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We use Doppler lidar wind profiles from six locations around the globe to evaluate the wind profile forecasts in the boundary layer generated by the operational global Integrated Forecast System (IFS) from the European Centre for Medium-range Weather Forecasts (ECMWF). The six locations selected cover a variety of surfaces with different characteristics (rural, marine, mountainous urban, and coastal urban). We first validated the Doppler lidar observations at four locations by comparison with co-located radiosonde profiles to ensure that the Doppler lidar observations were of sufficient quality. The two observation types agree well, with the mean absolute error (MAE) in wind speed almost always less than 1 m s -1. Large deviations in the wind direction were usually only seen for low wind speeds and are due to the wind direction uncertainty increasing rapidly as the wind speed tends to zero. Time–height composites of the wind evaluation with 1 h resolution were generated, and evaluation of the model winds showed that the IFS model performs best over marine and coastal locations, where the mean absolute wind vector error was usually less than 3 m s -1 at all heights within the boundary layer. Larger errors were seen in locations where the surface was more complex, especially in the wind direction. For example, in Granada, which is near a high mountain range, the IFS model failed to capture a commonly occurring mountain breeze, which is highly dependent on the sub-grid-size terrain features that are not resolved by the model. The uncertainty in the wind forecasts increased with forecast lead time, but no increase in the bias was seen. At one location, we conditionally performed the wind evaluation based on the presence or absence of a low-level jet diagnosed from the Doppler lidar observations. The model was able to reproduce the presence of the low-level jet, but the wind speed maximum was about 2 m s -1 lower than observed. This is attributed to the effective vertical resolution of the model being too coarse to create the strong gradients in wind speed observed. Our results show that Doppler lidar is a suitable instrument for evaluating the boundary layer wind profiles in atmospheric models. [ABSTRACT FROM AUTHOR]

We use Doppler lidar wind profiles from six locations around the globe to evaluate the wind profile forecasts in the boundary layer generated by the operational global integrated forecast system (IFS) from the European Centre for Mediumrange Weather Forecasts (ECMWF). The six locations selected cover a variety of surfaces with different characteristics (rural, marine, mountainous urban, coastal urban). We first validated the Doppler lidar observations at four locations by comparison with collocated radiosonde profiles to ensure that the Doppler lidar observations were of sufficient quality. The two observation types agree well, with the mean absolute error (MAE) in wind speed almost always less than 1 ms-1. Large deviations in the wind direction were usually seen only for low wind speeds, and is due to the wind direction uncertainty increasing rapidly as the wind speed tends to zero. Time-height composites of the wind evaluation with one-hour resolution were generated and evaluation of the model winds showed that the IFS model performs best over marine and coastal locations, where the mean absolute wind vector error was usually less than 3 ms-1 at all heights within the boundary layer. Larger errors were seen in locations where the surface was more complex, especially in the wind direction. For example, in Granada, which is near a high mountain range, the IFS model failed to capture a commonly occurring mountain breeze, which is highly dependent on the sub grid-size terrain features that are not resolved by the model. The uncertainty in the wind forecasts increased with forecast lead time, but no increase in the bias was seen. At one location, we conditionally performed the wind evaluation based on the presence or absence of a low-level-jet diagnosed from the Doppler lidar observations. The model was able to reproduce the presence of the low-level-jet but the wind speed maximum was about 2 ms-1 lower than observed. This is attributed to the effective vertical resolution of the model being too coarse to create the strong gradients in wind speed observed. Our results show that Doppler lidar is a suitable instrument for evaluating the boundary layer wind profiles in atmospheric models. [ABSTRACT FROM AUTHOR]

It has been demonstrated that HALO Photonics Doppler lidars (denoted HALO Doppler lidar hereafter) have the capability for retrieving the aerosol particle depolarization ratio at a wavelength of 1565 nm. For these lidars operating at such a long wavelength, the retrieval quality depends to a large degree on an accurate representation of the instrumental noise floor and the performance of the internal polarizer, whose stability has not yet been assessed for long-term operation. Here, we use 4 years of measurements at four sites in Finland to investigate the long-term performance of HALO Doppler lidars, focusing on aerosol particle depolarization ratio retrieval. The instrumental noise level, represented by noise-only signals in aerosol- and hydrometeor-free regions, shows stable performance for most instruments but clear differences between individual instruments. For all instruments, the polarizer bleed-through evaluated at liquid cloud base remains reasonably constant at approximately 1 % with a standard deviation of less than 1 %. We find these results to be sufficient for long-term aerosol particle depolarization ratio measurements and proceed to analyse the seasonal and diurnal cycles of the aerosol particle depolarization ratio in different environments in Finland, including in the Baltic Sea archipelago, a boreal forest and rural sub-arctic. To do so, we further develop the background correction method and construct an algorithm to distinguish aerosol particles from hydrometeors. The 4-year averaged aerosol particle depolarization ratio ranges from 0.07 in sub-arctic Sodankylä to 0.13 in the boreal forest in Hyytiälä. At all sites, the aerosol particle depolarization ratio is found to peak during spring and early summer, even exceeding 0.20 at the monthly-mean level, which we attribute to a substantial contribution from pollen. Overall, our observations support the long-term usage of HALO Doppler lidar depolarization ratio measurements, including detection of aerosols that may pose a safety risk for aviation. [ABSTRACT FROM AUTHOR]

