scholarly journals Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part I: The retrieval algorithms

2021 ◽  
Vol 14 (5) ◽  
pp. 3253-3276 ◽  
Author(s):  
Anne Garnier ◽  
Jacques Pelon ◽  
Nicolas Pascal ◽  
Mark A. Vaughan ◽  
Philippe Dubuisson ◽  
...  
Keyword(s):  
Liquid Water ◽  
Cloud Base ◽  
Transfer Model ◽  
Effective Diameter ◽  
Clear Sky ◽  
Brightness Temperatures ◽  
Microphysical Properties ◽  
Data Products ◽  
Level 2 ◽  
Infrared Radiometer

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.

scholarly journals Version 4 CALIPSO IIR ice and liquid water cloud microphysical properties, Part I: the retrieval algorithms

2020 ◽  
Author(s):  
Anne Garnier ◽  
Jacques Pelon ◽  
Nicolas Pascal ◽  
Mark A. Vaughan ◽  
Philippe Dubuisson ◽  
...  
Keyword(s):  
Liquid Water ◽  
Cloud Base ◽  
Transfer Model ◽  
Effective Diameter ◽  
Ice Clouds ◽  
Clear Sky ◽  
Brightness Temperatures ◽  
Microphysical Properties ◽  
Data Products ◽  
Level 2

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.

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 ◽  
...  
Keyword(s):  
Liquid Water ◽  
Effective Diameter ◽  
Ice Clouds ◽  
Water Path ◽  
Random Uncertainty ◽  
Microphysical Properties ◽  
Uncertainty Estimates ◽  
Data Products ◽  
Level 2 ◽  
Infrared Radiometer

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.

scholarly journals Version 4 CALIPSO IIR ice and liquid water cloud microphysical properties, Part II: results over oceans

2020 ◽  
Author(s):  
Anne Garnier ◽  
Jacques Pelon ◽  
Nicolas Pascal ◽  
Mark A. Vaughan ◽  
Philippe Dubuisson ◽  
...  
Keyword(s):  
Liquid Water ◽  
Effective Diameter ◽  
Liquid Water Path ◽  
Ice Clouds ◽  
Water Path ◽  
Random Uncertainty ◽  
Microphysical Properties ◽  
Uncertainty Estimates ◽  
Data Products ◽  
Level 2

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.

scholarly journals Long term assessment of the CALIPSO Imaging Infrared Radiometer (IIR) calibration and stability through comparisons with MODIS/Aqua and SEVIRI/Meteosat

2016 ◽  
Author(s):  
Anne Garnier ◽  
Noëlle A. Scott ◽  
Jacques Pelon ◽  
Raymond Armante ◽  
Laurent Crépeau ◽  
...  
Keyword(s):  
Radiative Transfer Model ◽  
Transfer Model ◽  
Clear Sky ◽  
Brightness Temperatures ◽  
Medium Resolution ◽  
Wide Range ◽  
Air Mass Types ◽  
June July ◽  
The Tropics ◽  
Infrared Radiometer

Abstract. The quality of the calibrated radiances of the medium-resolution Imaging Infrared Radiometer (IIR) on-board the CALIPSO satellite is quantitatively controlled since the beginning of the mission in June 2006. Two complementary “relative” and “stand-alone” approaches are used, which are related to comparisons of measured brightness temperatures, and to model-to-observations comparisons, respectively. In both cases, IIR channels 1 (8.65 μm), 2 (10.6 μm), and 3 (12.05 μm) are paired with MODIS/Aqua “companion” channels 29, 31, and 32, respectively, as well as with SEVIRI/Meteosat companion channels IR8.7, IR10.8 and IR12, respectively. These pairs were selected before launch to meet radiometric, geometric and space-time constraints. The pre-launch studies were based on simulations and sensitivity studies using the 4A/OP radiative transfer model fed with the more than 2300 atmospheres of the climatological TIGR dataset further sorted out in five air mass types. Over the 9.5 years of operation since launch, in a semi-operational process, collocated measurements of IIR and of its companion channels have been compared at all latitudes over ocean, during day and night, and for all types of scenes in a wide range of brightness temperatures when dealing with the relative approach. The relative approach shows an excellent stability of IIR2-MODIS31 and IIR3-MODIS32 brightness temperature differences (BTD) since launch A slight trend of the IIR1-MODIS29 BTD, equal to −0.02 K/year on average over 9.5 years, is detected by the relative approach at all latitudes and all scene temperatures. For the stand-alone approach, clear sky measurements only are considered, which are directly compared with simulations using 4A/OP and collocated ERA-Interim reanalyses. The clear sky mask is derived from collocated observations from IIR and the CALIPSO lidar. Simulations for clear sky pixels in the tropics reproduce the differences between IIR1 and MODIS29 within 0.02 K, and between IIR2 and MODIS31 within 0.04 K, whereas IIR3-MODIS32 is larger than simulated by 0.26 K. The stand-alone approach indicates that the trend identified from the relative approach originates from MODIS29, whereas no trend (less than ±0.004 K/year) is evidenced for any of the IIR channels. Finally, a year-by-year seasonal bias between nighttime and daytime IIR-MODIS BTDs was found at mid-latitude in the northern hemisphere by the relative approach. It is due to a nighttime IIR bias as determined by the stand-alone approach, which originates from a calibration drift during day-to-night transitions. The largest bias is in June/July with IIR2 and IIR3 too warm by 0.4 K on average, and IIR1 too warm by 0.2 K.

