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Weather features, such as extratropical cyclones, atmospheric rivers (ARs), and fronts, contribute to substantial amounts of precipitation globally and are associated with different precipitation characteristics. However, future changes in these characteristics, as well as their representation in climate models, remain uncertain. We attribute 6‐hourly accumulated precipitation to cyclones, moisture transport axes (AR‐like features), fronts, and cold air outbreaks, and the combinations thereof in 10 ensemble members of the CESM2‐LE between 1960 and 2100 under the SSP3‐7.0 scenario. We find that, despite some biases in both precipitation and weather features, CESM2‐LE adeptly represents the precipitation characteristics associated with the different combinations of weather features. The combinations of weather features that contribute most to precipitation in the present climate also contribute the most to future changes, both due to changes in intensity as well as frequency. While the increase in precipitation intensity dominates the overall response for total precipitation in the storm track regions, the precipitation intensity for the individual weather features does not necessarily change significantly. Instead, approximately half of the increase in precipitation intensity in the storm track regions can be attributed to a higher occurrence of the more intensely precipitating combinations of weather features, such as the co‐occurrence of extratropical cyclones, fronts, and moisture transport axes. Plain Language Summary: Most precipitation is associated with weather features such as storms, atmospheric rivers, and fronts. Different combinations of these weather features are associated with different precipitation characteristics, but how these characteristics are represented in climate models as well as their possible future changes is not known. We attribute 6‐hourly accumulated precipitation to weather features, such as storms, fronts, and atmospheric rivers, from 1960 to 2100 under a high greenhouse emission scenario in a climate model. Despite some biases, the climate model represents the precipitation characteristics associated with these weather features well. We find that the weather features with the largest contribution to precipitation in the current climate also contribute the most to future changes in precipitation. The changes are caused by changes in both frequency of occurrence and precipitation intensity. Key Points: We attribute precipitation to cyclones, fronts, moisture transport axes, and cold air outbreaks in 10 ensemble members CESM2‐LE in 1960–2100CESM2‐LE adeptly represents the precipitation characteristics associated with the different weather features and their combinationsCo‐occurring weather features, associated with intense precipitation, contribute to a larger fraction of the precipitation in the future [ABSTRACT FROM AUTHOR]

Extreme winds are by far the largest contributor to Norway's insurance claims related to natural hazards. The predictive skills of four different damage functions are assessed for Norway at the municipality and national levels on daily and annual temporal scales using municipality-level insurance data and the high-resolution Norwegian hindcast (NORA3) wind speed data for the period 1985–2020. Special attention is given to extreme damaging events and occurrence probabilities of wind-speed-induced damage. Because of the complex topography of Norway and the resulting high heterogeneity of the population density, the wind speed is weighted with the population. The largest per capita losses and severe damage occur most frequently in the western municipalities of Norway, which are more exposed to incoming storms from the North Atlantic, whilst there are seldom any large losses further inland. There is no single damage function that outperforms others. However, a good agreement between the observed and estimated losses at municipality and national levels for a combination of damage functions suggests their usability in estimating severe damage associated with windstorms. Furthermore, the damage functions are able to successfully reconstruct the geographical pattern of losses caused by extreme windstorms with a high degree of correlation. From event occurrence probabilities, the present study devises a damage classifier that exhibits some skill at distinguishing between daily damaging and non-damaging events at the municipality level. While large-loss events are well captured, the skewness and zero inflation of the loss data greatly reduce the quality of both the damage functions and the classifier for moderate- and weak-loss events. [ABSTRACT FROM AUTHOR]

