Este trabalho, sendo pioneiro no Brasil, teve o intuito de efetuar uma investigação das nuvens cirrus na região Metropolitana de São Paulo (23,33ºS / 46,44ºW), SP, através do sistema MSP-Lidar para o período de Junho à Julho de 2007. Durante este período, foi verificada uma ocorrência de cirrus de aproximadamente 54% sobre o total de medidas efetuadas pelo sistema Lidar. Medidas com Lidar nos forneceram uma alta resolução espacial e temporal destas nuvens, permitindo assim caracterizá-las e classificá-las de acordo com as suas propriedades macro- e microfísicas. Para obter tais parâmetros, uma metodologia própria foi desenvolvida na recuperação dos dados de Lidar e uma robusta estatística foi aplicada para determinar as diferentes classes de cirrus. A metodologia adotada se resumiu basicamente (a) na determinação de períodos estacionários (ou observações) durante a evolução temporal de detecção de cirrus, (b) determinação da base e topo através de um valor limiar para o cálculo das variáveis macrofísicas (altitudes, temperaturas, espessuras geométricas), (c) aplicação do método da transmitância para cada camada de nuvem e a determinação das variáveis microfísicas (profundidade óptica e razão de Lidar). Neste processo, a razão de Lidar é calculada iterativamente até que haja a convergência da mesma. Análises estatísticas de multivariáveis foram efetuadas para a determinação das classes de cirrus. Estas classes são baseadas na espessura geométrica, altitude média e sua respectiva temperatura, a altitude relativa (diferença entre a altura da tropopausa e topo da nuvem) e a profundidade óptica. O uso sucessivo da Análise de Componentes Principais (PCA), do Método de Cluster Hierárquico (MCH) e da Análise de Discriminantes (AD) permitiu a identificação de 4 classes. Vale ressaltar que tais métodos foram aplicados somente para os casos identificados como camadas únicas de nuvens, pois não se observou significativamente a ocorrência de nuvens com multicamadas. A origem de formação das classes de cirrus encontradas, embora apresentando propriedades macro- e microfísicas distintas, foi identificada basicamente como a mesma, isto é, provenientes da injeção de vapor dágua na atmosfera por meio de sistemas frontais e seu respectivo resfriamento para a formação dos cristais de gelo. O mesmo mecanismo de formação também é atribuído aos jatos subtropicais. Uma análise em relação ao perfil de temperatura e a comparação com a literatura mostrou que as cirrus classificadas apresentam possivelmente cristais em forma de placas e colunas hexagonais. As razões de lidar (RL) calculadas também estão de acordo com a literatura. / This pioneer work in Brazil, aimed at investigating cirrus clouds in the metropolitan region of São Paulo (23.33 ºS / 46.44 ºW), SP, observed by the MSP-Lidar system in June and July 2007. During this period, cirrus clouds were observed during approximately 54% of the time of all Lidar measurements available. The Lidar provided measurements with high spatial and temporal resolution measurements of these clouds that allowed characterizing and classifying them according to their macro-and microphysical properties. For such parameters, a unique methodology was developed for the Lidar data retrieval and a robust statistic was applied to determine the different classes of cirrus. The following steps were adopted to characterize the observations: (a) the determination of stationary periods (or observations) during the time evolution of cirrus detection, (b) determination of the base and top of clouds through a so called threshold value to derive the macrophysical variables (altitude, temperature, geometrical thickness), (c) the application of the transmittance method for each layer and the determination of cloud microphysical variables (optical depth and Lidar ratio). In this process, the Lidar ratio is calculated iteratively until a convergence of this value is achieved. Multivariate statistical analyses were performed to determine the classes of cirrus. These classes are based on geometric thickness, average altitude and the respective temperature, relative altitude (difference between tropopause height and cloud top) and optical depth. The successive use of Principal Component Analysis (PCA), Hierarchical Clustering Method (HCM) and Discriminant Analysis (DA) allowed the identification of four classes of cirrus. It is important to point out here that such methods were applied only to cases identified as single layers of clouds, due to the rare occurrence of multilayered clouds. The origin of formation for the four cirrus classes, though they have distinct macro-and microphysical properties, was found to be basically the same, i.e., from the injection of water vapor in the atmosphere provided by frontal systems, followed by the cooling process to form ice crystals. The same formation mechanism is also attributed to the subtropical jet. An analysis of the temperature profile and comparison with the literature showed that the cirrus crystals possibly have the form of hexagonal plates and columns. The Lidar Ratio (LR) was also found to be in accordance with the literature.

