Changes In Land Surface Albedo Research Articles

Reponses of Land Surface Albedo to Global Vegetation Greening: An Analysis Using GLASS Data

Global vegetation greening during recent decades has been observed from various remote sensing data. The global and regional climate can be altered by an increase in carbon storage, as well as changes in land surface albedo (LSA) and evaporation. However, the LSA changes induced by global vegetation greening are still not clear, and contrasting responses of LSA to vegetation changes were reported in previous studies. In this study, we analyzed the LSA in response to global vegetation greening using the Global Land Surface Satellite (GLASS) data and a vegetation-induced LSA change model. The results showed that vegetation greening trends could be observed worldwide, which resulted in contrasting LSA responses at regional scales (LSA increased as leaf area index (LAI) increased, or LSA decreased as LAI increased). Moreover, these contrasting LSA responses to global vegetation greening were effectively explained by the albedo difference between a vegetation and soil background. The results provide new insights into the relationship between LSA changes and global vegetation dynamics, and can support recommendations for policies of vegetation protection, and large-scale afforestation and deforestation.

Converted vegetation type regulates the vegetation greening effects on land surface albedo in arid regions of China

Land surface albedo (LSA) is a key parameter in the process of vegetation feedback to climate due to its decisive role in land surface radiation budget. However, our current knowledge on the relationship between LSA and vegetation changes is limited by one-sided attention to sole vegetation growth change or land use/land cover change (LULCC). How vegetation growth or LULCC respectively contributes to LSA change under their interactions remains poorly quantified. In this study, the arid and semi-arid areas of China (ASAC) with profound vegetation changes were selected to tackle this problem. The LSA showed a general downward trend (-0.00009 year−1) during 2000-2018 in response to ASAC's wide-range greening (0.0086 m2m−2year−1). Pairwise comparison analysis revealed that under the same unit of vegetation coverage change, the LSA change magnitude was contracted when grassland was converted to cultivated land or forest land, while the conversions of forest land to other vegetations led to an amplified change magnitude of LSA. Vegetation type directly leads to a difference in LSA change magnitude under greening due to their distinct canopy spectral characteristics. Grassland possesses lower LAI and its pixel-level LSA is more prone to be contaminated by background coverage, while LSA of forest land contains more vegetation canopy signal. In most areas where vegetation type converted, greening dominated LSA change with a contribution rate up to 98.14 %, except for the conversion of grassland to forest land, where LULCC accounted for about 66.38 % of LSA change. This study could improve the estimation of LSA from LAI, which is useful for optimizing vegetation-climate interaction models.

Identifying the paths and contributions of climate impacts on the variation in land surface albedo over the Arctic

Understanding historical changes in land surface albedo (ALB) is critical for projecting future climate changes over the Arctic. Previous studies have reported the important role of snow cover and vegetation growth in regulating Arctic land ALB, but their main influencing paths and separate contributions remain underexamined. In this study, the partial least squares path model (PLS-PM) and random forest model (RFM) are adopted to explore the dominant paths of three climate variables—temperature (Tem), precipitation (Pre) and wet days (WD)—in influencing the interannual variations in ALB (IVA) by regulating vegetation and snow cover. The results show that ALB in October and December exhibit significant (p < 0.05) upward and downward trends, respectively. ALB in the Northwest Territories, Victoria Island and Nunavut of the Arctic significantly (p < 0.05) increase in summer and October. The summer snow cover fraction (SCF) shows a significant positive correlation with ALB (R: 0.60‒0.78), while significant negative (R = -0.60) and positive (R = 0.50) relations are found between the enhanced vegetation index (EVI) and ALB during July and September, respectively. According to PLS−PM, the dominant paths that affect the IVA exhibit a prominent seasonal feature. Pre → EVI → ALB and Tem → SCF → ALB are identified as the main paths for ALB changes during spring, while in summer, the only significant path is Tem → SCF → ALB. In autumn, nonsignificant impacts on the variations in EVI and SCF (p > 0.05) are observed, while a significant path WD → SCF → ALB is found in winter. Based on RFM, the relative contribution (RC) of vegetation change to March IVA can reach 52.1 ± 9.2%, while snow variations play a dominant role in April and May, with contributions of 57.8 ± 8.4% and 68.4 ± 4.1%, respectively. Seasonally, summer IVA is mainly impacted by snow (RC from 50.5 ± 4.5% to 65.9 ± 4.5%), while vegetation exerts the dominant influence on IVA in autumn except for September. In winter, however, the dominant strength of vegetation is weakened except in December, with IVA mainly controlled by snow (RC above 50%).

