LH surge in response to the treatment with GnRH analog or estradiol in ovariectomized buffaloes with or without progesterone pre-exposition

The aim of the present study was to evaluate the LH surge after EB (estradiol benzoate) or GnRH administration with or without P4 (progesterone) pre-exposure in ovariectomized (OVX) buffalo cows. Females were randomly assigned to receive an intravaginal P4 device (D0–D9). They were then given EB 24 h or GnRH 36 h post-P4 device removal (factorial 2×2, n=6 per group). Blood collection for LH measurement began 36 h after the P4 device removal and continued at 3 h intervals. The area under the LH curve (AUC; 30.2 ng2 and 13.41 ng2; P=0.007) and the area of the LH peak (AP; 19.0 ng2 and 8.9 ng2; P=0.009) were greater for EB than GnRH. We did not observe an effect of P4 pre-exposure on the AUC and AP. Furthermore, there was no interaction between P4 pre-exposure and EB or GnRH treatment on the AUC and AP. However, there was an interaction (P<0.01) between P4 pre-exposure and the type of inducer (EB or GnRH) to release a preovulatory-like LH surge at the beginning (BP), final (FP) and time (TP) of the LH peak. The P4 pre-exposure anticipated the BP (2.5 and 7.4 h), TP (6.0 and 12.0 h) and FP (11.5 and 17.1 h) when EB was used to induce a preovulatory-like LH surge (P<0.01). However, there was no effect of P4 pre-exposure on BP (0.4 and 0.4 h), TP (3.0 and 3.0 h) and FP (5.9 and 6.1 h) with GnRH treatment. There was also no effect of the pre-exposure to P4, type of inducer or interaction on the amplitude of the LH peak. We concluded that EB therefore led to greater LH release than GnRH, and pre-exposure to P4 before EB administration anticipated the preovulatory-like LH surge in buffalo cows.

Future storm surge impacts on insurable losses for the North Sea region

The influence of climate change on storm surges including increased mean sea level change and the associated insurable losses are assessed for the North Sea basin. In doing so, the newly developed approach couples a dynamical storm surge model with a loss model. The key element of the approach is the generation of a probabilistic storm surge event set. Together with parametrizations of the inland propagation and the coastal protection failure probability this enables the estimation of annual expected losses. The sensitivity to the parametrizations is rather weak except when the assumption of high level of increased mean sea level change is made. Applying this approach to future scenarios shows a substantial increase of insurable losses with respect to the present day. Superimposing different mean sea level changes shows a nonlinear behavior at the country level, as the future storm surge changes are higher for Germany and Denmark. Thus, the study exhibits the necessity to assess the socio-economic impacts of coastal floods by combining the expected sea level rise with storm surge projections.

Reanalysis of the Hamburg Storm Surge of 1962

In February 1962, Hamburg experienced its most catastrophic storm surge event of the 20th century. This paper analyses the event using the Twentieth Century Reanalysis (20CR) dataset. Responsible for the major flood was a strong low pressure system centred over Scandinavia that was associated with strong north-westerly winds towards the German North Sea coast – the ideal storm surge situation for the Elbe estuary. A comparison of the 20CR dataset with observational data proves the applicability of the reanalysis data for this extreme event.

The Storm Surge Event of the Netherlands in 1953

A disastrous storm surge hit the coast of the Netherlands on 31 January and 1 February 1953. We examine the meteorological situation during this event using the Twentieth Century Reanalysis (20CR) data set. We find a strong pressure gradient between Ireland and northern Germany accompanied by strong north-westerly winds over the North Sea. Storm driven sea level rise combined with spring tide contributed to this extreme event. The state of the atmosphere in 20CR during this extreme event is in good agreement with historical observational data

Cold surge episodes over southeastern Brazil - a potential vorticity perspective

Most intense cold surges and associated frost events in southern and southeastern Brazil are characterized by a large amplitude trough over South America extending toward tropical latitudes and a ridge to the west of it over the Pacific Ocean. In this study, potential vorticity (PV) streamers serve to examine the flow condition leading to cold surges. Case studies suggest that several PV anomalies are related to cold surge episodes: (1) the potential vorticity unit (2-PVU) isoline upstream of South America becomes progressively more distorted prior and during the cold surge episode, indicating a flow situation which is conducive for Rossby wave breaking and hence a flow which strongly deviates from zonality; (2) the initial stage of a cold surge episode is characterized by a northward bulging of high-PV air to the east of the Andes, resulting in a PV streamer whose northern end reaches Uruguay and southeastern Brazil; the strong PV gradient on its western flank constitutes a flow configuration that induces and maintains the transport of sub-Antarctic air toward the subtropics; (3) a distinct negative PV anomaly, a blocking, originates over the eastern South Pacific, upstream of the South America sector. A composite analysis of 27 cold surges is performed for stratospheric PV streamer frequency on several isentropic surfaces. It reveals that equatorward wave breaking over South America and the western South Atlantic represents an important potential component of the dynamics of intense cold surges. The indications are most pronounced around the isentropic levels of 320 K and immediately before the day with largest temperature drops over subtropical Brazil.

The 1872 Baltic Sea storm surge

On 13 November 1872, the Baltic Sea coast from Denmark to Pomerania was devastated by an extreme storm surge caused by high winds. This is still the strongest surge on record, and understanding its development can contribute to improved risk assessment and protection. In this paper we trace this event in sea-level pressure and wind data from the “Twentieth Century Reanalysis” (20CR) and compare the results with other observation-based data sources. The analysis shows that, in the ensemble mean of 20CR, the general development is qualitatively well depicted, but with much reduced strength compared to other data sets. The same is true when selecting the ensemble member with maximum wind speeds.

Probability inundation map for a scenario combining storm surge and sea-level rise

Coastal managers require reliable spatial data on the extent and timing of potential coastal inundation, particularly in a changing climate. Most sea level rise (SLR) vulnerability assessments are undertaken using the easily implemented bathtub approach, where areas adjacent to the sea and below a given elevation are mapped using a deterministic line dividing potentially inundated from dry areas. This method only requires elevation data usually in the form of a digital elevation model (DEM). However, inherent errors in the DEM and spatial analysis of the bathtub model propagate into the inundation mapping. The aim of this study was to assess the impacts of spatially variable and spatially correlated elevation errors in high-spatial resolution DEMs for mapping coastal inundation. Elevation errors were best modelled using regression-kriging. This geostatistical model takes the spatial correlation in elevation errors into account, which has a significant impact on analyses that include spatial interactions, such as inundation modelling. The spatial variability of elevation errors was partially explained by land cover and terrain variables. Elevation errors were simulated using sequential Gaussian simulation, a Monte Carlo probabilistic approach. 1,000 error simulations were added to the original DEM and reclassified using a hydrologically correct bathtub method. The probability of inundation to a scenario combining a 1 in 100 year storm event over a 1 m SLR was calculated by counting the proportion of times from the 1,000 simulations that a location was inundated. This probabilistic approach can be used in a risk-aversive decision making process by planning for scenarios with different probabilities of occurrence. For example, results showed that when considering a 1% probability exceedance, the inundated area was approximately 11% larger than mapped using the deterministic bathtub approach. The probabilistic approach provides visually intuitive maps that convey uncertainties inherent to spatial data and analysis.