Satellite monitoring of global land cover changes and their impact on climate

Land cover is a crucial, spatially and temporally varying component of global carbon and climate systems. Therefore accurate estimation and monitoring of land cover changes is important in global change research. Although, land cover has dramatically changed over the last few centuries, until now there has been no consistent way of quantifying the changes globally.In this study we used long-term climate, soils data along with coarse resolution satellite observations to quantify the magnitude and spatial extent of global land cover changes due to anthropogenic processes. Differences between potential leaf area index, derived from climate-soil-leaf area equilibrium and actual leaf area index obtained from satellite data were used to estimate changes in land cover.Forest clearing for agriculture and irrigated farming in arid and semi-arid lands are found to be two major sources of climatically important land cover changes. Satellite derived Spectral Vegetation indices (SV I) and surface temperatures (T s) show strong impact of land cover changes on climatic processes. Irrigated agriculture in dry areas increased energy absorption and evapotranspiration (ET) compared to natural vegetation. On the other hand, forest clearing for crops decreased energy absorption andET. A land cover classification and monitoring system is proposed using satellite derivedSV I andT s that simultaneously characterize energy absorption and exchange processes. This completely remote sensing based approach is useful for monitoring land cover changes as well as their impacts on climate. Monitoring the spatio-temporal dynamics of land cover is possible with current operational satellites, and could be substantially improved with the Earth Observing System (EOS) era satellite sensors.     

The impact of land cover change on the atmospheric circulation

 The NCAR Community Climate Model (version 3), coupled to the Biosphere Atmosphere Transfer scheme and a mixed layer ocean model is used to investigate the impact on the climate of a conservative change from natural to present land cover. Natural vegetation cover was obtained from an ecophysiologically constrained biome model. The current vegetation cover was obtained by perturbing the natural cover from forest to grass over areas where land cover has been observed to change. Simulations were performed for 17 years for each case (results from the last 15 years are presented here). We find that land cover changes, largely constrained to the tropics, SE Asia, North America and Europe, cause statistically significant changes in regional temperature and precipitation but cause no impact on the globally averaged temperature or precipitation. The perturbation in land cover in the tropics and SE Asia teleconnect to higher latitudes by changing the position and strength of key elements of the general circulation (the Hadley and Walker circulations). Many of the areas where statistically significant changes occur are remote from the location of land cover change. Historical land cover change is not typically included in transitory climate simulations, and it may be that the simulation of the patterns of temperature change over the twentieth century by climate models will be further improved by taking it into account. Received: 27 May 1999 / Accepted: July 2000     

No peace for the forest: Rapid,widespread land changes in the Andes-Amazon region following the Colombian civil war

Negative environmental impacts of violent conflict have been observed worldwide. Whether or not active global conflicts are declining in number remains hotly debated, the number of countries entering post-conflict periods is on the rise, and the impact of this transition on land cover changes remains poorly understood. In Colombia, though large-scale armed conflict has concluded, the post-conflict period represents an ongoing threat to forest conservation, putting at risk commitments to meet global conservation goals and even those stipulated in the peace accord. This paper aims to assess land cover change associated with the Colombian conflict in the Andes-Amazon region between 1988 and 2019. First, we use the Landsat archive to map land cover and characterize the spatial patterns of change at the regional level. Second, to empirically identify the effect of conflict on land cover change, we employ a difference-in-difference approach using local conflict events data. During conflict (1988–2011), land cover in the Andes-Amazon remained relatively stable, however during the post-conflict period (2012–2019), the conversion from forest to agriculture increased by 40%. We find that forest cover surrounding conflict events (1 km radius) decreased significantly, on average by ~ 19% during conflict, which accelerated to ~ 30% in the post-conflict period. Similarly, agriculture expansion is most substantial during the post-conflict period, but exclusively in municipalities with population below the 50th percentile. Landscape metrics show that in peripheral municipalities (<50th), agriculture occurs in clumped distributions during the conflict period. Meanwhile, during the post-conflict period, this expansion happens more quickly, with significantly greater agricultural patch sizes than during the conflict period. We conclude that a slow implementation of conservation governance, the emergence of illegal land markets, and illicit land uses (i.e., coca and illegal cattle ranching) may accelerate land cover change in the coming years.     

