On the Sensitivity of a Ground-Based Tropospheric Lidar to Aitken Mode Particles in the Upper Troposphere
Airborne observations have shown high concentrations of ultrafine aerosols in the Amazon upper troposphere (UT), which are key for replenishing the planetary boundary layer (PBL) with cloud condensation nuclei that sustain the “green ocean” clouds. Given their climatic relevance, long-term observati...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/19/4913 |
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| author | Matheus T. Silva Juan Luis Guerrero-Rascado Alexandre L. Correia Diego A. Gouveia Henrique M. J. Barbosa |
| author_facet | Matheus T. Silva Juan Luis Guerrero-Rascado Alexandre L. Correia Diego A. Gouveia Henrique M. J. Barbosa |
| author_sort | Matheus T. Silva |
| collection | DOAJ |
| description | Airborne observations have shown high concentrations of ultrafine aerosols in the Amazon upper troposphere (UT), which are key for replenishing the planetary boundary layer (PBL) with cloud condensation nuclei that sustain the “green ocean” clouds. Given their climatic relevance, long-term observations are needed, but aircraft measurements are only available in short-term campaigns. Alternatively, continuous observations of the aerosol vertical structure could be performed by a lidar (acronym for “light detection and ranging”) system in long-term campaigns. Here we assess whether a ground-based tropospheric lidar system could detect these ultrafine UT aerosols. To this aim, we simulated the lidar signal of a real instrument and then varied the instrument’s efficiency and the UT-particle concentration to determine under which conditions the detection is possible. Optical properties were computed with a Mie code based on the size distributions and numerical concentration profiles measured by the aircraft, and on the refractive indexes inverted from AERONET measurements. The aerosol optical depth (AOD) was retrieved by inverting the elastic lidar signal, and a statistical test was applied to evaluate the detection of the UT-aerosol layer. Our results indicate that, for the instrument we simulated, a 55-fold increase in the signal-to-noise ratio (SNR) is required for a 100% detection rate. This could be achieved by simultaneously time averaging over 30 min and spatially averaging to vertical bin lengths of 375 m, or by modifying the hardware. We repeated the analysis for under- and overestimated aerosol lidar ratio (L<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mrow><mi>a</mi><mi>e</mi><mi>r</mi></mrow></msub></semantics></math></inline-formula>), and found that possible systematic errors did not affect the detection rate. Further studies are necessary to assess whether such long-time averages are feasible in the Amazon region (given the very high cloud cover), and to design a hardware upgrade. Although simulations and analyses here were based on a particular instrument and for the presence of new organic particles in the Amazonian upper troposphere, our methodology and results are general and applicable to other instruments and sites. |
| first_indexed | 2024-03-09T21:13:01Z |
| format | Article |
| id | doaj.art-73636659492043cc91733e08d43135ae |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T21:13:01Z |
| publishDate | 2022-10-01 |
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| series | Remote Sensing |
| spelling | doaj.art-73636659492043cc91733e08d43135ae2023-11-23T21:40:46ZengMDPI AGRemote Sensing2072-42922022-10-011419491310.3390/rs14194913On the Sensitivity of a Ground-Based Tropospheric Lidar to Aitken Mode Particles in the Upper TroposphereMatheus T. Silva0Juan Luis Guerrero-Rascado1Alexandre L. Correia2Diego A. Gouveia3Henrique M. J. Barbosa4Physics Institute, University of Sao Paulo, Sao Paulo 05508-090, BrazilDepartment of Applied Physics, University of Granada, 18071 Granada, SpainPhysics Institute, University of Sao Paulo, Sao Paulo 05508-090, BrazilRoyal Netherlands Meteorological Institute (KNMI), 3731 GA De Bilt, The NetherlandsPhysics Institute, University of Sao Paulo, Sao Paulo 05508-090, BrazilAirborne observations have shown high concentrations of ultrafine aerosols in the Amazon upper troposphere (UT), which are key for replenishing the planetary boundary layer (PBL) with cloud condensation nuclei that sustain the “green ocean” clouds. Given their climatic relevance, long-term observations are needed, but aircraft measurements are only available in short-term campaigns. Alternatively, continuous observations of the aerosol vertical structure could be performed by a lidar (acronym for “light detection and ranging”) system in long-term campaigns. Here we assess whether a ground-based tropospheric lidar system could detect these ultrafine UT aerosols. To this aim, we simulated the lidar signal of a real instrument and then varied the instrument’s efficiency and the UT-particle concentration to determine under which conditions the detection is possible. Optical properties were computed with a Mie code based on the size distributions and numerical concentration profiles measured by the aircraft, and on the refractive indexes inverted from AERONET measurements. The aerosol optical depth (AOD) was retrieved by inverting the elastic lidar signal, and a statistical test was applied to evaluate the detection of the UT-aerosol layer. Our results indicate that, for the instrument we simulated, a 55-fold increase in the signal-to-noise ratio (SNR) is required for a 100% detection rate. This could be achieved by simultaneously time averaging over 30 min and spatially averaging to vertical bin lengths of 375 m, or by modifying the hardware. We repeated the analysis for under- and overestimated aerosol lidar ratio (L<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mrow><mi>a</mi><mi>e</mi><mi>r</mi></mrow></msub></semantics></math></inline-formula>), and found that possible systematic errors did not affect the detection rate. Further studies are necessary to assess whether such long-time averages are feasible in the Amazon region (given the very high cloud cover), and to design a hardware upgrade. Although simulations and analyses here were based on a particular instrument and for the presence of new organic particles in the Amazonian upper troposphere, our methodology and results are general and applicable to other instruments and sites.https://www.mdpi.com/2072-4292/14/19/4913elastic lidarsensitivitysignal-to-noise ratioMonte Carlo simulationAmazonnew particle formation |
| spellingShingle | Matheus T. Silva Juan Luis Guerrero-Rascado Alexandre L. Correia Diego A. Gouveia Henrique M. J. Barbosa On the Sensitivity of a Ground-Based Tropospheric Lidar to Aitken Mode Particles in the Upper Troposphere Remote Sensing elastic lidar sensitivity signal-to-noise ratio Monte Carlo simulation Amazon new particle formation |
| title | On the Sensitivity of a Ground-Based Tropospheric Lidar to Aitken Mode Particles in the Upper Troposphere |
| title_full | On the Sensitivity of a Ground-Based Tropospheric Lidar to Aitken Mode Particles in the Upper Troposphere |
| title_fullStr | On the Sensitivity of a Ground-Based Tropospheric Lidar to Aitken Mode Particles in the Upper Troposphere |
| title_full_unstemmed | On the Sensitivity of a Ground-Based Tropospheric Lidar to Aitken Mode Particles in the Upper Troposphere |
| title_short | On the Sensitivity of a Ground-Based Tropospheric Lidar to Aitken Mode Particles in the Upper Troposphere |
| title_sort | on the sensitivity of a ground based tropospheric lidar to aitken mode particles in the upper troposphere |
| topic | elastic lidar sensitivity signal-to-noise ratio Monte Carlo simulation Amazon new particle formation |
| url | https://www.mdpi.com/2072-4292/14/19/4913 |
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