Microscale Reynold Averaged Navier Stockes (RANS) models, while providing high-resolution urban climate simulations, are computationally demanding. This restricts their use for comparing and assessing the impact of urban planning scenarios from a climatological perspective. To overcome this limitation and support the development of climatologically resilient cities, we trained a neural network on a comprehensive dataset of RANS model outputs from numerous cities in Germany and Switzerland, enabling it to learn the complex relationships between urban morphology and microclimate. The GIS-based "Klimascanner" delivers rapid and accurate predictions of key urban climate parameters, like temperature and wind speed, and ensures immediate assessment of urban planning impacts. Validated and reliable, its user-friendly interface makes it accessible to planners and decision-makers, facilitating informed urban climate mitigation strategies.
The correct model-based estimation of evaporation rates form water surfaces is crucial for an efficient water management of reservoirs and other water storages as well as for a successful implementation of flooding projects former opencast mines, and a sustainable and economical operation of aquacultures. This study aims to model the daily evaporation and the diurnal course of evaporation rates from extensive open water surfaces and to compare and evaluate these model estimates using measured values from a floating evaporation pan and eddy covariance (EC) measurements. In par-ticular, the reasons for the unavoidable differences between the model and measurement results, but also between the two comparative measurements methods used for the evaluation, are discussed and quantitatively assessed. Over the decades, various modelling approaches have been developed and proposed to estimate evaporation from water surfaces of different sizes (ranging from 1 m(2) to 106 m(2)). These methods include the DALTON, BULK, PENMAN, and ENERGY BALANCE approaches, each focusing on daily evaporation values. In this work, we use experimental data to compare these modelling approaches and evaluate with respect to their effectiveness in representing the daily course of evaporation and capturing the underlying physical processes. Our comparison of the DALTON and BULK approaches led to the development of a wind speed (u(2))-dependent DALTON number, C-E, which can be integrated into the BULK method to better model the daily evaporation cycle. The proposed formulation for C-E is: C-E,C-2=(0.0011 m s(-1)/u(2) +0.0014) Additionally, we discuss the variability of C-E with respect to the size of the water body. Our comparison between modelling and measurement results, but also between the EC data and the data of the direct evaporation measurements from a floating evaporation pan, revealed significant discrepancies. Specifically, evaporation estimates using the direct measurements can be up to 100% higher than those obtained from EC-measurements. These discrepancies cannot be attributed entirely to the well-known phenomenon of the energy-balance-closure gap, which is typically for EC measurements but is also very significantly and substantially caused by methodological limitations of the measurements using evaporation pans. Considering that floating evaporation pans have served as a reference for estimat-ing water evaporation for decades, this methodological problem is not limited to our study, but also affects the modelling methods used to estimate open water evaporation in general.
This paper for the first time documents the wakes associated with Yakushima island of Japan in a super typhoon based on synthetic aperture radar (SAR) ocean surface winds, and explores the feasibility of simulating the major features of the wakes using higher spatial resolution numerical weather prediction model for comparison with the actual SAR observation. Three images during Super Typhoon Shanshan (2024) are considered. The model simulations are found to reproduce reasonably well the main features of the wakes. They capture much finer details, such as wakes associated with individual mountains of the island, and the waves in the wakes, which are not apparent in the SAR images. On the other hand, SAR images indicate recirculation in the edges of the island, though not very apparent, while the suspected recirculation does not show up in the numerical simulation. The quantitative comparison reveals some discrepancies, particularly in the wake region, where the model predicts low wind speeds that are not seen in the SAR data. These findings emphasize the necessity for enhanced observational and modeling techniques to improve the accuracy of wind field evaluation over complex terrain during tropical cyclones.
