Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Alain Protat is active.

Publication


Featured researches published by Alain Protat.


Bulletin of the American Meteorological Society | 2007

Cloudnet: Continuous Evaluation of Cloud Profiles in Seven Operational Models Using Ground-Based Observations

Anthony J. Illingworth; Robin J. Hogan; Ewan J. O'Connor; Dominique Bouniol; Malcolm E. Brooks; Julien Delanoë; David P. Donovan; J.D. Eastment; Nicolas Gaussiat; J.W.F. Goddard; Martial Haeffelin; H. Klein Baltink; Oleg A. Krasnov; Jacques Pelon; J.-M. Piriou; Alain Protat; H.W.J. Russchenberg; A. Seifert; Adrian M. Tompkins; G.-J. van Zadelhoff; F. Vinit; Ulrika Willén; Damian R. Wilson; C. L. Wrench

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.


Journal of Geophysical Research | 2012

Toward Understanding of Differences in Current Cloud Retrievals of ARM Ground-Based Measurements

Chuanfeng Zhao; Shaocheng Xie; Stephen A. Klein; Alain Protat; Matthew D. Shupe; Sally A. McFarlane; Jennifer M. Comstock; Julien Delanoë; Min Deng; Maureen Dunn; Robin J. Hogan; Dong Huang; Michael Jensen; Gerald G. Mace; Renata McCoy; Ewan J. O'Connor; David D. Turner; Zhien Wang

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.


Journal of Applied Meteorology and Climatology | 2008

Testing IWC retrieval methods using radar and ancillary measurements with in-situ data

Andrew J. Heymsfield; Alain Protat; R. T. Austin; Dominique Bouniol; Robin J. Hogan; Julien Delanoë; Hajime Okamoto; Kaori Sato; Gerd Jan van Zadelhoff; David P. Donovan; 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...


Journal of Applied Meteorology | 2005

The retrieval of ice-cloud properties from cloud radar and lidar synergy

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

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 z0 must be known. Because the algorithms are stable for inversion performed from range z0 toward the emitter, z0 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.


Journal of Atmospheric and Oceanic Technology | 2010

The Evaluation of CloudSat and CALIPSO Ice Microphysical Products Using Ground-Based Cloud Radar and Lidar Observations

Alain Protat; Julien Delanoë; Ewan J. O'Connor; Tristan S. L'Ecuyer

In this paper, the statistical properties of tropical ice clouds (ice water content, visible extinction, effective radius, and total number concentration) derived from 3 yr of ground-based radar–lidar retrievals from the U.S. Department of Energy Atmospheric Radiation Measurement Climate Research Facility in Darwin, Australia, are compared with the same properties derived using the official CloudSat microphysical retrieval methods and from a simpler statistical method using radar reflectivity and air temperature. It is shown that the two official CloudSat microphysical products (2B-CWC-RO and 2B-CWC-RVOD) are statistically virtually identical. The comparison with the ground-based radar–lidar retrievals shows that all satellite methods produce ice water contents and extinctions in a much narrower range than the ground-based method and overestimate the mean vertical profiles of microphysical parameters below 10-km height by over a factor of 2. Better agreements are obtained above 10-km height. Ways to improve these estimates are suggested in this study. Effective radii retrievals from the standard CloudSat algorithms are characterized by a large positive bias of 8–12 mm. A sensitivity test shows that in response to such a bias the cloud longwave forcing is increased from 44.6 to 46.9 W m 22 (implying an error of about 5%), whereas the negative cloud shortwave forcing is increased from 281.6 to 282.8 W m 22 . Further analysis reveals that these modest effects (although not insignificant) can be much larger for optically thick clouds. The statistical method usingCloudSat reflectivities and air temperature was found to produce inaccurate mean vertical profiles and probability distribution functions of effective radius. This study also shows that the retrieval of the total number concentration needs to be improved in the official CloudSat microphysical methods prior to a quantitative use for the characterization of tropical ice clouds. Finally, the statistical relationship used to produce ice water content from extinction and air temperature obtained by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is evaluated for tropical ice clouds. It is suggested that the CALIPSO ice water content retrieval is robust for tropical ice clouds, but that the temperature dependence of the statistical relationship used should be slightly refined to better reproduce the radar–lidar retrievals.


Journal of Applied Meteorology and Climatology | 2013

A Summary of Convective-Core Vertical Velocity Properties Using ARM UHF Wind Profilers in Oklahoma

Scott E. Giangrande; Scott Collis; Jerry M. Straka; Alain Protat; Christopher R. Williams; Steven K. Krueger

This study presents a summary of the properties of deep convective updraft and downdraft cores over the central plains of the United States, accomplished using a novel and now-standard Atmospheric Radiation Measurement Program (ARM) scanning mode for a commercial wind-profiler system. A unique profilerbased hydrometeor fall-speed correction method modeled for the convective environment was adopted. Accuracyofthevelocity retrievalsfromthis effortis expectedtobe within2ms 21 , with minimalbiasandbase core resolution expected near 1km. Updraft cores are found to behave with height in reasonable agreement with aircraft observations of previous continental convection, including those of the Thunderstorm Project. Intense updraft cores with magnitudes exceeding 15ms 21 are routinely observed. Downdraft cores are less frequently observed, with weaker magnitudes than updrafts. Weak, positive correlations are found between updraft intensity (maximum) and updraft diameter length (coefficient r to 0.5 aloft). Negligible correlations are observed for downdraft core lengths and intensity.


