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LIFE07 ENV/FIN/000133 SNOWCARBO Stakeholder Meeting 14.12.2011 Helsinki-Finland.

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  • Slide 1
  • LIFE07 ENV/FIN/000133 SNOWCARBO Stakeholder Meeting 14.12.2011 Helsinki-Finland
  • Slide 2
  • CONTENTS INTRODUCTION BACKGROUND & AIMS MAIN ACTIVITIES EXPECTED RESULTS METHODOLOGY PROGRESSES MAIN TECHNICAL ACHIEVEMENTS FUTURE WORK
  • Slide 3
  • PROJECT LOCATION: Helsinki BUDGET INFO: Total amount: 2 155 000 % EC Co-funding: 1 046 000 PROJECTS IMPLEMENTORS: Coordinating Beneficiary: Finnish Meteorological Institute (FMI) Associated Beneficiary(ies): Finnish Environment Institute (SYKE), Commissariat l'nergie atomique Laboratoire des Sciences du Climat et de lEnvironnement (CEA-LSCE) DURATION: Start: 01/01/09 - End: 31/12/12 Helsinki
  • Slide 4
  • Project management
  • Slide 5
  • National stakeholders Ministry of Transport and Communications (governing body of FMI) Ministry of the Environment (governing body of SYKE) Ministry of Agriculture and Forestry, National Forestry Board (Metshallitus) and forestry industry Statistics Finland Finnish Forest Research Institute (METLA) Agrifood Research Finland (MTT) European Comission Green Paper follow up (adaption policy development) European Climate Change Programme II (ECCP) International environmental monitoring activities including Arctic Monitoring and Assessment Programme (AMAP) Sustained Arctic Observing Networks (SAON) initiative of the Arctic Council Global Atmosphere Watch (GAW) programme of the World Meteorological Organization (WMO). Project primary stakeholders
  • Slide 6
  • The spatial and temporal changes in snow cover have widespread impacts on ecosystems and human activities flooding, water resources management, agriculture, transportation, hydropower production, reindeer husbandry, game management, biological diversity, insurance, tourism and recreational use of nature. => national and international organizations and companies related to these issues are secondary stakeholders of the project Secondary stakeholders include organizations that support the snow monitoring systems used in the project Snow and phenology monitoring services of FMI and SYKE applied in the project are part of European Space Agencys (ESA) GMES (Global Monitoring of Environment and Security) Services (projects Polar View and Land). Environment Canada snow melt monitoring data (based on space-borne microwave scatterometers) covering northern Eurasia and America. Secondary stakeholders
  • Slide 7
  • BACKGROUND & AIMS Magnitudes of carbon sinks and sources of boreal forests are currently estimated only in single locations or coarsely for very large regions => Handicap the performance of climate scenarios and the evaluation of anthropogenic influences to climate change The information on global and regional level is limited as the distributed ground-based point-wise observations do not provide data sufficient spatially => Effect the high uncertainty in the location and magnitude of carbon sinks The mapping of carbon sinks is a major issue concerning the implementation of Kyoto protocol and concerning future climate treaties
  • Slide 8
  • MAIN EU POLICY(IES) TARGETED DG ENV: Action on Climate Change Post 2012 DG ENV: European Climate Change Programme (ECCP) Relevant to: European Strategic Energy Technology Plan SET (DG TREN), Integration of climate change into the EU s Rural Development Policy (DG AGRI), Water Information System for Europe, WISE (DG ENV)
  • Slide 9
  • MAIN ACTIVITIES Development of a novel Earth observation satellite data-aided system for the monitoring of annual carbon balance by applying observations of hydrological phenomena, phenology, CO2 fluxes and CO2 concentration. Use of snow melt information together with GIS land cover data and CO2 flux/concentration measurements to assess the annual carbon balance with a high spatial resolution Use of dedicated models for different soil/vegetation types and CO2 together with a climate model are applied for the determination of carbon sinks and sources
  • Slide 10
  • EXPECTED RESULTS Maps of carbon uptake by terrestrial vegetation, soil respiration and net carbon balance in different land use and cover classes Demonstration of the mapping of carbon sources and sinks in boreal forest zone (northern Finland, northern Eurasia) and the assessment of natural background sources from the anthropogenic influence Evaluation of the required performance characteristics of Eurasian land cover information for the needs of net carbon balance mapping/monitoring
  • Slide 11
  • METHODOLOGY
  • Slide 12
  • Weather station data: Synoptic weather data Direct validation: CO2- flux measurements CO2- consentration measurements Product validation Validation and error estimation In-direct validation: NDVI time-series driven features Spring increase in photosynthesis Vegetation summer maximum Beginning of dormancy Timing of soil freezing Snow melt onset Snow clearance Satellite data: Snow Covered Area Snow Depth/Water equivalent Land Cover Data Output: CO2 flux maps with error estimates CO2 consentration maps with error estimates Carbon balance atlas for Finland and Baltic EU Guidelines for stakeholders and policy makers (in Finnish and English) REMO JSBACH Model System REMO Regional Climate Model JSBACH Biosphere-Atmosphere Model
  • Slide 13
  • METHODOLOGY
  • Slide 14
  • PROGRESSES
  • Slide 15
  • A novel Earth observation satellite data-aided modeling system to produce CO2 balance in resolution of 0.16 degrees for a domain covering Finland, Sweden, Norway and Denmark as whole as well as the Baltic countries: Estonia, Latvia and Lithuania; together with areas from most Northern Germany and Western parts of Russia IS READY.
