SSS retrieval from space Comparison study using Aquarius and SMOS data
|
|
- Allen Hart
- 5 years ago
- Views:
Transcription
1 44 th International Liège Colloquium on Ocean Dynamics 7-11 May 2012 SSS retrieval from space Comparison study using Aquarius and SMOS data Physical Oceanography Department Institute of Marine Sciences (ICM) CSIC S. Guimbard, J. Font (co lead investigator), J. Gourrion, J. Ballabrera, A. Turiel, J. Martínez, F. Perez
2 Outline Introduction SMOS data processing status SSS comparisons between Aquarius and SMOS Conclusion
3 The Soil Moisture and Ocean Salinity ESA earth mission explorer Since November 2009, a new concept of measurement from space is available. Microwave imaging Radiometer using Aperture synthesis (2D imaging by Fourier synthesis) L-band radiation measured at 1.43 GHz ( protected band for scientific applications) Sun-synchronous (6 am local equator crossing times) Multiple incidence and azimuthal observation angles It has not been design for Sea Surface Salinity only ->Even with a well calibrated instrument, SSS retrieval was expect to be tough. We are at the limit of the instrumental sensitivity
4 Concept of the measurement Discrete sampling produces spatial periodicity: Aliases Visibility: (u-v) domain Visibility: (u-v) domain T B : (ξ-η) domain Geo-location Alias-Free Field of View T B : (lat-lon) domain Extended Alias-Free Field of view Main issues : Reconstruction, Radio frequency interferences, Sea/land transition
5 SMOS sea surface salinity status SMOS Level 1 processor v5.04 In operation since November 2011 Principal modifications: Reduction of short and long term drifts Decrease of contaminations due to land and ice Better RFI detection/mitigation Improved sun impact correction Caveats: Fixed spatial bias (2.8K RMS) -> corrected at L2 Software bug: corrupted measurements in polar region (Sea-ice conditions and salinity studies not possible with this version)
6 SSS retrieval concept Many models with very good prediction accuracies are needed For example, 0.1 K (~0,003) error on a model component can lead to an error of 0.2 psu
7 SMOS sea surface salinity status SMOS Level 1 processor v5.04 In operation since November 2011 Principal modifications: Reduction of short and long term drifts Decrease of contaminations due to land and ice Better RFI detection/mitigation Improved sun impact correction Caveats: Fixed spatial bias (2.8K RMS) -> corrected at L2 Software bug: corrupted measurements in polar region (Sea-ice conditions and salinity studies not possible with this version SMOS Level 2 processor v5.50 In operation since December 2011 Principal modifications: Time-varying residual spatial bias correction (Ocean Target Transformation); different ascending/descending Roughness effect correction models tuned to SMOS data Improved flagging /data filtering strategy -> Used to reprocess the full data set
8 WOA 2009 SSS SMOS through the years SSS anomalies (WOA 2009) SSS difference : El niño 2011: La niña
9 Study angle What are the common points between SMOS and Aquarius missions? Produce global salinity maps on a monthly basis with a spatial resolution of ~100 km with an accuracy of psu Both radiometer measuring radiation at 1.4 GHz Physical laws ( Kirchhoff's law of thermal radiation, planck law) 8 months period of SSS products What are the differences? Instrument design and accuracy Spatial and temporal sampling Ascending passes (6am for SMOS vs 6pm for Aquarius) Forward model (or contamination corrections) and auxiliary parameters (SST,wind speed ) used to retrieved salinity We expect differences but let s see what it looks like on a monthly basis.
10 2011 L3 binned SSS anomaly (Aquarius-WOA09) Sep Oct Nov Dec 2012 Jan Fev Mar Apr L2 v1.3 Aquarius data bin averaged on a regular grid of 1 x1 Minus monthly World Ocean Atlas 2009 OI SSS
11 2011 L3 binned SSS anomaly (SMOS-WOA09) Sep Oct Nov Dec 2012 Jan Fev Mar Apr L2 SMOS data bin averaged on a regular grid of 1 x1 minus monthly World Ocean Atlas 2009 OI SSS
12 2011 L3 binned SSS difference (Aquarius-SMOS) Sep Oct Nov Dec 2012 Jan Fev Mar Apr L2 AQUARIUS data bin averaged on a regular grid of 1 x1 minus L2 SMOS data bin averaged on a regular grid of 1 x1
13 Aquarius vs SMOS? Which one has the ground truth? I compared these Aquarius and SMOS datasets with all in situ data available (ARGO, TAO, RAMA, PIRATA ) -> no clear answer arise, only other questions (surface stratification, spatial representativeness ) The only thing I am sure of, is that we are still missing something in our understanding of this 2 instruments and only time will give us answers
14 Future improvements Improving land/sea transition impact on L1 signal (Gibbs phenomenon) Better residual bias removal techniques under analysis (understanding the problem at L1; mitigating it as L2 preprocessing) Galactic noise degrades retrieval in function of region and season. New correction model at L2 tested and ready for operational implementation. Sun signal tails on alias-free field-of-view still a problem. Removal techniques under investigation RFI degrades/corrupts salinity retrieval in large areas. Switching-off illegal sources and improving mitigation procedures Still need to improve correction for faraday rotation 14