Reconstruction of Historical Land Surface Albedo Changes in China From 850 to 2015 Using Land Use Harmonization Data and Albedo Look‐Up Maps

AbstractLand surface albedo is a critical parameter of the Earth's energy budget and has been greatly altered by climate change and human activities. To improve our understanding of historical land surface albedo changes and their climatic effects before the satellite remote sensing era, we reconstructed land surface albedo in China from 850 to 2015 using the historical land use harmonization version 2 (LUH2) data set and albedo look‐up maps, and estimated the radiative forcing induced by land surface albedo changes using atmospheric radiative kernels. The reconstruction results showed that the annual‐mean land surface albedo in China increased by 0.00110 during 850–2015, and the rate of increase was accelerated by the expansion of croplands during recent centuries. The most significant increases in land surface albedo were found in the Huang‐Huai‐Hai (HHH; +0.00646) and Northeast China (NE; +0.00501), which were primarily driven by anthropogenic land cover transformations (e.g., land reclamation, deforestation, and urbanization) and can be enhanced by the vegetation masking effect on snow cover. The radiative forcing induced by land surface albedo changes in China during 850–2015 and 1750–2015 was −0.09 ± 0.04 and −0.06 ± 0.02 W m−2, respectively, which indicated that the land surface albedo changes produced a slight climate cooling effect, helping to offset the warming effect caused by greenhouse gas emissions.

Development of Land Surface Albedo Algorithm for the GK-2A/AMI Instrument

The Korea Meteorological Administration successfully launched Korea’s next-generation meteorological satellite, Geo-KOMPSAT-2A (GK-2A), on 5 December 2018. It belongs to the new generation of GEO (Geostationary Elevation Orbit) satellite which offers capabilities to disseminate high spatial- (0.5–2 km) and high temporal-resolution (10 min) observations over a broad area, herein a geographic disk encompassing the Asia–Oceania region. The targeted objective is to enhance our understanding of climate change, owing to a bulk of coherent observations. For such, we developed an algorithm to map the land surface albedo (LSA), which is a major Essential Climate Variable (ECV). The retrieval algorithm devoted to GK-2A/Advanced Meteorological Imager (AMI) data considered Japan’s Himawari-8/Advanced Himawari Imager (AHI) data for prototyping, as this latter owns similar specifications to AMI. Our proposed algorithm is decomposed in three major steps: atmospheric correction, bidirectional reflectance distribution function (BRDF) modeling and angular integration, and narrow-to-broadband conversion. To perform BRDF modeling, the optimization method using normalized reflectance was applied, which improved the quality of BRDF modeling results, particularly when the number of observations was less than 15. A quality assessment was performed to compare our results to those of Moderate Resolution Imaging Spectroradiometer (MODIS) LSA products and ground measurement from Aerosol Robotic Network (AERONET) sites, Australian and New Zealand flux tower network (OzFlux) site and the Korea Flux Network (KoFlux) site from throughout 2017. Our results show dependable spatial and temporal consistency with MODIS broadband LSA data, and rapid changes in LSA due to snowfall and snow melting were well expressed in the temporal profile of our results. Our outcomes also show good agreement with the ground measurements from AERONET, OzFlux and KoFlux ground-based network with root mean square errors (RMSE) of 0.0223 and 0.0306, respectively, which is close to the accuracy of MODIS broadband LSA. Moreover, our results reveal still more reliable LSA products even when clouds are frequently present, such as during the summer monsoon season. It shows that our results are useful for continuous LSA monitoring.

Impact of Surface Albedo Assimilation on Snow Estimation

Surface albedo has a significant impact in determining the amount of available net radiation at the surface and the evolution of surface water and energy budget components. The snow accumulation and timing of melt, in particular, are directly impacted by the changes in land surface albedo. This study presents an evaluation of the impact of assimilating Moderate Resolution Imaging Spectroradiometer (MODIS)-based surface albedo estimates in the Noah multi-parameterization (Noah-MP) land surface model, over the continental US during the time period from 2000 to 2017. The evaluation of simulated snow depth and snow cover fields show that significant improvements from data assimilation (DA) are obtained over the High Plains and parts of the Rocky Mountains. Earlier snowmelt and reduced agreements with reference snow depth measurements, primarily over the Northeast US, are also observed due to albedo DA. Most improvements from assimilation are observed over locations with moderate vegetation and lower elevation. The aggregate impact on evapotranspiration and runoff from assimilation is found to be marginal. This study also evaluates the relative and joint utility of assimilating fractional snow cover and surface albedo measurements. Relative to surface albedo assimilation, fractional snow cover assimilation is found to provide smaller improvements in the simulated snow depth fields. The configuration that jointly assimilates surface albedo and fractional snow cover measurements is found to provide the most beneficial improvements compared to the univariate DA configurations for surface albedo or fractional snow cover. Overall, the study also points to the need for improving the albedo formulations in land surface models and the incorporation of observational uncertainties within albedo DA configurations.

