scholarly journals Estimating Geo‐Referenced Cloud‐Base Height with Whole‐Sky Imagers

2021 ◽  
Author(s):  
Baolei Lyu ◽  
Yang Chen ◽  
Yuqiu Guan ◽  
Tianlei Gao ◽  
Jun Liu
Keyword(s):  
Cloud Base ◽  
Cloud Base Height

A 42 year inference of cloud base height trends in the Luquillo Mountains of northeastern Puerto Rico

2018 ◽  
Vol 76 (1) ◽  
pp. 87-94 ◽  
Author(s):  
PW Miller ◽  
TL Mote ◽  
CA Ramseyer ◽  
AE Van Beusekom ◽  
M Scholl ◽  
...  
Keyword(s):  
Puerto Rico ◽  
Cloud Base ◽  
Luquillo Mountains ◽  
Cloud Base Height

Why sometimes its simply sunny (in the trades)

2021 ◽  
Author(s):  
Bjorn Stevens ◽  
Ilya Serikov ◽  
Anna Lea Albright ◽  
Sandrine Bony ◽  
Geet George ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Water Vapor ◽  
Marine Boundary Layer ◽  
Cloud Base ◽  
Lidar Signal ◽  
Cloud Base Height

<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>

A Validation of CloudSat and CALIPSO's Temperature, Humidity, Cloud Detection, and Cloud Base Height over the Arctic Marine Cryosphere

2013 ◽  
Vol 51 (3) ◽  
pp. 249-264 ◽  
Author(s):  
Lauren M. Candlish ◽  
Richard L. Raddatz ◽  
Geoffrey G. Gunn ◽  
Matthew G. Asplin ◽  
David G. Barber
Keyword(s):  
The Arctic ◽  
Cloud Base ◽  
Cloud Detection ◽  
Cloud Base Height

scholarly journals Characterisation and surface radiative impact of Arctic low clouds from the IAOOS field experiment

2021 ◽  
Vol 21 (5) ◽  
pp. 4079-4101
Author(s):  
Julia Maillard ◽  
François Ravetta ◽  
Jean-Christophe Raut ◽  
Vincent Mariage ◽  
Jacques Pelon
Keyword(s):  
Field Experiment ◽  
Cloud Cover ◽  
Great Majority ◽  
Cloud Base ◽  
The North ◽  
Low Clouds ◽  
Radiative Impact ◽  
Low Cloud ◽  
Ocean Observing ◽  
Cloud Base Height

Abstract. The Ice, Atmosphere, Arctic Ocean Observing System (IAOOS) field experiment took place from 2014 to 2019. Over this period, more than 20 instrumented buoys were deployed at the North Pole. Once locked into the ice, the buoys drifted for periods of a month to more than a year. Some of these buoys were equipped with 808 nm wavelength lidars which acquired a total of 1777 profiles over the course of the campaign. This IAOOS lidar dataset is exploited to establish a novel statistic of cloud cover and of the geometrical and optical characteristics of the lowest cloud layer. The average cloud frequency from April to December over the course of the campaign was 75 %. Cloud occurrence frequencies were above 85 % from May to October. Single layers are thickest in October/November and thinnest in the summer. Meanwhile, their optical depth is maximum in October. On the whole, the cloud base height is very low, with the great majority of first layer bases beneath 120 m. In April and October, surface temperatures are markedly warmer when the IAOOS profile contains at least one low cloud than when it does not. This temperature difference is statistically insignificant in the summer months. Indeed, summer clouds have a shortwave cooling effect which can reach −60 W m−2 and balance out their longwave warming effect.

scholarly journals A new classification of satellite derived liquid water cloud regimes at cloud scale

2019 ◽  
Author(s):  
Claudia Unglaub ◽  
Karoline Block ◽  
Johannes Mülmenstädt ◽  
Odran Sourdeval ◽  
Johannes Quaas
Keyword(s):  
Liquid Water ◽  
Smooth Transition ◽  
Cloud Base ◽  
Cloud Parameters ◽  
Stratiform Clouds ◽  
Inhomogeneity Parameter ◽  
Water Cloud ◽  
Cloud Regimes ◽  
Cloud Base Height

Abstract. Clouds are highly variable in time and space affecting climate sensitivity and climate change. To study and distinguish the different influences of clouds on the climate system it is useful to separate clouds into individual cloud regimes. In this work we present a new cloud classification for liquid water clouds at cloud scale defined using cloud parameters retrieved from combined satellite measurements from CloudSat and CALIPSO. The idea is that cloud heterogeneity is a measure that allows to distinguish cumuliform and stratiform clouds, and cloud base height a measure to distinguish cloud altitude. The approach makes use of a newly-developed cloud-base height retrieval. Using three cloud base height intervals and two intervals of cloud top variability as an inhomogeneity parameter provides six new liquid cloud classes. The results show a smooth transition between marine and continental clouds as well as between stratiform and cumuliform clouds in different latitudes at the high spatial resolution of about 20 km. Analyzing the micro- and macrophysical cloud parameters from collocated combined MODIS, CloudSat and CALIPSO retrievals shows distinct characteristics for each cloud regimes that are in agreement with expectation and literature. This demonstrates the usefulness of the classification.

Sign in / Sign up

Export Citation Format

Share Document