Looking Ahead Why Good LUCC Modeling is Important for Climate Models: The Challenges for Model Integration

1. Looking AheadWhy Good LUCC Modeling is Important for Climate Models: The Challenges for Model Integration Carlos A Nobre CPTEC-INPE Cachoeira Paulista, SP

2. When did LUCC Impacts Start? • Ruddiman suggests that human activities started increasing CO2 8Kybp (start of forest clearing) and CH4 5Kybp (rice farming). These events prevented an ice age that would have naturally occurred as a function of changing orbital parameters. Slide Courtesy of P House and P. Dirmeyer

3. Contents • Introduction: the Earth as a Complex System • Spatial and Temporal Scales • Land Surface-Atmosphere Interactions • Carbon Modeling in Amazonia

4. The Earth as a Complex System

5. Earth System Science • One planet - we don’t see the compartments • None of the compartments (or disciplines) operates independently • None of the compartments (or disciplines) are more important than the others • The Earth has 4.6B years of integration under its belt http://sohowww.nascom.nasa.gov/data/realtime-images.html We need disciplined interdisciplinary science Organize around science - build the structure to support it

6. Earth System Modelling: A Hierarchical Approach

7. Earth System Modeling From the simplest models to explore ideas to the most detailed model to check against observational data. Develop data assimilation and inversion schemes. Adapt models to help in the stewardship of the Earth System.

8. Modeling: A Hierarichal Approach • Continue to develop classic models of the Earth System, but at the same time use tools of complex system science which recognize that the interactions between parts of a system lead to the emergence of structures and to self-organization. • Open modeling framework in which different modules can be adapted, and different concepts can be tested, . • The development of future models should involve stakeholders, so that they understand concepts, uncertainties, etc.

10. DYNAMIC VEGATION: Yet another step forward in model development Typical GCM approach: ignore effects of climate variations on vegetation Early attempts at accounting for vegetation/ climate consistency Fully integrated dynamic vegetation model Figure from Foley et al., “Coupling dynamic models of climate and vegetation”, Global Change Biology, 4, 561-579, 1998.

11. 3-part diagram GCM ATMOSPHERE climate chemistry Ent Dynamic Global Terrestrial Ecosystem Model Lead: N. Kiang, GISS sensible/latent heat momentum P, VP, CO2 Tair, Precip SW , PAR beam/diffuse SW, CO2 fire aerosols VOCs ENT DGTEM seasonal-decadal LANDSCAPE & VEG STRUCTURE patch (age distrib) cohort (density) individual plant functional type (pft) plant mass C&N:foliage, stem, root C&N: labile storage plant geometry LAI, SLA profile, dbh, height, root depth crown size (axes) hourly DISTURBANCE fire(above-ground biomass, dryness(soil moisture)) combustion products litter, new patches CANOPY RADIATIVE TRANSFER LAI & clumping profiles leaf albedo PAR profiles, sunlit/shaded net SW to soil patch albedo (canopy, soil, snow) update structure ALLOMETRY/ GROWTH/REPROD update plant geometry establish new seedlings density dependence mortality net CO2 uptake [layer] PAR[layer] sunlit/shaded CANOPY BIOPHYSICS Ci Chl/N profile photosynthesis= Acan(leaf Chl, Ci, PAR, LAI,Tcan) conductance= gcan(moisture,Tcan,height,VPD, Acan) SOIL BGC labile C, labile N available N slow C, slow N soil respiration= (substrate, moisture, Tsoil) ALLOCATION/ PHENOLOGY budburst(Tgdd), cold/dry decid update individ C&N pools plant respiration N uptake, N fixation N litter landscape and veg structure Tsoil, Tcanopy snow albedo soil albedo, soil moisture conductance net SW LAND SURFACE ENERGY & WATER BALANCE canopy energy balance soil energy balance soil moisture snow cover, snow albedo soil albedo u,v, P, VP Tair , LW Precip

12. Atmosphere Models The Earth System Unifying the Models Climate / Weather Models Carbon Cycle and Biogeochemistry Water Cycle The Predictive Earth System Hydrology Process Models Ocean Models Land Surface Models Natural Hazard Prediction Terrestrial Biosphere Models Solid Earth Models Megaflops Gigaflops Teraflops Petaflops 2000 2010

13. Introducing the Human Dimension

14. Introducing Human Dynamics • The Earth System will have to be viewed as a single system in which interactions between natural and social systems play a crucial role. • The research communities involved will have to find a common language

