scholarly journals Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part II: Results over oceans

2021 ◽  
Vol 14 (5) ◽  
pp. 3277-3299
Author(s):  
Anne Garnier ◽  
Jacques Pelon ◽  
Nicolas Pascal ◽  
Mark A. Vaughan ◽  
Philippe Dubuisson ◽  
...  

Abstract. Following the release of the version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version 4 (V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and water path estimates for ice and liquid clouds. This paper (Part II) shows retrievals over ocean and describes the improvements made with respect to version 3 (V3) as a result of the significant changes implemented in the V4 algorithms, which are presented in a companion paper (Part I). The analysis of the three-channel IIR observations (08.65, 10.6, and 12.05 µm) is informed by the scene classification provided in the V4 CALIOP 5 km cloud layer and aerosol layer products. Thanks to the reduction of inter-channel effective emissivity biases in semi-transparent (ST) clouds when the oceanic background radiance is derived from model computations, the number of unbiased emissivity retrievals is increased by a factor of 3 in V4. In V3, these biases caused inconsistencies between the effective diameters retrieved from the 12/10 (βeff12/10 = τa,12/τa,10) and 12/08 (βeff12/08 = τa,12/τa,08) pairs of channels at emissivities smaller than 0.5. In V4, microphysical retrievals in ST ice clouds are possible in more than 80 % of the pixels down to effective emissivities of 0.05 (or visible optical depth ∼0.1). For the month of January 2008, which was chosen to illustrate the results, median ice De and ice water path (IWP) are, respectively, 38 µm and 3 g m−2 in ST clouds, with random uncertainty estimates of 50 %. The relationship between the V4 IIR 12/10 and 12/08 microphysical indices is in better agreement with the “severely roughened single column” ice habit model than with the “severely roughened eight-element aggregate” model for 80 % of the pixels in the coldest clouds (<210 K) and 60 % in the warmest clouds (>230 K). Retrievals in opaque ice clouds are improved in V4, especially at night and for 12/10 pair of channels, due to corrections of the V3 radiative temperature estimates derived from CALIOP geometric altitudes. Median ice De and IWP are 58 µm and 97 g m−2 at night in opaque clouds, with again random uncertainty estimates of 50 %. Comparisons of ice retrievals with Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua in the tropics show a better agreement of IIR De with MODIS visible–3.7 µm than with MODIS visible–2.1 µm in the coldest ST clouds and the opposite for opaque clouds. In prevailingly supercooled liquid water clouds with centroid altitudes above 4 km, retrieved median De and liquid water path are 13 µm and 3.4 g m−2 in ST clouds, with estimated random uncertainties of 45 % and 35 %, respectively. In opaque liquid clouds, these values are 18 µm and 31 g m−2 at night, with estimated uncertainties of 50 %. IIR De in opaque liquid clouds is smaller than MODIS visible–2.1 µm and visible–3.7 µm by 8 and 3 µm, respectively.

2020 ◽  
Author(s):  
Anne Garnier ◽  
Jacques Pelon ◽  
Nicolas Pascal ◽  
Mark A. Vaughan ◽  
Philippe Dubuisson ◽  
...  

Abstract. Following the release of the Version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version 4 (V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter (De) and ice or liquid water path estimates. This paper (Part II) shows retrievals over ocean and describes the improvements made with respect to version (V3) as a result of the significant changes implemented in the V4 algorithms, which are presented in a companion paper (Part I). The analysis of the three-channel IIR observations (08.65 μm, 10.6 μm, and 12.05 μm) is informed by the scene classification provided in the V4 CALIOP 5-km cloud layer and aerosol layer products. Thanks to the reduction of inter-channel effective emissivity biases in semi-transparent (ST) clouds when the oceanic background radiance is derived from model computations, the number of unbiased emissivity retrievals is increased by a factor 3 in V4. In V3, these biases caused inconsistencies between the effective diameters retrieved from the 12/10 and 12/08 pairs of channels at emissivities smaller than 0.5. In V4, microphysical retrievals in ST ice clouds are possible in more than 80 % of the pixels down to effective emissivities of 0.05 (or visible optical depth ~ 0.1). For the month of January 2008 chosen to illustrate the results, median ice De and ice water path (IWP) are, respectively, 38 µm and 3 g⋅m−2 in ST clouds, with random uncertainty estimates of 50 %. The relationship between the V4 IIR 12/10 and 12/08 microphysical indices is in better agreement with the severely roughened single column ice crystal model than with the severely roughened 8-element aggregate model for 80 % of the pixels in the coldest clouds ( 230 K). Retrievals in opaque ice clouds are improved in V4, especially at night and for 12/10 pair of channels, owing to corrections of the V3 radiative temperature estimates derived from CALIOP geometric altitudes. Median ice De and IWP are 58 µm and 97 g⋅m−2 at night in opaque clouds, with again random uncertainty estimates of 50 %. Comparisons of ice retrievals with Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) in the tropics show a better agreement of IIR De with MODIS visible/3.7 µm than with MODIS visible/2.1 µm in the coldest ST clouds and the opposite for opaque clouds. In prevailingly supercooled liquid water clouds with centroid altitudes above 4 km, retrieved median De and liquid water path are 13 µm and 3.4 g.m−2 in ST clouds, with estimated random uncertainties of 45 % and 35 % respectively. In opaque liquid clouds, these values are 18 µm and 31 g.m−2 at night, with estimated uncertainties of 50 %. IIR De in opaque liquid clouds is smaller than MODIS visible/2.1 and visible/3.7 by 8 µm and 3 µm, respectively.


