CLIMSLIP Climate Impacts of Short-Lived Pollutants

CLIMSLIP Climate Impacts of Short-Lived Pollutants

CLIMSLIP
Climate Impacts of Short-Lived Pollutants & Methane in
the Arctic
(Nov. 2011 – Sept. 2015)
Kathy Law (LATMOS)
Site web : http://www.latmos.ipsl.fr/index.php/fr/tact/themes-de-recherche/climslip…
Séminaire ANR Changements Environnementaux
19-20-21 mars 2014
Consortium
• 
Projet porté par :
• 
Partenaires :
–  Kathy Law/ Gerard Ancellet, LATMOS, Paris
–  LSCE (Jean-Daniel Paris, Isabelle Pison), Paris
–  LaMP (Olivier Jourdan, Alfons Schwarzenboeck),
Clermont Ferrand
–  LGGE (Hans-Werner Jacobi, Paolo Laj), Grenoble
–  LMD (Solene Turquety), Paris
• 
Additional funding/linked projects:
CLIMSLIP-LEFE(2010-2013), CLIMSLIP-ESF (2010-2013),
and CLIMSLIP-IPEV (2012-2014), EU ECLIPSE, CNES,
POLARCAT-France
S é m i n a i r e A N R C h a n g e m e n t s E n v i r o n n e m e n t a u x 1 9 -­‐ 2 0 -­‐ 2 1 m a r s 2 0 1 4 Participants
LATMOS: K. Law, G. Ancellet, J.-C. Raut, J. Thomas, J.
Pelon, F. Ravetta, A. Bazerau, J. Delanoe, L. Marelle, B.
Quennehen, L. Doppler
LSCE: J.-D. Paris, I. Pison, A. Berchet, E. Azoumanian, A.
Pruvost
LaMP: O. Jourdan, G. Guyot, A. Schwarzeboeck, W. Wobrock,
C. Gourbeyre
LGGE: H.-W. Jacobi, P. Laj, H. Gallee
LMD: S. Turquety, Y. Long
S é m i n a i r e A N R C h a n g e m e n t s E n v i r o n n e m e n t a u x 1 9 -­‐ 2 0 -­‐ 2 1 m a r s 2 0 1 4 Overland and Wang, GRL
(2013)
ANR CLIMSLIP Motivation:
89 ensembles from 36 CMIP5
models run with RCP8.5
Arctic warming more rapidly than elsewhere, summer sea-ice
disappearing – climate models do not perform well in Arctic
Why? E.g. representation of Arctic clouds/aerosol-cloud interactions
Short-lived pollutants (ozone and aerosols) and methane
warm the atmosphere – important contributors to Arctic warming –
pollutants transported from mid-latitudes + new local sources (e.g. oil/gas)
Much interest in mitigating short-lived
pollutants e.g. Climate & Clean Air Coalition
(http://www.unep.org/ccac/), Arctic Council AMAP
Expert Group on Black Carbon & Ozone
ANR CLIMSLIP Motivation:
carbon monoxide
black carbon
Lee et al. (2013)
Global chemistry-climate
models (e.g. IPCC CMIP5) have
problems simulating seasonal
cycle of pollutants in the Arctic
& thus climate impacts
Requires better understanding
about emissions (e.g. fires),
pollutant processing during
transport & loss processes
esp. washout (surface + free
troposphere)
IPCC AR5
models
CLIMSLIP objectives:
To improve understanding about short-­‐lived pollutants (ozone, aerosols) and methane in the Arc;c: – 
– 
– 
– 
– 
– 
Tropospheric ozone/aerosols – anthropogenic vs fire emissions Pollutant processing during transport to the ArcBc Arc;c methane – quan;fica;on of sources (e.g. oil/gas, wetlands) Aerosol-­‐cloud interac;ons – new data on mixed phase/ice clouds Black carbon (BC) – new data in atmosphere/snow Climate impacts (ozone, methane, aerosols (direct effects + BC snow-­‐
