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1.
Modeling studies of future changes in coastal hydrodynamics, in terms of storm surges and wave climate, need appropriate wind and atmospheric forcings, a necessary requirement for the realistic reproduction of the statistics and the resolution of small scale features. This work compares meteorological results from different climate models in the Mediterranean area, with a focus on the Adriatic Sea, in order to assess their capability to reproduce coastal meteorological features and their possibility to be used as forcings for hydrodynamic simulations. Five meteorological datasets are considered. They are obtained from two regional climate models, implemented with different spatial resolutions and setups and are downscaled from two different global climate models. Wind and atmospheric pressure fields are compared with measurements at four stations along the Italian Adriatic coast. The analysis is carried out both on simulations of the control period 1960–1990 and on the A1B Intergovernmental Panel for Climate Change scenario projections (2070–2100), highlighting the ability of each model in reproducing the statistical coastal meteorological behavior and possible changes. The importance of simulated global- and regional-scale meteorological processes, in terms of correct spatial resolution of the phenomena, is also discussed. Within the Adriatic Sea, the meteorological climate is influenced by the local orography that controls the strengthening of north-eastern katabatic winds like Bora. Results show indeed that the increase in spatial resolution provides a more realistic wind forcing for the hydrodynamic simulations. Moreover, the chosen setup and the global climate models that drive the regional downscalings appear to play an important role in reproducing correct atmospheric pressure fields. The comparison between scenario and control simulations shows a small increase in the mean atmospheric pressure values, while a decrease in mean wind speed and in extreme wind events is observed, particularly for the datasets with higher spatial resolution. Finally, results suggest that an ensemble of downscaled climate models is likely to provide the most suitable climatic forcings (wind and atmospheric pressure fields) for coastal hydrodynamic modeling.  相似文献   

2.
The 1953 North Sea floods, the Big Flood, was one of the worst natural disasters in Europe in modern times and is probably one of the most studied severe coastal floods. Several factors led to the devastating storm surge along the southern North Sea coast in combination of strong and sustained northerly winds, invert barometric effect, high spring tide, and an accumulation of the large surge in the Strait of Dover. However, the storm waves and their roles during the 1953 North Sea storm surge are not well investigated. Therefore, the effect of wave setup due to breaking waves in the storm surge processes is investigated through numerical experiments. A coupled process-based tide-wave-surge model was used to investigate and simulate the storm surge in the North Sea during January 31–February 1, 1953 and validated by comparing with historical water level records at tide gauges and wave observations at light vessels in the North Sea. Meteorological forcing inputs for the period, January 27–February 3, 1953 are reproduced from ERA-20C reanalysis data with a constant correction factor for winds. From the simulation results, it is found that, in addition to the high water due to wind setup, wave setup due to breaking waves nearshore play a role of approximately 10% of the storm surge peaks with approximately 0.2 m. The resulting modeling system can be used extensively for the preparedness of the storm surge and wave of extreme condition, and usual barotropic forecast.  相似文献   

3.
Planning and design of coastal protection rely on information about the probabilities of very severe storm tides and the possible changes that may occur in the course of climate change. So far, this information is mostly provided in the form of high percentiles obtained from frequency distributions or return values. More detailed information and assessments of events that may cause extreme damages or have extreme consequences at the coast are so far still unavailable. We describe and compare two different approaches that may be used to identify highly unlikely but still physically possible and plausible events from model simulations. Firstly, in the case when consistent wind and tide-surge data are available, different metrics such as the height of the storm surge can be derived directly from the simulated water levels. Secondly, in cases where only atmospheric data are available, the so called effective wind may be used. The latter is the projection of the horizontal wind vector on that direction which is most effective in producing surges at the coast. Comparison of events identified by both methods show that they can identify extreme events but that knowledge of the effective wind alone does not provide sufficient information to identify the highest storm surges. Tracks of the low-pressure systems over the North Sea need to be investigated to find those cases, where the duration of the high wind is too short to induce extreme storm tides. On the other hand, factors such as external surges or variability in mean sea level may enhance surge heights and are not accounted for in estimates based on effective winds only. Results from the analysis of an extended data set suggest that unprecedented storm surges at the German North Sea coast are possible even without taking effects from rising mean sea level into account. The work presented is part of the ongoing project “Extreme North Sea Storm Surges and Their Consequences” (EXTREMENESS) and represents the first step towards an impact assessment for very severe storm surges which will serve as a basis for development of adaptation options and evaluation criteria.  相似文献   

