Artic climate and Climate Change Oleg Anisimov, State Hydrological Institute, St.Petersburg, Russia oleg @oa7661. spb . edu
Jan 05, 2016
Artic climate and Climate Change
Oleg Anisimov, State Hydrological Institute, St.Petersburg, Russia [email protected]
• There were two periods in the beginning and at the end of the 20th
century when the global air temperature rose continuously. • Recent warming begun in 1970th, continues now, and is most likely attributable to the cumulative effect of natural variability and anthropogenic factors.
• Temperature increase over the 20th
century has been 0.6 0 C, which is the largest of any century during the past 1,000 years.
• Climate models predict amplified warming in the Arctic, and impacts on natural and human systems are expected
Is global climate changing?
Air temperature changes from 1951-1975 to the periods 1976-1985 (A)
and 1986-1997 (B).
-1 0 1 1 2 2
-0 .5 0.0 0.5 1.0 1.5 2.0 >2.0
-180 -120 -60 0 60 120 180
-180 -120 -60 0 60 120 180
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-20
0
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60
80
-180 -120 -60 0 60 120 180
-180 -120 -60 0 60 120 180
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-40
-20
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60
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-180 -120 -60 0 60 120 180
-60
-40
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0
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80
-60
-40
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0
20
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60
80
Summer
Winter
Year
-180 -120 -60 0 60 120 180
-180 -120 -60 0 60 120 180
-60
-40
-20
0
20
40
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80
-60
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-20
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-180 -120 -60 0 60 120 180
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-180 -120 -60 0 60 120 180
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-40
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0
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-40
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A B
Is regional climate changing?
1880 1900 1920 1940 1960 1980 2000
-16-14-12-10
-8-6-4
1880 1900 1920 1940 1960 1980 2000
-18
-16
-14
-12
Alaska
Siberia
http:/zubov.atmos.uiuc.edu/ACIA/
2000 2010 2030 2050 2070 2090
0
5
4
3
2
1
GCM-based scenarios of climate change for the GCM-based scenarios of climate change for the ArcticArctic
Annual-mean air temperature, Annual-mean air temperature, 606000 - 90 - 9000 North.North.
GCMs predict very different GCMs predict very different patterns of the future patterns of the future climateclimate
-160.00 -140.00 -120.00 -100.00
60.00
70.00
60.00 80.00 100.00 120.00 140.00
50.00
60.00
70.00
80.00
100.00 120.000.00
10.00
20.00
Correlations of local and global anom alies of the annual air tem perature
20.00 40.00 60.00 80.00 100.00 120.00 140.00 160.00-40.00
-30.00
-20.00
-140.00 -120.00 -100.00
30.00
40.00
50.00
60.00
-0.70
0.70
1.00
Legend
1
2 3
4
5
Empirical scenario of climate change based on regression analysis of historical weather records
-5.0 -1.0 1.0 2.0 3.0 4.5 6.0 12.0
Regional temperature changes under 1 C global warming
B est estim a te
-150 -100 -50 0 50 100 150
-50
0
50
-5.0
-1.0
1.0
2.0
3.0
4.5
6.0
12.0
U p p er b o u n d(d T + 1 ,96 S T )
-150 -100 -50 0 50 100 150
-50
0
50
L o w er b o u n d(d T -1 ,96 S T )
Regional temperaturechanges under 1 C global warming
Cryospheric indicators Cryospheric indicators of climate change:of climate change:
permafrostpermafrost ground iceground ice snowsnow sea icesea ice river and lake iceriver and lake ice glaciersglaciers ice capsice caps
Permafrost legendcontinuousdiscontinuous
sporadic
offshore permafrost
ice sheet
ice extent in September
ice extent in April
How are glaciers changing?How are glaciers changing?
1700 1800 1900 2000
Sw albard
Norw ay
Sw eden
I celand
Canadian R ockies
W est Europe
Africa
New Zealand
How is snow cover extent changing?How is snow cover extent changing?