15 Conclusions As the SSS sensitivity of the SMOS measurement is very low, space and time averaging are necessary Spatial averaging is more efficient since we are still dealing with unresolved temporal drift. Regional SSS retrieval algorithm will have to be developed in order to achieve mission requirements. A specific SSS retrieval algorithm for both SMOS & Aquarius sea surface brightness temperature with same dielectric constant is needed in order to achieve coherent synergy
16 L2 SSS statistics Sep Oct Nov ASC DES ASC/ DES
17 L2 SSS statistics Sep Oct Nov ASC DES ASC/ DES
18 L2 SSS statistics Sep Oct Nov ASC DES ASC/ DES
19 Monthly bin averaged SMOS SSS (1 x1 ) 2010
20 Monthly bin averaged SMOS SSS (1 x1 ) 2011
21 Yearly SMOS SSS anomalies WOA 2009
22
23
24
25
26 Global L2 retrieved SSS temporal evolution NO filtering Filtered
27 Roughness TB modulation
28 4. Sea Surface Temperature (SST) Anomaly SUMMARY: CRW's SST Anomaly is produced by subtracting the long-term mean SST (for that location in that time of year) from the current value. A positive anomaly means that the current sea surface temperature is warmer than average, and a negative anomaly means it is cooler than average. The spatial resolution is 0.5-degree (50-km), and the data and images are updated twice-weekly. Animations of the most recent SST Anomaly images are also available online. CRW's near-real-time global SST Anomaly product makes it possible to quickly pinpoint regions of elevated SSTs throughout the world oceans. It is especially valuable for the tropical regions where most of the world's coral reef ecosystems thrive. It is also very useful in assessing ENSO (El Niño-Southern Oscillation) development, monitoring hurricane "wake" cooling, observing major shifts in coastal upwellings, etc. A twice-weekly SST anomaly at a 0.5-degree (50-km) grid is calculated by subtracting the daily climatological SST of the last day of the twiceweekly period at that grid from the corresponding twice-weekly SST (described in Sea Surface Temperature Section). The formula for obtaining the anomaly is SST_anomaly = SST - Daily_SST_climatology The color range of temperature anomalies displayed on the SST Anomaly charts is -5.0 to +5.0 C (or Kelvin). Areas with SST anomaly values less than -5.0 C are displayed as -5.0 C, and areas with values greater than +5.0 C are displayed as +5.0 C. Note that these anomalies are somewhat less reliable at high latitudes where more persistent clouds limit the amount of satellite data available for deriving accurate SST analysis fields and climatologies. Data and images of both near-real-time and archived SST anomalies are available from the CRW website, along with the operational 0.5- degree monthly mean SST climatologies. Animations of SST Anomaly images for the past six months are also available. Charts of the retrospective monthly mean SST anomalies are available online at 36-km resolution.
29 Sunspot number Moscow Cosmic Rays GOES X-rays GOES Protons GOES magnetometer:hp, He
30 31 A SMOS snapshot is an irregular 1000 km x 1000 km hexagon image with variable incidence angles, pixel sizes and radiometric sensitivities As the satellite advances a single spot on earth is seen in different positions within the instrument field-of-view Many snapshots are used to retrieve a single SSS value
31 BEC OS products validation: L3 SMOS OS L3 map 1 o x1 o Optimal Interpolation using WOA2009 as background Jan Argo SSS interpolated at 7.5m depth SMOS - Argo 1299 points Bias = RMS = 0.42
32 BEC OS products validation: L4 SMOS OS L4 map 1 o x1 o Generated from L3 binned + SST singularity exponents Jan Argo SSS interpolated at 7.5m depth SMOS - Argo 1202 points Bias = RMS = 0.49
33
34
Sea water dielectric constant, temperature and remote sensing of Sea Surface Salinity
Sea water dielectric constant, temperature and remote sensing of Sea Surface Salinity E. P. Dinnat 1,2, D. M. Le Vine 1, J. Boutin 3, X. Yin 3, 1 Cryospheric Sciences Lab., NASA GSFC, Greenbelt, MD, U.S.A
More informationAquarius Data Release V2.0 Validation Analysis Gary Lagerloef, Aquarius Principal Investigator H. Kao, ESR And Aquarius Cal/Val Team
Aquarius Data Release V2.0 Validation Analysis Gary Lagerloef, Aquarius Principal Investigator H. Kao, ESR And Aquarius Cal/Val Team Analysis period: Sep 2011-Dec 2012 SMOS-Aquarius Workshop 15-17 April
More informationNOAA In Situ Satellite Blended Analysis of Surface Salinity: Preliminary Results for
NOAA In Situ Satellite Blended Analysis of Surface Salinity: Preliminary Results for 2010-2012 P.Xie 1), T. Boyer 2), E. Bayler 3), Y. Xue 1), D. Byrne 2), J.Reagan 2), R. Locarnini 2), F. Sun 1), R.Joyce
More informationPreliminary study of multi-year ocean salinity trends with merged SMOS and Aquarius data.
