Unveiling evapotranspiration patterns and energy balance in a subalpine forest of the Qinghai-Tibet Plateau:observations and analysis from an eddy covariance system

Evapotranspiration is an important parameter used to characterize the water cycle of ecosystems.To under-stand the properties of the evapotranspiration and energy balance of a subalpine forest in the southeastern Qinghai-Tibet Plateau,an open-path eddy covariance system was set up to monitor the forest from November 2020 to October 2021 in a core area of the Three Parallel Rivers in the Qing-hai-Tibet Plateau.The results show that the evapotranspira-tion peaked daily,the maximum occurring between 11:00 and 15:00.Environmental factors had significant effects on evapotranspiration,among them,net radiation the greatest(R^(2)=0.487),and relative humidity the least(R^(2)=0.001).The energy flux varied considerably in different seasons and sensible heat flux accounted for the main part of turbulent energy.The energy balance ratio in the dormant season was less than that in the growing season,and there is an energy imbalance at the site on an annual time scale.

Evolution of permafrost in Northeast Chinasince the Late Pleistocene

In Northeast China, permafrost advanced and retreated several times under the influences of fluctuating paleo-climatesand paleo-environments since the Late Pleistocene. During the last 60 years, many new data were obtained and studies wereconducted on the evolution of permafrost in Northeast China, but so far no systematic summary and review have been made.Based on sedimentary sequences, remains of past permafrost, paleo-flora and -fauna records, and dating data, permafrostevolution since the Late Pleistocene has been analyzed and reconstructed in this paper. Paleo-temperatures reconstructedfrom the remains of past permafrost and those from paleo-flora and -fauna are compared, and thus the southern limitof permafrost （SLP） in each climate period is inferred by the relationship of the permafrost distribution and the meanannual air/ground temperatures （MAAT/MAGT）. Thus, the evolutionary history of permafrost is here divided into fivestages： （1） the Late Pleistocene （Last Glaciation, or LG） （65 to 10–8.5 ka）, the Last Glaciation Maximum （LGM, 21–13 ka）in particular, the coldest period in the latest history with a cooling of about 6~10 °C, characterized by extensive occurrencesof glaciation, flourishing Mammathas-Coelodonta Faunal Complex （MCFC）, widespread aeolian deposits, and significantsea level lowering, and permafrost greatly expanded southwards almost to the coastal plains （37°N–41°N）; （2） the HoloceneMegathermal Period （HMP, 8.5–7.0 to 4.0–3.0 ka）, 3~5 °C warmer than today, permafrost retreated to about 52°N; （3） theLate Holocene Cold Period （Neoglaciation） （4.0–3.0 to 1.0–0.5 ka）, a cooling of 1~3 °C, some earlier thawed permafrost wasrefrozen or attached, and the SLP invaded southwards to 46°N; （4） the Little Ice Age （LIA, 500 to 100–150 a）, the latestcold period with significant permafrost expansion; and （5） climate warming since the last century, during which NortheastChina has undergone extensive permafrost degradation. The frequent and substantial expansions and retreats of permafrosthave greatly impacted cold-region environments in Northeast China. North of the SLP during the HMP, or in the presentcontinuous permafrost zone, the existing permafrost was largely formed during the LG and was later overlapped by thepermafrost formed in the Neoglaciation. To the south, it was formed in the Neoglaciation. However, many aspects ofpermafrost evolution still await further investigations, such as data integration, numerical reconstruction, and merging ofChinese permafrost history with those of bordering regions as well as collaboration with related disciplines. Of these, studies on the evolution and degradation of permafrost during the past 150 years and its hydrological, ecological, and environmentalimpacts should be prioritized.

The efficacy of Kriging spatial interpolation for filling temporal gaps in daily air temperature data: A case study in northeast China

Quality-controlled and serially complete daily air temperature data are essential to evaluating and modelling the influences of climate change on the permafrost in cold regions. Due to malfunctions and location changes of observing stations, temporal gaps （i.e., missing data） are common in collected datasets. The objective of this study was to assess the efficacy of Kriging spatial interpolation for estimating missing data to fill the temporal gaps in daily air temperature data in northeast China. A cross-validation experiment was conducted. Daily air temperature series from 1960 to 2012 at each station were estimated by using the universal Kriging （UK） and Kriging with an external drift （KED）, as appropriate, as if all the ob-servations at a given station were completely missing. The temporal and spatial variation patterns of estimation uncertainties were also checked. Results showed that Kriging spatial interpolation was generally desirable for estimating missing data in daily air temperature, and in this study KED performed slightly better than UK. At most stations the correlation coefficients （R2） between the observed and estimated daily series were 〉0.98, and root mean square errors （RMSEs） of the estimated daily mean （Tmean）, maximum （Tmax）, and minimum （Tmin） of air temperature were 〈3 ℃. However, the estimation quality was strongly affected by seasonality and had spatial variation. In general, estimation uncertainties were small in summer and large in winter. On average, the RMSE in winter was approximately 1 ℃ higher than that in summer. In addition, estimation uncertainties in mountainous areas with complex terrain were significantly larger than those in plain areas.

工业缺陷检测深度学习方法综述

基于深度学习的工业缺陷检测方法可以降低传统人工质检的成本,提升检测的准确性与效率,因而在智能制造中扮演重要角色,并逐渐成为计算机视觉领域新兴的研究热点之一.其被广泛地应用于无人质检、智能巡检、质量控制等各种生产与运维场景中.本综述旨在对工业缺陷检测的任务定义、难点、挑战、主流方法、公共数据集及评价指标等进行全面归纳,以帮助研究人员快速了解该领域.具体而言,本文首先介绍工业缺陷检测的背景与特点.接着,按照实际数据标注情况,划分出缺陷模式已知、缺陷模式未知与少量缺陷标注3种研究任务设置,并根据方法类型作进一步归纳与分析,探讨了各方法的性能优劣与适用场景,阐明了方法与实际应用需求的关联性.此外,本文还归纳了方法部署中的关键辅助技术,总结了现有方法在实际产业落地中存在的局限性.最后,本文对该领域未来的发展趋势和潜在研究方向进行了展望.

