[Show abstract][Hide abstract] ABSTRACT: Clouds still remain the largest source of uncertainty in model-based predictions of future climate, thus the description of the clouds in climate models needs to be evaluated. In particular, the cloud detailed vertical distribution that impacts directly the cloud radiative effect needs to be evaluated. Active satellite sensors directly measure the cloud vertical distribution with high accuracy; their observations should be used for model evaluation together with a satellite simulator in order to allow fair comparison between models and observations. The next cloud lidar in space, EarthCARE/ATLID, is planned for launch in 2018, while the current spaceborne cloud lidar CALIPSO/CALIOP is expected to stop collecting data within the next coming years. Here we describe the characteristics of the ATLID lidar onboard the EarthCARE satellite (spatial resolution, SNR, wavelength, field of view, PRF, orbit, HSRL) that need to be taken into account to build a COSP/ATLID simulator. We then present the COSP/ATLID simulator, and the Low, Mid, High level cloud covers it produces, as well as the zonal mean cloud fraction profiles and the Height-intensity histograms that are simulated by COSP/ATLID when overflying an atmosphere predicted by LMDZ5 GCM. Finally, we compare the clouds simulated by COSP/ATLID with those simulated by COSP/CALIPSO when overflying the same atmosphere. As the main differences between ATLID and CALIOP are taken into account in the simulators, the differences between COSP/ATLID and COSP/CALIPSO clouds covers are less than 1% in night time conditions.
Journal of Geophysical Research Atmospheres 09/2015; DOI:10.1002/2015JD023919 · 3.43 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: 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 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 cloud profiling 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 multispectral 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 km)2 scale by comparing the multiview broadband radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains.
Bulletin of the American Meteorological Society 08/2015; 96(8):1311–1332. · 11.57 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Precipitation isotopologues recorded in natural archives from the southern Tibetan Plateau may document past variations of Indian monsoon intensity. The exact processes controlling the variability of precipitation isotopologue composition must therefore first be deciphered and understood. This study investigates how atmospheric convection affects the summer variability of δ 18O in precipitation (δ 18O p ) and δD in water vapor (δ D v ) at the daily scale. This is achieved using isotopic data from precipitation samples at Lhasa, isotopic measurements of water vapor retrieved from satellites (Tropospheric Emission Spectrometer (TES), GOSAT) and atmospheric general circulation modeling. We reveal that both δ 18O p and δ D v at Lhasa are well correlated with upstream convective activity, especially above northern India. First, during days of strong convection, northern India surface air contains large amounts of vapor with relatively low δ D v . Second, when this low‐δ D v moisture is uplifted toward southern Tibet, this initial depletion in HDO is further amplified by Rayleigh distillation as the vapor moves over the Himalayan. The intraseasonal variability of the isotopologue composition of vapor and precipitation over the southern Tibetan Plateau results from these processes occurring during air mass transportation. Upstream convection controls isotopic compositionIsotopic composition is more influenced by encountered convectionCondensation over foothill is the most important process
[Show abstract][Hide abstract] ABSTRACT: The Arctic radiation balance is strongly affected by clouds and surface albedo. Prior work has identified Arctic cloud liquid water path (LWP) and surface radiative flux biases in the Community Atmosphere Model, version 5 (CAM5), and reductions to these biases with improved mixed-phase ice nucleation schemes. Here, CAM5 net top-of-atmosphere (TOA) Arctic radiative flux biases are quantified along with the contributions of clouds, surface albedos, and new mixed-phase ice nucleation schemes to these biases. CAM5 net TOA all-sky shortwave (SW) and outgoing longwave radiation (OLR) fluxes are generally within 10 W m−2 of Clouds and the Earth’s Radiant Energy System Energy Balanced and Filled (CERES-EBAF) observations. However, CAM5 has compensating SW errors: Surface albedos over snow are too high while cloud amount and LWP are too low. Use of a new CAM5 Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar simulator that corrects an error in the treatment of snow crystal size confirms insufficient cloud amount in CAM5 year-round. CAM5 OLR is too low because of low surface temperature in winter, excessive atmospheric water vapor in summer, and excessive cloud heights year-round. Simulations with two new mixed-phase ice nucleation schemes—one based on an empirical fit to ice nuclei observations and one based on classical nucleation theory with prognostic ice nuclei—improve surface climate in winter by increasing cloud amount and LWP. However, net TOA and surface radiation biases remain because of increases in midlevel clouds and a persistent deficit in cloud LWP. These findings highlight challenges with evaluating and modeling Arctic cloud, radiation, and climate processes.