4.
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5.
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6.
An analysis of today’s mean and extreme wave conditions in the North Sea and their possible future changes due to anthropogenic climate change are presented. The sea state was simulated for the 30-year period 2071–2100 using the wave model WAM and an ensemble of wind field data sets for four climate change realizations as driving data. The wind field data sets are based on simulation outputs from two global circulation models (GCMs: HadAM3H and ECHAM4/OPYC3) for two emission scenarios (A2 and B2, Intergovernmental Panel on Climate Change, Special Report on Emission Scenarios). They were regionalized by the Swedish Meteorological and Hydrological Institute using the regional climate model RCAO. The effects of the climate realizations on the sea state statistics were assessed by analyzing the differences between the patterns in the four CGM/emission scenario combinations and those in two control simulations representing reference wave climate conditions for the 30-year period 1961–1990. The analysis of the four emission scenario/GCM combinations has shown that the future long-term 99 percentile wind speed and significant wave height increase by up to 7% and 18%, respectively, in the North Sea, except for significant wave height off the English coast and to the north in the HadAM3H-driven simulation. The climate change response in the ECHAM4/OPYC3-forced experiments is generally larger than in the HadAM3H-driven simulations. The differences in future significant wave height between the different combinations are in the same order of magnitude as those between the control runs for the two GCMs. Nevertheless, there is agreement among the four combinations that extreme wave heights may increase in large parts in the southern and eastern North Sea by about 0.25 to 0.35 m (5–8% of present values) towards the end of the twenty first century in case of global warming. All combinations also show an increase in future frequency of severe sea state.  相似文献   

7.
The multi-decadal wave conditions in the North Sea can be influenced by anthropogenic climate change. That may lead to the intensification of wave extremes in the future and consequently increase risks for the coastal areas as well as for on- and offshore human activities. Potential changes caused by alteration of atmospheric patterns are investigated. Four transient climate projections (1961–2100), reflecting two IPCC emission scenarios (A1B and B1) and two different initial states, are used to simulate the wave scenarios. The potential wind-induced changes in waves are studied by comparing future statistics (2001–2100) with the corresponding reference conditions (1961–2000). Generally, there is a small increase in future 99th percentile significant wave height for most eastern parts of the North Sea towards the end of the twenty-first century. This small increase is superimposed by a strong variability of the annual extremes on time scales of decades. Opposite to the differences in wave height, the change in wave direction to more waves propagating east shows less decadal variability and is more uniform among all realizations. Nevertheless, temporal and spatial differences of the wave height in the four climate projections point to the uncertainties in the climate change signals.  相似文献   

8.
H. Moradkhani 《水文研究》2014,28(26):6292-6308
In this study the impact of climate change on runoff extremes is investigated over the Pacific Northwest (PNW). This paper aims to address the question of how the runoff extremes change in the future compared to the historical time period, investigate the different behaviors of the regional climate models (RCMs) regarding the runoff extremes and assess the seasonal variations of runoff extremes. Hydrologic modeling is performed by the variable infiltration capacity (VIC) model at a 1/8° resolution and the model is driven by climate scenarios provided by the North American Regional Climate Change Assessment Program (NARCCAP) including nine regional climate model (RCM) simulations. Analysis is performed for both the historical (1971–2000) and future (2041–2070) time periods. Downscaling of the climate variables including precipitation, maximum and minimum temperature and wind speed is done using the quantile‐mapping (QM) approach. A spatial hierarchical Bayesian model is then developed to analyse the annual maximum runoff in different seasons for both historical and future time periods. The estimated spatial changes in extreme runoffs over the future period vary depending on the RCM driving the hydrologic model. The hierarchical Bayesian model characterizes the spatial variations in the marginal distributions of the General Extreme Value (GEV) parameters and the corresponding 100‐year return level runoffs. Results show an increase in the 100‐year return level runoffs for most regions in particular over the high elevation areas during winter. The Canadian portions of the study region reflect higher increases during spring. However, reduction of extreme events in several regions is projected during summer. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

