Ground-based Remote-sensing Instruments Research Articles

Atmospheric boundary layer height from ground-based remote sensing: a review of capabilities and limitations

Abstract. 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.

Evaluating cloud liquid detection against Cloudnet using cloud radar Doppler spectra in a pre-trained artificial neural network

Abstract. Detection of liquid-containing cloud layers in thick mixed-phase clouds or multi-layer cloud situations from ground-based remote-sensing instruments still poses observational challenges, yet improvements are crucial since the existence of multi-layer liquid layers in mixed-phase cloud situations influences cloud radiative effects, cloud lifetime, and precipitation formation processes. Hydrometeor target classifications such as from Cloudnet that require a lidar signal for the classification of liquid are limited to the maximum height of lidar signal penetration and thus often lead to underestimations of liquid-containing cloud layers. Here we evaluate the Cloudnet liquid detection against the approach of Luke et al. (2010) which extracts morphological features in cloud-penetrating cloud radar Doppler spectra measurements in an artificial neural network (ANN) approach to classify liquid beyond full lidar signal attenuation based on the simulation of the two lidar parameters particle backscatter coefficient and particle depolarization ratio. We show that the ANN of Luke et al. (2010) which was trained under Arctic conditions can successfully be applied to observations at the mid-latitudes obtained during the 7-week-long ACCEPT field experiment in Cabauw, the Netherlands, in 2014. In a sensitivity study covering the whole duration of the ACCEPT campaign, different liquid-detection thresholds for ANN-predicted lidar variables are applied and evaluated against the Cloudnet target classification. Independent validation of the liquid mask from the standard Cloudnet target classification against the ANN-based technique is realized by comparisons to observations of microwave radiometer liquid-water path, ceilometer liquid-layer base altitude, and radiosonde relative humidity. In addition, a case-study comparison against the cloud feature mask detected by the space-borne lidar aboard the CALIPSO satellite is presented. Three conclusions were drawn from the investigation. First, it was found that the threshold selection criteria of liquid-related lidar backscatter and depolarization alone control the liquid detection considerably. Second, all threshold values used in the ANN framework were found to outperform the Cloudnet target classification for deep or multi-layer cloud situations where the lidar signal is fully attenuated within low liquid layers and the cloud radar is able to detect the microphysical fingerprint of liquid in higher cloud layers. Third, if lidar data are available, Cloudnet is at least as good as the ANN. The times when Cloudnet outperforms the ANN in liquid detections are often associated with situations where cloud dynamics smear the imprint of cloud microphysics on the radar Doppler spectra.

Application of the shipborne remote sensing supersite OCEANET for profiling of Arctic aerosols and clouds during <i>Polarstern</i> cruise PS106

Abstract. From 25 May to 21 July 2017, the research vessel Polarstern performed the cruise PS106 to the high Arctic in the region north and northeast of Svalbard. The mobile remote-sensing platform OCEANET was deployed aboard Polarstern. Within a single container, OCEANET houses state-of-the-art remote-sensing equipment, including a multiwavelength Raman polarization lidar PollyXT and a 14-channel microwave radiometer HATPRO (Humidity And Temperature PROfiler). For the cruise PS106, the measurements were supplemented by a motion-stabilized 35 GHz cloud radar Mira-35. This paper describes the treatment of technical challenges which were immanent during the deployment of OCEANET in the high Arctic. This includes the description of the motion stabilization of the cloud radar Mira-35 to ensure vertical-pointing observations aboard the moving Polarstern as well as the applied correction of the vessels heave rate to provide valid Doppler velocities. The correction ensured a leveling accuracy of ±0.5∘ during transits through the ice and an ice floe camp. The applied heave correction reduced the signal induced by the vertical movement of the cloud radar in the PSD of the Doppler velocity by a factor of 15. Low-level clouds, in addition, frequently prevented a continuous analysis of cloud conditions from synergies of lidar and radar within Cloudnet, because the technically determined lowest detection height of Mira-35 was 165 m above sea level. To overcome this obstacle, an approach for identification of the cloud presence solely based on data from the near-field receiver of PollyXT at heights from 50 m and 165 m above sea level is presented. We found low-level stratus clouds, which were below the lowest detection range of most automatic ground-based remote-sensing instruments during 25 % of the observation time. We present case studies of aerosol and cloud studies to introduce the capabilities of the data set. In addition, new approaches for ice crystal effective radius and eddy dissipation rates from cloud radar measurements and the retrieval of aerosol optical and microphysical properties from the observations of PollyXT are introduced.