Preliminary study of multi-year ocean salinity trends with merged SMOS and Aquarius data. Gary Lagerloef and Hsun-Ying Kao Earth & Space Research Seattle, USA Aquarius Status Completed 3-year Prime Mission
More informationEstimation de la salinité par radiométrie microonde depuis l espace
Estimation de la salinité par radiométrie microonde depuis l espace J. Boutin (1), N. Reul (2), J. Font (3), X. Yin (1), J. Tenerelli (4), N. Martin (1), J.L. Vergely (5), P. Spurgeon (6) And ESA level
More informationSea surface salinity from space: new tools for the ocean color community
Sea surface salinity from space: new tools for the ocean color community Joe Salisbury, Doug Vandemark, Chris Hunt, Janet Campbell, Dominic Wisser, Tim Moore (UNH) Nico Reul, Bertrand Chapron (IFREMR)
More informationOcean Vector Winds in Storms from the SMAP L-Band Radiometer
International Workshop on Measuring High Wind Speeds over the Ocean 15 17 November 2016 UK Met Office, Exeter Ocean Vector Winds in Storms from the SMAP L-Band Radiometer Thomas Meissner, Lucrezia Ricciardulli,
More informationNew Salinity Product in the Tropical Indian Ocean Estimated from OLR
New Salinity Product in the Tropical Indian Ocean Estimated from OLR Aquarius Bulusu Subrahmanyam and James J. O Brien Center for Ocean-Atmospheric Prediction Studies, Florida State University V.S.N. Murty
More informationOcean front maps for integrating dynamic thermal, colour and salinity features Peter Miller and Weidong Xu
Ocean front maps for integrating dynamic thermal, colour and salinity features Peter Miller and Weidong Xu 44 th International Liège Colloquium on Ocean Dynamics: Remote sensing of colour, temperature
More informationAtmospheric circulation analysis for seasonal forecasting
Training Seminar on Application of Seasonal Forecast GPV Data to Seasonal Forecast Products 18 21 January 2011 Tokyo, Japan Atmospheric circulation analysis for seasonal forecasting Shotaro Tanaka Climate
More informationSatellite-derived environmental drivers for top predator hotspots
Satellite-derived environmental drivers for top predator hotspots Peter Miller @PeterM654 South West Marine Ecosystems 2017 21 Apr. 2017, Plymouth University Satellite environmental drivers for hotspots
More informationATSR SST Observations of the Tropical Pacific Compared with TOPEX/Poseidon Sea Level Anomaly
ATSR SST Observations of the Tropical Pacific Compared with TOPEX/Poseidon Sea Level Anomaly J.P.Angell and S.P.Lawrence Earth Observation Science Group, Dept. Physics and Astronomy, Space Research Centre,
More informationThe Effect of Clouds and Rain on the Aquarius Salinity Retrieval
The Effect of Clouds and ain on the Aquarius Salinity etrieval Frank J. Wentz 1. adiative Transfer Equations At 1.4 GHz, the radiative transfer model for cloud and rain is considerably simpler than that
More informationSMOS L1 Sun BT Validation against on-ground radio-telescope network. Daniele Casella, Raffaele Crapolicchio, Emiliano Capolongo
SMOS L1 Sun BT Validation against on-ground radio-telescope network Daniele Casella, Raffaele Crapolicchio, Emiliano Capolongo Background Focus : SMOS L1b Sun BT Objectives: Evaluate the improvements of
More informationRSS SMAP Salinity. Version 2.0 Validated Release. Thomas Meissner + Frank Wentz, RSS Tony Lee, JPL
RSS SMAP Salinity Version 2.0 Validated Release Thomas Meissner + Frank Wentz, RSS Tony Lee, JPL hap://www.remss.com/missions/smap/salinity 1. Level 2C 2. Level 3 8-day running averages 3. Level 3 monthly
More informationSAC-D. SMOS 4th Science Workshop April 2003, Porto Presented by Jordi Font, Prepared by Gary Lagerloef
(Ocean Surface Salinity Measurement) Understanding the ocean s response to the global freshwater cycle SMOS 4th Science Workshop April 2003, Porto Presented by Jordi Font, Prepared by Gary Lagerloef 1
More informationVersion 7 SST from AMSR-E & WindSAT
Version 7 SST from AMSR-E & WindSAT Chelle L. Gentemann, Thomas Meissner, Lucrezia Ricciardulli & Frank Wentz www.remss.com Retrieval algorithm Validation results RFI THE 44th International Liege Colloquium
More informationRead-me-first note for the release of the SMOS level 2 Soil Moisture data products
Read-me-first note for the release of the SMOS level 2 Soil Moisture data products Processor version Release date by ESA Authors Further information Contact for helpline Comments to ESL Level 2 soil moisture
More informationAquarius L2 Algorithm: Geophysical Model Func;ons
Aquarius L2 Algorithm: Geophysical Model Func;ons Thomas Meissner and Frank J. Wentz, Remote Sensing Systems Presented at Aquarius Cal/Val Web- Workshop January 29 30, 2013 Outline 1. Aquarius Wind Speed
More informationSea Surface Salinity Retrieval within the ESA Soil Moisture and Ocean Salinity (SMOS) Mission
Sea Surface Salinity Retrieval within the ESA Soil Moisture and Ocean Salinity (SMOS) Mission Roberto Sabia, Adriano Camps, Mercè Vall-llossera, Ramón Villarino, Jorge Miranda, Alessandra Monerris, Miguel
More informationALASKA REGION CLIMATE OUTLOOK BRIEFING. December 22, 2017 Rick Thoman National Weather Service Alaska Region
ALASKA REGION CLIMATE OUTLOOK BRIEFING December 22, 2017 Rick Thoman National Weather Service Alaska Region Today s Outline Feature of the month: Autumn sea ice near Alaska Climate Forecast Basics Climate
More informationFrom L1 to L2 for sea ice concentration. Rasmus Tonboe Danish Meteorological Institute EUMETSAT OSISAF
From L1 to L2 for sea ice concentration Rasmus Tonboe Danish Meteorological Institute EUMETSAT OSISAF Sea-ice concentration = sea-ice surface fraction Water Ice e.g. Kern et al. 2016, The Cryosphere
More informationDISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited.
DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Northern Indian Ocean Salt Transport (NIOST): Estimation of Fresh and Salt Water Transports in the Indian Ocean using Remote
More informationThe SMOS Satellite Mission. Y. Kerr, and the SMOS Team
The SMOS Satellite Mission Y. Kerr, and the SMOS Team The 4 phases of a project The concept Expression of needs Theoretical solution Practical solution The selling Proposal writing Concept fine tuning
More informationName the surface winds that blow between 0 and 30. GEO 101, February 25, 2014 Monsoon Global circulation aloft El Niño Atmospheric water
GEO 101, February 25, 2014 Monsoon Global circulation aloft El Niño Atmospheric water Name the surface winds that blow between 0 and 30 What is the atmospheric pressure at 0? What is the atmospheric pressure
More informationResponding to the 2016 and 2017 Mass Coral Bleaching events on the Great Barrier Reef: from Observations to Modelling
Responding to the 2016 and 2017 Mass Coral Bleaching events on the Great Barrier Reef: from Observations to Modelling EMatson@aims Craig Steinberg & Claire Spillman N. Cantin, J. Benthuysen, H. Tonin,
More informationLand data assimilation in the NASA GEOS-5 system: Status and challenges
Blueprints for Next-Generation Data Assimilation Systems Boulder, CO, USA 8-10 March 2016 Land data assimilation in the NASA GEOS-5 system: Status and challenges Rolf Reichle Clara Draper, Ricardo Todling,
More informationA two-season impact study of the Navy s WindSat surface wind retrievals in the NCEP global data assimilation system
A two-season impact study of the Navy s WindSat surface wind retrievals in the NCEP global data assimilation system Li Bi James Jung John Le Marshall 16 April 2008 Outline WindSat overview and working
More informationInter-tropical Convergence Zone (ITCZ) analysis using AIRWAVE retrievals of TCWV from (A)ATSR series and potential extension of AIRWAVE to SLSTR
Inter-tropical Convergence Zone (ITCZ) analysis using AIRWAVE retrievals of TCWV from (A)ATSR series and potential extension of AIRWAVE to SLSTR Enzo Papandrea (SERCO, CNR-ISAC, Enzo.Papandrea@serco.com)
More informationSeasonal Climate Watch November 2017 to March 2018
Seasonal Climate Watch November 2017 to March 2018 Date issued: Oct 26, 2017 1. Overview The El Niño Southern Oscillation (ENSO) continues to develop towards a La Niña state, and is expected to be in at
More informationObservation Operators for sea ice thickness to L-band brightness temperatures
Observation Operators for sea ice thickness to L-band brightness temperatures F. Richter, M. Drusch, L. Kaleschke, N. Maass, X. Tian-Kunze, G. Heygster, S. Mecklenburg, T. Casal, and many others ESA, ESTEC
More informationAquarius/SAC-D Soil Moisture Product using V3.0 Observations
Aquarius/SAC-D Soil Moisture Product using V3. Observations R. Bindlish, T. Jackson, M. Cosh November 214 Overview Soil moisture algorithm Soil moisture product Validation Linkage between Soil Moisture
More informationCharacteristics of Global Precipitable Water Revealed by COSMIC Measurements
Characteristics of Global Precipitable Water Revealed by COSMIC Measurements Ching-Yuang Huang 1,2, Wen-Hsin Teng 1, Shu-Peng Ho 3, Ying-Hwa Kuo 3, and Xin-Jia Zhou 3 1 Department of Atmospheric Sciences,
More informationMarch was 3rd warmest month in satellite record
April 4, 2016 Vol. 25, No. 12 For Additional Information: Dr. John Christy, (256) 961-7763 john.christy@nsstc.uah.edu Dr. Roy Spencer, (256) 961-7960 roy.spencer@nsstc.uah.edu Global Temperature Report:
More informationInterpretation of Polar-orbiting Satellite Observations. Atmospheric Instrumentation
Interpretation of Polar-orbiting Satellite Observations Outline Polar-Orbiting Observations: Review of Polar-Orbiting Satellite Systems Overview of Currently Active Satellites / Sensors Overview of Sensor
More informationSeparation of a Signal of Interest from a Seasonal Effect in Geophysical Data: I. El Niño/La Niña Phenomenon
International Journal of Geosciences, 2011, 2, **-** Published Online November 2011 (http://www.scirp.org/journal/ijg) Separation of a Signal of Interest from a Seasonal Effect in Geophysical Data: I.