1965 1970 1975 1980 1985 1990 1995 2000
-0.2
0.2
0.4
0.6
0.8
0
Tem
pera
ture
an
om
aly
1965 1970 1975 1980 1985 1990 1995 2000
- 2
- 1
0
1
2
snow
ext
ent
anom
aly,
mln
km
**2
1965-2000 snow extent
linear fit
Anomalies of spring air temperature over snow covered areas in the Northern Hemisphere, 1972-2000
Anomalies of snow cover extent over Northern Hemisphere, 1966-2000
How is sea ice extent changing?How is sea ice extent changing?
1930 1950 1970 1990120
160
200
Yenisei
1930 1950 1970 1990100
120
140
O b
1930 1950 1970 19900
20
40
Pechora
1950 1970 19906 0
8 0
1 0 0
Yukon
Arctic hydrology
River runoff to the Eastern Arctic Seas increased by 10%-12% since 1970th, while in the Western Arctic there was no significant change.
Annual and winter temperature riseAnnual and winter temperature rise ( (deg. Cdeg. C) ) in the Arctic Ocean basin in the Arctic Ocean basin
during last two decades of XXth centuryduring last two decades of XXth century
Annual runoff changesAnnual runoff changes (%%) (%%) in the basins of Russian rivers in the basins of Russian rivers during last two decades of XXth centuryduring last two decades of XXth century
Winter runoff changesWinter runoff changes (%%) (%%) in the basins of Russian rivers in the basins of Russian rivers during last two decades of XXth centuryduring last two decades of XXth century
Circumpolar Active Layer Monitоring programme
Flow chart of equilibrium permafrost model of intermediate complexity
Air temperature
Precip
Vegetation
Soil
Snow
Snow model
Calculation of surface temperature
Surface temperature Temperature amplitude
Calculation of seasonal thawing
Map of seasonal thaw depth
Projected changes of near-surface Projected changes of near-surface permafrost distribution under permafrost distribution under
climatic scenarios for 2030, 2050, climatic scenarios for 2030, 2050, and 2080and 2080**..
**Scenarios were derived from the following GCMsScenarios were derived from the following GCMs
1 – Canadian Climate Center Model (CCC),1 – Canadian Climate Center Model (CCC),2 – NCAR model,2 – NCAR model,3 - European Max-Plank Institute model (ECHAM),3 - European Max-Plank Institute model (ECHAM),4 - GFDL climate model,4 - GFDL climate model,5 - UK Hadley Center model (HadCM3). 5 - UK Hadley Center model (HadCM3).
http:/zubov.atmos.uiuc.edu/ACIA/http:/zubov.atmos.uiuc.edu/ACIA/
SFI – based distribution of SFI – based distribution of near-surface permafrost.near-surface permafrost.
2 – reduction of sporadic zone by 20303 – reduction of sporadic zone by 20504 – reduction of sporadic zone by 2080
5 – stable discontinuous zone
6 – reduction of sporadic zone by 20307 – reduction of sporadic zone by 20508 – reduction of sporadic zone by 2080
9 – stable continuous zone
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HadCM3
CCC NCAR
ECHAM GFDL
Sce-nario
Total permafrost area, mln. Km2 and % from modern
Continuous permafrost area, mln. Km2 and % from modern
2030 2050 2080 2030 2050 2080
CCC 23.72 21.94 20.66 9.83 8.19 6.93
87% 81% 76% 79% 66% 56%ECHAM 22.30 19.31 17.64 9.37 7.25 5.88
82% 71% 65% 75% 58% 47%
GFDL 24.11 22.38 20.85 10.19 8.85 7.28
89% 82% 77% 82% 71% 59%HadCM3 24.45 23.07 21.36 10.47 9.44 7.71
90% 85% 78% 84% 76% 62%
NCAR
24.24 23.64 21.99 10.69 10.06 9.14
89% 87% 81% 86% 81% 74%
Predicted changes of the near-surface permafrost extentPredicted changes of the near-surface permafrost extent
Projected changes of seasonal Projected changes of seasonal thaw depth under climatic thaw depth under climatic
scenarios for the 11-year time scenarios for the 11-year time slices centered onslices centered on
2030, 2050, and 20802030, 2050, and 2080**..
