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Sudden-stratospheric-warming (SSW) events are often followed by significant weather and climate impacts at the surface. By affecting the North Atlantic Oscillation (NAO), SSWs can lead to periods of extreme cold in parts of Europe and North America. Previous studies have used observations and free-running climate models to try to identify features of the atmosphere prior to an SSW that can determine the subsequent impact at the surface. However, the limited observational record makes it difficult to accurately quantify these relationships. Here, we instead use a large ensemble of seasonal hindcasts. We first test whether the hindcasts reproduce the observed characteristics of SSWs and their surface signature. We find that the simulations are statistically indistinguishable from the observations, in terms of the overall risk of an SSW per winter (56 %), the frequency of SSWs with negative NAO responses (65 %), the magnitude of the NAO responses, and the frequency of wavenumber-2-dominated SSWs (26 %). We also assess the relationships between prior conditions and the NAO response in the 30 d following an SSW. We find that there is little information in the precursor state to guide differences in the subsequent NAO behaviour between one SSW and another, reflecting the substantial natural variability between SSW events. The strongest relationships with the NAO response are from pre-SSW sea level pressure anomalies over the polar cap and from zonal-wind anomalies in the lower stratosphere, both exhibiting correlations of around 0.3. The pre-SSW NAO has little bearing on its post-SSW state. The strength of the pre-SSW zonal-wind anomalies at 10 hPa is also not significantly correlated with the NAO response. Finally, we find that the mean NAO response in the first 10 d following wave-2-dominated SSWs is much more strongly negative than in wave-1 cases. However, the subsequent response in days 11–30 is very similar regardless of the dominant wavenumber. In all cases, the composite mean responses are the result of very broad distributions from individual SSW events, necessitating a probabilistic analysis using large ensembles.

Seasonal forecasts for Yangtze River basin rainfall in June, May–June–July (MJJ), and June–July–August (JJA) 2020 are presented, based on the Met Office GloSea5 system. The three-month forecasts are based on dynamical predictions of an East Asian Summer Monsoon (EASM) index, which is transformed into regional-mean rainfall through linear regression. The June rainfall forecasts for the middle/lower Yangtze River basin are based on linear regression of precipitation. The forecasts verify well in terms of giving strong, consistent predictions of above-average rainfall at lead times of at least three months. However, the Yangtze region was subject to exceptionally heavy rainfall throughout the summer period, leading to observed values that lie outside the 95% prediction intervals of the three-month forecasts. The forecasts presented here are consistent with other studies of the 2020 EASM rainfall, whereby the enhanced mei-yu front in early summer is skillfully forecast, but the impact of midlatitude drivers enhancing the rainfall in later summer is not captured. This case study demonstrates both the utility of probabilistic seasonal forecasts for the Yangtze region and the potential limitations in anticipating complex extreme events driven by a combination of coincident factors.

Variability in the East Asian Summer Monsoon (EASM) brings the risk of heavy flooding or drought to the Yangtze River Basin, with potentially devastating impacts. Early forecasts of the likelihood of enhanced or reduced monsoon rainfall can enable better management of water and hydropower resources by decision-makers, supporting livelihoods and major economic and population centres across Eastern China. This paper demonstrates that the EASM is predictable in a dynamical forecast model from the preceding November, and that this allows skilful forecasts of summer mean rainfall in the Yangtze River Basin at a lead time of 6 months. Skill for May–June–July rainfall is of a similar magnitude to seasonal forecasts initialised in spring, although the skill in June–July–August is much weaker and not consistently significant. However, there is some evidence for enhanced skill following El Niño events. The potential for decadal-scale variability in forecast skill is also examined, although we find no evidence for significant variation.

During June and July of 2020, the Yangtze River basin suffered from extreme mei-yu rainfall and catastrophic flooding. This study explores the seasonal predictability and associated dynamical causes for this extreme Yangtze River rainfall event, based on forecasts from the Met Office GloSea5 operational forecast system. The forecasts successfully predicted above-average rainfall over the Yangtze River basin, which arose from the successful reproduction of the anomalous western North Pacific subtropical high (WNPSH). Our results indicate that both the Indian Ocean warm sea surface temperature (SST) and local WNP SST gradient were responsible for the westward extension of the WNPSH, and the forecasts captured these tropical signals well. We explore extratropical drivers but find a large model spread among the forecast members regarding the meridional displacements of the East Asian mid-latitude westerly jet (EAJ). The forecast members with an evident southward displacement of the EAJ favored more extreme Yangtze River rainfall. However, the forecast Yangtze River rainfall anomaly was weaker compared to that was observed and no member showed such strong rainfall. In observations, the EAJ displayed an evident acceleration in summer 2020, which could lead to a significant wind convergence in the lower troposphere around the Yangtze River basin, and favor more mei-yu rainfall. The model forecast failed to satisfactorily reproduce these processes. This difference implies that the observed enhancement of the EAJ intensity gave a large boost to the Yangtze River rainfall, hindering a better forecast of the intensity of the event and disaster mitigation.

Sudden stratospheric warming events (SSWs) are often followed by significant weather and climate impacts at the surface. By affecting the North Atlantic Oscillation (NAO), SSWs can lead to periods of extreme cold in parts of Europe and North America. Previous studies have used observations and free-running climate models to try to identify features of the atmosphere prior to an SSW that can determine the subsequent impact at the surface. However, the limited observational record makes it difficult to accurately quantify these relationships. Here, we instead use a large ensemble of seasonal hindcasts. We first test whether the hindcasts reproduce the observed characteristics of SSWs and their surface signature. We find that the simulations are statistically indistinguishable from the observations, in terms of the overall risk of an SSW per winter (56 %), the frequency of SSWs with negative NAO responses (65 %), the magnitude of the NAO responses, and the frequency of wavenumber-2 dominated SSWs (26 %). We also assess the relationships between prior conditions and the NAO response following an SSW. We find that there is little information in the precursor state to guide differences in the subsequent NAO behaviour between one SSW and another, reflecting the substantial natural variability between SSW events. The strongest relationships with the NAO response are from pre-SSW sea level pressure anomalies over the polar cap, and from zonal wind anomalies in the lower stratosphere, both exhibiting correlations of around 0.3. The pre-SSW NAO has little bearing on its post-SSW state. The strength of the pre-SSW zonal wind anomalies at 10 hPa is also not significantly correlated with the NAO response. Finally, we find that there is no significant difference in the likelihood of a post-SSW negative NAO response between wave-1 and wave-2 dominated SSWs, although the latter result in a stronger negative NAO anomaly on average.

