A comparison among four different retrieval methods for ice-cloud properties using data from CloudSat, CALIPSO, and MODIS

The A-Train constellation of satellites provides a new capability to measure vertical cloud profiles that leads to more detailed information on ice-cloud microphysical properties than has been possible up to now. A variational radar–lidar ice-cloud retrieval algorithm (VarCloud) takes advantage of the complementary nature of the CloudSat radar and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar to provide a seamless retrieval of ice water content, effective radius, and extinction coefficient from the thinnest cirrus (seen only by the lidar) to the thickest ice cloud (penetrated only by the radar). In this paper, several versions of the VarCloud retrieval are compared with the CloudSat standard ice-only retrieval of ice water content, two empirical formulas that derive ice water content from radar reflectivity and temperature, and retrievals of vertically integrated properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) radiometer. The retrieved variables typically agree to within a factor of 2, on average, and most of the differences can be explained by the different microphysical assumptions. For example, the ice water content comparison illustrates the sensitivity of the retrievals to assumed ice particle shape. If ice particles are modeled as oblate spheroids rather than spheres for radar scattering then the retrieved ice water content is reduced by on average 50% in clouds with a reflectivity factor larger than 0 dBZ. VarCloud retrieves optical depths that are on average a factor-of-2 lower than those from MODIS, which can be explained by the different assumptions on particle mass and area; if VarCloud mimics the MODIS assumptions then better agreement is found in effective radius and optical depth is overestimated. MODIS predicts the mean vertically integrated ice water content to be around a factor-of-3 lower than that from VarCloud for the same retrievals, however, because the MODIS algorithm assumes that its retrieved effective radius (which is mostly representative of cloud top) is constant throughout the depth of the cloud. These comparisons highlight the need to refine microphysical assumptions in all retrieval algorithms and also for future studies to compare not only the mean values but also the full probability density function

Combined CloudSat-CALIPSO-MODIS retrievals of the properties of ice clouds

In this paper, data from spaceborne radar, lidar and infrared radiometers on the “A-Train” of satellites are combined in a variational algorithm to retrieve ice cloud properties. The method allows a seamless retrieval between regions where both radar and lidar are sensitive to the regions where one detects the cloud. We first implement a cloud phase identification method, including identification of supercooled water layers using the lidar signal and temperature to discriminate ice from liquid. We also include rigorous calculation of errors assigned in the variational scheme. We estimate the impact of the microphysical assumptions on the algorithm when radiances are not assimilated by evaluating the impact of the change in the area-diameter and the density-diameter relationships in the retrieval of cloud properties. We show that changes to these assumptions affect the radar-only and lidar-only retrieval more than the radar-lidar retrieval, although the lidar-only extinction retrieval is only weakly affected. We also show that making use of the molecular lidar signal beyond the cloud as a constraint on optical depth, when ice clouds are sufficiently thin to allow the lidar signal to penetrate them entirely, improves the retrieved extinction. When infrared radiances are available, they provide an extra constraint and allow the extinction-to-backscatter ratio to vary linearly with height instead of being constant, which improves the vertical distribution of retrieved cloud properties

On the relationship between Arctic ice clouds and polluted air masses over the North Slope of Alaska in April 2008

Recently, two Types of Ice Clouds (TICs) properties have been characterized using ISDAC airborne measurements (Alaska, April 2008). TIC-2B were characterized by fewer (110 μm) ice crystals, a larger ice supersaturation (>15%) and a fewer ice nuclei (IN) concentration (<2 order of magnitude) when compared to TIC-1/2A. It has been hypothesized that emissions of SO2 may reduce the ice nucleating properties of IN through acidification, resulting to a smaller concentration of larger ice crystals and leading to precipitation (e.g. cloud regime TIC-2B) because of the reduced competition for the same available moisture. Here, the origin of air masses forming the ISDAC TIC-1/2A (1 April 2008) and TIC-2B (15 April 2008) is investigated using trajectory tools and satellite data. Results show that the synoptic conditions favor air masses transport from the three potentials SO2 emission areas to Alaska: eastern China and Siberia where anthropogenic and biomass burning emission respectively are produced and the volcanic region from the Kamchatka/Aleutians. Weather conditions allow the accumulation of pollutants from eastern China/Siberia over Alaska, most probably with the contribution of acid volcanic aerosol during the TIC-2B period. OMI observations reveal that SO2 concentrations in air masses forming the TIC-2B were larger than in air masses forming the TIC-1/2A. Airborne measurements show high acidity near the TIC-2B flight where humidity was low. These results strongly support the hypothesis that acidic coating on IN are at the origin of the formation of TIC-2B

The variability of tropical ice cloud properties as a function of the large-scale context from ground-based radar-lidar observations over Darwin, Australia

The high complexity of cloud parameterizations now held in models puts more pressure on observational studies to provide useful means to evaluate them. One approach to the problem put forth in the modelling community is to evaluate under what atmospheric conditions the parameterizations fail to simulate the cloud properties and under what conditions they do a good job. It is the ambition of this paper to characterize the variability of the statistical properties of tropical ice clouds in different tropical "regimes" recently identified in the literature to aid the development of better process-oriented parameterizations in models. For this purpose, the statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden-Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The vertical variability of ice cloud occurrence and microphysical properties is largest in all regimes (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98 % of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). In the ice part of the troposphere three distinct layers characterized by different statistically-dominant microphysical processes are identified. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is large, producing mean differences of up to a factor 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes and mean differences of a factor 2 typically in all microphysical properties. Finally, the diurnal cycle of the frequency of occurrence of ice clouds is also very different between regimes and MJO phases, with diurnal amplitudes of the vertically-integrated frequency of ice cloud occurrence ranging from as low as 0.2 (weak diurnal amplitude) to values in excess of 2.0 (very large diurnal amplitude). Modellers should now use these results to check if their model cloud parameterizations are capable of translating a given atmospheric forcing into the correct statistical ice cloud properties

