scholarly journals Towards using state-of-the-art climate models to help constrain estimates of unprecedented UK storm surges

2021 ◽  
Vol 21 (12) ◽  
pp. 3693-3712
Author(s):  
Tom Howard ◽  
Simon David Paul Williams
Keyword(s):  
Climate Model ◽  
State Of The Art ◽  
Tide Gauge ◽  
Storm Surges ◽  
Shape Parameters ◽  
Model Simulations ◽  
Shelf Seas ◽  
Coastal Flood Risk ◽  
Current Guidance ◽  
The Uk

Abstract. Our ability to quantify the likelihood of present-day extreme sea level (ESL) events is limited by the length of tide gauge records around the UK, and this results in substantial uncertainties in return level curves at many sites. In this work, we explore the potential for a state-of-the-art climate model, HadGEM3-GC3, to help refine our understanding of present-day coastal flood risk associated with extreme storm surges, which are the dominant driver of ESL events for the UK and wider European shelf seas. We use a 483-year present-day control simulation from HadGEM3-GC3-MM (1/4∘ ocean, approx. 60 km atmosphere in mid-latitudes) to drive a north-west European shelf seas model and generate a new dataset of simulated UK storm surges. The variable analysed is the skew surge (the difference between the high water level and the predicted astronomical high tide), which is widely used in analysis of storm surge events. The modelling system can simulate skew surge events comparable to the catastrophic 1953 North Sea storm surge, which resulted in widespread flooding, evacuation of 32 000 people, and hundreds of fatalities across the UK alone, along with many hundreds more in mainland Europe. Our model simulations show good agreement with an independent re-analysis of the 1953 surge event at the mouth of the river Thames. For that site, we also revisit the assumption of skew surge and tide independence. Our model results suggest that at that site for the most extreme surges, tide–surge interaction significantly attenuates extreme skew surges on a spring tide compared to a neap tide. Around the UK coastline, the extreme tail shape parameters diagnosed from our simulation correlate very well (Pearson's r greater than 0.85), in terms of spatial variability, with those used in the UK government's current guidance (which are diagnosed from tide gauge observations), but ours have smaller uncertainties. Despite the strong correlation, our diagnosed shape parameters are biased low relative to the current guidance. This bias is also seen when we replace HadGEM3-GC3-MM with a reanalysis, so we conclude that the bias is likely associated with limitations in the shelf sea model used here. Overall, the work suggests that climate model simulations may prove useful as an additional line of evidence to inform assessments of present-day coastal flood risk.

scholarly journals Towards using state-of-the-art climate models to help constrain estimates of unprecedented UK storm surges

2021 ◽  
Author(s):  
Tom Howard ◽  
Simon David Paul Williams
Keyword(s):  
Climate Model ◽  
State Of The Art ◽  
Tide Gauge ◽  
Storm Surges ◽  
Shape Parameters ◽  
Model Simulations ◽  
Shelf Seas ◽  
Coastal Flood Risk ◽  
Current Guidance ◽  
The Uk

Abstract. Our ability to quantify the likelihood of present-day extreme sea level (ESL) events is limited by the length of tide gauge records around the UK, and this results in substantial uncertainties in return level curves at many sites. In this work, we explore the potential for a state-of-the-art climate model, HadGEM3-GC3, to help refine our understanding of present-day coastal flood risk associated with extreme storm surges, which are the dominant driver of ESL events for the UK and wider European shelf seas. We use a 483-year present-day control simulation from HadGEM3-GC3-MM (1/4 degree ocean, approx 60 km atmosphere in mid-latitudes) to drive a northwest European shelf seas model and generate a new dataset of simulated UK storm surges. The variable analysed is the skew surge (the difference between the high water level and the predicted astronomical high tide), which is widely used in analysis of storm surge events.  The modelling system can simulate skew surge events comparable to the catastrophic 1953 North Sea storm surge, which resulted in widespread flooding, evacuation of 32 thousand people and hundreds of fatalities across the UK alone, along with many hundreds more in mainland Europe. Our model simulations show good agreement with an independent re-analysis of the 1953 surge event and suggest that a skew surge event of this magnitude has an expected frequency of about 1 in 500 years at the mouth of the river Thames.  For that site, we also revisit the assumption of skew surge/tide independence. Our model results suggest that at that site for the most extreme surges, tide/surge interaction significantly attenuates extreme skew surges on a spring tide compared to a neap tide. Around the UK coastline, the extreme tail shape parameters diagnosed from our simulation correlate very well (Pearson's r greater than 0.85), in terms of spatial variability, with those used in the UK government's current guidance (which are diagnosed from tide-gauge observations), but ours can be diagnosed without the use of a subjective prior. Despite the strong correlation, our diagnosed shape parameters are biased low relative to the current guidance. This bias is also seen when we replace HadGEM3-GC3-MM with a reanalysis, so we conclude that the bias is likely associated with limitations in the shelf sea model used here. Overall, the work suggests that climate model simulations may prove useful as an additional line of evidence to inform assessments of present-day coastal flood risk.

