Profiles Of Liquid Water Content Research Articles

A Meteorological Supersite for Aviation and Cold Weather Applications

The goal of this study is to better understand atmospheric boundary layer processes and parameters, and to evaluate physical processes for aviation applications using data from a supersite observing site. Various meteorological sensors, including a weather and environmental unmanned aerial vehicle (WE-UAV), and a fog and snow tower (FSOS) observations are part of the project. The PanAm University of Ontario Institute of Technology (UOIT) Meteorological Supersite (PUMS) observations are being collected from April 2015 to date. The FSOS tower gathers observations related to rain, snow, fog, and visibility, aerosols, solar radiation, and wind and turbulence, as well as surface and sky temperature. The FSOSs are located at three locations at about 450–800 m away from the PUMS supersite. The WE-UAV measurements representing aerosol, wind speed and direction, as well as temperature (T) and relative humidity (RH) are provided during clear weather conditions. Other measurements at the PUMS site include cloud backscattering profiles from CL51 ceilometer, MWR observations of liquid water content (LWC), T, and RH, and Microwave Rain Radar (MRR) reflectivity profile, as well as the present weather type, snow water depth, icing rate, 3D-ultrasonic wind and turbulence, and conventional meteorological observations from compact weather stations, e.g., WXTs. The results based on important weather event studies, representing fog, snow, rain, blowing snow, wind gust, planetary boundary layer (PBL) wind research for UAV, and icing conditions are given. The microphysical parameterizations and analysis processes for each event are provided, but the results should not be generalized for all weather events and be used cautiously. Results suggested that integrated observing systems based on data from a supersite as well as satellite sites can provide better information applicable to aviation meteorology, including PBL weather research, validation of numerical weather model predictions, and remote-sensing retrievals. Overall, the results from the five cases are provided and challenges related to observations applicable to aviation meteorology are discussed.

Evaluation of Fog and Low Stratus Cloud Microphysical Properties Derived from In Situ Sensor, Cloud Radar and SYRSOC Algorithm

The microphysical properties of low stratus and fog are analyzed here based on simultaneous measurement of an in situ sensor installed on board a tethered balloon and active remote-sensing instruments deployed at the Instrumented Site for Atmospheric Remote Sensing Research (SIRTA) observatory (south of Paris, France). The study focuses on the analysis of 3 case studies where the tethered balloon is deployed for several hours in order to derive the relationship between liquid water content (LWC), effective radius (Re) and cloud droplet number concentration (CDNC) measured by a light optical aerosol counter (LOAC) in situ granulometer and Bistatic Radar System for Atmospheric Studies (BASTA) cloud radar reflectivity. The well-known relationship Z = α × (LWC)β has been optimized with α ϵ [0.02, 0.097] and β ϵ [1.91, 2.51]. Similar analysis is done to optimize the relationship Re = f(Z) and CDNC = f(Z). Two methodologies have been applied to normalize the particle-size distribution measured by the LOAC granulometer with a visible extinction closure (R² ϵ [0.73, 0.93]) and to validate the LWC profile with a liquid water closure using the Humidity and Temperature Profiler (HATPRO) microwave radiometer (R² ϵ [0.83, 0.91]). In a second step, these relationships are used to derive spatial and temporal variability of the vertical profile of LWC, Re and CDNC starting from BASTA measurement. Finally, the synergistic remote sensing of clouds (SYRSOC) algorithm has been tested on three tethered balloon flights. Generally, SYRSOC CDNC and Re profiles agreed well with LOAC in situ and BASTA profiles for the studied fog layers. A systematic overestimation of LWC by SYRSOC in the top half of the fog layer was found due to fog processes that are not accounted for in the cloud algorithm SYRSOC.

