Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Assessment of Climate Change Impacts on Forest Growth and Yield Xinbiao Zhu.

Slides:



Advertisements
Similar presentations
Integrating climate and weather products in Water Resources Management by Francis Mutua University of Nairobi.
Advertisements

The Canadian Climate Impacts Scenarios (CCIS) Project is funded by the Climate Change Action Fund and provides climate change scenarios and related information.
Short Background on Climate Change and Greenhouse Gases Dr Ruth Nussbaum ProForest Presentation to the RSPO GHG WG2 meeting in Feb 2010.
FVS, State - Transition Model Assumptions, and Yield tables – an Application in National Forest Planning Eric Henderson Analyst, Hiawatha National Forest,
Figure 3. Outlines of the study with links between different components used. The figure presents the main inputs and outputs from the model used (Glob3PG)
The Canadian Climate Impacts Scenarios (CCIS) Project is funded by the Climate Change Action Fund and provides climate change scenarios and related information.
Scaling Laws, Scale Invariance, and Climate Prediction
A statistical method for calculating the impact of climate change on future air quality over the Northeast United States. Collaborators: Cynthia Lin, Katharine.
“what a climate model is, and what uncertainty means” Noah S. Diffenbaugh Department of Environmental Earth System Science and Woods Institute for the.
1/18 Long-term Scenarios for Climate Change-Implications for Energy, GHG Emissions and Air Quality Shilpa Rao, International Institute of Applied Systems.
Climate modeling Current state of climate knowledge – What does the historical data (temperature, CO 2, etc) tell us – What are trends in the current observational.
Landslide Susceptibility Mapping to Inform Land-use Management Decisions in an Altered Climate Muhammad Barik and Jennifer Adam Washington State University,
Climate Change, Biofuels, and Land Use Legacy: Trusting Computer Models to Guide Water Resources Management Trajectories Anthony Kendall Geological Sciences,
Crop Yield Modeling through Spatial Simulation Model.
Large-scale atmospheric circulation characteristics and their relations to local daily precipitation extremes in Hesse, central Germany Anahita Amiri Department.
“And see this ring right here, Jimmy?... That’s another time the old fellow miraculously survived some big forest fire.” ENFA/INSEA FORESTRY…..
MET 112 Global Climate Change - Lecture 11 Future Predictions Craig Clements San Jose State University.
Assessment of Future Change in Temperature and Precipitation over Pakistan (Simulated by PRECIS RCM for A2 Scenario) Siraj Ul Islam, Nadia Rehman.
Hydrological Modeling FISH 513 April 10, Overview: What is wrong with simple statistical regressions of hydrologic response on impervious area?
INTRODUCTION Weather and climate remain among the most important variables involved in crop production in the U.S. Great Lakes region states of Michigan,
Climate Change Impacts on Georgia’s Natural Resources Steven McNulty, Ph.D. Research Ecologist USDA Forest Service Raleigh, NC.
Protecting our Health from Climate Change: a Training Course for Public Health Professionals Chapter 2: Weather, Climate, Climate Variability, and Climate.
Rising Temperatures. Various Temperature Reconstructions from
An introduction to the monitoring of forestry carbon sequestration projects Developing Forestry and Bioenergy Projects within CDM Ecuador March, 2004 Igino.
1 MET 12 Global Climate Change - Lecture 9 Climate Models and the Future Shaun Tanner San Jose State University Outline  Current status  Scenarios 
Vulnerability and Adaptation Assessments Hands-On Training Workshop Impact, Vulnerability and Adaptation Assessment for the Agriculture Sector – Part 2.
European capacity building initiativeecbi Climate Change: an Introduction ecbi Workshops 2007 Claire N Parker Environmental Policy Consultant european.
OUCE Oxford University Centre for the Environment “Applying probabilistic climate change information to strategic resource assessment and planning” Funded.
Rapid Ecoregional Assessment. Climate was primarily modeled using models and data from the Scenarios Network for Alaska and Arctic Planning. See
Modeling the effects of climate change on multiple ecosystem services Marc Conte Stanford University Natural Capital Project Marc Conte, Josh Lawler, Erik.
South Eastern Latin America LA26: Impact of GC on coastal areas of the Rio de la Plata: Sea level rise and meteorological effects LA27: Building capacity.
