Copernicus Sentinel-2A Calibration and Products Validation Status
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Evaluation of Multiple Satellite Precipitation Products and Their Use in Hydrological Modelling Over the Luanhe River Basin, China
water Article Evaluation of Multiple Satellite Precipitation Products and Their Use in Hydrological Modelling over the Luanhe River Basin, China Peizhen Ren, Jianzhu Li *, Ping Feng, Yuangang Guo and Qiushuang Ma State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China; [email protected] (P.R.); [email protected] (P.F.); [email protected] (Y.G.); [email protected] (Q.M.) * Correspondence: [email protected]; Tel.: +86-136-2215-1558 Received: 26 March 2018; Accepted: 14 May 2018; Published: 24 May 2018 Abstract: Satellite precipitation products are unique sources of precipitation measurement that overcome spatial and temporal limitations, but their precision differs in specific catchments and climate zones. The purpose of this study is to evaluate the precipitation data derived from the Tropical Rainfall Measuring Mission (TRMM) 3B42RT, TRMM 3B42, and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) products over the Luanhe River basin, North China, from 2001 to 2012. Subsequently, we further explore the performances of these products in hydrological models using the Soil and Water Assessment Tool (SWAT) model with parameter and prediction uncertainty analyses. The results show that 3B42 and 3B42RT overestimate precipitation, with BIAs values of 20.17% and 62.80%, respectively, while PERSIANN underestimates precipitation with a BIAs of −6.38%. Overall, 3B42 has the smallest RMSE and MAE and the highest CC values on both daily and monthly scales and performs better than PERSIANN, followed by 3B42RT. The results of the hydrological evaluation suggest that precipitation is a critical source of uncertainty in the SWAT model, and different precipitation values result in parameter uncertainty, which propagates to prediction and water resource management uncertainties. -
Assessment of DUACS Sentinel-3A Altimetry Data in the Coastal Band of the European Seas: Comparison with Tide Gauge Measurements
remote sensing Article Assessment of DUACS Sentinel-3A Altimetry Data in the Coastal Band of the European Seas: Comparison with Tide Gauge Measurements Antonio Sánchez-Román 1,* , Ananda Pascual 1, Marie-Isabelle Pujol 2, Guillaume Taburet 2, Marta Marcos 1,3 and Yannice Faugère 2 1 Instituto Mediterráneo de Estudios Avanzados, C/Miquel Marquès, 21, 07190 Esporles, Spain; [email protected] (A.P.); [email protected] (M.M.) 2 Collecte Localisation Satellites, Parc Technologique du Canal, 8-10 rue Hermès, 31520 Ramonville-Saint-Agne, France; [email protected] (M.-I.P.); [email protected] (G.T.); [email protected] (Y.F.) 3 Departament de Física, Universitat de les Illes Balears, Cra. de Valldemossa, km 7.5, 07122 Palma, Spain * Correspondence: [email protected]; Tel.: +34-971-61-0906 Received: 26 October 2020; Accepted: 1 December 2020; Published: 4 December 2020 Abstract: The quality of the Data Unification and Altimeter Combination System (DUACS) Sentinel-3A altimeter data in the coastal area of the European seas is investigated through a comparison with in situ tide gauge measurements. The comparison was also conducted using altimetry data from Jason-3 for inter-comparison purposes. We found that Sentinel-3A improved the root mean square differences (RMSD) by 13% with respect to the Jason-3 mission. In addition, the variance in the differences between the two datasets was reduced by 25%. To explain the improved capture of Sea Level Anomaly by Sentinel-3A in the coastal band, the impact of the measurement noise on the synthetic aperture radar altimeter, the distance to the coast, and Long Wave Error correction applied on altimetry data were checked. -
Use of Simulated Reflectances Over Bright Desert