Weather features, such as extratropical cyclones (ETCs), atmospheric rivers (ARs), and fronts, contribute to substantial amounts of precipitation globally. However, previous estimates of how much these individual features contribute to precipitation are very sensitive to subjectively chosen metrics. Furthermore, there is no information on how these weather features contribute to precipitation poleward of 60° latitude. To alleviate these shortcomings, we introduce a more robust attribution method applicable at all latitudes. Based on ERA5, we present the first global climatology of the contributions from cyclones, fronts, moisture transport axes (MTAs; AR-like features), and cold air outbreaks, as well as their combinations, to summer and winter precipitation as well as extreme precipitation. Most of the precipitation in the midlatitudes relates to the combination of ETC, fronts, and MTAs (28%), while in polar regions most precipitation occurs within the ETC-only category (27%). Extreme precipitation events in all extratropical regions are predominantly associated with the combination of ETCs, fronts, and MTAs (46%). In the midlatitudes, the combination of ETCs, fronts, and MTAs occurs almost 4 times as often during extreme events compared to regular events. [ABSTRACT FROM AUTHOR]

The Norwegian government recently agreed on the goal 30by40, which involves opening Norwegian offshore areas to host 30 GW of installed wind power by 2040. We address this goal by presenting a first mapping of wind power suitability scores (WPSS) for the entire Norwegian economic zone (NEZ) using a multi‐criteria decision analysis framework (MCDA), namely, the analytical hierarchical process (AHP) approach. We obtain WPSS considering relevant criteria like wind resources, techno‐economic aspects, social acceptance, environmental considerations, and met‐ocean constraints such as wind and wave conditions. The results starts with a baseline scenario, where the criterion importance is pairwise compared in the context of balancing economic incentives and conflicting interests. Additionally, to reveal regions that are robust to changes in criterion importance, we carry out a sensitivity analysis by introducing three additional scenarios. These scenarios represent stereotypical actors with distinct preferences for siting of wind farms: the investor, the environmentalist, and the fisherman. The results show that the southern part of the NEZ is the most suitable and robust region for offshore wind power deployment. This region receives the highest suitability category ("very high" suitability for wind power application) throughout all the scenarios. Areas in the Norwegian part of the Barents Sea and the near‐coastal areas outside mid‐Norway are also well suited regions, but these are more sensitive to the choice of criterion importance. The use of AHP within the framework of MCDA is shown to be a promising tool for pinpointing the best Norwegian offshore areas for wind power application. [ABSTRACT FROM AUTHOR]

Extreme winds are by far the largest contributor to Norway's insurance claims related to natural hazards. The predictive skills of four different damage functions are assessed for Norway at the municipality and national levels on daily and annual temporal scales using municipality level insurance data and the high-resolution Norwegian hindcast (NORA3) wind speed data for the period 1985-2020. Special attention is given to extreme damaging events and occurrence probabilities of wind speed induced damages. Because of the complex topography of Norway and the resulting high heterogeneity of the population density' the wind speed is weighted with population. The largest per-capita losses and severe damages occur most frequently in the western municipalities of Norway more exposed to incoming storms from the North Atlantic whilst there are seldom any large losses further inland. There is no single damage function that outperforms others. However a good agreement between the observed and estimated losses at municipality and national levels for a combination of damage functions suggests their usability in estimating severe damages associated with windstorms. Furthermore' the damage functions are able to successfully reconstruct the geographical pattern of losses caused by extreme windstorms with a high degree of correlation. From event occurrence probabilities' the present study devises a damage classifier that exhibits some skill at distinguishing between daily damaging and non-damaging events at the municipality level. While large loss events are well captured' the skewness and zero-inflation of the loss data greatly reduces the quality of both the damage functions and the classifier for moderate and weak loss events. [ABSTRACT FROM AUTHOR]

