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

2010 ◽  
Vol 10 (15) ◽  
pp. 7369-7387 ◽  
Author(s):  
A. Bozzo ◽  
T. Maestri ◽  
R. Rizzi
Keyword(s):  
High Resolution ◽  
Optical Depth ◽  
Near Infrared ◽  
Natural Variability ◽  
Cloud Optical Depth ◽  
Cloud Parameters ◽  
Modeling Methodology ◽  
Particles Size Distribution ◽  
Spectral Data Analysis ◽  
The Impact

Abstract. 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. 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. 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. 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. The paper dwells on a possible explanation of these contradictory results, involving the phase function of ice particles in the shortwave.

scholarly journals Combining visible and infrared radiometry and lidar data to test ice clouds optical properties

2010 ◽  
Vol 10 (3) ◽  
pp. 7215-7264
Author(s):  
A. Bozzo ◽  
T. Maestri ◽  
R. Rizzi
Keyword(s):  
High Resolution ◽  
Optical Depth ◽  
Near Infrared ◽  
Natural Variability ◽  
Ice Clouds ◽  
Cloud Optical Depth ◽  
Cloud Parameters ◽  
Modeling Methodology ◽  
Clear Cases ◽  
Spectral Data Analysis

Abstract. 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. CPL data is used to estimate the particulate optical depth at 532 nm for the clear and cloudy scenes. Cloud optical depth is also 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 cases and for the three 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. 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. The paper dwells on a possible explanation of these contraddictory results, involving the phase function of ice particles in the shortwave.

scholarly journals The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations

2019 ◽  
Vol 12 (9) ◽  
pp. 5087-5099 ◽  
Author(s):  
Jonathan K. P. Shonk ◽  
Jui-Yuan Christine Chiu ◽  
Alexander Marshak ◽  
David M. Giles ◽  
Chiung-Huei Huang ◽  
...  
Keyword(s):  
Linear Equation ◽  
Optical Depth ◽  
Climate Models ◽  
Deep Convection ◽  
Surface Flux ◽  
Climate Modelling ◽  
Cloud Optical Depth ◽  
The Impact ◽  
Ice Fraction

Abstract. Clouds present many challenges to climate modelling. To develop and verify the parameterisations needed to allow climate models to represent cloud structure and processes, there is a need for high-quality observations of cloud optical depth from locations around the world. Retrievals of cloud optical depth are obtainable from radiances measured by Aerosol Robotic Network (AERONET) radiometers in “cloud mode” using a two-wavelength retrieval method. However, the method is unable to detect cloud phase, and hence assumes that all of the cloud in a profile is liquid. This assumption has the potential to introduce errors into long-term statistics of retrieved optical depth for clouds that also contain ice. Using a set of idealised cloud profiles we find that, for optical depths above 20, the fractional error in retrieved optical depth is a linear function of the fraction of the optical depth that is due to the presence of ice cloud (“ice fraction”). Clouds that are entirely ice have positive errors with magnitudes of the order of 55 % to 70 %. We derive a simple linear equation that can be used as a correction at AERONET sites where ice fraction can be independently estimated. Using this linear equation, we estimate the magnitude of the error for a set of cloud profiles from five sites of the Atmospheric Radiation Measurement programme. The dataset contains separate retrievals of ice and liquid retrievals; hence ice fraction can be estimated. The magnitude of the error at each location was related to the relative frequencies of occurrence in thick frontal cloud at the mid-latitude sites and of deep convection at the tropical sites – that is, of deep cloud containing both ice and liquid particles. The long-term mean optical depth error at the five locations spans the range 2–4, which we show to be small enough to allow calculation of top-of-atmosphere flux to within 10 % and surface flux to about 15 %.

scholarly journals Statistics of vertical backscatter profiles of cirrus clouds

2011 ◽  
Vol 11 (24) ◽  
pp. 12925-12943 ◽  
Author(s):  
P. Veglio ◽  
T. Maestri
Keyword(s):  
Optical Depth ◽  
Satellite Observation ◽  
Cirrus Clouds ◽  
Cloud Base ◽  
Physical Parameters ◽  
Cloud Optical Depth ◽  
Cloud Temperature ◽  
The Mean ◽  
Depth Increase ◽  
The Impact