2020 ◽  
Author(s):  
Anne Garnier ◽  
Jacques Pelon ◽  
Nicolas Pascal ◽  
Mark A. Vaughan ◽  
Philippe Dubuisson ◽  
...  

Abstract. Following the release of the Version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version 4 (V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter and ice or liquid water path estimates. Dedicated retrievals for water clouds were added in V4, taking advantage of the high sensitivity of the IIR retrieval technique to small particle sizes. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results will be presented in a companion (Part II) paper. To reduce biases at very small emissivities that were made evident in V3, the radiative transfer model used to compute clear sky brightness temperatures over oceans has been updated and tuned for the simulations using MERRA-2 data to match IIR observations in clear sky conditions. Furthermore, the clear-sky mask has been refined compared to V3 by taking advantage of additional information now available in the V4 CALIOP 5-km layer products used as an input to the IIR algorithm. After sea surface emissivity adjustments, observed and computed brightness temperatures differ by less than ± 0.2 K at night for the three IIR channels centered at 08.65, 10.6, and 12.05 µm, and inter-channel biases are reduced from several tens of Kelvin in V3 to less than 0.1 K in V4. We have also aimed at improving retrievals in ice clouds having large optical depths by refining the determination of the radiative temperature needed for emissivity computation. The initial V3 estimate, namely the cloud centroid temperature derived from CALIOP, is corrected using a parameterized function of temperature difference between cloud base and top altitudes, cloud absorption optical depth, and the CALIOP multiple scattering correction factor. As shown in Part II, this improvement reduces the low biases at large optical depths that were seen in V3, and increases the number of retrievals in dense ice clouds. As in V3, the IIR microphysical retrievals use the concept of microphysical indices applied to the pairs of IIR channels at 12.05 μm and 10.6 μm and at 12.05 μm and 08.65 μm. The V4 algorithm uses ice look-up tables (LUTs) built using two ice crystal models from the recent TAMUice 2016 database, namely the single hexagonal column model and the 8-element column aggregate model, from which bulk properties are synthesized using a gamma size distribution. Four sets of effective diameters derived from a second approach are also reported in V4. Here, the LUTs are analytical functions relating microphysical index applied to IIR channels 12.05 µm and 10.6 µm and effective diameter as derived from in situ measurements at tropical and mid-latitudes during the TC4 and SPARTICUS field experiments.


2021 ◽  
Vol 14 (5) ◽  
pp. 3253-3276 ◽  
Author(s):  
Anne Garnier ◽  
Jacques Pelon ◽  
Nicolas Pascal ◽  
Mark A. Vaughan ◽  
Philippe Dubuisson ◽  
...  

