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The NAEC catalogue comprises information on extratropical cyclone (ETC) tracks in North America (20–80 N and 180-0W) from January 1979 to December 2020. The source data used to produce this dataset is obtained from the ECMWF ERA5 reanalysis at 1-hour spatial resolution and 0.25x0.25 degree spatial resolution. In addition to the location, time, and intensity, this dataset also includes ETC-associated impact variables such as the near-surface wind speed, wind gust, and precipitation, averaged using different radii around the ETC center. Both absolute and relative (to the local climatology) measures are provided. This catalogue provides useful information for the assessment of ETC-induced impacts over North America.

The NA-ISD2ERA is a station-based gridded dataset of hourly 10-m wind speed, surface total precipitation, sea-level pressure, and 2-m air and dew point temperature observations interpolated on the regular 0.25° latitude-longitude ERA5 grid over North America for the 1990-2021 period. Station observations are from the Integrated Surface Database (ISD) developed by the National Centers for Environmental Information (NCEI) of the National Oceanic and Atmospheric Administration (NOAA) (Smith et al. 2011). It includes over 35,000 weather stations around the world of hourly to sub-hourly in situ observations for numerous variables such as wind speed, precipitation, sea-level pressure, air and dew point temperature. The NCEI ISD dataset is available at https://www.ncei.noaa.gov. ERA5 is the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (Hersbach et al., 2020). Quality checks implemented in ISD are used to select reliable observations. For each ERA5 grid cell and at each hour, the data are interpolated by taking the nearest available ISD observation to the grid cell center that is located within the targeted grid cell.

This catalogue includes seasonal mean precipitation fields from simulations and reanalysis used for the calculation of the Spatial Spin-Up Distance (SSUD). A total of seven simulation were conducted using the convection-permitting configuration (2.5-km grid spacing) of version 6 of the Canadian Regional Climate Model (CRCM6/GEM5; hereafter denoted as GEM2.5 for simplicity). The CRCM6/GEM5 version used here is based on version 5.0.2 of the Global Environmental Multiscale model (GEM5). GEM2.5 simulations were driven directly by the ERA5 reanalysis or by 12-km (GEM12) simulations also performed using the CRCM6/GEM5 model (which was in turn driven by the ERA5 reanalysis). The catalogue comprises seasonal mean precipitation fields from all seven GEM2.5 simulations, from the ERA5 reanalysis and from two GEM12 intermediate simulations (GEM12_SUN and GEM12_P3). Seasonal means were calculated using the common convention: December, January and February (DJF) for winter; March, April and May (MAM) for spring; June, July and August (JJA) for summer; and September, October and November (SON) for fall. Precipitations fields are given in mm/h.

The UQAM Heatwave ERA5 Archive and Temperatures (U-HEAT) catalog is a global dataset of temperature and heatwave data spanning 1940 to 2022. The temperature data features the maximum daily 2-m temperature, the 90th percentile of the maximum daily 2-m temperature, and an indication as to whether a given location (grid point) is experiencing a heatwave or not on a given day. The heatwave data includes metrics such as the duration, the cumulated intensity and the maximum intensity of heatwaves occuring in the study period as well as their location (grid point) and start date. Both the temperature and the heatwave metrics data were calculated from the ERA5 data produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). More information on the catalog can be found in the documentation and the README files. Le catalogue UQAM Heatwave ERA5 Archive and Temperatures (U-HEAT) est un jeu de données global de température et de vague de chaleur pour la période entre 1940 et 2022. Les données de température comprennent le maximum quotidien de la température à 2m, le 90e percentile du maximum quotidien de la température à 2m et une indication permettant de savoir si un lieu donné (point de grille) subit ou non une vague de chaleur pour un jour donné. Les données de vague de chaleur incluent des métriques comme la durée, l'intensité cumulée et l'intensité maximale de vagues de chaleur qui se sont produites durant la période d'étude en plus de leur emplacement (point de grille) et leur date de début. Les données de température et de vague de chaleur ont été calculées à partir du jeu de données ERA5 produit par le European Centre for Medium-Range Weather Forecasts (ECMWF). Le fichier de documentation et le fichier README peuvent être consultés pour obtenir plus d'information à propos du catalogue.