Winter wheat, the primary grain grown in Switzerland plays a crucial role for domestic food security. It is typically harvested in July and early August, roughly coinciding with the peak of the hail season. Recent global warming has led to earlier harvest dates, thus shortening the time window during which wheat is potentially exposed to hail. At the same time, the frequency of hailstorms in Switzerland has increased. In view of these two opposing trends, the question arises as to whether the risk of hail damage to wheat has decreased or increased over the past few decades. To address this question and evaluate the relative importance of the two trends, we combined wheat phenology simulated with the World Food Studies (WOFOST) model with a reconstruction of the seasonal distribution of hail days over the periods 1972-1991 and 2002-2021. We find that across Switzerland, harvest dates advanced by an average of 13.4 days between 1972-1991 and 2002-2021, while the mean number of hail days during wheat's growing season increased from 0.79 to 1.12. Thus, while early harvests have potentially reduced hail risk by 13%, the significant 55% increase in hail frequency has offset this benefit, resulting in a net 42% increase in hail risk. It is beyond doubt that efforts are needed to enhance the agricultural sector's resilience against increasing hail damage risks. Our findings emphasize the importance of quantitative assessments that combine the development of hail scenarios, on the one hand, and crop growth modeling, on the other.
In November 2024, four tropical cyclones (TCs) developed consecutively over the South China Sea and the western North Pacific. This is the first time that the simultaneous occurrence of four TCs was documented in this ocean basin. The climatological background for this phenomenon was analysed in this paper. The observational aspects of the three TCs affecting Hong Kong have been analysed using dropsonde data, weather buoy observations (particularly change in sea temperatures in the upper ocean), and radar imageries (in the region of gale force winds around Hong Kong). The forecasting aspects of the TCs are also discussed. In particular, the performance of artificial intelligence models in forecasting TC tracks and intensities has been reviewed. The first time real-time, operational use of an atmosphere-wave-ocean coupled model was discussed. The significant wave height forecasts during the passage of the three TCs over the South China Sea was also analysed using the Operational Marine Forecasting System of the Hong Kong Observatory (HKO) in comparison with the weather buoy observations of this basin. This paper serves to document the climatological, observational and forecasting aspects of this unprecedented case of simultaneous occurrence of four TCs in the fall season over the South China Sea and western North Pacific for future reference.
A detailed statistical analysis of tornadoes in Germany is performed based on the European Severe Weather Database using all available quality controlled tornado reports, with a focus on the period 2000-2024. Statistical analyses raise a general awareness of the possibility of tornadoes, which are an underestimated threat in Europe. Most of the tornadoes occur between May and September with a maximum in August, mainly due to a distinct maximum of waterspouts. Significant tornadoes (F2+) have their maximum in late spring to early summer. The majority of all tornadoes occurs in the afternoon and evening, while waterspouts mainly occur in the morning. Tornadoes occur everywhere in Germany; the population density influences the spatial distribution of tornado reports. Furthermore, local hotspots, which are best visible for significant tornadoes, are induced by local topography. Given the inhomogeneities of the time series, and based on the available data, a statement on an underlying climatological trend cannot be made.
The Asian summer monsoon anticyclone is a dominant circulation system in the upper troposphere and lower stratosphere (UTLS) in boreal summer (about June–September). An appropriate simulation of the monsoon anticyclone is an important challenge for chemistry climate and chemistry transport models. Here we compare simulations of the ECHAM5/MESSy Chemistry Climate model (EMAC) and the Chemical Lagrangian Model of the Stratosphere (CLaMS) based on the European Centre for Medium-Range Weather Forecasts Reanalysis-Interim (ERA-Interim); EMAC simulations are nudged towards ERA-Interim, whereas transport in CLaMS is driven by ERA-Interim. We employ surface origin tracers for continental South Asia. These surface origin tracers are lifted upward into the Asian summer monsoon anticyclone, both in EMAC and CLaMS. We investigate monsoon conditions for boreal summer 2015. In summer 2015, the entire monsoon, and in particular upward transport in the monsoon anticyclone, was strongly influenced by El Niño. In both models, in 2015, the simulated impact of surface origin tracers on the composition of air in the Asian summer monsoon anticyclone is very weak at 420 K. Further, in both models, a very strong decline with altitude (between ≈ 370–400 K) of surface origin tracers is obvious. The pattern of the Asian monsoon anticyclone in August and early September is represented very similarly in EMAC and CLaMS, with a lower fraction of the surface origin tracer for continental South Asia in CLaMS. The simulated pattern of surface origin tracers in the Asian summer monsoon anticyclone in CLaMS is much less smooth than in EMAC. Finally, we find a strong day-to-day variability in the Asian summer monsoon anticyclone and a confinement of monsoon air at UTLS altitudes (≈370 K to 400 K) similarly in both, EMAC and CLaMS.
