Vertically pointing Doppler cloud radars have been operated for over a decade by research networks around the globe, providing important insights into cloud microphysical processes and dynamics. In contrast, national weather radar networks mainly provide data at low-elevation angles to cover large areas and generally operate at longer wavelengths (typically at C-or S-band). Nonetheless, most polarimetric weather radars are also capable of collecting vertical profiling measurements, and such "birdbath" scans are already used routinely for radar calibration. Deutscher Wetterdienst (DWD)'s birdbath scan, for example, is repeated every 5 min within the operational scanning cycle and records the standard radar moments and full Doppler spectra. Analysis methods developed for cloud radars can be readily applied to C-band birdbath data, opening another avenue to study precipitation processes. Despite the lower sensitivity and coarser time resolution of C-band birdbath scans, our comparison of vertical C-band and Ka-band radar observations of winter and summer precipitation events shows remarkable agreement for light to moderate precipitation. One important advantage of a C-band system is the much weaker attenuation due to heavy precipitation so that the entire vertical structure of severe weather systems, such as hailstorms, can be resolved. As birdbath scans are already performed in many weather radar networks, these birdbath data should be leveraged to complement sparse cloud radar observations. Using this "new" data source, novel vertical cloud and precipitation products can be developed not only for validating model outputs and satellite observations but also for operational warning products. SIGNIFICANCE STATEMENT: A vertical profiler scan for calibration purposes is often part of the operational scanning in weather radar networks but usually not used for meteorological applications. We show remarkable agreement between weather radar and cloud radar measurements. In this paper, we argue for exploiting these data to study precipitation and cloud processes. Less sensitive to attenuation, a direct look into hail-producing thunderstorms becomes possible. Only a minor investment in software extension was needed at the German Meteorological Service to fully open up this fascinating data stream for research and new meteorological product development.

Wind turbine clutter (WTC) is a serious threat to radar measurements from polarimetric weather radar. In Germany, wind turbines can now be built within the 5-15 km range of a weather radar in order to support and further increase the production of green energy. In order to protect the remaining 5 km radius from further wind turbine expansion, WTC is monitored and the consequences on radar data quality are quantified. There are currently no filter methods that can reliably separate wind turbine clutter from desired weather information. It is shown, that a dynamic WTC detection algorithm on the signal processor level performs well in over 80 % of the time if the rotor speed of the wind turbine is larger than 5 rpm (i.e. wind turbine is running). The dynamic WTC detection algorithm fails in situations where, presumably, the static clutter contribution from the wind turbine tower is too large. This is assessed for the first time by using wind turbine operator data from two wind turbines at a distance of about 10 km from a radar system, which are provided in real-time to the Deutscher Wetterdienst (DWD). For the DWD radar system Ummendorf, persistent WTC occupies 5 % of the area in the 5 km radius (approx. 4 km2), and 3 % in the 5-15 km radius (approx. 18 km2). WTC is found up to an antenna elevation of 3.5 degrees within the 5 km radius, and 1.5 degrees with the 5-15 km radius. Using wind measurements from a synoptic weather station near the radar system Ummendorf, a wind turbine (WT) detection probability between 60 % and 80 % can be deduced for the WTs at around the 5 km radius. We show that polarimetric radar measurements are more sensitive to WTC. Especially the areal coverage of the disturbance is larger than that observed for radar reflectivity. Also, the vertical extent of WTC on polarimetric moments, illustrated by the depolarisation ratio (DR), is clearly present at 3.5 degrees antenna elevation, and less so in radar reflectivity.A wind park at the 5 km range from the radar system Ummendorf is used to quantify the beam blockage by WTs statistically. Though the data are noisy, a 0.5 dB blockage can be estimated for this particular wind park. This is significant, as the overall accuracy of the radar reflectivity has to be within +/- 1 dB, meaning 50 % of the radar reflectivity error budget is consumed by this particular wind park. Further, the radar looses sensitivity in measuring precipitation, in particular at long ranges. Static beam-blockage corrections are not applicable to WTC. We conclude, that the 5 km radius must be kept free from WT expansion.