A Method for Estimating the Cost of CO2 Mitigation through Afforestation

The Kyoto Protocol allows Annex I countries to use afforestation (theconversion of non-forest landto forest) to meet emissions reduction targets. We present a new method forestimating the cost of CO₂mitigation through afforestation based on econometric models of land use. Landuse models are developed from dataon observed land allocation decisions and quantify the relationship betweenthe share of land in forest and the netreturns to forestry, among other land use determinants. The econometricapproach measures the actual responsesby landowners to observed changes in net returns, in contrast to earlierstudies in which landowner responses aredictated by the researcher. Models are estimated for Maine, South Carolina,and Wisconsin. The estimated modelsare used to simulate subsidies for afforestation, which imply increases inforest area and net reductions inatmospheric CO₂ concentrations. Average cost measures – totalsubsidies divided by total carbon sequestered –are derived for afforestation programs with and without timber harvesting. Theuse of econometric land use modelsin integrated assessments of climate change is explored. We model the effectson land use patterns and the costsof CO₂ mitigation of changes in the net returns to agricultureinduced by climate change.     

Natural and anthropogenic climate change: incorporating historical land cover change,vegetation dynamics and the global carbon cycle

This study explores natural and anthropogenic influences on the climate system, with an emphasis on the biogeophysical and biogeochemical effects of historical land cover change. The biogeophysical effect of land cover change is first subjected to a detailed sensitivity analysis in the context of the UVic Earth System Climate Model, a global climate model of intermediate complexity. Results show a global cooling in the range of –0.06 to –0.22 °C, though this effect is not found to be detectable in observed temperature trends. We then include the effects of natural forcings (volcanic aerosols, solar insolation variability and orbital changes) and other anthropogenic forcings (greenhouse gases and sulfate aerosols). Transient model runs from the year 1700 to 2000 are presented for each forcing individually as well as for combinations of forcings. We find that the UVic Model reproduces well the global temperature data when all forcings are included. These transient experiments are repeated using a dynamic vegetation model coupled interactively to the UVic Model. We find that dynamic vegetation acts as a positive feedback in the climate system for both the all-forcings and land cover change only model runs. Finally, the biogeochemical effect of land cover change is explored using a dynamically coupled inorganic ocean and terrestrial carbon cycle model. The carbon emissions from land cover change are found to enhance global temperatures by an amount that exceeds the biogeophysical cooling. The net effect of historical land cover change over this period is to increase global temperature by 0.15 °C.     

A comparison of a GCM response to historical anthropogenic land cover change and model sensitivity to uncertainty in present-day land cover representations

This study assesses the sensitivity of the fully coupled NCAR-DOE PCM to three different representations of present-day land cover, based on IPCC SRES land cover information. We conclude that there is significant model sensitivity to current land cover characterization, with an observed average global temperature range of 0.21 K between the simulations. Much larger contrasts (up to 5 K) are found on the regional scale; however, these changes are largely offsetting on the global scale. These results show that significant biases can be introduced when outside data sources are used to conduct anthropogenic land cover change experiments in GCMs that have been calibrated to their own representation of present-day land cover. We conclude that hybrid systems that combine the natural vegetation from the native GCM datasets combined with human land cover information from other sources are best for simulating such impacts. We also performed a prehuman simulation, which had a 0.39 K ~higher average global temperature and, perhaps of greater importance, temperature changes regionally of about 2 K. In this study, the larger regional changes coincide with large-scale agricultural areas. The initial cooling from energy balance changes appear to create feedbacks that intensify mid-latitude circulation features and weaken the summer monsoon circulation over Asia, leading to further cooling. From these results, we conclude that land cover change plays a significant role in anthropogenically forced climate change. Because these changes coincide with regions of the highest human population this climate impact could have a disproportionate impact on human systems. Therefore, it is important that land cover change be included in past and future climate change simulations.     

