Description: This paper introduces the Distribution-Independent Storm Severity Index (DI-SSI). The DI-SSI represents an approach to quantify the severity of exceptional surface wind speeds of large scale windstorms that is complementary to the SSI introduced by Leckebusch et al. While the SSI approaches the extremeness of a storm from a meteorological and potential loss (impact) perspective, the DI-SSI defines the severity in a more climatological perspective. The idea is to assign equal index values to wind speeds of the same singularity (e.g. the 99th percentile) under consideration of the shape of the tail of the local wind speed climatology. Especially in regions at the edge of the classical storm track, the DI-SSI shows more equitable severity estimates, e.g. for the extra-tropical cyclone Klaus. In order to compare the indices, their relation with the North Atlantic Oscillation is studied, which is one of the main large scale drivers for the intensity of European windstorms.

Description: The Water and Global Change (WATCH) forcing datasets have been created to support the use of hydrological and land surface models for the assessment of the water cycle within climate change studies. They are based on 40-yr ECMWF Re-Analysis (ERA-40) or ECMWF interim reanalysis (ERA-Interim) with temperatures (among other variables) adjusted such that their monthly means match the monthly temperature dataset from the Climatic Research Unit. To this end, daily minimum, maximum, and mean temperatures within one calendar month have been subjected to a correction involving monthly means of the respective month. As these corrections can be largely different for adjacent months, this procedure potentially leads to implausible differences in daily temperatures across the boundaries of calendar months. We analyze day-to-day temperature fluctuations within and across months and find that across-months differences are significantly larger, mostly in the tropics and frigid zones. Average across-months differences in daily mean temperature are typically between 10% and 40% larger than their corresponding within-months average temperature differences. However, regions with differences up to 200% can be found in tropical Africa. Particularly in regions where snowmelt is a relevant player for hydrology, a few degrees Celsius difference can be decisive for triggering this process. Daily maximum and minimum temperatures are affected in the same regions, but in a less severe way.

Description: Mid-latitudinal cyclones are a key factor for understanding regional anomalies in primary meteorological parameters such as temperature or precipitation. Extreme cyclones can produce notable impacts on human society and economy, for example, by causing enormous economic losses through wind damage. Based on 41 annually initialised (1961–2001) hindcast ensembles, this study evaluates the ability of a single-model decadal forecast system (MPI-ESM-LR) to provide skilful probabilistic three-category forecasts (enhanced, normal or decreased) of winter (ONDJFM) extra-tropical cyclone frequency over the Northern Hemisphere with lead times from 1 yr up to a decade. It is shown that these predictions exhibit some significant skill, mainly for lead times of 2–5 yr, especially over the North Atlantic and Pacific. Skill for intense cyclones is generally higher than for all detected systems. A comparison of decadal hindcasts from two different initialisation techniques indicates that initialising from reanalysis fields yields slightly better results for the first forecast winter (month 10–15), while initialisation based on an assimilation experiment provides better skill for lead times between 2 and 5 yr. The reasons and mechanisms behind this predictive skill are subject to future work. Preliminary analyses suggest a strong relationship of the model’s skill over the North Atlantic with the ability to predict upper ocean temperatures modulating lower troposphere baroclinicity for the respective area and time scales.

Description: This paper describes an approach to derive probabilistic predictions of local winter storm damage occurrences from a global medium-range ensemble prediction system (EPS). Predictions of storm damage occurrences are subject to large uncertainty due to meteorological forecast uncertainty (typically addressed by means of ensemble predictions) and uncertainties in modelling weather impacts. The latter uncertainty arises from the fact that local vulnerabilities are not known in sufficient detail to allow for a deterministic prediction of damages, even if the forecasted gust wind speed contains no uncertainty. Thus, to estimate the damage model uncertainty, a statistical model based on logistic regression analysis is employed, relating meteorological analyses to historical damage records. A quantification of the two individual contributions (meteorological and damage model uncertainty) to the total forecast uncertainty is achieved by neglecting individual uncertainty sources and analysing resulting predictions. Results show an increase in forecast skill measured by means of a reduced Brier score if both meteorological and damage model uncertainties are taken into account. It is demonstrated that skilful predictions on district level (dividing the area of Germany into 439 administrative districts) are possible on lead times of several days. Skill is increased through the application of a proper ensemble calibration method, extending the range of lead times for which skilful damage predictions can be made.

