The Pyrenean Platform for Observation of the Atmosphere (P2OA) is a coupled plain–mountain instrumented platform in southwestern France. It is composed of two physical sites: the “Pic du Midi” mountaintop observatory (2877 m a.s.l.) and the “Centre de Recherches Atmosphériques” (600 m a.s.l). Both sites are complementarily instrumented for the monitoring of climate-relevant variables and the study of meteorological processes in a mountainous region. The scientific topics covered by P2OA include surface–atmosphere interactions in heterogeneous landscapes and complex terrain, the physics and chemistry of atmospheric trace species at a large scale, the influence of local- and regional-scale emissions and transport on the atmospheric composition, and transient luminous events above thunderstorms. With a large number of instruments and a high hosting capacity, P2OA contributes to atmospheric sciences through (i) building long-term series of atmospheric observations, (ii) hosting experimental field campaigns and instrumental tests, and (iii) educational training in atmospheric observation techniques. In this context, P2OA is part of the French component of the Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS-Fr) and also contributes to the Integrated Carbon Observation System (ICOS) research infrastructure and to several European or international networks. Here, we present the complete instrumentation of P2OA and the associated datasets, give a meteorological characterization of the platform, and illustrate the potential of P2OA and its dataset with past or ongoing studies and projects.

The European Aerosol Research Lidar Network (EARLINET), part of the Aerosols, Clouds and Trace gases Research Infrastructure (ACTRIS), organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during the COVID-19 lockdown and relaxation period. Besides the standard operational processing of the lidar data in EARLINET, for seven EARLINET sites having collocated sun-photometric observations in the Aerosol Robotic Network (AERONET), a network exercise was held in order to derive profiles of the concentration and effective column size distributions of the aerosols in the atmosphere, by applying the GRASP/GARRLiC (from Generalized Aerosol Retrieval from Radiometer and Lidar Combined data – GARRLiC – part of the Generalized Retrieval of Atmosphere and Surface Properties – GRASP) inversion algorithm. The objective of this network exercise was to explore the possibility of identifying the anthropogenic component and of monitoring its spatial and temporal characteristics in the COVID-19 lockdown and relaxation period. While the number of cases is far from being statistically significant so as to provide a conclusive description of the atmospheric aerosols over Europe during this period, this network exercise was fundamental to deriving a common methodology for applying GRASP/GARRLiC to a network of instruments with different characteristics. The limits of the approach are discussed, in particular the missing information close to the ground in the lidar measurements due to the instrument geometry and the sensitivity of the GRASP/GARRLiC retrieval to the settings used, especially for cases with low aerosol optical depth (AOD) like the ones we show here. We found that this sensitivity is well-characterized in the GRASP/GARRLiC products, since it is included in their retrieval uncertainties.

Following the release of the version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version (version 4; V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter and ice or liquid water path estimates. Dedicated retrievals for water clouds were added in V4, taking advantage of the high sensitivity of the IIR retrieval technique to small particle sizes. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results will be presented in a companion (Part II) paper. The IIR Level 2 algorithm has been modified in the V4 data release to improve the accuracy of the retrievals in clouds of very small (close to 0) and very large (close to 1) effective emissivities. To reduce biases at very small emissivities that were made evident in V3, the radiative transfer model used to compute clear-sky brightness temperatures over oceans has been updated and tuned for the simulations using Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) data to match IIR observations in clear-sky conditions. Furthermore, the clear-sky mask has been refined compared to V3 by taking advantage of additional information now available in the V4 CALIOP 5 km layer products used as an input to the IIR algorithm. After sea surface emissivity adjustments, observed and computed brightness temperatures differ by less than ±0.2 K at night for the three IIR channels centered at 08.65, 10.6, and 12.05 µm, and inter-channel biases are reduced from several tens of Kelvin in V3 to less than 0.1 K in V4. We have also improved retrievals in ice clouds having large emissivity by refining the determination of the radiative temperature needed for emissivity computation. The initial V3 estimate, namely the cloud centroid temperature derived from CALIOP, is corrected using a parameterized function of temperature difference between cloud base and top altitudes, cloud absorption optical depth, and CALIOP multiple scattering correction factor. As shown in Part II, this improvement reduces the low biases at large optical depths that were seen in V3 and increases the number of retrievals. As in V3, the IIR microphysical retrievals use the concept of microphysical indices applied to the pairs of IIR channels at 12.05 and 10.6 µm and at 12.05 and 08.65 µm. The V4 algorithm uses ice look-up tables (LUTs) built using two ice habit models from the recent “TAMUice2016” database, namely the single-hexagonal-column model and the eight-element column aggregate model, from which bulk properties are synthesized using a gamma size distribution. Four sets of effective diameters derived from a second approach are also reported in V4. Here, the LUTs are analytical functions relating microphysical index applied to IIR channels 12.05 and 10.6 µm and effective diameter as derived from in situ measurements at tropical and midlatitudes during the Tropical Composition, Cloud, and Climate Coupling (TC4) and Small Particles in Cirrus Science and Operations Plan (SPARTICUS) field experiments.