BASTA : a 95GHz FM-­‐CW Cloud radar

International audienceGround-based continuous observation of non-precipitating clouds and fo

Toward understanding of differences in current cloud retrievals of ARM ground-based measurements

Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models and better estimate of the Earth radiative budget. However, large differences are found in current cloud products retrieved from ground-based remote sensing measurements using various retrieval algorithms. Understanding the differences is an important step to address uncertainties in the cloud retrievals. In this study, an in-depth analysis of nine existing ground-based cloud retrievals using ARM remote sensing measurements is carried out. We place emphasis on boundary layer overcast clouds and high level ice clouds, which are the focus of many current retrieval development efforts due to their radiative importance and relatively simple structure. Large systematic discrepancies in cloud microphysical properties are found in these two types of clouds among the nine cloud retrieval products, particularly for the cloud liquid and ice particle effective radius. Note that the differences among some retrieval products are even larger than the prescribed uncertainties reported by the retrieval algorithm developers. It is shown that most of these large differences have their roots in the retrieval theoretical bases, assumptions, as well as input and constraint parameters. This study suggests the need to further validate current retrieval theories and assumptions and even the development of new retrieval algorithms with more observations under different cloud regimes

The North Atlantic Waveguide and Downstream Impact Experiment

The North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX) explored the impact of diabatic processes on disturbances of the jet stream and their influence on downstream high-impact weather through the deployment of four research aircraft, each with a sophisticated set of remote sensing and in situ instruments, and coordinated with a suite of ground-based measurements. A total of 49 research flights were performed, including, for the first time, coordinated flights of the four aircraft: the German High Altitude and Long Range Research Aircraft (HALO), the Deutsches Zentrum für Luft- und Raumfahrt (DLR) Dassault Falcon 20, the French Service des Avions Français Instrumentés pour la Recherche en Environnement (SAFIRE) Falcon 20, and the British Facility for Airborne Atmospheric Measurements (FAAM) BAe 146. The observation period from 17 September to 22 October 2016 with frequently occurring extratropical and tropical cyclones was ideal for investigating midlatitude weather over the North Atlantic. NAWDEX featured three sequences of upstream triggers of waveguide disturbances, as well as their dynamic interaction with the jet stream, subsequent development, and eventual downstream weather impact on Europe. Examples are presented to highlight the wealth of phenomena that were sampled, the comprehensive coverage, and the multifaceted nature of the measurements. This unique dataset forms the basis for future case studies and detailed evaluations of weather and climate predictions to improve our understanding of diabatic influences on Rossby waves and the downstream impacts of weather systems affecting Europe

HyMeX: A 10-Year Multidisciplinary Program on the Mediterranean Water Cycle

Drobinski, P. ... et. al.-- 20 pages, 10 figures, 1 table, supplement material http://journals.ametsoc.org/doi/suppl/10.1175/BAMS-D-12-00244.1HyMeX strives to improve our understanding of the Mediterranean water cycle, its variability from the weather-scale events to the seasonal and interannual scales, and its characteristics over one decade (2010–20), with a special focus on hydrometeorological extremes and the associated social and economic vulnerability of the Mediterranean territoriesHyMeX was developed by an international group of scientists and is currently funded by a large number of agencies. It has been the beneficiary of financial contributions from CNRS; Météo-France; CNES; IRSTEA; INRA; ANR; Collectivité Territoriale de Corse; KIT; CNR; Université de Toulouse; Grenoble Universités; EUMETSAT; EUMETNET; AEMet; Université Blaise Pascal, Clermont Ferrand; Université de la Méditerranée (Aix-Marseille II); Université Montpellier 2; CETEMPS; Italian Civil Protection Department; Université Paris- Sud 11; IGN; EPFL; NASA; New Mexico Tech; IFSTTAR; Mercator Ocean; NOAA; ENEA; TU Delft; CEA; ONERA; IMEDEA; SOCIB; ETH; MeteoCat; Consorzio LAMMA; IRD; National Observatory of Athens; Ministerio de Ciencia e Innovación; CIMA; BRGM; Wageningen University and Research Center; Department of Geophysics, University of Zagreb; Institute of Oceanography and Fisheries, Split, Croatia; INGV; OGS; Maroc Météo; DHMZ; ARPA Piemonte; ARPA-SIMC Emilia-Romagna; ARPA Calabria; ARPA Friuli Venezia Giulia; ARPA Liguria; ISPRA; University of Connecticut; Università degli Studi dell'Aquila; Università di Bologna; Università degli Studi di Torino; Università degli Studi della Basilicata; Università La Sapienza di Roma; Università degli Studi di Padova; Università del Salento; Universitat de Barcelona; Universitat de les Illes Balears; Universidad de Castilla-La Mancha; Universidad Complutense de Madrid; MeteoSwiss; and DLR. It also received support from the European Community's Seventh Framework Programme (e.g., PERSEUS, CLIM-RUN)Peer reviewe