Property loss potentials for European midlatitude storms in a changing climate

Winter storms of the midlatitudes are an important factor for property losses caused by natural hazards over Europe. The storm series in early 1990 and late 1999 led to enormous economic damages and insured claims. Although significant trends in North Atlantic/European storm activity have not been identified for the last few decades, recent studies provide evidence that under anthropogenic climate change the number of extreme storms could increase, whereas the total number of cyclones may be slightly reduced. In this study, loss potentials derived from an ensemble of climate models using a simple storm damage model under climate change conditions are shown. For the United Kingdom and Germany ensemble-mean storm-related losses are found to increase by up to 37%. Furthermore, the interannual variability of extreme events will increase leading to a higher risk of extreme storm activity and related losses

Climate and socioeconomic influences on interannual variability of cholera in Nigeria

AbstractCholera is one of the most important climate sensitive diseases in Nigeria that pose a threat to public health because of its fatality and endemic nature. This study aims to investigate the influences of meteorological and socioeconomic factors on the spatiotemporal variability of cholera morbidity and mortality in Nigeria. Stepwise multiple regression and generalised additive models were fitted for individual states as well as for three groups of the states based on annual precipitation. Different meteorological variables were analysed, taking into account socioeconomic factors that are potentially enhancing vulnerability (e.g. absolute poverty, adult literacy, access to pipe borne water). Results quantify the influence of both climate and socioeconomic variables in explaining the spatial and temporal variability of the disease incidence and mortality. Regional importance of different factors is revealed, which will allow further insight into the disease dynamics. Additionally, cross validated models suggest a strong possibility of disease prediction, which will help authorities to put effective control measures in place which depend on prevention, and or efficient response

Extra-tropical cyclones in the present and future climate: a review

Based on the availability of hemispheric gridded data sets from observations, analysis and global climate models, objective cyclone identification methods were developed and applied to these data sets. Due to the large amount of investigation methods combined with the variety of different datasets, a multitude of results exist, not only for the recent climate period but also for the next century, assuming anthropogenic changed conditions. Different thresholds, different physical quantities, and considerations of different atmospheric vertical levels add to a picture that is difficult to combine into a common view of cyclones, their variability and trends, in the real world and in GCM studies. Thus, this paper will give a comprehensive review of the actual knowledge on climatologies of mid-latitude cyclones for the Northern and Southern Hemisphere for the present climate and for its possible changes under anthropogenic climate conditions

Improvement of decadal predictions of monthly extreme Mei-yu rainfall via a causality guided approach

While the improved performance of climate prediction systems has allowed better predictions of the East Asian Summer Monsoon rainfall to be made, the ability to predict extreme Mei-yu rainfall (MYR) remains a challenge. Given that large scale climate modes (LSCMs) tend to be better predicted by climate prediction systems than local extremes, one useful approach is to employ causality-guided statistical models (CGSMs), which link known LSCMs to improve MYR prediction. However, previous work suggests that CGSMs trained with data from 1979–2018 might struggle to model MYR in the pre-1978 period. One hypothesis is that this is due to potential changes in causal processes, which modulate MYR in different phases of the multidecadal variability, such as the Pacific decadal oscillation (PDO). In this study, we explore this hypothesis by constructing CGSMs for different PDO phases, which reflect the different phases of specific causal process, and examine the difference in quality as well as with respect to difference drivers and thus causal links between CGSMs of different PDO phases as well as the non-PDO phase specific CGSMs. Our results show that the set of predictors of CGSMs is PDO phase specific. Furthermore, the performance of PDO phase specific CGSMs are better than the non-PDO phase specific CGSMs. To demonstrate the added value of CGSMs, the PDO phase specific versions are applied to the latest UK Met Office decadal prediction system, DePreSys4, and it is shown that the root-mean squared errors of MYR prediction based on PDO phase specific CGSMs is consistently smaller than the MYR predicted based on the direct DePreSys4 extreme rainfall simulations. We conclude that the use of a causality approach improves the prediction of extreme precipitation based solely on known LSCMs because of the change in the main drivers of extreme rainfall during different PDO-phases

Test and data processing of a stepped-frequency GPR array

Recording of ground-penetrating radar data is very time consuming compared to other geophysical prospection methods like magnetics. The spatial resolution of the technique is so high, that a very dense survey grid is necessary to properly record the anomalies and to prevent aliasing. Additionally the antennas need direct contact with the ground, which reduces the maximum possible survey speed in the field. In magnetometry it has become standard to use several sensors to speed up field recordi..

