Ground-based all-sky mid-infrared and visible imagery for purposes of characterizing cloud properties

This paper describes the All Sky Infrared Visible Analyzer (ASIVA), a multi-purpose visible and infrared sky imaging and analysis instrument whose primary function is to provide radiometrically calibrated imagery in the mid-infrared (mid-IR) atmospheric window. This functionality enables the determination of diurnal fractional sky cover and estimates of sky/cloud temperature from which one can derive estimates of sky/cloud emissivity and cloud height. This paper describes the calibration methods and performance of the ASIVA instrument with particular emphasis on data products being developed for the meteorological community. Data presented here were collected during the Solmirus' ASIVA campaign conducted at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Climate Research Facility from 21 May to 27 July 2009. The purpose of this campaign was to determine the efficacy of IR technology in providing reliable nighttime sky cover data. Significant progress has been made in the analysis of the campaign data over the past several years and the ASIVA has proven to be an excellent instrument for determining sky cover as well as the potential for determining sky/cloud temperature, sky/cloud emissivity, precipitable water vapor (PWV), and ultimately cloud height

Cloud fraction determined by thermal infrared and visible all-sky cameras

The thermal infrared cloud camera (IRCCAM) is a prototype instrument that determines cloud fraction continuously during daytime and night-time using measurements of the absolute thermal sky radiance distributions in the 8–14&thinsp;µm wavelength range in conjunction with clear-sky radiative transfer modelling. Over a time period of 2 years, the fractional cloud coverage obtained by the IRCCAM is compared with two commercial cameras (Mobotix Q24M and Schreder VIS-J1006) sensitive in the visible spectrum, as well as with the automated partial cloud amount detection algorithm (APCADA) using pyrgeometer data. Over the 2-year period, the cloud fractions determined by the IRCCAM and the visible all-sky cameras are consistent to within 2&thinsp;oktas (0.25 cloud fraction) for 90&thinsp;% of the data set during the day, while for day- and night-time data the comparison with the APCADA algorithm yields an agreement of 80&thinsp;%. These results are independent of cloud types with the exception of thin cirrus clouds, which are not detected as consistently by the current cloud algorithm of the IRCCAM. The measured absolute sky radiance distributions also provide the potential for future applications by being combined with ancillary meteorological data from radiosondes and ceilometers.</p

Cirrus Occurrence and Properties Determined From Ground-Based Remote Sensing

The ultimate application of this work is constraining the optical properties of cirrus particles, which are poorly understood, by providing an automatic method, using all-sky cameras and an infrared radiometer, to identify the occurrence of the 22° halo formed by cirrus. This is done by interpreting all sky images in terms of a scattering phase function (SPF), from which the halo ratio (HR) is calculated, and by implementing a cirrus detection algorithm to associate HR measures to ice cloud occurrences. Cirrus reflectivity at solar wavelengths is inversely related to the HR which, being an indirect measure of the regularity of the shape of the ice crystals forming the cloud, relates in turn inversely to the asymmetry parameter g. Therefore, the method proposed here to derive statistics of HRs is expected to reduce the uncertainty over the optical and microphysical properties of cirrus. The light intensity measured by the all sky camera is transformed into a scattering phase function, from which the halo formation is identified. This is done by developing image transformations and corrections needed to interpret all sky images quantitatively in terms of scattering phase function, specifically by transforming the original image from the zenith-centred to the light-source-centred system of coordinates and correcting for the air mass and for vignetting. The SPF is then determined by averaging the image brightness over the azimuth angle and the HR by calculating the ratio of brightness at two scattering angles in the vicinity of the 22⁰ halo peak. The instrument transformation and corrections are performed using a series of Matlab scripts. Given that the HR is an ice cloud characteristic and since the method needs additional temperature information if the halo observation is to be associated with cirrus, a cirrus detection algorithm is necessary to screen out non-ice clouds before deriving reliable HR statistics. Cloud detection is determined by quantifying the temporal fluctuations of sky radiance, expressed as brightness temperature (BT), through De-trended Fluctuation Analysis and setting a clear sky fluctuation threshold. Cloud phase discrimination instead is achieved through first constructing an analytic radiative transfer model to obtain an estimate for average molecular absorption cross-section of water vapour within the spectral window of the radiometer. This is done to model the down-welling clear sky radiance, which is in turn used to correct cirrus emissivity and ultimately determine a dynamic BT threshold for the transition from ice to liquid-containing clouds. In addition to the molecular cross section the screen level air temperature and integrated water vapour are used as input parameters to the model. The utilisation of the all sky camera for such quantitative measurement was the particularly novel aspect of this work; this has not been done previously to the best of my knowledge. The cirrus detection method proposed is also innovative in that with respect to previous works it does not rely on the use of additional techniques such as LIDAR or microwave radiometry for discriminating cloud phase. Furthermore, the cirrus threshold proposed is not fixed but accounts for the attenuating properties of the atmosphere below the cloud. Once the cirrus detection algorithm is validated and cirrus occurrences determinable, the HR could be extended to estimating the asymmetry parameter and crystal roughness. These are retrievable, for instance, from in-situ observations of single ice crystal 2D scattering patterns from cloud probes of the SID (Small Ice Detector) type. This would be significant for the constraining of the optical and microphysical properties of cirrus

Polarimetric weather radar:from signal processing to microphysical retrievals

Accurate modelling of liquid, solid and mixed-phase precipitation requires a thorough understanding of phenomena occurring at various spatial and temporal scales. At the smallest scales, precipitation microphysics defines all the processes occurring at the level where precipitation is a discrete process. The knowledge of these microphysical processes originates from the interpretation of snowfall and rainfall measurements collected with various sensors. Direct sampling, performed with in-situ instruments, provides data of superior quality. However, the development of remote sensing (and dual-polarization radar in particular) offers a noteworthy alternative: large domains can in fact be sampled in real time and with a single instrument. The drawback is obviously the fact that radars measure precipitation indirectly. Only through appropriate interpretation radar data can be translated into physical mechanisms of precipitation. This thesis contributes to the effort to decode polarimetric radar measurements into microphysical processes or microphysical quantities that characterize precipitation. The first part of the work is devoted to radar data processing. In particular, it focuses on how to obtain high resolution estimates of the specific differential phase shift, a very important polarimetric variable with significant meteorological importance. Then, hydrometeor classification, i.e. the first qualitative microphysical aspect that may come to mind, is tackled and two hydrometeor classification methods are proposed. One is designed for polarimetric radars and one for an in-situ instrument: the two-dimensional video disdrometer. These methods illustrate the potential that supervised and unsupervised techniques can have for the interpretation of meteorological measurements. The combination of in-situ measurements and polarimetric data (including hydrometeor classification) is exploited in the last part of the thesis, devoted to the microphysics of snowfall and in particular of rimed precipitation. Riming is shown to be an important factor leading to significant accumulation of snowfall in the alpine environment. Additionally, the vertical structure of rimed precipitation is examined and interpreted