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M. Chiriaco, H. Chepfer, V. Noel, M. Haeffelin, and P. Drobinski

Abstract

To improve the estimation of the infrared radiances in cirrus clouds, one needs to consider the vertical inhomogeneities of the cloud properties. The position of the maximum of absorption within an ice cloud is potentially important to the improvement of the split-window techniques for retrieving particle size and for understanding the radiative effect of the cloud in the infrared spectrum. Current remote sensing techniques used for inferring ice clouds hardly reach the level of accuracy required to resolve the vertical inhomogeneities of a cloud and to determine the position of absorption. This study explores the possibility of retrieving the vertical structures of ice clouds by combining data from two lidar measurements acquired at the wavelengths of 532 nm and 10.6 μm. A method is proposed to retrieve the variability of ice crystal absorption efficiency at 10.6 μm, the particle concentration weighted by the crystal area, and the attenuation by absorption at 10.6 μm. The method is tested against observations collected at Site Instrumental de Recherche en Télédétection Atmosphérique (SIRTA) in Palaiseau, France. Observations and simulations both show that lidar observations collected simultaneously at those two wavelengths can be used to determine the level within the ice cloud where maximum attenuation of infrared radiation occurs. The maximum attenuation may occur near the cloud base or the cloud top, depending on the case studied.

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Y. Morille, M. Haeffelin, P. Drobinski, and J. Pelon

Abstract

Today several lidar networks around the world provide large datasets that are extremely valuable for aerosol and cloud research. Retrieval of atmospheric constituent properties from lidar profiles requires detailed analysis of spatial and temporal variations of the signal. This paper presents an algorithm called Structure of the Atmosphere (STRAT), which is designed to retrieve the vertical distribution of cloud and aerosol layers in the boundary layer and through the free troposphere and to identify near-particle-free regions of the vertical profile and the range at which the lidar signal becomes too attenuated for exploitation, from a single lidar channel. The paper describes each detection method used in the STRAT algorithm and its application to a tropospheric backscatter lidar operated at the SIRTA observatory, in Palaiseau, 20 km south of Paris, France. STRAT retrievals are compared to other means of layer detection and classification; retrieval performances and uncertainties are discussed.

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O. Coindreau, F. Hourdin, M. Haeffelin, A. Mathieu, and C. Rio

Abstract

The Laboratoire de Météorologie Dynamique atmospheric general circulation model with zooming capability (LMDZ) has been used in a nudged mode to enable comparison of model outputs with routine observations and evaluate the model physical parameterizations. Simulations have been conducted with a stretched grid refined over the vicinity of Paris, France, where observations, collected at the Trappes station (Météo-France) and at the Site Instrumental de Recherche par Télédétection Atmosphérique observatory, are available. For the purpose of evaluation of physical parameterizations, the large-scale component of the modeled circulation is adjusted toward ECMWF analyses outside the zoomed area only, whereas the inside region can evolve freely. A series of sensitivity experiments have been performed with different parameterizations of land surface and boundary layer processes. Compared with previous versions of the LMDZ model, a “thermal plume model,” in association with a constant resistance to evaporation improves agreement with observations. The new parameterization significantly improves the representation of seasonal and diurnal cycles of near-surface meteorology, the day-to-day variability of planetary boundary layer height, and the cloud radiative forcing. This study emphasizes the potential of using a climate model with a nudging and zooming capability to assess model physical parameterizations.

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M. Chiriaco, H. Chepfer, V. Noel, A. Delaval, M. Haeffelin, P. Dubuisson, and P. Yang

Abstract

This study is intended to illustrate the potential advantage of combining lidar measurements and the split-window technique based on the infrared spectral information contained at the 8.65-, 11.15-, and 12.05-μm bands for inferring the microphysical properties of cirrus clouds. The lidar returns are employed to detect cirrus clouds. The optical properties of nonspherical ice crystals computed from the state-of-the-art scattering computational methods are used for the present forward radiative transfer simulation that fully accounts for both gaseous absorption and multiple scattering processes in the atmosphere. A combination of the radiances at the three infrared (IR) bands with lidar backscatter returns cannot uniquely specify the effective size of ice crystals because of its dependence on the particle aspect ratios. To avoid the shortcoming associated with a potential multivalued retrieval, lidar depolarization observation is used to constrain the specification of the particle aspect ratio in the retrieval implementation based on a precalculated lookup library.

