Evaluating the climate effects of mid-1800s deforestation in New England, USA, using a Weather, Research, and Forecasting (WRF) Model Multi-Physics Ensemble

The New England region of the northeastern United States has a land use history characterized by forest clearing for agriculture and other uses during European colonization and subsequent reforestation following widespread farm abandonment. Despite these broad changes, the potential influence on local and regional climate has received relatively little attention. This study investigated wintertime (December through March) climate impacts of reforestation in New England using a high-resolution (4 km) multiphysics ensemble of the Weather Research and Forecasting Model. In general, the conversion from mid-1800s cropland/grassland to forest led to warming, but results were sensitive to physics parameterizations. The 2-m maximum temperature (T2max) was most sensitive to choice of land surface model, 2-m minimum temperature (T2min) was sensitive to radiation scheme, and all ensemble members simulated precipitation poorly. Reforestation experiments suggest that conversion of mid-1800s cropland/grassland to present-day forest warmed T2max +0.5 to +3 K, with weaker warming during a warm, dry winter compared to a cold, snowy winter. Warmer T2max over forests was primarily the result of increased absorbed shortwave radiation and increased sensible heat flux compared to cropland/grassland. At night, T2min warmed +0.2 to +1.5 K where deciduous broadleaf forest replaced cropland/grassland, a result of decreased ground heat flux. By contrast, T2min of evergreen needleleaf forest cooled –0.5 to –2.1 K, primarily owing to increased ground heat flux and decreased sensible heat flux

KLUM@GTAP: Introducing biophysical aspects of land-use decisions into a general equilibrium model: A coupling experiment

In this paper the global agricultural land use model KLUM is coupled to an extended version of the computable general equilibrium model (CGE) GTAP in order to consistently assess the integrated impacts of climate change on global cropland allocation and its implication for economic development. The methodology is innovative as it introduces dynamic economic land-use decisions based also on the biophysical aspects of land into a state-ofthe- art CGE; it further allows the projection of resulting changes in cropland patterns on a spatially more explicit level. A convergence test and illustrative future simulations underpin the robustness and potentials of the coupled system. Reference simulations with the uncoupled models emphasize the impact and relevance of the coupling; the results of coupled and uncoupled simulations can differ by several hundred percent.Land-use change, computable general equilibrium modeling, integrated assessment, climate change

Klum@Gtap: Introducing Biophysical Aspects of Land-Use Decisions Into a General Equilibrium Model A Coupling Experiment

In this paper the global agricultural land use model KLUM is coupled to an extended version of the computable general equilibrium model (CGE) GTAP in order to consistently assess the integrated impacts of climate change on global cropland allocation and its implication for economic development. The methodology is innovative as it introduces dynamic economic land-use decisions based also on the biophysical aspects of land into a state-of-the-art CGE; it further allows the projection of resulting changes in cropland patterns on a spatially more explicit level. A convergence test and illustrative future simulations underpin the robustness and potentials of the coupled system. Reference simulations with the uncoupled models emphasize the impact and relevance of the coupling; the results of coupled and uncoupled simulations can differ by several hundred percent.Land-Use Change, Computable General Equilibrium Modeling, Integrated Assessment, Climate Change

Are there interactive effects of physiological and radiative forcing produced by increased CO2 concentration on changes of land hydrological cycle?

