Cloud temperature measurement using rotational Raman lidar

Jia, Suotang; McCormick, M. P.; Wu, Yonghua; Lee, Robert B.; Lei, Liqiao; Liu, Zhaoyan; Leavor, Kevin

doi:10.1016/j.jqsrt.2013.04.007

Cited by 30 publications

(19 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…CLN is comprised of lidar facilities at mainly 4 sites (campuses) supported by the NOAA CREST Center (see Fig.1 [5,6,7]. The high pulse powers allow the observation and quantification of multi-layer plumes; and the multiwavelength capacity enables us to classify aloft aerosol type (smoke or dust).…”

Section: Lidar System and Methodologymentioning

confidence: 99%

New Results from the NOAA CREST Lidar Network (CLN) Observations in the US Eastcoast

Moshary

Han

et al. 2016

EPJ Web of Conferences

Self Cite

View full text Add to dashboard Cite

This paper presents coordinated ground-based observations by the NOAA-CREST Lidar Network (CLN) for profiling of aerosols, cloud, water vapor, and wind along the US east coast including Caribbean region at Puerto Rico. The instrumentation, methodology and observation capability are reviewed. The applications to continental and intercontinental-scale transport of smoke and dust plumes, and their large scale regional impact are discussed.

show abstract

Section: Lidar System and Methodologymentioning

confidence: 99%

New Results from the NOAA CREST Lidar Network (CLN) Observations in the US Eastcoast

Moshary

Han

et al. 2016

EPJ Web of Conferences

Self Cite

View full text Add to dashboard Cite

show abstract

“…In order to avoid these drawbacks, in recent field deployments the second cascading filter was removed from the Lo-J channel, and we were fully aware that this would have determined an overall lower blocking at 354.7 nm for the Lo-J interference filter and a consequent crosstalk of the 354.7 nm elastic lidar signal into the Lo-J rotational Raman signal. However, we were also fully aware of the different research efforts and corresponding literature papers dedicated to the definition of approaches to identify and remove elastic signal leakages from the rotational Raman signals (Behrendt et al, 2002;Su et al, 2013). These authors demonstrated that elastic signal crosstalk into the Lo-J rotational Raman signals can be completely removed if simultaneous and co-located measurements of the elastic signal are available.…”

Section: Elastic Signal Crosstalk Into the Rotational Raman Signals Amentioning

confidence: 99%

“…These authors demonstrated that elastic signal crosstalk into the Lo-J rotational Raman signals can be completely removed if simultaneous and co-located measurements of the elastic signal are available. Behrendt et al (2002) tested their approach on a rotational Raman lidar operating at 532 nm, while Su et al (2013) applied their approach to a rotational Raman lidar operating at 354.7 nm. At 354.7 nm, the approach considers the following equation: with P leak LoJ (z) being the leaked Lo-J rotational Raman lidar signal, P LoJ (z) being the effective Lo-J rotational Raman lidar signal used for the derivation of temperature profiles, P 354.7 (z) being the 354.7 nm elastic lidar signal, T F being the transmission of neutral density filters (used to attenuate the elastic signals and avoid signal induced noise effects associated with the low range echoes), and k being the crosstalk factor.…”

Section: Elastic Signal Crosstalk Into the Rotational Raman Signals Amentioning

confidence: 99%

Characterisation of boundary layer turbulent processes by the Raman lidar BASIL in the frame of HD(CP)<sup>2</sup> Observational Prototype Experiment

et al. 2017

View full text Add to dashboard Cite

Abstract. Measurements carried out by the University of Basilicata Raman lidar system (BASIL) are reported to demonstrate the capability of this instrument to characterise turbulent processes within the convective boundary layer (CBL). In order to resolve the vertical profiles of turbulent variables, high-resolution water vapour and temperature measurements, with a temporal resolution of 10 s and vertical resolutions of 90 and 30 m, respectively, are considered. Measurements of higher-order moments of the turbulent fluctuations of water vapour mixing ratio and temperature are obtained based on the application of autocovariance analyses to the water vapour mixing ratio and temperature time series. The algorithms are applied to a case study (11:30-13:30 UTC, 20 April 2013) from the High Definition Clouds and Precipitation for Climate Prediction (HD(CP) 2 ) Observational Prototype Experiment (HOPE), held in western Germany in the spring 2013. A new correction scheme for the removal of the elastic signal crosstalk into the low quantum number rotational Raman signal is applied. The noise errors are small enough to derive up to fourth-order moments for both water vapour mixing ratio and temperature fluctuations.To the best of our knowledge, BASIL is the first Raman lidar with a demonstrated capability to simultaneously retrieve daytime profiles of water vapour turbulent fluctuations up to the fourth order throughout the atmospheric CBL. This is combined with the capability of measuring daytime profiles of temperature fluctuations up to the fourth order. These measurements, in combination with measurements from other lidar and in situ systems, are important for verifying and possibly improving turbulence and convection parameterisation in weather and climate models at different scales down to the grey zone (grid increment ∼ 1 km; .For the considered case study, which represents a wellmixed and quasi-stationary CBL, the mean boundary layer height is found to be 1290 ± 75 m above ground level (a.g.l.). Values of the integral scale for water vapour and temperature fluctuations at the top of the CBL are in the range of 70-125 and 75-225 s, respectively; these values are much larger than the temporal resolution of the measurements (10 s), which testifies that the temporal resolution considered for the measurements is sufficiently high to resolve turbulent processes down to the inertial subrange and, consequently, to resolve the major part of the turbulent fluctuations. Peak values of all moments are found in the interfacial layer in the proximity of the top of the CBL. Specifically, water vapour and temperature second-order moments ( confidence in the possibility of using these measurements for turbulence parameterisation in weather and climate models.In the determination of the temperature profiles, particular care was dedicated to minimise potential effects associated with elastic signal crosstalk on the rotational Raman signals. For this purpose, a specific algorithm was defined and tested to identify and remove the ela...

