ISSN 00014338, Izvestiya, Atmospheric and Oceanic Physics, 2011, Vol. 47, No. 1, pp. 15–30. © Pleiades Publishing, Ltd., 2011. Original Russian Text © A.V. Eliseev, I.I. Mokhov, 2011, published in Izvestiya AN. Fizika Atmosfery i Okeana, 2011, Vol. 47, No. 1, pp. 18–34.
Effect of Including LandUse Driven Radiative Forcing of the Surface Albedo of Land on Climate Response in the 16th–21st Centuries A. V. Eliseev and I. I. Mokhov Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, per. Pyzhevskii 3, Moscow, 119017 Russia email:
[email protected] Received February 3, 2010; in final form, March 16, 2010
Abstract—A change in ecosystem types, such as through naturalvegetation–agriculture conversion, alters the surface albedo and triggers attendant shortwave radiative forcing (RF). This paper describes numerical experiments performed using the climate model (CM) of the Institute of Atmospheric Physics (IAP), Russian Academy of Sciences, for the 16th–21st centuries; this model simulated the response to a change in the con tents of greenhouse gases (tropospheric and stratospheric), sulfate aerosols, solar constant, as well as the response to change in surface albedo of land due to naturalvegetation–agriculture conversion. These forcing estimates relied on actual data until the late 20th century. In the 21st century, the agricultural area was spec ified according to scenarios of the Land Use Harmonization project and other anthropogenic impacts were specified using SRES scenarios. The change in the surface vegetation during conversion from natural vegeta tion to agriculture triggers a cooling RF in most regions except for those of natural semiarid vegetation. The global and annual average RF derived from the IAP RAS CM in late 20th century is –0.11 W m–2. Including the landuse driven RF in IAP RAS CM appreciably reconciled the model calculations to observations in this historical period. For instance, in addition to the net climate warming, IAP RAS CM predicted an annually average cooling and reduction in precipitation in the subtropics of Eurasia and North America and in Ama zonia and central Africa, as well as a local maximum in annually average and summertime warming in East China. The landuse driven RF alters the sign in the dependence that the amplitude of the annual cycle of the nearsurface atmospheric temperature has on the annually averaged temperature. One reason for the decrease in precipitation as a result of a change in albedo due to land use may be the suppression of the con vective activity in the atmosphere in the warm period (throughout the year in the tropics) and the correspond ing decrease in convective precipitation. In the 21st century, the effect that the landuse driven RF has on the climate response for scenarios of anthropogenic impact is generally small. Keywords: land use, radiative forcing, future climate change scenarios, IAP RAS CM. DOI: 10.1134/S0001433811010075
1. INTRODUCTION
By the early 18th century (the preindustrial era), 3–6% of land not covered by ice sheets was permanent agricultural land [8, 9]. By the late 20th century, this percentage had increased to approximately a third of the icefree area [9, 10]. The estimates presented in [11] suggest that the current topofatmosphere (TOA) radiative forcing (RF) in terms of albedo changes due to the conversion of natural vegetation into agricultural species ranges from 0.0 to (–0.4) W m –2, the central value being (–0.2) W m2 for a characteristic local to continental scale climate response (see also [12]). Generally speaking, this is not a negligibly small value relative to the general anthropogenically induced RF over an industrial era, ranging from 0.6 to 2.4 W m–2, the central estimate being 1.6 W m–2. A marked climate response to the landuse driven RF has been reported in numerical experiments with the use of climate models. For instance, calculations
Land use leads to a change in the surface albedo of land and in the intensity of turbulent heat and mois ture transfer between the atmosphere and the soil management layer [1–7]. In particular, the conversion of midlatitude and boreal forests to grass and scru bland vegetation, which are characteristic for agricul tural lands at these latitudes, leads to a net growth in the surface albedo, primarily due to snow masking by woody vegetation during winter [2, 3, 6], which favors climate cooling. Moreover, these practices lead to a change in the intensity of moisture transfer from the soil to the atmosphere by vegetation and to a change in the roughness height, which, in turn, affects the turbu lent heat and moisture exchange between the land sur face and the atmosphere [2, 6]. The effects that land use driven disturbances of different types have on cli mate may be mutually compensating [4]. 15
