European Geosciences Union General Assembly 2015

Slides:

Advertisements

Similar presentations

Coupled modelling - snow Patrick Samuelsson Rossby Centre, SMHI

Advertisements

Land Surface Evaporation 1. Key research issues 2. What we learnt from OASIS 3. Land surface evaporation using remote sensing 4. Data requirements Helen.

Collaboration with ECMWF on Land Surface Hydrology Hannah Cloke Department of Meteorology Department of Geography & Environmental Science

Polly Smith, Alison Fowler, Amos Lawless School of Mathematical and Physical Sciences, University of Reading Exploring coupled data assimilation using.

Assessing the impact of a soil surface crust on simulated overland flow at the field scale. N. Chahinian (1, 2), M. Voltz (2), R. Moussa (2), G. Trotoux.

NAFE’06 Planning Workshop 1 A BMRC and eWater Perspective Clara Draper Dr. Jeffrey Walker & Dr. Peter Steinle (BMRC)

Vienna 15 th April 2015 Luca Brocca(1), Clement Albergel(2), Christian Massari(1), Luca Ciabatta(1), Tommaso Moramarco (1), Patricia de Rosnay(2) (1) Research.

1 Climate change and the cryosphere. 2 Outline Background, climatology & variability Role of snow in the global climate system Contemporary observations.

Slide 1 Assimilation of near real time GEOV Albedo and Leaf Area Index within the ECMWF modelling system Souhail Boussetta, Gianpaolo Balsamo, Emanuel.

© ECMWF GCW contribution from ECMWF Use of snow observations in NRT Analysis, Reanalysis and Verification prepared by Patricia de Rosnay, Gianpaolo Balsamo,

1 Streamflow Data Assimilation - Field requirements and results -

SMOS – The Science Perspective Matthias Drusch Hamburg, Germany 30/10/2009.

Catchment Monitoring for Scaling and Assimilation of Soil Moisture and Streamflow C. Rüdiger a, R.E. Davidson b, H.M. Hemakumara b, J.P. Walker a, J.D.

Outline Background, climatology & variability Role of snow in the global climate system Indicators of climate change Future projections & implications.

Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean model Polly Smith, Alison Fowler & Amos Lawless School of.

Assimilation of MODIS and AMSR-E Land Products into the NOAH LSM Xiwu Zhan 1, Paul Houser 2, Sujay Kumar 1 Kristi Arsenault 1, Brian Cosgrove 3 1 UMBC-GEST/NASA-GSFC;

Slide 1/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Value of Ground Network Observations in Development of Satellite.

Microwave Remote Sensing Group 1 P. Pampaloni Microwave Remote Sensing Group (MRSG) Institute of Applied Physics -CNR, Florence, Italy Microwave remote.

The ELDAS system implementation and output production at Météo-France Gianpaolo BALSAMO, François BOUYSSEL, Jöel NOILHAN ELDAS 2nd progress meetin – INM.

L. Kergoat, F. Timouk, E. Mougin, E. Ceschia, P. Hiernaux, P. de Rosnay, V. Le Dantec CESBIO, Toulouse, France C.R. Lloyd, C.M. Taylor, CEH, Wallingford.

DA Surface Analysis (II) M. Drusch Room TT 063, Phone 2759.

Project Title: High Performance Simulation using NASA Model and Observation Products for the Study of Land Atmosphere Coupling and its Impact on Water.

Enhancing the Value of GRACE for Hydrology

1 Soil Moisture Assimilation in NCEP Global Forecast System Weizhong Zheng 1, Jerry Zhan 2, Jiarui Dong 1, Michael Ek 1 1 Environmental Modeling Center,

IntroductionPurposesMethods Study area ResultsConclusions EGU 2012 Wien 24 th April 2012 Brocca Luca 1 Research Institute for Geo-Hydrological Protection,

Evaluating hydrological model structure using tracer data within a multi-model framework Hilary McMillan 1, Doerthe Tetzlaff 2, Martyn Clark 3, Chris Soulsby.

Soil moisture generation at ECMWF Gisela Seuffert and Pedro Viterbo European Centre for Medium Range Weather Forecasts ELDAS Interim Data Co-ordination.

