent necessity. Here, we describe the current situations and issues related to the tumorigenicity testing of hPSC-derived products and we review the advantages and disadvantages of several types of tumorigenicity-associated tests. We also refer to important considerations in the execution and design of specific studies to monitor the tumorigenicity of hPSC-derived products.

Particle production in higher derivative theory

Indian Academy of Sciences (India)

Cosmological models; particle production; higher derivative theory of gravitation. PACS No. 98.80. 1. ... is of singular models where the cosmic expansion is driven by the big-bang impulse; all ... According to Gibbs integrability condition, one cannot independently specify an equa- .... [3] B Hartle and S W Hawking Phys. Rev.

VHR satellite imagery for humanitarian crisis management: a case study

Science.gov (United States)

Bitelli, Gabriele; Eleias, Magdalena; Franci, Francesca; Mandanici, Emanuele

2017-09-01

During the last years, remote sensing data along with GIS have been largely employed for supporting emergency management activities. In this context, the use of satellite images and derived map products has become more common also in the different phases of humanitarian crisis response. In this work very high resolution satellite imagery was processed to assess the evolution of Za'atari Refugee Camp, built in Jordan in 2012 by the UN Refugee Agency to host Syrian refugees. Multispectral satellite scenes of the Za'atari area were processed by means of object-based classifications. The main aim of the present work is the development of a semiautomated procedure for multi-temporal camp monitoring with particular reference to the dwellings detection. Whilst in the emergency mapping domain automation of feature extraction is widely investigated, in the field of humanitarian missions the information is often extracted by means of photointerpretation of the satellite data. This approach requires time for the interpretation; moreover, it is not reliable enough in complex situations, where features of interest are often small, heterogeneous and inconsistent. Therefore, the present paper discusses a methodology to obtain information for assisting humanitarian crisis management, using a semi-automatic classification approach applied to satellite imagery.

Evaluation of Satellite Precipitation Products with Rain Gauge Data at Different Scales: Implications for Hydrological Applications

Directory of Open Access Journals (Sweden)

Ruifang Guo

2016-07-01

Full Text Available Rain gauge and satellite-retrieved data have been widely used in basin-scale hydrological applications. While rain gauges provide accurate measurements that are generally unevenly distributed in space, satellites offer spatially regular observations and common error prone retrieval. Comparative evaluation of gauge-based and satellite-based data is necessary in hydrological studies, as precipitation is the most important input in basin-scale water balance. This study uses quality-controlled rain gauge data and prevailing satellite products (Tropical Rainfall Measuring Mission (TRMM 3B43, 3B42 and 3B42RT to examine the consistency and discrepancies between them at different scales. Rain gauges and TRMM products were available in the Poyang Lake Basin, China, from 1998 to 2007 (3B42RT: 2000–2007. Our results show that the performance of TRMM products generally increases with increasing spatial scale. At both the monthly and annual scales, the accuracy is highest for TRMM 3B43, with 3B42 second and 3B42RT third. TRMM products generally overestimate precipitation because of a high frequency and degree of overestimation in light and moderate rain cases. At the daily scale, the accuracy is relatively low between TRMM 3B42 and 3B42RT. Meanwhile, the performances of TRMM 3B42 and 3B42RT are highly variable in different seasons. At both the basin and pixel scales, TRMM 3B43 and 3B42 exhibit significant discrepancies from July to September, performing worst in September. For TRMM 3B42RT, all statistical indices fluctuate and are low throughout the year, performing worst in July at the pixel scale and January at the basin scale. Furthermore, the spatial distributions of the statistical indices of TRMM 3B43 and 3B42 performed well, while TRMM 3B42RT displayed a poor performance.

Assessment and Comparison of TMPA Satellite Precipitation Products in Varying Climatic and Topographic Regimes in Morocco

Directory of Open Access Journals (Sweden)

Adam Milewski

2015-05-01

Full Text Available TRMM Multi-satellite Precipitation Analysis (TMPA satellite precipitation products have been utilized to quantify, forecast, or understand precipitation patterns, climate change, hydrologic models, and drought in numerous scientific investigations. The TMPA products recently went through a series of algorithm developments to enhance the accuracy and reliability of high-quality precipitation measurements, particularly in low rainfall environments and complex terrain. In this study, we evaluated four TMPA products (3B42: V6, V7temp, V7, RTV7 against 125 rain gauges in Northern Morocco to assess the accuracy of TMPA products in various regimes, examine the performance metrics of new algorithm developments, and assess the impact of the processing error in 2012. Results show that the research products outperform the real-time products in all environments within Morocco, and the newest algorithm development (3B42 V7 outperforms the previous version (V6, particularly in low rainfall and high-elevation environments. TMPA products continue to overestimate precipitation in arid environments and underestimate it in high-elevation areas. Lastly, the temporary processing error resulted in little bias except in arid environments. These results corroborate findings from previous studies, provide scientific data for the Middle East, highlight the difficulty of using TMPA products in varying conditions, and present preliminary research for future algorithm development for the GPM mission.

Incorporating GOES Satellite Photosynthetically Active Radiation (PAR) Retrievals to Improve Biogenic Emission Estimates in Texas

Science.gov (United States)

Zhang, Rui; White, Andrew T.; Pour Biazar, Arastoo; McNider, Richard T.; Cohan, Daniel S.

2018-01-01

This study examines the influence of insolation and cloud retrieval products from the Geostationary Operational Environmental Satellite (GOES) system on biogenic emission estimates and ozone simulations in Texas. Compared to surface pyranometer observations, satellite-retrieved insolation and photosynthetically active radiation (PAR) values tend to systematically correct the overestimation of downwelling shortwave radiation in the Weather Research and Forecasting (WRF) model. The correlation coefficient increases from 0.93 to 0.97, and the normalized mean error decreases from 36% to 21%. The isoprene and monoterpene emissions estimated by the Model of Emissions of Gases and Aerosols from Nature are on average 20% and 5% less, respectively, when PAR from the direct satellite retrieval is used rather than the control WRF run. The reduction in biogenic emission rates using satellite PAR reduced the predicted maximum daily 8 h ozone concentration by up to 5.3 ppbV over the Dallas-Fort Worth (DFW) region on some days. However, episode average ozone response is less sensitive, with a 0.6 ppbV decrease near DFW and 0.3 ppbV increase over East Texas. The systematic overestimation of isoprene concentrations in a WRF control case is partially corrected by using satellite PAR, which observes more clouds than are simulated by WRF. Further, assimilation of GOES-derived cloud fields in WRF improved CAMx model performance for ground-level ozone over Texas. Additionally, it was found that using satellite PAR improved the model's ability to replicate the spatial pattern of satellite-derived formaldehyde columns and aircraft-observed vertical profiles of isoprene.

On the use of satellite-derived CH4 : CO2 columns in a joint inversion of CH4 and CO2 fluxes

NARCIS (Netherlands)

Pandey, S.

2015-01-01

We present a method for assimilating total column CH4 : CO2 ratio measurements from satellites for inverse modeling of CH4 and CO2 fluxes using the variational approach. Unlike conventional approaches, in which retrieved CH4 : CO2 are multiplied by model-derived total column CO2 and only the

An analysis of FDA-approved drugs: natural products and their derivatives.

Science.gov (United States)

Patridge, Eric; Gareiss, Peter; Kinch, Michael S; Hoyer, Denton

2016-02-01

Natural products contribute greatly to the history and landscape of new molecular entities (NMEs). An assessment of all FDA-approved NMEs reveals that natural products and their derivatives represent over one-third of all NMEs. Nearly one-half of these are derived from mammals, one-quarter from microbes and one-quarter from plants. Since the 1930s, the total fraction of natural products has diminished, whereas semisynthetic and synthetic natural product derivatives have increased. Over time, this fraction has also become enriched with microbial natural products, which represent a significant portion of approved antibiotics, including more than two-thirds of all antibacterial NMEs. In recent years, the declining focus on natural products has impacted the pipeline of NMEs from specific classes, and this trend is likely to continue without specific investment in the pursuit of natural products. Copyright © 2015 Elsevier Ltd. All rights reserved.

Satellite Ocean Heat Content Suite

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This collection contains an operational Satellite Ocean Heat Content Suite (SOHCS) product generated by NOAA National Environmental Satellite, Data, and Information...

Precision Orbit Derived Atmospheric Density: Development and Performance

Science.gov (United States)

McLaughlin, C.; Hiatt, A.; Lechtenberg, T.; Fattig, E.; Mehta, P.

2012-09-01

Precision orbit ephemerides (POE) are used to estimate atmospheric density along the orbits of CHAMP (Challenging Minisatellite Payload) and GRACE (Gravity Recovery and Climate Experiment). The densities are calibrated against accelerometer derived densities and considering ballistic coefficient estimation results. The 14-hour density solutions are stitched together using a linear weighted blending technique to obtain continuous solutions over the entire mission life of CHAMP and through 2011 for GRACE. POE derived densities outperform the High Accuracy Satellite Drag Model (HASDM), Jacchia 71 model, and NRLMSISE-2000 model densities when comparing cross correlation and RMS with accelerometer derived densities. Drag is the largest error source for estimating and predicting orbits for low Earth orbit satellites. This is one of the major areas that should be addressed to improve overall space surveillance capabilities; in particular, catalog maintenance. Generally, density is the largest error source in satellite drag calculations and current empirical density models such as Jacchia 71 and NRLMSISE-2000 have significant errors. Dynamic calibration of the atmosphere (DCA) has provided measurable improvements to the empirical density models and accelerometer derived densities of extremely high precision are available for a few satellites. However, DCA generally relies on observations of limited accuracy and accelerometer derived densities are extremely limited in terms of measurement coverage at any given time. The goal of this research is to provide an additional data source using satellites that have precision orbits available using Global Positioning System measurements and/or satellite laser ranging. These measurements strike a balance between the global coverage provided by DCA and the precise measurements of accelerometers. The temporal resolution of the POE derived density estimates is around 20-30 minutes, which is significantly worse than that of accelerometer

Gravity Anomalies and Estimated Topography Derived from Satellite Altimetry

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — In many areas of the global ocean, the depth of the seafloor is not well known because survey lines by ships are hundreds of kilometers apart. Satellites carrying...

Satellite-Based Precipitation Datasets

Science.gov (United States)

Munchak, S. J.; Huffman, G. J.

2017-12-01

Of the possible sources of precipitation data, those based on satellites provide the greatest spatial coverage. There is a wide selection of datasets, algorithms, and versions from which to choose, which can be confusing to non-specialists wishing to use the data. The International Precipitation Working Group (IPWG) maintains tables of the major publicly available, long-term, quasi-global precipitation data sets (http://www.isac.cnr.it/ ipwg/data/datasets.html), and this talk briefly reviews the various categories. As examples, NASA provides two sets of quasi-global precipitation data sets: the older Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and current Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG). Both provide near-real-time and post-real-time products that are uniformly gridded in space and time. The TMPA products are 3-hourly 0.25°x0.25° on the latitude band 50°N-S for about 16 years, while the IMERG products are half-hourly 0.1°x0.1° on 60°N-S for over 3 years (with plans to go to 16+ years in Spring 2018). In addition to the precipitation estimates, each data set provides fields of other variables, such as the satellite sensor providing estimates and estimated random error. The discussion concludes with advice about determining suitability for use, the necessity of being clear about product names and versions, and the need for continued support for satellite- and surface-based observation.

In-Orbit Vicarious Calibration for Ocean Color and Aerosol Products

National Research Council Canada - National Science Library

Wang, Menghua

2005-01-01

It is well known that, to accurately retrieve the spectrum of the water-leaving radiance and derive the ocean color products from satellite sensors, a vicarious calibration procedure, which performs...

Land Data Assimilation of Satellite-Based Soil Moisture Products Using the Land Information System Over the NLDAS Domain

Science.gov (United States)

Mocko, David M.; Kumar, S. V.; Peters-Lidard, C. D.; Tian, Y.

2011-01-01

This presentation will include results from data assimilation simulations using the NASA-developed Land Information System (LIS). Using the ensemble Kalman filter in LIS, two satellite-based soil moisture products from the AMSR-E instrument were assimilated, one a NASA-based product and the other from the Land Parameter Retrieval Model (LPRM). The domain and land-surface forcing data from these simulations were from the North American Land Data Assimilation System Phase-2, over the period 2002-2008. The Noah land-surface model, version 3.2, was used during the simulations. Changes to estimates of land surface states, such as soil moisture, as well as changes to simulated runoff/streamflow will be presented. Comparisons over the NLDAS domain will also be made to two global reference evapotranspiration (ET) products, one an interpolated product based on FLUXNET tower data and the other a satellite- based algorithm from the MODIS instrument. Results of an improvement metric show that assimilating the LPRM product improved simulated ET estimates while the NASA-based soil moisture product did not.

Characterization of buffy coat-derived granulocytes for clinical use: a comparison with granulocyte colony-stimulating factor/dexamethasone-pretreated donor-derived products.

Science.gov (United States)

van de Geer, A; Gazendam, R P; Tool, A T J; van Hamme, J L; de Korte, D; van den Berg, T K; Zeerleder, S S; Kuijpers, T W

2017-02-01

Buffy coat-derived granulocytes have been described as an alternative to the apheresis product from donors pretreated with dexamethasone and granulocyte colony-stimulating factor (G-CSF). The latter is - dependent on the local and national settings - obtained following a demanding and time-consuming procedure, which is undesirable in critically ill septic patients. In contrast, buffy coat-derived products have a large volume and are often heavily contaminated with red cells and platelets. We developed a new pooled buffy coat-derived product with high purity and small volume, and performed a comprehensive functional characterization of these granulocytes. We pooled ten buffy coats following the production of platelet concentrates. Saline 0·9% was added to decrease the viscosity and the product was split into plasma, red cells and a 'super' buffy coat. Functional data of the granulocytes were compared to those obtained with granulocytes from healthy controls and G-CSF/dexamethasone-pretreated donors. Buffy coat-derived granulocytes showed adhesion, chemotaxis, reactive oxygen species production, degranulation, NETosis and in vitro killing of Staphylococcus aureus, Escherichia coli and Aspergillus species comparable to control and G-CSF/dexamethasone-derived granulocytes. Candida killing was superior compared to G-CSF/dexamethasone-derived granulocytes. Immunophenotyping was normal; especially no signs of activation in the buffy coat-derived granulocytes were seen. Viability was reduced. Buffy coats are readily available in the regular blood production process and would take away the concerns around the apheresis product. The product described appears a promising alternative for transfusion purposes. © 2017 International Society of Blood Transfusion.

Assessing the Impact of Earth Radiation Pressure Acceleration on Low-Earth Orbit Satellites

Science.gov (United States)

Vielberg, Kristin; Forootan, Ehsan; Lück, Christina; Kusche, Jürgen; Börger, Klaus

2017-04-01

The orbits of satellites are influenced by several external forces. The main non-gravitational forces besides thermospheric drag, acting on the surface of satellites, are accelerations due to the Earth and Solar Radiation Pres- sure (SRP and ERP, respectively). The sun radiates visible and infrared light reaching the satellite directly, which causes the SRP. Earth also emits and reflects the sunlight back into space, where it acts on satellites. This is known as ERP acceleration. The influence of ERP increases with decreasing distance to the Earth, and for low-earth orbit (LEO) satellites ERP must be taken into account in orbit and gravity computations. Estimating acceler- ations requires knowledge about energy emitted from the Earth, which can be derived from satellite remote sensing data, and also by considering the shape and surface material of a satellite. In this sensitivity study, we assess ERP accelerations based on different input albedo and emission fields and their modelling for the satellite missions Challenging Mini-Satellite Payload (CHAMP) and Gravity Recovery and Climate Experiment (GRACE). As input fields, monthly 1°x1° products of Clouds and the Earth's Radiant En- ergy System (CERES), L3 are considered. Albedo and emission models are generated as latitude-dependent, as well as in terms of spherical harmonics. The impact of different albedo and emission models as well as the macro model and the altitude of satellites on ERP accelerations will be discussed.

Space transportation. [user needs met by information derived from satellites and the interface with space transportation systems

Science.gov (United States)

1975-01-01

User-oriented panels were formed to examine practical applications of information or services derived from earth orbiting satellites. Topics discussed include: weather and climate; uses of communication; land use planning; agriculture, forest, and range; inland water resources; retractable resources; environmental quality; marine and maritime uses; and materials processing in space. Emphasis was placed on the interface of the space transportation system (STS) with the applications envisioned by the user panels. User requirements were compared with expected STS capabilities in terms of availability, carrying payload to orbit, and estimated costs per launch. Conclusions and recommendations were reported.

