Search

We estimate top-of-the-atmosphere (TOA) cirrus cloud radiative forcing from satellite lidar observations. We describe the technical innovations necessary to conduct this experiment. Specifically, we highlight advances in broadband radiative transfer modeling, and the optical and physical parameterizations necessary to run them. We present two years of results, across two decades (2008 vs. 2018), highlighting seasonal and annual differences. The goal of this endeavor is to standardize mechanics for transitioning this work to operational Level 2 ground and satellite lidar products moving forward. However, the unique TOA forcing characteristics of cirrus clouds are also discussed, including specifically daytime characteristics than can oscillate between warming and cooling regionally.

The National Aeronautics and Space Administration Micro Pulse Lidar Network, version 3, cloud detection algorithm is described and differences relative to the previous version are highlighted. Clouds are identified from normalized level 1 signal profiles using two complementary methods. The first method considers vertical signal derivatives for detecting low-level clouds. The second method, which detects high-level clouds like cirrus, is based on signal uncertainties necessitated by the relatively low signal-to-noise ratio exhibited in the upper troposphere by eye-safe network instruments, especially during daytime. Furthermore, a multitemporal averaging scheme is used to improve cloud detection under conditions of a weak signal-to-noise ratio. Diurnal and seasonal cycles of cloud occurrence frequency based on one year of measurements at the Goddard Space Flight Center (Greenbelt, Maryland) site are compared for the new and previous versions. The largest differences, and perceived improvement, in detection occurs for high clouds (above 5 km, above MSL), which increase in occurrence by over 5%. There is also an increase in the detection of multilayered cloud profiles from 9% to 19%. Macrophysical properties and estimates of cloud optical depth are presented for a transparent cirrus dataset. However, the limit to which the cirrus cloud optical depth could be reliably estimated occurs between 0.5 and 0.8. A comparison using collocated CALIPSO measurements at the Goddard Space Flight Center and Singapore Micro Pulse Lidar Network (MPLNET) sites indicates improvements in cloud occurrence frequencies and layer heights.

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.

The water cycle strongly influence life on Earth and precipitation especially modifies the atmospheric column thermodynamics through the evaporation process and serving as a proxy for latent heat modulation. For this reason, a correct light precipitation parameterization at global scale, it is of fundamental importance, bedsides improving our understanding of the hydrological cycle, to reduce the associated uncertainty of the global climate models to correctly forecast future scenarios. In this context we developed a full automatic algorithm based on morphological filters that, once operational, will make available a new rain product for the NASA Micropulse Lidar Network (MPLNET) and the European Aerosol Research Lidar Network (EARLINET) in the frame of WMO GALION Project

We assess the impact of swath width on the statistics of aerosol optical thickness (AOT) retrieved by satellite, as inferred from observations made by the Moderate Resolution Imaging Spectroradiometer (MODIS). Using collocated AERONET sun photometer observations we develop a correction to the MODIS data to account for calibration and algorithmic view angle dependency in the retrieved AOT. We sub-sample and correct the AOT data from the MODIS Aqua instrument along several candidate swaths of various widths for the years 2003–2011. We find that over ocean the global, annual mean AOT is within ± 0.01 of the full swath AOT for all of our sub-samples. Over land, however, most of our sub-samples are outside of this criterion range in the global, annual mean. Moreover, at smaller spatial and temporal scales we find wide deviation in the sub-sample AOT relative to the full swath over both land and ocean. In all, the sub-sample AOT is within ± 0.01 of the full swath value less than 25% of the time over land, and less than 50% of the time over ocean (less than 35% for all but the widest of our sub-sample swaths). These results suggest that future aerosol satellite missions having only narrow swath views may not sample the true AOT distribution sufficiently to reduce significantly the uncertainty in aerosol direct forcing of climate.

