Late Holocene great earthquakes and relative sea‐level change at Kenai,southern Alaska

Kenai, located on the west coast of the Kenai Peninsula, Alaska, subsided during the great earthquake of AD 1964. Regional land subsidence is recorded within the estuarine stratigraphy as peat overlain by tidal silt and clay. Reconstructions using quantitative diatom transfer functions estimate co‐seismic subsidence (relative sea‐level rise) between 0.28±0.28 m and 0.70±0.28 m followed by rapid post‐seismic recovery. Stratigraphy records an earlier co‐seismic event as a second peat‐silt couplet, dated to ～1500–1400 cal. yr BP with 1.14±0.28 m subsidence. Two decimetre‐scale relative sea‐level rises are more likely the result of glacio‐isostatic responses to late Holocene and Little Ice Age glacier expansions rather than to co‐seismic subsidence during great earthquakes. Comparison with other sites around Cook Inlet, at Girdwood and Ocean View, helps in constructing regional patterns of land‐level change associated with three great earthquakes, AD 1964, ～950–850 cal. yr BP and ～1500–1400 cal. yr BP. Each earthquake has a different spatial pattern of co‐seismic subsidence which indicates that assessment of seismic hazard in southern Alaska requires an understanding of multiple great earthquakes, not only the most recent. All three earthquakes show a pre‐seismic phase of gradual land subsidence that marked the end of relative land uplift caused by inter‐seismic strain accumulation. Copyright © 2005 John Wiley & Sons, Ltd.     

Estimation of snow water equivalent using microwave radiometry over Arctic first‐year sea ice

The magnitude and spatial distribution of snow on sea ice are both integral components of the ocean–sea‐ice–atmosphere system. Although there exists a number of algorithms to estimate the snow water equivalent (SWE) on terrestrial surfaces, to date there is no precise method to estimate SWE on sea ice. Physical snow properties and in situ microwave radiometry at 19, 37 and 85 GHz, V and H polarization were collected for a 10‐day period over 20 first‐year sea ice sites. We present and compare the in situ physical, electrical and microwave emission properties of snow over smooth Arctic first‐year sea ice for 19 of the 20 sites sampled. Physical processes creating the observed vertical patterns in the physical and electrical properties are discussed. An algorithm is then developed from the relationship between the SWE and the brightness temperature measured at 37 GHz (55°) H polarization and the air temperature. The multiple regression between these variables is able to account for over 90% of the variability in the measured SWE. This algorithm is validated with a small in situ data set collected during the 1999 field experiment. We then compare our data against the NASA snow thickness algorithm, designed as part of the NASA Earth Enterprise Program. The results indicated a lack of agreement between the NASA algorithm and the algorithm developed here. This lack of agreement is attributed to differences in scale between the Special Sensor Microwave/Imager and surface radiometers and to differences in the Antarctic versus Arctic snow physical and electrical properties. Copyright © 2003 John Wiley & Sons, Ltd.     

The Early Pleistocene Praetiglian and Ludhamian pollen stages in the North Sea Basin and their relationship to the marine isotope record

In this paper, the currently accepted correlation of the Early Pleistocene Ludhamian stage of England with the Tiglian‐A sub‐stage of the Netherlands is challenged. Recent investigations of Early Pleistocene marine North Sea deposits from a borehole near Noordwijk (the Netherlands) yielded evidence from molluscs, dinoflagellate cysts and sporomorphs for an alternation of warm‐temperate and arctic intervals within the Praetiglian and Tiglian stages. Marine equivalents of the terrestrial‐based pollen sub‐stages Tiglian A and B have been recognised in the upper part of the sequence. A Praetiglian age can be assigned to the lower part of the sequence on the basis of mollusc analysis. Within the Praetiglian, an alternation of warm and cold phases has been recognised from both the dinoflagellate cyst and molluscan records. Three cold phases within the Praetiglian are tentatively correlated with marine isotope stages (MIS) 96–100. The molluscan assemblages provide evidence for climate forcing of the sea level: highest sea levels are reached in the warm‐temperate intervals. Within the Praetiglian, an interval with an acme zone of the dinoflagellate cyst Impagidinium multiplexum, is correlated with the Ludhamian and tentatively linked to MIS 97 and/or MIS 96. The cold molluscan assemblages from the Noordwijk borehole include an acme zone of Megayoldia thraciaeformis, the first and only occurrence of this North Pacific bivalve in the North Sea Basin. Copyright © 2006 John Wiley & Sons, Ltd.     