**Scenarios were derived from the following GCMsScenarios were derived from the following GCMs
1 – Canadian Climate Center Model (CCC),1 – Canadian Climate Center Model (CCC),2 – NCAR model,2 – NCAR model,3 - European Max-Plank Institute model (ECHAM),3 - European Max-Plank Institute model (ECHAM),4 - GFDL climate model,4 - GFDL climate model,5 - UK Hadley Center model (HadCM3). 5 - UK Hadley Center model (HadCM3).
http:/zubov.atmos.uiuc.edu/ACIA/http:/zubov.atmos.uiuc.edu/ACIA/
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HadCM3
CCC NCAR
ECHAM GFDL
Projected for 2030 changes of seasonal thaw depth (relative to 2000)
0 – ocean1 – permafrost-free land
2 – 0% - 20% increase3 – 20% - 30% increase4 – 30%-50% increase5 – >50% increase
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Projected for 2050 changes of seasonal thaw depth (relative to 2000)
0 – ocean1 – permafrost-free land
2 – 0% - 20% increase3 – 20% - 30% increase4 – 30%-50% increase5 – >50% increase
HadCM3
CCC NCAR
ECHAM GFDL
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Projected for 2080 changes of seasonal thaw depth (relative to 2000)
0 – ocean1 – permafrost-free land
2 – 0% - 20% increase3 – 20% - 30% increase4 – 30%-50% increase5 – >50% increase
HadCM3
CCC NCAR
ECHAM GFDL
Feedbacks in climate-permafrost-vegetation system
Circumpolar Arctic tundra
Arctic polar desert
Shrub tundra
Southerntundra
Northern Arctic tundra
Polar desert
ShrublandTussock tundra
Northern tundra
Plant-cover induced pattern in the active layer of dwarf shrub-tussock tundra: a) Sphagnum mosses preserve permafrost from thawing b) under tussocks, dwarf shrubs and especially bare ground the active layer gradually increases
(adopted from Razzhivin 1999).
Climate-induced changes of vegetation may either enhance, or mitigate the direct impact of warming on permafrost. None of the currently existing permafrost or vegetation models accounts for such effects.
Total non-vascularplant biomass
warm
Fert.+
warm
Ferti-lization
Biomass ofDeciduous shrubs
warm
Fert.+
warm
Ferti-lization
Biomass ofEvergreen shrubs
warm
Fert.+
warm
Ferti-lization
Biomass oflichens
warm
Fert.+
warm
Ferti-lization
Biomass ofmosses
warm
Fert.+
warm
Ferti-lization
Total vascularplant biomass
Ferti-lization
Fert.+
warm
warm
Empirical evidence of vegetation response to changing climate, Toolik Lake, Alaska, and Abisco
Research station, Sweden
(Preliminary data from the paper by M.T. van Wijk et all., in review for publiction)
Treatments:
1. Fertilization 10 g m2 y-1 N; 2.6 g m2 y-1 P; 9 g m2 y-1 K; 0.8 g m2 y-1 Mg2. Warming 2 – 4 0C3. Shading 50% - 65%
Biomass changes in logarithmic scale in the range –0.8 +0.8, response bars correspond to individual biomes.
Active-layer thickness and permafrost temperature calculated under the conditions of projected for 2030
climate (HadCM2 scenario) and various vegetation conditions.
1. Bare ground.2. 5 cm thick organic layer3. 10 cm thick organic layer4. 15 cm thick organic layer5. 20 cm thick organic layer.
