scholarly journals Changes in the Land Surface Energy Budget in Eastern China over the Past Three Decades: Contributions of Land-Cover Change and Climate Change

2014 ◽  
Vol 27 (24) ◽  
pp. 9233-9252 ◽  
Author(s):  
J. W. Yan ◽  
J. Y. Liu ◽  
B. Z. Chen ◽  
M. Feng ◽  
S. F. Fang ◽  
...  
Keyword(s):  
Climate Change ◽  
Heat Flux ◽  
Surface Energy ◽  
Land Cover ◽  
Land Cover Change ◽  
Land Surface ◽  
Energy Exchange ◽  
Eastern China ◽  
Incident Solar Radiation ◽  
The Past

Abstract Sensible heat flux (H), latent heat flux (LE), and net radiation (NR) are important surface energy components that directly influence climate systems. In this study, the changes in the surface energy and their contributions from global climate change and/or land-cover change over eastern China during the past nearly 30 years were investigated and assessed using a process-based land surface model [the Ecosystem–Atmosphere Simulation Scheme (EASS)]. The modeled results show that climate change contributed more to the changes of land surface energy fluxes than land-cover change, with their contribution ratio reaching 4:1 or even higher. Annual average temperature increased before 2000 and reversed thereafter; annual total precipitation continually decreased, and incident solar radiation continually increased over the past nearly 30 years. These climatic changes could lead to increased NR, H, and LE, assuming land cover remained unchanged during the past nearly 30 years. Among these meteorological variables, at spatial distribution, the incident solar radiation has the greatest effect on land surface energy exchange. The impacts of land-cover change on the seasonal variations in land surface heat fluxes between the four periods were large, especially for H. The changes in the regional energy fluxes resulting from different land-cover type conversions varied greatly. The conversion from farmland to evergreen coniferous forests had the greatest influence on land surface energy exchange, leading to a decrease in H by 19.39% and an increase in LE and NR by 7.44% and 2.74%, respectively. The results of this study can provide a basis and reference for climate change adaptation.

scholarly journals Research on Land Surface Thermal-Hydrologic Exchange in Southern China under Future Climate and Land Cover Scenarios

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Jianwu Yan ◽  
Baozhang Chen ◽  
Min Feng ◽  
John L. Innes ◽  
Guangyu Wang ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Water ◽  
Land Cover ◽  
Land Cover Change ◽  
Land Surface ◽  
Southern China ◽  
Future Climate ◽  
Land Surface Water ◽  
Hydrologic Exchange ◽  
Heat Exchanges

Climate change inevitably leads to changes in hydrothermal circulation. However, thermal-hydrologic exchanging caused by land cover change has also undergone ineligible changes. Therefore, studying the comprehensive effects of climate and land cover changes on land surface water and heat exchanges enables us to well understand the formation mechanism of regional climate and predict climate change with fewer uncertainties. This study investigated the land surface thermal-hydrologic exchange across southern China for the next 40 years using a land surface model (ecosystem-atmosphere simulation scheme (EASS)). Our findings are summarized as follows. (i) Spatiotemporal variation patterns of sensible heat flux (H) and evapotranspiration (ET) under the land cover scenarios (A2a or B2a) and climate change scenario (A1B) are unanimous. (ii) BothHand ET take on a single peak pattern, and the peak occurs in June or July. (iii) Based on the regional interannual variability analysis,Hdisplays a downward trend (10%) and ET presents an increasing trend (15%). (iv) The annual averageHand ET would, respectively, increase and decrease by about 10% when woodland converts to the cultivated land. Through this study, we recognize that land surface water and heat exchanges are affected greatly by the future climate change as well as land cover change.

scholarly journals Mesoscale Simulations of the Land Surface Effects of Historical Logging in a Moist Continental Climate Regime

2008 ◽  
Vol 47 (8) ◽  
pp. 2166-2182 ◽  
Author(s):  
Nicholas P. Klingaman ◽  
Jason Butke ◽  
Daniel J. Leathers ◽  
Kevin R. Brinson ◽  
Elsa Nickl
Keyword(s):  
Climate Change ◽  
Heat Flux ◽  
Land Cover ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Climate Regime ◽  
Clear Cut ◽  
Atmosphere System ◽  
Regional Climates

