Climate mitigation from vegetation biophysical feedbacks during the past three decades

Zeng, Zhenzhong; Piao, Shilong; Li, Laurent; Zhou, Liming; Ciais, Philippe; Wang, Tao; Li, Yue; Lian, Xu; Wood, Eric F.; Friedlingstein, Pierre; Mao, Jiafu; Estes, Lyndon; Myneni, Ranga B.; Peng, Shushi; Shi, Xiaoying; Seneviratne, Sonia I.; Ying-ping, Wang

doi:10.1038/nclimate3299

Cited by 357 publications

(296 citation statements)

References 46 publications

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“…S23 in the Supplement). This discrepancy positively enlarges the biases in the trends in T a due to the vegetation cooling effect (Zeng et al, 2017;Trigo et al, 2015). This effect is reflected by the negative spatial correlation (r = −0.26, p = 0.00) between the inverted trend in the normalized difference vegetation index and the biases in the trend in T a (Fig.…”

Section: Discussionmentioning

confidence: 96%

On the suitability of current atmospheric reanalyses for regional warming studies over China

Zhou

Wang

2018

Atmos. Chem. Phys.

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Abstract. Reanalyses are widely used because they add value to routine observations by generating physically or dynamically consistent and spatiotemporally complete atmospheric fields. Existing studies include extensive discussions of the temporal suitability of reanalyses in studies of global change. This study adds to this existing work by investigating the suitability of reanalyses in studies of regional climate change, in which land-atmosphere interactions play a comparatively important role. In this study, surface air temperatures (T a ) from 12 current reanalysis products are investigated; in particular, the spatial patterns of trends in T a are examined using homogenized measurements of T a made at ∼ 2200 meteorological stations in China from 1979 to 2010. The results show that ∼ 80 % of the mean differences in T a between the reanalyses and the in situ observations can be attributed to the differences in elevation between the stations and the model grids. Thus, the T a climatologies display good skill, and these findings rebut previous reports of biases in T a . However, the biases in theT a trends in the reanalyses diverge spatially (standard deviation = 0.15-0.30 • C decade −1 using 1 • × 1 • grid cells). The simulated biases in the trends in T a correlate well with those of precipitation frequency, surface incident solar radiation (R s ) and atmospheric downward longwave radiation (L d ) among the reanalyses (r = −0.83, 0.80 and 0.77; p < 0.1) when the spatial patterns of these variables are considered. The biases in the trends in T a over southern China (on the order of −0.07 • C decade −1 ) are caused by biases in the trends in R s , L d and precipitation frequency on the order of 0.10, −0.08 and −0.06 • C decade −1 , respectively. The biases in the trends in T a over northern China (on the order of −0.12 • C decade −1 ) result jointly from those in L d and precipitation frequency. Therefore, improving the simulation of precipitation frequency and R s helps to maximize the signal component corresponding to regional climate. In addition, the analysis of T a observations helps represent regional warming in ERA-Interim and JRA-55. Incorporating vegetation dynamics in reanalyses and the use of accurate aerosol information, as in the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), would lead to improvements in the modelling of regional warming. The use of the ensemble technique adopted in the twentieth-century atmospheric model ensemble ERA-20CM significantly narrows the uncertainties associated with regional warming in reanalyses (standard deviation = 0.15 • C decade −1 ).

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Section: Discussionmentioning

confidence: 96%

On the suitability of current atmospheric reanalyses for regional warming studies over China

Zhou

Wang

2018

Atmos. Chem. Phys.

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“…Thus, high latitude terrestrial ecosystem productivity is still limited by summer temperatures, which restrict the amount of plant vegetative growth possible in any year. The length and the timing of POS are not only indispensable indicators of Earth's physical systems through altered surface albedo and energy budget (Penuelas et al, 2009;Richardson et al, 2013;Zeng et al, 2017) and maximum C uptake as shown by increased peak-to-trough CO 2 amplitude (Forkel et al, 2016;Gonsamo et al, 2017;Graven et al, 2013;Keeling et al, 1996Keeling et al, , 2005Keenan et al, 2014;Myneni et al, 1997), but also important indicators of ecological functions by providing maximum habitat and forage for animals and synchrony to plant-pollinator interactions (Hegland et al, 2009). The length and the timing of POS are not only indispensable indicators of Earth's physical systems through altered surface albedo and energy budget (Penuelas et al, 2009;Richardson et al, 2013;Zeng et al, 2017) and maximum C uptake as shown by increased peak-to-trough CO 2 amplitude (Forkel et al, 2016;Gonsamo et al, 2017;Graven et al, 2013;Keeling et al, 1996Keeling et al, , 2005Keenan et al, 2014;Myneni et al, 1997), but also important indicators of ecological functions by providing maximum habitat and forage for animals and synchrony to plant-pollinator interactions (Hegland et al, 2009).…”