The effects of climate change on a German low mountain range are examined using the example of the Fichtel Mountains. The increase in annual mean air temperature corresponds to that measured at lower-lying stations in the surrounding area, which is 0.5 K per decade. There are hardly any changes in annual precipitation. The increase in winter temperatures is delayed, so that snow cover can still form at times at altitudes above 500 m. However, the number of days with snow cover is decreasing significantly with 12 days per decade, and periods with continuous snow cover are becoming shorter and shorter. Snow is only guaranteed above 900-1000 m a.s.l. This has serious consequences for winter sports. All details are comprehensively documented by homogenized data from meteorological measuring stations in the region from 1950 to 2024.
Worldwide, researchers and urban planners are looking for innovative approaches to mitigate the increasing heat stress and thus the UHI effect in growing cities. Urban trees, with their various positive ecosystem services are an essential part of green infrastructure. Especially during the daytime, trees increase the thermal comfort on hot, sunny summer days by significantly reducing the perceived temperature, particularly due to their shading effect (Ziemann et al. 2024). Therefore, the planting of additional trees is considered a suitable measure to implement climate adaptation strategies in cities. However, during summer nights, cities in valley locations are mainly cooled by the nocturnal cold air drainage flows from the surrounding rural areas. Placing trees in unfavorable locations can prevent the cold air flows and thus hinder the urban cooling in city centers. Hence, the plantation of urban trees needs to be planned carefully. For this reason, model simulations with the cold air drainage model KLAM_21 developed by the German Weather Service, DWD (Sievers 2005) were performed for the city of Plauen, which is located in a low mountain range region in Germany. The objective of this work was to analyze the effects of additional urban trees distributed throughout the city (maximum scenario) on the cold air flows and thus on the nocturnal ventilation compared to the current situation. In addition, the results of the simulations are evaluated in terms of the advantages and disadvantages of planting trees in cold air corridors. In general, the results showed that the implementation of the maximum amount of urban trees throughout the city can lead to a moderate or locally intense negative change in the ventilation potential along the main cold air corridor. Therefore, it is recommended to keep the exposed cold air corridors open and to carefully manage the tree planting in such critical areas. On the positive side, the valley of Weisse Elster remains in a very high to extremely high climatic-ecological compensation potential even in the maximum scenario.
The first European Nowcasting and Weather Forecasting Conference (ENWFC-2024) dedicated to nowcasting, seamless forecasting, statistical postprocessing and ensemble prediction took place in Oslo, Norway (Oslo Science Park) from 4 to 8 November 2024, organized by EUMETNET (European National Meteorological and Hydrological Services Network) within the Weather Forecasting Cooperation Programme (E-WFC). More than 70 participants attended the conference in person; and ca. 100 more were joining via livestream. 67 conference's presentations (45 oral and 22 posters) were given. The sections in this conference report summarize key topics and discussions of the ENWFC-2024 within: Innovations in satellite and radar technology, early warnings, and crowdsourced data; Advancements in statistical and AI-based weather forecasting; Verification and societal impacts; and Applications. A particular focus was provided to the use of Machine Learning techniques and their applications in the context of the listed key topics.