More informationECMWF: Weather and Climate Dynamical Forecasts
ECMWF: Weather and Climate Dynamical Forecasts Medium-Range (0-day) Partial coupling Extended + Monthly Fully coupled Seasonal Forecasts Fully coupled Atmospheric model Atmospheric model Wave model Wave
More informationOutline of 4 Lectures
Outline of 4 Lectures 1. Sept. 17, 2008: TC best track definition and datasets, global distribution of TCs; Review of history of meteorological satellites, introducing different orbits, scanning patterns,
More informationALASKA REGION CLIMATE OUTLOOK BRIEFING. November 17, 2017 Rick Thoman National Weather Service Alaska Region
ALASKA REGION CLIMATE OUTLOOK BRIEFING November 17, 2017 Rick Thoman National Weather Service Alaska Region Today Feature of the month: More climate models! Climate Forecast Basics Climate System Review
More informationT. Meissner and F. Wentz Remote Sensing Systems
T. Meissner and F. Wentz Remote Sensing Systems meissner@remss.com 2014 Aquarius / SAC- D Science Team Mee8ng November 11-14, 2014 Sea?le. Washington, USA Outline 1. Current Status: Observed Biases Post-
More informationRAIN RATE RETRIEVAL ALGORITHM FOR AQUARIUS/SAC-D MICROWAVE RADIOMETER. ROSA ANA MENZEROTOLO B.S. University of Central Florida, 2005
RAIN RATE RETRIEVAL ALGORITHM FOR AQUARIUS/SAC-D MICROWAVE RADIOMETER by ROSA ANA MENZEROTOLO B.S. University of Central Florida, 2005 A thesis submitted in partial fulfillment of the requirements for
More informationEarth & Space Research, Seattle WA, USA
Aquarius Satellite Salinity Measurement Mission Status, and Science Results from the initial 3-Year Prime Mission Gary Lagerloef, 1 Hsun-Ying Kao 1, and Aquarius Cal/Val/Algorithm Team 1 Earth & Space
More informationSMOS L1 Sun BT Valida0on against on-ground radio-telescope network
SMOS L1 Sun BT Valida0on against on-ground radio-telescope network Daniele Casella 1, Raffaele Crapolicchio 1;2, Nicola Compare7 1, Christophe Marqué 3 1 Serco 2 ESA-ESRIN 3 Royal Observatory of Belgium
More informationOcean Observations for an End-to-End Seasonal Forecasting System
Ocean Observations for an End-to-End Seasonal Forecasting System Magdalena A. Balmaseda Yosuke Fujii Oscar Alves Tong Lee Michele Rienecker Tony Rosati Detlef Stammer Yan Xue Howard Freeland Michael McPhaden
More informationENSO UPDATE By Joseph D Aleo, CCM
ENSO UPDATE By Joseph D Aleo, CCM El Nino is still hanging on but likely not for very long. Warmer than normal water can still be seen along the equator in the tropical Pacific. It is even warmer in the
More informationan accessible interface to marine environmental data Russell Moffitt
an accessible interface to marine environmental data Russell Moffitt The Atlas Project GOAL: To provide a single point of access to oceanographic and environmental data for use by marine resource researchers,
More informationWill a warmer world change Queensland s rainfall?
Will a warmer world change Queensland s rainfall? Nicholas P. Klingaman National Centre for Atmospheric Science-Climate Walker Institute for Climate System Research University of Reading The Walker-QCCCE
More informationAquarius Cal/Val: Salinity Retrieval Algorithm V1.3. Thomas Meissner Frank Wentz
Aquarius Cal/Val: Salinity Retrieval Algorithm V1.3 Thomas Meissner Frank Wentz L2 Algorithm: Overview Aquarius Radiometer Counts Earth + Calibration View Radiometer Calibration Algorithm RFI flagging
More informationLab 12: El Nino Southern Oscillation
Name: Date: OCN 104: Our Dynamic Ocean Lab 12: El Nino Southern Oscillation Part 1: Observations of the tropical Pacific Ocean during a normal year The National Oceanographic and Atmospheric Administration
More informationGlobal Ocean Monitoring: A Synthesis of Atmospheric and Oceanic Analysis
Extended abstract for the 3 rd WCRP International Conference on Reanalysis held in Tokyo, Japan, on Jan. 28 Feb. 1, 2008 Global Ocean Monitoring: A Synthesis of Atmospheric and Oceanic Analysis Yan Xue,
More informationSMOS NRT BUFR specification
SMOS_NRT_BUFR_ECMWF - v3.0 02 April 2015 SMOS NRT BUFR specification P. de Rosnay¹, M. Dragosavac¹, M. Drusch¹, A. Gutiérrez², M. Rodríguez López³, N. Wright, 4 J. Muñoz Sabater 1, Raffaele Crapolicchio
More informationAssimilation of Satellite Sea-surface Salinity Fields: Validating Ocean Analyses and Identifying Errors in Surface Buoyancy Fluxes
Assimilation of Satellite Sea-surface Salinity Fields: Validating Ocean Analyses and Identifying Errors in Surface Buoyancy Fluxes Eric Bayler Sudhir Nadiga Avichal Mehra David Behringer NOAA/NESDIS/STAR
More informationSoil moisture Product and science update
Soil moisture Product and science update Wouter Dorigo and colleagues Department of Geodesy and Geo-information, Vienna University of Technology, Vienna, Austria 2 June 2013 Soil moisture is getting mature
More informationScarborough Tide Gauge
Tide Gauge Location OS: 504898E 488622N WGS84: Latitude: 54 16' 56.990"N Longitude: 00 23' 25.0279"W Instrument Valeport 740 (Druck Pressure Transducer) Benchmarks Benchmark Description TGBM = 4.18m above
More informationOcean Surface Salinity Validation in Canadian Waters
Ocean Surface Salinity Validation in Canadian Waters Jim Gower, Institute of Ocean Sciences, Sidney, BC Élizabeth Simms, Memorial University, St-John s, NF Brenda Topliss, Bedford Institute of Oceanography,
More informationComparison of NASA AIRS and MODIS Land Surface Temperature and Infrared Emissivity Measurements from the EOS AQUA platform
Comparison of NASA AIRS and MODIS Land Surface Temperature and Infrared Emissivity Measurements from the EOS AQUA platform Robert Knuteson, Steve Ackerman, Hank Revercomb, Dave Tobin University of Wisconsin-Madison
More informationEarly Successes El Nino Southern Oscillation and seasonal forecasting. David Anderson, With thanks to Magdalena Balmaseda, Tim Stockdale.
