Extending the paleoglaciological record of the southeastern Tibetan Plateau by combining geochronological and high-resolution remote sensing techniques

2020 ◽  
Author(s):  
Arjen P. Stroeven ◽  
Ramona A.A. Schneider ◽  
Robin Blomdin ◽  
Natacha Gribenski ◽  
Marc W. Caffee ◽  
...  
Keyword(s):  
High Resolution ◽  
Tibetan Plateau ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Luminescence Dating ◽  
The Tibetan Plateau ◽  
Exposure Dating ◽  
Southeastern Margin ◽  
Downstream Communities

<p>Paleoglaciological data is a crucial source of information towards insightful paleoclimate reconstructions by providing vital boundary conditions for regional and global climate models. In this context, the Third Pole Environment is considered a key region because it is highly sensitive to global climate change and its many glaciers constitute a diminishing but critical supply of freshwater to downstream communities in SE Asia. Despite its importance, extents of past glaciation on the Tibetan Plateau remain poorly documented or controversial largely because of the lack of well define glacial chronostratigraphies and reconstructions of former glacier extent. This study contributes to a better documentation of the extent and improved resolution of the timing of past glaciations on the southeastern margin of the Tibetan Plateau. We deploy a high-resolution TanDEM-X Digital Elevation Model (12 m resolution) to produce maps of glacial and proglacial fluvial landforms in unprecedented detail. Geomorphological and sedimentological field observations complement the mapping while cosmogenic nuclide exposure dating of quartz samples from boulders on end moraines detail the timing of local glacier expansion. Additionally, samples for optically stimulated luminescence dating were taken from extensive and distinct terraces located in pull-apart basins downstream of the end moraines to determine their formation time. We compare this new dataset with new and published electron spin resonance ages from terraces. Temporal coherence between the different chronometers strengthens the geochronological record while divergence highlights limitations in the applicability of the chronometers to glacial research or in our conceptual understanding of landscape changes in tectonic regions. Results highlight our current understanding of paleoglaciation, landscape development, and paleoclimate on the SE Tibetan Plateau.</p>

scholarly journals Assessing the Performance of CMIP5 Global Climate Models for Simulating Future Precipitation Change in the Tibetan Plateau

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1771 ◽  
Author(s):  
Kun Jia ◽  
Yunfeng Ruan ◽  
Yanzhao Yang ◽  
Chao Zhang
Keyword(s):  
Tibetan Plateau ◽  
Climate Models ◽  
Global Climate ◽  
Precipitation Change ◽  
Multiple Criteria ◽  
Global Climate Models ◽  
The Tibetan Plateau ◽  
Spatial Distributions ◽  
Near Term ◽  
Far Future

In this study, the performance of 33 Coupled Model Intercomparison Project 5 (CMIP5) global climate models (GCMs) in simulating precipitation over the Tibetan Plateau (TP) was assessed using data from 1961 to 2005 by an improved score-based method, which adopts multiple criteria to achieve a comprehensive evaluation. The future precipitation change was also estimated based on the Delta method by selecting the submultiple model ensemble (SMME) in the near-term (2006–2050) and far future (2051–2095) periods under Representative Concentration Pathways (RCP) scenarios RCP4.5 and RCP8.5. The results showed that most GCMs can reasonably simulate the precipitation pattern of an annual cycle; however, all GCMs overestimated the precipitation over TP, especially in spring and summer. The GCMs generally provide good simulations of the temporal characteristics of precipitation, while they did not perform as well in reproducing its spatial distributions. Different assessment criteria lead to inconsistent results; however, the improved rank score method, which adopts multiple criteria, provided a robust assessment of GCMs performance. The future annual precipitation was projected to increase by ~6% in the near-term with respect to the period 1961–2005, whereas increases of 12.3% and 16.7% are expected in the far future under RCP4.5 and RCP8.5 scenarios, respectively. Similar spatial distributions of future precipitation changes can be seen in the near-term and far future periods under the two scenarios, and indicate that the most predominant increases occurred in the north of TP. The results of this study are expected to provide valuable information on climate change, and for water resources and agricultural management in TP.

scholarly journals Comparison of Statistical and Dynamic Downscaling Techniques in Generating High-Resolution Temperatures in China from CMIP5 GCMs