Abstract. Following the release of the version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version (version 4; V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter and ice or liquid water path estimates. Dedicated retrievals for water clouds were added in V4, taking advantage of the high sensitivity of the IIR retrieval technique to small particle sizes. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results will be presented in a companion (Part II) paper. The IIR Level 2 algorithm has been modified in the V4 data release to improve the accuracy of the retrievals in clouds of very small (close to 0) and very large (close to 1) effective emissivities. To reduce biases at very small emissivities that were made evident in V3, the radiative transfer model used to compute clear-sky brightness temperatures over oceans has been updated and tuned for the simulations using Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) data to match IIR observations in clear-sky conditions. Furthermore, the clear-sky mask has been refined compared to V3 by taking advantage of additional information now available in the V4 CALIOP 5 km layer products used as an input to the IIR algorithm. After sea surface emissivity adjustments, observed and computed brightness temperatures differ by less than ±0.2 K at night for the three IIR channels centered at 08.65, 10.6, and 12.05 µm, and inter-channel biases are reduced from several tens of Kelvin in V3 to less than 0.1 K in V4. We have also improved retrievals in ice clouds having large emissivity by refining the determination of the radiative temperature needed for emissivity computation. The initial V3 estimate, namely the cloud centroid temperature derived from CALIOP, is corrected using a parameterized function of temperature difference between cloud base and top altitudes, cloud absorption optical depth, and CALIOP multiple scattering correction factor. As shown in Part II, this improvement reduces the low biases at large optical depths that were seen in V3 and increases the number of retrievals. As in V3, the IIR microphysical retrievals use the concept of microphysical indices applied to the pairs of IIR channels at 12.05 and 10.6 µm and at 12.05 and 08.65 µm. The V4 algorithm uses ice look-up tables (LUTs) built using two ice habit models from the recent “TAMUice2016” database, namely the single-hexagonal-column model and the eight-element column aggregate model, from which bulk properties are synthesized using a gamma size distribution. Four sets of effective diameters derived from a second approach are also reported in V4. Here, the LUTs are analytical functions relating microphysical index applied to IIR channels 12.05 and 10.6 µm and effective diameter as derived from in situ measurements at tropical and midlatitudes during the Tropical Composition, Cloud, and Climate Coupling (TC4) and Small Particles in Cirrus Science and Operations Plan (SPARTICUS) field experiments.


2013 ◽  
Vol 52 (11) ◽  
pp. 2582-2599 ◽  
Author(s):  
Anne Garnier ◽  
Jacques Pelon ◽  
Philippe Dubuisson ◽  
Ping Yang ◽  
Michaël Faivre ◽  
...  

AbstractThis paper describes the version-3 level-2 operational analysis of the Imaging Infrared Radiometer (IIR) data collected in the framework of the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission to retrieve cirrus cloud effective diameter and ice water path in synergy with the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) collocated observations. The analysis uses a multisensor split-window technique relying on the concept of microphysical index applied to the two pairs of channels (12.05, 10.6 μm) and (12.05, 8.65 μm) to retrieve cirrus microphysical properties (effective diameter, ice water path) at 1-km pixel resolution. Retrievals are performed for three crystal families selected from precomputed lookup tables identified as representative of the main relationships between the microphysical indices. The uncertainties in the microphysical indices are detailed and quantified, and the impact on the retrievals is simulated. The possible biases have been assessed through consistency checks that are based on effective emissivity difference. It has been shown that particle effective diameters of single-layered cirrus clouds can be retrieved, for the first time, down to effective emissivities close to 0.05 when accurate measured background radiances can be used and up to 0.95 over ocean and land, as well as over low opaque clouds. The retrieval of the ice water path from the IIR effective optical depth and the effective diameter is discussed. Taking advantage of the cloud boundaries retrieved by CALIOP, an IIR power-law relationship between ice water content and extinction is established for four temperature ranges and shown to be consistent with previous results on average for the chosen dataset.


2018 ◽  
Vol 11 (10) ◽  
pp. 5701-5727 ◽  
Author(s):  
Stuart A. Young ◽  
Mark A. Vaughan ◽  
Anne Garnier ◽  
Jason L. Tackett ◽  
James D. Lambeth ◽  
...  

Abstract. The Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud–Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) satellite has been making near-global height-resolved measurements of cloud and aerosol layers since mid-June 2006. Version 4.10 (V4) of the CALIOP data products, released in November 2016, introduces extensive upgrades to the algorithms used to retrieve the spatial and optical properties of these layers, and thus there are both obvious and subtle differences between V4 and previous data releases. This paper describes the improvements made to the extinction retrieval algorithms and illustrates the impacts of these changes on the extinction and optical depth estimates reported in the CALIPSO lidar level 2 data products. The lidar ratios for both aerosols and ice clouds are generally higher than in previous data releases, resulting in generally higher extinction coefficients and optical depths in V4. A newly implemented algorithm for retrieving extinction coefficients in opaque layers is described and its impact examined. Precise lidar ratio estimates are also retrieved in these opaque layers. For semi-transparent cirrus clouds, comparisons between CALIOP V4 optical depths and the optical depths reported by MODIS collection 6 show substantial improvements relative to earlier comparisons between CALIOP version 3 and MODIS collection 5.


