Recommendations for processing atmospheric attenuated backscatter profiles from Vaisala CL31 ceilometers

Kotthaus, Simone; O’Connor, Ewan; Münkel, Christoph; Charlton‐Perez, Cristina; Haeffelin, Martial; Gabey, A. M.; Grimmond, Sue

doi:10.5194/amt-9-3769-2016

Cited by 118 publications

(162 citation statements)

References 47 publications

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“…The CL31 ran with firmware v1.7 and noise_h2 on. For morein-depth information about the instrument see Münkel et al (2007) and Kotthaus et al (2016).…”

Section: Vaisala Cl31mentioning

confidence: 99%

Comparison of aerosol lidar retrieval methods for boundary layer height detection using ceilometer aerosol backscatter data

Caicedo

Rappenglück

Lefer³

et al. 2017

Atmos. Meas. Tech.

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Abstract. Three algorithms for estimating the boundary layer heights are assessed: an aerosol gradient method, a cluster analysis method, and a Haar wavelet method. Over 40 daytime clear-sky radiosonde profiles are used to compare aerosol backscatter boundary layer heights retrieved by a Vaisala CL31 ceilometer. Overall good agreement between radiosonde-and aerosol-derived boundary layer heights was found for all methods. The cluster method was found to be particularly sensitive to noise in ceilometer signals and lofted aerosol layers (48.8 % of comparisons), while the gradient method showed limitations in low-aerosol-backscatter conditions. The Haar wavelet method was demonstrated to be the most robust, only showing limitations in 22.5 % of all observations. Occasional differences between thermodynamically and aerosol-derived boundary layer heights were observed.

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“…The CL31 ran with firmware v1.7 and noise_h2 on. For morein-depth information about the instrument see Münkel et al (2007) and Kotthaus et al (2016).…”

Section: Vaisala Cl31mentioning

confidence: 99%

Comparison of aerosol lidar retrieval methods for boundary layer height detection using ceilometer aerosol backscatter data

Caicedo

Rappenglück

Lefer³

et al. 2017

Atmos. Meas. Tech.

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“…A Vaisala CL31 ceilometer operating at 905 nm provides the profile of (attenuated) light backscatter at 15 m vertical resolution (Kotthaus et al, 2016), from which the cloud-base height can be determined (see Sect. 3.1).…”

Section: Observational Site and Instrumentationmentioning

confidence: 99%

Radiation in fog: quantification of the impact on fog liquid water based on ground-based remote sensing

Wærsted¹,

Haeffelin

Dupont

et al. 2017

Atmos. Chem. Phys.

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Abstract. Radiative cooling and heating impact the liquid water balance of fog and therefore play an important role in determining their persistence or dissipation. We demonstrate that a quantitative analysis of the radiation-driven condensation and evaporation is possible in real time using groundbased remote sensing observations (cloud radar, ceilometer, microwave radiometer). Seven continental fog events in midlatitude winter are studied, and the radiative processes are further explored through sensitivity studies. The longwave (LW) radiative cooling of the fog is able to produce 40-70 g m −2 h −1 of liquid water by condensation when the fog liquid water path exceeds 30 g m −2 and there are no clouds above the fog, which corresponds to renewing the fog water in 0.5-2 h. The variability is related to fog temperature and atmospheric humidity, with warmer fog below a drier atmosphere producing more liquid water. The appearance of a cloud layer above the fog strongly reduces the LW cooling relative to a situation with no cloud above; the effect is strongest for a low cloud, when the reduction can reach 100 %. Consequently, the appearance of clouds above will perturb the liquid water balance in the fog and may therefore induce fog dissipation. Shortwave (SW) radiative heating by absorption by fog droplets is smaller than the LW cooling, but it can contribute significantly, inducing 10-15 g m −2 h −1 of evaporation in thick fog at (winter) midday. The absorption of SW radiation by unactivated aerosols inside the fog is likely less than 30 % of the SW absorption by the water droplets, in most cases. However, the aerosols may contribute more significantly if the air mass contains a high concentration of absorbing aerosols. The absorbed radiation at the surface can reach 40-120 W m −2 during the daytime depending on the fog thickness. As in situ measurements indicate that 20-40 % of this energy is transferred to the fog as sensible heat, this surface absorption can contribute significantly to heating and evaporation of the fog, up to 30 g m −2 h −1 for thin fog, even without correcting for the typical underestimation of turbulent heat fluxes by the eddy covariance method. Since the radiative processes depend mainly on the profiles of temperature, humidity and clouds, the results of this paper are not site specific and can be generalised to fog under different dynamic conditions and formation mechanisms, and the methodology should be applicable to warmer and moister climates as well. The retrieval of approximate emissivity of clouds above fog from cloud radar should be further developed.