Rainfall forecasts for the summer monsoon season in the Yangtze River basin (YRB) allow decision-makers to plan for possible flooding, which can affect the lives and livelihoods of millions of people. A trial climate service was developed in 2016, producing a prototype seasonal forecast product for use by stakeholders in the region, based on rainfall forecasts directly from a dynamical model. Here, we describe an improved service based on a simple statistical downscaling approach. Through using dynamical forecast of an East Asian summer monsoon (EASM) index, seaso-nal mean rainfall for the upper and middle/lower reaches of YRB can be forecast separately by use of the statistical downscaling, with significant skills for lead times of up to at least three months. The skill in different sub-basin regions of YRB varies with the target season. The rainfall forecast skill in the middle/lower reaches of YRB is significant in May–June–July (MJJ), and the forecast skill for rainfall in the upper reaches of YRB is significant in June–July–August (JJA). The mean rainfall for the basin as a whole can be skillfully forecast in both MJJ and JJA. The forecasts issued in 2019 gave good guidance for the enhanced rainfall in the MJJ period and the near-average conditions in JJA. Initial feedback from users in the basin suggests that the improved forecasts better meet their needs and will enable more robust decision-making.

Changes in climate pose major challenges to society, and so decision-makers need actionable climate information to inform their planning and policies to make society more resilient to climatic changes. Climate services are being developed to provide such actionable climate information. The successful development and use of climate services benefits greatly from close engagement between developers, providers, and users of the services. The Climate Science for Service Partnership China (CSSP China) is a China–UK collaboration fostering closer engagement between climate scientists, providers of climate services, and users of climate services. We describe the process within CSSP China of co-developing climate services through trials with users to revise and improve a prototype. Examples are provided covering various scientific capabilities, user needs, and parts of China. The development process is yielding many benefits, such as increasing the engagement between providers and users, making users more aware of how climate information can be of use in their decision-making, giving the climate service providers a better understanding of the users’ requirements for climate information, and shaping future scientific research and development. In addition to the benefits, we also document some challenges that have emerged, along with ways of alleviating them. We have two key recommendations from our experiences: make the time and space for effective engagement between the users and developers of any climate service; bring the needs of the users in to the design and delivery of the climate service as early as possible and throughout the development cycle.

A prototype climate service was developed and trialled in early 2019 to provide seasonal forecast of the June–July–August (JJA) tropical cyclone (TC) landfall risk for the East China region ahead of the forthcoming typhoon season. Test forecasts were produced in both March and April 2019 and a final forecast was released to the China Meteorological Administration (CMA) on 1 May 2019. The trial service was produced by using the Met Office Global Seaso-nal forecast system (GloSea5), and a forecast of the western Pacific subtropical high (WPSH) index was used to infer the TC landfall risk based on a simple linear regression between historical model WPSH indices and observed TC landfalls in East China. The forecast method shows significant skill for forecasting the JJA TC landfall risk in East China with up to three-month lead time, with the greatest skill for predictions initialized in May. The 2019 forecast provided good guidance of the near-average TC activity observed in East China in JJA 2019. Success of the forecast adds confidence to an improved climate service ahead of the 2020 typhoon season.

We demonstrate that there is significant skill in the GloSea5 operational seasonal forecasting system for predicting June mean rainfall in the middle/lower Yangtze River basin up to four months in advance. Much of the rainfall in this region during June is contributed by the mei-yu rain band. We find that similar skill exists for predicting the East Asian summer monsoon index (EASMI) on monthly time scales, and that the latter could be used as a proxy to predict the regional rainfall. However, there appears to be little to be gained from using the predicted EASMI as a proxy for regional rainfall on monthly time scales compared with predicting the rainfall directly. Although interannual variability of the June mean rainfall is affected by synoptic and intraseasonal variations, which may be inherently unpredictable on the seasonal forecasting time scale, the major influence of equatorial Pacific sea surface temperatures from the preceding winter on the June mean rainfall is captured by the model through their influence on the western North Pacific subtropical high. The ability to predict the June mean rainfall in the middle and lower Yangtze River basin at a lead time of up to 4 months suggests the potential for providing early information to contingency planners on the availability of water during the summer season.

We demonstrate robust skill in forecasting winter (DJF) mean 10 m wind speeds for the period 1992/3–2011/12 over south-eastern China and the South China Sea (SE China) and northern-central (NC) China, with correlations exceeding 0.8 and 0.6 respectively. High skill over these regions is seen in two independent initialised ensembles which cover different time periods. The NC China region suffers from a similar signal-to-noise problem as identified in forecasts of the North Atlantic Oscillation, where the model appears to be less predictable than the real world. In SE China, the predictability of wind speeds comes from the model’s ability to predict the El Nino Southern Oscillation. In NC China, the wind speed is strongly related to two neighbouring geopotential height anomalies. Cross-validated linear regression models using the above climate indices give similar skill to using the direct model wind predictions in both regions. The model also has significant skill in predicting the strength of the Middle Eastern jet stream, which has previously been shown to be related to winter climate in central China. The model skill demonstrated here may be high enough to develop useful sector-specific seasonal forecasts, for example wind power forecasts for the energy industry, or air quality forecasts for the health sector.

The Yangtze River Basin in China is subject to high inter- and intra-annual variability in its rainfall, leading to challenges in flood protection and for the high-value agricultural activity and large urban populations and infrastructure along its banks. As part of the Climate Science for Services Partnership in China, Chinese and UK scientists, along with key decision makers in this region, are working closely together to understand the needs for climate information, co-develop a seasonal rainfall forecast service aiming to help meet these needs, and evaluate the value or usefulness of this service in supporting decision making to manage risk in the lower Yangtze Basin. We find that there is a range of users reliant on such a service, and that the current service contributes strongly to decision-making for many users. Through close co-operation between providers and users of the service, we also gain a good understanding of the limitations of the current service and outline developments needed to enhance its utility. Keywords: Seasonal forecast, Climate service, User engagement, Co-development, Yangtze River

Climate simulations consistently show an increase in European near-surface air temperature by the late 21st century, although projections for near-surface wind speeds and irradiance differ between models, and are accompanied by large natural variability. These factors make it difficult to estimate the effects of physical climate change on power system planning. Here, the impact of climate change on future European power systems is estimated. We show for the first time how a set of divergent future power system scenarios lead to marked differences in Europe’s total energy balance (demand-net-renewable supply) by 2050, which dominate over the uncertainty associated with climate change (∼50% and ∼5% respectively). However, within any given power system scenario, national power systems may be subject to considerable impacts from climate change, particularly for seasonal differences between renewable resources (e.g., wind power may be impacted by ∼20% or more). There is little agreement between climate models in terms of the spatio-temporal pattern of these impacts, and even in the direction of change for wind and solar. More thorough consideration of climate uncertainty is therefore needed, as it is likely to be of great importance for robust future power system planning and design.