Abstract. Following the release of the Version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version 4 (V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part II) shows retrievals over ocean and describes the improvements made with respect to version (V3) as a result of the significant changes implemented in the V4 algorithms, which are presented in a companion paper (Part I). The analysis of the three-channel IIR observations (08.65 μm, 10.6 μm, and 12.05 μm) is informed by the scene classification provided in the V4 CALIOP 5-km cloud layer and aerosol layer products. Thanks to the reduction of inter-channel effective emissivity biases in semi-transparent (ST) clouds when the oceanic background radiance is derived from model computations, the number of unbiased emissivity retrievals is increased by a factor 3 in V4. In V3, these biases caused inconsistencies between the effective diameters retrieved from the 12/10 and 12/08 pairs of channels at emissivities smaller than 0.5. In V4, microphysical retrievals in ST ice clouds are possible in more than 80 % of the pixels down to effective emissivities of 0.05 (or visible optical depth ~ 0.1). For the month of January 2008 chosen to illustrate the results, median ice De and ice water path (IWP) are, respectively, 38 µm and 3 g⋅m−2 in ST clouds, with random uncertainty estimates of 50 %. The relationship between the V4 IIR 12/10 and 12/08 microphysical indices is in better agreement with the severely roughened single column ice crystal model than with the severely roughened 8-element aggregate model for 80 % of the pixels in the coldest clouds ( 230 K). Retrievals in opaque ice clouds are improved in V4, especially at night and for 12/10 pair of channels, owing to corrections of the V3 radiative temperature estimates derived from CALIOP geometric altitudes. Median ice De and IWP are 58 µm and 97 g⋅m−2 at night in opaque clouds, with again random uncertainty estimates of 50 %. Comparisons of ice retrievals with Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) in the tropics show a better agreement of IIR De with MODIS visible/3.7 µm than with MODIS visible/2.1 µm in the coldest ST clouds and the opposite for opaque clouds. In prevailingly supercooled liquid water clouds with centroid altitudes above 4 km, retrieved median De and liquid water path are 13 µm and 3.4 g.m−2 in ST clouds, with estimated random uncertainties of 45 % and 35 % respectively. In opaque liquid clouds, these values are 18 µm and 31 g.m−2 at night, with estimated uncertainties of 50 %. IIR De in opaque liquid clouds is smaller than MODIS visible/2.1 and visible/3.7 by 8 µm and 3 µm, respectively.