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performed with climate model of intermediate com plexity [13, 14] predict globally average climate cool ing due to general landuse caused increase in the sur face albedo of land over the last few centuries in the range from 0.13 to 0.25 K [5]. At present, the LandUse and Climate Identification of Robust Impacts (LUCID) project is undertaking a comparison between responses of the climate general circulation models (GCMs) and the landuse driven RF [7]. The objective of this paper is to estimate how a landuse driven change in the surface albedo of the land affects the climate response over the last few cen turies and the 21st century due to anthropogenic and natural impacts of different origins. This estimate is derived using a climate model of intermediate com plexity developed at the A.M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences (IAP RAS CM) [15–17]. 2. MODEL AND NUMERICAL EXPERIMENTS In this work we used a IAP RAS CM version [18, 19] modified to include changes in the earth’s surface albedo due to land use. In the warm (snowfree) period of the year, in the part of the model grid cell occupied by agricultural land, the surface albedo was specified under the category “Agricultural Land” in the Biosphere–Atmosphere Transfer Scheme (BATS) model [20]. The average surface albedo in a model grid cell was calculated as a weightedaverage albedo between agricultural land α s, agro and the albedo of nat ural ecosystems α s, nat weighted by the fraction of the cell f agro, occupied by agricultural land α s = f agroα s , agro + (1 − f agro ) α s , nat.
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The annual behavior of foliage cover (also influ encing the albedo of ecosystem) of the natural and agricultural plants for both vegetation types was calcu lated the ВАТS model. Additionally, the model included a parameterization of “masking” the snow by vegetation for mid to highlatitude woody vegetation, the albedo (α s, nat ) of which, even in the presence of snow, was assigned to the albedo of vegetation rather than to that of snow. For other vegetation types, the surface albedo in the presence of snow was assigned to the albedo of snow. If the current vegetation type for a given model cell was classified by BATS as agricultural land, the type of natural vegetation in this cell was assigned according to a simplified Holdridge classification [21] using the data of [22]. In winter at middle to high latitudes, the effect of the elimination of snow “masking” by natural woody vegetation is most significant when it is converted to agricultural species: under these conditions, the win tertime surface albedo changes from α s, nat = 0.13– 0.22 to an albedo of snow of 0.6. On account of the fact
that that summertime IAP RAS CM albedo α s, agro = 0. 22 normally exceeds the albedo of natural vegetation α s, nat, an increase in the agricultural area may give rise to cooling RF. However, in regions where the semiarid albedo is assigned to a natural vegetation cover, a change in the annual behavior of the leaf area index (LAI) in the case of an increase in the agricul tural area may lead to a net decrease in the surface albedo. It is noteworthy that the available data on the types of natural and agricultural ecosystems suggest that both livestock pastures and irrigated agricultural lands are currently widespread in central Eurasia in regions of semiarid vegetation and livestock pastures are ubiquitous in Australia. This paper made no account for the direct landuse effect on the state of the atmosphere by altering the intensity of plant evapotranspiration or through changing the turbulent heat fluxes between the land surface and atmosphere due to a change in the rough ness height. Further IAP RAS CM versions, with the more detailed soil hydrology scheme [23], are envis aged to include this landuse effect on climate. The IAP RAS CM was used to perform transitive ensemble numerical experiments for 1500–2100 with agricultural land areas (both cropland and grassland areas) set according to Land Use Harmonization (LUH, http://luh.uhh.edu/data.shtml) annual aver age data [24]. From the 16th century to the 20th cen tury, this dataset is based on the HYDE 3.1 data [9]. Future changes in ecosystem areas are estimated based on the AIM, IMAGE, MESSAGE, and MiniCAM model calculations performed within this same project. It should be noted that, despite the fact that all four models use the same input data within the LUH project, they give different results. For instance, whereas the IMAGE and MESSAGE models predict an increase in the agricultural area in the 21st century, the MiniCAM model predicts its decrease. The AIM model also predicts a general increase in the agricul tural area, except for the tropical regions, showing its decrease. Analyzing