Liu Yaling

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Liu
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Yaling
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  • Article
    Evapotranspiration in Northern Eurasia : impact of forcing uncertainties on terrestrial ecosystem model estimates
    (John Wiley & Sons, 2015-04-03) Liu, Yaling ; Zhuang, Qianlai ; Miralles, Diego ; Pan, Zhihua ; Kicklighter, David W. ; Zhu, Qing ; He, Yujie ; Chen, Jiquan ; Tchebakova, Nadja M. ; Sirin, Andrey ; Niyogi, Dev ; Melillo, Jerry M.
    The ecosystems in Northern Eurasia (NE) play an important role in the global water cycle and the climate system. While evapotranspiration (ET) is a critical variable to understand this role, ET over this region remains largely unstudied. Using an improved version of the Terrestrial Ecosystem Model with five widely used forcing data sets, we examine the impact that uncertainties in climate forcing data have on the magnitude, variability, and dominant climatic drivers of ET for the period 1979–2008. Estimates of regional average ET vary in the range of 241.4–335.7 mm yr−1 depending on the choice of forcing data. This range corresponds to as much as 32% of the mean ET. Meanwhile, the spatial patterns of long-term average ET across NE are generally consistent for all forcing data sets. Our ET estimates in NE are largely affected by uncertainties in precipitation (P), air temperature (T), incoming shortwave radiation (R), and vapor pressure deficit (VPD). During the growing season, the correlations between ET and each forcing variable indicate that T is the dominant factor in the north and P in the south. Unsurprisingly, the uncertainties in climate forcing data propagate as well to estimates of the volume of water available for runoff (here defined as P-ET). While the Climate Research Unit data set is overall the best choice of forcing data in NE according to our assessment, the quality of these forcing data sets remains a major challenge to accurately quantify the regional water balance in NE.
  • Article
    Aseismic transient slip on the Gofar transform fault, East Pacific Rise
    (National Academy of Sciences, 2020-04-28) Liu, Yajing ; McGuire, Jeffrey J. ; Behn, Mark D.
    Oceanic transform faults display a unique combination of seismic and aseismic slip behavior, including a large globally averaged seismic deficit, and the local occurrence of repeating magnitude (M) ∼6 earthquakes with abundant foreshocks and seismic swarms, as on the Gofar transform of the East Pacific Rise and the Blanco Ridge in the northeast Pacific Ocean. However, the underlying mechanisms that govern the partitioning between seismic and aseismic slip and their interaction remain unclear. Here we present a numerical modeling study of earthquake sequences and aseismic transient slip on oceanic transform faults. In the model, strong dilatancy strengthening, supported by seismic imaging that indicates enhanced fluid-filled porosity and possible hydrothermal circulation down to the brittle–ductile transition, effectively stabilizes along-strike seismic rupture propagation and results in rupture barriers where aseismic transients arise episodically. The modeled slow slip migrates along the barrier zones at speeds ∼10 to 600 m/h, spatiotemporally correlated with the observed migration of seismic swarms on the Gofar transform. Our model thus suggests the possible prevalence of episodic aseismic transients in M ∼6 rupture barrier zones that host active swarms on oceanic transform faults and provides candidates for future seafloor geodesy experiments to verify the relation between aseismic fault slip, earthquake swarms, and fault zone hydromechanical properties.
  • Article
    Performance of solar-induced chlorophyll fluorescence in estimating water-use efficiency in a temperate forest
    (MDPI AG, 2018-05-20) Lu, Xiaoliang ; Liu, Zhunqiao ; Zhou, Yuyu ; Liu, Yaling ; Tang, Jianwu
    Water-use efficiency (WUE) is a critical variable describing the interrelationship between carbon uptake and water loss in land ecosystems. Different WUE formulations (WUEs) including intrinsic water use efficiency (WUEi), inherent water use efficiency (IWUE), and underlying water use efficiency (uWUE) have been proposed. Based on continuous measurements of carbon and water fluxes and solar-induced chlorophyll fluorescence (SIF) at a temperate forest, we analyze the correlations between SIF emission and the different WUEs at the canopy level by using linear regression (LR) and Gaussian processes regression (GPR) models. Overall, we find that SIF emission has a good potential to estimate IWUE and uWUE, especially when a combination of different SIF bands and a GPR model is used. At an hourly time step, canopy-level SIF emission can explain as high as 65% and 61% of the variances in IWUE and uWUE. Specifically, we find that (1) a daily time step by averaging hourly values during daytime can enhance the SIF-IWUE correlations, (2) the SIF-IWUE correlations decrease when photosynthetically active radiation and air temperature exceed their optimal biological thresholds, (3) a low Leaf Area Index (LAI) has a negative effect on the SIF-IWUE correlations due to large evaporation fluxes, (4) a high LAI in summer also reduces the SIF-IWUE correlations most likely due to increasing scattering and (re)absorption of the SIF signal, and (5) the observation time during the day has a strong impact on the SIF-IWUE correlations and SIF measurements in the early morning have the lowest power to estimate IWUE due to the large evaporation of dew. This study provides a new way to evaluate the stomatal regulation of plant-gas exchange without complex parameterizations.