Development of West-European PM2.5 and NO2 land use regression models incorporating satellite-derived and chemical transport modelling data

NARCIS (Netherlands)

de Hoogh, Kees; Gulliver, John; Donkelaar, Aaron van; Martin, Randall V; Marshall, Julian D; Bechle, Matthew J; Cesaroni, Giulia; Pradas, Marta Cirach; Dedele, Audrius; Eeftens, Marloes|info:eu-repo/dai/nl/315028300; Forsberg, Bertil; Galassi, Claudia; Heinrich, Joachim; Hoffmann, Barbara; Jacquemin, Bénédicte; Katsouyanni, Klea; Korek, Michal; Künzli, Nino; Lindley, Sarah J; Lepeule, Johanna; Meleux, Frederik; de Nazelle, Audrey; Nieuwenhuijsen, Mark; Nystad, Wenche; Raaschou-Nielsen, Ole; Peters, Annette; Peuch, Vincent-Henri; Rouil, Laurence; Udvardy, Orsolya; Slama, Rémy; Stempfelet, Morgane; Stephanou, Euripides G; Tsai, Ming Y; Yli-Tuomi, Tarja; Weinmayr, Gudrun; Brunekreef, Bert|info:eu-repo/dai/nl/067548180; Vienneau, Danielle; Hoek, Gerard|info:eu-repo/dai/nl/069553475

2016-01-01

Satellite-derived (SAT) and chemical transport model (CTM) estimates of PM2.5 and NO2 are increasingly used in combination with Land Use Regression (LUR) models. We aimed to compare the contribution of SAT and CTM data to the performance of LUR PM2.5 and NO2 models for Europe. Four sets of models,

Comment on 'The remote sensing of ocean primary productivity - Use of a new data compilation to test satellite algorithms' by William Balch et al

Science.gov (United States)

Platt, Trevor; Sathyendranath, Shubha

1993-01-01

Various conclusions by Balch et al. (1992) about the current state of modeling primary production in the sea (lack of improvement in primary production models, since 1957, utility of analytical models, and merits or weaknesses of complex models) are commented on. It is argued that since they are based on a false premise, these conclusions are not robust, and that the approach used by Balch et al. (the model of Platt and Sathyendranath, 1988) was inadequate for the question they set out to address. The present criticism is based mainly on the issue of whether implementation was correct with respect to parameter selection. It is concluded that the findings of Balch et al. with respect to the model of Platt and Sathyendranath is unreliable. Balch replies that satellite-derived estimates of primary production should be compared directly to that measured in situ in as many regions as possible. This will provide a first-order estimate of the magnitude of the error involved in estimating primary production from space.

Rainfall frequency analysis for ungauged sites using satellite precipitation products

Science.gov (United States)

Gado, Tamer A.; Hsu, Kuolin; Sorooshian, Soroosh

2017-11-01

The occurrence of extreme rainfall events and their impacts on hydrologic systems and society are critical considerations in the design and management of a large number of water resources projects. As precipitation records are often limited or unavailable at many sites, it is essential to develop better methods for regional estimation of extreme rainfall at these partially-gauged or ungauged sites. In this study, an innovative method for regional rainfall frequency analysis for ungauged sites is presented. The new method (hereafter, this is called the RRFA-S) is based on corrected annual maximum series obtained from a satellite precipitation product (e.g., PERSIANN-CDR). The probability matching method (PMM) is used here for bias correction to match the CDF of satellite-based precipitation data with the gauged data. The RRFA-S method was assessed through a comparative study with the traditional index flood method using the available annual maximum series of daily rainfall in two different regions in USA (11 sites in Colorado and 18 sites in California). The leave-one-out cross-validation technique was used to represent the ungauged site condition. Results of this numerical application have found that the quantile estimates obtained from the new approach are more accurate and more robust than those given by the traditional index flood method.

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

Directory of Open Access Journals (Sweden)

Carolien Toté

2015-02-01

Full Text Available Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT v2.0, Famine Early Warning System NETwork (FEWS NET Rainfall Estimate (RFE v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS are compared to independent gauge data (2001–2012. This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique

Science.gov (United States)

Tote, Carolien; Patricio, Domingos; Boogaard, Hendrik; van der Wijngaart, Raymond; Tarnavsky, Elena; Funk, Christopher C.

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001–2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

Mosaic of 5m gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Swains Island, Territory of American Samoa, South Pacific, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

Satellite Radiation Products for Ocean Biology and Biogeochemistry: Needs, State-of-the-Art, Gaps, Development Priorities, and Opportunities

Directory of Open Access Journals (Sweden)

Robert Frouin

2018-02-01

Full Text Available Knowing the spatial and temporal distribution of the underwater light field, i.e., the spectral and angular structure of the radiant intensity at any point in the water column, is essential to understanding the biogeochemical processes that control the composition and evolution of aquatic ecosystems and their impact on climate and reaction to climate change. At present, only a few properties are reliably retrieved from space, either directly or via water-leaving radiance. Existing satellite products are limited to planar photosynthetically available radiation (PAR and ultraviolet (UV irradiance above the surface and diffuse attenuation coefficient. Examples of operational products are provided, and their advantages and drawbacks are examined. The usefulness and convenience of these products notwithstanding, there is a need, as expressed by the user community, for other products, i.e., sub-surface planar and scalar fluxes, average cosine, spectral fluxes (UV to visible, diurnal fluxes, absorbed fraction of PAR by live algae (APAR, surface albedo, vertical attenuation, and heating rate, and for associating uncertainties to any product on a pixel-by-pixel basis. Methodologies to obtain the new products are qualitatively discussed in view of most recent scientific knowledge and current and future satellite missions, and specific algorithms are presented for some new products, namely sub-surface fluxes and average cosine. A strategy and roadmap (short, medium, and long term for usage and development priorities is provided, taking into account needs and readiness level. Combining observations from satellites overpassing at different times and geostationary satellites should be pursued to improve the quality of daily-integrated radiation fields, and products should be generated without gaps to provide boundary conditions for general circulation and biogeochemical models. Examples of new products, i.e., daily scalar PAR below the surface, daily average

An initial ULF wave index derived from 2 years of Swarm observations

Science.gov (United States)

Papadimitriou, Constantinos; Balasis, Georgios; Daglis, Ioannis A.; Giannakis, Omiros

2018-03-01

The ongoing Swarm satellite mission provides an opportunity for better knowledge of the near-Earth electromagnetic environment. Herein, we use a new methodological approach for the detection and classification of ultra low-frequency (ULF) wave events observed by Swarm based on an existing time-frequency analysis (TFA) tool and utilizing a state-of-the-art high-resolution magnetic field model and Swarm Level 2 products (i.e., field-aligned currents - FACs - and the Ionospheric Bubble Index - IBI). We present maps of the dependence of ULF wave power with magnetic latitude and magnetic local time (MLT) as well as geographic latitude and longitude from the three satellites at their different locations in low-Earth orbit (LEO) for a period spanning 2 years after the constellation's final configuration. We show that the inclusion of the Swarm single-spacecraft FAC product in our analysis eliminates all the wave activity at high altitudes, which is physically unrealistic. Moreover, we derive a Swarm orbit-by-orbit Pc3 wave (20-100 MHz) index for the topside ionosphere and compare its values with the corresponding variations of solar wind variables and geomagnetic activity indices. This is the first attempt, to our knowledge, to derive a ULF wave index from LEO satellite data. The technique can be potentially used to define a new Level 2 product from the mission, the Swarm ULF wave index, which would be suitable for space weather applications.

Precipitation Analysis at Fine Time Scales using TRMM and Other Satellites: Realtime and Research Products and Applications

Science.gov (United States)

Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold; Gu, Guojon

2004-01-01

Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the TRMM Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) by the end of 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25 deg latitude-longitude resolution over the latitude range from 50 deg N-50 deg S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, including: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

Correcting Measurement Error in Satellite Aerosol Optical Depth with Machine Learning for Modeling PM2.5 in the Northeastern USA

Directory of Open Access Journals (Sweden)

Allan C. Just

2018-05-01

Full Text Available Satellite-derived estimates of aerosol optical depth (AOD are key predictors in particulate air pollution models. The multi-step retrieval algorithms that estimate AOD also produce quality control variables but these have not been systematically used to address the measurement error in AOD. We compare three machine-learning methods: random forests, gradient boosting, and extreme gradient boosting (XGBoost to characterize and correct measurement error in the Multi-Angle Implementation of Atmospheric Correction (MAIAC 1 × 1 km AOD product for Aqua and Terra satellites across the Northeastern/Mid-Atlantic USA versus collocated measures from 79 ground-based AERONET stations over 14 years. Models included 52 quality control, land use, meteorology, and spatially-derived features. Variable importance measures suggest relative azimuth, AOD uncertainty, and the AOD difference in 30–210 km moving windows are among the most important features for predicting measurement error. XGBoost outperformed the other machine-learning approaches, decreasing the root mean squared error in withheld testing data by 43% and 44% for Aqua and Terra. After correction using XGBoost, the correlation of collocated AOD and daily PM2.5 monitors across the region increased by 10 and 9 percentage points for Aqua and Terra. We demonstrate how machine learning with quality control and spatial features substantially improves satellite-derived AOD products for air pollution modeling.

Modernized Techniques for Dealing with Quality Data and Derived Products

Science.gov (United States)

Neiswender, C.; Miller, S. P.; Clark, D.

2008-12-01

"I just want a picture of the ocean floor in this area" is expressed all too often by researchers, educators, and students in the marine geosciences. As more sophisticated systems are developed to handle data collection and processing, the demand for quality data, and standardized products continues to grow. Data management is an invisible bridge between science and researchers/educators. The SIOExplorer digital library presents more than 50 years of ocean-going research. Prior to publication, all data is checked for quality using standardized criterion developed for each data stream. Despite the evolution of data formats and processing systems, SIOExplorer continues to present derived products in well- established formats. Standardized products are published for each cruise, and include a cruise report, MGD77 merged data, multi-beam flipbook, and underway profiles. Creation of these products is made possible by processing scripts, which continue to change with ever-evolving data formats. We continue to explore the potential of database-enabled creation of standardized products, such as the metadata-rich MGD77 header file. Database-enabled, automated processing produces standards-compliant metadata for each data and derived product. Metadata facilitates discovery and interpretation of published products. This descriptive information is stored both in an ASCII file, and a searchable digital library database. SIOExplorer's underlying technology allows focused search and retrieval of data and products. For example, users can initiate a search of only multi-beam data, which includes data-specific parameters. This customization is made possible with a synthesis of database, XML, and PHP technology. The combination of standardized products and digital library technology puts quality data and derived products in the hands of scientists. Interoperable systems enable distribution these published resources using technology such as web services. By developing modernized

Mosaic of gridded multibeam bathymetry, gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tinian Island, Commonwealth of the Northern Marianas Islands, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size)...

Minimizing Gaps of Daily Ndvi Map with Geostationary Satellite Remote Sensing Data

Science.gov (United States)

Lee, S.; Ryu, Y.; Jiang, C.

2015-12-01

Satellite based remote sensing has been used to monitor plant phenology. Numerous studies have generally utilized normalized difference vegetation index (NDVI) to quantify phenological patterns and changes in regional to the global scales. Obtaining the NDVI values during summer in East Asian Monsoon regions is important because most plants grow vigorously in this season. However, satellite derived NDVI data are error prone to clouds during most of the period. Various methods have attempted to reduce the effect of cloud in temporal and spatial NDVI monitoring; the fundamental solution is to have a large data pool that includes multiple images in short period and supplements NDVI values in same period. Multiple images of geostationary satellite in a day can be a method to expand the pool. In this study, we suggest an approach that minimizes data gaps in NDVI of the day through geostationary satellite derived NDVI composition. We acquired data from Geostationary Ocean Color Imager (GOCI) which is a satellite that was launched to monitor ocean around the Korean peninsula, China, Japan and Russia. The satellite observes eight times per day (09:00 - 16:00, every hour) at 500 x 500 m resolution from 2011 to 2015. GOCI red- and near infrared radiance was converted into surface reflectance by using 6S Radiative Transfer Model (6S). We calculated NDVI tiles for each of observed eight tiles per day and made one day NDVI through maximum-value composite method. We evaluated the composite GOCI derived NDVI by comparing with daily MODIS-derived NDVI (composited from MOD09GA and MYD09GA), 16-day Landsat 8-derived NDVI, and in-situ light emitting diode (LED) NDVI measurements at a homogeneous deciduous forest and rice paddy sites. We found that GOCI-derived NDVI maps revealed little data gaps compared to MODIS and Landsat, and GOCI derived NDVI time series were smoother than MODIS derived NDVI time series in summer. GOCI-derived NDVI agreed well with in-situ observations of NDVI

Reconstruction and downscaling of Eastern Mediterranean OSCAR satellite surface current data using DINEOF

Science.gov (United States)

Nikolaidis, Andreas; Stylianou, Stavros; Georgiou, Georgios; Hajimitsis, Diofantos; Gravanis, Elias; Akylas, Evangelos

2015-04-01

During the last decade, Rixen (2005) and Alvera-Azkarate (2010) presented the DINEOF (Data Interpolating Empirical Orthogonal Functions) method, a EOF-based technique to reconstruct missing data in satellite images. The application of DINEOF method, proved to provide relative success in various experimental trials (Wang and Liu, 2013; Nikolaidis et al., 2013;2014), and tends to be an effective and computationally affordable solution, on the problem of data reconstruction, for missing data from geophysical fields, such as chlorophyll-a, sea surface temperatures or salinity and geophysical fields derived from satellite data. Implementation of this method in a GIS system will provide with a more complete, integrated approach, permitting the expansion of the applicability over various aspects. This may be especially useful in studies where various data of different kind, have to be examined. For this purpose, in this study we have implemented and present a GIS toolbox that aims to automate the usage of the algorithm, incorporating the DINEOF codes provided by GHER (GeoHydrodynamics and Environment Research Group of University of Liege) into the ArcGIS®. ArcGIS® is a well known standard on Geographical Information Systems, used over the years for various remote sensing procedures, in sea and land environment alike. A case-study of filling the missing satellite derived current data in the Eastern Mediterranean Sea area, for a monthly period is analyzed, as an example for the effectiveness and simplicity of the usage of this toolbox. The specific study focuses to OSCAR satellite data (http://www.oscar.noaa.gov/) collected by NOAA/NESDIS Operational Surface Current Processing and Data Center, from the respective products of OSCAR Project Office Earth and Space Research organization, that provides free online access to unfiltered (1/3 degree) resolution. All the 5-day mean products data coverage were successfully reconstructed. KEY WORDS: Remote Sensing, Cyprus

Patchiness in semi-arid dwarf shrublands: evidence from satellite ...

African Journals Online (AJOL)

... Plants; Remote sensing; Rhigozum obovatum Burch; Satellite-derived vegetation indices; Woody species; patchiness; semi-arid; dwarf shrubland; shrublands; co2; assimilation; karoo; south africa; ndvi; satellite imagery; geochemical mound; rhigozum obovatum; eriocephalus ericoides; pentzia incana; vegetation; botany

Mobile satellite communications in the 1990's

Science.gov (United States)

Singh, Jai

1992-07-01

The evolution of Inmarsat global services from a single market and single service of the 1980's to all of the key mobile markets and a wide range of new terminals and services in the 1990's is described. An overview of existing mobile satellite services, as well as new services under implementation for introduction in the near and longer term, including a handheld satellite phone (Inmarsat-P), is provided. The initiative taken by Inmarsat in the integration of its global mobile satellite services with global navigation capability derived from GPS (Global Positioning System) and the GLONASS (Russian GPS) navigation satellite systems and the provision of an international civil overlay for GPS/GLONASS integrity and augmentation is highlighted. To complete the overview of the development of mobile satellite services in the 1990's, the known national and regional mobile satellite system plans and the various recent proposals for both orbiting and geostationary satellite systems for proving handheld satellite phone and/or data messaging services are described.

Forecasting Global Horizontal Irradiance Using the LETKF and a Combination of Advected Satellite Images and Sparse Ground Sensors

Science.gov (United States)

Harty, T. M.; Lorenzo, A.; Holmgren, W.; Morzfeld, M.

2017-12-01

The irradiance incident on a solar panel is the main factor in determining the power output of that panel. For this reason, accurate global horizontal irradiance (GHI) estimates and forecasts are critical when determining the optimal location for a solar power plant, forecasting utility scale solar power production, or forecasting distributed, behind the meter rooftop solar power production. Satellite images provide a basis for producing the GHI estimates needed to undertake these objectives. The focus of this work is to combine satellite derived GHI estimates with ground sensor measurements and an advection model. The idea is to use accurate but sparsely distributed ground sensors to improve satellite derived GHI estimates which can cover large areas (the size of a city or a region of the United States). We use a Bayesian framework to perform the data assimilation, which enables us to produce irradiance forecasts and associated uncertainties which incorporate both satellite and ground sensor data. Within this framework, we utilize satellite images taken from the GOES-15 geostationary satellite (available every 15-30 minutes) as well as ground data taken from irradiance sensors and rooftop solar arrays (available every 5 minutes). The advection model, driven by wind forecasts from a numerical weather model, simulates cloud motion between measurements. We use the Local Ensemble Transform Kalman Filter (LETKF) to perform the data assimilation. We present preliminary results towards making such a system useful in an operational context. We explain how localization and inflation in the LETKF, perturbations of wind-fields, and random perturbations of the advection model, affect the accuracy of our estimates and forecasts. We present experiments showing the accuracy of our forecasted GHI over forecast-horizons of 15 mins to 1 hr. The limitations of our approach and future improvements are also discussed.

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.

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.