Cloud and precipitation properties from ground-based remote-sensing instruments in East Antarctica

Abstract. A new comprehensive cloud–precipitation–meteorological observatory has been established at Princess Elisabeth base, located in the escarpment zone of Dronning Maud Land (DML), East Antarctica. The observatory consists of a set of ground-based remote-sensing instruments (ceilometer, infrared pyrometer and vertically profiling precipitation radar) combined with automatic weather station measurements of near-surface meteorology, radiative fluxes, and snow height. In this paper, the observatory is presented and the potential for studying the evolution of clouds and precipitating systems is illustrated by case studies. It is shown that the synergetic use of the set of instruments allows for distinguishing ice, liquid-containing clouds and precipitating clouds, including some information on their vertical extent. In addition, wind-driven blowing snow events can be distinguished from deeper precipitating systems. Cloud properties largely affect the surface radiative fluxes, with liquid-containing clouds dominating the radiative impact. A statistical analysis of all measurements (in total 14 months mainly during summer–beginning of winter) indicates that these liquid-containing clouds occur during as much as 20% of the cloudy periods. The cloud occurrence shows a strong bimodal distribution with clear-sky conditions 51% of the time and complete overcast conditions 35% of the time. Snowfall occurred during 17% of the cloudy periods with a predominance of light precipitation and only rare events with snowfall >1 mm h−1 water equivalent (w.e.). Three of such intense snowfall events occurred during 2011 contributing to anomalously large annual surface mass balance (SMB). Large accumulation events (>10 mm w.e. day−1) during the radar-measurement period of 26 months were always associated with snowfall, but at the same time other snowfall events did not always lead to accumulation. The multiyear deployment of a precipitation radar in Antarctica allows for assessing the contribution of the snowfall to the local SMB and comparing it to the other SMB components. During 2012, snowfall rate was 110 ± 20 mm w.e. yr−1, from which surface and drifting snow sublimation removed together 23%. Given the measured yearly SMB of 52 ± 3 mm w.e., the residual term of 33 ± 21 mm w.e. yr−1 was attributed to the wind-driven snow erosion. In general, this promising set of robust instrumentation allows for improved insight into cloud and precipitation processes in Antarctica and can be easily deployed at other Antarctic stations.

New York City Panel on Climate Change 2015 Report. Chapter 6: Indicators and monitoring.

William Solecki,1,a Cynthia Rosenzweig,2,a Reginald Blake,3,a Alex de Sherbinin,4 Tom Matte,5 Fred Moshary,6 Bernice Rosenzweig,7 Mark Arend,6 Stuart Gaffin,8 Elie Bou-Zeid,9 Keith Rule,10 Geraldine Sweeny,11 and Wendy Dessy11 1City University of New York, CUNY Institute for Sustainable Cities, New York, NY. 2Climate Impacts Group, NASA Goddard Institute for Space Studies, Center for Climate Systems Research, Columbia University Earth Institute, New York, NY. 3Physics Department, New York City College of Technology, CUNY, Brooklyn, NY; Climate Impacts Group, NASA Goddard Institute for Space Studies. 4 Center for International Earth Science Information Network (CIESIN), Columbia University, Palisades, NY. 5New York City Department of Health and Mental Hygiene, New York, NY. 6NOAA CREST, City College of New York, CUNY, New York, NY. 7CUNY Environmental Crossroads, City College of New York, CUNY, New York, NY. 8Center for Climate Systems Research, Columbia University Earth Institute, New York, NY. 9Department of Civil & Environmental Engineering, Princeton University, Princeton, NJ. 10Princeton Plasma Physics Laboratory, Princeton, NJ. 11New York City Mayor’s Office of Operation, New York, NY