Over two years of meteorological observations from Utö, a small island in the Finnish outer archipelago in the Baltic Sea, were used to investigate the occurrence and characteristics of low-level jets (LLJs) and the diurnal and seasonal variations in these properties. An objective LLJ identification algorithm that is suitable for high-temporal-and-vertical-resolution Doppler lidar data was created and applied to wind profiles obtained from a combination of Doppler lidar data and two-dimensional sonic anemometer observations. This algorithm was designed to identify coherent LLJ structures and requires that they persist for at least 1 h. The long-term mean LLJ frequency of occurrence at Utö was 12%, the mean LLJ wind speed was 11.6 m s−1, and the vast majority of identified LLJs occurred below 150 m above ground level. The LLJ frequency of occurrence was much higher during summer (21%) and spring (18%) than in autumn (8%) and winter (3%). During winter and spring, the LLJ frequency of occurrence is evenly distributed throughout the day. In contrast, the LLJ frequency of occurrence peaks at night (1900-0100 UTC) during summer and during the evening hours (1700-1900 UTC) in autumn. The highest and strongest LLJs come from the southwest, which is also the predominant LLJ direction in all seasons. LLJs below 100 m are common in spring and summer, are weaker, and do not show a strong directional dependence. [ABSTRACT FROM AUTHOR]

The article focuses on a study related to a field campaign the Biogenic Aerosols—Effects on Clouds and Climate (BAECC) to explain the impact on cloud and climate by biogenic aerosols. Topics discussed include BAECC experiment provided Station for Measuring Forest Ecosystem-Atmosphere Relations (SMEAR-II) observation record to the impact of biogenic aerosol on climate in Hyytiälä, Finland, the annual-mean global temperature have biogeophysical effect due to boreal forests.

Cloud retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the satellites Terra and Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument aboard the Suomi-NPP satellite are evaluated using a combination of ground-based instruments providing vertical profiles of clouds. The ground-based measurements are obtained from the Atmospheric Radiation Measurement (ARM) programme mobile facility, which was deployed in Hyytiälä, Finland, between February and September 2014 for the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) campaign. The satellite cloud parameters cloud top height (CTH) and liquid water path (LWP) are compared with ground-based CTH obtained from a cloud mask created using lidar and radar data and LWP acquired from a multi-channel microwave radiometer. Clouds from all altitudes in the atmosphere are investigated. The clouds are diagnosed as single or multiple layer using the ground-based cloud mask. For single-layer clouds, satellites overestimated CTH by 326 m (14 %) on average. When including multilayer clouds, satellites underestimated CTH by on average 169 m (5.8 %). MODIS collection 6 overestimated LWP by on average 13 g m−2 (11 %). Interestingly, LWP for MODIS collection 5.1 is slightly overestimated by Aqua (4.56 %) but is underestimated by Terra (14.3 %). This underestimation may be attributed to a known issue with a drift in the reflectance bands of the MODIS instrument on Terra. This evaluation indicates that the satellite cloud parameters selected show reasonable agreement with their ground-based counterparts over Finland, with minimal influence from the large solar zenith angle experienced by the satellites in this high-latitude location. [ABSTRACT FROM AUTHOR]

