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During the EUREC4A field study, microwave radiometric measurements were performed at Barbados Cloud Observatory (BCO) and aboard RV Meteor and RV Maria S Merian in the downstream winter trades of the North Atlantic. We present retrieved integrated water vapor (IWV), liquid water path (LWP), and temperature and humidity profiles as a unified, quality-controlled, multi-site data set on a 3 s temporal resolution for a core period between 19 January and 14 February 2020 in which all instruments were operational. Multi-channel radiometric measurements were performed at BCO and aboard RV Meteor between 22 and 31 GHz (K-band) and from 51 to 58 GHz (V-band). Combined radar–radiometer measurements of a W-band Doppler radar with a single-channel radiometer instrument were conducted at 89 GHz aboard RV Meteor and RV Maria S Merian. We present a novel retrieval method to retrieve LWP from single-channel 89 GHz measurements, evaluate retrieved quantities with independent measurements, and analyze retrieval uncertainties by site and instrument intercomparison. Mean IWV conditions of 31.8 kg m−2 match independent radiosoundings at BCO with a root-mean-square difference of 1.1 kg m−2. Mean LWP conditions in confidently liquid cloudy, non-precipitating conditions ranged between 63.1 g m−2 at BCO and 46.8 g m−2 aboard RV Maria S Merian. Aboard the ships, 90 % of LWP was below 120 g m−2 with a 30 % uncertainty for LWP of 50 g m−2. Up to 20 % of confidently liquid cloudy profiles ranged below the LWP detection limit due to optically thin clouds. The data set comprises of processed raw data (Level 1), full quality-controlled post-processed instrument data (Level 2), a unified temporal resolution (Level 3), and a ready-to-use multi-site time series of IWV and LWP (Level 4), available to the public via AERIS (https://doi.org/10.25326/454##v2.0; Schnitt et al., 2023a). The data set complements the airborne LWP measurements conducted during EUREC4A and provides a unique benchmark tool for satellite evaluation and model–observation studies.

In order to improve observations of the atmospheric boundary layer (ABL), the European Meteorological Network, EUMETNET, and the Aerosol, Clouds, and Trace Gases Research Infrastructure, ACTRIS, are currently working on building networks of microwave radiometers (MWRs). Elevation-scanning MWRs are well suited to obtain temperature profiles of the atmosphere, especially within the ABL. Understanding and assessing measurement uncertainties of state-of-the-art scanning MWRs is therefore crucial for accurate temperature profiling. In this paper, we discuss measurement uncertainties due to the instrument setup and originating from external sources, namely (1) horizontal inhomogeneities of the atmosphere, (2) pointing errors or a tilt of the instrument, (3) physical obstacles in the line of sight of the instrument, and (4) radio frequency interference (RFI). Horizontal inhomogeneities from observations at the Jülich Observatory for Cloud Evolution (JOYCE) are shown to have a small impact on retrieved temperature profiles (<|0.22K| in the 25th and 75th percentiles below 3000 m). Typical instrument tilts, that could be caused by uncertainties during the instrument setup, also have a very small impact on temperature profiles and are smaller than 0.1 K below 3000 m for up to 1∘ of tilt. Physical obstacles at ambient temperatures and in the line of sight and filling the complete beam of the MWR at the lowest elevation angle of 5.4∘ have to be at least 600 m away from the instrument in order to have an impact of less than 0.1 K on obtained temperature profiles. If the obstacle is 5 K warmer than its surroundings then the obstacle should be at least 2700 m away. Finally, we present an approach on how to detect RFI with an MWR with azimuth and elevation-scanning capabilities. In this study, we detect RFIs in a water vapor channel that does not influence temperature retrievals but would be relevant if the MWR were used to detect horizontal humidity inhomogeneities.

