Storm observations by remote sensing and influences of gustiness on ocean waves and on generation of rogue waves

The impact of the gustiness on surface waves under storm conditions is investigated with focus on the appearance of wave groups with extreme high amplitude and wavelength in the North Sea. During many storms characterized by extremely high individual waves measured near the German coast, especially in cold air outbreaks, the moving atmospheric open cells are observed by optical and radar satellites. According to measurements, the footprint of the cell produces a local increase in the wind field at sea surface, moving as a consistent system with a propagation speed near to swell wave-traveling speed. The optical and microwave satellite data are used to connect mesoscale atmospheric turbulences and the extreme waves measured. The parameters of open cells observed are used for numerical spectral wave modeling. The North Sea with horizontal resolution of 2.5?km and with focus on the German Bight was simulated. The wind field “storm in storm,” including moving organized mesoscale eddies with increased wind speed, was generated. To take into account the rapid moving gust structure, the input wind field was updated each 5?min. The test cases idealized with one, two, and four open individual cells and, respectively, with groups of open cells, with and without preexisting sea state, as well the real storm conditions, are simulated. The model results confirm that an individual-moving open cell can cause the local significant wave height increase in order of meters within the cell area and especially in a narrow area of 1–2?km at the footprint center of a cell (the cell's diameter is 40–90?km). In a case of a traveling individual open cell with 15?m·s^?1 over a sea surface with a preexisting wind sea of and swell, a local significant wave height increase of 3.5?m is produced. A group of cells for a real storm condition produces a local increase of significant wave height of more than 6?m during a short time window of 10–20?min (cell passing). The sea surface simulation from modeled wave spectra points out the appearance of wave groups including extreme individual waves with a period of about 25?s and a wavelength of more than 350?m under the cell's footprint. This corresponds well with measurement of a rogue wave group with length of about 400?m and a period of near 25?s. This has been registered at FiNO-1 research platform in the North Sea during Britta storm on November 1, 2006 at 04:00 UTC. The results can explain the appearance of rogue waves in the German Bight and can be used for ship safety and coastal protection. Presently, the considered mesoscale gustiness cannot be incorporated in present operational wave forecasting systems, since it needs an update of the wind field at spatial and temporal scales, which is still not available for such applications. However, the scenario simulations for cell structures with appropriate travel speed, observed by optical and radar satellites, can be done and applied for warning messages.     

Radar rainfall estimation for flash flood forecasting in small urban watersheds

Radar rainfall estimation for flash flood forecasting in small, urban catchments is examined through analyses of radar, rain gage and discharge observations from the 14.3 km² Dead Run drainage basin in Baltimore County, Maryland. The flash flood forecasting problem pushes the envelope of rainfall estimation to time and space scales that are commensurate with the scales at which the fundamental governing laws of land surface processes are derived. Analyses of radar rainfall estimates are based on volume scan WSR-88D reflectivity observations for 36 storms during the period 2003–2005. Gage-radar analyses show large spatial variability of storm total rainfall over the 14.3 km² basin for flash flood producing storms. The ability to capture the detailed spatial variation of rainfall for flash flood producing storms by WSR-88D rainfall estimates varies markedly from event to event. As spatial scale decreases from the 14.3 km² scale of the Dead Run watershed to 1 km² (and the characteristic time scale of flash flood producing rainfall decreases from 1 h to 15 min) the predictability of flash flood response from WSR-88D rainfall estimates decreases sharply. Storm to storm variability of multiplicative bias in storm total rainfall estimates is a dominant element of the error structure of radar rainfall estimates, and it varies systematically over the warm season and with flood magnitude. Analyses of the 7 July 2004 and 28 June 2005 storms illustrate microphysical and dynamical controls on radar estimation error for extreme flash flood producing storms.     