This paper describes the data quality of the first weather radar with a solid state power amplifier (SSPA) in use at the German Meteorological Service. The new transmitter has been integrated into the existing C-Band radar at the Observatory Hohenpeissenberg in October 2023. The resulting setup is unique: most of the radar hardware (wave guides, pedestal, antenna, radome) is shared between the magnetron and solid state transmitters. The same weather situation can therefore be observed with both transmitter types with a small time difference of around 5 min, so that most elements of uncertainty from the hardware can be disregarded for their comparison. A two pulse scheme is investigated with an un-modulated short pulse and a long pulse with non-linear frequency modulation. The scheme provides similar spatial resolution compared to the magnetron system. We show the results of the comparison of the data from both transmitters, focusing on reflectivity, Doppler moments and dual-polarization data. Magnetron and SSPA transmitters provide comparable data quality in areas where the magnetron's signal-to-noise ratio (SNR) is > 20 dB. When the magnetron SNR is lower, the SSPA outperforms the magnetron transmitter. This is especially noticeable in ranges above 130 km from the radar. Data at the transition between the modulated long pulse and the un-modulated gap filler short pulse are investigated in detail. It is shown that the matching works well and a simple approach with fixed offsets is sufficient to provide a smooth transition. Range sidelobes are investigated with examples originating from strong clutter targets and an intense convective cell. For targets stronger than 55 dB, range-time sidelobes reach levels in many radar moments (including dual-polarization moments) that resemble meteorological echoes. They influence the whole length of the compressed pulse (30 km in the presented case). The effect on radar products and possible mitigation approaches still have to be investigated. In general, SSPA transmitters for weather radars are assessed as viable in terms of data quality and are considered as an option to replace magnetron transmitters in the DWD weather radar network.

The 17 operational German C-band polarimetric weather radars routinely perform a vertical "birdbath" scan, which has so far primarily been used for calibration of differential moments. In this study, we transfer a retrieval algorithm for the rime fraction of snowflakes - originally developed for Ka-band cloud research radars - to the operational birdbath scan. This retrieval, which relies on the increase in detected mean Doppler velocity, serves as our benchmark. To validate the transfer of the retrieval, we apply it to a resampled birdbath dataset, constructed by downsampling cloud radar data to match the resolution of the operational birdbath scan. In addition, we present a new clutter filter and a melting layer detection algorithm for the operational birdbath scan. Finding good agreement between resampled and benchmark datasets, we apply the new retrieval to radar data recorded during the winters of 2021 to 2024. This results in a nationwide map of riming events in wintertime clouds. There is a north-south gradient in the riming distribution, which can be linked to Germany's precipitation climatology. Notably, we show that the occurrence of riming events correlates more strongly with precipitation intensity than with the total number of precipitation hours across sites. The temperature distribution associated with riming is consistently between -15 and 0 degrees C at all sites, except for the Feldberg site, which hints at a possible orographic effect. This study demonstrates that the operational birdbath scan of C-Band weather radars can be used for the retrieval of microphysical processes. Corresponding solutions, challenges and methods to transfer retrieval algorithms from research cloud radars to the operational weather radars are discussed.

Rainfall is a critical component of the Earth's water cycle, influencing global economic stability, access to food and freshwater, and daily life. Rain is also frequently used as a calibration target for various remote-sensing instruments. As such, timely and accurate observations of rainfall are vital for meteorological applications. The microphysical properties of rain are commonly characterized by the drop-size distribution (DSD), which determines the water content, intensity of precipitation, and kinetic energy of the rain. Conventional methods for measuring DSD include in situ instruments such as optical disdrometers and polarimetric weather radars. Disdrometers measure the size and velocity of raindrops within a narrow laser beam, providing data only at the surface level and having uncertainties due to the limited sampling area. Polarimetric weather radars, on the other hand, can observe rain profiles over larger areas, but typically only capture higher moments of the DSD, which then require specialized retrieval methods to derive DSD properties. Such retrievals are typically based on known size-shape-velocity relations for raindrops and a scattering model. Polarimetric variables are of an especial value because they allow to decouple the contribution of shape, size, and concentration of raindrops to the observations. In addition, the polarimetric variables can be accurately calibrated. The results of retrieval based on the moments are, however, prone to uncertainties related to measurement errors and limited information content of the DSD moments. Polarimetric Doppler cloud radars, operating at millimeter wavelengths, offer an alternative to traditional methods of the DSD estimation. They can measure the same set of parameters as weather radars but spectrally resolved, i.e. the cloud radar can separately measure droplets coexisting in the same volume but moving with different velocities relative to the radar. Since velocity of droplets is a proxy of their size, spectrally resolved measurements contain much more information about the underlying DSD. This study explores the potential of polarimetric cloud radars to retrieve DSD profiles. We highlight the advantages of this approach, including the ability of the non-parametric estimation of DSD profiles. We also examine existing challenges, such as the impact of resonance effects on observations due to the comparable wavelength of cloud radars and droplet sizes. These effects require accurate representation in scattering models and size-shape-velocity relationships. Current literature lacks explanations for some observations, indicating a need for further research and development of retrieval methods based on spectral polarimetric cloud radar data.

