The Sensitivity of Ground Surface Temperature Prediction to Soil Thermal Properties Using the Simple Biosphere Model(SiB2)

Using the Simple Biosphere Model （SiB2）, soil thermal properties （STP） were examined in a Tibetan prairie during the monsoon period to investigate ground surface temperature prediction. We improved the SiB2 model by incorporating a revised force-restore method （FRM） to take the vertical heterogeneity of soil thermal diffusivity （k） into account. The results indicate that （1） the revised FRM alleviates daytime overestimation and nighttime underestimation in modeled ground surface temperature （Tg）, and （2） its role in little rainfall events is significant because the vertical gradient of k increases with increasing surface evaporation. Since the original formula of thermal conductivity （A） in the SiB2 greatly underestimates soil thermal conductivity, we compared five Mgorithms of A involving soil moisture to investigate the cause of overestimation during the day and underestimation at night on the basis of the revised FRM. The results show that （1） the five algorithms significantly improve Tg prediction, especially in daytime, and （2） taking one of these five algorithms as an example, the simulated Tg values in the daytime are closer to the field measurements than those in the nighttime. The differences between modeled Tg and field measurements are mostly within the margin of error of -4-2 K during 3 August to 4 September 1998.

Recent changes in ground surface thermal regimes in the context of air temperature warming over the Heihe River Basin, China

Changes in ground surface thermal regimes play a vital role in surface and subsurface hydrology, ecosystem diversity and productivity, and global thermal, water and carbon budgets as well as climate change. Estimating spring, summer, autumn and winter air temperatures and mean annual air temperature（MAAT） from 1960 through 2008 over the Heihe River Basin reveals a statistically significant trend of 0.31 °C/decade, 0.28 °C/decade, 0.37 °C/decade, 0.50 °C/decade, and 0.37 °C /decade, respectively. The averaged time series of mean annual ground surface temperature（MAGST） and maximum annual ground surface temperature（MaxAGST） for 1972–2006 over the basin indicates a statistically significant trend of 0.58 °C/decade and 1.27 °C/decade, respectively. The minimum annual ground surface temperature（MinAGST） in the same period remains unchanged as a whole. Estimating surface freezing/thawing index as well as the ratio of freezing index to thawing index（RFT） in the period between 1959 and 2006 over the basin indicates a statistically significant trend of-42.5 °C-day/decade, 85.4 °C-day/decade and-0.018/decade, respectively.

Changes in the ground surface temperature in permafrost regions along the Qinghaie-Tibet engineering corridor from 1900 to 2014:A modified assessment of CMIP6

Numerous studies were published in the last two decades to evaluate and project the permafrost changes in its thermal state,mainly based on the soil temperature datasets from the Coupled Model Intercomparison Project(CMIP),and discuss the impacts of permafrost changes on regional hydrological,ecological and climatic systems and even carbon cycles.However,limited monitored soil temperature data are available to validate the CMIP outputs,resulting in the over-projection of future permafrost changes in CMIP3 and CMIP5.Moreover,future permafrost changes in CMIP6,particularly over the QinghaieTibet Plateau(QTP),where permafrost covers more than 40%of its territory,are still unknown.To address this gap,we evaluated and calibrated the monthly ground surface temperature(GST;5 cm below the ground surface),which was often used as the upper boundary to simulate and project permafrost changes derived from 19 CMIP6 Earth System Models(ESMs)against in situ measurements over the QTP.We generated the monthly GST series from 1900 to 2014 for five sites based on the linear calibration models and validated them through the three other sites using the same calibration methods.Results showed that all of the ESMs could capture the dynamics of in situ GST with high correlations(r>0.90).However,large errors were detected with a broad range of centred root-mean-square errors(1.14-4.98℃).The Top 5 model ensembles(MME5)performed better than most individual ESMs and averaged multi-model ensembles(MME19).The calibrated GST performed better than the GST obtained from MME5.Both annual and seasonal GSTs exhibited warming trends with an average annual rate of 0.04℃ per decade in the annual GST.The average seasonal warming rate was highest in winter and spring and lowest in summer.This reconstructed GST data series could be used to simulate the long-term permafrost temperature over the QTP.

