68 research outputs found
Atmospheric blocking: space-time links to the NAO and PNA
In the Northern hemisphere, regions characterized by an enhanced frequency of atmospheric blocking overlap significantly with those associated with the major extra-tropical patterns of large-scale climate variability—namely the North Atlantic Oscillation (NAO) and the Pacific North American (PNA) pattern. There is likewise an overlap in the temporal band-width of blocks and these climate patterns. Here the nature of the linkage between blocks and the climate patterns is explored by using the ERA-40 re-analysis data set to examine (1) their temporal and spatial correlation and (2) the interrelationship between blocks and the NAO/PNA. It is shown that a strong anti-correlation exists between blocking occurrence and the phase of the NAO (PNA) in the North Atlantic (western North Pacific), and that there are distinctive inter-basin differences with a clear geographical (over North Atlantic) and quantitative (over North Pacific) separation of typical blocking genesis/lysis regions during the opposing phases of the climate patterns. An Empirical Orthogonal Function (EOF) analysis points to a significant influence of blocking upon the NAO pattern (identifiable as the leading EOF in the Euro-Atlantic), and a temporal analysis indicates that long-lasting blocks are associated with the development of negative NAO/PNA index values throughout their life-time. In addition an indication of a cause-and effect relationship is set-out for the North Atlantic linkag
Multidecadal daily hail time series for Switzerland from radar proxies and ERA-5 reanalysis
Hailstorms regularly cause substantial damage and costs in Switzerland. Addressing this hail risk is challenging, especially in a changing climate, when hail
occurence and frequency may change. Recent studies showed significant differences in interannual variability of hail occurrence north and south of the Alps in
the last two decades (Barras et al. 2021, Nisi et al. 2018). However, this variability and its changes and drivers have not been analysed in a long-term approach.
To do that a new daily hail time series for Northern and Southern Switzerland from 1959 to today is produced from radar proxies and ERA5 reanalysis data
Hail time series from radar proxies for decadal variability of hail in Switzerland
In Switzerland hail regularly causes substantial damage to agriculture, cars, and infrastructure. However, addressing hail damage is challenging, as hail is related to severe thunderstorms, one of the most complex atmospheric phenomena due to its small spatial scale, vigorous development, and intricate physical interactions. In a changing climate, hail frequency and its patterns of occurrence may change, with potentially negative ramifications, e.g. when considering agricultural losses. According to the new Swiss hail climatologies (Madonna et al. 2018; Nisi et al. 2016; Nisi et al. 2020) there is a significant difference between the interannual hail variability on the north and south sides of the Alps. Understanding the drivers of this variability is essential for possible adaptation strategies. In contrast to North America, where important drivers of interannual variability of severe convection are well studied (see Tippett et al. 2015 and Allen et al. 2020), a comprehensive analysis of the year-to-year variability of hail in Switzerland has only been done for the last 20 years (in preparation by Katharina Schröer2). A long-term analysis, however, is still missing.
Therefore, this study presents a daily hail time series for Northern and Southern Switzerland from 1950 to today. The time series is produced from radar hail proxies and ERA-5 reanalysis data. Daily POH (Probability of Hail) data from MeteoSwiss is used to identify haildays in the region north and south of the Alps (plus 140km radar buffer) from 2002 to 2021 for the hail months April - September. The decision hailday yes/no is based on surpassing a POH ≥ 80 for a certain minimum footprint area of the domains. Then, a logistic regression model is constructed for each domain to predict the occurrence of a hailday depending on various environmental variables and indices. 70 different variables were tested. The predictors were chosen based on model performance, collinearity, and expert judgement. With the two best models, haildays are reconstructed back to 1950 for each region. The time series is then used to study the local and remote drivers of interannual variability, e.g. central European weather types, large-scale variability patterns, etc., as well as to investigate past changes or shifts in hailstorm seasonality. With this knowledge, we could improve our understanding of the meteorological-climatological variability, and, with the help of climate scenarios, infer about possible changes in the future
Climate change scenarios in use: heat stress in Switzerland
Under hot conditions the human body is able to regulate its core temperature via sweat evaporation, but this ability is reduced when air humidity is high. These conditions of high temperature and high humidity invoke heat stress which is a major problem for humans, in particular for vulnerable groups of the population and people under physical stress (e.g. heavy duty work without appropriate cooling systems). It is generally expected that the frequency, duration and magnitude of such unfavorable conditions will increase with further climate warming. In this respect, climate services play a crucial role by putting together climatological information and adaptation solutions to reduce future heat stress. We here assess the recently developed CH2018 scenarios for Switzerland (https://www.climate-scenarios.ch) in terms of heat stress conditions including their future projections. For this purpose, we characterize future extreme heat conditions with the use of climate analogs. By doing so, we attempt to produce more accessible climate information which might foster the use and understanding of regional-scale climate scenarios.
Here heat stress is expressed through the Wet Bulb Temperature (TW), which is a relatively simple proxy for heat stress on the human body and which depends non-linearly on temperature and humidity. It is assessed in terms of single-day events and heat stress spells. Projections based on the CH2018 scenarios indicate increasing heat stress over Switzerland, which is accentuated towards the end of the century. High heat stress conditions might be about 3?5 times more frequent for an emission scenario without mitigation (RCP 8.5) than for the mitigation scenario (RCP 2.6) by the end of the 21st century. The projected increase of heat stress results in more and longer heat stress spells, thus highlighting the importance of timely and precise prevention strategies in the context of heat-health action plans. Spatial climate analogs based on heat stress spells in Switzerland greatly vary depending on the emission scenario and are found in Central Europe under a mitigation scenario and in southern Europe under unmitigated warming.Financial support for this work is provided by the HEAT-SHIELD Project (European Commission HORIZON 2020, research and innovation programme under the grant agreement 668786). A.C. acknowledges support from Project COMPOUND (TED2021-131334A-I00) funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR
Challenges posed by and approaches to the study of seasonal-to-decadal climate variability
The tasks of providing multi-decadal climate projections and seasonal plus sub-seasonal climate predictions are of significant societal interest and pose major scientific challenges. An outline is presented of the challenges posed by, and the approaches adopted to, tracing the possible evolution of the climate system on these various time-scales. First an overview is provided of the nature of the climate system's natural internal variations and the uncertainty arising from the complexity and non-linearity of the system. Thereafter consideration is given sequentially to the range of extant approaches adopted to study and derive multi-decadal climate projections, seasonal predictions, and significant sub-seasonal weather phenomena. For each of these three time-scales novel results are presented that indicate the nature (and limitations) of the models used to forecast the evolution, and illustrate the techniques adopted to reduce or cope with the forecast uncertainty. In particular, the contributions (i) appear to exemplify that in simple climate models uncertainties in radiative forcing outweigh uncertainties associated with ocean models, (ii) examine forecast skills for a state-of-the-art seasonal prediction system, and (iii) suggest that long-lived weather phenomena can help shape intra-seasonal climate variability. Finally, it is argued, that co-consideration of all these scales can enhance our understanding of the challenges associated with uncertainties in climate predictio
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