Despite the relevancy of riming for precipitation formation, our observational knowledge of spatiotemporal scales of riming in clouds is poor. We use long-term cloud radar observations to statistically investigate the horizontal and vertical dimensions as well as the typical duration of riming events. We extend a recent retrieval for rime mass fraction into an algorithm that can separate the data into individual riming events and estimate the spatial dimensions using horizontal wind profiles. For 2,500 riming events, we find an average horizontal extent of the riming regions of 13 km and a duration of 18 min. Vertical profiles indicate that the majority of rime mass is built within the uppermost 250 m of the region where the radar can detect riming. Similar to previous studies, the riming events are almost exclusively detected between 0 degrees C and -15 degrees C. To further examine the correlation between riming and thermodynamic profiles, we derived liquid water content from radiosonde data. We find that strong riming usually starts close to the level where the liquid water path exceeds 0.2 kg m-2. By defining a control group of nonriming events, we also find significantly enhanced liquid water below the -15 degrees C isotherm for the riming cases. However, the existence of the 0.2 kg m-2 level in ice clouds alone is not indicative of strong riming. We find this level to be four times more likely than strong riming events. We expect our multiyear statistical riming characteristics to be valuable for the future development of riming retrievals and model validation.

The established relationships between the size, shape, and terminal velocity of raindrops, along with the spheroidal shape approximation (SSA), are commonly employed for calculating radar observables in rain. This study, however, reveals the SSA's limitations in accurately simulating spectral and integrated backscattering polarimetric variables in rain at the W-band. Improving existing models is a complex task that demands high-precision data from both laboratory settings and natural rain, enhanced stochastic shape approximation techniques, and comprehensive scattering simulations. To circumvent these challenges, this study introduces a simpler and more straightforward approach – the empirical scattering model (ESM). The ESM is derived from an analysis of high-quality, low-turbulence Doppler spectra, which were selected from measurements taken with a 94 GHz radar at three different locations between 2021 and 2024. The ESM's primary advantages over the SSA include superior accuracy and the direct incorporation of microphysical effects observed in natural rain. This study demonstrates that the ESM can potentially clarify issues in existing retrieval and calibration methods that use polarimetric observations at the W-band. The findings of this study are valuable not only for experts in cloud radar polarimetry but also for scattering modelers and laboratory experimenters since explaining the presented observations necessitates a more profound understanding of the microphysical properties and processes in rain.

Lightning protection is important for weather radars to prevent critical damage or outages, but this can have negative effects on data quality. The existing lightning protection of the German Meteorological Service (Deutscher Wetterdienst, DWD) polarimetric C-band weather radar network consists of four vertical poles with a maximum diameter of 10 cm. During radar operation, these rods cause local scattering in the near field of the antenna, resulting in negative impacts on radar products. One effect is the removal of significant transmission power from the main beam axis and its addition to other areas or the side lobes. This results in wrongly localised precipitation fields in a radial direction. The second effect is the loss of transmitted and received power, appearing as a decrease in system gain, and subsequently an underestimation of all power-based radar moments in the vicinity of the rods. The underestimation in radar reflectivity Z then leads to a negative bias of approximately 20 % in the actual rain rate if a Z–R relationship is applied. These detrimental effects on data quality led to the requirement of developing a new lightning protection concept. The new concept must minimise the effect on data quality but also provide sufficient protection from lightning strikes according to the existing regulations and requirements. Three possible lighting protection concepts are described in this paper: two using vertical rods of different diameters (16 and 40 mm) and one with horizontally placed rods outside the antenna aperture. Their possible influence on data quality is quantified through a dedicated measurement campaign by analysing resulting antenna patterns and precipitation sum products. Antenna patterns are analysed with respect to the side-lobe levels compared to antenna patterns without lightning protection and the original lightning protection. With the newly tested lightning rods, the apparent side-lobe levels are slightly increased compared to an antenna pattern taken without lightning protection but are within the accepted antenna specifications. Compared to the original lightning protection, a decrease of up to −15 dB in apparent side-lobe levels is found for all tested lightning protection options. Beam blockage is substantially reduced compared to the existing lightning protection, as shown by the evaluation of quantitative precipitation estimation (QPE) sums. These results and some structural considerations are a solid basis to recommend the installation of four rods with a maximum 40 mm diameter for all 17 radar systems of the DWD weather radar network.

