Marjolaine Chiriaco

Combined influence of atmospheric physics and soil hydrology on the simulated meteorology at the SIRTA atmospheric observatory

The identification of the land-atmosphere interactions as one of the key source of uncertainty in climate models calls for process-level assessment of the coupled atmosphere/land continental surface system in numerical climate models. To this end, we propose a novel approach and apply it to evaluate the standard and new parametrizations of boundary layer/convection/clouds in the Earth System Model (ESM) of Institut Pierre Simon Laplace (IPSL), which differentiate the IPSL-CM5A and IPSL-CM5B climate change simulations produced for the Coupled Model Inter-comparison Project phase 5 exercise. Two different land surface hydrology parametrizations are also considered to analyze different land-atmosphere interactions. Ten-year simulations of the coupled land surface/atmospheric ESM modules are confronted to observations collected at the SIRTA (Site Instrumental de Recherche par Télédection Atmosphérique), located near Paris (France). For sounder evaluation of the physical parametrizations, the grid of the model is stretched and refined in the vicinity of the SIRTA, and the large scale component of the modeled circulation is adjusted toward ERA-Interim reanalysis outside of the zoomed area. This allows us to detect situations where the parametrizations do not perform satisfactorily and can affect climate simulations at the regional/continental scale, including in full 3D coupled runs. In particular, we show how the biases in near surface state variables simulated by the ESM are explained by (1) the sensible/latent heat partitionning at the surface, (2) the low level cloudiness and its radiative impact at the surface, (3) the parametrization of turbulent transport in the surface layer, (4) the complex interplay between these processes. We also show how the new set of parametrizations can improve these biases.

The ability of MM5 to simulate ice clouds: Systematic comparison between simulated and measured fluxes and lidar/radar profiles at the SIRTA atmospheric observatory

The ability of the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) to simulate midlatitude ice clouds is evaluated. Model outputs are compared to long-term meteorological measurements by active (radar and lidar) and passive (infrared and visible fluxes) remote sensing collected at an atmospheric observatory near Paris, France. The goal is to understand which of four microphysical schemes is best suited to simulate midlatitude ice clouds. The methodology consists of simulating instrument observables from the model outputs without any profile inversion, which allows the authors to use fewer assumptions on microphysical and optical properties of ice particles. Among the four schemes compared in the current study, the best observation-to-simulations scores are obtained with Reisner et al. provided that the particles’ sedimentation velocity from Heymsfield and Donner is used instead of that originally proposed. For this last scheme, the model gives results close to the measurements for clouds with medium optical depth of typically 1 to 3, whatever the season. In this configuration, MM5 simulates the presence of midlatitude ice clouds in more than 65% of the authors’ selection of observed cloud cases. In 35% of the cases, the simulated clouds are too persistent whatever the microphysical scheme and tend to produce too much solid water (ice and snow) and not enough liquid water.

Improving Retrievals of Cirrus Cloud Particle Size Coupling Lidar and Three-Channel Radiometric Techniques

This study is intended to illustrate the potential advantage of combining lidar measurements and the split-window technique based on the infrared spectral information contained at the 8.65-, 11.15-, and 12.05-μm bands for inferring the microphysical properties of cirrus clouds. The lidar returns are employed to detect cirrus clouds. The optical properties of nonspherical ice crystals computed from the state-of-the-art scattering computational methods are used for the present forward radiative transfer simulation that fully accounts for both gaseous absorption and multiple scattering processes in the atmosphere. A combination of the radiances at the three infrared (IR) bands with lidar backscatter returns cannot uniquely specify the effective size of ice crystals because of its dependence on the particle aspect ratios. To avoid the shortcoming associated with a potential multivalued retrieval, lidar depolarization observation is used to constrain the specification of the particle aspect ratio in the retrieval implementation based on a precalculated lookup library. The present methodology for inferring the microphysical properties of cirrus clouds is implemented for nine cases by using the measurements from a 532-nm lidar located at the Palaiseau, France, ground-based site and the infrared spectral bands from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra platform. It is shown that the three IR wavelengths are quite complementary in constraining the retrieval of the particle size, leading to a significant advance in comparison with two-channel techniques, whereas the aspect ratio constraint due to lidar depolarization reduces the uncertainty of retrieved particle size by more than 20% for 70% of the cases and more than 65% for 40% of the cloud cases.