Journal of Climate 07/2014; 27(13):5174–5197. DOI:10.1175/JCLI-D-13-00608.1 · 4.44 Impact Factor
[Show abstract][Hide abstract] ABSTRACT:  Level 1 measurements, including cross-polarized backscatter, from the Cloud-Aerosol Lidar with Orthogonal Polarization lidar, have been used to document the vertical structure of the cloud thermodynamic phase at global scale. We built a cloud phase identification (liquid, ice, or undefined) in the Global Climate Model (GCM)–oriented Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud Product (GOCCP) and analyzed the spatial distribution of liquid and ice clouds in five January, February, March (JFM) seasons of global-scale observations (2007–2011). We developed a cloud phase diagnosis in the Cloud Feedback Model Intercomparison Program Observation Simulator Package to evaluate the cloud phase description in the LMDZ5B climate model. The diagnosis in the simulator is fully consistent with the CALIPSO-GOCCP observations to ensure that differences between the observations and the “model + simulator” ensemble outputs can be attributed to model biases. We compared the liquid and ice cloud vertical distributions simulated by the model with and without the simulator to quantify the impact of the simulator. The model does not produce liquid clouds above 3 km and produces ice instead of liquid at low and middle altitudes in polar regions, as well as along the Intertropical Convergence Zone. The model is unable to replicate the observed coexistence of liquid and ice cloud between 0°C and −40°C. Liquid clouds dominate T > −21°C in the observations, T > −12°C in the model + simulator, and T > −7.5°C in the model parameterization. Even if the simulator shifts the model cloud phase parameterization to colder temperature because of the lidar instrument peculiarities, the cloud phase transition remains too warm compared to the observations.
[Show abstract][Hide abstract] ABSTRACT: Clouds cover about 70% of the Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the entire globe and across the wide range of spatial and temporal scales that comprise weather and climate variability.
cloud data records now exceed more than 25 years; however, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors. The Global Energy and Water cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel, provides the first coordinated intercomparison of publicly available, global cloud products (gridded, monthly statistics) retrieved from measurements of multi-spectral imagers (some with multi-angle view and polarization capabilities), IR sounders and lidar. Cloud
properties under study include cloud amount, cloud height (in terms of pressure, temperature or altitude), cloud radiative properties (optical depth or emissivity), cloud
thermodynamic phase and bulk microphysical properties (effective particle size and water path). Differences in average cloud
properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. The monthly, gridded database presented here facilitates further assessments, climate studies, and the evaluation of climate models.
International Radiation Symposium on Radiation Processes in the; 05/2013
[Show abstract][Hide abstract] ABSTRACT: Evaluation of clouds in climate models is essential judging from the
strong impact of clouds on the earth's radiation budget. Cloud phase
influences many cloud properties and leads to different cloud
interactions with the climate system. Since june 2006, CALIPSO satellite
has provided new measurements of backscattered lidar profiles, which
have been used to evaluate the cloud description in CMIP5 climate models
through a lidar simulator (CFMIP Observation Simulator Package, COSP).
In this study, we present results of this evaluation focused on vertical
structure of clouds, global coverage and coverage above "hard to observe
regions" such as the desert and polar regions, and partition between
liquid and ice in clouds. The total cloud cover is underestimated in
all models and continental cloud covers (at low, mid, high altitudes)
are highly variable depending on the model. In the tropics, all models
underestimate the low cloud amount and none of them correctly simulate
the top of deep convective compare to observations. In the Arctic, the
modelled low cloud amounts are slightly biased compared to observations
and seasonal variation not reproduced. Thanks to a new cloud phase
diagnosis in the GCM-Oriented CALIPSO Cloud Product (GOCCP) and its
counterpart within the lidar simulator, we evaluate the cloud phase in
LMDZ5B model. Comparisons show that, contrary to ice clouds, liquid
clouds are largely underestimated in the model. Liquid clouds occur at
temperatures as cold as -40°C in the observations, but only as cold
as -20°C in the model. They are dominant at temperatures warmer than
-21°C in observations but only warmer than -12°C in the model.