Donor Satellite Cell Engraftment is Significantly Augmented When the Host Niche is Preserved and Endogenous Satellite Cells are Incapacitated

Science.gov (United States)

Boldrin, Luisa; Neal, Alice; Zammit, Peter S; Muntoni, Francesco; Morgan, Jennifer E

2012-01-01

Stem cell transplantation is already in clinical practice for certain genetic diseases and is a promising therapy for dystrophic muscle. We used the mdx mouse model of Duchenne muscular dystrophy to investigate the effect of the host satellite cell niche on the contribution of donor muscle stem cells (satellite cells) to muscle regeneration. We found that incapacitation of the host satellite cells and preservation of the muscle niche promote donor satellite cell contribution to muscle regeneration and functional reconstitution of the satellite cell compartment. But, if the host niche is not promptly refilled, or is filled by competent host satellite cells, it becomes nonfunctional and donor engraftment is negligible. Application of this regimen to aged host muscles also promotes efficient regeneration from aged donor satellite cells. In contrast, if the niche is destroyed, yet host satellite cells remain proliferation-competent, donor-derived engraftment is trivial. Thus preservation of the satellite cell niche, concomitant with functional impairment of the majority of satellite cells within dystrophic human muscles, may improve the efficiency of stem cell therapy. Stem Cells2012;30:1971–1984 PMID:22730231

Satellite orbits in Levi-Civita space

Science.gov (United States)

Humi, Mayer

2018-03-01

In this paper we consider satellite orbits in central force field with quadratic drag using two formalisms. The first using polar coordinates in which the satellite angular momentum plays a dominant role. The second is in Levi-Civita coordinates in which the energy plays a central role. We then merge these two formalisms by introducing polar coordinates in Levi-Civita space and derive a new equation for satellite orbits which unifies these two paradigms. In this equation energy and angular momentum appear on equal footing and thus characterize the orbit by its two invariants. Using this formalism we show that equatorial orbits around oblate spheroids can be expressed analytically in terms of Elliptic functions. In the second part of the paper we derive in Levi-Civita coordinates a linearized equation for the relative motion of two spacecrafts whose trajectories are in the same plane. We carry out also a numerical verification of these equations.

Estimation of time-series properties of gourd observed solar irradiance data using cloud properties derived from satellite observations

Science.gov (United States)

Watanabe, T.; Nohara, D.

2017-12-01

The shorter temporal scale variation in the downward solar irradiance at the ground level (DSI) is not understood well because researches in the shorter-scale variation in the DSI is based on the ground observation and ground observation stations are located coarsely. Use of dataset derived from satellite observation will overcome such defect. DSI data and MODIS cloud properties product are analyzed simultaneously. Three metrics: mean, standard deviation and sample entropy, are used to evaluate time-series properties of the DSI. Three metrics are computed from two-hours time-series centered at the observation time of MODIS over the ground observation stations. We apply the regression methods to design prediction models of each three metrics from cloud properties. The validation of the model accuracy show that mean and standard deviation are predicted with a higher degree of accuracy and that the accuracy of prediction of sample entropy, which represents the complexity of time-series, is not high. One of causes of lower prediction skill of sample entropy is the resolution of the MODIS cloud properties. Higher sample entropy is corresponding to the rapid fluctuation, which is caused by the small and unordered cloud. It seems that such clouds isn't retrieved well.

The along track scanning radiometer - an analysis of coincident ship and satellite measurements

Science.gov (United States)

Barton, I. J.; Prata, A. J.; Llewellyn-Jones, D. T.

1993-05-01

Following the successful launch of the ERS-1 satellite in July 1991 we have undertaken several geophysical validation cruises in the Coral Sea. The prime aim of these cruises was to compare the sea surface temperature (SST) derived from the Along Track Scanning Radiometer (ATSR) with that measured using precision radiometers mounted on the ships. On most occasions when simultaneous satellite and ship measurements were taken we also launched a radiosonde from one of the research vessels. The results suggest that the ATSR is able to measure the ``skin'' temperature of the sea surface with an accuracy suitable for climate research applications. A case study comparison between the AVHRR and ATSR SST products will also be presented.

Vegetable milks and their fermented derivative products

Directory of Open Access Journals (Sweden)

Neus Bernat

2014-04-01

Full Text Available The so-called vegetable milks are in the spotlight thanks to their lactose-free, animal protein-free and cholesterol-free features which fit well with the current demand for healthy food products. Nevertheless, and with the exception of soya, little information is available about these types of milks and their derivatives. The aims of this review, therefore, are to: highlight the main nutritional benefits of the nut and cereal vegetable milks available on the market, fermented or not; describe the basic processing steps involved in their manufacturing process; and analyze the major problems affecting their overall quality, together with the current feasible solutions. On the basis of the information gathered, vegetable milks and their derivatives have excellent nutritional properties which provide them a high potential and positive market expectation. Nevertheless, optimal processing conditions for each raw material or the application of new technologies have to be researched in order to improve the quality of the products. Hence, further studies need to be developed to ensure the physical stability of the products throughout their whole shelf-life. These studies would also allow for a reduction in the amount of additives (hydrocolloids and/or emulsifiers and thus reduce the cost of the products. In the particular case of fermented products, the use of starters which are able to both improve the quality (by synthesizing enhanced flavors and providing optimal textures and exert health benefits for consumers (i.e. probiotics is the main challenge to be faced in future studies.

A Fifteen Year Record of Global Natural Gas Flaring Derived from Satellite Data

International Nuclear Information System (INIS)

Elvidge, Ch. D.; Erwin, E. H.; Ziskin, D.; Baugh, K. E.; Tuttle, B. T.; Ghosh, T.; Tuttle, B. T.; Ghosh, T.; Pack, D. W.; Zhizhin, M.

2009-01-01

We have produced annual estimates of national and global gas flaring and gas flaring efficiency from 1994 through 2008 using low light imaging data acquired by the Defense Meteorological Satellite Program (DMSP). Gas flaring is a widely used practice for the disposal of associated gas in oil production and processing facilities where there is insufficient infrastructure for utilization of the gas (primarily methane). Improved utilization of the gas is key to reducing global carbon emissions to the atmosphere. The DMSP estimates of flared gas volume are based on a calibration developed with a pooled set of reported national gas flaring volumes and data from individual flares. Flaring efficiency was calculated as the volume of flared gas per barrel of crude oil produced. Global gas flaring has remained largely stable over the past fifteen years, in the range of 140 to 170 billion cubic meters (BCM). Global flaring efficiency was in the seven to eight cubic meters per barrel from 1994 to 2005 and declined to 5.6 m 3 per barrel by 2008. The 2008 gas flaring estimate of 139 BCM represents 21% of the natural gas consumption of the USA with a potential retail market value of 68 billions USD. The 2008 flaring added more than 278 million metric tons of carbon dioxide equivalent (CO 2e ) into the atmosphere. The DMSP estimated gas flaring volumes indicate that global gas flaring has declined by 19% since 2005, led by gas flaring reductions in Russia and Nigeria, the two countries with the highest gas flaring levels. The flaring efficiency of both Russia and Nigeria improved from 2005 to 2008, suggesting that the reductions in gas flaring are likely the result of either improved utilization of the gas, reinjection, or direct venting of gas into the atmosphere, although the effect of uncertainties in the satellite data cannot be ruled out. It is anticipated that the capability to estimate gas flaring volumes based on satellite data will spur improved utilization of gas that

Establishing best practices for the validation of atmospheric composition measurements from satellites

Science.gov (United States)

Lambert, Jean-Christopher

As a contribution to the implementation of the Global Earth Observation System of Systems (GEOSS), the Committee on Earth Observation Satellites (CEOS) is developing a data quality strategy for satellite measurements. To achieve GEOSS requirements of consistency and interoperability (e.g. for comparison and for integrated interpretation) of the measurements and their derived data products, proper uncertainty assessment is essential and needs to be continuously monitored and traceable to standards. Therefore, CEOS has undertaken the task to establish a set of best practices and guidelines for satellite validation, starting with current practices that could be improved with time. Best practices are not intended to be imposed as firm requirements, but rather to be suggested as a baseline for comparing against, which could be used by the widest community and provide guidance to newcomers. The present paper reviews the current development of best practices and guidelines for the validation of atmospheric composition satellites. Terminologies and general principles of validation are reminded. Going beyond elementary definitions of validation like the assessment of uncertainties, the specific GEOSS context calls also for validation of individual service components and against user requirements. This paper insists on two important aspects. First one, the question of the "collocation". Validation generally involves comparisons with "reference" measurements of the same quantities, and the question of what constitutes a valid comparison is not the least of the challenges faced. We present a tentative scheme for defining the validity of a comparison and of the necessary "collocation" criteria. Second focus of this paper: the information content of the data product. Validation against user requirements, or the verification of the "fitness for purpose" of both the data products and their validation, needs to identify what information, in the final product, is contributed really

Office of Satellite and Product Operations

Science.gov (United States)

; Strategy » International Agreements » POES Current » GOES Current History » History in Images » POES History » GOES History OSPO Information » Access and Distribution Policy » Organization Chart  Branch utilizes interactive processing technology to integrate multiple satellite sensor data streams

DEVELOPMENT OF IMPROVED TECHNIQUES FOR SATELLITE REMOTE SENSING OF CLOUDS AND RADIATION USING ARM DATA, FINAL REPORT

Energy Technology Data Exchange (ETDEWEB)

Minnis, Patrick [NASA Langley Research Center, Hampton, VA

2013-06-28

During the period, March 1997 – February 2006, the Principal Investigator and his research team co-authored 47 peer-reviewed papers and presented, at least, 138 papers at conferences, meetings, and workshops that were supported either in whole or in part by this agreement. We developed a state-of-the-art satellite cloud processing system that generates cloud properties over the Atmospheric Radiation (ARM) surface sites and surrounding domains in near-real time and outputs the results on the world wide web in image and digital formats. When the products are quality controlled, they are sent to the ARM archive for further dissemination. These products and raw satellite images can be accessed at http://cloudsgate2.larc.nasa.gov/cgi-bin/site/showdoc?docid=4&cmd=field-experiment-homepage&exp=ARM and are used by many in the ARM science community. The algorithms used in this system to generate cloud properties were validated and improved by the research conducted under this agreement. The team supported, at least, 11 ARM-related or supported field experiments by providing near-real time satellite imagery, cloud products, model results, and interactive analyses for mission planning, execution, and post-experiment scientific analyses. Comparisons of cloud properties derived from satellite, aircraft, and surface measurements were used to evaluate uncertainties in the cloud properties. Multiple-angle satellite retrievals were used to determine the influence of cloud structural and microphysical properties on the exiting radiation field.

Solar power satellites: Commercialization and socio-economic impacts

International Nuclear Information System (INIS)

Storelli, V.

1993-01-01

Commercialization prospects for solar power satellites are assessed with reference to their possible impacts on the viability of the fossil fuel market and on international energy and environmental policies. The technical aspects which are examined include: solar panel sizing in relation to solar cell efficiency; the development of point-contact solar cell technology; the feasibility of the use of lunar materials; microwave transmission from the moon; optimum satellite positioning; the use of robots for in-space satellite assembly; satellite transmitted power for hydrogen production and storage; marketable product estimated development time

Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Agrihan Island, Territory of Mariana, USA from 2003-08-26 to 2012-05-03 (NODC Accession 0126914)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

Spatio-temporal Root Zone Soil Moisture Estimation for Indo - Gangetic Basin from Satellite Derived (AMSR-2 and SMOS) Surface Soil Moisture

Science.gov (United States)

Sure, A.; Dikshit, O.

2017-12-01

Root zone soil moisture (RZSM) is an important element in hydrology and agriculture. The estimation of RZSM provides insight in selecting the appropriate crops for specific soil conditions (soil type, bulk density, etc.). RZSM governs various vadose zone phenomena and subsequently affects the groundwater processes. With various satellite sensors dedicated to estimating surface soil moisture at different spatial and temporal resolutions, estimation of soil moisture at root zone level for Indo - Gangetic basin which inherits complex heterogeneous environment, is quite challenging. This study aims at estimating RZSM and understand its variation at the level of Indo - Gangetic basin with changing land use/land cover, topography, crop cycles, soil properties, temperature and precipitation patterns using two satellite derived soil moisture datasets operating at distinct frequencies with different principles of acquisition. Two surface soil moisture datasets are derived from AMSR-2 (6.9 GHz - `C' Band) and SMOS (1.4 GHz - `L' band) passive microwave sensors with coarse spatial resolution. The Soil Water Index (SWI), accounting for soil moisture from the surface, is derived by considering a theoretical two-layered water balance model and contributes in ascertaining soil moisture at the vadose zone. This index is evaluated against the widely used modelled soil moisture dataset of GLDAS - NOAH, version 2.1. This research enhances the domain of utilising the modelled soil moisture dataset, wherever the ground dataset is unavailable. The coupling between the surface soil moisture and RZSM is analysed for two years (2015-16), by defining a parameter T, the characteristic time length. The study demonstrates that deriving an optimal value of T for estimating SWI at a certain location is a function of various factors such as land, meteorological, and agricultural characteristics.

Particle production after inflation with non-minimal derivative coupling to gravity

International Nuclear Information System (INIS)

Ema, Yohei; Jinno, Ryusuke; Nakayama, Kazunori; Mukaida, Kyohei

2015-01-01

We study cosmological evolution after inflation in models with non-minimal derivative coupling to gravity. The background dynamics is solved and particle production associated with rapidly oscillating Hubble parameter is studied in detail. In addition, production of gravitons through the non-minimal derivative coupling with the inflaton is studied. We also find that the sound speed squared of the scalar perturbation oscillates between positive and negative values when the non-minimal derivative coupling dominates over the minimal kinetic term. This may lead to an instability of this model. We point out that the particle production rates are the same as those in the Einstein gravity with the minimal kinetic term, if we require the sound speed squared is positive definite

Classification of Dust Days by Satellite Remotely Sensed Aerosol Products

Science.gov (United States)

Sorek-Hammer, M.; Cohen, A.; Levy, Robert C.; Ziv, B.; Broday, D. M.

2013-01-01

Considerable progress in satellite remote sensing (SRS) of dust particles has been seen in the last decade. From an environmental health perspective, such an event detection, after linking it to ground particulate matter (PM) concentrations, can proxy acute exposure to respirable particles of certain properties (i.e. size, composition, and toxicity). Being affected considerably by atmospheric dust, previous studies in the Eastern Mediterranean, and in Israel in particular, have focused on mechanistic and synoptic prediction, classification, and characterization of dust events. In particular, a scheme for identifying dust days (DD) in Israel based on ground PM10 (particulate matter of size smaller than 10 nm) measurements has been suggested, which has been validated by compositional analysis. This scheme requires information regarding ground PM10 levels, which is naturally limited in places with sparse ground-monitoring coverage. In such cases, SRS may be an efficient and cost-effective alternative to ground measurements. This work demonstrates a new model for identifying DD and non-DD (NDD) over Israel based on an integration of aerosol products from different satellite platforms (Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI)). Analysis of ground-monitoring data from 2007 to 2008 in southern Israel revealed 67 DD, with more than 88 percent occurring during winter and spring. A Classification and Regression Tree (CART) model that was applied to a database containing ground monitoring (the dependent variable) and SRS aerosol product (the independent variables) records revealed an optimal set of binary variables for the identification of DD. These variables are combinations of the following primary variables: the calendar month, ground-level relative humidity (RH), the aerosol optical depth (AOD) from MODIS, and the aerosol absorbing index (AAI) from OMI. A logistic regression that uses these variables, coded as binary

Inter-comparison of ice sheet mass balance products from GRACE: ESA CCI Round Robin results

DEFF Research Database (Denmark)

Groth, A.; Horwath, M.; Horvath, A.

-term satellite-based data products are generated for selected ECVs. Since ice sheet mass balance is an ECV parameter of highest interest, both the AIS_cci and the GIS_cci project will provide mass balance products based on satellite gravimetry data: (a) time series of monthly mass changes for individual drainage...... basins, and (b) gridded mass changes covering the entire ice sheet.Gravimetry Mass Balance (GMB) products are derived from data acquired by the GRACE (Gravity Recovery and Climate Experiment) mission. Although GRACE data have the advantage of being directly sensitive to mass changes, their limited...... drainage basins the GMB time series are compared to independent mass balance products based on satellite altimetry and firn densification information from a regional climate model. This inter-comparison has aided the algorithm definition for the operational ECV production....

Inferring biome-scale net primary productivity from tree-ring isotopes

Science.gov (United States)

Pederson, N.; Levesque, M.; Williams, A. P.; Hobi, M. L.; Smith, W. K.; Andreu-Hayles, L.

2017-12-01

Satellite estimates of vegetation growth (net primary productivity; NPP), tree-ring records, and forest inventories indicate that ongoing climate change and rising atmospheric CO2 concentration are altering productivity and carbon storage of forests worldwide. The impact of global change on the trends of NPP, however, remain unknown because of the lack of long-term high-resolution NPP data. For the first time, we tested if annually resolved carbon (δ13C) and oxygen (δ18O) stable isotopes from the cellulose of tree rings from trees in temperate regions could be used as a tool for inferring NPP across spatiotemporal scales. We compared satellite NPP estimates from the moderate-resolution imaging spectroradiometer sensor (MODIS, product MOD17A) and a newly developed global NPP dataset derived from the Global Inventory Modeling and Mapping Studies (GIMMS) dataset to annually resolved tree-ring width and δ13C and δ18O records from four sites along a hydroclimatic gradient in Eastern and Central United States. We found strong correlations across large geographical regions between satellite-derived NPP and tree-ring isotopes that ranged from -0.40 to -0.91. Notably, tree-ring derived δ18O had the strongest relation to climate. The results were consistent among the studied tree species (Quercus rubra and Liriodendron tulipifera) and along the hydroclimatic conditions of our network. Our study indicates that tree-ring isotopes can potentially be used to reconstruct NPP in time and space. As such, our findings represent an important breakthrough for estimating long-term changes in vegetation productivity at the biome scale.