It has been demonstrated that Halo Doppler lidars have the capability for retrieving the aerosol particle linear depolarization ratio at a wavelength of 1565 nm. However, the retrieval depends on an accurate representation of the instrumental noise floor and the performance of the internal polarizer, whose stability have not been assessed in long-term operation. Here, we use four years of measurements at four sites in Finland to investigate the long-term performance of Halo Doppler lidars for aerosol particle depolarization ratio retrieval. The instrumental noise level, represented by noise-only signals in aerosol- and hydrometeor-free regions, shows stable performance for most instruments, but clear differences between individual instruments. For all instruments, the polarizer bleed-through evaluated at liquid cloud base remains reasonably constant at approximately 1% with a standard deviation less than 1%. We find these results sufficient for long-term aerosol particle linear depolarization ratio measurements and proceed to analyse the seasonal and diurnal cycles of the aerosol particle depolarization ratio in different environments in Finland including in the Baltic Sea archipelago, boreal forest and rural subarctic. To do so, we further develop the background correction method and construct an algorithm to distinguish aerosol particles from hydrometeors. The four-year averaged aerosol particle depolarization ratio ranges from 0.07 in sub-arctic Sodankylä to 0.13 in the boreal forest in Hyytiälä. At all sites, the aerosol particle depolarization ratio is found to peak during spring and early summer, even exceeding 0.20 at the monthly-mean level, which we attribute to a substantial contribution from pollen. Overall, our observations support the long-term usage of Halo Doppler lidar depolarization ratio including detection of aerosols that may pose a safety risk for aviation. [ABSTRACT FROM AUTHOR]

A method of estimating dissipation rates from a vertically pointing Doppler lidar with high temporal and spatial resolution has been evaluated by comparison with independent measurements derived from a balloon-borne sonic anemometer. This method utilizes the variance of the mean Doppler velocity from a number of sequential samples and requires an estimate of the horizontal wind speed. The noise contribution to the variance can be estimated from the observed signal-to-noise ratio and removed where appropriate. The relative size of the noise variance to the observed variance provides a measure of the confidence in the retrieval. Comparison with in situ dissipation rates derived from the balloon-borne sonic anemometer reveal that this particular Doppler lidar is capable of retrieving dissipation rates over a range of at least three orders of magnitude. This method is most suitable for retrieval of dissipation rates within the convective well-mixed boundary layer where the scales of motion that the Doppler lidar probes remain well within the inertial subrange. Caution must be applied when estimating dissipation rates in more quiescent conditions. For the particular Doppler lidar described here, the selection of suitably short integration times will permit this method to be applicable in such situations but at the expense of accuracy in the Doppler velocity estimates. The two case studies presented here suggest that, with profiles every 4 s, reliable estimates of ε can be derived to within at least an order of magnitude throughout almost all of the lowest 2 km and, in the convective boundary layer, to within 50%. Increasing the integration time for individual profiles to 30 s can improve the accuracy substantially but potentially confines retrievals to within the convective boundary layer. Therefore, optimization of certain instrument parameters may be required for specific implementations. [ABSTRACT FROM AUTHOR]

Stratocumulus is one of the most common cloud types globally, with a profound effect on the earth’s radiation budget, and the drizzle process is fundamental in understanding the evolution of these boundary layer clouds. In this paper a combination of 94-GHz Doppler radar and backscatter lidar is used to investigate the microphysical properties of drizzle falling below the base of stratocumulus clouds. The ratio of the radar to lidar backscatter power is proportional to the fourth power of mean size, and so potentially it can provide an accurate size estimate. Information about the shape of the drop size distribution is then inferred from the Doppler spectral width. The algorithm estimates vertical profiles of drizzle parameters such as liquid water content, liquid water flux, and vertical air velocity, assuming that the drizzle size spectrum may be represented by a gamma distribution. The depletion time scale of cloud liquid water through the drizzle process can be estimated when the liquid water path of the cloud is available from microwave radiometers, and observations suggest that this time scale varies from a few days in light drizzle to a few hours in strong drizzle events. Radar and lidar observations from Chilbolton (in southern England) and aircraft size spectra taken during the Atlantic Stratocumulus Transition Experiment have both been used to derive the following power-law relationship between liquid water flux (LWF) (g m-2 s-1) and radar reflectivity (Z) (mm6 m-3): LWF = 0.0093Z0.69. This relation is valid for frequencies up to 94 GHz and therefore would allow a forthcoming spaceborne radar to measure liquid water flux around the globe to within a factor of 2 for values of Z above -20 dBZ. [ABSTRACT FROM AUTHOR]

In this paper a technique for autocalibration of a cloud lidar is demonstrated. It is shown that the lidar extinction-to-backscatter ratio derived from integrated backscatter for stratocumulus is, in the absence of drizzle, constrained to a theoretical value of 18.8 &plusm; 0.8 sr at a wavelength of 905 nm. The lidar can be calibrated by scaling the backscatter signal so that the observed lidar ratio matches the theoretical value when suitable conditions of stratocumulus are available. For a beam divergence of 1–1.5 mrad, multiple scattering introduces an uncertainty of about 10% into the calibration and for a narrow-beam ground-based lidar, with negligible multiple scattering, calibration may be possible to better than 5%. Some examples of the mean lidar ratio of supercooled liquid water layers and ice clouds inferred using this technique are also shown. [ABSTRACT FROM AUTHOR]

