«Investigating the Relative Roles of the Degradation of Land and Global Warming in Amazonia Sergio H. Franchito, J. P. R. Fernandez and David Pareja ...»
Investigating the Relative Roles of the Degradation of
Land and Global Warming in Amazonia
Sergio H. Franchito, J. P. R. Fernandez and
Additional information is available at the end of the chapter
Large-scale removal of the tropical rain forest will have significant negative effects on regional
water and energy balance, climate and global bio-geochemical cycles. Numerical experiments
using General Circulation Models (GCMs) [1, 2, 3 and many others], using statistical-dynam‐ ical simple climate models (SDMs) [4, 5, 6] and field observations)  have shown that the large-scale deforestation in Amazonia may indeed influence regional climate. Reduction in evapotranspiration and precipitation and an increase in the surface temperature in the tropical region occur when the forest is replaced by pasture.
Projections of future climate given in IPCC AR5 (2013) (to be published) indicated that climate change due to anthropogenic human activities is affecting adversely the ecosystems. Many model studies showed that the global warming may affect the biomes distribution over South America, where significant portions of rain forest may be replaced by nonforested areas [8, 9, 10, 11]. These studies suggest that due to increase of greenhouse gases concentration the process of savannization of the tropical forest can be accelerated. This indicates that the future distribution of biomes in the tropical region depends on the combination of the effects of the degradation of land surface and climate changes due to global warming. Some studies have been made to investigate the relative roles of future changes in greenhouse gases compared with future changes in land cover.  and  compared the climate change simulated under a 2050 SRES B2 greenhouse gases scenario to the one under a 2050 SRES B2 land cover change scenario. It was noted that the relative impact of vegetation change compared to greenhouse gas concentration increase was of the order of 10%, and could reach 30% over limited areas of tropical region. The same methodology was applied for the SRES A2 and B1 scenario over the 2000 to 2100 period . It was also found that although there was no signiﬁcant effect at the © 2015 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
74 Global Warming - Causes, Impacts and Remedies global scale, a large effect at the regional scale may occur, such as a warming of 2°C by 2100 over the Amazon for the A2 land cover change scenario. Recently, studies using SDMs showed that the percentage of the warming due to deforestation relative to the warming when greenhouse gas concentration increase was included together was around 60% in the tropical region [5, 6]. These results suggest that the climate change due to land cover changes may be important relative to the change due to greenhouse gases at the regional level, where intense land cover change occurs. Globally, however, the impact of greenhouse gas concentrations seems to dominate over the impact of land cover change.
Although GCMs and SDMs can provide useful information regarding the response of the global circulation to large-scale forcing, due to their coarse resolution the mesoscale forcing, such as complex topography, vegetation cover, lakes, etc, are not well represented. In this sense Regional Climate Models (RCMs) may be more adequate. RCMs have therefore been developed to downscale larger scale simulations and to provide predictions for speciﬁc regions [15, 16, 17, 18].
In this paper the relative roles of the land surface degradation in Amazonia and global warming are investigated using a RCM. The purpose is to inquire how is the effect on the regional climate and aridity due to deforestation and when the increase of concentration of greenhouse gases is also taken into account together. The model to be used is The Abdus Salam International Centre for Theoretical Physics Regional Climate Model v. 4 (ICTP/RegCM4) .
In order to take into account the effect of global warming the model will be run using a methodology for generating surrogate climate-change scenarios with a regional climate model . The distribution of aridity is determined using the radiative dryness index of Budyko (AIB)  and the UNEP aridity index (AIU) . A brief description of the RCM, the method‐ ology employed and the experiments design are given in section 2; the model simulations are presented in section 3 and section 4 contains the summary and conclusions.
2. Regional climate change model
The model ICTP RegCM4  is the version 4 of the regional climate model (RegCM) originally developed at the National Center for Atmospheric Research (NCAR) [15, 16]. The dynamic component of the model is based on the NCAR-Pennsylvania State University meso-escale model (MM5) . For application in climate studies, a number of physical parameterizations were incorporated in the model. More details about the model and physical configurations for South America is given in . In the present study modified parameters of BATS land-surface model for vegetation type 6 (tropical rain forest) are used to reduce the rainfall dry bias over tropical South America, as reported in earlier RegCM versions .
performed (after discarding a 1 yr spin-up period), extending from 1 January of 1990 to 31 December of 1999.
Figure 1. Model domain.
Also shown is the topography of South America. Units, m.
2.1. Control experiment model In the control experiment the model is forced using the ERA-Interim reanalysis data . The greenhouse gas concentration corresponds to the present-day conditions. The distribution of aridity is obtained using the Budyko radiative dryness  and the UNEP aridity index .
The Budyko index has been used in many studies of land-surface effects, climate change and biogeography [27, 28, 29 and many others]. The UNEP index was adopted by UNEP to produce a dryness map .
The Budyko index, AIB, is defined as AIB=R/ (LP), where R is the mean annual net radiation;
P, the mean annual precipitation and L is the latent heat of evaporation. Thresholds for
different climate regimes are defined as:
0 AIB ≤ 1=humid (surplus moisture regime; steppe to forest vegetation) 1 AIB ≤ 2=semi-humid (moderately insufficient moisture; savanna) 2 AIB ≤ 3=semi-arid (insufficient moisture; semi-desert) AIB 3=arid (very insufficient moisture; desert) 76 Global Warming - Causes, Impacts and Remedies The UNEP index, AIU, is defined by AIU=P / PET, where P is the annual precipitation and PET is the annual potential evapotranspiration. P is provided by the model while PET is calculated
using the formula of . Thresholds for different climate regimes are:
AIU ≥ 1= humid regime 0.65 ≤ AIU 1=dry land 0.50 ≤ AIU 0.65=dry sub-humid regime 0.20 ≤ AIU 0.50=semi-arid regime 0.05 ≤ AIU 0.20=arid regime AIU 0.05=hyper-arid regime Results of  showed that in general the climate variables, such as temperature, precipitation and evaporation, and the distribution of aridity over South America using both the Budyko and UNEP indices, for the present-day climate are well simulated by the model.