This article was downloaded by: [European Space Agency] On: 06 August 2014, At: 01:49 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Remote Sensing Letters Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/trsl20 Use of simulated reflectances over bright desert target as an absolute calibration reference Yves Govaerts a , Sindy Sterckx b & Stefan Adriaensen b a Govaerts Consulting , Brussels , Belgium b VITO, Centre for Remote Sensing and Earth Observation , Mol , Belgium Published online: 05 Feb 2013. To cite this article: Yves Govaerts , Sindy Sterckx & Stefan Adriaensen (2013) Use of simulated reflectances over bright desert target as an absolute calibration reference, Remote Sensing Letters, 4:6, 523-531, DOI: 10.1080/2150704X.2013.764026 To link to this article: http://dx.doi.org/10.1080/2150704X.2013.764026 PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. -
(CALIPSO-PARASOL) to Evaluate Tropical Cloud Properties in the LMDZ5 GCM D
Use of A-train satellite observations (CALIPSO-PARASOL) to evaluate tropical cloud properties in the LMDZ5 GCM D. Konsta, J.-L Dufresne, H Chepfer, A Idelkadi, G Cesana To cite this version: D. Konsta, J.-L Dufresne, H Chepfer, A Idelkadi, G Cesana. Use of A-train satellite observations (CALIPSO-PARASOL) to evaluate tropical cloud properties in the LMDZ5 GCM. Climate Dynamics, Springer Verlag, 2016, 47 (3), pp.1263-1284. 10.1007/s00382-015-2900-y. hal-01384436 HAL Id: hal-01384436 https://hal.archives-ouvertes.fr/hal-01384436 Submitted on 19 Oct 2016 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Manuscript Click here to download Manuscript: Use of A.pdf Click here to view linked References 1 Use of A-train satellite observations (CALIPSO-PARASOL) to evaluate tropical cloud properties in the LMDZ5 GCM D. Konsta, J.-L. Dufresne, H. Chepfer, A. Idelkadi, G.Cesana Laboratoire de Météorologie Dynamique (LMD/IPSL), Paris, France LMD/IPSL, UMR 8539, CNRS, Ecole Normale Supérieure, Université Pierre et Marie Curie, Ecole Polytechnique 2 3 4 5 1 6 Abstract 7 The evaluation of key cloud properties such as cloud cover, vertical profile and optical depth as well as the analysis of their 8 intercorrelation lead to greater confidence in climate change projections. -
Quickbird (Digital Globe) Scene Over Purdue Campus, 0.6M
QuickBird (Digital Globe) scene over Purdue campus, 0.6m GSD EROS‐A (ImageSat Int’l) scene over Purdue campus, GSD 2m Example of radiometry outside design limits – specular reflections from car windshields cause saturation and corruption of surrounding pixel data. Quickbird scene over Indianapolis qb_eph_short.txt satId = "QB02"; revNumber = 6984; stripId = "018F24"; type = "R"; version = "A"; generationTime = 2003-01-16T19:58:19.000000Z; startTime = 2003-01-15T16:30:25.613302Z; numPoints = 1536; timeInterval = 0.020; ephemList = ( ( 1, 408384.8844293977000000, -5163749.7635908620000000, 4436609.3965829052000000, -1239.4888535016760000, -5028.7879607649920000, -5720.9589832489428000, 0.0047847180901878, 0.0001857647065552, -0.0004488663884886, 0.0104184982125138, 0.0034951595622186, 0.0033038605521562), ( 2, 408360.0945991199100000, -5163850.3368877340000000, 4436494.9775853315000000, -1239.5137702293241000, -5028.6552395191966000, -5721.0706890709816000, 0.0047847180901878, 0.0001857647065552, -0.0004488663884886, 0.0104184982125138, 0.0034951595622186, 0.0033038605521562), ( 3, 408335.3042634393800000, -5163950.9075712236000000, 4436380.5563067487000000, -1239.5386860655569000, -5028.5225194834038000, -5721.1823886786469000, 0.0047847180901878, 0.0001857647065552, -0.0004488663884886, 0.0104184982125138, 0.0034951595622186, 0.0033038605521562), ( 4, 408310.5134390606000000, -5164051.4755447917000000, 4436266.1328579923000000, -1239.5636011559900000, -5028.3897989066654000, -5721.2940835802046000, 0.0047847180901878, 0.0001857647065552, -
Satellite Contributions to the Quantitative Characterization of Biomass Burning for Climate Modeling