Influence of snow cover changes on surface radiation and heat balance based on the WRF model

The snow cover extent in mid-high latitude areas of the Northern Hemisphere has significantly declined corresponding to the global warming, especially since the 1970s. Snow-climate feedbacks play a critical role in regulating the global radiation balance and influencing surface heat flux exchange. However, the degree to which snow cover changes affect the radiation budget and energy balance on a regional scale and the difference between snow-climate and land use/cover change (LUCC)-climate feedbacks have been rarely studied. In this paper, we selected Heilongjiang Basin, where the snow cover has changed obviously, as our study area and used the WRF model to simulate the influences of snow cover changes on the surface radiation budget and heat balance. In the scenario simulation, the localized surface parameter data improved the accuracy by 10 % compared with the control group. The spatial and temporal analysis of the surface variables showed that the net surface radiation, sensible heat flux, Bowen ratio, temperature and percentage of snow cover were negatively correlated and that the ground heat flux and latent heat flux were positively correlated with the percentage of snow cover. The spatial analysis also showed that a significant relationship existed between the surface variables and land cover types, which was not obviously as that for snow cover changes. Finally, six typical study areas were selected to quantitatively analyse the influence of land cover types beneath the snow cover on heat absorption and transfer, which showed that when the land was snow covered, the conversion of forest to farmland can dramatically influence the net radiation and other surface variables, whereas the snow-free land showed significantly reduced influence. Furthermore, compared with typical land cover changes, e.g., the conversion of forest into farmland, the influence of snow cover changes on net radiation and sensible heat flux were 60 % higher than that of land cover changes, indicating the importance of snow cover changes in the surface-atmospheric feedback system.     

Recent progress in studies on land cover change and its regional climatic effects over China during historical times

The recent progresses on the reconstruction of historical land cover and the studies on regional climatic effects to temperature,precipitation,and the East Asian Monsoon across China were reviewed.Findings show that the land cover in China has been significantly modified by human activities over the last several thousands years,mainly through cropland expansion and forest clearance.The cropland over traditional Chinese agricultural areas increased from 5.32×105 km2 in the mid-17th century to 8.27×105 km2 in...     

基于三种WRF陆面过程方案的东南亚毁林增温响应研究

选取东南亚中南半岛地区作为模拟区域,基于高分辨率的遥感观测森林变化数据和WRF数值模式,设计毁林前后的两种情景对旱季气候进行模拟,评估NoahMP、CLM和Noah mosaic三种陆面过程方案对热带毁林增温响应的模拟能力。结果表明,CLM方案在模拟历史气温中有着更好的表现,Noah mosaic方案的结果存在明显低估。然而,对比毁林前后两种情景的模拟结果,本文发现,只有采用了"次格网"方式的Noah mosaic方案较好地模拟出毁林增温响应特征。在格网尺度采用"主导类型"计算方式的NoahMP方案没有合理地呈现出森林损失对区域气候的影响。理论上,CLM模式在计算中同时考虑格网内所有植被类型,然而本文发现CLM方案在主导类型不变的格网对森林损失比例不敏感,而且对毁林反馈的模拟结果与NoahMP方案的结果更接近。据此推测,在WRF模式耦合CLM方案的过程中,格网内参数处理方式可能产生了错误,实际采用的是"主导类型"方式。在模拟土地覆盖类型变化对气候的影响时,本文推荐使用Noah mosaic方案。同时,建议在未来版本的WRF模型中修正目前耦合的CLM方案关于次格网方法的处理方式,提供更合理的水热通量模拟。     

Baseline scenarios of global environmental change

This paper presents three baseline scenarios of no policy action computed by the IMAGE 2 model. These scenarios cover a wide range of coupled global change Indicators, including: energy demand and consumption; food demand, consumption, and production; changes in land cover including changes in extent of agricultural land and forest; emissions of greenhouse gases and ozone precursors; and climate change and its impacts on sea level rise, crop productivity and natural vegetation. Scenario information is available for the entire world with regional and grid scale detail, and covers from 1970 to 2100. The scenarios indicate that the coming decades could be a period of relatively rapid global environmental change as compared to the period before and after. The natural vegetation in industrialized regions could be threatened by climate change, but abandonment of agricultural lands could also make new lands available for reforestation and revegetation. The opposite is true for most of Asia and Africa. Here the impacts of climate change on vegetation may not be as significant as in temperate climates, but the demand for food will lead to a significant expansion of agricultural lands at the expense of remaining forests and other natural areas.     

