Paleo-reconstructed net basin supply scenarios and their effect on lake levels in the upper great lakes

Paleo-reconstructed hydrologic records offer the potential to evaluate water resources system performance under conditions that may be more extreme than seen in the historical record. This study uses a stochastic simulation framework consisting of a non-homogeneous Markov chain model (NHMM) to simulate the climate state using Palmer Drought Severity Index (PDSI)-reconstructed data, and K-nearest neighbor (K-NN) to resample observational net basin supply magnitudes for the Great Lakes of North America. The method was applied to generate 500 plausible simulations, each with 100 years of monthly net basin supply for the Upper Great Lakes, to place the observed data into a longer temporal context. The range of net basin supply sequences represents what may have occurred in the past 1,000 years and which can occur in future. The approach was used in evaluation of operational plans for regulation of Lake Superior outflows with implications for lake levels of Superior, Michigan, Huron and Erie, and their interconnecting rivers. The simulations generally preserved the statistics of the observed record while providing new variability statistics. The framework produced a variety of high and low net basin supply sequences that provide a broader estimate of the likelihood of extreme lake levels and their persistence than with the historical record. The method does not rely on parametrically generated net basin supply values unlike parametric stochastic simulation techniques, yet still generates new variability through the incorporation of the paleo-record. The process described here generated new scenarios that are plausible based on the paleo and historic record. The evaluation of Upper Great Lakes regulation plans, subject to these scenarios, was used to evaluate robustness of the regulation plans. While the uncertain future climate cannot be predicted, one can evaluate system performance on a wide range of plausible climate scenarios.     

利用随机模拟研究极值天气的预报模型试验

将随机过程的交叉理论应用于天气气候极值分析，以长江三角洲地区逐月最高最低气温为例，说明了交叉理论在极值研究中的作用。基于该理论，对上海市近100a一月气温序列，用随机模拟的方法讨论了极端温度出现的频数、持续时间、时间间隔等参数对于气候变化的敏感性，并根据气候变化趋势，预测了未来气候极值统计特征的变化规律。     

Fuzzy logic model of lake water level fluctuations in Lake Van, Turkey

Summary Lake Van is one of the largest terminal lakes in the world. In recent years, significant lake level fluctuations have occurred and can be related to global climatic change. This fluctuation sometimes exhibits abrupt shifts. Floods originating from the lake can cause considerable damage and loss in agriculture and urban areas. Therefore, water level forecasting plays a significant role in planning and design. This study is aimed at predicting future lake levels from past rainfall amounts and water level records. A dynamical change of the lake level is evaluated by the fuzzy approach. The fuzzy inference system has the ability to use fuzzy membership functions that include the uncertainties of the concerned event. This method is applied for Lake Van, in east Turkey. Furthermore, model capabilities are compared with ARMAX model. It is shown that lower absolute errors are obtained with the Takagi-Sugeno fuzzy approach than with the ARMAX model.     

西藏冰湖溃决灾害事件极端气候特征

以1960年以来西藏境内已有记载的27次冰湖溃决灾害事件作为研究对象,基于西藏国家气象站点长时间序列（有效记录至今）日气温和日降雨数据,计算得到16个极端气温指数和6个极端降雨指数。通过主成分变换,提取综合极端气温指数和综合极端降雨指数,并进行历史（10年内对比）极端气候特征对比,获得冰湖溃决灾害发生当年及当月极端气候状态,结果表明西藏冰湖溃决灾害发生期（当年及当月）极端气候特征显著,反映极端气候状态对于激发西藏冰湖溃决灾害发生的重要贡献,具体表现为：(1) 67%（18次）的冰湖溃决事件发生当年综合极端气温指数和综合极端降雨指数均大于前期50%年份的综合极端气候指数,其中,13次灾害发生当年极端气候异常水平超过前期70%年份;(2)已有灾害暴发月份记载的25次冰湖溃决事件中,19次冰湖溃决事件发生当月极端气候指数异常偏高,11次冰湖溃决事件发生当月极端气温和极端降水均大于75%往年同期综合极端气候指数;(3)部分灾害事件如扎日错（1981年6月)、龙纠错溃决（2000年8月）等,灾害发生当年极端气温状态低于往年,而暴发当月综合极端气温指数和综合极端降雨指数均大于历史同期水平,表现为加剧状态;(4)所有冰湖溃决灾害发生当月的综合极端气温指数均高于往年同期指数,表明短历时极端气温事件对高原冰湖溃决灾害形成具有重要影响。     