2020 ◽  
Author(s):  
Andrew M. Dzambo ◽  
Tristan L'Ecuyer ◽  
Kenneth Sinclair ◽  
Bastiaan van Diedenhoven ◽  
Siddhant Gupta ◽  
...  

Abstract. This study presents a new algorithm that combines W-band reflectivity measurements from the Airborne Precipitation Radar-3rd generation (APR-3), passive radiometric cloud optical depth and effective radius retrievals from the Research Scanning Polarimeter (RSP) to estimate total liquid water path in warm clouds and identify the contributions from cloud water path (CWP) and rainwater path (RWP). The resulting CWP estimates are primarily determined by the optical depth input, although reflectivity measurements contribute ~ 10–50 % of the uncertainty due to attenuation through the profile. Uncertainties in CWP estimates across all conditions are 25 % to 35 %, while RWP uncertainty estimates frequently exceed 100 %. Two thirds of all radar-detected clouds observed during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign that took place from 2016–2018 over the southeast Atlantic Ocean have CWP between 41 and 168 g m−2 and almost all CWPs (99 %) between 6 to 445 g m−2. RWP, by contrast, typically makes up a much smaller fraction of total liquid water path (LWP) with more than 70 % of raining clouds having less than 10 g m−2 of rainwater. In heavier warm rain (i.e. rain rate exceeding 40 mm h−1 or 1000 mm d−1), however, RWP is observed to exceed 2500 g m−2. CWP (RWP) is found to be approximately 30 g m−2 (7 g m−2) larger in unstable environments compared to stable environments. Surface precipitation is also more than twice as likely in unstable environments. Comparisons against in-situ cloud microphysical probe data spanning the range of thermodynamic stability and meteorological conditions encountered across the southeast Atlantic basin demonstrate that the combined APR-3 and RSP dataset enable a robust joint cloud-precipitation retrieval algorithm to support future ORACLES precipitation susceptibility and cloud–aerosol–precipitation interaction studies.


2020 ◽  
Vol 20 (23) ◽  
pp. 14491-14507
Author(s):  
Hwayoung Jeoung ◽  
Guosheng Liu ◽  
Kwonil Kim ◽  
Gyuwon Lee ◽  
Eun-Kyoung Seo

Abstract. Ground-based radar and radiometer data observed during the 2017–2018 winter season over the Pyeongchang area on the east coast of the Korean Peninsula were used to simultaneously estimate both the cloud liquid water path and snowfall rate for three types of snow clouds: near-surface, shallow, and deep. Surveying all the observed data, it is found that near-surface clouds are the most frequently observed cloud type with an area fraction of over 60 %, while deep clouds contribute the most in snowfall volume with about 50 % of the total. The probability distributions of snowfall rates are clearly different among the three types of clouds, with the vast majority hardly reaching 0.3 mm h−1 (liquid water equivalent snowfall rate) for near-surface, 0.5 mm h−1 for shallow, and 1 mm h−1 for deep clouds. However, the liquid water paths in the three types of clouds all have the substantial probability to reach 500 g m−2. There is no clear correlation found between snowfall rate and the liquid water path for any of the cloud types. Based on all observed snow profiles, brightness temperatures at Global Precipitation Measurement Microwave Imager (GPM/GMI) channels are simulated, and the ability of a Bayesian algorithm to retrieve snowfall rate is examined using half the profiles as observations and the other half as an a priori database. Under an idealized scenario, i.e., without considering the uncertainties caused by surface emissivity, ice particle size distribution, and particle shape, the study found that the correlation as expressed by R2 between the “retrieved” and “observed” snowfall rates is about 0.32, 0.41, and 0.62, respectively, for near-surface, shallow, and deep snow clouds over land surfaces; these numbers basically indicate the upper limits capped by cloud natural variability, to which the retrieval skill of a Bayesian retrieval algorithm can reach. A hypothetical retrieval for the same clouds but over ocean is also studied, and a major improvement in skills is found for near-surface clouds with R2 increasing from 0.32 to 0.52, while a smaller improvement is found for shallow and deep clouds. This study provides a general picture of the microphysical characteristics of the different types of snow clouds and points out the associated challenges in retrieving their snowfall rate from passive microwave observations.