Description: Climate simulations are the fuel to drive hydrological models that are used to assess the impacts of climate change and variability on hydrological parameters, such as river discharges, soil moisture, and evapotranspiration. Unlike with cars, where we know which fuel the engine requires, we never know in advance what unexpected side effects might be caused by the fuel we feed our models with. Sometimes we increase the fuel's octane number (bias correction) to achieve better performance and find out that the model behaves differently but not always as was expected or desired. This study investigates the impacts of projected climate change on the hydrology of the Upper Blue Nile catchment using two model ensembles consisting of five global CMIP5 Earth system models and 10 regional climate models (CORDEX Africa). WATCH forcing data were used to calibrate an eco-hydrological model and to bias-correct both model ensembles using slightly differing approaches. On the one hand it was found that the bias correction methods considerably improved the performance of average rainfall characteristics in the reference period (1970–1999) in most of the cases. This also holds true for non-extreme discharge conditions between Q20 and Q80. On the other hand, bias-corrected simulations tend to overemphasize magnitudes of projected change signals and extremes. A general weakness of both uncorrected and bias-corrected simulations is the rather poor representation of high and low flows and their extremes, which were often deteriorated by bias correction. This inaccuracy is a crucial deficiency for regional impact studies dealing with water management issues and it is therefore important to analyse model performance and characteristics and the effect of bias correction, and eventually to exclude some climate models from the ensemble. However, the multi-model means of all ensembles project increasing average annual discharges in the Upper Blue Nile catchment and a shift in seasonal patterns, with decreasing discharges in June and July and increasing discharges from August to November.

Description: Winter wind storms related to intense extra-tropical cyclones are meteorological extreme events, often with major impacts on economy and human life, especially for Europe and the mid-latitudes. Hence, skillful decadal predictions regarding the frequency of their occurrence would be of great socio-economic value. The present paper extends the study of Kruschke et al. (2014) in several aspects. First, this study is situated in a more impact oriented context by analyzing the frequency of potentially damaging wind storm events instead of targeting at cyclones as general meteorological features which was done by Kruschke et al. (2014). Second, this study incorporates more data sets by analyzing five decadal hindcast experiments – 41 annual (1961–2001) initializations integrated for ten years each – set up with different initialization strategies. However, all experiments are based on the Max-Planck-Institute Earth System Model in a low-resolution configuration (MPI-ESM-LR). Differing combinations of these five experiments allow for more robust estimates of predictive skill (due to considerably larger ensemble size) and systematic comparisons of the underlying initialization strategies. Third, the hindcast experiments are corrected for model bias and potential drifts over lead time by means of a novel parametric approach, accounting for non-stationary model drifts. We analyze whether skillful probabilistic three-category forecasts (enhanced, normal or decreased) can be provided regarding winter (ONDJFM) wind storm frequencies over the Northern Hemisphere (NH). Skill is assessed by using climatological probabilities and uninitialized transient simulations as reference forecasts. It is shown that forecasts of average winter wind storm frequencies for winters 2–5 and winters 2–9 are skillful over large parts of the NH. However, most of this skill is associated with external forcing from transient greenhouse gas and aerosol concentrations, already included in the uninitialized simulations. Only over East Asia and the Northwest Pacific, the Northwest Atlantic as well as the Eastern Mediterranean the initialized hindcasts perform significantly better than the uninitialized simulations. While no significant differences are evident between anomaly- and full-field-initialization, initializing the model's ocean component from GECCO2-ocean-reanalysis yields slightly better results than from ORA-S4, especially over the Northeast Pacific. Additionally, it is shown that the novel parametric drift-correction approach – estimating potential cubic drifts with parameters linearly changing in time – is more appropriate than the standard procedure – estimating constant model drifts via the lead-time-dependent bias – and, hence, yields higher skill estimates.

Description: The properties of European wind storms under present climate conditions are estimated on the basis of surface wind forecasts from the European Center of Medium-Range Weather Forecast (ECMWF) Ensemble Prediction System (EPS). While the EPS is designed to provide forecast information of the range of possible weather developments starting from the observed state of weather, we use its archive in a climatological context. It provides a large number of modifications of observed storm events, and includes storms that did not occur in reality. Thus it is possible to create a large sample of storm events, which entirely originate from a physically consistent model, whose ensemble spread represents feasible alternative storm realizations of the covered period. This paper shows that the huge amount of identifiable events in the EPS is applicable to reduce uncertainties in a wide range of fields of research focusing on winter storms. Wind storms are identified and tracked in this study over their lifetime using an algorithm, based on the local exceedance of the 98th percentile of instantaneous 10 m wind speed, calculating a storm severity measure. After removing inhomogeneities in the dataset arising from major modifications of the operational system, the distributions of storm severity, storm size and storm duration are computed. The overall principal properties of the homogenized EPS storm data set are in good agreement with storms from the ERA-Interim dataset, making it suitable for climatological investigations of these extreme events. A demonstrated benefit in the climatological context by the EPS is presented. It gives a clear evidence of a linear increase of maximum storm intensity and wind field size with storm duration. This relation is not recognizable from a sparse ERA-Interim sample for long lasting events, as the number of events in the reanalysis is not sufficient to represent these characteristics.