Angular momentum is fundamental to the structure and variability of the atmosphere and hence regional weather and climate. Total atmospheric angular momentum (AAM) is also directly related to the rotation rate of the Earth and hence the length of day. However, the long-range predictability of fluctuations in the length of day, atmospheric angular momentum and the implications for climate prediction are unknown. Here we show that fluctuations in AAM and the length of day are predictable out to more than a year ahead and that this provides an atmospheric source of long-range predictability of surface climate. Using ensemble forecasts from a dynamical climate model we demonstrate predictable signals in the atmospheric angular momentum field that propagate slowly and coherently polewards into the northern and southern hemisphere due to wave-mean flow interaction within the atmosphere. These predictable signals are also shown to precede changes in extratropical surface climate via the North Atlantic Oscillation. These results provide a novel source of long-range predictability of climate from within the atmosphere, greatly extend the lead time for length of day predictions and link geodesy with climate variability.

European climate is influenced by a number of large-scale phenomena which are typically poorly represented by global climate models. A key motivation in generating a coupled perturbed parameter ensemble (PPE) for use in the latest UK climate projections (UKCP18) was to exploit the significant improvements in regional dynamics that have been demonstrated at higher vertical and horizontal resolutions.The UKCP18 package includes a number of products, including a set of 28 global model ‘realizations’ comprising a 15-member PPE and a filtered sub-set of 13 CMIP5 members. These physically coherent, spatially and temporally complete scenarios of future change provide a flexible tool for exploring plausible future changes and their likely impacts.We present an assessment of the PPE’s ability to represent key aspects of the regional large-scale circulation and its implications for the realistic simulation of UK and European climate and its variability. These include the large-scale circulation climatology, frequencies of weather types determined by clustering of north Atlantic MSLP anomalies, latitude and strength of the north Atlantic jet, location and frequency of north Atlantic and European storms and the frequency of blocking events. We show that the PPE members perform at least at as well as, or better than, the filtered 13-member CMIP5 subset with respect to these circulation characteristics. This realistic behaviour offers a good basis for UK and European climate impacts studies, as well as the further development of ‘storylines’ approaches.

UK Climate Projections 2018 (UKCP18) included land and marine projections and were published in 2018 to replace UKCP09. The land projections had three components, and all were designed to provide more information on future weather compared to UKCP09. The first component updated the UKCP09 probabilistic projections by including newer CMIP5 data and focussing on seasonal means from individual years rather than 30-year averages. The probabilistic projections represent the wider uncertainty. The second two components (global and regional projections) both had the aim of providing plausible examples of future climate, but at different resolutions.The global projections were a combination of 13 CMIP5 models and a 15-member perturbed parameter ensemble (PPE) of coupled simulations for 1900-2100 using CMIP5 RCP8.5 from 2005 onwards. The PPE was provided at 60km atmosphere, quarter degree ocean and the large-scale conditions from twelve of the members were used to drive the regional model at both 12km and 2.2km resolution. These plausible examples are more useful for providing information about weather in a future climate to support a storyline approach for decision making.The talk will present examples of new ways to use UKCP18 compared to UKCP09. We will show how the global projections can be used to understand that the recent record winter daily maximum temperature in the UK in 2019 had a large contribution from internal variability and what this means for breaking the record in a warming climate. We also use an example from China to demonstrate one way to exploit information at different time scales, looking at how a circulation index, which is predictable and related to tropical cyclone landfall, changes in a future climate.Finally, we show that while the enhanced resolution of the global and regional projections has improved our capability to provide climate information linked to the better representation of circulation, they lack diversity in some of the key drivers of future climate. Therefore, a key way forward will be to find an appropriate balance between the need for better diversity (e.g. multiple ensembles such as CMIP or PPEs) and the need for an appropriate resolution to retain this new capability.

The development of successful climate services faces a number of challenges, including the identification of the target audience and their needs and requirements, and the effective communication of complex climate information, through engagement with a range of stakeholders. This paper describes how these challenges were tackled during the European Climatic Energy Mixes (ECEM) project, part of the Copernicus Climate Change Service (C3S), in order to deliver a pre-operational, proof-of-concept climate service for the European renewable energy sector. The process of iterative user engagement adopted in ECEM is described, from the initial presentation of the team’s first vision for such a service to support external stakeholders, through to evaluation of the final interactive tool for visualisation, data download and supporting documentation (the C3S ECEM Demonstrator). The outcomes of this evaluation are outlined, together with a retrospective reflection on the engagement and development process. The extent to which co-production and co-design were achieved in practice is assessed. The paper also highlights the distance travelled from the start to end of ECEM in terms of building capacity, developing a community of practice, and raising the Technology Readiness Level. The relevance of ECEM for the European climate services market is briefly considered, including the development of downstream commercial services which build upon the public C3S services. Keywords: Climate services, Sectoral information system, Renewable energy, User needs and requirements, Stakeholder engagement, Co-production

Variations of surface air temperature (SAT) are key in affecting the hydrological cycle, ecosystems and agriculture in western China in summer. This study assesses the seasonal forecast skill and reliability of SAT in western China, using the GloSea5 operational forecast system from the UK Met Office. Useful predictions are demonstrated, with considerable skill over most regions of western China. The temporal correlation coefficients of SAT between model predictions and observations are larger than 0.6, in both northwestern China and the Tibetan Plateau. There are two important sources of skill for these predictions in western China: interannual variation of SST in the western Pacific and the SST trend in the tropical Pacific. The tropical SST change in the recent two decades, with a warming in the western Pacific and cooling in the eastern Pacific, which is reproduced well by the forecast system, provides a large contribution to the skill of SAT in northwestern China. Additionally, the interannual variation of SST in the western Pacific gives rise to the reliable prediction of SAT around the Tibetan Plateau. It modulates convection around the Maritime Continent and further modulates the variation of SAT on the Tibetan Plateau via the surrounding circulation. This process is evident irrespective of detrending both in observations and the model predictions, and acts as a source of skill in predictions for the Tibetan Plateau. The predictability and reliability demonstrated in this study is potentially useful for climate services providing early warning of extreme climate events and could imply useful economic benefits.

