Overview of MPLNET Version 3 Cloud Detection.

The National Aeronautics and Space Administration Micropulse Lidar Network Version 3 cloud detection algorithm is described and its differences relative to the previous version highlighted. Clouds are identified from normalized Level 1 signal profiles using two complementary methods. The first considers signal derivatives vertically for resolving low-level clouds. The second, which resolves high-level clouds like cirrus, is based on signal uncertainties given the relatively low signal-to-noise ratio exhibited in the upper troposphere by eye-safe network instruments, especially during daytime. Furthermore, a multi-temporal averaging scheme is used to improve cloud detection under conditions of weak signal-to-noise. Diurnal and seasonal cycles of cloud occurrence frequency based on one year of measurements at the Goddard Space Flight Center (Greenbelt, MD) site are compared for the new and previous versions. The largest differences, and perceived improvement, in detection occurs for high clouds (above 5-km, mean sea level) which increase in occurrence by nearly 6%. There is also an increase in the detection of multi-layered cloud profiles from 9% to 20%. Macrophysical properties and estimates of cloud optical depth are presented for a transparent cirrus dataset. However, the limit to which molecular signal can be reliably retrieved above cirrus clouds occurs between cloud optical depths of 0.5 and 0.8.

RELATIONSHIP BETWEEN AEROSOL OPTICAL DEPTH AND PARTICULATE MATTER OVER SINGAPORE: EFFECTS OF AEROSOL VERTICAL DISTRIBUTIONS.

As part of the Seven Southeast Asian Studies (7SEAS) program, an Aerosol Robotic Network (AERONET) sun photometer and a Micro-Pulse Lidar Network (MPLNET) instrument have been deployed at Singapore to study the regional aerosol environment of the Maritime Continent (MC). In addition, the Navy Aerosol Analysis and Prediction System (NAAPS) is used to model aerosol transport over the region. From 24 September 2009 to 31 March 2011, the relationships between ground-, satellite- and model-based aerosol optical depth (AOD) and particulate matter with aerodynamic equivalent diameters less than 2.5 µm (PM2.5) for air quality applications are investigated. When MPLNET-derived aerosol scale heights are applied to normalize AOD for comparison with surface PM2.5 data, the empirical relationships are shown to improve with an increased 11 %, 10 % and 5 % in explained variances, for AERONET, MODIS and NAAPS respectively. The ratios of root mean square errors to standard deviations for the relationships also show corresponding improvements of 8 %, 6 % and 2 %. Aerosol scale heights are observed to be bimodal with a mode below and another above the strongly-capped/deep near-surface layer (SCD; 0 - 1.35 km). Aerosol extinctions within SCD are well-correlated with surface PM2.5 concentrations, possibly due to strong vertical mixing in the region.

Daytime Cirrus Cloud Top-of-Atmosphere Radiative Forcing Properties at a Midlatitude Site and their Global Consequence.

One-year of continuous ground-based lidar observations (2012) are analyzed for single-layer cirrus clouds at the NASA Micro Pulse Lidar Network site at the Goddard Space Flight Center to investigate top-of-atmosphere (TOA) annual net daytime radiative forcing properties. A slight positive net daytime forcing is estimated (i.e., warming) : 0.07 - 0.67 W/m2 in relative terms, which reduces to 0.03 - 0.27 W/m2 in absolute terms after normalizing to unity based on approximated 40% midlatitude occurrence frequency rate estimated from satellite. Results are based on bookend solutions for lidar extinction-to-backscatter (20 and 30 sr) and corresponding retrievals for 532 nm cloud extinction coefficient. Uncertainties due to cloud undersampling, attenuation effects, sample selection and lidar multiple scattering are described. A net daytime cooling effect is found from the very thinnest clouds (cloud optical depth ≤ 0.01) that is attributed to relatively high solar zenith angles. A relationship between positive/negative daytime cloud forcing is demonstrated as a function of solar zenith angle and cloud top temperature. These properties, combined with the influence of varying surface albedos, are used to conceptualize how daytime cloud forcing likely varies with latitude and season, with cirrus clouds exerting less positive forcing and potentially net TOA cooling approaching the summer poles (non-ice and snow covered) versus greater warming at the equator. The existence of such a gradient would lead cirrus to induce varying daytime TOA forcing annually and seasonally, making it a far greater challenge than presently believe to constrain daytime and diurnal cirrus contributions to global radiation budgets.

Evaluating the Height of Biomass Burning Smoke Aerosols Retrieved from Synergistic Use of Multiple Satellite Sensors over Southeast Asia.

This study evaluates the height of biomass burning smoke aerosols retrieved from a combined use of Visible Infrared Imaging Radiometer Suite (VIIRS), Ozone Mapping and Profiler Suite (OMPS), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations. The retrieved heights are compared against spaceborne and ground-based lidar measurements during the peak biomass burning season (March and April) over Southeast Asia from 2013 to 2015. Based on the comparison against CALIOP, a quality assurance (QA) procedure is developed. It is found that 74% (81-84%) of the retrieved heights fall within 1 km of CALIOP observations for unfiltered (QA-filtered) data, with root-mean-square error (RMSE) of 1.1 km (0.8-1.0 km). Eliminating the requirement for CALIOP observations from the retrieval process significantly increases the temporal coverage with only a slight decrease in the retrieval accuracy; for best QA data, 64% of data fall within 1 km of CALIOP observations with RMSE of 1.1 km. When compared with Micro-Pulse Lidar Network (MPLNET) measurements deployed at Doi Ang Khang, Thailand, the retrieved heights show RMSE of 1.7 km (1.1 km) for unfiltered (QA-filtered) data for the complete algorithm, and 0.9 km (0.8 km) for the simplified algorithm.

Optical remote sensing to quantify fugitive particulate mass emissions from stationary short-term and mobile continuous sources: part I. Method and examples.

The emissions of particulate matter (PM) from anthropogenic sources raise public concern. A new method is described here that was developed to complete in situ rapid response measurements of PM mass emissions from fugitive dust sources by use of optical remote sensing (ORS) and an anemometer. The ORS system consists of one ground-based micropulse light detection and ranging (MPL) device that was mounted on a positioner, two open path-Fourier transform infrared (OP-FTIR) spectrometers, and two open path-laser transmissometers (OP-LT). An algorithm was formulated to compute PM light extinction profiles along each of the plume's cross sections that were determined with the MPL. Size-specific PM mass emission factors were then calculated by integrating the light extinction profiles with particle mass extinction efficiencies (determined with the OP-FTIRs/OP-LTs) and the wind's speed and direction. This method also quantifies the spatial and temporal variability of the plume's PM mass concentrations across each of the plume's cross sections. Example results from three field studies are also described to demonstrate how this new method is used to determine mass emission factors as well as characterize the dust plumes' horizontal and vertical dimensions and temporal variability of the PM's mass concentration.