Abstract An enhanced knowledge of the feedbacks from land surface changes on regional climates is of great importance in the attribution of climate change. To explore the effects of deforestation on a midlatitude climate regime, two sets of two five-member ensembles of 28-day simulations were conducted using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) coupled to the “Noah” land surface model. The four ensembles represented conditions in summer (August) and winter (February) across the northern mid-Atlantic United States before and after extensive late-nineteenth-century logging of hardwood forests in central and northern Pennsylvania. Prelogging ensembles prescribed a vegetative cover of an evergreen needleleaf forest; postlogging ensembles prescribed sparse vegetation and bare soil to simulate clear-cut deforestation. The results of the MM5 experiments showed a decided seasonality in the response of the land surface–atmosphere system to deforestation, with much stronger effects arising in summer. In August, deforestation caused a repartitioning of the surface energy budget, beginning with a decrease in the latent heat flux of more than 60 W m−2 across the land cover–forcing area, representing almost one-half of the latent heat flux under prelogging land cover. Concomitant with this decrease in evapotranspiration, mean 2-m air temperatures warmed by at least 1.5°C. Increases in sensible heat flux led to a 150-m mean increase in the height of the atmospheric boundary layer over the deforested area. Low-level atmospheric mixing ratios and total precipitation decreased under clear-cut conditions. Mean soil moisture increased in all model levels to 150 cm because of a decrease in vegetative uptake of water, except at the 5-cm level at which such decreases were effectively balanced by greater soil evaporation and less precipitation. A strong diurnal variation in the response to deforestation of ground and lower-atmosphere temperatures and heat fluxes was also identified for the summer season. The February simulations showed the effects of deforestation during low-insolation months to be small and variable. The strong response of the summer land surface–atmosphere system to deforestation shown here suggests that land cover changes can appreciably affect regional climates. Thus, the role of human-induced and naturally occurring land cover variability should not be ignored in the attribution of climate change.

scholarly journals Impact of urban expansion on continental- to regional-scale warming

2022 ◽  
Author(s):  
TC Chakraborty ◽  
Yun Qian
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Land Surface ◽  
Urban Expansion ◽  
Regional Scale ◽  
Land Use Land Cover ◽  
Earth System ◽  
Earth System Models

Abstract Although the influence of land use/land cover change on climate has become increasingly apparent, cities and other built-up areas are usually ignored when estimating large-scale historical climate change or for future projections since cities cover a small fraction of the terrestrial land surface1,2. As such, ground-based observations of urban near-surface meteorology are rare and most earth system models do not represent historical or future urban land cover3–7. Here, by combining global satellite observations of land surface temperature with historical estimates of built-up area, we demonstrate that the urban temperature signal on continental- to regional-scale warming has become non-negligible, especially for rapidly urbanizing regions in Asia. Consequently, expected urban expansion over the next century suggest further increased urban influence on surface climate under all future climate scenarios. Based on these results, we argue that, in line with other forms of land use/land cover change, urbanization should be explicitly included in future climate change assessments. This would require extensive model development to incorporate urban extent and biophysics in current-generation earth system models to quantify potential urban feedbacks on the climate system at multiple scales.

scholarly journals Impacts of future deforestation and climate change on the hydrology of the Amazon Basin: a multi-model analysis with a new set of land-cover change scenarios

2017 ◽  
Vol 21 (3) ◽  
pp. 1455-1475 ◽  
Author(s):  
Matthieu Guimberteau ◽  
Philippe Ciais ◽  
Agnès Ducharne ◽  
Juan Pablo Boisier ◽  
Ana Paula Dutra Aguiar ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Cover ◽  
Land Cover Change ◽  
Land Surface ◽  
River Discharge ◽  
General Circulation ◽  
Amazon Basin ◽  
General Circulation Models ◽  
Dry Season ◽  
Regional Patterns

