Assimilation of atmospheric constituents: highlights from

ASSIMILATION OF
ATMOSPHERIC
CONSTITUENTS
HIGHLIGHTS FROM MACCII-III / COPERNICUS
[email protected]
© ECMWF
« La composition chimique de l’air, la nature des poussières
qu’il charrie nous offrent aussi leurs renseignements
particuliers. On ne saurait trop s’entourer de lumière dans la
solution d’un problème aussi difficile et aussi grave que la
prévision du temps [...] »
The chemical composition of air and the nature of the dusts it
carries provide us also with their particular information. One
has never too many pieces of information for solving such a
difficult and serious problem as weather forecasting
H. Marié-Davy
"Les mouvements de l’atmosphère
et les variations du temps"
Masson, Paris, 1877
1877
© ECMWF
MONITORING ATMOSPHERIC COMPOSITION
is now a REALITY
MA
MACC‐II Dust Aerosol Optical Depth, 2 to 6 April 2014
© ECMWF
CHEMICAL DATA ASSIMILATION
 Austin, 1992: Nudging in a stratospheric CTM (simplified chemistry)
 Fisher and Lary, 1995: 4D-Var in trajectory box model (reduced strato. chemistry)
 Elbern and Schmidt, 1999: 4D-Var in a regional Air Quality CTM
 Khattatov et al., 2000; Ménard et al., 2000; Errera and Fonteyn, 2001;...: Kalman filter
or 4D-var in global stratospheric CTMs (homogeneous and heterogeneous chemistry)
 Elbern et al., 2007: Emission rate and chemical state estimation by 4-dimensional
variational inversion in a regional Air Quality CTM
 Zhang et al., 2008; Benedetti et al., 2009;...: 3D- or 4D-var AOD assimilation
 Semane et al., 2009: impact on (UTLS) winds from ozone profile observations
 Sekiyama et al. 2010 : EnKF assimilation of lidar data (aerosol)
 Engelen and Bauer, 2011: use of composition information (CO2) for improving IR
radiance assimilation
 ...
.
(sorry for all the pioneering work not mentioned in this short anthology!)
© ECMWF
This is Copernicus!
© ECMWF
Sentinel 1a launch (3 April 2014)
This is
!
© ECMWF
© ECMWF
I
MACC-III is the fourth in a series of FP6, FP7 and
Horizon 2020 EU R&D projects (since 2005).
It is coordinated by ECMWF and the consortium
comprises 36 partners from 13 countries. It runs until
April 2015, when Copernicus Atmosphere Monitoring
Service operations will ramp up.
The main aim of the series of projects was to develop
pre-operational services in the wider field of
atmospheric composition which meet the needs of
users.
© ECMWF
Satellite and in‐situ observations
of atmospheric composition Observations Acquisition & Processing, including Emissions Estimation
Observations & Emissions
Observations & Emissions
Global Data Assimilation and Forecasting System for Atmospheric Composition
LOTOS
LOTOS
European Air
LOTOS
Quality models
LOTOS
LOTOS
Chemical Boundary
LOTOS
EM magazine
November 2013
Conditions & Meteorology
Global Analyses and Forecasts
Regional Ensemble Analyses and Forecasts
Products & Feedback
Users
Verification, Dissemination, Users Support and Interaction 