Climate normal periods are frequently used to describe the average atmospheric conditions at a specific location and allow the investigation of climate change by comparing different 30-year periods. To investigate the climatic conditions in Austria, climate indices based on different parameters were calculated for the two consecutive 30-year periods 1961-1990 and 1991-2020. The data used for the temperature-and precipitation-based climate indices was homogenised with the ACMANT method considering data of both 30-year periods. Comparisons between homogenised and non-homogenised data showed more consistent temporal trends for homogenised data. The evaluation of the two climate normal periods showed that the mean air temperature increased between 1.1 and 1.8 degrees C. This increase also caused, on average, an increase in warm conditions (e.g. hot days) anda decrease in cold conditions (e.g. frost days). The precipitation sum increased at 48 out of 50 analysed stations. While days with a daily precipitation sum > 1 mm decreased, days with a daily precipitation sum > 10 mm increased. This behaviour indicates an increase in more intense precipitation events. The spatial analysis of the climate indices for the period 1991-2020 confirmed the altitude dependence of several climate indices. This result was supported by the comparison with data from neighbouring countries. Overall, for the climate indices clear changes with time and robust spatial patterns were found. The available dataset and its analysis provide reliable information for the climate monitoring in Austria.
A simple theory is developed to measure the utility of the avoidance of single contrails out of a larger ensemble of contrails. The utility is defined here as the mitigated contrail climate effect resulting from contrail avoidance. Side effects of increasing fuel consumption and corresponding emissions are considered in the form of a separate cost function. The model is simple and its results are qualitative only. This is sufficient for the desired insight into and illustration of the principles. A quantitative treatment would need the application of a detailed numerical model that takes the complete air traffic in a certain region and time into account; this is beyond the current purpose. The utility function is expressed as a function of the fraction of the avoided contrails in a given area at a certain time relative to all contrails present. It is a more or less non-linearly increasing function. The non-linearity is weak if the total contrail cover is low, but there is strong non-linearity in cases with high contrail coverage. In a given synoptic situation, the maximum achievable utility increases with total contrail coverage: low/high contrail coverage implies small/large achievable utility (climate benefit). The strong non-linearity in the high coverage case implies that most of the contrails must be avoided to achieve high utility. If only single or a few contrails are avoided in such a situation, the utility is low and it may well be smaller than the corresponding climate cost. The main result is that in order to estimate the climate benefit of avoiding single contrails it is necessary to consider the whole traffic situation with all other contrail-producing aircraft. Otherwise, gross errors result. For eco-efficient contrailavoiding strategic flight-planning it is required as well to consider in advance all the other flights in the same region that might produce contrails.
Terrain-induced windshear and turbulence are known to be serious threats to airplanes during takeoff and landing. However, it is less known that low-level windshear and turbulence induced by buildings/manmade structures situated near the airport runway may also be an important danger under fair weather conditions. To elucidate the structure and physics of microscale anticyclones observed at the Hong Kong International Airport (HKIA) and their impact on aviation safety, an investigation using a multiscale modelling framework by coupling large eddy simulation with mesoscale model is carried out under realistic weather conditions with tiny anticyclic vortices being observed. After validation with field observations, the multiscale model (MM) successfully predicts the microscale anticyclones generated from both the Passenger Terminal Building (PTB) and the AsiaWorld-Expo (AWE) located at HKIA. It is found that the microscale anticyclones from the east side of the PTB and the west side of the AWE interact with a flight glide path, causing low-level windshear and turbulence and posing potential aviation risks. By simulating another scenario without the AWE, it is revealed that the microscale anticyclones interacting with the flight glide path are significantly reduced, confirming that the increase in microscale anticyclone events is closely related to the presence of the AWE. Furthermore, the simulation without the PTB indicates a further reduction of the tiny anticyclonic vortices near the AWE and under the prevailing southwesterly flows; the interaction between the wakes of the PTB and the downstream AWE is likely to contribute to the generation of these microscale anticyclones. Our study adds evidence that the tiny anticyclonic vortices are a result of the interaction between the southwesterly background flows and major buildings (i.e., the PTB and AWE) at HKIA; this understanding could help enhance sustainability and resilience of the airport and meet the city's growing demand for safe aviation services.