Insights from watershed simulations around the world: Watershed service-based restoration does not significantly enhance streamflow

Increased water yield and baseflow and decreased peak flow are common goals of watershed service programs. However, is the forest management often used in such programs likely to provide these beneficial watershed services? Many watershed service investments such as water funds typically change less than 10% of watershed land cover. We simulate the effects of 10% forest-cover change on water yield, low flow, and high flow in hydrologic models of 29 watersheds around the world. The forest-cover changes considered are: forest restoration from degraded natural lands or agriculture, forest conversion to agriculture, and forest conversion to urban cover. We do not consider grassland restoration by removal of alien tree species from riparian zones, which does increase water yield and low flow. Forest restoration from locally-predominant agricultural land resulted in median loss in annual water yield of 1.4%. Forest restoration reduced low flow and high flow by ∼3%. After forest restoration, low flow increased in ∼25% of cases while high flow and water yield declined in nearly all cases. Development of forest to agriculture or urban cover resulted in a 1–2% median increase in water yield, a 0.25–1% increase in low flow, and a 5–7% increase in high flow. We show that hydrologic responses to forest cover changes are not linearly related to climate, physiography, initial land cover, nor a multitude of watershed characteristics in most cases. These results suggest that enhanced streamflow watershed services anticipated from forest restoration or conservation of 10% or less of a watershed are generally modest.     

Climate Change Scenarios for the Hudson Bay Region: An Intermodel Comparison

General circulation models (GCMs) are unanimous in projecting warmer temperatures in an enhanced CO₂ atmosphere, with amplification of this warming in higher latitudes. The Hudson Bay region, which is located in the Arctic and subarctic regions of Canada, should therefore be strongly influenced by global warming. In this study, we compare the response of Hudson Bay to a transient warming scenario provided by six-coupled atmosphere-ocean models. Our analysis focuses on surface temperature, precipitation, sea-ice coverage, and permafrost distribution. The results show that warming is expected to peak in winter over the ocean, because of a northward retreat of the sea-ice cover. Also, a secondary warming peak is observed in summer over land in the Canadian and Australian-coupled GCMs, which is associated with both a reduction in soil moisture conditions and changes in permafrost distribution. In addition, a relationship is identified between the retreat of the sea-ice cover and an enhancement of precipitation over both land and oceanic surfaces. The response of the sea-ice cover and permafrost layer to global warming varies considerably among models and thus large differences are observed in the projected regional increase in temperature and precipitation. In view of the important feedbacks that a retreat of the sea-ice cover and the distribution of permafrost are likely to play in the doubled and tripled CO₂ climates of Hudson Bay, a good representation of these two parameters is necessary to provide realistic climate change scenarios. The use of higher resolution regional climate model is recommended to develop scenarios of climate change for the Hudson Bay region.     

Assessing impacts of climate change on forests: The state of biological modeling

Models that address the impacts of climate change on forests are reviewed at four levels of biological organization: global, regional or landscape, community, and tree. The models are compared for their ability to assess changes in fluxes of biogenic greenhouse gases, land use, patterns of forest type or species composition, forest resource productivity, forest health, biodiversity, and wildlife habitat. No one model can address all of these impacts, but landscape transition models and regional vegetation and land-use models have been used to consider more impacts than the other models. The development of landscape vegetation dynamics models of functional groups is suggested as a means to integrate the theory of both landscape ecology and individual tree responses to climate change. Risk assessment methodologies can be adapted to deal with the impacts of climate change at various spatial and temporal scales. Four areas of research needing additional effort are identified: (1) linking socioeconomic and ecologic models; (2) interfacing forest models at different scales; (3) obtaining data on susceptibility of trees and forest to changes in climate and disturbance regimes; and (4) relating information from different scales.The U.S. Government right to retain a non-exclusive, royalty-free license in and to any copyright is acknowledged.Managed by Martin Marietta Energy Systems, Inc., for the U.S. Department of Energy under contract DE-AC05-84OR21400.     