The atmospheric molecular number density can be obtained from atmospheric temperature and pressure profiles and is a significant input parameter for the inversion of lidar measurements. When measurements of vertical profiles of temperature and pressure are not available, atmospheric models are typically considered a valid alternative option. This paper investigates the influence of different atmospheric models (forecast and reanalysis) on the retrieval of aerosol optical properties (extinction and backscatter coefficients) by applying Raman and elastic-only methods to lidar measurements, to assess their use in lidar data processing. In general, reanalyzes are more accurate than forecasts, but, typically, they are not delivered in time for allowing near-real-time lidar data analysis. However, near-real-time observation is crucial for real-time monitoring of the environment and meteorological studies. The forecast models used in the paper are provided by the Integrated Forecasting System operated by the European Centre for Medium-Range Weather Forecasts (IFS_ECMWF) and the Global Data Assimilation System (GDAS), whereas the reanalysis model is obtained from the fifth-generation European Centre for Medium-Range Weather Forecasts ReAnalysis v5 (ERA5). The lidar dataset consists of measurements collected from four European Aerosol Research Lidar Network (EARLINET) stations during two intensive measurement campaigns and includes more than 200 cases at wavelengths of 355 nm, 532 nm, and 1064 nm. We present and discuss the results and influence of the forecast and reanalysis models in terms of deviations of the derived aerosol optical properties. The results show that the mean relative deviation in molecular number density is always below ±3%, while larger deviations are shown in the derived aerosol optical properties, and the size of the deviation depends on the retrieval method together with the different wavelengths. In general, the aerosol extinction coefficient retrieval is more dependent on the model used than the aerosol backscatter retrievals are. The larger influence on the extinction retrieval is mainly related to the deviation in the gradient of the temperature profile provided by forecast and reanalysis models rather than the absolute deviation of the molecular number density. We found that deviations in extinction were within ±5%, with a probability of 83% at 355 nm and 60% at 532 nm. Moreover, for aerosol backscatter coefficient retrievals, different models can have a larger impact when the backscatter coefficient is retrieved with the elastic method than when the backscatter coefficient is calculated using the Raman method at both 355 nm and 532 nm. In addition, the atmospheric aerosol load can also influence the deviations in the aerosol extinction and backscatter coefficients, showing a larger impact under low aerosol loading scenarios. [ABSTRACT FROM AUTHOR]

Aerosol emissions in South Asia are large. The emitted aerosols can travel significant distances and, during the Asian southwest monsoon especially, are prone to modification through cloud processing and wet scavenging while being transported. The scale of emissions and transport means that the global climate impact of these aerosols are sensitive to modification en route, but the process-level understanding is still largely lacking. In this study, we analyse long-term aerosol data measured at an observatory established in Hanimaadhoo, Republic of Maldives, to investigate the long-term properties of aerosols over the Indian Ocean as well as to understand the effect of precipitation on the aerosol particle size distribution during long-range transport. The observatory location is ideal because it is a receptor site with little local influence, and, depending on the season, receives either polluted air masses coming from the Indian subcontinent or clean marine air masses from the Indian Ocean. We analysed the sub-micron particle number size distribution measured during the years 2004-2008, and 2014 2017, and this is the first inter-seasonal longterm study of the sub-micron aerosol features in the region. The aerosol origin and its relative exposure to wet scavenging during long-range transport were analysed using back-trajectory analysis from HYSPLIT. By comparing aerosol measurements to precipitation along its transport, this study shows that there is a substantial change in particle number size distributions and concentrations depending on the amount of rainfall during transport. During the southwest monsoon season, the aerosol size distribution was notably bimodal and total particle concentrations clearly reduced in comparison with the prevailing aerosol size distribution during the northeast monsoon season. Precipitation during transport usually corresponded with a greater reduction in accumulation mode concentrations than for smaller sizes, and the shape of the median size distribution showed a clear dependence on the trajectory origin and route taken. [ABSTRACT FROM AUTHOR]

Commercially available Doppler lidars have now been proven to be efficient tools for studying winds and turbulence in the planetary boundary layer. However, in many cases low signal-to-noise ratio is still a limiting factor for utilising measurements by these devices. Here, we present a novel post-processing algorithm for Halo Stream Line Doppler lidars, which enables an improvement in sensitivity of a factor of 5 or more. This algorithm is based on improving the accuracy of the instrumental noise floor and it enables longer integration times or averaging of high temporal resolution data to be used to obtain signals down to -32 dB. While this algorithm does not affect the measured radial velocity, it improves the accuracy of radial velocity uncertainty estimates and consequently the accuracy of retrieved turbulent properties. Field measurements using three different Halo Doppler lidars deployed in Finland, Greece and South Africa demonstrate how the new post-processing algorithm increases data availability for turbulent retrievals in the planetary boundary layer, improves detection of high-altitude cirrus clouds and enables the observation of elevated aerosol layers. [ABSTRACT FROM AUTHOR]