Early Successes El Nino Southern Oscillation and seasonal forecasting David Anderson, With thanks to Magdalena Balmaseda, Tim Stockdale. Summary Pre TOGA, the 1982/3 El Nino was not well predicted. In
More informationENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 23 April 2012
ENSO Cycle: Recent Evolution, Current Status and Predictions Update prepared by Climate Prediction Center / NCEP 23 April 2012 Outline Overview Recent Evolution and Current Conditions Oceanic Niño Index
More informationLong-Term Time Series of Water Vapour Total Columns from GOME, SCIAMACHY and GOME-2
Graphics: ESA Graphics: ESA Graphics: ESA Long-Term Time Series of Water Vapour Total Columns from GOME, SCIAMACHY and GOME-2 S. Noël, S. Mieruch, H. Bovensmann, J. P. Burrows Institute of Environmental
More informationImage Reconstruction Algorithms for 2D Aperture Synthesis Radiometers
Image Reconstruction Algorithms for 2D Aperture Synthesis Radiometers E. Anterrieu 1 and A. Camps 2 1 Dept. Signal, Image & Instrumentation Laboratoire d Astrophysique de Toulouse-Tarbes Université de
More informationANNUAL CLIMATE REPORT 2016 SRI LANKA
ANNUAL CLIMATE REPORT 2016 SRI LANKA Foundation for Environment, Climate and Technology C/o Mahaweli Authority of Sri Lanka, Digana Village, Rajawella, Kandy, KY 20180, Sri Lanka Citation Lokuhetti, R.,
More informationENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 11 November 2013
ENSO Cycle: Recent Evolution, Current Status and Predictions Update prepared by Climate Prediction Center / NCEP 11 November 2013 Outline Overview Recent Evolution and Current Conditions Oceanic Niño Index
More informationYellow Sea Thermohaline and Acoustic Variability
Yellow Sea Thermohaline and Acoustic Variability Peter C Chu, Carlos J. Cintron Naval Postgraduate School, USA Steve Haeger Naval Oceanographic Office, USA Yellow Sea Bottom Sediment Chart Four Bottom
More informationIntroduction to SMAP. ARSET Applied Remote Sensing Training. Jul. 20,
National Aeronautics and Space Administration ARSET Applied Remote Sensing Training http://arset.gsfc.nasa.gov @NASAARSET Introduction to SMAP Jul. 20, 2016 www.nasa.gov Outline 1. Mission objectives 2.
More informationSynergetic Aspects and Auxiliary Data Concepts for Sea Surface Salinity Measurements from Space
Synergetic Aspects and Auxiliary Data Concepts for Sea Surface Salinity Measurements from Space AO/1-4505/03/NL/CB An ESA study Kicked-off 1st April 2004 Objectives of the study The present project has
More informationIASI RADIANCES CLIMATOLOGY. Thierry PHULPIN* and Joaquin GONZALEZ** *Now at TIRSEC **Now at CNES/DLA
IASI RADIANCES CLIMATOLOGY Thierry PHULPIN* and Joaquin GONZALEZ** *Now at TIRSEC **Now at CNES/DLA 1 ITSC 19 JEJU 25 March- 1 April 2014 OUTLINE RATIONALE METHODOLOGY PRODUCTS EXPLOITATION OF THE STATISTICS
More informationThe MSC Beaufort Wind and Wave Reanalysis
The MSC Beaufort Wind and Wave Reanalysis Val Swail Environment Canada Vincent Cardone, Brian Callahan, Mike Ferguson, Dan Gummer and Andrew Cox Oceanweather Inc. Cos Cob, CT, USA Introduction: History
More informationRegents Earth Science Unit 7: Water Cycle and Climate
Regents Earth Science Unit 7: Water Cycle and Climate Name Section Coastal and Continental Temperature Ranges Lab # Introduction: There are large variations in average monthly temperatures among cities
More informationThe SeaFlux Turbulent Flux Dataset Version 1.0 Documentation
The SeaFlux Turbulent Flux Dataset The SeaFlux Turbulent Flux Dataset Version 1.0 Documentation Carol Anne Clayson1 J. Brent Roberts2 Alec S. Bogdanoff1,3 1. Woods Hole Oceanographic Institution, Woods
More informationDaily OI SST Trip Report Richard W. Reynolds National Climatic Data Center (NCDC) Asheville, NC July 29, 2005
Daily OI SST Trip Report Richard W. Reynolds National Climatic Data Center (NCDC) Asheville, NC July 29, 2005 I spent the month of July 2003 working with Professor Dudley Chelton at the College of Oceanic
More informationRichard W. Reynolds * NOAA National Climatic Data Center, Asheville, North Carolina
8.1 A DAILY BLENDED ANALYSIS FOR SEA SURFACE TEMPERATURE Richard W. Reynolds * NOAA National Climatic Data Center, Asheville, North Carolina Kenneth S. Casey NOAA National Oceanographic Data Center, Silver
More informationRead-me-first note for the release of the SMOS Level 3 ice thickness data products
Read-me-first note for the release of the SMOS Level 3 ice thickness data products Processor version Level 3 sea ice thickness v3.1 Release date by ESA Released in December 2016 Authors Xiangshan Tian-Kunze
More informationALASKA REGION CLIMATE OUTLOOK BRIEFING. November 16, 2018 Rick Thoman Alaska Center for Climate Assessment and Policy
ALASKA REGION CLIMATE OUTLOOK BRIEFING November 16, 2018 Rick Thoman Alaska Center for Climate Assessment and Policy Today s Outline Feature of the month: Southeast Drought Update Climate Forecast Basics