scholarly journals Simultaneous and synergistic profiling of cloud and drizzle properties using ground-based observations

2017 ◽  
Author(s):  
Stephanie P. Rusli ◽  
David P. Donovan ◽  
Herman W. J. Russchenberg
Keyword(s):  
Liquid Water ◽  
Optimal Estimation ◽  
Liquid Water Content ◽  
Cloud Base ◽  
Unified Framework ◽  
Forward Models ◽  
Eddy Simulation ◽  
Brightness Temperatures ◽  
Microphysical Properties ◽  
Cloud Properties

Abstract. Despite the importance of radar reflectivity (Z) measurements in the retrieval of liquid water cloud properties, it remains non-trivial to interpret Z due to the possible presence of drizzle droplets within the clouds. So far, there has been no published work that utilizes Z to identify the presence of drizzle above the cloud base in an optimized and a physically-consistent manner. In this work, we develop a retrieval technique that exploits the synergy of different remote sensing systems to carry out this task and to subsequently profile the microphysical properties of the cloud and drizzle in a unified framework. This is accomplished by using ground-based measurements of Z, lidar attenuated backscatter below as well as above the cloud base, and microwave brightness temperatures. Fast physical forward models coupled to cloud and drizzle structure parametrization are used in an optimal estimation type framework in order to retrieve the best-estimate for the cloud and drizzle property profiles. The cloud retrieval is first evaluated using synthetic signals generated from large-eddy simulation output to verify the forward models used in the retrieval procedure and the vertical parametrization of the liquid water content. From this exercise it is found that, on average, the cloud properties can be retrieved within 5 % of the mean truth. The full cloud-drizzle retrieval method is then applied to a selected ACCEPT campaign dataset collected in Cabauw, The Netherlands. An assessment of the retrieval products is performed using three independent methods from the literature, each was specifically developed to retrieve only the cloud properties, the drizzle properties below the cloud base, or the drizzle fraction within the cloud, respectively. One-to-one comparisons, taking into account the uncertainties or limitations of each retrieval, show that our results are generally consistent with what is derived using the three independent methods.

scholarly journals Simultaneous and synergistic profiling of cloud and drizzle properties using ground-based observations

2017 ◽  
Vol 10 (12) ◽  
pp. 4777-4803 ◽  
Author(s):  
Stephanie P. Rusli ◽  
David P. Donovan ◽  
Herman W. J. Russchenberg
Keyword(s):  
Liquid Water ◽  
Optimal Estimation ◽  
Liquid Water Content ◽  
Cloud Base ◽  
Unified Framework ◽  
Forward Models ◽  
Eddy Simulation ◽  
Brightness Temperatures ◽  
Microphysical Properties ◽  
Cloud Properties