scholarly journals Radiational tides: their double-counting in storm surge forecasts and contribution to the Highest Astronomical Tide

Ocean Science ◽  
2018 ◽  
Vol 14 (5) ◽  
pp. 1057-1068 ◽  
Author(s):  
Joanne Williams ◽  
Maialen Irazoqui Apecechea ◽  
Andrew Saulter ◽  
Kevin J. Horsburgh
Keyword(s):  
Tide Gauge ◽  
Storm Surges ◽  
Double Counting ◽  
Atmospheric Conditions ◽  
Sea Level Changes ◽  
Astronomical Tide ◽  
Operational Forecasts ◽  
The Difference ◽  
The Uk ◽  
Total Water Level

Abstract. Tide predictions based on tide-gauge observations are not just the astronomical tides; they also contain radiational tides – periodic sea-level changes due to atmospheric conditions and solar forcing. This poses a problem of double-counting for operational forecasts of total water level during storm surges. In some surge forecasting, a regional model is run in two modes: tide only, with astronomic forcing alone; and tide and surge, forced additionally by surface winds and pressure. The surge residual is defined to be the difference between these configurations and is added to the local harmonic predictions from gauges. Here we use the Global Tide and Surge Model (GTSM) based on Delft-FM to investigate this in the UK and elsewhere, quantifying the weather-related tides that may be double-counted in operational forecasts. We show that the global S2 atmospheric tide is captured by the tide-and-surge model and observe changes in other major constituents, including M2. The Lowest and Highest Astronomical Tide levels, used in navigation datums and design heights, are derived from tide predictions based on observations. We use our findings on radiational tides to quantify the extent to which these levels may contain weather-related components.

Improved numerical solvers for coupled chemistry-climate model simulations

2020 ◽  
Author(s):  
Emre Esenturk
Keyword(s):  
Atmospheric Chemistry ◽  
Climate Model ◽  
Numerical Solutions ◽  
Iterative Algorithms ◽  
Box Model ◽  
Stiff Systems ◽  
Atmospheric Conditions ◽  
Model Simulations ◽  
Climate Model Simulations ◽  
The Uk

<p>A key and expensive part of coupled atmospheric chemistry-climate model simulations is the integration of gas phase chemistry, which involves dozens of species and hundreds of reactions. These species and reactions form a highly-coupled network of Differential Equations (DEs). There exists orders of magnitude variability in the lifetimes of the different species present in the atmosphere and so solving these DEs to obtain robust numerical solutions poses a “stiff problem”. With newer models having more species and increased complexity it is now becoming increasingly important to have chemistry solving schemes that reduce time but maintain accuracy.</p><p>A sound way to handle stiff systems is by using implicit DE solvers but the computational costs for such solvers are high due to internal iterative algorithms (e.g., Newton-Raphson (NR) methods). Here we propose an approach for implicit DE solvers that improves their convergence speed and robustness with relatively small modification in the code. We achieve this by using Quasi-Newton (QN) methods. We test our approach with numerical experiments on the UK Chemistry and Aerosol (UKCA) model, part of the UK Met Office Unified Model suite, run in both an idealized box-model environment and under realistic 3D atmospheric conditions. The box model tests reveal that the proposed method reduces the time spent in the solver routines significantly, with each QN call costing 27% of a call to the full NR routine. A series of experiments over a range of chemical environments was conducted with the box-model to find the optimal iteration steps to call the QN routine which result in the greatest reduction in the total number of NR iterations whilst minimising the chance of causing instabilities and maintaining solver accuracy. The 3D simulations show that our method for the chemistry solver, speeds up the chemistry routines by around 13%, resulting in a net improvement in overall run-time of the full model by approximately 3% with negligible loss in the accuracy (relative error of order 10<sup>-7</sup>) . The QN method also improves the robustness of the solver by significantly reducing (40% ) the number of grid cells which fail to converge hence avoiding unnecessary timestep adjustments. </p>

scholarly journals Climate change increases the probability of heavy rains like those of storm Desmond in the UK – an event attribution study in near-real time