Precipitation Analysis at Fine Time Scales using TRMM and Other Satellites: Real-time and Research Products and Applications

Science.gov (United States)

Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold; Gu, Guo-Jon

2004-01-01

Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the TRMM Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) by the end of 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25" latitude-longitude resolution over the latitude range from 5O0N-50"S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, includmg: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

Performance of High Resolution Satellite Rainfall Products over Data Scarce Parts of Eastern Ethiopia

Directory of Open Access Journals (Sweden)

Shimelis B. Gebere

2015-09-01

Full Text Available Accurate estimation of rainfall in mountainous areas is necessary for various water resource-related applications. Though rain gauges accurately measure rainfall, they are rarely found in mountainous regions and satellite rainfall data can be used as an alternative source over these regions. This study evaluated the performance of three high-resolution satellite rainfall products, the Tropical Rainfall Measuring Mission (TRMM 3B42, the Global Satellite Mapping of Precipitation (GSMaP_MVK+, and the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Networks (PERSIANN at daily, monthly, and seasonal time scales against rain gauge records over data-scarce parts of Eastern Ethiopia. TRMM 3B42 rain products show relatively better performance at the three time scales, while PERSIANN did much better than GSMaP. At the daily time scale, TRMM correctly detected 88% of the rainfall from the rain gauge. The correlation at the monthly time scale also revealed that the TRMM has captured the observed rainfall better than the other two. For Belg (short rain and Kiremt (long rain seasons, the TRMM did better than the others by far. However, during Bega (dry season, PERSIANN showed a relatively good estimate. At all-time scales, noticing the bias, TRMM tends to overestimate, while PERSIANN and GSMaP tend to underestimate the rainfall. The overall result suggests that monthly and seasonal TRMM rainfall performed better than daily rainfall. It has also been found that both GSMaP and PERSIANN performed better in relatively flat areas than mountainous areas. Before the practical use of TRMM, the RMSE value needs to be improved by considering the topography of the study area or adjusting the bias.

Green leaf phenology at Landsat resolution: scaling from the plot to satellite

Science.gov (United States)

Fisher, J. I.; Mustard, J. F.; Vadeboncour, M.

2005-12-01

Despite the large number of in situ, plot-level phenological measurements and satellite-derived phenological studies, there has been little success to date in merging these records temporally or spatially. In particular, while most phenological patterns and trends derived from satellites appear realistic and coherent, they may not reflect spatial and temporal patterns at the plot level. An obvious explanation is the drastic scale difference from plot-level to most satellite observations. In this research, we bridge this scale gap through higher resolution satellite records (Landsat) and quantify the accuracy of satellite-derived metrics with direct field measurements. We compiled fifty-seven Landsat scenes from southern New England (P12 R51) from 1984 to 2002. Green vegetation areal abundance for each scene was derived from spectral mixture analysis and a single set of endmembers. The leaf area signal was fit with a logistic-growth simulating sigmoid curve to derive phenological markers (half-maximum leaf-onset and offset). Spring leaf-onset dates in homogenous stands of deciduous forests displayed significant and persistent local variability. The local variability was validated with multiple springtime ground observations (r2 = 0.91). The highest degree of verified small-scale variation occurred where contiguous forests displayed leaf-onset gradients of 10-14 days over short distances (example, our results indicate that deciduous forests in the Providence, RI metropolitan area leaf out 5-7 days earlier than comparable rural areas. In preliminary work, we validated the Landsat-derived metrics with similar analyses of MODIS and AVHRR, and demonstrate that aggregating diverse local phenologies into coarse grids may convolute interpretations. Despite these complications, the platform-independent curve-fit methodology may be extended across platforms and field data. The methodologically consistent approach, in tandem with Landsat data, allows us to effectively scale

Can Airborne Laser Scanning (ALS and Forest Estimates Derived from Satellite Images Be Used to Predict Abundance and Species Richness of Birds and Beetles in Boreal Forest?

Directory of Open Access Journals (Sweden)

Eva Lindberg

2015-04-01

Full Text Available In managed landscapes, conservation planning requires effective methods to identify high-biodiversity areas. The objective of this study was to evaluate the potential of airborne laser scanning (ALS and forest estimates derived from satellite images extracted at two spatial scales for predicting the stand-scale abundance and species richness of birds and beetles in a managed boreal forest landscape. Multiple regression models based on forest data from a 50-m radius (i.e., corresponding to a homogenous forest stand had better explanatory power than those based on a 200-m radius (i.e., including also parts of adjacent stands. Bird abundance and species richness were best explained by the ALS variables “maximum vegetation height” and “vegetation cover between 0.5 and 3 m” (both positive. Flying beetle abundance and species richness, as well as epigaeic (i.e., ground-living beetle richness were best explained by a model including the ALS variable “maximum vegetation height” (positive and the satellite-derived variable “proportion of pine” (negative. Epigaeic beetle abundance was best explained by “maximum vegetation height” at 50 m (positive and “stem volume” at 200 m (positive. Our results show that forest estimates derived from satellite images and ALS data provide complementary information for explaining forest biodiversity patterns. We conclude that these types of remote sensing data may provide an efficient tool for conservation planning in managed boreal landscapes.

Global analysis of approaches for deriving total water storage changes from GRACE satellites and implications for groundwater storage change estimation

Science.gov (United States)

Long, D.; Scanlon, B. R.; Longuevergne, L.; Chen, X.

2015-12-01

Increasing interest in use of GRACE satellites and a variety of new products to monitor changes in total water storage (TWS) underscores the need to assess the reliability of output from different products. The objective of this study was to assess skills and uncertainties of different approaches for processing GRACE data to restore signal losses caused by spatial filtering based on analysis of 1°×1° grid scale data and basin scale data in 60 river basins globally. Results indicate that scaling factors from six land surface models (LSMs), including four models from GLDAS-1 (Noah 2.7, Mosaic, VIC, and CLM 2.0), CLM 4.0, and WGHM, are similar over most humid, sub-humid, and high-latitude regions but can differ by up to 100% over arid and semi-arid basins and areas with intensive irrigation. Large differences in TWS anomalies from three processing approaches (scaling factor, additive, and multiplicative corrections) were found in arid and semi-arid regions, areas with intensive irrigation, and relatively small basins (e.g., ≤ 200,000 km2). Furthermore, TWS anomaly products from gridded data with CLM4.0 scaling factors and the additive correction approach more closely agree with WGHM output than the multiplicative correction approach. Estimation of groundwater storage changes using GRACE satellites requires caution in selecting an appropriate approach for restoring TWS changes. A priori ground-based data used in forward modeling can provide a powerful tool for explaining the distribution of signal gains or losses caused by low-pass filtering in specific regions of interest and should be very useful for more reliable estimation of groundwater storage changes using GRACE satellites.

A cloud-ozone data product from Aura OMI and MLS satellite measurements

Directory of Open Access Journals (Sweden)

J. R. Ziemke

2017-11-01

Full Text Available Ozone within deep convective clouds is controlled by several factors involving photochemical reactions and transport. Gas-phase photochemical reactions and heterogeneous surface chemical reactions involving ice, water particles, and aerosols inside the clouds all contribute to the distribution and net production and loss of ozone. Ozone in clouds is also dependent on convective transport that carries low-troposphere/boundary-layer ozone and ozone precursors upward into the clouds. Characterizing ozone in thick clouds is an important step for quantifying relationships of ozone with tropospheric H2O, OH production, and cloud microphysics/transport properties. Although measuring ozone in deep convective clouds from either aircraft or balloon ozonesondes is largely impossible due to extreme meteorological conditions associated with these clouds, it is possible to estimate ozone in thick clouds using backscattered solar UV radiation measured by satellite instruments. Our study combines Aura Ozone Monitoring Instrument (OMI and Microwave Limb Sounder (MLS satellite measurements to generate a new research product of monthly-mean ozone concentrations in deep convective clouds between 30° S and 30° N for October 2004–April 2016. These measurements represent mean ozone concentration primarily in the upper levels of thick clouds and reveal key features of cloud ozone including: persistent low ozone concentrations in the tropical Pacific of  ∼ 10 ppbv or less; concentrations of up to 60 pphv or greater over landmass regions of South America, southern Africa, Australia, and India/east Asia; connections with tropical ENSO events; and intraseasonal/Madden–Julian oscillation variability. Analysis of OMI aerosol measurements suggests a cause and effect relation between boundary-layer pollution and elevated ozone inside thick clouds over landmass regions including southern Africa and India/east Asia.

A high-resolution and observationally constrained OMI NO2 satellite retrieval

International Nuclear Information System (INIS)

Goldberg, Daniel L.; Lamsal, Lok N.; Loughner, Christopher P.

2017-01-01

Here, this work presents a new high-resolution NO 2 dataset derived from the NASA Ozone Monitoring Instrument (OMI) NO 2 version 3.0 retrieval that can be used to estimate surface-level concentrations. The standard NASA product uses NO 2 vertical profile shape factors from a 1.25° × 1° (~110 km × 110 km) resolution Global Model Initiative (GMI) model simulation to calculate air mass factors, a critical value used to determine observed tropospheric NO 2 vertical columns. To better estimate vertical profile shape factors, we use a high-resolution (1.33 km × 1.33 km) Community Multi-scale Air Quality (CMAQ) model simulation constrained by in situ aircraft observations to recalculate tropospheric air mass factors and tropospheric NO 2 vertical columns during summertime in the eastern US. In this new product, OMI NO 2 tropospheric columns increase by up to 160% in city centers and decrease by 20–50 % in the rural areas outside of urban areas when compared to the operational NASA product. Our new product shows much better agreement with the Pandora NO 2 and Airborne Compact Atmospheric Mapper (ACAM) NO 2 spectrometer measurements acquired during the DISCOVER-AQ Maryland field campaign. Furthermore, the correlation between our satellite product and EPA NO 2 monitors in urban areas has improved dramatically: r 2 = 0.60 in the new product vs. r 2 = 0.39 in the operational product, signifying that this new product is a better indicator of surface concentrations than the operational product. Our work emphasizes the need to use both high-resolution and high-fidelity models in order to recalculate satellite data in areas with large spatial heterogeneities in NO x emissions. Although the current work is focused on the eastern US, the methodology developed in this work can be applied to other world regions to produce high-quality region-specific NO 2 satellite retrievals.

Assessment of GPM and TRMM Multi-Satellite Precipitation Products in Streamflow Simulations in a Data-Sparse Mountainous Watershed in Myanmar

Directory of Open Access Journals (Sweden)

Fei Yuan

2017-03-01

Full Text Available Satellite precipitation products from the Global Precipitation Measurement (GPM mission and its predecessor the Tropical Rainfall Measuring Mission (TRMM are a critical data source for hydrological applications in ungauged basins. This study conducted an initial and early evaluation of the performance of the Integrated Multi-satellite Retrievals for GPM (IMERG final run and the TRMM Multi-satellite Precipitation Analysis 3B42V7 precipitation products, and their feasibility in streamflow simulations in the Chindwin River basin, Myanmar, from April 2014 to December 2015 was also assessed. Results show that, although IMERG and 3B42V7 can potentially capture the spatiotemporal patterns of historical precipitation, the two products contain considerable errors. Compared with 3B42V7, no significant improvements were found in IMERG. Moreover, 3B42V7 outperformed IMERG at daily and monthly scales and in heavy rain detections at four out of five gauges. The large errors in IMERG and 3B42V7 distinctly propagated to streamflow simulations via the Xinanjiang hydrological model, with a significant underestimation of total runoff and high flows. The bias correction of the satellite precipitation effectively improved the streamflow simulations. The 3B42V7-based streamflow simulations performed better than the gauge-based simulations. In general, IMERG and 3B42V7 are feasible for use in streamflow simulations in the study area, although 3B42V7 is better suited than IMERG.

Spatiotemporal fusion of multiple-satellite aerosol optical depth (AOD) products using Bayesian maximum entropy method

Science.gov (United States)

Tang, Qingxin; Bo, Yanchen; Zhu, Yuxin

2016-04-01

Merging multisensor aerosol optical depth (AOD) products is an effective way to produce more spatiotemporally complete and accurate AOD products. A spatiotemporal statistical data fusion framework based on a Bayesian maximum entropy (BME) method was developed for merging satellite AOD products in East Asia. The advantages of the presented merging framework are that it not only utilizes the spatiotemporal autocorrelations but also explicitly incorporates the uncertainties of the AOD products being merged. The satellite AOD products used for merging are the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Level-2 AOD products (MOD04_L2) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Deep Blue Level 2 AOD products (SWDB_L2). The results show that the average completeness of the merged AOD data is 95.2%,which is significantly superior to the completeness of MOD04_L2 (22.9%) and SWDB_L2 (20.2%). By comparing the merged AOD to the Aerosol Robotic Network AOD records, the results show that the correlation coefficient (0.75), root-mean-square error (0.29), and mean bias (0.068) of the merged AOD are close to those (the correlation coefficient (0.82), root-mean-square error (0.19), and mean bias (0.059)) of the MODIS AOD. In the regions where both MODIS and SeaWiFS have valid observations, the accuracy of the merged AOD is higher than those of MODIS and SeaWiFS AODs. Even in regions where both MODIS and SeaWiFS AODs are missing, the accuracy of the merged AOD is also close to the accuracy of the regions where both MODIS and SeaWiFS have valid observations.

Cross-validation Methodology between Ground and GPM Satellite-based Radar Rainfall Product over Dallas-Fort Worth (DFW) Metroplex

Science.gov (United States)

Chen, H.; Chandrasekar, V.; Biswas, S.

2015-12-01

Over the past two decades, a large number of rainfall products have been developed based on satellite, radar, and/or rain gauge observations. However, to produce optimal rainfall estimation for a given region is still challenging due to the space time variability of rainfall at many scales and the spatial and temporal sampling difference of different rainfall instruments. In order to produce high-resolution rainfall products for urban flash flood applications and improve the weather sensing capability in urban environment, the center for Collaborative Adaptive Sensing of the Atmosphere (CASA), in collaboration with National Weather Service (NWS) and North Central Texas Council of Governments (NCTCOG), has developed an urban radar remote sensing network in DFW Metroplex. DFW is the largest inland metropolitan area in the U.S., that experiences a wide range of natural weather hazards such as flash flood and hailstorms. The DFW urban remote sensing network, centered by the deployment of eight dual-polarization X-band radars and a NWS WSR-88DP radar, is expected to provide impacts-based warning and forecasts for benefit of the public safety and economy. High-resolution quantitative precipitation estimation (QPE) is one of the major goals of the development of this urban test bed. In addition to ground radar-based rainfall estimation, satellite-based rainfall products for this area are also of interest for this study. Typical example is the rainfall rate product produced by the Dual-frequency Precipitation Radar (DPR) onboard Global Precipitation Measurement (GPM) Core Observatory satellite. Therefore, cross-comparison between ground and space-based rainfall estimation is critical to building an optimal regional rainfall system, which can take advantages of the sampling differences of different sensors. This paper presents the real-time high-resolution QPE system developed for DFW urban radar network, which is based upon the combination of S-band WSR-88DP and X

Analysis of Satellite AIS Data to Derive Weather Judging Criteria for Voyage Route Selection

Directory of Open Access Journals (Sweden)

Michio Fujii

2017-06-01

Full Text Available The operational limitations are discussed at the IMO as a part of the second generation intact stability criteria. Since it is a first attempt to introduce operational efforts into safety regulations, comprehensive discussions are necessary to realize practically acceptable ones. Therefore this study investigates actual navigation routes of container ships and pure car carriers in the trans-North Pacific Ocean in winter, because they are prone to suffer significant parametric roll which is one of stability failure modes. Firstly, interviews are made to shipmasters who have experiences to have operated the subject ships to identify major elements for route selection in the North Pacific Ocean. Secondly, sufficient number of actual navigation records is collected from Satellite AIS data to derive the weather criteria for the route selection in severe weather condition. Finally, shipmaster’s on-board decision-making criteria are discussed by analysing the ship tracking data and weather data.

Evaluation of altimetry-derived surface current products using Lagrangian drifter trajectories in the eastern Gulf of Mexico

Science.gov (United States)

Liu, Yonggang; Weisberg, Robert H.; Vignudelli, Stefano; Mitchum, Gary T.

2014-05-01

Lagrangian particle trajectory models based on several altimetry-derived surface current products are used to hindcast the drifter trajectories observed in the eastern Gulf of Mexico during May to August 2010 (the Deepwater Horizon oil spill incident). The performances of the trajectory models are gauged in terms of Lagrangian separation distances (d) and a nondimensional skill score (s), respectively. A series of numerical experiments show that these altimetry-based trajectory models have about the same performance, with a certain improvement by adding surface wind Ekman components, especially over the shelf region. However, their hindcast skills are slightly better than those of the data assimilative numerical model output. After 3 days' simulation the altimetry-based trajectory models have mean d values of 75-83 and 34-42 km (s values of 0.49-0.51 and 0.35-0.43) in the Gulf of Mexico deep water area and on the West Florida Continental Shelf, respectively. These satellite altimetry data products are useful for providing essential information on ocean surface currents of use in water property transports, offshore oil and gas operations, hazardous spill mitigation, search and rescue, etc.