Commercially available Doppler lidars have now been proven to be efficient tools for studying winds and turbulence in the planetary boundary layer. However, in many cases low signal-to-noise ratio is still a limiting factor for utilising measurements by these devices. Here, we present a novel postprocessing algorithm for Halo Streamline Doppler lidars, which enables an improvement in sensitivity of a factor of five or more. This algorithm is based on improving the accuracy of the instrumental noise floor and it enables using longer integration times or averaging of high temporal resolution data to obtain signals down to -32 dB. While this algorithm does not affect the measured radial velocity, it improves the accuracy of radial velocity uncertainty estimates and consequently the accuracy of retrieved turbulent properties. Field measurements with three different Halo Doppler lidars deployed in Finland, Greece and South Africa demonstrate how the new post-processing algorithm increases data availability for turbulent retrievals in the planetary boundary layer, improves detection of high-altitude cirrus clouds, and enables the observation of elevated aerosol layers. [ABSTRACT FROM AUTHOR]

A new methodology is proposed for scaling Doppler lidar observations of wind gusts to make them comparable with those observed at a meteorological mast. Doppler lidars can then be used to measure wind gusts in regions and heights where traditional meteorological mast measurements are not available. This novel method also provides estimates for wind gusts at arbitrary gust durations, including those shorter than the temporal resolution of the Doppler lidar measurements. The input parameters for the scaling method are the measured wind-gust speed as well as the mean and standard deviation of the horizontal wind speed. The method was tested using WindCube V2 Doppler lidar measurements taken next to a 100 m high meteorological mast. It is shown that the method can provide realistic Doppler lidar estimates of the gust factor, i.e. the ratio of the wind-gust speed to the mean wind speed. The method reduced the bias in the Doppler lidar gust factors from 0.07 to 0.03 and can be improved further to reduce the bias by using a realistic estimate of turbulence. Wind gust measurements are often prone to outliers in the time series, because they represent the maximum of a (moving-averaged) horizontal wind speed. To assure the data quality in this study, we applied a filtering technique based on spike detection to remove possible outliers in the Doppler lidar data. We found that the spike detection-removal method clearly improved the wind-gust measurements, both with and without the scaling method. Spike detection also outperformed the traditional Doppler lidar quality assurance method based on carrier-to-noise ratio, by removing additional unrealistic outliers present in the time series. [ABSTRACT FROM AUTHOR]

The atmospheric boundary layer (ABL) defines the volume of air adjacent to the Earth's surface for the dilution of heat, moisture, and trace substances. Quantitative knowledge on the temporal and spatial variations in the heights of the ABL and its sub-layers is still scarce, despite their importance for a series of applications (including, for example, air quality, numerical weather prediction, greenhouse gas assessment, and renewable energy production). Thanks to recent advances in ground-based remote-sensing measurement technology and algorithm development, continuous profiling of the entire ABL vertical extent at high temporal and vertical resolution is increasingly possible. Dense measurement networks of autonomous ground-based remote-sensing instruments, such as microwave radiometers, radar wind profilers, Doppler wind lidars or automatic lidars and ceilometers are hence emerging across Europe and other parts of the world. This review summarises the capabilities and limitations of various instrument types for ABL monitoring and provides an overview on the vast number of retrieval methods developed for the detection of ABL sub-layer heights from different atmospheric quantities (temperature, humidity, wind, turbulence, aerosol). It is outlined how the diurnal evolution of the ABL can be monitored effectively with a combination of methods, pointing out where instrumental or methodological synergy are considered particularly promising. The review highlights the fact that harmonised data acquisition across carefully designed sensor networks as well as tailored data processing are key to obtaining high-quality products that are again essential to capture the spatial and temporal complexity of the lowest part of the atmosphere in which we live and breathe. [ABSTRACT FROM AUTHOR]

Data collected over a period of 18 months (December 2019–May 2021) at the Bucharest–Măgurele Cloudnet station were analysed for the first time to determine the macrophysical and microphysical cloud properties over this site. A total number of 1,327,680 vertical profiles containing the target classification based on the Cloudnet algorithm were analysed, of which 1,077,858 profiles contained hydrometeors. The highest number of profiles with hydrometeors (>60%) was recorded in December 2020, with hydrometeors being observed mainly below 5 km. Above 5 km, the frequency of occurrence of hydrometeors was less than <20%. Based on the initial Cloudnet target classification, a cloud classification scheme was implemented. Clouds were more frequently observed during winter compared with other seasons (45% of all profiles). Ice clouds were the most frequent type of cloud (468,463 profiles) during the study period, followed by mixed phases (220,280 profiles) and mixed phased precipitable clouds (164,868 profiles). The geometrical thickness varied from a median value of 244 m for liquid clouds during summer to 3362 m for mix phased precipitable clouds during spring. [ABSTRACT FROM AUTHOR]

