A national-scale seasonal hydrological forecast system: development and evaluation over Britain

Skilful winter seasonal predictions for the North Atlantic circulation and northern Europe have now been demonstrated and the potential for seasonal hydrological forecasting in the UK is now being explored. One of the techniques being used combines seasonal rainfall forecasts provided by operational weather forecast systems with hydrological modelling tools to provide estimates of seasonal mean river flows up to a few months ahead. The work presented here shows how spatial information contained in a distributed hydrological model typically requiring high-resolution (daily or better) rainfall data can be used to provide an initial condition for a much simpler forecast model tailored to use low-resolution monthly rainfall forecasts. Rainfall forecasts (“hindcasts”) from the GloSea5 model (1996 to 2009) are used to provide the first assessment of skill in these national-scale flow forecasts. The skill in the combined modelling system is assessed for different seasons and regions of Britain, and compared to what might be achieved using other approaches such as use of an ensemble of historical rainfall in a hydrological model, or a simple flow persistence forecast. The analysis indicates that only limited forecast skill is achievable for Spring and Summer seasonal hydrological forecasts; however, Autumn and Winter flows can be reasonably well forecast using (ensemble mean) rainfall forecasts based on either GloSea5 forecasts or historical rainfall (the preferred type of forecast depends on the region). Flow forecasts using ensemble mean GloSea5 rainfall perform most consistently well across Britain, and provide the most skilful forecasts overall at the 3-month lead time. Much of the skill (64 %) in the 1-month ahead seasonal flow forecasts can be attributed to the hydrological initial condition (particularly in regions with a significant groundwater contribution to flows), whereas for the 3-month ahead lead time, GloSea5 forecasts account for  ∼ 70 % of the forecast skill (mostly in areas of high rainfall to the north and west) and only 30 % of the skill arises from hydrological memory (typically groundwater-dominated areas). Given the high spatial heterogeneity in typical patterns of UK rainfall and evaporation, future development of skilful spatially distributed seasonal forecasts could lead to substantial improvements in seasonal flow forecast capability, potentially benefitting practitioners interested in predicting hydrological extremes, not only in the UK but also across Europe

Statistical adjustment, calibration and downscaling of seasonal forecasts: a case-study for Southeast Asia

The present paper is a follow-on of the work presented in Manzanas et al. (Clim Dyn 53(3–4):1287–1305, 2019) which provides a comprehensive intercomparison of alternatives for the post-processing (statistical adjustment, calibration and downscaling) of seasonal forecasts for a particularly interesting region, Southeast Asia. To answer the questions that were raised in the preceding work, apart from Bias Adjustment (BA) and ensemble Re-Calibration (RC) methods—which transform directly the variable of interest,—we include here more complex Perfect Prognosis (PP) and Model Outputs Statistics (MOS) downscaling techniques—which operate on a selection of large-scale model circulation variables linked to the local observed variable of interest. Moreover, we test the suitability of BA and PP methods for the post-processing of daily—not only seasonal—time-series, which are often needed in a variety of sectoral applications (crop, hydrology, etc.) or to compute specific climate indices (heat waves, fire weather index, etc.). In addition, we also undertake an assessment of the effect that observational uncertainty may have for statistical post-processing. Our results indicate that PP methods (and to a lesser extent MOS) are highly case-dependent and their application must be carefully analyzed for the region/season/application of interest, since they can either improve or degrade the raw model outputs. Therefore, for those cases for which the use of these methods cannot be carefully tested by experts, our overall recommendation would be the use of BA methods, which seem to be a safe, easy to implement alternative that provide competitive results in most situations. Nevertheless, all methods (including BA ones) seem to be sensitive to observational uncertainty, especially regarding the reproduction of extremes and spells. For MOS and PP methods, this issue can even lead to important regional differences in interannual skill. The lessons learnt from this work can substantially benefit a wide range of end-users in different socio-economic sectors, and can also have important implications for the development of high-quality climate services.This work has been funded by the C3S activity on Evaluation and Quality Control for seasonal forecasts and the EU project AfriCultuReS (H2020-EU.3.5.5, GA 774652). JMG was partially supported by the Project MULTI-SDM (CGL2015-66583-R, MINECO/FEDER). FJDR was partially funded by the H2020 EUCP project (GA 776613). The authors also acknowledge the SA-OBS dataset and the data providers in the SACA&D Project ( http://saca-bmkg.knmi.nl )

Recent applications and potential of near-term (interannual to decadal) climate predictions

Following efforts from leading centres for climate forecasting, sustained routine operational near-term climate predictions (NTCP) are now produced that bridge the gap between seasonal forecasts and climate change projections offering the prospect of seamless climate services. Though NTCP is a new area of climate science and active research is taking place to increase understanding of the processes and mechanisms required to produce skillful predictions, this significant technical achievement combines advances in initialisation with ensemble prediction of future climate up to a decade ahead. With a growing NTCP database, the predictability of the evolving externally-forced and internally-generated components of the climate system can now be quantified. Decision-makers in key sectors of the economy can now begin to assess the utility of these products for informing climate risk and for planning adaptation and resilience strategies up to a decade into the future. Here, case studies are presented from finance and economics, water management, agriculture and fisheries management demonstrating the emerging utility and potential of operational NTCP to inform strategic planning across a broad range of applications in key sectors of the global economy