Abstract. Despite the importance of radar reflectivity (Z) measurements in the retrieval of liquid water cloud properties, it remains nontrivial to interpret Z due to the possible presence of drizzle droplets within the clouds. So far, there has been no published work that utilizes Z to identify the presence of drizzle above the cloud base in an optimized and a physically consistent manner. In this work, we develop a retrieval technique that exploits the synergy of different remote sensing systems to carry out this task and to subsequently profile the microphysical properties of the cloud and drizzle in a unified framework. This is accomplished by using ground-based measurements of Z, lidar attenuated backscatter below as well as above the cloud base, and microwave brightness temperatures. Fast physical forward models coupled to cloud and drizzle structure parameterization are used in an optimal-estimation-type framework in order to retrieve the best estimate for the cloud and drizzle property profiles. The cloud retrieval is first evaluated using synthetic signals generated from large-eddy simulation (LES) output to verify the forward models used in the retrieval procedure and the vertical parameterization of the liquid water content (LWC). From this exercise it is found that, on average, the cloud properties can be retrieved within 5 % of the mean truth. The full cloud–drizzle retrieval method is then applied to a selected ACCEPT (Analysis of the Composition of Clouds with Extended Polarization Techniques) campaign dataset collected in Cabauw, the Netherlands. An assessment of the retrieval products is performed using three independent methods from the literature; each was specifically developed to retrieve only the cloud properties, the drizzle properties below the cloud base, or the drizzle fraction within the cloud. One-to-one comparisons, taking into account the uncertainties or limitations of each retrieval, show that our results are consistent with what is derived using the three independent methods.

scholarly journals Long-term assessment of the CALIPSO Imaging Infrared Radiometer (IIR) calibration and stability through simulated and observed comparisons with MODIS/Aqua and SEVIRI/Meteosat

2017 ◽  
Vol 10 (4) ◽  
pp. 1403-1424 ◽  
Author(s):  
Anne Garnier ◽  
Noëlle A. Scott ◽  
Jacques Pelon ◽  
Raymond Armante ◽  
Laurent Crépeau ◽  
...  
Keyword(s):  
Satellite Observation ◽  
Initial Guess ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Clear Sky ◽  
Brightness Temperatures ◽  
Wide Range ◽  
Resolution Imaging ◽  
The Tropics ◽  
Infrared Radiometer

Abstract. The quality of the calibrated radiances of the medium-resolution Imaging Infrared Radiometer (IIR) on-board the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite is quantitatively evaluated from the beginning of the mission in June 2006. Two complementary relative and stand-alone approaches are used, which are related to comparisons of measured brightness temperatures and to model-to-observations comparisons, respectively. In both cases, IIR channels 1 (8.65 µm), 2 (10.6 µm), and 3 (12.05 µm) are paired with the Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua Collection 5 companion channels 29, 31, and 32, respectively, as well as with the Spinning Enhanced Visible and Infrared Imager (SEVIRI)/Meteosat companion channels IR8.7, IR10.8, and IR12, respectively. These pairs were selected before launch to meet radiometric, geometric, and space-time constraints. The prelaunch studies were based on simulations and sensitivity studies using the 4A/OP radiative transfer model and the more than 2300 atmospheres of the climatological Thermodynamic Initial Guess Retrieval (TIGR) input dataset further sorted into five air mass types. Using data from over 9.5 years of on-orbit operation, and following the relative approach technique, collocated measurements of IIR and of its companion channels have been compared at all latitudes over ocean, during day and night, and for all types of scenes in a wide range of brightness temperatures. The relative approach shows an excellent stability of IIR2–MODIS31 and IIR3–MODIS32 brightness temperature differences (BTDs) since launch. A slight trend within the IIR1–MODIS29 BTD, that equals −0.02 K yr−1 on average over 9.5 years, is detected when using the relative approach at all latitudes and all scene temperatures. For very cold scene temperatures (190–200 K) in the tropics, each IIR channel is warmer than its MODIS companion channel by 1.6 K on average. For the stand-alone approach, clear sky measurements only are considered, which are directly compared with simulations using 4A/OP and collocated ERA-Interim (ERA-I) reanalyses. The clear sky mask is derived from collocated observations from IIR and the CALIPSO lidar. Simulations for clear sky pixels in the tropics reproduce the differences between IIR1 and MODIS29 within 0.02 K and between IIR2 and MODIS31 within 0.04 K, whereas IIR3–MODIS32 is larger than simulated by 0.26 K. The stand-alone approach indicates that the trend identified from the relative approach originates from MODIS29, whereas no trend (less than ±0.004 K yr−1) is identified for any of the IIR channels. Finally, using the relative approach, a year-by-year seasonal bias between nighttime and daytime IIR–MODIS BTD was found at mid-latitude in the Northern Hemisphere. It is due to a nighttime IIR bias as determined by the stand-alone approach, which originates from a calibration drift during day-to-night transitions. The largest bias is in June and July when IIR2 and IIR3 are warmer by 0.4 K on average, and IIR1 is warmer by 0.2 K.