01
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Organic layer
5cmTotal decrease of AL volume -2265 km3
ALT reduction relative to bare ground, %
2% < dALT < 10% 10% < dALT < 20% 20% < dALT < 50% dALT > 50%
Mean ALT reduction -12%
0 25 50 75 100
ALT reduction, cm
2см < dALT < 10см 10см < dALT < 30см 30см < dALT < 50см dALT > 50см
Mean ALT reduction -15cm
0 25 50 75 100
Permafrost cooling compared to bare ground
0.1 С < dT < 0.5 С 0.5 С < dT < 1.0 С 1.0 С < dT < 1.5 С 1.5 С < dT < 2.0 С dT > 2.0 С
01
2
34
5
ALT reduction relative to bare ground, % Permafrost cooling compared to bare groundALT reduction, cm
Organic layer
10cm
Mean ALT reduction -27%
Total decrease of AL volume -4399 km3
Mean ALT reduction -28сm
0 25 50 75 100 0 25 50 75 100
2% < dALT < 10% 10% < dALT < 20% 20% < dALT < 50% dALT > 50%
2см < dALT < 10см 10см < dALT < 30см 30см < dALT < 50см dALT > 50см
0.1 С < dT < 0.5 С 0.5 С < dT < 1.0 С 1.0 С < dT < 1.5 С 1.5 С < dT < 2.0 С dT > 2.0 С
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ALT reduction relative to bare ground, % Permafrost cooling compared to bare groundALT reduction, cm
Organic layer
15cm
Mean ALT reduction -43%
Total decrease of AL volume -6408 km3
Mean ALT reduction -41cm
0 25 50 75 100 0 25 50 75 100
2% < dALT < 10% 10% < dALT < 20% 20% < dALT < 50% dALT > 50%
2см < dALT < 10см 10см < dALT < 30см 30см < dALT < 50см dALT > 50см
0.1 С < dT < 0.5 С 0.5 С < dT < 1.0 С 1.0 С < dT < 1.5 С 1.5 С < dT < 2.0 С dT > 2.0 С
01
2
34
5
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5
ALT reduction relative to bare ground, % Permafrost cooling compared to bare groundALT reduction, cm
Organic layer
20cm
Mean ALT reduction -60%
Total decrease of AL volume -8301 km3
Mean ALT reduction –54cm
0 25 50 75 100 0 25 50 75 100
2% < dALT < 10% 10% < dALT < 20% 20% < dALT < 50% dALT > 50%
2см < dALT < 10см 10см < dALT < 30см 30см < dALT < 50см dALT > 50см
0.1 С < dT < 0.5 С 0.5 С < dT < 1.0 С 1.0 С < dT < 1.5 С 1.5 С < dT < 2.0 С dT > 2.0 С
Concluding remarks1. To get insight into the current and future climatic and environmental changes in the Arctic we
need to combine and analyze data coming from different observational networks and obtained using different technlogies (i.e. ground vs remote observations), which is why coordination with other national and international scientific initiatives focused on high latitudes is needed. Several such initiatives (NEESPI, Boreas, etc.) are on the way.
2. Models are (almost?) the only tool currently used to predict future environmental situation in the Artic. Important task is to minimize the gap between the scales at which environmental data in the Arctic are available and models operate and to validate the models using observational data making them thus capable of predicting the future changes of the environment in the Arctic.
3. One of the important deliverables of the CEON may be an effective data assimilation system that includes both observations and modeling. Example of such system in climatology is reanalysis of the temperature and precipitation fields, and our challenging task is to develop similar system for the environmental parameters in the Arctic.
4. To be easily disseminated and used effectively by the scientific community, deliverables of the project such as data bases, models and data assimilation techniques, should be usable as stand-alone products.
5. This will require developing a dedicated computerized information system in association with the project. The role of such system is three-fold:
- depository of the project deliverables;
- research and educational tool;
- stand-alone product for easy dissemination.