Abstract. A nearly global statistical analysis of vertical backscatter and extinction profiles of cirrus clouds collected by the CALIOP lidar, on-board of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation, is presented. Statistics on frequency of occurrence and distribution of bulk properties of cirrus clouds in general and, for the first time, of horizontally homogeneous (on a 5-km field of view) cirrus clouds only are provided. Annual and seasonal backscatter profiles (BSP) are computed for the horizontally homogeneous cirri. Differences found in the day/night cases and for midlatitudes and tropics are studied in terms of the mean physical parameters of the clouds from which they are derived. The relationship between cloud physical parameters (optical depth, geometrical thickness and temperature) and the shape of the BSP is investigated. It is found that cloud geometrical thickness is the main parameter affecting the shape of the mean CALIOP BSP. Specifically, cirrus clouds with small geometrical thicknesses show a maximum in mean BSP curve located near cloud top. As the cloud geometrical thickness increases the BSP maximum shifts towards cloud base. Cloud optical depth and temperature have smaller effects on the shape of the CALIOP BSPs. In general a slight increase in the BSP maximum is observed as cloud temperature and optical depth increase. In order to fit mean BSPs, as functions of geometrical thickness and position within the cloud layer, polynomial functions are provided. The impact on satellite radiative transfer simulations in the infrared spectrum when using either a constant ice-content (IWC) along the cloud vertical dimension or an IWC profile derived from the BSP fitting functions is evaluated. It is, in fact, demonstrated that, under realistic hypotheses, the mean BSP is linearly proportional to the IWC profile.

scholarly journals Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples

2021 ◽  
Vol 14 (7) ◽  
pp. 5107-5126
Author(s):  
Hartwig Deneke ◽  
Carola Barrientos-Velasco ◽  
Sebastian Bley ◽  
Anja Hünerbein ◽  
Stephan Lenk ◽  
...  
Keyword(s):  
High Resolution ◽  
Optical Depth ◽  
Spatial Resolution ◽  
High Frequency ◽  
Spatiotemporal Variability ◽  
High Frequency Component ◽  
Cloud Optical Depth ◽  
Cloud Property ◽  
Cloud Properties ◽  
Narrowband Channels

Abstract. The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the geostationary Meteosat satellites is described to utilize its high-resolution visible (HRV) channel for increasing the spatial resolution of its physical outputs. This results in products with a nadir spatial resolution of 1×1 km2 compared to the standard 3×3 km2 resolution offered by the narrowband channels. This improvement thus greatly reduces the resolution gap between current geostationary and polar-orbiting meteorological satellite imagers. In the first processing step, cloudiness is determined from the HRV observations by a threshold-based cloud masking algorithm. Subsequently, a linear model that links the 0.6 µm, 0.8 µm, and HRV reflectances provides a physical constraint to incorporate the spatial high-frequency component of the HRV observations into the retrieval of cloud optical depth. The implementation of the method is described, including the ancillary datasets used. It is demonstrated that the omission of high-frequency variations in the cloud-absorbing 1.6 µm channel results in comparatively large uncertainties in the retrieved cloud effective radius, likely due to the mismatch in channel resolutions. A newly developed downscaling scheme for the 1.6 µm reflectance is therefore applied to mitigate the effects of this scale mismatch. Benefits of the increased spatial resolution of the resulting SEVIRI products are demonstrated for three example applications: (i) for a convective cloud field, it is shown that significantly better agreement between the distributions of cloud optical depth retrieved from SEVIRI and from collocated MODIS observations is achieved. (ii) The temporal evolution of cloud properties for a growing convective storm at standard and HRV spatial resolutions are compared, illustrating an improved contrast in growth signatures resulting from the use of the HRV channel. (iii) An example of surface solar irradiance, determined from the retrieved cloud properties, is shown, for which the HRV channel helps to better capture the large spatiotemporal variability induced by convective clouds. These results suggest that incorporating the HRV channel into the retrieval has potential for improving Meteosat-based cloud products for several application domains.

scholarly journals The CARMENES search for exoplanets around M dwarfs

2020 ◽  
Vol 642 ◽  
pp. A22 ◽  
Author(s):  
V. M. Passegger ◽  
A. Bello-García ◽  
J. Ordieres-Meré ◽  
J. A. Caballero ◽  
A. Schweitzer ◽  
...  
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Network Architecture ◽  
Near Infrared ◽  
Rotational Velocity ◽  
M Dwarfs ◽  
Convolutional Network ◽  
Fast Analysis ◽  
Infrared Wavelength ◽  
The Impact