Projections of climate change impacts on central America tropical rainforest

Tropical rainforest plays an important role in the global carbon cycle, accounting for a large part of global net primary productivity and contributing to CO₂ sequestration. The objective of this work is to simulate potential changes in the rainforest biome in Central America subject to anthropogenic climate change under two emissions scenarios, RCP4.5 and RCP8.5. The use of a dynamic vegetation model and climate change scenarios is an approach to investigate, assess or anticipate how biomes respond to climate change. In this work, the Inland dynamic vegetation model was driven by the Eta regional climate model simulations. These simulations accept boundary conditions from HadGEM2-ES runs in the two emissions scenarios. The possible consequences of regional climate change on vegetation properties, such as biomass, net primary production and changes in forest extent and distribution, were investigated. The Inland model projections show reductions in tropical forest cover in both scenarios. The reduction of tropical forest cover is greater in RCP8.5. The Inland model projects biomass increases where tropical forest remains due to the CO₂ fertilization effect. The future distribution of predominant vegetation shows that some areas of tropical rainforest in Central America are replaced by savannah and grassland in RCP4.5. Inland projections under both RCP4.5 and RCP8.5 show a net primary productivity reduction trend due to significant tropical forest reduction, temperature increase, precipitation reduction and dry spell increments, despite the biomass increases in some areas of Costa Rica and Panama. This study may provide guidance to adaptation studies of climate change impacts on the tropical rainforests in Central America.     

Determining Effects of Area Burned and Fire Severity on Carbon Cycling and Emissions in Siberia

The Russian boreal forest contains about 25% of the global terrestrial biomass, and even a higher percentage of the carbon stored in litter and soils. Fire burns large areas annually, much of it in low-severity surface fires – but data on fire area and impacts or extent of varying fire severity are poor. Changes in land use, cover, and disturbance patterns such as those predicted by global climate change models, have the potential to greatly alter current fire regimes in boreal forests and to significantly impact global carbon budgets. The extent and global importance of fires in the boreal zone have often been greatly underestimated. For the 1998 fire season we estimate from remote sensing data that about 13.3 million ha burned in Siberia. This is about 5 times higher than estimates from the Russian Aerial Forest Protection Service (Avialesookhrana) for the same period. We estimate that fires in the Russian boreal forest in 1998 constituted some 14–20% of average annual global carbon emissions from forest fires. Average annual emissions from boreal zone forests may be equivalent to 23–39% of regional fossil fuel emissions in Canada and Russia, respectively. But the lack of accurate data and models introduces large potential errors into these estimates. Improved monitoring and understanding of the landscape extent and severity of fires and effects of fire on carbon storage, air chemistry, vegetation dynamics and structure, and forest health and productivity are essential to provide inputs into global and regional models of carbon cycling and atmospheric chemistry.     

土地利用变化对我国区域气候影响的数值试验

使用RegCM2区域气候模式单向嵌套澳大利亚CSIRO R21L9全球海-气耦合模式,通过将中国区域植被覆盖由理想状况改变为实际状况的数值试验对比分析,探讨了当代中国土地利用变化对中国区域气候的影响,并对结果进行了统计显著性检验。研究表明,土地利用的变化,会导致我国西北等地区年平均降水减少,导致年平均气温在内陆部分地区升高和在沿海个别地区降低,引起许多地方夏季日平均最高气温升高,而冬季日平均最低气温则在我国东部部分地区降低的同时在西北地区升高,土壤湿度的变化表现为大范围的降低。研究同时表明,相同的土地变化在不同的地理环境下引起的气候要素变化有一定的不一致性。     

Biogeophysical impacts of land use on present-day climate: near-surface temperature change and radiative forcing

Changes in land cover affect climate through the surface energy and moisture budgets, but these biogeophysical impacts of land use have not yet been included in General Circulation Model (GCM) simulations of 20th century climate change. Here, the importance of these effects was assessed by comparing climate simulations performed with current and potential natural vegetation. The northern mid-latitude agricultural regions were simulated to be approximately 1–2 K cooler in winter and spring in comparison with their previously forested state, due to deforestation increasing the surface albedo by approximately 0.1 during periods of snow cover. Some other regions such as the Sahel and India experienced a small warming due to land use. Although the annual mean global temperature is only 0.02 K lower in the simulation with present-day land use, the more local temperature changes in some regions are of a similar magnitude to those observed since 1860. The global mean radiative forcing by anthropogenic surface albedo change relative to the natural state is simulated to be −0.2 Wm², which is comparable with the estimated forcings relative to pre-industrial times by changes in stratospheric and tropospheric ozone, N₂O, halocarbons, and the direct effect of anthropogenic aerosols. Since over half of global deforestation has occurred since 1860, simulations of climate since that date should include the biogeophysical effects of land use.     

