1,721,987 research outputs found
Retrieval of liquid water cloud properties from ground-based remote sensing observations
No full textAccurate ground-based remotely sensed microphysical and optical properties of liquid water clouds are essential references to validate satellite-observed cloud properties and to improve cloud parameterizations in weather and climate models. This requires the evaluation of algorithms for retrieval of cloud microphysical and optical properties using ground-based remote sensing observations, because there are large differences between the cloud property retrievals of various algorithms due to the differences in the applied retrieval theories, assumptions, retrieval inputs and constraints. This thesis focuses on three commonly used vertical cloud models for the parameterization of the in-cloud vertical structure in cloud property retrieval schemes. The objective is to explore the impact of the vertical cloud models on the computations of microphysical and optical properties of liquid water clouds and to evaluate their uncertainties. This information can help to improve current liquid water cloud property retrieval schemes and to increase the accuracy of the obtained cloud physical properties. A comparison of three algorithms with different vertical cloud models for the retrieval of liquid water cloud microphysical and optical properties is performed. In the first algorithm, the vertical structure of the cloud is parameterized as being vertically homogeneous (Vertically Uniform, VU). In the second algorithm, the used vertical cloud model originates from an adiabatic model (Scaled Adiabatic Stratified, SAS) and the third algorithm relies on a vertical model, which considers the impact of cloud top entrainment mixing processes on the cloud microphysical properties (Homogenous-Mixing, HM). All three algorithms use observations of the cloud radar reflectivity, the microwave radiometer obtained liquid water path (LWP) and the cloud geometrical thickness from lidar and cloud radar. They require a priori assumptions on the cloud droplet size distribution (DSD). Hence, the gamma function is used to parametrize the DSDs and possible values for the gamma DSD shape parameter are evaluated from reanalyzed in-situ observations. All three algorithms investigated here retrieve vertical profiles of the liquid water content (LWC), the droplet concentration, the effective radius, the visible optical extinction and the visible optical depth. The differences between the cloud property retrievals of each algorithm are explained on the basis of remote sensing observations that appear to be typical for low-level water clouds. The results of the VU cloud model per se lack detailed information on the vertical distribution of the cloud property retrievals. Under adiabatic conditions, the retrievals of the SAS and the HM models are equivalent, while the vertical distributions of the LWC, the effective radius and the optical extinction differ substantially under non-adiabatic conditions, especially at the cloud boundaries. The droplet concentrations of the SAS and HM models are very close to each other for both conditions. The model of uniform cloud properties yields values of the droplet concentration that are 25% lower than those from the models of non-uniform cloud properties. Interestingly, the differences between the cloud microphysical properties lead to very similar values of the retrieved visible optical depths. Sensitivity and error analyses suggest that the droplet concentration retrieval is generally most strongly affected by errors in the radar reflectivity and the LWP, while the retrievals of the effective radius are most robust in all three models. The retrievals of the optical depth and the effective radius are less affected by the variations in the DSD shape parameter as compared to the impact of the errors in observations. In contrast, the droplet concentration is more sensitive to changes in the gamma DSD shape parameter. Consequently the DSD shape parameter should be known a priori with reasonable precision. In order to evaluate the validity of the cloud property retrievals, the three algorithms are applied to synthetic surface remote sensing observations of a modeled liquid water cloud layer. The retrievals are compared with the physical properties of the modeled cloud layer as a function of the cloud height. Applying the algorithms to the best estimate “observations” and the assumed value for the DSD shape parameter leads to consistent HM model cloud property retrievals. In turn, significant overestimations of the SAS model LWC (50%) and the effective radius (10%) occur at cloud top where the SAS model retrieves the maximum values in the profiles. In all layers below the cloud top, the SAS cloud model retrievals of the LWC and the effective radius are very close to the modeled ones, because the true properties are increasing nearly adiabatically. As expected, the differences in the LWC and the effective radius profiles are largest upon the application of the VU model, which significantly overestimates both properties in the lower levels and underestimates them in the upper height levels. The very simple assumption that all cloud properties are uniformly distributed leads to a significant underestimation of the droplet concentration by about 20%. The SAS model droplet concentration is only slightly overestimated by 7%. Nevertheless, all cloud model retrievals of the optical depth agree well with those of the modeled cloud layer. To evaluate the performance of the cloud property retrievals obtained from real remote sensing observations, a broadband shortwave (SW) radiation closure analysis is performed for a selected water cloud