Zhang Mingwei 1, Deng Hui 2,3, Ren Jianqiang 2,3, Fan Jinlong 1, Li Guicai 1, Chen Zhongxin 2,3 1. National satellite Meteorological Center, Beijing, China.
Irrigation Australia/7 th Asian Regional Conference Assessment of Water Supply Capability in Agricultural Reservoirs according to Climate Change Tuesday.
Combining historic growth and climate data to predict growth response to climate change in balsam fir in the Acadian Forest region Elizabeth McGarrigle.
Carbon Dioxide (CO 2 ) Recent CO 2 Changes IPCC Reports.
An Application of Field Monitoring Data in Estimating Optimal Planting Dates of Cassava in Upper Paddy Field in Northeast Thailand Meeting Notes.
Climate Modeling Jamie Anderson May Monitoring tells us how the current climate has/is changing Climate Monitoring vs Climate Modeling Modeling.
Assessment of the impacts of and adaptations to climate change in the plantation sector, with particular reference to coconut and tea, in Sri Lanka. AS-12.
Modelling of climate and climate change Čedo Branković Croatian Meteorological and Hydrological Service (DHMZ) Zagreb
© Crown copyright Met Office Providing High-Resolution Regional Climates for Vulnerability Assessment and Adaptation Planning Joseph Intsiful, African.
Modeling experience of non- point pollution: CREAMS (R. Tumas) EPIC (A. Povilaitis and R.Tumas SWRRBWQ (A. Dumbrauskas and R. Tumas) AGNPS (Sileika and.
Reducing Canada's vulnerability to climate change - ESS J28 Earth Science for National Action on Climate Change Canada Water Accounts AET estimates for.
15 december 2009 Usefulness of GCM data for predicting global hydrological changes Frederiek Sperna Weiland Rens van Beek Jaap Kwadijk Marc Bierkens.
Modern Climate Change Darryn Waugh OES Summer Course, July 2015.
Predicting climate change impacts on southern pines productivity in SE United States using physiological process based model 3-PG Carlos A. Gonzalez-Benecke.
IPCC WG1 AR5: Key Findings Relevant to Future Air Quality Fiona M. O’Connor, Atmospheric Composition & Climate Team, Met Office Hadley Centre.
Future climate change drives increases in forest fires and summertime Organic Carbon Aerosol concentrations in the Western U.S. Dominick Spracklen, Jennifer.
Understanding hydrologic changes: application of the VIC model Vimal Mishra Assistant Professor Indian Institute of Technology (IIT), Gandhinagar
PROJECT TO INTERCOMPARE REGIONAL CLIMATE SIMULATIONS Carbon Dioxide and Climate Change Eugene S. Takle Agronomy Department Geological and Atmospheric Science.
E.A. Mathez, 2009, Climate Change: The Science of Global Warming and Our Energy Future, Columbia University Press. Source: Solomon et al., 2007 Chapter.
The evolution of climate modeling Kevin Hennessy on behalf of CSIRO & the Bureau of Meteorology Tuesday 30 th September 2003 Canberra Short course & Climate.
Panut Manoonvoravong Bureau of research development and hydrology Department of water resources.
Evapotranspiration Estimates over Canada based on Observed, GR2 and NARR forcings Korolevich, V., Fernandes, R., Wang, S., Simic, A., Gong, F. Natural.
1 Greenhouse Gas Emissions, Global Climate Models, and California Climate Change Impacts.
1 UIUC ATMOS 397G Biogeochemical Cycles and Global Change Lecture 14: Methane and CO Don Wuebbles Department of Atmospheric Sciences University of Illinois,
© Crown copyright Met Office Uncertainties in the Development of Climate Scenarios Climate Data Analysis for Crop Modelling workshop Kasetsart University,
1 MET 112 Global Climate Change MET 112 Global Climate Change - Lecture 12 Future Predictions Eugene Cordero San Jose State University Outline  Scenarios.
Impacts of Landuse Management and Climate Change on Landslides Susceptibility over the Olympic Peninsula of Washington State Muhammad Barik and Jennifer.
Future Air Quality in Representative Concentration Pathway Scenarios: Relationships Between Economic Wellbeing and Air Quality J. Jason West Steven J.
Schematic framework of anthropogenic climate change drivers, impacts and responses to climate change, and their linkages (IPCC, 2007).
Climate Change Observation, Inference & Prediction
Global Impacts and Consequences of Climate Change
Western Mensurationists Meeting 2016
3-PG The Use of Physiological Principles in Predicting Forest Growth
Model Summary Fred Lauer
Interactive C-cycle in Earth System models
South Eastern Latin America
Twentieth Century & Future Trends.
RC Izaurralde – JGCRI With contributions from NJ Rosenberg – JGCRI
Presentation transcript:

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Assessment of Climate Change Impacts on Forest Growth and Yield Xinbiao Zhu CIF-NL-AGM St John’s, NL November 12–14, 2014

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Forest inventory (stand type, site quality…) Planning periods (5yrs) Planning horizon (160 yrs) Decision variables Management strategies G & Y curves Coefficients Objective functions (management goals, Constraints) LP AAC Stocking level Species composition Age structure Harvest schedule Forest Planning System

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service GIS forestry inventory

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Sources of forest growth & yield curves Stand table projection model (stand simulator): Best possible regression equations link growth and influencing factors derived from PSP data, and calibrated using TSP data. Calculate periodic recruitment, increment and survival of tree cohort (defined by species, DBH, and age). Project overall stand development over time based on characterising the stand structure at the start of the projection period (initial condition). A conventional stand table format is used to define structure of a stand on a specific site at any point in time. Simplicity, relative accuracy in prediction of volume growth, largely used in forest industry for timber supply analysis and management planning. Require no climate data in projection of stand development (assuming that tree growth conditions remain constant over time).

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Process-based forest growth model Physiological process-based growth model: Key physiological processes are driven by climate and soil variables that define tree growth and biomass yield. Complex data of many parameters for calibration, validation, and prediction. Don’t have the same accuracy as empirical G & Y model. Need professional expertise to calibrate and use. Useful tools in research of climate change impacts, but rarely suitable for practical forestry. Forest gap model: Key physiological processes are simplified and driven by climate and soil variables that define tree growth and biomass yield. Less parameters for calibration, validation, and prediction. Don’t have the same accuracy as empirical G & Y model. Need professional expertise to calibrate and use. Popular tools in research of climate change impacts, but rarely suitable for practical forestry.

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Jabowa III forest gap model Initial Stand Condition (PSPs) DBH, Height, Species Site Conditions (PSPs) Elevation, Latitude, Soil texture, Soil rock percentage, Soil depth, Soil fertility status, Root depth, Depth of water table Historical weather records Future climate change scenarios Temperature Precipitation

Composition of the Atmosphere and Radiative Forcing Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service PERMANENT GASESVARIABLE GASES GasPercentGasPercentPPM(by volume) Dry air N H 2 O0 to 4 O CO Ar0.93 (<1%)CH Ne0.0018N 2 O He0.0005O H *CFCs Xe *F-gases (HFC, PFC, SF6)

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service IPCC Assessment Reports:1990 SR90, 1992 IS92, 2000 SAR, TAR, 2007 AR4, 2013 AR5 Others: academic (1/2/4xCO2), Stabilization Pathways (S, SRE, SP), etc. IPCC scenario development process Socio- economic scenarios Population GDP Energy Industry Transportation Agriculture … Emission scenarios GHGs Aerosols & VOCs… Land use & land cover Radiative forcing scenarios to GCM Atmospheric concentration Global carbon cycle Atmospheric chemistry Global climate model (GCM) scenarios Temperature Humidity Soil moisture Extreme events …

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service GCM calibration IPCC AR5 Report

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service (Moss et al., Nature 2010, IPCC AR5 2013) IPCC 2013 AR5 Scenarios Representative Concentration Pathways (RCPs) NameRadiative forcing CO 2 - equiv. emissions PathwayAR 5 surface temperature projections ( o C) 2046 – 2065 Mean & range Mean & range RCP2.6 RCP4.5 RCP6.0 RCP8.5 ~2.6 W m -2, peak b/w ~4.5 W m -2, peak at 2010 ~6.0 W m -2, peak at 2080 ~8.0 W m -2, rising in 21 st century ~490 ppm ~650 ppm ~850 ppm >1,370 ppm peak & decline stabilization rising 1.0 ( ) 1.4 (0.9 – 2.0) 1.3 (0.8 – 1.8) 2.0 (1.4 – 2.6) 1.0 ( ) 1.8 (1.1 – 2.6) 2.2 (1.4 – 3.1) 3.7 (2.6 – 4.8)