An analysis of observed daily maximum wind gusts in the UK

The greatest attention to the UK wind climatology has focused upon mean windspeeds, despite a knowledge of gust speeds being essential to a variety of users. This paper goes some way to redressing this imbalance by analysing observed daily maximum gust speeds from a 43-station network over the period 1980–2005. Complementing these data are dynamically downscaled reanalysis data, generated using the PRECIS Regional Climate Modelling system, for the period 1959–2001. Inter-annual variations in both the observed and downscaled reanalysis gust speeds are presented, with a statistically significant (at the 95% confidence interval) 5% increase across the network in daily maximum gust speeds between 1959 and the early 1990s, followed by an apparent decrease. The benefit of incorporating dynamically downscaled reanalysis data is revealed by the fact that the decrease in gust speeds since 1993 may be placed in the context of a very slight increase displayed over the longer 1959–2001 period. Furthermore, the severity of individual windstorm events is considered, with high profile recent events placed into the context of the long term record. A daily cycle is identified from the station observations in the timing of the daily maximum gust speeds, with an afternoon peak occurring between 12:00–15:00, exhibiting spatial and intra-annual variations

Objective Identification of Tropical Cyclones with Severe Storm Surge Potential for the North-west Pacific

Storm surges caused by tropical cyclones can significantly impact on coastal areas in East Asia, including megacities e.g., in China. To inform effective adaptation and mitigation planning, a robust storm surge hazard assessment is essential. Unfortunately, the real frequency-intensity distribution of relevant storm-surge levels can only be estimated with large uncertainly based on limited historical observations.This study demonstrates the successful development of a two-step, objective and automated identification and selection approach of storm-surge relevant TCs for large model data sets where no ground truth verification is possible. In our approach, we combine for the first time two established identification and tracking tools originally developed for extra-tropical cyclones and storms and apply these to identify tropical cyclones. In the first step, we adapted the widely used Murray & Simmonds (1991) University of Melbourne tracking scheme (MS-Track) to the specific conditions of TC tracking in the North-west Pacific. In the second step, we apply the windstorm tracking tool WiTRACK to TC-induced severe wind fields to provide and attach the potential storm-surge relevant information in addition to just the core track provided by the MS-Track.By validating our results with ERA5 reanalysis data and IBTrACS, we show that our method is simple yet has a well comparable performance in detecting and assessing relevant TC events than more complex tracking approaches. Based on this performance this approach is well-designed and specifically intended to specific applications in CAT modelling approaches, e.g. for the creation of physically consistent event sets for storm surges

Research Data Supporting the publication “Improvement of decadal predictions of monthly extreme Mei-yu rainfall via a causality guided approach”

This data accompanies the peer-reviewed article Kelvin S. Ng et al. (2024): Improvement of decadal predictions of monthly extreme Mei-yu rainfall via a causality guided approach. Environ. Res.: Climate https://doi.org/10.1088/2752-5295/ad6631 Please see Data_description.pdf for more details

Understanding winter windstorm predictability over Europe

Winter windstorms belong to the most damaging meteorological events in the extra-tropics. Their impact on society makes it essential to understand and improve seasonal forecasts of these extreme events. Skilful predictions on a seasonal timescale have been shown in previous studies by investigating hindcasts from various forecast centres. This study aims to explain storm forecast skill based on relevant dynamical factors. Therefore, a number of factors which are known to influence either windstorms directly or their synoptic relevant systems, mid-latitude cyclones, are investigated. These factors are analysed for their relation to windstorm forecast performance based on a reanalysis (ERA5) and the seasonal hindcast of the UK Met Office (Global Seasonal forecasting system version 5, GloSea5). Within GloSea5, relevant dynamical factors are (1) validated with respect to their physical connections to windstorms, (2) investigated with respect to the seasonal forecast skill of the factors themselves, and (3) assessed on the relevance and influence of their forecast performance to and on windstorm forecast skill. Although not all investigated factors reveal a clear and consistent influence on windstorm forecast skill over Europe, core factors like mean sea level pressure gradient, sea surface temperature, equivalent potential temperature and Eady growth rate show consistent results within these three steps: their physical connection is well represented in the model; these factors are skilfully predicted in storm-relevant regions, and, consequently, this skill leads to increased forecast skill of winter windstorms over Europe. This study thus explains existing forecast skill in winter windstorms but also indicates potential for further model developments to improve seasonal winter windstorm predictions