Vincent Noel

Polar stratospheric clouds over Antarctica from the CALIPSO spaceborne lidar

[1]xa0This paper presents statistics of polar stratospheric clouds (PSCs) above Antarctica from June to October 2006 using observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) spaceborne lidar, part of the CALIPSO mission. Synoptic-scale changes in geographic and temporal distribution are documented weekly and correlated with temperature fields. A high spatial and temporal variability tends to contradict the hypothesis that PSCs are mostly created via slow processes mainly governed by large-scale temperature changes. Linear depolarization ratios reveal strongly typed PSCs with distinct characteristics (implying different microphysics), but unique cloud compositions cannot be singled out. A west/east imbalance is observed in the depolarization distribution, symptomatic of microphysical disparities. A classification based on depolarization and scattering ratios suggests more than 60% of mixed PSCs, followed by more than 20% of STS, and a roughly equal concentration of nitric acid trihydrate (NAT)-based and pure ice PSCs (∼8%). Up to the beginning of August, supercooled ternary solution (STS) PSCs experience a steady decrease in concentration correlated with an increase in ice-based and mixed PSCs; this tendency gets reversed after the first week of August, hinting at the existence of a large-scale seasonal cycle in PSC population.

Using in-situ airborne measurements to evaluate three cloud phase products derived from CALIPSO

We compare the cloud detection and cloud phase determination of three independent climatologies based on Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) to airborne in situ measurements. Our analysis of the cloud detection shows that the differences between the satellite and in situ measurements mainly arise from three factors. First, averaging CALIPSO Level l data along track before cloud detection increases the estimate of high- and low-level cloud fractions. Second, the vertical averaging of Level 1 data before cloud detection tends to artificially increase the cloud vertical extent. Third, the differences in classification of fully attenuated pixels among the CALIPSO climatologies lead to differences in the low-level Arctic cloud fractions. In another section, we compare the cloudy pixels detected by colocated in situ and satellite observations to study the cloud phase determination. At midlatitudes, retrievals of homogeneous high ice clouds by CALIPSO data sets are very robust (more than 94.6% of agreement with in situ). In the Arctic, where the cloud phase vertical variability is larger within a 480u2009m pixel, all climatologies show disagreements with the in situ measurements and CALIPSO-General Circulation Models-Oriented Cloud Product (GOCCP) report significant undefined-phase clouds, which likely correspond to mixed-phase clouds. In all CALIPSO products, the phase determination is dominated by the cloud top phase. Finally, we use global statistics to demonstrate that main differences between the CALIPSO cloud phase products stem from the cloud detection (horizontal averaging, fully attenuated pixels) rather than the cloud phase determination procedures.

Where and when will we observe cloud changes due to climate warming

Climate models predict that the geographic distribution of clouds will change in response to anthropogenic warming, though uncertainties in the existing satellite record are larger than the magnitude of the predicted effects. Here we argue that cloud vertical distribution, observable by active spaceborne sensors, is a more robust signature of climate change. Comparison of Atmospheric Model Intercomparison Project present day and +4u2009K runs from Coupled Model Intercomparison Project Phase 5 shows that cloud radiative effect and total cloud cover do not represent robust signatures of climate change, as predicted changes fall within the range of variability in the current observational record. However, the predicted forced changes in cloud vertical distribution (directly measurable by spaceborne active sensors) are much larger than the currently observed variability and are expected to first appear at a statistically significant level in the upper troposphere, at all latitudes.

CALIPSO observations of wave‐induced PSCs with near‐unity optical depth over Antarctica in 2006–2007

[1]xa0Ground-based and satellite observations have hinted at the existence of polar stratospheric clouds (PSCs) with relatively high optical depths, even if optical depth values are hard to come by. This study documents a type II PSC observed from spaceborne lidar, with visible optical depths up to 0.8. Comparisons with multiple temperature fields, including reanalyses and results from mesoscale simulations, suggest that intense small-scale temperature fluctuations due to gravity waves play an important role in its formation, while nearby observations show the presence of a potentially related type Ia PSC farther downstream inside the polar vortex. Following this first case, the geographic distribution and microphysical properties of PSCs with optical depths above 0.3 are explored over Antarctica during the 2006 and 2007 austral winters. These clouds are rare (less than 1% of profiles) and concentrated over areas where strong winds hit steep ground slopes in the Western Hemisphere, especially over the peninsula. Such PSCs are colder than the general PSC population, and their detection is correlated with daily temperature minima across Antarctica. Lidar and depolarization ratios within these clouds suggest they are most likely ice-based (type II). Similarities between the case study and other PSCs suggest they might share the same formation mechanisms.

