artic climate and climate change oleg anisimov, state hydrological institute, st.petersburg, russia...

Artic climate and Climate Change

Oleg Anisimov, State Hydrological Institute, St.Petersburg, Russia [email protected]

mailto:[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

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-180 -120 -60 0 60 120 180

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Summer

Winter

Year

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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

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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

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30.00

40.00

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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

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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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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.

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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


Total decrease of AL volume -4399 km3

Mean ALT reduction -28сm

0 25 50 75 100 0 25 50 75 100




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Organic layer

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Mean ALT reduction -41cm

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Organic layer

20cm



Mean ALT reduction –54cm

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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.

artic climate and climate change oleg anisimov, state hydrological institute, st.petersburg, russia...

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