The Yangtze River has been subject to heavy flooding throughout history, and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods. Dams along the river help to manage flood waters, and are important sources of electricity for the region. Being able to forecast high-impact events at long lead times therefore has enormous potential benefit. Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used directly for operational services. The teleconnection from El Ni\~no to Yangtze River basin rainfall meant that the strong El Ni\~no in winter 2015/2016 provided a valuable opportunity to test the application of a dynamical forecast system. This paper therefore presents a case study of a real time seasonal forecast for the Yangtze River basin, building on previous work demonstrating the retrospective skill of such a forecast. A simple forecasting methodology is presented, in which the forecast probabilities are derived from the historical relationship between hindcast and observations. Its performance for 2016 is discussed. The heavy rainfall in the May-June-July period was correctly forecast well in advance. August saw anomalously low rainfall, and the forecasts for the June-July-August period correctly showed closer to average levels. The forecasts contributed to the confidence of decision-makers across the Yangtze River basin. Trials of climate services such as this help to promote appropriate use of seasonal forecasts, and highlight areas for future improvements., Comment: 10 pages, 6 figures. This is the original pre-print version as submitted to Adv. Atmos. Sci., and prior to peer review. Please read the final, peer-reviewed article by following the DOI link below, or at https://rdcu.be/Udte

We assess the skill and reliability of forecasts of winter and summer temperature, wind speed and irradiance over China, using the GloSea5 seasonal forecast system. Skill in such forecasts is important for the future development of seasonal climate services for the energy sector, allowing better estimates of forthcoming demand and renewable electricity supply. We find that although overall the skill from the direct model output is patchy, some high-skill regions of interest to the energy sector can be identified. In particular, winter mean wind speed is skilfully forecast around the coast of the South China Sea, related to skilful forecasts of the El Ni\~no--Southern Oscillation. Such information could improve seasonal estimates of offshore wind power generation. Similarly, forecasts of winter irradiance have good skill in eastern central China, with possible use for solar power estimation. Much of China shows skill in summer temperatures, which derives from an upward trend. However, the region around Beijing retains this skill even when detrended. This temperature skill could be helpful in managing summer energy demand. While both the strengths and limitations of our results will need to be considered when developing seasonal climate services in the future, the outlook for such service development in China is promising., Comment: 14 pages, 9 figures; maps at reduced quality due to arXiv size limits. This is the original pre-print version as submitted to J. Appl. Met. Climatol., and prior to peer review. Please read the final, peer-reviewed article by following the DOI link below

We explore the impact of climate change, and its uncertainty, on the prospects for wave power generation at two sites off the south-west and north-west coasts of Britain. We compare the distributions of annual mean significant wave height, mean wave energy period and wave power density in a present-day (1981–2010) and future (2040–2069) period, using a high resolution (~8km$\sim 8\,{\text{km}}$) wave model driven by a perturbed physics ensemble of dynamically downscaled regional climate model simulations. The five ensemble members were chosen (from a pool of 11) to sample the range of uncertainty in climate sensitivity, under an A1B emissions scenario. The present-day wave climate simulations were found to systematically overestimate wave energy periods when compared to an observation-based wave hindcast. There was more similarity in the wave heights, although some members still differed significantly.We tested for changes in the annual-mean wave parameters in the 2050s period. The ensemble member with the highest climate sensitivity showed a statistically significant reduction in mean significant wave height, but this was not seen in the other members. No member showed a significant change in wave energy period or wave power density.The climate change-induced differences in the wave parameters are smaller than the uncertainty of the wave climate projections, and the interannual variability of the wave climate itself, in both periods. Therefore characterising the interannual variability at these sites remains at least as important as the impact of climate change for assessing wave power output around Britain out to the 2050s.

Extra‐tropical cyclones and their associated extreme wind speeds are a major cause of vast damage and large insured losses in several European countries. Reliable seasonal predictions of severe extra‐tropical winter cyclones and associated windstorms would thus have great social and economic benefits, especially in the insurance sector. We analyse the climatological representation and assess the seasonal prediction skill of wintertime extra‐tropical cyclones and windstorms in three multi‐member seasonal prediction systems: ECMWF‐System3, ECMWF‐System4 and Met Office‐GloSea5, based on hindcasts over a 20 year period (1992–2011). Small to moderate positive skill in forecasting the winter frequency of extra‐tropical cyclones and windstorms is found over most of the Northern Hemisphere. The skill is highest for extra‐tropical cyclones at the downstream end of the Pacific storm track and for windstorms at the downstream end of the Atlantic storm track. We also assess the forecast skill of windstorm frequency by using the North Atlantic Oscillation (NAO) as the predictor. Prediction skill improves when using this technique over parts of the British Isles and North Sea in GloSea5 and ECMWF‐S4, but reduces over central western Europe. This suggests that using the NAO is a simple and effective method for predicting wind storm frequency, but that increased forecast skill can be achieved in some regions by identifying windstorms directly using an objective tracking algorithm. Consequently, in addition to the large‐scale influence of the NAO, other factors may contribute to the predictability of wind storm frequency seen in existing forecast suites, across impact relevant regions of Europe. Overall, this study reveals for the first time significant skill in forecasting the winter frequency of high‐impact windstorms ahead of the season in regions that are vulnerable to such events.