Subtidal sea level and current variations in the northern reach of San Francisco Bay

Analyses of sea level and current-meter data using digital filters and a variety of statistical methods show a variety of phenomena related to non-local coastal forcing and local tidal forcing in the northern reach of San Francisco Bay, a partially mixed estuary. Low-frequency variations in sea level are dominated by non-local variations in coastal sea level and also show a smaller influence from tidally induced fortnightly sea level variations. Low-frequency currents demonstrate a gravitational circulation which is modified by changes in tidal-current speed over the spring-neap tidal cycle. Transients in gravitational circulation induce internal oscillations with periods of two to four days.     

预测有效波高的深度学习模型研究

研究基于RNN、LSTM、GRU深度学习模型,针对NOAA浮标数据集中的44013、44014、44017浮标的数据,通过斯皮尔曼相关性分析提高模型预测效果。实验结果表明,在进行相关性分析后,S-RNN、S-LSTM、 S-GRU的预测效果均比原始RNN、LSTM、GRU模型预测效果好。此外,提出一种基于LSTM的LSTM-Attention 波高预测模型,并进行相关实验,量化LSTM-Attention模型的预测效果,实验结果表明LSTM-Attention模型有更好的预测效果。为评估模型的泛化能力,研究还提出了一种采用邻近浮标数据进行学习,预测浮标缺失数据的方 法。实验结果表明,该方法的预测精度可以达到97.93%。本研究为海浪预测提供了新的方法和思路,也为未来深 度学习模型在海浪预测中的应用提供了参考。     

可解释性长短期记忆模型用于预测湖泊总磷浓度变化

对湖泊总磷的变化预测和来源识别对水资源调度和流域生态治理有着重要的意义,然而复杂的生化反应和水动力条件导致的非平稳性给湖泊总磷浓度的准确预测带来极大的困难。为克服这一挑战,本文引入了基于加权回归的季节趋势分解(seasonal and trend decomposition using Loess,STL)技术和夏普利加法(SHapley additive exPlanations,SHAP)结合长短期记忆网络(long short-term memory neural network,LSTM)和门控循环单元(gated recurrent unit,GRU)构建了一个可解释的预测框架,以增强对湖泊总磷浓度演变的预测并提高其可解释性。研究表明:(1)在骆马湖总磷浓度的预测中,该框架拥有较好的预报精度(R²=0.878),优于LSTM和卷积长短期记忆模型(convolutional neural networks and long short term memory network,CNN-LSTM)。当预测时间步长增加到8 h时,该框架有效提高了总磷浓度的预测精度,平均相对误差和均方根误差分别降低了47.1%和33.3%。从预测趋势来看,骆马湖在汛期的总磷平均浓度为0.158 mg/L,相较于非汛期的平均浓度,增加了202.1%。(2)运河来水是骆马湖总磷浓度最重要的影响因素,贡献权重为60.0%,并且不同断面(三湾、三场)的污染源受水动力、气象等因素的影响存在显著的时空差异。本文凸显了神经网络模型在预警水体污染方面的可实施性,并且为提高传统神经网络的学习能力和可解释性的开发与验证提供了重要方向。     

Seasonal change of ice algal and phytoplankton assemblages in the Nella Fjord near Zhongshan Station, East Antarctica