Comparison of CALIPSO-Like, LaRC, and MODIS Retrievals of Ice-Cloud Properties over SIRTA in France and Florida during CRYSTAL-FACE

This study compares cirrus-cloud properties and, in particular, particle effective radius retrieved by a Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)-like method with two similar methods using Moderate-Resolution Imaging Spectroradiometer (MODIS), MODIS Airborne Simulator (MAS), and Geostationary Operational Environmental Satellite imagery. The CALIPSO-like method uses lidar measurements coupled with the split-window technique that uses the infrared spectral information contained at the 8.65-, 11.15-, and 12.05-μm bands to infer the microphysical properties of cirrus clouds. The two other methods, using passive remote sensing at visible and infrared wavelengths, are the operational MODIS cloud products (using 20 spectral bands from visible to infrared, referred to by its archival product identifier MOD06 for MODIS Terra) and MODIS retrievals performed by the Clouds and the Earths Radiant Energy System (CERES) team at Langley Research Center (LaRC) in support of CERES algorithms (using 0.65-, 3.75-, 10.8-, and 12.05-μm bands); the two algorithms will be referred to as the MOD06 and LaRC methods, respectively. The three techniques are compared at two different latitudes. The midlatitude ice-clouds study uses 16 days of observations at the Palaiseau ground-based site in France [Site Instrumental de Recherche par Teledetection Atmospherique (SIRTA)], including a ground-based 532-nm lidar and the MODIS overpasses on the Terra platform. The tropical ice-clouds study uses 14 different flight legs of observations collected in Florida during the intensive field experiment known as the Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE), including the airborne cloud-physics lidar and the MAS. The comparison of the three methods gives consistent results for the particle effective radius and the optical thickness but discrepancies in cloud detection and altitudes. The study confirms the value of an active remote sensing method (CALIPSO like) for the study of subvisible ice clouds, in both the midlatitudes and Tropics. Nevertheless, this method is not reliable in optically very thick tropical ice clouds, because of their particular microphysical properties.

Evaluation of MM5 Optically Thin Clouds over Europe in Fall Using ICESat Lidar Spaceborne Observations

The description of clouds in mesoscale models has progressed significantly during recent years by improving microphysical schemes with more physical parameterizations deduced from observations. Recently, the first lidar in space, the Ice, Cloud, and Land Elevation Satellite (ICESat)/Geosciences Laser Altimeter System, has collected a valuable dataset that improves the knowledge of occurrence and macrophysical properties of clouds, and particularly high-altitude clouds, which are usually optically thin. This study evaluates the capability of the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) to reproduce optically thin clouds using the ICESat October–November 2003 dataset. Initial and boundary conditions are prescribed from NCEP products and MM5 run over the European continent with a 40-km spatial resolution. Spaceborne lidar profiles are diagnosed from model outputs and compared with the observed ones at the same location and time. One month of simulations–observations comparisons shows that the model correctly reproduces cloud structures on average, but underestimates the thinnest clouds (by 0%–20%) and overestimates less thin clouds in the upper troposphere (altitude 6 km). The total low-level water cloud amount (altitude 6 km) appears fairly well reproduced, although the masking effect of higher clouds does not allow for a firm conclusion. The clouds are rarely simulated and observed simultaneously, 50% for high clouds and 20% for low clouds. The lack of high-altitude very thin clouds is possibly due to dry biases in the upper-troposphere humidity fields used to force the model. The overestimation of optically less thin cloud may be due to an overestimation of the cloud lifetime or water vapor supersaturation around ice clouds that is not taken into account in the model. When the upper troposphere and low warm clouds appear in the model at the same time and location as in the observations, they are optically too thick, likely because their water/ice content and particle concentration are overestimated simultaneously.

Control of radiation and evaporation on temperature variability in a WRF regional climate simulation: comparison with colocated long term ground based observations near Paris

The objective of this paper is to understand how large-scale processes, cloud cover and surface fluxes affect the temperature variability over the SIRTA site, near Paris, and in a regional climate simulation performed in the frame of HyMeX/Med-CORDEX programs. This site is located in a climatic transitional area where models usually show strong dispersions despite the significant influence of large scale on interannual variability due to its western location. At seasonal time scale, the temperature is mainly controlled by surface fluxes. In the model, the transition from radiation to soil moisture limited regime occurs earlier than in observations leading to an overestimate of summertime temperature. An overestimate of shortwave radiation (SW), consistent with a lack of low clouds, enhances the soil dryness. A simulation with a wet soil is used to better analyse the relationship between dry soil and clouds but while the wetter soil leads to colder temperature, the cloud cover during daytime is not increased due to the atmospheric stability. At shorter time scales, the control of surface radiation becomes higher. In the simulation, higher temperatures are associated with higher SW. A wet soil mitigates the effect of radiation due to modulation by evaporation. In observations, the variability of clouds and their effect on SW is stronger leading to a nearly constant mean SW when sorted by temperature quantile but a stronger impact of cloud cover on day-to-day temperature variability. Impact of cloud albedo effect on precipitation is also compared.