albedo feedback) Combina;on of new (exis;ng) data analysis + regional/global modelling) S é m i n a i r e A N R C h a n g e m e n t s E n v i r o n n e m e n t a u x 1 9 -­‐ 2 0 -­‐ 2 1 m a r s 2 0 1 4 Etat d’avancement:
•  Field campaign in Svalbard (spring 2012)  new data on black carbon & aerosol-­‐cloud interacBons •  Analysis of new YAK aircraQ data over Siberia 2012/1 (trace gases (CH4, O3) and aerosols •  State of art inversions of methane sources over Siberia •  Regional case studies of ozone/aerosol plume processing •  New scheme for fire plume rise in global chemistry-­‐climate model (LMDzORINCA) •  New retrievals of Arc;c aerosols/clouds using CALIOP/
CloudSAT satellite data + validaBon (IASI, CALIOP) •  1 year extension to Sept. 2015 (addi%onal YAK campaign with new French aerosol lidar instrument (fall 2014), chemistry-­‐climate modelling) S é m i n a i r e A N R C h a n g e m e n t s E n v i r o n n e m e n t a u x 1 9 -­‐ 2 0 -­‐ 2 1 m a r s 2 0 1 4 ANR CLIMSLIP: CAMPAIGNS
x
YAK-­‐AEROSIB Yakutsk
Trace gas & aerosols summer 2012/13, Siberia Analysis of ANR-­‐POLARCAT(IPY) spring/summer 2008 data X
x
ANR CLIMSLIP: Svalbard, spring 2012 (soot dNorilsk
eposi;on & aerosol-­‐cloud interac;ons) Xx Svalbard
Kangerlussuaq
X Kiruna
Arctic Aerosol distributions (CALIOP) - spring 2008
based on new retrieval algorithms
0 to 2 km
4 to 6 km
532nm aerosol scattering ratio
Ancellet et al. (ACPD)
Evidence for secondary aerosol max. in free tropopshere due to boreal fires
+ Asian emissions transported to Arctic in spring 2008 – superimposed on
declining « Arctic Haze » below 2km (Law et al., 2014 – POLARCAT review)
Improved characterization of Arctic mixed phase
clouds using aircraft data and satellite retrievals
Cloud top
 In situ characteriza;on of mixed phase clouds microphysical proper;es (Svalbard/ASTAR)) Supercooled droplets (cloud top) + precipita;ng ice (cloud base) Cloud base
WINTER SPRING Cloud fracBon (%) Below cloud
Seasonal frequency occurrences of mixed  phase clouds from CALIPSO-­‐CloudSat observa;ons (2007-­‐2010) – DARDAR algorithm Svalbard in region with high % of mixed-­‐phase clouds (use to improve washout processes in models) SUMMER FALL Mioche et al. (in prep.)/collab. ECCLAT
Pollution transport
from North America to
Greenland
4 July – 7 July 2008 Pollutant plumes upliQed from 1-­‐2km to 8km by synop;c fronts Fire Analysis of POLARCAT data using regional WRF-­‐Chem model Anthropogenic Pommier et al. (2010) Thomas et al. (2013) Pollution impact on ozone in the Arctic
troposphere
Significant ozone production in fire and anthropogenic plumes transported from North America to Greenland
Thomas, et al., 2013.