Global system evolution
Pre-GEMS, GEMS studies : IFS and CTMs separate
IFS NWPM
ECMWF
4d-var strat. ozone
assimilation (linear
scheme)
MOZART CTM
Jülich, NCAR
TM5 CTM
KNMI
GEMS: 2005-09
MACC: 2009-11
MACC-II: 2011-14
MACC-III: 2014-15
MOCAGE CTM
Météo-France
GEMS-MACC-MACC-II production : IFS and CTMs coupled
OASIS
coupler
CERFACS
MACC-III production : IFS with online chemistry
C-IFS v1
4d-var assimilation
for ozone, CO, NO2,
SO2…
C-IFS v2
Couple with aerosol and
greenhouse gases
(already online)
(keynote by V. Huijnen, KNMI)
http://atmosphere.copernicus.eu
Online catalogue, quicklooks and data
European Air
Quality
Global
atmospheric
composition
Surface fluxes:
greenhouse
gases, fires,
emissions
Radiation and
ozone layer
http://atmosphere.copernicus.eu
Main menu
Information about operational
systems
Today’s
forecast and
analysis
Five Service themes
Product
Catalogue
In Focus: recent highlight
The (distributed) products catalogue
Products
found
Search criteria
based on service
themes, species,
geographic area,
etc.
Pop-up window
with product
description
and links to
plots, data, and
validation
Atmospheric composition from space
CO2, GOSAT, ACOS/JAXA/NIES
SO2, GOME-2, SACS, BIRA/DLR/EUMETSAT
Aerosol Optical Depth, MODIS, NASA
NO2, OMI, KNMI/NASA
Satellite data monitored in the
NRT global system
Composition satellite data products are used on top of meteorological ones, in the same 4D‐Var framework but @T255L60 (ECMWF HR is run @T1279L137)
Ozone profiles
Use of MLS V3.4 shows improved fit to sondes compared to previous MACC‐II operations and T159 MLS V2 control
(A. Inness)
Natal
(5.5S, 35.3W)
Alert
(82.5N, 62.3W)
MACC
(A. Inness)
(90S,18.5W)
South Pole
Ozone in the re-analyses
ERA-Interim
[%]
Impact of assimilating NO2 and CO on O3
Mean ozone profiles for 371 ascents or descents of IAGOS aircraft
Frankfurt, February to June, 2003
With NO2 and CO
With NO2 but
not CO
IAGOS
Neither NO2 nor CO
MACC IFS-MOZART ozone
(A. Inness)
The Global Fire assimilation System
Fire Radiative Power from satellite measurements (MODIS and GEOs)...
...Converted to emissions (with estimation of plume height)
Canadian fires (July 2013)
Satellite observation of meteorology and composition (in the case of CO from MOPITT and IASI) are used for assimilation while the pollutant plumes travels in the atmosphere (one daily update)
Singapore fires (June 2013)
x
Fires from illegal burning of
forests to clear land for palm
oil plantations (Indonesia).
Record hazardous levels of
pollution were monitored in
Singapore.
Applications (solar energy)
AOD (MACC daily values)
Missing extreme values
Direct normal irradiance [W/m2]
Valladolid (Spain)
AOD (monthly climatology)
AOD assimilation & issues
Variational bias correction for March 2013 for MODIS AOD at 550 nm for global
constant and wind speed over ocean formulation (old, left) and global constant, wind
speed over ocean, and cloud cover formulation (new, right).
(A. Benedetti)
AOD assimilation & issues
CALIPSO feature mask
Aerosol & cloud amounts, Forecast only
MODIS Aerosol Optical Depth
Assimilation of AOD
only does not modify
significantly the vertical
distribution of aerosol
Aerosol & clouds amounts,
AOD Assimilation
(A. Benedetti)
Assimilation of CALIOP data (L1.5)
Period: March 21- April 2, 2012
Data: all operational data plus MODIS AOD and CALIOP Level 1.5 backscatter
Lidar backscatter x 1e7 (sr m)-1
(A. Benedetti)
GREENHOUSE GASES
COLUMN-AVERAGED DRY AIR MOLE FRACTION OF CO2 [ppm]
September 2013
WE DO
(A. Agusti Panareda, S. Massart)
© ECMWF
Assimilated GHG data in MACC-II
ENVISAT/SCIAMACHY
CH4 and CO2 – Lower tropo.
METOP-A/IASI
CH4 and CO2 – Middle tropo.
Not available since
April 2012
GOSAT/TANSO
CH4 and CO2 – Lower tropo.
Column-averaged dry-air mole fractions
of CO2 and CH4 provided by:
(S. Massart)
Assimilated GHG data in MACC-II
OCO-2
CO2 – Lower tropo.
METOP-A/IASI
CH4 and CO2 – Middle tropo.
Soon available
(early 2015)
GOSAT/TANSO
CH4 and CO2 – Lower tropo.
Column-averaged dry-air mole fractions
of CO2 and CH4 provided by:
(S. Massart)
Validation of XCO2 at Lamont
2013
Observations
Model
(S. Massart)
Validation of XCH4 at Lamont
SCIA. + TANSO
SCIA.
TANSO
TANSO + IASI
2009-13
Observations
Model
(S. Massart)
Some applications
 Support to measurement campaigns : GLAM campain over the
Mediterranean basin (August 2014)
 Reanalysis using data from ESA's Climate Change Initiative (CCI):
year 2008 using SCIAMACHY and IASI data
Some research directions
 Assimilation of profile information
 Characterisation of background errors (especially using
Ensemble Data Assimilation)
 L1 (radiances) vs L2 (products) assimilation
 Assimilation of chemically-related species
 Bias correction and its anchoring with reference data
 Coupled composition/meteorological assimilation
 high-end chemistry / lower resolution vs low-end
chemistry / higher resolution or other options
© ECMWF
Website:
http://atmosphere.copernicus.eu
Contact:
[email protected]
Copernicus Atmosphere
© ECMWF

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