In agreement with theory, statistical observations show that liquid and
ice co-exist between 0°C and -40°C, and that the cloud phase
depends not only on the temperature but also on humidity. For
comparison, ice and liquid do not co-exist in the model, and the
modelled cloud phase does not reproduce the observed sensitivity to the
atmospheric humidity. A specific focus on Arctic region shows that a
lack of liquid-containing Arctic clouds contributes to a lack of
"radiatively opaque" states in LMDZ5B model. The surface radiation
biases found in this one model are found in multiple models,
highlighting the need for improved modelling of Arctic cloud phase.
Further analysis will use learning from this study to investigate how
changes in the LMDZ5B cloud phase parameterization (and possibly other
models) impact cloud fractions, temperatures and fluxes for inter-annual
and long term period simulations.
[Show abstract][Hide abstract] ABSTRACT: Tropical islands, such as Reunion Island (21°S, 55.5°E) in the southwestern Indian Ocean, have significant solar resource that is highly variable in both spatial and temporal scales because of heterogeneous and rapidly changing cloudiness. The characterization of this variability is essential to enhance penetration of solar energy systems, such as photovoltaic or thermal farms. This work focuses on the large-scale, meso-scale and local-scale variability in cloudiness and surface solar irradiance at different temporal scales. Vertical velocity at 500 hPa from ERA-Interim reanalyses are used to study large-scale subsidence. CALIPSO, MODIS and Meteosat-7 satellite observations are used to study cloud properties and associated irradiances at the meso-scale. Solar irradiance measurements at seven Meteo-France stations around Reunion Island are used to investigate three meteorologically-distinct regions, namely the windward and leeward coasts, and the coasts parallel to the general trade wind direction. Day-to-day variations in daily irradiation values and diurnal-scale variability of solar irradiances are seasonally dependent. Winter seasons are characterized by large-scale atmospheric subsidence and broken low-level cloudiness, while in summer, clouds are found both at low and high altitudes. Three parameters are introduced to characterize solar irradiance diurnal cycle regimes. Five physically-sensible regimes are found, identified as clear, morning clear, overcast, afternoon clear, and random cloudiness. Regime occurrences have marked seasonal dependencies and vary significantly between the windward, leeward and lateral coasts. In winter and early summer, when cloudiness is driven predominantly by local (thermal, orographic) processes, the aggregated solar daily irradiation (average of the seven ground stations) remains near 80% of the clear-sky irradiation. In late summer, this values drops below 65% as large-scale overcast systems regularly affect the entire island. The station-to-station dis-correlation distance in terms of daily clear-sky index, defined as the distance for which the correlation coefficient drops to 0.5, is 62 km in summer and 29 km in winter. For hourly clear-sky indexes, the station-to-station dis-correlation distances is 4 and 3 km, for summer and winter, respectively. Accordingly, aggregate analyses show that compensation effects are more important at hourly than daily time scales. The measurements also reveal that the atmosphere over the island tends to be clearer in the morning than in the afternoon while over the ocean surrounding the island, the opposite is true. These results provide insights and tools to help develop improved diurnal-scale solar irradiance forecast systems for tropical islands.
