Types Of Frozen Ground Research Articles

The Minimum Temperature Outweighed the Maximum Temperature in Determining Plant Growth over the Tibetan Plateau from 1982 to 2017

The Tibetan Plateau (TP) plays a crucial role in the climate change of China as well as global climate change. It is therefore of great practical significance to study vegetation and its dynamic changes for regional ecological protection. The combination of a dry climate and notable temperature disparities can lead to intricate effects on the region’s vegetation. However, there are few studies exploring the complex effects of diurnal temperature variations on vegetation growth that differ from the effects of mean temperature on the TP, especially under different frozen ground types. Based on the long-time series maximum temperature (Tmax), minimum temperature (Tmin), and Normalized Difference Vegetation Index (NDVI) of the TP, we conducted a comparative study of the warming effects on plant growth under different frozen types. The results exhibit that it warms up faster at night (0.223 °C de−1; p < 0.01) than during the day (0.06 °C de−1; p < 0.01), resulting in a significant decrease in the temperature difference between day and night (−0.078 °C de−1; p < 0.01) in the past few decades. The principal finding of this paper is that Tmin is the dominant temperature indicator for vegetation growth on the TP, which dominates 63.3% of the area for NDVI and 61.4% of the area for GPP, respectively. The results further identify a stronger correlation between air temperature and vegetation growth in seasonal frozen grounds (R = 0.68, p < 0.01) and permafrost regions (R = 0.7, p < 0.01) compared to unfrozen grounds (R = 0.58, p < 0.01). Moreover, the physiological mechanism underlying the asymmetric influence of Tmin and Tmax on vegetation growth is further elucidated in this study. Given that future climate changes are expected to exacerbate these changes, it is imperative to explore additional avenues in pursuit of potential mechanisms that can offer adaptive strategies for safeguarding the ecology of the TP.

Different Responses of Vegetation to Frozen Ground Degradation in the Source Region of the Yellow River from 1980 to 2018

Frozen ground degradation under a warming climate profoundly influences the growth of alpine vegetation in the source region of the Qinghai-Tibet Plateau. This study investigated spatiotemporal variations in the frozen ground distribution, the active layer thickness (ALT) of permafrost (PF) soil and the soil freeze depth (SFD) in seasonally frozen soil from 1980 to 2018 using the temperature at the top of permafrost (TTOP) model and Stefan equation. We compared the effects of these variations on vegetation growth among different frozen ground types and vegetation types in the source region of the Yellow River (SRYR). The results showed that approximately half of the PF area (20.37% of the SRYR) was projected to degrade into seasonally frozen ground (SFG) during the past four decades; furthermore, the areal average ALT increased by 3.47 cm/yr, and the areal average SFD decreased by 0.93 cm/yr from 1980 to 2018. Accordingly, the growing season Normalized Difference Vegetation Index (NDVI) presented an increasing trend of 0.002/10yr, and the increase rate and proportion of areas with NDVI increase were largest in the transition zone where PF degraded to SFG (the PF to SFG zone). A correlation analysis indicated that variations in ALT and SFD in the SRYR were significantly correlated with increases of NDVI in the growing season. However, a rapid decrease in SFD (< −1.4 cm/10yr) could have reduced the soil moisture and, thus, decreased the NDVI. The NDVI for most vegetation types exhibited a significant positive correlation with ALT and a negative correlation with SFD. However, the steppe NDVI exhibited a significant negative correlation with the SFD in the PF to SFG zone but a positive correlation in the SFG zone, which was mainly limited by water condition because of different change rates of the SFD.

Remote sensing spatiotemporal patterns of frozen soil and the environmental controls over the Tibetan Plateau during 2002–2016

The changing climate is affecting the frozen soil at an unprecedented rate across the Northern Hemisphere. However, due to sparse ground measurements, the changes of frozen soil and the environmental controls over the vast cryosphere are still unclear, such as in the Tibetan Plateau (TP). In this study, a process-based model solely driven by satellite remote sensing data is employed to investigate the spatiotemporal changes of seasonally frozen ground and permafrost over the entire TP (~3 million km2) during 2002–2016 at a spatial resolution of 1 km. Comprehensive validations against in situ observations of frozen ground types, mean annual ground temperature, active layer thickness, soil temperature, and frozen depth at 608 boreholes and 109 meteorological stations demonstrate an overall satisfactory performance of the model in reproducing the spatial pattern and temporal evolution of the frozen soil in the region. Spatially, land surface temperature (LST; both in-season and off-season) primarily controls the frozen ground types and frozen depth, with seasonally frozen ground and permafrost covering ~56% and ~ 37% of the plateau, respectively. The estimated spatial-averaged annual maximum soil freeze depth (SFD) is ~1.29 m, and the annual maximum active layer thickness (ALT) of permafrost is ~1.85 m. Temporally, ALT shows an overall increasing trend at an average rate of +3.17 cm yr−1, while SFD exhibits both decreasing (at ~62% areas) and increasing (at ~38% areas) trends in the region. Again, LST is found to be the dominant factor that controls the temporal changes in both SFD and ALT while precipitation (i.e., both rainfall and snowfall) plays an important (especially in more arid areas and regions near the lower limit of permafrost) but secondary role. Our results demonstrate the advantages of the satellite-based method in frozen soil simulations over large scales with complex topography and landscape and highlight the important roles of both temperature and precipitation in shaping the frozen soil patterns on the TP or other cold, dry regions.

