Cloud fraction, liquid and ice water contents derived from long-term radar, lidar, and microwave radiometer data are systematically compared to models to quantify and improve their performance.
International audienceThe 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 degrees W-10 degrees 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
Abstract. Ground-based remote sensing observatories have a crucial role to play in providing data to improve our understanding of atmospheric processes, to test the performance of atmospheric models, and to develop new methods for future space-borne observations. Institut Pierre Simon Laplace, a French research institute in environmental sciences, created the Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA), an atmospheric observatory with these goals in mind. Today SIRTA, located 20 km south of Paris, operates a suite a state-of-the-art active and passive remote sensing instruments dedicated to routine monitoring of cloud and aerosol properties, and key atmospheric parameters. Detailed description of the state of the atmospheric column is progressively archived and made accessible to the scientific community. This paper describes the SIRTA infrastructure and database, and provides an overview of the scientific research associated with the observatory. Researchers using SIRTA data conduct research on atmospheric processes involving complex interactions between clouds, aerosols and radiative and dynamic processes in the atmospheric column. Atmospheric modellers working with SIRTA observations develop new methods to test their models and innovative analyses to improve parametric representations of sub-grid processes that must be accounted for in the model. SIRTA provides the means to develop data interpretation tools for future active remote sensing missions in space (e.g. CloudSatCorrespondence to: M. Haeffelin (martial.haeffelin@lmd.polytechnique.fr) and CALIPSO). SIRTA observation and research activities take place in networks of atmospheric observatories that allow scientists to access consistent data sets from diverse regions on the globe.
[1] Testud et al. (2001) have recently developed a formalism, known as the ''normalized particle size distribution (PSD)'', which consists in scaling the diameter and concentration axes in such a way that the normalized PSDs are independent of water content and mean volume-weighted diameter. In this paper we investigate the statistical properties of the normalized PSD for the particular case of ice clouds, which are known to play a crucial role in the Earth's radiation balance. To do so, an extensive database of airborne in situ microphysical measurements has been constructed. A remarkable stability in shape of the normalized PSD is obtained. The impact of using a single analytical shape to represent all PSDs in the database is estimated through an error analysis on the instrumental (radar reflectivity and attenuation) and cloud (ice water content, effective radius, terminal fall velocity of ice crystals, visible extinction) properties. This resulted in a roughly unbiased estimate of the instrumental and cloud parameters, with small standard deviations ranging from 5 to 12%. This error is found to be roughly independent of the temperature range. This stability in shape and its single analytical approximation implies that two parameters are now sufficient to describe any normalized PSD in ice clouds: the intercept parameter N* 0 and the mean volume-weighted diameter D m . Statistical relationships (parameterizations) between N* 0 and D m have then been evaluated in order to reduce again the number of unknowns. It has been shown that a parameterization of N* 0 and D m by temperature could not be envisaged to retrieve the cloud parameters. Nevertheless, D m -T and mean maximum dimension diameter -T parameterizations have been derived and compared to the parameterization of Kristjánsson et al. (2000) currently used to characterize particle size in climate models. The new parameterization generally produces larger particle sizes at any temperature than the Kristjánsson et al. (2000) parameterization. These new parameterizations are believed to better represent particle size at global scale, owing to a better representativity of the in situ microphysical database used to derive it. We then evaluated the potential of a direct N* 0 -D m relationship. While the model parameterized by temperature produces strong errors on the cloud parameters, the N* 0 -D m model parameterized by radar reflectivity produces accurate cloud parameters (less than 3% bias and 16% standard deviation). This result implies that the cloud parameters can be estimated from the estimate of only one parameter of the normalized PSD (N* 0 or D m ) and a radar reflectivity measurement.
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) Ϯ 0.66 for all teams, 1.08 (1.00) Ϯ 0.60 for those employing a lidar-radar approach, and 1.27 (1.12) Ϯ 0.78 for the standard CloudSat radar-visible optical depth algorithm for Z e Ͼ Ϫ28 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 lidarradar approach, as applied to measurements from CALIPSO and CloudSat, is useful only in a narrow range of ice water paths (IWP) (40 Ͻ IWP Ͻ 100 g m Ϫ2 ). 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 Ϯ50%.
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