800
800
CO (ppbv)
800
O3 (ppbv)
200
0
800
50 100 150 200 250 300
CO (ppbv)
DC8 20080629-20080713
800
1000
0
r=0.83
r=0.81
r=0.82
r=0.88
r=0.91
r=0.86
r=0.76
r=0.69
r=0.86
r=0.89
0
0
0
50
600
1000
0.00
DC8 20080629-20080713
0.05 0.10 0.15
OH (pptv)
0.20
DC8 20080629-20080713
50 100 150 200 250 300
200 (ppbv)
CO
r=0.97
r=0.97
r=0.99
r=0.95
r=0.96
r=0.93
r=0.78
r=0.98
r=0.98
r=0.97
400
400
800
100
O3 (ppbv)
200
Alt (hPa)
0
1000
10
600
r=0.97
r=0.97
r=0.99
r=0.99
r=0.99
r=0.99
r=0.88
r=0.98
r=0.99
r=1.00
r=0.82
r=0.88
r=0.94
r=0.91
r=0.93
r=0.95
r=0.86
r=0.66
r=0.93
r=0.76
r=0.91
r=0.98
r=0.69
r=0.93
r=0.83
r=0.86
r=0.63
r=0.89
Alt (hPa)
600
r=0.83
DC8 20080401-20080419
r=0.81
200
Alt (hPa)
0
400
400
Alt (hPa)
r=0.99
r=0.98
r=0.99
r=0.99
r=0.98
r=0.96
r=0.99
r=0.99
r=0.99
r=0.99
0
Alt (hPa)
200
Alt (hPa)
DC8 20080401-20080419
400
r=0.30
r=0.33
r=0.88
r=0.64
r=0.58
r=0.60
r=0.80
r=0.35
r=0.27
r=0.34
0.05 0.10
OH (pptv)
DC8 20080629-20080713
DC8 20080629-2
POLARCAT model intercomparison project (POLMIP): models run with same emissions 200
200
•  General underesBmaBon of carbon monoxide r=0.97
(CO), except LMDzORINCA r=0.97
400
• 400
Fire plumes strongly r=0.99
underesBmated (Monks et al., 2014) r=0.95
r=0.96
600
Obs.
CAM4Chem
800
CAM5Chem
CIFS
GEOSChem
GMI
1000
LMDZ-INCA
MATCH
10
MOZART
TM5
TOMCAT
Alt (hPa)
20080629-20080713
NASA DC8 aDC8
ircraQ data (June-­‐July 2008) 0
0
0
r=0.88
r=0.98
r=0.99
r=1.00
Global modelling of ozone and its
1000
1000
1000
precursors
–
role
of
boreal
fires
0 50 100 150 200 250 300
10
100
0.00
DC8 20080401-20080419
0
0
r=0.99
r=0.99
r=0.99
r=0.99
r=0.93
600
r=0.78
r=0.98
r=0.98 of CO (850hPa) ModificaBon 800
r=0.97
(plume rise – surface emission) 100
O3 (ppbv)
1000
0.0
0.1
0.2 0.3
OH (pptv)
600 of plume rise fire model to Implementa;on account for pyro-­‐convec;on in LMDZORINCA : 800
800
•  EvaluaBon against satellite ofrom
bservaBons Fig.
7.
DC8
vertical
the
spring
(top)
and
summer
(botto
1000
1000 profiles
100 150 200 250 300
10
100
0.0 0.1 0.2 0.3 0.4 0.5
shows (first results) CO (ppbv)
O (ppbv)good consistency OH (pptv)
concentrations
of
CO
(left),
Oof 3pollutants (middle)
•  Direct impact on transport and OH (right) along with erro
S é m i n a i r e A N R C h a n g e m e n t s E n v i r o n n e m e n t a u x 1 9 -­‐ 2 0 -­‐ 2 1 m a r s 2 0 1 4 Long et al., in prep. percentiles of the observations.
