Scientific basis for network evaluation and planning. Oleg Anisimov State Hydrological Institute St.Petersburg, Russia

Transcription

1 Scientific basis for network evaluation and planning Oleg Anisimov State Hydrological Institute St.Petersburg, Russia

2 Presentation overview Climatic and environmental changes in the Russian Arctic. Spatial coherence of climatic variations. Case study of permafrost network.

3 Manifestations of changing climate in Russia Changing temperature and precipitation Up to 1.3 C temperature rise since 198; increased variability of precipitation Environmental impacts 1. Siberian river discharge: 1% increase since Ground water: 1. m increase in water table since Cryosphere: sea ice (-1%), glaciers ( ), permafrost ( ), snow period ( ) 4. Ecosystems: changes in animal habitats; displacement of tree line Economical and societal impacts 1. Severity of climate: less severe winters with implications for human health 2. Heating energy: 5-15 days shorter heating period since Water resources: 5-7% increase since Sea navigation: more navigatable northern sea routes 5. Permafrost: destructive impacts on infrastructure

4 Russian meteorological network 455 weather stations, 282 above 6 N, 156 in permafrost regions. (Map shows the sub-set of 122 stations with continuous century-scale observations in the period 19-26)

5 Changes in seasonal temperatures, C/1 years, Climate assessment by Roshydromet, 27 Winter, spring, summer, fall,

6 E - 35% W - 4% C - 25%

7 E - 4% W - 4% C - 2%

8 E - 35% W - 4% C - 25%

9 E - 35% W - 4% C - 25%

10 E - 35% W - 5% C - 15% Typical pattern with distinct zonal gradient

11 E - 45% W - 4% C - 15%

12 E - 4% W - 3% C - 3%

13 E - 45% W - 3% C - 25% Iconic latitudinal zonation

14 E - 35% W - 3% C - 35%

15 E - 3% W - 3% C - 4%

16 E - 45% W - 3% C - 25% Mixed pattern with latitudinal and zonal gradients

17 E - 45% W - 2% C - 35%

18 E - 45% W - 3% C - 25%

19 E - 55% W - 2% C - 25%

20 E - 6% W - 2% C - 2%

21 E - 6% W - 2% C - 2%

22 E - 6% W - 25% C - 15%

23 E - 45% W - 3% C - 25%

24 E - 4% W - 35% C - 25%

25 E - 4% W - 4% C - 2%

26 E - 35% W - 4% C - 25% E - 35% W - 5% C - 15% E - 45% W - 3% C - 25% E - 6% W - 2% C - 2% Departures from norm, MAAT 1.

27 Spatial coherence of the temperature variations characterized by mean regional correlation coefficient, Numerator mean annual T; denominator winter / summer

28 Regional temperature trends, , о С/1 years. Numerator annual mean, denominator - winter/ summer Mean for Russia:.38 (annual);.51 (winter);.32 (summer) Б

29 Implications for permafrost observations Mean annual air temperature, C А veg А a ATMOSPHERE А org А sn Т a vegetation h veg Т veg Annual air temperature amplitude, C Snow h sn Т sn Organic layer z org Т org Thawing degree-days, C d Active layer ALD Т AL Permafrost Т p

30 Implications for permafrost observations Frequency distribution of the decadal changes of temperature characteristics in the period based on data from weather stations in Russian permafrost regions (156 stations)..4 A.5 B.3 C Mean annual air temperature, o C/1y Annual temperature amplitude, o C/1y Thawing degree-days, d o C/1y

31 Implications for permafrost observations Mean annual air temperature, Numerator - trends, C/1 years, denominator regional mean of 12 regions are not covered

32 Implications for permafrost observations Annual air temperature amplitude, Numerator - trends, C/1 years, denominator regional mean of 12 regions are not covered

33 Implications for permafrost observations Thawing degree days, Numerator - trends, C d/1 years, denominator regional mean of 18 regions are not covered

34 Conclusions 1. Climatic changes have distinct coherence patterns that depend on the atmospheric circulation. 2. Existing networks are not targeted at representation of spatial coherence and thus do not capture the full range of variability under different conditions of atmospheric circulation. 3. Case study indicated that up to 65% of variability is lost in the currently existing permafrost (CALM) network. 4. Analysis of spatial coherence may be used as effective tool for the cost-effective network planning.

35 3 April 27, sub-urban St.Petersburg Thank you! Special thanks to AMAP secretariat that provided funding for my trip to this workshop