Il est maintenant bien établi que les cirrus ont un impact important sur le climat. Cependant, l'estimation de cet effet est difficile car notre connaissance des propriétés microphysiques de ce type de nuage est encore incertaine. L'objectif de cette thèse est donc d’améliorer notre compréhension de la microphysique complexe du cirrus composé principalement de cristaux de glace de forme irrégulière et d'estimer ainsi un contenu en glace (ice water content, IWC) plus précis. Pour cela, nous avons développé un algorithme permettant de restituer le profil vertical d'IWC du cirrus. La méthodologie considère une synergie entre les mesures d'un lidar et celles d'un radiomètre infrarouge thermique (IRT) effectuées depuis le sol, via une méthode d'estimation optimale. Ce travail s’est déroulé en trois étapes: (1) Le contenu en glace intégré verticalement (ice water path, IWP) est estimé à partir des mesures passives IRT. (2) L'information sur la distribution verticale d'IWC à l'intérieur du nuage est obtenue avec les mesures actives du lidar. Cette restitution dépend fortement du rapport entre la rétrodiffusion et l'extinction des cristaux de glace obtenu avec un modèle microphysique. La fonction de phase du modèle utilisée pour définir ce rapport ne prend pas en compte le pic de rétrodiffusion. Nous montrons que cette hypothèse aboutit à des résultats non réalistes par rapport aux mesures IRT. (3) Par conséquent, les deux types d’informations sont combinées en synergie pour estimer, lors de la restitution des profils verticaux d'IWC, un facteur correctif permettant de rendre compte de ce pic de rétrodiffusion. Finalement, les résultats et les hypothèses associées sont discutés. / There is a broad consensus that cirrus clouds strongly influence the climate of the Earth. However, their net radiative effect is still poorly quantified nowadays due to an insufficient knowledge of their microphysical properties. This thesis aims to improve our understanding of the complex microphysics of this cloud type mainly composed of irregularly shaped ice crystals and thereby improve estimates of the ice water content (IWC). For this purpose, we developed an algorithm to retrieve vertical profiles of the IWC of cirrus clouds. The methodology combines the measurements of a ground-based lidar and a thermal infrared (TIR) radiometer in a common optimal estimation framework. It follows three steps: (1) An algorithm to retrieve the vertically integrated amount of ice (ice water path, IWP) from the passive TIR measurements is established. (2) The information about the vertical distribution of the IWC inside the cloud is obtained from the active lidar measurements. These retrievals strongly depend on the backscatter-to-extinction ratio of the ice crystals which is obtained from a bulk ice microphysical model. The scattering phase function of this model used to define the backscatter-to-extinction ratio assumes a flat ending without backscattering peak. We show that this assumption is unrealistic since it results in the retrieval of IWC profiles which are inconsistent with the TIR measurements. (3) Consequently, both types of measurements are combined in a synergistic algorithm allowing to estimate together with the IWC profiles a correction factor for the phase function in backscattering direction. Finally, the retrieval results and associated hypotheses are discussed.

Cirrus clouds are known to play a key role in the earth's radiation budget, yet are one of the most uncertain components of the earth-atmosphere system. With the development of instruments such as the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the Moderate-resolution Infrared Spectroradiometer (MODIS), scientists now have an unprecedented ability to study cirrus clouds. To aid in the understanding of such clouds, a significant study of cirrus radiative properties has been undertaken. This research is composed of three parts: 1) the retrieval of tropical cirrus optical thickness using MODIS level-1b calibrated radiance data, 2) a survey of tropical cirrus cloud cover, including seasonal variations, using MODIS level-3 global daily gridded data, and 3) the simultaneous retrieval of cirrus optical thickness and ice crystal effective diameter using AVIRIS reflectance measurements.

