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Precipitation sustains life and supports human activities, making its prediction one of the most societally relevant challenges in weather and climate modeling. Limitations in modeling precipitation underscore the need for diagnostics and metrics to evaluate precipitation in simulations and predictions. While routine use of basic metrics is important for documenting model skill, more sophisticated diagnostics and metrics aimed at connecting model biases to their sources and revealing precipitation characteristics relevant to how model precipitation is used are critical for improving models and their uses. This paper illustrates examples of exploratory diagnostics and metrics including 1) spatiotemporal characteristics metrics such as diurnal variability, probability of extremes, duration of dry spells, spectral characteristics, and spatiotemporal coherence of precipitation; 2) process-oriented metrics based on the rainfall–moisture coupling and temperature–water vapor environments of precipitation; and 3) phenomena-based metrics focusing on precipitation associated with weather phenomena including low pressure systems, mesoscale convective systems, frontal systems, and atmospheric rivers. Together, these diagnostics and metrics delineate the multifaceted and multiscale nature of precipitation, its relations with the environments, and its generation mechanisms. The metrics are applied to historical simulations from phases 5 and 6 of the Coupled Model Intercomparison Project. Models exhibit diverse skill as measured by the suite of metrics, with very few models consistently ranked as top or bottom performers compared to other models in multiple metrics. Analysis of model skill across metrics and models suggests possible relationships among subsets of metrics, motivating the need for more systematic analysis to understand model biases for informing model development.

Meteorological fronts are important due to their associated surface impacts, including extreme precipitation and extreme winds. Objective identification of fronts is therefore of interest in both operational weather prediction and research settings. The aim of this study is to produce a front identification algorithm based on earlier studies that is portable and scalable to different resolution datasets. We have made a number of changes to an earlier objective front identification algorithm, applied these to reanalysis datasets, and present the improvements associated with these changes. First, we show that a change in the order of operations yields smoother fronts with fewer breaks. Next, we propose the selection of the front identification thresholds in terms of climatological quantiles of the threshold fields. This allows for comparison between datasets of differing resolutions. Finally, we include a number of numerical improvements in the implementation of the algorithm and better handling of short fronts, which yield further benefits in the smoothness and number of breaks. This updated version of the algorithm has been made fully portable and scalable to different datasets in order to enable future climatological studies of fronts and their impacts. [ABSTRACT FROM AUTHOR]

Mediterranean cyclones are the primary driver of many types of surface weather extremes in the Mediterranean region, the association with extreme rainfall being the most established. Although smaller in size compared to Atlantic cyclones, they share a similar synoptic structure organised in distinct air streams, such as the warm conveyor belt and the dry intrusion, and are associated with low-level temperature fronts. The large-scale characteristics of a Mediterranean cyclone, the properties of the associated airflows, the interaction with the topography around the Mediterranean basin, and the season of occurrence, all contribute in determining its surface impacts. Here, we take these factors into account to establish statistical links between Mediterranean cyclones and weather compounds of two types, namely co-occurring rain-wind and wave-wind extremes. Specifically, compound extremes are attributed to a cyclone if they fall within the system's impact area, using a definition that is expressly tested on Mediterranean cyclones and on the compound selection. Our results show that the majority of Mediterranean compound rain-wind and wave-wind extremes occur in the neighbourhood of a Mediterranean cyclone, with peaks exceeding 80 %; the proportion of cyclone-related compounds is highest when considering transition seasons, and rain-wind events. Winter cyclones show highest compound frequency, matching with the peak winter occurrence of distinctively baroclinic cyclones. A novelty of this work, the de-construction of the cyclones' impact areas based on the presence of objectively-identified air streams and fronts, reveals a high incidence of both types of compound extremes below warm conveyor belt ascent regions, of wave-wind extremes below dry intrusions. [ABSTRACT FROM AUTHOR]

Taking advantage of the Polar Amplification Model Intercomparison Project simulations and using a Lagrangian objective feature tracking algorithm, we determine the response of extratropical cyclones to sea‐ice loss and consequent weakening of the equator‐to‐pole near‐surface temperature gradient. The wintertime storm tracks are found to shift equatorward in the North Atlantic and over Europe, and eastward in the North Pacific. In both regions, cyclones become weaker and slower, particularly on the poleward flank of the storm tracks. On average, there are fewer individual cyclones in the extratropics each winter, they last longer, are weaker, and travel more slowly. These changes are greatest over the Arctic, but still statistically significant in midlatitudes despite being small compared to internal variability. Inter‐model spread in cyclone responses are not strongly correlated with that in Arctic warming or Arctic amplification. Little change in summertime cyclones is found. Plain Language Summary: Using identically performed experiments from eight different climate models, we study how low pressure systems, known as cyclones or storms, may change as Arctic sea ice diminishes. An algorithm is used to identify the weather systems and track them across their lifecycle. In the wintertime, the typical path of storms over the Atlantic Ocean shifts southward toward the equator. Over the Pacific, the storm tracks shifts toward North America. Arctic sea‐ice loss causes there to be fewer storms each winter across the northern midlatitudes, and these tend to be weaker, slower moving, but longer lasting. These changes are largest over the Arctic itself but also found over mid‐latitudes. These changes may be important because the number, location, and character of storms control the winter weather over Europe, North America and Asia. In the summertime, we did not find any detectable impact of Arctic sea‐ice loss on storms. Key Points: The Northern Hemisphere winter storm tracks shift south and/or east in response to Arctic sea‐ice lossSea ice loss leads to fewer, slower, longer lasting, and weaker wintertime cyclonesResponses are small compared to internal variability, but larger in winter than summer [ABSTRACT FROM AUTHOR]