Cryosphere Monitoring from Satellites and Aircrafts

DEFF Research Database (Denmark)

Nilsson, Johan

The cryosphere is collective term for all the components containing frozen water on the Earth’s surface. These components are highly sensitive to changes in the air temperature and precipitation, and hence to climate change. The major components of frozen water in the cryosphere are the ice sheet...... is of vital importance to gain insight into the behaviour of these systems and how they affect the global sea level. Satellite altimetry has for the last two decades been used to monitor the changes of the worlds ice sheets, allowing for the determination of their mass balance. In recent years this has been...... terrain in the Arctic region. The results from this validation study was then inter-compared with results derived from the ESA L2 baseline-B product to judge the quality of both products. From this inter-comparison it was shown that the new processing chains, developed in this thesis, performed better...

Satellite-derived temperature data for monitoring water status in a floodplain forest of the Upper Sabine River, Texas

Science.gov (United States)

Lemon, Mary Grace T.; Allen, Scott T.; Edwards, Brandon L.; King, Sammy L.; Keim, Richard F.

2016-01-01

Decreased water availability due to hydrologic modifications, groundwater withdrawal, and climate change threaten bottomland hardwood (BLH) forest communities. We used satellite-derived (MODIS) land-surface temperature (LST) data to investigate spatial heterogeneity of canopy temperature (an indicator of plant-water status) in a floodplain forest of the upper Sabine River for 2008–2014. High LST pixels were generally further from the river and at higher topographic locations, indicating lower water-availability. Increasing rainfall-derived soil moisture corresponded with decreased heterogeneity of LST between pixels but there was weaker association between Sabine River stage and heterogeneity. Stronger dependence of LST convergence on rainfall rather than river flow suggests that some regions are less hydrologically connected to the river, and vegetation may rely on local precipitation and other contributions to the riparian aquifer to replenish soil moisture. Observed LST variations associated with hydrology encourage further investigation of the utility of this approach for monitoring forest stress, especially with considerations of climate change and continued river management.

Towards a Quantitative Use of Satellite Remote Sensing in Crop Growth Models for Large Scale Agricultural Production Estimate (Invited)

Science.gov (United States)

Defourny, P.

2013-12-01

The development of better agricultural monitoring capabilities is clearly considered as a critical step for strengthening food production information and market transparency thanks to timely information about crop status, crop area and yield forecasts. The documentation of global production will contribute to tackle price volatility by allowing local, national and international operators to make decisions and anticipate market trends with reduced uncertainty. Several operational agricultural monitoring systems are currently operating at national and international scales. Most are based on the methods derived from the pioneering experiences completed some decades ago, and use remote sensing to qualitatively compare one year to the others to estimate the risks of deviation from a normal year. The GEO Agricultural Monitoring Community of Practice described the current monitoring capabilities at the national and global levels. An overall diagram summarized the diverse relationships between satellite EO and agriculture information. There is now a large gap between the current operational large scale systems and the scientific state of the art in crop remote sensing, probably because the latter mainly focused on local studies. The poor availability of suitable in-situ and satellite data over extended areas hampers large scale demonstrations preventing the much needed up scaling research effort. For the cropland extent, this paper reports a recent research achievement using the full ENVISAT MERIS 300 m archive in the context of the ESA Climate Change Initiative. A flexible combination of classification methods depending to the region of the world allows mapping the land cover as well as the global croplands at 300 m for the period 2008 2012. This wall to wall product is then compared with regards to the FP 7-Geoland 2 results obtained using as Landsat-based sampling strategy over the IGADD countries. On the other hand, the vegetation indices and the biophysical variables

Impact of Satellite Remote Sensing Data on Simulations of ...

Science.gov (United States)

We estimated surface salinity flux and solar penetration from satellite data, and performed model simulations to examine the impact of including the satellite estimates on temperature, salinity, and dissolved oxygen distributions on the Louisiana continental shelf (LCS) near the annual hypoxic zone. Rainfall data from the Tropical Rainfall Measurement Mission (TRMM) were used for the salinity flux, and the diffuse attenuation coefficient (Kd) from Moderate Resolution Imaging Spectroradiometer (MODIS) were used for solar penetration. Improvements in the model results in comparison with in situ observations occurred when the two types of satellite data were included. Without inclusion of the satellite-derived surface salinity flux, realistic monthly variability in the model salinity fields was observed, but important inter-annual variability wasmissed. Without inclusion of the satellite-derived light attenuation, model bottom water temperatures were too high nearshore due to excessive penetration of solar irradiance. In general, these salinity and temperature errors led to model stratification that was too weak, and the model failed to capture observed spatial and temporal variability in water-column vertical stratification. Inclusion of the satellite data improved temperature and salinity predictions and the vertical stratification was strengthened, which improved prediction of bottom-water dissolved oxygen. The model-predicted area of bottom-water hypoxia on the

Nutritional value of milk and meat products derived from cloning.

Science.gov (United States)

Tomé, Daniel; Dubarry, Michel; Fromentin, Gilles

2004-01-01

The development and use of milk and meat products derived from cloning depends on their safety and on the nutritional advantages they can confer to the products as perceived by consumers. The development of such products thus implies (i) to demonstrate their safety and security, (ii) to show that their nutritional value is equivalent to the traditional products, and (iii) to identify the conditions under which cloning could allow additional nutritional and health benefit in comparison to traditional products for the consumers. Both milk and meat products are a source of high quality protein as determined from their protein content and essential amino acid profile. Milk is a source of calcium, phosphorus, zinc, magnesium and vitamin B2 and B12. Meat is a source of iron, zinc and vitamin B12. An important issue regarding the nutritional quality of meat and milk is the level and quality of fat which usually present a high content in saturated fat and some modification of the fat fraction could improve the nutritional quality of the products. The role of the dietary proteins as potential allergens has to be taken into account and an important aspect regarding this question is to evaluate whether the cloning does not produce the appearance of novel allergenic structures. The presence of bio-activities associated to specific components of milk (lactoferrin, immunoglobulins, growth factors, anti-microbial components) also represents a promising development. Preliminary results obtained in rats fed cow's milk or meat-based diets prepared from control animals or from animals derived from cloning did not show any difference between control and cloning-derived products.

A multifaceted approach to understanding dynamic urban processes: satellites, surveys, and censuses.

Science.gov (United States)

Jones, B.; Balk, D.; Montgomery, M.; Liu, Z.

2014-12-01

Urbanization will arguably be the most significant demographic trend of the 21st century, particularly in fast-growing regions of the developing world. Characterizing urbanization in a spatial context, however, is a difficult task given only the moderate resolution data provided by traditional sources of demographic data (i.e., censuses and surveys). Using a sample of five world "mega-cities" we demonstrate how new satellite data products and new analysis of existing satellite data, when combined with new applications of census and survey microdata, can reveal more about cities and urbanization in combination than either data type can by itself. In addition to the partially modelled Global Urban-Rural Mapping Project (GRUMP) urban extents we consider four sources of remotely sensed data that can be used to estimate urban extents; the NOAA Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) intercallibrated nighttime lights time series data, the newer NOAA Visible Infrared Imager Radiometer Suite (VIIRS) nighttime lights data, the German Aerospace Center (DLR) radar satellite data, and Dense Sampling Method (DSM) analysis of the NASA scatterometer data. Demographic data come from national censuses and/or georeferenced survey data from the Demographic & Health Survey (DHS) program. We overlay demographic and remotely sensed data (e.g., Figs 1, 2) to address two questions; (1) how well do satellite derived measures of urban intensity correlate with demographic measures, and (2) how well are temporal changes in the data correlated. Using spatial regression techniques, we then estimate statistical relationships (controlling for influences such as elevation, coastal proximity, and economic development) between the remotely sensed and demographic data and test the ability of each to predict the other. Satellite derived imagery help us to better understand the evolution of the built environment and urban form, while the underlying demographic

Validation of the CHIRPS Satellite Rainfall Estimates over Eastern of Africa

Science.gov (United States)

Dinku, T.; Funk, C. C.; Tadesse, T.; Ceccato, P.

2017-12-01

Long and temporally consistent rainfall time series are essential in climate analyses and applications. Rainfall data from station observations are inadequate over many parts of the world due to sparse or non-existent observation networks, or limited reporting of gauge observations. As a result, satellite rainfall estimates have been used as an alternative or as a supplement to station observations. However, many satellite-based rainfall products with long time series suffer from coarse spatial and temporal resolutions and inhomogeneities caused by variations in satellite inputs. There are some satellite rainfall products with reasonably consistent time series, but they are often limited to specific geographic areas. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite-based rainfall products with relatively high spatial and temporal resolutions and quasi-global coverage. In this study, CHIRP and CHIRPS were evaluated over East Africa at daily, dekadal (10-day) and monthly time scales. The evaluation was done by comparing the satellite products with rain gauge data from about 1200 stations. The is unprecedented number of validation stations for this region covering. The results provide a unique region-wide understanding of how satellite products perform over different climatic/geographic (low lands, mountainous regions, and coastal) regions. The CHIRP and CHIRPS products were also compared with two similar satellite rainfall products: the African Rainfall Climatology version 2 (ARC2) and the latest release of the Tropical Applications of Meteorology using Satellite data (TAMSAT). The results show that both CHIRP and CHIRPS products are significantly better than ARC2 with higher skill and low or no bias. These products were also found to be slightly better than the latest version of the TAMSAT product. A comparison was also done between the latest release of the TAMSAT product

Improved estimates of net primary productivity from MODIS satellite data at regional and local scales

Science.gov (United States)

Yude Pan; Richard Birdsey; John Hom; Kevin McCullough; Kenneth Clark

2006-01-01

We compared estimates of net primary production (NPP) from the MODIS satellite with estimates from a forest ecosystem process model (PnET-CN) and forest inventory and analysis (FIA) data for forest types of the mid-Atlantic region of the United States. The regional means were similar for the three methods and for the dominant oak? hickory forests in the region. However...

A hydro-optical model for deriving water quality variables from satellite images (HydroSat): A case study of the Nile River demonstrating the future Sentinel-2 capabilities

NARCIS (Netherlands)

Salama, M.; Radwan, M.; van der Velde, R.

2012-01-01

This paper describes a hydro-optical model for deriving water quality variables from satellite images, hereafter HydroSat. HydroSat corrects images for atmospheric interferences and simultaneously retrieves water quality variables. An application of HydroSat to Landsat Enhanced Thematic Mapper (ETM)

Production of Fatty Acid-Derived Valuable Chemicals in Synthetic Microbes

International Nuclear Information System (INIS)

Yu, Ai-Qun; Pratomo Juwono, Nina Kurniasih; Leong, Susanna Su Jan; Chang, Matthew Wook

2014-01-01

Fatty acid derivatives, such as hydroxy fatty acids, fatty alcohols, fatty acid methyl/ethyl esters, and fatty alka(e)nes, have a wide range of industrial applications including plastics, lubricants, and fuels. Currently, these chemicals are obtained mainly through chemical synthesis, which is complex and costly, and their availability from natural biological sources is extremely limited. Metabolic engineering of microorganisms has provided a platform for effective production of these valuable biochemicals. Notably, synthetic biology-based metabolic engineering strategies have been extensively applied to refactor microorganisms for improved biochemical production. Here, we reviewed: (i) the current status of metabolic engineering of microbes that produce fatty acid-derived valuable chemicals, and (ii) the recent progress of synthetic biology approaches that assist metabolic engineering, such as mRNA secondary structure engineering, sensor-regulator system, regulatable expression system, ultrasensitive input/output control system, and computer science-based design of complex gene circuits. Furthermore, key challenges and strategies were discussed. Finally, we concluded that synthetic biology provides useful metabolic engineering strategies for economically viable production of fatty acid-derived valuable chemicals in engineered microbes.

Production of Fatty Acid-Derived Valuable Chemicals in Synthetic Microbes

Energy Technology Data Exchange (ETDEWEB)

Yu, Ai-Qun; Pratomo Juwono, Nina Kurniasih [Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (Singapore); Synthetic Biology Research Program, National University of Singapore, Singapore (Singapore); Leong, Susanna Su Jan [Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (Singapore); Synthetic Biology Research Program, National University of Singapore, Singapore (Singapore); Singapore Institute of Technology, Singapore (Singapore); Chang, Matthew Wook, E-mail: bchcmw@nus.edu.sg [Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (Singapore); Synthetic Biology Research Program, National University of Singapore, Singapore (Singapore)

2014-12-23

Fatty acid derivatives, such as hydroxy fatty acids, fatty alcohols, fatty acid methyl/ethyl esters, and fatty alka(e)nes, have a wide range of industrial applications including plastics, lubricants, and fuels. Currently, these chemicals are obtained mainly through chemical synthesis, which is complex and costly, and their availability from natural biological sources is extremely limited. Metabolic engineering of microorganisms has provided a platform for effective production of these valuable biochemicals. Notably, synthetic biology-based metabolic engineering strategies have been extensively applied to refactor microorganisms for improved biochemical production. Here, we reviewed: (i) the current status of metabolic engineering of microbes that produce fatty acid-derived valuable chemicals, and (ii) the recent progress of synthetic biology approaches that assist metabolic engineering, such as mRNA secondary structure engineering, sensor-regulator system, regulatable expression system, ultrasensitive input/output control system, and computer science-based design of complex gene circuits. Furthermore, key challenges and strategies were discussed. Finally, we concluded that synthetic biology provides useful metabolic engineering strategies for economically viable production of fatty acid-derived valuable chemicals in engineered microbes.

Evaluating water storage variations in the MENA region using GRACE satellite data

KAUST Repository

Lopez, Oliver

2013-12-01

Terrestrial water storage (TWS) variations over large river basins can be derived from temporal gravity field variations observed by the Gravity Recovery and Climate Experiment (GRACE) satellites. These signals are useful for determining accurate estimates of water storage and fluxes over areas covering a minimum of 150,000 km2 (length scales of a few hundred kilometers) and thus prove to be a valuable tool for regional water resources management, particularly for areas with a lack of in-situ data availability or inconsistent monitoring, such as the Middle East and North Africa (MENA) region. This already stressed arid region is particularly vulnerable to climate change and overdraft of its non-renewable freshwater sources, and thus direction in managing its resources is a valuable aid. An inter-comparison of different GRACE-derived TWS products was done in order to provide a quantitative assessment on their uncertainty and their utility for diagnosing spatio-temporal variability in water storage over the MENA region. Different processing approaches for the inter-satellite tracking data from the GRACE mission have resulted in the development of TWS products, with resolutions in time from 10 days to 1 month and in space from 0.5 to 1 degree global gridded data, while some of them use input from land surface models in order to restore the original signal amplitudes. These processing differences and the difficulties in recovering the mass change signals over arid regions will be addressed. Output from the different products will be evaluated and compared over basins inside the MENA region, and compared to output from land surface models.

Evaluating Water Storage Variations in the MENA region using GRACE Satellite Data

Science.gov (United States)

Lopez, O.; Houborg, R.; McCabe, M. F.

2013-12-01

Terrestrial water storage (TWS) variations over large river basins can be derived from temporal gravity field variations observed by the Gravity Recovery and Climate Experiment (GRACE) satellites. These signals are useful for determining accurate estimates of water storage and fluxes over areas covering a minimum of 150,000 km2 (length scales of a few hundred kilometers) and thus prove to be a valuable tool for regional water resources management, particularly for areas with a lack of in-situ data availability or inconsistent monitoring, such as the Middle East and North Africa (MENA) region. This already stressed arid region is particularly vulnerable to climate change and overdraft of its non-renewable freshwater sources, and thus direction in managing its resources is a valuable aid. An inter-comparison of different GRACE-derived TWS products was done in order to provide a quantitative assessment on their uncertainty and their utility for diagnosing spatio-temporal variability in water storage over the MENA region. Different processing approaches for the inter-satellite tracking data from the GRACE mission have resulted in the development of TWS products, with resolutions in time from 10 days to 1 month and in space from 0.5 to 1 degree global gridded data, while some of them use input from land surface models in order to restore the original signal amplitudes. These processing differences and the difficulties in recovering the mass change signals over arid regions will be addressed. Output from the different products will be evaluated and compared over basins inside the MENA region, and compared to output from land surface models.

Online Tools for Uncovering Data Quality (DQ) Issues in Satellite-Based Global Precipitation Products

Science.gov (United States)

Liu, Zhong; Heo, Gil

2015-01-01

Data quality (DQ) has many attributes or facets (i.e., errors, biases, systematic differences, uncertainties, benchmark, false trends, false alarm ratio, etc.)Sources can be complicated (measurements, environmental conditions, surface types, algorithms, etc.) and difficult to be identified especially for multi-sensor and multi-satellite products with bias correction (TMPA, IMERG, etc.) How to obtain DQ info fast and easily, especially quantified info in ROI Existing parameters (random error), literature, DIY, etc.How to apply the knowledge in research and applications.Here, we focus on online systems for integration of products and parameters, visualization and analysis as well as investigation and extraction of DQ information.