9.
The effect of climate change on extreme waves in front of the Dutch coast   总被引：1，自引：1，他引：0  
Coastal safety may be influenced by climate change, as changes in wave conditions (height, period, direction) may increase the vulnerability of dunes and other coastal defences. Dune erosion depends on mean water level, storm surge height and wave conditions. In this paper, we investigate the change in wave conditions in the North Sea in a changing climate. Until now, the effect of climate change on annual maximum wave conditions has been investigated, while events with higher return periods are actually most damaging for the coast (e.g. severe dune erosion). Here, we use the 17-member Ensemble SimulationS of Extreme weather under Non-linear Climate changeE (ESSENCE) change of climate change simulations, to analyse A1b-induced changes in the mean wave climate, the annual maxima and wave conditions with return periods of up to 1:10,000?years in front of the Dutch coast. The mean wave climate is not projected to differ between 1961–1990 and 2071–2100, with both wave height (H s) and wave period (T m) remaining unaltered. In the annual maximum conditions, a decrease is projected; especially, the annual T m maximum decreases significantly by 0.3 to 0.6?s over the whole study area. Furthermore, we find that the direction of the annual maximum wave conditions shifts from north and north-west to west and south-west for both H s and T m. This is induced by a similar shift in the direction of the extreme wind speeds. Despite the decrease in annual maximum conditions, the return H s and T m are not projected to change significantly as a result of climate change in front of the Dutch coast for the period 2071–2100 relative to 1961–1990.  相似文献   

10.
Cyclogenesis and long-fetched winds along the southeastern coast of South America may lead to floods in populated areas, as the Buenos Aires Province, with important economic and social impacts. A numerical model (SMARA) has already been implemented in the region to forecast storm surges. The propagation time of the surge in such extensive and shallow area allows the detection of anomalies based on observations from several hours up to the order of a day prior to the event. Here, we investigate the impact and potential benefit of storm surge level data assimilation into the SMARA model, with the objective of improving the forecast. In the experiments, the surface wind stress from an ensemble prediction system drives a storm surge model ensemble, based on the operational 2-D depth-averaged SMARA model. A 4-D Local Ensemble Transform Kalman Filter (4D-LETKF) initializes the ensemble in a 6-h cycle, assimilating the very few tide gauge observations available along the northern coast and satellite altimeter data. The sparse coverage of the altimeters is a challenge to data assimilation; however, the 4D-LETKF evolving covariance of the ensemble perturbations provides realistic cross-track analysis increments. Improvements on the forecast ensemble mean show the potential of an effective use of the sparse satellite altimeter and tidal gauges observations in the data assimilation prototype. Furthermore, the effects of the localization scale and of the observational errors of coastal altimetry and tidal gauges in the data assimilation approach are assessed.  相似文献   

11.
Climate models are increasingly being used to force dynamical wind wave models in order to assess the potential climate change-driven variations in wave climate. In this study, an ensemble of wave model simulations have been used to assess the ability of climate model winds to reproduce the present-day (1981–2000) mean wave climate and its seasonal variability for the southeast coast of Australia. Surface wind forcing was obtained from three dynamically downscaled Coupled Model Intercomparison Project (CMIP-3) global climate model (GCM) simulations (CSIRO Mk3.5, GFDLcm2.0 and GFDLcm2.1). The downscaling was performed using CSIRO’s cubic conformal atmospheric model (CCAM) over the Australian region at approximately 60-km resolution. The wind climates derived from the CCAM downscaled GCMs were assessed against observations (QuikSCAT and NCEP Re-analysis 2 (NRA-2) reanalyses) over the 1981–2000 period and were found to exhibit both bias in mean wind conditions (climate bias) as well as bias in the variance of wind conditions (variability bias). Comparison of the modelled wave climate with over 20 years of wave data from six wave buoys in the study area indicates that direct forcing of the wave models with uncorrected CCAM winds result in suboptimal wave hindcast. CCAM winds were subsequently adjusted for climate and variability bias using a bivariate quantile adjustment which corrects both directional wind components to align in distribution to the NRA-2 winds. Forcing of the wave models with bias-adjusted winds leads to a significant improvement of the hindcast mean annual wave climate and its seasonal variability. However, bias adjustment of the CCAM winds does not improve the ability of the model to reproduce the storm wave climate. This is likely due to a combination of storm systems tracking too quickly through the wave generation zone and the performance of the NRA-2 winds used as a benchmark in this study.  相似文献   