This dissertation consists of three parts, each devoted to a particular issue of significant importance for satellite-based remote sensing of cirrus clouds. In the first part, we develop and present a fast infrared radiative transfer model on the basis of the adding-doubling principle. The model aims to facilitate the radiative transfer computations involved in hyperspectral remote sensing applications. The model is applicable to a variety of cloud conditions, including vertically inhomogeneous or multilayered clouds. It is shown that for hyperspectral applications the model is two order-of-magnitude faster than the well-known discrete ordinate transfer (DISORT) model, while maintains a similar accuracy. The second part is devoted to the investigation of uncertainties in the FSSP (Forward Scattering Spectrometer Probe) measurement of cloud extinction by small ice particles. First, the single-scattering properties of small ice particles in cirrus clouds are derived and compared to those of equivalent spheres according to various definitions. It is found that, although small ice particles in cirrus clouds are often “quasi-spherical”, their scattering phase functions and asymmetry factors are significant different from those of ice spheres. Such differences may lead to substantial underestimation of cloud extinction in FSSP measurement, if small ice particles are assumed to be spheres. In the third part, we present a comparison of cirrus cloud optical thickness retrievals from two important instruments, MODIS (Moderate Resolution Imaging Spectrometer) and POLDER (Polarization and Directionality of Earth’s Reflection), on board NASA’s A-train satellite constellation. The comparison reveals a large difference. Several possible reasons are discussed. It is found that much of the difference is attributable to the difference between the MODIS and POLDER retrieval algorithm in the assumption of cirrus cloud bulk scattering properties. Potential implications of the difference for climate studies are investigated. An important finding is that the use of an unrealistic cirrus bulk scattering model might introduce artificial seasonal variation of cirrus optical thickness and shortwave radiative forcing into the retrieval.

Cirrus clouds are known to play a key role in the earth's radiation budget, yet are one of the most uncertain components of the earth-atmosphere system. With the development of instruments such as the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the Moderate-resolution Infrared Spectroradiometer (MODIS), scientists now have an unprecedented ability to study cirrus clouds. To aid in the understanding of such clouds, a significant study of cirrus radiative properties has been undertaken. This research is composed of three parts: 1) the retrieval of tropical cirrus optical thickness using MODIS level-1b calibrated radiance data, 2) a survey of tropical cirrus cloud cover, including seasonal variations, using MODIS level-3 global daily gridded data, and 3) the simultaneous retrieval of cirrus optical thickness and ice crystal effective diameter using AVIRIS reflectance measurements.

