Integrating ground observation, satellite remote sensing, and terrestrial ecosystem model for future carbon monitoring systems Nobuko Saigusa National Institute for Environmental Studies (NIES), Japan AsiaFlux Tsukuba Office Slides Contributed by Dr. R. Hirata & M. Hayashi (NIES) 1. Networking cross-disciplinary ground observations and their capacity building programs 2. Integrating ground observation, satellite remote sensing, and terrestrial ecosystem model for better estimates of regional C-budget 3. Summary
Integrating ground observation, satellite remote sensing, and terrestrial ecosystem model for future carbon monitoring systems Nobuko Saigusa National Institute for Environmental Studies (NIES), Japan AsiaFlux Tsukuba Office Slides Contributed by Dr. R. Hirata & M. Hayashi (NIES) 1. Networking cross-disciplinary ground observations and their capacity building programs 2. Integrating ground observation, satellite remote sensing, and terrestrial ecosystem model for better estimates of regional C-budget 3. Summary
Networking cross-disciplinary ground observations to monitor changes in terrestrial ecosystems IGBP&IHDP- GLP IGBP-iLEAPS GEO International Long Term Biodiversity observation Carbon, water and energy budget Ecological Research ( ILTER) FLUXNET GEO BON AsiaFlux AP BON ILTER Asia-Pacific Network: ILTER-EAP JaLTER JapanFlux J-BON Monitoring sites 1000 (MOE)
Networking cross-disciplinary ground observations to monitor changes in terrestrial ecosystems FLUXNET (1996 ~ ) World-wide network for monitoring CO 2 , H 2 O, and energy exchanges between terrestrial ecosystems and the atmosphere (> 500 sites) Archiving CH 4 , N 2 O flux data (started) Eddy covariance method Location of FLUXNET sites http://fluxnet.ornl.gov
Networking cross-disciplinary ground observations to monitor changes in terrestrial ecosystems AsiaFlux: a regional network in FLUXNET AsiaFlux sites Information NEW! forests http://asiaflux.net/ Indonesia India Norway Thailand grasslands Vietnam Information sharing: croplands Antarctica 92 sites supported by: 12th AsiaFlux International Workshop Philippines, August 18-23, 2014 Data sharing:
Networking cross-disciplinary ground observations to monitor changes in terrestrial ecosystems JapanFlux, JaLTER, JAXA & JAMSTEC select several common sites to share data and technical skills for advanced multi-scale, long-term, and consistent ecosystem observations on the ground and from space. (Oct. 2008) Remote sensing Long-term ground Japan Aerospace observation Exploration Agency Japan Long-Term Terrestrial modeling Ecological Research Global Change Observation Mission (GCOM)
Model – data integration (so far mainly CO 2 & ET) Monthly GPP (total photosynthesis) at CO 2 , water vapor and energy flux data 24 sites & simulated by 8 models 450 450 TUR 2004 NEE YLF 2004 NEE 450 YPF 2004 NEE Seasonal GPP GPP GPP Deciduous 450 SKT 2004 NEE RE RE RE 300 300 300 GPP RE 300 patterns of Conifer 150 150 150 150 (Larch) 0 0 0 C-budget J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D 0 J F M A M J J A S O N D -150 -150 -150 450 LSH 2004 -150 NEE TMK 2003 NEE GPP 400 GPP Total photosynthesis (GPP) RE RE 300 200 Total Respiration (RE) 150 Net CO 2 Exchange (NEE) 0 0 J F M A M J J A S O N D J F M A M J J A S O N D (negative: uptake) -150 -200 450 450 CBS 2004 NEE 450 MBF 2005 NEE GDK 2006 NEE GPP GPP GPP Mixed RE RE 300 RE 300 300 Evergreen & 150 150 150 Deciduous 0 0 0 J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D Deciduous -150 -150 -150 450 Broadleaved MMF 2004 NEE 450 GPP 450 QYZ 2004 NEE TKC 2007 NEE 450 SMF 2003 NEE 450 TKY 2003 NEE GPP RE GPP GPP GPP 300 RE RE RE RE 300 300 300 300 150 Evergreen 150 150 150 150 0 J F M A M J J A S O N D 0 0 0 0 Conifer J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D -150 -150 -150 -150 -150 450 450 BNS 2003 NEE MKL 2004 NEE 450 450 SKR 2002 NEE PDF 2004 NEE Tropical GPP GPP GPP GPP RE RE RE RE 300 300 300 300 Forests 150 150 150 150 0 0 0 0 J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D -150 -150 -150 -150 Alpine Grassland 500 500 Crop Crop MSE 2004 NEE YCS 2004 NEE GPP GPP 450 450 QHB 2004 NEE HBG 2004 NEE RE RE (Wheat & (Rice) GPP GPP 250 250 RE RE 300 300 Maize) 150 150 0 0 J F M A M J J A S O N D J F M A M J J A S O N D 0 0 J F M A M J J A S O N D J F M A M J J A S O N D -150 -150 -250 -250 Regional & continental C-budget estimations July-August 2003 F F D D Anomaly in GPP (gC m -2 day -1 ) E E A A B B C C Ichii et al. (2010) (2013) Saigusa et al. (2010) (2013) (base period 2001-2006)