This study investigates the spatiotemporal distribution of potential temperature (theta) hot-and coldspots in an urban environment for one day in a summerly heat wave, as reflected by a large eddy simulation (LES) model as well as reproduced by a multiple linear regression (MLR) model based on an observation network. The spatial variation of static surface characteristics only partly explains the observed patterns for both approaches. The question of which additional factors, mainly those related to atmospheric circulation, are essential for the development of theta hot-and coldspots is addressed. For this purpose, real case simulations with the LES model PALM-4U were conducted for the city of Augsburg, Southern Germany. Hot-and coldspots were detected in the modelled theta fields with the Gi* statistic. The theta and Gi* patterns were compared to the results of the MLR model, using only static surface characteristics for the referring daytime, season and weather type as predictors. For some times of the day, the patterns from the two approaches show good agree-ment, but there are considerable differences for other situations, although the weather type does not change over the studied period. In a next step, the detected hotspots are classified into expected and unexpected hotspots according to their surface characteristics, and differences in the meteorological variables for both groups are investigated. A similar procedure is applied to areas apart from hotspots, which could be expected to be hotspots, and those which are not expected to be one. The results indicate that even in summerly anticyclonic conditions with low wind speeds, horizontal circulation and vertical mixing play a significant role in manifesting urban theta patterns. It is concluded that more than a single simulation may be required to represent typical urban temperature patterns during heat waves since they cannot reflect the critical influence of varying circulation dynamics at different synoptic conditions. This should be considered in urban planning.
In this paper, a validation of the torus mapping dealiasing method for observations of Doppler velocities by meteorological radars is presented for the purpose of using dealiased data in data assimilation for operational numerical weather prediction. Analysis was done on a large sample of Doppler velocity data from German and Slovenian radar networks preprocessed by the Operational Program for Exchange of Weather Radar Information. The quality of dealiased data is assessed by a comparison to collocated radiosonde and aircraft observations and also through analysis of differences between observations and corresponding values from a regional numerical weather prediction model. Performance of model's quality control on dealiased data is also evaluated. We show that the torus mapping method is a robust procedure where it produces radar datasets of comparable quality to aircraft and radiosonde data and has potential for operational applications in data assimilation.
Contrail avoidance by operational means is often considered a quick and easy way to mitigate the climate impacts of aviation. However, several studies in the past assumed that the necessary weather forecasts were perfect. This is, of course, not true, and the question arises how imperfect weather forecasts impact contrail avoidance measures. Imperfections have several origins, but the most important one is the non-linear character of atmospheric dynamics, which renders forecasts of ice supersaturation as well as many other atmospheric features like rain and fronts difficult: In general, predicted features are not located where they are observed and they appear earlier or later than predicted. We demonstrate this for two versions of a weather forecast model (World Aviation Weather FORecast (WAWFOR), produced by the global numerical weather prediction model ICON, Icosahedral Nonhydrostatic) equipped with two kinds of ice cloud microphysics, a one-moment and a two-moment scheme. The results are similar, which clearly shows that good treatment of microphysics is not a sufficient condition for successful contrail forecasts. For contrail avoidance, the imperfection leads to false alarms and misses which spoils the avoidance measures and diminishes the desired climate benefit. Whether the currently achievable benefit is sufficient is a question beyond the scope of the present study. But the situation can obviously be improved. To this end, it would be necessary to keep the forecast of ice supersaturation always close to measured reality. This implies the necessity of humidity measurements in the upper troposphere for data assimilation, which are currently rare. Potential data sources would be modern high-quality radiosondes and humidity measurements from passenger and cargo aircraft.
An efficient method to simulate time series of wind speed and wind turbine electricity generation on a microscale grid resolution is described. Speed-up factors are simulated by the microscale model Meteodyn for 12 wind direction sectors and 10 stability classes. The speed-up factors on the microscale grid are combined with wind speed time series simulated with the mesoscale model WRF (Weather Research & Forecasting Model) resulting in long-term wind speed time series on the microscale grid. Thermal effects are considered by translating the near-surface Monin-Obukhov-Length L which is a WRF output parameter into the stability classes defined by the CFD model Meteodyn.Wind simulations are compared to LiDAR (Light Detection and Ranging) measurements at two sites during a summer and winter period showing an under- and overestimation, respectively. The vertical wind shear and the temporal variability are reasonably well simulated. The bias differs for the summer and winter period and depends on the meso-cell option selected for the microscale model forcing. The effect of this “representativeness error” is shown by comparing the vertical wind profile simulated with different mesoscale grid cell forcings.The particular winter and summer case used here as an example show a different behavior. In summer wind speed is underestimated which results in an electricity production close to the one recorded by a nearby wind farm. The winter case for a different site shows an overestimation of the wind speed which would lead to unrealistic production data. Therefore, we correct for this bias by scaling the modelled wind speed at hub height to match on-site measurements by a LiDAR device. This correction will make the simulated electricity production comparable to the actual production which is deduced from an analysis of SCADA (Supervisory Control and Data Acquisition) data. No correction was necessary for the summer period. A site-specific correction factor will be essential for a realistic estimate of the wind turbine electricity production with an uncertainty as low as required for financial investments. On-site measurements and an adequate site-specific scaling of the simulated wind conditions will form the basis for reasonable site assessments.