As the frequency of extreme heat events in cities is significantly increasing due to climate change, the implementation of adaptation measures is important for urban planning. Microclimate modelling approaches enable scenario analyses and evaluations of adaptation potentials. An ENVI-met microclimate model was setup for a heterogeneous urban study area in Cologne/Germany characterized by closed building structures in the eastern part and an urban park area in the western part. The goal of this paper is to evaluate the model sensitivity and performance to different wind direction forcing and demonstrate the importance of accurate wind forcing data for precise microclimate modelling evaluated with sensor measurements. To this end, we compared simulated air temperatures at 3 m height level using measured wind direction forcing data with simulated air temperatures using constant wind direction forcing from west, north, east and south direction. All other forcing data like wind speed were kept exactly the same as in the reference run. This sensitivity study was performed for a warm summer day in 2022. The model results of all five model runs (reference plus four scenarios) were compared to microclimatological measurements derived from one station of a dense meteorological sensor network located in the study area using the simulated mean air temperatures. We found significant temperature differences between the four sensitivity tests and the reference run as well as to the sensor measurements. Temperature differences between the reference run and the measurements were small and a high statistical model fit could be determined (Nash Sutcliffe Model Efficiency Coefficient/NSE = 0.91). The four model runs with constant wind directions showed significantly larger differences to measurement data and a worse statistical correlation between simulated and observed data (NSE between 0.62 and 0.15). For constant west winds, cooler air temperatures and higher wind speeds were found in the urban park and in the streets and courtyards east of the park. Constant east wind causes warmer air temperatures in the urban park area and lower wind speeds in the street canyons and inner courtyards. This shows that cooling effects in adjacent building blocks due to the greened urban park largely depend on the wind direction. The sensitivity tests show that the wind direction effect can result in local air temperature differences of up to 4 K on average. These results shows that even on summer days with low wind speeds, accurate wind direction data is highly relevant for accurate air temperature simulation. This finding can have important implications for urban planning and the design of green infrastructures in cities, e. g. for the design of fresh air corridors.

Marine stratocumulus clouds of the eastern Pacific play an essential role in the earth's energy and radiation budget. Parts of these clouds off the western coast of South America form the major source of water to the hyperarid Atacama Desert coastal region at the northern coast of Chile. For the first time, a full year of vertical structure observations of the coastal stratocumulus and their environment is presented and analyzed. Installed at Iquique Airport in northern Chile in 2018/2019, three state-of-the-art remote sensing instruments provide vertical profiles of cloud macro- and micro-physical properties, wind, turbulence, and temperature as well as integrated values of water vapor and liquid water. Distinct diurnal and seasonal patterns of the stratocumulus life cycle are observed. Embedded in a land–sea circulation with a superimposed southerly wind component, maximum cloud occurrence and vertical extent occur at night but minima at local noon. Nighttime clouds are maintained by cloud-top cooling, whereas afternoon clouds reappear within a convective boundary layer driven through local moisture advection from the Pacific. During the night, these clouds finally re-connect to the maritime clouds in the upper branch of the land–sea circulation. The diurnal cycle is much more pronounced in austral winter, with lower, thicker, and more abundant (5×) clouds than in summer. This can be associated with different sea surface temperature (SST) gradients in summer and winter, leading to a stable or neutral stratification of the maritime boundary layer at the coast of the Atacama Desert in Iquique.

Doppler wind lidars (DWLs) have increasingly been used over the last decade to derive the mean wind in the atmospheric boundary layer. DWLs allow the determination of wind vector profiles with high vertical resolution and provide an alternative to classic meteorological tower observations. They also receive signals from altitudes higher than a tower and can be set up flexibly in any power-supplied location. In this work, we address the question of whether and how wind gusts can be derived from DWL observations. The characterization of wind gusts is one central goal of the Field Experiment on Sub-Mesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL). Obtaining wind gusts from a DWL is not trivial because a monostatic DWL provides only a radial velocity per line of sight, i.e., only one component of a three-dimensional vector, and measurements in at least three linearly independent directions are required to derive the wind vector. Performing them sequentially limits the achievable time resolution, while wind gusts are short-lived phenomena. This study compares different DWL configurations in terms of their potential to derive wind gusts. For this purpose, we develop a new wind retrieval method that is applicable to different scanning configurations and various time resolutions. We test eight configurations with StreamLine DWL systems from HALO Photonics and evaluate gust peaks and mean wind over 10 min at 90 m a.g.l. against a sonic anemometer at the meteorological tower in Falkenberg, Germany. The best-performing configuration for retrieving wind gusts proves to be a fast continuous scanning mode (CSM) that completes a full observation cycle within 3.4 s. During this time interval, about 11 radial Doppler velocities are measured, which are then used to retrieve single gusts. The fast CSM configuration was successfully operated over a 3-month period in summer 2020. The CSM paired with our new retrieval technique provides gust peaks that compare well to classic sonic anemometer measurements from the meteorological tower.