In this paper we illustrate a new, simple and complementary ground-based methodology to retrieve the vertically resolved atmospheric precipitation intensity through a synergy between measurements from the National Aeronautics and Space Administration (NASA) Micropulse Lidar network (MPLNET), an analytical model solution and ground-based disdrometer measurements. The presented results are obtained at two mid-latitude MPLNET permanent observational sites, located respectively at NASA Goddard Space Flight Center, USA, and at the Universitat Politècnica de Catalunya, Barcelona, Spain. The methodology is suitable to be applied to existing and/or future lidar/ceilometer networks with the main objective of either providing near-real time (3h latency) rainfall intensity measurements and/or to validate satellite missions, especially for critical light precipitation (

In this paper, we illustrate a new, simple and complementary ground-based methodology to retrieve the vertically resolved atmospheric precipitation intensity through a synergy between measurements from the National Aeronautics and Space Administration (NASA) Micropulse Lidar network (MPLNET), an analytical model solution and ground-based disdrometer measurements. The presented results are obtained at two mid-latitude MPLNET permanent observational sites, located respectively at NASA Goddard Space Flight Center, USA, and at the Universitat Politècnica de Catalunya, Barcelona, Spain. The methodology is suitable to be applied to existing and/or future lidar/ceilometer networks with the main objective of either providing near real-time (3 h latency) rainfall intensity measurements and/or to validate satellite missions, especially for critical light precipitation (

We use observations from the space-based Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) to evaluate global aerosol distributions simulated in the NASA Modern Era Retrospective Analysis for Research and Applications aerosol reanalysis (MERRAero). We focus particularly on an evaluation of aerosol types, using the CALIOP vertical feature mask (VFM) algorithm, and look especially at Saharan dust distributions during July 2009. MERRAero consists of an aerosol simulation produced in the Goddard Earth Observing System version 5 (GEOS-5) Earth system model and incorporates assimilation of MODIS-derived aerosol optical thickness (AOT) to constrain column aerosol loadings. For comparison to the CALIOP VFM we construct two synthetic VFMs using the MERRAero aerosol distributions: a CALIOP-like VFM in which we simulate the total attenuated backscatter and particle depolarization ratio from the MERRAero output and pass those into the CALIOP VFM typing algorithm (MERRAero-CALIOP), and an extinction-based VFM in which we use the MERRAero-simulated species-resolved extinction to map the MERRAero species to the CALIOP VFM types (MERRAero-Extinction). By comparing the MERRAero-CALIOP VFM to CALIOP VFM, we can diagnose the aerosol transport and speciation in MERRAero. By comparing the MERRAero-CALIOP and MERRAero-Extinction-simulated VFM, we perform a simple observing system experiment (OSE), which is useful for identifying limitations of the CALIOP VFM algorithm itself. We find that, despite having our column AOT constrained by MODIS, comparison to the CALIOP VFM reveals a greater occurrence of dusty aerosol layers in our MERRAero-CALIOP VFM due to errors in MERRAero aerosol speciation. Additionally, we find that the CALIOP VFM algorithm is challenged when classifying aerosol features when multiple aerosol types are present, as our application of the CALIOP VFM algorithm to MERRAero aerosol distributions classified marine-dominated aerosol layers with low aerosol loadings as polluted dust when the contribution of dust to the total extinction was low.

Aerosols are tiny atmospheric particles that are emitted from various natural and anthropogenic sources. They affect climate through direct and indirect interactions with solar and thermal radiation, clouds, and atmospheric circulation (Solomon et al. 2007). The launch of a variety of sophisticated satellite-based observing systems aboard the Terra, Aqua, Aura, SeaWiFS (see appendix for all acronym expansions), CALIPSO, and other satellites in the late 1990s to mid-2000s through the NASA EOS and other U.S. and non-U.S. programs ushered in a golden era in aerosol research. NASA has been a leader in providing global aerosol characterizations through observations from satellites, ground networks, and field campaigns, as well as from global and regional modeling. AeroCenter (http://aerocenter.gsfc.nasa.gov/), which was formed in 2002 to address the many facets of aerosol research in a collaborative manner, is an interdisciplinary union of researchers (~200 members) at NASA GSFC and other nearby institutions, including NOAA, several universities, and research laboratories. AeroCenter hosts a web-accessible regular seminar series and an annual meeting to present up-to-date aerosol research, including measurement techniques; remote sensing algorithms; modeling development; field campaigns; and aerosol interactions with radiation, clouds, precipitation, climate, biosphere, atmospheric chemistry, air quality, and human health. The 2013 annual meeting was held at the NASA GSFC Visitor Center on 31 May 2013, which coincided with the seventh anniversary of the passing of Yoram Kaufman, a modern pioneer in satellite-based aerosol science and the founder of AeroCenter. The central theme of this year's meeting was "current and future perspectives" of NASA's aerosol science and satellite missions.

