Combining visible and infrared radiometry and lidar data to test simulations in clear and ice cloud conditions

Measurements taken during the 2003 Pacific THORPEX Observing System Test (P-TOST) by the MODIS Airborne Simulator (MAS), the Scanning High-resolution Interferometer Sounder (S-HIS) and the Cloud Physics Lidar (CPL) are compared to simulations performed with a line-by-line and multiple scattering modeling methodology (LBLMS). Formerly used for infrared hyper-spectral data analysis, LBLMS has been extended to the visible and near infrared with the inclusion of surface bi-directional reflectance properties. A number of scenes are evaluated: two clear scenes, one with nadir geometry and one cross-track encompassing sun glint, and three cloudy scenes, all with nadir geometry. <br><br> CPL data is used to estimate the particulate optical depth at 532 nm for the clear and cloudy scenes and cloud upper and lower boundaries. Cloud optical depth is retrieved from S-HIS infrared window radiances, and it agrees with CPL values, to within natural variability. MAS data are simulated convolving high resolution radiances. The paper discusses the results of the comparisons for the clear and cloudy cases. LBLMS clear simulations agree with MAS data to within 20% in the shortwave (SW) and near infrared (NIR) spectrum and within 2 K in the infrared (IR) range. It is shown that cloudy sky simulations using cloud parameters retrieved from IR radiances systematically underestimate the measured radiance in the SW and NIR by nearly 50%, although the IR retrieved optical thickness agree with same measured by CPL. <br><br> MODIS radiances measured from Terra are also compared to LBLMS simulations in cloudy conditions, using retrieved cloud optical depth and effective radius from MODIS, to understand the origin for the observed discrepancies. It is shown that the simulations agree, to within natural variability, with measurements in selected MODIS SW bands. <br><br> The impact of the assumed particles size distribution and vertical profile of ice content on results is evaluated. Sensitivity is much smaller than differences between measured and simulated radiances in the SW and NIR. <br><br> The paper dwells on a possible explanation of these contradictory results, involving the phase function of ice particles in the shortwave

Comparison of mid-latitude single- And mixed-phase cloud optical depth from co-located infrared spectrometer and backscatter lidar measurements

The long-wave downwelling spectral radiance measurements performed by means of the Far-Infrared Radiation Mobile Observation System (FIRMOS) spectrometer at the summit of the Zugspitze (German Alps) in the winter 2018/19 allowed the retrieval of the optical and micro-physical properties of ice and mixed clouds, showing a good agreement of the statistical relationship between the ice water path and the ice optical depth with the ones from previous works. In this paper the optical depths retrieved from FIRMOS are initially compared with selected cases calculated from backscattering light detection and ranging (lidar) data by using a transmittance method. Then, in order to compare the whole FIRMOS dataset, the power-law relationship between backscattering and extinction is used to apply the Klett method and automatize the routine. Minimizing the root mean square differences, the exponent k of the power-law relationship is assessed to be 0.85 with a variability in the range of 0.60–1.10 for ice clouds and 0.50 with a variability within 0.30–0.70 for mixed clouds

Thin ice clouds in the Arctic: cloud optical depth and particle size retrieved from ground-based thermal infrared radiometry

Multiband downwelling thermal measurements of zenith sky radiance, along with cloud boundary heights, were used in a retrieval algorithm to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice clouds cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several cloud parameters including optical depth, effective particle diameter and shape, water vapor content, cloud geometric thickness and cloud base altitude. A lookup table retrieval method was used to successfully extract, through an optimal estimation method, cloud optical depth up to a maximum value of 2.6 and to separate thin ice clouds into two classes: (1) TIC1 clouds characterized by small crystals (effective particle diameter  ≤  30 µm), and (2) TIC2 clouds characterized by large ice crystals (effective particle diameter  >  30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave Cloud Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation (R2 =  0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 clouds. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21 µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes

Planning, implementation, and first results of the Tropical Composition, Cloud and Climate Coupling Experiment (TC4)