12.
The storm surge period of 13–16 November 1977 when there was a major positive surge followed by a negative surge in the Irish Sea is investigated using a two-dimensional unstructured mesh model of the west coast of Britain. The model accounts for tidal and external surge forcing across its open boundaries which are situated in the Celtic Sea and off the west coast of Scotland. Although this period has been examined previously using a uniform finite-difference model, and a finite element model, neither of these could resolve the Mersey estuary which is the focus of the present study. By using a finite element model with very high mesh resolution within the Mersey, the spatial variability of surge elevations and currents within the Mersey to rapidly changing surge dynamics can be examined. The mesh in the model varies from about 7 km in deep water, to the order of 100 m in the Mersey, with the largest mesh length reaching 17 km in deep offshore regions, and smallest of order 26 m occurring in shallow coastal regions of the Mersey estuary. The model accounts for wetting/drying which occurs in shallow water coastal areas. Calculations showed that during the positive surge period, the amplitude and speed of propagation of the surge was largest in the deep water channels. This gave rise to significant spatial variability of surge elevations and currents within the estuary. As wind stresses decreased over the Irish Sea, a negative surge occurred over Liverpool Bay and at the entrance to the Mersey. However, within the Mersey there was a local positive surge which continued to propagate down the estuary. This clearly showed that although the large scale response of the Irish Sea to changing wind fields occurred rapidly, the response in the Mersey was much slower. These calculations with a west coast variable mesh model that included a high-resolution representation of the Mersey revealed for the first time how elevations and currents within the Mersey responded to Irish Sea surges that rapidly changed from positive to negative.  相似文献   

13.
This study shows that storm surge model performance in the North Sea is mostly unaffected by the application of temporal variations of surface drag due to changes in sea state provided the choice of a suitable constant Charnock parameter in the sea-state-independent case. Including essential meteorological features on smaller scales and minimising interpolation errors by increasing forcing data resolution are shown to be more important for the improvement of model performance particularly at the high tail of the probability distribution. This is found in a modelling study using WAQUA/DCSMv5 by evaluating the influence of a realistic air-sea momentum transfer parameterization and comparing it to the influence of changes in the spatial and temporal resolution of the applied forcing fields in an effort to support the improvement of impact and climate analysis studies. Particular attention is given to the representation of extreme water levels over the past decades based on the example of the Netherlands. For this, WAQUA/DCSMv5 is forced with ERA-Interim reanalysis data. Model results are obtained from a set of different forcing fields, which either (i) include a wave-state-dependent Charnock parameter or (ii) apply a constant Charnock parameter (α C h =?0.032) tuned for young sea states in the North Sea, but differ in their spatial and/or temporal resolution. Increasing forcing field resolution from roughly 79 to 12 km through dynamically downscaling can reduce the modelled low bias, depending on coastal station, by up to 0.25 m for the modelled extreme water levels with a 1-year return period and between 0.1 m and 0.5 m for extreme surge heights.  相似文献   

14.
A two-dimensional coupled tide-surge model was used to investigate the effects of tide-surge interactions on storm surges along the coast of the Bohai Sea, Yellow Sea, and East China Sea. In order to estimate the impacts of tide-surge interactions on storm surge elevations, Typhoon 7203 was assumed to arrive at 12 different times, with all other conditions remaining constant. This allowed simulation of tide and total water levels for 12 separate cases. Numerical simulation results for Yingkou, Huludao, Shijiusuo, and Lianyungang tidal stations were analyzed. Model results showed wide variations in storm surge elevations across the 12 cases. The largest difference between 12 extreme storm surge elevation values was of up to 58 cm and occurred at Yingkou tidal station. The results indicate that the effects of tide-surge interactions on storm surge elevations are very significant. It is therefore essential that these are taken into account when predicting storm surge elevations.  相似文献   