Trustworthy Variant Derivation with Translation Validation for Safety Critical Product Lines

DEFF Research Database (Denmark)

Iosif-Lazăr, Alexandru Florin; Wasowski, Andrzej

2016-01-01

Software product line (SPL) engineering facilitates development of entire families of software products with systematic reuse. Model driven SPLs use models in the design and development process. In the safety critical domain, validation of models and testing of code increases the quality...... of the products altogether. However, to maintain this trustworthiness it is necessary to know that the SPL tools, which manipulate models and code to derive concrete product variants, do not introduce errors in the process. We propose a general technique of checking correctness of product derivation tools through...... translation validation. We demonstrate it using Featherweight VML—a core language for separate variability modeling relying on a single kind of variation point to define transformations of artifacts seen as object models. We use Featherweight VML with its semantics as a correctness specification...

Comparison between satellite precipitation product and observation rain gauges in the Red-Thai Binh River Basin

Science.gov (United States)

Lakshmi, V.; Le, M. H.; Sutton, J. R. P.; Bui, D. D.; Bolten, J. D.

2017-12-01

The Red-ThaiBinh River is the second largest river in Vietnam in terms of economic impact and is home to around 29 million people. The river has been facing challenges for water resources allocation, which require reliable and routine hydrological assessments. However, hydrological analysis is difficult due to insufficient spatial coverage by rain gauges. Satellite-based precipitation estimates are a promising alternative with high-resolution in both time and space. This study aims at investigating the uncertainties in satellite-based precipitation product TRMM 3B42 v7.0 by comparing them against in-situ measurements over the Red-ThaiBinh River basin. The TRMM 3B42 v7.0 are assessed in terms of seasonal, monthly and daily variations over a 17-year period (1998 - 2014). Preliminary results indicate that at a daily scale, except for low Mean Bias Error (MBE), satellite based rainfall product has weak relationship with ground observation data, indicating by average performance of 0.326 and -0.485 for correlation coefficient and Nash Sutcliffe Efficiency (NSE), respectively. At monthly scale, we observe that the TRMM 3B42 v7.0 has higher correlation with the correlation increased significantly to 0.863 and NSE of 0.522. By analyzing wet season (May - October) and dry season (November - April) separately we find that the correlation between the TRMM 3B42 v7.0 with ground observations were higher for wet season than the dry season.

Influence of tides in viscoelastic bodies of planet and satellite on the satellite's orbital motion

Science.gov (United States)

Emelyanov, N. V.

2018-06-01

The problem of influence of tidal friction in both planetary and satellite bodies upon satellite's orbital motion is considered. Using the differential equations in satellite's rectangular planetocentric coordinates, the differential equations describing the changes in semimajor axis and eccentricity are derived. The equations in rectangular coordinates were taken from earlier works on the problem. The calcultations carried out for a number of test examples prove that the averaged solutions of equations in coordinates and precise solutions of averaged equations in the Keplerian elements are identical. For the problem of tides raised on planet's body, it was found that, if satellite's mean motion n is equal to 11/18 Ω, where Ω is the planet's angular rotation rate, the orbital eccentricity does not change. This conclusion is in agreement with the results of other authors. It was also found that there is essential discrepancy between the equations in the elements obtained in this paper and analogous equations published by earlier researchers.

Improving Satellite Retrieved Infrared Sea Surface Temperatures in Aerosol-Contaminated Regions

Science.gov (United States)

Luo, B.; Minnett, P. J.; Szczodrak, G.; Kilpatrick, K. A.

2017-12-01

Infrared satellite observations of sea surface temperature (SST) have become essential for many applications in meteorology, climatology, and oceanography. Applications often require high accuracy SST data: for climate research and monitoring an absolute uncertainty of 0.1K and stability of better than 0.04K per decade are required. Tropospheric aerosol concentrations increase infrared signal attenuation and prevent the retrieval of accurate satellite SST. We compare satellite-derived skin SST with measurements from the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) deployed on ships during the Aerosols and Ocean Science Expeditions (AEROSE) and with quality-controlled drifter temperatures. After match-up with in-situ SST and filtering of cloud contaminated data, the results indicate that SST retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) aboard the Terra and Aqua satellites have negative (cool) biases compared to shipboard radiometric measurements. There is also a pronounced negative bias in the Saharan outflow area that can introduce SST errors >1 K at aerosol optical depths > 0.5. In this study, we present a new method to derive night-time Saharan Dust Index (SDI) algorithms based on simulated brightness temperatures at infrared wavelengths of 3.9, 10.8 and 12.0 μm, derived using RTTOV. We derived correction coefficients for Aqua MODIS measurements by regression of the SST errors against the SDI. The biases and standard deviations are reduced by 0.25K and 0.19K after the SDI correction. The goal of this study is to understand better the characteristics and physical mechanisms of aerosol effects on satellite retrieved infrared SST, as well as to derive empirical formulae for improved accuracies in aerosol-contaminated regions.

A global reference database from very high resolution commercial satellite data and methodology for application to Landsat derived 30 m continuous field tree cover data

Science.gov (United States)

Pengra, Bruce; Long, Jordan; Dahal, Devendra; Stehman, Stephen V.; Loveland, Thomas R.

2015-01-01

The methodology for selection, creation, and application of a global remote sensing validation dataset using high resolution commercial satellite data is presented. High resolution data are obtained for a stratified random sample of 500 primary sampling units (5 km  ×  5 km sample blocks), where the stratification based on Köppen climate classes is used to distribute the sample globally among biomes. The high resolution data are classified to categorical land cover maps using an analyst mediated classification workflow. Our initial application of these data is to evaluate a global 30 m Landsat-derived, continuous field tree cover product. For this application, the categorical reference classification produced at 2 m resolution is converted to percent tree cover per 30 m pixel (secondary sampling unit)for comparison to Landsat-derived estimates of tree cover. We provide example results (based on a subsample of 25 sample blocks in South America) illustrating basic analyses of agreement that can be produced from these reference data. Commercial high resolution data availability and data quality are shown to provide a viable means of validating continuous field tree cover. When completed, the reference classifications for the full sample of 500 blocks will be released for public use.

Validation of satellite SAR offshore wind speed maps to in-situ data, microscale and mesoscale model results

DEFF Research Database (Denmark)

Hasager, C.B.; Astrup, Poul; Barthelmie, R.J.

2002-01-01

the assumption of no error in the SAR wind speed maps and for an uncertainty of ± 10% at a confidence level of 90%. Around 100 satellite SAR scenes may be available for some sites on Earth but far few at other sites. Currently the numberof available satellite SAR scenes is increasing rapidly with ERS-2, RADARSAT......A validation study has been performed in order to investigate the precision and accuracy of the satellite-derived ERS-2 SAR wind products in offshore regions. The overall project goal is to develop a method for utilizing the satellite wind speed maps foroffshore wind resources, e.g. in future...... band in which the SAR wind speed observations have a strong negative bias. The bathymetry of Horns Rev combined with tidal currents give rise to bias in the SAR wind speed maps near areas of shallow, complex bottom topography in some cases. Atotal of 16 cases were analyzed for Horns Rev. For Maddalena...

Satellite Communications for ATM

Science.gov (United States)

Shamma, Mohammed A.

2003-01-01

This presentation is an overview on Satellite Communication for the Aeronautical Telecommunication Management (ATM) research. Satellite Communications are being considered by the FAA and NASA as a possible alternative to the present and future ground systems supporting Air Traffic Communications. The international Civil Aviation Organization (ICAO) have in place Standards and Recommended Practices (SARPS) for the Aeronautical Mobile Satellite Services (AMSS) which is mainly derived from the pre-existing Inmarsat service that has been in service since the 1980s. The Working Group A of the Aeronautical Mobile Communication Panel of ICAO has also been investigating SARPS for what is called the Next Generation Satellite Service (NGSS) which conforms less to the Inmarsat based architecture and explores wider options in terms of satellite architectures. Several designs are being proposed by Firms such as Boeing, ESA, NASA that are geared toward full or secondary usage of satellite communications for ATM. Satellite communications for ATM can serve several purposes ranging from primary usage where ground services would play a minimal backup role, to an integrated solution where it will be used to cover services, or areas that are less likely to be supported by the proposed and existing ground infrastructure. Such Integrated roles can include usage of satellite communications for oceanic and remote land areas for example. It also can include relieving the capacity of the ground network by providing broadcast based services of Traffic Information Services messages (TIS-B), or Flight Information Services (FIS-B) which can take a significant portion of the ground system capacity. Additionally, satellite communication can play a backup role to support any needs for ground replacement, or additional needed capacity even after the new digital systems are in place. The additional bandwidth that can be provided via satellite communications can also open the door for many new

Large divergence of satellite and Earth system model estimates of global terrestrial CO2 fertilization

Science.gov (United States)

Smith, W. Kolby; Reed, Sasha C.; Cleveland, Cory C.; Ballantyne, Ashley P; Anderegg, William R. L.; Wieder, William R.; Liu, Yi Y; Running, Steven W.

2015-01-01

Atmospheric mass balance analyses suggest that terrestrial carbon (C) storage is increasing, partially abating the atmospheric [CO2] growth rate, although the continued strength of this important ecosystem service remains uncertain. Some evidence suggests that these increases will persist owing to positive responses of vegetation growth (net primary productivity; NPP) to rising atmospheric [CO2] (that is, ‘CO2 fertilization’). Here, we present a new satellite-derived global terrestrial NPP data set, which shows a significant increase in NPP from 1982 to 2011. However, comparison against Earth system model (ESM) NPP estimates reveals a significant divergence, with satellite-derived increases (2.8 ± 1.50%) less than half of ESM-derived increases (7.6  ±  1.67%) over the 30-year period. By isolating the CO2 fertilization effect in each NPP time series and comparing it against a synthesis of available free-air CO2 enrichment data, we provide evidence that much of the discrepancy may be due to an over-sensitivity of ESMs to atmospheric [CO2], potentially reflecting an under-representation of climatic feedbacks and/or a lack of representation of nutrient constraints. Our understanding of CO2 fertilization effects on NPP needs rapid improvement to enable more accurate projections of future C cycle–climate feedbacks; we contend that better integration of modelling, satellite and experimental approaches offers a promising way forward.

Methods for conversion of lignocellulosic-derived products to transportation fuel precursors

Science.gov (United States)

Lilga, Michael A.; Padmaperuma, Asanga B.

2017-10-03

Methods are disclosed for converting a biomass-derived product containing levulinic acid and/or gamma-valerolactone to a transportation fuel precursor product containing diesel like hydrocarbons. These methods are expected to produce fuel products at a reduced cost relative to conventional approaches.

Mapping Global Ocean Surface Albedo from Satellite Observations: Models, Algorithms, and Datasets

Science.gov (United States)

Li, X.; Fan, X.; Yan, H.; Li, A.; Wang, M.; Qu, Y.

2018-04-01

Ocean surface albedo (OSA) is one of the important parameters in surface radiation budget (SRB). It is usually considered as a controlling factor of the heat exchange among the atmosphere and ocean. The temporal and spatial dynamics of OSA determine the energy absorption of upper level ocean water, and have influences on the oceanic currents, atmospheric circulations, and transportation of material and energy of hydrosphere. Therefore, various parameterizations and models have been developed for describing the dynamics of OSA. However, it has been demonstrated that the currently available OSA datasets cannot full fill the requirement of global climate change studies. In this study, we present a literature review on mapping global OSA from satellite observations. The models (parameterizations, the coupled ocean-atmosphere radiative transfer (COART), and the three component ocean water albedo (TCOWA)), algorithms (the estimation method based on reanalysis data, and the direct-estimation algorithm), and datasets (the cloud, albedo and radiation (CLARA) surface albedo product, dataset derived by the TCOWA model, and the global land surface satellite (GLASS) phase-2 surface broadband albedo product) of OSA have been discussed, separately.

Water Level Fluctuations in the Congo Basin Derived from ENVISAT Satellite Altimetry

Directory of Open Access Journals (Sweden)

Mélanie Becker

2014-09-01

Full Text Available In the Congo Basin, the elevated vulnerability of food security and the water supply implies that sustainable development strategies must incorporate the effects of climate change on hydrological regimes. However, the lack of observational hydro-climatic data over the past decades strongly limits the number of studies investigating the effects of climate change in the Congo Basin. We present the largest altimetry-based dataset of water levels ever constituted over the entire Congo Basin. This dataset of water levels illuminates the hydrological regimes of various tributaries of the Congo River. A total of 140 water level time series are extracted using ENVISAT altimetry over the period of 2003 to 2009. To improve the understanding of the physical phenomena dominating the region, we perform a K-means cluster analysis of the altimeter-derived river level height variations to identify groups of hydrologically similar catchments. This analysis reveals nine distinct hydrological regions. The proposed regionalization scheme is validated and therefore considered reliable for estimating monthly water level variations in the Congo Basin. This result confirms the potential of satellite altimetry in monitoring spatio-temporal water level variations as a promising and unprecedented means for improved representation of the hydrologic characteristics in large ungauged river basins.

Seeing is believing I: The use of thermal sensing from satellite imagery to predict crop yield

International Nuclear Information System (INIS)

Potgieter A B; Rodriguez D; Power B; Mclean J; Davis P

2014-01-01

Volatility in crop production has been part of the Australian environment since cropping began with the arrival of the first European settlers. Climate variability is the main factor affecting crop production at national, state and local scales. At field level spatial patterns on yield production are also determined by spatially changing soil properties in interaction with seasonal climate conditions and weather patterns at critical stages in the crop development. Here we used a combination of field level weather records, canopy characteristics, and satellite information to determine the spatial performance of a large field of wheat. The main objective of this research is to determine the ability of remote sensing technologies to capture yield losses due to water stress at the canopy level. The yield, canopy characteristics (i.e. canopy temperature and ground cover) and seasonal conditions of a field of wheat (∼1400ha) (-29.402° South and 149.508°, New South Wales, Australia) were continuously monitored during the winter of 2011. Weather and crop variables were continuously monitored by installing three automatic weather stations in a transect covering different positions and soils in the landscape. Weather variables included rainfall, minimum and maximum temperatures and relative humidity, and crop characteristics included ground cover and canopy temperature. Satellite imagery Landsat TM 5 and 7 was collected at five different stages in the crop cycle. Weather variables and crop characteristics were used to calculate a crop stress index (CSI) at point and field scale (39 fields). Field data was used to validate a spatial satellite image derived index. Spatial yield data was downloaded from the harvester at the different locations in the field. We used the thermal band (land surface temperature, LST) and enhanced vegetation index (EVI) bands from the MODIS (250 m for visible bands and 1km for thermal band) and a derived EVI from Landsat TM 7 (25 m for visible

Validation of vertical profile from atmosphere using ATOVS products and its impact over Indian region.

Science.gov (United States)

Mahandru, Riddhi; Kumar, Adarsh; Mitra, Ashim kumar

This research paper summarizes the validation of atmospheric vertical profile using NOAA(National Oceanic and Atmospheric Administration)/ MetOp satellite derived data over India with radiosonde observations over a span of 8 months. NOAA's International Advanced Television and Infrared Observations satellite Vertical Sounder (ATOVS) processing package (IAPP) obtains temperature and moisture profiles in different pressure levels ranging from 1000hpa to 10hpa from real time direct broadcast (DB) receiving system installed at India Meteorological department. Different pressure levels were substituted to the same pressure levels for calculations of standard deviation, bias and RMSE (root mean square error) The sounder derived products like Total precipitable water vapor (TPW) and Lifting index(LI) from NOAA Satellite was also validated with radiosonde data which provided significant results for weather forecasting. The validation shows that the sounder provides unique information about the state of atmosphere and monitoring the convective environment for severe weather forecasting In addition to this, case study on severe weather events was analyzed using ATOVS products.

Quad-Tree Visual-Calculus Analysis of Satellite Coverage

Science.gov (United States)

Lo, Martin W.; Hockney, George; Kwan, Bruce

2003-01-01

An improved method of analysis of coverage of areas of the Earth by a constellation of radio-communication or scientific-observation satellites has been developed. This method is intended to supplant an older method in which the global-coverage-analysis problem is solved from a ground-to-satellite perspective. The present method provides for rapid and efficient analysis. This method is derived from a satellite-to-ground perspective and involves a unique combination of two techniques for multiresolution representation of map features on the surface of a sphere.

A review of the PERSIANN family global satellite precipitation data products

Science.gov (United States)

Nguyen, P.; Ombadi, M.; Ashouri, H.; Thorstensen, A.; Hsu, K. L.; Braithwaite, D.; Sorooshian, S.; William, L.

2017-12-01

Precipitation is an integral part of the hydrologic cycle and plays an important role in the water and energy balance of the Earth. Careful and consistent observation of precipitation is important for several reasons. Over the last two decades, the PERSIANN system of precipitation products have been developed at the Center for Hydrometeorology and Remote Sensing (CHRS) at the University of California, Irvine in collaboration with NASA, NOAA and the UNESCO G-WADI program. The PERSIANN family includes three main satellite-based precipitation estimation products namely PERSIANN, PERSIANN-CCS, and PERSIANN-CDR. They are accessible through several web-based interfaces maintained by CHRS to serve the needs of researchers, professionals and general public. These interfaces are CHRS iRain, Data Portal and RainSphere, which can be accessed at http://irain.eng.uci.edu, http://chrsdata.eng.uci.edu, and http://rainsphere.eng.uci.edu respectively and can be used for visualization, analysis or download of the data. The main objective of this presentation is to provide a concise and clear summary of the similarities and differences between the three products in terms of attributes and algorithm structure. Moreover, the presentation aims to provide an evaluation of the performance of the products over the Contiguous United States (CONUS) using Climate Prediction Center (CPC) precipitation dataset as a baseline of comparison. Also, an assessment of the behavior of PERSIANN family products over the globe (60°S - 60°N) is performed.