Pearson’s
correlation coefficients are al
600
3
vertical profiles from the spring (top) and summer (bottom) ARCTAS campaign. Median
s of CO (left), O3 (middle) and OH (right) along with error bars showing the 25th and 75th
New yak aircraft campaigns over siberia in
Summer 2012/2013 2013 campaign: CO concentraBons Backplume for high CO, fires in 2012 •  Signal dominated by fires in 2012 (very high CO in plumes) •  Analysis of air mass origins (ozone) (Berchet et al., 2013) •  InstallaBon of aerosol micro-­‐
lidar (LATMOS, IAO Tomsk, LSCE) + analysis of Russian aerosol data •  New CH4 data over Siberia (LSCE) Inverse modelling of natural &
anthropogenic CH4 fluxes in Siberia
 
 
 
 
 
 
Total emissions over Siberia (2010) (5.5-­‐22.7 TgCH4 yr-­‐1): Natural : 0-­‐12 TgCH4yr-­‐1 Anthropogenic : 5-­‐12 TgCH4yr-­‐1 => 60% reduc;on uncertain;es over study region (lowlands) Berchet et al., in prep. Methane sources : oil/gas, urban, wetlands, boreal fires New analyBc method to reduce uncertainBes Used regional model CHIMERE & available data (13 staBons (10 conBnuous & 3 daily flasks) Climslip Field Campaign Svalbard (Mar. -May 2012) :
Aerosol-Cloud Interactions on Mount Zeppelin (480m)
-­‐  “Aged” pollu;on -­‐ low concentraBon of -­‐  Local pollu;on -­‐ higher fracBon of « small » aerosols (D<100nm) “small” aerosols -­‐  Lower acBvaBon fracBon ranging from -­‐  Aerosol acBvaBon fracBon (red dots) 40% to 60 % from 60% to 100 % -­‐  Long-­‐range transport of aerosols from -­‐  Local sources (ArcBc or Kola Peninsula) Russia or Canada Air masses from Russia:
SP2 Zeppelin (32 ± 23) ng m-­‐3 Aethalometer Corbel (48 ± 27) ng m-­‐3 Aethalometer Zeppelin (48 ± 24) ng m-­‐3 Laboratoire de Glaciologie et Géophysique de l’Environnement, Grenoble, France
CLIMSLIP Field Campaign (March/April 2012):
New measurements of atmospheric black carbon
svalbard (zeppelin) using SP2 instrument
Modelling black carbon in the Arctic
NASA ARCTAS BC data Regional models (e.g. WRF-­‐Chem) & other global models compared to aircrap & surface data 12 April 2008 aircraft
sampling
flight paths
WRF-­‐Chem performs « well » compared to other models Contribu;ng to Arc;c Council AMAP report on BC & ozone color shading = emission rates of BC
(red and gray = high rates)
emissions from flaring not included in previous
inventories (EU ECLIPSE (Stohl et al., 2013))
Kongsvegen
Avg = (0.6 ± 0.4) ppb
Avg = (1.9 ± 0.9) ppb
Avg = (1.3 ± 0.5) ppb
Work in progress to assess impacts of BC in snow on surface albedo
Laboratoire de Glaciologie et Géophysique de l’Environnement, Grenoble, France
First BC measurements in surface snow at Corbel
(15 m), Austre/Vestre Lovenbren (300 m) and in a
snow pit on the Kongsvegen glacier (670 m)
Dissémination et valorisation
•  12 papers published, 1 in revision (5 in prep.) •  Conferences (LEFE, EGU, AGU, ChanBer ArcBque) + popular arBcles •  4 PhD theses + 4 postdocs/CDDs http://www.latmos.ipsl.fr/index.php/fr/tact/
themes-de-recherche/climslip S é m i n a i r e A N R C h a n g e m e n t s E n v i r o n n e m e n t a u x 1 9 -­‐ 2 0 -­‐ 2 1 m a r s 2 0 1 4 Perspectives …..
•  YAK campaign – september 2014 (collab. NILU) •  Aerosol radia;ve impacts + ozone source airibu;on over the ArcBc •  Chemistry-­‐climate modelling – climate impacts of short-­‐lived pollutants •  Arc;c Council expert group on Black Carbon & Ozone (report due fall 2014, mtg Paris-­‐June 2014) •  Discussing new interna;onal ini;a;ve on ArcBc air polluBon •  ChanBer ArcBque … S é m i n a i r e A N R C h a n g e m e n t s E n v i r o n n e m e n t a u x 1 9 -­‐ 2 0 -­‐ 2 1 m a r s 2 0 1 4