The Tropical Composition, Cloud and Climate Coupling Experiment (TC4), was based in Costa Rica and Panama during July and August 2007. The NASA ER-2, DC-8, and WB-57F aircraft flew 26 science flights during TC4. The ER-2 employed 11 instruments as a remote sampling platform and satellite surrogate. The WB-57F used 25 instruments for in situ chemical and microphysical sampling in the tropical tropopause layer (TTL). The DC-8 used 25 instruments to sample boundary layer properties, as well as the radiation, chemistry, and microphysics of the TTL. TC4 also had numerous sonde launches, two ground-based radars, and a ground-based chemical and microphysical sampling site. The major goal of TC4 was to better understand the role that the TTL plays in the Earth's climate and atmospheric chemistry by combining in situ and remotely sensed data from the ground, balloons, and aircraft with data from NASA satellites. Significant progress was made in understanding the microphysical and radiative properties of anvils and thin cirrus. Numerous measurements were made of the humidity and chemistry of the tropical atmosphere from the boundary layer to the lower stratosphere. Insight was also gained into convective transport between the ground and the TTL, and into transport mechanisms across the TTL. New methods were refined and extended to all the NASA aircraft for real-time location relative to meteorological features. The ability to change flight patterns in response to aircraft observations relayed to the ground allowed the three aircraft to target phenomena of interest in an efficient, well-coordinated manner

The life cycle of anvil cirrus clouds from a combination of passive and active satellite remote sensing

Anvil cirrus clouds form in the upper troposphere from the outflow of ice crystals from deep convective cumulonimbus clouds. By reflecting incoming solar radiation as well as absorbing terrestrial thermal radiation, and re-emitting it at significantly lower temperatures, they play an important role for the Earth’s radiation budget. Nevertheless the processes that govern their life cycle are not well understood and, hence, they remain one of the largest uncertainties in atmospheric remote sensing and climate and weather modelling. In this thesis the temporal evolution of the anvil cirrus properties throughout their life cycle is investigated, as is their relationship with the meteorological conditions. For a comprehensive retrieval of the anvil cirrus properties, a new algorithm for the remote sensing of cirrus clouds called CiPS (Cirrus Properties from SEVIRI) is developed. Utilising a set of artificial neural networks, CiPS combines the large spatial coverage and high temporal resolution of the imaging radiometer SEVIRI aboard the geostationary satellites Meteosat Second Generation, with the high vertical resolution and sensitivity to thin cirrus clouds of the lidar CALIOP aboard the polar orbiting satellite CALIPSO. In comparison to CALIOP, CiPS detects 71 % and 95 % of all cirrus clouds with an ice optical thickness (IOT) of 0.1 and 1.0 respectively. Furthermore, CiPS retrieves the corresponding cloud top height, IOT, ice water path (IWP) and, by parameterisation, effective ice crystal radius. This way, macrophysical, microphysical and optical properties can be combined to interpret the temporal evolution of the anvil cirrus clouds. Together with a tool for identifying convective activity and a new cirrus tracking algorithm, CiPS is used to analyse the life cycle of 132 anvil cirrus clouds observed over southern Europe and northern Africa in July 2015. Although the anvil cirrus clouds grow optically thick during the convective phase, they become thinner at a rapid pace as convection ceases. Two hours after the last observed convective activity, 92±7 % of the anvil cirrus area has IOT_CiPS < 1 and IWP_CiPS < 30 g m−2 on average, with highest probability density around 0.1–0.2 and 1.5–3 g m−2 respectively. During the same time period, the cloud top height is observed to decrease. Since this is observed for both long-lived and short-lived anvil cirrus, it is deduced that in this life phase the amount of ice in the anvil is mainly controlled by sedimentation. This is in line with a corresponding decrease in the estimated effective radius. While the convective strength has no evident effect on the IOT and IWP, stronger vertical updraught is clearly correlated with higher cloud top height and larger effective radius. Larger ice crystals are, however, observed to be removed effectively within 2-3 h after convection has ceased, suggesting that the convective strength has no impact on the ice crystal sizes in ageing anvils. In this life stage, upper tropospheric relative humidity, as derived from ERA5 reanalysis data, is shown to have a larger impact on the anvil cirrus life cycle, where higher relative humidity govern larger and especially more long-lived anvil cirrus clouds