Abstract. Deforestation in Amazon is expected to decrease evapotranspiration (ET) and to increase soil moisture and river discharge under prevailing energy-limited conditions. The magnitude and sign of the response of ET to deforestation depend both on the magnitude and regional patterns of land-cover change (LCC), as well as on climate change and CO2 levels. On the one hand, elevated CO2 decreases leaf-scale transpiration, but this effect could be offset by increased foliar area density. Using three regional LCC scenarios specifically established for the Brazilian and Bolivian Amazon, we investigate the impacts of climate change and deforestation on the surface hydrology of the Amazon Basin for this century, taking 2009 as a reference. For each LCC scenario, three land surface models (LSMs), LPJmL-DGVM, INLAND-DGVM and ORCHIDEE, are forced by bias-corrected climate simulated by three general circulation models (GCMs) of the IPCC 4th Assessment Report (AR4). On average, over the Amazon Basin with no deforestation, the GCM results indicate a temperature increase of 3.3 °C by 2100 which drives up the evaporative demand, whereby precipitation increases by 8.5 %, with a large uncertainty across GCMs. In the case of no deforestation, we found that ET and runoff increase by 5.0 and 14 %, respectively. However, in south-east Amazonia, precipitation decreases by 10 % at the end of the dry season and the three LSMs produce a 6 % decrease of ET, which is less than precipitation, so that runoff decreases by 22 %. For instance, the minimum river discharge of the Rio Tapajós is reduced by 31 % in 2100. To study the additional effect of deforestation, we prescribed to the LSMs three contrasted LCC scenarios, with a forest decline going from 7 to 34 % over this century. All three scenarios partly offset the climate-induced increase of ET, and runoff increases over the entire Amazon. In the south-east, however, deforestation amplifies the decrease of ET at the end of dry season, leading to a large increase of runoff (up to +27 % in the extreme deforestation case), offsetting the negative effect of climate change, thus balancing the decrease of low flows in the Rio Tapajós. These projections are associated with large uncertainties, which we attribute separately to the differences in LSMs, GCMs and to the uncertain range of deforestation. At the subcatchment scale, the uncertainty range on ET changes is shown to first depend on GCMs, while the uncertainty of runoff projections is predominantly induced by LSM structural differences. By contrast, we found that the uncertainty in both ET and runoff changes attributable to uncertain future deforestation is low.

scholarly journals Impacts of historical climate and land cover changes on tropospheric ozone air quality and public health in East Asia over 1980–2010

2015 ◽  
Vol 15 (10) ◽  
pp. 14111-14139 ◽  
Author(s):  
Y. Fu ◽  
A. P. K. Tai
Keyword(s):  
Public Health ◽  
Climate Change ◽  
Air Quality ◽  
Land Cover ◽  
East Asia ◽  
Land Cover Change ◽  
Surface Ozone ◽  
Land Cover Changes ◽  
The Past ◽  
Premature Deaths

Abstract. Understanding how historical climate and land cover changes have affected tropospheric ozone in East Asia would help constrain the large uncertainties associated with future East Asian air quality projections. We perform a series of simulations using a global chemical transport model driven by assimilated meteorological data and a suite of land cover and land use data to examine the public health effects associated with changes in climate, land cover, land use, and anthropogenic emissions over the past 30 years (1980–2010) in East Asia. We find that over 1980–2010 land cover change alone could lead to a decrease in summertime surface ozone by up to 4 ppbv in East Asia and ~2000 fewer ozone-related premature deaths per year, driven mostly by enhanced dry deposition resulting from climate- and CO2-induced increase in vegetation density, which more than offsets the effect of reduced isoprene emission arising from cropland expansion. Over the same period, climate change alone could lead to an increase in summertime ozone by 2–10 ppbv in most regions of East Asia and ~6000 more premature deaths annually, mostly attributable to warming. The combined impacts (−2 to +12 ppbv) show that while the effect of climate change is more pronounced, land cover change could offset part of the climate effect and lead to a previously unknown public health benefit. While the changes in anthropogenic emissions remain the largest contributor to deteriorating ozone air quality in East Asia over the past 30 years, we show that climate change and land cover changes could lead to a substantial modification of ozone levels, and thus should come into consideration when formulating future air quality management strategies. We also show that the sensitivity of surface ozone to land cover change is more dependent on dry deposition than isoprene emission in most of East Asia, leading to ozone responses that are quite distinct from that in North America, where most ozone-vegetation sensitivity studies to date have been conducted.

