Simultaneous and synergistic profiling of cloud and drizzle properties using ground-based observations
Despite the importance of radar reflectivity (<i>Z</i>) measurements in the retrieval of liquid water cloud properties, it remains nontrivial to interpret <i>Z</i> due to the possible presence of drizzle droplets within the clouds. So far, there has been no published work...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-12-01
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| Series: | Atmospheric Measurement Techniques |
| Online Access: | https://www.atmos-meas-tech.net/10/4777/2017/amt-10-4777-2017.pdf |
| _version_ | 1828842445108936704 |
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| author | S. P. Rusli S. P. Rusli D. P. Donovan H. W. J. Russchenberg |
| author_facet | S. P. Rusli S. P. Rusli D. P. Donovan H. W. J. Russchenberg |
| author_sort | S. P. Rusli |
| collection | DOAJ |
| description | Despite the importance of radar reflectivity (<i>Z</i>) measurements in the
retrieval of liquid water cloud properties, it remains nontrivial to
interpret <i>Z</i> due to the possible presence of drizzle droplets within the
clouds. So far, there has been no published work that utilizes <i>Z</i> 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 <i>Z</i>, 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. |
| first_indexed | 2024-12-12T20:23:29Z |
| format | Article |
| id | doaj.art-fd0dc40ea66c4d68b40adda352735e06 |
| institution | Directory Open Access Journal |
| issn | 1867-1381 1867-8548 |
| language | English |
| last_indexed | 2024-12-12T20:23:29Z |
| publishDate | 2017-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Measurement Techniques |
| spelling | doaj.art-fd0dc40ea66c4d68b40adda352735e062022-12-22T00:13:12ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482017-12-01104777480310.5194/amt-10-4777-2017Simultaneous and synergistic profiling of cloud and drizzle properties using ground-based observationsS. P. Rusli0S. P. Rusli1D. P. Donovan2H. W. J. Russchenberg3Department of Geoscience and Remote Sensing, Faculty of Civil Engineering and Geosciences, TU Delft, Delft, the NetherlandsRoyal Netherlands Meteorological Institute (KNMI), De Bilt, the NetherlandsRoyal Netherlands Meteorological Institute (KNMI), De Bilt, the NetherlandsDepartment of Geoscience and Remote Sensing, Faculty of Civil Engineering and Geosciences, TU Delft, Delft, the NetherlandsDespite the importance of radar reflectivity (<i>Z</i>) measurements in the retrieval of liquid water cloud properties, it remains nontrivial to interpret <i>Z</i> due to the possible presence of drizzle droplets within the clouds. So far, there has been no published work that utilizes <i>Z</i> 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 <i>Z</i>, 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.https://www.atmos-meas-tech.net/10/4777/2017/amt-10-4777-2017.pdf |
| spellingShingle | S. P. Rusli S. P. Rusli D. P. Donovan H. W. J. Russchenberg Simultaneous and synergistic profiling of cloud and drizzle properties using ground-based observations Atmospheric Measurement Techniques |
| title | Simultaneous and synergistic profiling of cloud and drizzle properties using ground-based observations |
| title_full | Simultaneous and synergistic profiling of cloud and drizzle properties using ground-based observations |
| title_fullStr | Simultaneous and synergistic profiling of cloud and drizzle properties using ground-based observations |
| title_full_unstemmed | Simultaneous and synergistic profiling of cloud and drizzle properties using ground-based observations |
| title_short | Simultaneous and synergistic profiling of cloud and drizzle properties using ground-based observations |
| title_sort | simultaneous and synergistic profiling of cloud and drizzle properties using ground based observations |
| url | https://www.atmos-meas-tech.net/10/4777/2017/amt-10-4777-2017.pdf |
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