The national German weather radar network operates in C-band between 5.6 and 5.65 GHz. In a radar network, individual transmit frequencies have to be chosen such that radar–radar-induced interferences are avoided. In a unique experiment the Hohenpeißenberg research radar and five operational systems from the radar network were used to characterize radar–radar-induced interferences as a function of the radar frequency. The results allow assessment of the possibility of adding additional C-band radars with magnetron transmitters into the existing network. Based on the experiment, at least a 15 MHz separation of the nominal radar frequency is needed to avoid a radar–radar interference. The most efficient mitigation of radar–radar interference is achieved by the “Radar Tango”, which refers to the synchronized scanning of all radar systems in the network. Based on those results, additional C-band radar systems can be added to the German weather radar network if a further improvement of the radar coverage is needed.

Abstract. C-Band weather radar data are commonly compromised by interference from external sources even though weather radars are the primary and therefore privileged user of this frequency band. This is also the case for the radar network of the German Weather Service (Deutscher Wetterdienst, DWD). Theoretically, dynamic frequency stepping (DFS) by devices operating in the C-Band should prevent any disturbance of the primary user. In practice, this does not always work as intended by the current regulations. As it is not possible to separate a superimposed interference signal from measured weather radar data, the protection of the frequency band is of utmost importance. Currently the only available option is to discard the compromised portions of the radar data. Therefore, the current best course of action is to shut down interference (RFI) sources as fast as possible. The automated RFI detection algorithm for the German C-Band weather radar network is operational since July 2017, which makes use of routinely measured radar moments. Built upon the data gathered since 2017, an RFI classification with respect to the severity and duration of RFIs was first implemented in 2019. An independent verification of the RFI detection algorithm was performed by using a commercially available WIFI adapter, which is directly integrated into the radar receiver. Subsequently, a mitigation workflow was implemented to efficiently identify and shut down detected RFI sources by the German Federal Network Agency (BNetzA). By following this workflow with great effort, the number of persistent RFIs is decreasing since October 2019 while a steady increase in short lived RFIs over the last 5 years exists. In total, 11889 RFIs have been identified since July 2017 until May 2022. The majority of these (94.8 %) are so short lived that an unambiguous identification by the BNetzA is, in general, not feasible. However, as stated by the C-Band regulations, any non-compliant transmitter compromising the operation of a weather radar has to be shut down. This is important, as even these short lived RFIs negatively affect the meteorological product generation.

C-band weather radar data are commonly compromised by interference from external sources even though weather radars are the primary and therefore privileged user of this frequency band. This is also the case for the radar network of the German Meteorological Service (Deutscher Wetterdienst, DWD). Theoretically, dynamic frequency selection (DFS) by devices operating in the C band should prevent any disturbance of the primary user. In practice, this does not always work as intended under the current regulations. As it is not possible to separate a superimposed interference signal from measured weather radar data, the protection of the frequency band is of utmost importance. Currently, the only available option is to discard the compromised portions of the radar data. Therefore, the current best course of action is to shut down radio frequency interference (RFI) sources as quickly as possible. The automated RFI detection algorithm for the German C-band weather radar network, operational since July 2017, makes use of routinely measured radar moments. Built upon data gathered since 2017, an RFI classification with respect to the severity and duration of RFI sources was first implemented in 2019. An independent verification of the RFI detection algorithm was performed by using a commercially available Wi-Fi adapter, which is directly integrated into the radar receiver. Subsequently, a mitigation workflow was implemented to efficiently identify and shut down detected RFI sources by the German Federal Network Agency (Bundesnetzagentur, BNetzA). By following this workflow with great effort, the number of persistent RFI sources has been decreasing since October 2019, while a steady increase in short-lived RFI sources over the last 5 years also exists. In total, 11 889 RFI sources have been identified from July 2017 to May 2022. Most of these (94.8 %) are such short-lived sources that an unambiguous identification by the BNetzA is, in general, not feasible. However, as stated by the C-band regulations, any non-compliant transmitter compromising the operation of a weather radar has to be shut down. This is important, as even these short-lived RFI sources negatively affect meteorological product generation.