赤道东太平洋地区海温的随机模拟

本文对描述海气相互作用的随机模型作进一步的解释,考虑周期性外力对海气系统的影响,并用这一改进随机进随机动力模型对赤道东太平洋地区的海温作随机模拟,模拟序列的解释方差达到70%。试验表明,考虑周期性外力对海气系统的作用是明显的,它能进一步提高模拟效果,使随机模型更接近实际。      

Climatic change and great lakes levels the impact on shipping

This paper represents an attempt to combine the output of several models that deal with future climatic, hydrologic and economic conditions in the Great Lakes and makes some predictions about the possible impact of one scenario of 2 × CO₂ climate on Great Lakes shipping. It is realized that there is a great deal of uncertainty in all the models and that improvements are continually being made. Data from a General Circulation Model of future temperature and precipitation in the Great Lakes basin, a Great Lakes levels and flows model from the Canada Centre for Inland Waters and an International Joint Commision's Great Lakes economic model modified by the University of Wisconsin were used. The 1900–1976 period of lake levels and flows was used. The hydrologic model indicated that future mean lake levels may be reduced by one-half meter, and that the extreme low levels of the mid 1960's could occur 77% of the time in the future. No ice cover is predicted for any lake except Erie, permitting an eleven month shipping season. Five scenarios of future impact on shipping were evaluated. It was found that mean annual shipping costs may increase by 30% and the frequency of years when costs exceed those of the period of low lake levels (1963–65) could rise to 97%. Possible policy options in a future with climatically induced lower lake levels could include regulation to keep levels artificially high by diversions into the system, or increased dredging of the connecting channels.     

Estimating present day extreme water level exceedance probabilities around the coastline of Australia: tides, extra-tropical storm surges and mean sea level

The occurrence of extreme water levels along low-lying, highly populated and/or developed coastlines can lead to considerable loss of life and billions of dollars of damage to coastal infrastructure. Therefore it is vitally important that the exceedance probabilities of extreme water levels are accurately evaluated to inform risk-based flood management, engineering and future land-use planning. This ensures the risk of catastrophic structural failures due to under-design or expensive wastes due to over-design are minimised. This paper estimates for the first time present day extreme water level exceedence probabilities around the whole coastline of Australia. A high-resolution depth averaged hydrodynamic model has been configured for the Australian continental shelf region and has been forced with tidal levels from a global tidal model and meteorological fields from a global reanalysis to generate a 61-year hindcast of water levels. Output from this model has been successfully validated against measurements from 30 tide gauge sites. At each numeric coastal grid point, extreme value distributions have been fitted to the derived time series of annual maxima and the several largest water levels each year to estimate exceedence probabilities. This provides a reliable estimate of water level probabilities around southern Australia; a region mainly impacted by extra-tropical cyclones. However, as the meteorological forcing used only weakly includes the effects of tropical cyclones, extreme water level probabilities are underestimated around the western, northern and north-eastern Australian coastline. In a companion paper we build on the work presented here and more accurately include tropical cyclone-induced surges in the estimation of extreme water level. The multi-decadal hindcast generated here has been used primarily to estimate extreme water level exceedance probabilities but could be used more widely in the future for a variety of other research and practical applications.     