Revised Version of Review Article for Atmospheric Research Satellite Contributions to the Quantitative Characterization of Biomass Burning for Climate Modeling Charles Ichoku, Ralph Kahn, Mian Chin Lab. for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA Corresponding Author: Dr. Charles Ichoku Climate & Radiation Branch, Code 613.2 NASA Goddard Space Flight Center Greenbelt, MD 20771, USA Phone : +1-301-614-6212 Fax : +1-301-614-6307 or +1-301-614-6420 Email : [email protected] Abstract Characterization of biomass burning from space has been the subject of an extensive body of literature published over the last few decades. Given the importance of this topic, we review how satellite observations contribute toward improving the representation of biomass burning quantitatively in climate and air-quality modeling and assessment. Satellite observations related to biomass burning may be classified into five broad categories: (i) active fire location and energy release, (ii) burned areas and burn severity, (iii) smoke plume physical disposition, (iv) aerosol distribution and particle properties, and (v) trace gas concentrations. Each of these categories involves multiple parameters used in characterizing specific aspects of the biomass-burning phenomenon. Some of the parameters are merely qualitative, whereas others are quantitative, although all are essential for improving the scientific understanding of the overall distribution (both spatial and temporal) and impacts of biomass burning. Some of the qualitative satellite datasets, such as fire locations, aerosol index, and gas estimates have fairly long-term records. They date back as far as the 1970s, following the launches of the DMSP, Landsat, NOAA, and Nimbus series of earth observation satellites. -
SOP 402 Sentinel Rodent Exposure
STANDARD OPERATING PROCEDURES DIVISION OF COMPARATIVE MEDICINE UNIVERSITY OF SOUTH FLORIDA SOP #402.6 Date Issued: 10/98 Date Revised: 5/17 Page 1 of 2 _____________________________________________________________________________________ TITLE: Sentinel Rodent Exposure SCOPE: All Authorized Personnel RESPONSIBILITY: Facility Manager and Technical Staff PURPOSE: Expose Sentinel Animals to Possible Pathogens in Animal Rooms I. PURPOSE 1. To outline the proper procedures for exposing sentinel rodents to soiled bedding. II. RESPONSIBILITY 1. The Facility Manager is responsible for ensuring: a. All animal care staff is adequately trained to perform the husbandry practices described. b. Implementation of the procedures described. 2. It is the responsibility of the animal care staff to read, understand, and follow the procedures outlined below. III. PROCEDURES 1. Sentinel rodents are pair housed in individual microisolator or ventilated cages, and are placed on each rack with like species with the exception of isolation housing rooms located in the Stabile Research Building (SRB) which will use pooled fecal samples in conjunction with collection of air handling unit/rack exhaust plenums sampling in lieu of dirty bedding sentinels. Racks housing mice on both sides will have 2 sentinel cages, one located on each side of the rack. 2. All racks must be labeled with the rack number (see SOP #410). In addition, racks housing mice on both sides must be labeled to identify one side as A and the opposite side as B. 3. To maximize exposure to potential infectious agents, upon arrival all sentinel rodents are housed solely on soiled bedding obtained from other cages on the same rack/side. Mouse sentinels in cage A are housed on the soiled bedding obtained from mice housed on rack-side A. -
PARASOL/GRASP No Location Specific Assumptions!!! Bodélé Depression AOD(565 Nm) Scale Height (M) Sensitivity Test for Aerosol Vertical Information Retrieval
GRASP aerosol from POLDER, 3MI, etc. polarimeters: towards estimation PM2.5 Oleg Dubovik1, Anton Lopatin1, Pavel Litvinov2, Yevgeny Derimian1, Tatyana Lapyonok1, Anton Lopatin1, David Fuertes2, Fabrice Ducos1, Xin Huang1, Benjamin Torres2, Michael Aspsetsberger3 and Christian Federspiel3 1 - Laboratoire d’Optique Atmosphérique, CNRS – Université Lille 1, France; 2 - GRASP-SAS, LOA, Université Lille 1, Villeneuve d’Ascq, France 3 - Catalysts GmbH, High Performance Computing, Linz, Austria AC-VC-13, Satellite aerosol for AQ, CNES, Paris, France, 29 June, 2017 Strength of GRASP algorithm concept: Based on accurate rigorous physics and math; Versatile (applicable to different sensors and retrieval of different parameters); Designed for multi-sensor retrieval (satellite, ground- based, airborne; polar and geostationary, ); Not-stagnant (different concept can be tested and compared within