FIRE Arctic Clouds Experiment

An overview is given of the First ISCCP Regional Experiment (FIRE) Arctic Clouds Experiment that was conducted in the Arctic during April through July, 1998. The principal goal of the field experiment was to gather the data needed to examine the impact of arctic clouds on the radiation exchange between the surface, atmosphere, and space, and to study how the surface influences the evolution of boundary layer clouds. The observations will be used to evaluate and improve climate model parameterizations of cloud and radiation processes, satellite remote sensing of cloud and surface characteristics, and understanding of cloud-radiation feedbacks in the Arctic. The experiment utilized four research aircraft that flew over surface-based observational sites in the Arctic Ocean and Barrow, Alaska. In this paper we describe the programmatic and science objectives of the project, the experimental design (including research platforms and instrumentation), conditions that were encountered during the field experiment, and some highlights of preliminary observations, modelling, and satellite remote sensing studies

Exploring Aerosols near Clouds with High-Spatial-Resolution Aircraft Remote Sensing During SEAC4RS

Since aerosols are important to our climate system, we seek to observe the variability of aerosol properties within cloud systems. When applied to the satelliteborne Moderateresolution Imaging Spectroradiometer (MODIS), the Dark Target retrieval algorithm provides global aerosol optical depth (AOD; at 0.55 m) in cloudfree scenes. Since MODIS' resolution (500m pixels, 3 or 10km product) is too coarse for studying nearcloud aerosol, we ported the Dark Target algorithm to the highresolution (~50m pixels) enhancedMODIS Airborne Simulator (eMAS), which flew on the highaltitude ER2 during the Studies of Emissions, Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys Airborne Science Campaign over the United States in 2013. We find that even with aggressive cloud screening, the ~0.5km eMAS retrievals show enhanced AOD, especially within 6 km of a detected cloud. To determine the cause of the enhanced AOD, we analyze additional eMAS products (cloud retrievals and degradedresolution AOD), coregistered Cloud Physics Lidar profiles, MODIS aerosol retrievals, and groundbased Aerosol Robotic Network observations. We also define spatial metrics to indicate local cloud distributions near each retrieval and then separate into nearcloud and farfromcloud environments. The comparisons show that low cloud masking is robust, and unscreened thin cirrus would have only a small impact on retrieved AOD. Some of the enhancement is consistent with clearcloud transition zone microphysics such as aerosol swelling. However, 3D radiation interaction between clouds and the surrounding clear air appears to be the primary cause of the high AOD near clouds

L'approche méthodologique à la validation d'une paramétrisation des aérosols et nuages en utilisant le simulateur des instruments d'Earthcare

