On the role of cloud adjustment time scale in simulating precipitation with Relaxed Arakawa-Schubert convection scheme

The precipitation by Relaxed Arakawa-Schubert cumulus parameterization in a General Circulation Model (GCM) is sensitive to the choice of relaxation parameter or specified cloud adjustment time scale. In the present study, we examine sensitivity of simulated precipitation to the choice of cloud adjustment time scale (tau(adj)) over different parts of the tropics using National Center for Environmental Prediction (NCEP) Seasonal Forecast Model (SFM) during June-September. The results show that a single specified value of tau(adj) performs best only over a particular region and different values are preferred over different parts of the world. To find a relation between tau(adj) and cloud depth (convective activity) we choose six regions over the tropics. Based on the observed relation between outgoing long-wave radiation and tau(adj), we propose a linear cloud-type dependent relaxation parameter to be used in the model. The simulations over most parts of the tropics show improved results due to this newly formulated cloud-type dependent relaxation parameter.

Effect of improving representation of horizontal and vertical cloud structure on the Earth's global radiation budget. Part I: review and parametrization

A poor representation of cloud structure in a general circulation model (GCM) is widely recognised as a potential source of error in the radiation budget. Here, we develop a new way of representing both horizontal and vertical cloud structure in a radiation scheme. This combines the ‘Tripleclouds’ parametrization, which introduces inhomogeneity by using two cloudy regions in each layer as opposed to one, each with different water content values, with ‘exponential-random’ overlap, in which clouds in adjacent layers are not overlapped maximally, but according to a vertical decorrelation scale. This paper, Part I of two, aims to parametrize the two effects such that they can be used in a GCM. To achieve this, we first review a number of studies for a globally applicable value of fractional standard deviation of water content for use in Tripleclouds. We obtain a value of 0.75 ± 0.18 from a variety of different types of observations, with no apparent dependence on cloud type or gridbox size. Then, through a second short review, we create a parametrization of decorrelation scale for use in exponential-random overlap, which varies the scale linearly with latitude from 2.9 km at the Equator to 0.4 km at the poles. When applied to radar data, both components are found to have radiative impacts capable of offsetting biases caused by cloud misrepresentation. Part II of this paper implements Tripleclouds and exponential-random overlap into a radiation code and examines both their individual and combined impacts on the global radiation budget using re-analysis data.

A regime-dependent parametrization of subgrid-scale cloud water content variability

The subgrid-scale spatial variability in cloud water content can be described by a parameter f called the fractional standard deviation. This is equal to the standard deviation of the cloud water content divided by the mean. This parameter is an input to schemes that calculate the impact of subgrid-scale cloud inhomogeneity on gridbox-mean radiative fluxes and microphysical process rates. A new regime-dependent parametrization of the spatial variability of cloud water content is derived from CloudSat observations of ice clouds. In addition to the dependencies on horizontal and vertical resolution and cloud fraction included in previous parametrizations, the new parametrization includes an explicit dependence on cloud type. The new parametrization is then implemented in the Global Atmosphere 6 (GA6) configuration of the Met Office Unified Model and used to model the effects of subgrid variability of both ice and liquid water content on radiative fluxes and autoconversion and accretion rates in three 20-year atmosphere-only climate simulations. These simulations show the impact of the new regime-dependent parametrization on diagnostic radiation calculations, interactive radiation calculations and both interactive radiation calculations and in a new warm microphysics scheme. The control simulation uses a globally constant f value of 0.75 to model the effect of cloud water content variability on radiative fluxes. The use of the new regime-dependent parametrization in the model results in a global mean which is higher than the control's fixed value and a global distribution of f which is closer to CloudSat observations. When the new regime-dependent parametrization is used in radiative transfer calculations only, the magnitudes of short-wave and long-wave top of atmosphere cloud radiative forcing are reduced, increasing the existing global mean biases in the control. When also applied in a new warm microphysics scheme, the short-wave global mean bias is reduced.

