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Atmospheric rivers (ARs) are narrow and elongated regions of enhanced horizontal water vapour transport. Considerable research on understanding Northern Hemisphere ARs and their relationship with extreme precipitation has shown that ARs have a strong association with heavy rainfall and flooding. While there has been very little work on ARs in the Southern Hemisphere, global climatologies suggest that ARs are equally as common in both hemispheres. New Zealand in particular is located in a region of high AR frequency. This study aims to test the hypothesis that ARs play a significant role in heavy precipitation and flooding events in New Zealand. We used a recently developed AR identification method and daily station data across New Zealand to test for the concurrence of ARs and extreme rainfall. We found that, at each of the eleven stations analysed, at least seven to all ten of the top ten heaviest precipitation days between 1980 and 2018 were associated with AR conditions. Nine of the ten most damaging floods in New Zealand between 2007 and 2017 occurred during AR events. These results have important implications for understanding extreme rainfall in New Zealand, and ultimately for predicting some of the most hazardous events in the region. This work also highlights that more research on ARs in New Zealand is needed.

Weather and climate service providers around the world are looking to issue assessments of the human role in recent extreme weather events. For this attribution to be of value, it is important that vulnerability is acknowledged and questions are framed appropriately.

Hurricane Harvey is one of the costliest tropical cyclones in history. In this paper, we use a probabilistic event attribution framework to estimate the costs associated with Hurricane Harvey that are attributable to anthropogenic influence on the climate system. Results indicate that the “fraction of attributable risk” for the rainfall from Harvey was likely about at least a third with a preferable/best estimate of three quarters. With an average estimate of damages from Harvey assessed at about US$90bn, applying this fraction gives a best estimate of US$67bn, with a likely lower bound of at least US$30bn, of these damages that are attributable to the human influence on climate. This “bottom-up” event-based estimate of climate change damages contrasts sharply with the more “top-down” approach using integrated assessment models (IAMs) or global macroeconometric estimates: one IAM estimates annual climate change damages in the USA to be in the region of US$21.3bn. While the two approaches are not easily comparable, it is noteworthy that our “bottom-up” results estimate that one single extreme weather event contributes more to climate change damages in the USA than an entire year by the “top-down” method. Given that the “top-down” approach, at best, parameterizes but does not resolve the effects of extreme weather events, our findings suggest that the “bottom-up” approach is a useful avenue to pursue in future attempts to refine estimates of climate change damages.

As greenhouse gases continue to accumulate in Earth’s atmosphere, the nature of extreme weather events (EWEs) has been changing and is expected to change in the future. EWEs have contributions from anthropogenic climate change as well as from natural variability, which complicates attribution statements. EWERAM is a project that has been funded through the New Zealand Ministry of Business, Innovation and Employment Smart Ideas programme to develop the capability to provide, within days of an EWE having occurred over New Zealand, and while public interest is still high, scientifically defensible statements about the role of climate change in both the severity and frequency of that event. This is expected to raise public awareness and understanding of the effects of climate change on EWEs.A team of researchers from five institutions across New Zealand are participating in EWERAM. EWE attribution is a multi-faceted problem and different approaches are required to address different research aims. Although robustly assessing the contribution of changes in the thermodynamic state to an observed event can be more tractable than including changes in the dynamics of weather systems, for New Zealand, changes in dynamics have had a large impact on the frequency and location of EWEs. As such, we have initiated several lines of research to deliver metrics on EWE attribution, tailored to meet the needs of various stakeholders, that encompass the effects of both dynamical and thermodynamical changes in the atmosphere. This presentation will give an overview of EWERAM and present the methodologies and tools used in the project.