Simulating Radiative Fluxes through Southeastern Pacific Stratocumulus Clouds during VOCALS-REx

ABSTRACTTime series of solar and thermal infrared radiative flux profiles are simulated with the Rapid Radiative Transfer Model (RRTM) using a hierarchy of constraints from radar reflectivity and passive microwave cloud remote sensing measurements collected over a ship in the southeastern tropical Pacific Ocean (20°S) during the second leg of the Variability of American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-REx). Incorporating additional constraints results in simulations of physically consistent radiative profiles throughout the atmosphere, especially within the cloud, where they are difficult to observe precisely. Simulated surface radiative fluxes are compared with those observed on the ship and by aircraft.Due to the strong Rayleigh scattering of drizzle drops compared to cloud droplets that absorb, emit, and scatter natural radiation, cloud radar reflectivity overestimates cloud liquid water content (LWC). As a result, clouds are optically too thick and transmission ratios are too low in simulations using radar LWC. Imposing a triangular (increasing linearly with height from zero at cloud base) LWC profile in agreement with microwave liquid water path (LWP) improves the simulation of the transmission ratio. Constraining the corresponding microphysical cloud effective radius to that retrieved from optical depth, LWP, and cloud thickness results in additional improvements to the simulations. Time series, averages, and composite diurnal cycles of radiative fluxes, heating rates, and cloud radiative forcing are presented.

Negative Aerosol‐Cloud re Relationship From Aircraft Observations Over Hebei, China

AbstractUsing six flights observations in September 2015 over Hebei, China, this study shows a robust negative aerosol‐cloud droplet effective radius (re) relationship for liquid clouds, which is different from previous studies that found positive aerosol‐cloud re relationship over East China using satellite observations. A total of 27 cloud samples was analyzed with the classification of clean and polluted conditions using lower and upper 1/3 aerosol concentration at 200 m below the cloud bases. By normalizing the profiles of cloud droplet re, we found significant smaller values under polluted than under clean condition at most heights. Moreover, the averaged profiles of cloud liquid water content (LWC) show larger values under polluted than clean conditions, indicating even stronger negative aerosol‐cloud re relationship if LWC is kept constant. The droplet size distributions further demonstrate that more droplets concentrate within smaller size ranges under polluted conditions. Quantitatively, the aerosol‐cloud interaction is found around 0.10–0.19 for the study region.

Proof of Concept: Development of Snow Liquid Water Content Profiler Using CS650 Reflectometers at Caribou, ME, USA.

The quantity of liquid water in the snowpack defines its wetness. The temporal evolution of snow wetness’s plays a significant role in wet-snow avalanche prediction, meltwater release, and water availability estimations and assessments within a river basin. However, it remains a difficult task and a demanding issue to measure the snowpack’s liquid water content (LWC) and its temporal evolution with conventional in situ techniques. We propose an approach based on the use of time-domain reflectometry (TDR) and CS650 soil water content reflectometers to measure the snowpack’s LWC and temperature profiles. For this purpose, we created an easily-applicable, low-cost, automated, and continuous LWC profiling instrument using reflectometers at the Cooperative Remote Sensing Science and Technology Center-Snow Analysis and Field Experiment (CREST-SAFE) in Caribou, ME, USA, and tested it during the snow melt period (February–April) immediately after installation in 2014. Snow Thermal Model (SNTHERM) LWC simulations forced with CREST-SAFE meteorological data were used to evaluate the accuracy of the instrument. Results showed overall good agreement, but clearly indicated inaccuracy under wet snow conditions. For this reason, we present two (for dry and wet snow) statistical relationships between snow LWC and dielectric permittivity similar to Topp’s equation for the LWC of mineral soils. These equations were validated using CREST-SAFE in situ data from winter 2015. Results displayed high agreement when compared to LWC estimates obtained using empirical formulas developed in previous studies, and minor improvement over wet snow LWC estimates. Additionally, the equations seemed to be able to capture the snowpack state (i.e., onset of melt, medium, and maximum saturation). Lastly, field test results show advantages, such as: automated, continuous measurements, the temperature profiling of the snowpack, and the possible categorization of its state. However, future work should focus on improving the instrument’s capability to measure the snowpack’s LWC profile by properly calibrating it with in situ LWC measurements. Acceptable validation agreement indicates that the developed snow LWC, temperature, and wetness profiler offers a promising new tool for snow hydrology research.

