Wednesday, April 4, 2012 CC-BY-NC
Lecture 24

Maintainer: admin

Terrestrial Vegetation Influences the Climate

• The presence and characteristics of vegetation have a substantial impact on the climate, at all spatial scales: Locally, we can feel it, Regionally, empirical data shows it
• The presence and characteristics of vegetation are not fixed, but constantly changing: naturally (ex: leaves fall from deciduous trees), due to human actions (ex: deforestation)
• Dynamic Global Vegetation Models (DGVM) are the most advanced tools to simulate the two-way interactions between climate and terrestrial vegetation (two-way relationship)
• DGVM Simulate
• Quantities Computed by DGVM: carbon balance (take in CO2, give off O2, die and decompose), energy balance (some energy from the sun is reflected back), water balance (plants use roots to pump water from soil and transpire it back into atmosphere through leaves)
• Purpose of DGVM is to compute two categories of variables: land-atmosphere exchanges (fluxes) and the status of different vegetation elements (ex: stocks)

IBIS: Integrated Biosphere Simulator Model
• IBIS: one of the many DGVM’s (integrated biosphere simulator model): wind speed, air humidity, precipitation
• Hourly: Upper Canopy Transpiration
• Daily: Snow Depth 1965-1966
• Monthly: Upper Canopy Leaf Cover: January (Canada)
• Canopy: Competition amoung vegetation for sunlight
• Biomass: total mass of trees, shrubs, ect
• Yearly: Total Biomass: After 1 Year (Canada), Remove all vegetation and then let it compete and grow, Light blue: small amount of vegetation, light blue: zero vegetation
• After 5 Years, 25 Years: prairies (SW Canada) biomass is decreasing because it is so dry (grasses are thriving but they don’t weigh a lot), 50 years forests are maturing, 100 years see the same biomass pattern we see today in Canada, after 100 years the results don’t change that much if the climates remain constant
• Huge trees and forests in BC are not shown in IBIS…because there was oversimplification when IBIS was made, they did not include certain kinds of trees in the program (huge coniferous trees which accumulate a lot of biomass over a long period of time)

Research Questions Addressed with DGVM
• Do boreal forests cool or warm the global climate? Carbon cycle cools the global climate, but vegetation also influences the climate in other ways. Reflection of solar radiation because of snow cover in the boreal region (albedo) warming effect
• How fire and insect outbreaks might impact forests in the future?
• What about crops productivity? How climate change will affect crops? Biofuel crops and essential crops (rice, wheat). Using DGVM to find impact of biofuels

The Take Home Message
• Climate models need to account for terrestrial vegetation
• DGVM are sufficiently elaborate and accurate to: estimate the main land-atmosphere fluxes, and study some of the impact of climate on vegetation stocks
• Many elements are not (well) represented yet…

Permafrost Thaw Sensitivity: Detection and Assessment
• Permafrost covers 50% of Canada

Ground Ice in Permafrost
• Massive ice at a thaw slump, half meter of soil and ice goes down 20 meters into the ground
• Ice wedges
• Ice lenses: thin strips of ice separated by soil
• Massive ice core: moisture content of 250% and thickness of greater than 2 meters – amount of moisture exceeds saturation point
• Building on top of ice can cause building, pipeline, and road problems
• Can lift it above ground so warm oil doesn’t affect temperature of soil

What Causes Permafrost Degration?
• Geomorphic: excavating and removing insulating layers
• Vegetation: impact amount of snow on surface, snow can buffer surface from atmosphere, peat changes thermo properties throughout year (quite colder compared to other terrains)
• Climatic: climate changes

Ground Thermal Regime
• Trumpet
• Diagonal line on bottom dictated from heat emanated from Earth’s core
• Reach a point close enough to the surface, affected by surface heat
• Sub-surface is no longer affected by weather patterns at surface
• Permafrost starts at the depth at which the maximum temperature for the year is 0 C
• Can have various shapes depending on type of environment we are in
• Wide trumpet: area where there is a large temperature variation over an entire year
• Snow would warm the permafrost because it is thermal insulation
• Area with snow is much more suspectible to permafrost degradation

How do we detect ground ice?
• Coring
• Drilling is expensive, time-consuming, and only provides point samples
• Understanding conditions between boreholes is unreliable in areas of high variability
• Geophysical investigations allow for cheap and rapid data acquisition in an environmentally-friendly manner
• Ground-penetrating radar: when it encounters a boundary, a reflection is generated and it is captured by the receiver; done at multiple depths; can get a 2-D picture of subsurface structure; doesn’t tell you what the material is, just its geometry
• Electrical resistivity: see how resistive different materials are; can adjust spacing between transmitter and receiver; the further away they are the deeper you can go

Case Study at Parsons Lake, NWT
• A lot of natural gas
• Key site for proposed Mackenzie valley pipeline, 1500 km pipeline from North Canada to Southern Alberta
• Objectives:
• Construct thermal models that predict ground temperatures recorded in 2004
• Project maximum active layer thickness (MALT) changes from 2011-2070
• Access the spatial applicability of the MALT projections between the boreholes using geophysical data
• Is it worth it to drill? Will the ice melt and water run??
• Thermal Modelling Strategy: examine core at specific interval, assess unfrozen water content and melting temperature (fine grain materials can hold water below 0 C)
• Want to know how much unfrozen water content you have at a specific temperature
• Heat capacities of materials to parameterize layers
• Geothermal heat flux: energy coming from the earth’s core
• Pool information together, run model, see what we get (able to generate pretty accurate results)
• Results vary due to amount of snowcover – have a good regional estimate of average snowcover
• Silty clay causes ice to melt faster
• Encountered massive ice body:
• A lot of energy required for phase change in ice

Key Conclusions from Case Study
• 1D thermal models are accurate, we are confident in how the materials were parameterized, minimal lateral heat flow
• anticipated climate warming effects (2011-2070): MALT will increase by a factor of 3 for the silty clay underlain by gravelly sand
• Geophysics: the gravelly sand pocket is 90m in length and is therefore not insignificant, results shoe that multi-dimensional models are needed for long-term projections