2.1.1. Climate change experiment on deforestation
The biomes distribution over South America according to the vegetation types given by BATS1e is given in Fig. 2a. In the deforestation experiment the entire tropical forest zone is converted into short grass (Fig. 2b). So, all the characteristic parameters of the tropical forest are replaced by those from short grass conditions according to BATS1e. Though extreme, it is important to evaluate a scenario of a hypothetical complete Amazon deforestation. The extreme scenario of total deforestation is useful to provide insight into underlying physical principles of the functioning of the climate system. Although it is unlikely that deforestation will affect the entire Amazonian forest, the extreme scenario of total deforestation is useful to identify the sensitivity of the climate system to changes in the land surface properties. In this experiment the effects of deforestation in Amazonia on the regional climate and aridity is studied.
2.1.2. Surrogate climate change experiment including deforestation
In this experiment the effects of global warming is taken into account together with the deforestation in Amazonia. For this purpose the methodology for generating a surrogate climate change scenario with a RCM proposed by  is used. It consists of a uniform 3 K temperature increase and an attendant increase of specific humidity. In this scenario, the ERAInterim dataset of temperature is increased by 3K throughout the atmospheric column and the sea surface temperature OISST dataset  are warmed by 3 K. The atmospheric greenhouse gases concentration of the sensitivity experiment is set to two times its present-day values. A global mean equilibrium surface temperature increase of 3 K corresponds approximately to a CO2 equivalent concentration of 710 ppm .
The methodology for generating a surrogate climate change scenario is dynamically consistent and easy to incorporate in a RCM. The procedure can be applied to the study of the regional response to a pseudo-global warming with an accompanying increase of the Investigating the Relative Roles of the Degradation of Land and Global Warming in Amazonia 77 http://dx.doi.org/10.5772/58991 Figure 2. a) Vegetation types over South America according BATS1e; b) Region of Amazonia where the evergreen broadleaf trees are replaced by short grass in the deforestation experiment. Also shown are the areas denoting: north Amazonia (NAM), central Amazonia (CAM) and south Amazonia (SAM).
atmospheric water vapor content. However, the surrogate climate change scenario is only a sensitivity experiment and not a real climate change experiment. In a surrogate climate change scenario the response to a combination of a horizontally uniform thermodynamic modification of the initial and external fields plus an unmodified external flow evolution is studied. Otherwise a real climate change would be accompanied by changes in the planetary and synoptic-scale circulation. In spite of this drawback, the methodology allows us to examine certain processes in isolation [20, 34, 35].
78 Global Warming - Causes, Impacts and Remedies
3. Results and discussion
In order to discuss with more regional details the effects of deforestation and the pseudowarming on Amazonia, three regions are considered: north (0-5N, 70W-52W), central (8S-0, 74W-50W) and south (13S-8S, 70W-52W) Amazonia (Fig. 2b). This is because the changes are different in these regions, as will be seen in the next sections.
3.1. Effect of deforestation
Figure 3 shows the distribution of aridity for the control and deforestation experiments and the change (deforestation minus control) using the Budyko and UNEP indices. As can be seen in Figs. 3a and 3b, areas of humid regime (forest) are replaced by sub-humid regime (savanna) in the part of central Amazonia southward from 5S and in the south Amazonia in the defor‐ estation experiment compared with the control. The Budyko index increases (increase of aridity) in these regions. In the north and most of the central Amazonia the aridity is decreased (Fig. 3c). As shown in Table 1, taking into account the values of AIB averaged over the entire three regions of Amazonia, the aridity increases 22% relative to the control in the south region.
In the north and central areas there is a decrease of the aridity of 4% and 1.1%, respectively.
For the case of the UNEP index, it can be noted from Figs. 3d and 3e that dry land substitutes regions of humid regime in Amazonia. The UNEP index decreases (the aridity increases) in the central and south Amazonia while in the north Amazonia it increases, as seen in Fig. 3f.
These changes in the UNEP indicate an increase in the aridity of 22% and 4.8% relative to the control in the south and central Amazonia, respectively, while in the north Amazonia there is a decrease of 3% (Table 1).
Although the changes in the distribution of aridity due to deforestation using Budyko and UNEP indices show a very good agreement in the south and north Amazonia, the results diverge in the central region: the use of Budyko index indicates a decrease of aridity while the UNEP index suggests an increase.
Table 1. Values of AIB and AIU and the relative changes in the experiments of deforestation and deforestation plus pseudo-warming.
Figure 3. Distribution of aridity using Budyko index: a) control experiment, b) deforestation experiment and c) changes (deforestation minus control); and using UNEP index: d) control experiment, e) deforestation experiment and
f) changes (deforestation minus control).
80 Global Warming - Causes, Impacts and Remedies The changes (perturbed minus control) in the net surface radiation, precipitation, evapotrans‐ piration and surface temperature due to deforestation are shown in Table 2. There is a decrease of the mean net surface radiation (-7.8 W m-2) due to the increase of the land surface albedo;