Physical and optical properties of 2010 Eyjafjallajökull volcanic eruption aerosol: ground-based, Lidar and airborne measurements in France

Abstract. During the Eyjafjallajökull eruption (14 April to 24 May 2010), the volcanic aerosol cloud was observed across Europe by several airborne in situ and ground-based remote-sensing instruments. On 18 and 19 May, layers of depolarizing particles (i.e. non-spherical particles) were detected in the free troposphere above the Puy de Dôme station, (PdD, France) with a Rayleigh-Mie LIDAR emitting at a wavelength of 355 nm, with parallel and crossed polarization channels. These layers in the free troposphere (FT) were also well captured by simulations with the Lagrangian particle dispersion model FLEXPART, which furthermore showed that the ash was eventually entrained into the planetary boundary layer (PBL). Indeed, the ash cloud was then detected and characterized with a comprehensive set of in situ instruments at the Puy de Dôme station (PdD). In agreement with the FLEXPART simulation, up to 65 μg m−3 of particle mass and 2.2 ppb of SO2 were measured at PdD, corresponding to concentrations higher than the 95 percentile of 2 yr of measurements at PdD. Moreover, the number concentration of particles increased to 24 000 cm−3, mainly in the submicronic mode, but a supermicronic mode was also detected with a modal diameter of 2 μm. The resulting optical properties of the ash aerosol were characterized by a low scattering Ångström exponent (0.98), showing the presence of supermicronic particles. For the first time to our knowledge, the combination of in situ optical and physical characterization of the volcanic ash allowed the calculation of the mass-to-extinction ratio (η) with no assumptions on the aerosol density. The mass-to-extinction ratio was found to be significantly different from the background boundary layer aerosol (max: 1.57 g m−2 as opposed to 0.33 ± 0.03 g m−2). Using this ratio, ash mass concentration in the volcanic plume derived from LIDAR measurements was found to be 655 ± 23 μg m−3 when the plume was located in the FT (3000 m above the sea level – a.s.l.). This ratio could also be used to retrieve an aerosol mass concentration of 579 ± 60 μg m−3 on 19 April, when LIDAR observations detected the ash cloud at 3000 m a.s.l. in correspondence with model simulations (FLEXPART). On 22 April, another ash plume entered the BL, and although it was more diluted than during the May episode, the French research aircraft ATR42 that passed over Clermont-Ferrand in the PBL confirmed the presence of particles with a supermicronic mode, again with a modal diameter at 2 μm. This data set combining airborne, ground-based and remote sensing observations with dispersion model simulations shows an overall very good coherence during the volcanic eruption period, which allows a good confidence in the characteristics of the ash particles that can be derived from this unique data set.

Temperature retrieval with VHF radar using combined techniques

Abstract. The purpose of this study is to evaluate the practical contribution of a VHF radar to high time resolution automatic temperature profiling both for research and operational applications in the frame of an integrated system of ground-based remote-sensing instruments. Based on the most prominent results already mentioned about this instrumentation, different techniques, related to the temperature data retrieval, are experimentally tested and documented using the INSU/Meteo 45 MHz wind profiler operating at CNRM/Toulouse or during cooperative campaigns. In parallel to the self-sufficient Radio Acoustic Sounding System (RASS), other approaches, using the Brunt-Vaisala frequency measurements, allow an extension of height coverage up to the higher troposphere and the tropopause. As only temperature gradients can be measured by this way, complementary data from other instruments are desirable. This makes it particularly fitted to an integrated remote-sensing system operating from the ground combining wind profilers with GPS, radiometers, lidar ceilometers and sodars.

