Chinese Science Bulletin
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Effects of historical land cover changes on climate
SHI ZhengGuo1,2, YAN XiaoDong1†, YIN ChongHua1,2 & WANG ZhaoMin3 1 Key Laboratory of Regional Climate-Environment Research for Temperate East Asia, Chinese Academy of Sciences, Beijing
100029, China; 2 Graduate University of Chinese Academy of Sciences, Beijing 100049, China; 3 British Antarctic Survey, Cambridge CB30ET, UK
In order to explore the influence of anthropogenic land use on the climate system during the last mil-lennium, a set of experiments is performed with an Earth system model of intermediate complexity——
the McGill Paleoclimate Model (MPM-2). The present paper mainly focuses on biogeophysical effects of historical land cover changes. A dynamic scenario of deforestation is described based on changes in cropland fraction (RF99). The model simulates a decrease in global mean annual temperature in the range of 0.09－0.16℃, especially 0.14－0.22℃ in Northern Hemisphere during the last 300 years. The responses of climate system to GHGs concentration changes are also calculated for comparisons. Now, afforestation is becoming an important choice for the enhancement of terrestrial carbon sequestration and adjustment of regional climate. The results indicate that biogeophysical effects of land cover changes cannot be neglected in the assessments of climate change.
climate change, radiative forcing, land cover changes, deforestation, climate-biosphere interactions
With the development of our society, especially after the Industrial Evolution, the effects of anthropogenic activi- ties on climate are becoming more and more important, and now the climate system would be influenced by both nature and humankind. Compared to the natural factors, such as insolation and volcanic activities, humankind affects the climate system in many ways, particularly by modifying atmospheric gas composition and by chang- ing land surface properties. Till now, global warming induced by increasing greenhouse gases (GHGs) has been paid close attention to, however, the influence of land cover changes has not been considered enough and few researches have been focused on these. In fact, hu-man-induced land cover changes began probably as early as 8000 years ago[1], and at present, about one third of global vegetation cover has being modified by agri-cultural and forestry activities[2]. Therefore, it is neces-sary for us to evaluate the effects of land cover changes.
Changes in land cover have affected the climate sys-tem through emissions of GHGs (biogeochemical effects) and modification of land surface albedo and roughness
(biogeophysical effects). Biogeophysical mechanisms of land cover changes are considered quite complex and could affect not only regional but also global climate. Hansen et al.[3] emphasized the radiative effects of vegetation cover changes in the review of climate forc-ings, pointing out that their radiative forcing was in the range of about (−0.2 ± 0.2) W/m2 and maybe leads to a global cooling by 0.14℃. The mechanism of this forcing is mainly that land surface albedo increases a lot due to the replacement of forests by croplands and pastures, and it could be more notable in the high northern lati-tudes, where snow-masking effect of vegetations is very remarkable. Bonan et al.[4] revealed a cooling effect of boreal deforestation and except for direct influences of deforestation, the sea ice-albedo feedback also played an important role in the cooling, while Henderson-Seller et al.[5] simulated a warming effect of tropical deforestation Received February 26, 2007; accepted April 19, 2007 doi: 10.1007/s11434-007-0381-z †Corresponding author (email: [email protected]) Supported by the Project of “Aridification over Northern China and Human Adapta-tion” (Grant No. 2006 CB400500)
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due to reduction in latent heat flux. Most simulations on land cover changes have been carried out with atmos-pheric general circulation models (GCMs) without in-teractive ocean parts. And the response might be limited since feedbacks with sea surface temperature and sea ice are neglected. However, experiments indicate that the climate system is very sensitive to changes of sea sur-face temperature[6]. Because GCMs are computationally expensive, at most time we can only assess the equilib-rium response of climate system but it would be difficult to incorporate the transient response of dynamic land cover forcing on the long time scale.