Thermodynamic profiles in the planetary boundary layer (PBL) are important observations for a range of atmospheric research and operational needs. These profiles can be retrieved from passively sensed spectral infrared (IR) or microwave (MW) radiance observations or can be more directly measured by active remote sensors such as water vapor differential absorption lidars (DIALs). This paper explores the synergy of combining ground-based IR, MW, and DIAL observations using an optimal-estimation retrieval framework, quantifying the reduction in the uncertainty in the retrieved profiles and the increase in information content as additional observations are added to IR-only and MW-only retrievals. This study uses ground-based observations collected during the Perdigão field campaign in central Portugal in 2017 and during the DIAL demonstration campaign at the Atmospheric Radiation Measurement Southern Great Plains site in 2017. The results show that the information content in both temperature and water vapor is higher for the IR instrument relative to the MW instrument (thereby resulting in smaller uncertainties) and that the combined IR + MW retrieval is very similar to the IR-only retrieval below 1.5 km. However, including the partial profile of water vapor observed by the DIAL increases the information content in the combined IR + DIAL and MW + DIAL water vapor retrievals substantially, with the exact impact vertically depending on the characteristics of the DIAL instrument itself. Furthermore, there is a slight increase in the information content in the retrieved temperature profile using the IR + DIAL relative to the IR-only; this was not observed in the MW + DIAL retrieval.

The occurrence of events with increased and decreased integrated water vapor (IWV) at the Arctic site Ny-Ålesund, their relation to cloud properties, and the surface cloud radiative effect (CRE) is investigated. For this study, we used almost 2.5 years (from June 2016 to October 2018) of ground-based cloud observations processed with the Cloudnet algorithm, IWV from a microwave radiometer (MWR), long-term radiosonde observations, and backward trajectories FLEXTRA. Moist and dry anomalies were found to be associated with North Atlantic flows and air transport within the Arctic region, respectively. The amount of water vapor is often correlated to cloud occurrence, presence of cloud liquid water, and liquid water path (LWP) and ice water path (IWP). In turn, changes in the cloud properties cause differences in surface CRE. During dry anomalies, in autumn, winter, and spring, the mean net surface CRE was lower by 2–37 W m−2 with respect to normal conditions, while in summer the cloud-related surface cooling was reduced by 49 W m−2. In contrast, under moist conditions in summer the mean net surface CRE becomes more negative by 25 W m−2, while in other seasons the mean net surface CRE was increased by 5–37 W m−2. Trends in the occurrence of dry and moist anomalies were analyzed based on a 25-year radiosonde database. Dry anomalies have become less frequent, with rates for different seasons ranging from −12.8 % per decade to −4 % per decade, while the occurrence of moist events has increased at rates from 2.8 % per decade to 6.4 % per decade.

Low-level mixed-phase clouds (MPCs) are common in the Arctic. Both local and large-scale phenomena influence the properties and lifetime of MPCs. Arctic fjords are characterized by complex terrain and large variations in surface properties. Yet, not many studies have investigated the impact of local boundary layer dynamics and their relative importance on MPCs in the fjord environment. In this work, we used a combination of ground-based remote sensing instruments, surface meteorological observations, radiosoundings, and reanalysis data to study persistent low-level MPCs at Ny-Ålesund, Svalbard, for a 2.5-year period. Methods to identify the cloud regime, surface coupling, and regional and local wind patterns were developed. We found that persistent low-level MPCs were most common with westerly winds, and the westerly clouds had a higher mean liquid (42 g m−2) and ice water path (16 g m−2) compared to those with easterly winds. The increased height and rarity of persistent MPCs with easterly free-tropospheric winds suggest the island and its orography have an influence on the studied clouds. Seasonal variation in the liquid water path was found to be minimal, although the occurrence of persistent MPCs, their height, and their ice water path all showed notable seasonal dependency. Most of the studied MPCs were decoupled from the surface (63 %–82 % of the time). The coupled clouds had 41 % higher liquid water path than the fully decoupled ones. Local winds in the fjord were related to the frequency of surface coupling, and we propose that katabatic winds from the glaciers in the vicinity of the station may cause clouds to decouple. We concluded that while the regional to large-scale wind direction was important for the persistent MPC occurrence and properties, the local-scale phenomena (local wind patterns in the fjord and surface coupling) also had an influence. Moreover, this suggests that local boundary layer processes should be described in models in order to present low-level MPC properties accurately.