Existing and upcoming instrumentation is collecting large amounts of astrophysical data, which require efficient and fast analysis techniques. We present a deep neural network architecture to analyze high-resolution stellar spectra and predict stellar parameters such as effective temperature, surface gravity, metallicity, and rotational velocity. With this study, we firstly demonstrate the capability of deep neural networks to precisely recover stellar parameters from a synthetic training set. Secondly, we analyze the application of this method to observed spectra and the impact of the synthetic gap (i.e., the difference between observed and synthetic spectra) on the estimation of stellar parameters, their errors, and their precision. Our convolutional network is trained on synthetic PHOENIX-ACES spectra in different optical and near-infrared wavelength regions. For each of the four stellar parameters, Teff, log g, [M/H], and v sin i, we constructed a neural network model to estimate each parameter independently. We then applied this method to 50 M dwarfs with high-resolution spectra taken with CARMENES (Calar Alto high-Resolution search for M dwarfs with Exo-earths with Near-infrared and optical Échelle Spectrographs), which operates in the visible (520–960 nm) and near-infrared wavelength range (960–1710 nm) simultaneously. Our results are compared with literature values for these stars. They show mostly good agreement within the errors, but also exhibit large deviations in some cases, especially for [M/H], pointing out the importance of a better understanding of the synthetic gap.

scholarly journals A novel method for estimating shortwave direct radiative effect of above-cloud aerosols using CALIOP and MODIS data

2014 ◽  
Vol 7 (6) ◽  
pp. 1777-1789 ◽  
Author(s):  
Z. Zhang ◽  
K. Meyer ◽  
S. Platnick ◽  
L. Oreopoulos ◽  
D. Lee ◽  
...  
Keyword(s):  
Atlantic Ocean ◽  
Optical Depth ◽  
Radiative Forcing ◽  
Orthogonal Polarization ◽  
Radiative Effect ◽  
Cloud Optical Depth ◽  
Modis Data ◽  
Joint Histogram ◽  
The Impact ◽  
Southeastern Atlantic

Abstract. This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) and MODIS (Moderate Resolution Imaging Spectroradiometer) data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a precomputed look-up table based on radiative transfer calculations. We verify that for smoke and polluted dust over the southeastern Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 13:30 local time) shortwave DRE of above-cloud aerosol (ACA) that generally agrees with a more rigorous pixel-level computation within 4%. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeastern Atlantic Ocean would increase, from the original value of 6.4 W m−2 based on operational CALIOP AOD to 9.6 W m−2 if CALIOP AOD retrievals are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m−2 if CALIOP AOD retrievals are biased low by a factor of 5 as suggested in Jethva et al. (2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m−2 AOD−1, suggesting a near-linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that given an above-cloud aerosol type the optical depth of the underlying clouds plays a larger role than above-cloud AOD in the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets.

scholarly journals Application of oxygen A-band equivalent width to disambiguate downwelling radiances for cloud optical depth measurement

2016 ◽  
Vol 9 (9) ◽  
pp. 4167-4179 ◽  
Author(s):  
Edward R. Niple ◽  
Herman E. Scott ◽  
John A. Conant ◽  
Stephen H. Jones ◽  
Frank J. Iannarilli ◽  
...  
Keyword(s):  
Optical Depth ◽  
Near Infrared ◽  
Spectral Radiance ◽  
Retrieval Method ◽  
Cloud Optical Depth ◽  
Depth Measurement ◽  
The Us ◽  
Linear Fit ◽  
Radiation Measurements ◽  
Better Than

Abstract. This paper presents the three-waveband spectrally agile technique (TWST) for measuring cloud optical depth (COD). TWST is a portable field-proven sensor and retrieval method offering a unique combination of fast (1 Hz) cloud-resolving (0.5° field of view) real-time-reported COD measurements. It entails ground-based measurement of visible and near-infrared (VNIR) zenith spectral radiances much like the Aerosol Robotic Network (AERONET) cloud-mode sensors. What is novel in our approach is that we employ absorption in the oxygen A-band as a means of resolving the COD ambiguity inherent in using up-looking spectral radiances. We describe the TWST sensor and algorithm, and assess their merits by comparison to AERONET cloud-mode measurements collected during the US Department of Energy's Atmospheric Radiation Measurements (ARM) Two-Column Aerosol Project (TCAP). Spectral radiance agreement was better than 1 %, while a linear fit of COD yielded a slope of 0.905 (TWST reporting higher COD) and offset of −2.1.