We validate a new high-resolution (3 km) numerical mesoscale weather simulation for offshore wind power purposes for the time period 2004-2016 for the North Sea and the Norwegian Sea. The 3 km Norwegian reanalysis (NORA3) is a dynamically downscaled data set, forced with state-of-the-art atmospheric reanalysis as boundary conditions. We conduct an in-depth validation of the simulated wind climatology towards the observed wind climatology to determine whether NORA3 can serve as a wind resource data set in the planning phase of future offshore wind power installations. We place special emphasis on evaluating offshore wind-power-related metrics and the impact of simulated wind speed deviations on the estimated wind power and the related variability. We conclude that the NORA3 data are well suited for wind power estimates but give slightly conservative estimates of the offshore wind metrics. In other words, wind speeds in NORA3 are typically 5% (0.5ms-1) lower than observed wind speeds, giving an underestimation of offshore wind power of 10 %-20% (equivalent to an underestimation of 3 percentage points in the capacity factor) for a selected turbine type and hub height. The model is biased towards lower wind power estimates due to overestimation of the wind speed events below typical wind speed limits of rated wind power (u < 11-13ms-1) and underestimation of high-wind-speed events (u > 11-13ms-1). The hourly wind speed and wind power variability are slightly underestimated in NORA3. However, the number of hours with zero power production caused by the wind conditions (around 12% of the time) is well captured, while the duration of each of these events is slightly overestimated, leading to 25-year return values for zero-power duration being too high for the majority of the sites. The model performs well in capturing spatial co-variability in hourly wind power production, with only small deviations in the spatial correlation coefficients among the sites. We estimate the observation-based decorrelation length to be 425.3 km, whereas the model-based length is 19% longer. [ABSTRACT FROM AUTHOR]

Pore pressure is crucial in triggering debris slides and flows. Here we present measurements of ground water pore pressure and temperature recorded by a piezometer 1.6 m below the surface on a slope susceptible to debris flows in Western Norway. One of the largest oscillations in data collected over four years coincided with a debris flow event on the slope that occurred during storm Hilde on 15-16 November 2013. More than 100 landslides were registered during the storm. Rainfall totalled about 80-100 mm in 24 hours, locally up to 129 mm, and an additional trigger factor for the slides was a rapid rise in air temperature that caused snowmelt. On 15 November, the groundwater level in the hillslope rose by 10 cm per hour and reached 44 cm below the surface. At the same time, air temperature rose from 0 °C to over 8 °C, and the groundwater temperature dropped by 1.5 °C. The debris flow probably occurred late in the evening of 15 November, when the groundwater level reached its peak. Measurements of the groundwater in the hillslope in the period 2010-2013 show that the event in 2013 was not exceptional. Storm Dagmar on 25-26 December 2011 caused a similar rise in groundwater level, but did not trigger any failures. The data suggest that during heavy rainstorms the slope is in a critical state for a slide to be triggered for a short time - about 4-5 hours. [ABSTRACT FROM AUTHOR]

This study focuses on the analysis of the extreme precipitation event in Central Nepal on 19 July 2007 which was part of a sequence of rain events leading to the devastating South Asia flood of 2007. We investigate synoptic‐scale conditions using reanalyses and attribute moisture sources with a Lagrangian moisture source diagnostic. Further, we characterize the mesoscale precipitation event with a high‐resolution numerical simulation. The simulation reveals an intense wide convective event with a simulated 40 dBZ echo core of considerable horizontal extent (1,550 km2) exceeding a height of 12 km. Initially small convective cells were invigorated by high CAPE and a potentially unstable layer at mid‐tropospheric levels. This layer reached conditional instability adding latent energy to the system. Isolated convective cells organized upscale into a wide intense convective system, fuelled with moist low‐level inflow. The result was torrential rain with over 250 mm within 24 hr. Several synoptic‐scale conditions contributed to the intense development: (a) supply of moist air with the help of a typical monsoon break condition flow pattern, (b) anomalously significant moisture sources along this path due to prior precipitation events, (c) an upper‐tropospheric trough orienting the atmospheric flow against the Himalayas with associated quasi‐geostrophic forcing creating a favourable environment for convection, and (d) destabilized stratification due to an upslope flow. This analysis encompasses multiple scales and shows how a wide intense convective system, not unusual for this region, can be intensified by distinct synoptic constituents. This study describes processes that facilitate an extreme precipitation event in Nepal. We explain how these processes enable the unusual and intense convective development of a not unusual (for the considered region) convective system. The figure shows the simulated daily precipitation against the records of rain‐gauge stations in Nepal. [ABSTRACT FROM AUTHOR]