In view of the actual or future ground-based networks and space missions involving lidar instruments, we evaluated the comparability of extinction coefficient atmospheric profiles directly retrieved or estimated with different lidar techniques, i. e. Raman and elastic lidar, and different data processing/smoothing for a transported upper atmospheric dust layer and for a cirrus cloud case through Fu-Liou-Gu radiative transfer model net forcing calculations, both at surface and at the top-of-the-atmosphere. The results put in evidence discrepancies up to 7 % on net radiative forcing for the case of dust layer case and up to 35 % for the cirrus cloud case. The main objective of this analysis is to quantitatively raise awareness on the inconsistences in calculating a significant climatological variable as the aerosol and cloud net radiative forcing due to the large diversification in lidar data measurements.

Continuous lidar observations of the planetary boundary layer (PBL) depth have been made at the Micropulse Lidar Network (MPLNET) site in Greenbelt, MD since April 2001. However, because of issues with the operational PBL depth algorithm, the data is not reliable for determining seasonal and diurnal trends. Therefore, an improved PBL depth algorithm has been developed which uses a combination of the wavelet technique and image processing. The new algorithm is less susceptible to contamination by clouds and residual layers, and in general, produces lower PBL depths. A 2010 comparison shows the operational algorithm overestimates the daily mean PBL depth when compared to the improved algorithm (1.85 and 1.07 km, respectively). The improved MPLNET PBL depths are validated using radiosonde comparisons which suggests the algorithm performs well to determine the depth of a fully developed PBL. A comparison with the Goddard Earth Observing System-version 5 (GEOS-5) model suggests that the model may underestimate the maximum daytime PBL depth by 410 m during the spring and summer. The best agreement between MPLNET and GEOS-5 occurred during the fall and they diered the most in the winter.

Optically thin cirrus cloud (optical depth < 0.3) net radiative forcing represents one of the primary uncertainties in climate feedback, as sub-visible clouds play a fundamental role in atmospheric radiation balance and climate change. A lidar is a very sensitive optical device to detect clouds with an optical depth as low as 10-4. In this paper we assess the daytime net radiative forcing of sub-visible cirrus clouds detected at Goddard Space Flight Center, a permanent observational site of the NASA Micro Pulse Lidar Network in 2012. Depending on their height, season and hour of the day, the solar albedo effect can outweigh the infrared greenhouse effect, cooling the earth atmosphere system rather than warming it exclusively. As result, based on latitude, the net forcing of sub-visible cirrus clouds can be more accurately parameterized in climate models.

Cirrus clouds are endemic to Southeast Asia and are a source of potential bias in regional passive aerosol remote sensing datasets. Here, performance of the cloud-screening algorithm for the ground-based Aerosol Robotic Network (AERONET) sun photometer data is evaluated for cirrus cloud contamination at Singapore (1.30° N, 103.77° E). Using twelve months of concurrent AERONET Level 1.5 and 2.0 cloud-screened aerosol optical depth (AOD) data, and collocated Level 1.0 Micro-Pulse Lidar Network (MPLNET) measurements, we investigate the baseline AOD bias due to cirrus cloud presence. Observations are considered for a primary sample of all data and a secondary sample where AERONET data are restricted to a zenith viewing angle ≤ 45°. Cirrus clouds are present in zenith-viewing MPL profiles for 34% and 23% of these samples respectively. Based on approximations of cirrus cloud optical properties necessary to estimate cloud optical depth from the single-channel lidar signal, and assuming partial forward scattering of diffuse light by cirrus clouds into the sun photometer’s field of view, we estimate a range in AOD bias due to unscreened cloud presence of 0.034 to 0.060 and 0.031 to 0.055 ± 0.01 for the primary and secondary sample respectively. From the analysis of AERONET AOD for the angle-limited subset alone, we also derive a positive AOD bias of 0.034, which is comparable to the lower bounds for the estimated cloud bias reported for our datasets. These findings, which we attribute to the prevalence of cirrus clouds present from regional convection, are higher than previous reports of global AOD bias in the Moderate Resolution Infrared Spectroradiometer (MODIS) satellite-borne measurements due to residual cirrus cloud presence.