The emerging class of Earth system models of inter-mediate complexity (EMICs) could give us some new choices. By the way of parameterizations, EMICs have simplified the complex processes and feedbacks in the climate system so that they could contain all the neces-sary components such as atmosphere, ocean, biosphere and ice sheets. Compared with GCMs, EMICs are more computationally efficient and make it possible to evalu-ate transient response. Brovkin et al.[7] highlighted that land cover changes helped to explain changes of global temperature during the last 150 years. In particular, the biogeophysical cooling would have counterbalanced the warming effect of increasing GHGs from the second part of 19th century. Transient experiments by Brovkin et al.[8] suggest that historical land cover changes during the last millennium lead to a global cooling by 0.35℃, while the result of Bertrand et al.[9] is −0.1℃, and they also suggest that the cooling in Little Ice Age might be amplified by vegetation cover changes.
In China, researchers have also paid more and more attention to the effects of land cover changes on cli- mate[10－14]. An et al.[10] pointed out that due to the ex- panding of croplands, global forest cover has reduced a lot in the last 300 years, particularly in Asia. So it is in-deed necessary to evaluate the effects of land cover changes. Furthermore, Fu et al.[11] advised that heavy deforestation largely bringed about regional climate changes in Asia in both conditions near surface and the density of monsoon. Yet, researches focused on the ra-diative forcing of global deforestation are still very few now.
To recognize the mechanism of temperature trend in the last millennium and predict climate change in the future, the relative contributions of natural and anthro-pogenic activities have to be clarified first. We have well
simulated the effects of natural forcings on climate be-fore, by an EMIC－MPM-2[15]. And now, we continue to perform some experiments on the influences of land cover changes, in order to evaluate their radiative effects on global scale and explore the applicability of MPM-2 in the multi-century simulations. For simple comparison, GHGs forcing is also considered at the same time. We hope it could help to research the influences of regional climate due to land cover changes in China.
1 Methods 1.1 Model description
MPM-2 employed in this paper is an Earth system model of intermediate complexity (EMIC)[16], which consists of an energy and moisture balance atmosphere model, a multi-basin zonally averaged dynamic ocean model, a dynamic ice sheet model, a zero-layer thermo-dynamic-dynamic sea-ice model and a land biosphere model. MPM-2 has a coarse resolution, as shown in Figure 1, and has been downscaled to 5°×5° in 30°－75°N.
The atmosphere module of MPM-2 is a simple 2D EMBM[17], which has a new parameterized solar energy disposition scheme[18]. The meridional heat transport is parameterized by a combination of advection and diffu-sion processes and the zonal heat transport is parameter-ized as a diffusion process only. However, the zonal moisture transport is parameterized so that the moisture is always transported from the ocean to the land in all seasons. The ocean module is a zonally averaged dy-namic model based on vorticity conservation, which has nine vertical layers[19]; MPM-2 employs a simple ther-modynamic sea ice module, in which sea ice surface temperature and averaged thickness are predicted by the method of Semtner[20] and the meridional advection is prescribed. The vegetation module VECODE is based on a continuous bioclimatic classification which pro-vides the relative cover of tree, grass and potential desert for each latitude[21]. MPM-2 has successfully simulated changes in the thermohaline circulation state[22,23] and the last glacial inception[24]. Furthermore, MPM-2 have also well simulated the climate changes on thousand- year scale since Holocene, such as temperature, precipi-tation and vegetation distribution[25].
1.2 Global land cover dynamic
Till now, knowledge about global historical vegetation
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Figure 1 The land-sea configuration of MPM-2.
cover changes is still very limited, and there had been even no definite descriptions before 1700 AD[26,27], which might be a missing key to test hypotheses of hu-man influence on climate through land cover changes. Owing to this limitation, we have to employ fractional cropland dataset of Ramankutty and Foley for the years 1700－1992 AD(RF99)[26], and suppose that changes in cropland area are interpreted as the conversion from forest to grassland since cropland and grassland have similar properties influencing heat balance and water cycle. Ramankutty and Foley[26] suggested that although differences between changes in forest and crop area would be quite substantial on the regional scale, the in-crease in cropland area is approximately equal to the decrease in forest area on the global scale. So this as-sumption sounds reasonable on the global scale, al-
though in general, the increase in crop fraction and de-forestation are not the same, for example, some crop area might be the results of grassland conversion.