Nitric acid particles in cold thick ice clouds observed at global scale: Link with lightning, temperature, and upper tropospheric water vapor

Signatures of nitric acid particles (NAP) in cold thick ice clouds have been derived from satellite observations. Most NAP are detected in the tropics (9 to 20% of clouds with T < 202.5 K). Higher occurrences were found in the rare midlatitudes very cold clouds. NAP occurrence increases as cloud temperature decreases, and NAP are more numerous in January than July. Comparisons of NAP and lightning distributions show that lightning seems to be the main source of the NOx, which forms NAP in cold clouds over continents. Qualitative comparisons of NAP with upper tropospheric humidity distributions suggest that NAP may play a role in the dehydration of the upper troposphere when the tropopause is colder than 195 K.

Dual Lidar Observations at 10.6 μm and 532 nm for Retrieving Semitransparent Cirrus Cloud Properties

Abstract To improve the estimation of the infrared radiances in cirrus clouds, one needs to consider the vertical inhomogeneities of the cloud properties. The position of the maximum of absorption within an ice cloud is potentially important to the improvement of the split-window techniques for retrieving particle size and for understanding the radiative effect of the cloud in the infrared spectrum. Current remote sensing techniques used for inferring ice clouds hardly reach the level of accuracy required to resolve the vertical inhomogeneities of a cloud and to determine the position of absorption. This study explores the possibility of retrieving the vertical structures of ice clouds by combining data from two lidar measurements acquired at the wavelengths of 532 nm and 10.6 μm. A method is proposed to retrieve the variability of ice crystal absorption efficiency at 10.6 μm, the particle concentration weighted by the crystal area, and the attenuation by absorption at 10.6 μm. The method is tested agains...

The influence of synoptic circulations and local processes on temperature anomalies at three French observatories.

The relative contribution of the synoptic-scale circulations to local and mesoscale processes was quantified in terms of the variability of middle latitude temperature anomalies from 2003 to 2013 using meteorological variables collected from three French observatories and reanalyses. Four weather regimes were defined from sea level pressure anomalies using National Center for Environmental Prediction (NCEP) reanalyses with a K-means algorithm. No correlation was found between daily temperature anomalies and weather regimes, and the variability of temperature anomalies within each regime was large. It was therefore not possible to evaluate the effect of large scales on temperature anomalies by this method. An alternative approach was found with the use of the analogues method: the principle being that for each day of the considered time series, a set of days which had a similar large-scale 500 hPa geopotential height field within a fixed domain were considered. The observed temperature anomalies were then compared to those observed during the analogue days: the closer the two types of series, the greater the mark of the large scale. This method highlights a widely predominant influence of the large-scale atmospheric circulation on the temperature anomalies. It showed a potentially larger influence of the Mediterranean Sea and orographic flow on the two southern observatories. Low-level cloud radiative effects substantially modulated the variability of the daily temperature anomalies.

Disagreement among global cloud distributions from CALIOP, passive satellite sensors and general circulation models

Cloud detection is the first step of any complex satellite-based cloud retrieval. No instrument detects all clouds, and analyses that use a given satellite climatology can only discuss a specific subset of clouds. We attempt to clarify which subsets of clouds are detected in a robust way by passive sensors, and which require active sensors. To do so, we identify where retrievals of Cloud Amounts (CAs), based on numerous sensors and algorithms, differ the most. We investigate large uncertainties, and confront retrievals from the CALIOP lidar, which detects semitransparent clouds and directly measures their vertical distribution, whatever the surface below. We document the cloud vertical distribution, opacity and seasonal variability where CAs from passive sensors disagree most. CALIOP CAs are larger than the passive average by +0.05 (AM) and +0.07 (PM). Over land, the +0.1 average difference rises to +0.2 over the African desert, Antarctica and Greenland, where large passive disagreements are traced to unfavorable surface conditions. Over oceans, CALIOP retrievals are closer to the average of passive retrievals except over the ITCZ (+0.1). Passive CAs disagree more in tropical areas associated with large-scale subsidence, where CALIOP observes a specific multi-layer cloud population: optically thin, high-level clouds and opaque (z>7km), shallow boundary layer clouds (z<2km). We evaluate the CA and cloud vertical distribution from 8 General Circulation Models where passive retrievals disagree and CALIOP provides new information. We find that modeled clouds are not more realistic where cloud detections from passive observations have long been robust, than where active sensors provide more reliable information.