冰川模型及其在古冰川模拟研究中的应用

Glacial models have been widely used in simulating and predicting the impact of climate change on glaciers in the future. With the development of geomorphological mapping, digital elevation models, geochronology, and palaeo-climate records, glacial models have also been used in simulate palaeoglacier evolution and reconstruct palaeo-climate conditions. In this paper, we reviewed the two types of glacial models: landform-ice surface profile models and coupled mass balance-glacial dynamic models, which have been used for palaeo-glacial reconstruction. We first introduced the principles and framework of using these models for palaeoglacier simulation, as well as the methods to calibrate model parameters and validate model outputs using geomorphic evidence. We then summarized the studies and major findings in using glacial models to reconstruct the extent, volume, and equilibrium-line altitude(ELA)of palaeoglaciers, estimate palaeo-climate conditions during different glacial stages, and evaluate the results derived from geochronological datasets on the Tibetan Plateau and its surrounding mountains. The landform-ice surface profile models interpret ice thickness, area, and volume of a palaeoglacier based on the steady-state ice surface profile derived from the principles of ice physics and flow dynamics, as well as the geomorphic landforms to constrain ice boundary(e. g. , moraines)and local heights(e. g. , trimlines). The commonly used model is the one-dimensional flowline model, which has been implemented in Excel and ArcGIS. The landform-ice surface profile models are relatively easy to use but cannot directly derive the palaeo-climate information associated with glacial stages. Indirect methods are necessary for the palaeo-climate reconstruction based on the estimated ELA of the palaeoglacier. The coupled mass balance-glacial dynamic models simulate glacial evolution based on mass balance and ice flow dynamic models using climate data or scenarios. The mass balance of a glacier can be determined by the energy and mass balance model, positive degree-day model, and the ΔT-ΔP empirical relationships at the ELA. The ice dynamic models can be one-dimensional, two-dimensional, and three-dimensional based on model complexity. These models can be used to reconstruct palaeoglaciers based on the steady-state simulation of a set of ΔT-ΔP scenarios and the continuous simulation using long-term climate records, such as the proxy records reconstructed by tree rings, ice cores, and lake sediments, and the climate records simulated by the GCM models. The coupled mass balance-glacial dynamic models require the calibration of a lot of parameters, limiting the use in areas where required data are unavailable. The simulated glaciers have been mainly validated with field-observed geomorphic evidence by visual comparison. Several methods have been developed to validate the simulations by quantifying the overlap-fit percentage or measuring the offset between model-simulated and field-reconstructed ice boundaries for large ice sheets, which also have the potential to be implemented in the reconstruction of mountain glaciers. The coupled mass balance-glacial dynamic models are driven by the climate data or scenarios;thus, these models can be used directly to estimate suitable palaeo-climate conditions associated with glacial evolution. Both landform-ice surface profile and coupled mass balance-glacial dynamic models have been applied to the palaeoglacier reconstructions on the Tibetan Plateau and its surrounding mountains. The studies have been mainly from the marginal mountains on the southern, southeastern, and northeast Tibetan Plateau, whereas few studies have been conducted on the central and northern plateau. In terms of glacial stages, most reconstructions have focused on the Last Glacial Maximum, lacking the reconstructions of other glacial stages. Due to the requirement of long-term climate records, the continuous simulation of glacial evolution based on the coupled mass balance-glacial dynamic models are still in the early stage. Future studies are necessary to continuously improve model structure and efficiency, integrate model input/output with ArcGIS or other GIS packages, encourage the share of source codes and data, and establish standard test datasets for model comparison. The integration of geomorphic evidence to calibrate model parameters and the investigation of the relationships between changing climate systems, glaciated topography, and mass balance during different glacial stages are also critical to improve the applications of glacial models on palaeo-glacial reconstruction. This review provides a solid foundation to promote the applications of glacial models on palaeo-glacial reconstruction and improve the understanding of the extent, evolution, and climate-driven mechanism of palaeoglaciers.