Urban boundary layer characterization is currently a challenging and relevant issue, because of its role in weather and air quality modelling and forecast. In many cities, the effect of complex topography at local scale makes this modelling even more complicated. This is the case of mid-latitude urban areas located in typical basin topographies, which usually present low winds and high turbulence within the atmospheric boundary layer (ABL). This study focuses on the analysis of the first ever measurements of wind with high temporal and vertical resolution throughout the ABL over a medium-sized city surrounded by mountains in southern Spain. These measurements have been gathered with a scanning Doppler lidar system and analyzed using the Halo lidar toolbox processing chain developed at the Finnish Meteorological Institute. We have used the horizontal wind product and the ABL turbulence classification product to carry out a statistical study using a two-year database. The data availability in terms of maximum analyzed altitudes for statistically significant results was limited to around 1000–1500 m above ground level (a.g.l.) due to the decreasing signal intensity with height that also depends on aerosol load. We have analyzed the differences and similarities in the diurnal evolution of the horizontal wind profiles for different seasons and their modelling with Weibull and von Mises probability distributions, finding a general trend of mean daytime wind from the NW with mean speeds around 3–4 m/s at low altitudes and 6–10 m/s at higher altitudes, and weaker mean nocturnal wind from the SE with similar height dependence. The highest speeds were observed during spring, and the lowest during winter. Finally, we studied the turbulent sources at the ABL with temporal (for each hour of the day) and height resolution. The results show a clear convective activity during daytime at altitudes increasing with time, and a significant wind-shear-driven turbulence during night-time. [ABSTRACT FROM AUTHOR]

The atmospheric boundary layer (ABL) height defines the volume of air within which heat, moisture and pollutants released at the Earth's surface are rapidly diluted. Despite the importance for air quality interpretation, numerical weather prediction, greenhouse gas assessment and renewable energy applications, amongst others, quantitative knowledge on the temporal and spatial variation in ABL height is still scarce. With continuous profiling of the entire ABL vertical extent at high temporal and vertical resolution now increasingly possible due to recent advances in ground-based remote sensingmeasurement technology and algorithm development, there are also dense measurement networks emerging across Europe and other parts of the world. To effectively monitor the spatial and temporal evolution of the ABL continuously at continent-scale, harmonised operations and data processing are key. Autonomous ground-based remote sensing instruments, such as microwave radiometers, radar wind profilers, Doppler wind lidars or automatic lidars and ceilometers, each offer different capabilities. The overarching objective of this review is to emphasize how these instruments are best exploited with informed network design, algorithm implementation, and data interpretation. A summary of the capability and limitations of each instrument type is provided together with a review of the vast number of retrieval methods developed for ABL height detection from different atmospheric quantities (temperature, humidity, wind, turbulence, aerosol). It is outlined how the diurnal evolution of the ABL can be monitored effectively with a combination of methods, highlighting where instrument or methodological synergy promise to be particularly valuable. To demonstrate the vast potential of increased ABL monitoring efforts, long-term observational studies are reviewed summarising our current understanding of ABL height variations. The review emphasizes that harmonised data acquisition and careful data processing are key to obtaining high-quality products, which are essential to capture the spatial and temporal complexity of the lowest part of the atmosphere in which we live and breathe. [ABSTRACT FROM AUTHOR]

Atmospheric icing can cause severe damage and danger for many different sectors of society, and accurate forecasts of icing can help mitigate this. The aim of the study is to demonstrate how new ceilometer-based icing observations can be used in icing model verification. The study focuses on icing in the lowest 2 km of the atmosphere. The lowest 400 m of the atmosphere is essential for wind energy production and electricity power lines, while the higher elevations are essential from the aviation point of view. For aviation, the most risky situations are take-offs and landings. The ceilometer observations provide a new way to investigate atmospheric icing. Ceilometers provide vertical profiles of clouds which can be further processed in order to identify in-cloud icing conditions. The new type of ceilometer-based icing observations enables more detailed verification of icing forecasts both in the vertical and in terms of geographical location. Overall, the model shows good skill in predicting clear-sky situations. The verification results show that the icing model performs better for inland areas than for coastal areas, which is attributed to the tendency of the model to forecast clouds, and in-cloud icing, at higher altitudes than observed. [ABSTRACT FROM AUTHOR]