Description: This paper describes the recommended solar forcing dataset for CMIP6 and highlights changes with respect to CMIP5. The solar forcing is provided for radiative properties, namely total solar irradiance (TSI), solar spectral irradiance (SSI), and the F10.7 index as well as particle forcing, including geomagnetic indices Ap and Kp, and ionization rates to account for effects of solar protons, electrons, and galactic cosmic rays. This is the first time that a recommendation for solar-driven particle forcing has been provided for a CMIP exercise. The solar forcing datasets are provided at daily and monthly resolution separately for the CMIP6 preindustrial control, historical (1850–2014), and future (2015–2300) simulations. For the preindustrial control simulation, both constant and time-varying solar forcing components are provided, with the latter including variability on 11-year and shorter timescales but no long-term changes. For the future, we provide a realistic scenario of what solar behavior could be, as well as an additional extreme Maunder-minimum-like sensitivity scenario. This paper describes the forcing datasets and also provides detailed recommendations as to their implementation in current climate models. For the historical simulations, the TSI and SSI time series are defined as the average of two solar irradiance models that are adapted to CMIP6 needs: an empirical one (NRLTSI2–NRLSSI2) and a semi-empirical one (SATIRE). A new and lower TSI value is recommended: the contemporary solar-cycle average is now 1361.0 W m−2. The slight negative trend in TSI over the three most recent solar cycles in the CMIP6 dataset leads to only a small global radiative forcing of −0.04 W m−2. In the 200–400 nm wavelength range, which is important for ozone photochemistry, the CMIP6 solar forcing dataset shows a larger solar-cycle variability contribution to TSI than in CMIP5 (50 % compared to 35 %). We compare the climatic effects of the CMIP6 solar forcing dataset to its CMIP5 predecessor by using time-slice experiments of two chemistry–climate models and a reference radiative transfer model. The differences in the long-term mean SSI in the CMIP6 dataset, compared to CMIP5, impact on climatological stratospheric conditions (lower shortwave heating rates of −0.35 K day−1 at the stratopause), cooler stratospheric temperatures (−1.5 K in the upper stratosphere), lower ozone abundances in the lower stratosphere (−3 %), and higher ozone abundances (+1.5 % in the upper stratosphere and lower mesosphere). Between the maximum and minimum phases of the 11-year solar cycle, there is an increase in shortwave heating rates (+0.2 K day−1 at the stratopause), temperatures ( ∼  1 K at the stratopause), and ozone (+2.5 % in the upper stratosphere) in the tropical upper stratosphere using the CMIP6 forcing dataset. This solar-cycle response is slightly larger, but not statistically significantly different from that for the CMIP5 forcing dataset. CMIP6 models with a well-resolved shortwave radiation scheme are encouraged to prescribe SSI changes and include solar-induced stratospheric ozone variations, in order to better represent solar climate variability compared to models that only prescribe TSI and/or exclude the solar-ozone response. We show that monthly-mean solar-induced ozone variations are implicitly included in the SPARC/CCMI CMIP6 Ozone Database for historical simulations, which is derived from transient chemistry–climate model simulations and has been developed for climate models that do not calculate ozone interactively. CMIP6 models without chemistry that perform a preindustrial control simulation with time-varying solar forcing will need to use a modified version of the SPARC/CCMI Ozone Database that includes solar variability. CMIP6 models with interactive chemistry are also encouraged to use the particle forcing datasets, which will allow the potential long-term effects of particles to be addressed for the first time. The consideration of particle forcing has been shown to significantly improve the representation of reactive nitrogen and ozone variability in the polar middle atmosphere, eventually resulting in further improvements in the representation of solar climate variability in global models.

Description: A German national project coordinates research on improving a global decadal climate prediction system for future operational use. MiKlip, an eight-year German national research project on decadal climate prediction, is organized around a global prediction system comprising the climate model MPI-ESM together with an initialization procedure and a model evaluation system. This paper summarizes the lessons learned from MiKlip so far; some are purely scientific, others concern strategies and structures of research that targets future operational use. Three prediction-system generations have been constructed, characterized by alternative initialization strategies; the later generations show a marked improvement in hindcast skill for surface temperature. Hindcast skill is also identified for multi-year-mean European summer surface temperatures, extra-tropical cyclone tracks, the Quasi-Biennial Oscillation, and ocean carbon uptake, among others. Regionalization maintains or slightly enhances the skill in European surface temperature inherited from the global model and also displays hindcast skill for wind-energy output. A new volcano code package permits rapid modification of the predictions in response to a future eruption. MiKlip has demonstrated the efficacy of subjecting a single global prediction system to a major research effort. The benefits of this strategy include the rapid cycling through the prediction-system generations, the development of a sophisticated evaluation package usable by all MiKlip researchers, and regional applications of the global predictions. Open research questions include the optimal balance between model resolution and ensemble size, the appropriate method for constructing a prediction ensemble, and the decision between full-field and anomaly initialization. Operational use of the MiKlip system is targeted for the end of the current decade, with a recommended generational cycle of two to three years.