Recently, the National Ocean Partnership Program funded the phase A of a lidar cubesat mission: Rainbow. This mission aims to provide information about surface height, surface vector winds, sea-ice, coastal land surface and liquid water clouds. Depending on the final system characteristics, it could also contribute to our knowledge of coastal ocean turbidity and ecology. We propose here to focus on the wind vector retrieval. Wind is a major source of momentum to the upper ocean and modulates the coupling between the atmosphere and the ocean. In littoral areas, wind influences economic activities like ship navigation and fisheries. The Lidar can provide a retrieval of wind properties closer to the coastlines and at a finer scale than typical microwave systems. We will present the theoretical basis of how the lidar can retrieve the wind speed through the surface roughness measurement [1] and wind direction from the multistatic measurement of the wave slope asymmetry. It is well known that the upwind and crosswind components of the mean square slope are drastically different [2] and several lidar receivers looking at the laser light coming from different directions will be sensitive to this asymmetry. The CALIPSO lidar mission has conducted several large off-nadir angle maneuvers (10° to 30° off-nadir) that show this signature of wind direction but with a limited ability for retrieval because it's a single monostatic system. We will present a preliminary analysis of these data and an overview of the features of the Rainbow mission that will allow us to retrieve wind vector from a cubesat lidar constellation.

In the context of a network of sky cameras installed on atmospheric multi-instrumented sites, we present an algorithm named ELIFAN, which aims to estimate the cloud cover amount from full-sky visible daytime images with a common principle and procedure. ELIFAN was initially developed for a self-made full-sky image system presented in this article and adapted to a set of other systems in the network. It is based on red-to-blue ratio thresholding for the distinction of cloudy and cloud-free pixels of the image and on the use of a cloud-free sky library, without taking account of aerosol loading. Both an absolute (without the use of a cloud-free reference image) and a differential (based on a cloud-free reference image) red-to-blue ratio thresholding are used. An evaluation of the algorithm based on a 1-year-long series of images shows that the proposed algorithm is very convincing for most of the images, with about 97 % of relevance in the process, outside the sunrise and sunset transitions. During those latter periods, however, ELIFAN has large difficulties in appropriately processing the image due to a large difference in color composition and potential confusion between cloud-free and cloudy sky at that time. This issue also impacts the library of cloud-free images. Beside this, the library also reveals some limitations during daytime, with the possible presence of very small and/or thin clouds. However, the latter have only a small impact on the cloud cover estimate. The two thresholding methodologies, the absolute and the differential red-to-blue ratio thresholding processes, agree very well, with departure usually below 8 % except in sunrise–sunset periods and in some specific conditions. The use of the cloud-free image library gives generally better results than the absolute process. It particularly better detects thin cirrus clouds. But the absolute thresholding process turns out to be better sometimes, for example in some cases in which the sun is hidden by a cloud.

Version 2 of the Level 1b calibrated radiances of the Imaging Infrared Radiometer (IIR) on board the Cloud-Aerosol Lidar and Infrared Satellite Observation (CALIPSO) satellite has been released recently. This new version incorporates corrections of small but systematic seasonal calibration biases previously revealed in Version 1 data products mostly north of 30 degrees N. These biases - of different amplitudes in the three IIR channels 8.65 mu m (IIR1), 10.6 mu m (IIR2), and 12.05 mu m (IIR3) - were made apparent by a striping effect in images of IIR inter-channel brightness temperature differences (BTDs) and through seasonal warm biases of night-time IIR brightness temperatures in the 30-60 degrees N latitude range. The latter were highlighted through observed and simulated comparisons with similar channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua spacecraft. To characterize the calibration biases affecting Version 1 data, a semi-empirical approach is developed, which is based on the in-depth analysis of the IIR internal calibration procedure in conjunction with observations such as statistical comparisons with similar MODIS/Aqua channels. Two types of calibration biases are revealed: an equalization bias affecting part of the individual IIR images and a global bias affecting the radiometric level of each image. These biases are observed only when the temperature of the instrument increases, and they are found to be functions of elapsed time since night-to-day transition, regard-less of the season. Correction coefficients of Version 1 radiances could thus be defined and implemented in the Version 2 code. As a result, the striping effect seen in Version 1 is significantly attenuated in Version 2. Systematic discrepancies between nighttime and daytime IIR-MODIS BTDs in the 30-60 degrees N latitude range in summer are reduced from 0.2 K in Version 1 to 0.1 K in Version 2 for IIR1-MODIS29. For IIR2-MODIS31 and IIR3-MODIS32, they are reduced from 0.4 K to close to zero, except for IIR3-MODIS32 in June, where the night-minus-day difference is around -0.1 K.

