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 ESA-JAXA EarthCARE satellite mission, scheduled for launch in 2017, 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, CALIPSO, and Aqua. Specifically, EarthCARE's Cloud Profling 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 Multi-Spectral 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 km2) scale by comparing the multi-view Broad-Band Radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains.

/pdf/the-earthcare-satellite-the-next-step-forward-in-global-4w19jz39pk.pdf

The EarthCARE Satellite: The Next Step Forward in Global Measurements of Clouds, Aerosols, Precipitation, and Radiation

A compact, highly robust airborne High Spectral Resolution Lidar (HSRL) that provides measurements of aerosol backscatter and extinction coefficients and aerosol depolarization at two wavelengths has been developed, tested, and deployed on nine field experiments (over 650 flight hours). A unique and advantageous design element of the HSRL system is the ability to radiometrically calibrate the instrument internally, eliminating any reliance on vicarious calibration from atmospheric targets for which aerosol loading must be estimated. This paper discusses the design of the airborne HSRL, the internal calibration and accuracy of the instrument, data products produced, and observations and calibration data from the first two field missions: the Joint Intercontinental Chemical Transport Experiment--Phase B (INTEX-B)/Megacity Aerosol Experiment--Mexico City (MAX-Mex)/Megacities Impacts on Regional and Global Environment (MILAGRO) field mission (hereafter MILAGRO) and the Gulf of Mexico Atmospheric Composition and Climate Study/Texas Air Quality Study II (hereafter GoMACCS/TexAQS II).

Airborne High Spectral Resolution Lidar for profiling aerosol optical properties

The European Aerosol Research Lidar Network, EARLINET, was founded in 2000 as a research project for establishing a quantitative, comprehensive, and statistically significant database for the horizontal, vertical, and tempo- ral distribution of aerosols on a continental scale. Since then EARLINET has continued to provide the most extensive col- lection of ground-based data for the aerosol vertical distribu- tion over Europe. This paper gives an overview of the network's main de- velopments since 2000 and introduces the dedicated EAR- LINET special issue, which reports on the present innova- tive and comprehensive technical solutions and scientific re- sults related to the use of advanced lidar remote sensing tech- niques for the study of aerosol properties as developed within the network in the last 13 years. Since 2000, EARLINET has developed greatly in terms of number of stations and spatial distribution: from 17 sta- tions in 10 countries in 2000 to 27 stations in 16 countries in 2013. EARLINET has developed greatly also in terms of technological advances with the spread of advanced multi- wavelength Raman lidar stations in Europe. The develop- ments for the quality assurance strategy, the optimization of instruments and data processing, and the dissemination of data have contributed to a significant improvement of the net- work towards a more sustainable observing system, with an increase in the observing capability and a reduction of oper- ational costs. Consequently, EARLINET data have already been ex- tensively used for many climatological studies, long-range transport events, Saharan dust outbreaks, plumes from vol- canic eruptions, and for model evaluation and satellite data validation and integration. Future plans are aimed at continuous measurements and near-real-time data delivery in close cooperation with other ground-based networks, such as in the ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) www.actris.net, and with the modeling and satellite commu- nity, linking the research community with the operational world, with the aim of establishing of the atmospheric part of the European component of the integrated global observ- ing system.

https://www.dwd.de/DWD/forschung/projekte/ceilomap/files/amt-7-2389-2014.pdf

EARLINET: towards an advanced sustainable European aerosol lidar network

. The NASA Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL) on the NASA B200 aircraft has acquired extensive datasets of aerosol extinction (532 nm), aerosol optical depth (AOD) (532 nm), backscatter (532 and 1064 nm), and depolarization (532 and 1064 nm) profiles during 18 field missions that have been conducted over North America since 2006. The lidar measurements of aerosol intensive parameters (lidar ratio, depolarization, backscatter color ratio, and spectral depolarization ratio) are shown to vary with location and aerosol type. A methodology based on observations of known aerosol types is used to qualitatively classify the extensive set of HSRL aerosol measurements into eight separate types. Several examples are presented showing how the aerosol intensive parameters vary with aerosol type and how these aerosols are classified according to this new methodology. The HSRL-based classification reveals vertical variability of aerosol types during the NASA ARCTAS field experiment conducted over Alaska and northwest Canada during 2008. In two examples derived from flights conducted during ARCTAS, the HSRL classification of biomass burning smoke is shown to be consistent with aerosol types derived from coincident airborne in situ measurements of particle size and composition. The HSRL retrievals of AOD and inferences of aerosol types are used to apportion AOD to aerosol type; results of this analysis are shown for several experiments.

