scholarly journals Analyzing Monthly Extreme Sea Levels with a Time-Dependent GEV Model

2007 ◽  
Vol 24 (5) ◽  
pp. 894-911 ◽  
Author(s):  
Fernando J. Méndez ◽  
Melisa Menéndez ◽  
Alberto Luceño ◽  
Inigo J. Losada
Keyword(s):  
San Francisco ◽  
Time Scales ◽  
Southern Oscillation ◽  
Efficient Estimation ◽  
Time Dependent ◽  
Seasonal Effects ◽  
Complete Analysis ◽  
Sea Levels ◽  
Data Variability ◽  
Extreme Sea Levels

Abstract A statistical model to analyze different time scales of the variability of extreme high sea levels is presented. This model uses a time-dependent generalized extreme value (GEV) distribution to fit monthly maxima series and is applied to a large historical tidal gauge record (San Francisco, California). The model allows the identification and estimation of the effects of several time scales—such as seasonality, interdecadal variability, and secular trends—in the location, scale, and shape parameters of the probability distribution of extreme sea levels. The inclusion of seasonal effects explains a large amount of data variability, thereby allowing a more efficient estimation of the processes involved. Significant correlation with the Southern Oscillation index and the nodal cycle, as well as an increase of about 20% for the secular variability of the scale parameter have been detected for the particular dataset analyzed. Results show that the model is adequate for a complete analysis of seasonal-to-interannual sea level extremes providing time-dependent quantiles and confidence intervals.

scholarly journals Influence of Terrestrial Precipitation on the Variability of Extreme Sea Levels along the Coast of Bangladesh

Water ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 2915
Author(s):  
Md. Anowarul Islam ◽  
Tomonori Sato
Keyword(s):  
Sea Level ◽  
Coastal Area ◽  
Southern Oscillation ◽  
Monsoon Season ◽  
Population Exposure ◽  
Sea Level Pressure ◽  
Indian Ocean Dipole Mode ◽  
Sea Levels ◽  
Extreme Sea Levels ◽  
Resultant Increase

The coastal area of Bangladesh is highly vulnerable to extreme sea levels because of high population exposure in the low-lying deltaic coast. Since the area lies in the monsoon region, abundant precipitation and the resultant increase in river discharge have raised a flood risk for the coastal area. Although the effects of atmospheric forces have been investigated intensively, the influence of precipitation on extreme sea levels in this area remains unknown. In this study, the influence of precipitation on extreme sea levels for three different stations were investigated by multivariate regression using the meteorological drivers of precipitation, sea level pressure, and wind. The prediction of sea levels considering precipitation effects outperformed predictions without precipitation. The benefit of incorporating precipitation was greater at Cox’s Bazar than at Charchanga and Khepupara, reflecting the hilly landscape at Cox’s Bazar. The improved prediction skill was mainly confirmed during the monsoon season, when strong precipitation events occur. It was also revealed that the precipitation over the Bangladesh area is insensitive to the El Niño-Southern Oscillation and Indian Ocean Dipole mode. The precipitation over northern Bangladesh tended to be high in the year of a high sea surface temperature over the Bay of Bengal, which may have contributed to the variation in sea level. The findings suggest that the effect of precipitation plays an essential role in enhancing sea levels during many extreme events. Therefore, incorporating the effect of terrestrial precipitation is essential for the better prediction of extreme sea levels, which helps coastal management and reduction of hazards.

scholarly journals Complex network approach for detecting tropical cyclones

2021 ◽  
Author(s):  
Shraddha Gupta ◽  
Niklas Boers ◽  
Florian Pappenberger ◽  
Jürgen Kurths
Keyword(s):  
Sea Level ◽  
Tropical Cyclones ◽  
Complex Network ◽  
Time Scales ◽  
Southern Oscillation ◽  
Volcanic Eruptions ◽  
Network Approach ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Climate Networks

AbstractTropical cyclones (TCs) are one of the most destructive natural hazards that pose a serious threat to society, particularly to those in the coastal regions. In this work, we study the temporal evolution of the regional weather conditions in relation to the occurrence of TCs using climate networks. Climate networks encode the interactions among climate variables at different locations on the Earth’s surface, and in particular, time-evolving climate networks have been successfully applied to study different climate phenomena at comparably long time scales, such as the El Niño Southern Oscillation, different monsoon systems, or the climatic impacts of volcanic eruptions. Here, we develop and apply a complex network approach suitable for the investigation of the relatively short-lived TCs. We show that our proposed methodology has the potential to identify TCs and their tracks from mean sea level pressure (MSLP) data. We use the ERA5 reanalysis MSLP data to construct successive networks of overlapping, short-length time windows for the regions under consideration, where we focus on the north Indian Ocean and the tropical north Atlantic Ocean. We compare the spatial features of various topological properties of the network, and the spatial scales involved, in the absence and presence of a cyclone. We find that network measures such as degree and clustering exhibit significant signatures of TCs and have striking similarities with their tracks. The study of the network topology over time scales relevant to TCs allows us to obtain crucial insights into the effects of TCs on the spatial connectivity structure of sea-level pressure fields.