Este trabalho, sendo pioneiro no Brasil, teve o intuito de efetuar uma investigação das nuvens cirrus na região Metropolitana de São Paulo (23,33ºS / 46,44ºW), SP, através do sistema MSP-Lidar para o período de Junho à Julho de 2007. Durante este período, foi verificada uma ocorrência de cirrus de aproximadamente 54% sobre o total de medidas efetuadas pelo sistema Lidar. Medidas com Lidar nos forneceram uma alta resolução espacial e temporal destas nuvens, permitindo assim caracterizá-las e classificá-las de acordo com as suas propriedades macro- e microfísicas. Para obter tais parâmetros, uma metodologia própria foi desenvolvida na recuperação dos dados de Lidar e uma robusta estatística foi aplicada para determinar as diferentes classes de cirrus. A metodologia adotada se resumiu basicamente (a) na determinação de períodos estacionários (ou observações) durante a evolução temporal de detecção de cirrus, (b) determinação da base e topo através de um valor limiar para o cálculo das variáveis macrofísicas (altitudes, temperaturas, espessuras geométricas), (c) aplicação do método da transmitância para cada camada de nuvem e a determinação das variáveis microfísicas (profundidade óptica e razão de Lidar). Neste processo, a razão de Lidar é calculada iterativamente até que haja a convergência da mesma. Análises estatísticas de multivariáveis foram efetuadas para a determinação das classes de cirrus. Estas classes são baseadas na espessura geométrica, altitude média e sua respectiva temperatura, a altitude relativa (diferença entre a altura da tropopausa e topo da nuvem) e a profundidade óptica. O uso sucessivo da Análise de Componentes Principais (PCA), do Método de Cluster Hierárquico (MCH) e da Análise de Discriminantes (AD) permitiu a identificação de 4 classes. Vale ressaltar que tais métodos foram aplicados somente para os casos identificados como camadas únicas de nuvens, pois não se observou significativamente a ocorrência de nuvens com multicamadas. A origem de formação das classes de cirrus encontradas, embora apresentando propriedades macro- e microfísicas distintas, foi identificada basicamente como a mesma, isto é, provenientes da injeção de vapor dágua na atmosfera por meio de sistemas frontais e seu respectivo resfriamento para a formação dos cristais de gelo. O mesmo mecanismo de formação também é atribuído aos jatos subtropicais. Uma análise em relação ao perfil de temperatura e a comparação com a literatura mostrou que as cirrus classificadas apresentam possivelmente cristais em forma de placas e colunas hexagonais. As razões de lidar (RL) calculadas também estão de acordo com a literatura. / This pioneer work in Brazil, aimed at investigating cirrus clouds in the metropolitan region of São Paulo (23.33 ºS / 46.44 ºW), SP, observed by the MSP-Lidar system in June and July 2007. During this period, cirrus clouds were observed during approximately 54% of the time of all Lidar measurements available. The Lidar provided measurements with high spatial and temporal resolution measurements of these clouds that allowed characterizing and classifying them according to their macro-and microphysical properties. For such parameters, a unique methodology was developed for the Lidar data retrieval and a robust statistic was applied to determine the different classes of cirrus. The following steps were adopted to characterize the observations: (a) the determination of stationary periods (or observations) during the time evolution of cirrus detection, (b) determination of the base and top of clouds through a so called threshold value to derive the macrophysical variables (altitude, temperature, geometrical thickness), (c) the application of the transmittance method for each layer and the determination of cloud microphysical variables (optical depth and Lidar ratio). In this process, the Lidar ratio is calculated iteratively until a convergence of this value is achieved. Multivariate statistical analyses were performed to determine the classes of cirrus. These classes are based on geometric thickness, average altitude and the respective temperature, relative altitude (difference between tropopause height and cloud top) and optical depth. The successive use of Principal Component Analysis (PCA), Hierarchical Clustering Method (HCM) and Discriminant Analysis (DA) allowed the identification of four classes of cirrus. It is important to point out here that such methods were applied only to cases identified as single layers of clouds, due to the rare occurrence of multilayered clouds. The origin of formation for the four cirrus classes, though they have distinct macro-and microphysical properties, was found to be basically the same, i.e., from the injection of water vapor in the atmosphere provided by frontal systems, followed by the cooling process to form ice crystals. The same formation mechanism is also attributed to the subtropical jet. An analysis of the temperature profile and comparison with the literature showed that the cirrus crystals possibly have the form of hexagonal plates and columns. The Lidar Ratio (LR) was also found to be in accordance with the literature.

Cirrus cloud forecasting is of particular importance to various Department of Defense programs. This thesis takes a case study approach to study Air Force Weather Agency Mesoscale Model 5 (AFWA MM5) skill in forecasting cirrus clouds, which are not represented explicitly by the model (ice water mixing ratio is used as a surrogate.) Two cases are selected for study. For each case, an initial forecast time of interest is determined which serves as the beginning point for the case study. GOES data and 3-hourly MM5 data are then obtained at 3- hourly intervals to coincide with model forecast time steps between the initial time through the 30-hour forecast. A standard analysis is performed on all data to determine general atmospheric structure for each case at each 3- hourly point. Following this, the model's relative humidity with respect to ice, explicit ice water content, vertical velocity, and other fields are considered to determine if the model possesses the proper dynamical factors for cirrus formation. Finally, model coverage of ice cloud is compared to the ABL cloud mask results to determine how well the model s ice cloud forecasts verify against each 3-hourly observed ice water field taken from the GOES data. Results indicate that the MM5 underforecasts cirrus coverage, and that the 90% relative humidity field with respect to ice may be a better approximation of observed cirrus coverage than the ice water field.