Arctic shrub colonization lagged peak postglacial warmth: Molecular evidence in lake sediment from Arctic Canada.

Arctic shrubification is an observable consequence of climate change, already resulting in ecological shifts and global-scale climate feedbacks including changes in land surface albedo and enhanced evapotranspiration. However, the rate at which shrubs can colonize previously glaciated terrain in a warming world is largely unknown. Reconstructions of past vegetation dynamics in conjunction with climate records can provide critical insights into shrubification rates and controls on plant migration, but paleoenvironmental reconstructions based on pollen may be biased by the influx of exotic pollen to tundra settings. Here, we reconstruct past plant communities using sedimentary ancient DNA (sedaDNA), which has a more local source area than pollen. We additionally reconstruct past temperature variability using bacterial cell membrane lipids (branched glycerol dialkyl glycerol tetraethers) and an aquatic productivity indicator (biogenic silica) to evaluate the relative timing of postglacial ecological and climate changes at a lake on southern Baffin Island, Arctic Canada. The sedaDNA record tightly constrains the colonization of dwarf birch (Betula, a thermophilous shrub) to 5.9±0.1ka, ~3ka after local deglaciation as determined by cosmogenic 10 Be moraine dating and >2ka later than Betula pollen is recorded in nearby lake sediment. We then assess the paleovegetation history within the context of summer temperature and find that paleotemperatures were highest prior to 6.3ka, followed by cooling in the centuries preceding Betula establishment. Together, these molecular proxies reveal that Betula colonization lagged peak summer temperatures, suggesting that inefficient dispersal, rather than climate, may have limited Arctic shrub migration in this region. In addition, these data suggest that pollen-based climate reconstructions from high latitudes, which rely heavily on the presence and abundance of pollen from thermophilous taxa like Betula, can be compromised by both exotic pollen fluxes and vegetation migration lags.

Estimation of the Land Surface Albedo Changes in the Broader Mediterranean Area, Based on 12 Years of Satellite Observations

The Land Surface Albedo (LSA) was estimated in the broader Mediterranean area, on an 8-day basis, for the period 2001–2012. MODIS (Moderate Resolution Imaging Spectroradiometer) albedo product parameters, at 1 km × 1 km spatial resolution, were used. LSA changes during the above study period were also estimated, based on annual average values. Results revealed increasing LSA trends dominating in the Levant region and decreasing in NW Africa, of the order of 3.3% and −6.6%, respectively, while mixed signs were observed in southern Europe. Three factors that can determine the LSA changes were investigated: land cover changes, rainfall changes and Aerosol Optical Thickness (AOT) spatio-temporal variability. The analysis made clear that land cover and rainfall changes affect LSA at local and regional scales, while the effect of AOT was not important. Land cover changes revealed deforestation hot spots, where LSA was increased by 13%–14%, while an increase in rainfall over many areas in NW Africa appears to have caused a corresponding decrease in LSA by over 5%. These findings highlight the importance of a global and continuous LSA monitoring at both regional and local scales, which is necessary for both climate monitoring and modeling studies.

Satellite observations of changes in snow-covered land surface albedo during spring in the Northern Hemisphere

Abstract. Thirteen years of Moderate Resolution Imaging Spectroradiometer (MODIS) surface albedo data for the Northern Hemisphere during the spring months (March–May) were analyzed to determine temporal and spatial changes over snow-covered land surfaces. Tendencies in land surface albedo change north of 50° N were analyzed using data on snow cover fraction, air temperature, vegetation index and precipitation. To this end, the study domain was divided into six smaller areas, based on their geographical position and climate similarity. Strong differences were observed between these areas. As expected, snow cover fraction (SCF) has a strong influence on the albedo in the study area and can explain 56 % of variation of albedo in March, 76 % in April and 92 % in May. Therefore the effects of other parameters were investigated only for areas with 100 % SCF. The second largest driver for snow-covered land surface albedo changes is the air temperature when it exceeds a value between −15 and −10 °C, depending on the region. At monthly mean air temperatures below this value no albedo changes are observed. The Enhanced Vegetation Index (EVI) and precipitation amount and frequency were independently examined as possible candidates to explain observed changes in albedo for areas with 100 % SCF. Amount and frequency of precipitation were identified to influence the albedo over some areas in Eurasia and North America, but no clear effects were observed in other areas. EVI is positively correlated with albedo in Chukotka Peninsula and negatively in eastern Siberia. For other regions the spatial variability of the correlation fields is too high to reach any conclusions.

