Open Access
| Issue |
EPJ Web Conf.
Volume 237, 2020
The 29th International Laser Radar Conference (ILRC 29)
|
|
|---|---|---|
| Article Number | 05006 | |
| Number of page(s) | 3 | |
| Section | Lidar Networks | |
| DOI | https://doi.org/10.1051/epjconf/202023705006 | |
| Published online | 07 July 2020 | |
- Ciofini, et al.,. "Diffractive optical components for high power laser beam sampling." Journal of Optics A: Pure and Applied Optics 5.3 (2003): 186. [CrossRef] [Google Scholar]
- Welton, E.J., J. R. Campbell, J. D. Spinhirne, and V. S. Scott, Global monitoring of clouds and aerosols using a network of micro-pulse lidar systems, Proc. SPIE, 4153, 151-158 (2001) [CrossRef] [Google Scholar]
- Campbell, J.R. J.R., D.L. Hlavka, E.J. Welton, C.J. Flynn, D.D. Turner, J.D. Spinhirne, V.S. Scott, and I.H. Hwang. Full-time, Eye-Safe Cloud and Aerosol Lidar Observation at Atmospheric Radiation Measurement Program Sites: Instrument and Data Processing, J. Atmos. Oceanic Technol., 19, 431-442 (2002) [Google Scholar]
- Lolli, S., P. Di Girolamo, Principal Component Analysis Approach to Evaluate Instrument Performances in Developing a Cost-Effective Reliable Instrument Network for Atmospheric Measurements. J. Atmos. Oceanic Technol., 32, 1642–164 (2015) [CrossRef] [Google Scholar]
- Lolli, S., Madonna, F., Rosoldi, M., Campbell, J. R., Welton, E. J., Lewis, J. R., Gu, Y., and Pappalardo, G.: Impact of varying lidar measurement and data processing techniques in evaluating cirrus cloud and aerosol direct radiative effects, Atmos. Meas. Tech., 11, 1639-1651 (2018) [Google Scholar]
- Lolli, S., J.R. Campbell, J.R. Lewis, Y. Gu, J.W. Marquis, B.N. Chew, S. Liew, S.V. Salinas, and E.J. Welton: Daytime Top-of-the-Atmosphere Cirrus Cloud Radiative Forcing Properties at Singapore. J. Appl. Meteor. Climatol., 56, 1249–1257 (2017) [CrossRef] [Google Scholar]
- Milroy, C, et al. "An assessment of pseudo-operational ground-based light detection and ranging sensors to determine the boundary-layer structure in the coastal atmosphere." Advances in Meteorology 2012 (2012). [Google Scholar]
- Lolli, S., Delaval, A., Loth, C., Garnier, A., and Flamant, P. H.: 0.355-micrometer direct detection wind lidar under testing during a field campaign in consideration of ESA's ADM-Aeolus mission, Atmos. Meas. Tech., 6, 3349-3358 (2013) [CrossRef] [Google Scholar]
- Lolli, S., Khor, W. Y., Matjafri, M. Z., & Lim, H. S. (2019). Monsoon Season Quantitative Assessment of Biomass Burning Clear-Sky Aerosol Radiative Effect at Surface by Ground-Based Lidar Observations in Pulau Pinang, Malaysia in 2014. Remote Sensing, 11(22), 2660. [CrossRef] [Google Scholar]
- Campbell, J.R., C. Ge, J. Wang, E.J. Welton, A. Bucholtz, E.J. Hyer, E.A. Reid, B.N. Chew, S. Liew, S.V. Salinas, S. Lolli, K.C. Kaku, P. Lynch, M. Mahmud, M. Mohamad, and B.N. Holben,: Applying Advanced Ground-Based Remote Sensing in the Southeast Asian Maritime Continent to Characterize Regional Proficiencies in Smoke Transport Modeling. J. Appl. Meteor. Climatol., 55, 3–22 (2016) [CrossRef] [Google Scholar]
- Lolli, S., E.J. Welton, and J.R. Campbell, Evaluating Light Rain Drop Size Estimates from Multiwavelength Micropulse Lidar Network Profiling, J. Atmos. Oceanic Tech., 30, 2798-2807 (2013) [Google Scholar]
- Lolli, S., P.D. Girolamo, B. Demoz, X. Li, and E.J. Welton, 2016. Rain evaporation rate estimates from dual-wavelength lidar measurements and intercomparison against a model analytical solution. J. Atmos. Oceanic Tech., DOI: 10.1175/JTECH-D-16-0146.1. [Google Scholar]
- Lolli, S.; D’Adderio, L.P.; Campbell, J.R.; Sicard, M.; Welton, E.J.; Binci, A.; Rea, A.; Tokay, A.; Comerón, A.; Barragan, R.; Baldasano, J.M.; Gonzalez, S.; Bech, J.; Afflitto, N.; Lewis, J.R.; Madonna, F. Vertically Resolved Precipitation Intensity Retrieved through a Synergy between the Ground-Based NASA MPLNET Lidar Network Measurements, Surface Disdrometer Datasets and an Analytical Model Solution. Remote Sens., 10, 1102 (2018 [CrossRef] [Google Scholar]
- Lolli, S., Vivone, G., Lewis, J. R., Sicard, M., Welton, E. J., Campbell, J. R., ... & Pappalardo, G. (2020). Overview of the New Version 3 NASA Micro-Pulse Lidar Network (MPLNET) Automatic Precipitation Detection Algorithm. Remote Sensing, 12(1), 71. [CrossRef] [Google Scholar]
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