Causes and underlying processes of measurement variability in field erosion plots in Mediterranean conditions

An understanding of the sources of variation in the use of erosion plots and of their feasibility to meet the objectives of each specific research project is key to improving future field designs, selecting data for modelling purposes and furthering knowledge of soil erosion processes. Our own field experiences from ongoing research on soil erosion processes since 1989, have allowed us to detect several methodological problems that cause measurement variability. Here several examples are presented concerning: (i) differences in long‐term soil erosion data between open and closed plots; (ii) differences in soil loss derived from replica soil erosion plots; and (iii) differences in soil loss data derived from plots at a range of spatial scales. Closed plots are not the most suitable method for long‐term monitoring of soil erosion rates due to the risk of exhaustion of available material within the plot. The difference in time after which exhaustion occurs depends on the surface soil characteristics, the climatological conditions and the size of the plots. We detected four and seven years as ‘time to exhaustion’. Different results are frequently obtained between pairs of replica plots. Differences up to a factor of nine have been detected in total soil loss between replica plots due to different spatial patterns of surface components. Different constraints appear depending on the spatial scale of measurement of soil loss. We obtained lower runoff percentages at coarser scales; however, larger sediment concentrations are observed at coarser scales (1·32 g l^?1, catchment; 0·30 g l^?1, 30 m²; 0·17 g l^?1, 1 m² scales). The smaller the plot, the larger the hydrological disconnection within the system, the lower the energy flows due to short distances and the quicker the response to runoff due to an artificial decrease of concentration times for continuous flow. Copyright © 2006 John Wiley & Sons, Ltd.     

Decadal variability and scales of the sea surface structure in the northern Ionian

The variability and scales of the sea surface structure of the northern Ionian Sea from January 1993 to December 2007 were studied by means of altimeter remotely-sensed weekly Sea Level Anomaly (SLA) objective maps. Variability in the sea surface structure was addressed by means of empirical orthogonal function (EOF) analysis and, assuming an exponential correlation model, scales of the SLA field were quantified as e-folding distances of the SLA autocorrelation function. The variability in the sea surface structure, described by the first three EOFs, which cumulatively explain 60.3% of the data set variance, is characterized by a large-scale structure with variability on a time scale of ∼10-13 years and, on shorter scales, an eddy system with variability on an annual scale. The variability in the large-scale structure describes an overturning of the SLA field, which took place in 1997, and determines a reversal of the geostrophic upper-layer circulation. As the large-scale circulation transition takes place, time-dependent spectral analysis of EOF coefficients shows a redistribution of the spectral energy from inter-annual to semi-annual and monthly components. Spatial scales display variability on an annual and inter-annual time scale. On the annual time scale, variability in spatial scales is characterized by longer values in summer-fall and shorter in winter-spring. Inter-annual variability in spatial scales is demonstrated by a remarkable drop in the values during fall in the period 1998-2000. We propose an explanation of the variability in horizontal scales in terms of the redistribution of water masses and related modifications of the vertical structure of the water column associated with different regimes of the basin-scale circulation.     

Sea level variability in the Gulf of Mexico since 1900 and its link to the Yucatan Channel and the Florida Strait flows

The long-term variability of sea level and surface flows in the Gulf of Mexico (GOM) is studied using global monthly sea level reconstruction (RecSL) for 1900–2015. The study explored the long-term relation between the dynamics of the GOM and inflows/outflows through the Yucatan Channel (YC) and the Florida Straits (FS). The results show a century-long trend of increased mean velocity and variability in the Loop Current (LC); however, no significant upward trend was found in the YC and FS flows, only increased variability. Empirical orthogonal function (EOF) analysis of sea surface height found spatial patterns dominated by variations in the LC and temporal variations on time scales ranging from a few months to multidecadal. The time evolution of each EOF mode of sea level is correlated with the velocity of either the LC, the YC, or the FS or some combination of the different flows. The mean sea level difference between the GOM and the northwestern Caribbean Sea was found to be influenced by the North Atlantic Oscillation (NAO), with unusually high differences during the 1970s when the NAO index was low and the Atlantic Ocean circulation was weak. Extreme peaks in SL difference coincide with the extension of the LC and the seasonal eddy shedding pattern. The observed seasonal cycle in the extension area of the LC as obtained from 20 years of altimeter data is significantly correlated (R = 0.63; confidence level = 98%) with the seasonal YC flow obtained from 116 years of the RecSL data. However, the same LC extension record had lower correlation (R = 0.45; confidence level = 90%) with the observed YC transport obtained from direct moored measurements over ~ 5 years, indicating the need for much longer measurements, since the LC extension and the YC flow are strongly affected by interannual and decadal variations. The study demonstrates the usefulness of even a coarse-resolution reconstruction for studies of regional ocean variability and climate change over longer time scales than current direct observations allow.