RF99, with a resolution of 0.5°×0.5°, has described the changes in cropland fraction during the years 1700―1992 AD. It indicates that the cropland fractions are very large in China, South Asia and Europe. Zonally averaged deforestation dynamic for the last 300 years is shown in Figure 2. During this period, decrease in global forest area could reach nearly 1.2 billion ha, while cropland area has increased by about 1.2 billion ha.
The temporal dynamic of deforestation prior to 1700 AD is still uncertain now. To evaluate the relative role of the last 300 years in the history and simplify the compu-tations, a linear interpolation of data is used in the period 1000―1700 AD assuming no cropland in the year
Figure 2 Zonally averaged distribution of deforestation for the period during 1700―1992 AD (in model resolution).
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1700[28].
1.3 Experiments
Our experiments are briefly described in Table 1. At first, a series of transient experiments is performed with the forcings of land cover changes and GHGs. Taking ac-count of the nonlinear responses of climate system, the biogeophysical effects of land cover changes are evalu-ated through two kinds of methods: (i) We consider straight the climate change due to land cover changes (ED-Control) and (ii) the differences between climate reponses due to both and the forcing GHGs only (EGD- EG). Then we repeat the simulations (i) when the albedo of grassland is prescribed at 0.16, 0.18 and 0.20, respec-tively, to analyse MPM-2’s sensitivity to land surface albedo changes. Besides, an equilibrium experiment is also performed under the scenario that no forests exist in the world and all forests are converted to grass, so as to assess the potential influence of cropland expansion.
Since the time step of our dataset RF99 is 10 years, it is vital to incorporate changes in global cropland frac-tion during this period into our MPM-2 model, compute the following vegetation distribution, then fix it and simulate the corresponding changes of other climate factors. In order to obtain the same initial conditions, we integrate all our simulations from 1000 to 2000 AD after a spin-up time of 5300 years to equilibrium.
2 Results 2.1 Transient response of global temperature to GHGs
Here, changes in atmospheric concentration of GHGs over the past millennium are taken from the ice core data of Law Dome, D47, D57, Mauna Loa, and so on[29－31]. We have calculated the equivalent CO2 con- centration from the formulations given in IPCC report (2001) and the time evolution of CO2 concentration is shown in Figure 3(a). It is shown that there were few changes in GHGs concentration before 19th century, but
after the Industrial Evolution, they increased gradually and became more rapid in the past 50―100 years. The transient response of global mean temperature due to GHGs forcing is given in Figure 3(b). Global mean tem-perature has already increased by 0.97℃ in the last millennium and CO2 could play a dominant role, ac-counting for about 70 percents of all.
Figure 3 (a) The time evolution of equivalent CO2 concentration in the last millennium (μL·L−1); (b) The transient response of global mean tem-perature to changes in GHGs concentration: CO2 (black) and others (grey).
2.2 Response of Global and Northern Hemispheric (NH) temperatures to land cover changes
In response to land cover changes, our model simulates a decline in the NH mean temperature, as given in Fig-ure 4. The rate of this cooling trend accelerated during the 19th century, reached a maximum at the first half of 20th century and declined in the last 50 years. Actually, cropland expansion in NH extratropics and the tropical regions was rapid in the first half of 20th century and however, during the second half of 20th century, crop-land expansion was replaced by reforestation in Europe, North America and China, although cropland still ex-panded in the tropics.