the intermodel differences in the projected future changes is beyond the scope of this paper; therefore, henceforth the variance in the calcu lated results is considered an uncertainty interval of future changes in the agricultural land area. For the first, third, and fourth models, we used the version 1 LUH data; for the IMAGE model, we used the version 1.1_rc1 LUH data (see http://luh.unh.edu/ data.shtml for more detail). For the 16th century through to the 20th century, we also prescribed the annual carbon dioxide emissions due to fossil fuel combustion [25] and due to land use [26] extended back in time as proposed in [27] and annually averaged concentrations of methane [28], nitrous oxide [28], freons CFC11 and CFC12 [29] (all these gases were assumed to be mixed well in the atmosphere), tropo spheric sulfates [30], and variations in the solar con stant [31], as well as the zonal average optical depth of
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stratospheric aerosols (annual average values [32] until 1889 and monthly average values [33] for 1890–2000). For the 21st century, these anthropogenic impacts (except for landuse scenarios) were specified accord ing to the SRES В1, А1В, and А2 scenarios [34]; moreover, the CH4, N2O, CFC11, and CFC12 con centrations were specified from ВеrnCC model calcu lations [34], and the tropospheric sulfate fields were specified from MOZART2.0 model calculations [30]. Possible variations in the solar constant and stratospheric aerosol depth were not considered. Henceforth, these numerical experiments are desig nated as SRESxxx–LUyyy, where xxx stands for SRES scenario and yyy indicates the model used in the prep aration of landuse scenarios for the 21st century. The agricultural land areas obtained with each of these models were used to perform three IAP RAS CM inte grations differing in initial conditions. The method used for selecting these initial conditions was the same as described in [35]. Besides the SRESxxx–LUyyy numerical experi ments, we also performed the corresponding SRESxxx calculations disregarding landuse driven changes in the surface albedo of land and the LUyyy calculations in which, on the contrary, only this forcing was consid ered. It should be noted that the SRESxxx numerical experiments differ from those performed earlier in [18, 19, 36] in that they additionally take into account RF due to freons. It should also be kept in mind that landuse driven CO2 emissions to the atmosphere in the SRES scenar ios generally mismatch changes in the agricultural land area in LUH scenarios. The IAP RAS CM ver sion used here cannot strictly distinguish between how LUH scenarios influence these emissions, because it employs only a global average module of the ground based carbon cycle. However, this does not apprecia bly bias the estimates of climate change in the 21st century, because CO2 emissions due to fossil fuel combustion and industrial activity dominate in the general anthropogenic carbon dioxide emissions in SRES scenarios [34]. At present, we have almost com pleted a IAP RAS CM modification to incorporate a spa tially distributed module of groundbased carbon cycle which will more adequately take into account the influ ence that landuse scenarios have on CO2 emission into the atmosphere. Calculations with this model version are planned to be published in a separate paper. The LU numerical experiments were analyzed in detail in [37]; therefore they are addressed here only partly. 3. RESULTS 3.1. RF from a LandUse Driven Change in Land Surface Albedo The instantaneous TOA RF due to changes in the surface albedo in the case of an increase in the agricul IZVESTIYA, ATMOSPHERIC AND OCEANIC PHYSICS
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tural area FTOA, alb within IAP RAS CM was considered in detail in [37]. Globally and annually averaged, it does not exceed 0.02 W m2 in absolute value until the beginning of the 18th century. Then, FTOA, alb increases in absolute value, reaching (–0.05) W m–2 by the beginning of the 20th century and (–0.11) W m–2 toward its end. This last value is well within the uncer tainty interval [11], but below its central estimate. It also agrees well with the estimate of (–0.1) W m–2 [12] obtained with use of stateofart data on the state of vegetation cover and a detailed atmospheric radiative transfer model. In the 21st century, the globally and annually aver age FTOA, alb value in AIM, IMAGE, and MESSAGE scenarios monotonically decreases in absolute value, reaching (–0.13) W m–2, although the first of these models predicts a small RF decrease in absolute value in the last decades of the 21st century. At the same time, in the scenario using the MiniCAM model, the absolute FTOA, alb value in the 21st century monotonically decreases in absolute