The atmospheric boundary layer (BL) is the atmospheric layer coupled to the Earth's surface at relatively short timescales. A key quantity is the BL depth, which is important in many applied areas of weather and climate such as air-quality forecasting. Studying BLs in climates and biomes across the globe is important, particularly in the under-sampled southern hemisphere. The present study is based on a grazed grassland-savannah area in northwestern South Africa during October 2012–August 2014. Ceilometers are probably the cheapest method for measuring continuous aerosol profiles up to several kilometers above ground and are thus an ideal tool for long-term studies of BLs. A ceilometer-estimated BL depth is based on profiles of attenuated backscattering coefficients from atmospheric aerosols; the sharpest drop often occurs at BL top. Based on this, we developed a new method for layer detection that we call the signal-limited layer method. The new algorithm was applied to ceilometer profiles which thus classified BL into classic regime types: daytime convective mixing, and a double layer at night of surface-based stable with a residual layer above it. We employed wavelet fitting to increase successful BL estimation for noisy profiles. The layer-detection algorithm was supported by an eddy-flux station, rain gauges, and manual inspection. Diurnal cycles were often clear, with BL depth detected for 50% of the daytime typically being 1–3 km, and for 80% of the night-time typically being a few hundred meters. Variability was also analyzed with respect to seasons and years. Finally, BL depths were compared with ERA-Interim estimates of BL depth to show reassuring agreement. [ABSTRACT FROM AUTHOR]

The Atmospheric Boundary Layer (ABL) over two middle-latitude rural sites was characterized in terms of mean horizontal wind and turbulence sources using a standard classification methodology based on Doppler lidar. The first location was an irrigated olive orchard in Úbeda (Southern Spain), representing one of the most important crops in the Mediterranean basin and a typical site with Mediterranean climate. The second location was PolWET peatland site in Rzecin (Northwestern Poland), representing one of the largest natural terrestrial carbon storages that have a strong interaction with the climate system. The results showed typical situations for non cloud-topped ABL cases, where ABL is fully developed during daytime due to convection, with high turbulent activity and strong positive skewness indicating frequent and powerful updrafts. The cloud-topped cases showed the strong influence that clouds can have on ABL development, preventing it to reach the same maximum height and introducing top-down movements as an important contribution to mixing. The statistical analysis of turbulent sources allowed for finding a common diurnal cycle for convective mixing at both sites, but nocturnal wind shear driven turbulence with marked differences in its vertical distribution. This analysis demonstrates the Doppler lidar measurements and the classification algorithm strong potential to characterize the dynamics of ABL in its full extent and with high temporal resolution. Moreover, some recommendations for future improvement of the classification algorithm were provided on the basis of the experience gained. • Doppler lidar potential for a comprehensive analysis of boundary layer dynamics. • Turbulence classification algorithm able to follow quick changes in the dynamics. • Results suggest some improvements needed in the turbulence classification mask. [ABSTRACT FROM AUTHOR]

The article focuses on observations of the clouds, aerosols, meteorology, and precipitation in the Marine Boundary Layer on Graciosa Island in the Azores. It states Graciosa witnesses a range of cloud types nearly as diverse as those over the Earth as a whole and comments on the value of the data in improving climatic models. It mentions that global models tested simulated the time-varying vertical cloud distribution and strong precipitation events, while aerosol simulations were less accurate.

This study focuses on the occurrence and type of clouds observed in West Africa, a subject that has been neither much documented nor quantified. It takes advantage of data collected above Niamey, Niger, in 2006 with the Atmospheric Radiation Measurement (ARM) Mobile Facility. A survey of cloud characteristics inferred from ground measurements is presented with a focus on their seasonal evolution and diurnal cycle. Four types of clouds are distinguished: high-level clouds, deep convective clouds, shallow convective clouds, and midlevel clouds. A frequent occurrence of the latter clouds located at the top of the Saharan air layer is highlighted. High-level clouds are ubiquitous throughout the period whereas shallow convective clouds are mainly noticeable during the core of the monsoon. The diurnal cycle of each cloud category and its seasonal evolution are investigated. CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO) data are used to demonstrate that these four cloud types (in addition to stratocumulus clouds over the ocean) are not a particularity of the Niamey region and that midlevel clouds are present over the Sahara during most of the monsoon season. Moreover, using complementary datasets, the radiative impact of each type of clouds at the surface level has been quantified in the short- and longwave domains. Midlevel clouds and anvil clouds have the largest impact, respectively, in longwave (about 15 W m−2) and shortwave (about 150 W m−2) radiation. Furthermore, midlevel clouds exert a strong radiative forcing during the spring at a time when the other cloud types are less numerous. [ABSTRACT FROM AUTHOR]