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Outputs from GCMs

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Outputs from GCMs

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service CGCM3T47 has a resolution of 4.7 o Latitude x 4.7 o Longitude (map grids) Wood supply analysis is based on ecoregion. GCM Resolution

GCM Outputs vs. Observed Data Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Port Aux Basque Corner Brook Deer LakeSt. Anthony

GCM Outputs vs. Observed Data Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Port Aux Basque Corner Brook Deer LakeSt. Anthony

A Downscaling Technique (Weather Generator) Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Distribution of dry & wet length Mean temp standard deviation dry/wet days Distribution of dry & wet days Inputs: historical weather records (30 years) Solar radiation air temperature precipitation Outputs: synthetic surface weather (30 years) Solar radiation air temperature precipitation Seasonal cycles of MEANS and STDEVs are modeled with Fourier Series

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Downscaled Minimum Temperature Port Aux Basque Corner Brook Deer LakeSt. Anthony

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Downscaled Precipitation Port Aux Basque Corner Brook Deer LakeSt. Anthony

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Spatial interpolation of downscaled climate data Prepare database (daily minimum and maximum temperature, precipitation, solar radiation*) for all sites. Temperature adjustment based on the lapse rate (6 o C/km ) before and after applying the GIS surface interpolation.

Natural Resources Ressources naturelles CanadaCanada Converting data to the required format for JABOWA III forest gap model Deer Lake – Baseline –

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Jabowa III forest gap model Initial Stand Condition (PSPs) DBH, Height, Species Site Conditions (PSPs) Elevation, Latitude, Soil texture, Soil rock percentage, Soil depth, Soil fertility status, Root depth, Depth of water table Historical weather records Future climate change scenarios Temperature Precipitation

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Model calibration and simulation PSP growth data – historical JABOWA-III Gap Model Historical climate data PSP tree list Initial stand condition AR 5 climate change scenarios Simulated growth – RCP 2.6 Simulated growth – RCP 4.5 Simulated growth – RCP 6.0 Simulated growth – RCP 8.5Simulated growth – Historical Calibration

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Model Calibration Immature balsam fir (Plot number , District 14) Balsam fir White birch

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Simulated basal Area Balsam fir – Avalon Ecoregion Simulation Period (1 = 5 yrs)

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Simulated stand volume Balsam fir – Central Ecoregion Simulation Period (1 = 5 yrs)

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Estimate of climate change impacts PSP growth data – historical JABOWA-III Gap Model Historical climate data PSP tree list Initial stand condition AR 5 climate change scenarios Simulated growth – RCP 2.6 Simulated growth – RCP 4.5 Simulated growth – RCP 6.0 Simulated growth – RCP 8.5Simulated growth – Historical Calibration Strata-b ased climate change modifiers– RCP 2.6 Strata-b ased climate change modifiers– RCP 4.5 Strata-b ased climate change modifiers– RCP 6.0 Strata-b ased climate change modifiers– RCP 8.5 Calculation of climate change modifiers

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Climate Change Modifiers Province Average RCP 2.6bSbFwSwBtL Year RCP RCP 4.5bSbFwSwBtL Year RCP RCP 8.5bSbFwSwBtL Year RCP

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Climate Modifiers

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Climate Modifiers

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Yield curves x Climate modifiers Original yield curves Climate modifiers

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Climate-modified yield curves

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Forest inventory (stand type, site quality…) Planning periods (5yrs) Planning horizon (160 yrs) Decision variables Management strategies Modified G & Y curves Coefficients Objective functions (management goals, Constraints) LP AAC Stocking level Species composition Age structure Harvest schedule Forest Planning System

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service Acknowledgement CFSI and IBES funded the project through graduate student fellowship UNB colleagues provide supervision of graduate student activities NRCan colleagues provide downscaled climate change scenarios data

Natural Resources Ressources naturelles CanadaCanada Canadian Forest Service