Abstract

Vertical profiles of ice water content (IWC) can now be derived globally from spaceborne cloud satellite radar (CloudSat) data. Integrating these data with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data may further increase accuracy. Evaluations of the accuracy of IWC retrieved from radar alone and together with other measurements are now essential. A forward model employing aircraft Lagrangian spiral descents through mid- and low-latitude ice clouds is used to estimate profiles of what a lidar and conventional and Doppler radar would sense. Radar reflectivity Z_e and Doppler fall speed at multiple wavelengths and extinction in visible wavelengths were derived from particle size distributions and shape data, constrained by IWC that were measured directly in most instances. These data were provided to eight teams that together cover 10 retrieval methods. Almost 3400 vertically distributed points from 19 clouds were used. Approximate cloud optical depths ranged from below 1 to more than 50. The teams returned retrieval IWC profiles that were evaluated in seven different ways to identify the amount and sources of errors. The mean (median) ratio of the retrieved-to-measured IWC was 1.15 (1.03) ± 0.66 for all teams, 1.08 (1.00) ± 0.60 for those employing a lidar–radar approach, and 1.27 (1.12) ± 0.78 for the standard CloudSat radar–visible optical depth algorithm for Z_e > −28 dBZ_e . The ratios for the groups employing the lidar–radar approach and the radar–visible optical depth algorithm may be lower by as much as 25% because of uncertainties in the extinction in small ice particles provided to the groups. Retrievals from future spaceborne radar using reflectivity–Doppler fall speeds show considerable promise. A lidar–radar approach, as applied to measurements from CALIPSO and CloudSat, is useful only in a narrow range of ice water paths (IWP) (40 < IWP < 100 g m⁻²). Because of the use of the Rayleigh approximation at high reflectivities in some of the algorithms and differences in the way nonspherical particles and Mie effects are considered, IWC retrievals in regions of radar reflectivity at 94 GHz exceeding about 5 dBZ_e are subject to uncertainties of ±50%.

Abstract

High ice water content (IWC) regions in mesoscale convective systems (MCSs) are a potential threat to commercial aviation, as they are suspected to cause in-service engine power-loss events and air data probe malfunctions. To investigate this, the high-altitude ice crystals (HAIC)/high ice water content (HIWC) projects set up a first field campaign in Darwin (Australia) in 2014. The airborne instrumentation was selected to provide the most accurate measurements of both the bulk total water content (TWC), using a specially developed isokinetic evaporator, and the individual ice crystals properties, using particle imaging probes.

This study focuses on determining the size ranges of ice crystals responsible for the mass in high IWC regions, defined here as cloud regions with IWC greater than 1.5 g m⁻³. It is shown that for high IWC areas in most of the encountered MCSs, median mass diameters (MMDs) of ice crystals range from 250 to 500 μm and decrease with increasing TWC and decreasing temperature. At the same time, the mass contribution of the smallest crystals (below 100 μm) remains generally low (below 15%).

In contrast, data from two flight missions in a long-lasting quasi-stationary tropical storm reveal that high IWC values can also be associated with MMDs in the range 400–800 μm and peak values of up to 2 mm. Ice crystal images suggest a major growth contribution by vapor deposition (columns, capped columns) even for such larger MMD values.

Abstract

The radar network deployed in southern France during the first special observing period (SOP 1) of the Hydrological Cycle in the Mediterranean Experiment (HyMeX) was designed to precisely document the 3D structure of moist upstream flow impinging on complex terrain as a function of time, height, and along-barrier distance, and surface rainfall patterns associated with orographic precipitation events. This deployment represents one of the most ambitious field experiments yet, endeavoring to collect high-quality observations of thunderstorms and precipitation systems developing over and in the vicinity of a major mountain chain.

Radar observations collected during HyMeX represent a valuable, and potentially unique, dataset that will be used to improve our knowledge of physical processes at play within coastal orographic heavy precipitating systems and to develop, and evaluate, novel radar-based products for research and operational activities. This article provides a concise description of this radar network and discusses innovative research ideas based upon preliminary analyses of radar observations collected during this field project with emphasis on the synergetic use of dual-polarimetric radar measurements collected at multiple frequencies.