The ice algal and phytoplankton assemblages were studied from Nella Fjord near Zhongshan Station, East Antarctica from April 12 to December 30, 1992. Algal blooms occurred about 3 cm thick on the bottom of sea ice in late April and mid November to early December respectively, and a phytoplankton bloom appeared in the underlying surface water in mid December following the spring ice algal bloom. The biomass in ice bottom was 1 to 3 orders of magnitude higher than that of surface water. Amphiprora kjellmanii, Berkeleya sp., Navicula glaciei, Nitzschia barkelyi, N. cylindrus /N. curta, N. lecointei and Nitzschia sp. were common in the sea ice temporarily or throughout the study period. The biomass in a certain ice segment was decreased gradually and the dominant species were usually succeeded as the season went on. Nitzschia sublineata and Dactyliosolen antarctica were two seasonal dominant species only observed in underlying water column. The assemblages between bottom of ice and underlying surface water were different except when spring ice algae bloomed. The evidence shows that the ice algal blooms occurred mainly by in situ growth of ice algae, and the phytoplankton bloom was mostly caused by the release of ice algae.     

Thickness distribution and extent of sea ice and snow in Prydz Bay and surrounding waters observed in 2012/2013 austral summer

Three ship-based observational campaigns were conducted to survey sea ice and snow in Prydz Bay and the surrounding waters(64.40°S–69.40°S, 76.11°E–81.29°E) from 28 November 2012 to 3 February 2013. In this paper, we present the sea ice extent and its variation, and the ice and snow thickness distributions and their variations with time in the observed zone. In the pack ice zone, the southern edge of the pack ice changed little, whereas the northern edge retreated significantly during the two earlier observation periods. Compared with the pack ice, the fast ice exhibited a significantly slower variation in extent with its northernmost edge retreating southwards by 6.7 km at a rate of 0.37 km?d-1. Generally, ice showed an increment in thickness with increasing latitude from the end of November to the middle of December. Ice and snow thickness followed an approximate normal distribution during the two earlier observations(79.7±28.9 cm, 79.1±19.1 cm for ice thickness, and 11.6±6.1 cm, 9.6±3.4 cm for snow thickness, respectively), and the distribution tended to be more concentrated in mid-December than in late November. The expected value of ice thickness decreased by 0.6 cm, whereas that of snow thickness decreased by 2 cm from 28 November to 18 December 2012. Ice thickness distribution showed no obvious regularity between 31 January and 3 February, 2013.     

面向未来的海面变化研究

长期以来以地质时期海面变化过程等理论性研究为主要方向的海面变化研究经过７０年代在观念、方法和资料积累方面的突破，自８０年代初期以来进入了以“面向未来”为基调的成熟发展的新阶段，出现了一大批关于未来海面变化幅度及其影响和对策的研究成果，形成了较为完整的研究体系。９０年代初以来的几年间，世界海面研究的活跃领域是地质历史时期（例如ＬＧＭ，５ｅ等阶段）的海面实况、极地冰原对气候变化的反应、海面控制原理、海面模型以及绝对海面的航天测量技术与应用等方面。这一情况在一定程度上体现了“预测热”之后的“冷思考”。中国海面变化研究近年来取得了令世人瞩目的迅速发展，今后应注意引进先进技术方法，加强学科间的交叉合作，发掘自身的优势，向纵深发展     

A DIAGNOSTIC ANALYSIS OF AIR TEMPERATURE ANOMALY MODE OVER CHINA IN 2009/2010 WINTER BASED ON GENERALIZED EQUILIBRIUM FEEDBACK ASSESSMENT (GEFA) METHOD

By using the observed monthly mean data over 160 stations of China and NCAR/NCEP reanalysis data, the generalized equilibrium feedback assessment(GEFA) method, combined with the methods of EOF analysis, correlation and composite analysis, is used to explore the influence of different SST modes on a wintertime air temperature pattern in which it is cold in the northeast and warm in the southwest in China. The results show that the 2009/2010 winter air temperature oscillation mode between the northern and southern part of China is closely related to the corresponding sea surface temperature anomalies(SSTA) and its associated atmospheric circulation anomalies. Exhibiting warming in Northeast China and cooling in Southwest China, the mode is significantly forced by the El Nio mode and the North Atlantic SSTA mode, which have three poles. Under the influence of SSTA modes, the surface northerly flow transported cold air to North and Northeast China, resulting in low temperatures in the regions. Meanwhile, the mid-latitude westerlies intensify and the polar cold air stays in high latitudes and cannot affect the Southwest China, resulting in the warming there.