The book presents my PhD thesis, which is about aerosol-cloud interactions by means of a dual-field-of-view polarization lidar.
Aerosol-cloud interactions (ACI) are a big challenge to quantify the overall effect of human activities on the radiative, heat, and precipitation budgets of the atmosphere. New observational capabilities are demanded. To study the influence of aerosol particles on cloud microphysics an analysis scheme composed of newly-developed arrays is introduced. The retrieval of microphysical properties of liquid-water clouds and of the aerosol particles below the clouds from lidar observations, in a practical and replicable way, is the major challenge tackled in this work.
A lidar-based approach to derive liquid-water cloud microphysical properties from dual-field-of-view (DFOV) depolarization measurements is introduced. In addition, a new method to accurately obtain the aerosol properties below cloud layers was developed and implemented into the analysis infrastructure. Comparisons with alternative observational and modeling approaches corroborate the accuracy of both methods. The number concentration of cloud condensation nuclei (CCN) is derived from the aerosol particle extinction coefficient below the cloud, and in combination with the cloud-microphysics retrieval, they provide an aerosol-cloud scene, which allow us to study ACI. Long-term observations at the pristine location of Punta Arenas (PA), Chile, and at the polluted site of Dushanbe (DB), Tajikistan, were analyzed for this purpose. On average, similar values of cloud droplet and below-cloud CCN number concentrations, in the range of 10--150~cm$^{-3}$, were observed at PA. At DB, larger cloud droplet number concentrations were observed, in the order of 200--400 cm-3 but much larger CCN concentrations of about 700--900 cm-3 were found.
The so-called ACI index was assessed from the collected data sets. The most robust estimate of the index was obtained when calculating monthly averages over the whole measurement periods, fourteen months at PA and seven months at DB. Values of 0.83 +/- 0.20 and 0.57+/ 0.26 were derived at PA and DB, respectively, and they were used to estimate the radiative forcing due to the Twomey effect. A radiative cooling from -0.70 to -0.17 Wm-2 for PA and between -1.89 and -0.66 Wm-2 for DB is found. These results agree with global estimates of the cloud-mediated aerosol effect but are slightly larger than those values usually found at the specific locations considered. Furthermore, the results obtained at PA show the relevance of updraft movements to trigger ACI. When considering only updraft-dominated periods, the ACI index is up to 50% larger than when no wind information is considered.
The new capabilities illuminated during this work may provide a big help for estimations of the cloud-mediated radiative effect and may provide a baseline to confront models dealing with cloud microphysics in future studies.:1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1
2 Aerosol, clouds and their interaction - State of the art and research questions. . 7
2.1 Aerosol and clouds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1.1 Aerosol effect on liquid-water clouds . . . . . . . . . . . . . . . . . . . . . . . . .8
2.1.2 Aerosol effect on ice-containing clouds . . . . . . . . . . . . . . . . . . . . . . .9
2.1.3 Cloud processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 10
2.1.4 Modeling droplet number concentration Nd . . . . . . . . . . . . . . . . . . 10
2.2 Aerosol radiative effect via ACI in liquid-water clouds . . . . . . . . . . . . . .11
2.2.1 Aerosol-cloud-interaction index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.2.2 Observational approaches for the ACI index. . . . . . . . . . . . . . . . . . . .14
2.2.3 Strategies to evaluate the ACI index from observations . . . . . . . . . . .16
2.2.4 ACI studies based on lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.3 Research questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3 Lidar measurements of aerosol-cloud interaction – Overview of applied
methodologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23
3.1 Multiple-scattering lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23
3.2 DFOV-Raman technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.3 Single-FOV polarization lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25
3.3.1 Comparison between DFOV-Raman and SFOV-Depol methods . . . 27
3.4 Dual-FOV depolarization approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.4.1 Calibration of the lidar system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.4.2 DFOV-Depol measurement cases . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.5 Implementation of the DFOV-Depol approach into the standardized lidar sys-
tem Polly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33
4 Research results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37
4.1 First publication:
Polarization lidar: an extended three-signal calibration approach . . . . . . .39
4.2 Second publication:
The dual-field-of-view polarization lidar technique: A new concept in monitoring aerosol effects in liquid-water clouds – Theoretical framework . . . . . . . . .59
4.3 Third publication:
The dual-field-of-view polarization lidar technique: A new concept in monitoring aerosol effects in liquid-water clouds – Case studies . . . . . . . . . . . . . . . .79
5 Discussion and further applications – Long-term observations of aerosol-
cloud interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .101
5.1 Observations on cloud scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .102
5.2 Long-term results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
5.2.1 Comparison of DFOV-Depol products with available estimations and
observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .108
5.3 Assessment of the ACI index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
5.4 Relevance of the ACI index for the radiative effect . . . . . . . . . . . . 112
6 Summary and outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .117
Appendix A: Aerosol properties with lidar . . . . . . . . . . . . . . . . . . . .125
A.1 Lidar principles of elastic and Raman lidar . . . . . . . . . . . . . . . .125
A.2 Raman lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
A.2.1 Retrieval of extinction coefficient . . . . . . . . . . . . . . . . . . . . . 128
A.2.2 Retrieval of backscattering coefficient. . . . . . . . . . . . . . . . . . 128
A.2.3 Bottom-up approximation for Raman Signals . . . . .. . . . . . . 129
A.2.4 Evaluation of Raman methods. . . . . . . . . . . . . . . . . . . . . . . 130
A.3 Elastic Lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .132
A.3.1 Klett-Fernald Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
A.3.2 Quasi-backscattering for high resolved retrievals. . . . . . . . . 133
A.3.3 Bottom-up approximation for elastic signals . . . . . . . . . . . . 135
A.3.4 Evaluation of methods based on elastic lidar. . . . . . . . . . . . 137
A.3.5 Microphysical properties from optical properties. . . . . . . . . . 139
Appendix B Characterization of DFOV-Depol lidar . . . . . . . . . . . . 143
B.1 Transmission ratio based on long-term analysis . . . . . . . . . . . 144
Appendix C: Author’s contributions to the three publications . . . . 149
Appendix D Lists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .151
D.1 List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .151
D.2 List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
D.3 List of Symbols (excluding cumulative part) . . . . . . . . . . 156
D.4 List of Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:76905 |
| Date | 07 December 2021 |
| Creators | Jiménez Jiménez, Cristofer Andrés |
| Contributors | Universität Leipzig |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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