In the Southern Hemisphere atmospheric circulation, one of the most prominent wave patterns is zonal wave three (ZW3), which exhibits three positive and three negative anomalies in the zonal eddy field around the Southern Hemisphere, with maximum amplitude over the Southern Oceans. Using ERA5 data, this presentation will describe the form of ZW3 and trends in its behaviour. Over the past 60 years, the amplitude of ZW3 exhibits significant upward trends throughout the year but most prominently in summer (Dec-Feb). Such trends are related to increasing meridional temperature gradients and to trends in eddy activity in general and to trends in poleward energy fluxes. Implications for surface climate temperature and precipitation extremes will be outlined.

The mean climate characteristics of the Mediterranean region with temperate, wet winter and warm (or hot) dry summer is common to other regions of the world, like the west coast of North America, central Chile, the far southwest tip of Southern Africa and southwest Australia, which are all identified as Mediterranean climate regions (MCRs). Following from the Koppen-Geiger classification of climates, they share similar location and lie on the western edge of continents in the subtropics to mid-latitude thus being overall transition areas between wet and dry climates. In a previous work, with a probabilistic approach, we have quantified the risk of a poleward shift of MCRs, mostly over the Mediterranean region and western North America, with the equatorward margins replaced by arid climate type using CMIP5 21st century projections. Following on from the above and using newly available CMIP6 simulations we have designed an update of the assessment of future climate changes in MCRs. The objective is to identify how MCRs are projected to change in CMIP6 simulations either in terms of hydroclimate conditions and of expansion or retreat of the areas considering the high impact these changes may have on water resources, ecosystem and human livelihood over these vulnerable climate regions. On top of the overall picture of hydroclimate changes over the regions with commonalities and differences, as expected from current dynamical understanding, we will provide an evaluation of the uncertainties in the projections and estimates of the models’ reliability in representing observed past changes.

Tropical cyclones (TCs) are modulated by El Ni & ntilde;o-Southern Oscillation (ENSO) on interannual timescales as ENSO impacts tropical sea surface temperatures (SST) and atmospheric conditions, especially in the Pacific basin. The frequency, intensity, startup SST, windshear, and life cycle of TCs vary between ENSO phases and TC seasons. Previous research focused on the Southwest Pacific (SWP) Basin has consistently shown that during El Ni & ntilde;o phases, TCs tend to form more towards the central Pacific, while during La Ni & ntilde;a, their formation shifts towards the northeast coast of Australia. Also, TCs form more frequently during the late TC seasons than during the early TC seasons. Here, TC genesis is assessed using a Coupled ENSO Index (using Ni & ntilde;o 3.4 SST and the Southern Oscillation index [SOI]) and a grouping into early (October-January) and late (February-May) TC seasons, in the decades from 1971 to 2020. We find that though the number of TCs in SWP is decreasing over the years, their SST at genesis and maximum wind speed are increasing, generating more intense TCs over the SWP basin. TCs formed during El Ni & ntilde;o are more intense in comparison to those formed during La Ni & ntilde;a even though there is no significant difference in their SST at genesis. We find that the threshold of environmental factors responsible for cyclogenesis in SWP is gradually changing, leading to more severe TC events in the region.

The anthropogenic fingerprint has been detectable in observed global climate change for decades, yet it is still difficult to detect at the regional scale beyond temperature due to the presence of large internal variability and modeling and observational uncertainties. Here we demonstrate regional optimal fingerprinting of long-term fire weather trends in western North America, leveraging large ensembles of high resolution, atmosphere-only climate models to adequately sample internal variability. Considering the full spatiotemporal response to thermodynamic and dynamic climate change, we find that anthropogenic forcings have contributed 81-188% of the region's observed increasing linear trend in fire weather over the last 50+ years. The natural fingerprint, which contains inter-annual and decadal variability, is also robustly detected. We detect the anthropogenic fingerprint in relevant meteorological variables - temperature, precipitation, and relative humidity - and link model differences in fire weather response to differences in simulated precipitation and relative humidity responses.

Tropical cyclones (TCs) are modulated by El Niño-Southern Oscillation (ENSO) on interannual timescales as ENSO impacts local Sea Surface Temperatures (SST) and atmospheric conditions, especially in the Pacific basin. The frequency, intensity, startup SST, windshear and life cycle of TCs vary between ENSO phases and TC seasons. Previous research focused on the Southwest Pacific (SWP) Basin has consistently shown that during El Niño phases TCs tend to form more towards the central Pacific, while during La Niña, their formation shifts towards the northeast coast of Australia. Also, TCs form more frequently during the late TC seasons than during the early TC seasons. Here, TC genesis is assessed using a Coupled ENSO index (using Niño 3.4 SST and the Southern Oscillation Index (SOI)) and a grouping into early (Oct-Jan) and late (Feb-May) TC seasons, in the decades from 1971 to 2020. We find that though the number of TCs in SWP are decreasing over the years, their SST at genesis and maximum wind speed are increasing, generating more intense TCs over the SWP basin. TCs formed during El Niño are more intense than those formed during La Niña even though there is no significant difference in their SST at genesis. We find that the threshold of environmental factors responsible for cyclogenesis in SWP are gradually changing, leading to more severe TC events in the region.