We expand our previous study on the relationship between changes in the orientation of the angular momentum vector of dark matter haloes ("spin flips") and changes in their mass (Bett & Frenk 2012), to cover the full range of halo masses in a simulation cube of length 100 $h^{-1}$ Mpc. Since strong disturbances to a halo (such as might be indicated by a large change in the spin direction) are likely also to disturb the galaxy evolving within, spin flips could be a mechanism for galaxy morphological transformation without involving major mergers. We find that 35% of haloes have, at some point in their lifetimes, had a spin flip of at least $45��$ that does not coincide with a major merger. Over 75% of large spin flips coincide with non-major mergers; only a quarter coincide with major mergers. We find a similar picture for changes to the inner-halo spin orientation, although here there is an increased likelihood of a flip occurring. Changes in halo angular momentum orientation, and other such measures of halo perturbation, are therefore very important quantities to consider, in addition to halo mergers, when modelling the formation and evolution of galaxies and confronting such models with observations., 19 pages, 26 figures. Updated to match version accepted for publication in MNRAS

We use reanalysis data to investigate the daily co-variability of wind and solar irradiance in Britain, and its implications for renewable energy supply balancing. The joint distribution of daily-mean wind speeds and irradiances shows that irradiance has a much stronger seasonal cycle than wind, due to the rotational tilt of the Earth. Irradiance is weakly anticorrelated with wind speed throughout the year ($-0.4 \lesssim \rho \lesssim -0.2$): there is a weak tendency for windy days to be cloudier. This is particularly true in Atlantic-facing regions (western Scotland, south-west England). The east coast of Britain has the weakest anticorrelation, particularly in winter, primarily associated with a relative increase in the frequency of clear-but-windy days. We also consider the variability in total power output from onshore wind turbines and solar photovoltaic panels. In all months, daily variability in total power is always reduced by incorporating solar capacity. The scenario with the least seasonal variability is approximately 70%-solar to 30%-wind. This work emphasises the importance of considering the full distribution of daily behaviour rather than relying on long-term average relationships or correlations. In particular, the anticorrelation between wind and solar power in Britain cannot solely be relied upon to produce a well-balanced energy supply., Comment: 19 pages, 19 figures, accepted for publication in Renewable Energy. Text updated to match accepted version (one footnote added, some references corrected)

Sudden stratospheric warmings are amongst the most dramatic events in the Earth's atmosphere and they drive extreme surface weather conditions. They have been recently linked to the hot and dry weather conditions that favour wildfires over Australia. However, the chance of a southern hemisphere event is unknown because it has only been observed once. Legitimate estimation of the frequency of sudden stratospheric warming events requires a large sample of realistic model simulations. Here we show that the chance of an event is close to 4% per year, implying that an event will occur, on average, every 25 years, using a state-of-the-art model that simulates sudden stratospheric warmings accurately. It is thus not surprising that there was a near miss in the September prior to the Australian wildfire of 2019, given the 40 years of comprehensive satellite records and just one observed Antarctic event. According to this new estimate, it would also not be surprising to see a second sudden stratospheric warming event in the coming years in the southern hemisphere. Such a stratospheric warming event might bring further extreme surface weather conditions and natural hazards, as it may raise the risk of increased rainfall in the latitudinal band of 35–50°S. Meanwhile, the associated hot and dry weather conditions over austral subtropical continents might increase the risk of wildfires over these regions.

The article [Predicting June Mean Rainfall in the Middle/Lower Yangtze River Basin], written by [Gill M. MARTIN, Nick J. DUNSTONE, Adam A. SCAIFE, and Philip E. BETT], was originally published electronically on the publisher’s internet portal on [10 December 2019] without open access. With the author(s)’ decision to opt for Open Choice, the copyright of the article changed to © Crown 2020. This article contains public sector information licensed under the Open Government Licence v3.0, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Open Government licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Open Government licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Open Government licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ The original version has been updated.

We investigate the skill of the GloSea5 seasonal forecasting system for two carbon cycle processes, which are strong contributors to global CO2 variability: the impact of meteorological conditions on CO2 uptake by vegetation (characterised by net primary productivity, NPP), and on fire occurrences (characterised by fire risk indices). Current seasonal forecasts of global CO2 concentrations rely on the relationship with the El Niño–Southern Oscillation (ENSO), combined with estimated anthropogenic emissions. NPP and fire are key processes underlying that global CO2–ENSO relationship: In the tropics, during El Niño events, CO2 uptake by vegetation is reduced and fires occur more frequently, leading to higher global CO2 levels. Our study assesses the skill of these processes in the forecast model for the first time. We use the McArthur forest fire index, calculated from daily data from several meteorological variables. We also assess a simpler fire index, based solely on seasonal mean temperature and relative humidity, to test the need for additional complexity. For NPP, the skill is high in regions that respond strongly to ENSO, such as equatorial South America in boreal winter, and northeast Brazil in boreal summer. There is also skill in some regions without a strong ENSO response. The fire risk indices show significant skill across much of the tropics, including Indonesia, southern and eastern Africa, and parts of the Amazon. We relate this skill to the underlying meteorological variables, finding that fire risk in particular follows similar patterns to relative humidity. On the seasonal-mean timescale, the McArthur index offers no benefits over the simpler fire index: they show the same relationship to burnt area and response to ENSO, and the same levels of skill, in almost all cases. Our results highlight potentially useful prediction skill, as well as important limitations, for seasonal forecasts of land-surface impacts of climate variability.

We investigate the relationship between the western Pacific subtropical high (WPSH) and tropical cyclone (TC) landfall in the ERA‐Interim reanalysis and two configurations of the UK Met Office Global Seasonal forecasting system version 5 (GloSea5): Global Atmosphere 3.0 (GA3) and Global Coupled configuration 2 (GC2). Both model configurations have the same horizontal and vertical resolution in the ocean and the atmosphere, but differ in terms of model physics. The WPSH strongly modulates TC activity over the subtropical western North Pacific (WNP) and TC landfall over East Asia (Japan, Korea and East China). Here we show that both model configurations GA3 and GC2 show significant skill for predictions of the WPSH and TC variability over the subtropical WNP, as well as TC frequency along the coast of East Asia, during the boreal summer (June–August). An extension of the analysis to include the full WNP typhoon season (June–November) is also examined; however, only a weak significant relationship between the WPSH index and the observed TC frequency over East Asia is found during this period, and no significant relationship is present in either GloSea5 GA3 or GC2. Results highlight the potential for operational seasonal forecasts of TC landfall risk for Japan, Korea and East China over the June–August period using predictions of the WPSH indices from GloSea5.