scholarly journals Quantitative analysis of the impacts of climate and land-cover changes on urban flood runoffs: a case of Dar es Salaam, Tanzania

2021 ◽  
Author(s):  
Philip Mzava ◽  
Patrick Valimba ◽  
Joel Nobert
Keyword(s):  
Climate Change ◽  
Land Cover ◽  
Land Cover Change ◽  
Dar Es Salaam ◽  
Land Cover Changes ◽  
Urban Flooding ◽  
Combined Effects ◽  
Peak Flows ◽  
The Past ◽  
The Future

Abstract Over the past half-century, the risk of urban flooding in Dar es Salaam has increased due to changes in land cover coupled with climatic changes. This paper aimed to quantify the impacts of climate and land-cover changes on the magnitudes and frequencies of flood runoffs in urban Dar es Salaam, Tanzania. A calibrated and validated SWAT rainfall-runoff model was used to generate flood hydrographs for the period 1969–2050 using historical rainfall data and projected rainfall based on the CORDEX-Africa regional climate model. Results showed that climate change has a greater impact on change in peak flows than land-cover change when the two are treated separately in theory. It was observed that, in the past, the probability of occurrence of urban flooding in the study area was likely to be increased up to 1.5-fold by climate change relative to land-cover change. In the future, this figure is estimated to decrease to 1.1-fold. The coupled effects of climate and land-cover changes cause a much bigger impact on change in peak flows than any separate scenario; this scenario represents the actual scenario on the ground. From the combined effects of climate and land-cover changes, the magnitudes of mean peak flows were determined to increase between 34.4 and 58.6% in the future relative to the past. However, the change in peak flows from combined effects of climate and land-cover changes will decrease by 36.3% in the future relative to the past; owing to the lesser variations in climate and land-cover changes in the future compared with those of the past.

scholarly journals Pairing FLUXNET Sites to Validate Model Representations of Land Use/Land Cover Change

2017 ◽  
Author(s):  
Liang Chen ◽  
Paul A. Dirmeyer ◽  
Zhichang Guo ◽  
Natalie M. Schultz
Keyword(s):  
Land Use ◽  
Heat Flux ◽  
Land Cover ◽  
Land Cover Change ◽  
Land Surface ◽  
Surface Fluxes ◽  
Late Winter ◽  
Land Use Land Cover ◽  
Community Land Model ◽  
Ground Heat Flux

Abstract. Land surface energy and water fluxes play an important role in land-atmosphere interactions, especially for the climatic feedback effects driven by land use/land cover change (LULCC). These have long been documented in model-based studies, but the performance of land surface models in representing LULCC-induced responses has not been well investigated. In this study, measurements from proximate paired (open versus forest) flux tower sites are used to represent observed deforestation-induced changes in surface fluxes, which are compared with simulations from the Community Land Model (CLM) and the Noah Multi-Parameterization (Noah-MP) land model. Point-scale simulations suggest CLM can represent the observed diurnal and seasonal changes in net radiation (Rnet) and ground heat flux (G), but difficulties remain in the energy partitioning between latent (LE) and sensible (H) heat flux. CLM does not capture the observed decreased daytime LE, and overestimates the increased H during summer. These biases are mainly associated with deficiencies over forest land-cover types and the parameterization of soil evaporation. Global gridded simulations with CLM show uncertainties in the estimation of LE and H at the grid level for regional and global simulations. Noah-MP exhibits a similar ability to simulate the surface flux changes, but with larger biases in H, G, and Rnet change during late winter and early spring, which are related to a deficiency in estimating albedo. Differences in meteorological conditions between paired sites is not a factor in these results. Attention needs to be devoted to improving the representation of surface heat flux processes in land models to increase confidence in LULCC simulations.

scholarly journals Pairing FLUXNET sites to validate model representations of land-use/land-cover change