Solar Energy 02/2013; 88:42-56. DOI:10.1016/j.solener.2012.11.007 · 3.47 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: This paper aims at characterizing how different key cloud properties (cloud fraction, cloud vertical distribution, cloud reflectance, a surrogate of the cloud optical depth) vary as a function of the others over the tropical oceans. The correlations between the different cloud properties are built from 2 years of collocated A-train observations (CALIPSO-GOCCP and MODIS) at a scale close to cloud processes; it results in a characterization of the physical processes in tropical clouds, that can be used to better understand cloud behaviors, and constitute a powerful tool to develop and evaluate cloud parameterizations in climate models. First, we examine a case study of shallow cumulus cloud observed simultaneously by the two sensors (CALIPSO, MODIS), and develop a methodology that allows to build global scale statistics by keeping the separation between clear and cloudy areas at the pixel level (250, 330 m). Then we build statistical instantaneous relationships between the cloud cover, the cloud vertical distribution and the cloud reflectance. The vertical cloud distribution indicates that the optically thin clouds (optical thickness <1.5) dominate the boundary layer over the trade wind regions. Optically thick clouds (optical thickness >3.4) are composed of high and mid-level clouds associated with deep convection along the ITCZ and SPCZ and over the warm pool, and by stratocumulus low level clouds located along the East coast of tropical oceans. The cloud properties are analyzed as a function of the large scale circulation regime. Optically thick high clouds are dominant in convective regions (CF > 80 %), while low level clouds with low optical thickness (<3.5) are present in regimes of subsidence but in convective regimes as well, associated principally to low cloud fractions (CF < 50 %). A focus on low-level clouds allows us to quantify how the cloud optical depth increases with cloud top altitude and with cloud fraction.
[Show abstract][Hide abstract] ABSTRACT: CALIOP is the first lidar to monitor the Earth from space autonomously and continuously. Since its laser first fired in April 2006, it has been docu- menting atmospheric particles: aero- sols, liquid cloud droplets, ice crystals. In this article, we describe the scientific discoveries CALIOP helped make possible about atmospheric crystals: vertical struc- ture of ice clouds, global maps, micro- physical properties (shape and orientation), the link between ice crystals and water vapour in the Tropics, and crystals in the polar stratosphere...
[Show abstract][Hide abstract] ABSTRACT: The interannual variability of cloud properties in a tropical subsidence area (South Atlantic Ocean) is examined using 23 years of ISCCP cloud fractions and optical depths, complemented with ISCCP/Meteosat visible reflectance and a four-years comparison with CALIPSO-GOCCP products. The mean seasonal cloud properties are examined in the area, as their interannual evolution. Circulation regimes (characterized with the SST and w500 from NCEP and ERA-Interim) that dominate summer and winter are also examined, and atmospheric situations are classified in five circulation regimes: ascending air masses, and moderate or strong subsidence with warm or cold SSTs. We examine the mean cloud cover, optical depth, and reflectance in each regime and their evolution in time over 23 years. Observational results (mean values and interannual variability) are compared with simulations from the IPSL and CNRM climate models (part of the CMIP5 experiment), using simulators to ensure that differences can be attributed to model defects. It results that regime occurrence strongly depends on the dataset (NCEP or ERA-Interim), as do their evolution in time along 23 years. The observed cloud cover is stable in time and weakly regime-dependent, whereas the cloud optical depth and reflectance are clearly regime-dependent. Some cloud properties trends actually do exist only in some particular regimes. Compared to observations, models underestimate cloud cover and overestimate cloud optical depth and reflectance. Climate models poorly reproduce regime occurrence and their evolution in time, as well as variations in cloud properties associated with regime change. It means that errors in the simulation of clouds from climate models are firstly due to errors in the simulation of the dynamic and thermodynamic environmental conditions.
[Show abstract][Hide abstract] ABSTRACT: A Saharan dust event affected the Rhine valley in southwestern Germany and eastern France on 1 August 2007 during the Convective and Orographically-induced Precipitation Study (COPS) experiment. Prior to an episode of intense convection, a layer of dry, clean air capped by a moist, dusty layer was observed using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite
Observation (CALIPSO), airborne and ground-based lidar observations from North Africa to western Europe. The origin of the different layers was investigated using the regional model Meso-NH. For the purpose of modeling evaluation, a lidar simulator was
developed for directly comparing observed and simulated vertical structures of the lidar backscattered signal. Overall, the model reproduced the vertical structure of dust probed at several times by the different lidar systems during its long-range transport. From Lagrangian back trajectories it was found that the dust was mobilized from sources inMauritania six days earlier, while the dry layer subsided over the north Atlantic. Off the Moroccan coasts, the dry layer folded down beneath the dusty airmass and the two-layer
structure was advected to the Rhine valley in about two days. By heating the atmosphere, the dust layer changed the static stability of the atmosphere and thus the occurrence of convection. A sensitivity study to the radiative effect of dust indeed shows a better prediction of precipitation when a dust prognostic scheme was used rather than climatology or when dust effects were ignored. This result suggests that dust episodes that occur prior to convective events might be important for quantitative precipitation forecasts.