algorithm); Flexible: - generalizable (to IR, hypo spectral, to retrieval of gases and clouds, etc.); - or degradable (to less accurate but fast solution, LUT,…); Practical (rather fast and easy to use for given level fundamental complexity); Current and potential applications: Satellite instruments: polar: POLDER/PARASOL, 3MI/MetOp-SG, MERIS/Envisat, Sentinel-3 (OLCI, SLSTR), etc. geostationary: Sentinel-4, FCI, GOCO, Himawari-8, etc. Ground-based, airborne and laboratory instruments: passive: AERONET radiometers, sun/luna/star-photometers, etc. active: multi-wavelength elastic and non-elastic lidars; airborne and laboratory: polar nephelometers, Multi-instrument synergy: ground-based: lidar + radiometers + photometers , sun/luna/star-photometers, etc. satellite: OLCI + SLSTR, polarimeter + lidar (e.g. PARASOL + CALIPSO) Support: CNES (ТOSCA, RD), ANR (CaPPA), ESA (S-4, MERIS/S-3, GPGPU, CCI, CCI-2,CC+); EUMETSAT (3MI NRT), FP6-7 (ACTRIS 1-2), Catalysts GmbH, etc. -
Principles of Active Remote Sensing: Radar. Radar Sensing of Clouds and Precipitation. Objectives: 1
Lecture 13. Principles of active remote sensing: Radar. Radar sensing of clouds and precipitation. Objectives: 1. Radar basics. Main types of radars. 2. Basic antenna parameters. 3. Particle backscattering and radar equation. 4. Sensing precipitation and clouds with ground-based and space-borne radars (weather radars, TRMM, and CloudSat). Required reading: S: 8.1, p.401-402, 5.7, 8.2.1, 8.2.2, 8.2.3, 8.3 Additional/advanced reading: Tutorials on ground-based weather radars: http://www.srh.noaa.gov/srh/jetstream/doppler/doppler_intro.htm http://www.weathertap.com/guides/radar/weather-radar-tutorial.html Tropical Rainfall Measuring Mission (TRMM) web site: http://trmm.gsfc.nasa.gov/ http://www.eorc.jaxa.jp/en/hatoyama/satellite/satdata/trmm_e.html Liu, Zhong, Dana Ostrenga, William Teng, Steven Kempler, 2012: Tropical Rainfall Measuring Mission (TRMM) Precipitation Data and Services for Research and Applications. Bull. Amer. Meteor. Soc., 93, 1317–1325. CloudSat web site: http://cloudsat.atmos.colostate.edu/ CloudSat Data Center: http://www.cloudsat.cira.colostate.edu/ 1 1. Radar basics. Main types of radars. Radar is an active remote sensing system operating at the microwave wavelength. Radar is a ranging instrument: (RAdio Detection And Ranging) Basic principles: The sensor transmits a microwave (radio) signal towards a target and detects the backscattered radiation. The strength of the backscattered signal is measured to discriminate between different targets and the time delay between the transmitted and reflected signals determines the distance (or range) to the target. Two primary advantages of radars: all-weather and day /night imaging Radar modes of operation: Constant wave (CW) mode: continuous beam of electromagnetic radiation is transmitted and received => provides information about the path integrated backscattering radiation Pulsed mode: transmits short pulses (typically 10-6-10-8 s) and measures backscattering radiation (also called echoes) as a function of range. -
POLDER-3 / PARASOL Land Surface Level 3 Albedo & NDVI Products
Date Issued :08.09.2010 Issue : I2.00 POLDER-3 / PARASOL Land Surface Level 3 Albedo & NDVI Products Data Format and User Manual Issue 2.00 8th September 2010 Author : R. Lacaze (HYGEOS) POLDER-3/PARASOL Land Surface Level-3 Albedo and NDVI Products. Product Format & User manual Change Record Issue/Rev Date Pages Description of Change Release I1.00 01.03.2006 All First Issue I2.00 08.09.2010 All Focus on Albedos and NDVI provided in raw binary format. Page 3 sur 17 POLDER-3/PARASOL Land Surface Level-3 Albedo and NDVI Products. Product Format & User manual Table of contents 1 Background ................................................................................................................... 6 2 Introduction ................................................................................................................... 7 3 Algorithm ....................................................................................................................... 8 3.1 The spectral directional and hemispheric albedos .................................................... 8 3.2 The broadband albedos ............................................................................................ 9 3.3 The normalized Difference Vegetation Index ............................................................ 9 4 Product Description .................................................................................................... 11 4.1 Product identification ............................................................................................. -