The present methodology for inferring the microphysical properties of cirrus clouds is implemented for nine cases by using the measurements from a 532-nm lidar located at the Palaiseau, France, ground-based site and the infrared spectral bands from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra platform. It is shown that the three IR wavelengths are quite complementary in constraining the retrieval of the particle size, leading to a significant advance in comparison with two-channel techniques, whereas the aspect ratio constraint due to lidar depolarization reduces the uncertainty of retrieved particle size by more than 20% for 70% of the cases and more than 65% for 40% of the cloud cases.

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M. Chiriaco, R. Vautard, H. Chepfer, M. Haeffelin, J. Dudhia, Y. Wanherdrick, Y. Morille, and A. Protat

Abstract

The ability of the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) to simulate midlatitude ice clouds is evaluated. Model outputs are compared to long-term meteorological measurements by active (radar and lidar) and passive (infrared and visible fluxes) remote sensing collected at an atmospheric observatory near Paris, France. The goal is to understand which of four microphysical schemes is best suited to simulate midlatitude ice clouds. The methodology consists of simulating instrument observables from the model outputs without any profile inversion, which allows the authors to use fewer assumptions on microphysical and optical properties of ice particles.

Among the four schemes compared in the current study, the best observation-to-simulations scores are obtained with Reisner et al. provided that the particles’ sedimentation velocity from Heymsfield and Donner is used instead of that originally proposed. For this last scheme, the model gives results close to the measurements for clouds with medium optical depth of typically 1 to 3, whatever the season. In this configuration, MM5 simulates the presence of midlatitude ice clouds in more than 65% of the authors’ selection of observed cloud cases. In 35% of the cases, the simulated clouds are too persistent whatever the microphysical scheme and tend to produce too much solid water (ice and snow) and not enough liquid water.

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M. Haeffelin, S. Crewell, A. J. Illingworth, G. Pappalardo, H. Russchenberg, M. Chiriaco, K. Ebell, R. J. Hogan, and F. Madonna
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A. J. Illingworth, D. Cimini, C. Gaffard, M. Haeffelin, V. Lehmann, U. Löhnert, E. J. O’Connor, and D. Ruffieux

Abstract

A new generation of high-resolution (1 km) forecast models promises to revolutionize the prediction of hazardous weather such as windstorms, flash floods, and poor air quality. To realize this promise, a dense observing network, focusing on the lower few kilometers of the atmosphere, is required to verify these new forecast models with the ultimate goal of assimilating the data. At present there are insufficient systematic observations of the vertical profiles of water vapor, temperature, wind, and aerosols; a major constraint is the absence of funding to install new networks. A recent research program financed by the European Union, tasked with addressing this lack of observations, demonstrated that the assimilation of observations from an existing wind profiler network reduces forecast errors, provided that the individual instruments are strategically located and properly maintained. Additionally, it identified three further existing European networks of instruments that are currently underexploited, but with minimal expense they could deliver quality-controlled data to national weather services in near–real time, so the data could be assimilated into forecast models. Specifically, 1) several hundred automatic lidars and ceilometers can provide backscatter profiles associated with aerosol and cloud properties and structures with 30-m vertical resolution every minute; 2) more than 20 Doppler lidars, a fairly new technology, can measure vertical and horizontal winds in the lower atmosphere with a vertical resolution of 30 m every 5 min; and 3) about 30 microwave profilers can estimate profiles of temperature and humidity in the lower few kilometers every 10 min. Examples of potential benefits from these instruments are presented.