Bias Analysis and Correction of Ground Surface Temperature Observations across China

Based on the ground surface temperature(GST)and snow surface temperature(SST)measurements during the period of adjustment from manual to automatic observation systems in China,the influence of observation methods on GST and its relationship with snow cover is analyzed.GST is corrected by SST,and the correction effect is evaluated.The results show that,during the parallel observation period,the winter GSTs from automatic observations are generally higher than those from manual observations,with the automatically observed national daily GST 1.18°C higher.The adjustment has a greater impact on GSTs at 0200,0800,and 2000 Beijing Time(BT)than at 1400 BT,and it has the greatest impact in Northeast and Northwest China,with deviations of 5.24 and 2.09°C,respectively.The GST deviation is closely related to the snow depth and annual snow totals.The average daily GST deviation increases at the rate of 0.66°C per 1-cm increase of snow depth when it is<15 cm,while it tends to be stable at around 10°C for snow depth over 15 cm.The GST deviation at a station is affected by its winter snow totals in Northeast and Northwest China,where the largest deviations are found where snow totals are all above 1000 cm.After the correction with SST,the mean deviation between the automatic and manual observations as well as the false trend can be effectively reduced.Following the correction,the mean deviation of daily GST decreases by 5.8°C,and its trend decreases from 1.87 to 0.65°C decade-1.

Climate warming over 1961–2019 and impacts on permafrost zonation in Northeast China

In boreal forest ecosystems, permafrost and forest types are mutually interdependent;permafrost degradation impacts forest ecosystem structure and functions. The Xing’an permafrost in Northeast China is on the southern margin of the Eastern Asia latitudinal permafrost body. Under a warming climate, permafrost undergoes rapid and extensive degradation. In this study, the frost-number (Fn) model based on air temperatures and ground surface temperatures was used to predict the distribution of the Xing’an permafrost, and, temporal and spatial changes in air and ground-surface temperatures from 1961 to 2019 are analyzed. The results show that Northeast China has experienced a rapid and substantial climate warming over the past 60 years. The rises in mean annual air and mean annual ground-surface temperatures were higher in permafrost zones than those in the seasonal frost zone. The frost numbers of air and ground-surface temperatures were calculated for determining the southern limit of latitudinal permafrost and for permafrost zonation. The southern limits of discontinuous permafrost, sporadic permafrost, and latitudinal permafrost moved northward significantly. According to the air-temperature frost-number criteria for permafrost zoning, compared with that in the 1960s, the extent of Xing’an permafrost in Northeast China had decreased by 40.6% by the 2010s. With an average rate of increase in mean annual air temperatures at 0.03 ℃ a^(−1), the extent of permafrost in Northeast China will decrease to 26.42 × 10^(4) by 2020, 14.69 × 10^(4) by 2040 and to 11.24 × 10^(4) km^(2) by 2050. According to the ground-surface temperature frost-number criteria, the southern limit of latitudinal permafrost was at the 0.463. From the 1960s to the 2010s, the extent of latitudinal permafrost declined significantly. Due to the nature of the ecosystem-protected Xing’an-Baikal permafrost, management and protection (e.g., more prudent and effective forest fire management and proper logging of forests) of the Xing’an permafrost eco-environment should be strengthened.

Assessment of the spatial extent of permafrost in the Upper Indus Basin(UIB)

Climate change differentially influences the frozen ground,a major dynamic component of the cryosphere,on a local and regional scale.Under the warming climate with pronounced effects reported at higher altitudes,the characterization of the frozen ground is very important in the Upper Indus Basin(UIB),an important and critical region with respect to climate and hydro-glaciological dynamics.In this study,the efficiency and reliability of the surface frost number model are assessed in delineating the spatial extent of different classes of frozen ground in the region.The daily MODIS land surface temperature(LST)with ground surface temperature(GST)and surface geomorphological expressions as ground validation datasets are used jointly in efficiently determining the extent of different classes of frozen ground(continuous and discontinuous permafrost and seasonal frost).The LST and GST resonate with each other in the annual cycle of temperature variation,however,with mean annual LST exhibiting an offset(cold bias)of 5 to 7℃relative to mean GST.This study shows that the highest permafrost extent is observed in areas where the lowest thinning rates of glacier ice are reported and vice versa.The surface frost number model categorizes an area of 38%±3%and 15%±3%in the UIB as permafrost and seasonal frost,respectively.Based on the altitude model,the lower limit of alpine permafrost is approximated at a mean altitude of 4919±590 m a.s.l.in the UIB.The present study acts as preliminary work in the data sparse and inaccessible regions of the UIB in characterizing the frozen and unfrozen ground and may act as a promising input data source in glaciohydro-meteorological models for the Himalaya and Karakoram.In addition,the study also underlines the consideration of this derelict cryospheric climatic variable in defining and accounting for the sustainable development of socio-economic systems through its intricate ramification on agricultural activity,landscape stability and infrastructure.