The water cycle strongly influences life on Earth. In particular, the precipitation modifies the 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 low-intensity precipitation) at global scale, bedsides improving our understanding of the hydrological cycle, it is crucial to reduce the associated uncertainty of the global climate models to correctly forecast future scenarios, i.e. to apply fast mitigation strategies. In this study we developed an algorithm to automatically detect precipitation from lidar measurements obtained by the National and Aeronautics Space Administration (NASA) Micropulse lidar network (MPLNET) permanent observational site in Goddard. The algorithm, once full operational, will deliver in Near Real Time (latency 1.5h) a new rain mask product that will be publicly available on MPLNET website as part of the new Version 3 Level 1.5 data. The methodology, based on an image processing technique, can detect only light precipitation events (defined by intensity and duration) as the morphological filters used through the detection process are applied on the lidar volume depolarization ratio range corrected composite images, i.e. heavy rain events are unusable as the lidar signal is completely extinguished after few meters in the precipitation or no signal detected because of the water accumulated on the receiver optics. Results from the algorithm, besides filling a gap in precipitation and virga detection by radars, are of particular interest for the scientific community because will help to better understand long-term aerosol-cloud interactions and aerosol atmospheric removal (scavenging effect) by rain as multi-year database being available for several MPLNET permanent observational sites across the globe. Moreover, we developed the automatic algorithm at Universitat Politecnica de Catalunya (UPC) Barcelona, the unique permanent observation station member of MPLNET and the European Aerosol Lidar Network (EARLINET) In the future the algorithm can be then easily applied to any other lidar and/or ceilometer network infrastructure in the frame of World Meteorological Organization (WMO) Global Aerosol Watch (GAW) aerosol lidar observation network (GALION)
Aerosol, together with cirrus clouds, play a fundamental role in the earth-atmosphere system radiation budget, especially at tropical latitudes, where the Earth surface coverage by cirrus cloud can easily reach 70%. In this study we evaluate the combined aerosol and cirrus cloud net radiative effects in a wild and barren region like South East Asia. This part of the world is extremely vulnerable to climate change and it is source of important anthropogenic and natural aerosol emissions. The analysis has been carried out by computing cirrus cloud and aerosol net radiative effects through the Fu-Liou-Gu atmospheric radiative transfer model, adequately adapted to input lidar measurements, at surface and top-of-the atmosphere. The aerosol radiative effects were computed respectively using the retrieved lidar extinction from Cloud-Aerosol Lidar with Orthogonal Polarization in 2011 and 2012 and the lidar on-board of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations for the South East Asia Region (27N-12S, 77E-132E) with 5° x 5° spatial resolution. To assess the cirrus cloud radiative effect, we used the ground-based Micro Pulse Lidar Network measurements at Singapore permanent observational site. Results put in evidence that strong aerosol emission areas are related on average to a net surface cooling. On the contrary, cirrus cloud radiative effect shows a net daytime positive warming of the system earth-atmosphere. This effect is weak over the ocean where the albedo is lower and never counter-balances the net cooling produced by aerosols. The net cooling is stronger in 2011, with an associated reduction in precipitations by the four of the five rain-gauges stations deployed in three regions as Sumatra, Kalimantan and Java with respect to 2012. We can speculate that aerosol emissions may be associated with lower rainfall, however some very important phenomena as El Nino Southern Oscillation , Madden-Julian Oscillation, Monsoon and Indian Dipole are not considered in the analysis.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.