The Eye2Sky network is a measurement network in north-western Germany consisting of 29 all-sky imagers (ASI) and 12 meteorological and solar irradiance measurement stations. Since 2018, the network collects high temporal and spatial resolution data for meteorological and especially solar energy related applications. Quality control schemes have been developed for the different sensors and are applied on the data in order to ensure a high quality. Quality controlled minute-resolution measurements (1 year) and ASI images (4 months) in the year 2022 are published for open access. Eye2Sky data is used in the development of new technologies and methodologies for accurate solar irradiance forecasts, facing the demand for grid integration of high shares of photovoltaic-generated power. The ASIs used in Eye2Sky record 180 degrees field of view hemispherical sky images from fish-eye lensed cameras. Accompanied with local point measurements of solar irradiance components (global, direct and diffuse) a very short-term forecast of the solar resource is possible. A single ASI can provide such so-called nowcasts as minutely updated information. Nowcasts with a temporal resolution in the intra-minute range and a spatial resolution of a few meters are possible. Depending on the prevailing cloud dynamics the spatial coverage can be several kilometers and the maximum forecast horizon varies in the intra-hour range. The used ASI based approach shows superior forecasting results for the next minutes ahead compared to single ASI systems and traditional methods based on lower resolved satellite images or numerical weather prediction models. Eye2Sky, a unique network with multiple ASIs in a regional domain (about 110 km x 100 km coverage), enables an increased spatial coverage and an extended forecast horizon requested by many applications. In this article, the Eye2Sky network, its data and the quality control procedures are described. The potential of the network for solar energy applications and research topics is introduced.
Scenarios of energy transition in Germany project large wind capacity deployment in the German Bight by 2050. They use models that estimate technical potential or annual generation by fixing energy loss from atmosphereturbine interactions to 10% to manage computational cost. This approach, which we call Fixed, underestimates losses as it discounts impacts of wind resource depletion that manifest as reduced wind speeds and lowered turbine yields. We explore the influence of kinetic energy (KE) removal by wind turbines and stability conditions on wind resource depletion and turbine yield. Using wind speeds, turbine yields and capacity factor estimates from three approaches that include the Fixed approach, a simplified representation of atmospheric KE budgets and their depletion (KEBA), and mesoscale simulations from the Weather Research and Forecasting (WRF) model with a wind farm parameterisation we investigate the predominant influence on the Bight's potential that is relevant for energy scenarios. WRF, the most physically comprehensive model among the three, reveals that reductions in these estimates are highest during stable conditions. KEBA, which incorporates only KE removal effects, aligns closely with WRF. Under highly unstable conditions KEBA's wind speed and capacity factors estimates are within 10% and 20% of WRF, respectively. Under stable conditions they are within 20 and 45%. As unstable conditions dominate the German Bight, KEBA estimates of technical potential are within 35% of WRF, suggesting that KE removal primarily shapes depletion effects and technical potential. Disregarding it leads to an overestimation of almost 90%. Despite depletion effects, the Bight's potential remains substantial, generating about 200-250 TWh yr-1 or 3000-3400 full load hours yr-1 from a 72 GW deployment. We conclude that using a simplified yet physical model of KE budgets provides more representative technical potential estimates for energy scenarios compared to the fixed approach.
