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Dominique Bouniol, Rémy Roca, Thomas Fiolleau, and D. Emmanuel Poan

Abstract

Mesoscale convective systems (MCSs) are important drivers of the atmospheric large-scale circulation through their associated diabatic heating profile. Taking advantage of recent tracking techniques, this study investigates the evolution of macrophysical, microphysical, and radiative properties over the MCS life cycle by merging geostationary and polar-orbiting satellite data. These observations are performed in three major convective areas: continental West Africa, the adjacent Atlantic Ocean, and the open Indian Ocean. MCS properties are also investigated according to internal subregions (convective, stratiform, and nonprecipitating anvil). Continental MCSs show a specific life cycle, with more intense convection at the beginning. Larger and denser hydrometeors are thus found at higher altitudes, as well as up to the cirriform subregion. Oceanic MCSs have more constant reflectivity values, suggesting a less intense convective updraft, but more persistent intensity. A layer of small crystals is found in all subregions, but with a depth that varies according to the MCS subregion and life cycle. Radiative properties are also examined. It appears that the evolution of large and dense hydrometeors tends to control the evolution of the cloud albedo and the outgoing longwave radiation. The impact of dense hydrometeors, detrained from the convective towers, is also seen in the radiative heating profiles, in particular in the shortwave domain. A dipole of cooling near the cloud top and heating near the cloud base is found in the longwave; this cooling intensifies near the end of the life cycle.

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Robin J. Hogan, Dominique Bouniol, Darcy N. Ladd, Ewan J. O'Connor, and Anthony J. Illingworth

Abstract

Absolute calibration of cloud radars is very difficult. A new method is proposed for 94/95-GHz radars that exploits the fact that at this frequency, the radar reflectivity factor of rain measured at a range of 250 m is approximately constant at 19 dBZ for rain rates between 3 and 10 mm h–1, due to the combined effects of extinction and non-Rayleigh scattering. The standard deviation of around 1.5 dB is due to natural variations in the number concentration of drops and is consistent with the variation predicted from theory, but averaging over a number of different rain events over a month or more should be sufficient to reduce the calibration error to less than 1 dB. A thin layer of rainwater on the radomes of the 94-GHz radar at Chilbolton, in southern England, was found to cause a two-way attenuation of between 9 and 14 dB, but it is shown here that the technique may be successfully implemented by operating the radar at a low elevation angle and employing a shelter to keep it dry. Most 94-GHz cloud radars worldwide use the same amplifier, and monitoring the calibration of this radar over a 2-yr period of continuous use reveals a loss of power of around 1 dB in the first year and 10 dB in the second. Frequent calibration is therefore recommended.

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Claire Tinel, Jacques Testud, Jacques Pelon, Robin J. Hogan, Alain Protat, Julien Delanoë, and Dominique Bouniol

Abstract

Clouds are an important component of the earth’s climate system. A better description of their microphysical properties is needed to improve radiative transfer calculations. In the framework of the Earth, Clouds, Aerosols, and Radiation Explorer (EarthCARE) mission preparation, the radar–lidar (RALI) airborne system, developed at L’Institut Pierre Simon Laplace (France), can be used as an airborne demonstrator. This paper presents an original method that combines cloud radar (94–95 GHz) and lidar data to derive the radiative and microphysical properties of clouds. It combines the apparent backscatter reflectivity from the radar and the apparent backscatter coefficient from the lidar. The principle of this algorithm relies on the use of a relationship between the extinction coefficient and the radar specific attenuation, derived from airborne microphysical data and Mie scattering calculations. To solve radar and lidar equations in the cloud region where signals can be obtained from both instruments, the extinction coefficients at some reference range z 0 must be known. Because the algorithms are stable for inversion performed from range z 0 toward the emitter, z 0 is chosen at the farther cloud boundary as observed by the lidar. Then, making an assumption of a relationship between extinction coefficient and backscattering coefficient, the whole extinction coefficient, the apparent reflectivity, cloud physical parameters, the effective radius, and ice water content profiles are derived. This algorithm is applied to a blind test for downward-looking instruments where the original profiles are derived from in situ measurements. It is also applied to real lidar and radar data, obtained during the 1998 Cloud Lidar and Radar Experiment (CLARE’98) field project when a prototype airborne RALI system was flown pointing at nadir. The results from the synergetic algorithm agree reasonably well with the in situ measurements.

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Romain Roehrig, Dominique Bouniol, Francoise Guichard, Frédéric Hourdin, and Jean-Luc Redelsperger

Abstract

The present assessment of the West African monsoon in the models of the Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5) indicates little evolution since the third phase of CMIP (CMIP3) in terms of both biases in present-day climate and climate projections.

The outlook for precipitation in twenty-first-century coupled simulations exhibits opposite responses between the westernmost and eastern Sahel. The spread in the trend amplitude, however, remains large in both regions. Besides, although all models predict a spring and summer warming of the Sahel that is 10%–50% larger than the global warming, their temperature response ranges from 0 to 7 K.

CMIP5 coupled models underestimate the monsoon decadal variability, but SST-imposed simulations succeed in capturing the recent partial recovery of monsoon rainfall. Coupled models still display major SST biases in the equatorial Atlantic, inducing a systematic southward shift of the monsoon. Because of these strong biases, the monsoon is further evaluated in SST-imposed simulations along the 10°W–10°E African Monsoon Multidisciplinary Analysis (AMMA) transect, across a range of time scales ranging from seasonal to intraseasonal and diurnal fluctuations.

The comprehensive set of observational data now available allows an in-depth evaluation of the monsoon across those scales, especially through the use of high-frequency outputs provided by some CMIP5 models at selected sites along the AMMA transect. Most models capture many features of the African monsoon with varying degrees of accuracy. In particular, the simulation of the top-of-atmosphere and surface energy balances, in relation with the cloud cover, and the intermittence and diurnal cycle of precipitation demand further work to achieve a reasonable realism.