Climate engineering of vegetated land for hot extremes mitigation: An Earth system model sensitivity study

AbstractVarious climate engineering schemes have been proposed as a way to curb anthropogenic climate change. Land climate engineering schemes aiming to reduce the amount of solar radiation absorbed at the surface by changes in land surface albedo have been considered in a limited number of investigations. However, global studies on this topic have generally focused on the impacts on mean climate rather than extremes. Here we present the results of a series of transient global climate engineering sensitivity experiments performed with the Community Earth System Model over the time period 1950–2100 under historical and Representative Concentration Pathway 8.5 scenarios. Four sets of experiments are performed in which the surface albedo over snow‐free vegetated grid points is increased respectively by 0.05, 0.10, 0.15, and 0.20. The simulations show a preferential cooling of hot extremes relative to mean temperatures throughout the Northern midlatitudes during boreal summer under the late twentieth century conditions. Two main mechanisms drive this response: On the one hand, a stronger efficacy of the albedo‐induced radiative forcing on days with high incoming shortwave radiation and, on the other hand, enhanced soil moisture‐induced evaporative cooling during the warmest days relative to the control simulation due to accumulated soil moisture storage and reduced drying. The latter effect is dominant in summer in midlatitude regions and also implies a reduction of summer drought conditions. It thus constitutes another important benefit of surface albedo modifications in reducing climate change impacts. The simulated response for the end of the 21st century conditions is of the same sign as that for the end of the twentieth century conditions but indicates an increasing absolute impact of land surface albedo increases in reducing mean and extreme temperatures under enhanced greenhouse gas forcing.

Evaluating key parameters for the initiation of a Neoproterozoic Snowball Earth with a single Earth System Model of intermediate complexity

Even after more than two decades of intense research the main drivers for a potential Neoproterozoic Snowball Earth continue to be discussed controversially. In this study we present results from 37 sensitivity experiments that were performed with the Planet Simulator (PlaSim), an Earth System Model of intermediate complexity. In contrast to previous studies, in which only a limited number of potential climate-controlling parameters were assessed with different climate models, we tested our presumed key parameters within one single model. This approach makes it easier to compare the influence of the various parameters on extreme climate change as postulated for the Neoproterozoic Era. Furthermore we compare the results obtained to most recent high complexity state-of-the-art approaches. This comparison helps to estimate, which internal model interactions and physics are crucial for a Snowball Earth simulation and hence should be included into a model that is capable of realistically simulating a Neoproterozoic climate. To this effect we carried out simulations that involved reduced solar irradiation, land–sea distributions, atmospheric CO2 concentrations, relief of the land surface and length of day. In addition, we focus on different land surface albedo values, which were most likely exceptionally low and similar to the Martian albedo, and obliquity changes between 23.5° and 80°. Our findings suggest that changes in land surface albedo are a strong climate driver that can compensate a much lower Neoproterozoic total solar irradiance if it is combined with shifts in obliquity or atmospheric CO2 levels. We also obtained a critical threshold for increased obliquities beyond which a Snowball Earth situation turns into an extreme greenhouse climate with almost absent cryosphere, and furthermore, obliquity values that lead to a tropical ice age with sea ice spreading from the equator to high latitudes.

Response of vegetation to the 2003 European drought was mitigated by height

Abstract. The effects on climate of land-cover change, predominantly from the conversion of forests to crops or grassland, are reasonably well understood for low and high latitudes but are largely unknown for temperate latitudes. The main reason for this gap in our knowledge is that there are compensating effects on the energy and water balance that are related to changes in land-surface albedo, soil evaporation and plant transpiration. We analyse how vegetation height affected the response of vegetation during the 2003 European drought using precipitation data, temperature data, normalized difference vegetation index data and a new vegetation height data set obtained from the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat). At the height of the 2003 drought we find for tall vegetation a significantly smaller decrease in vegetation index and a smaller diurnal temperature (DTR) range, indicating less water stress and drought impacts on tall vegetation. Over Germany for example, 98% of significant correlations showed a smaller anomaly in vegetation index anomaly with greater height, and 95% of significant correlations showed a smaller DTR with greater vegetation height. Over France the equivalent percentages were 94 and 88%, respectively. Vegetation height is likely associated with greater rooting depth, canopy heat capacity or both. Our results suggest that land-surface models can be improved by better estimates of vegetation height and associated with this a more realistic response to drought.