Thin clouds are the most difficult cloud type to observe. The recent availability of joint cloud products from the active remote sensing instruments aboard CloudSat and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO) facilitates the study of these clouds. Using one of these joint cloud products, 2B-GEOPROF-Lidar, and a post-processing algorithm designed to find horizontally continuous thin clouds within the cloud product, the locations, length scales, and vertical distributions by length of thin clouds are determined. It is found that thin clouds vary in length from a few km to over 2900 km and tend to be longer in the tropical upper troposphere than lower in the atmosphere and at higher latitudes. In the upper troposphere between 0° and 40°N, over 20% of all thin cloud measurements in the 2B-GEOPROF-Lidar product are contributed by thin clouds that are longer than 500 km. In fact, in this latitude range, over 65% of all thin cloud measurements are contributed by clouds longer than 100 km. Also, thin cloud length and frequency differ between the four seasons in the year of data used here.

The dissertation first investigates the single-scattering properties of inhomogeneous ice crystals containing air bubbles. Specifically, a combination of the ray-tracing technique and the Monte Carlo method is used to simulate the scattering of light by randomly oriented large hexagonal ice crystals containing spherical or spheroidal air bubbles. The effect of the air bubbles within ice crystals is to smooth the phase functions, diminish the 22° and 46° halo peaks, and reduce the backscatter in comparison with the case of bubble-free ice crystals. Cloud reflectance look-up tables were generated at the wavelengths of 0.65 μm and 2.13 μm to examine the impact of accounting for air bubbles in ice crystal morphology on the retrieval of ice cloud optical thickness and effective particle size. To investigate the effect of the representation of aggregates on electromagnetic scattering calculations, an algorithm is developed to efficiently specify the geometries of aggregates and to compute some of their geometric parameters such as the projected area. Based on in situ observations, aggregates are defined as clusters of hexagonal plates with a chain-like overall shape. An aggregate model is developed with 10 ensemble members, each consisting of between 4-12 hexagonal plates. The scattering properties of an individual aggregate ice particle are computed using the discrete dipole approximation or an Improved Geometric Optics Method, depending upon the size parameter. The aggregate model provides an accurate and computationally efficient way to represent all aggregates occurring within ice clouds. We developed an algorithm to determine an appropriate ice cloud model for application to satellite-based retrieval of ice cloud properties. Collocated Moderate Resolution Imaging Spectroradiometer and Multi-angle Imaging SpectroRadiometer (MISR) data are used to retrieve the optical thicknesses of ice clouds as a function of scattering angle in the nine MISR viewing directions. The difference between cloud optical thickness and its averaged value over the nine viewing angles can be used to validate the ice cloud models. Using the data obtained on 2 July 2009, an appropriate ice cloud model is determined. With the presence of all the uncertainties in the current operational satellite-based retrievals of ice cloud properties, this ice cloud model has excellent performance in terms of consistency in cloud property retrievals with the nine MISR viewing angles.

Two mechanisms appear to be primarily responsible for the formation of cirrus clouds in Tropical Tropopause Layer (TTL): detrainment from deep convective anvils and in situ initiation. Here we propose to identify TTL cirrus clouds by analyzing water content measurements from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and Aura Microwave Limb Sounder (MLS). Using ice water content (IWC) and water vapor (H2O) abundances we identify TTL cirrus clouds that contain too much ice to have been formed in situ — and therefore must be of convective origin. We use two methods to infer amounts of water vapor available for in situ formation. Clouds with IWC greater than this threshold are categorized as being of convective origin; clouds with IWC below the threshold are ambiguous — they could either form from in situ or still be of convective origin. Applying the thresholds from December 2008 to November 2009, we found that at least 19.2% of tropical cirrus were definitively of convective origin at the tropopause (375 K) during boreal winter. At each level, we found three maxima in the occurrence of convective cirrus: western Pacific, equatorial Africa, and South America. Averaged over the entire tropics (30oS to 30oN), we found convective cirrus occurs more frequently in boreal winter and less frequently in boreal summer, basically following the a decreasing trend from DJF, MAM, SON, to JJA. During boreal summer, we found that only 4.6% of tropical cirrus come from convection. Sensitivity tests show that the thresholds derived at 390 K have the largest uncertainty. At lower levels, especially 375 K, our thresholds are robust.