We demonstrate a 1-year lagged extratropical response to the El Ni & ntilde;o-Southern Oscillation (ENSO) in observational analyses and climate models. The response maps onto the Arctic Oscillation and is strongest in the North Atlantic, where it resembles the North Atlantic Oscillation (NAO). Unexpectedly, these 1-year lagged teleconnections are at least as strong as the better-known simultaneous winter connections. However, the 1-year lagged response is opposite in sign to the simultaneous response such that 1 year later, El Ni & ntilde;o is followed by a positive NAO, whereas La Ni & ntilde;a is followed by a negative NAO. The lagged response may also interfere with simultaneous ENSO teleconnections. We show here that these effects are unlikely to be caused by residual aliasing of ENSO cycles; rather, slowly migrating atmospheric angular momentum anomalies explain both the sign and the timing of the extratropical response. Our results have implications for understanding ENSO teleconnections, explaining observed extratropical climate variability and interpreting seasonal to interannual climate predictions.

Sea-level rise is accelerating globally and will continue for centuries under all shared socioeconomic pathways. Although sea-level rise is a global issue, its impacts manifest heterogeneously at the local scale, with some coastal communities and infrastructure considerably more vulnerable than others. Aotearoa New Zealand is poorly prepared to deal with sea-level rise impacts, and some places are already approaching the limits of adaptation, short of relocation. Maladaptive choices threaten Aotearoa’s ongoing ability to adapt going forward. Development of climate-resilient pathways requires an immediate adoption of non-partisan, long-term, systemscale approaches to governance and decision making (from local to national), that integrate effective adaptation and emissions mitigation. This also requires proactive and collective action underpinned by indigenous and actionable knowledge (e.g., NZ SeaRise projections) designed for our unique circumstances. There is still time to put in place sustainable, equitable and effective solutions, but funding and governance models need urgent attention.

The changing climate is threatening everything we hold dear, increasing dangers to food production, to the availability of water, to land and to livelihoods across the globe. In the past century, humanity has become the dominant force shaping the climate system, ramping up greenhouse gas emissions and air pollution. To halt climate change, emissions of greenhouse gases must be reduced to zero as soon as possible. However, the necessary action has not been forthcoming and the overall response has been painfully slow, for a number of reasons. This special issue of the Journal of the Royal Society Te Apārangi addresses many of these issues, with a focus on Aotearoa New Zealand, looking at how we think about climate change and the nature and pace of our response.

This study quantifies the influences of anthropogenic forcing to date on precipitation over Aotearoa New Zealand (ANZ). Large ensembles of simulations from the weather@home regional climate model experiments are analysed under two scenarios, a natural (NAT) or counter-factual scenario which excludes human-induced changes to the climate system and an anthropogenic (ANT) or factual scenario. The impacts of anthropogenic forcing on precipitation are analysed in the context of large-scale circulation types characterized using an existing Self Organizing Map classification. The combined effect of both thermodynamics and dynamics are compared with values expected from the Clausius–Clapeyron (C–C) relation. Changes in the precipitation intensity due to greenhouse gas-forced temperature rise are lower than the expected C–C value. However extreme precipitation changes approach the C–C value for some circulation types. Specifically westerly flows enhance precipitation change across ANZ relative to the C–C rate, particularly over the West Coast. Conversely, northwesterly flows reduce the change over the North Island relative to the C–C value. Moreover, the wet day frequency generally reduces in the ANT scenario relative to NAT, reductions are largest on the West Coast of the South Island for westerly flows. Additionally, the frequency of days with extreme precipitation rises over ANZ for most circulation patterns, except in Northland and for northwesterly flows. This underscores the combined influence of dynamics and thermodynamics in shaping both precipitation intensity and frequency patterns across ANZ.

We are already experiencing an increase in the frequency and severity of climate-related events. Back-to-back climate disruptions such as tropical cyclones, droughts and marine heatwaves are having significant social, environmental and economic costs on the country. Climate science is vital if the country is to have the information needed to adapt to climate change, but the current absence of a clear research investment strategy risks the country's capacity to provide this information.