The quantification of aerosol and cloud radiative properties, optical depth (OD), and phase function is of high importance to quantify the human impact on climate. Several approaches now exist based on both active (lidar) and passive (spectroradiometers) sensors. However, passive space observations over land are hindered by the important contribution of the surface to the total reflectance. Retrievals of OD from backscatter lidars do not face this issue but are usually based on the use of an a priori value of the so-called lidar ratio, which may lead to a significant uncertainty. The objective of this paper is to analyze a possible path for the space borne backscatter lidar onboard the Cloud Aerosol Lidar Pathfinder Observations satellite to overcome those issues. We will discuss the space-borne retrievals of ODs based on the land surface returns, either in combination with the Moderate Resolution Imaging Spectroradiometer or as a stand-alone lidar method. Analyses will be presented for a few cases on different surface types. The different error sources are discussed and further solutions to reduce them are explored. We show that the surface types have different polarization and multispectral properties, which can open new research areas based on space lidars. Using such an approach, we show that a retrieval technique based on the use of lidar land surface returns can be used to directly retrieve OD of aerosols and semitransparent cloud.

High pollution events frequently occurred in China during the last years, as industrial activity, traffic, and urban heating has been increasing sources of pollutants (gases and particles). High particle concentrations, well above the recommended threshold values have been measured in large urban areas of eastern and southern China. A major contributor to summertime pollution episodes is dust. Main dust sources are located in the western part of China but mineral surface active in dry periods may contribute to aerosol sources over eastern urban areas in winter. To allow a comprehensive regional survey, ground-based measurements have been developed and satellite radiometric observations (as for example MODIS, MISR or OMI) have been extensively used to derive pollution index and particulate matter (PM) concentration estimates from optical properties over the column (aerosol optical depth -AOD-and size information). Satellites have revealed that pollution was extending over large areas at the regional scale, and that they could be used as first estimates of pollution with good accuracy on average. However, the dispersion due to the nature of the particles in space and time, and the sensitivity of their size to relative humidity has been a limitation in this observational approach. To better characterize and predict pollution events, chemical transport models are now used as integration tools to account for aerosol formation and composition, meteorological and physical constraints on links between microphysical and optical particle properties. Matching observed and modeled parameters and understanding biases is however a prerequisite for that. Radiometric satellite AODs have been first used in models, but it has further been shown that the integration of active sensor profiles allowed significant information to be added on the vertical to account for moisture impact, using data from groundbased lidar (acronym of light detection and ranging, also identified as an optical radar) networks and more widely from the space lidar CALIOP (Cloud and Aerosol Lidar with Orthogonal Polarization) onboard CALIPSO (Cloud and Aerosol Lidar and Infrared Pathfinder Space Observations). CALIOP is providing data on aerosol type and distribution which are further expected to bridge the gap between in situ and radiometric remote sensing space observations, better constrain models, and help deriving more accurate retrieval of particle extinction near the surface. Although CALIPSO satellite track and repeat cycle do not allow to revisit the same place within days, the duration and extent of pollution episodes over eastern China is such that CALIOP measurements offer a way to constrain regional models to better analyze such episodes, accounting for a better categorization of aerosols. After discussing the context of observations and analyses, a presentation of satellite analyses is presented in the light of examples on severe winter regional pollution episodes.

