Chunqiao Song

Accelerated lake expansion on the Tibetan Plateau in the 2000s: Induced by glacial melting or other processes?

ccelerated lake expansion in the 2000s has been confirmed by both dramatic lake-area increases (for 312 lakes larger than 10 km2) derived from optical images, and rapid water-level rises (for 117 lakes with water-level data) measured by satellite altimetry. However, the underlying climate causes remain unclear. This paper analyzes the relationship between the water-level changes of lakes on the plateau and the potential driving factors, such as the glacier meltwater supply and a dependency on precipitation and runoff over the whole plateau and in each zone. The results show that the rates of change of non-glacier-fed lakes in the 2000s were as high as those of glacier-fed lakes across the whole plateau and the lake-level changes were closely associated with the lake supply coefficients (the basin/lake area ratio). The lake variations agreed well with the spatial pattern of precipitation changes. However, in different zones, especially at around 33°N north of the plateau, glacier-fed lakes did exhibit faster lake level increases than no-glacier-fed lakes, indicating that the presence of a glacier meltwater supply augmented the precipitation-driven lake expansions in these areas. Despite the absence of quantitative modeling due to limited data availability, this study provides qualitative support that the lake expansions on the Tibetan Plateau in the 2000s have been driven primarily by changes in precipitation and evapotranspiration and not solely by the effect of glacier wastage.

Unified fusion of remote-sensing imagery: generating simultaneously high-resolution synthetic spatial–temporal–spectral earth observations

Current satellite remote-sensing systems compromise between spatial resolution and spectral and/or temporal resolution, which potentially limits the use of remotely sensed data in various applications. Image fusion processes, including spatial and spectral fusion (SSF) and spatial and temporal fusion (STF), provide powerful tools for addressing these technological limitations. Although SSF and STF have been extensively studied separately, they have not yet been integrated into a unified framework to generate synthetic satellite images with high spatial, temporal and spectral resolution. By formulating these two types of fusion into one general problem, i.e. super resolving a low spatial resolution image with a high spatial resolution image acquired under different conditions (e.g. at different times and/or in different acquisition bands), this letter proposes a notion of unified fusion that can accomplish both SSF and STF in one process. A Bayesian framework is subsequently developed to implement SSF, STF and unified fusion to generate ‘virtual sensor’ data, characterized by high spatial, temporal and spectral resolution simultaneously. The proposed method was then applied to the fusion of Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat Enhanced Thematic Mapper Plus (ETM+) images of the Hong Kong area, with the average spatial correlation coefficient exceeding 0.9 for near infrared–red–green bands between the fused result and the input Landsat image and with good preservation of the MODIS spectral properties.

Contrasting evolution patterns between glacier-fed and non-glacier-fed lakes in the Tanggula Mountains and climate cause analysis

High-altitude lakes in the Tibetan Plateau (TP) showed strong spatio-temporal variability during past decades. The lake dynamics could be associated with several important factors including lake type, supply of glacial meltwater, local climate variations. It is important to differentiate these factors when analyzing the driving forces of lakes dynamics. With a focus on lakes over the Tanggula Mountains of the central TP, this study investigates the temporal evolution patterns of lake area and water level of different types: glacier-fed closed lake, non-glacier-fed closed lake and upstream lake (draining into closed lakes). We collected all available Landsat archive data and quantified the inter-annual variability of lake extents. Results reveal accelerated expansions of both glacier-fed and non-glacier-fed lakes during 1970s–2013, and different temporal patterns of the two types of lakes: the non-glacier-fed lakes displayed a batch-wise growth pattern, with obvious growth in 2002, 2005 and 2011 and slight changes in other years, while glacier-fed lakes showed steady expanding tendency. The contrasting patterns are confirmed by distinct lake level changes between the two groups derived from satellite altimetry during 2003–2013. The upstream lakes remained basically stable due to natural drainage regulation. The intermittent expansions for non-glacier-fed lakes are found to be related to excessive precipitation events and positive “precipitation–evaporation”. In contrast, glacier-fed lake changes showed weak correlations with precipitation variations, which implies a joint contribution from glacial meltwater to water budgets. Our study suggests that glacial meltwater supply may have an equivalent influence on lake growth with precipitation/evaporation in the study area.

