Miaogen Shen

Evaporative cooling over the Tibetan Plateau induced by vegetation growth

Significance Understanding land-surface biophysical feedbacks to the atmosphere is needed if we are to simulate regional climate accurately. In the Arctic, previous studies have shown that enhanced vegetation growth decreases albedo and amplifies warming. In contrast, on the Tibetan Plateau, a statistical model based on in situ observations and decomposition of the surface energy budget suggests that increased vegetation activity may attenuate daytime warming by enhancing evapotranspiration (ET), a cooling process. A regional climate model also simulates daytime cooling when prescribed with increased vegetation activity, but with a magnitude smaller than observed, likely because this model simulates weaker ET enhancement in response to increased vegetation growth. In the Arctic, climate warming enhances vegetation activity by extending the length of the growing season and intensifying maximum rates of productivity. In turn, increased vegetation productivity reduces albedo, which causes a positive feedback on temperature. Over the Tibetan Plateau (TP), regional vegetation greening has also been observed in response to recent warming. Here, we show that in contrast to arctic regions, increased growing season vegetation activity over the TP may have attenuated surface warming. This negative feedback on growing season vegetation temperature is attributed to enhanced evapotranspiration (ET). The extra energy available at the surface, which results from lower albedo, is efficiently dissipated by evaporative cooling. The net effect is a decrease in daily maximum temperature and the diurnal temperature range, which is supported by statistical analyses of in situ observations and by decomposition of the surface energy budget. A daytime cooling effect from increased vegetation activity is also modeled from a set of regional weather research and forecasting (WRF) mesoscale model simulations, but with a magnitude smaller than observed, likely because the WRF model simulates a weaker ET enhancement. Our results suggest that actions to restore native grasslands in degraded areas, roughly one-third of the plateau, will both facilitate a sustainable ecological development in this region and have local climate cobenefits. More accurate simulations of the biophysical coupling between the land surface and the atmosphere are needed to help understand regional climate change over the TP, and possible larger scale feedbacks between climate in the TP and the Asian monsoon system.

Leaf onset in the northern hemisphere triggered by daytime temperature

Recent warming significantly advanced leaf onset in the northern hemisphere. This signal cannot be accurately reproduced by current models parameterized by daily mean temperature (Tmean). Here using in situ observations of leaf unfolding dates (LUDs) in Europe and the United States, we show that the interannual anomalies of LUD during 1982–2011 are triggered by daytime (Tmax) more than by nighttime temperature (Tmin). Furthermore, an increase of 1 °C in Tmax would advance LUD by 4.7 days in Europe and 4.3 days in the United States, more than the conventional temperature sensitivity estimated from Tmean. The triggering role of Tmax, rather than the Tmin or Tmean variable, is also supported by analysis of the large-scale patterns of satellite-derived vegetation green-up in spring in the northern hemisphere (>30°N). Our results suggest a new conceptual framework of leaf onset using daytime temperature to improve the performance of phenology modules in current Earth system models.

Estimating aboveground biomass of grassland having a high canopy cover: an exploratory analysis of in situ hyperspectral data

To improve the estimation of aboveground biomass of grassland having a high canopy cover based on remotely sensed data, we measured in situ hyperspectral reflectance and the aboveground green biomass of 42 quadrats in an alpine meadow ecosystem on the Qinghai–Tibetan Plateau. We examined the relationship between aboveground green biomass and the spectral features of original reflectance, first-order derivative reflectance (FDR), and band-depth indices by partial least squares (PLS) regression, as well as the relationship between the aboveground biomass and narrow-band vegetation indices by linear and nonlinear regression analyses. The major findings are as follows. (1) The effective portions of spectra for estimating aboveground biomass of a high-cover meadow were within the red-edge and near infrared (NIR) regions. (2) The band-depth ratio (BDR) feature, using NIR region bands (760–950 nm) in combination with the red-edge bands, yields the best predictive accuracy (RMSE = 40.0 g m−2) for estimating biomass among all the spectral features used as independent variables in the partial least squares regression method. (3) The ratio vegetation index (RVI2) and the normalized difference vegetation index (NDVI2) proposed by Mutanga and Skidmore (Mutanga, O. and Skidmore, A.K., 2004a, Narrow band vegetation indices solve the saturation problem in biomass estimation. International Journal of Remote Sensing, 25, pp. 1–6) are better correlated to the aboveground biomass than other VIs (R 2 = 0.27 for NDVI2 and 0.26 for RVI2), while RDVI, TVI and MTV1 predicted biomass with higher accuracy (RMSE = 37.2 g m−2, 39.9 g m−2 and 39.8 g m−2, respectively). Although all of the models developed in this study are probably acceptable, the models developed in this study still have low accuracy, indicating the urgent need for further efforts.