Biorefineries for the production of top building block chemicals and their derivatives

DEFF Research Database (Denmark)

Choi, Sol; Song, Chan Woo; Shin, Jae Ho

2015-01-01

commercialized or are close to commercialization. In this paper, we review the current status of biorefinery development for the production of these platform chemicals and their derivatives. In addition, current technological advances on industrial strain development for the production of platform chemicals...... years after its announcement, many studies have been performed for the development of efficient technologies for the bio-based production of these chemicals and derivatives. Now, ten chemicals among these top 12 chemicals, excluding the l-aspartic acid and 3-hydroxybutyrolactone, have already been...

A Regional-Scale Assessment of Satellite Derived Precipitable Water Vapor Across The Amazon Basin

Science.gov (United States)

DeLiberty, Tracy; Callahan, John; Guillory, Anthony R.; Jedlovec, Gary

2000-01-01

Atmospheric water vapor is widely recognized as a key climate variable, linking an assortment of poorly understood and complex processes. It is a major element of the hydrological cycle and provides a mechanism for energy exchange among many of the Earth system components. Reducing uncertainty in our current knowledge of water vapor and its role in the climate system requires accurate measurement, improved modeling techniques, and long-term prediction. Satellites have the potential to satisfy these criteria, as well as provide high resolution measurements that are not available from conventional sources. The focus of this paper is to examine the temporal and mesoscale variations of satellite derived precipitable water vapor (PW) across the Amazon Basin. This region is pivotal in the functioning of the global climate system through its abundant release of latent heat associated with heavy precipitation events. In addition, anthropogenic deforestation and biomass burning activities in recent decades are altering the conditions of the atmosphere, especially in the planetary boundary layer. A physical split-window (PSW) algorithm estimates PW using images from the GOES satellites along with the NCEP/NCAR Reanalysis data that provides the first guess information. Retrievals are made at a three-hourly time step during daylight hours in the Amazon Basin and surrounding areas for the months of June and October in 1988 (dry year) and 1995 (wet year). Spatially continuous fields are generated 5 times daily at 12Z, 15Z, 18Z, 21Z, and 00Z. These fields are then averaged to create monthly and 3 hourly monthly grids. Overall, the PSW estimates PW reasonable well in the Amazon with MAE ranging from 3.0 - 9.0 mm and MAE/observed mean around 20% in comparison to radiosonde observations. The distribution of PW generally mimics that of precipitation. Maximum values (42 - 52 mm) are located in the Northwest whereas minimum values (18 - 27 mm) are found along Brazil's East coast. Aside

Real-Time Estimation of Volcanic ASH/SO2 Cloud Height from Combined Uv/ir Satellite Observations and Numerical Modeling

Science.gov (United States)

Vicente, Gilberto A.

An efficient iterative method has been developed to estimate the vertical profile of SO2 and ash clouds from volcanic eruptions by comparing near real-time satellite observations with numerical modeling outputs. The approach uses UV based SO2 concentration and IR based ash cloud images, the volcanic ash transport model PUFF and wind speed, height and directional information to find the best match between the simulated and the observed displays. The method is computationally fast and is being implemented for operational use at the NOAA Volcanic Ash Advisory Centers (VAACs) in Washington, DC, USA, to support the Federal Aviation Administration (FAA) effort to detect, track and measure volcanic ash cloud heights for air traffic safety and management. The presentation will show the methodology, results, statistical analysis and SO2 and Aerosol Index input products derived from the Ozone Monitoring Instrument (OMI) onboard the NASA EOS/Aura research satellite and from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument in the MetOp-A. The volcanic ash products are derived from AVHRR instruments in the NOAA POES-16, 17, 18, 19 as well as MetOp-A. The presentation will also show how a VAAC volcanic ash analyst interacts with the system providing initial condition inputs such as location and time of the volcanic eruption, followed by the automatic real-time tracking of all the satellite data available, subsequent activation of the iterative approach and the data/product delivery process in numerical and graphical format for operational applications.

Water resource monitoring systems and the role of satellite observations

Directory of Open Access Journals (Sweden)

A. I. J. M. van Dijk

2011-01-01

Full Text Available Spatial water resource monitoring systems (SWRMS can provide valuable information in support of water management, but current operational systems are few and provide only a subset of the information required. Necessary innovations include the explicit description of water redistribution and water use from river and groundwater systems, achieving greater spatial detail (particularly in key features such as irrigated areas and wetlands, and improving accuracy as assessed against hydrometric observations, as well as assimilating those observations. The Australian water resources assessment (AWRA system aims to achieve this by coupling landscape models with models describing surface water and groundwater dynamics and water use. A review of operational and research applications demonstrates that satellite observations can improve accuracy and spatial detail in hydrological model estimation. All operational systems use dynamic forcing, land cover classifications and a priori parameterisation of vegetation dynamics that are partially or wholly derived from remote sensing. Satellite observations are used to varying degrees in model evaluation and data assimilation. The utility of satellite observations through data assimilation can vary as a function of dominant hydrological processes. Opportunities for improvement are identified, including the development of more accurate and higher spatial and temporal resolution precipitation products, and the use of a greater range of remote sensing products in a priori model parameter estimation, model evaluation and data assimilation. Operational challenges include the continuity of research satellite missions and data services, and the need to find computationally-efficient data assimilation techniques. The successful use of observations critically depends on the availability of detailed information on observational error and understanding of the relationship between remotely-sensed and model variables, as

Seasonal and nonseasonal variability of satellite-derived chlorophyll and colored dissolved organic matter concentration in the California Current

Science.gov (United States)

Kahru, Mati; Mitchell, B. Greg

2001-02-01

Time series of surface chlorophyll a concentration (Chl) and colored dissolved organic matter (CDOM) derived from the Ocean Color and Temperature Sensor and Sea-Viewing Wide Field-of-View Sensor were evaluated for the California Current area using regional algorithms. Satellite data composited for 8-day periods provide the ability to describe large-scale changes in surface parameters. These changes are difficult to detect based on in situ observations alone that suffer from undersampling the large temporal and spatial variability, especially in Chl. We detected no significant bias in satellite Chl estimates compared with ship-based measurements. The variability in CDOM concentration was significantly smaller than that in Chl, both spatially and temporally. While being subject to large interannual and short-term variations, offshore waters (100-1000 km from the shore) have an annual cycle of Chl and CDOM with a maximum in winter-spring (December-March) and a minimum in late summer. For inshore waters the maximum is more likely in spring (April-May). We detect significant increase in both Chl and CDOM off central and southern California during the La Niña year of 1999. The trend of increasing Chl and CDOM from October 1996 to June 2000 is statistically significant in many areas.

Assimilation of GMS-5 satellite winds using nudging method with MM5

Science.gov (United States)

Gao, Shanhong; Wu, Zengmao; Yang, Bo

2006-09-01

With the aid of Meteorological Information Composite and Processing System (MICAPS), satellite wind vectors derived from the Geostationary Meteorological Statellite-5 (GMS-5) and retrieved by National Satellite Meteorology Center of China (NSMC) can be obtained. Based on the nudging method built in the fifth-generation Mesoscale Model (MM5) of Pennsylvania State University and National Center for Atmospheric Research, a data preprocessor is developed to convert these satellite wind vectors to those with specified format required in MM5. To examine the data preprocessor and evaluate the impact of satellite winds from GMS-5 on MM5 simulations, a series of numerical experimental forecasts consisting of four typhoon cases in 2002 are designed and implemented. The results show that the preprocessor can process satellite winds smoothly and MM5 model runs successfully with a little extra computational load during ingesting these winds, and that assimilation of satellite winds by MM5 nudging method can obviously improve typhoon track forecast but contributes a little to typhoon intensity forecast. The impact of the satellite winds depends heavily upon whether the typhoon bogussing scheme in MM5 was turned on or not. The data preprocessor developed in this paper not only can treat GMS-5 satellite winds but also has capability with little modification to process derived winds from other geostationary satellites.

Natural product derived insecticides: discovery and development of spinetoram.

Science.gov (United States)

Galm, Ute; Sparks, Thomas C

2016-03-01

This review highlights the importance of natural product research and industrial microbiology for product development in the agricultural industry, based on examples from Dow AgroSciences. It provides an overview of the discovery and development of spinetoram, a semisynthetic insecticide derived by a combination of a genetic block in a specific O-methylation of the rhamnose moiety of spinosad coupled with neural network-based QSAR and synthetic chemistry. It also emphasizes the key role that new technologies and multidisciplinary approaches play in the development of current spinetoram production strains.

Resonant satellite transitions in argon

International Nuclear Information System (INIS)

Samson, J.A.R.; Lee Eunmee; Chung, Y.

1990-01-01

The production of specific Ar + satellite states has been studied with synchrotron radiation at wavelengths between 300 and 350 A with an effective energy resolution of 20 meV. The specific states studied were the ( 3 P)4p( 2 P 3/2 ), ( 1 D)4p( 2 F 7/2 ), and ( 1 D)4p( 2 P 1/2 ) states. The fluorescent radiation emitted from these excited ionic states was measured at 4766, 4611, and 4133 A by the use of narrow band interference filters. The variation of the fluorescence intensity was measured as a function of wavelength. This provided a measure of the relative cross section for production of the satellite states. Each satellite state was found to be completely dominated by autoionization of the neutral doubly excited states (3s 2 3p 4 )nl, n'l' found in this spectral region. (orig.)

Satellite Derived Water Quality Observations Are Related to River Discharge and Nitrogen Loads in Pensacola Bay, Florida

Directory of Open Access Journals (Sweden)

John C. Lehrter

2017-09-01

Full Text Available Relationships between satellite-derived water quality variables and river discharges, concentrations and loads of nutrients, organic carbon, and sediments were investigated over a 9-year period (2003–2011 in Pensacola Bay, Florida, USA. These analyses were conducted to better understand which river forcing factors were the primary drivers of estuarine variability in several water quality variables. Remote sensing reflectance time-series data were retrieved from the MEdium Resolution Imaging Spectrometer (MERIS and used to calculate monthly and annual estuarine time-series of chlorophyll a (Chla, colored dissolved organic matter (CDOM, and total suspended sediments (TSS. Monthly MERIS Chla varied from 2.0 mg m−3 in the lower region of the bay to 17.2 mg m−3 in the upper bay. MERIS CDOM and TSS exhibited similar patterns with ranges of 0.51–2.67 (m−1 and 0.11–8.9 (g m−3. Variations in the MERIS-derived monthly and annual Chla, CDOM, and TSS time-series were significantly related to monthly and annual river discharge and loads of nitrogen, organic carbon, and suspended sediments from the Escambia and Yellow rivers. Multiple regression models based on river loads (independent variables and MERIS Chla, CDOM, or TSS (dependent variables explained significant fractions of the variability (up to 62% at monthly and annual scales. The most significant independent variables in the regressions were river nitrogen loads, which were associated with increased MERIS Chla, CDOM, and TSS concentrations, and river suspended sediment loads, which were associated with decreased concentrations. In contrast, MERIS water quality variations were not significantly related to river total phosphorus loads. The spatially synoptic, nine-year satellite record expanded upon the spatial extent of past field studies to reveal previously unseen system-wide responses to river discharge and loading variation. The results indicated that variations in Pensacola Bay Chla

Kojyl cinnamate ester derivatives promote adiponectin production during adipogenesis in human adipose tissue-derived mesenchymal stem cells.

Science.gov (United States)

Rho, Ho Sik; Hong, Soo Hyun; Park, Jongho; Jung, Hyo-Il; Park, Young-Ho; Lee, John Hwan; Shin, Song Seok; Noh, Minsoo

2014-05-01

The subcutaneous fat tissue mass gradually decreases with age, and its regulation is a strategy to develop anti-aging compounds to ameliorate the photo-aging of human skin. The adipogenesis of human adipose tissue-mesenchymal stem cells (hAT-MSCs) can be used as a model to discover novel anti-aging compounds. Cinnamomum cassia methanol extracts were identified as adipogenesis-promoting agents by natural product library screening. Cinnamates, the major chemical components of Cinnamomum cassia extracts, promoted adipogenesis in hAT-MSCs. We synthesized kojyl cinnamate ester derivatives to improve the pharmacological activity of cinnamates. Structure-activity studies of kojyl cinnamate derivatives showed that both the α,β-unsaturated carbonyl ester group and the kojic acid moiety play core roles in promoting adiponectin production during adipogenesis in hAT-MSCs. We conclude that kojyl cinnamate ester derivatives provide novel pharmacophores that can regulate adipogenesis in hAT-MSCs. Copyright © 2014 Elsevier Ltd. All rights reserved.

Regionally and seasonally differentiated primary production in the North Atlantic

Science.gov (United States)

Sathyendranath, Shubha; Longhurst, Alan; Caverhill, Carla M.; Platt, Trevor

1995-10-01

A bio-geochemical classification of the N. Atlantic Basin is presented according to which the basin is first divided into four primary algal domains: Polar, West-Wind, Trades and Coastal. These are in turn sub-divided into smaller provinces. The classification is based on differences in the physical environment which are likely to influence regional algal dynamics. The seasonally-differentiated parameters of the photosynthesis-light curve ( P-I curve) and parameters that define the vertical structure in chlorophyll profile are then established for each province, based on an analysis of an archive of over 6000 chlorophyll profiles, and over 1800 P-I curves. These are then combined with satellite-derived chlorophyll data for the N. Atlantic, and information on cloud cover, to compute primary production at the annual scale. using a model that computes spectral transmission of light underwater, and spectral, photosynthetic response of phytoplankton to available light. The results are compared with earlier, satellite-derived, estimates of basin-scale primary production.

Temporal variatiions of Sea ice cover in the Baltic Sea derived from operational sea ice products used in NWP.

Science.gov (United States)

Lange, Martin; Paul, Gerhard; Potthast, Roland

2014-05-01

Sea ice cover is a crucial parameter for surface fluxes of heat and moisture over water areas. The isolating effect and the much higher albedo strongly reduces the turbulent exchange of heat and moisture from the surface to the atmosphere and allows for cold and dry air mass flow with strong impact on the stability of the whole boundary layer and consequently cloud formation as well as precipitation in the downstream regions. Numerical weather centers as, ECMWF, MetoFrance or DWD use external products to initialize SST and sea ice cover in their NWP models. To the knowledge of the author there are mainly two global sea ice products well established with operational availability, one from NOAA NCEP that combines measurements with satellite data, and the other from OSI-SAF derived from SSMI/S sensors. The latter one is used in the Ostia product. DWD additionally uses a regional product for the Baltic Sea provided by the national center for shipping and hydrografie which combines observations from ships (and icebreakers) for the German part of the Baltic Sea and model analysis from the hydrodynamic HIROMB model of the Swedish meteorological service for the rest of the domain. The temporal evolution of the three different products are compared for a cold period in Februar 2012. Goods and bads will be presented and suggestions for a harmonization of strong day to day jumps over large areas are suggested.

A satellite digital controller or 'play that PID tune again, Sam'. [Position, Integral, Derivative feedback control algorithm for design strategy

Science.gov (United States)

Seltzer, S. M.

1976-01-01

The problem discussed is to design a digital controller for a typical satellite. The controlled plant is considered to be a rigid body acting in a plane. The controller is assumed to be a digital computer which, when combined with the proposed control algorithm, can be represented as a sampled-data system. The objective is to present a design strategy and technique for selecting numerical values for the control gains (assuming position, integral, and derivative feedback) and the sample rate. The technique is based on the parameter plane method and requires that the system be amenable to z-transform analysis.

Near Real Time Operational Satellite Ocean Color Products From NOAA OSPO CoastWatch Okeanos System:: Status and Challenges

Science.gov (United States)

Banghua Yan, B.

2016-02-01

Near real-time (NRT) ocean color (OC) satellite operation products are generated and distributed in NOAA Okeanos Operational Product System, by using the CWAPS including the Multi-Sensor Level (MSL) 12 and the chlorophyll-a frontal algorithms. Current OC operational products include daily chlorophyll concentration (anomaly), water turbidity, remote sensing reflectance and chlorophyll frontal products from Moderate-resolution Imaging Spectroradiometer (MODIS)/Aqua. The products have been widely applied to USA local and state ecosystem research, ecosystem observations, and fisheries managements for coastal and regional forecasting of ocean water quality, phytoplankton concentrations, and primary production. Users of the products have the National Ocean Service, National Marine Fisheries Service, National Weather Service, and Oceanic and Atmospheric Research. Recently, the OC products are being extended to S-NPP VIIRS to provide global NRT ocean color products to user community suh as National Weatrher Service for application for Global Data Assimilation System and Real-Time Ocean Forecast System. However, there remain some challenges in application of the products due to certain product quality and coverage issues. Recent efforts were made to provide a comprehensive web-based Quality Assurance (QA) tool for monitoring OC products quality in near real time mode, referring to http://www.ospo.noaa.gov/Products/ocean/color_new/color.htm. The new QA monitoring tool includes but not limited to the following advanced features applicable for MODIS/Aqua and NPP/VIIRS OC products: 1) Monitoring product quality in NRT mode; 2) Monitoring the availability and quality of OC products with time; 3) Detecting anomalous OC products due to low valid pixels and other quality issues. As an example, potential application and challenges of the ocean color products to oceanic oil spill detection are investigated. It is thus expected that the Okeanos ocean color operational system in

Cost function approach for estimating derived demand for composite wood products

Science.gov (United States)

T. C. Marcin

1991-01-01

A cost function approach was examined for using the concept of duality between production and input factor demands. A translog cost function was used to represent residential construction costs and derived conditional factor demand equations. Alternative models were derived from the translog cost function by imposing parameter restrictions.