2011 ◽  
Vol 11 (9) ◽  
pp. 24671-24725
Author(s):  
A. Guignard ◽  
C. J. Stubenrauch ◽  
A. J. Baran ◽  
R. Armante

Abstract. This article presents a retrieval method and a statistical analysis of the bulk micropysical properties of semi-transparent ice clouds using the Atmospheric Infrared Sounder (AIRS). Global and long-term coverage provides information on the effective diameter (De) and habits of ice crystals in relation with their environment, ice water path (IWP) and temperature. The method relies on spectral absorption differences between 8 and 12 μm that depend on ice crystal properties. Using single scattering properties for column-like or aggregate-like ice crystals, the method is sensitive to De of up to 85 μm and IWP of up to 120 g m−2. Uncertainties due to the hypotheses on atmospheric parameters and ice crystal single scattering properties as well as horizontal heterogeneities have been demonstrated to be small. The behaviour of bulk microphysical properties as a function of temperature demonstrates that pure ice clouds only occur when Tcld<230 K. On a global scale, these clouds represent practically 25 % of all high clouds and are mainly encountered in the mid-latitudes during winter and in the tropics. Colocated Radar-Lidar Geometrical Profiling (GEOPROF) data reveal an increase in the vertical extent of these cloud layers during mid-latitude winter but which does not significantly impact ice crystal characteristics. A comparative study with bulk microphysical properties from the TIROS-N Operational Vertical Sounder (TOVS) reveals improvements, especially for optically thin and thick semi-transparent ice clouds. Finally, we investigated parametrizations of De as a function of IWP or Ice Water Content (IWC), which could be useful for modelling cirrus in General Circulation Models.


2018 ◽  
Author(s):  
Stuart A. Young ◽  
Mark A. Vaughan ◽  
Anne Garnier ◽  
Jason L. Tackett ◽  
James B. Lambeth ◽  
...  

Abstract. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud-Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) satellite has been making near-global height-resolved measurements of cloud and aerosol layers since mid-June 2006. Version 4.10 (V4) of the CALIOP data products, released in November, 2016, introduces extensive upgrades to the algorithms used to retrieve the spatial and optical properties of these layers, and thus there are both obvious and subtle differences between V4 and previous data releases. This paper describes the improvements made to the extinction retrieval algorithms and illustrates the impacts of these changes on the extinction and optical depth estimates reported in the CALIPSO lidar level 2 data products. The lidar ratios for both aerosols and ice clouds are generally higher than in previous data releases, resulting in generally higher extinction coefficients and optical depths in V4. A newly implemented algorithm for retrieving extinction coefficients in opaque layers is described and its impact examined. Precise lidar ratio estimates are also retrieved in these opaque layers. For semi-transparent cirrus clouds, comparisons between CALIOP V4 optical depths and the optical depths reported by MODIS collection 6 show substantial improvements relative to earlier comparisons between CALIOP version 3 and MODIS collection 5.


2005 ◽  
Vol 44 (10) ◽  
pp. 1544-1562 ◽  
Author(s):  
Matthew D. Shupe ◽  
Taneil Uttal ◽  
Sergey Y. Matrosov

Abstract An operational suite of ground-based, remote sensing retrievals for producing cloud microphysical properties is described, assessed, and applied to 1 yr of observations in the Arctic. All measurements were made in support of the Surface Heat Budget of the Arctic (SHEBA) program and First International Satellite Cloud Climatology Project Regional Experiment (FIRE) Arctic Clouds Experiment (ACE) in 1997–98. Retrieval techniques and cloud-type classifications are based on measurements from a vertically pointing 35-GHz Doppler radar, microwave and infrared radiometers, and radiosondes. The retrieval methods are assessed using aircraft in situ measurements from a limited set of case studies and by intercomparison of multiple retrievals for the same parameters. In all-liquid clouds, retrieved droplet effective radii Re have an uncertainty of up to 32% and liquid water contents (LWC) have an uncertainty of 49%–72%. In all-ice clouds, ice particle mean sizes Dmean can be retrieved with an uncertainty of 26%–46% while retrieved ice water contents (IWC) have an uncertainty of 62%–100%. In general, radar-only, regionally tuned empirical power-law retrievals were best suited among the tested retrieval algorithms for operational cloud monitoring at SHEBA because of their wide applicability, ease of use, and reasonable statistical accuracy. More complex multisensor techniques provided a moderate improvement in accuracy for specific case studies and were useful for deriving location-specific coefficients for the empirical retrievals but were not as frequently applicable as the single sensor methods because of various limitations. During the yearlong SHEBA program, all-liquid clouds were identified 19% of the time and were characterized by an annual average droplet Re of 6.5 μm, LWC of 0.10 g m−3, and liquid water path of 45 g m−2. All-ice clouds were identified 38% of the time with an annual average particle Dmean of 73 μm, IWC of 0.014 g m−3, and ice water path of 30 g m−2.


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