Preliminary study on direct assimilation of cloud-affected satellite microwave brightness temperatures

Direct assimilation of cloud-affected microwave brightness temperatures from AMSU-A into the GSI three-dimensional variational (3D-Var) assimilation system is preliminarily studied in this paper. A combination of cloud microphysics parameters retrieved by the 1D-Var algorithm (including vertical profiles of cloud liquid water content, ice water content, and rain water content) and atmospheric state parameters from objective analysis fields of an NWP model are used as background fields. Three cloud microphysics parameters (cloud liquid water content, ice water content, and rain water content) are applied to the control variable. Typhoon Halong (2014) is selected as an example. The results show that direct assimilation of cloud-affected AMSU-A observations can effectively adjust the structure of large-scale temperature, humidity and wind analysis fields due to the assimilation of more AMSU-A observations in typhoon cloudy areas, especially typhoon spiral cloud belts. These adjustments, with temperatures increasing and humidities decreasing in the movement direction of the typhoon, bring the forecasted typhoon moving direction closer to its real path. The assimilation of cloud-affected satellite microwave brightness temperatures can provide better analysis fields that are more similar to the actual situation. Furthermore, typhoon prediction accuracy is improved using these assimilation analysis fields as the initial forecast fields in NWP models.

Observations of capillary barriers and preferential flow in layered snow during cold laboratory experiments

Abstract. Data of liquid water flow around a capillary barrier in snow are still limited. To gain insight into this process, we carried out observations of dyed water infiltration in layered snow at 0 °C during cold laboratory experiments. We considered three different finer-over-coarser textures and three different water input rates. By means of visual inspection, horizontal sectioning, and measurements of liquid water content (LWC), capillary barriers and associated preferential flow were characterized. The flow dynamics of each sample were also simulated solving the Richards equation within the 1-D multi-layer physically based snow cover model SNOWPACK. Results revealed that capillary barriers and preferential flow are relevant processes ruling the speed of water infiltration in stratified snow. Both are marked by a high degree of spatial variability at centimeter scale and complex 3-D patterns. During unsteady percolation of water, observed peaks in bulk volumetric LWC at the interface reached ∼ 33–36 vol % when the upper layer was composed by fine snow (grain size smaller than 0.5 mm). However, LWC might locally be greater due to the observed heterogeneity in the process. Spatial variability in water transmission increases with grain size, whereas we did not observe a systematic dependency on water input rate for samples containing fine snow. The comparison between observed and simulated LWC profiles revealed that the implementation of the Richards equation reproduces the existence of a capillary barrier for all observed cases and yields a good agreement with observed peaks in LWC at the interface between layers.

Validation of MODIS liquid water path for oceanic nonraining warm clouds: Implications on the vertical profile of cloud water content

AbstractLiquid water path (LWP) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) is validated using the Advanced Microwave Scanning Radiometer–EOS (AMSR‐E) retrievals for global oceanic nonraining warm clouds, with focus on the vertically homogeneous (VH) model and adiabatically stratified (AS) model of liquid water content (LWC) profile used in MODIS retrieval. With respect to AMSR‐E LWP that acts as ground truth under a series of constraints, the global average of MODIS‐LWPVH and MODIS‐LWPAS has a positive (11.8%) and negative (−6.8%) bias, respectively. Most of the oceanic warm clouds tend to have adiabatic origin and correspondingly form AS‐like profiles, which could be well retained if drizzle is absent. Besides, the presence of drizzle, cloud top entrainment seems to be another cause that modifies the original LWC profiles to become VH‐like, which is notable for the very low clouds that have rather small thickness. These factors jointly determine the appearance of LWP profiles and in turn their spatial pattern across global oceans, with AS‐like profiles dominant in the areas where nonraining warm clouds occur very frequently in the form of stratocumulus. The modified MODIS LWP shows significant improvement compared with either MODIS‐LWPVH or MODIS‐LWPAS. This is achieved by using the two physically explicit models flexibly, in which the elementary MODIS retrievals of cloud top temperature, cloud optical thickness, and droplet effective radius play a determinant role. A combined use of VH and AS model in the MODIS retrieval is demonstrated to be effective for improving the LWP estimation for oceanic nonraining warm clouds.