2015 ◽  
Vol 12 (12) ◽  
pp. 13197-13216 ◽  
Author(s):  
G. J. van Oldenborgh ◽  
F. E. L. Otto ◽  
K. Haustein ◽  
H. Cullen
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Extreme Event ◽  
Initial Assessment ◽  
Model Simulations ◽  
Event Attribution ◽  
Climate Model Simulations ◽  
Using Data ◽  
The Uk ◽  
Precipitation Events

Abstract. On 4–6 December 2015, the storm "Desmond" caused very heavy rainfall in northern England and Scotland, which led to widespread flooding. Here we provide an initial assessment of the influence of anthropogenic climate change on the likelihood of one-day precipitation events averaged over an area encompassing northern England and southern Scotland using data and methods available immediately after the event occurred. The analysis is based on three independent methods of extreme event attribution: historical observed trends, coupled climate model simulations and a large ensemble of regional model simulations. All three methods agree that the effect of climate change is positive, making precipitation events like this about 40 % more likely, with a provisional 2.5–97.5 % confidence interval of 5–80 %.

Global storm surges during a past warm climate, the Last Interglacial

2020 ◽  
Author(s):  
Pepijn Bakker ◽  
Paolo Scussolini ◽  
Sanne Muis ◽  
Job Dullaart ◽  
Alessio Rovere ◽  
...  
Keyword(s):  
Climate Model ◽  
State Of The Art ◽  
Storm Surges ◽  
Horizontal Resolution ◽  
Climate Variables ◽  
Last Interglacial ◽  
Warm Climate ◽  
Equilibrium Conditions ◽  
Temperature And Precipitation ◽  
First Time

<p>We present here a novel application of state-of-the-art surge modeling on a past climate of special interest. The Last Interglacial (LIG; 125,000 years ago) was the latest instance of a climate (slightly) warmer than present: for this reason its study can inform on the response of several climate components to a climate state with partial resemblance to possible futures. Climate variables like temperature and precipitation have been extensively studied for the LIG. Here, we calculate for the first time the implications of the altered LIG atmospheric circulation (both in mean state and extremes) for storm surges along the global coastline. This presents particular interest since it is often claimed that a warmer climate may imply enhanced storminess in some ocean basins. We use sub-daily results from simulations of the LIG and of the pre-industrial periods with the climate model CESM1.2 (equipped with atmosphere module CAM5, with ca. 1 degree horizontal resolution) to force the Global Tide and Surge Model (GTSM) for 30-years at climate equilibrium conditions. We analyze patterns of storminess and of storm surges, and report on the anomalies in those metrics between the LIG and the pre-industrial climate. These results can help contextualize proxy-based reconstructions of storms of the LIG, as well as projections of storm surges in a future warmer climate. Finally, we also reconstruct tides of the LIG, aiming to provide useful constrains to paleo sea-level reconstructions.</p>

scholarly journals Evaluating Model Simulations of Twentieth-Century Sea-Level Rise. Part II: Regional Sea-Level Changes

2017 ◽  
Vol 30 (21) ◽  
pp. 8565-8593 ◽  
Author(s):  
B. Meyssignac ◽  
A. B. A Slangen ◽  
A. Melet ◽  
J. A. Church ◽  
X. Fettweis ◽  
...  
Keyword(s):  
Twentieth Century ◽  
Sea Level ◽  
Climate Models ◽  
Climate Model ◽  
Tide Gauge ◽  
Groundwater Depletion ◽  
Sea Level Changes ◽  
Tide Gauge Records ◽  
Model Simulations ◽  
Regional Sea Level

