Natural and anthropogenic climate change: incorporating historical land cover change, vegetation dynamics and the global carbon cycle

Abstract

This study explores natural and anthropogenic influences on the climate system, with an emphasis on the biogeophysical and biogeochemical effects of historical land cover change. The biogeophysical effect of land cover change is first subjected to a detailed sensitivity analysis in the context of the UVic Earth System Climate Model, a global climate model of intermediate complexity. Results show a global cooling in the range of –0.06 to –0.22 °C, though this effect is not found to be detectable in observed temperature trends. We then include the effects of natural forcings (volcanic aerosols, solar insolation variability and orbital changes) and other anthropogenic forcings (greenhouse gases and sulfate aerosols). Transient model runs from the year 1700 to 2000 are presented for each forcing individually as well as for combinations of forcings. We find that the UVic Model reproduces well the global temperature data when all forcings are included. These transient experiments are repeated using a dynamic vegetation model coupled interactively to the UVic Model. We find that dynamic vegetation acts as a positive feedback in the climate system for both the all-forcings and land cover change only model runs. Finally, the biogeochemical effect of land cover change is explored using a dynamically coupled inorganic ocean and terrestrial carbon cycle model. The carbon emissions from land cover change are found to enhance global temperatures by an amount that exceeds the biogeophysical cooling. The net effect of historical land cover change over this period is to increase global temperature by 0.15 °C.

Appendix 1

1.1 Modified bucket model description

In the standard bucket model, soil moisture (W) is calculated using a budget approach:

$$ \frac{{\delta W}} {{\delta t}} = P_{R} + S_{M} - E - R $$

(8)

Inputs to the soil moisture bucket come in the form of precipitation (P _R ) and snowmelt (S _M ); outputs take the form of evapotranspiration (E) and runoff (R).

The simplest parametrisation of evaporation is that used in the original version of the bucket model, and is based on a bulk formulation of potential evaporation and the specification of a surface resistance that reduces evaporation from its potential rate in cases where soil moisture is limiting. Following the methodology of a number of other land-surface models (see e.g. Dickinson 2001; Zeng et al. 2000; Cox et al. 1999), we improve on the original bulk formulation of evaporation by parametrizing evapotranspiration as:

$$ E_{r} = \rho _{a} \frac{\beta } {{r_{a} + r_{s} }}[q_{{sat}} (T_{s} ) - q_{a} ] $$

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where ρ _a is the density of air, q _sat (T _s ) is the saturation specific humidity of air at the surface temperature and q _a is the atmospheric specific humidity. The term β imposes a damp on evaporation as water availability decreases, and is calculated as β = (W/W ₀)^1/4 where W is the soil moisture content and W ₀ is the soil water holding capacity or bucket depth (15 cm).

The resistance terms r _a and r _s are the aerodynamic and surface resistances, which impose physical and physiological constraints on evapotranspiration. The first of these (r _a ) is simply a function of the Dalton number for evaporation and the surface wind speed: r _a = (C _D ·U)^–1. The Dalton number is calculated from a specified surface roughness length (z ₀) according to the methodology of Brutsaert (1982):

$$ C_{D} = k^{2} {\left( {\ln \frac{z} {{z_{0} }}} \right)}^{{ - 1}} {\left( {\ln \frac{z} {{z_{{0q}} }}} \right)}^{{ - 1}} $$

(10)

where z is a reference height (z = 10 m) and k is the von Karman constant (k = 0.4). The roughness length for moisture (z _0q ) is calculated as z _0q = e ^–2 z ₀.

When snow is present in a grid cell, the surface albedo is determined on the basis of the of underlying vegetation albedo and a fractional snow cover. Using the vegetation snow-masking depths, the fractional area of snow in a grid cell (A _snow , constrained between 0.0 and 1.0) is calculated as:

$$ A_{snow} = \max {\left[ {H_{{snow,}} \frac{{T_{{air}} - T_{{start}} }} {{T_{{end}} - T_{{start}} }}} \right]} \cdot \frac{1} {{SMD}} $$

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where T _start and T _end are set to –5 °C and –10 °C respectively, T _air is the atmospheric temperature, H _snow is the snow height in metres (Weaver et al. 2001) and SMD is a vegetation-type dependant snow-masking depth. The albedo for snow is then applied to this fractional area, with the underlying snow-free albedo given to the remaining portion of the grid cell.

Surface temperature is calculated from the energy balance equation:

$$R_{{NET}} = LE + SH {\enspace}. $$

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R _NET is the net radiation at the surface (comprising downward shortwave and upward longwave), LE is the latent heat from evaporation and SH is the sensible heat exchange. There is no heat storage in the land surface.