scholarly journals Analysis of actinic flux profiles measured from an ozonesonde balloon

2015 ◽  
Vol 15 (8) ◽  
pp. 4131-4144 ◽  
Author(s):  
P. Wang ◽  
M. Allaart ◽  
W. H. Knap ◽  
P. Stammes
Keyword(s):  
Atmospheric Chemistry ◽  
Low Cost ◽  
Green Light ◽  
Single Layer ◽  
Radiative Transfer Model ◽  
Cloud Base ◽  
Transfer Model ◽  
Actinic Flux ◽  
Clear Sky ◽  
The Impact

Abstract. A green light sensor has been developed at KNMI to measure actinic flux profiles using an ozonesonde balloon. In total, 63 launches with ascending and descending profiles were performed between 2006 and 2010. The measured uncalibrated actinic flux profiles are analysed using the Doubling–Adding KNMI (DAK) radiative transfer model. Values of the cloud optical thickness (COT) along the flight track were taken from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Cloud Physical Properties (CPP) product. The impact of clouds on the actinic flux profile is evaluated on the basis of the cloud modification factor (CMF) at the cloud top and cloud base, which is the ratio between the actinic fluxes for cloudy and clear-sky scenes. The impact of clouds on the actinic flux is clearly detected: the largest enhancement occurs at the cloud top due to multiple scattering. The actinic flux decreases almost linearly from cloud top to cloud base. Above the cloud top the actinic flux also increases compared to clear-sky scenes. We find that clouds can increase the actinic flux to 2.3 times the clear-sky value at cloud top and decrease it to about 0.05 at cloud base. The relationship between CMF and COT agrees well with DAK simulations, except for a few outliers. Good agreement is found between the DAK-simulated actinic flux profiles and the observations for single-layer clouds in fully overcast scenes. The instrument is suitable for operational balloon measurements because of its simplicity and low cost. It is worth further developing the instrument and launching it together with atmospheric chemistry composition sensors.

scholarly journals Impacts of the Manaus pollution plume on the microphysical properties of Amazonian warm-phase clouds in the wet season

2016 ◽  
Author(s):  
Micael A. Cecchini ◽  
Luiz A. T Machado ◽  
Jennifer M. Comstock ◽  
Fan Mei ◽  
Jian Wang ◽  
...  
Keyword(s):  
Growth Rates ◽  
Urban Pollution ◽  
Droplet Size Distribution ◽  
Bimodal Distribution ◽  
Anthropogenic Sources ◽  
Cloud Base ◽  
Effective Diameter ◽  
Wet Season ◽  
Coalescence Process ◽  
Microphysical Properties

Abstract. The remote atmosphere over the Amazon can be similar to oceanic regions in terms aerosol conditions and cloud type formations. This is especially true during the wet season. The main aerosol-related disturbances over the Amazon have both natural sources, such as dust transport from Africa, and anthropogenic sources, such as biomass burning or urban pollution. The present work considers the impacts of the latter on the microphysical properties of warm-phase clouds by analyzing observations of the interactions between Manaus city and its surroundings, as part of the GoAmazon2014/5 Experiment. The analyzed period corresponds to the wet season over a tropical rain forest (i.e., Feb to Mar 2014 and corresponding to the first Intensive Operating Period (IOP1) of GoAmazon2014/5), and the droplets observed are in the range 1 μm ≤ D ≤ 50 μm. The wet season largely presents a clean background atmosphere characterized by frequent rain showers. As such, the contrast between background clouds compared to those affected by the Manaus pollution can be observed and detailed. The focus is on the characteristics of the initial microphysical properties in cumulus clouds predominantly at their early stages. The pollution-affected clouds are found to have lower effective diameters and higher droplet number concentrations. The average differences range from 10% to 40% for the effective diameter and are as high as 1000% for droplet concentration across different vertical levels (0 to 3200 m). The growth rates of droplets with altitude are slower for pollution-affected clouds (2.90 compared to 5.59 μm km-1), as explained by the absence of bigger droplets at the onset of cloud development. Clouds under background conditions have higher concentrations of larger d roplets (e.g., > 20 μm) close to cloud base, which would contribute significantly to the growth rates through the collision-coalescence process. The droplet size distribution (DSD) overall shape do not appear to be predominantly determined by updraft strength, especially beyond the 20 μm range. The aerosol conditions play a major role in that case. However, the updrafts modulate the DSD concentrations and are responsible for the vertical transport of water in the cloud. The larger droplets found in background clouds are associated with weak water vapour competition and a bimodal distribution of droplets in the lower levels of the cloud, that enables an earlier initiation of collision-coalescence process. This study shows that the pollution produced by Manaus affects significantly warm-phase microphysical properties of the surrounding clouds by changing the initial DSD formation. The corresponding effects on ice-phase processes and precipitation formation should be the focus of future endeavors.