Daytime Low Stratiform Cloud Detection on AVHRR Imagery

The near-real time retrieval of low stratiform cloud (LSC) coverage is of vital interest for such disciplines as meteorology, transport safety, economy and air quality. Within this scope, a novel methodology is proposed which provides the LSC occurrence probability estimates for a satellite scene. The algorithm is suited for the 1 × 1 km Advanced Very High Resolution Radiometer (AVHRR) data and was trained and validated against collocated SYNOP observations. Utilisation of these two combined data sources requires a formulation of constraints in order to discriminate cases where the LSC is overlaid by higher clouds. The LSC classification process is based on six features which are first converted to the integer form by step functions and combined by means of bitwise operations. Consequently, a set of values reflecting a unique combination of those features is derived which is further employed to extract the LSC occurrence probability estimates from the precomputed look-up vectors (LUV). Although the validation analyses confirmed good performance of the algorithm, some inevitable misclassification with other optically thick clouds were reported. Moreover, the comparison against Polar Platform System (PPS) cloud-type product revealed superior classification accuracy. From the temporal perspective, the acquired results reported a presence of diurnal and annual LSC probability cycles over Europe.

Cloud observations in Switzerland using hemispherical sky cameras

We present observations of total cloud cover and cloud type classification results from a sky camera network comprising four stations in Switzerland. In a comprehensive intercomparison study, records of total cloud cover from the sky camera, long-wave radiation observations, Meteosat, ceilometer, and visual observations were compared. Total cloud cover from the sky camera was in 65–85% of cases within ±1 okta with respect to the other methods. The sky camera overestimates cloudiness with respect to the other automatic techniques on average by up to 1.1 ± 2.8 oktas but underestimates it by 0.8 ± 1.9 oktas compared to the human observer. However, the bias depends on the cloudiness and therefore needs to be considered when records from various observational techniques are being homogenized. Cloud type classification was conducted using the k-Nearest Neighbor classifier in combination with a set of color and textural features. In addition, a radiative feature was introduced which improved the discrimination by up to 10%. The performance of the algorithm mainly depends on the atmospheric conditions, site-specific characteristics, the randomness of the selected images, and possible visual misclassifications: The mean success rate was 80–90% when the image only contained a single cloud class but dropped to 50–70% if the test images were completely randomly selected and multiple cloud classes occurred in the images.

Clouds, aerosols, and precipitation in the marine boundary layer: an ARM Mobile Facility Deployment

The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21-month (April 2009–December 2010) comprehensive dataset documenting clouds, aerosols, and precipitation using the Atmospheric Radiation Measurement Program (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols, and precipitation in the marine boundary layer. Graciosa Island straddles the boundary between the subtropics and midlatitudes in the northeast Atlantic Ocean and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulus and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1 to 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back-trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging. The data from Graciosa are being compared with short-range forecasts made with a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.

The role of clouds in improving the regression model for hourly values of diffuse solar radiation

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The role of clouds in improving the regression model for hourly values of diffuse solar radiation

The study introduces a new regression model developed to estimate the hourly values of diffuse solar radiation at the surface. The model is based on the clearness index and diffuse fraction relationship, and includes the effects of cloud (cloudiness and cloud type), traditional meteorological variables (air temperature, relative humidity and atmospheric pressure observed at the surface) and air pollution (concentration of particulate matter observed at the surface). The new model is capable of predicting hourly values of diffuse solar radiation better than the previously developed ones (R-2 = 0.93 and RMSE = 0.085). A simple version with a large applicability is proposed that takes into consideration cloud effects only (cloudiness and cloud height) and shows a R-2 = 0.92. (C) 2011 Elsevier Ltd. All rights reserved.

Cirrus clouds observation in Santa Maria, Rio Grande do Sul during the experiment Chuva - Sul.

Cirrus clouds are an interesting point in the research of the atmosphere due their behavior and the effect on the earth radiation budget. They can affect the atmospheric radiation budget by reflecting the incoming solar radiation and absorbing the outgoing terrestrial radiation. Also, this cloud type is involved in the dehydration of the upper troposphere and lower stratosphere. So, it is interesting to increment the measurements of this type of clouds from the ground. During November and December 2012, through the CHUVA-SUL campaign, measurements with lidar in Santa Maria, Rio Grande do Sul were conducted. The system installed in Santa Maria site (29.8 °S; 53.7 °W, 100 m asl) was a single elastic-backscatter lidar using the wavelength of 532 nm. Some days with cirrus clouds lidar measurements were detected. Four days with presence of cirrus cloud are showed in the present study. These days, 7, 8, 19 and 28 November 2012, was selected due the persistence of cirrus clouds over many hours. The raw retrieval lidar signals and inverted backscatter coefficient profiles were analyzed for the selected days. Base and top height was obtained by analysis of raw signal and backscatter coefficient. Extinction coefficient profiles were obtained by the assumption of the lidar ratio. Cirrus cloud optical depth (COD) values were calculated, from the integration of the extinction coefficient between the base and top altitudes of the cirrus clouds.