Finding observational evidence of land surface and atmosphere interactions is crucial for understanding the spatial and temporal evolution of the boundary layer, as well as for model evaluation, and in particular for large-eddy simulation (LES) models. In this study, the influence of a heterogeneous land surface on the spatial distribution of atmospheric water vapor is assessed. Ground-based remote sensing measurements from a scanning microwave radiometer (MWR) are used in a long-term study over 6 years to characterize spatial heterogeneities in integrated water vapor (IWV) during clear-sky conditions at the Jülich ObservatorY for Cloud Evolution (JOYCE). The resulting deviations from the mean of the scans reveal a season- and direction-dependent IWV that is visible throughout the day. Comparisons with a satellite-derived spatial IWV distribution show good agreement for a selection of satellite overpasses during convective situations but no clear seasonal signal. With the help of a land use type classification and information on the topography, the main types of regions with a positive IWV deviation were determined to be agricultural fields and nearby open pit mines. Negative deviations occurred mainly above elevated forests and urban areas. In addition, high-resolution large-eddy simulations (LESs) are used to investigate changes in the water vapor and cloud fields for an altered land use input.

The French–German Arctic research base AWIPEV (the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research – AWI – and the French Polar Institute Paul Emile Victor – PEV) at Ny-Ålesund, Svalbard, is a unique station for monitoring cloud-related processes in the Arctic. For the first time, data from a set of ground-based instruments at the AWIPEV observatory are analyzed to characterize the vertical structure of clouds. For this study, a 14-month dataset from Cloudnet combining observations from a ceilometer, a 94 GHz cloud radar, and a microwave radiometer is used. A total cloud occurrence of ∼81 %, with 44.8 % multilayer and 36 % single-layer clouds, was found. Among single-layer clouds the occurrence of liquid, ice, and mixed-phase clouds was 6.4 %, 9 %, and 20.6 %, respectively. It was found that more than 90 % of single-layer liquid and mixed-phase clouds have liquid water path (LWP) values lower than 100 and 200 g m−2, respectively. Mean values of ice water path (IWP) for ice and mixed-phase clouds were found to be 273 and 164 g m−2, respectively. The different types of single-layer clouds are also related to in-cloud temperature and the relative humidity under which they occur. Statistics based on observations are compared to ICOsahedral Non-hydrostatic (ICON) model output. Distinct differences in liquid-phase occurrence in observations and the model at different environmental temperatures lead to higher occurrence of pure ice clouds. A lower occurrence of mixed-phase clouds in the model at temperatures between −20 and −5 ∘C becomes evident. The analyzed dataset is useful for satellite validation and model evaluation.

Ground-based microwave radiometers (MWRs) offer the capability to provide continuous, high-temporal-resolution observations of the atmospheric thermodynamic state in the planetary boundary layer (PBL) with low maintenance. This makes MWR an ideal instrument to supplement radiosonde and satellite observations when initializing numerical weather prediction (NWP) models through data assimilation. State-of-the-art data assimilation systems (e.g. variational schemes) require an accurate representation of the differences between model (background) and observations, which are then weighted by their respective errors to provide the best analysis of the true atmospheric state. In this perspective, one source of information is contained in the statistics of the differences between observations and their background counterparts (O–B). Monitoring of O–B statistics is crucial to detect and remove systematic errors coming from the measurements, the observation operator, and/or the NWP model. This work illustrates a 1-year O–B analysis for MWR observations in clear-sky conditions for an European-wide network of six MWRs. Observations include MWR brightness temperatures (TB) measured by the two most common types of MWR instruments. Background profiles are extracted from the French convective-scale model AROME-France before being converted into TB. The observation operator used to map atmospheric profiles into TB is the fast radiative transfer model RTTOV-gb. It is shown that O–B monitoring can effectively detect instrument malfunctions. O–B statistics (bias, standard deviation, and root mean square) for water vapour channels (22.24–30.0 GHz) are quite consistent for all the instrumental sites, decreasing from the 22.24 GHz line centre ( ∼ 2–2.5 K) towards the high-frequency wing ( ∼ 0.8–1.3 K). Statistics for zenith and lower-elevation observations show a similar trend, though values increase with increasing air mass. O–B statistics for temperature channels show different behaviour for relatively transparent (51–53 GHz) and opaque channels (54–58 GHz). Opaque channels show lower uncertainties (