Evolution of permafrost in China during the last 20 ka

The formation and evolution of permafrost in China during the last 20 ka were reconstructed on the basis of large amount of paleo-permafrost remains and paleo-periglacial evidence, as well as paleo-glacial landforms, paleo-flora and paleofauna records. The results indicate that, during the local Last Glacial Maximum(LLGM) or local Last Permafrost Maximum(LLPMax), the extent of permafrost of China reached 5.3×106-5.4×106 km2, or thrice that of today, but permafrost shrank to only0.80×106-0.85×106 km2, or 50% that of present, during the local Holocene Megathermal Period(LHMP), or the local Last Permafrost Minimum(LLPMin). On the basis of the dating of periglacial remains and their distributive features, the extent of permafrost in China was delineated for the two periods of LLGM(LLPMax) and LHMP(LLPMin), and the evolution of permafrost in China was divided into seven periods as follows:(1) LLGM in Late Pleistocene(ca. 20000 to 13000-10800 a BP)with extensive evidence for the presence of intensive ice-wedge expansion for outlining its LLPMax extent;(2) A period of dramatically changing climate during the early Holocene(10800 to 8500-7000 a BP) when permafrost remained relatively stable but with a general trend of shrinking areal extent;(3) The LHMP in the Mid-Holocene(8500-7000 to 4000-3000 a BP)when permafrost degraded intensively and extensively, and shrank to the LLPMin;(4) Neoglaciation during the late Holocene(4000-3000 to 1000 a BP, when permafrost again expanded;(5) Medieval Warming Period(MWP) in the late Holocene(1000-500 a BP) when permafrost was in a relative decline;(6) Little Ice Age(LIA) in the late Holocene(500-100 a BP), when permafrost relatively expanded, and;(7) Recent warming(during the 20 th century), when permafrost continuously degraded and still is degrading. The paleo-climate, geography and paleopermafrost extents and other features were reconstructed for each of these seven periods.

Mapping the permafrost stability on the Tibetan Plateau for 2005–2015

Data scarcity is a major obstacle for high-resolution mapping of permafrost on the Tibetan Plateau(TP).This study produces a new permafrost stability distribution map for the 2010 s(2005–2015)derived from the predicted mean annual ground temperature(MAGT)at a depth of zero annual amplitude(10–25 m)by integrating remotely sensed freezing degree-days and thawing degree-days,snow cover days,leaf area index,soil bulk density,high-accuracy soil moisture data,and in situ MAGT measurements from 237 boreholes on the TP by using an ensemble learning method that employs a support vector regression model based on distance-blocked resampled training data with 200 repetitions.Validation of the new permafrost map indicates that it is probably the most accurate of all currently available maps.This map shows that the total area of permafrost on the TP,excluding glaciers and lakes,is approximately 115.02(105.47–129.59)×10^4 km^2.The areas corresponding to the very stable,stable,semi-stable,transitional,and unstable types are 0.86×10^4,9.62×10^4,38.45×10^4,42.29×10^4,and 23.80×10^4 km^2,respectively.This new map is of fundamental importance for engineering planning and design,ecosystem management,and evaluation of the permafrost change in the future on the TP as a baseline.

Spatiotemporal characteristics of freezing and thawing of the active layer in the source areas of the Yellow River(SAYR)

Based on the analysis of data on temperatures and moisture of soils in the active layer at four different permafrost sites in the source areas of the Yellow River(SAYR)in 2010–2012,the freeze–thaw processes of soils in the active layer were compared and contrasted for understanding the spatiotemporal variations.At the four studied sites,the thickness and mean annual temperature of permafrost are different.The temperatures at the top of permafrost(TTOP),i.e.,the maximum depth(s)of seasonal frost and/or thaw penetration,are-1.9°C at the Chalaping site(CLP),-0.9°C at the site on the southern bank of the Zhaling Lake(ZLH),-0.4°C at the Maduo Town site(MDX),and 1.1°C at the site on the northern bank of the Eling Lake(ELH).Differences in the mean annual ground temperature of permafrost and TTOPs may be responsible for the differentiations in the freeze–thaw processes of soils in the active layer.With rising TTOPs,the ground thawing started earlier:CLP in early June,ZLH in late May,MDX in early May,and ELH in mid-April,while the freezing began later:CLP in early October,ZLH in early to midOctober,MDX in mid-October,and ELH in the mid-to late October.With increasing TTOPs,the freeze-up periods for permafrost sites were shortened:202 days at CLP,130 days at ZLH,100 days at MDX,and the period of complete thaw was 89 days at ELH.At the CLP and ZLH sites,the two-directional ground freezing(downwards from ground surfaces and upwards from the permafrost table)and thawing finished in the same year,but the ground freezing at the MDX continued to the end of the nextJanuary,with very slow freezing rates in the end.At the ELH site,ground freezing kept on until early May when thawing began on the surface,and upward and downward thawing became increasingly stable in late June to early July.At each site,with rising TTOPs,the downward freezing accelerated in comparison with the upward freezing,and with an increasing proportion of downward frozen depth,and with the larger ratios of freezing to thawing duration.In summary,the patterns of thawing and freezing processes in the active layer in the SAYR differ from those in other parts of the Qinghai–Tibet Plateau to a noticeable extent.