Satellite-based simulation of soil freezing/thawing processes in the northeast Tibetan Plateau

Accurate quantification of the distribution and characteristics of frozen soil is critical for evaluating the impacts of climate change on the ecological and hydrological systems in high-latitude and -altitude regions, such as the Tibetan Plateau (TP). However, field observations have been limited by the harsh climate and complex terrain on the plateau, which greatly restricts our ability to predict the existence of and variations in frozen soils, especially at the regional scale. Here, we present a study relying solely on satellite data to drive process-based simulation of soil freeze-thaw processes. Modifications are made to an existing process-based model (Geomorphology-Based Eco-Hydrological Model, GBEHM) such that the model is fully adaptable to remote sensing inputs. The developed model fed with a combination of MODIS, TRMM and AIRX3STD satellite products is applied in the upper Yellow River Basin (coverage of ~2.54 × 105 km2) in the northeast TP and validated against field observations of freezing and thawing front depths (Dft) and soil temperature (Tsoil) at 54 China Meteorological Administration (CMA) stations, as well as frozen-ground types at 22 boreholes. Results indicate that the developed model performs reasonably well in simulating Dft (R2 = 0.69; mean bias = −0.03 m) and Tsoil (station averaged R2 and mean bias range between 0.90–0.96 and −0.51~−0.14 °C at eight observational depths, respectively), and outperforms the original GBEHM forced with ground-measured meteorological variables. The frozen-ground types are also (in general) accurately identified by the satellite-based approach, except for a few permafrost boreholes located near the permafrost boundary regions. Additionally, we also demonstrate the importance of considering dynamic soil water content in frozen soil simulation: We find that a static-soil-moisture assumption (as used in previous studies) would lead to biased soil temperature estimates by >0.5 °C. Our study demonstrates the value of using satellite data in frozen-soil simulation over complex landscapes, potentially leading to a greater understanding of soil freeze-thaw processes at the regional scale.

Hydrological insights from hydrogen and oxygen isotopes in Source Area of the Yellow River, east-northern part of Qinghai–Tibet Plateau

Analyses of stable (D and 18O) and radioactive (T) isotopes of different waters were applied to obtain the hydrological information in watersheds with different frozen ground types in the Source Area of the Yellow River, northeastern of Qinghai–Tibet Plateau in 2014 and 2016. Variations of oxygen and hydrogen isotope ratios, statistically higher tritium concentrations and lower water yields in thaw lakes confirm disparate sources of recharges to thaw lakes and other lakes. Thaw lakes at various stages of evolution influence the surface and subsurface water systems differently.

LGM permafrost distribution: how well can the latest PMIP multi-model ensembles perform reconstruction?

Abstract. Here, global-scale frozen ground distribution from the Last Glacial Maximum (LGM) has been reconstructed using multi-model ensembles of global climate models, and then compared with evidence-based knowledge and earlier numerical results. Modeled soil temperatures, taken from Paleoclimate Modelling Intercomparison Project phase III (PMIP3) simulations, were used to diagnose the subsurface thermal regime and determine underlying frozen ground types for the present day (pre-industrial; 0 kya) and the LGM (21 kya). This direct method was then compared to an earlier indirect method, which categorizes underlying frozen ground type from surface air temperature, applying to both the PMIP2 (phase II) and PMIP3 products. Both direct and indirect diagnoses for 0 kya showed strong agreement with the present-day observation-based map. The soil temperature ensemble showed a higher diversity around the border between permafrost and seasonally frozen ground among the models, partly due to varying subsurface processes, implementation, and settings. The area of continuous permafrost estimated by the PMIP3 multi-model analysis through the direct (indirect) method was 26.0 (17.7) million km2 for LGM, in contrast to 15.1 (11.2) million km2 for the pre-industrial control, whereas seasonally frozen ground decreased from 34.5 (26.6) million km2 to 18.1 (16.0) million km2. These changes in area resulted mainly from a cooler climate at LGM, but from other factors as well, such as the presence of huge land ice sheets and the consequent expansion of total land area due to sea-level change. LGM permafrost boundaries modeled by the PMIP3 ensemble – improved over those of the PMIP2 due to higher spatial resolutions and improved climatology – also compared better to previous knowledge derived from geomorphological and geocryological evidence. Combinatorial applications of coupled climate models and detailed stand-alone physical-ecological models for the cold-region terrestrial, paleo-, and modern climates will advance our understanding of the functionality and variability of the frozen ground subsystem in the global eco-climate system.