Quantifying the Relative Importance of Direct and Indirect Biophysical Effects of Deforestation on Surface Temperature and Teleconnections

Devaraju, N.; Noblet‐Ducoudré, Nathalie de; Quesada, Benjamín; Bala, Govindasamy

doi:10.1175/jcli-d-17-0563.1

Cited by 83 publications

(81 citation statements)

References 53 publications

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“…Greening can also trigger a series of changes through atmospheric circulation that indirectly affect the surface temperature 154 . For example, the additionally transpired water enhances atmospheric water vapour content, which results in more longwave solar radiation entrapment and re-emission in the atmosphere, but reduces the amount of shortwave solar radiation reaching the Earth's surface through increased cloud formation 19,155,156 (Fig. 7).…”

Section: Wwwnaturecom/natrevearthenvironmentioning

confidence: 99%

Characteristics, drivers and feedbacks of global greening

Piao

Wang

Park

et al. 2019

Nat Rev Earth Environ

1,133

712

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Vegetation controls the exchange of carbon, water, momentum and energy between the land and the atmosphere, and provides food, fibre, fuel and other valuable ecosystem services 1,2. Changes in vegetation structure and function are driven by climatic and environmental changes, and by human activities such as land-use change. Given that increased carbon storage in vegetation, such as through afforestation, could combat climate change 3,4 , quantifying vegetation change and its impact on carbon storage and climate has elicited considerable interest from scientists and policymakers. However, it is not possible to detect vegetation changes at the global scale using ground-based observations due to the heterogeneity of change and the lack of observations that can detect these changes both spatially and temporally. While monitoring the changes in some vegetation properties (for example, stem-size distribution and below-ground biomass) at the global scale remains impossible, satellite-based remote sensing has enabled continuous estimation of a few important metrics, including vegetation greenness, since the 1980s (Box 1). In 1986, a pioneering study by Tucker et al. 5 on remotely sensed normalized difference vegetation index (NDVI; a radiometric measure of vegetation greenness) (Box 1) revealed a close connection between vegetation canopy greenness and photosynthesis acti vity (as inferred from seasonal variations in atmospheric CO 2 concentration). This index was successfully used to constrain vegetation primary production globally 6. Using NDVI data from 1981 to 1991, Myneni et al. 7 reported an increasing trend in vegetation greenness in the Northern Hemisphere, which was subsequently observed across the globe 8-13. This 'vegetation greening' is defined as a statistically signi ficant increase in annual or seasonal vegetation greenness at a location resulting, for instance, from increases in average leaf size, leaf number per plant, plant density, species composition, duration of green-leaf presence due to changes in the growing season and increases in the number of crops grown per year. There has also been considerable interest in understanding the mechanisms or drivers of greening 11,14. Lucht et al. 14 and Xu et al. 10 revealed that warming has eased climatic constraints, facilitating increasing vegetation greenness over the high latitudes. Zhu et al. 11 further investigated key drivers of greenness trends and concluded that CO 2 fertilization is a major factor driving vegetation greening at the global scale. Subsequent studies based on fine-resolution and medium-resolution satel lite data 13 have shown the critical role of land-surface history, including afforestation and agricultural intensification, in enhancing vegetation greenness. The large spatial scale of vegetation greening and the robustness of its signal have led the Intergovernmental Panel on Climate Change (IPCC) special report on climate change Afforestation The conversion of treeless lands to forests through planting trees.

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Section: Wwwnaturecom/natrevearthenvironmentioning

confidence: 99%

Characteristics, drivers and feedbacks of global greening

Piao

Wang

Park

et al. 2019

Nat Rev Earth Environ

1,133

712

View full text Add to dashboard Cite

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“…Forest change can significantly affect surface temperature, and the area, magnitude, and direction of any changes vary significantly from local to global scales [7,17,18]. Some studies have found the inconsistent warming or cooling effects of forest change on temperature [7,[19][20][21]. For example, forest cooling becomes more obvious as latitude decreases, but planted forests replacing natural forests will reduce ET and thus reduce biophysical cooling [22].…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Actual Impacts of Forest Cover Change on Surface Temperature in Guangdong, China