This study explores the potential of using Doppler (power) spectra from vertically pointing C-band radar birdbath scans to investigate precipitating clouds above the radar. First, the new birdbath scan strategy for the network of dual-polarization C-band radars operated by the German Meteorological Service (Deutscher Wetterdienst, DWD) is outlined, and a novel spectral postprocessing and analysis method is presented. The postprocessing algorithm isolates the weather signal from non-meteorological contributions in the radar output based on polarimetric attributes, identifies the statistically significant precipitation modes contained in each Doppler spectrum, and calculates characteristics of every precipitation mode as well as multimodal properties that describe the relation among different modes when more than a single mode is identified. To achieve a high degree of automation and flexibility, the postprocessing chain combines classical signal processing with clustering algorithms. Uncertainties in the calculated modal and multimodal properties are estimated from the small variations associated with smoothing the measured radar signal. The analysis of five birdbath scans recorded at different radar sites and for various precipitation conditions delivers reliable profiles of the derived modal and multimodal properties for two snowfall cases and for stratiform precipitation above and below the melting layer. To help identify the dominant precipitation growth mechanism, Doppler spectra from DWD's birdbath scans can be used to retrieve the typical degree of riming for individual snow modes. Here, the automatically identified snow modes span a wide range of riming conditions with estimated rime mass fractions (RMFs) of up to RMF>0.5. The evaluation of Doppler spectra inside the melting layer and for an intense frontal shower, with observed radar reflectivities of up to about 40 dBZ, occasionally shows erroneously identified precipitation modes and spurious results for the calculated higher-order Doppler moments of skewness and kurtosis. Nonetheless, the Doppler spectra from DWD's operational C-band radar birdbath scan provide a detailed view into the precipitating clouds and allow for calculating a high-resolution profile of radar reflectivity, mean Doppler velocity, and spectral width even in intense frontal precipitation.

The weather radar is one of the most important components of DWD warning management. For example, in summer, small-scale thunderstorm cells with heavy precipitation can form within a few minutes. These can only be detected and tracked area-wide and three-dimensionally using weather radar. For nowcasting, i.e. with a forecast time of up to two hours, weather radar plays a major role in assessing the type, strength and movement of precipitation areas, among other things. The quality of the detection and prediction and ultimately the warning of such events depends crucially on the quality of the underlying radar data. This is increasingly impaired by the expansion of wind energy, since more and increasingly larger wind turbines are being built in the near vicinity of weather radar systems (conflict of use of space). The meteorological radar echo can be significantly disturbed by the wind turbines (often arranged in wind farms) and the weather observation options can therefore be severely restricted or made completely impossible (priority conflict wind turbine weather radar). In order to protect its warning management and to support the energy transition, the DWD must take into account the conflicts of use of space and the conflict of priority. Therefore DWD endeavors to work with various partners to develop possible solutions that maintain the quality of the radar data and ultimately the weather warnings despite the expansion of wind energy.

Cloud and precipitation processes are still a main source of uncertainties in numerical weather prediction and climate change projections. The Priority Programme "Polarimetric Radar Observations meet Atmospheric Modelling (PROM)", funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), is guided by the hypothesis that many uncertainties relate to the lack of observations suitable to challenge the representation of cloud and precipitation processes in atmospheric models. Such observations can, however, at present be provided by the recently installed dual-polarization C-band weather radar network of the German national meteorological service in synergy with cloud radars and other instruments at German supersites and similar national networks increasingly available worldwide. While polarimetric radars potentially provide valuable in-cloud information on hydrometeor type, quantity, and microphysical cloud and precipitation processes, and atmospheric models employ increasingly complex microphysical modules, considerable knowledge gaps still exist in the interpretation of the observations and in the optimal microphysics model process formulations. PROM is a coordinated interdisciplinary effort to increase the use of polarimetric radar observations in data assimilation, which requires a thorough evaluation and improvement of parameterizations of moist processes in atmospheric models. As an overview article of the inter-journal special issue "Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes", this article outlines the knowledge achieved in PROM during the past 2 years and gives perspectives for the next 4 years.