     

The assumption of uniform specific discharge: unsafe at any time?

Nearby catchments in the same landscape are often assumed to have similar specific discharge (runoff per unit catchment area). Five years of streamflow from 14 nested catchments in a 68 km² landscape was used to test this assumption, with the hypothesis that the spatial variability in specific discharge is smaller than the uncertainties in the measurement. The median spatial variability of specific discharge, defined as subcatchment deviation from the catchment outlet, was 33% at the daily scale. This declined to 24% at a monthly scale and 19% at an annual scale. These specific discharge differences are on the same order of magnitude as predicted for major land‐use conversions or a century of climate change. Spatial variability remained when considering uncertainties in specific discharge, and systematic seasonal patterns in specific discharge variation further provide confidence that these differences are more than just errors in the analysis of catchment area, rainfall variability or gauging. Assuming similar specific discharge in nearby catchments can thus lead to spurious conclusions about the effects of disturbance on hydrological and biogeochemical processes. Copyright © 2016 John Wiley & Sons, Ltd.     

Influence of rainfall and soil properties spatial aggregation on extreme flash flood response modelling: An evaluation based on the Sesia river basin,North Western Italy

High resolution radar rainfall fields and a distributed hydrologic model are used to evaluate the sensitivity of flood and flash flood simulations to spatial aggregation of rainfall and soil properties at catchment scales ranging from 75 to 983 km². Hydrologic modeling is based on a Hortonian infiltration model and a network-based representation of hillslope and channel flow. The investigation focuses on three extreme flood and flash flood events occurred on the Sesia river basin, North Western Italy, which are analysed by using four aggregation lengths ranging from 1 to 16 km. The influence of rainfall spatial aggregation is examined by using the flow distance as a spatial coordinate, hence emphasising the role of river network in the averaging of space–time rainfall. The effects of reduced and distorted rainfall spatial variability on peak discharge have been found particularly severe for the flash flood events, with peak errors up to 35% for rainfall aggregation of 16 km and at 983 km² catchment size. Effects are particularly remarkable when significant structured rainfall variability combines with relatively important infiltration volumes due to dry initial conditions, as this emphasises the non-linear character of the rainfall–runoff relationship. In general, these results confirm that the correct estimate of rainfall volume is not enough for the accurate reproduction of flash flood events characterised by large and structured rainfall spatial variability, even at catchment scales around 250 km². However, accurate rainfall volume estimation may suffice for less spatially variable flood events. Increasing the soil properties aggregation length exerts similar effects on peak discharge errors as increasing the rainfall aggregation length, for the cases considered here and after rescaling to preserve the rainfall volume. Moreover, peak discharge errors are roughly proportional to runoff volume errors, which indicates that the shape of the flood wave is influenced in a limited way by modifying the detail of the soil property spatial representation. Conversely, rainfall aggregation may exert a pronounced influence on the discharge peak by reshaping the spatial organisation of the runoff volumes and without a comparable impact on the runoff volumes.     

Summertime Characteristics of the Atmospheric Boundary Layer and Relationships to Ozone Levels over the Eastern United States