15.
This work presents a methodology to make statistical significant and robust inferences on climate change from an ensemble of model simulations. This methodology is used to assess climate change projections of the Iberian daily-total precipitation for a near-future (2021–2050) and a distant-future (2069–2098) climates, relatively to a reference past climate (1961–1990).Climate changes of precipitation spatial patterns are estimated for annual and seasonal values of: (i) total amount of precipitation (PRCTOT), (ii) maximum number of consecutive dry days (CDD), (iii) maximum of total amount of 5-consecutive wet days (Rx5day), and (iv) percentage of total precipitation occurred in days with precipitation above the 95th percentile of the reference climate (R95T). Daily-total data were obtained from the multi-model ensemble of fifteen Regional Climate Model simulations provided by the European project ENSEMBLES. These regional models were driven by boundary conditions imposed by Global Climate Models that ran under the 20C3M conditions from 1961 to 2000, and under the A1B scenario, from 2001 to 2100, defined by the Special Report on Emission Scenarios of the Intergovernmental Panel on Climate Change.Non-parametric statistical methods are used for significant climate change detection: linear trends for the entire period (1961–2098) estimated by the Theil-Sen method with a statistical significance given by the Mann-Kendall test, and climate-median differences between the two future climates and the past climate with a statistical significance given by the Mann-Whitney test. Significant inferences of climate change spatial patterns are made after these non-parametric statistics of the multi-model ensemble median, while the associated uncertainties are quantified by the spread of these statistics across the multi-model ensemble. Significant and robust climate change inferences of the spatial patterns are then obtained by building the climate change patterns using only the grid points where a significant climate change is found with a predefined low uncertainty.Results highlight the importance of taking into account the spread across an ensemble of climate simulations when making inferences on climate change from the ensemble-mean or ensemble-median. This is specially true for climate projections of extreme indices such CDD and R95T. For PRCTOT, a decrease in annual precipitation over the entire peninsula is projected, specially in the north and northwest where it can decrease down to 400 mm by the middle of the 21st century. This decrease is expected to occur throughout the year except in winter. Annual CDD is projected to increase till the middle of the 21st century overall the peninsula, reaching more than three weeks in the southwest. This increase is projected to occur in summer and spring. For Rx5day, a decrease is projected to occur during spring and autumn in the major part of the peninsula, and during summer in northern Iberia. Finally, R95T is projected to decrease around 20% in northern Iberia in summer, and around 15% in the south-southwest in autumn.  相似文献   

16.
In this paper, a data assimilation scheme based on the adjoint free Four-Dimensional Variational(4DVar) method is applied to an existing storm surge model of the German North Sea. To avoid the need of an adjoint model, an ensemble-like method to explicitly represent the linear tangent equation is adopted. Results of twin experiments have shown that the method is able to recover the contaminated low dimension model parameters to their true values. The data assimilation scheme was applied to a severe storm surge event which occurred in the North Sea in December 5, 2013. By adjusting wind drag coefficient, the predictive ability of the model increased significantly. Preliminary experiments have shown that an increase in the predictive ability is attained by narrowing the data assimilation time window.  相似文献   

17.
The study evaluates relationships between the North Atlantic Oscillation (NAO) index and winter temperatures (including indices of extremes) over Europe in an ensemble of transient simulations of current global climate models (GCMs). We focus on identification of areas in which the NAO index is linked to winter temperatures and temperature extremes in simulations of the recent climate (1961–2000), and evaluate how these relationships change in climate change scenarios for the late 21st century (2071–2100). Most GCMs are able to reproduce main features of the observed links. The NAO index is more important for cold than warm extremes, which is also reproduced by the GCMs. However, all GCMs underestimate the magnitude of the NAO influence on cold extremes when averaged over northern and western Europe. For future scenarios, the links between the NAO and temperatures are mostly analogous to those in the recent climate, except for one GCM (CM3) in which the influence of the NAO on temperature almost disappears over whole Europe. This suggests that future scenarios from this particular GCM should be evaluated with caution. The NAO index is found to represent a useful covariate that explains an important fraction of variability of cold extremes in winter, and its incorporation into extreme value models for daily temperatures (and their possible changes under climate change) may improve performance of these models and reliability of estimates of extremes and their uncertainty.  相似文献   

