Showing papers in "Meteorologische Zeitschrift in 2020"

Long-range modifications of the wind field by offshore wind parks – results of the project WIPAFF

Abstract: This publication synthesizes the results of the WIPAFF (WInd PArk Far Fields) project. WIPAFF focused on the far field of large offshore wind park wakes (more than 5 km downstream of the wind parks) located in the German North Sea. The research project combined in situ aircraft and remote sensing measurements, satellite SAR data analysis and model simulations to enable a holistic coverage of the downstream wakes. The in situ measurements recorded on-board the research aircraft DO-128 and remote sensing by laser scanner and SAR prove that wakes of more than 50 kilometers exist under certain atmospheric conditions. Turbulence occurs at the lateral boundaries of the wakes, due to shear between the reduced wind speed inside the wake and the undisturbed flow. The results also reveal that the atmospheric stability plays a major role in the evolution of wakes and can increase the wake length significantly by a factor of three or more. On the basis of the observations existing mesoscale and industrial models were validated and updated. The airborne measurement data is available at PANGAEA/ESSD.

The Research Unit VolImpact: Revisiting the volcanic impact on atmosphere and climate – preparations for the next big volcanic eruption

Abstract: This paper provides an overview of the scientific background and the research objectives of the Research Unit “VolImpact” (Revisiting the volcanic impact on atmosphere and climate – preparations for the next big volcanic eruption, FOR 2820). VolImpact was recently funded by the Deutsche Forschungsgemeinschaft (DFG) and started in spring 2019. The main goal of the research unit is to improve our understanding of how the climate system responds to volcanic eruptions. Such an ambitious program is well beyond the capabilities of a single research group, as it requires expertise from complementary disciplines including aerosol microphysical modelling, cloud physics, climate modelling, global observations of trace gas species, clouds and stratospheric aerosols. The research goals will be achieved by building on important recent advances in modelling and measurement capabilities. Examples of the advances in the observations include the now daily near-global observations of multi-spectral aerosol extinction from the limb-scatter instruments OSIRIS, SCIAMACHY and OMPS-LP. In addition, the recently launched SAGE III/ISS and upcoming satellite missions EarthCARE and ALTIUS will provide high resolution observations of aerosols and clouds. Recent improvements in modeling capabilities within the framework of the ICON model family now enable simulations at spatial resolutions fine enough to investigate details of the evolution and dynamics of the volcanic eruptive plume using the large-eddy resolving version, up to volcanic impacts on larger-scale circulation systems in the general circulation model version. When combined with state-of-the-art aerosol and cloud microphysical models, these approaches offer the opportunity to link eruptions directly to their climate forcing. These advances will be exploited in VolImpact to study the effects of volcanic eruptions consistently over the full range of spatial and temporal scales involved, addressing the initial development of explosive eruption plumes (project VolPlume), the variation of stratospheric aerosol particle size and radiative forcing caused by volcanic eruptions (VolARC), the response of clouds (VolCloud), the effects of volcanic eruptions on atmospheric dynamics (VolDyn), as well as their climate impact (VolClim).

Detection of structures in the horizontal wind field over complex terrain using coplanar Doppler lidar scans

Abstract: Coplanar scans from three Doppler lidars are used to retrieve the horizontal wind field in a horizontal plane of about 5 km × 5 km in size above the city of Stuttgart in south-western Germany. Stuttgart is located in moderate mountainous terrain that is characterized by a basin-shaped valley (Stuttgart basin) which opens into the larger Neckar Valley. Using the retrieved horizontal wind field, which is available on 22 days with a temporal resolution of 1 min and a horizontal resolution of 100 m, we investigate the mesoscale structure of the horizontal flow in the valleys with respect to time of the day, stratification and wind above the mean ridge height, and determine how fast the cells in the convective boundary layer move downstream, i.e. we estimate the convection velocity. The measurements reveal a large spatial and temporal variability of the flow. During stable conditions, the flow below the mean ridge height is decoupled from the flow aloft and downvalley wind dominates in the valleys. At the opening of the Stuttgart basin into the Neckar Valley outflow dominates during nighttime, whereas inflow into the basin prevails in the early morning. During thermally unstable conditions the flow in the valleys is mainly coupled to the flow aloft with a preference for upvalley wind direction. Convective cells moving downstream are detected in the horizontal wind field and a method to estimate the convection velocity from the horizontal wind field measurements is presented. The mean convection velocity is found to be higher by 24 % than the mean horizontal wind speed at the same height and about similar to the wind speed 100 m further up.