value, equaling (–0.08) W m–2 at the end of the century. The cooling TOA RF FTOA, alb for the late 20th cen tury is the largest in the summer hemisphere (through out the year in the tropics) in the largest agricultural land areas. Its absolute value exceeds 6 W m–2 in southern Siberia, Southeastern Asia, north Hin dustan, some regions of North America, Europe, Amazonia, Central Africa, Indochina, and Indonesia. A marked cooling RF (up to a few W m–2) is develop ing in Amazonia and Central Africa. However, we simulate a relatively small positive FTOA, alb in the sum mer in regions with a natural semiarid vegetation cur rently occupied by agricultural species (a number of southern regions in Russia, north Kazakhstan, Sahel, Australia, and South Africa). In the 21st century, in scenarios of changing agricul tural land areas obtained with IMAGE and MESSAGE models, a further increase in the agricultural land area in South Siberia, Amazonia, Central Africa, and regions of North America leads to a continued growth of the modulus of FTOA, alb by a few tenths of W m–2. It is noteworthy that the cooling RF decreases in the north of Hindustan and in a number of European regions. The AIMbased scenario of the change in RF primarily differs from IMAGE and MESSAGE based scenarios in the 21st century in that it predicts a decrease (and not an increase) in the absolute value of FTOA, alb in Amazonia and, to a lesser degree, in South Siberia and in the west of the North America midlati tudes. In the MiniCAMbased scenario, the RF decreases in all basic regions of agricultural lands. Vol. 47
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ΔTg, K 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0 –0.5 1700
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Fig. 1. Globally and decadally averaged changes of the nearsurface atmospheric temperature in the SRES (dashed lines), SRESLU (solid lines with circles, crosses, and upwardpointing triangles), and LU (lines with down wardpointing triangles) numerical experiments with IAP RAS CM. For SRES and SRESLU experiments, the cir cles, crosses, and upwardpointing triangles indicate SRES B1, A1B, and A2 (without accounting for land use) anthropogenic impact scenarios, respectively. For the SRESLU and LU experiments, the curves are plotted by averaging the results of the numerical experiments for the LUH АIM, IMAGE, MESSAGE, and MiniCAM scenar ios. The grey solid line shows the HadCRUT2v empirical data [50].
3.2. Global Average Climatic Response The response of global and annual average temper ature Ta, s, g to external impact does not exceed 0.15 K until the beginning of the 20th century (Fig. 1). In the 20th century, the linear trend of Ta, s, g in the SRES numerical experiments is 0.67 ± 0.11 K/century (from here on, we indicate a sample average for the coeffi cient of the trend and the corresponding standard deviation), which is close to the upper empirical esti mate of 0.6 ± 0.2 K/century [11]. In the LU numerical estimates, in turn, the corresponding linear trend is –0.07 ± 0.02 K/century. In the combined SRESLU scenario, the linear trend of Ta, s, g is 0.56 ± 0.08 K/cen tury, which is consistent with the empirical estimate [11]. In the LU numerical experiments, the Ta, s, g value varies by –0.11 K toward the end of the 20th century relative to calculations assuming only the presence of natural vegetation. This value is close to that obtained in [38] using the MOBIDIC model and to that obtained in [39] using a version of the UVic ESCM model disregarding the succession of ecosystems (it should be remembered that the current version of IAP RAS CM disregards this succession too). On the other hand, the IAP RAS CM response is a little smaller (in
absolute value) than the lowermost value of the corre sponding interval from (–0.13) to (–0.25) K obtained in [5] for an ensemble of climate models; this latter is because, in particular, the IAP RAS CM version used here has lower climatic sensitivity than the climate models used in [5]. For instance, the IAP RAS CM equilibrium response that the global and annual aver age nearsurface atmospheric temperatures have to the atmospheric CO2 doubling is 2.2 K, which is in the lower part of the range from 2 to 4.5 K, which is char acteristic for the current climate models [11]. The rea son for the discrepancy may also be due to the use of intermodel differences in specifying different ecosys tem types and to the use of different reconstruction data for past changes in the agricultural land area. In particular, the authors of [39] used different data on the agricultural land area, albedo of different vegeta tion types, and included or disregarded the interactive response of the natural ecosystems to climate change; as a result, their Ta, s, g value changed in the interval from –(0.06) to (–0.22) K toward the end of the 20th century. Also, the models appreciably disagreed about the temperature response to landuse driven albedo change during an analysis of calculations performed as part of the LUCID project [7]. The global annual precipitation totals in the LU exper iments decrease in the range from 0.7 to 0.8 cm yr–1 (about 0.7%) toward the end of the 20th century com pared with model calculations assuming only natural vegetation (Fig. 2). In the 20th century, the linear pre cipitation trend in the SRESLU (SRES, LU) numer ical experiments is 3.2 ± 0.5 cm yr–1 (4.1 ± 0.6 cm yr–1, –0.4 ±0.2 cm yr–1). In the 21st century, calculations with the anthropo genic impact scenario SRES В1 (А1В, А2) predict that Ta, s, g increases in the range of from 1.40 to 1.45 K (from 2.01 to 2.05 K and from 2.48 to 2.53 K), depending on the land use scenario. These values are in the lower parts of the global warming ranges (from 1.1 to 2.9 K, from 1.7 to 1.4 K, and from 2.0 to 5.4 K, respectively) characteristic for an ensemble of other modern cli mate models, assuming these same anthropogenic impact scenarios [11]. Also, the global atmospheric nearsurface temperature in the scenarios used here increases by amounts differing insignificantly from those presented in [19, 36], indicating that the direct freon RF weakly affects the climate changes in 21st century. Depending on the landuse scenario, the global precipitation totals in the 21st century increase by 7–8 cm yr–1 (11–12 cm yr–1 and 14–15 cm yr–1) in the anthropogenic impact scenario SRES В1 (А1В, А2). Both temperature and precipitation show the largest (smallest) increase if calculated with the Mini CAMbased landuse scenario assuming the reduc tion of the agricultural area in the 21st century by 18% (if calculated with MESSAGE and IMAGEbased scenarios assuming 11 and 13% increases in the total agricultural area, respectively).
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3.3. Spatial Distribution of the Effect that Land Use has on the Climatic Response in the Period up to the Late 20th Century The inclusion of the landuse driven change in land surface albedo leads to a net decrease in annual aver age and seasonal nearsurface atmospheric warming. For instance, in the SRES numerical experiments, the nearsurface atmospheric temperature Ta, s in the 20th century typically increases by 0.2–0.5 K in the tropics and by 0.5–1.2 K at higher latitudes (Fig. 3a). In the SRESLU experiments, the warming decreases and turns to cooling (up to ≈ 1 К ) at midlatitudes in Eurasia and in the subtropics of North America, as well as in Amazonia and Central Africa (Fig. 3b). It is precisely these regions that show the largest increase in agricultural areas in the 20th century. Interestingly, the warming intensifies at subtropical latitudes in Eurasia, especially in eastern China, where it reaches 2 K, as opposed to the SRES value of about 1 K. The warming in this region intensifies both in the warm and cold seasons, probably due to RF, which develops in this region because semiarid natural vegetation has been converted into agricultural lands [37]. A similar, but less significant, enhancement of the warming is also recorded in subtropics of South America. It should be noted that the liner trend of decreasing Ta, s in the 20th century in the subtropics of the North America, in Central Africa, and in Amazonia, as well as one of the warming maxima in the subtropics of Eurasia, are also easily identified from observation data [11] (see Fig. 3.9a in that work). However, the negative trend of the nearsurface atmospheric temperature at the middle latitudes of Eurasia, which is well discernible in IAP RAS CM, is not apparent from observation data [11]. Its model manifestation seemingly stems from the crudity of the model’s dynamic scheme and lack of heat transfer to Eastern Europe by atmospheric circulation. The seasonal features of warming in the numerical experiments used in this work were analyzed with the help of the amplitude Ta, s , 1 of the annual harmonic Ta, s [40, 41]. The net Ta, s , 1 decrease over land at mid dle and subpolar latitudes, which was revealed earlier from observation and reanalysis data [1, 11, 41–47], is reproduced well both in the SRES and SRESLU numerical experiments (Figs. 4a, 4b). However, one important difference between the SRES and SRES LU experiments is the appearance of a region of a pos itive correlation between Ta, s , 1 and annually average Ta, s value in the subtropics of Eurasia and North America (Fig. 4b). This conforms the predominating role of the response in the warm period of the year for the abovementioned region where the annual average warming in the subtropics of Eurasia is enhanced. It is noteworthy that observations at the subtropical lati tudes of the continents of the Northern Hemisphere suggest that the negative time correlation becomes sta tistically insignificant and that a statistically signifi IZVESTIYA, ATMOSPHERIC AND OCEANIC PHYSICS
