Julien Delanoë

Cloudnet: Continuous Evaluation of Cloud Profiles in Seven Operational Models Using Ground-Based Observations

Cloud fraction, liquid and ice water contents derived from long-term radar, lidar and microwave radiometer data are systematically compared to models to quantify and improve their performance.

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

AbstractThe 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 European Space Agency (ESA)–Japan Aerospace Exploration Agency (JAXA) Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) satellite mission, scheduled for launch in 2018, 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, Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Aqua. Specifically, EarthCARE’s c...

Evaluation of Ice Water Content Retrievals from Cloud Radar Reflectivity and Temperature Using a Large Airborne In Situ Microphysical Database

Abstract The objective of this paper is to assess the performances of the proposed ice water content (IWC)–radar reflectivity Z and IWC–Z–temperature T relationships for accurate retrievals of IWC from radar in space or at ground-based sites, in the framework of the forthcoming CloudSat spaceborne radar, and of the European CloudNET and U.S. Atmospheric Radiation Measurement Program projects. For this purpose, a large airborne in situ microphysical database is used to perform a detailed error analysis of the IWC–Z and IWC–Z–T methods. This error analysis does not include the error resulting from the mass–dimension relationship assumed in these methods, although the expected magnitude of this error is bounded in the paper. First, this study reveals that the use of a single IWC–Z relationship to estimate IWC at global scale would be feasible up to −15 dBZ, but for larger reflectivities (and therefore larger IWCs) different sets of relationships would have to be used for midlatitude and tropical ice clouds. ...

Frequency of occurrence of rain from liquid-, mixed- and ice-phase clouds derived from A-Train satellite retrievals

A climatology of thermodynamic phase of precipitating cloud is presented derived from global, land and ocean, retrievals from Cloudsat, CALIPSO, and MODIS. Like precipitation rate, precipitation frequency is dominated by warm rain, defined as rain produced via the liquid phase only, over the tropical oceans outside the ITCZ and by cold rain, produced via the ice phase, over the midlatitude oceans and continents. Warm rain is very infrequent over the continents, with significant warm rain found only in onshore flow in the tropics, and over India, China, and Indochina. Comparison of the properties of precipitating and non-precipitating warm clouds shows that the scarcity of warm rain over land can be explained by smaller effective radii in continental clouds that delay the onset of precipitation. The results highlight the importance of ice-phase processes for the global hydrological cycle and may lead to an improved parameterization of precipitation in general circulation models.

A study on the low-altitude clouds over the Southern Ocean using the DARDAR-MASK

[1]xa0A climatology of the thermodynamic phase of the clouds over the Southern Ocean (40–65°S,100–160°E) has been constructed with the A-Train merged data product DARDAR-MASK for the four-year period 2006–2009 during Austral winter and summer. Low-elevation clouds with little seasonal cycle dominate this climatology, with the cloud tops commonly found at heights less than 1 km. Such clouds are problematic for the DARDAR-MASK in that the Cloud Profiling Radar (CPR) of CloudSat is unable to distinguish returns from the lowest four bins (heights up to 720–960 m), and the CALIOP lidar of CALIPSO may suffer from heavy extinction. The CPR is further limited for all of the low-altitude clouds (tops below 3 km) as they are predominantly in the temperature range from 0°C to −20°C, where understanding the CPR reflectivity becomes difficult due to the unknown thermodynamic phase. These shortcomings are seen to flow through to the merged CloudSat-CALIPSO product. A cloud top phase climatology comparison has been made between CALIPSO, the DARDAR-MASK and MODIS. All three products highlight the extensive presence of supercooled liquid water over the Southern Ocean, particularly during summer. The DARDAR-MASK recorded substantially more ice at cloud tops as well as mixed-phase in the low-elevation cloud tops in comparison to CALIPSO and MODIS. Below the cloud top through the body of the cloud, the DARDAR-MASK finds ice to be dominant at heights greater than 1 km, especially once the lidar signal is attenuated. The limitations demonstrated in this study highlight the continuing challenge that remains in better defining the energy and water budget over the Southern Ocean.

