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Understanding the impact of urban environments on the local climate has been a crucial topic in recent years. Changes in the cities structure are expected due to the ongoing urbanization trends and climate-aware mitigation planning. These policy implementations are expected to affect the local urban surface and its interaction with the climate system. Here, we are interested in investigating these impacts coupled to a heatwave condition, due to its adverse impact on human health. In the presented work, we investigate the multi-model response to different urbanization and urban greening scenarios. We employ two NWP models at the 2.1 km convection-permitting resolution: ICON-LAM (ICOsahedral Nonhydrostatic Model in Limited Area Mode) and WRF-ARW (Weather Research and Forecasting Model). Our one-month experiments comprise the 2019 ``record-breaking'' heatwave in Western Europe and they are all a downscaling of ICON-EU (6.5km resolution). The urban policy scenarios are built from the CORINE land use dataset and they include two urbanization and two urban greening settings, for each model. Urbanization is represented as a sprawl of the main urban areas within the domain towards the natural surrounding areas. To increase the urban green fraction within the main cities, we increase the number of green areas within each city. Our analysis shows the multi-model comparison of the effects of the mentioned urban policies on the urban heat island (UHI) under heatwave conditions. Further, we quantify the effects of urban greening as an efficient tool to mitigate expected climate impacts in terms of the Discomfort Index, and not just for the UHI.Further, we evaluate the similarities and dissimilarities between the two models in terms of multiple correlation decomposition accordingly to Glowienka-Hense et al. 2020.

The decadal hindcast simulations performed for the Mittelfristige Klimaprognosen (MiKlip) project are evaluated using satellite-retrieved cloud parameters from the CM SAF cLoud, Albedo and RAdiation dataset from AVHRR data (CLARA-A1) provided by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) and from the International Satellite Cloud Climatology Project (ISCCP). The forecast quality of two sets of hindcasts, Baseline-1-LR and Baseline-0, which use differing initialisations, is assessed. Basic evaluation focuses on multi-year ensemble mean fields and cloud-type histograms utilizing satellite simulator output. Additionally, ensemble evaluation employing analysis of variance (ANOVA), analysis rank histograms (ARH) and a deterministic correlation score is performed. Satellite simulator output is available for a subset of the full hindcast ensembles only. Therefore, the raw model cloud cover is complementary used. The new Baseline-1-LR hindcasts are closer to satellite data with respect to the simulated tropical/subtropical mean cloud cover pattern than the reference hindcasts (Baseline-0) emphasizing improvements of the new MiKlip initialisation procedure. A slightly overestimated occurrence rate of optically thick cloud-types is analysed for different experiments including hindcasts and simulations using realistic sea surface boundaries according to the Atmospheric Model Intercomparison Project (AMIP). By contrast, the evaluation of cirrus and cirrostratus clouds is complicated by observational based uncertainties. Time series of the 3-year mean total cloud cover averaged over the tropical warm pool (TWP) region show some correlation with the CLARA-A1 cloud fractional cover. Moreover, ensemble evaluation of the Baseline-1-LR hindcasts reveals potential predictability of the 2–5 lead year averaged total cloud cover for a large part of this region when regarding the full observational period. However, the hindcasts show only moderate positive correlations with the CLARA-A1 satellite retrieval for the TWP region which are hardly statistical significant. Evidence for predictability of the 2–5 lead year averaged total cloud cover is found for parts of the equatorial to mid-latitudinal North Atlantic.

Decadal climate predictions and their verification are part of ongoing research. This article studies different methods applied to decadal hindcasts of three-dimensional atmospheric variables to evaluate the MiKlip (Mittelfristige Klimaprognosen) prediction system. Variables such as upper air temperature are tight to the core of the prediction system and hence help to reveal its power and deficiencies. The verification uses both, necessary and sufficient probabilistic measures. We analyze annual and multi-year averages of air temperature and geopotential height and the parametrized quantity net water flux at the ocean surface, the so-called freshwater flux, also known as E‑P (evaporation minus precipitation), as an important variable for atmosphere-ocean coupling. The model data stem from various versions of the MiKlip prediction system and constitute different sets of ensemble hindcasts covering 1979–2012. The results reveal that the freshwater flux is far more sensitive to model deficiencies than the basic dynamical variables and the predictability decays much earlier with prediction lead time. Initializing the atmospheric component is more important for the predictability than the difference in resolution between two model versions. The combined initialization of atmosphere and ocean has the effect of increasing the predictability in the inner tropics from 1 to 2 years compared to the ocean only initialization. For prediction year 7–10, the hindcasts are still closer to each other than to the uninitialized historical runs indicating that the prediction system is still influenced by the initial conditions. The skill for prediction year 7–10 is, however, only marginally larger than the skill of the uninitialized ensemble. The three-dimensional skill analysis reveals a clear indication of a mid-tropospheric temperature error developing in the tropical Pacific area.

