scholarly journals Retrieval of cloud properties from sky radiometer observed spectral zenith radiances

Author(s):  
Pradeep Khatri ◽  
Hironobu Iwabuchi ◽  
Tadahiro Hayasaka ◽  
Hitoshi Irie ◽  
Tamio Takamura ◽  
...  

Abstract. An optimal-estimation based algorithm to retrieve cloud optical thickness (COD) and cloud-particle effective radius (CER) from spectral zenith radiances observed by a narrow field of view (FOV) ground-based sky radiometer is developed. To further address the filter-degradation problem while analyzing data of long-term observation, an on-site calibration procedure is proposed, which is found to have a very good accuracy with respect to a standard procedure, i.e., a procedure of deriving calibration constants using a master instrument. An error evaluation study conducted by assuming errors in observation-based transmittances and ancillary data of water vapor concentration and surface albedo suggests that the errors in input data can influence retrieved CER more effectively than COD. Except for some narrow domains that fall within COD 

2019 ◽  
Vol 12 (11) ◽  
pp. 6037-6047 ◽  
Author(s):  
Pradeep Khatri ◽  
Hironobu Iwabuchi ◽  
Tadahiro Hayasaka ◽  
Hitoshi Irie ◽  
Tamio Takamura ◽  
...  

Abstract. An optimal estimation algorithm to retrieve the cloud optical depth (COD) and cloud particle effective radius (CER) from spectral zenith radiances observed by narrow field-of-view (FOV) ground-based sky radiometers was developed. To further address the filter degradation problem while analyzing long-term observation data, an on-site calibration procedure is proposed, which has good accuracy compared with the standard calibration transfer method. An error evaluation study conducted by assuming errors in observed transmittances and ancillary data for water vapor concentration and surface albedo suggests that the errors in input data affect retrieved CER more than COD. Except for some narrow domains that fall within a COD of < 15, the retrieval errors are small for both COD and CER. The retrieved cloud properties reproduce the broadband radiances observed by a narrow FOV radiometer more precisely than broadband irradiances observed by a wide-FOV pyranometer, justifying the quality of the retrieved product (at least of COD) and indicating the important effect of the instrument FOV in cloud remote sensing. Furthermore, CODs (CERs) from sky radiometer and satellite observations show good (poor) agreement.


2021 ◽  
Vol 14 (3) ◽  
pp. 1917-1939
Author(s):  
Sebastian O'Shea ◽  
Jonathan Crosier ◽  
James Dorsey ◽  
Louis Gallagher ◽  
Waldemar Schledewitz ◽  
...  

Abstract. The cloud particle concentration, size, and shape data from optical array probes (OAPs) are routinely used to parameterise cloud properties and constrain remote sensing retrievals. This paper characterises the optical response of OAPs using a combination of modelling, laboratory, and field experiments. Significant uncertainties are found to exist with such probes for ice crystal measurements. We describe and test two independent methods to constrain a probe's sample volume that remove the most severely mis-sized particles: (1) greyscale image analysis and (2) co-location using stereoscopic imaging. These methods are tested using field measurements from three research flights in cirrus. For these cases, the new methodologies significantly improve agreement with a holographic imaging probe compared to conventional data-processing protocols, either removing or significantly reducing the concentration of small ice crystals (< 200 µm) in certain conditions. This work suggests that the observational evidence for a ubiquitous mode of small ice particles in ice clouds is likely due to a systematic instrument bias. Size distribution parameterisations based on OAP measurements need to be revisited using these improved methodologies.


2021 ◽  
pp. 1-62
Author(s):  
William B. Rossow ◽  
Kenneth R. Knapp ◽  
Alisa H Young

AbstractISCCP continues to quantify the global distribution and diurnal-to-interannual variations of cloud properties in a revised version. This paper summarizes assessments of the previous version, describes refinements of the analysis and enhanced features of the product design, discusses the few notable changes in the results, and illustrates the long-term variations of global mean cloud properties and differing high cloud changes associated with ENSO. The new product design includes a global, pixel-level product on a 0.1°?grid, all other gridded products at 1.0°-equivalent equal-area, separate-satellite products with ancillary data for regional studies, more detailed, embedded quality information, and all gridded products in netCDF format. All the data products including all input data), expanded documentation, the processing code and an Operations Guide are available online. Notable changes are: (1) a lowered ice-liquid temperature threshold, (2) a treatment of the radiative effects of aerosols and surface temperature inversions, (3) refined specification of the assumed cloud microphysics, and (4) interpolation of the main daytime cloud information overnight. The changes very slightly increase the global monthly mean cloud amount with a little more high and a little less middle and low cloud. Over the whole period, total cloud amount slowly decreases caused by decreases in cumulus/altocumulus; consequently, average cloud top temperature and optical thickness have increased. The diurnal and seasonal cloud variations are very similar to earlier versions. Analysis of the whole record shows that high cloud variations, but not low clouds, exhibit different patterns in different ENSO events.