Extreme sea levels at Rapa Nui (Easter Island) during intense atmospheric rivers

2021 ◽  
Author(s):  
Matías Carvajal ◽  
Patricio Winckler ◽  
René Garreaud ◽  
Felipe Igualt ◽  
Manuel Contreras-López ◽  
...  
Keyword(s):  
Easter Island ◽  
Rapa Nui ◽  
Atmospheric Rivers ◽  
Sea Levels ◽  
Extreme Sea Levels

El Niño driven extreme sea levels in an Eastern Pacific tropical river delta: Landward amplification and shift from oceanic to fluvial forcing

2021 ◽  
pp. 103529
Author(s):  
Jean-Philippe Belliard ◽  
Luis Dominguez-Granda ◽  
John A. Ramos-Veliz ◽  
Andrea M. Rosado-Moncayo ◽  
Jorge Nath ◽  
...  
Keyword(s):  
El Niño ◽  
El Nino ◽  
River Delta ◽  
Eastern Pacific ◽  
Tropical River ◽  
Sea Levels ◽  
Extreme Sea Levels

Estimating contribution of high-frequency sea-level oscillations to the extreme sea levels in the Adriatic Sea

2021 ◽  
Author(s):  
Krešimir Ruić ◽  
Jadranka Šepić ◽  
Maja Karlović ◽  
Iva Međugorac
Keyword(s):  
Time Series ◽  
Sea Level ◽  
High Frequency ◽  
Adriatic Sea ◽  
Tide Gauge ◽  
Data Series ◽  
Sea Levels ◽  
Short Period ◽  
Extreme Sea Levels ◽  
Sea Level Oscillations

<p>Extreme sea levels are known to hit the Adriatic Sea and to occasionally cause floods that produce severe material damage. Whereas the contribution of longer-period (T > 2 h) sea-level oscillations to the phenomena has been well researched, the contribution of the shorter period (T < 2 h) oscillations is yet to be determined. With this aim, data of 1-min sampling resolution were collected for 20 tide gauges, 10 located at the Italian (north and west) and 10 at the Croatian (east) Adriatic coast. Analyses were done on time series of 3 to 15 years length, with the latest data coming from 2020, and with longer data series available for the Croatian coast. Sea level data were thoroughly checked, and spurious data were removed. </p><p>For each station, extreme sea levels were defined as events during which sea level surpasses its 99.9 percentile value. The contribution of short-period oscillations to extremes was then estimated from corresponding high-frequency (T < 2 h) series. Additionally, for four Croatian tide gauge stations (Rovinj, Bakar, Split, and Dubrovnik), for period of 1956-2004, extreme sea levels were also determined from the hourly sea level time series, with the contribution of short-period oscillations visually estimated from the original tide gauge charts.  </p><p>Spatial and temporal distribution of contribution of short-period sea-level oscillations to the extreme sea level in the Adriatic were estimated. It was shown that short-period sea-level oscillation can significantly contribute to the overall extremes and should be considered when estimating flooding levels. </p>

scholarly journals Responses of groundwater to precipitation variability and ENSO in the Vietnamese Mekong Delta

2021 ◽  
Author(s):  
Phong V. V. Le ◽  
Hai V. Pham ◽  
Luyen K. Bui ◽  
Anh N. Tran ◽  
Chien V. Pham ◽  
...  
Keyword(s):  
Water Resources ◽  
Climate Variability ◽  
Time Scales ◽  
Groundwater Level ◽  
Southern Oscillation ◽  
Mekong Delta ◽  
Precipitation Variability ◽  
Annual Precipitation ◽  
Aquifer Recharge ◽  
Deep Aquifers

Abstract Groundwater is a critical component of water resources and has become the primary water supply for agricultural and domestic uses in the Vietnamese Mekong Delta (VMD). Widespread groundwater level declines have occurred in the VMD over recent decades, reflecting that extraction rates exceed aquifer recharge in the region. However, the impacts of climate variability on groundwater system dynamics in the VMD remain poorly understood. Here, we explore recent changes in groundwater levels in shallow and deep aquifers from observed wells in the VMD and investigate their relations to the annual precipitation variability and El Niño–Southern Oscillation (ENSO). We show that groundwater level responds to changes in annual precipitation at time scales of approximately 1 year. Moreover, shallow (deep) groundwater in the VMD appears to correlate with the ENSO over intra-annual (inter-annual) time scales. Our findings reveal a critical linkage between groundwater level changes and climate variability, suggesting the need to develop an understanding of the impacts of climate variability across time scales on water resources in the VMD.