Reconstruction of Time-Series MODIS LST in Central Qinghai-Tibet Plateau Using Geostatistical Approach

We present an approach for reconstructing land surface temperature (LST) time series over mountainous areas based on Regression Kriging (RK) technique and a data processing scheme for filtering out LST noise and artifacts. A total of 1462 eight-day composite Moderate Resolution Imaging Spectroradiometer LST images over central Qinghai-Tibet Plateau over 2003-2010 are reconstructed. The regression model includes four auxiliary predictors-latitude, longitude, elevation, and NDVI-which are proven to be a good estimator for the 8-day LST. Comparison of ground surface temperature (GST) measurements at eight meteorological stations with the raw and reconstructed LST series shows that the reconstruction strategy can effectively recover complete high-quality over-land LST maps and significantly improve the consistency between LST and GST.

The potential of GRACE gravimetry to detect the heavy rainfall‐induced impoundment of a small reservoir in the upper Yellow River

Artificial reservoirs are important indicators of anthropogenic impacts on environments, and their cumulative influences on the local water storage will change the gravity signal. However, because of their small signal size, such gravity changes are seldom studied using satellite gravimetry from the Gravity Recovery and Climate Experiment (GRACE). Here we investigate the ability of GRACE to detect water storage changes in the Longyangxia Reservoir (LR), which is situated in the upper main stem of the Yellow River. Three different GRACE solutions from the CSR, GFZ, and JPL with three different processing filters are compared here. We find that heavy precipitation in the summer of 2005 caused the LR water storage to increase by 37.9 m in height, which is equivalent to 13.0 Gt in mass, and that the CSR solutions with a DDK4 filter show the best performance in revealing the synthetic gravity signals. We also obtain 109 pairs of reservoir inundation area measurements from satellite imagery and water level changes from laser altimetry and in situ observations to derive the area-height ratios for the LR. The root mean square of GRACE series in the LR is reduced by 39% after removing synthetic signals caused by mass changes in the LR or by 62% if the GRACE series is further smoothed. We conclude that GRACE data show promising potential in detecting water storage changes in this ∼400 km2 reservoir and that a small signal size is not a restricting factor for detection using GRACE data.

Identifying the Relative Contributions of Climate and Grazing to Both Direction and Magnitude of Alpine Grassland Productivity Dynamics from 1993 to 2011 on the Northern Tibetan Plateau

Alpine grasslands on the Tibetan Plateau are claimed to be sensitive and vulnerable to climate change and human disturbance. The mechanism, direction and magnitude of climatic and anthropogenic influences on net primary productivity (NPP) of various alpine pastures remain under debate. Here, we simulated the potential productivity (with only climate variables being considered as drivers; NPPP) and actual productivity (based on remote sensing dataset including both climate and anthropogenic drivers; NPPA) from 1993 to 2011. We denoted the difference between NPPP and NPPA as NPPpc to quantify how much forage can be potentially consumed by livestock. The actually consumed productivity (NPPac) by livestock were estimated based on meat production and daily forage consumption per standardized sheep unit. We hypothesized that the gap between NPPpc and NPPac (NPPgap) indicates the direction of vegetation dynamics, restoration or degradation. Our results show that growing season precipitation rather than temperature significantly relates with NPPgap, although warming was significant for the entire study region while precipitation only significantly increased in the northeastern places. On the Northern Tibetan Plateau, 69.05% of available alpine pastures showed a restoration trend with positive NPPgap, and for 58.74% of alpine pastures, stocking rate is suggested to increase in the future because of the positive mean NPPgap and its increasing trend. This study provides a potential framework for regionally regulating grazing management with aims to restore the degraded pastures and sustainable management of the healthy pastures on the Tibetan Plateau.

Recent Changes in Land Water Storage and its Contribution to Sea Level Variations

Sea level rise is generally attributed to increased ocean heat content and increased rates glacier and ice melt. However, human transformations of Earth’s surface have impacted water exchange between land, atmosphere, and ocean, ultimately affecting global sea level variations. Impoundment of water in reservoirs and artificial lakes has reduced the outflow of water to the sea, while river runoff has increased due to groundwater mining, wetland and endorheic lake storage losses, and deforestation. In addition, climate-driven changes in land water stores can have a large impact on global sea level variations over decadal timescales. Here, we review each component of negative and positive land water contribution separately in order to highlight and understand recent changes in land water contribution to sea level variations.

