Characteristics of cloud properties over South America and over Andes observed using CloudSat and reanalysis data
CloudSat profile of attenuated corrected radar reflectivity (Ze) and cloud mask data are used to investigate the cloud properties over South America (SA) during Austral Summer monsoon seasons. Deep convective core (DCC), deep & intense convective systems (DCSs & ICSs), and cloud clusters (CCs) are defined based on the Ze and cloud mask values. The spatial distributions of DCCs show that land-dominated areas have higher frequency of DCCs and Atlantic Ocean has less DCCs. The Pacific Ocean does not consist of DCCs, whereas eastern flank of Andes has higher frequency of DCCs compared to western flank of the Andes. North La Plata basin (Sierra de Cordoba) has a higher fraction of deeper (shallower) DCCs. Deep convection over the Sierra de Cordoba and South La Plata Basin is characterized by precipitation-size particles compared to cloud-size particles, whereas deep convection over north La Plata Basin is dominated by mostly cloud-size particles. The horizontal span of DCSs and ICSs is higher over south La Plata Basin and Atlantic Oceans compared to other SA areas. Sierra de Cordoba (Atlantic Ocean) has the highest (lowest) frequency of small DCSs and vice versa. DCSs and ICSs show the opposite characteristic, as all the selected areas consist of a higher fraction of large (small) sized DCSs (ICSs). CCs develop more in horizontal than in vertical direction over the high latitude and vice versa over lower latitude. The CCs distribution reflects the orography and moisture flow pattern at the east and west side of Andes. The higher Ze, which is the proxy for rainfall, occurs at the eastern flank/slope of the Andes, and related to easterly moisture loaded synoptic flow, transported from Amazon and upslope flow along the slope.
Main Authors: | Shailendra Kumar, Jose Luis Flores, Aldo S. Moya-Álvarez, Daniel Martinez-Castro, Yamina Silva |
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Format: | Article biblioteca |
Language: | English |
Published: |
International Journal of Remote Sensing
2023-04-11
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Online Access: | https://doi.org/10.1080/01431161.2023.2193301 https://doi.org/10.1080/01431161.2023.2193301 https://repositorio.inaigem.gob.pe/handle/16072021/493 |
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