case study. The SW fluxes at the surface calculated on the basis of the cloud properties of VU, SAS and HM models agree well with the surface radiation observations. The mean difference between the simulated and the measured SW fluxes is 2 W/m2 to 5 W/m2 with a standard deviation of 13W/m2. The uncertainty in the simulated fluxes can be explained by the uncertainty in the LWC and the effective radius due to errors in the LWP, the reflectivity and the assumption on the gamma DSD shape parameter. The three presented retrieval methods provide reliable cloud optical depth values for the selected water cloud case study. The different vertical distributions of the LWC and the effective radius, as well as differences in the droplet concentration, have a minor effect on simulating SW fluxes, because they lead to similar values of the optical depth. The present work shows that the liquid water cloud property retrievals obtained from the remote sensing observations depend on the model that is used to describe the vertical cloud structure. It shows that systematic deviations between the microphysical cloud properties of the VU, SAS and HM cloud models exist, especially regarding the droplet concentration, the LWC, the effective radius and the optical extinction at the cloud boundaries. The cloud microphysical properties estimated using the HM model parametrization show the best performance. The SAS cloud model can represent the vertically resolved microphysical properties well if they are very close to being adiabatic. Clearly, there are significant deviations in the cloud microphysics from the clouds that are parameterized as being vertically homogeneous (VU model). The different combinations of the microphysical properties in the three models lead to almost equivalent VU, SAS and HM optical depth retrievals, which agree well with the values of the modeled liquid water cloud. They are all able to reproduce the surface shortwave broadband radiative flux. However, by modeling clouds as being vertically homogeneous, sufficient accuracy in both the microphysical and the optical property retrievals cannot be achieved.Geoscience and Remote SensingCivil Engineering and Geoscience
Ice crystal properties retrieval using radar spectral polarimetric measurements within ice/mixed-phase clouds
No full textIn the field of atmospheric research, ground-based radar systems are often employed to study ice/mixed-phase cloud properties based on retrieval techniques. These techniques convert the radar signal backscattered by each bulk of ice crystals being probed within the same radar resolution volume to cloud’s microphysical characteristics. However, the size of a radar resolution volume is often too large compared to the microphysical and thermodynamical variability of the atmosphere. The microphysical information contained in the radar signal is then complex and difficult to retrieve. Therefore, the ground-based observations of the cloud’s particles microphysical characteristics are a real challenge in atmospheric science. In this thesis, an advanced atmospheric profiling radar (TARA - IRCTR) simultaneously uses Doppler and polarimetric capabilities in order to characterise the microphysical properties of the ice crystals present in ice/mixed-phase clouds. On the one hand, the polarimetric response of an atmospheric target is related to its axis ratio, assuming a spheroidal shape. On the other hand, the Doppler effect induced by the particle motion is measured by the radar and is referred as particle radial velocity. Therefore, compared to conventional weather radars, Doppler-polarimetric measurements better describe the radar resolution volume of ice particles which are categorised according to particle shape and velocity (see Chapter 3). The main objective of this PhD thesis is to develop a new type of retrieval technique, where the microphysical characteristics of ice / mixed-phase clouds are obtained from the radar spectral polarimetric measurements. High data quality is required for the reliability of spectral polarimetric parameters. Thus, a specific signal processing is performed for each radar cell, so that noise and clutter free radar parameters are obtained. Moreover, the atmospheric instability effect on radar signal data has to be removed by correctly averaging the signal over time. A strong point of this thesis comes from the derivation of averaging on a radar cell basis, based on a statistical study of the spectral polarimetric parameters determining the time slots of the atmospheric instability (see Chapter 4). In Chapter 5, a microphysical model for the study of ice crystals conversion into raindrops was improved in order to relate the ice crystals properties of ice/mixed-phase cloud regions to spectral polarimetric data. The model is based on different relations which take into account the particle habit (assuming spheroidal shapes) and orientation, ice crystals’ maximum size and their size distribution (assuming that particles fit in a modified gamma distribution). The model for ice/mixed-phase cloud study was enhanced, following these three points: 1) the implementation of the column-like pristine ice, 2) the implementation of the vertical orientation of the ice particles; and 3) a full sensitivity analysis of the input as well as model related parameters. The major breakthrough of this thesis is described in Chapter 6 with the development of a new microphysical retrieval technique. For the first time, a detailed microphysical analysis of the ice crystals present in ice/mixed-phase clouds is obtained, at each radar cell, from the sole use of TARA radar (Transportable Atmospheric Radar) Doppler polarimetric measurements. The spectral polarimetric