hymn
DESCRIPTION
Hydrogen, Methane and Nitrous oxide: Trend variability, budgets and interactions with the biosphere GOCE-CT-2006-037048. HYMN. September 2007. Contents. Objectives Partners Project overview Biosphere-atmosphere interactions Ground-based observations Satellite observations - PowerPoint PPT PresentationTRANSCRIPT
Hydrogen, Methane and Nitrous oxide:Trend variability, budgets and interactions with the
biosphere
GOCE-CT-2006-037048
HYMN
September 2007
Contents
Objectives Partners Project overview Biosphere-atmosphere interactions Ground-based observations Satellite observations Chemistry-transport modeling CH4, N2O and H2 Improved source estimations (inverse modeling)
HYMN Objectives
Improve process models of land-biosphere-atmosphere exchange of the HYMN gases and provide global and regional estimates of their natural sources and sinks.
Provision of multi-year global satellite data sets of CH4 and CO and long-term time series of CH4 and N2O at a range of observing stations.
Provide advice on further optimization of monitoring networks for the HYMN gases (esp. FTIR).
Quantify atmospheric loss of CH4 and H2 and the impact of changing anthropogenic and natural (climate-induced) emissions on regional OH trends and on current and future global CH4 and H2 levels.
Quantify how the possible future change to a hydrogen economy will affect the H2 distribution and the distribution of CH4 and O3 through changes in emissions of H2 and pollutants (NOx, CO, VOCs).
Evaluate simulations with a new coupled atmospheric chemistry-biosphere model for CH4, N2O and H2 by comparison with ground based and satellite observations on a global and regional scale.
Provide new estimates of the sources and sinks of CH4 and H2 including their temporal and spatial variability.
Partners
No Partner Short name Country
1 Royal Netherlands Meteorological Institute (coordinator) KNMI NL
2 University of Bristol UNIVBRIS UK
3 University of Oslo UiO NO
4 University of Heidelberg UHEI.IUP DE
5 Centre National de la Recherche Scientifique-Laboratoire des Sciences du Climat et de l’Environnement
CNRS-LSCE FR
6 University of Bremen Uni-HB DE
7 Belgian Institute for Space Aeronomy BIRA-IASB BE
8 University of Liège ULg BE
9 Chalmers Tekniska Hoegskola Aktiebolag Chalmers SV
10 Forschungszentrum Karlsruhe, Institut für Meteorologie und Klimaforschung – Atmospheric Environmental Research
FZK-IMK-IFU DE
11 University of Karlsruhe, Institut für Meteorologie und Klimaforschung – Atmospheric Trace Constituents and Remote Sensing
UniKarl DE
12 Commisariat à l’Energie Atomique - Laboratoire des Sciences du Climat et de l’Environnement
CEA-LSCE FR
HYMN Project overview
WP2 Biosphere-atmosphereinteractions
WP
1 P
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HYMN
WP3 Satelliteobservations
WP5 Model Integration and
Evaluation
WP4 Observationsfrom ground networks
WP6 Inverse Modelling and 4d-var
Data Assimilation
Modules
Satellite obs
FTIR obsSurface obs
Integrated Models
Monitoring database
Sinks and sources
Suggestions for Improvements
Trends
Assessment
WP2: Biosphere-atmosphere interactions
Objective: further develop and provide a climate-driven global biosphere/land model for HYMN gases
Based on LPJ and including
CH4 emissions from wetlands, permafrost (LPJ-WHy) CH4, CO, NOx, H2 emissions from fires (SPITFIRE) N2O & NOx fluxes from soils (microbes) H2 fluxes from N-fixation
Interface to global atmospheric chemistry-transport models
Sitch et al., 2003
LPJ: modeling biosphere-atmosphere interactions
Comparison to Satellite Observations
LPJ-WHy model
WP3: Satellite observations
Objectives consistent data set of SCIAMACHY CH4 and CO from 2003 onward