A framework of ensemble forecast verification tools is discussed which is founded on the concept of information entropy. It can be based on a common yardstick namely that of "correlation". With these measures calibration is deduced from the balance between ensemble sharpness and resolution. With the same units these features can be put into one diagram for continuous time series from Gaussian processes and exceedance probabilities, the latter usually tested with the reliability term from the Brier score. The sharpness and resolution terms allow to use the same vocabulary of over- and underdispersion which is established for frequency histograms. The concept is based on the fact that mutual information (MI) of two Gaussian processes is directly related to Pearson's anomaly correlation. Further MI can be written as the Kullback-Leibler divergence of the conditional probability of observations given the model forecasts and the unconditioned observations. Thus the MI is a measure of resolution. The mean of the UTILITY defined by (Kleeman, 2002) is the corresponding measure of sharpness. For Gaussian processes the mean UTILITY is very close to the ratio of ensemble mean variance to mean ensemble variance (ANOVA) which is the analysis of variance factor when time is taken as treatment. The ensemble spread score (ESS) (Palmer et al., 2006) is shown to be a measure of calibration if model and observed data are scaled with their respective means and standard deviations. For exceedance probabilities the resolution term of the divergence score (Weijs et al., 2010) is already defined as a MI term and it is here complemented with a mean UTILITY formed similarly to the resolution term but with forecasts only. The entropy terms are then rescaled to the "correlation" yardstick. The concept is applied to temperature data from the German project on decadal climate prediction, Mittelfristige Klimaprognose (MiKlip). It is shown that both over – and underdispersion can be found for the 2m temperature forecasts. Increasing ensemble sharpness of surface ocean temperature with lead year in the southern ocean hints at model-data inconsistencies at some locations in the ocean. Finally empirical orthogonal functions (EOF) of northern hemisphere annual mean surface temperature for ERA-40/ERA-Interim and MiKlip retrospective hindcasts are determined. For both data sets the respective first EOF represents the low frequency temperature development. The time coefficients of the EOF are used to compare resolution and sharpness of continuous data and exceedance probabilities in one diagram.

We present a method to quality control and analyse a series of phenological observations and, from there, construct a spatial map for a given phenological stage or phase. In this case, data for full bloom of apple, stemming from a volunteer network managed by the German Weather Service, were used as an example. The data span the period from 1951 to 1997 and cover an area of around 14,000 km 2 in western Germany. First, the method itself is presented. It includes quality control of raw data, construction of a field for the mean date over all years of a given phenological stage and construction of the respective anomaly fields for each year. Then, the determination of a statistically correct spatial resolution of the final field is presented, which in this case is around 10–15 km. The final analysis of the time mean field and the respective anomaly fields indicates a possible way to extract all relevant climate factors determining phenological events overcoming the problems of a standard site-specific adaptation of a model.

The time-dependent variability of the North Atlantic Oscillation is examined in an observational data set and several model data sets with greenhouse-gas-induced external forcings. The index of the North Atlantic Oscillation state is derived from the time series of mean latitudinal position and central pressure of the Icelandic Low and the Azores High considering the synchronous meridional shifting of the two pressure systems. While the North Atlantic Oscillation is characterized by intensive interannual variability, the low-pass filtered index time series shows a decadal component with a time scale of about 50 y within almost 120 y of observation. Since the late 1960s we observe a positive trend and a transition to a strong positive phase of the phenomenon indicative of a pre-dominantly zonal circulation over the North Atlantic. This trend occurs equally in the observations and all examined model data sets with increasing greenhouse-gas-concentration and atmosphere-ocean coupling. We find statistical evidence that the radiative forcing by increasing CO2 concentration has a significant influence on the simulated variability of the North Atlantic Oscillation on time scales of 60 y and longer, independent of the initial conditions and the model version. The seasonal response is strongest in late summer and winter. The interannual variability of the North Atlantic Oscillation states on time scales less than 10 y decreases synchronously with the positive trend of its decadal-mean state implying a stabilization of its present and future zonal state.

The semi-annual oscillation (SAO) of the southern hemispheric sea-level pressure (SLP) in the global atmospheric GCM ECHAM is examined. Five model runs initiated from different atmospheric states were conducted. Monthly values of sea surface temperature (SST) and sea-ice distribution for the period 1950–1994 are specified boundary conditions for each run. The interdecadal change of the SAO as forced by the changing boundary conditions is compared to the internal model variability, represented by the five runs. The performance of the SAO in the ECHAM model is much improved compared to that of its precursor the T21 Hamburg version of the ECMWF model in 1990. Analysis of observed SLP shows that between 1973–1979 the SAO had high amplitude whereas from 1980–89 its amplitude was low. These changes go along with significant changes in SLP, i.e. the subpolar trough does not expand as far equatorward from September to December as in the years before. The model does not show this reduction of SAO strength in recent years. Multivariate Hotelling-T2 statistic and analysis of variance techniques (ANOVA) are used to determine the boundary forced part of variance of SLP and SAO in the ECHAM simulations. The result is that only a small part of the SAO seems to be externally forced mainly from the tropics.