Trans-Pacific Asian dust transport has been well documented, but little is known about dust invasion to the South China Sea (SCS). This study presents the first detailed characterization of dust aerosols transported to the northern SCS. On 21 March 2010, a strong Asian dust storm affected large areas from the Gobi deserts to the West Pacific, including Taiwan and Hong Kong, and was also observed by a comprehensive set of instruments at Dongsha Island, a small island (about 2 km 2 , 20°42′52" N, 116°43′51" E) in the northern SCS. Aerosol measurements including particle mass concentrations, size distribution, optical properties, hygroscopicity, and vertical profiles help depict the evolution of this dust event. Our results indicate that the dust particles were mixed with anthropogenic and marine aerosols, and transported within 250 m above ground level. The long-range transport of Asian dust to the northern SCS could significantly impact the ecosystems in the region.

The aerosol vertical distribution is an important factor in determining the relationship between satellite retrieved aerosol optical depth (AOD) and ground-level fine particle pollution concentrations. We evaluate how aerosol profiles measured by ground-based lidar and simulated by models can help improve the association between AOD retrieved by the Multi-angle Imaging Spectroradiometer (MISR) and fine particle sulfate (SO4) concentrations using matched data at two lidar sites. At the Goddard Space Flight Center (GSFC) site, both lidar and model aerosol profiles marginally improve the association between SO4 concentrations and MISR fractional AODs, as the correlation coefficient between cross-validation (CV) and observed SO4 concentrations changes from 0.87 for the no-scaling model to 0.88 for models scaled with aerosol vertical profiles. At the GSFC site, a large amount of urban aerosols resides in the well-mixed boundary layer so the column fractional AODs are already excellent indicators of ground-level particle pollution. In contrast, at the Atmospheric Radiation Measurement Program (ARM) site with relatively low aerosol loadings, scaling substantially improves model performance. The correlation coefficient between CV and observed SO4 concentrations is increased from 0.58 for the no-scaling model to 0.76 in the GEOS-Chem scaling model, and the model bias is reduced from 17% to 9%. In summary, despite the inaccuracy due to the coarse horizontal resolution and the challenges of simulating turbulent mixing in the boundary layer, GEOS-Chem simulated aerosol profiles can still improve methods for estimating surface aerosol (SO4) mass from satellite-based AODs, particularly in rural areas where aerosols in the free troposphere and any long-range transport of aerosols can significantly contribute to the column AOD.

Polar stratospheric clouds (PSC) play a primary role in the formation of annual ozone holes over Antarctica during the austral sunrise. Meridional temperature gradients in the lower stratosphere and upper troposphere, caused by strong radiative cooling, induce a broad dynamic vortex centered near the South Pole that decouples and insulates the winter polar airmass. PSC nucleate and grow as vortex temperatures gradually fall below equilibrium saturation and frost points for ambient sulfate, nitrate, and water vapor concentrations (generally below 197 K). Cloud surfaces promote heterogeneous reactions that convert stable chlorine and bromine-based molecules into photochemically active ones. As spring nears, and the sun reappears and rises, photolysis decomposes these partitioned compounds into individual halogen atoms that react with and catalytically destroy thousands of ozone molecules before they are stochastically neutralized. Despite a generic understanding of the ozone hole paradigm, many key components of the system, such as cloud occurrence, phase, and composition; particle growth mechanisms; and denitrification of the lower stratosphere have yet to be fully resolved. Satellite-based observations have dramatically improved the ability to detect PSC and quantify seasonal polar chemical partitioning. However, coverage directly over the Antarctic plateau is limited by polar-orbiting tracks that rarely exceed 80 degrees S. In December 1999, a NASA Micropulse Lidar Network instrument (MPLNET) was first deployed to the NOAA Earth Systems Research Laboratory (ESRL) Atmospheric Research Observatory at the Amundsen-Scott South Pole Station for continuous cloud and aerosol profiling. MPLNET instruments are eye-safe, capable of full-time autonomous operation, and suitably rugged and compact to withstand long-term remote deployment. With only brief interruptions during the winters of 2001 and 2002, a nearly continuous data archive exists to the present.

