Martial Haeffelin

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.

STRAT: An Automated Algorithm to Retrieve the Vertical Structure of the Atmosphere from Single-Channel Lidar Data

Today several lidar networks around the world provide large datasets that are extremely valuable for aerosol and cloud research. Retrieval of atmospheric constituent properties from lidar profiles requires detailed analysis of spatial and temporal variations of the signal. This paper presents an algorithm called Structure of the Atmosphere (STRAT), which is designed to retrieve the vertical distribution of cloud and aerosol layers in the boundary layer and through the free troposphere and to identify near-particle-free regions of the vertical profile and the range at which the lidar signal becomes too attenuated for exploitation, from a single lidar channel. The paper describes each detection method used in the STRAT algorithm and its application to a tropospheric backscatter lidar operated at the SIRTA observatory, in Palaiseau, 20 km south of Paris, France. STRAT retrievals are compared to other means of layer detection and classification; retrieval performances and uncertainties are discussed.

Evaluation of Mixing-Height Retrievals from Automatic Profiling Lidars and Ceilometers in View of Future Integrated Networks in Europe

The determination of the depth of daytime and nighttime mixing layers must be known very accurately to relate boundary-layer concentrations of gases or particles to upstream fluxes. The mixing-height is parametrized in numerical weather prediction models, so improving the determination of the mixing height will improve the quality of the estimated gas and particle budgets. Datasets of mixing-height diurnal cycles with high temporal and spatial resolutions are sought by various end users. Lidars and ceilometers provide vertical profiles of backscatter from aerosol particles. As aerosols are predominantly concentrated in the mixing layer, lidar backscatter profiles can be used to trace the depth of the mixing layer. Large numbers of automatic profiling lidars and ceilometers are deployed by meteorological services and other agencies in several European countries providing systems to monitor the mixing height on temporal and spatial scales of unprecedented density. We investigate limitations and capabilities of existing mixing height retrieval algorithms by applying five different retrieval techniques to three different lidars and ceilometers deployed during two 1-month campaigns. We studied three important steps in the mixing height retrieval process, namely the lidar/ceilometer pre-processing to reach sufficient signal-to-noise ratio, gradient detection techniques to find the significant aerosol gradients, and finally quality control and layer attribution to identify the actual mixing height from multiple possible layer detections. We found that layer attribution is by far the most uncertain step. We tested different gradient detection techniques, and found no evidence that the first derivative, wavelet transform, and two-dimensional derivative techniques have different skills to detect one or multiple significant aerosol gradients from lidar and ceilometer attenuated backscatter. However, our study shows that, when mixing height retrievals from a ultraviolet lidar and a near-infrared ceilometer agreed, they were 25–40% more likely to agree with an independent radiosonde mixing height retrieval than when each lidar or ceilometer was used alone. Furthermore, we point to directions that may assist the layer attribution step, for instance using commonly available surface measurements of radiation and temperature to derive surface sensible heat fluxes as a proxy for the intensity of convective mixing. It is a worthwhile effort to pursue such studies so that within a few years automatic profiling lidar and ceilometer networks can be utilized efficiently to monitor mixing heights at the European scale.

A High-Accuracy Multiwavelength Radiometer for In Situ Measurements in the Thermal Infrared. Part I: Characterization of the Instrument

Abstract The new infrared radiometer (conveyable low-noise infrared radiometer for measurements of atmosphere and ground surface targets, or CLIMAT) is a highly sensitive field instrument designed to measure brightness temperatures or radiances in the infrared, from the ground level, or from an aircraft. It can be equipped with up to six channels in the 8–14-μm range. This instrument is characterized by its portability (total mass less than 5 kg), its self-sufficiency, and its automated operation. It can be operated either manually or automatically. The optical head of the instrument contains an objective lens and a condenser mounted according to the Kohler design, providing a uniform irradiation on the detector and a well-delimited field of view. The radiation is measured by a low-noise fast thermopile whose responsivity is slightly temperature dependent. The radiometric noise expressed as an equivalent brightness temperature is on the order of 50 mK for a 1-μm bandwidth at room temperature. The applicat...

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.

Macrophysical and optical properties of midlatitude cirrus clouds from four ground-based lidars and collocated CALIOP observations

Ground-based lidar and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data sets gathered over four midlatitude sites, two U.S. and two French sites, are used to evaluate the consistency of cloud macrophysical and optical property climatologies that can be derived by such data sets. The consistency in average cloud height (both base and top height) between the CALIOP and ground data sets ranges from −0.4 km to +0.5 km. The cloud geometrical thickness distributions vary significantly between the different data sets, due in part to the original vertical resolutions of the lidar profiles. Average cloud geometrical thicknesses vary from 1.2 to 1.9 km, i.e., by more than 50%. Cloud optical thickness distributions in subvisible, semitransparent, and moderate intervals differ by more than 50% between ground- and space-based data sets. The cirrus clouds with optical thickness below 0.1 (not included in historical cloud climatologies) represent 30–50% of the nonopaque cirrus class. An important part of this work consists in quantifying the different possible causes of discrepancies between CALIOP and surface lidar. The differences in average cloud base altitude between ground and CALIOP data sets can be attributed to (1) irregular sampling of seasonal variations in the ground-based data, (2) day-night differences in detection capabilities by CALIOP, and (3) the restriction to situations without low-level clouds in ground-based data. Cloud geometrical thicknesses are not affected by irregular sampling of seasonal variations in the ground-based data but by the day-night differences in detection capabilities of CALIOP and by the restriction to situations without low-level clouds in ground-based data.