Liquid and ice water content in clouds and their variability with temperature in Africa based on ERA-Interim, JRA-55, MERRA and ISCCP

This study presents seasonal vertical structure from 1000 to 100 hPa of liquid water content (LWC) and ice water content (IWC) and investigates their variability with temperature in Africa from climatological perspective. Both LWC and IWC may increase or decrease with temperature by season and by region. We compared vertical distribution of LWC and IWC from ERA-Interim, JRA-55 and MERRA reanalysis to the distribution of cloud types from ISCCP and we found that cloud type with highest liquid content is Stratocumulus (Sc) in JJA for both East of Africa (13.3 %) and West of Africa (19.3 %) while Cumulus (Cu) in MAM for both South of Africa (8.6 %) and North of Africa (13.5 %). Cirrus (Ci) is the most frequent cloud with ice with 24.6 % presence in East Africa, 20.4 % in West Africa, 7.2 % in North Africa during MAM and 21.3 % in South Africa during SON. The LWC exists below 400 hPa for both ERA-I and JRA-55, whereas below 200 hPa based on MERRA in all regions of Africa. The IWC exists above 600 hPa for both East and West Africa, above 800 hPa in South Africa and above 900 hPa in North Africa for both ERA-I and JRA-55, whereas above 500 hPa in both East and West of Africa, above 800 hPa in South of Africa and above 850 hPa in North of Africa based on MERRA. The ERA-I, JRA-55 and MERRA are in agreement in low and mid troposphere while in upper troposphere only ERA-I and JRA-55 are in agreement. The MERRA disagrees with ERA-I and JRA-55 in the upper troposphere. The difference of LWC and IWC seasonal vertical distribution in Africa is due to different climatic features between tropic regions and subtropic regions. All three reanalyses show the LWC and IWC between −22.7 and 1.6 °C over Africa. The coexistence temperature between LWC and IWC may be useful to estimate the temperature at which there are the supercooled liquid water and mixed clouds. The ERA-I and JRA-55 may be good proxies in precipitation and cloud monitoring in regions with a lack of in situ observations in Africa. Our results reveal that ISCCP and the two reanalyses (ERA-I and JRA-55) are more reliable for characterizing cloud types and the vertical profile of LWC and IWC climatology, respectively.

Vertical profile of rain: Ka band radar observations at tropical locations

Summary Information of vertical rain structure is important for accurate quantitative precipitation estimation from weather radars and space-borne radars. In this paper, some characteristics of the vertical rain structure observed using a Ka band Micro Rain Radar at three tropical locations in India are presented. The average vertical structure is studied in terms of drop size distribution (DSD), fall velocity, rain rate, liquid water content and radar reflectivity profile. The changes in vertical rain structure with rain rate is observed to be significant only above 20 mm/h in Ahmedabad and Trivandrum, although, in Shillong, significant variation is observed starting from 2 mm/h. Results show a significant negative slope of the fall velocity of rain drops and Ka band radar reflectivity up to melting layer height for rain rate above 20 mm/h indicating a shift in the drop size distribution (DSD) toward lower size at all sites. The near ground measurements show strong variation of rain structure for all rain rates. The mean DSD near ground (

A synthetic study to assess the applicability of full-waveform inversion to infer snow stratigraphy from upward-looking ground-penetrating radar data