2020 ◽  
Vol 59 (2) ◽  
pp. 207-235 ◽  
Author(s):  
Lei Zhang ◽  
YinLong Xu ◽  
ChunChun Meng ◽  
XinHua Li ◽  
Huan Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
The Tibetan Plateau ◽  
Dynamic Downscaling

AbstractIn aiming for better access to climate change information and for providing climate service, it is important to obtain reliable high-resolution temperature simulations. Systematic comparisons are still deficient between statistical and dynamic downscaling techniques because of their inherent unavoidable uncertainties. In this paper, 20 global climate models (GCMs) and one regional climate model [Providing Regional Climates to Impact Studies (PRECIS)] are employed to evaluate their capabilities in reproducing average trends of mean temperature (Tm), maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature range (DTR), and extreme events represented by frost days (FD) and heat-wave days (HD) across China. It is shown generally that bias of temperatures from GCMs relative to observations is over ±1°C across more than one-half of mainland China. PRECIS demonstrates better representation of temperatures (except for HD) relative to GCMs. There is relatively better performance in Huanghuai, Jianghuai, Jianghan, south Yangzi River, and South China, whereas estimation is not as good in Xinjiang, the eastern part of northwest China, and the Tibetan Plateau. Bias-correction spatial disaggregation is used to downscale GCMs outputs, and bias correction is applied for PRECIS outputs, which demonstrate better improvement to a bias within ±0.2°C for Tm, Tmax, Tmin, and DTR and ±2 days for FD and HD. Furthermore, such improvement is also verified by the evidence of increased spatial correlation coefficient and symmetrical uncertainty, decreased root-mean-square error, and lower standard deviation for reproductions. It is seen from comprehensive ranking metrics that different downscaled models show the most improvement across different climatic regions, implying that optional ensembles of models should be adopted to provide sufficient high-quality climate information.

Evaluation of global climate models for downscaling applications centred over the Tibetan Plateau

2016 ◽  
Vol 37 (2) ◽  
pp. 657-671 ◽  
Author(s):  
Jianwei Xu ◽  
Yanhong Gao ◽  
Deliang Chen ◽  
Linhong Xiao ◽  
Tinghai Ou
Keyword(s):  
Tibetan Plateau ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
The Tibetan Plateau

Effects of the horizontal resolution of climate models on the simulation of extreme hourly precipitation in the Tibetan Plateau and surrounding areas

2021 ◽  
Author(s):  
Qing Bao ◽  
Lei Wang ◽  
Yimin Liu ◽  
Guoxiong Wu ◽  
Jinxiao Li ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Global Climate ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Boreal Summer ◽  
The Tibetan Plateau ◽  
Standard Resolution ◽  
Surrounding Areas

<p>Extreme precipitation events, represented by the extreme hourly precipitation (EHP), often occur in the Tibetan Plateau and surrounding areas (TPS) as a result of the complex topography and unique geographical location of this region and can lead to large losses of human life. Previous studies have shown that the performance of extreme precipitation simulations can be improved by increasing the resolution of the model, although the mechanisms are not yet not clear. In this study, we firstly compared the most recent high-quality satellite precipitation product  with station data from Nepal, which is located on the southern edge of the Tibetan Plateau. The results showed that the GPM dataset can reproduce extreme precipitation well and we therefore used these data as a benchmark for climate models of the TPS. We then evaluated the fidelity of global climate models in the representation of the boreal summer EHP in the TPS using datasets from the CMIP6 High-Resolution Model Intercomparison Project (HighResMIP). We used four global climate models with standard (about 100 km) and enhanced (up to 25 km) resolution configurations to simulate the EHP. The models with a standard resolution largely underestimated the intensity of EHP, especially over the southern edge of the Tibetan Plateau. The EHP can reach up to 50 mm h<sup>−1</sup>in the TPS, whereas the maximum simulated EHP was <35 mm h<sup>−1</sup> for all the standard resolution models. The mean intensity of EHP is about 5.06 mm h<sup>−1</sup> in the GPM satellite products, whereas it was <3 mm h<sup>−1</sup> in standard resolution models. The skill of the simulation of EHP is significantly improved at increased horizontal resolutions. The high-resolution models with a horizontal resolution of 25 km can reproduce the geographical distribution of the intensity of EHP in the TPS. The intensity–frequency distribution of EHP also resembles that from GPM products, showing the same features up to 50 mm h<sup>−1</sup>, although it slightly overestimates heavy precipitation events. Finally, we propose possible physical linkages between the simulation of EHP and the impacts of the resolution of the model and physical processes. Phenomena over the Indian Ocean at different timescales and the diurnal variation of precipitation in the TPS are used to propose possible physical linkages as they may play an important part in the simulation of EHP in the TPS. Further analysis shows that an increase in the horizontal resolution helps to accurately reproduce the features of water vapor transport on days with extreme precipitation, the northward-propagating intraseasonal oscillation over the Indian and western Pacific Ocean monsoon regions in the boreal summer, the intensity and number of tropical cyclones over the southern Asian monsoon regions, and the peak time and amplitude of the diurnal cycle of precipitation. This increase in accuracy contributes to the improvements in the simulation of EHP in the TPS. This study suggests improvements to increase the horizontal resolution of the GCMs and lay a solid foundation for the accurate reproduction and prediction of EHP in the TPS.</p>