A threshold-based detection algorithm for cloud and aerosol layer heights in elevated micropulse lidar data (0.523 μm) is described. Thresholds for differentiating cloud and aerosol signals from that of the molecular atmosphere are based on the signal uncertainties of the level 1.0 Micropulse Lidar Network (MPLNET) data product. To illustrate the algorithm, data from 1 to 10 June 2003 collected by an MPLNET instrument at the South Pole are discussed for polar stratospheric cloud-height retrievals. Additional tests are run for algorithm sensitivity relative to variable solar background scenes. The algorithm is run at multiple temporal resolutions. Results derived at a base resolution are used to screen attenuation-limited profiles from longer time averages to improve performance. A signal normalization step using a theoretical molecular scattering profile limits the application of the technique in the lower atmosphere for a ground-based instrument. This would not be the case for some nadir-viewing lidars, and the application of the algorithm to airborne and satellite datasets is speculated.

Pulsed lidars are commonly used to retrieve vertical distributions of cloud and aerosol layers. It is widely believed that lidar cloud retrievals (other than cloud base altitude) are limited to optically thin clouds. Here, we demonstrate that lidars can retrieve optical depths of thick clouds using solar background light as a signal, rather than (as now) merely a noise to be subtracted. Validations against other instruments show that retrieved cloud optical depths agree within 10%-15% for overcast stratus and broken clouds. In fact, for broken cloud situations, one can retrieve not only the aerosol properties in clear-sky periods using lidar signals, but also the optical depth of thick clouds in cloudy periods using solar background signals. This indicates that, in general, it may be possible to retrieve both aerosol and cloud properties using a single lidar. Thus, lidar observations have great untapped potential to study interactions between clouds and aerosols.

From August 2012 to February 2013 a High Resolution Spectral Lidar (HSRL; 532 nm) was deployed at that National University of Singapore near a NASA Micro Pulse Lidar NETwork (MPLNET; 527 nm) site. A primary objective of the MPLNET lidar project is the production and dissemination of reliable Level 1 measurements and Level 2 retrieval products. This paper characterizes and quantifies error in Level 2 aerosol optical property retrievals conducted through inversion techniques that derive backscattering and extinction coefficients from MPLNET elastic single-wavelength datasets. MPLNET Level 2 retrievals for aerosol optical depth and extinction/backscatter coefficient profiles are compared with corresponding HSRL datasets, for which the instrument collects direct measurements of each using a unique optical configuration that segregates aerosol and cloud backscattered signal from molecular signal. The intercomparison is performed, and error matrices reported, for lower (0-5km) and the upper (>5km) troposphere, respectively, to distinguish uncertainties observed within and above the MPLNET instrument optical overlap regime.

Atmospheric profiles of the optical aerosol properties through the retrieved backscattering or extinction coefficients by lidar measurements can improve drastically the MACC-II aerosol model performances on vertical dimension. Currently the MODIS Aerosol Optical Depth data (both from Terra and Aqua) are assimilated into the model. Being a columnintegrated quantity, these data do not modify the model aerosol vertical profile, especially if the aerosols are not interactive with the meteorology. Since 1999, the MPLNET lidar network provides continuously lidar data measurements from worldwide permanent stations (currently 21), deployed from the Arctic to the Antarctic regions and in tropical and equatorial zones. The purpose of this study is to show the first preliminary results of the intercomparison of MPLNET lidar data against the ECWMF MACC-II aerosol model, for a selected MPLNET permanent observational site at National Central University of Taiwan. Assessing the model performances it is the first step for future near-real time lidar data assimilation into MACC-II aerosol model forecast.