Snow stratigraphy and liquid water content are key contributing factors to avalanche formation. Upward-looking ground-penetrating radar (upGPR) systems allow nondestructive monitoring of the snowpack, but deriving density and liquid water content profiles is not yet possible based on the direct analysis of the reflection response. We have investigated the feasibility of deducing these quantities using full-waveform inversion (FWI) techniques applied to upGPR data. For that purpose, we have developed a frequency-domain FWI algorithm in which we additionally took advantage of time-domain features such as the arrival times of reflected waves. Our results indicated that FWI applied to upGPR data is generally feasible. More specifically, we could show that in the case of a dry snowpack, it is possible to derive snow densities and layer thicknesses if sufficient a priori information is available. In case of a wet snowpack, in which it also needs to be inverted for the liquid water content, the algorithm might fail, even if sufficient a priori information is available, particularly in the presence of realistic noise. Finally, we have investigated the capability of FWI to resolve thin layers that play a key role in snow stability evaluation. Our simulations indicate that layers with thicknesses well below the GPR wavelengths can be identified, but in the presence of significant liquid water, the thin-layer properties may be prone to inaccuracies. These results are encouraging and motivate applications to field data, but significant issues remain to be resolved, such as the determination of the generally unknown upGPR source function and identifying the optimal number of layers in the inversion models. Furthermore, a relatively high level of prior knowledge is required to let the algorithm converge. However, we feel these are not insurmountable and the new technology has significant potential to improve field data analysis.

On Depolarization Lidar-Based Method for The Determination of Liquid-Cloud Microphysical Properties

Abstract : Under single scattering conditions, water droplets clouds do not depolarize the backscattered light. However, backscattered light from multiple scattering will be depolarized. The level of depolarization is a function of the droplets size, the cloud extinction coefficient value and profile; it has also an important dependency on the lidar field-of-view (FOV). The use of depolarization information to retrieve cloud microphysical properties, using Multiple-FOV has been the object of studies, [1], [2]. Recently the use of the depolarization, at a single FOV, has been studied for cloud with linear liquid water content profiles, [3], [4]. In this paper we present the mechanism leading to depolarization and identify the FOV values for which the information on particle size is high. Also Monte Carlo simulations for cloud with constant and ramp up profiles are presented. The degree of linear depolarization as a function of cloud penetration is significantly different for both cloud profiles. This suggests that the use of the degree of linear depolarization at a single FOV should be used with caution to determine clouds micro-physical parameters.

Algorithm for the Retrieval of Liquid Water Content Profile of Clouds by Active and Passive Remote Sensing

Algorithm for the Retrieval of Liquid Water Content Profile of Clouds by Active and Passive Remote Sensing

A depolarisation lidar-based method for the determination of liquid-cloud microphysical properties

Abstract. The fact that polarisation lidars measure a depolarisation signal in liquid clouds due to the occurrence of multiple scattering is well known. The degree of measured depolarisation depends on the lidar characteristics (e.g. wavelength and receiver field of view) as well as the cloud macrophysical (e.g. cloud-base altitude) and microphysical (e.g. effective radius, liquid water content) properties. Efforts seeking to use depolarisation information in a quantitative manner to retrieve cloud properties have been undertaken with, arguably, limited practical success. In this work we present a retrieval procedure applicable to clouds with (quasi-)linear liquid water content (LWC) profiles and (quasi-)constant cloud-droplet number density in the cloud-base region. Thus limiting the applicability of the procedure allows us to reduce the cloud variables to two parameters (namely the derivative of the liquid water content with height and the extinction at a fixed distance above cloud base). This simplification, in turn, allows us to employ a fast and robust optimal-estimation inversion using pre-computed look-up tables produced using extensive lidar Monte Carlo (MC) multiple-scattering simulations. In this paper, we describe the theory behind the inversion procedure and successfully apply it to simulated observations based on large-eddy simulation (LES) model output. The inversion procedure is then applied to actual depolarisation lidar data corresponding to a range of cases taken from the Cabauw measurement site in the central Netherlands. The lidar results were then used to predict the corresponding cloud-base region radar reflectivities. In non-drizzling condition, it was found that the lidar inversion results can be used to predict the observed radar reflectivities with an accuracy within the radar calibration uncertainty (2–3 dBZ). This result strongly supports the accuracy of the lidar inversion results. Results of a comparison between ground-based aerosol number concentration and lidar-derived cloud-droplet number densities are also presented and discussed. The observed relationship between the two quantities is seen to be consistent with the results of previous studies based on aircraft-based in situ measurements.

