Spatiotemporal Path-Matching for Comparisons Between Ground- Based and Satellite Lidar Measurements

The spatiotemporal sampling differences between ground-based and satellite lidar data can contribute to significant errors for direct measurement comparisons. Improvement in sample correspondence is examined by the use of radiosonde wind velocity to vary the time average in ground-based lidar data to spatially match coincident satellite lidar measurements. Results are shown for the 26 February 2004 GLAS/ICESat overflight of a ground-based lidar stationed at NASA GSFC. Statistical analysis indicates that improvement in signal correlation is expected under certain conditions, even when a ground-based observation is mismatched in directional orientation to the satellite track

Arctic experiment for ICESat/GLAS ground validation with a Micro-Pulse Lidar at Ny-Alesund, Svalbard

A Micro-Pulse Lidar (MPL) has been operated in Ny-Alesund, Svalbard (78°55\u27N, 11°56\u27E, 0.010 km msl) to collect zenith scattering profiles of aerosols and clouds since 1998. The Ice, Cloud, and land Elevation Satellite (ICESat) was launched by NASA in January 2003 with a single payload instrument, the Geoscience Laser Altimeter System (GLAS), designed for active remote sensing of the atmosphere as well as ice sheet height change in the cryosphere. Overpass experiments for ground validation of the ICESat/GLAS atmospheric measurements were performed in 2003 and 2004. Two case-studies comparing lidar measurements from space-borne GLAS and ground-based MPL in the Arctic are described here for a geometrically thick but optically thin cloud and a geometrically thin but optically thick cloud. The result validates the basic procedure for cloud signal processing and attenuation correction of the GLAS data

Effects of local meteorology and aerosols on ozone and nitrogen dioxide retrievals from OMI and pandora spectrometers in Maryland, USA during DISCOVER-AQ 2011

An analysis is presented for both ground- and satellite-based retrievals of total column ozone and nitrogen dioxide levels from the Washington, D.C., and Baltimore, Maryland, metropolitan area during the NASA-sponsored July 2011 campaign of Deriving Information on Surface COnditions from Column and VERtically Resolved Observations Relevant to Air Quality (DISCOVER-AQ). Satellite retrievals of total column ozone and nitrogen dioxide from the Ozone Monitoring Instrument (OMI) on the Aura satellite are used, while Pandora spectrometers provide total column ozone and nitrogen dioxide amounts from the ground. We found that OMI and Pandora agree well (residuals within ±25 % for nitrogen dioxide, and ±4.5 % for ozone) for a majority of coincident observations during July 2011. Comparisons with surface nitrogen dioxide from a Teledyne API 200 EU NOx Analyzer showed nitrogen dioxide diurnal variability that was consistent with measurements by Pandora. However, the wide OMI field of view, clouds, and aerosols affected retrievals on certain days, resulting in differences between Pandora and OMI of up to ±65 % for total column nitrogen dioxide, and ±23 % for total column ozone. As expected, significant cloud cover (cloud fraction \u3e0.2) was the most important parameter affecting comparisons of ozone retrievals; however, small, passing cumulus clouds that do not coincide with a high (\u3e0.2) cloud fraction, or low aerosol layers which cause significant backscatter near the ground affected the comparisons of total column nitrogen dioxide retrievals. Our results will impact post-processing satellite retrieval algorithms and quality control procedures

Evaluations of Thin Cirrus Contamination and Screening in Ground Aerosol Observations Using Collocated Lidar Systems

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

Stratospheric AOD after the 2011 eruption of Nabro volcano measured by lidars over the Northern Hemisphere

International audienceNabro volcano (13.37°N, 41.70°E) in Eritrea erupted on 13 June 2011 generating a layer of sulfate aerosols that persisted in the stratosphere for months. For the first time we report on ground-based lidar observations of the same event from every continent in the Northern Hemisphere, taking advantage of the synergy between global lidar networks such as EARLINET, MPLNET and NDACC with independent lidar groups and satellite CALIPSO to track the evolution of the stratospheric aerosol layer in various parts of the globe. The globally averaged aerosol optical depth (AOD) due to the stratospheric volcanic aerosol layers was of the order of 0.018 ± 0.009 at 532 nm, ranging from 0.003 to 0.04. Compared to the total column AOD from the available collocated AERONET stations, the stratospheric contribution varied from 2% to 23% at 532 nm

Quantifying TOLNet Ozone Lidar Accuracy During the 2014 DISCOVER-AQ and FRAPP Campaigns