It is a challenge to calibrate differential reflectivity ZDR to within 0.1–0.2 dB uncertainty for dual-polarization weather radars that operate 24∕7 throughout the year. During operations, a temperature sensitivity of ZDR larger than 0.2 dB over a temperature range of 10 ∘C has been noted. In order to understand the source of the observed ZDR temperature sensitivity, over 2000 dedicated solar box scans, two-dimensional scans of 5∘ azimuth by 8∘ elevation that encompass the solar disk, were made in 2018 from which horizontal (H) and vertical (V) pseudo antenna patterns are calculated. This assessment is carried out using data from the Hohenpeißenberg research radar which is identical to the 17 operational radar systems of the German Meteorological Service (Deutscher Wetterdienst, DWD). ZDR antenna patterns are calculated from the H and V patterns which reveal that the ZDR bias is temperature dependent, changing about 0.2 dB over a 12 ∘C temperature range. One-point-calibration results, where a test signal is injected into the antenna cross-guide coupler outside the receiver box or into the low-noise amplifiers (LNAs), reveal only a very weak differential temperature sensitivity (<0.02 dB) of the receiver electronics. Thus, the observed temperature sensitivity is attributed to the antenna assembly. This is in agreement with the NCAR (National Center for Atmospheric Research) S-Pol (S-band polarimetric radar) system, where the primary ZDR temperature sensitivity is also related to the antenna assembly (Hubbert, 2017). Solar power measurements from a Canadian calibration observatory are used to compute the antenna gain and to validate the results with the operational DWD monitoring results. The derived gain values agree very well with the gain estimate of the antenna manufacturer. The antenna gain shows a quasi-linear dependence on temperature with different slopes for the H and V channels. There is a 0.6 dB decrease in gain for a 10 ∘C temperature increase, which directly relates to a bias in the radar reflectivity factor Z which has not been not accounted for previously. The operational methods used to monitor and calibrate ZDR for the polarimetric DWD C-band weather radar network are discussed. The prime sources for calibrating and monitoring ZDR are birdbath scans, which are executed every 5 min, and the analysis of solar spikes that occur during operational scanning. Using an automated ZDR calibration procedure on a diurnal timescale, we are able to keep ZDR bias within the target uncertainty of ±0.1 dB. This is demonstrated for data from the DWD radar network comprising over 87 years of cumulative dual-polarization radar operations.

The exact navigation of detected radar signals is crucial for usage of radar data in meteorological application, in particular in radar networks, where radar data from multiple radars may be used to characterize the precipitation process in a given observation volume. Based on the pioneering work of Huuskonen and Holleman (2007), the method to monitor and quantify the pointing error from operational radar data has essentially become a standard in weather radar networks worldwide. We extend this methodology and assess the antenna pointing accuracy in azimuth and elevation of a polarimetric weather research radar depending on position of the sun using dedicated solar boxscans in a sequence of 10 min (Frech et al, 2019). In doing so, we assess the quality of the mechanical design to steer the antenna in azimuth and elevation. Furthermore we assess the design to encode the pointing angles and determine characteristics of the antenna main. The research radar of the German Meteorological Service (DeutscherWetterdienst, DWD) is located at the meteorological observatory Hohenpeissenberg. It is identical to the 17 weather radars of the German weather radar network. During the summer time, an azimuth range from 50-300° is covered and over 90 boxscans are available per day for analysis. A non-linear azimuthal variation of azimuthal pointing bias of up to 0.1° is found, which is significant as this is commonly viewed as the target pointing accuracy. We can attribute this azimuthal variation to the mechanical design of the drive train with the angle encoder. This includes the inherent backlash of the gear-drive assembly. The pointing bias estimates based on over 1000 boxscans from 26 days show a small case by case variability, which indicates that dedicated solar boxscans from one day are sufficient to characterize the pointing performance of a particular system. We show that the pointing biases based on solar boxscan data are consistent with results from the operational assessment of pointing bias using solar hits from operational scanning. Furthermore the pedestal levelling can be assessed with the proposed methodology. A trend in elevation bias as function solar azimuth is indicative of a pedestal tilt. Examples are shown for the Hohenpeißenberg radar and from four operational radar systems of the German weather radar network. The analysis of a full diurnal cycle of boxscans from four operational radar systems shows that the azimuthal dependence of azimuth bias needs to be evaluated individually for each system. For one of the systems, the azimuthal variation of the pointing bias of about 0.2° is related to the bull gear. This analysis from four operational radar systems also reveals the need to optimize the built-in angle encoder.