PISTE: A Snow-Physics Model Incorporating Human Factors for Groomed Ski Slopes*

Abstract Accurately calculating snow-surface temperature and liquid water content for a groomed ski run, known as a ski piste, is crucial to the preparation of fast skis for alpine racing. Ski technicians can use forecasts of these variables to reduce ski–snow friction by applying layers of wax ahead of time. A new one-dimensional numerical Lagrangian snowpack model, Prognostic Implementation for Snow Temperature Estimation (PISTE), is presented that solves the heat-, liquid water–, and ice-budget equations to calculate these snow variables. In addition, the human effects of skiing and grooming are modeled. Meteorological measurements from a 5-day, clear-sky case study at a ski piste on Whistler Mountain, British Columbia, Canada, are prescribed to PISTE as boundary conditions. Because of a lack of interior snowpack measurements, PISTE was spun up from a dry, isothermal snowpack using repeated boundary conditions from 1 day of measurements. Initial conditions for the main model run that used the subsequent 4 days were taken from this spinup. Simulated and measured snow-surface temperatures show very good agreement, with slight cold daytime and warm nighttime biases (averaging 0.5° and 1°C, respectively). The modeled behavior of snowpack temperature and liquid water content profiles is consistent with previous literature having similar radiative boundary conditions. The case study indicates that PISTE is useful under simple conditions. It shows the potential to be developed into a more sophisticated model that can incorporate complex boundary conditions such as cloudiness and precipitation and can be driven by numerical weather prediction output.

Vertical distribution of microphysical properties in radiation fogs — A case study

The present study investigates the validity of a theoretical liquid water content (LWC) profile in fog layers currently used for satellite based ground fog detection, with a special focus on the temporal dynamics during fog life cycle. For this purpose, LWC profiles recorded during two different fog events by means of a tethered balloon borne measurement system are presented and discussed. The results indicate a good agreement in trend and gradient between measured and theoretical LWC profiles during the mature stage of the fog life cycle. The profile obtained during the dissipation stage shows less accordance with the theoretical profile. To improve the agreement between theoretical and measured LWC profiles, the evolutionary stages during the fog life cycle should be incorporated. However, the variability within the prenoted measurements points out that more LWC profiles during a great variety of different fog events have to be collected for a well-justified adaptation of the theoretical LWC profile, considering fog life cycle phases in the future. In general, this underlines the existing knowledge gap regarding the vertical distribution of microphysical properties in natural fogs.

Supercooled liquid water content profiling case studies with a new vibrating wire sonde compared to a ground-based microwave radiometer

An improved version of the vibrating wire sensor, used to measure supercooled cloud liquid water content, was developed by Anasphere Inc. and tested during early 2012. The sensor works on the principle that supercooled liquid will freeze to the vibrating wire and reduce the frequency at a known rate proportional to the liquid water content as the sensor rises through the cloud attached to a weather balloon and radiosonde. The disposable Anasphere sensor interfaces with an InterMet Systems iMet radiosonde. This updated sensor reduces the weight of the instrument while updating the technology when compared to the preceding balloon-borne sensor that was developed in the 1980's by Hill and Woffinden.Balloon-borne test flights were performed from Boulder, Colorado during February and March of 2012. These flights provided comparisons to integrated liquid water and profiles of liquid water content derived from a collocated multichannel microwave radiometer, built and operated by Radiometrics Corporation. Inter-comparison data such as these are invaluable for calibration, verification and validation of remote-sensing instruments. The data gathered from this sensor are potentially important to detection of icing hazards to aircraft, validation of microphysical output from numerical models, and calibrating remote sensors measuring supercooled liquid water.