— This paper examines the spatial and temporal distributions of the mixing height, ventilation coefficient (defined as the product of mixing height and surface wind speed), and cloud cover over the eastern United States during the summer of 1995, using the high-resolution meteorological data generated by MM5 (Version 1), a mesoscale model widely used in air quality studies. The ability of MM5 to simulate the key temporal and spatial features embedded in the time series of observations of temperature, wind speed, and moisture is assessed using spectral decomposition methods. Also, mixing heights estimated from the MM5 outputs are compared with those derived from observations at a few locations where data with high temporal resolution are available in the Northeast. In addition, the uncertainties associated with the estimation of the evolution of the boundary layer during the morning time are examined. The results indicate that nighttime mixing heights averaged <200?m, rising to 1 km by 10 EST, and to about 2.5?km in the afternoon. Ventilation coefficients followed a similar diurnal pattern, increasing from 500?m²/s at night?to 15,000?m²/s in the afternoon; the increase due to the growing mixing height and increasing surface wind speeds. Spatial variability of these parameters was relatively small (coefficient of variation=0.25) at?night and in the afternoon when conditions were quasi-stationary, but increased (to 0.5) during morning?and evening hours when mixing heights and wind speeds were changing rapidly. Analyses of surface ozone observations from about 400 sites throughout the eastern United States indicate that days with numerous stations reporting surface ozone concentrations in excess of 80 ppb (i.e., “high ozone” days) generally had less daytime cloud cover, lower surface wind speeds, higher mixing heights, and lower ventilation coefficients than did comparable “low ozone” days. Such meteorological features are consistent with a synoptic anticyclone centered over the mid-south region (Kentucky, Tennessee). Low ozone days were characterized by more disturbed weather conditions (low pressure systems, fronts, greater cloud cover, and precipitation events). Ozone observations at two elevated platforms (～400?m agl) in Garner, NC, and Chicago, IL, indicated that ozone concentrations aloft were about 40% larger on “high ozone” days than on “low ozone” days. On average, high levels of ozone persist aloft for about 2 to 3 days. Strong vertical mixing in the daytime can bring this pool of upper-level ozone downward to augment surface ozone production. Since ozone can be transported downwind several hundred kilometers from its source region over this time scale, depending on upper-level winds, effective ozone control strategies must take into consideration spatial scales ranging from local to regional, and time scales of the order of several days.     

High-frequency vertical current observations in stratified seas

Although large-scale tidal and inertial motions dominate the kinetic energy and vertical current shear in shelf seas and ocean, short-scale internal waves at higher frequencies close to the local buoyancy frequency are of some interest for studying internal wave breaking and associated diapycnal mixing. Such waves near the upper limit of the inertio-gravity wave band are thought to have relatively short O (10²–10³ m) horizontal scales and to show mainly up- and downward motions, which contrasts with generally low aspect ratio large-scale ocean currents. Here, short-term vertical current (w) observations using moored acoustic Doppler current profiler (ADCP) are presented from a shelf sea, above a continental slope and from the open ocean. The observed w, with amplitudes between 0.015 and 0.05 m s⁻¹, all span a considerable part of the water column, which is not a small vertical scale O(water depth) or O (100–500 m, the maximum range of observations), with either 0 or π phase change. This implies that they actually represent internal waves of low vertical modes 1 or 2. Maximum amplitudes are found in layers of largest stratification, some in the main pycnocline bordering the frictional bottom boundary layer, suggesting a tidal source. These ‘pycnocline-w’ compose a regular train of (solitary) internal waves and linearly decrease to small values near surface and bottom.     

Coastal sea level variability in the US West Coast Ocean Forecast System (WCOFS)

Sea level variability along the US West Coast is analyzed using multi-year time series records from tide gauges and a high-resolution regional ocean model, the base of the West Coast Ocean Forecast System (WCOFS). One of the metrics utilized is the frequency of occurrences when model prediction is within 0.15 m from the observed sea level, F. A target level of F?=?90% is set by an operational agency. A combination of the tidal sea level from a shallow water inverse model, inverted barometer (IB) term computed using surface air pressure from a mesoscale atmospheric model, and low-pass filtered sea level from WCOFS representing the effect of coastal ocean dynamics (DYN) provides the most straightforward approach to reaching levels F>80%. The IB and DYN components each add between 5 and 15% to F. Given the importance of the DYN term bringing F closer to the operational requirement and its role as an indicator of the coastal ocean processes on scales from days to interannual, additional verification of the WCOFS subtidal sea level is provided in terms of the model-data correlation, standard deviation of the band-pass filtered (2–60 days) time series, the annual cycle amplitude, and alongshore sea level coherence in the range of 5–120-day periods. Model-data correlation in sea level increases from south to north along the US coast. The rms amplitude of model sea level variability in the 2–60-day band and its annual amplitude are weaker than observed north of 42 N, in the Pacific Northwest (PNW) coast region. The alongshore coherence amplitude and phase patterns are similar in the model and observations. Availability of the multi-year model solution allows computation and analysis of spatial maps of the coherence amplitude. For a reference location in the Southern California Bight, relatively short-period sea level motions (near 10 days) are incoherent with those north of the Santa Barbara Channel (in part, due to coastal trapped wave scattering and/or dissipation). At a range of periods around 60 days, the coastal sea level in Southern California is coherent with the sea surface height (SSH) variability over the shelf break in Oregon, Washington, and British Columbia, more than with the coastal SSH at the same latitudes.     