Intrinsic problems in the seasonal prediction of the Indian summer monsoon rainfall

Summary The latest non-parametric statistical tool Singular Spectrum Analysis (SSA) has been shown to extract deterministic oscillations present in a nonlinear dynamical system. It has been hypothesized that the tropical ocean-atmosphere system consists of both deterministic and stochastic parts in the interannual time scales. In the present study SSA has been employed to extract the deterministic and random parts present in the Indian summer monsoon (ISM) and its predictors time series data sets.The dominant eigenmode pair of the ISM does not emerge as a pure and deterministic oscillation. However, about 34% variance is deterministically predictable in the inter-annual range. The second pair is significantly related to the first pair of Darwin pressure tendency and both emerge as deterministic parts. This relationship partially answers the questions raised by Webster and Yang (1992). The low frequency component of ENSO emerges as a deterministic oscillation in all the variables, except in Bombay pressure tendency. The presence of decadal-scale oscillations may possibly be responsible for the instability in the relationship between the ISM and its predictors. Some plausible explanations for the percent variance explained by the predictors in the existing empirical models have also been discussed. It has been proposed that empirical models can be constructed only with the deterministic parts which may help improve the predictive skill of existing models.With 12 Figures     

Stochastic and deterministic multicloud parameterizations for tropical convection

Despite recent advances in supercomputing, current general circulation models poorly represent the variability associated with organized tropical convection. In a recent study, the authors have shown, in the context of a paradigm two baroclinic mode system, that a stochastic multicloud convective parameterization based on three cloud types (congestus, deep and stratiform) can be used to improve the variability and the dynamical structure of tropical convection. Here, the stochastic multicloud model is modified with a lag type stratiform closure and augmented with an explicit mechanism for congestus detrainment moistening. These modifications improve the representation of intermittent coherent structures such as synoptic and mesoscale convective systems. Moreover, the new stratiform-lag closure allows for increased robustness of the coherent features of the model with respect to the amount of stochastic noise and leading to a multi-scale organization of slowly moving waves envelopes in which short-lived and chaotic convective events persist. Congestus cloud decks dominate the suppressed-dry phase of the wave envelopes. The simulations with the new closure have a higher amount of stochastic noise and result in a Walker type circulation with realistic mean and coherent variability which surpasses results of previous deterministic and stochastic multicloud models in the same parameter regime. Further, deterministic mean field limit equations (DMFLE) for the stochastic multicloud model are considered. Aside from providing a link to the deterministic multicloud parameterization, the DMFLE allow a judicious way of determining the amount of deterministic and stochastic “chaos” in the system. It is shown that with the old stratiform heating closure, the stochastic process accounts for most of the chaotic behavior. The simulations with the new stratiform heating closure exhibit a mixture of stochastic and deterministic chaos. The highly chaotic dynamics in the simulations with congestus detrainment mechanism is due to the strongly nonlinear and numerically stiff deterministic dynamics. In the latter two cases, the DMFLE can be viewed as a “standalone” parameterization, which is capable of capturing some dynamical features of the stochastic parameterization. Furthermore, it is shown that, in spatially extended simulations, the stochastic multicloud model can capture qualitatively two local statistical features of the observations: long and short auto-correlation times of moisture and precipitation, respectively and the approximate power-law in the probability density of precipitation event size for large precipitation events. The latter feature is not reproduced in the column simulations. This fact underscores the importance of gravity waves and large scale moisture convergence.     

Estimating present day extreme water level exceedance probabilities around the coastline of Australia: tropical cyclone-induced storm surges

