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Using a large ensemble of simulations from the Polar Amplification Model Intercomparison Project (PAMIP) and Coupled Model Intercomparison Project Phase 6 (CMIP6), we compare the response of winter-mean precipitation and daily extremes across the North Hemisphere in response to future Arctic sea-ice loss and global ocean warming. 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 analysed, 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 northeastern extension of the North Atlantic storm track and weakening of 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 2 °C global warming projected in CMIP6. Our results suggest that projected future precipitation change over North Atlantic reflects a ‘tug-of-war’ between Arctic sea-ice loss and global ocean warming, but the latter dominates over the former.

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.

The ability of climate models to represent extratropical storm tracks is vital to provide useful projections. In previous work, the representation of the extratropical storm tracks in the Northern Hemisphere was found to have improved from phase 5 to phase 6 of the Coupled Model Intercomparison Project (CMIP). Here we investigate the remaining and persistent biases in models from phase 6 of CMIP, by contrasting the atmosphere-only simulations (AMIP6) with the historical coupled simulations (CMIP6). The comparison of AMIP6 and CMIP6 simulations reveals that biases in sea surface temperatures (SSTs) in the coupled simulations across the North Pacific Ocean in winter modify the atmospheric temperature gradient, which is associated with an equatorward bias of the storm track. In the North Atlantic Ocean, cyclones do not propagate poleward enough in coupled simulations, which is partly driven by cold SSTs to the south of Greenland, decreasing the latent heat fluxes. In summer, excessive heating across central Asia and the Tibetan Plateau reduces the local baroclinicity, causing fewer cyclones to form and propagate from eastern China into the North Pacific in both the coupled and atmosphere-only simulations. Several of the biases described in the coupled models are reduced considerably in the atmosphere-only models when the SSTs are prescribed. For example, the equatorward bias of the North Pacific storm track is reduced significantly. However, other biases are apparent in both CMIP6 and AMIP6 (e.g., persistent reduction in track density and cyclogenesis over eastern Asia in summer), which are associated with other processes (e.g., land surface temperatures).

Extratropical cyclones produce extreme surface wind speeds and heavy rainfall which can individually and jointly influence impacts and potentially produce large aggregate impacts. Within this study, we assess the UKCP 12-member ensemble of local convection-permitting 2.2 km climate projections. We quantify the likelihood of cyclones producing large footprints of both extreme winds and rainfall over the UK in a control (1981-2000) and future (2061-2080, RCP8.5) climate simulation. Following this, we characterise the convective and frontal drivers of wet and windy conditions within cyclones, and identify the characteristics of cyclones, their tracks and interactions with the jet stream that contribute to the occurrence of large, combined footprints in the control and future simulations. The future simulations project an increased probability of extratropical cyclones producing extremely wet and windy conditions in the same storm, as well as an increase in the land area covered by such conditions. In both the control and future simulations, combined wet and windy extremes largely occur close to cold and warm fronts, likely due to the warm conveyor belt which produces heavy rainfall (due its ascent over the frontal boundaries) and high winds (when occurring within a region of tight pressure gradients). Cyclone composites reveal that the largest changes in joint extremes are closely located within the sector of cyclones where we expect to see the warm conveyor belt, suggesting their change arises partly through the response of this shared driver rather than being a simple consequence of increased rainfall due to thermodynamics. In further analysis, we identify favourable conditions and cyclone characteristics that lead to cyclones producing large rainfall and wind footprints over the UK.