The Yangtze river basin, in South East China, experiences anomalously high precipitation in summers following El Niño. This can lead to extensive flooding and loss of life. However, the response following La Niña has not been well documented. In this study, the response of Yangtze summer rainfall to El Niño/La Niña is found to be asymmetric, with no significant response following La Niña. The nature of this asymmetric response is found to be in good agreement with that simulated by the Met Office seasonal forecast system. Yangtze summer rainfall correlates positively with spring sea surface temperatures in the Indian Ocean and northwest Pacific. Indian Ocean sea surface temperatures are found to respond linearly to El Niño/La Niña, and to have a linear impact on Yangtze summer rainfall. However, northwest Pacific sea surface temperatures respond much more strongly following El Niño and, further, correlate more strongly with positive rainfall years. It is concluded that, whilst delayed Indian Ocean signals may influence summer Yangtze rainfall, it is likely that they do not lead to the asymmetric nature of the rainfall response to El Niño/La Niña.

The needs of decision makers in China are being used to develop climate science and climate services through the Climate Science for Services Partnership. Focusing on examples of work for the energy and urban sectors, this paper outlines the approach taken and gives case studies of climate service development. We find that there is great opportunity for climate service development within the existing China Framework for Climate Services, and for enhancing the science that underpins such services. We also find challenges unique to the socio-economic and cultural environment in China, which must be taken into account when developing climate services here, as well as challenges common to all climate service development.

In Britain, residential properties are predominantly heated using gas central heating systems. Ensuring a reliable supply of gas is therefore vital in protecting vulnerable sections of society from the adverse effects of cold weather. Ahead of the winter, the grid operator makes a prediction of gas demand to better anticipate possible conditions. Seasonal weather forecasts are not currently used to inform this demand prediction. Here we assess whether seasonal weather forecasts can skilfully predict the weather-driven component of both winter mean gas demand and the number of extreme gas demand days over the winter period. We find that both the mean and the number of extreme days are predicted with some skill from early November using seasonal forecasts of the large-scale atmospheric circulation (r > 0.5). Although temperature is most strongly correlated with gas demand, the more skilful prediction of the atmospheric circulation means it is a better predictor of demand. If seasonal weather forecasts are incorporated into pre-winter gas demand planning, they could help improve the security of gas supplies and reduce the impacts associated with extreme demand events.

We use the Millennium Simulation series to study the relation between the accretion history (MAH) and mass profile of cold dark matter halos. We find that the mean density within the scale radius, r_{-2} (where the halo density profile has isothermal slope), is directly proportional to the critical density of the Universe at the time when the main progenitor's virial mass equals the mass enclosed within r_{-2}. Scaled to these characteristic values of mass and density, the mean MAH, expressed in terms of the critical density of the Universe, M(\rho_{crit}(z)), resembles that of the enclosed density profile, M(), at z=0. Both follow closely the NFW profile, suggesting that the similarity of halo mass profiles originates from the mass-independence of halo MAHs. Support for this interpretation is provided by outlier halos whose accretion histories deviate from the NFW shape; their mass profiles show correlated deviations from NFW and are better approximated by Einasto profiles. Fitting both M() and M(\rho_{crit}) with either NFW or Einasto profiles yield concentration and shape parameters that are correlated, confirming and extending earlier work linking the concentration of a halo with its accretion history. These correlations also confirm that halo structure is insensitive to initial conditions: only halos whose accretion histories differ greatly from the NFW shape show noticeable deviations from NFW in their mass profiles. As a result, the NFW profile provides acceptable fits to hot dark matter halos, which do not form hierarchically, and for fluctuation power spectra other than CDM. Our findings, however, predict a subtle but systematic dependence of mass profile shape on accretion history which, if confirmed, would provide strong support for the link between accretion history and halo structure we propose here., Comment: 12 pages, 8 figures, MNRAS 432 1103L (2013)

We use the Millennium Simulation series to study how the dynamical state of dark matter halos affects the relation between mass and concentration. We find that a large fraction of massive systems are identified when they are substantially out of equilibrium and in a particular phase of their dynamical evolution: the more massive the halo, the more likely it is found at a transient stage of high concentration. This state reflects the recent assembly of massive halos and corresponds to the first pericentric passage of recently-accreted material when, before virialization, the kinetic and potential energies reach maximum and minimum values, respectively. This result explains the puzzling upturn in the mass-concentration relation reported in recent work for massive halos; indeed, the upturn disappears when only dynamically-relaxed systems are considered in the analysis. Our results warn against applying simple equilibrium models to describe the structure of rare, massive galaxy clusters and urges caution when extrapolating scaling laws calibrated on lower-mass systems, where such deviations from equilibrium are less common. The evolving dynamical state of galaxy clusters ought to be carefully taken into account if cluster studies are to provide precise cosmological constraints.

We analyse the impact of galaxy--halo misalignment on the ability of weak lensing studies to constrain the shape of dark matter haloes, using a combination of the Millennium dark matter N-body simulation and different semi-analytic galaxy formation models, as well as simpler Monte Carlo tests. Since the distribution of galaxy--halo alignments is not known in detail, we test various alignment models, together with different methods of determining the halo shape. In addition to alignment, we examine the interplay of halo mass and shape, and galaxy colour and morphology with the resulting stacked projected halo shape. We find that only in the case where significant numbers of galaxy and halo minor axes are parallel does the stacked, projected halo axis ratio fall below 0.95. When using broader misalignment distributions, such as those found in recent simulations of galaxy formation, the halo ellipticity signal is washed out and would be extremely difficult to measure observationally. It is important to note that the spread in stacked halo axis ratio due to theoretical unknowns (differences between semi-analytic models, and between alignment models) are much bigger than any statistical uncertainty: It is naive to assume that, simply because LCDM predicts aspherical haloes, the stacked projected shape will be elliptical. In fact, there is no robust LCDM prediction yet for this procedure, and the interpretation of any such elliptical halo signal from lensing in terms of physical halo properties will be extremely difficult.