The incidence of major storm surges in the last decade have dramatically emphasized the immense destructive capabilities of extreme water level events, particularly when driven by severe tropical cyclones. Given this risk, it is vitally important that the exceedance probabilities of extreme water levels are accurately evaluated to inform risk-based flood and erosion management, engineering and for future land-use planning and to ensure the risk of catastrophic structural failures due to under-design or expensive wastes due to over-design are minimised. Australia has a long history of coastal flooding from tropical cyclones. Using a novel integration of two modeling techniques, this paper provides the first estimates of present day extreme water level exceedance probabilities around the whole coastline of Australia, and the first estimates that combine the influence of astronomical tides, storm surges generated by both extra-tropical and tropical cyclones, and seasonal and inter-annual variations in mean sea level. Initially, an analysis of tide gauge records has been used to assess the characteristics of tropical cyclone-induced surges around Australia. However, given the dearth (temporal and spatial) of information around much of the coastline, and therefore the inability of these gauge records to adequately describe the regional climatology, an observationally based stochastic tropical cyclone model has been developed to synthetically extend the tropical cyclone record to 10,000 years. Wind and pressure fields derived for these synthetically generated events have then been used to drive a hydrodynamic model of the Australian continental shelf region with annual maximum water levels extracted to estimate exceedance probabilities around the coastline. To validate this methodology, selected historic storm surge events have been simulated and resultant storm surges compared with gauge records. Tropical cyclone induced exceedance probabilities have been combined with estimates derived from a 61-year water level hindcast described in a companion paper to give a single estimate of present day extreme water level probabilities around the whole coastline of Australia. Results of this work are freely available to coastal engineers, managers and researchers via a web-based tool (www.sealevelrise.info). The described methodology could be applied to other regions of the world, like the US east coast, that are subject to both extra-tropical and tropical cyclones.     

An Investigation into Effect of Randomly Distributed Small Scale

Previous studies concerning the interaction of dual vortices have been made generally in the deterministic framework. In this paper, by using an advection equation model, eight numerical experiments whose integration times are 30 h are performed in order to analyze the interaction of dual vortices and the vortex self-organization in a coexisting system of deterministic and stochastic components. The stochastic components are introduced into the model by the way that the Iwayama scheme is used to produce the randomly distributed small-scale vortices which are then added into the initial field. The different intensity of the small-scale vortices is described by parameter K being 0.0, 0.4, 0.6, 0.8, and 1.0, respectively. When there is no small-scale vortex （K=0.0）, two initially separated meso-beta vortices rotate counterclockwise mutually, and their quasi-final flow pattern is still two separated vortices; after initially incorporating small-scale vortices （K=0.8, 1.0）, the two separated meso-beta vortices of initially same intensity gradually evolve into a major and a secondary vortex in time integration. The major vortex pulls the secondary one, which gradually evolves into the spiral band of the major vortex. The quasi-final flow pattern is a self-organized vortex with typhoon-like circulation, and the relative vorticity at its center increases with increasing in K value, suggesting that small-scale vortices feed the self-organized vortex with vorticity. This may be a possible mechanism responsible for changes in the strength of the self-organized vortex. Results also show that the quasi-final pattern not only relates with the initial intensity of the small-scale vortices, but also with their initial distribution. In addition, three experiments are also performed in the case of various boundary conditions. Firstly, the periodic condition is used on the E-W boundary, but the fixed condition on the S-N boundary; secondly, the fixed condition is set on all the boundaries; and thirdly, the periodic conditio     

随机分布的小尺度涡对涡旋自组织影响的研究

以往双涡相互作用的动力学一般都在决定性的框架内研究。文中用一个平流方程模式,实施积分时间为30 h的8组试验,分析决定性和随机性共存系统中双涡相互作用和涡旋自组织的问题。随机性通过以下方式引入模式:先用Iwayama方案生成随机分布的小尺度涡,再将这些小尺度涡加入初始场。试验中,初始随机分布小尺度涡的强度参数K分别取0.0、0.4、0.6、0.8和1.0。结果表明,没有小尺度涡的条件下(K=0.0),初始分离的两个β中尺度涡逆时针互旋,其准终态流型是两个分离的涡;引进小尺度涡后,K取0.8、1.0时,初始分离强度相同的两个β中尺度涡,逐渐形成主次之分。主涡将次涡拉伸成为螺旋带,其准终态流型是一个自组织起来的类似于台风环流的涡旋。准终态涡中心的相对涡度值随K值的加大而加大。结果还表明,准终态流型不仅与初始小尺度涡的强度参数有关,而且与初始小尺度涡的分布有关。此外,在相同初始场的情况下,还实施了3类不同边畀条件的试验:第1类,在东西边界取周期条件,在南北边界取固定条件;第2类,在所有边界均取固定条件;第3类,在所有边界均取周期条件。这3类试验的准终态流型相同,都显示出一个类似于台风涡旋的环流。根据这些结果可以初步认为,涡旋自组织的研究从决定性动力学向随机动力学的过渡是值得探索的。     