This study presents a comparison between the retrieval of optical properties of aerosol above clouds (AAC) from different techniques developed for the A-Train sensors CALIOP/CALIPSO and POLDER/PARASOL. The main objective is to analyse the consistency between the results derived from the active and the passive measurements. We compare the aerosol optical thickness (AOT) above optically thick clouds (cloud optical thickness (COT) larger than 3) and their Ångström exponent (AE). These parameters are retrieved with the CALIOP operational method, the POLDER operational polarization method and the CALIOP-based depolarization ratio method (DRM) – for which we also propose a calibrated version (denominated DRMSODA, where SODA is the Synergized Optical Depth of Aerosols). We analyse 6 months of data over three distinctive regions characterized by different types of aerosols and clouds. Additionally, for these regions, we select three case studies: a biomass-burning event over the South Atlantic Ocean, a Saharan dust case over the North Atlantic Ocean and a Siberian biomass-burning event over the North Pacific Ocean. Four and a half years of data are studied over the entire globe for distinct situations where aerosol and cloud layers are in contact or vertically separated. Overall, the regional analysis shows a good correlation between the POLDER and the DRMSODA AOTs when the microphysics of aerosols is dominated by fine-mode particles of biomass-burning aerosols from southern Africa (correlation coefficient (R2) of 0.83) or coarse-mode aerosols of Saharan dust (R2 of 0.82). A good correlation between these methods (R2 of 0.68) is also observed in the global treatment, when the aerosol and cloud layers are separated well. The analysis of detached layers also shows a mean difference in AOT of 0.07 at 532 nm between POLDER and DRMSODA at a global scale. The correlation between the retrievals decreases when a complex mixture of aerosols is expected (R2 of 0.37) – as in the East Asia region – and when the aerosol–cloud layers are in contact (R2 of 0.36). The correlation coefficient between the CALIOP operational method and POLDER is found to be low, as the CALIOP method largely underestimates the aerosol loading above clouds by a factor that ranges from 2 to 4. Potential biases on the retrieved AOT as a function of cloud properties are also investigated. For different types of scenes, the retrieval of above-cloud AOT from POLDER and from DRM are compared for different underlying cloud properties (droplet effective radius (reff) and COT retrieved with MODIS). The results reveal that DRM AOT vary with reff. When accounting for reff in the DRM algorithm, the consistency between the methods increases. The sensitivity study shows that an additional polarized signal coming from aerosols located within the cloud could affect the polarization method, which leads to an overestimation of the AOT retrieved with POLDER algorithm. In addition, the aerosols attached to or within the cloud can potentially impact the DRM retrievals through the modification of the cloud droplet chemical composition and its ability to backscatter light. The next step of this work is to combine POLDER and CALIOP to investigate the impacts of aerosols on clouds and climate when these particles are transported above or within clouds.

The quality of the calibrated radiances of the medium-resolution Imaging Infrared Radiometer (IIR) on-board the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite is quantitatively evaluated from the beginning of the mission in June 2006. Two complementary relative and stand-alone approaches are used, which are related to comparisons of measured brightness temperatures and to model-to-observations comparisons, respectively. In both cases, IIR channels 1 (8.65 µm), 2 (10.6 µm), and 3 (12.05 µm) are paired with the Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua Collection 5 companion channels 29, 31, and 32, respectively, as well as with the Spinning Enhanced Visible and Infrared Imager (SEVIRI)/Meteosat companion channels IR8.7, IR10.8, and IR12, respectively. These pairs were selected before launch to meet radiometric, geometric, and space-time constraints. The prelaunch studies were based on simulations and sensitivity studies using the 4A/OP radiative transfer model and the more than 2300 atmospheres of the climatological Thermodynamic Initial Guess Retrieval (TIGR) input dataset further sorted into five air mass types. Using data from over 9.5 years of on-orbit operation, and following the relative approach technique, collocated measurements of IIR and of its companion channels have been compared at all latitudes over ocean, during day and night, and for all types of scenes in a wide range of brightness temperatures. The relative approach shows an excellent stability of IIR2–MODIS31 and IIR3–MODIS32 brightness temperature differences (BTDs) since launch. A slight trend within the IIR1–MODIS29 BTD, that equals −0.02 K yr−1 on average over 9.5 years, is detected when using the relative approach at all latitudes and all scene temperatures. For very cold scene temperatures (190–200 K) in the tropics, each IIR channel is warmer than its MODIS companion channel by 1.6 K on average. For the stand-alone approach, clear sky measurements only are considered, which are directly compared with simulations using 4A/OP and collocated ERA-Interim (ERA-I) reanalyses. The clear sky mask is derived from collocated observations from IIR and the CALIPSO lidar. Simulations for clear sky pixels in the tropics reproduce the differences between IIR1 and MODIS29 within 0.02 K and between IIR2 and MODIS31 within 0.04 K, whereas IIR3–MODIS32 is larger than simulated by 0.26 K. The stand-alone approach indicates that the trend identified from the relative approach originates from MODIS29, whereas no trend (less than ±0.004 K yr−1) is identified for any of the IIR channels. Finally, using the relative approach, a year-by-year seasonal bias between nighttime and daytime IIR–MODIS BTD was found at mid-latitude in the Northern Hemisphere. It is due to a nighttime IIR bias as determined by the stand-alone approach, which originates from a calibration drift during day-to-night transitions. The largest bias is in June and July when IIR2 and IIR3 are warmer by 0.4 K on average, and IIR1 is warmer by 0.2 K.