We study the aerosol radiative forcing at infrared (IR) wavelengths using data from the Aerosol Characterization Experiment, ACE-Asia, cruise of the National Oceanic and Atmospheric Administration research vessel Ronald H. Brown. The analyses apply to the daytime periods of clear-sky conditions for the area within the immediate vicinity of the ship. An optical model is derived from chemical measurements, lidar proe les, and visible-extinction measurements, which are used to estimate the IR aerosol optical thickness and the singlescattering albedo. The IR model results are compared to detailed Fourier transform interferometer-based IR aerosol forcing estimates, pyrgeometer-based IR downward e uxes, and to observations of the direct aerosol solar forcing. This combined approach attests to the self-consistency of the optical model, and allows us to derive quantities such as the IR forcing at the top of the atmosphere (TOA) and the IR optical thickness. The mean IR aerosol optical thickness at 10 πm is 0.08 and the single-scattering albedo is 0.55. The modelled IR aerosol surface forcing reaches 10 W m i2 during the cruise, which is a signie cant contribution compared to the total direct aerosol forcing. The surface IR aerosol radiative forcing is between 10 and 25% of the short-wave aerosol forcing. The IR aerosol forcing at the TOA can be up to 19% of the solar aerosol forcing. We show good agreement between TOA aerosol IR forcing derived from the model and from the CERES (Clouds and the Earth’s Radiant Energy System) satellite data. Over the Sea of Japan, the average IR aerosol radiative forcing is 4.6 W m i2 at the surface, and 1.5 W m i2 at the TOA. The IR forcing efe ciency at the TOA is a strong function of aerosol temperature (which is coupled to vertical structure) and changes between 10 and 18 W m i2 (per IR optical depth unit), while the surface IR forcing efe ciency varies between 37 and 55 W m i2 (per IR optical depth unit).

Aerosol is one of the important factors that will influence the air quality, visibility, clouds, and precipitation processes in the troposphere. In this work, we investigated the variation of aerosol during daytime in Penang, Malaysia in certain days within July 2013. Vertical LIDAR scattering ratio and backscattering profiles, and columnar optical properties (optical depth, Angstrom exponent) of aerosols were measured using Raymetrics LIDAR and a CIMEL sunphotometer respectively. Specifically, we have determined the daytime variation of intensity and distribution level of aerosol, as well as the planetary boundary layer (PBL) and cloud classification. Subsequently, the data of columnar aerosol optical depth (AOD) and size distribution in the atmospheric were used to quantify the properties of aerosol variation during daytime over Penang, Malaysia.

A backscattering lidar at 355 nm wavelength with Raman channel produced by Raymetrics was operated in Universiti Sains Malaysia (USM) in Penang Island. This lidar is currently taking measurements of the vertical distribution of clouds and aerosol layers over Penang Island. Background subtraction such as solar radiation for the range corrected signal during day time is needed. Dead-time correction was then applied to improve the lidar signal. In order to obtain the better signal for near and far range, gluing both analog and photon counting (PC) is necessary. Temporal evolution is plotted to determine variation planetary boundary layer (PBL) structure and the altitude of PBL also can be identify from time to time. Cloud distribution and cloud base layer can be retrieved from the temporal evolution plot and aerosol concentration pattern also can be determined.