  • Article
    Comparison of phenology estimated from reflectance-based indices and solar-induced chlorophyll fluorescence (SIF) observations in a temperate forest using GPP-based phenology as the standard
    (MDPI AG, 2018-06-13) Lu, Xiaoliang ; Liu, Zhunqiao ; Zhou, Yuyu ; Liu, Yaling ; An, Shuqing ; Tang, Jianwu
    We assessed the performance of reflectance-based vegetation indices and solar-induced chlorophyll fluorescence (SIF) datasets with various spatial and temporal resolutions in monitoring the Gross Primary Production (GPP)-based phenology in a temperate deciduous forest. The reflectance-based indices include the green chromatic coordinate (GCC), field measured and satellite remotely sensed Normalized Difference Vegetation Index (NDVI); and the SIF datasets include ground-based measurement and satellite-based products. We found that, if negative impacts due to coarse spatial and temporal resolutions are effectively reduced, all these data can serve as good indicators of phenological metrics for spring. However, the autumn phenological metrics derived from all reflectance-based datasets are later than the those derived from ground-based GPP estimates (flux sites). This is because the reflectance-based observations estimate phenology by tracking physiological properties including leaf area index (LAI) and leaf chlorophyll content (Chl), which does not reflect instantaneous changes in phenophase transitions, and thus the estimated fall phenological events may be later than GPP-based phenology. In contrast, we found that SIF has a good potential to track seasonal transition of photosynthetic activities in both spring and fall seasons. The advantage of SIF in estimating the GPP-based phenology lies in its inherent link to photosynthesis activities such that SIF can respond quickly to all factors regulating phenological events. Despite uncertainties in phenological metrics estimated from current spaceborne SIF observations due to their coarse spatial and temporal resolutions, dates in middle spring and autumn—the two most important metrics—can still be reasonably estimated from satellite SIF. Our study reveals that SIF provides a better way to monitor GPP-based phenological metrics.
  • Article
    A large-scale methane model by incorporating the surface water transport
    (John Wiley & Sons, 2016-06-28) Lu, Xiaoliang ; Zhuang, Qianlai ; Liu, Yaling ; Zhou, Yuyu ; AghaKouchak, Amir
    The effect of surface water movement on methane emissions is not explicitly considered in most of the current methane models. In this study, a surface water routing was coupled into our previously developed large-scale methane model. The revised methane model was then used to simulate global methane emissions during 2006–2010. From our simulations, the global mean annual maximum inundation extent is 10.6 ± 1.9 km2 and the methane emission is 297 ± 11 Tg C/yr in the study period. In comparison to the currently used TOPMODEL-based approach, we found that the incorporation of surface water routing leads to 24.7% increase in the annual maximum inundation extent and 30.8% increase in the methane emissions at the global scale for the study period, respectively. The effect of surface water transport on methane emissions varies in different regions: (1) the largest difference occurs in flat and moist regions, such as Eastern China; (2) high-latitude regions, hot spots in methane emissions, show a small increase in both inundation extent and methane emissions with the consideration of surface water movement; and (3) in arid regions, the new model yields significantly larger maximum flooded areas and a relatively small increase in the methane emissions. Although surface water is a small component in the terrestrial water balance, it plays an important role in determining inundation extent and methane emissions, especially in flat regions. This study indicates that future quantification of methane emissions shall consider the effects of surface water transport.