The northern and the eastern Adriatic Sea floods: connecting the extreme sea-levels to cyclone pathways 

2021 ◽  
Author(s):  
Tihana Dević ◽  
Jadranka Šepić ◽  
Darko Koračin
Keyword(s):  
Sea Level ◽  
Tide Gauge ◽  
Middle Eastern ◽  
Origin Time ◽  
Northern Adriatic ◽  
Sea Levels ◽  
North West ◽  
Mediterranean Cyclones ◽  
Extreme Sea Levels ◽  
The Moment

<p>An objective method for tracking pathways of cyclone centres over Europe was developed and applied to the ERA-Interim reanalysis atmospheric data (1979-2014). The method was used to determine trajectories of those Mediterranean cyclones which generated extreme sea levels along the northern and the eastern Adriatic coast during the period from 1979 to 2014. Extreme events were defined as periods during which sea level was above 99.95 percentile value of time series of hourly sea-level data measured at the Venice (northern Adriatic), Split (middle eastern Adriatic) and Dubrovnik (south-eastern Adriatic) tide-gauge stations. The cyclone pathways were tracked backwards from the moment closest to the moment of maximum sea level up to the cyclone origin time, or at most, up to 72 hours prior the occurrence of the sea-level maximum.</p><p>Our results point out that extreme sea levels in Venice normally appear during synoptic situations in which a cyclone centre is located to the south-west and north-west of Venice, i.e., when it can be found over the Gulf of Genoa, or the Alps. On the contrary, extreme sea levels in Dubrovnik are usually associates with cyclone centres above the middle Adriatic, whereas floods in Split seem to appear during both above-described types of situations.</p><p>Occurrence times and intensity of cyclones and extreme sea-levels was further associated with the NAO index. It has been shown that the deepest cyclones and corresponding extreme floods tend to occur during the negative NAO phase.   </p>

Multiple drivers of extreme sea levels in the northern Adriatic Sea

2021 ◽  
Author(s):  
Christian Ferrarin ◽  
Piero Lionello ◽  
Mirko Orlic ◽  
Fabio Raicich ◽  
Gianfausto Salvadori
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Adriatic Sea ◽  
Driving Factors ◽  
Northern Adriatic Sea ◽  
Relative Sea Level ◽  
Northern Adriatic ◽  
Sea Levels ◽  
Extreme Sea Levels ◽  
Relative Sea Level Rise

<p><span><span>Extreme sea levels at the coast result from the combination of astronomical tides with atmospherically forced fluctuations at multiple time scales. Seiches, river floods, waves, inter-annual and inter-decad</span></span><span><span>al dynamics and relative sea-level rise can also contribute to the total sea level. While tides are usually well described and predicted, the effect of the different atmospheric contributions to the sea level and their trends are still not well understood. Meso-scale atmospheric disturbances, synoptic-scale phenomena and planetary atmospheric waves (PAW) act at different temporal and spatial scales and thus generate sea-level disturbances at different frequencies. In this study, we analyze the 1872-2019 sea-level time series in Venice (northern Adriatic Sea, Italy) to investigate the relative role of the different driving factors in the extreme sea levels distribution. The adopted approach consists in 1) isolating the different contributions to the sea level by applying least-squares fitting and Fourier decomposition; 2) performing a multivariate statistical analysis which enables the dependencies among driving factors and their joint probability of occurrence to be described; 3) analyzing temporal changes in extreme sea levels and extrapolating possible future tendencies. The results highlight the fact that the most extreme sea levels are mainly dominated by the non-tidal residual, while the tide plays a secondary role. The non-tidal residual of the extreme sea levels is attributed mostly to PAW surge and storm surge, with the latter component becoming dominant for the most extreme events. The results of temporal evolution analysis confirm previous studies according to which the relative sea-level rise is the major driver of the increase in the frequency of floods in Venice over the last century. However, also long term variability in the storm activity impacted the frequency and intensity of extreme sea levels and have contributed to an increase of floods in Venice during the fall and winter months of the last three decades.</span></span></p>

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