15. INSTITUTIONS • (Banking, judicial, • Education) • POLICY • (Incentives, • Conservation, • Land tenure) • CULTURE • (Perception, values, • Ethics) • ECONOMY • (valuation, cost-profit, discounting) • DEMOGRAPHICS • (Number, gender, age) • BioGeochemistry • (Soil fertility, • OM levels, • Fluxes) • BioDiversity • (Species, • Community, • Landscape, • Genetic, • Functional) • BioPhysics • (Albedo, • Energy exchange, • Structure) COUPLED HUMAN - ENVIRONMENT SYSTEM LAND USE DECISION MAKING UTILIZATION

16. Modeling the human element Geist & Lambin, 2002

17. Merging our “Physical” Models with Economic, Policy and Decision Support Models – the Next Frontier

18. Meta-Analysis of Deforestation Combinations of multiple factors according to time-scale: • Short time scales: individual & social responses to new opportunities & constraints created by markets& policies. • Long time scales:demographic factors: population increase & decrease, breakdown of extended families, migration. • Extreme biophysical events trigger further change. Geist and Lambin (2001)

19. Global Land Cover Types 1700 to 1992 300 Years of Land Use Change BIOME 300

20. The Spread of Agriculture BIOME 300 Global Crop Cover Change1700 to 1992 Fraction of Grid Cell in Croplands

21. Estimated changes in land use from 1700 to 1995 Goldewijk K and Battjes J.J., 1997

22. Ecological footprint of cities Night-time data from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) Point: Area of urban-industrial infrastructure remains small relative to other land-use/cover changes, but its “footprint” has significant land implications. Elvidge et al., 1997

23. Ecological Scaling 1 cm 1 m 10 m 1 km 1000 km Scale: the spatial and temporal frequency of a process or structure. A scale domain is bounded by the grain size of processes detected and the extent or span of processes attended. 10000 yrs 4 1000 yrs 3 century 2 1 decade Log Time (years) year 0 month -1 -2 day -3 hour -4 - 6 - 4 - 2 0 2 4 Log Space (km) Slide Courtesy of P House and P. Dirmeyer

24. Vegetative Scales Forest is patterned across a range of scales. Larger slower structures usually constrain the behavior of faster smaller scales. Occasionally change at a small and fast scale spreads up to a larger scale. 1 cm 1 m 100 m 1 km 10 km 1000 km 10 000 yrs 4 region 1 000 yrs 3 forest century 2 stand patch LOG TIME - years 1 decade crown year 0 needle/leaf month -1 -2 day -3 hour -4 - 6 - 4 - 2 0 2 4 LOG SPACE- km Slide Courtesy of P House and P. Dirmeyer

25. Atmospheric Processes 1 cm 1 m 100 m 1 km 10 km 1000 km Atmospheric processes occur faster than vegetative processes occurring at the same spatial scale. 4 region 1 000 yrs 3 forest century 2 climate change patch stand 1 decade LOG TIME - years El Niño crown year 0 needle month -1 long waves -2 Vegetative Structures day fronts Atmospheric Processes -3 thunderstorms hour -4 - 6 - 4 - 2 0 2 4 LOG SPACE- km Slide Courtesy of P House and P. Dirmeyer

26. Disturbance Regimes: • Fire enhancement • Fire suppression • Increased erosion • Decreased erosion • Increased deforestation • Afforestation • Increased biotic disturbance • Change in consequences of disturbance • Change in susceptibility to physical forces Slide Courtesy of P House and P. Dirmeyer

27. Mesoscale Processes 1 cm 1 m 100 m 1 km 10 km 1000 km 10 000 yrs 4 Mesoscale disturbance processes such as fire and spruce budworm outbreaks link the atmospheric processes and vegetative structures. 1 000 yrs 3 Disease/pest Outbreaks century 2 1 decade LOG TIME - years year 0 Fire month -1 -2 day -3 hour -4 - 6 - 4 - 2 0 2 4 LOG SPACE- km Mesoscale Processes Vegetative Structures Atmospheric Processes Slide Courtesy of P House and P. Dirmeyer