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confidence: 99%

Peak season plant activity shift towards spring is reflected by increasing carbon uptake by extratropical ecosystems

Gonsamo

Chen

Ooi

2017

Global Change Biology

104

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Climate change is lengthening the growing season of the Northern Hemisphere extratropical terrestrial ecosystems, but little is known regarding the timing and dynamics of the peak season of plant activity. Here, we use 34-year satellite normalized difference vegetation index (NDVI) observations and atmospheric CO concentration and δ C isotope measurements at Point Barrow (Alaska, USA, 71°N) to study the dynamics of the peak of season (POS) of plant activity. Averaged across extratropical (>23°N) non-evergreen-dominated pixels, NDVI data show that the POS has advanced by 1.2 ± 0.6 days per decade in response to the spring-ward shifts of the start (1.0 ± 0.8 days per decade) and end (1.5 ± 1.0 days per decade) of peak activity, and the earlier onset of the start of growing season (1.4 ± 0.8 days per decade), while POS maximum NDVI value increased by 7.8 ± 1.8% for 1982-2015. Similarly, the peak day of carbon uptake, based on calculations from atmospheric CO concentration and δ C data, is advancing by 2.5 ± 2.6 and 4.3 ± 2.9 days per decade, respectively. POS maximum NDVI value shows strong negative relationships (p < .01) with the earlier onset of the start of growing season and POS days. Given that the maximum solar irradiance and day length occur before the average POS day, the earlier occurrence of peak plant activity results in increased plant productivity. Both the advancing POS day and increasing POS vegetation greenness are consistent with the shifting peak productivity towards spring and the increasing annual maximum values of gross and net ecosystem productivity simulated by coupled Earth system models. Our results further indicate that the decline in autumn NDVI is contributing the most to the overall browning of the northern high latitudes (>50°N) since 2011. The spring-ward shift of peak season plant activity is expected to disrupt the synchrony of biotic interaction and exert strong biophysical feedbacks on climate by modifying the surface albedo and energy budget.

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“…Forests cover more than~42 million km 2 in the Northern Hemisphere (~30% of the land surface), and affects local climate mainly through biophysical processes [1][2][3][4]. The biophysical processes (e.g., albedo, evapotranspiration rate (ET) and surface roughness) all have effects on surface energy fluxes, which causes the effects of forests on local climates to be complicated [5].…”

Section: Introductionmentioning

confidence: 99%

Local Effects of Forests on Temperatures across Europe

Tang

Zhao

2018

Remote Sensing

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Forests affect local climate through biophysical processes in terrestrial ecosystems. Due to the spatial and temporal heterogeneity of ecosystems in Europe, climate responses to forests vary considerably with diverse geographic and seasonal patterns. Few studies have used an empirical analysis to examine the effect of forests on temperature and the role of the background climate in Europe. In this study, we aimed to quantitatively determine the effects of forest on temperature in different seasons with MODIS (MODerate-resolution Imaging Spectroradiometer) land surface temperature (LST) data and in situ air temperature measurements. First, we compared the differences in LSTs between forests and nearby open land. Then, we paired 48 flux sites with nearby weather stations to quantify the effects of forests on surface air temperature. Finally, we explored the role of background temperatures on the above forests effects. The results showed that (1) forest in Europe generally increased LST and air temperature in northeastern Europe and decreased LST and air temperature in other areas; (2) the daytime cooling effect was dominate and produced a net cooling effect from forests in the warm season. In the cold season, daytime and nighttime warming effects drove the net effect of forests; (3) the effects of forests on temperatures were mainly negatively correlated with the background temperatures in Europe. Under extreme climate conditions, the cooling effect of forests will be stronger during heatwaves or weaker during cold spring seasons; (4) the background temperature affects the spatiotemporal distribution of differences in albedo and evapotranspiration (forest minus open land), which determines the spatial, seasonal and interannual effects of forests on temperature. The extrapolation of the results could contribute not only to model validation and development but also to appropriate land use policies for future decades under the background of global warming.

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Climate mitigation from vegetation biophysical feedbacks during the past three decades

Cited by 357 publications

References 46 publications

On the suitability of current atmospheric reanalyses for regional warming studies over China

On the suitability of current atmospheric reanalyses for regional warming studies over China

Peak season plant activity shift towards spring is reflected by increasing carbon uptake by extratropical ecosystems

Local Effects of Forests on Temperatures across Europe

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