ALBERT

Description: This study has investigated serial (temporal) clustering of extra-tropical cyclones simulated by 17 climate models that participated in CMIP5. Clustering was estimated by calculating the dispersion (ratio of variance to mean) of 30 December-February counts of Atlantic storm tracks passing nearby each grid point. Results from single historical simulations of 1975-2005 were compared to those from historical ERA40 reanalyses from 1958-2001 ERA40 and single future model projections of 2069-2099 under the RCP4.5 climate change scenario. Models were generally able to capture the broad features in reanalyses reported previously: underdispersion/regularity (i.e. variance less than mean) in the western core of the Atlantic storm track surrounded by overdispersion/clustering (i.e. variance greater than mean) to the north and south and over western Europe. Regression of counts onto North Atlantic Oscillation (NAO) indices revealed that much of the overdispersion in the historical reanalyses and model simulations can be accounted for by NAO variability. Future changes in dispersion were generally found to be small and not consistent across models. The overdispersion statistic, for any 30 year sample, is prone to large amounts of sampling uncertainty that obscures the climate change signal. For example, the projected increase in dispersion for storm counts near London in the CNRMCM5 model is 0.1 compared to a standard deviation of 0.25. Projected changes in the mean and variance of NAO are insufficient to create changes in overdispersion that are discernible above natural sampling variations.

Description: This study investigates whether or not predictability always decreases for more extreme events. Predictability is measured by the Mean Squared Error (MSE), estimated here from the difference of pairs of ensemble forecasts, conditioned on one of the forecast variables (the “pseudo-observation”) exceeding a threshold. Using an exchangeable linear regression model for pairs of forecast variables, we show that the MSE can be decomposed into the sum of three terms: a threshold-independent constant, a mean term that always increases with threshold, and a variance term that can either increase, decrease, or stay constant with threshold. Using the Generalised Pareto Distribution to model wind speed excesses over a threshold, we show that MSE always increases with threshold at sufficiently high threshold. However, MSE can be a decreasing function of threshold at lower thresholds but only if the forecasts have finite upper bounds. The methods are illustrated by application to daily wind speed forecasts for London made using the 24 member Met Office Global and Regional Ensemble Prediction System from 1 Jan 2009 to 31 May 2011. For this example, the mean term increases faster than the variance term decreases with increasing threshold, and so predictability decreases for more extreme events.

Description: Extreme wave events in coastal zones are principal drivers of geomorphic change. Evidence of boulder entrainment and erosional impact during storms is increasing. However, there is currently poor time coupling between pre- and post-storm measurements of coastal boulder deposits. Importantly there are no data reporting shore platform erosion, boulder entrainment and/or boulder transport during storm events – rock coast dynamics during storm events are currently unexplored. Here, we use high-resolution (daily) field data to measure and characterise coastal boulder transport before, during and after the extreme Northeast Atlantic extra-tropical cyclone Johanna in March 2008. Forty-eight limestone fine-medium boulders (n = 46) and coarse cobbles (n = 2) were tracked daily over a 0.1 km 2 intertidal area during this multi-day storm. Boulders were repeatedly entrained, transported and deposited, and in some cases broken down (n = 1) or quarried (n = 3), during the most intense days of the storm. Eighty-one percent (n = 39) of boulders were located at both the start and end of the storm. Of these, 92% were entrained where entrainment patterns were closely aligned to wave parameters. These data firmly demonstrate rock coasts are dynamic and vulnerable under storm conditions. No statistically significant relationship was found between boulder size (mass) and net transport distance. Graphical analyses suggest that boulder size limits the maximum longshore transport distance but that for the majority of boulders lying under this threshold, other factors influence transport distance. Paired analysis of 20 similar sized and shaped boulders in different morphogenic zones demonstrates that geomorphological control affects entrainment and transport distance – where net transport distances were up to 39 times less where geomorphological control was greatest. These results have important implications for understanding and for accurately measuring and modelling boulder entrainment and transport. Coastal managers require these data for assessing erosion risk.

Description: The microtopography of two sandstone blocks with and without colonization of biofilms were measured with a traversing micro‐erosoin meter (TMEM) under different simulated environmental conditions. Two‐hourly microtopographic fluctuations of supratidal sandstone were mainly induced by the colonized biofilms and influenced by environmental factors. By increasing the magnitude and number of cycles of expansion and contraction, lithobiontic biofilms were proposed to play an erosive role in rock decay at hourly scale. Abstract In this study laboratory experiments were used to explore the role of biofilms, formed by lithobiontic microorganism communities, in causing hourly surface changes of supratidal sandstone and the potential linkage to long‐term rock decay. To isolate the influence of individual environmental factors (temperature and humidity) on rock surface changes (expansion and contraction), a colonized (biofilm‐covered) and a non‐colonized sandstone block (biofilm‐free) underwent the same univariate microclimatic simulations closely controlled by an environmental chamber. Simulations were run under three different light conditions, with a natural light lamp on, on and off at 20‐min intervals and off, to investigate the impact of light on rock surface dynamics. Measured with a traversing micro‐erosion meter (TMEM), two‐hourly microtopographic fluctuations of these two sandstone blocks were compared in the same environment. Induced by microclimatic variations, surface movements of significantly higher magnitude (12–120% under varying tempeature and 121–154% under varying humidity) and different change patterns were observed on the colonized block, indicating the primary role of biofilm in driving microtopographic fluctuations of supratidal sandstone. However, thermally driven changes of similar magnitude and pattern were observed on both surfaces, suggesting other mechanisms also operating on the non‐colonized rock surface in this process. Due to the sensitivity of biofilm microorganism communities to light, the magnitude and pattern of surface changes was impacted by light condition. Because biofilms increased the magnitude and number of cycles of expansion and contraction of the experimental rock surface, we propose that lithobiontic biofilms facilitate the detachment of grains and granular disintegration on the rock surface, consequently contributing to rock decay and accelerating the rate of breakdown of supratidal rock. This short‐term episode therefore needs to be superimposed on longer term studies to fully understand the role of biofilms in rock surface change. © 2019 John Wiley & Sons, Ltd.