Using Continuous Ground-Based Radar and Lidar Measurements for Evaluating the Representation of Clouds in Four Operational Models

The ability of four operational weather forecast models [ECMWF, Action de Recherche Petite Echelle Grande Echelle model (ARPEGE), Regional Atmospheric Climate Model (RACMO), and Met Office] to generate a cloud at the right location and time (the cloud frequency of occurrence) is assessed in the present paper using a two-year time series of observations collected by profiling ground-based active remote sensors (cloud radar and lidar) located at three different sites in western Europe (Cabauw, Netherlands; Chilbolton, United Kingdom; and Palaiseau, France). Particular attention is given to potential biases that may arise from instrumentation differences (especially sensitivity) from one site to another and intermittent sampling. In a second step the statistical properties of the cloud variables involved in most advanced cloud schemes of numerical weather forecast models (ice water content and cloud fraction) are characterized and compared with their counterparts in the models. The two years of observations are first considered as a whole in order to evaluate the accuracy of the statistical representation of the cloud variables in each model. It is shown that all models tend to produce too many high-level clouds, with too-high cloud fraction and ice water content. The midlevel and low-level cloud occurrence is also generally overestimated, with too-low cloud fraction but a correct ice water content. The dataset is then divided into seasons to evaluate the potential of the models to generate different cloud situations in response to different large-scale forcings. Strong variations in cloud occurrence are found in the observations from one season to the same season the following year as well as in the seasonal cycle. Overall, the model biases observed using the whole dataset are still found at seasonal scale, but the models generally manage to well reproduce the observed seasonal variations in cloud occurrence. Overall, models do not generate the same cloud fraction distributions and these distributions do not agree with the observations. Another general conclusion is that the use of continuous ground-based radar and lidar observations is definitely a powerful tool for evaluating model cloud schemes and for a responsive assessment of the benefit achieved by changing or tuning a model cloud parameterization.

Improved retrievals of the optical properties of cirrus clouds by a combination of lidar methods

We focus on improvement of the retrieval of optical properties of cirrus clouds by combining two lidar methods. We retrieve the clouds optical depth by using independently the molecular backscattering profile below and above the cloud [molecular integration (MI) method] and the backscattering profile inside the cloud with an a priori effective lidar ratio [particle integration (PI) method]. When the MI method is reliable, the combined MI-PI method allows us to retrieve the optimal effective lidar ratio. We compare these results with Raman lidar retrievals. We then use the derived optimal effective lidar ratio for retrieval with the PI method for situations in which the MI method cannot be applied.

Assessment of Physical Parameterizations Using a Global Climate Model with Stretchable Grid and Nudging

Abstract The Laboratoire de Meteorologie Dynamique atmospheric general circulation model with zooming capability (LMDZ) has been used in a nudged mode to enable comparison of model outputs with routine observations and evaluate the model physical parameterizations. Simulations have been conducted with a stretched grid refined over the vicinity of Paris, France, where observations, collected at the Trappes station (Meteo-France) and at the Site Instrumental de Recherche par Teledetection Atmospherique observatory, are available. For the purpose of evaluation of physical parameterizations, the large-scale component of the modeled circulation is adjusted toward ECMWF analyses outside the zoomed area only, whereas the inside region can evolve freely. A series of sensitivity experiments have been performed with different parameterizations of land surface and boundary layer processes. Compared with previous versions of the LMDZ model, a “thermal plume model,” in association with a constant resistance to evapora...

Reference Upper-Air Observations for Climate: From Concept to Reality

AbstractThe three main objectives of the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) are to provide long-term high-quality climate records of vertical profiles of selected essential climate variables (ECVs), to constrain and calibrate data from more spatially comprehensive global networks, and to provide measurements for process studies that permit an in-depth understanding of the properties of the atmospheric column. In the five years since the first GRUAN implementation and coordination meeting and the printing of an article (Seidel et al.) in this publication, GRUAN has matured to become a functioning network that provides reference-quality observations to a community of users.This article describes the achievements within GRUAN over the past five years toward making reference-quality observations of upper-air ECVs. Milestones in the evolution of GRUAN are emphasized, including development of rigorous criteria for site certification and assessment, the formal certificatio...