Changes in the Global and NH temperature in the past 300 years in all our simulations are clearly seen in Table 2 (the albedo of grassland is 0.l6). During this period,
Table 1 Experiments
Experiment Descriptions of climate forcings ED Land cover changes only, CO2 concentration is fixed at 280 μL·L−1, grassland albedo is 0.16(0.18, 0.20) EG GHGs concentration only
EGD Both GHGs and land cover changes Control Control experiments with no forcings, CO2 is fixed at 280 μL·L−1, grassland albedo is 0.16(0.18, 0.20) EnoT “No forests” scenario, and CO2 concentration is 280 μL·L−1
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Table 2 Differences in Global/NH averaged temperature during the past 300 years in our simulations( minus control)
Temperature differences due to climate forcings Global/ NH
ΔTED −0.09℃/−0.15℃ ΔTEG 0.98℃/1.01℃ ΔTEGD 0.89℃/0.87℃
ΔTEGD−ΔTEG −0.09℃/−0.14℃ ΔTED−(ΔTEGD−ΔTEG) −0.00℃/−0.01℃
deforestation in the NH is much heavier than SH. And due to the much larger land mass in the NH relative to SH, the response to the NH is more pronounced. In the past 300 years, our model simulated a decline of about 0.14℃ in the NH mean temperature and 0.09℃ in global one. At the same time, all historical land cover changes in the last millennium made the NH and Global
temperatures decrease by about 0.18 and 0.11℃, respec-tively. So we conclude that radiative forcing of vegeta-tion cover changes is mainly concentrated in the last 300 years, about four fifths in total.
For the “no forests” scenario that all forests on land are converted to grass, the changes in both NH tempera-ture and sea ice cover are shown in Figure 5. A signifi-cant nonlinear response of temperature to vegetation cover changes has been suggested and could be ex-plained by the positive feedback of sea ice. As a result of reduction in temperature, the sea ice cover expands, which leads to the decrease in absorbing short-wave ra-diation, and could even affect the thermohaline circula-tion. It takes hundreds of years for climate system to reach the equilibrium, finally indicating a decline of
Figure 4 The transient response of the NH averaged temperature to land cover changes between 1000 and 1992 AD (10-year average) by method II: EGD (red) minus EG (blue).
Figure 5 The transient responses of the NH averaged temperature (a) and sea ice cover (b) under “no forests” scenario (10-year average).
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0.85℃ and 1.1℃ in the Global and NH temperatures. The results suggest that the potential influence of land cover changes could be very large, which should be paid more attention to. However, compared to GHGs, the biogeophysical effects of land cover changes are less significant by far.
2.3 Response of zonal and seasonal temperatures and precipitation to land cover changes
In order to evaluate the response of temperatures at dif-ferent latitudes in the last 300 years, seasonal tempera-tures in the transient experiments of EGD and ED are analysed, and their zonal differences are shown in Fig-ure 6(a). In the NH mid and high latitudes, heavy defor-estation leads to a decline of about 0.3℃, while in the tropics and SH, the temperature changes are not very significant due to the less land mass and cropland ex-pansion. For example, in the region of 30°―40°S, al-though cropland area has increased by 15%, the slight changes in temperature could still be neglected. It is in accordance with that of Claussen et al.[32].
The significant cooling in the northern high latitudes is explained mostly by changes in land surface albedo due to the snow-masking effect of forests. The zonal and seasonal distributions of differences in albedo are clearly given in Figure 6(b). In these regions, annually averaged albedo has increased by 0.02, and in particular, the in-crease in spring is rather high and approaches 0.04 since during this season, the snow-masking effect is the most pronounced. That is why temperature change in spring (about 0.4℃) is the largest in our simulations. Whereas, the increase in land surface albedo is merely 0.01 in summer and autumn as a result of the absence of snow. In addition, the cooling is also amplified by the feedback of expansion of the NH sea ice cover due to deforesta-tion.