AbstractThree coupled climate–carbon cycle models including CESM (Community Earth System Model), CanEsm (the Canadian Centre for Climate Modelling and Analysis Earth System Model) and BCC (Beijing Climate Center Climate System Model) were used to estimate whether changes in land hydrological cycle responded to the interactive effects of CO2-physiological forcing and CO2-radiative forcing. No signs could be indicated that the interactive effects of CO2-physiological forcing and CO2-radiative forcing on the hydrological variables (e.g. precipitation, evapotranspiration and runoff) were detected at global and regional scales. For each model, increases in precipitation, evapotranspiration and runoff (e.g. 0.37, 0.18 and 0.25mm/year2) were simulated in response to CO2-radiative forcing (experiment M3). Decreases in precipitation and evapotranspiration (about −0.02 and −0.09mm/year2) were captured if the CO2 physiological effect was only accounted for (experiment M2). In this experiment, a reverse sign in runoff (the increase of 0.08mm/year2) in contrast to M3 is presented. All models simulated the same signs across Eastern Asia in response to the CO2 physiological forcing and radiative forcing: increases in precipitation and evapotranspiration only considering greenhouse effect; reductions in precipitation and evapotranspiration in response to CO2-physiological effect; and enhanced trends in runoff from all experiments. However, there was still a large uncertainty on the magnitude of the effect of transpiration on runoff (decreased transpiration accounting for 8% to 250% of the increased runoff) from the three models. Two models (CanEsm and BCC) attributed most of the increase in runoff to the decrease in transpiration if the CO2-physiological effect was only accounted for, whereas CESM exhibited that the decrease in transpiration could not totally explain the increase in runoff. The attribution of the CO2-physiological forcing to changes in stomatal conductance versus changes in vegetation structure (e.g. increased Leaf Area Index) is an issue to discuss, and among the three models, no agreement appeared

Pesticide externalities from the US agricultural sector -- The impact of internalization, reduced pesticide application rates, and climate change

Pesticides used in agricultural production affect environmental quality and human health. These external costs can amplify due to climate change because pest pressure and optimal pesticide application rates vary with weather and climate conditions. This study uses mathematical programming to examine alternative assumptions about regulations of external costs from pesticide applications in US agriculture. We use two climate projections given by the Canadian and Hadley climate models. The impacts of the internalization of the pesticide externality and climate change are assessed both independently and jointly. We find that, without external cost regulation, climate change benefits from increased agricultural production in the US may be more than offset by increased environmental costs. The internalization of the pesticide externalities increase farmers’ production costs but increase farmers’ income because of price adjustments and associated welfare shifts from consumers to producers. Our results also show that full internalizations of external pesticide costs substantially reduces preferred pesticide applications rates for corn and soybeans as climate change.climate change impacts, pesticide externalities, farm management adaptation, agricultural sector model, welfare maximization, environmental policy analysis, mathematical programming, United States

The biophysical climate mitigation potential of boreal peatlands during the growing season

Peatlands and forests cover large areas of the boreal biome and are critical for global climate regulation. They also regulate regional climate through heat and water vapour exchange with the atmosphere. Understanding how land-atmosphere interactions in peatlands differ from forests may therefore be crucial for modelling boreal climate system dynamics and for assessing climate benefits of peatland conservation and restoration. To assess the biophysical impacts of peatlands and forests on peak growing season air temperature and humidity, we analysed surface energy fluxes and albedo from 35 peatlands and 37 evergreen needleleaf forests-the dominant boreal forest type-and simulated air temperature and vapour pressure deficit (VPD) over hypothetical homogeneous peatland and forest landscapes. We ran an evapotranspiration model using land surface parameters derived from energy flux observations and coupled an analytical solution for the surface energy balance to an atmospheric boundary layer (ABL) model. We found that peatlands, compared to forests, are characterized by higher growing season albedo, lower aerodynamic conductance, and higher surface conductance for an equivalent VPD. This combination of peatland surface properties results in a similar to 20% decrease in afternoon ABL height, a cooling (from 1.7 to 2.5 degrees C) in afternoon air temperatures, and a decrease in afternoon VPD (from 0.4 to 0.7 kPa) for peatland landscapes compared to forest landscapes. These biophysical climate impacts of peatlands are most pronounced at lower latitudes (similar to 45 degrees N) and decrease toward the northern limit of the boreal biome (similar to 70 degrees N). Thus, boreal peatlands have the potential to mitigate the effect of regional climate warming during the growing season. The biophysical climate mitigation potential of peatlands needs to be accounted for when projecting the future climate of the boreal biome, when assessing the climate benefits of conserving pristine boreal peatlands, and when restoring peatlands that have experienced peatland drainage and mining.Peer reviewe