Abstract

The ability of four operational weather forecast models [ECMWF, Action de Recherche Petite Echelle Grande Echelle model (ARPEGE), Regional Atmospheric Climate Model (RACMO), and Met Office] to generate a cloud at the right location and time (the cloud frequency of occurrence) is assessed in the present paper using a two-year time series of observations collected by profiling ground-based active remote sensors (cloud radar and lidar) located at three different sites in western Europe (Cabauw, Netherlands; Chilbolton, United Kingdom; and Palaiseau, France). Particular attention is given to potential biases that may arise from instrumentation differences (especially sensitivity) from one site to another and intermittent sampling. In a second step the statistical properties of the cloud variables involved in most advanced cloud schemes of numerical weather forecast models (ice water content and cloud fraction) are characterized and compared with their counterparts in the models. The two years of observations are first considered as a whole in order to evaluate the accuracy of the statistical representation of the cloud variables in each model. It is shown that all models tend to produce too many high-level clouds, with too-high cloud fraction and ice water content. The midlevel and low-level cloud occurrence is also generally overestimated, with too-low cloud fraction but a correct ice water content. The dataset is then divided into seasons to evaluate the potential of the models to generate different cloud situations in response to different large-scale forcings. Strong variations in cloud occurrence are found in the observations from one season to the same season the following year as well as in the seasonal cycle. Overall, the model biases observed using the whole dataset are still found at seasonal scale, but the models generally manage to well reproduce the observed seasonal variations in cloud occurrence. Overall, models do not generate the same cloud fraction distributions and these distributions do not agree with the observations. Another general conclusion is that the use of continuous ground-based radar and lidar observations is definitely a powerful tool for evaluating model cloud schemes and for a responsive assessment of the benefit achieved by changing or tuning a model cloud parameterization.

Abstract

One of the most challenging problems in predicting the Madden–Julian oscillation (MJO) is the initiation of large-scale convective activity associated with the MJO over the tropical Indian Ocean. The lack of observations is a major obstacle. The Dynamics of the MJO (DYNAMO) field campaign collected unprecedented observations from air-, land-, and ship-based platforms from October 2011 to February 2012. Here we provide an overview of the aircraft observations in DYNAMO, which captured an MJO initiation event from November to December 2011. The National Oceanic and Atmospheric Administration (NOAA) WP-3D aircraft was stationed at Diego Garcia and the French Falcon 20 aircraft on Gan Island in the Maldives. Observations from the two aircraft provide a unique dataset of three-dimensional structure of convective cloud systems and their environment from the flight level, airborne Doppler radar, microphysics probes, ocean surface imaging, global positioning system (GPS) dropsonde, and airborne expendable bathythermograph (AXBT) data. The aircraft observations revealed interactions among dry air, the intertropical convergence zone (ITCZ), convective cloud systems, and air–sea interaction induced by convective cold pools, which may play important roles in the multiscale processes of MJO initiation. This overview focuses on some key aspects of the aircraft observations that contribute directly to better understanding of the interactions among convective cloud systems, environmental moisture, and the upper ocean during the MJO initiation over the tropical Indian Ocean. Special emphasis is on the distinct characteristics of convective cloud systems, environmental moisture and winds, air–sea fluxes, and convective cold pools during the convectively suppressed, transition/onset, and active phases of the MJO.

The Cloudnet project aims to provide a systematic evaluation of clouds in forecast and climate models by comparing the model output with continuous ground-based observations of the vertical profiles of cloud properties. In the models, the properties of clouds are simplified and expressed in terms of the fraction of the model grid box, which is filled with cloud, together with the liquid and ice water content of the clouds. These models must get the clouds right if they are to correctly represent both their radiative properties and their key role in the production of precipitation, but there are few observations of the vertical profiles of the cloud properties that show whether or not they are successful. Cloud profiles derived from cloud radars, ceilometers, and dual-frequency microwave radiometers operated at three sites in France, Netherlands, and the United Kingdom for several years have been compared with the clouds in seven European models. The advantage of this continuous appraisal is that the feedback on how new versions of models are performing is provided in quasi-real time, as opposed to the much longer time scale needed for in-depth analysis of complex field studies. Here, two occasions are identified when the introduction of new versions of the ECMWF and Météo-France models leads to an immediate improvement in the representation of the clouds and also provides statistics on the performance of the seven models. The Cloudnet analysis scheme is currently being expanded to include sites outside Europe and further operational forecasting and climate models.