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cant positive correlation between Ta, s , 1 and the local annually average temperature is apparent in a number of regions of this latitudinal belt [47]. The predomi nant role of summertime warming in the annually average behavior in this region was also indicated by empirical data (see Fig. 3.10 in [11]). The SRES numerical experiments are character ized by a growth in the annual precipitation amount in all regions around the globe (Fig. 5a). This is also characteristic of calculations using different IAP RAS CM versions, which do not account for the landuse caused change in the land albedo [17, 36, 48, 49]. However, the SRESLU experiments show a decrease in precipitation in the subtropics of Eurasia and North America, Amazonia, and Central Africa (Fig. 5b). A net decrease in precipitation in these regions was also identified from observation data (Figs. 3.13, 3.14 in [11]). A decrease in the precipitation in the subtropics of Eurasia was especially evident in the summer period (Fig. 6). In the subtropics of North America, in Ama zonia, and in the Central Africa, the decrease in pre cipitation is apparent throughout the year. On the con trary, the calculations for the abovementioned region, taking into account landuse driven RF, show an increase in precipitation in the summer season (Fig. 6b). This precipitation response may be due to a change in the atmospheric convection due to the surface albedo. For instance, the net growth of albedo due to the conversion of natural vegetation into agricultural land leads to the cooling of the lower troposphere. This leads to a decrease in the atmospheric static energy (due to both a decrease in the temperature lapse rate during cooling and to the net decrease in the atmo spheric moisture content). This decrease, in turn, Vol. 47
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should depress the atmospheric convective activity in the corresponding regions and, hence, reduce the convective precipitation amount, whose role is signif icant over continents throughout the year and over land at extratropical latitudes in the warm season. A comparison of results of this work with those of the LUCID project (which obtained a wide range of model responses to an increase in the agricultural land area differing both in absolute value and in the sign between various models) shows that the summertime temperature and precipitation response in IAP RAS CM in LU numerical experiments to the anthropogenic change in the land surface albedo in the 20th century is closest to the ССАМCABLE and SPEEDYLPJmL model responses (see [7]). 3.4. Spatial Distribution of LandUse Effect on the Climatic Response in the 21st Century In the 21st century, changes in the land surface albedo due to land use relatively weakly influenced changes in the temperature and precipitation. As an example, with the anthropogenic impact scenarios used here, the largest changes Ta, s, g were recorded over land at middle to high latitudes. The warming is max imum in the internal Eurasian regions, where it reaches 4 K (6 K, 7 K) in the SRES B1 (SRES A1B, SRES A2) numerical experiments (Fig. 7). On the whole, the spatial distribution is close to that obtained in [36], which used a IAP RAS CM version close to ours but without accounting for the effect of direct freon RF. Including the direct landuse driven RF changes these values generally by no more than a few tenths of Kelvin (Fig. 8). One exception is the IAP RAS CM numerical experiment, which specified the agricul tural land area according to MiniCAM model calcula tions. For this numerical experiment, the enhance ment of warming at midlatitudes in Eurasia reaches 1.5 K. On the annual average basis for all landuse sce narios, the warming increases in a number of midlati tude regions of Eurasia and North America (especially for the scenario obtained with the MiniCAM model). For the landuse scenarios based on the IMAGE and MESSAGE models, a further increase in the agricul tural land area in tropics and subtropics leads to a decrease in warming in northern Hindustan and Indochina, the subtropics of North and South Amer ica, and the equatorial regions of Africa and South America (Figs. 8a, 8b). A similar change in the Ta, s response was also observed in the SRESxxxLUAIM numerical experiments (xxx stands for either B1, А1В, or А2), but no region of decrease in the warming is identified (Fig. 8c). For the landuse scenario obtained with the MiniCAM model, a decrease in the agricultural land area in all current agricultural regions leads to an enhancement of the local warming (Fig. 8d).