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Dominique Bouniol, Alain Protat, Artemio Plana-Fattori, Manuel Giraud, Jean-Paul Vinson, and Noël Grand

Abstract

This paper provides an evaluation of the level 1 (reflectivity) CloudSat products by making use of coincident measurements collected by an airborne 95-GHz radar during the African Monsoon Multidisciplinary Analysis (AMMA) experiment that took place in summer 2006 over West Africa. In a first step the airborne radar calibration is assessed. Collocated measurements of the spaceborne and airborne radars within the ice anvil of a mesoscale convective system are then compared. Several aspects are interesting in this comparison: First, both instruments exhibit attenuation within the ice part of the convective system, which suggests either the presence of a significant amount of supercooled liquid water above the melting layer or the presence of wet and very dense ice. Second, from the differences in the observed reflectivity values, a multiple scattering enhancement of at least 2.5 dB in the CloudSat reflectivities at flight altitude is estimated. The main conclusion of this paper is that in such thick anvils of mesoscale convective systems the CloudSat measurements have to be corrected for this effect, if one wants to derive accurate level 2 products such as the ice water content from radar reflectivity. This effect is expected to be much smaller in nonprecipitating clouds though.

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Dominique Bouniol, Fleur Couvreux, Pierre-Honoré Kamsu-Tamo, Madeleine Leplay, Françoise Guichard, Florence Favot, and Ewan J. O’Connor

Abstract

This study focuses on the occurrence and type of clouds observed in West Africa, a subject that has been neither much documented nor quantified. It takes advantage of data collected above Niamey, Niger, in 2006 with the Atmospheric Radiation Measurement (ARM) Mobile Facility. A survey of cloud characteristics inferred from ground measurements is presented with a focus on their seasonal evolution and diurnal cycle. Four types of clouds are distinguished: high-level clouds, deep convective clouds, shallow convective clouds, and midlevel clouds. A frequent occurrence of the latter clouds located at the top of the Saharan air layer is highlighted. High-level clouds are ubiquitous throughout the period whereas shallow convective clouds are mainly noticeable during the core of the monsoon. The diurnal cycle of each cloud category and its seasonal evolution are investigated. CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are used to demonstrate that these four cloud types (in addition to stratocumulus clouds over the ocean) are not a particularity of the Niamey region and that midlevel clouds are present over the Sahara during most of the monsoon season. Moreover, using complementary datasets, the radiative impact of each type of clouds at the surface level has been quantified in the short- and longwave domains. Midlevel clouds and anvil clouds have the largest impact, respectively, in longwave (about 15 W m−2) and shortwave (about 150 W m−2) radiation. Furthermore, midlevel clouds exert a strong radiative forcing during the spring at a time when the other cloud types are less numerous.

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Robin J. Hogan, Malcolm E. Brooks, Anthony J. Illingworth, David P. Donovan, Claire Tinel, Dominique Bouniol, and J. Pedro V. Poiares Baptista

Abstract

The combination of radar and lidar in space offers the unique potential to retrieve vertical profiles of ice water content and particle size globally, and two algorithms developed recently claim to have overcome the principal difficulty with this approach—that of correcting the lidar signal for extinction. In this paper “blind tests” of these algorithms are carried out, using realistic 94-GHz radar and 355-nm lidar backscatter profiles simulated from aircraft-measured size spectra, and including the effects of molecular scattering, multiple scattering, and instrument noise. Radiation calculations are performed on the true and retrieved microphysical profiles to estimate the accuracy with which radiative flux profiles could be inferred remotely. It is found that the visible extinction profile can be retrieved independent of assumptions on the nature of the size distribution, the habit of the particles, the mean extinction-to-backscatter ratio, or errors in instrument calibration. Local errors in retrieved extinction can occur in proportion to local fluctuations in the extinction-to-backscatter ratio, but down to 400 m above the height of the lowest lidar return, optical depth is typically retrieved to better than 0.2. Retrieval uncertainties are greater at the far end of the profile, and errors in total optical depth can exceed 1, which changes the shortwave radiative effect of the cloud by around 20%. Longwave fluxes are much less sensitive to errors in total optical depth, and may generally be calculated to better than 2 W m−2 throughout the profile. It is important for retrieval algorithms to account for the effects of lidar multiple scattering, because if this is neglected, then optical depth is underestimated by approximately 35%, resulting in cloud radiative effects being underestimated by around 30% in the shortwave and 15% in the longwave. Unlike the extinction coefficient, the inferred ice water content and particle size can vary by 30%, depending on the assumed mass–size relationship (a problem common to all remote retrieval algorithms). However, radiative fluxes are almost completely determined by the extinction profile, and if this is correct, then errors in these other parameters have only a small effect in the shortwave (around 6%, compared to that of clear sky) and a negligible effect in the longwave.

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Andrew J. Heymsfield, Alain Protat, Dominique Bouniol, Richard T. Austin, Robin J. Hogan, Julien Delanoë, Hajime Okamoto, Kaori Sato, Gerd-Jan van Zadelhoff, David P. Donovan, and Zhien Wang

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 Ze 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 Ze > −28 dBZe. 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 dBZe are subject to uncertainties of ±50%.

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Dominique Bouniol, Alain Protat, Julien Delanoë, Jacques Pelon, Jean-Marcel Piriou, François Bouyssel, Adrian M. Tompkins, Damian R. Wilson, Yohann Morille, Martial Haeffelin, Ewan J. O’Connor, Robin J. Hogan, Anthony J. Illingworth, David P. Donovan, and Henk-Klein Baltink

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.

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