Description: Ensemble forecasts are routinely used as a basis for probabilistic predictions. The skill of probabilistic predictions derived from ensemble forecasts depends on the number of ensemble members. We derive a new verification score, called the ensemble‐adjusted Ignorance Score, which can correct for the effect of limited ensemble size and therefore allows for a more robust comparison of forecasts based on different ensemble sizes. The unadjusted Ignorance Score (solid line) depends on the ensemble size m, assigning higher (worse) scores to smaller ensembles drawn from the same forecast distribution. The ensemble‐adjusted Ignorance Score (dashed line) proposed here does not depend on ensemble size and thus allows for a fair comparison of equivalent ensembles of different sizes. This study considers the application of the Ignorance Score (IS, also known as the Logarithmic Score) for ensemble verification. In particular, we consider the case where an ensemble forecast is transformed to a normal forecast distribution, and this distribution is evaluated by the IS. It is shown that the IS systematically depends on the ensemble size, such that larger ensembles yield better expected scores. An ensemble‐adjusted IS is proposed, which extrapolates the score of an m‐member ensemble to the score that the ensemble would achieve if it had fewer or more than m members. Using the ensemble adjustment, a fair version of the IS is derived, which is optimized if ensembles are statistically consistent with the observations. The benefit of the ensemble adjustment is illustrated by comparing ISs of ensembles of different sizes in a seasonal climate forecasting context and a medium‐range weather forecasting context. An ensemble‐adjusted score can be used for a fair comparison between ensembles of different sizes, and to accurately estimate the expected score of a large operational ensemble by running a much smaller hindcast ensemble.

Description: We investigate how waves are transformed across a shore platform as this is a central question in rock coast geomorphology. We present results from deployment of three pressure transducers over four days, across a sloping, wide (~200 m) cliff-backed shore platform in a macrotidal setting, in South Wales, United Kingdom. Cross shore variations in wave heights were evident under the predominantly low to moderate (significant wave height 〈 1.4 m) energy conditions measured. At the outer transducer 50 m from the seaward edge of the platform (163 m from the cliff) high tide water depths were 8+ m meaning that waves crossed the shore platform without breaking. At the mid platform position water depth was 5 m. Water depth at the inner transducer (6 m from the cliff platform junction) at high tide was 1.4 m. This shallow water depth forced wave breaking, thereby limiting wave heights on the inner platform. Maximum wave height at the middle and inner transducers were 2.41 and 2.39 m respectively and significant wave height 1.35 m and 1.34 m respectively. Inner platform high tide wave heights were generally larger where energy was up to 335% greater than near the seaward edge where waves were smaller. Infragravity energy was less than 13% of the total energy spectra with energy in the swell, wind and capillary frequencies accounting for 87% of the total energy. Wave transformation is thus spatially variable and is strongly modulated by platform elevation and the tidal range. While shore platforms in microtidal environments have been shown to be highly dissipative, in this macro-tidal setting up to 90% of the offshore wave energy reached the landward cliff at high tide, so that the shore platform cliff is much more reflective.

Description: ABSTRACT We describe the immediate impact of the 14 November 2016 Kaikoura magnitude 7.8 (Mw) earthquake on shore platforms and cliffs around Kaikoura Peninsula. The earthquake caused an instantaneous uplift of ~1.01 m of the peninsula. We resurveyed 7 profiles previously used for erosion monitoring and observed changes in the configuration of the shoreline. The coseismic uplift has fundamentally changed the process regime operating on the platforms and altered the future trajectory of shore platform and cliff development. Our observations highlight the interplay of waves, weathering, biology and tectonics. At this location tectonism strongly modulates the process regime, driving instantaneous changes in morphology and altering rates and patterns of erosion. Finally, the uplift of the Kaikoura coast has implications for changing resilience to climate change and sea level rise.

Description: In this study the dependence between the frequency and intensity of extratropical cyclones over the North Atlantic is investigated. A cyclone track database of extended October to March winters was obtained from the NCEP-NCAR reanalysis. Large positive correlation is found between winter cyclone counts and local sample mean vorticity over the exit region of the North Atlantic storm track in this cyclone track database. Conversely, negative correlation is found over the Gulf stream. Possible causes for the dependence are investigated by regressing winter cyclone counts and local sample mean vorticity on teleconnection indices with Poisson and linear models. The indices for the Scandinavian pattern, North Atlantic Oscillation and East Atlantic Pattern are able to account for most of the observed positive correlation over the North Atlantic. To consider the implications of frequency intensity dependence for the insurance industry an aggregate risk metric was used as a proxy for the annual aggregate insured loss. Here the aggregate risk is defined as the sum of the intensities of all events occurring within a season. Assuming independence between the frequency and intensity results in large biases in the variance and the extremes of the aggregate risk, especially over Scandinavia. Therefore including frequency intensity dependence in extratropical cyclone loss models is necessary to model the risk of extreme losses.