Ice crystal number concentration estimates from lidar-radar satellite retrievals. Part 2: Controls on the ice crystal number concentration

The ice crystal number concentration (Ni) is a keyproperty of ice clouds, both radiatively and microphysically.Due to sparse in situ measurements of ice cloud properties,the controls on theNihave remained difficult to determine.As more advanced treatments of ice clouds are included inglobal models, it is becoming increasingly necessary to de-velop strong observational constraints on the processes in-volved.This work uses the DARDAR-NiceNiretrieval describedin Part 1 to investigate the controls on theNiat a globalscale. The retrieved clouds are separated by type. The ef-fects of temperature, proxies for in-cloud updraft and aerosolconcentrations are investigated. Variations in the cloud topNi(Ni(top)) consistent with both homogeneous and hetero-geneous nucleation are observed along with differing rela-tionships between aerosol andNi(top)depending on the pre-vailing meteorological situation and aerosol type. Away fromthe cloud top, theNidisplays a different sensitivity to thesecontrolling factors, providing a possible explanation for thelowNisensitivity to temperature and ice nucleating particles(INP) observed in previous in situ studies.This satellite dataset provides a new way of investigat-ing the response of cloud properties to meteorological andaerosol controls. The results presented in this work increaseour confidence in the retrievedNiand will form the basis for further study into the processes influencing ice and mixedphase clouds

La solidarité écologique : un nouveau concept pour une gestion intégrée des parcs nationaux et des territoires

Cet article propose une première exploration du nouveau concept de solidarité écologique introduit dans le droit de l'environnement lors de la réforme de la loi sur les parcs nationaux français en 2006. Nous montrons que ce concept polysémique, tirant les enseignements de l'application de la loi de 1960, se fonde sur la prise de conscience des interdépendances du vivant et une nouvelle vision de la conservation de la nature. La solidarité écologique permet d'asseoir un compromis pragmatique entre écocentrisme et anthropocentrisme. Fondée sur les évolutions conceptuelles de l'écologie de la conservation, la solidarité écologique se décline selon une typologie qui intègre les enjeux de l'hétérogénéité spatiotemporelle de la biodiversité. Elle donne sens à l'élaboration des réseaux écologiques nationaux et internationaux et à la gestion intégrée des territoires de la biodiversité. La mise en débat public de ses spécificités locales et des valeurs qui lui sont attachées est nécessaire afin d'assurer sa considération et sa préservation

Ice crystal number concentration estimates from lidar–radar satellite remote sensing – Part 2: Controls on the ice crystal number concentration

The ice crystal number concentration (Ni) is a key property of ice clouds, both radiatively and microphysically. Due to sparse in situ measurements of ice cloud properties, the controls on the Ni have remained difficult to determine. As more advanced treatments of ice clouds are included in global models, it is becoming increasingly necessary to develop strong observational constraints on the processes involved.This work uses the DARDAR-Nice Ni retrieval described in Part 1 to investigate the controls on the Ni at a global scale. The retrieved clouds are separated by type. The effects of temperature, proxies for in-cloud updraft and aerosol concentrations are investigated. Variations in the cloud top Ni (Ni(top)) consistent with both homogeneous and heterogeneous nucleation are observed along with differing relationships between aerosol and Ni(top) depending on the prevailing meteorological situation and aerosol type. Away from the cloud top, the Ni displays a different sensitivity to these controlling factors, providing a possible explanation for the low Ni sensitivity to temperature and ice nucleating particles (INP) observed in previous in situ studies.This satellite dataset provides a new way of investigating the response of cloud properties to meteorological and aerosol controls. The results presented in this work increase our confidence in the retrieved Ni and will form the basis for further study into the processes influencing ice and mixed phase clouds.</p

Lidar–radar synergistic method to retrieve ice, supercooled water and mixed-phase cloud properties

Mixed-phase clouds are not well represented in climate and weather forecasting models, due to a lack of the key processes controlling their life cycle. Developing methods to study these clouds is therefore essential, despite the complexity of mixed-phase cloud processes and the difficulty of observing two cloud phases simultaneously. We propose in this paper a new method to retrieve the microphysical properties of mixed-phase clouds, ice clouds and supercooled water clouds using airborne or satellite radar and lidar measurements, called VarPy-mix. This new approach extends an existing variational method developed for ice cloud retrieval using lidar, radar and passive radiometers. We assume that the lidar attenuated backscatter β at 532 nm is more sensitive to particle concentration and is consequently mainly sensitive to the presence of supercooled water. In addition, radar reflectivity Z at 95 GHz is sensitive to the size of hydrometeors and hence more sensitive to the presence of ice particles. Consequently, in the mixed phase the supercooled droplets are retrieved with the lidar signal and the ice particles with the radar signal, meaning that the retrievals rely strongly on a priori and error values. This method retrieves simultaneously the visible extinction for ice αice and liquid αliq particles, the ice and liquid water contents IWC and LWC, the effective radius of ice re,ice and liquid re,liq particles, and the ice and liquid number concentrations Nice and Nliq. Moreover, total extinction αtot, total water content (TWC) and total number concentration Ntot can also be estimated. As the retrieval of ice and liquid is different, it is necessary to correctly identify each phase of the cloud. To this end, a cloud-phase classification is used as input to the algorithm and has been adapted for mixed-phase retrieval. The data used in this study are from DARDAR-MASK v2.23 products, based on the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) observations from the CALIPSO and CloudSat satellites, respectively, belonging to the A-Train constellation launched in 2006. Airborne in situ measurements performed on 7 April 2007 during the Arctic Study of Tropospheric Aerosol, Clouds and Radiation (ASTAR) campaign and collected under the track of CloudSat–CALIPSO are compared with the retrievals of the new algorithm to validate its performance. Visible extinctions, water contents, effective radii and number concentrations derived from in situ measurements and the retrievals showed similar trends and are globally in good agreement. The mean percent error between the retrievals and in situ measurements is 39 % for αliq, 398 % for αice, 49 % for LWC and 75 % for IWC. It is also important to note that temporal and spatial collocations are not perfect, with a maximum spatial shift of 1.68 km and a maximum temporal shift of about 10 min between the two platforms. In addition, the sensitivity of remote sensing and that of in situ measurements is not the same, and in situ measurement uncertainties are between 25 % and 60 %.</p

SIRTA, a ground-based atmospheric observatory for cloud and aerosol research

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 T&amp;#233;l&amp;#233;d&amp;#233;tection Atmosph&amp;#233;rique (SIRTA), an atmospheric observatory with these goals in mind. Today SIRTA, located 20km 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. CloudSat 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