2018 ◽  
Vol 22 (1) ◽  
pp. 111-125 ◽  
Author(s):  
Liang Chen ◽  
Paul A. Dirmeyer ◽  
Zhichang Guo ◽  
Natalie M. Schultz
Keyword(s):  
Land Use ◽  
Heat Flux ◽  
Land Cover ◽  
Land Cover Change ◽  
Land Surface ◽  
Surface Fluxes ◽  
Late Winter ◽  
Land Use Land Cover ◽  
Community Land Model ◽  
Ground Heat Flux

Abstract. Land surface energy and water fluxes play an important role in land–atmosphere interactions, especially for the climatic feedback effects driven by land-use/land-cover change (LULCC). These have long been documented in model-based studies, but the performance of land surface models in representing LULCC-induced responses has not been investigated well. In this study, measurements from proximate paired (open versus forest) flux tower sites are used to represent observed deforestation-induced changes in surface fluxes, which are compared with simulations from the Community Land Model (CLM) and the Noah Multi-Parameterization (Noah-MP) land model. Point-scale simulations suggest the CLM can represent the observed diurnal and seasonal changes in net radiation (Rnet) and ground heat flux (G), but difficulties remain in the energy partitioning between latent (LE) and sensible (H) heat flux. The CLM does not capture the observed decreased daytime LE, and overestimates the increased H during summer. These deficiencies are mainly associated with models' greater biases over forest land-cover types and the parameterization of soil evaporation. Global gridded simulations with the CLM show uncertainties in the estimation of LE and H at the grid level for regional and global simulations. Noah-MP exhibits a similar ability to simulate the surface flux changes, but with larger biases in H, G, and Rnet change during late winter and early spring, which are related to a deficiency in estimating albedo. Differences in meteorological conditions between paired sites is not a factor in these results. Attention needs to be devoted to improving the representation of surface heat flux processes in land models to increase confidence in LULCC simulations.

scholarly journals Spatially explicit statistical modeling of random and systematic land cover transitions in the main grassland plain of Nech Sar National Park, Ethiopia

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Kiros Tsegay Deribew
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Statistical Modeling ◽  
National Park ◽  
Spatial Extent ◽  
Aerial Photographs ◽  
Woody Vegetation ◽  
Spatially Explicit ◽  
Strong Signal ◽  
The Past

AbstractThe main grassland plain of Nech Sar National Park (NSNP) is a federally managed protected area in Ethiopia designated to protect endemic and endangered species. However, like other national parks in Ethiopia, the park has experienced significant land cover change over the past few decades. Indeed, the livelihoods of local populations in such developing countries are entirely dependent upon natural resources and, as a result, both direct and indirect anthropogenic pressures have been placed on natural parks. While previous research has looked at land cover change in the region, these studies have not been spatially explicit and, as a result, knowledge gaps in identifying systematic transitions continue to exist. This study seeks to quantify the spatial extent and land cover change trends in NSNP, identify the strong signal transitions, and identify and quantify the location of determinants of change. To this end, the author classifies panchromatic aerial photographs in 1986, multispectral SPOT imagery in 2005, and Sentinel imagery in 2019. The spatial extent and trends of land cover change analysis between these time periods were conducted. The strong signal transitions were systematically identified and quantified. Then, the basic driving forces of the change were identified. The locations of these transitions were also identified and quantified using the spatially explicit statistical model. The analysis revealed that over the past three decades (1986–2019), nearly 52% of the study area experienced clear landscape change, out of which the net change and swap change attributed to 39% and 13%, respectively. The conversion of woody vegetation to grassland (~ 5%), subsequently grassland-to-open-overgrazed land (28.26%), and restoration of woody vegetation (0.76%) and grassland (0.72%) from riverine forest and open-overgrazed land, respectively, were found to be the fully systematic transitions whereas the rest transitions were recorded either partly systematic or random transitions. The location of these most systematic land cover transitions identified through the spatially explicit statistical modeling showed drivers due to biophysical conditions, accessibility, and urban/market expansions, coupled with successive government policies for biodiversity management, geo-politics, demographic, and socioeconomic factors. These findings provide important insights into biodiversity loss, land degradation, and ecosystem disruption. Therefore, the model for predicted probability generally suggests a 0.75 km and 0.72 km buffers which are likely to protect forest and grassland from conversion to grassland and open-overgrazed land, respectively.

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