The ability of four operational weather forecast models [ECMWF, Action de Recherche Petite Echelle Grande Echelle model (ARPEGE), Regional Atmospheric Climate Model (RACMO), and Met Office] to generate a cloud at the right location and time (the cloud frequency of occurrence) is assessed in the present paper using a two-year time series of observations collected by profiling ground-based active remote sensors (cloud radar and lidar) located at three different sites in western Europe (Cabauw, Netherlands; Chilbolton, United Kingdom; and Palaiseau, France). Particular attention is given to potential biases that may arise from instrumentation differences (especially sensitivity) from one site to another and intermittent sampling. In a second step the statistical properties of the cloud variables involved in most advanced cloud schemes of numerical weather forecast models (ice water content and cloud fraction) are characterized and compared with their counterparts in the models. The two years of observations are first considered as a whole in order to evaluate the accuracy of the statistical representation of the cloud variables in each model. It is shown that all models tend to produce too many high-level clouds, with too-high cloud fraction and ice water content. The midlevel and low-level cloud occurrence is also generally overestimated, with too-low cloud fraction but a correct ice water content. The dataset is then divided into seasons to evaluate the potential of the models to generate different cloud situations in response to different large-scale forcings. Strong variations in cloud occurrence are found in the observations from one season to the same season the following year as well as in the seasonal cycle. Overall, the model biases observed using the whole dataset are still found at seasonal scale, but the models generally manage to well reproduce the observed seasonal variations in cloud occurrence. Overall, models do not generate the same cloud fraction distributions and these distributions do not agree with the observations. Another general conclusion is that the use of continuous ground-based radar and lidar observations is definitely a powerful tool for evaluating model cloud schemes and for a responsive assessment of the benefit achieved by changing or tuning a model cloud parameterization. [ABSTRACT FROM AUTHOR]

Absolute calibration of cloud radars is very difficult. A new method is proposed for 94/95-GHz radars that exploits the fact that at this frequency, the radar reflectivity factor of rain measured at a range of 250 m is approximately constant at 19 dBZ for rain rates between 3 and 10 mm h[sup –1] , due to the combined effects of extinction and non-Rayleigh scattering. The standard deviation of around 1.5 dB is due to natural variations in the number concentration of drops and is consistent with the variation predicted from theory, but averaging over a number of different rain events over a month or more should be sufficient to reduce the calibration error to less than 1 dB. A thin layer of rainwater on the radomes of the 94-GHz radar at Chilbolton, in southern England, was found to cause a two-way attenuation of between 9 and 14 dB, but it is shown here that the technique may be successfully implemented by operating the radar at a low elevation angle and employing a shelter to keep it dry. Most 94-GHz cloud radars worldwide use the same amplifier, and monitoring the calibration of this radar over a 2-yr period of continuous use reveals a loss of power of around 1 dB in the first year and 10 dB in the second. Frequent calibration is therefore recommended. [ABSTRACT FROM AUTHOR]

CloudSat is a satellite experiment designed to measure the vertical structure of clouds from space. The expected launch of CloudSat is planned for 2004, and once launched, CloudSat will orbit in formation as part of a constellation of satellites (the A-Train) that includes NASA's Aqua and Aura satellites, a NASA–CNES lidar satellite (CALIPSO), and a CNES satellite carrying a polarimeter (PARASOL). A unique feature that CloudSat brings to this constellation is the ability to fly a precise orbit enabling the fields of view of the CloudSat radar to be overlapped with the CALIPSO lidar footprint and the other measurements of the constellation. The precision and near simultaneity of this overlap creates a unique multisatellite observing system for studying the atmospheric processes essential to the hydrological cycle. The vertical profiles of cloud properties provided by CloudSat on the global scale fill a critical gap in the investigation of feedback mechanisms linking clouds to climate. Measuring these profiles requires a combination of active and passive instruments, and this will be achieved by combining the radar data of CloudSat with data from other active and passive sensors of the constellation. This paper describes the underpinning science and general overview of the mission, provides some idea of the expected products and anticipated application of these products, and the potential capability of the A-Train for cloud observations. Notably, the CloudSat mission is expected to stimulate new areas of research on clouds. The mission also provides an important opportunity to demonstrate active sensor technology for future scientific and tactical applications. The CloudSat mission is a partnership between NASA's JPL, the Canadian Space Agency, Colorado State University, the U.S. Air Force, and the U.S. Department of Energy. [ABSTRACT FROM AUTHOR]