[Show abstract][Hide abstract] ABSTRACT: A Saharan dust event affected the Rhine valley in southwestern Germany and eastern France on 1 August 2007 during the Convective and Orographically induced Precipitation Study (COPS) experiment. Prior to an episode of intense convection, a layer of dry, clean air capped by a moist, dusty layer was observed using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and airborne and ground-based lidar observations from North Africa to western Europe. The origin of the different layers was investigated using the regional model Meso-NH. For the purpose of modelling evaluation, a lidar simulator was developed for direct comparison of observed and simulated vertical structures of the lidar backscattered signal. Overall, the model reproduced the vertical structure of dust probed several times by the different lidar systems during its long-range transport. From Lagrangian back trajectories it was found that the dust was mobilized from sources in Mauritania six days earlier, while the dry layer subsided over the north Atlantic. Off the Moroccan coasts, the dry layer folded down beneath the dusty air mass and the two-layer structure was advected to the Rhine valley in about two days. By heating the atmosphere, the dust layer changed the static stability of the atmosphere and thus the occurrence of convection. A study of sensitivity to the radiative effect of dust showed a better prediction of precipitation when a dust prognostic scheme was used rather than climatology or when dust effects were ignored. This result suggests that dust episodes that occur prior to convective events might be important for quantitative precipitation forecasts
Quarterly Journal of the Royal Meteorological Society 01/2011; 137(S1). DOI:10.1002/qj.719 · 3.25 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We analyze optical signatures in 18 months of CALIOP layer-integrated backscatter and depolarization ratio to investigate the geographical and seasonal distribution of oriented crystals in ice clouds on a global scale. Oriented crystals are found to be rare: they appear in ∼6% of all ice cloud layers, and inside these layers the proportion of oriented crystals is estimated below 5%, even though they have a significant effect on the cloud optical properties. The geographical pattern of crystal orientation is very stable over the year, without any noticeable cycle. We investigate the atmospheric conditions which might lead to crystal orientation, including synoptic-scale dynamics and thermodynamic profiles. In the tropics, detections of crystal orientation are more numerous in areas dominated by convection on a monthly basis, and at midlatitudes less numerous in areas dominated by strong horizontal winds. Synoptic effects, however, appear secondary; orientation is primarily driven by temperature. Oriented crystals are mostly nonexistent in ice clouds colder than −30°C, and very frequent in warmer ice clouds, appearing in 30% of such clouds in the tropics and up to 50% at higher latitudes. The temperatures where oriented crystals are found (−30°C to −10°C) are conducive to the formation of planar crystals. Results suggest oriented crystals are more frequent just above cloud base in slightly thicker cloud layers, which might provide clues to how and why orientation takes place.
Journal of Geophysical Research Atmospheres 05/2010; 115(10). DOI:10.1029/2009JD012365 · 3.43 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Observations of trace gases and aerosols from satellite remote sensing provide essential information on pollution emissions and transport. IASI/METOP allows the global monitoring of several key species for atmospheric chemistry analysis, with unprecedented spatial sampling and coverage. Its ability to detect a large series of species within fire plumes has recently been demonstrated, and could significantly improve current evaluation of the impact of such extreme pollution events on air quality. Aerosol observations from several remote sensors on board satellites of the A-Train (MODIS, POLDER/PARASOL, CALIOP/CALIPSO) are also now commonly used for the analysis of the long-range transport of pollution. In this presentation, we will discuss the information provided by the carbon monoxide (CO) retrievals, one of the main species measured by IASI, on fire emissions transport mechanisms and pathways. Therefore, IASI retrievals will be compared to simulations from the CHIMERE regional chemistry and transport model for the case study of the large fires which burned in Greece during August 2007. We will then present an analysis of the constraint provided by IASI on chemistry within the transported plumes using the retrievals for the shorter lived species and for ozone. Finally, the IASI observations will be coupled to the aerosol observations from the PARASOL mission in order to assess the impact of this specific fire event on air quality in the Euro-Mediterranean region (both PM2.5 and ozone).