Abstract. The quality of the calibrated radiances of the medium-resolution Imaging Infrared Radiometer (IIR) on-board the CALIPSO satellite is quantitatively controlled since the beginning of the mission in June 2006. Two complementary “relative” and “stand-alone” approaches are used, which are related to comparisons of measured brightness temperatures, and to model-to-observations comparisons, respectively. In both cases, IIR channels 1 (8.65 μm), 2 (10.6 μm), and 3 (12.05 μm) are paired with MODIS/Aqua “companion” channels 29, 31, and 32, respectively, as well as with SEVIRI/Meteosat companion channels IR8.7, IR10.8 and IR12, respectively. These pairs were selected before launch to meet radiometric, geometric and space-time constraints. The pre-launch studies were based on simulations and sensitivity studies using the 4A/OP radiative transfer model fed with the more than 2300 atmospheres of the climatological TIGR dataset further sorted out in five air mass types. Over the 9.5 years of operation since launch, in a semi-operational process, collocated measurements of IIR and of its companion channels have been compared at all latitudes over ocean, during day and night, and for all types of scenes in a wide range of brightness temperatures when dealing with the relative approach. The relative approach shows an excellent stability of IIR2-MODIS31 and IIR3-MODIS32 brightness temperature differences (BTD) since launch A slight trend of the IIR1-MODIS29 BTD, equal to −0.02 K/year on average over 9.5 years, is detected by the relative approach at all latitudes and all scene temperatures. For the stand-alone approach, clear sky measurements only are considered, which are directly compared with simulations using 4A/OP and collocated ERA-Interim reanalyses. The clear sky mask is derived from collocated observations from IIR and the CALIPSO lidar. Simulations for clear sky pixels in the tropics reproduce the differences between IIR1 and MODIS29 within 0.02 K, and between IIR2 and MODIS31 within 0.04 K, whereas IIR3-MODIS32 is larger than simulated by 0.26 K. The stand-alone approach indicates that the trend identified from the relative approach originates from MODIS29, whereas no trend (less than ±0.004 K/year) is evidenced for any of the IIR channels. Finally, a year-by-year seasonal bias between nighttime and daytime IIR-MODIS BTDs was found at mid-latitude in the northern hemisphere by the relative approach. It is due to a nighttime IIR bias as determined by the stand-alone approach, which originates from a calibration drift during day-to-night transitions. The largest bias is in June/July with IIR2 and IIR3 too warm by 0.4 K on average, and IIR1 too warm by 0.2 K.

