Investigating the vertical distribution of clouds in Central Amazon from the measurements of a ceilometer during the GoAmazon2014/15 experiment
Abstract
Clouds can alter Earth's energy balance and affect the global climate system. They can cool the planet by reflecting solar radiation, and they can warm it by blocking outgoing thermal radiation. Despite their importance, the physical processes governing clouds are not fully known and numerical models still fail to reproduce the diurnal cycle of cloudiness and precipitation.
The main goal of our study was to investigate the diurnal cycle of cloud coverage in central Amazon. We used data collected during the GoAmazon2014/15 experiment, which made continuous observations with high temporal and spatial resolution and aimed to provide a rich database to help solve some of the physical processes that control clouds. Specifically, we used data from the ARM ceilometer (Vaisala CL31) located at the T3-Manacapuru site, near Manaus - Brazil, from Jan/14 to Dec/15. The default algorithm provides the heights of up to three cloud bases; however there is no information about the thickness of the cloud layer, neither about the attenuation of the signal. In our study we applied a cloud detection algorithm developed in our laboratory for a UV Lidar (Gouveia, 2014)¹. This algorithm determines the altitude of the cloud base and top, the maximum backscatter and the thickness of the cloud layer. We found that the default cloud base heights are a few meters above the true cloud base heights, and they actually correspond to the maximum backscatter height. The adapted algorithm provides better accuracy in this aspect. After processing the raw data with the adapted algorithm, the diurnal cycle of cloud occurrence was computed for different seasons, and compared with the average lifting condensation level (LCL) obtained from radiosonde data (five per day). We see that the LCL for the wet season is lower compared to the dry season, which matches the pattern of formation of clouds at lower heights and higher cloud fraction that was detected by the adapted algorithm. During the dry season, we see that the rise in cloud base height throughout the day coincides with the rise of LCL values. - Gouveia, D. A.: Characterization of cirrus clouds in central Amazon region using a ground-based lidar (in Portuguese), 96 pp, Master dissertation, Physics Institute, University of São Paulo, 2014.- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.A31P3166V
- Keywords:
-
- 0365 Troposphere: composition and chemistry;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 0394 Instruments and techniques;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 3311 Clouds and aerosols;
- ATMOSPHERIC PROCESSESDE: 3360 Remote sensing;
- ATMOSPHERIC PROCESSES