parameters are first used to determine the type of ice particles present in the radar resolution volume, relating to their main orientation, main size and habit. The model described in Chapter 5 is then applied to the retrieval technique, as a forward model, in order to determine the mean ambient radial wind velocity and the three free parameters of the modified gamma distribution referring to each particle type. The retrieval technique was tested for a specific meteorological condition during the COPS (Convective and Orographically-induced Precipitation Study) measurement campaign, in summer 2007. As seen in Chapter 7, the microphysical results and the interpretation of the cloud processes obtained so far, within a convective nimbostratus cloud, showed good spatial and time regularity. The radar measurement results were compared and validated with other collocated sensors. The comparison of the microphysical cloud properties of a similar cloud condition was achieved with collocated aircraft measurements, flying over the ground-based site. The mean Ice Water Content (IWC), the mean ice Total Number Concentration (Nt) and the shape of the PSD, retrieved and measured by the ATR42 aircraft, were found in good agreement.TelecommunicationsElectrical Engineering, Mathematics and Computer Scienc
Design of a High Resolution X-band Doppler Polarimetric Weather Radar
No full textThe impact of the increase in anthropogenic aerosols on the global climate and the precipitation cycle is not yet fully understood. One of the reasons for that is the lack of sound measurements. In particular, high temporal and spatial resolution measurements of precipitation, coupled with measurements from other instruments, would be desired to better understand such complex processes. IRCTR has design a high resolution X-band Doppler Polarimetric Weather Radar called IDRA (IRCTR Drizzle Radar) to perform such measurements. The radar is placed on top of a 213 m high meteorological tower in the CESAR Observatory (Cabauw Experimental Site for Atmospheric Research) in Cabauw. The large range of instruments available on the site allow exploiting the synergies between them, greatly enhancing the capabilities of each individual instrument. This thesis describes the sort of measurements that can be performed using weather radar. It discusses in detail the radar principles and the design of the IDRA system in particular. It also analyzes several signal processing techniques implemented in the system. Finally, some study cases paramount of the capabilities of the system are presented. In conclusion, a new weather radar system providing unique data has been designed and its performance analyzed. The data is freely available to the whole scientific community.TelecommunicationsElectrical Engineering, Mathematics and Computer Scienc
Exploitation of homogeneous isotropic turbulence models for optimization of turbulence remote sensing
No full textHomogeneous isotropic turbulence (HIT) models are compared, with respect to optimization of turbulence remote sensing. HIT models have different applications such as load calculation for wind turbines (Mann, 1998) or droplet track modelling (Pinsky and Khain, 2006). Details of vortices seem of less relevance for modelling `realistic measurements', where the single purpose is to retrieve the eddy dissipation rate (EDR). Without the need for modelling the vortices, a faster and simpler approach might be favorable. The cascade turbulence model (CTM) is suggested. The CTM solution is scale invariant and a fast solution for one-dimensional HIT modelling. In this presentation modelled radar measruments for scanning mode (rotating antenna) are compared for different HIT models. The consequences for turbulence remote sensing optimization are discussed
Estimating cloud liquid water content from radar reflectivity for stratocumulus clouds during the Cloud Lidar and Radar Experiment
No full textIn order to obtain the cloud liquid water content from radar observations, a relationship between the radar reflectivity (Z) and the cloud liquid water content (LWC) must be found. In literature, empirical Z-LWC have been proposed. However these relationships ignore drizzle-sized droplets. Since the clouds were drizzling during Clare these relationships will not be valid for the Clare data set. In this report, a Z-LWC relation valid for clouds containing drizzle-sized droplets is developed based on the CLARE in-situ measurements and radar observations. The CLARE measurement campaign took place near Chilbolton (U.K.), between October 5th and October 23rd 1998.IRCTRElectrical Engineering, Mathematics and Computer Scienc
Field Observations of Atmospheric Aerosol Properties and the Impacts of New Particle Formation on the Radiative Properties of Clouds
No full textAtmospheric aerosol particles are solid or liquid particles suspended in the atmosphere. They are directly emitted into the atmosphere or they are formed via the oxidation of gaseous precursors. Understanding the behavior of particles in the atmosphere is particularly important because they can affect the Earth’s climate, visibility, air quality, human health, and the ecosystem. As a result, they are a topic of high interest for the scientific community...Atmospheric Remote Sensin
Advanced Techniques In Clutter Mitigation And Calibration For Weather Radars