Part I: Representation of the Effects of Sub- grid Scale Topography and Landuse on the Simulation of Surface Climate and Hydrology Part II: The Effects.

Pg. 1 Using the NASA Land Information System for Improved Water Management and an Enhanced Famine Early Warning System Christa Peters-Lidard Chief, Hydrological.

Page 1 Developments in regional DA Oct 2007 © Crown copyright 2007 Mark Naylor, Bruce Macpherson, Richard Renshaw, Gareth Dow Data Assimilation and Ensembles,

CMEMS Mediterranean MFC. Update on specific development for CMEMS Med-MFC V2 Analysis and Forecast Product 1.Data Assimilation: Grid point EOFs ( * )

1 INM’s contribution to ELDAS project E. Rodríguez and B. Navascués INM.

Contact © European Union, Monitoring the State of the Global Terrestrial Surfaces The state of vegetation is analysed using.

VERIFICATION OF A DOWNSCALING SEQUENCE APPLIED TO MEDIUM RANGE METEOROLOGICAL PREDICTIONS FOR GLOBAL FLOOD PREDICTION Nathalie Voisin, Andy W. Wood and.

EVALUATION OF A GLOBAL PREDICTION SYSTEM: THE MISSISSIPPI RIVER BASIN AS A TEST CASE Nathalie Voisin, Andy W. Wood and Dennis P. Lettenmaier Civil and.

© ECMWF ERA5: Collaboration between EUMETSAT and ECMWF (and TUWien) to use of reprocessed Scatterometer soil moisture data record for 1991-present in ERA5.

The SCM Experiments at ECMWF Gisela Seuffert and Pedro Viterbo European Centre for Medium Range Weather Forecasts ELDAS Progress Meeting 12./

 It is not representative of the whole water flow  High costs of installation and maintenance  It is not uniformly distributed in the world  Inaccessibility.

NASA, CGMS-44, 7 June 2016 Coordination Group for Meteorological Satellites - CGMS SURFACE PRESSURE MEASUREMENTS FROM THE ORBITING CARBON OBSERVATORY-2.

© Crown copyright Met Office Review topic – Impact of High-Resolution Data Assimilation Bruce Macpherson, Christoph Schraff, Claude Fischer EWGLAM, 2009.

In order to accurately estimate polar air/sea fluxes, sea ice drift and then ocean circulation, global ocean models should make use of ice edge, sea ice.

Luca Brocca, Christian Massari, Luca Ciabatta, Tommaso Moramarco Research Institute for Geo-Hydrological Protection (IRPI-CNR), Perugia, Italy …and many.

(1)IRPI-CNR, Perugia, Italy (2)IPF-TUWIEN, Vienna, Austria (3)ECMWF, Reading, UK (4)CRP - Gabriel Lippmann, Belvaux, Grand-Duchy of Luxemburg (5)UMR-6012.

Evaluation of TRMM satellite precipitation product in hydrologic simulations of La Plata Basin Fengge Su 1, Yang Hong 2, and Dennis P. Lettenmaier 1 1.

Role of ECVs in climate-carbon feedback assessment Claire Magand Patricia Cadule, Jean-Louis Dufresne Institut Pierre Simon Laplace CMUG Integration Meeting,

Snow data assimilation at ECMWF

Land Surface Data Assimilation – Part 2

IMAGE PIXELS OF RFI<0.2 ONLY

Soil Moisture: Synergistic approach for the merge of thermal and ASCAT information 2nd User Training Workshop of Land Surface Analysis Satellite Application.

Soil analysis scheme for AROME within SURFEX

1. Analysis and Reanalysis Products

Alexander Loew1, Mike Schwank2

ASCAT soil moisture data assimilation with SURFEX

RELIABLE VALIDATION OF SOIL MOISTURE

Canadian Seasonal to Interannual Prediction System (CanSIPS)

Simulation of stream flow using WetSpa Model

Coupled crop-climate modelling

The use of remotely-sensed snow, soil moisture and vegetation indices to develop resilience to climate change in Kazakhstan Institute of Geography Contact.