Lidar is a widely used instrument by scientists around the world because of its high temporal and spatial resolution. With these characteristics, the interpretation of lower atmosphere behavior is improved, especially for the structure of the boundary layer, strongly related to air quality in the region. For the first time a backscattering lidar with wavelength 355 nm and Raman capabilities produced by Raymetrics was operated in Universiti Sains Malaysia (USM) in Penang Island. Due to operational constraints, this study will only discuss backscattering signal at 60 degrees zenithal angle shooting. From this study, we found that the lidar signal was extinguished very quickly and with maximum range of 3 kilometers for 30 seconds temporal resolution. The signal was extremely noisy in this study and even after subtracting the backgrounds such as solar radiation in the range corrected signal. Dead-time correction was then applied to improve the lidar signal. The better signal for the near and far ranges of this angle shooting, gluing both analog and photon is necessary. Temporal evolution was plotted to determine the planetary boundary layer (PBL) structure and the altitude of PBL also can be identified. Moreover, cloud distribution and aerosol concentration pattern can be structured from the temporal evolution graph. However, for identifying the tendency of PBL structure in Penang Island, longer period and continuous data acquisition were needed.

The NASA Micropulse Lidar Network Version 3 algorithms for planetary boundary layer and cloud detection are described and differences relative to the previous Version 2 algorithms are highlighted. A year of data from the Goddard Space Flight Center site in Greenbelt, MD consisting of diurnal and seasonal trends is used to demonstrate the results. Both the planetary boundary layer and cloud algorithms show significant improvement of the previous version.

Cirrus clouds, particularly sub visual high thin cirrus with low optical thickness, are difficult to be screened in operational aerosol retrieval algorithms. Collocated aerosol and cirrus observations from ground measurements, such as the Aerosol Robotic Network (AERONET) and the Micro-Pulse Lidar Network (MPLNET), provide us with an unprecedented opportunity to examine the susceptibility of operational aerosol products to thin cirrus contamination. Quality assured aerosol optical thickness (AOT) measurements were also tested against the CALIPSO vertical feature mask (VFM) and the MODIS-derived thin cirrus screening parameters for the purpose of evaluating thin cirrus contamination. Key results of this study include: (1) Quantitative evaluations of data uncertainties in AERONET AOT retrievals are conducted. Although AERONET cirrus screening schemes are successful in removing most cirrus contamination, strong residuals displaying strong spatial and seasonal variability still exist, particularly over thin cirrus prevalent regions during cirrus peak seasons, (2) Challenges in matching up different data for analysis are highlighted and corresponding solutions proposed, and (3) Estimation of the relative contributions from cirrus contamination to aerosol retrievals are discussed. The results are valuable for better understanding and further improving ground aerosol measurements that are critical for aerosol-related climate research.

Lidar investigation of temporal and vertical optical atmospheric properties will play a key role in the future for a continuous monitoring over the whole planet through world ground based networks. The EZ Lidar™, manufactured by LEOSPHERE, has been validated in several campaigns as that one in Southern Great Plains (ARM) or at Goddard Space Flight Center (NASA). An EZ LIDAR™ with cross-polariza tion capabilities was deployed in Kanpur, India in the frame of TIGER-Z campaign organized by NASA/AERONET in order to measure aerosol microphysical and optical properties in the Gange basin. In addition, 12 sun-photometers were deployed during this campaign and CALIPSO (The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) data were also acquired. In this work we present the results in retrieving aerosol extinction and back scattering from EZ Lidar™ measurements , and the validation of the space borne instrument CALIPSO under the satellite track. EZ Lidar™ is also coupled with the photometers to provide the measurements of the Aerosol Optical Depth over the selected region. Keywords: Pollution, Aerosol Optical Depth, Aerosol Lidar

[1] Global space borne lidar profiling of atmospheric clouds and aerosol began in 2003 following the launch of the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite. GLAS obtains nadir profiles through the atmosphere in two wavelength channels, day and night, at a fundamental resolution of 76.8 m vertical and 172 m along track. The 532 nm channel uses photon-counting detectors and resolves profiles of observed backscatter cross sections to 10−7 1/m-sr. The 1064 nm channel employs analog detection adequate to 10−6 1/m-sr and with greater dynamic range. By 2005 approximately seven months of global data are available. Processing algorithms produce data products for the corrected lidar signal, cloud and aerosol layer boundaries and optical thickness and extinction and backscatter cross sections. Operational sensitivity is shown by the frequency distribution for cloud optical thickness peaking at approximately 0.02.

