| Autor: |
Simone Lolli, Gemine Vivone, Jasper R. Lewis, Michaël Sicard, Ellsworth J. Welton, James R. Campbell, Adolfo Comerón, Leo Pio D’Adderio, Ali Tokay, Aldo Giunta, Gelsomina Pappalardo |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
Remote Sensing, Vol 12, Iss 1, p 71 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2072-4292 |
| DOI: |
10.3390/rs12010071 |
| Popis: |
Precipitation modifies atmospheric column thermodynamics through the process of evaporation and serves as a proxy for latent heat modulation. For this reason, a correct precipitation parameterization (especially for low-intensity precipitation) within global scale models is crucial. In addition to improving our modeling of the hydrological cycle, this will reduce the associated uncertainty of global climate models in correctly forecasting future scenarios, and will enable the application of mitigation strategies. In this manuscript we present a proof of concept algorithm to automatically detect precipitation from lidar measurements obtained from the National Aeronautics and Space Administration Micropulse lidar network (MPLNET). The algorithm, once tested and validated against other remote sensing instruments, will be operationally implemented into the network to deliver a near real time (latency |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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