Spring phenology was not consistently related to winter warming on the Tibetan Plateau

Yu et al. (1) reported that the beginning of vegetation growing season (BGS) of the alpine steppe and meadow on the Tibetan Plateau was delayed since the mid-1990s under warming winter and spring (1). They wrote that “this delay appeared to be related to later fulfillment of chilling requirements,” and they suggested that “continued warming may strengthen this effect or even reverse the advancing trend in spring phenology” (1).

Changes in autumn vegetation dormancy onset date and the climate controls across temperate ecosystems in China from 1982 to 2010

Vegetation phenology is a sensitive indicator of the dynamic response of terrestrial ecosystems to climate change. In this study, the spatiotemporal pattern of vegetation dormancy onset date (DOD) and its climate controls over temperate China were examined by analysing the satellite-derived normalized difference vegetation index and concurrent climate data from 1982 to 2010. Results show that preseason (May through October) air temperature is the primary climatic control of the DOD spatial pattern across temperate China, whereas preseason cumulative precipitation is dominantly associated with the DOD spatial pattern in relatively cold regions. Temporally, the average DOD over Chinas temperate ecosystems has delayed by 0.13 days per year during the past three decades. However, the delay trends are not continuous throughout the 29-year period. The DOD experienced the largest delay during the 1980s, but the delay trend slowed down or even reversed during the 1990s and 2000s. Our results also show that interannual variations in DOD are most significantly related with preseason mean temperature in most ecosystems, except for the desert ecosystem for which the variations in DOD are mainly regulated by preseason cumulative precipitation. Moreover, temperature also determines the spatial pattern of temperature sensitivity of DOD, which became significantly lower as temperature increased. On the other hand, the temperature sensitivity of DOD increases with increasing precipitation, especially in relatively dry areas (e.g. temperate grassland). This finding stresses the importance of hydrological control on the response of autumn phenology to changes in temperature, which must be accounted in current temperature-driven phenological models.

No evidence of continuously advanced green-up dates in the Tibetan Plateau over the last decade

Zhang et al. (1) report that the green-up dates in the Tibetan Plateau (TP) have continuously advanced from 1982 to 2011. They retrieved green-up dates from the multiannual time-series of Normalized Difference Vegetation Index (NDVI) using the method proposed by Piao et al. (2). This method assumes that the nongrowing season NDVI values remain constant among the different years and thus requires sophisticated preprocess of the nongrowing season NDVI. Otherwise, the retrieved green-up dates by the step of polynomial fitting will be negatively biased (i.e., advanced) by the increase in the nongrowing season NDVI (Fig. 1A).

Earlier-Season Vegetation Has Greater Temperature Sensitivity of Spring Phenology in Northern Hemisphere

In recent decades, satellite-derived start of vegetation growing season (SOS) has advanced in many northern temperate and boreal regions. Both the magnitude of temperature increase and the sensitivity of the greenness phenology to temperature–the phenological change per unit temperature–can contribute the advancement. To determine the temperature-sensitivity, we examined the satellite-derived SOS and the potentially effective pre-season temperature (T eff) from 1982 to 2008 for vegetated land between 30°N and 80°N. Earlier season vegetation types, i.e., the vegetation types with earlier SOSmean (mean SOS for 1982–2008), showed greater advancement of SOS during 1982–2008. The advancing rate of SOS against year was also greater in the vegetation with earlier SOSmean even the T eff increase was the same. These results suggest that the spring phenology of vegetation may have high temperature sensitivity in a warmer area. Therefore it is important to consider temperature-sensitivity in assessing broad-scale phenological responses to climatic warming. Further studies are needed to explore the mechanisms and ecological consequences of the temperature-sensitivity of start of growing season in a warming climate.