Exact navigation of detected radar signals is crucial for usage of radar data in meteorological applications. The antenna pointing accuracy in azimuth and elevation of a polarimetric weather research radar depending on position of the sun is assessed using dedicated solar boxscans in a sequence of 10 min. The research radar of the German Meteorological Service (Deutscher Wetterdienst, DWD) is located at the meteorological observatory Hohenpeissenberg. It is identical to the 17 weather radars of the German weather radar network. A non-linear azimuthal variation of azimuthal pointing bias of up to 0.1 ∘ is found, which is significant as this is commonly viewed as the target pointing accuracy. This azimuthal variation can be attributed to the mechanical design of the drive train with the angle encoder. This includes the inherent backlash of the gear-drive assembly. The pointing bias estimates based on over 1000 boxscans from 26 days show a small case by case variability, which indicates that dedicated solar boxscans from one day are sufficient to characterize the pointing performance of a particular system. An azimuth and elevation range that is covered with this approach is limited and dependent on the time of the year. At Hohenpeißenberg, an azimuth range up to 50–300 ∘ was covered around summer solstice and about 90 boxscans were acquired. It is shown that the pointing bias based on solar boxscan data are consistent with results from the operational assessment of pointing bias using solar hits from operational scanning if we take into account the fact that the DWD operational scan definition has only a maximum elevation of 25 ∘ . The analysis of a full diurnal cycle of boxscans from four operational radar system shows that the azimuthal dependence of azimuth bias needs to be evaluated individually for each system. For one of the systems, the azimuthal variation of the pointing bias of about 0.2 ∘ seems related to the bull gear. A difference of the pointing bias for the horizontal and vertical polarization is an indication of beam squint and, eventually, that of a feed misalignment. Beam squint and, as such, the quality of the antenna assembly can easily be monitored with this method during the life-time of a weather radar.

AbstractThe absolute calibration of a dual-polarization radar of the German Weather Service is continuously monitored using the operational birdbath scan and collocated disdrometer measurements at the Hohenpeissenberg observatory. The goal is to measure the radar reflectivity constant Z better than ±1 dB. The assumption is that a disdrometer measurement close to the surface can be related to the radar measurement at the first far-field range bin. This is verified using a Micro Rain Radar (MRR). The MRR data fill the gap between the measurement near the surface and the far-field range bin at 650 m. Using data from the first half of the warm season in 2014, a bias in radar calibration of 1.8 dB is found. Data from only stratiform precipitation events are considered. After adjusting the radar calibration and using an independent data sample, very good agreement is found between the radar, the MRR, and the disdrometer with a bias in smaller than 1 dB. The bias in is not captured with the classic one-point cal...

There is a strong political and economic push to further expand renewable energy production in order to reduce the dependence on for example coal burning power plant and to achieve the CO2 reduction goals. The contribution of renewable energy production relies mainly on solar energy and wind power. The preferred location for wind turbines are areas with sufficient wind potential, such as off-shore areas, plains or mountain ranges. The increasing number of installed wind turbines is causing concern among weather radar operators and users. Basically, this is due to the difficulties to filter out the contribution of a wind turbine in the radar return signal from the weather return signal. Here, classic Doppler clutter filters do not work properly because of the moving rotor blades. So far new filter methods have not been developed for operational usage which could reliably remove the wind turbine signal and recover the weather signal. There are proposals to simply replace and fill the wind turbines contaminated area with radar information from undisturbed neighboring areas. This may be a possible approach for singular wind mills, but not for wind farms which often cover a much larger area.. Radar operators try to keep a wind turbine free zone around radars. A WMO recommendation proposes a 20 km area around a wind turbine to avoid the negative impact. However, this limit often cannot be guaranteed because radar locations are also preferred ar-

The Deutscher Wetterdienst (D WD) weather radar network has been upgraded with new C-band Polarimetrie radar systems. The current study presents the results of a field research campaign, which was designed to assess the radar systems through analyzing radar measurements. A novel point mode approach proposed recently by Enterprise Electronics Corporation (EEC) was used for the data collection and analysis. Results show that DWD weather radars generally have a high system quality and contribute a negligible uncertainty to the radar measurements, as compared to the uncertainty caused by the sampling effect. The proposed point mode approach is validated with DWD radar data analysis and highly recommended as quality measure for commercial weather radars.