The spatial structure of the change in the precipita tion response to anthropogenic landuse driven RF in IAP RAS CM, on the whole, is similar to that for the temperature. It is noteworthy that this change in the precipitation response in IAP RAS CM does not exceed a few millimeters per year. 4. CONCLUSIONS This paper presents numerical experiments with a moderately complex IAP climate model for the period from the 16th century to the 21st century with a spec ified anthropogenic impact due to the change in the content of greenhouse gases (tropospheric and strato spheric), sulfate aerosols, and solar constant, as well as to RF as a result of the conversion of natural vegetation to agricultural lands. The agriculturalland area was specified according HYDE 3.1 data for the period from the 16th century to the 20th century and accord ing to scenarios of the Land Use Harmonization project for the 21st century. Other natural and anthro pogenic impacts were specified according to recon struction data until the late 20th century; in 2000– 2100, the anthropogenic impacts (including the emis sions of greenhouse gases due to land use) were speci fied according to SRES scenarios and possible exter nal natural impacts on the climate system were not considered. A change in the surface albedo of the earth due to the conversion of natural vegetation into agricultural land leads to the development of cooling RF in most regions. However, during the summer, in regions with natural semiarid vegetation currently occupied by agricultural species (a number of southern regions of Russia, North Kazakhstan, Sahel, Australia, and South Africa), a relatively small warming RF develops. The global and annual average RF, as well as its spatial and seasonal distributions, on the whole, agree well with corresponding estimates obtained elsewhere. In particular, in the late 20th century, the global average RF in IAP RAS CM is –0.11 W m–2. The inclusion of direct landuse driven RF in IAP RAS CM has substantially reconciled the model cal culations and observation data in the historic period. In the 20th century, the contribution that this RF makes to the linear trend of the global nearsurface atmospheric temperature Ta, s, g is an order of magni tude less than the contribution that other external impacts make on climate. However, in the IAP RAS CM numerical experiments with the inclusion of this RF, the Ta, s, g trend approaches the center of the uncertainty interval of the corresponding observation data, whereas in numerical experiments, which disre garded changes in the surface albedo due to the con version of natural vegetation into agricultural species, the trend in the IAP RAS CM global temperature is close to the upper edge of this uncertainty interval. Also, the regional features of the climate change are
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Fig. 7. Change in the annual average nearsurface atmospheric temperature [K] between 1990–2000 and 2090–2100 in the IAP RAS CM numerical experiments with (a) SRES B1 and (b) SRES А2 scenarios taking into account the landuse driven RF. Aver ages are taken in scenarios SRESxxxIMAGE, SRESSxxxMESSAGE, SRESxxxAIM, and SRESxxxMiniCAM (xxx stands for either B1 or A2).
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Fig. 8. Effect that a landuse caused change in land surface albedo has on the response of the nearsurface atmospheric temper ature [K] between 1990–2000 and 2090–2100 calculated with (a) MESSAGE, (b) IMAGE, (c) AIM, and (d) MiniCAM scenar ios of change in the agricultural land area. In both cases, averages are taken in the SRES B1LUyyy, SRES A1BLUyyy and SRES A2LUyyy; yyy stands for either MESSAGE, IMAGE, AIM, or MiniCAM.
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reproduced better. For instance, in the 20th century, with the inclusion of landuse driven RF, the regions of annual average cooling (in the subtropics of North America, Amazonia, and Central Africa) and a local maximum of the annual average and summertime warming in East China are reproduced well; the corre sponding change in the response of the nearsurface air temperature Ta, s is 0.2–0.5 K in the tropics and 0.5–1.2 K at higher latitudes. Importantly, landuse driven RF also changes its sign of interrelation between the characteristics of the annual behavior of Ta, s and the local annual average temperature. Including the change in the land surface albedo due to the conversion of natural vegetation into agricul tural species in IAP RAS CM led to the fact that, in some regions (the subtropics of Eurasia and North America, Amazonia, and Central Africa) in the 20th century, the annual precipitation amount decreased, which is consistent with observation data. For the sub tropics of Eurasia, this decrease in the annual amount of precipitation is caused by a summertime decrease in the precipitation amount, which is again consistent with observation data. This precipitation response to land use may be due to a decay in the atmospheric convective activity in the warm season (throughout the year in the tropics) and to the corresponding decrease in the convective precipitation. In the 21st century, the landuse driven forcing of the climatic response in the employed scenarios of the anthropogenic effect is relatively small. For instance, toward the end of the this century, the difference in the Ta, s, g variations between different landuse scenarios is 0.05 K when the SRES scenario of the anthropogenic impact is used, i.e.,