Characteristics of autumn-winter extreme precipitation on the Norwegian west coast identified by cluster analysis

Extremely high autumn and winter precipitation events on the European west coast are often driven by low-pressure systems in the North Atlantic. Climate projections suggest the number and intensity of these events is likely to increase far more than the mean precipitation. In this study we investigate the autumn-winter extreme precipitation on the Norwegian west coast and the connection between its spatial distribution and sea level pressure (SLP) patterns using the k-means cluster analysis. We use three relatively high resolved downscalings of one global coupled model: the Arpège global atmospheric model (stretched grid with 35-km horizontal resolution over Norway) and the WRF-downscaled Arpège model (30 and 10-km) for the 30-year periods of 1961–1990 and 2021–2050. The cluster analysis finds three main SLP patterns responsible for extreme precipitation in different parts of the country. The SLP patterns found are similar to the NAO positive pattern known to strengthen the westerly flow towards European coast. We then apply the method to investigate future change in extreme precipitation. We find an increase in the number of days with extreme precipitation of 15, 39 and 35% in the two simulations (Arpège 35-km and WRF 30 and 10-km, respectively). We do not find evidence of a significant change in the frequency of weather patterns between the present and the future periods. Rather, it is the probability of a given weather pattern to cause extreme precipitation which is increased in the future, probably due to higher temperatures and an increased moisture content of the air. The WRF model predicts the increase in this probability caused by the most important SLP patterns to be >50%. The Arpège model does not predict such a significant change because the general increase in extreme precipitation predicted is smaller, probably due to its coarser resolution over ocean which leads to smoother representation of the low pressure systems.     

未来气候变化对黄河和长江流域极端径流影响的预估研究

使用NASA-NCAR全球环流模式FvGCM结果驱动高分辨率区域气候模式RegCM3 (20 km),进行1961～1990年当代气候模拟(控制试验)和2071～2100年IPCC A2排放情景下未来气候情景模拟(A2情景模拟试验)。将RegCM3同高分辨率大尺度汇流模型LRM(分辨率0.25°×0.25°)连接,分析水文极端事件在A2情景下相对于当代气候的变化,预估未来气候变化对我国黄河和长江流域水文极端事件的影响。结果表明:(1)未来黄河流域径流年变率增大,月变率减小,日变率在头道拐站以上流域减小,以下流域增大。未来兰州以上半湿润地区,流域东南部湿润区出现径流量峰值的可能性增大,而流域西北部干旱半干旱区出现径流量百分位极值的可能性减小。未来黄河流域中游地区发生流域洪水的风险在夏季月份减少,其余月份均增大。(2)未来长江干流径流年际变率增大,上中游地区径流日和月变率减小,下游地区略有增大;未来汉江流域径流量的年、月和日变率均增大。未来长江干流发生流域洪水的风险在夏季明显降低,而汉江流域各月发生流域洪水的可能性均增大。     

Multiple factors causing Holocene lake-level change in monsoonal and arid central Asia as identified by model experiments

Lake-level records provide a rich resource of information about past changes in effective moisture, but water-balance fluctuations can be driven by a number of different climate variables and it is often difficult to pinpoint their exact cause. This understanding is essential, however, for reconciling divergent paleo-records or for making predictions about future lake-level variations. This research uses a series of models, the NCAR CCSM3, a lake energy-balance and a lake water-balance model, to examine the reasons for lake-level changes in monsoonal Asia and arid central Asia between the early (8.5 ka), middle (6.0 ka) and late (ca. 1800 AD) Holocene. Our results indicate that the components of the lake water balance responsible for lake-level changes varied by region and through time. High lake levels at 8.5 and 6.0 ka in the monsoon region were caused by the combined effects of low lake evaporation and high precipitation. The low lake evaporation resulted from low winter solar radiation and high summer cloud cover. Precipitation associated with the mid-latitude westerlies increased from the early to middle Holocene and maintained high lake levels throughout most of arid central Asia ca. 6 ka. The modeled evolution of lake level in arid central Asia from the mid to late Holocene was spatially heterogeneous, due to different sensitivities of the northern and southern parts of the region to seasonally-changing insolation, particularly regarding the duration of lake ice cover. The model results do not suggest that precipitation and lake evaporation changes compete with one another in forcing lake-level change, as has been hypothesized.     