+ error estimates consistent data set of IMG/IASI CH4 + error estimates investigate combined SCIAMACHY-IASI CH4 retrieval
Clerbaux et al., ACP, 2003
WP3: IMG CH4 retrieval
April 1997
Forms basis for retrieval from IASI (launched October 2006)
WP3: IMG vertical information
WP3: Sciamachy CH4 new retrievals
• Improved T- profile (ECMWF)
• Updated spectroscopy
SCIAMACHY CH4 (2003-2004)
Frankenberg et al, JGR, 2006
Frankenberg et al, JGR, 2006
Cloud top height < 2.5km;shows CH4 long-range transport
Frankenberg et al, JGR, 2006
SCIAMACHY CH4 regional: AsiaFrankenberg et al, JGR, 2006
WP4: Observations from ground-based networks
Objectives Perform FTIR measurements at 7 stations (28-80 N) once a week
(if sky is clear) during HYMN (2006-2009). 3-month measurement campaign at La Réunion Optimise, standardise retrieval and error estimates CH4, N2O Construct historical time series Validate satellite CH4 with FTIR
WP4: FTIR time series from Jungfraujoch
Trend of tropospheric and stratospheric column abundances wrt 2000? Significantly positive: ranges from (0.1 0.05 )%/yr to (0.6 0.1 )%/yr ; except for tropo- column at Izana: - 0.26(±0.09) )%/yr
reasonably good agreement with UiO 3D model simulations
Seasonal variation is obvious
Consistent data sets; possibly not optimal yet...
UFTIR data set for CH4 (total column)
UFTIR data set for N2O (total column)
N2O
3.50E+18
4.00E+18
4.50E+18
5.00E+18
5.50E+18
6.00E+18
6.50E+18
-2500 -1500 -500 500 1500 2500
NyAl_TC
Kiruna
Izana
Harestua
Jungfraujoch
Zugspitze
Trend: significantly positive, in agreement with the surface trend of +(0.25 0.05) %/yr reported in IPCC 2003 based on in-situ observations
WP5: Model integration and evaluation
Objectives
Evaluate current chemistry models against satellite and ground-based observations
Same for new coupled biosphere-chemistry model
Quantify the effect of changing natural and anthropogenic emissions (including climate-driven vegetation fluxes) on CH4, OH, O3 and H2 – on decadal time scales
Quantify the effect of the transformation to a hydrogen economy
Tropospheric OH 1990-2001
Dalsoren and Isaksen,JGR, 2007
Emission changes in the period 1990-2001 caused a global average increase in OH of 0.08 %/yr. The global increase in OH is driven by changes in the Northern Hemisphere. Deviations from the trend were found in years with much biomass burning.
WP6: Inverse modelling & data assimilation
Objectives
Derive error estimates for model and observational errors (satellite and surface-based)
Determine surface fluxes of CH4 and H2 (1980-2000) by inverse modelling and data assimilation
Estimate evolution of OH (1980-2000)
Meirink et al., 2006 (Evergreen)
WP6: Inverse modelling & data assimilation
Large differences between tropical wetland CH4 emissions
Need for improved models and inversions
WP6: Inverse modelling & data assimilation
LMDZT-SACS: New simplified atmospheric chemistry system for inversions
WP6: Inverse modelling & data assimilation
LMDZT-SACS: New simplified atmospheric chemistry system for inversions
Links with other EU projects
ACCENT (Atmospheric Composition Change: the European NeTwork of excellence) Model evaluation, emissions
EUROHYDROS (A European Network for Atmospheric Hydrogen observations and studies) Surface observations and modeling
GEOMON (Global Earth Observation and Monitoring) Model evaluation Surface observations
QUANTIFY: Ship & aviation emissions
HyCARE (Hydrogen energy: ChAnces and Risks for the Environment) Hydrogen forum
Past related projects: Evergreen (EnVisat for Environmental Regulation of GREENhouse gases) UFTIR (Time series of Upper Free Troposphere observations from a
European ground-based FTIR network)