Quality assessment of water cycle parameters in REMO by radar-lidar synergy

Abstract. A comparison study of water cycle parameters derived from ground-based remote-sensing instruments and from the regional model REMO is presented. Observational data sets were collected during three measuring campaigns in summer/autumn 2003 and 2004 at Richard Aßmann Observatory, Lindenberg, Germany. The remote sensing instruments which were used are differential absorption lidar, Doppler lidar, ceilometer, cloud radar, and micro rain radar for the derivation of humidity profiles, ABL height, water vapour flux profiles, cloud parameters, and rain rate. Additionally, surface latent and sensible heat flux and soil moisture were measured. Error ranges and representativity of the data are discussed. For comparisons the regional model REMO was run for all measuring periods with a horizontal resolution of 18 km and 33 vertical levels. Parameter output was every hour. The measured data were transformed to the vertical model grid and averaged in time in order to better match with gridbox model values. The comparisons show that the atmospheric boundary layer is not adequately simulated, on most days it is too shallow and too moist. This is found to be caused by a wrong partitioning of energy at the surface, particularly a too large latent heat flux. The reason is obviously an overestimation of soil moisture during drying periods by the one-layer scheme in the model. The profiles of water vapour transport within the ABL appear to be realistically simulated. The comparison of cloud cover reveals an underestimation of low-level and mid-level clouds by the model, whereas the comparison of high-level clouds is hampered by the inability of the cloud radar to see cirrus clouds above 10 km. Simulated ABL clouds apparently have a too low cloud base, and the vertical extent is underestimated. The ice water content of clouds agree in model and observation whereas the liquid water content is unsufficiently derived from cloud radar reflectivity in the present study. Rain rates are similar, but the representativeness of both observations and grid box values is low.

The Convective Storm Initiation Project

The Convective Storm Initiation Project (CSIP) is an international project to understand precisely where, when, and how convective clouds form and develop into showers in the mainly maritime environment of southern England. A major aim of CSIP is to compare the results of the very high resolution Met Office weather forecasting model with detailed observations of the early stages of convective clouds and to use the newly gained understanding to improve the predictions of the model. A large array of ground-based instruments plus two instrumented aircraft, from the U.K. National Centre for Atmospheric Science (NCAS) and the German Institute for Meteorology and Climate Research (IMK), Karlsruhe, were deployed in southern England, over an area centered on the meteorological radars at Chilbolton, during the summers of 2004 and 2005. In addition to a variety of ground-based remote-sensing instruments, numerous rawinsondes were released at one- to two-hourly intervals from six closely spaced sites. The Met Office weather radar network and Meteosat satellite imagery were used to provide context for the observations made by the instruments deployed during CSIP. This article presents an overview of the CSIP field campaign and examples from CSIP of the types of convective initiation phenomena that are typical in the United Kingdom. It shows the way in which certain kinds of observational data are able to reveal these phenomena and gives an explanation of how the analyses of data from the field campaign will be used in the development of an improved very high resolution NWP model for operational use.

Observations of the plume generated by the December 2005 oil depot explosions and prolonged fire at Buncefield (Hertfordshire, UK) and associated atmospheric changes

The explosions and subsequent fire at the Buncefield oil depot in December 2005 afforded a rare opportunity to study the atmospheric consequences of a major oil fire at close range, using ground-based remote-sensing instruments. Near-source measurements (less than 10 km) suggest that plume particles were approximately 50% black carbon (BC) with refractive index 1.73−0.42i, effective radius ( R eff ) 0.45–0.85 μm and mass loading approximately 2000 μg m −3 . About 50 km downwind, particles were approximately 60–75% BC with refractive index between 1.80−0.52i and 1.89−0.69i, R eff ∼1.0 μm and mass loadings 320–780 μg m −3 . Number distributions were almost all monomodal with peak at r <0.1 μm. Near-source UV spectroscopy revealed elevated trace gas concentrations of SO 2 (70 ppbv), NO 2 (140 ppbv), HONO (20 ppbv), HCHO (160 ppbv) and CS 2 (40 ppbv). Our measurements are consistent with others of the Buncefield plume, and with studies of the 1991 Kuwaiti oil-fire plumes; differences from the latter reflecting in part contrasts in combustion efficiency and source composition (refined fuels versus crude oils) leading to important potential differences in atmospheric impacts. Other measurements made as the plume passed overhead approximately 50 km downwind showed a reduced solar flux reaching the surface, but little effect on the atmospheric potential gradient (electric field). The wind speed data from the day of the explosion hint at a possible explosion signature.