Recent dramatic variations of China's two largest freshwater lakes: natural process or influenced by the Three Gorges Dam?

Natural Process or Influenced by the Three Gorges Dam? F et al. (hereafter referred to as Feng) report that the dramatic decreasing trends (3.3 and 3.6%, p < 0.05) in the inundation area of two largest freshwater lakes in China (Poyang Lake and Dongting Lake) during 2000−2009 are highly attributed to the impoundment of the Three Gorges Dam (TGD). The lake inundation area was retrieved from time-series cloud-free MODIS images by using the method proposed by Feng et al. As pointed out in Feng, the coverage of employed 10-year MODIS data is not long enough to derive reliable the so-called long-term trends of lake changes. Particularly, the variable “inundation area” of the two lakes shows considerable interseasonal and interannual variability (shown in Figure.1A and B and also Figure 2 of Feng), thus the estimated linear trends based on limited records are highly sensitive to outliers, the starting and ending values. For example, as shown in Figure.1A (lake area derived from results by Feng et al.), the decreasing trend of Poyang Lake area is statistically significant during 2000−2009; however the trend becomes statistically insignificant when just extending the period to 2010 (−1.9%/yr, p > 0.1). In essential the decreasing trend over the study decade is amplified by the extremely large area in 2002. Furthermore, the contrast of lake areas before and after the dam’s impoundment relies greatly on the representation of lake situations during the short period of 2000−2002, considering the dramatically large inundation areas in 2002. Long-term water level changes of the two lakes based on time-series satellite radar altimetry data (Figure.1B) show that Dongting Lake is at a state of peak in 2002. The water level data are provided by Laboratoired’ Etudes en Geóphysique et Oceánographie Spatiales (LEGOS), and the accuracy has been demonstrated in previous studies, with a root-mean-square error of centimeter level. The water-level changes also agree well with area changes shown in Feng. The time series of water-level data show there is no significant declining trend in water level of Dongting Lake

Grazing exclusion by fencing non-linearly restored the degraded alpine grasslands on the Tibetan Plateau

Resilience is an important aspect of the non-linear restoration of disturbed ecosystems. Fenced grassland patches on the northern Tibetan Plateau can be used to examine the resistance and resilience of degraded alpine grasslands to grazing and to a changing climate. To examine the non-linearity of restoration, we used moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) as a proxy for productivity during a ten-year restoration by fencing. Degraded alpine grasslands exhibited three restoration trajectories: an equilibrium in meadows, a non-linear increase across steppes, and an abrupt impulse in desert-steppes following a slight increase in productivity. Combined with weather conditions, the ten-year grazing exclusion has successfully enhanced the NDVI on the most degraded steppes, but did not do so efficiently on either meadows or desert-steppes. Warming favors the NDVI enhancement of degraded meadows, but higher temperatures limited the restoration of degraded steppes and desert-steppes. Precipitation is necessary to restore degraded alpine grasslands, but more precipitation might be useless for meadows due to lower temperatures and for desert-steppes due to limitations caused by the small species pool. We suggest that detailed field observations of community compositional changes are necessary to better understand the mechanisms behind such non-linear ecological restorations.

Reconstructing complete MODIS LST based on temperature gradients in northeastern Qinghai-Tibet Plateau

MODIS LST products provided by NASA may suffer from missing values and noises from various sources, which can degrade the LST quality and hamper its efficient applications. The paper presents an algorithm to reconstruct complete LST image based on regression analysis of LST with elevation in each sliding window, after filtering low-quality and unreliable pixels. Comparison of reconstructed LST with meteorological temperature measurements (T) indicates that LST is significantly correlated with T with an average correlation coefficient of 0.96 and a mean absolute difference (MAE) of 2.02 K. LSTs and Ts show no significant differences at monthly and yearly scale. The differences between LSTs and Ts have certain correlations with their different spatial and temporal definitions; however some residual noises existing in the reconstructed LSTs indicate more meticulous algorithm needed to work out more accurate RS-LST data.