Cloud Doppler radars are increasingly used to study cloud and precipitation microphysical processes. Typical bulk cloud properties such as liquid or ice content are usually derived using the first three standard moments of the radar Doppler spectrum. Recent studies demonstrated the value of higher moments for the reduction of retrieval uncertainties and for providing additional insights into microphysical processes. Large effort has been undertaken, e.g., within the Atmospheric Radiation Measurement (ARM) program to ensure high quality of radar Doppler spectra. However, a systematic approach concerning the accuracy of higher moment estimates and sensitivity to basic radar system settings, such as spectral resolution, integration time and beam width, are still missing. In this study, we present an approach on how to optimize radar settings for radar Doppler spectra moments in the specific context of drizzle detection. The process of drizzle development has shown to be particularly sensitive to higher radar moments such as skewness. We collected radar raw data (I/Q time series) from consecutive zenith-pointing observations for two liquid cloud cases observed at the cloud observatory JOYCE in Germany. The I/Q data allowed us to process Doppler spectra and derive their moments using different spectral resolutions and integration times during identical time intervals. This enabled us to study the sensitivity of the spatiotemporal structure of the derived moments to the different radar settings. The observed signatures were further investigated using a radar Doppler forward model which allowed us to compare observed and simulated sensitivities and also to study the impact of additional hardware-dependent parameters such as antenna beam width. For the observed cloud with drizzle onset we found that longer integration times mainly modify spectral width (Sw) and skewness (Sk), leaving other moments mostly unaffected. An integration time of 2 s seems to be an optimal compromise: both observations and simulations revealed that a 10 s integration time – as it is widely used for European cloud radars – leads to a significant turbulence-induced increase of Sw and reduction of Sk compared to 2 s integration time. This can lead to significantly different microphysical interpretations with respect to drizzle water content and effective radius. A change from 2 s to even shorter integration times (0. 4 s) has much smaller effects on Sw and Sk. We also find that spectral resolution has a small impact on the moment estimations, and thus on the microphysical interpretation of the drizzle signal. Even the coarsest spectral resolution studied, 0. 08 ms−1, seems to be appropriate for calculation moments of drizzling clouds. Moreover, simulations provided additional insight into the microphysical interpretation of the skewness signatures observed: in low (high)-turbulence conditions, only drizzle larger than 20 µm (40 µm) can generate Sk values above the Sk noise level (in our case 0.4). Higher Sk values are also obtained in simulations when smaller beam widths are adopted.

The HD(CP)2 Observational Prototype Experiment (HOPE) was performed as a major 2-month field experiment in Jülich, Germany, in April and May 2013, followed by a smaller campaign in Melpitz, Germany, in September 2013. HOPE has been designed to provide an observational dataset for a critical evaluation of the new German community atmospheric icosahedral non-hydrostatic (ICON) model at the scale of the model simulations and further to provide information on land-surface–atmospheric boundary layer exchange, cloud and precipitation processes, as well as sub-grid variability and microphysical properties that are subject to parameterizations. HOPE focuses on the onset of clouds and precipitation in the convective atmospheric boundary layer. This paper summarizes the instrument set-ups, the intensive observation periods, and example results from both campaigns. HOPE-Jülich instrumentation included a radio sounding station, 4 Doppler lidars, 4 Raman lidars (3 of them provide temperature, 3 of them water vapour, and all of them particle backscatter data), 1 water vapour differential absorption lidar, 3 cloud radars, 5 microwave radiometers, 3 rain radars, 6 sky imagers, 99 pyranometers, and 5 sun photometers operated at different sites, some of them in synergy. The HOPE-Melpitz campaign combined ground-based remote sensing of aerosols and clouds with helicopter- and balloon-based in situ observations in the atmospheric column and at the surface. HOPE provided an unprecedented collection of atmospheric dynamical, thermodynamical, and micro- and macrophysical properties of aerosols, clouds, and precipitation with high spatial and temporal resolution within a cube of approximately 10 × 10 × 10 km3. HOPE data will significantly contribute to our understanding of boundary layer dynamics and the formation of clouds and precipitation. The datasets have been made available through a dedicated data portal. First applications of HOPE data for model evaluation have shown a general agreement between observed and modelled boundary layer height, turbulence characteristics, and cloud coverage, but they also point to significant differences that deserve further investigations from both the observational and the modelling perspective.