More informationTokyo Climate Center Website (TCC website) and its products -For monitoring the world climate and ocean-
Tokyo, 14 November 2016, TCC Training Seminar Tokyo Climate Center Website (TCC website) and its products -For monitoring the world climate and ocean- Yasushi MOCHIZUKI Tokyo Climate Center Japan Meteorological
More informationAssimilation of ASCAT soil wetness
EWGLAM, October 2010 Assimilation of ASCAT soil wetness Bruce Macpherson, on behalf of Imtiaz Dharssi, Keir Bovis and Clive Jones Contents This presentation covers the following areas ASCAT soil wetness
More informationA Comparison of Satellite and In Situ Based Sea Surface Temperature Climatologies
1848 JOURNAL OF CLIMATE VOLUME 12 A Comparison of Satellite and In Situ Based Sea Surface Temperature Climatologies KENNETH S. CASEY* AND PETER CORNILLON Graduate School of Oceanography, University of
More information8A Supplementary Material
8A Supplementary Material Supplementary material belonging to Chapter 2, derived from the following publication: Van der Schalie, R., Parinussa, R.M., Renzullo, L.J., Van Dijk, A.I.J.M., Su, C.H. and De
More informationData assimilation for ocean climate studies
Data assimilation for ocean climate studies James Carton, Gennady Chepurin, Steven Penny, and David Behringer (thanks Eugenia) University of Maryland, NOAA/NCEP, College Park, MD USA Chl concentration
More informationLectures 7 and 8: 14, 16 Oct Sea Surface Temperature
Lectures 7 and 8: 14, 16 Oct 2008 Sea Surface Temperature References: Martin, S., 2004, An Introduction to Ocean Remote Sensing, Cambridge University Press, 454 pp. Chapter 7. Robinson, I. S., 2004, Measuring
More informationOrbit Design Marcelo Suárez. 6th Science Meeting; Seattle, WA, USA July 2010
Orbit Design Marcelo Suárez Orbit Design Requirements The following Science Requirements provided drivers for Orbit Design: Global Coverage: the entire extent (100%) of the ice-free ocean surface to at
More informationDISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited.
DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Northern Indian Ocean Salt Transport (NIOST): Estimation of Fresh and Salt Water Transports in the Indian Ocean using Remote
More informationData Assimilation of Argo Profiles in Northwest Pacific Yun LI National Marine Environmental Forecasting Center, Beijing
Data Assimilation of Argo Profiles in Northwest Pacific Yun LI National Marine Environmental Forecasting Center, Beijing www.nmefc.gov.cn National Marine Environmental Forecasting Center Established in
More informationAppendix B. A proposition for updating the environmental standards using real Earth Albedo and Earth IR Flux for Spacecraft Thermal Analysis
19 Appendix B A proposition for updating the environmental standards using real Earth Albedo and Earth IR Romain Peyrou-Lauga (ESA/ESTEC, The Netherlands) 31 st European Space Thermal Analysis Workshop
More informationNew Zealand Climate Update No 226, April 2018 Current climate March 2018
New Zealand Climate Update No 226, April 2018 Current climate March 2018 March 2018 was characterised by significantly higher pressure than normal to the east of New Zealand. This pressure pattern, in
More informationENSO Outlook by JMA. Hiroyuki Sugimoto. El Niño Monitoring and Prediction Group Climate Prediction Division Japan Meteorological Agency
ENSO Outlook by JMA Hiroyuki Sugimoto El Niño Monitoring and Prediction Group Climate Prediction Division Outline 1. ENSO impacts on the climate 2. Current Conditions 3. Prediction by JMA/MRI-CGCM 4. Summary
More informationSMAP Radiometer Brightness Temperature Calibration for L1B_TB and L1C_TB Version 3 and L1C_TB_E Version 1 Data Products November 29, 2016
SMAP Radiometer Brightness Temperature Calibration for the L1B_TB (Version 3), L1C_TB (Version 3), and L1C_TB_E (Version 1) Data Products Citation: Soil Moisture Active Passive (SMAP) Project Jeffrey Piepmeier,
More informationSentinel-3A Product Notice SLSTR Level-2 Sea Surface Temperature
Sentinel-3A Product Notice SLSTR Level-2 Sea Surface Temperature Mission Sensor Product Sentinel-3A SLSTR Level 2 Sea Surface Temperature Product Notice ID EUM/OPS-SEN3/DOC/18/984462 S3A.PN-SLSTR-L2M.003
More informationENSO: Recent Evolution, Current Status and Predictions. Update prepared by: Climate Prediction Center / NCEP 30 October 2017
ENSO: Recent Evolution, Current Status and Predictions Update prepared by: Climate Prediction Center / NCEP 30 October 2017 Outline Summary Recent Evolution and Current Conditions Oceanic Niño Index (ONI)
More informationENVISAT - AATSR CYCLIC REPORT #63
ENVISAT - AATSR CYCLIC REPORT #63 START END DATE 29 OCT 2007 03 DEC 2007 TIME 21:59:29 21:59:29 ORBIT # 29614 30114 Himalayas, 18 November 2007 Daytime visible image showing snow on the Western Himalayas.