ERA5 reanalysis output is compared to WindSat polarimetric microwave radiometer measurements for Southern Hemisphere midlatitude to high‐latitude cyclones between 2003 and 2019. WindSat provides independent measures of low‐level wind speed, total column water vapor (TCWV), cloud liquid water (CLW), and precipitation, which are not assimilated into ERA5. We implement a tracking scheme to identify cyclone centers, before using cyclone composites to match concurrent data in ERA5 and WindSat. We find ERA5 and WindSat show comparable spatial structures for all variables, although their distributions show poorer agreement for CLW and precipitation. Compared to WindSat, ERA5 underestimates TCWV by up to 5% and CLW by up to 40%. ERA5 underestimates precipitation in the warm sector by up to 15%, but overestimates in the cold sector by up to 60%. Similar biases in ERA5 are seen compared to Advanced Microwave Scanning Radiometer for EOS (AMSR‐E) data, even though AMSR‐E radiances are assimilated into ERA5. Comparing ERA5 and WindSat across the cyclone lifecycle, strong spatial correlation is seen as the cyclone deepens and reaches peak intensity, before slightly declining as the cyclone decays. In the cold sector ERA5 shows an underestimation of CLW, yet overestimates precipitation at all lifecycle stages. However, in the warm sector precipitation is underestimated. This potentially suggests biases within the ERA5 parameterizations of cloud and precipitation causing a disconnect between the two. Despite this, ERA5 shows strong correlation with WindSat and determines cyclone structure well across the cyclone lifecycle, showing its value for use in cyclone compositing analysis.

Extreme temperature events (ETEs) have evolved alongside the warming climate over most parts of the world. This study provides a statistical quantification of how human influences have changed the frequencies of extreme temperatures in New Zealand, depending on the synoptic weather types. We use the ensembles under pre‐industrial conditions (natural scenarios with no human‐induced changes) and present‐day conditions (anthropogenic scenarios) from the weather@home regional climate model. The ensemble simulations under these two scenarios are used to identify how human influences have impacted the frequency and intensity of extreme temperatures based on their connection to different large‐scale circulation patterns derived using self‐organizing maps (SOMs). Over New Zealand, an average two to three fold rise in frequencies of extremes occurs irrespective of seasons due to anthropogenic influence with a mean temperature increase close to 1°C. For some synoptic situations, the frequency of extremes are especially enhanced; in particular, for low‐pressure centres to the northeast of New Zealand where the frequency of occurrence of daily temperature extremes has increased by a factor of 7 between anthropogenic and natural ensembles for the winter season, though these synoptic patterns rarely occur. For low‐pressure centres to the northwest of New Zealand, we observe high temperatures frequently in both anthropogenic and natural ensembles which we expect is probably associated with warm air advection from the Tropics. The frequency of occurrence of high temperatures in these synoptic patterns has also increased by a factor of 2 between the natural and anthropogenic ensembles. For these synoptic states, the extremes are observed in the North Island and along the east coast of the country with the highest temperature along the Canterbury coast and Northland. The change between the natural and anthropogenic ensembles is largest on the west coast along the Southern Alps for all the synoptic circulation types.

A polynya is an area of open water or reduced concentration of sea ice surrounded by either concentrated sea ice or land ice. They are often seen as sites of intense ocean–atmosphere heat exchange and as ice production factories. Given their importance, it is crucial to quantify the accuracy of satellite-derived polynya information. Polynyas in their early evolution phase are generally narrow and occur at scales likely too fine to be detected by widely used passive microwave (PMW) radiometric sensors. We derived 40 m scale polynya information over the western Ross Sea from high-resolution Synthetic Aperture Radar (SAR) Sentinel-1 C-band data and examined discrepancies with larger-scale estimates. We utilized two automated algorithms, supervised (a rule-based approach) and unsupervised (a combination of texture analysis with k-means clustering), to accurately identify the polynya areas. We generated data for validation using Sentinel-1 data at instances where polynyas can be visually delineated. Results from PMW sensors (NSIDC and AMSR2) and SAR-based algorithms (rule-based and texture-based) are compared with manually delineated polynya areas obtained through Sentinel-1. Analysis using PMW sensors revealed that NSIDC overestimates larger polynyas and underestimates smaller polynyas compared to AMSR2. We were more accurately able to identify polynya presence and area using Sentinel-1 SAR observations, especially in clear cases and cases when PMW data miscalculates the polynya’s presence. Of our SAR-based algorithms, the rule-based approach was more accurate than the texture-based approach at identifying clear polynyas when validated against manually delineated regions. Altogether, we emphasize the need for finer spatio-temporal resolution data for polynya studies.