18.
Storm-related sea level variations 1958–2002 along the North Sea coast from a high-resolution numerical hindcast are investigated and compared to the results of earlier studies. Considerable variations were found from year to year and over the entire period. The large-scale pattern of these variations is consistent with that derived from previous studies, while the magnitudes of the long-term trends differ. The latter is attributed to different analysis periods, improvements in the atmospheric forcing, and the enhanced spatial resolution of the numerical simulation. It is shown that the different analysis periods, in particular, represent an issue as the increase in storm-related sea levels was found to be weaker over the last few years that have not been included in earlier studies. These changes are consistent with observed changes of the storm climate over the North Sea. It is also shown that observed and hindcast trends may differ significantly. While the latter are in agreement with observed changes in the storm climate, it may be concluded that observed sea level changes along the North Sea coast comprise a considerable fraction that cannot be attributed to changes in the large-scale atmospheric circulation.
Ralf WeisseEmail:
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19.
The increasing frequency and/or severity of extreme climate events are becoming increasingly apparent over multi‐decadal timescales at the global scale, albeit with relatively low scientific confidence. At the regional scale, scientific confidence in the future trends of extreme event likelihood is stronger, although the trends are spatially variable. Confidence in these extreme climate risks is muddied by the confounding effects of internal landscape system dynamics and external forcing factors such as changes in land use and river and coastal engineering. Geomorphology is a critical discipline in disentangling climate change impacts from other controlling factors, thereby contributing to debates over societal adaptation to extreme events. We review four main geomorphic contributions to flood and storm science. First, we show how palaeogeomorphological and current process studies can extend the historical flood record while also unraveling the complex interactions between internal geomorphic dynamics, human impacts and changes in climate regimes. A key outcome will be improved quantification of flood probabilities and the hazard dimension of flood risk. Second, we present evidence showing how antecedent geomorphological and climate parameters can alter the risk and magnitude of landscape change caused by extreme events. Third, we show that geomorphic processes can both mediate and increase the geomorphological impacts of extreme events, influencing societal risk. Fourthly, we show the potential of managing flood and storm risk through the geomorphic system, both near‐term (next 50 years) and longer‐term. We recommend that key methods of managing flooding and erosion will be more effective if risk assessments include palaeodata, if geomorphological science is used to underpin nature‐based management approaches, and if land‐use management addresses changes in geomorphic process regimes that extreme events can trigger. We argue that adopting geomorphologically‐grounded adaptation strategies will enable society to develop more resilient, less vulnerable socio‐geomorphological systems fit for an age of climate extremes. © 2016 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.  相似文献   

20.
吴佳  周波涛  徐影 《地球物理学报》2015,58(9):3048-3060
基于24个CMIP5全球耦合模式模拟结果,分析了中国区域年平均降水和ETCCDI强降水量(R95p)、极端强降水量(R99p)对增暖的响应.定量分析结果显示,CMIP5集合模拟的当代中国区域平均降水对增温的响应较观测偏弱,而极端降水的响应则偏强.对各子区域气温与平均降水、极端降水的关系均有一定的模拟能力,并且极端降水的模拟好于平均降水.RCP4.5和RCP8.5情景下,随着气温的升高,中国区域平均降水和极端降水均呈现一致增加的趋势,中国区域平均气温每升高1℃,平均降水增加的百分率分别为3.5%和2.4%,R95p增加百分率为11.9%和11.0%,R99p更加敏感,分别增加21.6%和22.4%.就各分区来看,当代的区域性差异较大,未来则普遍增强,并且区域性差异减小,在持续增暖背景下,中国及各分区极端降水对增暖的响应比平均降水更强,并且越强的极端降水敏感性越大.未来北方地区平均降水对增暖的响应比南方地区的要大,青藏高原和西南地区的R95p和R99p增加最显著,表明未来这些区域发生暴雨和洪涝的风险将增大.  相似文献   

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