/pdf/aerosol-classification-using-airborne-high-spectral-2aq5zbqyza.pdf

Aerosol classification using airborne High Spectral Resolution Lidar measurements – methodology and examples

[1] In this paper, data from spaceborne radar, lidar and infrared radiometers on the “A‐Train” of satellites are combined in a variational algorithm to retrieve ice cloud properties. The method allows a seamless retrieval between regions where both radar and lidar are sensitive to the regions where one detects the cloud. We first implement a cloud phase identification method, including identification of supercooled water layers using the lidar signal and temperature to discriminate ice from liquid. We also include rigorous calculation of errors assigned in the variational scheme. We estimate the impact of the microphysical assumptions on the algorithm when radiances are not assimilated by evaluating the impact of the change in the area‐diameter and the density‐diameter relationships in the retrieval of cloud properties. We show that changes to these assumptions affect the radar‐only and lidar‐only retrieval more than the radar‐lidar retrieval, although the lidar‐only extinction retrieval is only weakly affected. We also show that making use of the molecular lidar signal beyond the cloud as a constraint on optical depth, when ice clouds are sufficiently thin to allow the lidar signal to penetrate them entirely, improves the retrieved extinction. When infrared radiances are available, they provide an extra constraint and allow the extinction‐to‐backscatter ratio to vary linearly with height instead of being constant, which improves the vertical distribution of retrieved cloud properties.

/pdf/combined-cloudsat-calipso-modis-retrievals-of-the-properties-4w9c3trsp9.pdf

Combined CloudSat-CALIPSO-MODIS retrievals of the properties of ice clouds

The high spectral resolution lidar (HSRL) measures optical properties of atmospheric aerosols by interferometrically separating the elastic aerosol backscatter from the Doppler broadened molecular contribution. Calibration and data analysis procedures developed for the HSRL are described. Data obtained during flight evaluation testing of the HSRL system are presented with estimates of uncertainties due to instrument calibration. HSRL measurements of the aerosol scattering cross section are compared with in situ integrating nephelometer measurements.

High spectral resolution lidar to measure optical scattering properties of atmospheric aerosols. 2: Calibration and data analysis

A scanning lidar system has been used to observe convection in the atmospheric boundary layer. In particular, cell sizes and geometry have been determined and circulation patterns in and around the cells have been measured. The lidar data show that the preferred form of convective cells are plumes with roots near the surface. The majority of these plumes have aspects ratios between 0.5 and 1.5. The measurements of circulation patterns show the strongest rising motion on the upwind side of the cell with sinking motion on the downwind side. These observations show that lidar is a powerful tool for observing convection.

Lidar Observations of the Convective Boundary Layer

Normalized scattering phase functions and extinction efficiencies for homogeneous dielectric spheres with size parameters 200 ≤ x ≤ 4520 and refractive index m = 1.333 − Oi are calculated directly from Mie theory. The results are compared to predictions cited in the literature. Averages of the angular structure and magnitude of the glory are given as a function of the dimensionless size parameter. The periods and amplitudes of regular oscillations in the backscatter phase function are determined. Distinct backscattering oscillations with periods Δx ≃ 0.41, 0.83, 1.1, and 14 are found.

A numerical study of scattering by large dielectric spheres

Monostatic lidar is explored as a means for determining the rainfall rate over an extended atmospheric path with a spatial resolution comparable to that of rain gages. An empirical relationship is established between the optical extinction coefficient of rain βr (km−1) and the rainfall rate R (mm hr−1). Correlation of lidar-derived rainfall extinction and gage rainfall rates at Madison gives βr = 0.16 R0.74. The βr-R relations obtained from the work of other authors compare well with this relationship. A lidar equation which accounts for the multiple scattering of light in rain is presented. A numerical procedure which derives estimates of βr as a function of range from lidar returns is developed. Examples of lidar-derived rainfall rate range profiles in spatially inhomogeneous thunderstorms are given.

Measurement of Rainfall Rates by Lidar

A Solution for Multiple Scattering

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