Continuous monitoring of atmospheric humidity profiles is important for many applications, e.g., assessment of atmospheric stability and cloud formation. Nowadays there are a wide variety of ground-based sensors for atmospheric humidity profiling. Unfortunately there is no single instrument able to provide a measurement with complete vertical coverage, high vertical and temporal resolution and good performance under all weather conditions, simultaneously. For example, Raman lidar (RL) measurements can provide water vapor with a high vertical resolution, albeit with limited vertical coverage, due to sunlight contamination and the presence of clouds. Microwave radiometers (MWRs) receive water vapor information throughout the troposphere, though their vertical resolution is poor. In this work, we present an MWR and RL system synergy, which aims to overcome the specific sensor limitations. The retrieval algorithm combining these two instruments is an optimal estimation method (OEM), which allows for an uncertainty analysis of the retrieved profiles. The OEM combines measurements and a priori information, taking the uncertainty of both into account. The measurement vector consists of a set of MWR brightness temperatures and RL water vapor profiles. The method is applied to a 2-month field campaign around Jülich (Germany), focusing on clear sky periods. Different experiments are performed to analyze the improvements achieved via the synergy compared to the individual retrievals. When applying the combined retrieval, on average the theoretically determined absolute humidity uncertainty is reduced above the last usable lidar range by a factor of ∼ 2 with respect to the case where only RL measurements are used. The analysis in terms of degrees of freedom per signal reveal that most information is gained above the usable lidar range, especially important during daytime when the lidar vertical coverage is limited. The retrieved profiles are further evaluated using radiosounding and Global Position Satellite (GPS) water vapor measurements. In general, the benefit of the sensor combination is especially strong in regions where Raman lidar data are not available (i.e., blind regions, regions characterized by low signal-to-noise ratio), whereas if both instruments are available, RL dominates the retrieval. In the future, the method will be extended to cloudy conditions, when the impact of the MWR becomes stronger.

The spatio-temporal variability of integrated water vapour (IWV) on small scales of less than 10 km and hours is assessed with data from the 2 months of the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE). The statistical intercomparison of the unique set of observations during HOPE (microwave radiometer (MWR), Global Positioning System (GPS), sun photometer, radiosondes, Raman lidar, infrared and near-infrared Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellites Aqua and Terra) measuring close together reveals a good agreement in terms of random differences (standard deviation &leq;1 kg m−2) and correlation coefficient (&geq; 0.98). The exception is MODIS, which appears to suffer from insufficient cloud filtering. For a case study during HOPE featuring a typical boundary layer development, the IWV variability in time and space on scales of less than 10 km and less than 1 h is investigated in detail. For this purpose, the measurements are complemented by simulations with the novel ICOsahedral Nonhydrostatic modelling framework (ICON), which for this study has a horizontal resolution of 156 m. These runs show that differences in space of 3–4 km or time of 10–15 min induce IWV variabilities on the order of 0.4 kg m−2. This model finding is confirmed by observed time series from two MWRs approximately 3 km apart with a comparable temporal resolution of a few seconds. Standard deviations of IWV derived from MWR measurements reveal a high variability (> 1 kg m−2) even at very short time scales of a few minutes. These cannot be captured by the temporally lower-resolved instruments and by operational numerical weather prediction models such as COSMO-DE (an application of the Consortium for Small-scale Modelling covering Germany) of Deutscher Wetterdienst, which is included in the comparison. However, for time scales larger than 1 h, a sampling resolution of 15 min is sufficient to capture the mean standard deviation of IWV. The present study shows that instrument sampling plays a major role when climatological information, in particular the mean diurnal cycle of IWV, is determined.