The 2015 Workshop at MOISST: The Dawn of the Soil Moisture Information Age? Stillwater 2nd June 2015 New information content from soil moisture data:

Environmental Intelligence Platform – Monitoring Nutrients Pollution with Earth Observation Data for Sustainable Agriculture and Clean Waters Blue.

Hydrologic Considerations in Global Precipitation Mission Planning

Snow Depth Reports Availability on the GTS

Vegetation stress and summer fire activity in Portugal

Situation in March 2012 from the Monthly Hydrological Summary

Daniel Leuenberger1, Christian Keil2 and George Craig2

Nathalie Voisin, Andy W. Wood and Dennis P. Lettenmaier

FSOI adapted for used with 4D-EnVar

The Global Observing System for Climate Carolin Richter, Director

Evaluation of the TRMM Multi-satellite Precipitation Analysis (TMPA) and its utility in hydrologic prediction in La Plata Basin Dennis P. Lettenmaier and.

Biomass and Soil Moisture simulation and assimilation over Hungary

Presentation transcript:

European Geosciences Union General Assembly 2015 Vienna | Austria | 12 – 17 April 2015 Long term global scale root zone soil moisture monitoring at ECMWF using a surface-only land data assimilation system C. Albergel(1), P. de Rosnay(1), C. Massari(2), L. Brocca(2), J. Munoz-Sabater(1), G. Balsamo(1), E. Dutra(1), T. Kral(1), L. Isaksen(1) and S. Boussetta(1) (1)European Centre for Medium Weather Forecast (ECMWF), Reading, UK (2)Research Institute for Geo-Hydrological Protection, CNR , Italy 28/05/2018

HSAF Project at ECMWF ECMWF H-SAF activities : developing surface and root zone SM based on satellite derived surface SM data assimilation (scatterometer data) Remote Sensing : shallow near surface layer Main variable of interest : root-zone soil moisture Complementarity between model and observations Assimilation algorithms : Combines observations and model trajectory Propagates information from surface observations into deeper layers 28/05/2018

SM-DAS-2 (H14), operational since 07/2012 Based on physical soil freezing processes representation, expressed into liquid soil moisture index (daily product, 25km) ASCAT operational SSM, screen level variables (T2M, RH2M) 0-7cm, 7-28cm, 28-100cm (100-289cm) SM-DAS-3 (H27) Re-analysis of SM-DAS-2 (16km) Provide long time series of the liquid root zone soil moisture index (covering 1992-2014) ASCAT & ERS reprocessed SSM, screen level variables (T2M, RH2M) 0-7cm 7-28cm http://hsaf.meteoam.it/soil-moisture.php 28/05/2018

SM-DAS-2 (H14), operational since 07/2012 Based on physical soil freezing processes representation, expressed into liquid soil moisture index (daily product, 25km) ASCAT operational SSM, screen level variables (T2M, RH2M) 0-7cm, 7-28cm, 28-100cm (100-289cm) SM-DAS-3 (H27) Re-analysis of SM-DAS-2 (16km) Provide long time series of the liquid root zone soil moisture index (covering 1992-2014) ASCAT & ERS reprocessed SSM, screen level variables (T2M, RH2M) 0-7cm 7-28cm http://hsaf.meteoam.it/soil-moisture.php 28/05/2018

SM-DAS-3 (H27) : 2007-2013 Surface-only Land Data Assimilation System : ASCAT reprocessed data and screen level variables (T2M, RH2M) 28/05/2018

SM-DAS-3 (H27) : 2007-2013 Surface-only Land Data Assimilation System : ASCAT reprocessed data and screen level variables (T2M, RH2M) R R Anomaly time series USCRN USCRN R R Anomaly time series SCAN SCAN Better quality More data available 28/05/2018

SM-DAS-3 (H27) : evaluation H27 vs. in situ measurements (France, USA) Winter Spring Summer Autumn Obs. H27 Monthly anomalies SCAN (USA) SMOSMANIA (Fr.) USCRN (USA) Obs. H27 2010-2011 28/05/2018