[1] Data from the satellite lidar Geoscience Laser Altimeter System (GLAS) has provided a new means to retrieve height and optical depth of transmissive cloud and aerosol layers globally. We compare data sets from GLAS and an airborne under-flight of the Cloud Physics Lidar (CPL) during a unique smoke opportunity as part of a validation experiment in October 2003. The CPL has known layer identification and optical retrieval performance. GLAS data products, including calibrated attenuated backscatter profiles, layer identification, and optical depth, are compared to simultaneous aircraft lidar retrievals with similar model assumptions with a goal toward discovering algorithm biases in GLAS. The case described here involves heavy smoke layers from large-scale fires in southern California and thin cirrus clouds. The GLAS optical retrievals agree with the CPL data when the GLAS aerosol lidar ratio, S, is reset from default maritime to smoke and in inland urban pollution localities.

The Geoscience Laser Altimeter System (GLAS) launched in 2003 has provided the first global aerosol profiling from space. GLAS is a two wavelength nadir viewing instrument. The measurement requirement to profile all radiatively significant aerosol layers has been exceeded. Data processing algorithms have provided aerosol scattering cross section profiles, boundary detection and height for all aerosol layers, aerosol optical depth and extinction cross section for data from 2003. The data products are openly available to the global science community.

The first polar orbiting satellite lidar instrument, the Geoscience Laser Altimeter System (GLAS), was launched in 2003 and is approaching six months of data operations. As part of the NASA Earth Observing System (EOS) project, the GLAS instrument is intended as a laser sensor fulfilling complementary requirements for several Earth science disciplines including atmospheric and surface applications on the Ice, Cloud and Land Elevation Satellite. In this paper we present examples of atmospheric measurement results and explain data products now accessible for the science community

The Geoscience Laser Altimeter System launched in early 2003 is the first satellite instrument in space to globally observe the distribution of clouds and aerosol through laser remote sensing. The instrument is a basic backscatter lidar that operates at two wavelengths, 532 and 1064 nm. The mission data products for atmospheric observations include the calibrated, observed, attenuated backscatter cross section for cloud and aerosol; height detection for multiple cloud layers; planetary boundary layer height; cirrus and aerosol optical depth and the height distribution of aerosol and cloud scattering cross section profiles. The data is expected to significantly enhance knowledge in several areas of atmospheric science, in particular the distribution, transport and influence of atmospheric aerosol. Measurements of the coverage and height of polar and cirrus cloud should be significantly more accurate than previous global measurement. Initial result from the first several months of operation will be presented.

[1] Smoke and pollutants from Canadian forest fires are sometimes transported over the United States at low altitudes behind advancing cold fronts. An unusual event occurred in July 2002 in which smoke from fires in Quebec was observed by satellite, lidar, and aircraft to arrive over the Washington, D.C., area at high altitudes. This elevated smoke plume subsequently mixed to the surface as it was entrained into the turbulent planetary boundary layer and had adverse effects on the surface air quality over the region. Trajectory and three-dimensional model calculations confirmed the origin of the smoke, its transport at high altitudes, and the mechanism for bringing the pollutants to the surface. Additionally, the modeled smoke optical properties agreed well with aircraft and remote sensing observations provided the smoke particles were allowed to age by coagulation in the model. These results have important implications for the long-range transport of pollutants and their subsequent entrainment to the surface, as well as the evolving optical properties of smoke from boreal forest fires.

A new era in atmospheric remote sensing is about to begin. Global monitoring of clouds and aerosols from space using a backscatter lidar system will greatly add to our knowledge in areas such as polar cloud climatology, aerosol loading and transport, and the planetary boundary layer. The Geoscience Laser Altimeter System (GLAS) will produce nearly 5 GB of data per day. A challenge is to create autonomous algorithms that will analyze the data in near-real time. This paper briefly discusses the algorithms and presents results of testing with simulated GLAS data sets.

Relatively little is known about polar cloud radiative properties. The region as a whole represents one of the few remaining global frontiers in atmospheric research.