Journal of Applied Meteorology and Climatology | 2010

Using Continuous Ground-Based Radar and Lidar Measurements for Evaluating the Representation of Clouds in Four Operational Models

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; Henk-Klein Baltink

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.


Journal of Applied Meteorology and Climatology | 2013

Statistics of Storm Updraft Velocities from TWP-ICE Including Verification with Profiling Measurements

Scott Collis; Alain Protat; Peter T. May; Christopher R. Williams

AbstractComparisons between direct measurements and modeled values of vertical air motions in precipitating systems are complicated by differences in temporal and spatial scales. On one hand, vertically profiling radars more directly measure the vertical air motion but do not adequately capture full storm dynamics. On the other hand, vertical air motions retrieved from two or more scanning Doppler radars capture the full storm dynamics but require model constraints that may not capture all updraft features because of inadequate sampling, resolution, numerical constraints, and the fact that the storm is evolving as it is scanned by the radars. To investigate the veracity of radar-based retrievals, which can be used to verify numerically modeled vertical air motions, this article presents several case studies from storm events around Darwin, Northern Territory, Australia, in which measurements from a dual-frequency radar profiler system and volumetric radar-based wind retrievals are compared. While a direct...


Journal of Atmospheric and Oceanic Technology | 2013

Comparison of Airborne In Situ, Airborne Radar–Lidar, and Spaceborne Radar–Lidar Retrievals of Polar Ice Cloud Properties Sampled during the POLARCAT Campaign

Julien Delanoë; Alain Protat; Olivier Jourdan; Jacques Pelon; Mathieu Papazzoni; R. Dupuy; Jean-François Gayet; Caroline Jouan

AbstractThis study illustrates the high potential of RALI, the French airborne radar–lidar instrument, for studying cloud processes and evaluating satellite products when satellite overpasses are available. For an Arctic nimbostratus ice cloud collected on 1 April 2008 during the Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols, and Transport (POLARCAT) campaign, the capability of this synergistic instrument to retrieve cloud properties and to characterize the cloud phase at scales smaller than a kilometer, which is crucial for cloud process analysis, is demonstrated. A variational approach, which combines radar and lidar, is used to retrieve the ice-water content (IWC), extinction, and effective radius. The combination of radar and lidar is shown to provide better retrievals than do stand-alone methods and, in general, the radar overestimates and the lidar underestimates IWC. As the sampled ice cloud was simultaneously observed by CloudSat and C...


Journal of Applied Meteorology and Climatology | 2014

Reconciling Ground-Based and Space-Based Estimates of the Frequency of Occurrence and Radiative Effect of Clouds around Darwin, Australia

Alain Protat; Stuart Young; Sally A. McFarlane; Tristan S. L'Ecuyer; Gerald G. Mace; Jennifer M. Comstock; Charles N. Long; Elizabeth Berry; Julien Delanoë

The objective of this paper is to investigate whether estimates of the cloud frequency of occurrence and associated cloud radiative forcing as derived from ground-based and satellite active remote sensing and radiative transfer calculations can be reconciled over a well-instrumented active remote sensing site located in Darwin, Australia, despite the very different viewing geometry and instrument characteristics. It is found that the ground-based radar–lidar combination at Darwin does not detect most of the cirrus clouds above 10km (because of limited lidar detection capability and signal obscuration by low-level clouds) and that the CloudSat radar–Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) combination underreports the hydrometeor frequency of occurrence below 2-km height because of instrument limitations at these heights. The radiative impact associated with these differences in cloud frequency of occurrence is large on the surface downwelling shortwave fluxes (ground and satellite) and the top-of-atmosphere upwelling shortwave and longwave fluxes (ground). Good agreement is found for other radiative fluxes. Large differences in radiative heating rate as derived from ground and satellite radar–lidar instruments and radiative transfer calculations are also found above 10km (up to 0.35Kday 21 for the shortwave and 0.8Kday 21 for the longwave). Given that the ground-based and satellite estimates of cloud frequency of occurrence and radiative impact cannot be fully reconciled over Darwin, caution should be exercised when evaluating the representation of clouds and cloud–radiation interactions in large-scale models, and limitations of each set of instrumentation should be considered when interpreting model–observation differences.

Collaboration


Dive into the Alain Protat's collaboration.

Top Co-Authors

Avatar

Julien Delanoë

Centre national de la recherche scientifique

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Julien Delanoë

Centre national de la recherche scientifique

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Alfons Schwarzenboeck

Centre national de la recherche scientifique

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Delphine Leroy

Blaise Pascal University

View shared research outputs
Researchain Logo
Decentralizing Knowledge