Evaluating the impact of aerosol particles above cloud on cloud optical depth retrievals from MODIS

2014 ◽  
Vol 119 (9) ◽  
pp. 5410-5423 ◽  
Author(s):  
Ricardo Alfaro-Contreras ◽  
Jianglong Zhang ◽  
James R. Campbell ◽  
Robert E. Holz ◽  
Jeffrey S. Reid
Keyword(s):  
Optical Depth ◽  
Aerosol Particles ◽  
Cloud Optical Depth ◽  
The Impact

scholarly journals The Influence of Entrainment and Mixing Assumption on Aerosol–Cloud Interactions in Marine Stratocumulus

2009 ◽  
Vol 66 (5) ◽  
pp. 1450-1464 ◽  
Author(s):  
Adrian A. Hill ◽  
Graham Feingold ◽  
Hongli Jiang
Keyword(s):  
Optical Depth ◽  
Relative Sensitivity ◽  
Number Concentration ◽  
Liquid Water Path ◽  
Marine Stratocumulus ◽  
Cloud Optical Depth ◽  
Aerosol Cloud ◽  
Aerosol Cloud Interactions ◽  
Entrainment Effect ◽  
The Impact

Abstract This study uses large-eddy simulation with bin microphysics to investigate the influence of entrainment and mixing on aerosol–cloud interactions in the context of idealized, nocturnal, nondrizzling marine stratocumulus (Sc). Of particular interest are (i) an evaporation–entrainment effect and a sedimentation–entrainment effect that result from increasing aerosol concentrations and (ii) the nature of mixing between clear and cloudy air, where homogeneous and extreme inhomogeneous mixing represent the bounding mixing types. Simulations are performed at low resolution (Δz = 20 m; Δx, y = 40 m) and high resolution (Δz = 10 m; Δx, y = 20 m). It is demonstrated that an increase in aerosol from clean conditions (100 cm−3) to polluted conditions (1000 cm−3) produces both an evaporation–entrainment and a sedimentation–entrainment effect, which couple to cause about a 10% decrease in liquid water path (LWP) when all warm microphysical processes are included. These dynamical effects are insensitive to both the resolutions tested and the mixing assumption. Regardless of resolution, assuming extreme inhomogeneous rather than homogeneous mixing results in a small reduction in cloud-averaged drop number concentration, a small increase in cloud drop effective radius, and ∼1% decrease in cloud optical depth. For the case presented, these small changes play a negligible role when compared to the impact of increasing aerosol and the associated entrainment effects. Finally, it is demonstrated that although increasing resolution causes an increase in LWP and number concentration, the relative sensitivity of cloud optical depth to changes in aerosol is unaffected by resolution.

scholarly journals Stellar atmospheric parameters of FGK-type stars from high-resolution optical and near-infrared CARMENES spectra

2020 ◽  
Vol 492 (4) ◽  
pp. 5470-5507
Author(s):  
E Marfil ◽  
H M Tabernero ◽  
D Montes ◽  
J A Caballero ◽  
M G Soto ◽  
...  
Keyword(s):  
High Resolution ◽  
Near Infrared ◽  
Signal To Noise Ratio ◽  
Wavelength Region ◽  
Infrared Region ◽  
High Signal ◽  
Atmospheric Parameters ◽  
Infrared Wavelength ◽  
The Impact ◽  
Higher Sensitivity

ABSTRACT With the purpose of assessing classic spectroscopic methods on high-resolution and high signal-to-noise ratio spectra in the near-infrared wavelength region, we selected a sample of 65 F-, G-, and K-type stars observed with CARMENES, the new, ultra-stable, double-channel spectrograph at the 3.5 m Calar Alto telescope. We computed their stellar atmospheric parameters (Teff, log g, ξ, and [Fe/H]) by means of the stepar code, a python implementation of the equivalent width method that employs the 2017 version of the moog code and a grid of MARCS model atmospheres. We compiled four Fe i and Fe ii line lists suited to metal-rich dwarfs, metal-poor dwarfs, metal-rich giants, and metal-poor giants that cover the wavelength range from 5300 to 17 100 Å, thus substantially increasing the number of identified Fe i and Fe ii lines up to 653 and 23, respectively. We examined the impact of the near-infrared Fe i and Fe ii lines upon our parameter determinations after an exhaustive literature search, placing special emphasis on the 14 Gaia benchmark stars contained in our sample. Even though our parameter determinations remain in good agreement with the literature values, the increase in the number of Fe i and Fe ii lines when the near-infrared region is taken into account reveals a deeper Teff scale that might stem from a higher sensitivity of the near-infrared lines to Teff.

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