Synergetic Aerosol Retrieval from SCIAMACHY and AATSR Onboard ENVISAT
Atmos. Chem. Phys. Discuss., 8, 2903–2951, 2008 Atmospheric www.atmos-chem-phys-discuss.net/8/2903/2008/ Chemistry © Author(s) 2008. This work is distributed under and Physics the Creative Commons Attribution 3.0 License. Discussions Synergetic aerosol retrieval from SCIAMACHY and AATSR onboard ENVISAT T. Holzer-Popp1, M. Schroedter-Homscheidt1, H. Breitkreuz2, D. Martynenko1, and L. Kluser¨ 1,3 1German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Oberpfaffenhofen, Germany 2Julius-Maximilians-University of Wurzburg,¨ Department of Geography, Wurzburg,¨ Germany 3University of Augsburg, Institute of Physics, Augsburg, Germany Received: 3 January 2008 – Accepted: 8 January 2008 – Published: 13 February 2008 Correspondence to: T. Holzer-Popp ([email protected]) Published by Copernicus Publications on behalf of the European Geosciences Union. 2903 Abstract The synergetic aerosol retrieval method SYNAER (Holzer-Popp et al., 2002a) has been extended to the use of ENVISAT measurements. It exploits the complementary infor- mation of a radiometer and a spectrometer onboard one satellite platform to extract 5 aerosol optical depth (AOD) and speciation (as choice from a representative set of pre-defined mixtures of water-soluble, soot, mineral dust, and sea salt components). SYNAER consists of two retrieval steps. In the first step the radiometer is used to do accurate cloud screening, and subsequently to quantify the aerosol optical depth (AOD) at 550 nm and spectral surface brightness through a dark field technique. In the second 10 step the spectrometer is applied to choose the most plausible aerosol type through a least square fit of the measured spectrum with simulated spectra using the AOD and surface brightness retrieved in the first step. -
Chenab River, Pakistan)
water Article Hydrologic Assessment of TRMM and GPM-Based Precipitation Products in Transboundary River Catchment (Chenab River, Pakistan) Ehtesham Ahmed 1,* , Firas Al Janabi 1, Jin Zhang 2 , Wenyu Yang 3, Naeem Saddique 4 and Peter Krebs 1 1 Institute of Urban and Industrial Water Management, Technische Universität Dresden, 01069 Dresden, Germany; fi[email protected] (F.A.J.); [email protected] (P.K.) 2 Institute of Groundwater and Earth Sciences, Jinan University, Guangzhou 510632, China; [email protected] 3 Institute of Environmental Sciences, Brandenburgische Technische Universität, 03046 Cottbus, Germany; [email protected] 4 Institute of Hydrology and Meteorology, Technische Universität Dresden, 01062 Dresden, Germany; [email protected] * Correspondence: [email protected]; Tel.: +49-1525-6918549 Received: 9 June 2020; Accepted: 1 July 2020; Published: 3 July 2020 Abstract: Water resources planning and management depend on the quality of climatic data, particularly rainfall data, for reliable hydrological modeling. This can be very problematic in transboundary rivers with limited disclosing of data among the riparian countries. Satellite precipitation products are recognized as a promising source to substitute the ground-based observations in these conditions. This research aims to assess the feasibility of using a satellite-based precipitation product for better hydrological modeling in an ungauged and riparian river in Pakistan, i.e., the Chenab River. A semidistributed hydrological model of The soil and water assessment tool (SWAT) was set up and two renowned satellite precipitation products, i.e., global precipitation mission (GPM) IMERG-F v6 and tropical rainfall measuring mission (TRMM) 3B42 v7, were selected to assess the runoff pattern in Chenab River.