scholarly journals Characteristics and Scenarios Projection of Climate Change on the Tibetan Plateau

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Zhenchun Hao ◽  
Qin Ju ◽  
Weijuan Jiang ◽  
Changjun Zhu
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Climate Models ◽  
Global Climate ◽  
Surface Air Temperature ◽  
Global Climate Models ◽  
The Tibetan Plateau ◽  
Intergovernmental Panel ◽  
Temperature And Precipitation ◽  
Ipcc Ar4

The Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4) presents twenty-two global climate models (GCMs). In this paper, we evaluate the ability of 22 GCMs to reproduce temperature and precipitation over the Tibetan Plateau by comparing with ground observations for 1961~1900. The results suggest that all the GCMs underestimate surface air temperature and most models overestimate precipitation in most regions on the Tibetan Plateau. Only a few models (each 5 models for precipitation and temperature) appear roughly consistent with the observations in annual temperature and precipitation variations. Comparatively, GFCM21 and CGMR are able to better reproduce the observed annual temperature and precipitation variability over the Tibetan Plateau. Although the scenarios predicted by the GCMs vary greatly, all the models predict consistently increasing trends in temperature and precipitation in most regions in the Tibetan Plateau in the next 90 years. The results suggest that the temperature and precipitation will both increase in all three periods under different scenarios, with scenario A1 increasing the most and scenario A1B increasing the least.

Extreme Events in High Resolution CMCC Regional and Global Climate Models

2011 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Antonella Sanna ◽  
Edoardo Bucchignani ◽  
Myriam Montesarchio
Keyword(s):  
High Resolution ◽  
Extreme Events ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models

Climate change in the High Mountain Asia simulated with CMIP6 models

2021 ◽  
Author(s):  
Mickaël Lalande ◽  
Martin Ménégoz ◽  
Gerhard Krinner
Keyword(s):  
High Resolution ◽  
Snow Cover ◽  
Climate Models ◽  
Global Climate Models ◽  
Cold Bias ◽  
High Mountain ◽  
The Tibetan Plateau ◽  
Near Surface ◽  
Model Biases ◽  
Snow Cover Extent

<p>The High Mountains of Asia (HMA) region and the Tibetan Plateau (TP), with an average altitude of 4000 m, are hosting the third largest reservoir of glaciers and snow after the two polar ice caps, and are at the origin of strong orographic precipitation. Climate studies over HMA are related to serious challenges concerning the exposure of human infrastructures to natural hazards and the water resources for agriculture, drinking water, and hydroelectricity to whom several hundred million inhabitants of the Indian subcontinent are depending. However, climate variables such as temperature, precipitation, and snow cover are poorly described by global climate models because their coarse resolution is not adapted to the rugged topography of this region. Since the first CMIP exercises, a cold model bias has been identified in this region, however, its attribution is not obvious and may be different from one model to another. Our study focuses on a multi-model comparison of the CMIP6 simulations used to investigate the climate variability in this area to answer the next questions: (1) are the biases in HMA reduced in the new generation of climate models? (2) Do the model biases impact the simulated climate trends? (3) What are the links between the model biases in temperature, precipitation, and snow cover extent? (4) Which climate trajectories can be projected in this area until 2100? An analysis of 27 models over 1979-2014 still show a cold bias in near-surface air temperature over the HMA and TP reaching an annual value of -2.0 °C (± 3.2 °C), associated with an over-extended relative snow cover extent of 53 % (± 62 %), and a relative excess of precipitation of 139 % (± 38 %), knowing that the precipitation biases are uncertain because of the undercatch of solid precipitation in observations. Model biases and trends do not show any clear links, suggesting that biased models should not be excluded in trend and projections analysis, although non-linear effects related to lagged snow cover feedbacks could be expected. On average over 2081-2100 with respect to 1995-2014, for the scenarios SSP126, SSP245, SSP370, and SSP585, the 9 available models shows respectively an increase in annual temperature of 1.9 °C (± 0.5 °C), 3.4 °C (± 0.7 °C), 5.2 °C (± 1.2 °C), and 6.6 °C (± 1.5 °C); a relative decrease in the snow cover extent of 10 % (± 4.1 %), 19 % (± 5 %), 29 % (± 8 %), and 35 % (± 9 %); and an increase in total precipitation of 9 % (± 5 %), 13 % (± 7 %), 19 % (± 11 %), and 27 % (± 13 %). Further analyses will be considered to investigate potential links between the biases at the surface and those at higher tropospheric levels as well as with the topography. The models based on high resolution do not perform better than the coarse-gridded ones, suggesting that the race to high resolution should be considered as a second priority after the developments of more realistic physical parameterizations.</p>