As is well known, the atmospheric module of MPM-2 is an energy balance model, which is sensitive to changes in land surface albedo. So we simulate the re-sponses of averaged temperature when the albedo is prescribed relatively to 0.16, 0.18 and 0.20, as shown in Table 3. It indicates that differences in temperature due
Figure 6 Zonal differences of seasonal temperatures (a), land surface Albedo (b) and precipitation (c) during the years 1700―1992 AD, MAM (red), JJA (green), SON (blue), DJF (yellow) and annual (black).
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Table 3 Differences of Global/NH mean temperature and downward short-wave radiation absorbed by atmosphere between different grassland albedos (1700―1992 AD)
Albedo Global (℃) NH (℃) Radiation (w·m−2)
0.16 −0.09 −0.14 −0.17
0.18 −0.12 −0.18 −0.20
0.20 −0.16 −0.22 −0.24
to albedo changes are highly significant. As land surface albedo increases, the temperature changes become more and more remarkable. Changes in downward short-wave radiation absorbed by atmosphere are −0.17 to −0.24 W/m2, being in the range of (−0.2 ± 0.2) W/m2 suggested by Hansen et al.[3].
Zonal differences of averaged precipitation during the last 300 years are given in Figure 6(c). Deforestation leads to a decline in the latent heat fluxes, and then cause a reduction in water vapour coming into the at-mosphere. Thus, annually averaged precipitation has decreased in most regions and is about 0.05 mm/d in the NH. Moreover, changes in precipitation are more sig-nificant in summer, with the largest being more than 0.1 mm/d in the tropics, since the hydrological cycle is most affected by vegetation growth during the growing season. However, the atmosphere module here is represented by a simple EMBM in the absence of detailed descriptions about atmospheric circulations and cloud dynamics, so there are still some limitations about rainfall in our simulations.
3 Discussion
The previous studies about biogeophysical effects of land cover changes are shown in Table 4. As noted in the introduction, GCMs and EMICs were usually employed in the previous simulations. On one hand, GCMs have their advantage of simulating high-resolution dynamics and feedbacks of inner atmosphere. Simulations with the NCAR model suggest that wave dynamics may offset the direct effect of albedo changes[33]. However, because
of their high computational costs, most GCM experi-ments have been performed in equilibrium simulations with fixed ocean mode, which might neglect feedbacks of SSTs and sea ice and severely limits the climate re-sponse. Simulations with the NCAR model indicate a pronounced warming in northern temperate and high latitudes that leads to a global warming by 0.06℃[33]; while the HadAM3 model reveals a cooling effect of 0.02℃ on the global scale with a cooler winter and a warmer summer[34]. On the other hand, EMICs have simplified parameterisations and often coarse resolution, but they contain all the important components (atmos-phere, ocean, sea ice and land) interacting with each other. The direct effect of land cover changes is ampli-fied by positive feedbacks, such as sea ice. Hence, EMICs usually have more significant responses in com-parison with GCMs. In our simulations, global mean temperature has changed about −0.09 to −0.16℃, as shown in Table 4. So we suppose that ability of MPM-2 in simulating multi-century climate change might be acceptable.