  • Slide 16
  • SNOWCARBO- Project Results Gross Primary Production, GPP (one month average,July, 2003), (mol/m^2/s). Same type of results will be reported in hourly, daily and monthly from 2001 to 2010. SnowCarbo project will also present NET CARBON BALANCE (NEE). Table shows National Greengases inventory reporting to UNFCCC By Statistics Finland
  • Slide 17
  • Implementing Yasso07 to JSBACH Soil carbon pools (kg m -2 ): CBALANCE vs. Yasso07 17 CBALANCE Yasso07 Replacing the original soil carbon model CBALANCE of JSBACH by a new soil carbon model Yasso07
  • Slide 18
  • 30 year-long CDR time-series on snow conditions of Northern Hemisphere (ESA-GlobSnow SWE) First time reliable daily spatial information on SWE (snow cover): -Snow Water Equivalent (SWE) -Snow Extent and melt (+grain size) -25 km resolution (EASE-grid) -Time-series for 1979-2011 Passive microwave radiometer data combined with ground-based synoptic snow observations Available at open data archive (www.globsnow.info) Demonstration of NRT processing started on October 2010 Greenland, glaciers & mountains masked out 15.7.2015Finnish Meteorological Institute18
  • Slide 19
  • Start of growing season of evergreen coniferous forest from MODIS time-series for comparison with model results Reference date for start of season is the final recovery of photosynthesis determined at CO 2 flux measurement sites in Finland Good correspondence between in situ dates and decrease of fractional snow cover and spring-rise of NDVI Temporal profiles at Sodankyl from February to July 2006 of: (a) Snow Covered Area and (b) NDVI in comparison with start of flux growing season (FGS, red line) at Sodankyl. FGS started on 26.04.2006. Extraction of start of season based on NDVI time-series for pixels with 90% coverage with coniferous forest Aggregation of results for comparison with model-derived start of season
  • Slide 20
  • Evaluation of required North-Eurasian Land cover information Collection of land cover data needs in carbon balance modeling at FMI Production of up-to-dated land cover data over the modeling area 1.Evaluation of existing, up-to-date global and regional land cover data GLOBCOVER (regional version 2.2) CORINE Land Cover (2000 and 2006) 2.Production of a new land cover data set for the modeling area Low resolution satellite data (TERRA MODIS) High resolution satellite data (IRS LISS, KOMPTSAT) >> Different revised land cover data sets with Olsson nomenclature provided
  • Slide 21
  • Snow water equivalent (30 years), on-set of snow melt (30 years), snow clearance (30 years), soil freezing (2008) weekly products Implemented a modified MODIS cloud masking algorithm and deployed a new data processing server. This increases the quality of raw time-series data. Spectral measurements from the winter field campaigns were processed. The measurements are used to aid the interpretation of NDVI and SCA time-series and in accuracy assessments. Autumn field campaign was conducted for land cover data validation and accuracy assessment and spectral measurements of vegetation. Carbon balance related features, like growing season beginning and end dates, were analyzed from the CO2 flux measurements. A method for the extraction of start of season in boreal coniferous forests from NDVI time-series was developed. The start of the growing season, derived from CO2- flux measurements, was compared with the start of the growing season from NDVI- time-series from satellite data. The two datasets show good correlation. The up-to-date versions of both REMO and JSBACH models have been one-way coupled, and the models are now properly running on the FMI supercomputers, producing regional present day climates and CO2 fluxes with all the different land cover datasets currently available. Assesment of system functionality in sitewise, Finland and Baltic area was done. Tools for data extraction from REMO- model data format have been created. First comparisons of modeled snow cover and satellite data time-series are currently being compiled for evaluation of the model performance. Up-to-date sets of nordic landcover information based on Globcover v2, CORINE2006 and TERRA MODIS data have been produced and reported for carbon balance modeling purposes. MAIN TECHNICAL ACHIEVEMENTS
  • Slide 22
  • FUTURE WORK Model intracomparison - among land cover maps Model intercomparison - REMO, JSBACH, ORCHIDEE Comparison with observations Comparison of carbon-balance-related features between modeling and satellite-derived time-series Model simulation results will be mapped to show the atmospheric load of the anthropogenic emissions. Biospheric component will also be mapped and shown for different seasons, as well as the total column average from satellite measurements REMO results to surface concentration observations in Pallas and Sodankyl will be compared and specifically examine those high CO2 episodes, which may be of anthropogenic origin. Other species (CO, NOx, BC etc.) assist in determining whether the observed high CO2 episodes were truly anthropogenic.
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