Transcript Document

LIFE07 ENV/FIN/000133
SNOWCARBO Stakeholder Meeting
14.12.2011 Helsinki-Finland
CONTENTS
• INTRODUCTION
• BACKGROUND & AIMS
• MAIN ACTIVITIES
• EXPECTED RESULTS
• METHODOLOGY
• PROGRESSES
• MAIN TECHNICAL ACHIEVEMENTS
• FUTURE WORK
PROJECT LOCATION: Helsinki
BUDGET INFO:
Helsinki
Total amount: 2 155 000 €
% EC Co-funding: 1 046 000 €
DURATION: Start: 01/01/09 - End: 31/12/12
PROJECT’S IMPLEMENTORS:
Coordinating Beneficiary: Finnish Meteorological Institute (FMI)
Associated Beneficiary(ies): Finnish Environment Institute (SYKE),
Commissariat à l'énergie atomique – Laboratoire des Sciences du
Climat et de l’Environnement (CEA-LSCE)
Project management
Project primary stakeholders
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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
(Metsähallitus) 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).
Secondary stakeholders
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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 Agency’s (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.
BACKGROUND & AIMS
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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
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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
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The mapping of carbon sinks is a major issue concerning the implementation
of Kyoto protocol and concerning future climate treaties
MAIN EU POLICY(IES) TARGETED
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DG ENV: Action on Climate Change Post 2012
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DG ENV: European Climate Change Programme (ECCP)
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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)
MAIN ACTIVITIES
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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.
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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
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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
EXPECTED RESULTS
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Maps of carbon uptake by terrestrial vegetation, soil respiration and net
carbon balance in different land use and cover classes
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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
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Evaluation of the required performance characteristics of Eurasian land
cover information for the needs of net carbon balance mapping/monitoring
METHODOLOGY
METHODOLOGY
Weather station data:
• Synoptic weather data
Satellite data:
• Snow Covered Area
• Snow Depth/Water equivalent
• Land Cover Data
REMO – JSBACH
Model System
Product
validation
REMO – Regional Climate Model
JSBACH – Biosphere-Atmosphere
Model
Validation and
error
estimation
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)
Direct validation:
• CO2- flux measurements
• CO2- consentration measurements
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
METHODOLOGY
PROGRESSES
PROGRESSES
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.
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
Implementing Yasso07 to JSBACH
• Replacing the original soil carbon model CBALANCE
of JSBACH by a new soil carbon model Yasso07
Soil carbon pools (kg m-2): CBALANCE
vs. Yasso07
CBALANCE
Yasso07
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30 year-long CDR time-series on snow conditions
of Northern Hemisphere (ESA-GlobSnow SWE)
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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
Finnish Meteorological Institute
16.7.2015
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Start of growing season of evergreen coniferous forest
from MODIS time-series for comparison with model results
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Reference date for start of season is the final
recovery of photosynthesis determined at
CO2 flux measurement sites in Finland
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Good correspondence between in situ dates
and decrease of fractional snow cover and
spring-rise of NDVI
Temporal profiles at Sodankylä 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 Sodankylä. FGS started on
26.04.2006.
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Extraction of start of season based on NDVI
time-series for pixels with 90% coverage with
coniferous forest
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Aggregation of results for comparison with
model-derived start of season
Evaluation of required North-Eurasian Land cover information
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Collection of land cover data needs in carbon
balance modeling at FMI
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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
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GLOBCOVER (regional version 2.2)
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CORINE Land Cover (2000 and 2006)
2. Production of a new land cover data set for the
modeling area
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Low resolution satellite data (TERRA MODIS)
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High resolution satellite data (IRS LISS,
KOMPTSAT)
>> Different revised land cover data sets with Olsson
nomenclature provided
MAIN TECHNICAL ACHIEVEMENTS
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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.
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
Sodankylä 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.