Spatial evolution equation of wind wave growth

Early in the thirties of the last century, the former Soviet scientists proposed characteristic waves (such as significant wave, and mean wave) to manifest the behavior of wind waves and began to study growth of wind waves. Later on Sverdrup and Munk[1] u…     

Spatial soil moisture scaling structure during Soil Moisture Experiment 2005

Soil moisture state and variability control many hydrological and ecological processes as well as exchanges of energy and water between the land surface and the atmosphere. However, its state and variability are poorly understood at spatial scales larger than the fields (i.e. 1 km²) as well as the ability to extrapolate field scale to larger spatial scales. This study investigates soil moisture profiles, their spatial organization, and physical drivers of variability within the Walnut Creek watershed, Iowa, during Soil Moisture Experiment 2005 and relates the watershed scale findings to previous field‐scale results. For all depths, the watershed soil moisture variability was negatively correlated with the watershed mean soil moisture and followed an exponential relationship that was nearly identical to that for field scales. This relationship differed during drying and wetting. While the overall time stability characteristics were improved with observation depth, the relatively wet and dry locations were consistent for all depths. The most time stable locations, capturing the mean soil moisture of the watershed within ± 0·9% volumetric soil moisture, were typically found on hill slopes regardless of vegetation type. These mild slope locations consistently preserve the time stability patterns from field to watershed scales. Soil properties also appear to impact stability but the findings are sensitive to local variations that may not be well defined by existing soil maps. Copyright © 2010 John Wiley & Sons, Ltd.     

Post-glacial rebound and present-day three-dimensional deformations

The WEGENER^† activities related to the study of post-glacial rebound are presented together with a review of the present state-of-the-art in this study field. Post-glacial rebound research is an unique tool for studying the viscoelastic behaviour of the Earth's mantle on time scales of thousands of years. The viscosity structure of the Earth's mantle determined from an inversion of observations of glacially induced deformations is a basic requirement for modelling long-term phenomena such as the convection in the Earth's mantle, and for better understanding unsolved questions such as the nature of the mantle discontinuities or the vertical scale of convection.First, an introduction to the scientific background is given, and the three principal ingredients for post-glacial rebound studies, namely the ice model, the Earth model, and the observations are briefly considered. For the ice model, the uncertainties due to a trade-off between ice model and Earth rheology are outlined. The different approaches used to model the Earth and its deformations in post-glacial rebound studies are discussed emphasising the preliminary nature of the derived rheologies and depth dependencies. The observations, in particular the relative sea-level changes and three-dimensional surface deformations, are described with special emphasis on observational gaps. Based on the discussion of the ingredients, an outline of the future developments in post-glacial rebound research is attempted with particular emphasis on the Earth model and the theory of deformations.For several decades extreme efforts have been made to precisely monitor the land uplift in Scandinavia. However, for the height component the existing data still are associated with large uncertainties while reliable data on the horizontal component are practically nil. The ongoing long-term (longer than ten years) spacegeodetic measurements are likely to provide the three-dimensional deformations with the spatial resolution and accuracy required in order to substantially contribute to post-glacial rebound studies. Thus, present-day three-dimensional deformations of the Earth's surface beneath and around the former ice sheets as a constraint for the mantle rheology and viscosity structure will increasingly become important as they become known from space-geodetic measurements with high spatial resolution and an accuracy approaching the mm/a-level.     

A method for finding the optimal predictor indices for local wave climate conditions

In this study, a method to obtain local wave predictor indices that take into account the wave generation process is described and applied to several locations. The method is based on a statistical model that relates significant wave height with an atmospheric predictor, defined by sea level pressure fields. The predictor is composed of a local and a regional part, representing the sea and the swell wave components, respectively. The spatial domain of the predictor is determined using the Evaluation of Source and Travel-time of wave Energy reaching a Local Area (ESTELA) method. The regional component of the predictor includes the recent historical atmospheric conditions responsible for the swell wave component at the target point. The regional predictor component has a historical temporal coverage (n-days) different to the local predictor component (daily coverage). Principal component analysis is applied to the daily predictor in order to detect the dominant variability patterns and their temporal coefficients. Multivariate regression model, fitted at daily scale for different n-days of the regional predictor, determines the optimum historical coverage. The monthly wave predictor indices are selected applying a regression model using the monthly values of the principal components of the daily predictor, with the optimum temporal coverage for the regional predictor. The daily predictor can be used in wave climate projections, while the monthly predictor can help to understand wave climate variability or long-term coastal morphodynamic anomalies.     