The worldwide C3S CORDEX grand ensemble: A major contribution to assess regional climate change in the IPCC AR6 Atlas

peer reviewedAbstract The collaboration between the Coordinated Regional Climate Downscaling Experiment (CORDEX) and the Earth System Grid Federation (ESGF) provides open access to an unprecedented ensemble of Regional Climate Model (RCM) simulations, across the 14 CORDEX continental-scale domains, with global coverage. These simulations have been used as a new line of evidence to assess regional climate projections in the latest contribution of the Working Group I (WGI) to the IPCC Sixth Assessment Report (AR6), particularly in the regional chapters and the Atlas. Here, we present the work done in the framework of the Copernicus Climate Change Service (C3S) to assemble a consistent worldwide CORDEX grand ensemble, aligned with the deadlines and activities of IPCC AR6. This work addressed the uneven and heterogeneous availability of CORDEX ESGF data by supporting publication in CORDEX domains with few archived simulations and performing quality control. It also addressed the lack of comprehensive documentation by compiling information from all contributing regional models, allowing for an informed use of data. In addition to presenting the worldwide CORDEX dataset, we assess here its consistency for precipitation and temperature by comparing climate change signals in regions with overlapping CORDEX domains, obtaining overall coincident regional climate change signals. The C3S CORDEX dataset has been used for the assessment of regional climate change in the IPCC AR6 (and for the interactive Atlas) and is available through the Copernicus Climate Data Store (CDS)

Long-range meteorological forecasting and links to agricultural applications

Reliable advance information about likely meteorological conditions during an agricultural season can potentially greatly benefit planning, risk management and productivity. In this article, we review the present state of production and dissemination of meteorological long-range (seasonal) forecast information and the use of such products in agricultural applications. There has been rapid development of dynamical prediction systems in particular, and several centres routinely provide seasonal forecasts of rainfall and temperature with global coverage. Currently the uptake of long-range forecast products by users has been limited, and the potential value is far from being attained. Various factors that inhibit usage are described. Further investment in the infrastructure is required, both in creating relevant specific products and in disseminating and applying them effectively. Investment in research is also required to investigate opportunities and beneficial strategies for a wide range of regions and activities, with closer interaction between the meteorological and agricultural communities and relevant intermediary agencies. Such development would complement separate ongoing efforts to improve the meteorological forecast systems and to improve agricultural management and technology.Seasonal climate Long-range forecast Forecast systems Agriculture ENSO

The science behind the Hydrological Outlook seasonal groundwater level forecasts

The Hydrological Outlook provides a forecast of groundwater levels (and river flows) across the UK over the next three months. To forecast groundwater levels the British Geological Survey uses models that simulate fluctuations in groundwater level at 25 sites across the UK. Each of these models is driven by rainfall and evaporation time-series and has been calibrated against past observations of groundwater level. To forecast groundwater levels the 1 and 3-month ahead climate forecasts produced by a Met Office climate model are used. These two climate forecasts are probabilistic and comprise an ensemble of up to 42 members. Consequently, a probabilistic groundwater level forecast is produced for each site. There will be a demonstration of the Hydrological Outlook web site and short talk on how the models are used to produce the forecasts and how the skill of the forecast has been tested

Securing 2020 vision for 2030: climate change and ensuring resilience in water and sanitation services.

Drinking-water supply and sanitation services are essential for human health, but their technologies and management systems are potentially vulnerable to climate change. An assessment was made of the resilience of water supply and sanitation systems against forecast climate changes by 2020 and 2030. The results showed very few technologies are resilient to climate change and the sustainability of the current progress towards the Millennium Development Goals (MDGs) may be significantly undermined. Management approaches are more important than technology in building resilience for water supply, but the reverse is true for sanitation. Whilst climate change represents a significant threat to sustainable drinking-water and sanitation services, through no-regrets actions and using opportunities to increase service quality, climate change may be a driver for improvements that have been insufficiently delivered to date

Skillful seasonal prediction of Yangtze river valley summer rainfall

China suffers from frequent summer floods and droughts, but seasonal forecast skill of corresponding summer rainfall remains a key challenge. In this study, we demonstrate useful levels of prediction skill over the Yangtze river valley for summer rainfall and river flows using a new high resolution forecast system. Further analysis of the sources of predictability suggests that the predictability of Yangtze river valley summer rainfall corresponds to skillful prediction of rainfall in the deep tropics and around the Maritime Continent. The associated dynamical signals favor increased poleward water vapor transport from South China and hence Yangtze river valley summer rainfall and river flow. The predictability and useful level of skill demonstrated by this study imply huge potential for flooding and drought related disaster mitigation and economic benefits for the region based on early warning of extreme climate events