During the growth of a cold dark matter halo, the direction of its spin can undergo rapid changes. These could disrupt or even destroy a stellar disc forming in the halo, possibly resulting in the generation of a bulge or spheroid. We investigate the frequency of significant changes in the orientation of the angular momentum vector of dark matter haloes (‘spin flips’) and their degree of correlation with mergers. We focus on haloes of mass similar to that of the Milky Way halo at redshift z= 0 (log10 M/h−1 M⊙= 12.0 → 12.5) and consider flips in the spin of the whole halo or just its inner parts. We find that a greater fraction of major mergers are associated with large spin flips than minor mergers. However, since major mergers are rare, the vast majority (93 per cent) of large whole-halo spin flips (θ≥ 45°) coincide with small mass changes, not major mergers. The spin vector of the inner halo experiences much more frequent flips than the halo as a whole. Over their entire lifetimes (i.e. after a halo acquires half of its final mass), more than 10 per cent of haloes experience a flip of at least 45° in the spin of the entire halo and nearly 60 per cent experience a flip this large in the inner halo. These numbers are reduced to 9 per cent for the whole halo and 47 per cent for the inner halo when we consider only haloes with no major mergers after formation. Our analysis suggests that spin flips (whose effects are not currently included in galaxy formation models) could be an important factor in the morphological transformation of disc galaxies.

We investigate the spins and shapes of over a million dark matter haloes identified at z=0 in the Millennium simulation. Our sample spans halo masses ranging from dwarf galaxies to rich galaxy clusters. The very large dynamic range of this simulation enables the distribution of spins and shapes and their variation with halo mass and environment to be characterised with unprecedented precision. We compare results for haloes identified using different algorithms, including a novel one based on the branches of the halo merger trees. We investigate (and remove) biases in the estimate of angular momentum introduced by both the algorithms themselves and by numerical effects. We find that for this many objects, the traditional lognormal function is no longer an adequate description of the distribution of the dimensionless spin parameter lambda, and we provide a different function that gives a better fit. The variation of spin with halo mass is weak but detectable, although the trend depends strongly on the halo definition used. The haloes exhibit a range of shapes, with a preference for prolateness over oblateness. More massive haloes tend to be less spherical and more prolate. We find that the more spherical haloes have spin in the median, and those closest to spherical have a spin independent of mass. The most massive have a spin independent of shape. The majority of haloes have their angular momentum vector aligned with their minor axis and perpendicular to their major axis. We find that higher tend to be more clustered, with a stronger effect for more massive haloes. (abridged)

We present weak lensing constraints on the ellipticity of galaxy-scale matter haloes and the galaxy-halo misalignment. Using data from the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS), we measure the weighted-average ratio of the aligned projected ellipticity components of galaxy matter haloes and their embedded galaxies, $f_\mathrm{h}$, split by galaxy type. We then compare our observations to measurements taken from the Millennium Simulation, assuming different models of galaxy-halo misalignment. Using the Millennium Simulation we verify that the statistical estimator used removes contamination from cosmic shear. We also detect an additional signal in the simulation, which we interpret as the impact of intrinsic shape-shear alignments between the lenses and their large-scale structure environment. These alignments are likely to have caused some of the previous observational constraints on $f_\mathrm{h}$ to be biased high. From CFHTLenS we find $f_\mathrm{h}=-0.04 \pm 0.25$ for early-type galaxies, which is consistent with current models for the galaxy-halo misalignment predicting $f_\mathrm{h}\simeq 0.20$. For late-type galaxies we measure $f_\mathrm{h}=0.69_{-0.36}^{+0.37}$ from CFHTLenS. This can be compared to the simulated results which yield $f_\mathrm{h}\simeq 0.02$ for misaligned late-type models., 21 pages, 3 tables, 9 figures. This replacement matches the version accepted for publication in MNRAS

We assess the utility of seasonal forecasts for the energy industry by showing how recently-established predictability of the North Atlantic Oscillation (NAO) in winter allows predictability of near-surface wind speed and air temperature and therefore energy supply and demand respectively. Our seasonal prediction system (GloSea5) successfully reproduces the influence of the NAO on European climate, leading to skilful forecasts of wind speed and wind power and hence wind driven energy supply. Temperature is skilfully forecast using the observed temperature-NAO relationship and the NAO forecast. Using the correlation between forecast NAO and observed GB electricity demand, we demonstrate that skilful predictions of winter demand are also achievable on seasonal timescales well in advance of the season. Finally, good reliability of probabilistic forecasts of above/below-average wind speed and temperature is also demonstrated.

We characterise the long-term variability of European near-surface wind speeds using 142 years of data from the Twentieth Century Reanalysis (20CR), and consider the potential of such long-baseline climate data sets for wind energy applications. The low resolution of the 20CR would severely restrict its use on its own for wind farm site-screening. We therefore perform a simple statistical calibration to link it to the higher-resolution ERA-Interim data set (ERAI), such that the adjusted 20CR data has the same wind speed distribution at each location as ERAI during their common period. Using this corrected 20CR data set, wind speeds and variability are characterised in terms of the long-term mean, standard deviation, and corresponding trends. Many regions of interest show extremely weak trends on century timescales, but contain large multidecadal variability. Since reanalyses such as ERAI are often used to provide the background climatology for wind farm site assessments, but contain only a few decades of data, our results can be used as a way of incorporating decadal-scale wind climate variability into such studies, allowing investment risks for wind farms to be reduced., 18 pages, plus 4 page supplementary information included here as Appendix D. This is the authors' corrected version, matching the content of the version accepted by Theoretical and Applied Climatology

Intrinsic galaxy alignments constitute the major astrophysical systematic of forthcoming weak gravitational lensing surveys but also yield unique insights into galaxy formation and evolution. We build analytic models for the distribution of galaxy shapes based on halo properties extracted from the Millennium Simulation, differentiating between early- and late-type galaxies as well as central galaxies and satellites. The resulting ellipticity correlations are investigated for their physical properties and compared to a suite of current observations. The best-faring model is then used to predict the intrinsic alignment contamination of planned weak lensing surveys. We find that late-type galaxy models generally have weak intrinsic ellipticity correlations, marginally increasing towards smaller galaxy separation and higher redshift. The signal for early-type models at fixed halo mass strongly increases by three orders of magnitude over two decades in galaxy separation, and by one order of magnitude from z=0 to z=2. The intrinsic alignment strength also depends strongly on halo mass, but not on galaxy luminosity at fixed mass, or galaxy number density in the environment. We identify models that are in good agreement with all observational data, except that all models over-predict alignments of faint early-type galaxies. The best model yields an intrinsic alignment contamination of a Euclid-like survey between 0.5-10% at z>0.6 and on angular scales larger than a few arcminutes. Cutting 20% of red foreground galaxies using observer-frame colours can suppress this contamination by up to a factor of two., 23 pages, 14 figures; minor changes to match version published in MNRAS