Abstract

The collective representation within global models of aerosol, cloud, precipitation, and their radiative properties remains unsatisfactory. They constitute the largest source of uncertainty in predictions of climatic change and hamper the ability of numerical weather prediction models to forecast high-impact weather events. The joint European Space Agency (ESA)–Japan Aerospace Exploration Agency (JAXA) Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) satellite mission, scheduled for launch in 2018, will help to resolve these weaknesses by providing global profiles of cloud, aerosol, precipitation, and associated radiative properties inferred from a combination of measurements made by its collocated active and passive sensors. EarthCARE will improve our understanding of cloud and aerosol processes by extending the invaluable dataset acquired by the A-Train satellites CloudSat, Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Aqua. Specifically, EarthCARE’s cloud profiling radar, with 7 dB more sensitivity than CloudSat, will detect more thin clouds and its Doppler capability will provide novel information on convection, precipitating ice particle, and raindrop fall speeds. EarthCARE’s 355-nm high-spectral-resolution lidar will measure directly and accurately cloud and aerosol extinction and optical depth. Combining this with backscatter and polarization information should lead to an unprecedented ability to identify aerosol type. The multispectral imager will provide a context for, and the ability to construct, the cloud and aerosol distribution in 3D domains around the narrow 2D retrieved cross section. The consistency of the retrievals will be assessed to within a target of ±10 W m^–2 on the (10 km)² scale by comparing the multiview broadband radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains.

Abstract

The goal of the Sea2Cloud project is to study the interplay between surface ocean biogeochemical and physical properties, fluxes to the atmosphere, and ultimately their impact on cloud formation under minimal direct anthropogenic influence. Here we present an interdisciplinary approach, combining atmospheric physics and chemistry with marine biogeochemistry, during a voyage between 41° and 47°S in March 2020. In parallel to ambient measurements of atmospheric composition and seawater biogeochemical properties, we describe semicontrolled experiments to characterize nascent sea spray properties and nucleation from gas-phase biogenic emissions. The experimental framework for studying the impact of the predicted evolution of ozone concentration in the Southern Hemisphere is also detailed. After describing the experimental strategy, we present the oceanic and meteorological context including provisional results on atmospheric thermodynamics, composition, and flux measurements. In situ measurements and flux studies were carried out on different biological communities by sampling surface seawater from subantarctic, subtropical, and frontal water masses. Air–Sea-Interface Tanks (ASIT) were used to quantify biogenic emissions of trace gases under realistic environmental conditions, with nucleation observed in association with biogenic seawater emissions. Sea spray continuously generated produced sea spray fluxes of 34% of organic matter by mass, of which 4% particles had fluorescent properties, and which size distribution resembled the one found in clean sectors of the Southern Ocean. The goal of Sea2Cloud is to generate realistic parameterizations of emission flux dependences of trace gases and nucleation precursors, sea spray, cloud condensation nuclei, and ice nuclei using seawater biogeochemistry, for implementation in regional atmospheric models.

The Mediterranean region is frequently affected by heavy precipitation events associated with flash floods, landslides, and mudslides that cause hundreds of millions of euros in damages per year and, often, casualties. A major field campaign was devoted to heavy precipitation and f lash f loods from 5 September to 6 November 2012 within the framework of the 10-yr international Hydrological Cycle in the Mediterranean Experiment (HyMeX) dedicated to the hydrological cycle and related high-impact events. The 2-month field campaign took place over the northwestern Mediterranean Sea and its surrounding coastal regions in France, Italy, and Spain. The observation strategy of the field experiment was devised to improve knowledge of the following key components leading to heavy precipitation and flash flooding in the region: 1) the marine atmospheric f lows that transport moist and conditionally unstable air toward the coasts, 2) the Mediterranean Sea acting as a moisture and energy source, 3) the dynamics and microphysics of the convective systems producing heavy precipitation, and 4) the hydrological processes during flash floods. This article provides the rationale for developing this first HyMeX field experiment and an overview of its design and execution. Highlights of some intensive observation periods illustrate the potential of the unique datasets collected for process understanding, model improvement, and data assimilation.