Direct atmosphere opacity observations from CALIPSO provide new constraints on cloud‐radiation interactions

The spaceborne lidar CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) directly measures atmospheric opacity. In 8 years of CALIPSO observations, we find that 69% of vertical profiles penetrate through the complete atmosphere. The remaining 31% do not reach the surface, due to opaque clouds. The global mean altitude of full attenuation of the lidar beam (z_opaque) is 3.2 km, but there are large regional variations in this altitude. Of relevance to cloud-climate studies, the annual zonal mean longwave cloud radiative effect and annual zonal mean z_opaque weighted by opaque cloud cover are highly correlated (0.94). The annual zonal mean shortwave cloud radiative effect and annual zonal mean opaque cloud cover are also correlated (A0.95). The new diagnostics introduced here are implemented within a simulator framework to enable scale-aware and definition-aware evaluation of the LMDZ5B global climate model. The evaluation shows that the model overestimates opaque cloud cover (31% obs. versus 38% model) and z_opaque (3.2 km obs. versus 5.1 km model). In contrast, the model underestimates thin cloud cover (35% obs. versus 14% model). Further assessment shows that reasonable agreement between modeled and observed longwave cloud radiative effects results from compensating errors between insufficient warming by thin clouds and excessive warming due to overestimating both z_opaque and opaque cloud cover. This work shows the power of spaceborne lidar observations to directly constrain cloud-radiation interactions in both observations and models.

Observational Constraints on Cloud Feedbacks: The Role of Active Satellite Sensors

Cloud profiling from active lidar and radar in the A-train satellite constellation has significantly advanced our understanding of clouds and their role in the climate system. Nevertheless, the response of clouds to a warming climate remains one of the largest uncertainties in predicting climate change and for the development of adaptions to change. Both observation of long-term changes and observational constraints on the processes responsible for those changes are necessary. We review recent progress in our understanding of the cloud feedback problem. Capabilities and advantages of active sensors for observing clouds are discussed, along with the importance of active sensors for deriving constraints on cloud feedbacks as an essential component of a global climate observing system.

Using space lidar observations to decompose Longwave Cloud Radiative Effect variations over the last decade

Measurements of the longwave cloud radiative effect (LWCRE) at the top of the atmosphere assess the contribution of clouds to the Earth warming but do not quantify the cloud property variations that are responsible for the LWCRE variations. The CALIPSO space lidar observes directly the detailed profile of cloud, cloud opacity, and cloud cover. Here we use these observations to quantify the influence of cloud properties on the variations of the LWCRE observed between 2008 and 2015 in the tropics and at global scale. At global scale, the method proposed here gives good results except over the Southern Ocean. We find that the global LWCRE variations observed over ocean are mostly due to variations in the opaque cloud properties (82%); transparent cloud columns contributed 18%. Variation of opaque cloud cover is the first contributor to the LWCRE evolution (58%); opaque cloud temperature is the second contributor (28%).

Reply to comment by Poole et al. on “A tropical ‘NAT‐like’ belt observed from space”

In their comment, Poole et al. (2009) aim to show it is highly improbable that the observations described in Chepfer and Noel (2009), and described as NAT-like therein, are produced by Nitric Acid Trihydrate (NAT) particles. In this reply, we attempt to show why there is, in our opinion, too little evidence to reject this interpretation right away.

The Potential of a Multidecade Spaceborne Lidar Record to Constrain Cloud Feedback

Synthetic multi‐decadal space‐borne lidar records are used to examine when a cloud response to anthropogenic forcing would be detectable from space‐borne lidar observations. The synthetic records are generated using long‐term cloud changes predicted by two CMIP5 (Coupled Model Intercomparison Program 5) models seen through the COSP/lidar (CFMIP –Cloud Feedback Model Intercomparison Project, Observation Simulators Package), and cloud inter‐annual variability observed by the CALIPSO (Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations) spaceborne lidar during the past decade. nCALIPSO observations do not show any significant trend yet. Our analysis of the synthetic time series suggests, the Tropical cloud longwave feedback and the Southern ocean cloud shortwave feedback might be constrained with 70% confidence with, respectively, a 20‐year and 29‐year uninterrupted lidar‐in‐space record. A 27‐year record might be needed to separate the two different models predictions in the tropical subsidence clouds. nAssuming that combining the CALIPSO and Earth‐CARE (Earth Clouds, Aerosols and Radiation Explorer) missions will lead to a space‐borne lidar record of at least 16 years, we examine the impact of gaps and calibration offsets between successive missions. A 2‐year gap between EarthCARE and the following space‐borne lidar would have no significant impact on the capability to constrain the cloud feedback if all the space lidars were perfectly inter‐calibrated. Any intercalibration shift between successive lidar missions would delay the capability to constrain the cloud feedback mechanisms, larger shifts leading to longer delays.