UTCI climatology and its future change in Germany – an RCM ensemble approach

Abstract: n the present study, the quantity, duration and intensity of heat stress events in Germany as well as their future change and relation with weather types were investigated. A small ensemble of regional climate simulations with the regional climate model (RCM) COSMO-CLM driven by four general circulation models (GCMs) was used to calculate the Universal Thermal Climate Index (UTCI); the UTCI is a well-accepted thermal comfort index which we use here to quantify thermal stress. The variables entering the UTCI were bias corrected with a method that preserves their interdependencies. The projected climate changes cause a significant increase of both the mean UTCI and the number, duration and intensity of heat stress events between the control period (1981–2000) and the projection period (2031–2050). The projected future hourly frequency distribution of the UTCI at a location can be described by a shift to higher UTCI values with an almost constant shape of distribution. The investigations of the projected changes in weather types show no significant changes between the periods covered, with a few exceptions. An exception concerning heat stress events is the increase of summer anticyclonic weather types. Although more anticyclonic weather types in summer lead to an increase in heat stress events, they are not the primary cause of the projected increases. Rather, it turns out that the characteristics of the air masses associated with the weather types change towards warmer and more humid conditions.

Physically based correction of systematic errors of Rotating Shadowband Irradiometers

Abstract: The new correction and calibration method, which is developed in this thesis, attempts to remove the measurement errors in the measurements using a physical method. It is based on information of the sensor properties and the atmospheric conditions at the measurement site. This way, no empiric relations obtained from a specific site are required. The method requires estimates of the current DHI and GHI spectra during each measurement of the sensor. Based on these spectra, a spectral correction, which includes a spectrum dependent temperature correction, can be made without employing empirical relationships.

Investigating predictability of offshore winds using a mesoscale model driven by forecast and reanalysis data

Abstract: The atmosphere is inherently unpredictable by deterministic Numerical Weather Prediction models at both small and large temporal and spatial scales with some intermediate regime where predictability has been demonstrated; this study deals with time scales only. The chaotic nature at the smaller time scales is predominantly caused by turbulence and at the large scales by non-linearity of the Navier-Stokes equations. We investigate, based on observations carried out with a wind-lidar at the FINO3 research platform in the North Sea, the ability of the Weather Research and Forecasting model (WRF) to simulate the changes in the observations ahead of time. The simulations are performed in two ways. In one type the model uses boundary conditions from a reanalysis data-set (WRF-ERA). Alternatively, the simulations are carried out using boundary conditions from a forecast (WRF-GFS). In this study focus is on the predictability of changes in the wind speed and direction. A metric is suggested that chiefly accounts for point-wise changes in the wind speed and direction including turbulent structures. However, for completeness, a traditional metric that compared predicted and observed wind speed and direction directly is also applied. This metric does not reflect the turbulent structures of the flow for small lead times, as the new metric does. The traditional metric reveals very good skills (Fig. 2) up to a lead time of 4 days for simulations in forecast mode (WRF-GFS). By applying the new metric and a correlation coefficient of 0.6 as the lower limit for the skill in the simulations at a height of 126 m, corresponds to a lead time of ≈4 hours (reanalysis) and ≈3 hours (forecast) for both wind speed and direction for turbulence limited lead times. This value is larger than typically found over land – being ≈2 hours. The difference likely relates to the marine conditions of the measurement site. For large lead times, when the simulations are nudged towards the reanalysis the forecast skill does not deteriorate for increasing lead times. This is in contrast to simulations nudged towards meteorological forecasts where the predictability is limited by the non-linearity of the Navier-Stokes equations and a correlation coefficient less than 0.6 was found for lead times larger than ≈6 days for wind speed and somewhat smaller – ≈4 days for the wind direction when applying the new metric. Thus, the window of predictability of the WRF simulations nudged towards a forecast is found to be in the interval ≈4 hours up to ≈6 days (wind speed) and ≈3 hours to ≈4 days (wind direction). These numbers refer to a height of 126 m. The predictive skill is found to be a function of height; at 626 m it is better than at 126 m for both wind speed and direction. For the traditional metric a correlation of less than 0.6 was realized for a lead time larger than ≈4 days for both wind speed and direction.

Miniature high-frequency chilled-mirror hygrometer for atmospheric measurements aboard fixed wing UAS

Abstract: A small light-weight in-house made miniature chilled-mirror hygrometer (CMH) for fixed wing UAS (unmanned aircraft system) is presented, with its features and limitations. Therefore, first measurements of the CMH equipped on the small research UAS of type MASC-3 (multi-purpose airborne sensor carrier) operated by the University of Tübingen are shown. A comparison against a very accurate state of the art capacitive industrial humidity sensor (SHT31) is done. The sensor consists of a TEC (thermoelectric cooler) covered by a gold mirror. The TEC is controlled by a commercially available microprocessor with an on-board PID (proportional-integral-derivative) controller. The results of the CMH measurements are in good agreement with the industrial-made capacitive sensor. The absolute accuracy of the measured dew point temperature by the CMH is in the range of ±0.2 K. Spectra show evidence that the CMH is capable to measure turbulent humidity fluctuations in the atmosphere with a temporal resolution of up to 10 Hz. Such a fast humidity sensor aboard a small UAS has the potential to study humidity fluxes in the surface layer over complex terrain, behind wind energy converters and humidity variations over land and sea surfaces in general.

