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Changes in the seasonal activity of temperate and boreal vegetation The critical role of Autumn temperatures. Shilong Piao, Philippe Ciais, Pierre Friedlingstein, Philippe Peylin, Nicolas Viovy and Peter Rayner LSCE, CEA-CNRS-UVSQ Gif sur Yvette, France Carbon Fusion Meeting 9-11 May 2006
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As temperature is rising, the length of growing season usually increases. How will the net Carbon Uptake Period respond to the warming ? JanDecJul Aug earlier spring delayed fall Background
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Global biospheric model ORCHIDEE ORCHIDEE SECHIBA energy & water cycle photosynthesis t = 1 hour LPJ spatial distribution of vegetation (competition, fire,…) t = 1 year STOMATE vegetation & soil carbon cycle (phénologie, allocation,…) t = 1 day NPP, biomass, litterfall vegetation types LAI, roughness, albedo soil water, surface temperature, GPP rain, température, humidity, incoming radiation, wind, CO 2 meteorological forcing sensible & latent heat fluxes, CO 2 flux, net radiation output variables prescribed vegetation vegetation types
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ORCHIDEE model simulations 1.Spin up (1000 y) using 1901 climate data, and 1850 CO 2 concentration 2.Simulate from 1850 to 1900 using 1901-1910 climate data, and corresponding every year CO 2 concentration. 3.Simulate from 1901 to 2002, using corresponding every year climate data and CO2 concentration. Save every day C flux from 1980 to 2002.
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Comparison of spring (AM) LAI Latitude (degree)
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Comparison of autumn (SO) LAI Latitude (degree)
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Interannual Variability in LAI Spring SD ORCHIDEE = 0.04 SD GIMMS = 0.06 SD PAL = 0.19 Satellite sensor change Autumn SD ORCHIDEE = 0.02 SD GIMMS = 0.07 SD PAL = 0.13
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Define growing season and carbon uptake periods A B C D A = growing season start B = growing season end AB = growing season length (GSL) C = net carbon uptake start D = net carbon uptake end CD = Carbon Uptake Period (CUP) Growing Season From rate of change of LAI CUP GSL Carbon Uptake From NEP zero-crossing dates
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Mapping the growing season and carbon uptake timing Onset date increases with increasing latitude CUP start occurs later than GS start (because of spring respiration) Shortest GSL = Central Siberia near the Arctic coast (4 months). Shortest CUP = Northern Eurasian forests and water limited steppes - also show the shortest GS length. The distribution of End date in autumn is less uniform than in spring, (reflects vegetation type, as well as water / temperature limitations on plant growth). Growing season (phenology) Carbon Uptake Start (day) End (day) Duration (days) Derived from ORCHIDEE simulation
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Trends GSL and CUP during 1980-2002 dGSL start /dt = 0.16 days/yr dCUP start /dt = 0.19 days/yr Same response of CUP start and GSL start to warming trend R GSLstart-temp = -0.91 P<0.001 R CUPstart-temp = -0.62 P=0.002 dGSL end /dt = 0.14 days/yr dCUP end /dt = -0.07 days/yr Opposite response of CUP end and GSL end to warming trend ! R GSLend-temp = 0.71 P<0.001 R CUPend-temp = -0.51 P=0.01 ORCHIDEE > 25°N Spring Autumn
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Mapping the trends More than 70% of the study region exhibits an advancing trend in the GSL start, especially in Eurasia. In North America, large regions show delayed trends in the CUP start GSL length : Trends to increasing GSL over high latitude regions, usually as a result of earlier beginning of growing season in Eurasia and later end of growing season in North America CUP length : North America shows a trend to shorter CUP length, Eurasia has the opposite behaviour GSL: most of northern North America shows a trend towards later GSL end, BUT there is a trend to earlier GSL end in temperate Western Eurasia (Europe). CUP: 70% of the study region display a trend towards an earlier CUP end. Growing season Trends Carbon Uptake Trends Beginning End Length Derived from ORCHIDEE
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(1) Period from 1980-2002; (2) Period from 1982-1998; (3) Period from 1988-2000 Comparison with satellite observation RegionChange in GSL start (days / year) >0 = earlier ; <0 = later Change in CUP (days / year) ORCHIDEE (1) Zhou et al. (2) Smith et al. (3) North America +0.04-0.4-0.080.12 Eurasia-0.32-0.3-0.39 RegionChange in GSL (days / year) >0 = earlier ; <0 = later Change in CUP (days / year) ORCHIDEE (1) Zhou et al. (2) Smith et al. (3) North America 0.27 0.22-0.11 Eurasia0.110.21-0.31-0.07 Spring Autumn
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Atmosphere CO2 measurements Although Keeling et al. (1996) found that there were no significant long-term changes in the upward zero crossing time at site Mauna Loa from mid-1970s to 1994, pronounced advancement at a rate of 0.77 days yr-1 (R=-0.65, P=0.001) is observed in the period of 1980-2002.
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Temperature vs. Carbon Uptake Period Spring R BRW = -0.85, P<0.001 R MLO = -0.40, P=0.056 Autumn R BRW = -0.60, P=0.003 R MLO = -0.59, P=0.005 (excluding 1992, 1993)
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Differential response of gross C Fluxes to the warming trend in Northern Hemisphere (>25°N) Spring: Warm temperatures accelerate growth more than soil decomposition. The annual relationship of NEP to temperature is positive => Warming enhances carbon uptake Autumn: Warm autumn accelerate growth less than soil decomposition. The annual relationship of flux to temperature is negative. => Warming reduces carbon uptake Derived from ORCHIDEE
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Autumn (SON) temperature vs. C Flux
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Conclusion Most of the study region exhibited extending of GSL, usually as a result of earlier vegetation green-up in Eurasia and later vegetation senescence in North America, which strongly supports a lengthening of growing season and greening trend at northern hemispheric observed in the past two decades. Due to parallel stimulating soil carbon decomposition, increase in GSL does not necessarily lead to increase in CUP and eventually result in higher C net uptake. Autumn warming does not benefit terrestrial net C uptake through postponing vegetation growing season end in the northern mid and high latitudes.
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Relevance to IGCO Need for in situ phenological data Need of long flux time series to confirm processe Need for snow cover / frozen status of soil data Long term satellite biophysical products (large differences between sensors & data processing) New CO 2 column satellite obseravtions may allow an unprecedented quantification of the spatial distribution in the CO 2 seasonal cycle -> regional trends detection Integration of surface with atmospheric information
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Thank you!
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