A field investigation of fracture compliance

A field measurement of fracture compliance is described. The aim was to determine how compliance scales with fracture size and, specifically, how laboratory measurements of fracture compliance compared with field estimates from sonic and seismic data. A test site was constructed, consisting of three 40 m vertical boreholes drilled in the floor of a Carboniferous Limestone quarry. Detailed knowledge of the rocks in the test area was obtained from core analysis, wireline logging and local area fracture mapping. Seismic cross‐hole surveys were performed using a sparker source with a dominant frequency of 2000 Hz and hydrophone receivers. The rocks had a compressional‐wave velocity anisotropy of 10%, which was attributed to the presence of predominantly horizontal, partially open fractures. Estimates of normal fracture compliance within a range from 2.5 × 10^?13 m/Pa to 3.5 × 10^?12 m/Pa were obtained from both the cross‐hole data and the sonic‐log data. This is an order of magnitude greater than values obtained from laboratory experiments which are reported elsewhere.     

Inference and uncertainty of snow depth spatial distribution at the kilometre scale in the Colorado Rocky Mountains: the effects of sample size,random sampling,predictor quality,and validation procedures

Historically, observing snow depth over large areas has been difficult. When snow depth observations are sparse, regression models can be used to infer the snow depth over a given area. Data sparsity has also left many important questions about such inference unexamined. Improved inference, or estimation, of snow depth and its spatial distribution from a given set of observations can benefit a wide range of applications from water resource management, to ecological studies, to validation of satellite estimates of snow pack. The development of Light Detection and Ranging (LiDAR) technology has provided non‐sparse snow depth measurements, which we use in this study, to address fundamental questions about snow depth inference using both sparse and non‐sparse observations. For example, when are more data needed and when are data redundant? Results apply to both traditional and manual snow depth measurements and to LiDAR observations. Through sampling experiments on high‐resolution LiDAR snow depth observations at six separate 1.17‐km² sites in the Colorado Rocky Mountains, we provide novel perspectives on a variety of issues affecting the regression estimation of snow depth from sparse observations. We measure the effects of observation count, random selection of observations, quality of predictor variables, and cross‐validation procedures using three skill metrics: percent error in total snow volume, root mean squared error (RMSE), and R². Extremes of predictor quality are used to understand the range of its effect; how do predictors downloaded from internet perform against more accurate predictors measured by LiDAR? Whereas cross validation remains the only option for validating inference from sparse observations, in our experiments, the full set of LiDAR‐measured snow depths can be considered the ‘true’ spatial distribution and used to understand cross‐validation bias at the spatial scale of inference. We model at the 30‐m resolution of readily available predictors, which is a popular spatial resolution in the literature. Three regression models are also compared, and we briefly examine how sampling design affects model skill. Results quantify the primary dependence of each skill metric on observation count that ranges over three orders of magnitude, doubling at each step from 25 up to 3200. Whereas uncertainty (resulting from random selection of observations) in percent error of true total snow volume is typically well constrained by 100–200 observations, there is considerable uncertainty in the inferred spatial distribution (R²) even at medium observation counts (200–800). We show that percent error in total snow volume is not sensitive to predictor quality, although RMSE and R² (measures of spatial distribution) often depend critically on it. Inaccuracies of downloaded predictors (most often the vegetation predictors) can easily require a quadrupling of observation count to match RMSE and R² scores obtained by LiDAR‐measured predictors. Under cross validation, the RMSE and R² skill measures are consistently biased towards poorer results than their true validations. This is primarily a result of greater variance at the spatial scales of point observations used for cross validation than at the 30‐m resolution of the model. The magnitude of this bias depends on individual site characteristics, observation count (for our experimental design), and sampling design. Sampling designs that maximize independent information maximize cross‐validation bias but also maximize true R². The bagging tree model is found to generally outperform the other regression models in the study on several criteria. Finally, we discuss and recommend use of LiDAR in conjunction with regression modelling to advance understanding of snow depth spatial distribution at spatial scales of thousands of square kilometres. Copyright © 2012 John Wiley & Sons, Ltd.     