Characteristics of deep moist convection over Germany in multi-source data

Abstract: This study analyses characteristics of deep moist convection (DMC) over Germany with the aim to select relevant parameters that have the skill to improve the identification of current life cycle phase and the forecast of a lifetime of DMCs in an operational weather forecasting environment. No differentiation between thunderstorm organization types is done, since no simple differentiation method is available in an operational environment. In contrast to previous analyses, multiple data sources are used synchronously to explore an extensive data set of DMCs at high resolution in space and time.

Classifying direct normal irradiance 1‑minute temporal variability from spatial characteristics of geostationary satellite-based cloud observations

Abstract: t Variability of solar surface irradiances in the 1-minute range is of interest especially for solar energy applications. Eight variability classes were previously defined for the 1 min resolved direct normal irradiance (DNI) variability inside an hour. In this study spatial structural parameters derived fromsatellite-based cloud observations are used as classifiers in order to detect the associated direct normal irradiance (DNI) variability class in a supervised classification scheme. A neighbourhood of 3×3 to 29×29 satellite pixels is evaluated to derive classifiers describing the actual cloud field better than just using a single satellite pixel at the location of the irradiance observation. These classifiers include cloud fraction in a window around the location of interest, number of cloud/cloud free changes in a binary cloud mask in this window, number of clouds, and a fractal box dimension of the cloud mask within the window. Furthermore, cloud physical parameters as cloud phase, cloud optical depth, and cloud top temperature are used as pixel-wise classifiers. A classification scheme is set up to search for the DNI variability class with a best agreement between these classifiers and the pre-existing knowledge on the characteristics of the cloud field within each variability class from the reference data base. Up to 55 % of all DNI variability class members are identified in the same class as in the reference data base. And up to 92 % cases are identified correctly if the neighbouring class is counted as success as well – the latter is a common approach in classifying natural structures showing no clear distinction between classes as in our case of temporal variability. Such a DNI variability classification method allows comparisons of different project sites in a statistical and automatic manner e.g. to quantify short-term variability impacts on solar power production. This approach is based on satellite-based cloud observations only and does not require any ground observations of the location of interest.

On ice supersaturation over the Arctic

Abstract: We study ice-supersaturation in the cold (< −38◦C) arctic troposphere and lower stratosphere using highresolution quality-controlled radiosonde data. On average, ice supersaturation occurs in about 40 % to 60 % of the profiles with frequency of occurrence increasing with geographic latitude. The frequencies of occurrence show (so far) no long-term trends. The seasonal cycles are not very clear but seem to reverse between more southern to more northern locations. Most profiles with ice-supersaturation have more than one supersaturated layer; this stacking increases as well to the north. Due to the 1-Hz resolution of the data we find icesupersaturated layers a few metres thick, but very thick layers extending over almost 5 km are found as well. Median thickness values are smaller than in previous studies, between 100 m and 200 m. The far northern locations display a strong seasonal cycle of the mean layer thickness with maxima in the polar night, probably caused by radiation cooling. Ice supersaturation occurs most frequently directly beneath the tropopause in an upper-tropospheric layer whose depth varies strongly seasonally, being thin in summer and much thicker in winter. Due to the very low temperatures in the Arctic ice supersaturation can occur at the ground. Temperatures in arctic supersaturated layers typically range from −40 to −60 °C, but can occasionally be lower than −70 °C. Water vapour volume mixing ratios range from a few to about 500 ppmv. The relative humidity with respect to ice can exceed 150–160 %. The thickness of supersaturated layers is weakly correlated with its maximum supersaturation, but not with temperature and absolute humidity.

Satellite image-based generation of high frequency solar radiation time series for the assessment of solar energy systems

Abstract: Solar energy is envisaged as a major pillar of the global transition to a climate-friendly energy system. Variability of solar radiation requires additional balancing measures to ensure a stable and secure energy supply. In order to analyze this issue in detail, solar radiation time series data of appropriate temporal and spatial resolution is necessary. Common weather models and satellites are only delivering solar surface irradiance with temporal resolutions of up to 15 min. Significant short-term variability in irradiances within seconds to minutes however is induced by clouds. Ground-based measurements typically used to capture this variability are costly and only sparsely available. Hence, a method to synthetically generate time series from currently available satellite imagery is of value for researchers, grid operators, and project developers. There are efforts to increase satellite resolution to 1 min, but this is not planned everywhere and will not change the spatial resolution. Therefore, the fundamental question remains if there are alternative strategies to obtain high temporal resolution observations at a pinpoint. This paper presents a method to generate 1 min resolved synthetic time series of global and direct normal irradiances for arbitrary locations. A neural network based on satellite image derived cloud structure parameters enables to classify high-frequency solar radiation variability. Combined with clear-sky radiation data, 1 min time series which reflect the typical variability characteristics of a site are reproduced. Testing and validation against ground observations (BSRN) show that the method can accurately reproduce characteristics such as frequency and ramp distributions. An application case demonstrates the usage in low-voltage grid studies.