In the past few years, we have demonstrated how the surface return measured by the active instruments onboard CloudSat and CALIPSO could be used to retrieve the optical depth and backscatter phase function (lidar ratio) of aerosols and ice clouds. This methodology lead to the development of a data fusion product publicly available at the ICARE archive center using the Synergized Optical Depth of Aerosols and Ice Clouds (SODA & ICE) algorithm1. This algorithm, also allowing to derive ocean surface wind speed, has been extended to include dense cloud surface return to analyze aerosol and cloud properties above such clouds. This low level data fusion of CALIPSO and CloudSat ocean surface echoes has been used by several researchers to explore different research paths. Among them, we can cite: • A new characterization of the lidar ratio of cirrus clouds2 • The analysis of the precipitable water and development of a new Millimeter-Wave Propagation Model for the W-Band observations (EMPIRIMA3) • The analysis of the lidar ratio of sea-spray aerosols4, and of Aerosol multilayer lidar ratio and extinction5 • A contribution to the retrieval of the subsurface particulate backscatter coefficients of phytoplankton particles6 In this paper, we present the main features of SODA & ICE, summarizing some of the results obtained. This low level data fusion of CALIPSO and CloudSat ocean surface echoes has been used by several researchers to explore different research paths. Among them, we can cite: A new characterization of the lidar ratio of cirrus clouds2 The analysis of the precipitable water and development of a new Millimeter-Wave Propagation Model for the W-Band observations (EMPIRIMA3) The analysis of the lidar ratio of sea-spray aerosols4, and of Aerosol multilayer lidar ratio and extinction5 A contribution to the retrieval of the subsurface particulate backscatter coefficients of phytoplankton particles6 In this paper, we present the main features of SODA & ICE, summarizing some of the results obtained.

Satellite data are increasingly used to provide observation-based estimates of the effects of aerosols on climate. The Aerosol-cci project, part of the European Space Agency's Climate Change Initiative (CCI), was designed to provide essential climate variables for aerosols from satellite data. Eight algorithms, developed for the retrieval of aerosol properties using data from AATSR (4), MERIS (3) and POLDER, were evaluated to determine their suitability for climate studies. The primary result from each of these algorithms is the aerosol optical depth (AOD) at several wavelengths, together with the Ångström exponent (AE) which describes the spectral variation of the AOD for a given wavelength pair. Other aerosol parameters which are possibly retrieved from satellite observations are not considered in this paper. The AOD and AE (AE only for Level 2) were evaluated against independent collocated observations from the ground-based AERONET sun photometer network and against “reference” satellite data provided by MODIS and MISR. Tools used for the evaluation were developed for daily products as produced by the retrieval with a spatial resolution of 10×10km2 (Level 2) and daily or monthly aggregates (Level 3). These tools include statistics for L2 and L3 products compared with AERONET, as well as scoring based on spatial and temporal correlations. In this paper we describe their use in a round robin (RR) evaluation of four months of data, one month for each season in 2008. The amount of data was restricted to only four months because of the large effort made to improve the algorithms, and to evaluate the improvement and current status, before larger data sets will be processed. Evaluation criteria are discussed. Results presented show the current status of the European aerosol algorithms in comparison to both AERONET and MODIS and MISR data. The comparison leads to a preliminary conclusion that the scores are similar, including those for the references, but the coverage of AATSR needs to be enhanced and further improvements are possible for most algorithms. None of the algorithms, including the references, outperforms all others everywhere. AATSR data can be used for the retrieval of AOD and AE over land and ocean. PARASOL and one of the MERIS algorithms have been evaluated over ocean only and both algorithms provide good results.