More informationLocation. Datum. Survey. information. Etrometa. Step Gauge. Description. relative to Herne Bay is -2.72m. The site new level.
Tide Gauge Location OS: 616895E 169377N WGS84: Latitude: 51 o 22.919196 N Longitude: 01 o 6.9335907 E Instrument Type Etrometa Step Gauge Benchmarks Benchmark TGBM = 5.524m above Ordnance Datum Newlyn
More informationAn Overview of Atmospheric Analyses and Reanalyses for Climate
An Overview of Atmospheric Analyses and Reanalyses for Climate Kevin E. Trenberth NCAR Boulder CO Analysis Data Assimilation merges observations & model predictions to provide a superior state estimate.
More informationENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 5 August 2013
ENSO Cycle: Recent Evolution, Current Status and Predictions Update prepared by Climate Prediction Center / NCEP 5 August 2013 Outline Overview Recent Evolution and Current Conditions Oceanic Niño Index
More informationLocation. Datum. Survey. information. Etrometa. Step Gauge. Description. relative to Herne Bay is -2.72m. The site new level.
Tide Gauge Location OS: 616895E 169377N WGS84: Latitude: 51 o 22.919196 N Longitude: 01 o 6.9335907 E Instrument Type Etrometa Step Gauge Benchmarks Benchmark TGBM = 5.524m above Ordnance Datum Newlyn
More informationOSSE OSE activities with Multivariate Ocean VariationalEstimation (MOVE)System. II:Impacts ofsalinity and TAO/TRITON.
G ODAE/O O P O SSE O SE m eeting,nov.5 7th,2007 in IO,Paris OSSE OSE activities with Multivariate Ocean VariationalEstimation (MOVE)System. II:Impacts ofsalinity and TAO/TRITON. S.Matsumoto,Y.Fujii,T.Soga,T.Yasuda,S.Ishizaki,N.Usui,and
More informationALASKA REGION CLIMATE FORECAST BRIEFING. October 27, 2017 Rick Thoman National Weather Service Alaska Region
ALASKA REGION CLIMATE FORECAST BRIEFING October 27, 2017 Rick Thoman National Weather Service Alaska Region Today Feature of the month: West Pacific Typhoons Climate Forecast Basics Climate System Review
More informationThe measurement of climate change using data from the Advanced Very High Resolution and Along Track Scanning Radiometers
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 109,, doi:10.1029/2003jc002104, 2004 The measurement of climate change using data from the Advanced Very High Resolution and Along Track Scanning Radiometers S. P.
More informationThe University of Texas at Austin, Jackson School of Geosciences, Austin, Texas 2. The National Center for Atmospheric Research, Boulder, Colorado 3
Assimilation of MODIS Snow Cover and GRACE Terrestrial Water Storage Data through DART/CLM4 Yong-Fei Zhang 1, Zong-Liang Yang 1, Tim J. Hoar 2, Hua Su 1, Jeffrey L. Anderson 2, Ally M. Toure 3,4, and Matthew
More informationOptimal Spectral Decomposition (OSD) for Ocean Data Analysis
Optimal Spectral Decomposition (OSD) for Ocean Data Analysis Peter C Chu (1) and Charles Sun (2) (1) Naval Postgraduate School, Monterey, CA 93943 pcchu@nps.edu, http://faculty.nps.edu/pcchu/ (2) NOAA/NODC,
More informationSimulated Radiances for OMI
Simulated Radiances for OMI document: KNMI-OMI-2000-004 version: 1.0 date: 11 February 2000 author: J.P. Veefkind approved: G.H.J. van den Oord checked: J. de Haan Index 0. Abstract 1. Introduction 2.
More informationNCODA Implementation with re-layerization
NCODA Implementation with re-layerization HeeSook Kang CIMAS/RSMAS/U. Miami with W. Carlisle Thacker NOAA/AOML HYCOM meeting December 6 2005 1 GULF OF MEXICO MODEL CONFIGURATION: Horizontal grid: 1/12
More information