Effect of Anthropogenic Land-Use and Land-Cover Changes on Climate and Land Carbon Storage in CMIP5 Projections for the Twenty-First Century

Abstract The effects of land-use changes on climate are assessed using specified-concentration simulations complementary to the representative concentration pathway 2.6 (RCP2.6) and RCP8.5 scenarios performed for phase 5 of the Coupled Model Intercomparison Project (CMIP5). This analysis focuses on differences in climate and land–atmosphere fluxes between the ensemble averages of simulations with and without land-use changes by the end of the twenty-first century. Even though common land-use scenarios are used, the areas of crops and pastures are specific for each Earth system model (ESM). This is due to different interpretations of land-use classes. The analysis reveals that fossil fuel forcing dominates land-use forcing. In addition, the effects of land-use changes are globally not significant, whereas they are significant for regions with land-use changes exceeding 10%. For these regions, three out of six participating models—the Second Generation Canadian Earth System Model (CanESM2); Hadley Centre Global Environmental Model, version 2 (Earth System) (HadGEM2-ES); and Model for Interdisciplinary Research on Climate, Earth System Model (MIROC-ESM)—reveal statistically significant changes in mean annual surface air temperature. In addition, changes in land surface albedo, available energy, and latent heat fluxes are small but significant for most ESMs in regions affected by land-use changes. These climatic effects are relatively small, as land-use changes in the RCP2.6 and RCP8.5 scenarios are small in magnitude and mainly limited to tropical and subtropical regions. The relative importance of the climatic effects of land-use changes is higher for the RCP2.6 scenario, which considers an expansion of biofuel croplands as a climate mitigation option. The underlying similarity among all models is the loss in global land carbon storage due to land-use changes.

Climate impacts of bioenergy: Inclusion of carbon cycle and albedo dynamics in life cycle impact assessment

Life cycle assessment (LCA) can be an invaluable tool for the structured environmental impact assessment of bioenergy product systems. However, the methodology's static temporal and spatial scope combined with its restriction to emission-based metrics in life cycle impact assessment (LCIA) inhibits its effectiveness at assessing climate change impacts that stem from dynamic land surface–atmosphere interactions inherent to all biomass-based product systems. In this paper, we focus on two dynamic issues related to anthropogenic land use that can significantly influence the climate impacts of bioenergy systems: i) temporary changes to the terrestrial carbon cycle; and ii) temporary changes in land surface albedo—and illustrate how they can be integrated within the LCA framework.In the context of active land use management for bioenergy, we discuss these dynamics and their relevancy and outline the methodological steps that would be required to derive case-specific biogenic CO2 and albedo change characterization factors for inclusion in LCIA. We demonstrate our concepts and metrics with application to a case study of transportation biofuel sourced from managed boreal forest biomass in northern Europe. We derive GWP indices for three land management cases of varying site productivities to illustrate the importance and need to consider case- or region-specific characterization factors for bioenergy product systems. Uncertainties and limitations of the proposed metrics are discussed.

Comparison of climatic efficiency of the mechanisms of land-surface albedo changes caused by land use

Changes in ecosystem types, including situations when natural vegetation is replaced by agricultural lands, leads to surface albedo changes and the development of the corresponding short-wave radiative forcing (RF). This work analyzes ensemble numerical experiments with the climatic model (CM) of the Institute of Atmospheric Physics at the Russian Academy of Sciences (IAP RAS) for the 16th–21st centuries. The responses to changes in the contents of greenhouse gases and sulfate aerosols (tropospheric and stratospheric), in the solar constant, and in the land-surface albedo when natural vegetation is replaced by agricultural lands were modeled during these experiments. Different members of these ensemble experiments were obtained by varying the model parameters affecting the RF on the climate during land use: the albedo of agricultural lands was varied within the interval from 0.15 to 0.25 and the parameter controlling the efficiency of snow masking by tree vegetation was varied in the range from the absence of this effect to its maximally possible efficiency. It has been established that changes in surface albedo when natural vegetation is replaced by agricultural lands have the largest influence on the globally averaged annual mean RF at the top of the atmosphere, whereas the influence of snow masking on the RF is substantially less. This phenomenon is caused by the fact that snow masking by tree vegetation can take place only in winter in regions of temperate and high latitudes, when insolation is relatively low. A comparison of the spatial structure of the annual mean response of the surface temperature with the HadCRUT3v and GISS observational data makes it possible to narrow the admissible range of model parameter values. In particular, it can be inferred that the key parameter values which control the influence that land use has on the surface albedo in the IAP RAS CM are close to optimal. In addition, variations in these parameters do not lead to a significant influence of land use on climate change in the 21st century if the Land Use Harmonization (LUH) scenarios of changes in the area of agricultural lands are used: the uncertainty of the model response associated with the uncertainty of values of such controlling parameters in the 21st century does not exceed 0.1 K.