BMP signaling regulates satellite cell-dependent postnatal muscle growth.

Science.gov (United States)

Stantzou, Amalia; Schirwis, Elija; Swist, Sandra; Alonso-Martin, Sonia; Polydorou, Ioanna; Zarrouki, Faouzi; Mouisel, Etienne; Beley, Cyriaque; Julien, Anaïs; Le Grand, Fabien; Garcia, Luis; Colnot, Céline; Birchmeier, Carmen; Braun, Thomas; Schuelke, Markus; Relaix, Frédéric; Amthor, Helge

2017-08-01

Postnatal growth of skeletal muscle largely depends on the expansion and differentiation of resident stem cells, the so-called satellite cells. Here, we demonstrate that postnatal satellite cells express components of the bone morphogenetic protein (BMP) signaling machinery. Overexpression of noggin in postnatal mice (to antagonize BMP ligands), satellite cell-specific knockout of Alk3 (the gene encoding the BMP transmembrane receptor) or overexpression of inhibitory SMAD6 decreased satellite cell proliferation and accretion during myofiber growth, and ultimately retarded muscle growth. Moreover, reduced BMP signaling diminished the adult satellite cell pool. Abrogation of BMP signaling in satellite cell-derived primary myoblasts strongly diminished cell proliferation and upregulated the expression of cell cycle inhibitors p21 and p57 In conclusion, these results show that BMP signaling defines postnatal muscle development by regulating satellite cell-dependent myofiber growth and the generation of the adult muscle stem cell pool. © 2017. Published by The Company of Biologists Ltd.

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors.

Science.gov (United States)

Lange, Maximilian; Dechant, Benjamin; Rebmann, Corinna; Vohland, Michael; Cuntz, Matthias; Doktor, Daniel

2017-08-11

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure.

SAMIRA - SAtellite based Monitoring Initiative for Regional Air quality

Science.gov (United States)

Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nicolae, Doina; Stachlewska, Iwona; Zehner, Claus

2016-04-01

Here, we present a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellites, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. Despite considerable improvements in the past decades, Europe is still far from achieving levels of air quality that do not pose unacceptable hazards to humans and the environment. Main concerns in Europe are exceedances of particulate matter (PM), ground-level ozone, benzo(a)pyrene (BaP) and nitrogen dioxide (NO2). While overall sulfur dioxide (SO2) emissions have decreased in recent years, regional concentrations can still be high in some areas. The objectives of SAMIRA are to improve algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from SEVIRI, and to develop robust methods for deriving column- and near-surface PM maps for the study area by combining satellite AOD with information from regional models. The benefit to existing monitoring networks (in situ, models, satellite) by combining these datasets using data fusion methods will be tested for satellite-based NO2, SO2, and PM/AOD. Furthermore, SAMIRA will test and apply techniques for downscaling air quality-related EO products to a spatial resolution that is more in line with what is generally required for studying urban and regional scale air quality. This will be demonstrated for a set of study sites that include the capitals of the four countries and the highly polluted areas along the border of Poland and the

Dispersion relation and relative intensity for double-plasmon satellites

International Nuclear Information System (INIS)

Srivastava, K.S.; Shiv Singh; Harsh, O.K.

1981-01-01

An expression for the dispersion relation and the relative intensity of double-plasmon oscillations and satellites has been derived by extending the dispersion relation and the extended Bohm and Pines Hamiltonian to second order. The calculated value of the relative intensity of the double-plasmon satellite for Be agrees fairly well with the value observed experimentally by other workers. (orig.)

Operational monitoring of turbidity in rivers: how satellites can contribute

Science.gov (United States)

Hucke, Dorothee; Hillebrand, Gudrun; Winterscheid, Axel; Kranz, Susanne; Baschek, Björn

2016-10-01

The applications of remote sensing in hydrology are diverse and offer significant benefits for water monitoring. Up to now, operational river monitoring and sediment management in Germany mainly rely on in-situ measurements and on results obtained from numerical modelling. Remote sensing by satellites has a great potential to supplement existing data with two-dimensional information on near-surface turbidity distributions at greater spatial scales than in-situ measurements can offer. Within the project WasMon-CT (WaterMonitoring-Chlorophyll/Turbidity), the Federal Institute of Hydrology (BfG) aims at the implementation of an operational monitoring of turbidity distributions based on satellite images (esp. Sentinel-2, Landsat7 and 8). Initially, selected federal inland and estuarine waterways will be addressed: Rhine, Elbe, Ems, Weser. WasMon-CT is funded within the German Copernicus activities. Within the project, a database of atmospherically corrected, geo-referenced turbidity data will be assembled. The collected corresponding meta-data will include aspects of satellite data as well as hydrological data, e.g. cloud cover and river run-off. Based on this catalogue of spatially linked meta-data, the satellite data will be selected by e.g. cloud cover or run-off. The permanently updated database will include past as well as recent satellite images. It is designed with a long-term perspective to optimize the existing in-situ measurement network, which will serve partly for calibration and partly as validation data set. The aim is to extend, but not to substitute, the existing frequent point measurements with spatially extensive, satellite-derived data from the near surface part of the water column. Here, turbidity is used as proxy for corresponding suspended sediment concentrations. For this, the relationship between turbidity and suspended sediment concentrations will be investigated. Products as e.g. longitudinal profiles or virtual measurement stations will be

Comparison of Satellite-Derived Phytoplankton Size Classes Using In-Situ Measurements in the South China Sea

Directory of Open Access Journals (Sweden)

Shuibo Hu

2018-03-01

Full Text Available Ocean colour remote sensing is used as a tool to detect phytoplankton size classes (PSCs. In this study, the Medium Resolution Imaging Spectrometer (MERIS, Moderate Resolution Imaging Spectroradiometer (MODIS, and Sea-viewing Wide Field-of-view Sensor (SeaWiFS phytoplankton size classes (PSCs products were compared with in-situ High Performance Liquid Chromatography (HPLC data for the South China Sea (SCS, collected from August 2006 to September 2011. Four algorithms were evaluated to determine their ability to detect three phytoplankton size classes. Chlorophyll-a (Chl-a and absorption spectra of phytoplankton (aph(λ were also measured to help understand PSC’s algorithm performance. Results show that the three abundance-based approaches performed better than the inherent optical property (IOP-based approach in the SCS. The size detection of microplankton and picoplankton was generally better than that of nanoplankton. A three-component model was recommended to produce maps of surface PSCs in the SCS. For the IOP-based approach, satellite retrievals of inherent optical properties and the PSCs algorithm both have impacts on inversion accuracy. However, for abundance-based approaches, the selection of the PSCs algorithm seems to be more critical, owing to low uncertainty in satellite Chl-a input data

Biome-Scale Forest Properties in Amazonia Based on Field and Satellite Observations

Directory of Open Access Journals (Sweden)

Liana O. Anderson

2012-05-01

Full Text Available Amazonian forests are extremely heterogeneous at different spatial scales. This review intends to present the large-scale patterns of the ecosystem properties of Amazonia, and focuses on two parts of the main components of the net primary production: the long-lived carbon pools (wood and short-lived pools (leaves. First, the focus is on forest biophysical properties, and secondly, on the macro-scale leaf phenological patterns of these forests, looking at field measurements and bringing into discussion the recent findings derived from remote sensing dataset. Finally, I discuss the results of the three major droughts that hit Amazonia in the last 15 years. The panorama that emerges from this review suggests that slow growing forests in central and eastern Amazonia, where soils are poorer, have significantly higher above ground biomass and higher wood density, trees are higher and present lower proportions of large-leaved species than stands in northwest and southwest Amazonia. However, the opposite pattern is observed in relation to forest productivity and dynamism, which is higher in western Amazonia than in central and eastern forests. The spatial patterns on leaf phenology across Amazonia are less marked. Field data from different forest formations showed that new leaf production can be unrelated to climate seasonality, timed with radiation, timed with rainfall and/or river levels. Oppositely, satellite images exhibited a large-scale synchronized peak in new leaf production during the dry season. Satellite data and field measurements bring contrasting results for the 2005 drought. Discussions on data processing and filtering, aerosols effects and a combined analysis with field and satellite images are presented. It is suggested that to improve the understanding of the large-scale patterns on Amazonian forests, integrative analyses that combine new technologies in remote sensing and long-term field ecological data are imperative.

Evaluation of cloud properties in the NOAA/NCEP global forecast system using multiple satellite products

Energy Technology Data Exchange (ETDEWEB)

Yoo, Hyelim [University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States); Li, Zhanqing [University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States); Beijing Normal University, State Key Laboratory of Earth Surface Processes and Resource Ecology, GCESS, Beijing (China)

2012-12-15

Knowledge of cloud properties and their vertical structure is important for meteorological studies due to their impact on both the Earth's radiation budget and adiabatic heating within the atmosphere. The objective of this study is to evaluate bulk cloud properties and vertical distribution simulated by the US National Oceanic and Atmospheric Administration National Centers for Environmental Prediction Global Forecast System (GFS) using three global satellite products. Cloud variables evaluated include the occurrence and fraction of clouds in up to three layers, cloud optical depth, liquid water path, and ice water path. Cloud vertical structure data are retrieved from both active (CloudSat/CALIPSO) and passive sensors and are subsequently compared with GFS model results. In general, the GFS model captures the spatial patterns of hydrometeors reasonably well and follows the general features seen in satellite measurements, but large discrepancies exist in low-level cloud properties. More boundary layer clouds over the interior continents were generated by the GFS model whereas satellite retrievals showed more low-level clouds over oceans. Although the frequencies of global multi-layer clouds from observations are similar to those from the model, latitudinal variations show discrepancies in terms of structure and pattern. The modeled cloud optical depth over storm track region and subtropical region is less than that from the passive sensor and is overestimated for deep convective clouds. The distributions of ice water path (IWP) agree better with satellite observations than do liquid water path (LWP) distributions. Discrepancies in LWP/IWP distributions between observations and the model are attributed to differences in cloud water mixing ratio and mean relative humidity fields, which are major control variables determining the formation of clouds. (orig.)

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

The Satellite based Monitoring Initiative for Regional Air quality (SAMIRA): Project summary and first results

Science.gov (United States)

Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nemuc, Anca; Stachlewska, Iwona; Zehner, Claus

2017-04-01

We present a summary and some first results of a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellite instruments, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. The primary goal of SAMIRA is to demonstrate the usefulness of existing and future satellite products of air quality for improving monitoring and mapping of air pollution at the regional scale. A total of six core activities are being carried out in order to achieve this goal: Firstly, the project is developing and optimizing algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard of Meteosat Second Generation. As a second activity, SAMIRA aims to derive particulate matter (PM2.5) estimates from AOD data by developing robust algorithms for AOD-to-PM conversion with the support from model- and Lidar data. In a third activity, we evaluate the added value of satellite products of atmospheric composition for operational European-scale air quality mapping using geostatistics and auxiliary datasets. The additional benefit of satellite-based monitoring over existing monitoring techniques (in situ, models) is tested by combining these datasets using geostatistical methods and demonstrated for nitrogen dioxide (NO2), sulphur dioxide (SO2), and aerosol optical depth/particulate matter. As a fourth activity, the project is developing novel algorithms for downscaling coarse

Satellite-based detection of global urban heat-island temperature influence

Science.gov (United States)

Gallo, K.P.; Adegoke, Jimmy O.; Owen, T.W.; Elvidge, C.D.

2002-01-01

This study utilizes a satellite-based methodology to assess the urban heat-island influence during warm season months for over 4400 stations included in the Global Historical Climatology Network of climate stations. The methodology includes local and regional satellite retrievals of an indicator of the presence green photosynthetically active vegetation at and around the stations. The difference in local and regional samples of the normalized difference vegetation index (NDVI) is used to estimate differences in mean air temperature. Stations classified as urban averaged 0.90??C (N. Hemisphere) and 0.92??C (S. Hemisphere) warmer than the surrounding environment on the basis of the NDVI-derived temperature estimates. Additionally, stations classified as rural averaged 0.19??C (N. Hemisphere) and 0.16??C (S. Hemisphere) warmer than the surrounding environment. The NDVI-derived temperature estimates were found to be in reasonable agreement with temperature differences observed between climate stations. The results suggest that satellite-derived data sets can be used to estimate the urban heat-island temperature influence on a global basis and that a more detailed analysis of rural stations and their surrounding environment may be necessary to assure that temperature trends derived from assumed rural environments are not influenced by changes in land use/land cover. Copyright 2002 by the American Geophysical Union.

GOES-R: Satellite Insight

Science.gov (United States)

Fitzpatrick, Austin J.; Leon, Nancy J.; Novati, Alexander; Lincoln, Laura K.; Fisher, Diane K.

2012-01-01

GOES-R: Satellite Insight seeks to bring awareness of the GOES-R (Geostationary Operational Environmental Satellite -- R Series) satellite currently in development to an audience of all ages on the emerging medium of mobile games. The iPhone app (Satellite Insight) was created for the GOES-R Program. The app describes in simple terms the types of data products that can be produced from GOES-R measurements. The game is easy to learn, yet challenging for all audiences. It includes educational content and a path to further information about GOESR, its technology, and the benefits of the data it collects. The game features action-puzzle game play in which the player must prevent an overflow of data by matching falling blocks that represent different types of GOES-R data. The game adds more different types of data blocks over time, as long as the player can prevent a data overflow condition. Points are awarded for matches, and players can compete with themselves to beat their highest score.

Data Filtering and Assimilation of Satellite Derived Aerosol Optical Depth, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Satellite observations of the Earth often contain excessive noise and extensive data voids. Aerosol measurements, for instance, are obscured and contaminated by...

Estimating Net Primary Productivity Using Satellite and Ancillary Data

Science.gov (United States)

Choudhury, Bhaskar J.

2002-01-01

The net primary productivity (C) or the annual rate of carbon accumulation per unit ground area by terrestrial plant communities is the difference of gross photosynthesis (A(sub g)) and respiration (R) per unit ground area. Available field observations show that R is a large and variable fraction of A(sub g), although it is generally recognized that there are considerable difficulties in determining these fluxes, and thus pose challenge in assessing the accuracy. Further uncertainties arise in extrapolating field measurements (which are acquired over a hectare or so area) to regional scale. Here, an approach is presented for determining these fluxes using satellite and ancillary data to be representative of regional scale and allow assessment of interannual variation. A, has been expressed as the product of radiation use efficiency for gross photosynthesis by an unstressed canopy and intercepted photosynthetically active radiation, which is then adjusted for stresses due to soil water shortage and temperature away from optimum. R has been calculated as the sum of growth and maintenance components (respectively, R(sub g) and R(sub m)).The R(sub m) has been determined from nitrogen content of plant tissue per unit ground area, while R(sub g) has been obtained as a fraction of the difference of A(sub g) and R(sub m). Results for five consecutive years (1986-1990) are presented for the Amazon-Tocontins, Mississippi, and Ob River basins.

Synthesis of integrated primary production in the Arctic Ocean: II. In situ and remotely sensed estimates

Science.gov (United States)

Hill, Victoria J.; Matrai, Patricia A.; Olson, Elise; Suttles, S.; Steele, Mike; Codispoti, L. A.; Zimmerman, Richard C.

2013-03-01

Recent warming of surface waters, accompanied by reduced ice thickness and extent may have significant consequences for climate-driven changes of primary production (PP) in the Arctic Ocean (AO). However, it has been difficult to obtain a robust benchmark estimate of pan-Arctic PP necessary for evaluating change. This paper provides an estimate of pan-Arctic PP prior to significant warming from a synthetic analysis of the ARCSS-PP database of in situ measurements collected from 1954 to 2007 and estimates derived from satellite-based observations from 1998 to 2007. Vertical profiles of in situ chlorophyll a (Chl a) and PP revealed persistent subsurface peaks in biomass and PP throughout the AO during most of the summer period. This was contradictory with the commonly assumed exponential decrease in PP with depth on which prior satellite-derived estimates were based. As remotely sensed Chl a was not a good predictor of integrated water column Chl a, accurate satellite-based modeling of vertically integrated primary production (IPPsat), requires knowledge of the subsurface distribution of phytoplankton, coincident with the remotely sensed ocean color measurements. We developed an alternative approach to modeling PP from satellite observations by incorporating climatological information on the depths of the euphotic zone and the mixed layer that control the distribution of phytoplankton that significantly improved the fidelity of satellite derived PP to in situ observations. The annual IPP of the Arctic Ocean combining both in situ and satellite based estimates was calculated here to be a minimum of 466 ± 94 Tg C yr-1 and a maximum of 993 ± 94 Tg C yr-1, when corrected for subsurface production. Inflow shelf seas account for 75% of annual IPP, while the central basin and Beaufort northern sea were the regions with the lowest annual integrated productivity, due to persistently stratified, oligotrophic and ice-covered conditions. Although the expansion of summertime

Global Land Product Validation Protocols: An Initiative of the CEOS Working Group on Calibration and Validation to Evaluate Satellite-derived Essential Climate Variables

Science.gov (United States)