2019 ◽  
Vol 12 (5) ◽  
pp. 2863-2879 ◽  
Author(s):  
Nikos Benas ◽  
Jan Fokke Meirink ◽  
Martin Stengel ◽  
Piet Stammes

Abstract. Retrievals of cloud properties from geostationary satellite sensors offer extensive spatial and temporal coverage and resolution. The high temporal resolution allows the observation of diurnally resolved cloud properties. However, retrievals are sensitive to varying illumination and viewing geometries, including cloud glory and cloud bow conditions, which can lead to irregularities in the diurnal data record. In this study, these conditions and their effects on liquid cloud optical thickness and effective radius retrievals are analyzed using the Cloud Physical Properties (CPP) algorithm. This analysis is based on the use of Spinning Enhanced Visible and Infrared Imager (SEVIRI) reflectances and products from Meteosat-8 and Meteosat-10, which are located over the Indian and Atlantic Ocean, respectively, and cover an extensive common area under different viewing angles. Comparisons of the retrievals from two full days, over ocean and land, and using different spectral combinations of visible and shortwave-infrared channels, are performed, to assess the importance of these factors in the retrieval process. The sensitivity of the cloud-bow- and cloud-glory-related irregularities to the width of the assumed droplet size distribution is analyzed by using different values of the effective variance of the size distribution. The results suggest for marine stratocumulus clouds an effective variance of around 0.05, which implies a narrower size distribution than typically assumed in satellite-based retrievals. For the case with continental clouds a broader size distribution (effective variance around 0.15) is obtained. This highlights the importance of appropriate size distribution assumptions and provides a way to improve the quality of cloud products in future climate data record releases.


2017 ◽  
Vol 10 (9) ◽  
pp. 3215-3230 ◽  
Author(s):  
André Ehrlich ◽  
Eike Bierwirth ◽  
Larysa Istomina ◽  
Manfred Wendisch

Abstract. The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff, C, and reff, S show a continuous transition of cloud properties across snow-covered sea ice and open water and are consistent with estimates based on satellite data. It is shown that the uncertainties of the trispectral retrieval increase for high values of τ, and low reff, S but nevertheless allow the effective snow grain size in cloud-covered areas to be estimated.


2016 ◽  
Vol 9 (3) ◽  
pp. 909-928 ◽  
Author(s):  
Daniel Fisher ◽  
Caroline A. Poulsen ◽  
Gareth E. Thomas ◽  
Jan-Peter Muller

Abstract. In this paper we evaluate the impact on the cloud parameter retrievals of the ORAC (Optimal Retrieval of Aerosol and Cloud) algorithm following the inclusion of stereo-derived cloud top heights as a priori information. This is performed in a mathematically rigorous way using the ORAC optimal estimation retrieval framework, which includes the facility to use such independent a priori information. Key to the use of a priori information is a characterisation of their associated uncertainty. This paper demonstrates the improvements that are possible using this approach and also considers their impact on the microphysical cloud parameters retrieved. The Along-Track Scanning Radiometer (AATSR) instrument has two views and three thermal channels, so it is well placed to demonstrate the synergy of the two techniques. The stereo retrieval is able to improve the accuracy of the retrieved cloud top height when compared to collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), particularly in the presence of boundary layer inversions and high clouds. The impact of the stereo a priori information on the microphysical cloud properties of cloud optical thickness (COT) and effective radius (RE) was evaluated and generally found to be very small for single-layer clouds conditions over open water (mean RE differences of 2.2 (±5.9) microns and mean COD differences of 0.5 (±1.8) for single-layer ice clouds over open water at elevations of above 9 km, which are most strongly affected by the inclusion of the a priori).


2009 ◽  
Vol 48 (11) ◽  
pp. 2242-2256 ◽  
Author(s):  
Anita D. Rapp ◽  
G. Elsaesser ◽  
C. Kummerow