Flugzeuggetragene in-situ Messungen zur Eis- und Flüssigphase troposphärischer Wolken

Die Mikrophysik in Wolken bestimmt deren Strahlungseigenschaften und beeinflusst somit auch den Strahlungshaushalt des Planeten Erde. Aus diesem Grund werden im Rahmen der vorliegenden Arbeit die mikrophysikalischen Charakteristika von Cirrus-Wolken sowie von arktischen Grenzschicht-Wolken behandelt. Die Untersuchung dieser Wolken wurde mithilfe verschiedener Instrumente verwirklicht, welche Partikel in einem Durchmesserbereich von 250nm bis zu 6.4mm vermessen und an Forschungsflugzeugen montiert werden. Ein Instrumentenvergleich bestätigt, dass innerhalb der Bereiche in denen sich die Messungen dieser Instrumente überlappen, die auftretenden Diskrepanzen als sehr gering einzustufen sind. Das vorrangig verwendete Instrument trägt die Bezeichnung CCP (Cloud Combination Probe) und ist eine Kombination aus einem Instrument, das Wolkenpartikel anhand von vorwärts-gerichtetem Streulicht detektiert und einem weiteren, das zweidimensionale Schattenbilder einzelner Wolkenpartikel aufzeichnet. Die Untersuchung von Cirrus-Wolken erfolgt mittels Daten der AIRTOSS-ICE (AIRcraft TOwed Sensor Shuttle - Inhomogeneous Cirrus Experiment) Kampagne, welche im Jahr 2013 über der deutschen Nord- und Ostsee stattfand. Parameter wie Partikeldurchmesser, Partikelanzahlkonzentration, Partikelform, Eiswassergehalt, Wolkenhöhe und Wolkendicke der detektierten Cirrus-Wolken werden bestimmt und im Kontext des aktuellen Wissenstandes diskutiert. Des Weiteren wird eine beprobte Cirrus-Wolke im Detail analysiert, welche den typischen Entwicklungsprozess und die vertikale Struktur dieser Wolkengattung widerspiegelt. Arktische Grenzschicht-Wolken werden anhand von Daten untersucht, die während der VERDI (VERtical Distribution of Ice in Arctic Clouds) Kampagne im Jahr 2012 über der kanadischen Beaufortsee aufgezeichnet wurden. Diese Messkampagne fand im Frühling statt, um die Entwicklung von Eis-Wolken über Mischphasen-Wolken bis hin zu Flüssigwasser-Wolken zu beobachten. Unter bestimmten atmosphärischen Bedingungen tritt innerhalb von Mischphasen-Wolken der sogenannte Wegener-Bergeron-Findeisen Prozess auf, bei dem Flüssigwassertropfen zugunsten von Eispartikeln verdampfen. Es wird bestätigt, dass dieser Prozess anhand von mikrophysikalischen Messungen, insbesondere den daraus resultierenden Größenverteilungen, nachweisbar ist. Darüber hinaus wird eine arktische Flüssigwasser-Wolke im Detail untersucht, welche im Inneren das Auftreten von monomodalen Tröpfchen-Größenverteilungen zeigt. Mit zunehmender Höhe wachsen die Tropfen an und die Maxima der Größenverteilungen verschieben sich hin zu größeren Durchmessern. Dahingegen findet im oberen Übergangsbereich dieser Flüssigwasser-Wolke, zwischen Wolke und freier Atmosphäre, ein Wechsel von monomodalen zu bimodalen Tröpfchen-Größenverteilungen statt. Diese weisen eine Mode 1 mit einem Tropfendurchmesser von 20μm und eine Mode 2 mit einem Tropfendurchmesser von 10μm auf. Das dieses Phänomen eventuell typisch für arktische Flüssigwasser-Wolken ist, zeigen an dem Datensatz durchgeführte Analysen. Mögliche Entstehungsprozesse der zweiten Mode können durch Kondensation von Wasserdampf auf eingetragenen Aerosolpartikeln, die aus einer Luftschicht oberhalb der Wolke stammen oder durch Wirbel, welche trockene Luftmassen in die Wolke induzieren und Verdampfungsprozesse von Wolkentröpfchen hervorrufen, erklärt werden. Unter Verwendung einer direkten numerischen Simulation wird gezeigt, dass die Einmischung von trockenen Luftmassen in den Übergangsbereich der Wolke am wahrscheinlichsten die Ausbildung von Mode 2 verursacht.