Asymmetric sensitivity of first flowering date to warming and cooling in alpine plants

Understanding how flowering phenology responds to warming and cooling (i.e., symmetric or asymmetric response) is needed to predict the response of flowering phenology to future climate change that will happen with the occurrence of warm and cold years superimposed upon a long-term trend. A three-year reciprocal translocation experiment was performed along an elevation gradient from 3200 m to 3800 m in the Tibetan Plateau for six alpine plants. Transplanting to lower elevation (warming) advanced the first flowering date (FFD) and transplanting to higher elevation (cooling) had the opposite effect. The FFD of early spring flowering plants (ESF) was four times less sensitive to warming than to cooling (by −2.1 d/°C and 8.4 d/°C, respectively), while midsummer flowering plants (MSF) were about twice as sensitive to warming than to cooling (−8.0 d/°C and 4.9 d/°C, respectively). Compared with pooled warming and cooling data, warming alone significantly underpredicted 3.1 d/°C for ESF and overestimated 1.7 d/°...

Can EVI-derived land-surface phenology be used as a surrogate for phenology of canopy photosynthesis?

Canopy phenology plays a prominent role in determining the timing and magnitude of carbon uptake by many ecosystems. The Moderate Resolution Imaging Spectroradiometer (MODIS) Global Land Cover Dynamics product developed from the enhanced vegetation index (EVI) provides broad spatial and temporal coverage of land-surface phenology (LSP), and may serve as a useful proxy for the phenology of canopy photosynthesis. Here, we compare the MODIS growing season start and end dates (SOS and EOS) with the seasonal phenology of canopy photosynthesis estimated using the eddy covariance approach. Using 153 site-years obtained from the Ameriflux database, we calculated the SOS and EOS of gross primary production (GPP) and canopy photosynthesis capacity (CPC) for seven different boreal and temperate vegetation types. CPC is GPP at maximum radiation, estimated by fitting half-hourly GPP and radiation to a rectangular hyperbolic function. We found large mean absolute differences of up to 53 days, depending on vegetation type, between the phenology of canopy development and photosynthesis, indicating that remotely sensed LSP is not a robust surrogate of seasonal changes in GPP, particularly for evergreen needleleaf forests. This limited correspondence of ecosystem carbon uptake with the MODIS LSP product points to the need for improved remotely sensed proxies of GPP phenology.

Earlier Vegetation Green-Up Has Reduced Spring Dust Storms

The observed decline of spring dust storms in Northeast Asia since the 1950s has been attributed to surface wind stilling. However, spring vegetation growth could also restrain dust storms through accumulating aboveground biomass and increasing surface roughness. To investigate the impacts of vegetation spring growth on dust storms, we examine the relationships between recorded spring dust storm outbreaks and satellite-derived vegetation green-up date in Inner Mongolia, Northern China from 1982 to 2008. We find a significant dampening effect of advanced vegetation growth on spring dust storms (r = 0.49, p = 0.01), with a one-day earlier green-up date corresponding to a decrease in annual spring dust storm outbreaks by 3%. Moreover, the higher correlation (r = 0.55, p < 0.01) between green-up date and dust storm outbreak ratio (the ratio of dust storm outbreaks to times of strong wind events) indicates that such effect is independent of changes in surface wind. Spatially, a negative correlation is detected between areas with advanced green-up dates and regional annual spring dust storms (r = −0.49, p = 0.01). This new insight is valuable for understanding dust storms dynamics under the changing climate. Our findings suggest that dust storms in Inner Mongolia will be further mitigated by the projected earlier vegetation green-up in the warming world.