Comparison of multiple datasets with gridded precipitation observations over the Tibetan Plateau

You, Qinglong; Min, Jinzhong; Zhang, Wei; Pepin, Nick; Kang, Shichang

doi:10.1007/s00382-014-2310-6

Cited by 165 publications

(107 citation statements)

References 41 publications

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“…2). This overestimate of precipitation over TP in ERA-Interim has been reported in previous studies (Tong et al 2013); it is a common issue for reanalyses (You et al 2015), especially in the southeastern TP where summer convection dominates. Part of these biases may be linked to the imbalance of the hydrological budget in the reanalyses.…”

Section: Uncertainty Of Era-interim Hydrological Variables Over Eamentioning

confidence: 85%

The contributions of local and remote atmospheric moisture fluxes to East Asian precipitation and its variability

et al. 2018

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We investigate the contribution of the local and remote atmospheric moisture fluxes to East Asia (EA) precipitation and its interannual variability during 1979-2012. We use and expand the Brubaker et al. (J Clim 6:1077(J Clim 6: -1089(J Clim 6: ,1993) method, which connects the area-mean precipitation to area-mean evaporation and the horizontal moisture flux into the region. Due to its large landmass and hydrological heterogeneity, EA is divided into five sub-regions: Southeast (SE), Tibetan Plateau (TP), Central East (CE), Northwest (NW) and Northeast (NE). For each region, we first separate the contributions to precipitation of local evaporation from those of the horizontal moisture flux by calculating the precipitation recycling ratio: the fraction of precipitation over a region that originates as evaporation from the same region. Then, we separate the horizontal moisture flux across the region's boundaries by direction. We estimate the contributions of the horizontal moisture fluxes from each direction, as well as the local evaporation, to the mean precipitation and its interannual variability. We find that the major contributors to the mean precipitation are not necessarily those that contribute most to the precipitation interannual variability. Over SE, the moisture flux via the southern boundary dominates the mean precipitation and its interannual variability. Over TP, in winter and spring, the moisture flux via the western boundary dominates the mean precipitation; however, variations in local evaporation dominate the precipitation interannual variability. The western moisture flux is the dominant contributor to the mean precipitation over CE, NW and NE. However, the southern or northern moisture flux or the local evaporation dominates the precipitation interannual variability over these regions, depending on the season. Potential mechanisms associated with interannual variability in the moisture flux are identified for each region. The methods and results presented in this study can be readily applied to model simulations, to identify simulation biases in precipitation that relate to the simulated moisture supplies and transport.

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Section: Uncertainty Of Era-interim Hydrological Variables Over Eamentioning

confidence: 85%

The contributions of local and remote atmospheric moisture fluxes to East Asian precipitation and its variability

et al. 2018

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“…Projecting the changes of climate conditions and assessing their effects on the hydrological regimes are typically affected by various uncertainties, such as data, downscaling methods, hydrological model structure, and parameter sets (Teutschbein, Wetterhall, & Seibert, ; Wilby & Harris, ; You, Min, Zhang, Pepin, & Kang, ). In order to increase the credibility of future results projected by the models in our study, great effort has been done during the baseline period to decrease the uncertainties.…”

Section: Discussionmentioning

confidence: 99%

Hydrological projections of future climate change over the source region of Yellow River and Yangtze River in the Tibetan Plateau: A comprehensive assessment by coupling RegCM4 and VIC model

Lü

Wang

Shao

et al. 2018

Hydrological Processes

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Understanding climate change impacts on hydrological regime and assessing future water supplies are essential to effective water resources management and planning, which is particularly true for the Tibetan Plateau (TP), one of the most vulnerable areas to climate change. In this study, future climate change in the TP was projected for 2041–2060 by a high‐resolution regional climate model, RegCM4, under 3 representative concentration pathways (RCPs): 2.6, 4.5, and 8.5. Response of all key hydrological elements, that is, evapotranspiration, surface run‐off, baseflow, and snowmelt, to future climate in 2 typical catchments, the source regions of Yellow and Yangtze rivers, was further investigated by the variable infiltration capacity microscale hydrological model incorporated with a 2‐layer energy balance snow model and a frozen soil/permafrost algorithm at a 0.25°×0.25° spatial scale. The results reveal that (a) spatial patterns of precipitation and temperature from RegCM4 agree fairly well with the data from China Meteorological Forcing Dataset, indicating that RegCM4 well reproduces historical climatic information and thus is reliable to support future projection; (b) precipitation increase by 0–70% and temperature rise by 1–4 °C would occur in the TP under 3 RCPs. A clear south‐eastern–north‐western spatial increasing gradient in precipitation would be seen. Besides, under RCP8.5, the peak increase in temperature would approach to 4 °C in spring and autumn in the east of the TP; (c) evapotranspiration would increase by 10–60% in 2 source regions due to the temperature rise, surface run‐off and baseflow in higher elevation region would experience larger increase dominantly due to the precipitation increase, and streamflow would display general increases by more than 3% and 5% in the source regions of Yellow and Yangtze rivers, respectively; (d) snowmelt contributes 11.1% and 16.2% to total run‐off in the source regions of Yellow and Yangtze rivers, respectively, during the baseline period. In the source region of Yangtze River, snowmelt run‐off would become more important with increase of 17.5% and 18.3%, respectively, under RCP2.6 and RCP4.5 but decrease of 15.0% under RCP8.5.

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“…A Digital elevation model (DEM) was used as a reference in the interpolation, and thus the dataset can represent climate over the mountainous regions. This dataset has been validated with good quality [37,38] and widely applied to analyze long-term climate change in China (e.g., [39]). We extracted monthly temperature and precipitation estimates over 1976-2013 from the grid where the glaciers are located.…”

Section: Glacier-climate Relationshipmentioning

confidence: 99%

Remote Sensing of Glacier Change in the Central Qinghai-Tibet Plateau and the Relationship with Changing Climate

Ding

et al. 2017

Remote Sensing

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During the past 38 years, glacier change in the DKMD area was dominated by the variation of mean annual temperature, and was influenced by the state of the North Atlantic Oscillation (NAO). The mechanism linking climate variability over the central QTP and the state of NAO is most likely via changes in the strength of westerlies and Siberian High. We found no evidence supporting the role of summer monsoons (Indian summer monsoon and East Asian monsoon) in driving local climate and glacier changes. In addition, El Niño Southern Oscillation (ENSO) may be associated with the extreme weather (snow storm) in October 1986 and 2000 which might have led to significant glacier expansion in the following years. Further research is needed to better understand the physical mechanisms linking NAO, ENSO and climate variability over the mid-latitude central QTP.

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Comparison of multiple datasets with gridded precipitation observations over the Tibetan Plateau

Cited by 165 publications

References 41 publications

The contributions of local and remote atmospheric moisture fluxes to East Asian precipitation and its variability

The contributions of local and remote atmospheric moisture fluxes to East Asian precipitation and its variability

Hydrological projections of future climate change over the source region of Yellow River and Yangtze River in the Tibetan Plateau: A comprehensive assessment by coupling RegCM4 and VIC model

Remote Sensing of Glacier Change in the Central Qinghai-Tibet Plateau and the Relationship with Changing Climate

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