Aerosol signatures observed by ceilometers are frequently used to derive mixing-layer height (MLH) which is an essential variable for air quality modelling. However, Doppler wind lidar measurements of vertical velocity can provide a more direct estimation of MLH via simple thresholding. A case study reveals difficulties in the aerosol-based MLH retrieval during transition times when the mixing layer builds up in the morning and when turbulence decays in the afternoon. The difficulties can be explained by the fact that the aerosol distribution is related to the history of the mixing process and aerosol characteristics are modified by humidification. The results of the case study are generalized by evaluating one year of joint measurements by a Vaisala CT25K and a HALO Photonics Streamline wind lidar. On average the aerosol-based retrieval gives higher MLH than the wind lidar with an overestimation of MLH by about 300 m (600 m) in the morning (late afternoon). Also, the daily aerosol-based maximum MLH is larger and occurs later during the day and the average morning growth rates are smaller than those derived from the vertical wind. In fair weather conditions classified by less than 4 octa cloud cover the mean diurnal cycle of cloud base height corresponds well to the mixing-layer height showing potential for a simplified MLH estimation.

Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals. The present work discusses the potential of G band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow.

Ground-based microwave radiometers (MWR) are becoming more and more common for remotely sensing the atmospheric temperature and humidity profile as well as path-integrated cloud liquid water content. The calibration accuracy of the state-of-the-art MWR HATPRO-G2 (Humidity And Temperature Profiler – Generation 2) was investigated during the second phase of the Radiative Heating in Underexplored Bands Campaign (RHUBC-II) in northern Chile (5320 m above mean sea level, 530 hPa) conducted by the Atmospheric Radiation Measurement (ARM) program conducted between August and October 2009. This study assesses the quality of the two frequently used liquid nitrogen and tipping curve calibrations by performing a detailed error propagation study, which exploits the unique atmospheric conditions of RHUBC-II. Both methods are known to have open issues concerning systematic offsets and calibration repeatability. For the tipping curve calibration an uncertainty of ±0.1 to ±0.2 K (K-band) and ±0.6 to ±0.7 K (V-band) is found. The uncertainty in the tipping curve calibration is mainly due to atmospheric inhomogeneities and the assumed air mass correction for the Earth curvature. For the liquid nitrogen calibration the estimated uncertainty of ±0.3 to ±1.6 K is dominated by the uncertainty of the reflectivity of the liquid nitrogen target. A direct comparison between the two calibration techniques shows that for six of the nine channels that can be calibrated with both methods, they agree within the assessed uncertainties. For the other three channels the unexplained discrepancy is below 0.5 K. Systematic offsets, which may cause the disagreement of both methods within their estimated uncertainties, are discussed.

More so than the traditional fixed radiometers, the scanning radiometer requires a careful design to ensure high quality measurements. Here the impact of the radiometer characteristics (e.g., antenna beam width and receiver bandwidth) and atmospheric propagation (e.g. curvature of the Earth and vertical gradient of refractive index) on scanning radiometer measurements are presented. A forward radiative transfer model that includes all these effects to represent the instrument measurements is used to estimate the biases. These biases are estimated using differences between the measurement with and without these characteristics for three commonly used frequency bands: K, V and W-band. The receiver channel bandwidth errors are less important in K-band and W-band. Thus, the use of a wider bandwidth to improve detection at low signal-to-noise conditions is acceptable at these frequencies. The biases caused by omitting the antenna beam width in measurement simulations are larger than those caused by omitting the receiver bandwidth, except for V-band where the bandwidth may be more important in the vicinity of absorption peaks. Using simple regression algorithms, the effects of the bandwidth and beam width biases in liquid water path, integrated water vapour, and temperature are also examined. The largest errors in liquid water path and integrated water vapour are associated with the beam width errors.