La validation d'un modèle atmosphérique avec les observations satellitaires est basée sur les différentes techniques de télédétection employées afin de récupérer des propriétés physiques et optiques de composantes atmosphériques, notamment des nuages et des aérosols. Il est bien connu que le « retrieval approach » introduit de grandes incohérences en raison des hypothèses diverses portant sur le problème d'inversion où la principale difficulté est l'unicité de la solution. Autrement dit, le milieu analysé peut être composé d'un certain nombre de paramètres physiques inconnus dont les combinaisons différentes mènent au même signal de radiation. En plus du problème d'unicité de la solution, il y a plusieurs problèmes mathématiques reliés à l'existence et à la stabilité de la solution ainsi qu'à la manière dont la solution est construite. Par contre, il est bien connu que les prévisions des modèles atmosphériques souffrent d'incertitudes portant sur l'approche numérique qui limite leurs applications à la simulation de phénomènes naturels. Malgré ces difficultés, certains aspects des prévisions numériques peuvent être considérées comme réalistes parce qu'elles prennent explicitement en considération les principes de la physique, dont des processus microphysiques des nuages et des aérosols. Dans ce contexte, la motivation principale de cette recherche est d'évaluer le potentiel de la validation des paramétrisations physiques des aérosols et des nuages dans les modèles climatiques par le biais des mesures satellitaires (radar et lidar) en utilisant les « simulation vers l'avant ». Dans cette étude, nous utilisons une approche qui emploie le modèle Simulateur des instruments d'EarthCARE afin de reproduire des mesures satellitaires comparables à celles du radar et du lidar. Compte tenu du manque de mesures satellitaires, la validation se base sur les mesures directes du lidar et du radar de l'expérience APEX-E3 réalisées au printemps 2003 où les fréquences et la performance des systèmes d'observation correspondent à celles qui vont être mesurées par le satellite EarthCARE. Les caractéristiques microphysiques des nuages et des aérosols ainsi que l'état de l'atmosphère sont produites par le modèle atmosphérique NARCM. Elles sont ensuite converties en données de réflectivité pour le radar et en données de rétrodiffusion pour lidar en utilisant le Simulateur des Instruments d'EarthCARE. Pour terminer, les résultats sont comparés aux mesures de radar et de lidar de l'expérience APEX-E3. Les champs d'aérosols simulés avec NARCM indiquent un accord important avec ceux qui sont observés, mais les propriétés microphysiques des nuages simulées ne sont pas compatibles avec les observations. Autrement dit, les résultats montrent un large désaccord entre la réflectivité observée et la réflectivité simulée en dépit du fait que ses étendues verticales sont relativement similaires. Le nuage simulé est plus mince, situé à plus haute altitude et les valeurs maximales de réflectivité dans le nuage sont environ 5-10 dBZ inférieures à celles du nuage observé. De plus, le coefficient de la rétrodiffusion simulé (sans eau liquide) au-dessous de la base et au-dessus du sommet du nuage est nettement plus faible par rapport au coefficient de rétrodiffusion observé. Il y a également, à ces deux niveaux une plus grande quantité d'eau glacée observée que dans le cas simulé par NARCM. Si la présence d'eau liquide est incluse dans le Simulateur des lnstruments d'EarthCARE, les valeurs simulées du coefficient de rétrodiffusion sont de plusieurs ordres de grandeurs supérieures à celles observées, ce qui suggère que les valeurs du contenu en eau liquide simulées par NARCM sont surestimées d'une manière significative par rapport à toutes les altitudes où le nuage observé est présent. En conclusion, l'analyse montre que la paramétrisation microphysique de Lohmann (Lohmann et Roeckner, 1996) ne possède pas la capacité de produire les quantités glace observées dans le cas de cirrostratus. Il est également constaté que le contenu d'eau glacé de NARCM est sous-estimé, et que le contenu d'eau liquide est surestimé. Les résultats de cette étude confirment donc que l'utilisation du « forward approach » a un grand potentiel dans la validation de la paramétrisation des aérosols et des nuages. Par contre, des nouvelles vérifications seront nécessaires pour accomplir le processus de validation. ______________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : Validation, Rétrodiffusion de lidar, Réflectivité de radar, Simulations régionales des modèles atmosphériques

A high-resolution oxygen A-band spectrometer (HABS) and its radiation closure

Various studies indicate that high-resolution oxygen A-band spectrum has the capability to retrieve the vertical profiles of aerosol and cloud properties. To improve the understanding of oxygen A-band inversions and utility, we developed a high-resolution oxygen A-band spectrometer (HABS), and deployed it at Howard University Beltsville site during the NASA Discover Air-Quality Field Campaign in July, 2011. By using a single telescope, the HABS instrument measures the direct solar and the zenith diffuse radiation subsequently. HABS exhibits excellent performance: stable spectral response ratio, high signal-to-noise ratio (SNR), high-spectrum resolution (0.016 nm), and high out-of-band rejection (10^&minus;5). For the spectral retrievals of HABS measurements, a simulator is developed by combining a discrete ordinates radiative transfer code (DISORT) with the High Resolution Transmission (HITRAN) database HITRAN2008. The simulator uses a double-<i>k</i> approach to reduce the computational cost. The HABS-measured spectra are consistent with the related simulated spectra. For direct-beam spectra, the discrepancies between measurements and simulations, indicated by confidence intervals (95%) of relative difference, are (−0.06, 0.05) and (−0.08, 0.09) for solar zenith angles of 27 and 72°, respectively. For zenith diffuse spectra, the related discrepancies between measurements and simulations are (−0.06, 0.05) and (−0.08, 0.07) for solar zenith angles of 27 and 72°, respectively. The main discrepancies between measurements and simulations occur at or near the strong oxygen absorption line centers. They are mainly due to two kinds of causes: (1) measurement errors associated with the noise/spikes of HABS-measured spectra, as a result of combined effects of weak signal, low SNR, and errors in wavelength registration; (2) modeling errors in the simulation, including the error of model parameters setting (e.g., oxygen absorption line parameters, vertical profiles of temperature and pressure) and the lack of treatment of the rotational Raman scattering. The high-resolution oxygen A-band measurements from HABS can constrain the active radar retrievals for more accurate cloud optical properties (e.g., cloud optical depth, effective radius), particularly for multi-layer clouds and for mixed-phase clouds