The vertical cloud structure of the West African monsoon: A 4 year climatology using CloudSat and CALIPSO

The West African summer monsoon (WAM) is an important driver of the global climate and locally provides most of the annual rainfall. A solid climatological knowledge of the complex vertical cloud structure is invaluable to forecasters and modelers to improve the understanding of the WAM. In this paper, 4 years of data from the CloudSat profiling radar and CALIPSO are used to create a composite zonal mean vertical cloud and precipitation structure for the WAM. For the first time, the near-coincident vertical radar and lidar profiles allow for the identification of individual cloud types from optically thin cirrus and shallow cumulus to congestus and deep convection. A clear diurnal signal in zonal mean cloud structure is observed for the WAM, with deep convective activity enhanced at night producing extensive anvil and cirrus, while daytime observations show more shallow cloud and congestus. A layer of altocumulus is frequently observed over the Sahara at night and day, extending southward to the coastline, and the majority of this cloud is shown to contain supercooled liquid in the top. The occurrence of deep convective systems and congestus in relation to the position of the African easterly jet is studied, but only the daytime cumulonimbus distribution indicates some influence of the jet position.

Impact of conditional sampling and instrumental limitations on the statistics of cloud properties derived from cloud radar and lidar at SIRTA

[1]xa0Clouds represent the largest uncertainty in future climate projections. As a result, unbiased long-term vertically-resolved cloud observations must be collected and analyzed in order to produce regional cloud climatologies. In the present study, we use model outputs to evaluate the impact of conditional temporal sampling and instrumental effects on the 2-year statistics of frequency of cloud occurrence and cloud fraction. We then quantify the radiative significance of the ice clouds undetected by cloud radars. We find that in order to evaluate the representation of all types of clouds in operational models both a cloud radar and a lidar must be used. The cloud radar alone can do a reasonable job at describing cloud properties up to 8–9 km, however the lidar is mandatory to detect most of the high-altitude clouds above 9 km. The sampling should be regular but not necessarily continuous, and should not be driven by meteorological conditions. This result applies to all sites having a lidar without a radome. It is finally suggested that a cloud radar of around −60 dBZ sensitivity at 1 km range would be required to detect almost all radiatively-significant ice clouds.

Normalized particle size distribution for remote sensing application

The ice particle size distribution (PSD) is fundamental to the quantitative description of a cloud. It is also crucial in the development of remote sensing retrieval techniques using radar and/or lidar measurements. The PSD allows one to link characteristics of individual particles (area, mass, and scattering properties) to characteristics of an ensemble of particles in a sampling volume (e.g., visible extinction (σ), ice water content (IWC), and radar reflectivity (Z)). The aim of this study is to describe a normalization technique to represent the PSD. We update an earlier study by including recent in situ measurements covering a large variety of ice clouds spanning temperatures ranging between −80°C and 0°C. This new data set also includes direct measurements of IWC. We demonstrate that it is possible to scale the PSD in size space by the volume-weighted diameter Dm and in the concentration space by the intercept parameter inline image and obtain the intrinsic shape of the PSD. Therefore, by combining inline image, Dm, and a modified gamma function representing the normalized PSD shape, we are able to approximate key cloud variables (such as IWC) as well as cloud properties which can be remotely observed (such as Z) with an absolute mean relative error smaller than 20%. The underlying idea is to be able to retrieve the PSD using two independent measurements. We also propose parameterizations for ice cloud key parameters derived from the normalized PSD. We also investigate the effects of uncertainty present in the ice crystal mass-size relationships on the parameterizations and the normalized PSD approach.

Multifrequency Radar Observations Collected in Southern France during HyMeX-SOP1

An ambitious radar deployment to collect high-quality observations of heavy precipitation systems developing over and in the vicinity of a coastal mountain chain is discussed.

Synergies and complementarities of CloudSat‐CALIPSO snow observations

[1]xa0Four years (2007–2010) of colocated 94u2009GHz CloudSat radar reflectivities and 532u2009nm CALIPSO Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) backscattering coefficients are used to globally characterize snow-precipitating clouds. CALIOP is particularly useful for the detection of mixed and supercooled liquid water (SLW) layers. Liquid layers are common in snow precipitating clouds: overall/over sea/over land 49%/57%/33% of the snowy profiles present SLW or mixed-phase layers. The spatial and seasonal dependencies of our results—with snowing clouds more likely to be associated with mixed phase during summer periods—are related to snow layer top temperatures. SLW occurs within the majority (>80%) of snow-precipitating clouds with cloud tops warmer than 250u2009K, and is present 50% of the time when the snow-layer top temperature is about 240u2009K. There is a marked tendency for such layers to occur close to the top of the snow-precipitating layer (75% of the times within 500u2009m). Both instruments can be synergetically used for profiling ice-phase-only snow, especially for light snow (Z<0 dBZ, S<0.16 mm/h) when CALIOP is capable of penetrating, on average, more than half of the snow layer depth. These results have profound impact for deepening our understanding of ice nucleation and snow growth processes, for improving active and passive snow remote sensing techniques, and for planning snow-precipitation missions.