Changes in the monsoon season rainfall over Peninsular Malaysia by the mid-21st century are examined using multi-model ensemble data from the CMIP6 HighResMIP experiments. We examine simulations of the present and future climate simulations run under a high emission scenario of greenhouse gases from the Shared Socioeconomic Pathways (SSP5-8.5). The combined effects of horizontal and vertical resolutions on the projected changes in monsoon rainfall and associated environmental fields are investigated by comparing the ensemble mean of the projected changes utilizing appropriate multi-model groupings. The results indicate a projected decrease (by up to 11% near Mersing of eastern Johor, for the period 2031–2050 relative to 1981–2000) in monsoon precipitation along the southeastern coast of Peninsular Malaysia during the northeast monsoon season associated with the projected weakening of the monsoon flow during boreal winter. For the northwestern regions (e.g. Perak) often affected by severe floods, a significant increase in precipitation (by up to 33%) is projected during the southwest monsoon season, partly driven by the projected strengthening of the cross-equatorial flow and the weakened low-level anti-cyclonic shear of winds in boreal summer. However, the magnitudes and signal-to-noise ratios of the projected changes vary considerably with respect to different horizontal and vertical resolutions. Firstly, models with relatively high horizontal and vertical resolutions project a more significant decrease in precipitation during the northeast monsoon season. Secondly, for the southwest monsoon season, models with relatively high horizontal resolutions project larger magnitudes of increases in precipitation over the northern region, while smaller increases are found in simulations with relatively high vertical resolutions. Generally, reduced ensemble spread and increased signal-to-noise ratios are found in simulations at higher horizontal and vertical resolutions, suggesting increased confidence in model projections with increased model resolution.

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.

Meteorological fronts are important for their associated surface impacts, including extreme precipitation and extreme winds. Objective identification of fronts is therefore of interest in both operational and research settings. We have implemented a number of changes in a widely used objective front identification algorithm, and present the improvements associated with these changes. First, we show that a change to the order of operations from applying a mask then joining frontal points to contouring the thermal field then applying the mask, yields smoother fronts with fewer breaks. Next we address the selection of the identification parameters, including the thresholds and number of smoothing passes. This allows a comparison between datasets of differing resolutions. Finally, we have made a number of numerical improvements in the implementation of the algorithm, such as more accurate finite differencing, direct calculation of the wet-bulb potential temperature, and better handling of short fronts, which yield further benefits in 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.

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.

Future changes in extratropical cyclones and the associated storm tracks are uncertain. Using the new CMIP6 models, we investigate changes to seasonal mean storm tracks and composite wind speeds at different levels of the troposphere for the winter and summer seasons in both the Northern (NH) and Southern Hemispheres (SH). Changes are assessed across four different climate scenarios. The seasonal mean storm tracks are predicted to shift polewards in the SH and also in the North Pacific, with an extension into Europe for the North Atlantic storm track. Overall, the number of cyclones will decrease by ~5 % by the end of the 21st century, although the number of extreme cyclones will increase by 4 % in NH winter. Cyclone wind speeds are projected to strengthen throughout the troposphere in the winter seasons and also summer in the SH, with a weakening projected in NH summer, although there are minimal changes in the maximum wind speed in the lower troposphere. Large amounts of this change can be associated with changes in the speed of cyclones in the future. Changes in wind speeds are concentrated in the warm sector of cyclones and the area of extreme winds may be up to 40 % larger by the end of the century. The largest changes are seen for the SSP5-85 scenario, although large amount of change can be mitigated by restricting warming to that seen in the SSP1-26 and 2-45 scenarios. Extreme cyclones show larger increases in wind speed and peak vorticity than the average strength cyclones, with the extreme cyclones showing a larger increase in wind speed in the warm sector.

Fire in the tropical peatland forests of Borneo is an environmental issue interactioning with climate change and deforestation, and the consequences have local and global implications. While research has shown that fire severity and frequency are expected to increase with climate change, there is conflicting model and observational data as to the effect of deforestation on precipitation, which is a key metric for fire risk. To better understand the changes in fire risk from deforestation and climate change we ran simulations of the climate scenario RCP8.5 with and without total deforestation using regional climate model RegCM4. The output was then used for calculations of the fire weather index. We find that annual temperature change from deforestation at elevations above 500 m is 53% of the change over the 21st century in RCP8.5. Fire risk is significantly affected by both climate change and deforestation, despite some increases in precipitation from deforestation. While the multi model dry season (June–August) mean increases in fire risk are larger from elevated atmospheric carbon dioxide, the increases in maximum fire risk are larger from deforestation. The altitude is a good predictor of fire risk change, with larger increases at more densely populated lower elevations where the peatlands are concentrated and smaller increases at higher elevations. Therefore, while deforestation generally causes a smaller increase in climate-related fire risk than climate change, its local control and heterogeneous effects compared to global carbon emissions makes it critical for climate mitigation policy. These high-resolution simulations provide a guide to the most vulnerable areas of Borneo from climatic increases in fire risk.