Abstract The complicated interactions between cloud processes in the tropical hydrologic cycle and their responses to changes in environmental variables have been the focus of many recent investigations. Most studies that examine the response of the hydrologic cycle to temperature changes focus on deep convection and cirrus production, but recent results suggest that warm rain clouds may be more sensitive to temperature changes. These clouds are prevalent in the tropics and make considerable contributions to the radiation budget and to total tropical rainfall, as well as serving to moisten and precondition the atmosphere for deep convection. A change in the properties of these clouds in climate-change scenarios could have significant implications for the hydrologic cycle. Existing microwave and visible retrievals of warm rain cloud liquid water path (LWP) disagree over the range of sea surface temperatures (SST) observed in the tropical western Pacific Ocean. Although both retrieval methods show similar behavior for nonraining clouds, the two methods show very different warm-rain-cloud LWP responses to SST, both in magnitude and trend. This makes changes to the relationship between precipitation and cloud properties in changing temperature regimes difficult to interpret. A combined optimal estimation retrieval algorithm that takes advantage of the strengths of the different satellite measurements available on the Tropical Rainfall Measuring Mission (TRMM) satellite has been developed. Deconvolved TRMM Microwave Imager brightness temperatures are combined with cloud fraction from the Visible and Infrared Scanner and rainwater estimates from the TRMM precipitation radar to retrieve the cloud LWP in warm rain systems. This algorithm is novel in that it takes into account the water in the rain and estimates the LWP due to only the cloud water in a raining cloud, thus allowing investigation of the effects of precipitation on cloud properties.


2021 ◽  
Author(s):  
Yi Zeng ◽  
Yannian Zhu ◽  
Jiaxi Hu ◽  
Minghuai Wang ◽  
Daniel Rosenfeld

&lt;p&gt;Cloud top thermodynamic phase (liquid, or ice) classification is critical for the retrieval of cloud properties such as cloud top particle effective radius, cloud optical thickness and cloud water path. The physical basis for phase classification is the different absorption and scattering properties between water droplets and ice crystals over different wavelengths. Passive sensors always use the hand-tuned phase classification algorithms such as decision trees or voting schemes involving multiple thresholds. In order to improve the accuracy and universal applicability of phase classification algorithms, this study uses unsupervised K-means clustering method to classify phase using Himawari-8 (H8) multi-channel RGB images (multi-channel image algorithm, MIA). In order to evaluate the phase classification obtained by MIA, H8-CLP (H8 official product), we use CALIOP phase product as a benchmark. Through the evaluation of cloud top phase of cases from April to October in 2017, the hit rate of liquid and ice phase from H8-MIA is 88% and 65% respectively, and the total hit rate of H8-MIA algorithm is 72%. The hit rate of liquid and ice phase from H8-CLP is 81% and 62% respectively, and the total hit rate of H8-CLP algorithm is 68%. The hit rate of H8-MIA is higher than that of H8-CLP in both liquid and ice phases. It shows that the application of MIA algorithm to H8 satellite can provide more accurate and continuous cloud top phase information with high spatial and temporal resolution.&lt;/p&gt;


2012 ◽  
Vol 5 (2) ◽  
pp. 2821-2855 ◽  
Author(s):  
N. Kurita ◽  
B. D. Newman ◽  
L. J. Araguas-Araguas ◽  
P. Aggarwal

Abstract. Recent commercially available laser spectroscopy systems enabled us to continuously and reliably measure the δD and δ18O of atmospheric water vapor. The use of this new technology is becoming popular because of its advantages over the conventional approach based on cold trap collection. These advantages include much higher temporal resolution/continuous monitoring and the ability to make direct measurements of both isotopes in the field. Here, we evaluate the accuracy and precision of the laser based water vapor isotope instrument through a comparison of measurements with those found using the conventional cold trap method. A commercially available water vapor isotope analyzer (WVIA) with the vaporization system of a liquid water standard (Water Vapor Isotope Standard Source, WVISS) from Los Gatos Research (LGR) Inc. was used for this study. We found that the WVIA instrument can provide accurate results if: (1) correction is applied for time-dependent isotope drift, (2) normalization to the VSMOW/SLAP scale is implemented, and (3) the water vapor concentration dependence of the isotopic ratio is also corrected. In addition, since the isotopic value of water vapor generated by the WVISS is also dependent on the concentration of water vapor, this effect must be considered to determine the true water vapor concentration effect on the resulting isotope measurement. To test our calibration procedure, continuous water vapor isotope measurements using both a laser instrument and a cold trap system were carried out at the IAEA Isotope Hydrology Laboratory in Vienna from August to December 2011. The calibrated isotopic values measured using the WVIA agree well with those obtained via the cold trap method. The standard deviation of the isotopic difference between both methods is about 1.4‰ for δD and 0.28‰ for δ18O. This precision allowed us to obtain reliable values for d-excess. The day-to-day variation of d-excess measured by WVIA also agrees well with that found using the cold trap method. These results demonstrate that a coupled system, using commercially available WVIA and WVISS instruments can provide continuous and accurate isotope data, with results achieved similar to those obtained using the conventional method, but with drastically improved temporal resolution.


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