Capacity Building (CB) for Asian Terrestrial Ecosystem Carbon Budget Monitoring Network CO 2 Research flow Effective CB can help solve flux bottlenecks in research flow. Networking ground- based observations For beginners: Observation, data quality control, paper writing, data Point-scale Cross-site analysis, 450 NEE 450 sharing C-budget YPF 2004 MBF 2005 NEE GPP GPP RE RE 300 300 model-data synthesis 150 150 For experts: Promotion of integrative 0 0 J F M A M J J A S O N D J F M A M J J A S O N D -150 -150 studies for global (Asian) C- 450 450 MMF 2004 NEE PDF 2004 NEE Regional-, country-, GPP GPP RE RE 300 300 budget estimations continental-scale C- 150 150 0 0 J F M A M J J A S O N D J F M A M J J A S O N D budget estimations -150 -150 (Bottom-up) in Asia- Country-scale Pacific (AP) region Effective CB for AP will bring: Comparison between (1) Reduction of blank area in Asia Top-down (inversion with Productivity satellite data) & Bottom- (2) Sustainable high-quality data up approaches in AP Continental-scale July-August 2003 F sharing F D D Anomaly in GPP (gC m -2 day -1 ) E E A A Detection of C-cycle (3) Better prediction for terrestrial B B climate hotspots in AP C-cycle climate feedbacks C C (base period 2001-2006)
Capacity building and technology transfer Learning to Learn Together Open-path CH 4 flux sensor TC for methane flux monitoring in S-Asia Supported by Supported by LI-COR Co. LI-COR Co. Financially supported by:
Data Registration Camp (JaLTER) Promoting data sharing with JaLTER DB and data paper ( Ecological Research) one page abstract in the print product & Invite young scientists or online data archive technical staffs and instruct data registration Encourage submission of data paper (Miyagi, Japan, Sep. 2012)
Integrating ground observation, satellite remote sensing, and terrestrial ecosystem model for future carbon monitoring systems Nobuko Saigusa National Institute for Environmental Studies (NIES), Japan AsiaFlux Tsukuba Office Slides Contributed by Dr. R. Hirata & M. Hayashi (NIES) 1. Networking cross-disciplinary ground observations and their capacity building programs 2. Integrating ground observation, satellite remote sensing, and terrestrial ecosystem model for better estimates of regional C-budget 3. Summary
Monitoring CO 2 uptake after artificial disturbance Teshio CC-LaG Site Clear-cut & plantation in 2003 (Hokkaido Univ., NIES, Hokkaido Electric Power Co., Inc.) Tower Larch Plantation (14ha) Teshio Carbon Cycle & Larch Growth Experiment Site
Monitoring C-budget in two larch forests with different age distribution Disturbed Mature mixed → Young larch forest Larix gmelinii × L. kaempferi TSE (Teshio CC-LaG experiment site) Hokkaido (Northern Japan) Takagi et al. (2009) GCB Observation period : 2002(mix) → 2003-2012 (larch) Tree Age : 200 years (mix) → 1 – 12 years Tree Height: 20 m → 1 – 2.5 m Annual temperature: 5.7 ℃ Annual precipitation: 1000mm Soil type: Gleyic Cambisol Disturbance: Bring out 55%, residual 45% Non-disturbed Mature larch forest Larix Kaempferi Sarg. TMK (Tomakomai flux research site) Hirata et al. (2007) AFM Observation period : 2001-2003 Tree Age : 42 – 44 years old Tree Height: About 15 m Annual temperature: 6.2 ℃ Annual precipitation: 1043mm Soil type: Volcanogenous regosol
VISIT (Vegetation Integrative Simulator for Trace Gases) Simulating C-budget in two larch forests with different age distribution Integration using a terrestrial ecosystem model Changes in (a) C-stock and (b) VISIT (Vegetation Integrative Simulator for Trace C-flux in a primary rainforest and in an oil palm plantation Gases) to estimate changes in GHGs flux and converted from the primary carbon stock caused by climate change as well as forest natural and artificial disturbances. Rainforest Oil palm (provided by A Ito) Adachi, Ito et al. (2011) Biogeosciences
Simulating C-budget in two larch forests with different age distribution Young larch forest Mature larch forest Mixed forest NEP (Net ecosystem production) Carbon absorption Carbon release GPP (Total photosynthesis) RE (Ecosystem respiration) Hirata, Takagi, Ito, Hirano, Saigusa (2014) Biogeosciences Discuss.
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