Previous studies evaluating anthropogenic influences on the meteorological drivers of drought have found mixed results owing to (1) the complex physical mechanisms which lead to the onset of drought, (2) differences in the characteristics and timescales of drought for different regions of the world, and (3) different approaches to the question of attribution. For a mid-latitude, temperate climate like New Zealand, strongly modulated by oceanic influences, summer droughts last on the order of three months, and are less strongly linked to persistent temperature anomalies than continental climates. Here, we demonstrate the utility of a novel approach for characterizing the meteorological conditions conducive to extreme drought over the North Island of New Zealand, using the January-March 2013 event as a case study. Specifically, we consider the use of self-organizing map (SOM) techniques in a multi-member coupled climate model ensemble to capture changes in daily circulation, between two 41-year periods (1861-1901 and 1993-2033). Comparisons are made with seasonal pressure and precipitation indices. Our results demonstrate robust (>99% confidence) increases in the likelihood of observing circulation patterns like those of the 2013 drought in the recent-climate simulations when compared with the early-climate simulations. Best-guess estimates of the fraction of attributable risk range from 0.2 to 0.4, depending on the metric used and threshold considered. Contributions to uncertainty in these attribution statements are discussed.

The crucial question in the public debate of extreme events is increasingly whether and to what extent the event has been caused by anthropogenic warming. In this study we investigate this question using extreme summer precipitation events in England and Wales as an example for probabilistic event attribution using very large ensembles of regional climate model (RCM) simulations within the weather@home.net project. This allows us to analyse the statistics of high precipitation events in England and Wales, a region with a high quality precipitation observational dataset. Validating the model simulations against observations shows a credible shape of the distribution of 5-day precipitation, and thus confidence in the results. While the risk of extreme July precipitation events has at least doubled due to anthropogenic climate change in the modelling framework, no significant changes can be detected for the other two summer months. This study thus highlights the challenges of probabilistic event attribution of complex weather events and identifies the need to further decompose atmospheric features responsible for an event to occur for quantitative attribution analysis.

A new climate modelling project has been developed for regional climate simulation and the attribution of weather and climate extremes over Australia and New Zealand. The project, known as weather@home Australia-New Zealand, uses public volunteers' home computers to run a moderate-resolution global atmospheric model with a nested regional model over the Australasian region. By harnessing the aggregated computing power of home computers, weather@home is able to generate an unprecedented number of simulations of possible weather under various climate scenarios. This combination of large ensemble sizes with high spatial resolution allows extreme events to be examined with more robust estimates of uncertainty. This paper provides an overview of the weather@home Australia-New Zealand project, including initial evaluation of the regional model performance. The model is seen to be capable of resolving many climate features that are important for the Australian and New Zealand regions, including the influence of El Niño-Southern Oscillation on driving natural climate variability. To date, 75 model simulations of the observed climate have been successfully integrated over the period 1985–2014 in a time-slice manner. In addition, multi-thousand member ensembles have also been generated for the years 2013, 2014 and 2015 under climate scenarios with and without the effect of human influences. All data generated by the project is freely available to the broader research community.

Incomplete understanding of three aspects of the climate system—equilibrium climate sensitivity, rate of ocean heat uptake and historical aerosol forcing—and the physical processes underlying them lead to uncertainties in our assessment of the global-mean temperature evolution in the twenty-first century 1,2 . Explorations of these uncertainties have so far relied on scaling approaches 3,4 , large ensembles of simplified climate models 1,2 , or small ensembles of complex coupled atmosphere‐ocean general circulation models 5,6 which under-represent uncertainties in key climate system properties derived from independent sources 7‐9 . Here we present results from a multi-thousand-member perturbed-physics ensemble of transient coupled atmosphere‐ocean general circulation model simulations. We find that model versions that reproduce observed surface temperature changes over the past 50 years show global-mean temperature increases of 1.4‐3 K by 2050, relative to 1961‐1990, under a mid-range forcing scenario. This range of warming is broadly consistent with the expert assessment provided by the Intergovernmental Panel on Climate Change Fourth Assessment Report 10 , but extends towards larger warming than observed in ensemblesof-opportunity 5 typically used for climate impact assessments. From our simulations, we conclude that warming by the middle of the twenty-first century that is stronger than earlier estimates is consistent with recent observed temperature changes and a mid-range ‘no mitigation’ scenario for greenhouse-gas emissions. In the latest generation of coupled atmosphereocean general circulation models (AOGCMs) contributing to the Coupled Model Intercomparison Project phase 3 (CMIP-3), uncertainties in key propertiescontrollingthetwenty-firstcenturyresponsetosustained anthropogenic greenhouse-gas forcing were not fully sampled, partially owing to a correlation between climate sensitivity and aerosol forcing 7,8 , a tendency to overestimate ocean heat uptake 11,12 and compensation between short-wave and long-wave feedbacks 9 . This complicates the interpretation of the ensemble spread as a direct uncertainty estimate, a point reflected in the fact that the ‘likely’ (>66% probability) uncertainty range on the transient response was explicitly subjectively assessed as40% to C60% of