North Sea wave conditions: an analysis of four transient future climate realizations

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.     

North Atlantic extratropical and subpolar gyre variability during the last 120 years: a gridded dataset of surface temperature,salinity, and density. Part 1: dataset validation and RMS variability

We present a binned annual product (BINS) of sea surface temperature (SST), sea surface salinity (SSS), and sea surface density (SSD) observations for 1896–2015 of the subpolar North Atlantic between 40° N and 70° N, mostly excluding the shelf areas. The product of bin averages over spatial scales on the order of 200 to 500 km, reproducing most of the interannual variability in different time series covering at least the last three decades or of the along-track ship monitoring. Comparisons with other SSS and SST gridded products available since 1950 suggest that BINS captures the large decadal to multidecadal variability. Comparison with the HadSST3 SST product since 1896 also indicates that the decadal and multidecadal variability is usually well-reproduced, with small differences in long-term trends or in areas with marginal data coverage in either of the two products. Outside of the Labrador Sea and Greenland margins, interannual variability is rather similar in different seasons. Variability at periods longer than 15 years is a large part of the total interannual variability, both for SST and SSS, except possibly in the south-western part of the domain. Variability in SST and SSS increases towards the west, with the contribution of salinity variability to density dominating that of temperature in the western Atlantic, except close to the Gulf Stream and North Atlantic Current in the southwest area. Weaker variability and larger relative temperature contributions to density changes are found in the eastern part of the gyre and south of Iceland.

     

Long-term statistics of potentially hazardous sea states in the North Sea 1958–2014

Significant wave height and mean wave period are two of the most commonly used parameters to describe wave climate, wave climate variability, and their potential long-term changes. While these parameters are generally useful to characterize the distribution of waves within a given sea state, they provide less information about potentially high-risk situations. Over the recent years, a number of criteria were suggested that are considered to better characterize high-risk situations and which could bear a potential for the development of safety warning indices. Based on a multi-decadal high-resolution wind-wave hindcast, a climatology of such parameters is developed for the North Sea covering the years 1958–2014. More specifically, average conditions, inter-annual variability and long-term changes for unusually steep, rapidly developing and crossing sea states are considered. Generally, there are pronounced spatial variations in the frequency of such sea states, while over time, there is some seasonal and inter-annual variability but no substantial long-term trend could be identified.     

Modeling the dynamic process of tsunami earthquake by liquid-solid coupling model

Tsunami induced by earthquake is an interaction problem between liquid and solid.Shallow-water wave equation is often used to modeling the tsunami,and the boundary or initial condition of the problem is determined by the displacement or velocity field from the earthquake under sea floor,usually no interaction between them is consid-ered in pure liquid model.In this study,the potential flow theory and the finite element method with the interaction between liquid and solid are employed to model the dynamic processes of the earthquake and tsunami.For model-ing the earthquake,firstly the initial stress field to generate the earthquake is set up,and then the occurrence of the earthquake is simulated by suddenly reducing the elastic material parameters inside the earthquake fault.It is dif-ferent from seismic dislocation theory in which the relative slip on the fault is specified in advance.The modeling results reveal that P,SP and the surface wave can be found at the sea surface besides the tsunami wave.The surface wave arrives at the distance of 600 km from the epicenter earlier than the tsunami 48 minutes,and its maximum amplitude is 0.55 m,which is 2 times as large as that of the sea floor.Tsunami warning information can be taken from the surface wave on the sea surface,which is much earlier than that obtained from the seismograph stations on land.The tsunami speed on the open sea with 3 km depth is 175.8 m/s,which is a little greater than that pre-dicted by long wave theory,(gh)1/2=171.5 m,and its wavelength and amplitude in average are 32 km and 2 m,respectively.After the tsunami propagates to the continental shelf,its speed and wavelength is reduced,but its amplitude become greater,especially,it can elevate up to 10 m and run 55 m forward in vertical and horizontal directions at sea shore,respectively.The maximum vertical accelerations at the epicenter on the sea surface and on the earthquake fault are 5.9 m/s2 and 16.5 m/s2,respectively,the later is 2.8 times the former,and therefore,sea water is a good shock