The feedback of an arctic polynya, which is a large ice-free zone within the sea ice, on the hemispheric climate is studied with the ECMWF T21 GCM. For this purpose a control and an anomaly integration, in which a polynya was introduced in the Kara Sea, are compared. As the GCM, like the real atmosphere, shows a high level of low frequency variability, the mean response to the changed boundary conditions is obscured by internal noise. The necessary significance analyses are thus performed to enhance the signal-tonoise ratio within the framework of an a priori chosen guess pattern and a multivariate test statistic. The sensible and latent heat fluxes increased above the polynya, which resulted in a warming of the lower troposphere above and near the polynya. No statistically significant local or global sea-level pressure changes are associated with this heating. However we find a significant change of hemispheric extent of the geopotential fields at 300 hPa, if we use as guess patterns the eigenmodes of the barotropic vorticity equation. The different mean flow field is accompanied by significant changes of the synoptic transient eddy field. We find a significant variation in the barotropic and baroclinic forcing of the mean flow by the eddies, a change in the location and intensity of the storm tracks and in the conversion between eddy available and eddy kinetic energy. The additional heat flux from the polynya results in a reduction of the meridional heat flux by the synoptic eddies on the western Atlantic.

A time series of wind stresses computed from European Centre for Medium Range Weather Forecast (ECMWF) wind data is compared to the climatology of Hellermann & Rosenstein (HR) for the Southern Hemisphere. ECMWF stresses are generally stronger, especially in the westerly belt. However they have an overall lower meridional component than the HR data. The dominance of the half annual cycle relative to the annual wave in the zonal stress at middle to high latitudes, which is documented for independent data sets, is seen in the ECMWF but not in the HR data. ECMWF winds are also compared with measurements from three expeditions to the Weddell Sea by RV Polarstern. Good correlations between Polarstern and ECMWF winds are found but for single dates the differences are above 10 ms −1. The differences are found to be uncorrelated in space and are thus due to observational errors and to the unresolved small scale variance in the ECMWF analysed winds.

Analyses indicate that the Atlantic Ocean SST was considerably colder at the beginning than in the middle of the century. Parallel to this a systematic change of the North Atlantic SLP pattern was observed. To find out whether the analyzed SST and SLP changes are consistent, which would indicate that the SST change was real and not an instrumental artifact, a response experiment with a low resolution (T21) atmospheric GCM was performed. Two perpetual January simulations were conducted which differ solely in Atlantic Ocean (40$ - 60N) SST: the ”cold” simulation utilizes the SSTs for the period 1904-13, the ”warm” simulation uses the SST’s for the period 1951—60. Also a ”control” run, with the model’s standard SST somewhat between the ”cold” and ”warm” SST, was made. For the response analysis a rigorous statistical approach was taken: First the null hypothesis of identical horizontal distributions was subjected to a multivariate significance test. Second, the level of recurrence was estimated. The multivariate statistical approaches are based on hierarchies of test models. We examined three different hierarchies: a scale dependent hierarchy based on spherical harmonics (S), and two physically motivated ones, one based on the barotropic normal modes of the mean 300 hPa flow (B) and one based on the eigenmodes of the advection diffusion operator at 1000 hPa (A). The intercomparison of the ”cold” and ”warm” experiments indicates a signal in the geostrophic stream function that is in the S-hierarchy significantly nonzero and highly recurrent. In the A—hierarchy, the low level temperature field is identi— fied as being significantly and recurrently affected by the altered SST distribution. The SLP signal is reasonably similar to the observed SLP change. Unexpectedly the upper level streamfunction signal does not appear significantly nonzero in the B—hierarchy. If, however the pairs of experiments ”warm vs. control” and ”cold vs. control” are examined in the B—hierarchy, a highly significant and recurrent signal emerges. We conclude that the ”cold vs. warm” response is not a ”small disturbance” which would allow the signal to be described by eigenmodes of the linearized system. An analysis of the three—dimensional structure of the signal leads to the hy— pothesis that two different mechanisms are acting to modify the model’s mean state. At low levels, the local heating and advection are dominant, but at upper levels the extratropical signal is a remote response to modifications of the tropical convection.

An analysis of the signature of the North Atlantic Oscillation (NAO) in the Atlantic-European sea level pressure (SLP) is presented for observed (German Weather Service) and ECMWF T21 model data. The former time series consists of 1881–1984 January to December fields and the latter of 42 monthly fields from 3 permanent January simulations. The NAO is shown to be one of the dominant eigenmodes of SLP for all calendar months. A very similar NAO anomaly pattern is filtered from the T21 model data, whereby the correspondence between model and reality is far better than for the mean states. Typical extreme states of the NAO, i.e. high- and low-index situations are reconstructed from the EOF (empirical orthogonal functions) and the mean fields. The annual cycle of these states and the differences between observed and simulated January extremes of the NAO are discussed. DOI: 10.1034/j.1600-0870.1990.t01-3-00001.x