Radiometric measurements of cloud attenuation at a tropical location in India

The effect of the earth's atmosphere on radio waves propagating over an earth-space path is a major concern in the design and performance of satellite communications systems. Some characteristics of cloud and its effect on signal propagation has been studied using multi-wavelength radiometer at a tropical location of Kolkata, India. The liquid water content profile shows high values at higher altitude during pre-monsoon season indicating the presence of cloud above zero degree isotherm. Significant change in attenuation value is observed for same liquid water content due to change in temperature and accordingly a suitable relationship is obtained for the present location. The measurements indicate that ~4dB and ~12dB attenuation is caused due to cloud at 0.01% outage probability at the Ka and V band, respectively. ITU-R model is found to be overestimating the cloud attenuation over this location and indicate the need for more experimental measurement from tropical region.

Radar-radiometer retrievals of cloud number concentration and dispersion parameter in nondrizzling marine stratocumulus

Abstract. The retrieval of cloud microphysical properties from remote sensors is challenging. In the past, ground-based radar-radiometer measurements have been successfully used to retrieve the liquid water content profile in nondrizzling clouds but offer little constraint in retrieving other moments of the cloud particle size distribution (PSD). Here, a microphysical condensational model under steady-state supersaturation conditions is utilized to provide additional constraints to the well-established radar-radiometer retrieval techniques. The coupling of the model with the observations allows the retrieval of the three parameters of a lognormal PSD, with two of them being height dependent. Two periods of stratocumulus from the Azores are used to evaluate the novel technique. The results appear reasonable in two nondrizzling periods: continental-like number concentrations are retrieved, in agreement with the drizzle-free cloud conditions. The cloud optical depth derived from the retrieved distributions compares well in magnitude and variability with the one derived independently from a narrow field of view zenith radiometer. Uncertainties coming from the measurements are propagated to the retrieved quantities to estimate their errors. In general, errors smaller than 20% should be attainable for most parameters, demonstrating the added value of the new technique.

Liquid Water Cloud Measurements Using the Raman Lidar Technique: Current Understanding and Future Research Needs

AbstractThis paper describes recent work in the Raman lidar liquid water cloud measurement technique. The range-resolved spectral measurements at the National Aeronautics and Space Administration Goddard Space Flight Center indicate that the Raman backscattering spectra measured in and below low clouds agree well with theoretical spectra for vapor and liquid water. The calibration coefficients of the liquid water measurement for the Raman lidar at the Atmospheric Radiation Measurement Program Southern Great Plains site of the U.S. Department of Energy were determined by comparison with the liquid water path (LWP) obtained with Atmospheric Emitted Radiance Interferometer (AERI) and the liquid water content (LWC) obtained with the millimeter wavelength cloud radar and water vapor radiometer (MMCR–WVR) together. These comparisons were used to estimate the Raman liquid water cross-sectional value. The results indicate a bias consistent with an effective liquid water Raman cross-sectional value that is 28%–46% lower than published, which may be explained by the fact that the difference in the detectors' sensitivity has not been accounted for. The LWP of a thin altostratus cloud showed good qualitative agreement between lidar retrievals and AERI. However, the overall ensemble of comparisons of LWP showed considerable scatter, possibly because of the different fields of view of the instruments, the 350-m distance between the instruments, and the horizontal inhomogeneity of the clouds. The LWC profiles for a thick stratus cloud showed agreement between lidar retrievals and MMCR–WVR between the cloud base and 150 m above that where the optical depth was less than 3. Areas requiring further research in this technique are discussed.