The Working Group I contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) provides a comprehensive assessment of the physical science basis of climate change. It considers in situ and remote observations; paleoclimate information; understanding of climate drivers and physical, chemical, and biological processes and feedbacks; global and regional climate modelling; advances in methods of analyses; and insights from climate services. It assesses the current state of the climate; human influence on climate in all regions; future climate change including sea level rise; global warming effects including extremes; climate information for risk assessment and regional adaptation; limiting climate change by reaching net zero carbon dioxide emissions and reducing other greenhouse gas emissions; and benefits for air quality. The report serves policymakers, decision makers, stakeholders, and all interested parties with the latest policy-relevant information on climate change. Available as Open Access on Cambridge Core.

Storms are the most significant meteorological phenomena that affect the formation of coasts and human livelihood along them. Thus, risks related to coastal storms, such as flooding, loss of land, shipping, and other offshore activity, have had a significant influence on coastal societies and their economies. In the early 21st century, anthropogenic climate change will affect the locations and intensities of coastal storminess, impacting society. Storms are studied not only by natural scientists but also by social scientists. The former deal with the climatologies, dynamics, and mechanisms of storms but also with the identification of different types of storms, such as extratropical baroclinic storms, explosive cyclones, tropical storms, polar lows, medicanes, Vb-cyclones, and Australian east coast storms. Their significance is often through their physical impacts, in particular ocean waves and storm surges, which were and are associated with massive losses of lives, sometimes up to several hundred thousand people, and wealth. The perceptions of what storms constitute were different in different cultural contexts and times. In earlier days, higher forces were responsible for such storms, which they used to transfer messages to humans, physically based ideas have been forming since the 16th century. Another significant historical development was societies preparing to reduce their vulnerability to storms and to implement practices of insurance and risk management.

Abstract The climate of the eastern seaboard of Australia is strongly influenced by the passage of low pressure systems over the adjacent Tasman Sea due to their associated precipitation and their potential to develop into extreme weather events. The aim of this study is to quantify differences in the climatology of east coast lows derived from the use of six global reanalyses. The methodology is explicitly designed to identify differences between reanalyses arising from differences in their horizontal resolution and their structure (type of forecast model, assimilation scheme, and the kind and number of observations assimilated). As a basis for comparison, reanalysis climatologies are compared with an observation-based climatology. Results show that reanalyses, specially high-resolution products, lead to very similar climatologies of the frequency, intensity, duration, and size of east coast lows when using spatially smoothed (about 300-km horizontal grid meshes) mean sea level pressure fields as input data. Moreover, at these coarse horizontal scales, monthly, interannual, and spatial variabilities appear to be very similar across the various reanalyses with a generally stronger agreement between winter events compared with summer ones. Results also show that, when looking at cyclones using reanalysis data at their native resolution (approaching 50-km grid spacing for the most recent products), uncertainties related to the frequency, intensity, and size of lows are very large and it is not clear which reanalysis, if any, gives a better description of cyclones. Further work is needed in order to evaluate the usefulness of the finescale information in modern reanalyses and to better understand the sources of their differences.

Abstract The Australian east coast low (ECL) is both a major cause of damaging severe weather and an important contributor to rainfall and dam inflow along the east coast, and is of interest to a wide range of groups including catchment managers and emergency services. For this reason, several studies in recent years have developed and interrogated databases of east coast lows using a variety of automated cyclone detection methods and identification criteria. This paper retunes each method so that all yield a similar event frequency within the ECL region, to enable a detailed intercomparison of the similarities, differences, and relative advantages of each method. All methods are shown to have substantial skill at identifying ECL events leading to major impacts or explosive development, but the choice of method significantly affects both the seasonal and interannual variation of detected ECL numbers. This must be taken into consideration in studies on trends or variability in ECLs, with a subcategorization of ECL events by synoptic situation of key importance.

Abstract This study evaluates the added value in the representation of surface climate variables from an ensemble of regional climate model (RCM) simulations by comparing the relative skill of the RCM simulations and their driving data over a wide range of RCM experimental setups and climate statistics. The methodology is specifically designed to compare results across different variables and metrics, and it incorporates a rigorous approach to separate the added value occurring at different spatial scales. Results show that the RCMs' added value strongly depends on the type of driving data, the climate variable, and the region of interest but depends rather weakly on the choice of the statistical measure, the season, and the RCM physical configuration. Decomposing climate statistics according to different spatial scales shows that improvements are coming from the small scales when considering the representation of spatial patterns, but from the large‐scale contribution in the case of absolute values. Our results also show that a large part of the added value can be attained using some simple postprocessing methods. , Key Points A rigorous methodology that allows evaluating the overall benefits of high‐resolution simulations The most reliable source of added value is the better representation of the spatial variability Substantial added value can also be attained using simple postprocessing methods