In our simulations, temperature changes due to an- thropogenic land use are very significant in the northern temperate and high latitudes, in accordance with GCMs[33], which indicates the important role of snow masking effect in the regions of heavy deforestation. But in the tropics, the cooling contradicts results of GCM simulations at a first glance. Snyder et al.[35] suggested a pronounced temperature increase over deforested tropi- cal land due to the decreased ratio of latent to sensible heat fluxes. Actually, SSTs are often prescribed in most GCM simulations, which neglects the water vapour feedback and may reverse the sign of mean temperature in the tropics. In the GCM simulations with interactive mixed layer ocean by Zhang et al.[36], averaged surface air temperature declines by 0.2℃ by tropical deforesta-tion in these regions; with coupled atmosphere-ocean GCM simulations, Feddema et al.[37] have also found a
Table 4 Reviews of previous studies about biogeophysical effects of land cover changes
Model Land cover dataset Ocean mode Time frame Global temperature changes (℃)HadAM3 Wilson and Henderson - Seller 1985 Fixed Preindustrial―1990s −0.02 NCAR CCM3 BATS Fixed Preindustrial―1990s +0.06 DOE-PCM IMAGE2.2 Dynamic Preindustrial―1990s −0.39 MOBIDIC HGT (1983) Dynamic 1000―2000 −0.11 UVIC RF99, HYDE Dynamic 1700―1992 −0.06―−0.22 CLIMBER HGT (1983), RF99 Dynamic 1000―1992 −0.35, −0.24 MPM-2 (This study) RF99 Dynamic 1000―1992/1700―1992 −0.11―−0.19/−0.09―0.16
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decrease in averaged surface air temperature in the trop-ics by 0.2℃, in line with our results. In addition, the lack of knowledge about historical land cover changes may also amplify the uncertainty of our simulations. Matthews et al.[38,39] pointed out that climate models might be sensible to different datasets, through their comparison between two popular datasets at present, RF99 and HYDE similar to averaged temperature, the precipitation has reduced all over the world, being about 0.05 mm/d in the NH. Brovkin et al.[8] indicated that due to deforestation, precipitation has decreased by 0.1 mm/d in most regions of NH, in good agreement with ours. In the tropical regions, our results also show a no-table reduction in averaged precipitation, which is con-sistent with most GCM simulations[40－42]. But some simulations with higher resolution models show oppo-site results. Baidya and Avissar[43] have found that de-forestation could cause changes of atmospheric circula-tions, which could affect the transport of heat and mois-ture, and then lead to a increase in precipitation.
Impacts of anthropogenic land use on regional cli-mate are also very significant. In comparison with greenhouse effect, land use could play a more important role in regional climate change. For East Asia, with a long-term cropland expansion and heavy deforestation (up to 90%), it is reasonable to suppose a very signifi-cant reduction in temperature due to land cover changes. Our experiments also show that in East Asia, South Asia and parts of Europe where deforestation is the heaviest, precipitation decrease could also be most pronounced. In particular, an incline of 0.1―0.3 mm/d in East Asia is simulated. At last, it is necessary to point out that al-though biogeophysical effects of land cover changes could counterbalance the warming effect of GHGs at present to a certain extent, it is still not expected that deforestation would only completely suppress the greenhouse effect.
4 Conclusions
In all, our simulations of biogeophysical effects of land
cover changes on climate indicate that anthropogenic land use has already played a very important role in cli-mate change during the last centuries, and also tell us that:
(i) The heaviest deforestation occurred during the pe-riod of the last 300 years. Global averaged temperature decreases by 0.09―0.16℃ due to land cover changes, accounting for about four fifths of the whole history, while in the NH, the decrease is 0.14―0.22℃. Mean-while, increase in GHGs concentration leads to a global warming by 0.97℃.
(ii) In the “no forests” scenario, the results suggest that potential impact of deforestation on climate could be very significant and even affect the thermohaline cir-culation. This process would last for a long period and finally cause a global/NH cooling by 0.85/1.1℃.
(iii) In comparison with other researches on biogeo-physical effects of land cover changes, we have found that the MPM-2 model, one of EMICs, can simulate multi-century climate change well and provide some new choices for model simulations on historical land use.
(iv) Due to the coarse resolution of our model, we can not simulate the details of climate change on the re-gional scale. For our simple atmosphere module (EMBM), details about atmospheric circulations and cloud physics have been neglected, and this causes some problems in climate simulations, especially for precipi-tation; in the absence of global carbon cycle module, we have not evaluated the biogeochemical effect of land cover changes; these questions are unsolved yet.
At present, afforestation is becoming an important choice for the enhancement of terrestrial carbon seques-tration and adjustment of regional climate and land cover changes may lead to a global warming in the fu-ture. Anyhow, we should pay more attention to the bio-geophysical effects of land cover changes in the assess-ments of climate change.
The authors thank RamanKutty N. and Foley J. for providing historical land use dataset (RF99).
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