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M. Chiriaco, H. Chepfer, P. Minnis, M. Haeffelin, S. Platnick, D. Baumgardner, P. Dubuisson, M. McGill, V. Noël, J. Pelon, D. Spangenberg, S. Sun-Mack, and G. Wind

Abstract

This study compares cirrus-cloud properties and, in particular, particle effective radius retrieved by a Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)-like method with two similar methods using Moderate-Resolution Imaging Spectroradiometer (MODIS), MODIS Airborne Simulator (MAS), and Geostationary Operational Environmental Satellite imagery. The CALIPSO-like method uses lidar measurements coupled with the split-window technique that uses the infrared spectral information contained at the 8.65-, 11.15-, and 12.05-μm bands to infer the microphysical properties of cirrus clouds. The two other methods, using passive remote sensing at visible and infrared wavelengths, are the operational MODIS cloud products (using 20 spectral bands from visible to infrared, referred to by its archival product identifier MOD06 for MODIS Terra) and MODIS retrievals performed by the Clouds and the Earth’s Radiant Energy System (CERES) team at Langley Research Center (LaRC) in support of CERES algorithms (using 0.65-, 3.75-, 10.8-, and 12.05-μm bands); the two algorithms will be referred to as the MOD06 and LaRC methods, respectively. The three techniques are compared at two different latitudes. The midlatitude ice-clouds study uses 16 days of observations at the Palaiseau ground-based site in France [Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA)], including a ground-based 532-nm lidar and the MODIS overpasses on the Terra platform. The tropical ice-clouds study uses 14 different flight legs of observations collected in Florida during the intensive field experiment known as the Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL-FACE), including the airborne cloud-physics lidar and the MAS. The comparison of the three methods gives consistent results for the particle effective radius and the optical thickness but discrepancies in cloud detection and altitudes. The study confirms the value of an active remote sensing method (CALIPSO like) for the study of subvisible ice clouds, in both the midlatitudes and Tropics. Nevertheless, this method is not reliable in optically very thick tropical ice clouds, because of their particular microphysical properties.

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A. J. Illingworth, D. Cimini, A. Haefele, M. Haeffelin, M. Hervo, S. Kotthaus, U. Löhnert, P. Martinet, I. Mattis, E. J. O’Connor, and R. Potthast

Abstract

To realize the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog, and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few kilometers are hardly accessible by satellite, especially in dynamically active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real time to forecast centers. The three classes of instruments are i) automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog, and volcanic ash, the last two being especially important for air traffic control; ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind gusts, and low-level jets; and iii) microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. The project includes collaboration from 22 European countries and 15 European national weather services, which involves the implementation of common operating procedures, instrument calibrations, data formats, and retrieval algorithms. Currently, data from 265 ceilometers in 19 countries are being distributed in near–real time to national weather forecast centers; this should soon rise to many hundreds. One wind lidar is currently delivering real time data rising to 5 by the end of 2019, and the plan is to incorporate radiometers in 2020. Initial data assimilation tests indicate a positive impact of the new data.

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J.-Ph. Duvel, M. Viollier, P. Raberanto, R. Kandel, M. Haeffelin, L. A. Pakhomov, V. A. Golovko, J. Mueller, R. Stuhlmann, and the International ScaRaB Scientific Working Group

Measurements made by the second flight model of the Scanner for Radiation Budget (ScaRaB) instrument have been processed and are now available for the scientific community. Although this set of data is relatively short and sparse, it is of excellent quality and is the only global broadband scanner radiance information for the period between October 1998 and April 1999. This second flight model marks the conclusion of the ScaRaB cooperative program of France, Russia, and Germany. The two flight models of the ScaRaB instrument gave broadband radiance measurements comparable in quality to those made by the Earth Radiation Budget Experiment and the Clouds and Earth Radiant Energy System scanning instruments. In addition, the ScaRaB instrument gave unique results for the comparison between narrowband (visible and infrared atmospheric window) and broadband radiance measurements. These measurements were mostly used to improve the broadband data processing and to study the error budget resulting when narrowband channel data are used to estimate the earth radiation budget. These concomitant narrow- and broadband measurements made by the two flight models of ScaRaB contain original information of considerable interest for further scientific use.

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