We present initial results of a study on the variability of wind speeds across Europe over the past 140 yr, making use of the recent Twentieth Century Reanalysis data set, which includes uncertainty estimates from an ensemble method of reanalysis. Maps of the means and standard deviations of daily wind speeds, and the Weibull-distribution parameters, show the expected features, such as the strong, highly-variable wind in the north-east Atlantic. We do not find any clear, strong long-term trends in wind speeds across Europe, and the variability between decades is large. We examine how different years and decades are related in the long-term context, by looking at the ranking of annual mean wind speeds. Picking a region covering eastern England as an example, our analyses show that the wind speeds there over the past ~ 20 yr are within the range expected from natural variability, but do not span the full range of variability of the 140-yr data set. The calendar-year 2010 is however found to have the lowest mean wind speed on record for this region., 8 pages, published in Adv.Sci.Res. for volume on proceedings of 12th EMS Annual Meeting & 9th European Conference on Applied Climatology (Lodz, Poland, September 2012). Minor updates made to incorporate referees' comments and typesetting changes. Please refer to journal for final open-access version

The statistical properties of the ellipticities of galaxy images depend on how galaxies form and evolve, and therefore constrain models of galaxy morphology, which are key to the removal of the intrinsic alignment contamination of cosmological weak lensing surveys, as well as to the calibration of weak lensing shape measurements. We construct such models based on the halo properties of the Millennium Simulation and confront them with a sample of 90,000 galaxies from the COSMOS Survey, covering three decades in luminosity and redshifts out to z=2. The ellipticity measurements are corrected for effects of point spread function smearing, spurious image distortions, and measurement noise. Dividing galaxies into early, late, and irregular types, we find that early-type galaxies have up to a factor of two lower intrinsic ellipticity dispersion than late-type galaxies. None of the samples shows evidence for redshift evolution, while the ellipticity dispersion for late-type galaxies scales strongly with absolute magnitude at the bright end. The simulation-based models reproduce the main characteristics of the intrinsic ellipticity distributions although which model fares best depends on the selection criteria of the galaxy sample. We observe fewer close-to-circular late-type galaxy images in COSMOS than expected for a sample of randomly oriented circular thick disks and discuss possible explanations for this deficit., Comment: 18 pages, 8 figures; updated simulations and galaxy sample definition, more galaxy samples analysed; matches version published in MNRAS

Semi-analytic models of galaxy formation typically form the spheroidal components of galaxies ("bulges"), solely through galactic major mergers. However, it is possible that non-merger events (e.g. a "fly-by" by a smaller halo) can perturb a galaxy--halo system sufficiently to form a bulge. We present a preliminary investigation into the frequency of major changes in halo and galaxy spin direction, which could be signatures of such events., Comment: 2 pages, 2 figures, to appear in "Hunting for the Dark: The Hidden Side of Galaxy Formation", Malta, 19-23 Oct. 2009, eds. V.P. Debattista & C.C. Popescu, AIP Conf. Ser., in press

We investigate the magnitude and internal alignment of the angular momentum of cold dark matter haloes in simulations with and without baryons. We analyse the cumulative angular momentum profiles of hundreds of thousands of haloes in the Millennium simulation and in a smaller, but higher resolution, simulation, in total spanning 5 orders of magnitude in mass. For haloes of a given mass, the median specific angular momentum increases as j(, Comment: 21 pages, 27 figures. Accepted for publication in MNRAS (abstract shown here is slightly abridged). Replaced with accepted version, which adds significant clarifications and expansion of discussions, including additional figures. All science content remains unchanged

We use the Millennium Simulation (MS) to study the statistics of LCDM halo concentrations at z = 0. Our results confirm that the average halo concentration declines monotonically with mass; a power-law fits well the concentration-mass relation for over 3 decades in mass, up to the most massive objects to form in a LCDM universe (~ 10^15 h^-1 Msol). This is in clear disagreement with the predictions of the model proposed by Bullock et al. for these rare objects, and agrees better with the original predictions of Navarro, Frenk, & White. The large volume surveyed, together with the unprecedented numerical resolution of the MS, allow us to estimate with confidence the distribution of concentrations and, consequently, the abundance of systems with unusual properties. About one in a hundred cluster haloes (M200 >~ 3x10^14 h^-1 Msol) have concentrations exceeding c200 = 7.5, a result that may be used to interpret the likelihood of unusually strong massive gravitational lenses, such as Abell 1689, in the LCDM cosmogony. A similar fraction (1 in 100) of galaxy-sized haloes (M200 ~ 10^12 h^-1 Msol) have c200 < 4.5, an important constraint on models that attempt to reconcile the rotation curves of low surface-brightness galaxies by appealing to haloes of unexpectedly low concentration. We find that halo concentrations are independent of spin once haloes manifestly out of equilibrium are removed from the sample. Compared to their relaxed brethren, the concentrations of out-of-equilibrium haloes tend to be lower and to have more scatter, while their spins tend to be higher... (continue), 14 pages, 13 eps figures; Submitted to MNRAS

Seasonal climate forecasts have the potential to support planning decisions and provide advanced warning to government, industry, and communities to help reduce the impacts of adverse climatic conditions. Assessing the reliability of seasonal forecasts, generated using different models and methods, is essential to ensure their appropriate interpretation and use. Here we assess the reliability of forecasts for seasonal total precipitation in Sahelian West Africa, a region of high year-to-year climate variability. Through digitizing forecasts issued from the regional climate outlook forum in West Africa known as Prévisions Climatiques Saisonnières en Afrique Soudano-Sahélienne (PRESASS), we assess their reliability by comparing them to the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) project observational data over the past 20 years. The PRESASS forecasts show positive skill and reliability, but a bias toward lower forecast probabilities in the below-normal precipitation category. In addition, we assess the reliability of seasonal precipitation forecasts for the same region using available global dynamical forecast models. We find all models have positive skill and reliability, but this varies geographically. On average, NCEP’s CFS and ECMWF’s SEAS5 systems show greater skill and reliability than the Met Office’s GloSea5, and in turn than Météo-France’s Sys5, but one key caveat is that model performance might depend on the meteorological situation. We discuss the potential for improving use of dynamical model forecasts in the regional climate outlook forums, to improve the reliability of seasonal forecasts in the region and the objectivity of the seasonal forecasting process used in the PRESASS regional climate outlook forum.