The effect on stratospheric temperatures of ozone change since 1979 is investigated using a general circulation model employing observations of the vertical profile of ozone change. The stratopause region is generally cooler in 1997 than in 1979 by about 2 K. Results from a ‘Seasonally Evolving Fixed Dynamical Heating’ simulation indicate that this cooling is mostly radiative in origin. In Antarctica the model indicates statistically significant cooling of the lower stratosphere between 1979 and 1997, peaking at 13 K in November; this agrees quite well with observations. In the Arctic no significant cooling is seen in winter or early spring, in contrast with observations, indicating that ozone loss is not the main cause of the observed temperature change here. The peak Antarctic cooling is accompanied by a warming of the upper stratosphere; dynamics are responsible for this warming and for making the lower stratospheric cooling less severe than it would otherwise be.

Twelve simulations of the stratosphere and mesosphere have been performed to investigate the near-major stratospheric warming of January 1992. All were initialized close to the observed warming. the resulting simulations fall into two classes: those that accurately reproduce the timing and anticyclonic merger mechanism of the observed warming and those that fail. the model used was a mechanistic stratosphere-mesosphere model. with a prescribed troposphere; thus differences among the simulations must only be due to differences among the initial conditions, which were constructed using different combinations of observed and climatological data. the main differences between the initial conditions of those simulations that succeed and those that fail are in low latitudes. A detailed analysis of two contrasting simulations reveals that the one which fails does not accurately reproduce the observed conveyor belt feeding tropical low-potential-vorticity (PV) air into the Aleutian high. Several factors appear to have combined to make the difference between the successful and the unsuccessful simulation of this sudden warming. the amount of low PV already present in higher latitudes in the initial condition appears to have an influence, as does the strength of the subtropical PV barrier. Also important is the Rossby wave structure which, by determining the degree of zonal asymmetry of the PV barrier, influences the injection of low PV into higher latitudes. In addition, however, we propose that the inertial stability of the tropical upper stratosphere might have played a significant role. In the unsuccessful simulation the tropical upper stratosphere is more inertially unstable than in the successful simulation; in this region more vigorous small-scale roll structures develop which, in stabilizing the flow, might have inhibited the northward transport of tropical air that appears to be a key part of the development of the observed sudden warming.

Perturbed physics experiments are among the most comprehensive ways to address uncertainty in climate change forecasts. In these experiments, parameters and parametrizations in atmosphere–ocean general circulation models are perturbed across ranges of uncertainty, and results are compared with observations. In this paper, we describe the largest perturbed physics climate experiment conducted to date, the British Broadcasting Corporation (BBC) climate change experiment, in which the physics of the atmosphere and ocean are changed, and run in conjunction with a forcing ensemble designed to represent uncertainty in past and future forcings, under the A1B Special Report on Emissions Scenarios (SRES) climate change scenario.

Ozone is an important gas in the atmosphere since, although it is only present in tiny quantities, it plays a vital role in protecting mankind from the harmful effects of solar radiation and a dominant part in determining the temperature structure of the atmosphere.

Dynamical fields based on temperature measurements from the Improved Stratospheric and Mesospheric Sounder on the Upper Atmosphere Research Satellite are presented for the Northern Hemisphere stratosphere for the period 28 October 1991 through 18 January 1992. Interpretation of these fields gives a picture of the dynamical evolution of this period in terms of the zonal-mean fields and the synoptic structures. Among the features of interest are the movements of the zonal-mean jets and several periods of stratospheric warming, culminating in a near-major warming in January.