Including CO2-emission equivalence of changes in land surface albedo in life cycle assessment. Methodology and case study on greenhouse agriculture

Purpose Climate change impacts in life cycle assessment (LCA) are usually assessed as the emissions of greenhouse gases expressed with the global warming potential (GWP). However, changes in surface albedo caused by land use change can also contribute to change the Earth’s energy budget. In this paper we present a methodology for including in LCA the climatic impacts of land surface albedo changes, measured as CO2-eq. emissions or emission offsets.

Combined climate and carbon-cycle effects of large-scale deforestation

The prevention of deforestation and promotion of afforestation have often been cited as strategies to slow global warming. Deforestation releases CO(2) to the atmosphere, which exerts a warming influence on Earth's climate. However, biophysical effects of deforestation, which include changes in land surface albedo, evapotranspiration, and cloud cover also affect climate. Here we present results from several large-scale deforestation experiments performed with a three-dimensional coupled global carbon-cycle and climate model. These simulations were performed by using a fully three-dimensional model representing physical and biogeochemical interactions among land, atmosphere, and ocean. We find that global-scale deforestation has a net cooling influence on Earth's climate, because the warming carbon-cycle effects of deforestation are overwhelmed by the net cooling associated with changes in albedo and evapotranspiration. Latitude-specific deforestation experiments indicate that afforestation projects in the tropics would be clearly beneficial in mitigating global-scale warming, but would be counterproductive if implemented at high latitudes and would offer only marginal benefits in temperate regions. Although these results question the efficacy of mid- and high-latitude afforestation projects for climate mitigation, forests remain environmentally valuable resources for many reasons unrelated to climate.

The effect of land surface changes on Eemian climate

Transient experiments for the Eemian (128–113 ky BP) were performed with a complex, coupled earth system model, including atmosphere, ocean, terrestrial biosphere and marine biogeochemistry. In order to investigate the effect of land surface parameters (background albedo, vegetation and tree fraction and roughness length) on the simulated changes during the Eemian, simulations with interactive coupling between climate and vegetation were compared with additional experiments in which these feedbacks were suppressed. The experiments show that the influence of land surface on climate is mainly caused by changes in the albedo. For the northern hemisphere high latitudes, land surface albedo is changed partially due to the direct albedo effect of the conversion of grasses into forest, but the indirect effect of forests on snow albedo appears to be the major factor influencing the total absorption of solar radiation. The Western Sahara region experiences large changes in land surface albedo due to the appearance of vegetation between 128 and 120 ky BP. These local land surface albedo changes can be as much as 20%, thereby affecting the local as well as the global energy balance. On a global scale, latent heat loss over land increases more than 10% for 126 ky BP compared to present-day.

LAND COVER, RAINFALL AND LAND-SURFACE ALBEDO IN WEST AFRICA

Land surface albedo is an important variable in General Circulation Models (GCMs). When land cover is modified through anthropogenic land use, changes in land-surface albedo may produce atmospheric subsidence and reduction of rainfall. In this study we examined albedo time series and their relationships with rainfall, land cover, and population in West Africa. This particular region was selected because it has become a focal point in debates over biophysical impacts of desertification and deforestation. Our analyses revealed that albedo and rainfall were related only modestly at short time scales (monthly and annual) and that mean annual albedo values remained relatively stable from 1982–1989 over a widerange of climatic and vegetation zones in West Africa. The relationship between long-term mean rainfall and mean albedo was strong and curvilinear(r2 = 0.802). The same was true for the relationship betweenpercent tree cover and mean albedo (r2 = 0.659). These results suggest that long-term climate patterns, which control vegetation type and canopy structure, have greater influence on albedo than short-term fluctuations in rainfall. Our results reinforce other recent studies based on satellite data that have questioned the extent and pervasiveness of desertification in West Africa.