A 19-Month Record of Marine Aerosol–Cloud–Radiation Properties Derived from DOE ARM Mobile Facility Deployment at the Azores. Part I: Cloud Fraction and Single-Layered MBL Cloud Properties

2014 ◽  
Vol 27 (10) ◽  
pp. 3665-3682 ◽  
Author(s):  
Xiquan Dong ◽  
Baike Xi ◽  
Aaron Kennedy ◽  
Patrick Minnis ◽  
Robert Wood
Keyword(s):  
Boundary Layer ◽  
High Pressure ◽  
Liquid Water ◽  
Mixed Boundary ◽  
Cloud Condensation Nuclei ◽  
Low Pressure ◽  
Cloud Fraction ◽  
Cloud Base ◽  
Microphysical Properties ◽  
Cloud Properties

Abstract A 19-month record of total and single-layered low (&lt;3 km), middle (3–6 km), and high (&gt;6 km) cloud fractions (CFs) and the single-layered marine boundary layer (MBL) cloud macrophysical and microphysical properties was generated from ground-based measurements at the Atmospheric Radiation Measurement Program (ARM) Azores site between June 2009 and December 2010. This is the most comprehensive dataset of marine cloud fraction and MBL cloud properties. The annual means of total CF and single-layered low, middle, and high CFs derived from ARM radar and lidar observations are 0.702, 0.271, 0.01, and 0.106, respectively. Greater total and single-layered high (&gt;6 km) CFs occurred during the winter, whereas single-layered low (&lt;3 km) CFs were more prominent during summer. Diurnal cycles for both total and low CFs were stronger during summer than during winter. The CFs are bimodally distributed in the vertical with a lower peak at ~1 km and a higher peak between 8 and 11 km during all seasons, except summer when only the low peak occurs. Persistent high pressure and dry conditions produce more single-layered MBL clouds and fewer total clouds during summer, whereas the low pressure and moist air masses during winter generate more total and multilayered clouds, and deep frontal clouds associated with midlatitude cyclones. The seasonal variations of cloud heights and thickness are also associated with the seasonal synoptic patterns. The MBL cloud layer is low, warm, and thin with large liquid water path (LWP) and liquid water content (LWC) during summer, whereas during winter it is higher, colder, and thicker with reduced LWP and LWC. The cloud LWP and LWC values are greater at night than during daytime. The monthly mean daytime cloud droplet effective radius re values are nearly constant, while the daytime droplet number concentration Nd basically follows the LWC variation. There is a strong correlation between cloud condensation nuclei (CCN) concentration NCCN and Nd during January–May, probably due to the frequent low pressure systems because upward motion brings more surface CCN to cloud base (well-mixed boundary layer). During summer and autumn, the correlation between Nd and NCCN is not as strong as that during January–May because downward motion from high pressure systems is predominant. Compared to the compiled aircraft in situ measurements during the Atlantic Stratocumulus Transition Experiment (ASTEX), the cloud microphysical retrievals in this study agree well with historical aircraft data. Different air mass sources over the ARM Azores site have significant impacts on the cloud microphysical properties and surface CCN as demonstrated by great variability in NCCN and cloud microphysical properties during some months.

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