Effects of Land Cover Conversion on Surface Climate

This study investigates the effects of large-scale human modification of land cover on regional and global climate. A general circulation model (Colorado State University GCM) coupled to a biophysically-based land surface model (SiB2) was used to run two 15-yr climate simulations. The control run used current vegetation distribution as observed by satellite for the year 1987 to derive the vegetation's physiological and morphological properties. The twin simulation used a realistic approximation of vegetation type distribution that would exist in the absence of human disturbance.In temperate latitudes, where anthropogenic modification of the landscape has converted large areas of forest and grassland to cropland, conversion cools canopy temperatures up to 0.7 ° C in summer and 1.1 ° C in winter. This cooling results from both (1) morphological changes in vegetation which increase albedo and (2) physiological changes in vegetation which increase latent heat flux of crops compared with undisturbed vegetation during the growing season. In the tropics and subtropics, conversion warms canopy temperature by about 0.8 ° C year round. The warming results from a combination of morphological changes in vegetation offset by physiological changes that reduce latent heat flux of existing compared with undisturbed vegetation. If water efficient, tropical C4 grasses replace C3 vegetation, latent heat flux is further reduced.The overall effect of land cover conversion is cooling in temperate latitudes and warming in the tropics. Because the effects are opposite in sign in tropics and middle latitudes, they cancel each other when averaged globally. Over land, the surface temperature increased by 0.2 C in winter and remained essentially unchanged in summer. The effects on land surface hydrology were also small when averaged globally. The results suggest that the effects of land use change of the observed magnitude do not have a strong impact on the globally averaged climate but their signature at regional scales is significant and vary according to the type of land cover conversion.     

Integrating global and regional analyses of the effects of climate change: A case study of land use in England and Wales

The purpose of this paper is to exemplify a means by which an integrated assessment can be made of global and regional effects on land use of climate change. This is achieved by use of data on the effects of climate change on world food prices as inputs to a regional land use allocation model.Data on world prices are drawn from a recent global study of climate change and crop yields. In a case study of England and Wales a land allocation model is used to infer changes of land use that are the product of the integrated effect of climate-induced global price changes and climate-related changes of yield in England and Wales. This combination of changed prices and yield potential is used to calculate the land use providing the highest returns for each of 155,235 1 km² cells of land in England and Wales for a future assumed for the year 2060 (without climate change) and then for that same environment with climate change. The difference between these two is then treated as an estimated effect resulting from climate change.     

The simulated atmospheric response to expansion of the Arctic boreal forest biome

Over the last century, the Arctic has warmed at twice the rate of the planet as a whole. Observational evidence indicates that this rapid warming is affecting the tundra and boreal forest biomes by changing their structure and geographic distribution. A global climate model (GCM) was used to explore the atmospheric response to boreal forest expansion by applying a one-grid cell shift of the forest into tundra. This subtle shift is meant to represent the expansion that would occur this century rather than more extreme scenarios predicted by dynamic vegetation models. Results show that this shift causes an average annual warming of 0.3 °C over the region because of a reduction in the surface albedo and an increase in net radiation. A warming of ~1.0 °C occurs in spring when the forest masks the higher albedo snow-covered surface and results in snowmelt and a reduction in cloud cover. Results fail to show a larger-scale dynamical response although some warming of the lower and mid troposphere occurs in July. No changes were found in the position or strength of the Arctic frontal zone as some studies have indicated will occur with a shift in the boreal forest-tundra boundary. These findings suggest that coupled model simulations that predict larger changes in vegetation distribution are likely overemphasizing the amount of Arctic warming that will occur this century. These findings also indicate that a realistic dynamical response to subtle land cover change might not be correctly simulated by GCMs run at coarse spatial resolutions.