Using a large ensemble of simulations from the Polar Amplification Model Intercomparison Project (PAMIP) and phase 6 of the Coupled Model Intercomparison Project (CMIP6), we compare the response of winter-mean precipitation and daily extremes across the Northern Hemisphere to future Arctic sea ice loss and global ocean warming. The North Atlantic is simulated to become drier in response to future Arctic sea ice loss, with reduced precipitation intensity and more dry days. A wetting response to sea ice loss is simulated over the midlatitude Atlantic Ocean. These responses are robust across the eight models analyzed, albeit with differences in their magnitude and spatial pattern. The precipitation response to global ocean warming is broadly opposite in sign, but larger in magnitude, compared to the response to sea ice loss, over these regions. The precipitation responses to both sea ice loss and ocean warming are strongly related to coincident changes in storm density and intensity. More specifically, there is an equatorward shift of the North Atlantic storm track in response to sea ice loss, and a northeastern extension of the North Atlantic storm track and a weakening of the Mediterranean storm track in response to ocean warming. The linear combination of the responses of future Arctic sea ice loss and global ocean warming explain well the spatial pattern of the precipitation change at 28C global warming projected in CMIP6. Our results suggest that the projected future precipitation change over the North Atlantic reflects a “tug of war” between Arctic sea ice loss and global ocean warming, but the latter dominates over the former. [ABSTRACT FROM AUTHOR]

Extra-tropical cyclones (ETCs) are the main cause of precipitation in the mid-latitudes, and there is substantial evidence that ETC-related precipitation will increase in the future. However, little is known about how this will impact on the dynamical strength of ETCs, and whether the impact will differ for different types of ETCs. We quantify the linear relationship between maximum vorticity and ETC-related precipitation in the current and idealised future climates and determine how this relationship depends on the structure and characteristics of the ETC. Three 10-year-long aqua-planet simulations are performed with a state-of-the-art global model, OpenIFS, that differ in their specified sea surface temperature (SST) distributions. A control simulation, a uniform warming simulation, and a polar amplification simulation are performed. ETCs are objectively identified using the feature-tracking software TRACK, and k -means clustering is applied to the ETC precipitation field to group the ETCs into clusters with similar precipitation structures. In all experiments, ETCs with stronger maximum vorticity are associated with more precipitation. For all cyclones considered together, we find that the slope of the linear relationship between maximum cyclone vorticity and ETC precipitation is larger in the uniform warming and polar amplification simulations than in the control simulation. We hypothesise that if an increase in precipitation in warmer climates were to feed back, via diabatic heating and potential vorticity anomalies, onto the dynamical intensity of the ETCs, precipitation and vorticity would increase at similar rates, and hence the slope of the linear regression line between precipitation and vorticity would remain similar. Our results indicate either that there is no feedback or that the increase in vorticity due to diabatic heating is masked by the decrease in the Eady growth rate which occurs in both the uniform warming and polar amplification simulations compared to the control. The k -means clustering identifies four distinct and physically realistic types of ETCs which are present in all experiments meaning that the average precipitation patterns associated with ETCs are unlikely to change in the future. The strongest dependency between ETC maximum vorticity and precipitation occurs for ETCs that have the most precipitation associated with the warm front. ETCs with the heaviest precipitation along the cold front, which are the most intense storms in terms of maximum vorticity, also exhibit a strong dependency between precipitation and maximum vorticity, but this dependency is weaker and has a smaller correlation coefficient than the warm-front ETCs. Not all ETC types exhibit a strong dependency between precipitation and maximum vorticity. ETCs located at high latitudes with weak precipitation show little dependency due to the lack of moisture, whereas ETCs with the precipitation located mainly in the centre of the ETCs have the weakest linear regression slope, which is likely due to the lack of upper-level forcing. These results stress that despite small changes in the strength of the cyclones, the precipitation increases are large, indicating potential future increases in flooding associated with cyclones. [ABSTRACT FROM AUTHOR]

The Southern Hemisphere storm tracks are commonly simulated too far equatorward in climate models for the historical period. In the latest generation of climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6), the equatorward bias that was present in CMIP5 models still persists, although it is reduced considerably. A further reduction of the equatorward bias is found in atmosphere-only simulations. Using diagnostic large-scale fields, we propose that an increase in the midlatitude temperature gradients contributes to the reduced equatorward bias in CMIP6 and AMIP6 models, reducing the biases relative to ERA5. These changes increase baroclinicity in the atmosphere and are associated with a storm track that is situated farther poleward. In CMIP6 models, the poleward shift of the storm tracks is associated with an amelioration of cold midlatitude SST biases in CMIP5 and not through a reduction of the long-standing warm Southern Ocean SST bias. We propose that increases in midlatitude temperature gradients in the atmosphere and ocean are connected to changes in the cloud radiative effect. Persistent track density biases to the south of Australia are shown to be connected to an apparent standing-wave pattern originating in the tropics, which modifies the split jet structure near Australia and subsequently the paths of cyclones. [ABSTRACT FROM AUTHOR]