No full textWeather observation is becoming more important than ever because extreme weather, such as tropical cyclones, thunderstorms and heavy rain, is more common nowadays. To observe and forecast the atmospheric phenomena at high spatial and temporal resolution, weather radar is well recognized as an effective tool. The prerequisite of using weather radar data is sufficient measurement accuracy. The focus of this thesis is to propose advanced techniques in clutter mitigation and calibration for weather radars to improve radar measurement accuracy. On the one hand, clutter mitigation techniques for signal-polarization, dual-polarization without cross-polar measurements and full-polarimetric radar systems are proposed to mitigate different types of clutter. On the other hand, a novel radar calibration technique is developed. With clutter suppression and techniques, clean and correct weather radar measurements are expected to be obtained
Studying ice particle growth processes in mixed-phase clouds using spectral polarimetric radar measurements
No full textClouds are a prominent part of the Earth hydrological cycle. In the mid latitudes, the ice phase of clouds is highly involved in the formation of precipitation. The ice particles in the clouds fall to earth either as snow flakes, in the winter month, or melting crystals that become rain drops. An efficient growth process is the interaction of ice crystals and supercooled liquid ater droplets in so called mixed-phase clouds. Mixed phase cloud systems contain both - ice crystals and super cooled cloud droplets - in the same volume of air. The interaction of ice and liquid phase leads to an enhanced growth of ice crystals and, therefore, enhances the amount of precipitation. However, such processes are still not fully understood. This work hows that such complex microphysical processes in mixed-phase clouds can be observed using state of the art ground based radar techniques. Analyzing spectral polarimetric radar data, different signatures of particle growth processes can be identified.The results presented are based on measurements obtained with the Transportable Atmospheric Radar (TARA) during the ACCEPT campaign (Analysis of the Composition of Clouds with Extended Polarization Techniques), in autumn 2014, Cabauw, the Netherlands. TARA is an S-band radar profiler that has full Doppler and spectral polarimetric measurement capabilities. TARAs unique three-beam configuration is also able to retrieve the full 3-D velocity vector. Because the high temporal and spatial resolutions and its configurations TARA can capture the complexity of cloud dynamics and microphysical variabilities involved in mixed-phase cloud systems. A new retrieval technique was applied to several case studies to qualitatively analyze ice particle growth processes within mixed phase cloud systems. These results demonstrate that using radar data re-arranged along fall streak, the interpretation of Doppler spectra and polarization parameters can improve. Based on synergetic measurements obtained during the ACCEPT campaign it was possible to detect possible to detect supercooled liquid water layers within the cloud system and relate them to TARA observations. Therefore, it was possible to even identify different growth processes, like particle riming, generation of the new particles, and particle diffusional growth within the TARA measurements. This demonstrates, that in order to observe ice particle growth processes within complex systems adequate radar technology and state of the art retrieval algorithms are required. Moreover, the ice particle growth processes within cloud systems can be linked directly to the increased rain intensities using along fall streak rearranged radar data.The last objective of the thesis is the extension of the spectral polarimetric measurement capabilities of TARA and the estimate of the differential phase and the specific differential phase in the spectral domain. These two parameters are frequently used to improve rain estimation, hydrometeor classifications and, currently, more and more to improve microphysical process understanding, e.g. the onset of the aggregation of ice particles. So far, the parameters are used only as integrated moments. Nevertheless, the work demonstrates that further work has to be done to completely understand the microphysical information of these spectral resolved parameters. Overall, this work demonstrates that spectral polarimetric radar data can be used to improve the microphysical process understanding. The presented work also shows that spectral polarimetric radar data can be used to estimate quantitative icrophysicalproperties related to ice particle growth.Atmospheric Remote Sensin
Advanced Techniques to Process Differential Phase Measurements for Polarimetric X-band Weather Radars
No full textObservations of weather phenomena have attracted many researchers because of their microphysical complexity, space-time variability, and more important, their impact on human life. In the efforts of studying weather, researchers have used a diverse number of instruments to obtain both in-situ (towers, tethered balloons, and weather station networks) and remote (radar, lidar, satellite) measurements. In this study, weather measurements are obtained using ground-based weather radars, which are able to scan over a large space domain, acquiring data from scanned hydrometeor targets, such as groups of rain and ice particles. Radar measurements require complex processes to extract reliable information that can be used by weather institutions, companies, and citizens. In this thesis, innovative methods are presented to process weather radar measurements, acquired at X-band frequencies and using polarimetric technology, with the aim of capturing the natural variability of storm events.Geoscience and Remote SensingAtmospheric Remote Sensin
Ground-based remote sensing of precipitation using a multi-polarized FM-CW Doppler radar
No full textElectrical Engineering, Mathematics and Computer Scienc
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