scholarly journals An evaluation of the importance of spatial resolution in a global climate and hydrological model based on the Rhine and Mississippi basin

2017 ◽  
Author(s):  
Imme Benedict ◽  
Chiel C. van Heerwaarden ◽  
Albrecht H. Weerts ◽  
Wilco Hazeleger
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Large Scale ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Scale ◽  
Global Climate Models ◽  
Convective Processes ◽  
Parameter Values

Abstract. The hydrological cycle of river basins can be simulated by combining global climate models (GCMs) and global hydrological models (GHMs). The spatial resolution of these models is restricted by computational resources and therefore limits the processes and level of detail that can be resolved. To further improve simulations of precipitation and river-runoff on a global scale, we assess and compare the benefits of an increased resolution for a GCM and a GHM. We focus on the Rhine and Mississippi basin. Increasing the resolution of a GCM (1.125° to 0.25°) results in more realistic large-scale circulation patterns over the Rhine and an improved precipitation budget. These improvements with increased resolution are not found for the Mississippi basin, most likely because precipitation is strongly dependent on the representation of still unresolved convective processes. Increasing the resolution of vegetation and orography in the high resolution GHM (from 0.5° to 0.05°) shows no significant differences in discharge for both basins, because the hydrological processes depend highly on other parameter values that are not readily available at high resolution. Therefore, increasing the resolution of the GCM provides the most straightforward route to better results. This route works best for basins driven by large-scale precipitation, such as the Rhine basin. For basins driven by convective processes, such as the Mississippi basin, improvements are expected with even higher resolution convection permitting models.

Using PRIMAVERA high-resolution global climate models for European windstorm risk assessment in present and future climates for the (re)insurance industry

2020 ◽  
Author(s):  
Julia Lockwood ◽  
Erika Palin ◽  
Galina Guentchev ◽  
Malcolm Roberts
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Climate Model ◽  
Insurance Industry ◽  
Global Climate ◽  
Storm Track ◽  
Global Climate Models ◽  
Climate Modelling ◽  
Business And Society ◽  
High Resolution Models

<p>PRIMAVERA is a European Union Horizon2020 project about creating a new generation of advanced and well-evaluated high-resolution global climate models, for the benefit of governments, business and society in general. The project has been engaging with several sectors, including finance, transport, and energy, to understand the extent to which any improved process understanding arising from high-resolution global climate modelling can – in turn – help with using climate model output to address user needs.</p><p>In this talk we will outline our work for the finance and (re)insurance industries.  Following consultation with members of the industry, we are using PRIMAVERA climate models to generate a European windstorm event set for use in catastrophe modelling and risk analysis.  The event set is generated from five different climate models, each run at a selection of resolutions ranging from 18-140km, covering the period 1950-2050, giving approximately 1700 years of climate model data in total.  High-resolution climate models tend to have reduced biases in storm track position (which is too zonal in low-resolution climate models) and windstorm intensity.  We will compare the properties of the windstorm footprints and associated risk across the different models and resolutions, to assess whether the high-resolution models lead to improved estimation of European windstorm risk.  We will also compare windstorm risk in present and future climates, to see if a consistent picture emerges between models.  Finally we will address the question of whether the event sets from each PRIMAVERA model can be combined to form a multi-model event set ensemble covering thousands of years of windstorm data.</p>

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