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“…To estimate the impacts of ceilometer response changing on backscatter measurements, we compared 3 years (2007,2008,2009) of yearly average ceilometer backscatter profiles under nighttime clear conditions (PM2.5 < 15 µm, relative humidity < 40 %). The method is similar to the method used in Kotthaus et al (2016) to illustrate impacts of background signal and cosmetic shift on ceilometer-reported signals. The largest difference of the yearly average backscatter below 150 m among the 3 years is found within 10 % for the CT25k ceilometer.…”

Section: Datamentioning

confidence: 99%

“…It is worth noting that both the instrument hardware-related background signals and software-related artifacts could impact attenuated backscatter profiles observed by ceilometers. Further processing of attenuated backscatter profiles is needed to get accurate attenuated backscatter observations from ceilometers especially under low signal-to-noise ratio situations (Kotthaus et al, 2016). In this study, we only use the attenuated backscatter at low altitude, where both the Vaisala CT25k and CL31 have high signal-to-noise ratio for lidar return signals and hourly average will also decrease noise.…”

Section: Test In a Different Regionmentioning

confidence: 99%

“…It worth noting that the CT25k is an uncalibrated instrument of which the response may change in time. That change may induce differences in retrieving attenuated backscatter at different times, especially in retrieving backscatter at high altitude where the signal-to-noise ratio is small (Kotthaus et al, 2016). To estimate the impacts of ceilometer response changing on backscatter measurements, we compared 3 years (2007,2008,2009) of yearly average ceilometer backscatter profiles under nighttime clear conditions (PM2.5 < 15 µm, relative humidity < 40 %).…”

Section: Datamentioning

confidence: 99%

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Remote sensing of PM2.5 during cloudy and nighttime periods using ceilometer backscatter

Joseph

Min

et al. 2017

Atmos. Meas. Tech.

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Abstract. Monitoring PM2.5 (particulate matter with aerodynamic diameter d ≤ 2.5 µm) mass concentration has become of more importance recently because of the negative impacts of fine particles on human health. However, monitoring PM2.5 during cloudy and nighttime periods is difficult since nearly all the passive instruments used for aerosol remote sensing are not able to measure aerosol optical depth (AOD) under either cloudy or nighttime conditions. In this study, an empirical model based on the regression between PM2.5 and the near-surface backscatter measured by ceilometers was developed and tested using 6 years of data (2006 to 2011) from the Howard University Beltsville Campus (HUBC) site. The empirical model can explain ∼ 56, ∼ 34 and ∼ 42 % of the variability in the hourly average PM2.5 during daytime clear, daytime cloudy and nighttime periods, respectively. Meteorological conditions and seasons were found to influence the relationship between PM2.5 mass concentration and the surface backscatter. Overall the model can explain ∼ 48 % of the variability in the hourly average PM2.5 at the HUBC site when considering the seasonal variation. The model also was tested using 4 years of data (2012 to 2015) from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site, which was geographically and climatologically different from the HUBC site. The results show that the empirical model can explain ∼ 66 and ∼ 82 % of the variability in the daily average PM2.5 at the ARM SGP site and HUBC site, respectively. The findings of this study illustrate the strong need for ceilometer data in air quality monitoring under cloudy and nighttime conditions. Since ceilometers are used broadly over the world, they may provide an important supplemental source of information of aerosols to determine surface PM2.5 concentrations.

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Recommendations for processing atmospheric attenuated backscatter profiles from Vaisala CL31 ceilometers

Cited by 118 publications

References 47 publications

Comparison of aerosol lidar retrieval methods for boundary layer height detection using ceilometer aerosol backscatter data

Comparison of aerosol lidar retrieval methods for boundary layer height detection using ceilometer aerosol backscatter data

Radiation in fog: quantification of the impact on fog liquid water based on ground-based remote sensing

Remote sensing of PM2.5 during cloudy and nighttime periods using ceilometer backscatter

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