The EMEP network aims at providing scientific supporton atmospheric monitoring and modelling, emissioninventories and projections, and integrated assessmentmodelling. To reach these objectives, it has encouragedlong- and short-term measurement periods in order toimprove the scientific knowledge on PM levels, sourcesand formation processes at the European scale.Within this framework and in coordination withthe existing ChArMEx French program and ACTRIS EUproject, two intensive periods have been held betweenJune 8 and July 12, 2012 for summer and January 11 toFebruary 8, 2013 for winter. Five locations in France (cf.Figure 1) were equipped with various on-line and offlineinstruments (cf. Table 1) aiming at measuring PMchemical and physical properties, as well as precursorgases (both organic and inorganic).The main objectives of these two campaigns wereto (i) provide a large quality controlled database of PMlevels and chemical composition for sites under rural,mid-altitude, urban or marine influences during twocontrasted seasons; (ii) measure simultaneously PMcompounds and their precursors to better understandprocesses such as secondary organic aerosols (SOA)formation or condensation of semi-volatile species; (iii)assess the importance of vertical exchanges in thevariability of PM ground levels, especially in case ofdust events; (iv) determine PM sources and their relativecontributions.Preliminary results will be presented anddiscussed.

This paper describes the version-3 level-2 operational analysis of the Imaging Infrared Radiometer (IIR) data collected in the framework of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission to retrieve cirrus cloud effective diameter and ice water path in synergy with the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) collocated observations. The analysis uses a multisensor split-window technique relying on the concept of microphysical index applied to the two pairs of channels (12.05, 10.6 m) and (12.05, 8.65 m) to retrieve cirrus microphysical properties (effective diameter, ice water path) at 1-km pixel resolution. Retrievals are performed for three crystal families selected from precomputed lookup tables identified as representative of the main relationships between the microphysical indices. The uncertainties in the microphysical indices are detailed and quantified, and the impact on the retrievals is simulated. The possible biases have been assessed through consistency checks that are based on effective emissivity difference. It has been shown that particle effective diameters of single-layered cirrus clouds can be retrieved, for the first time, down to effective emissivities close to 0.05 when accurate measured background radiances can be used and up to 0.95 over ocean and land, as well as over low opaque clouds. The retrieval of the ice water path from the IIR effective optical depth and the effective diameter is discussed. Taking advantage of the cloud boundaries retrieved by CALIOP, an IIR power-law relationship between ice water content and extinction is established for four temperature ranges and shown to be consistent with previous results on average for the chosen dataset.

Cirrus clouds are of particular importance for the understanding and the survey of climate change due to their impact on the Earth radiation budget. However, their optical and microphysical properties are still poorly known. The NASA-CNES CALIPSO mission provides new pieces of information by combining observations of active (lidar) and passive (radiometer) remote sensing instruments. Cirrus cloud optical depths derived in the thermal infrared (12 μm) from the IIR are found in excellent agreement with those retrieved in the visible spectrum (532 nm) from the CALIOP lidar, down to optical depths smaller than 0.05. The ice water paths derived from the two instruments use very different approaches, and show a highly correlated linear relationship. On average, CALIOP retrievals are 1.7 times larger than IIR estimates, requiring further studies.

The paper describes the operational analysis of the Imaging Infrared Radiometer (IIR) data, which have been collected in the framework of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CA LIPSO) mission for the purpose of retrieving high-altitude (above 7 km) cloud effective emissivity and optical depth that can be used in synergy with the vertically resolved Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) collocated observations. After an IIR scene classification is built under the CALIOP track, the analysis is applied to features detected by CALIOP when found alone in the atmospheric column or when CALIOP identifies an opaque layer underneath. The fast-calculation radiative transfer (FASRAD) model fed by ancillary meteorological and surface data is used to compute the different components involved in the effective emissivity retrievals under the CALIOP track. The track analysis is extended to the IIR swath using homogeneity criteria that are based on radiative equivalence. The effective optical depth at 12.05 mu m is shown to be a good proxy for about one-half of the cloud optical depth, allowing direct comparisons with other databases in the visible spectrum. A step-by-step quantitative sensitivity and performance analysis is provided. The method is validated through comparisons of collocated IIR and CALIOP optical depths for elevated single-layered semitransparent cirrus clouds, showing excellent agreement (within 20%) for values ranging from 1 down to 0.05. Uncertainties have been determined from the identified error sources. The optical depth distribution of semitransparent clouds is found to have a nearly exponential shape with a mean value of about 0.5-0.6.