show abstract

“…NASA's Goddard Space Flight Center (Di Girolamo et al, 2004), of the University of Hohenheim (UHOH; Radlach et al, 2008), of the University of Basilicata (Di Girolamo et al, 2009), of Xi'an University (Mao et al, 2009), and of Hampton University (Su et al, 2013) all operate in the UV with interference-filter polychromators. Rotational Raman lidars at 532 nm show lower performance during daytime but reach a larger range at night than an UV system due to the higher laser power available at 532 nm compared to 355 nm, higher efficiency in signal separation, and lower atmospheric extinction.…”

Section: E Hammann Et Al: Temperature Profiling With Rotational Rammentioning

confidence: 99%

Temperature profiling of the atmospheric boundary layer with rotational Raman lidar during the HD(CP)<sup>2</sup> Observational Prototype Experiment

et al. 2015

View full text Add to dashboard Cite

Abstract. The temperature measurements of the rotational Raman lidar of the University of Hohenheim (UHOH RRL) during the High Definition of Clouds and Precipitation for advancing Climate Prediction (HD(CP) 2 ) Observation Prototype Experiment (HOPE) in April and May 2013 are discussed. The lidar consists of a frequency-tripled Nd:YAG laser at 355 nm with 10 W average power at 50 Hz, a twomirror scanner, a 40 cm receiving telescope, and a highly efficient polychromator with cascading interference filters for separating four signals: the elastic backscatter signal, two rotational Raman signals with different temperature dependence, and the vibrational Raman signal of water vapor. The main measurement variable of the UHOH RRL is temperature. For the HOPE campaign, the lidar receiver was optimized for high and low background levels, with a novel switch for the passband of the second rotational Raman channel. The instrument delivers atmospheric profiles of water vapor mixing ratio as well as particle backscatter coefficient and particle extinction coefficient as further products. As examples for the measurement performance, measurements of the temperature gradient and water vapor mixing ratio revealing the development of the atmospheric boundary layer within 25 h are presented. As expected from simulations, a reduction of the measurement uncertainty of 70 % during nighttime was achieved with the new low-background setting. A two-mirror scanner allows for measurements in different directions. When pointing the scanner to low elevation, measurements close to the ground become possible which are otherwise impossible due to the non-total overlap of laser beam and receiving telescope field of view in the near range.An example of a low-level temperature measurement is presented which resolves the temperature gradient at the top of the stable nighttime boundary layer 100 m above the ground.

show abstract

Cloud temperature measurement using rotational Raman lidar

Cited by 30 publications

References 19 publications

New Results from the NOAA CREST Lidar Network (CLN) Observations in the US Eastcoast

New Results from the NOAA CREST Lidar Network (CLN) Observations in the US Eastcoast

Characterisation of boundary layer turbulent processes by the Raman lidar BASIL in the frame of HD(CP)<sup>2</sup> Observational Prototype Experiment

Temperature profiling of the atmospheric boundary layer with rotational Raman lidar during the HD(CP)<sup>2</sup> Observational Prototype Experiment

Contact Info

Product

Resources

About

Cloud temperature measurement using rotational Raman lidar

Cited by 30 publications

References 19 publications

New Results from the NOAA CREST Lidar Network (CLN) Observations in the US Eastcoast

New Results from the NOAA CREST Lidar Network (CLN) Observations in the US Eastcoast

Characterisation of boundary layer turbulent processes by the Raman lidar BASIL in the frame of HD(CP)&lt;sup&gt;2&lt;/sup&gt; Observational Prototype Experiment

Temperature profiling of the atmospheric boundary layer with rotational Raman lidar during the HD(CP)&lt;sup&gt;2&lt;/sup&gt; Observational Prototype Experiment

Contact Info

Product

Resources

About

Characterisation of boundary layer turbulent processes by the Raman lidar BASIL in the frame of HD(CP)<sup>2</sup> Observational Prototype Experiment

Temperature profiling of the atmospheric boundary layer with rotational Raman lidar during the HD(CP)<sup>2</sup> Observational Prototype Experiment