28. Anthropogenic Processes 1 cm 1 m 100 m 1 km 10 km 1000 km 10 000 yrs 4 Anthropogenic disturbance processes such as agriculture, logging, grazing and urbanization can impact vegetation more broadly and quickly than natural causes. 1 000 yrs 3 century 2 Land use changes 1 decade LOG TIME - years year 0 month -1 -2 day -3 hour -4 Anthropogenic Processes - 6 - 4 - 2 0 2 4 LOG SPACE- km Mesoscale Processes Vegetative Structures Atmospheric Processes Slide Courtesy of P House and P. Dirmeyer

29. Hydrological processes “Hydro-meteorological” processes Atmospheric Processes Source: Blöschl e Sivapalan (1995).

30. Aggregation and scaling in hydrological modelling Hydrological processes are strongly non-linear on small scales, and how these processes aggregate on a larger scale is not completely understood Source: Wood (1995)

31. Understanding how the hydrological signal propagates at different scales in the forest Asu catchment Central Amazonia

32. Scales in hydrologic modelling: Aggregate or effective parameters Basin Sub-grid Linear  radiation and evaporation Linear Non-linear (Arain et al., 1996; Arain et al., 1997)

33. Scales in hydrologic modelling: Probability-Distributed principle (Beven and Freer, 2001) (Wooldrige et al., 2001)

34. Energy Balance Over Land Absorbed energy raises the surface temperature; heat radiated from the surface increases The sun is the ultimate source of all energy Shortwave Longwave Evapotranspiration Sensible Heat If there is moisture available, most of the remaining energy will go towards evaporating it. Ta Water has a high heat, capacity, so retards warming. Dry soil will warm quickly, increasing sensible heat flux. Energy which reaches the ground and is not reflected is absorbed σTa4 σTs4 Ts

35. Only about 45% of the Sun’s energy is visible Plants mostly make use of visible light for photo-synthesis

36. The rest is in infrared (43%) and UV (12%) The ozone layer blocks most of the UV from reaching the surface

37. Deforestation Slide Courtesy of P House and P. Dirmeyer

38. Some facts about deforestation • More than 8 million km2 of forest (all latitudes) have been cleared globally, about half of it in this century alone. • Half of the world's population live in less developed countries in the tropics (between 23°N and 23°S), where deforestation is occurring the fastest. • Tropical forests are being lost at a rate of 2-3% per year. • 10% of global terrestrial net primary production (vegetative growth) occurs in the Amazon Basin alone. Slide Courtesy of P House and P. Dirmeyer

39. Conceptual models of regional deforestation in Amazonia “An alternative pattern could represent first an increase of precipitation as a result of partial deforestation, maybe due to the mesoescale circulations, ... followed by a catastrophic decrease passing some threshold value.” “Increase of the deforested areas Linear decrease of P” “Relatively small deforestation could cause a major decrease of precipitation, with a progressing deforestation not having further significant impact” Avissar et al., 2002

40. AMAZON SCENARIOS PROJECT CPTEC-INPE GLOBAL MODEL LUCC Model RESULTS

41. Amazon Scenarios Project, LBA Source: Soares-Filho (2004) ~45% ~28% YEAR Control 2025 2050 Distribution of SSiB vegetation types over South America on a 1° by 1° long grid. Vegetation classification Dorman and Sellers (1989) ~67% 100% 2100 Total

42. Warmer surface temperature in all deforestation cases ! Amazon Scenarios Project, LBA

43. The relative warming of the deforested land surface is consistent with the reduction in evapotranspiration and the lower surface roughness length. Amazon Scenarios Project, LBA

44. Decrease of precipitation with a progressing deforestation ! Amazon Scenarios Project, LBA

45. 0 % deforested area ~28 % deforested area ~45 % deforested area ~67 % deforested area 100 % deforested area Area: 6°N-6°S / 63°W-45°W “Increase of the deforested areas “Linear” decrease of P” Sampaio et al. (2006) Amazon Scenarios Project, LBA

46. Why the interest in carbon? One obvious reason: to address questions of global climate change. • Weather station records and ship-based observations indicate that global mean surface air temperature warmed between about 0.4 and 0.8o C (0.7 and 1.5 o F) during the 20th century.

47. Why the interest in modeling the land’s role in the carbon cycle? Land has a definite impact -- note how land seasonality affects the atmospheric CO2 content.

48. Estimates of flux changes with time: Note the incredible balance between high carbon flux rates. The only imbalance is in the fossil fuel emissions. Terrestrial sink mechanisms:

49. Amazonia: source or sink of carbon?

50. Amazonia: source or sink of carbon?