An Investigation into Effect of Randomly Distributed Small Scale Vortices on Vortex Self-Organization

Previous studies concerning the interaction of dual vortices have been made generally in the determin-istic framework. In this paper, by using an advection equation model, eight numerical experiments whose integration times are 30 h are performed in order to analyze the interaction of dual vortices and the vortex self-organization in a coexisting system of deterministic and stochastic components. The stochastic compo-nents are introduced into the model by the way that the Iwayama scheme is used to produce the randomly distributed small-scale vortices which are then added into the initial field. The different intensity of the small-scale vortices is described by parameter K being 0.0, 0.4, 0.6, 0.8, and 1.0, respectively. When there is no small-scale vortex (K=0.0), two initially separated meso-beta vortices rotate counterclockwise mutu-ally, and their quasi-final flow pattern is still two separated vortices; after initially incorporating small-scale vortices (K=0.8, 1.0), the two separated meso-beta vortices of initially same intensity gradually evolve into a major and a secondary vortex in time integration. The major vortex pulls the secondary one, which gradually evolves into the spiral band of the major vortex. The quasi-final flow pattern is a self-organized vortex with typhoon-like circulation, and the relative vorticity at its center increases with increasing in K value, suggesting that small-scale vortices feed the self-organized vortex with vorticity. This may be a pos-sible mechanism responsible for changes in the strength of the self-organized vortex. Results also show that the quasi-final pattern not only relates with the initial intensity of the small-scale vortices, but also with their initial distribution. In addition, three experiments are also performed in the case of various boundary conditions. Firstly, the periodic condition is used on the E-W boundary, but the fixed condition on the S-N boundary; secondly, the fixed condition is set on all the boundaries; and thirdly, the periodic condition is chosen on all the boundaries. Their quasi-final flow patterns in the three experiments are the same with each other, exhibiting a larger scale typhoon-like circulation. Based on these results mentioned above, authors think that the transition of vortex self-organization study from the deterministic system to the coexisting system of deterministic and stochastic components is worth exploring.     

Predicting Indian monsoon rainfall: a neural network approach

The summer monsoon rainfall over India is predicted by using neural networks. These computational structures are used as a nonlinear method to correlate preseason predictors to rainfall data, and as an algorithm for reconstruction of the rainfall time-series intrinsic dynamics. A combined approach is developed which captures the information built into both the stochastic approach based on suitable predictors and the deterministic dynamical model of the time series. The hierarchical network so obtained has forecasting capabilities remarkably improved with respect to conventional methods.     

基于CMIP6的西南暴雨洪涝灾害风险未来预估

为预估全球变暖背景下中国西南地区未来暴雨洪涝灾害风险的变化特征,研究挑选5个CMIP6模式和5个极端降水指数,结合地形因子、社会经济数据和耕地面积百分比,构建暴雨洪涝灾害风险评估模型,对西南暴雨洪涝灾害风险进行基准期(1995-2014年)评估、未来两个时期(2021-2040年,2041-2060年)3种情景(SSP...     

人工神经网络在月降水量预测业务中的研究和应用综述

月降水量的年际变化具有显著的非线性变化特征,预测难度大,历来是重大气象灾害预测的重点难点问题.BP(back propagation)神经网络在月降水量预测业务中的研究和应用中,取得了较好的成果,其中应用较广泛的是PCA-BP神经网络模型、遗传算法优化神经网络、RBF神经网络预测模型、小波神经网络模型、粒子群-神经网络...