Shen

Huang

et al. 2020

Remote Sensing

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Forest cover change is critical in the regulation of global and regional climate change through the alteration of biophysical features across the Earth’s surface. The accurate assessment of forest cover change can improve our understanding of its roles in the regulation processes of surface temperature. In spite of this, few researchers have attempted to discern the varying effects of multiple satellite-derived forest changes on local surface temperatures. In this study, we quantified the actual contributions of forest loss and gain associated with evapotranspiration (ET) and albedo to local surface temperature in Guangdong Province, China using an improved spatiotemporal change pattern analysis method, and explored the interrelationships between surface temperature and air temperature change. We specifically developed three forest change products for Guangdong, combining satellite observations from Landsat, PALSAR, and MODIS for comparison. Our results revealed that the adjusted simple change detection (SCD)-based Landsat/PALSAR forest cover data performed relatively well. We found that forest loss and gain between 2000 and 2010 had opposite effects on land surface temperature (LST), ET, and albedo. Forest gain led to a cooling of −0.12 ± 0.01 °C, while forest loss led to a warming of 0.07 ± 0.01 °C, which were opposite to the anomalous change of air temperature. A reduced warming to a considerable cooling was estimated due to the forest gain and loss across latitudes. Specifically, mid-subtropical forest gains increased LST by 0.25 ± 0.01 °C, while tropical forest loss decreased LST by −0.16 ± 0.05 °C, which can demonstrate the local differences in an overall cooling. ET induced cooling and warming effects were appropriate for most forest gain and loss. Meanwhile, the nearby temperature changes caused by no-change land cover types more or less canceled out some of the warming and cooling. Albedo exhibited negligible and complex impacts. The other two products (i.e., the GlobeLand30 and MCD12Q1) affect the magnitude of temperature response due to the discrepancies in forest definition, methodology, and data resolution. This study highlights the non-negligible contributions of high-resolution maps and a robust temperature response model in the quantification of the extent to which forest gain reverses the climate effects of forest loss under global warming.

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“…Similarly, lower height of the vegetation canopy in agriculture versus forest or savanna reduces land surface roughness, increasing aerodynamic resistance, and impeding turbulent exchange with the atmosphere. Consequently, the loss of natural ecosystems in the tropics results in a land surface that tends to warm faster and dissipate heat less effectively than a comparable area of intact tropical forest or woody savanna (Feddema et al 2005, Ban-Weiss et al 2011, Devaraju et al 2018. Of the myriad consequences such changes have for the climate, we focus on one; changes in daily maximum temperatures.…”

Section: Introductionmentioning

confidence: 99%

Forest loss in Brazil increases maximum temperatures within 50 km

Cohn

Bhattarai

Campolo

et al. 2019

Environ. Res. Lett.

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Forest cover loss in the tropics is well known to cause warming at deforested sites, with maximum temperatures being particularly sensitive. Forest loss causes warming by altering local energy balance and surface roughness, local changes that can propagate across a wide range of spatial scales. Consequently, temperature increases result from not only changes in forest cover at a site, but also by the aggregate effects of non-local forest loss. We explored such non-local warming within Brazil's Amazon and Cerrado biomes, the region with the world's single largest amount of forest loss since 2000. Two datasets, one consisting of in-situ air temperature observations and a second, larger dataset consisting of ATs derived from remotely-sensed observations of land surface temperature, were used to quantify changes in maximum temperature due to forest cover loss at varying length-scales. We considered undisturbed forest locations (1 km 2 in extent), and forest loss trends in annuli ('halos'), located 1-2 km, 2-4 km, 4-10 km and 10-50 km from these undisturbed sites. Our research finds significant and substantial non-local warming, suggesting that historical estimates of warming due to forest cover loss under-estimate warming or mis-attribute warming to local change, where non-local changes also influence the pattern of temperature warming.

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Quantifying the Relative Importance of Direct and Indirect Biophysical Effects of Deforestation on Surface Temperature and Teleconnections

Cited by 83 publications

References 53 publications

Characteristics, drivers and feedbacks of global greening

Characteristics, drivers and feedbacks of global greening

Quantifying the Actual Impacts of Forest Cover Change on Surface Temperature in Guangdong, China

Forest loss in Brazil increases maximum temperatures within 50 km

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