SM-DAS-3 (H27) : evaluation H27 used for initializing simple event based rainfall-runoff model “Simplified Continuous Rainfall Runoff” model (SCRRM, Massari et al. 2014, HESS) Chiani Catchment 460 km2 (sub catchment of the Tiber River) 19 flood events, mean Nash-Sutcliffe=0.59, median Nash-Sutcliffe=0.69 Results provided by C. Massari, L. Brocca, Research Institute for Geo-Hydrological Protection, CNR , Italy 28/05/2018

SM-DAS-3 (H27) : evaluation Estimating rainfall from soil moisture (Italy) talk from Brocca et al / EGU2015-2464 Better results compared to a control experiment (i.e. no data assimilation) 1 layer of soil [0-7] 5 days accumulated rainfall 1-3 layers of soil [0-100cm] 5 days accumulated rainfall Brocca, L., et al. (2013). A new method for rainfall estimation through soil moisture observations. Geophysical Research Letters, 40(5), 853-858, doi:10.1002/grl.50173. http://dx.doi.org/10.1002/grl.50173 Results provided by C. Massari, L. Brocca, Research Institute for Geo-Hydrological Protection, CNR , Italy 28/05/2018

SM-DAS-3 (H27) : evaluation Surface / atmosphere interaction 1-day forecast initialised everyday (00:00UTC) June-Aug. 2008 using a control (Tctrl) and H27 (TH27) [uncoupled system] Sensitivity(T2M) = TH27 - Tctrl Blue : more water, cooling Yellow-red : less water, heating 28/05/2018

Monthly mean soil moisture increments SM-DAS-3 (H27) : evaluation Surface / atmosphere interaction 1-day forecast initialised everyday (00:00UTC) June-Aug. 2008 using a control (Tctrl) and H27 (TH27) [uncoupled system] Sensitivity(T2M) = TH27 - Tctrl Blue : more water, cooling Yellow-red : less water, heating Monthly mean soil moisture increments (0-100cm) for July and June 2008 28/05/2018

SM-DAS-3 (H27) : evaluation Surface / atmosphere interaction 1-day forecast initialised everyday (00:00UTC) June-Aug. 2008 using a control (Tctrl) and H27 (TH27) [uncoupled system] Sensitivity(T2M) = TH27 - Tctrl Impact(T2M) = |TH27 – Tan*|-|Tctrl- Tan | *Tan ECMWF IFS Blue : more water, cooling Yellow-red : less water, heating Blue : reduces errors Yellow-red : increases errors 28/05/2018

Water holding capacity = f(soil texture) SM-DAS-3 (H27) : Perspectives Key aspect of DA : prescription of background and observations errors H14 (H27 preliminary version) : fixed in time and space (0.01 m3m-3 model, 0.05 m3m-3 ASCAT) Background error : % of the water holding capacity (varies in space) [e.g. 5%, 3%, 1% for soil layers 1-3] Observation error (ASCAT) : ASCAT noise (varies in time and space) Water holding capacity = f(soil texture) ASCAT monthly mean Noise (march 2010) 28/05/2018

SM-DAS-3 (H27) : Perspectives Key aspect of DA : prescription of background and observations errors H14 (H27 preliminary version) : fixed in time and space (0.01 m3m-3 model, 0.05 m3m-3 ASCAT) Background error : % of the water holding capacity (varies in space) [e.g. 5%, 3%, 1% for soil layers 1-3] Observation error (ASCAT) : ASCAT noise (varies in time and space) Layer 1 (0-7cm) Layer 2 (7-28cm) Layer 3 (28-100cm) 28/05/2018

SM-DAS-3 (H27) : Perspectives Develop & evaluate H27 over 1992-2014 In situ measurements when/where available Hydrological model T2m / RH2m forecast Optimise background and model errors Assess H27 added value compared to a control model experiment Impact of the different observations type (satellite derived SSM, screen level variables) 28/05/2018

http://hsaf.meteoam.it (/soil-moisture.php) European Geosciences Union General Assembly 2015 Vienna | Austria | 12 – 17 April 2015 Long term global scale root zone soil moisture monitoring at ECMWF using a surface-only land data assimilation system Thank you for your attention! Contact : clement.albergel@ecmwf.int http://hsaf.meteoam.it (/soil-moisture.php) 28/05/2018