The Tropospheric Ozone Lidar Network (TOLNet) is a unique network of lidar systems that measure high-resolution atmospheric profiles of ozone. The accurate characterization of these lidars is necessary to determine the uniformity of the network calibration. From July to August 2014, three lidars, the TROPospheric OZone (TROPOZ) lidar, the Tunable Optical Profiler for Aerosol and oZone (TOPAZ) lidar, and the Langley Mobile Ozone Lidar (LMOL), of TOLNet participated in the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission and the Front Range Air Pollution and Photochemistry xperiment (FRAPP) to measure ozone variations from the boundary layer to the top of the troposphere. This study presents the analysis of the intercomparison between the TROPOZ, TOPAZ, and LMOL lidars, along with comparisons between the lidars and other in situ ozone instruments including ozonesondes and a P-3B airborne chemiluminescence sensor. The TOLNet lidars measured vertical ozone structures with an accuracy generally better than 15 % within the troposphere. Larger differences occur at some individual altitudes in both the near-field and far-field range of the lidar systems, largely as expected. In terms of column average, the TOLNet lidars measured ozone with an accuracy better than 5 % for both the intercomparison between the lidars and between the lidars and other instruments. These results indicate that these three TOLNet lidars are suitable for use in air quality, satellite validation, and ozone modeling efforts

2005), Spatiotemporal path-matching for comparisons between ground-based and satellite lidar measurements

ABSTRACT: The spatiotemporal sampling differences between ground-based and satellite lidar data can contribute to significant errors for direct measurement comparisons. Improvement in sample correspondence is examined by the use of radiosonde wind velocity to vary the time average in ground-based lidar data to spatially match coincident satellite lidar measurements. Results are shown for the 26 February 2004 GLAS/ICESat overflight of a ground-based lidar stationed at NASA GSFC. Statistical analysis indicates that improvement in signal correlation is expected under certain conditions, even when a ground-based observation is mismatched in directional orientation to the satellite track. Key words: Lidar, Aerosols, Clouds, Satellite, Measurements. RESUMEN: Las diferencias espacio-temporales en el muestreo de datos de lidars de superficie terrestres y satelitales pueden contribuir a errores significativos en las comparaciones directas de las mediciones. El mejoramiento en la correlación del muestreo es examinado con el uso de la velocidad del viento, obtenida por medio de radiosondas, con el objetivo de variar el promedio en tiempo de las mediciones de lidares de superficie para correlacionar espacialmente las mediciones coincidentes de lidares satelitales. En este artículo se mostrarán los resultados del sobrevuelo del lidar GLAS en el satélite ICESat sobre un lidar de superficie ubicado en NASA GSFC el 26 de Febrero de 2004. Un análisis estadístico indica que se espera un mejoramiento en la correlación de la señal bajo ciertas circunstancias, incluso cuando las trayectorias del viento y el satélite no coinciden en orientación

An Optical Water Vapor Sensor for Unmanned Aerial Vehicles

The water vapor sensor developed by Aerodyne Research, based on the optical absorption of light at {approximately}935 nm, has been successfully demonstrated on board the Pacific Northwest National Laboratory's Gulfstream-1 research aircraft during the Department of Energy's ARM Intensive Operations Period in August 1998. Data taken during this field campaign show excellent agreement with a chilled mirror and Lyman-alpha hygrometers and measurements confirm the ability to measure rapid, absolute water vapor fluctuations with a high degree of instrument stability and accuracy, with a noise level as low 10 ppmv (1 Hz measurement bandwidth). The construction of this small, lightweight sensor contains several unique elements which result in several significant advantages when compared to other techniques. First, the low power consumption Argon discharge lamp provides an optical beam at a fixed wavelength without a need for temperature or precision current control. The multi-pass absorption cell developed for this instrument provides a compact, low cost method that can survive deployment in the field. Fiber-optic cables, which are used to convey to light between the absorption cell, light source, and detection modules enable remote placement of the absorption cell from the opto-electronics module. Finally, the sensor does not use any moving parts which removes a significant source of potential malfunction. The result is an instrument which maintained its calibration throughout the field measurement campaign, and was not affected by high vibration and large uncontrolled temperature excursions. We believe that the development of an accurate, fast response water vapor monitor described in this report will open up new avenues of aerial-vehicle-based atmospheric research which have been relatively unexplored due to the lack of suitable low-cost, light-weight instrumentation

Variation of Ozone and PBL from the Lidar Observations and WRF-Chem Model in NYC Area During the 2018 Summer LISTOS Campaign

High ozone (O3) episodes frequently occur in New York metropolitan and the downwind coastal area in summer. In this study, lidar/ceilometer are combined with WRF/Chem model to investigate an O3 event on Aug. 27~30 2018. We examine the spatial-temporal variabilities of O3 and planetary-boundary-layer height (PBLH) and assess the model performance on simulating surface O3 during this episode. By comparing with the lidar observations, the WRF/Chem is able to capture high O3 distribution in the PBL at noon and indicates consistent diurnal evolution for the ground O3. Nevertheless, in the early morning and night, the model overestimates the ground O3 and underestimates the PBLH