Review of Beyond Craig and Gordon: A model of water vapor isotopologues in the marine boundary layer

2018 ◽  
Author(s):  
Anonymous
2021 ◽  
Author(s):  
Bjorn Stevens ◽  
Ilya Serikov ◽  
Anna Lea Albright ◽  
Sandrine Bony ◽  
Geet George ◽  
...  

<p>Cloud free skies are rare in the trades.  We analyze conditions in which cloud-free conditions prevail.  For this purpose Raman water vapor measurements from the Barbados Cloud Observatory, complemented by ship-based measurements during EUREC4A are used to explore water vapor variability in the marine boundary layer.   We explore the consistency of the inferred cloud base height with estimates of temperature and water vapor from the lidar signal, and examine the co-variability of these quantities.  After having established the properties of these measurements, we seek to use them as well as others, to explain in what ways periods of cloud-free conditions are maintained, investigating the hypothesis that only when the wind stills is it simply sunny.</p>


2018 ◽  
Vol 45 (5) ◽  
pp. 2524-2532 ◽  
Author(s):  
M. Benetti ◽  
J.‐L. Lacour ◽  
A. E. Sveinbjörnsdóttir ◽  
G. Aloisi ◽  
G. Reverdin ◽  
...  

2021 ◽  
Author(s):  
Stephen Leroy ◽  
Igor Polonsky ◽  
Alexandra Meredith ◽  
Kerri Cahoy ◽  
Lucy Halperin ◽  
...  

2001 ◽  
Author(s):  
Shiv K. Sharma ◽  
Barry R. Lienert ◽  
John N. Porter ◽  
Antony D. Clarke

2016 ◽  
Vol 55 (1) ◽  
pp. 213-225 ◽  
Author(s):  
Luis Millán ◽  
M. Lebsock ◽  
E. Fishbein ◽  
P. Kalmus ◽  
J. Teixeira

AbstractThis study investigates the synergy of collocated microwave radiometry and near-infrared imagery to estimate the marine boundary layer water vapor beneath uniform cloud fields. Microwave radiometry provides the total column water vapor, while the near-infrared imagery provides the water vapor above the cloud layers. The difference between the two gives the vapor between the surface and the cloud top, which may be interpreted as the boundary layer water vapor. In combining the two datasets, we apply several flags as well as proximity tests to remove pixels with high clouds and/or intrapixel heterogeneity. Comparisons against radiosonde and ECMWF reanalysis data demonstrate the robustness of these boundary layer water vapor estimates. Last, it is shown that the measured AMSR-MODIS boundary layer water vapor can be analyzed using sea surface temperature and cloud-top pressure information by employing simple equations based on the Clausius–Clapeyron relationship.


1997 ◽  
Author(s):  
Shiv K. Sharma ◽  
Antony D. Clarke ◽  
John N. Porter ◽  
Barry R. Lienert

2021 ◽  
Author(s):  
Dean Henze ◽  
David Noone ◽  
Darin Toohey

Abstract. This paper presents the water vapor heavy isotope ratio measurement system developed for aircraft in-situ measurements and used in the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) project. The resultant dataset collected, which includes measurements of specific humidity and the heavy isotope ratios D / H and 18O / 16O, is also presented. Aircraft sampling took place in the southeast Atlantic marine boundary layer and lower troposphere (equator to 22° S) over the months of Sept. 2016, Aug. 2017, and Oct. 2018. Isotope measurements were made using cavity ring-down spectroscopic analyzers integrated into the Water Isotope System for Precipitation and Entrainment Research (WISPER). The water concentration and isotopic data accompanied a suite of other variables including standard meteorological quantities (wind, temperature, moisture), trace gas and aerosol concentrations, radar, and lidar remote sensing. From an isotope perspective, the 300+ hours of 1 Hz in-situ data at levels in the atmosphere ranging from 70 m to 6 km represents a remarkably large and vertically resolved dataset. This paper provides a brief overview of the ORACLES mission and describes how water vapor heavy isotope ratios fit within the experimental design. Overviews of the sampling region and WISPER system setup are presented, along with calibration details, measurement uncertainties, and suggested data usage. Characteristics in the spatial variability of the study region over the three sampling periods are highlighted with latitude-altitude curtains. A number of individual tropospheric profiles are presented to illustrate the fidelity with which a series of different hydrologic processes are captured by the observations. The curtains and profiles demonstrate the dataset’s potential to provide a comprehensive perspective on moisture transport and isotopic content in this region. Readers interested in a quick reference to data usage and uncertainty estimation can consult the beginning of section 5. Data for the Sept. 2016, Aug. 2017, and Oct. 2018 sampling periods can be accessed at https://doi.org/10.5067/Suborbital/ORACLES/P3/2016_V2, https://doi.org/10.5067/Suborbital/ORACLES/P3/2017_V2, and https://doi.org/10.5067/Suborbital/ORACLES/P3/2018_V2, respectively (see references for ORACLES Science Team, 2020 – 2016 P3 data, 2017 P3 data, and 2018 P3 data). 


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