Extreme events

26
Extreme events Extreme events Objective Objective : characterizing : characterizing ecosystem/carbon response to extreme ecosystem/carbon response to extreme climate events; understanding the climate events; understanding the processes and mechanisms that will be processes and mechanisms that will be useful for future projections useful for future projections Method Method : using a suite of models and : using a suite of models and data: foward/inversion/flux/satellite data: foward/inversion/flux/satellite Forcings: PDSI, P, Temp, … Forcings: PDSI, P, Temp, … Correlation analysis Correlation analysis Sensitivity experiments Sensitivity experiments Processes: NPP, Rh, … Processes: NPP, Rh, … Which events: 2002 (also 2007?, 3+ Which events: 2002 (also 2007?, 3+ models) models)

description

Extreme events. Objective : characterizing ecosystem/carbon response to extreme climate events; understanding the processes and mechanisms that will be useful for future projections Method : using a suite of models and data: foward/inversion/flux/satellite Forcings: PDSI, P, Temp, … - PowerPoint PPT Presentation

Transcript of Extreme events

Page 1: Extreme events

Extreme eventsExtreme events

ObjectiveObjective: characterizing ecosystem/carbon : characterizing ecosystem/carbon response to extreme climate events; response to extreme climate events; understanding the processes and mechanisms understanding the processes and mechanisms that will be useful for future projectionsthat will be useful for future projections

MethodMethod: using a suite of models and data: : using a suite of models and data: foward/inversion/flux/satellitefoward/inversion/flux/satellite

Forcings: PDSI, P, Temp, …Forcings: PDSI, P, Temp, … Correlation analysisCorrelation analysis Sensitivity experimentsSensitivity experiments

Processes: NPP, Rh, …Processes: NPP, Rh, …

Which events: 2002 (also 2007?, 3+ models)Which events: 2002 (also 2007?, 3+ models)

Page 2: Extreme events

Site flux measurementsForest/agriculture inventory

A

Carbon fluxes

Observed Climate+

ForcingPrecipitation, temp, radiation, etc.CO2

Land use

Mechanistic carbon models

InversionCarbon data assimilation

NEEGPP, ReNPP

Satellite: NDVI EVI LAI Fire and derived C-fluxes

Fire

LAI, NPP

Comparison, validation, synthesis

Page 3: Extreme events

Inversion

Forward

Page 4: Extreme events

NEE anomalies with 2000-05 mean removed

2002: drought2004: ?

Page 5: Extreme events

Inversion

Forward

Page 6: Extreme events

MODIS GPP

MODIS LAI

Page 7: Extreme events
Page 8: Extreme events
Page 9: Extreme events
Page 10: Extreme events
Page 11: Extreme events
Page 12: Extreme events
Page 13: Extreme events
Page 14: Extreme events
Page 15: Extreme events
Page 16: Extreme events

Variability of the North American Variability of the North American Carbon CycleCarbon Cycle

Ning Zeng and Jinho YoonNing Zeng and Jinho Yoon

Dept. Atmospheric and Oceanic Science andDept. Atmospheric and Oceanic Science andEarth System Science Interdisciplinary Center Earth System Science Interdisciplinary Center

University of MarylandUniversity of Maryland

Collaborators: G. J. Collatz, M. Heimman, C. Roedenbeck, H. Qian, R. Joseph,A. Kumar, A. Vintzileos, A. Mariotti, A. Busalacchi, S. Lord

The big question is, how much would it really cost

Page 17: Extreme events

Photosynthesis Autotrophic respiration

Carbon allocation

Turnover

Heterotrophic respiration

4 Plant Functional Types:Broadleaf treeNeedleleaf treeC3 Grass (cold)C4 Grass (warm)

3 Vegetation carbon pools:LeafRootWood

3 Soil carbon pools:FastIntermediateSlow

Atmospheric CO2

The VEgetation-Global Atmosphere-Soil Model (VEGAS)

Page 18: Extreme events

VEGAS IIVEGAS IIPhotosynthesis: Photosynthesis:

Light (PAR, LAI, Height), soil moisture, temperature, CO2Light (PAR, LAI, Height), soil moisture, temperature, CO2

Respiration: Respiration:

temperature, soil moisture, lower soil pools slower decaytemperature, soil moisture, lower soil pools slower decay

Competition:Competition:

Net growth, shading => fractional coverNet growth, shading => fractional cover

Fire: Fire:

moisture, fuel load, PFT dependent resistancemoisture, fuel load, PFT dependent resistance

Wetland/CH4: Wetland/CH4:

moisture, topography gradientmoisture, topography gradient

Carbon 13:Carbon 13:

C3/C4 competition: temperature, CO2C3/C4 competition: temperature, CO2

Page 19: Extreme events
Page 20: Extreme events
Page 21: Extreme events
Page 22: Extreme events

ConclusionsConclusions There is large differences in the spatial and temporal variability There is large differences in the spatial and temporal variability

on continental-regional scale among the modelson continental-regional scale among the models There is some agreement, especially associated with major There is some agreement, especially associated with major

climatic events such as drought among forward, inversion and climatic events such as drought among forward, inversion and satellite datasatellite data

Page 23: Extreme events
Page 24: Extreme events
Page 25: Extreme events
Page 26: Extreme events