Nicolas Pascal

Retrieval of Cloud Properties Using CALIPSO Imaging Infrared Radiometer. Part I: Effective Emissivity and Optical Depth

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 (CALIPSO) 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 m mi s 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.

Retrieval of Cloud Properties Using CALIPSO Imaging Infrared Radiometer. Part II: Effective Diameter and Ice Water Path

AbstractThis 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 μm) and (12.05, 8.65 μm) 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...

On the Use of CALIPSO Land Surface Returns to Retrieve Aerosol and Cloud Optical Depths

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.

Space Observation of Aerosols from Satellite Over China During Pollution Episodes: Status and Perspectives

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 ground-based 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.

Ocean and polarization observations from active remote sensing: atmospheric and ocean science applications

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.

Cirrus cloud properties from combined IIR and lidar observations of CALIPSO

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.