Twentieth-century regional sea level changes are estimated from 12 climate models from phase 5 of the Climate Model Intercomparison Project (CMIP5). The output of the CMIP5 climate model simulations was used to calculate the global and regional sea level changes associated with dynamic sea level, atmospheric loading, glacier mass changes, and ice sheet surface mass balance contributions. The contribution from groundwater depletion, reservoir storage, and dynamic ice sheet mass changes are estimated from observations as they are not simulated by climate models. All contributions are summed, including the glacial isostatic adjustment (GIA) contribution, and compared to observational estimates from 27 tide gauge records over the twentieth century (1900–2015). A general agreement is found between the simulated sea level and tide gauge records in terms of interannual to multidecadal variability over 1900–2015. But climate models tend to systematically underestimate the observed sea level trends, particularly in the first half of the twentieth century. The corrections based on attributable biases between observations and models that have been identified in Part I of this two-part paper result in an improved explanation of the spatial variability in observed sea level trends by climate models. Climate models show that the spatial variability in sea level trends observed by tide gauge records is dominated by the GIA contribution and the steric contribution over 1900–2015. Climate models also show that it is important to include all contributions to sea level changes as they cause significant local deviations; note, for example, the groundwater depletion around India, which is responsible for the low twentieth-century sea level rise in the region.

scholarly journals Storm surge forecasting: quantifying errors arising from the double-counting of radiational tides

2018 ◽  
Author(s):  
Joanne Williams ◽  
Maialen Irazoqui Apecechea ◽  
Andrew Saulter ◽  
Kevin J. Horsburgh
Keyword(s):  
Tide Gauge ◽  
Storm Surges ◽  
Double Counting ◽  
Atmospheric Conditions ◽  
Sea Level Changes ◽  
Astronomical Tide ◽  
Operational Forecasts ◽  
The Difference ◽  
The Uk ◽  
Total Water Level

Abstract. Tide predictions based on tide-gauge observations are not just the astronomical tides, they also contain radiational tides – periodic sea level changes due to atmospheric conditions and solar forcing. This poses a problem of double-counting for operational forecasts of total water level during storm surges. In some surge forecasting, a regional model is run as tide-only, with astronomic forcing alone; and tide-and-surge, forced additionally by surface winds and pressure. The surge residual is defined to be the difference between these configurations and is added to the local harmonic predictions from gauges. Here we use the Global Tide and Surge Model based on Delft-FM to investigate this in the UK and elsewhere, quantifying the weather-related tides that may be double-counted in operational forecasts. We show that the global S2 atmospheric tide is captured by the tide-surge model, and observe changes in other key constituents, including M2. We also quantify the extent to which the Highest Astronomical Tide, which is derived from tide predictions based on observations, may contain weather-related components.

scholarly journals A NOVEL HIGH-RESOLUTION STORM SURGE FORECAST FOR THE GERMAN BIGHT

2018 ◽  
pp. 80
Author(s):  
Sebastian Niehüser ◽  
Sönke Dangendorf ◽  
Arne Arns ◽  
Jürgen Jensen
Keyword(s):  
Storm Surge ◽  
High Frequency ◽  
State Of The Art ◽  
Tide Gauge ◽  
Storm Surges ◽  
Weather Forecast ◽  
The North ◽  
The North Sea ◽  
Numerical Weather Forecast ◽  
Model Output Statistics

Storm surges are one of the most dangerous natural hazards in coastal areas and have the ability to cause great damages including fatalities. To be prepared when another storm surge hits the coast, reliable storm surge forecasts are indispensable. Storm surge warnings are routinely provided for selected tide gauge locations along a coastline through state-of-the-art forecast systems. In Germany, the Federal Maritime and Hydrographic Agency (BSH) (in cooperation with the German Weather Service (DWD)) have the responsibility for storm surge forecasts and warnings along the German North and Baltic Sea coastlines. The operational system in place for the North Sea consists of numerical weather forecast systems, a surge model and model output statistics. It provides accurate high frequency water level forecasts up to six days ahead at selected tide gauge sites (Müller-Navarra and Knüpfer, 2010), but not for the coastline in between. Spatial forecasts are, however, currently not available for two reasons: first, the shallow coast with complex morphological structures leads to strong non-linearities between individual sites hampering simple interpolation schemes (Arns et al. 2015). Second, tidal predictions are limited to tide gauge locations, which do not fall dry during low tide, since the traditional estimation of tidal coefficients requires complete time series covering both low and high waters.

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