The motivation of this study is to verify theoretical expectations placed on ground-based microwave radiometer (MWR) techniques and to confirm whether they are suitable for supporting key missions of national weather services, such as timely and accurate weather advisories and warnings. We evaluate reliability and accuracy of atmospheric temperature profiles retrieved continuously by the microwave profiler system HATPRO (Humidity And Temperature PROfiler) operated at the aerological station of Payerne (MeteoSwiss) in the time period August 2006–December 2009. Assessment is performed by comparing temperatures from the radiometer against temperature measurements from a radiosonde accounting for a total of 2107 quality-controlled all-season cases. In the evaluated time period, the MWR delivered reliable temperature profiles in 86% of all-weather conditions on a temporal resolution of 12–13 min. Random differences between MWR and radiosonde are down to 0.5 K in the lower boundary layer and increase to 1.7 K at 4 km height. The differences observed between MWR and radiosonde in the lower boundary layer are similar to the differences observed between the radiosonde and another in-situ sensor located on a close-by 30 m tower. Temperature retrievals from above 4 km contain less than 5% of the total information content of the measurements, which makes clear that this technique is mainly suited for continuous observations in the boundary layer. Systematic temperature differences are also observed throughout the retrieved profile and can account for up to ±0.5 K. These errors are due to offsets in the measurements of the microwave radiances that have been corrected for in data post-processing and lead to nearly bias-free overall temperature retrievals. Different reasons for the radiance offsets are discussed, but cannot be unambiguously determined retrospectively. Monitoring and, if necessary, corrections for radiance offsets as well as a real-time rigorous automated data quality control are mandatory for microwave profiler systems that are designated for operational temperature profiling. In the analysis of a subset of different atmospheric situations, it is shown that lifted inversions and data quality during precipitation present the largest challenges for operational MWR temperature profiling.

Ground-based microwave radiometers (MWR) are becoming more and more common for remotely sensing the atmospheric temperature and humidity profile, as well as path integrated cloud liquid water content. The calibration accuracy of the state-of-the-art MWR HATPRO-G2 (Humidity And Temperature Profiler - Generation 2) was investigated during the second phase of the Radiative Heating in Underexplored Bands Campaign (RHUBC-II) in Northern Chile (5320ma.m.s.l. - above mean sea level, 530 hPa) conducted by the the Atmospheric Radiation Measurement (ARM) program conducted between August and October 2009. This study assesses the quality of the two frequently used liquid nitrogen and tipping curve calibrations by performing a detailed error propagation study by exploiting the unique atmospheric conditions of RHUBCII. Both methods are known to have open issues concerning systematic offsets and calibration repeatability. For the tipping curve calibration an uncertainty of 0.2-0.4K (K-band) and 1.0-1.2K (V-band) is found. The uncertainty in the tipping curve calibration is mainly due the atmospheric inhomogeneities. For the liquid nitrogen calibration the estimated uncertainty of 0.5-0.9 K is dominated by the uncertainty of the reflectivity of the liquid nitrogen target. Systematic offsets, which may cause the disagreement of both methods within their estimated uncertainties, are discussed. [ABSTRACT FROM AUTHOR]

A deeper understanding of how clouds will respond to a warming climate is one of the outstanding challenges in climate science. Uncertainties in the response of clouds, and particularly shallow clouds, have been identified as the dominant source of the discrepancy in model estimates of equilibrium climate sensitivity. As the community gains a deeper understanding of the many processes involved, there is a growing appreciation of the critical role played by fluctuations in water vapor and the coupling of water vapor and atmospheric circulations. Reduction of uncertainties in cloud-climate feedbacks and convection initiation as well as improved understanding of processes governing these effects will result from profiling of water vapor in the lower troposphere with improved accuracy and vertical resolution compared to existing airborne and space-based measurements. This paper highlights new technologies and improved measurement approaches for measuring lower tropospheric water vapor and their expected added value to current observations. Those include differential absorption lidar and radar, microwave occultation between low-Earth orbiters, and hyperspectral microwave remote sensing. Each methodology is briefly explained, and measurement capabilities as well as the current technological readiness for aircraft and satellite implementation are specified. Potential synergies between the technologies are discussed, actual examples hereof are given, and future perspectives are explored. Based on technical maturity and the foreseen near-mid-term development path of the various discussed measurement approaches, we find that improved measurements of water vapor throughout the troposphere would greatly benefit from the combination of differential absorption lidar focusing on the lower troposphere with passive remote sensors constraining the upper-tropospheric humidity., (© The Author(s) 2017.)