_version_ 1867170076130541568
author Bojanowski, Jedrzej S
Stöckli, Reto
author_facet Bojanowski, Jedrzej S
Stöckli, Reto
collection Datos científicos de ciencias marinas y ambientales
contents Automated high-temporal resolution cloud cover measurements can contribute to the weak understanding of the net radiative cloud effect and its evolution with climate change. They can further serve as a reference for satellite-based cloud retrievals. A dataset of 10-minute cloud amount estimates at 24 sites of the Baseline Surface Radiation Network is presented. These sites are located worldwide covering a wide range of climatic zones. The length of cloud amount time series vary among sites from 3 to 22 years (until 2014). Cloud amount was calculated from ground measurements of long-wave incoming radiation, air temperature and relative humidity by means of the Bayesian Automatic Cloud Detection Algorithm (BACADA), which builds on the Automatic Partial Cloud Amount Detection Algorithm (APCADA, Dürr and Philipona, JGR, 2004). Evaluation of cloud fraction (0-100%) was carried out based on comparison with synoptic and total-sky imager cloud observations. It is demonstrated that BACADA improves the performance of partial cloud amount estimates (MBE=1.55%, MAE=15.35%) as compared to the existing APCADA algorithm (MBE=7.18%, MAE=17.89%). Yet, the aim of BACADA is to provide total cloud amount. These estimates are of MBE=-1.53% and MAE=17.86%. Although the study focuses on the need of cloud amount estimates for evaluation of satellite-based retrievals, the dataset demonstrated here may potentially be valuable for other disciplines.
format Dataset Open Access
id pangaea_https___doi_org_10_1594_PANGAEA_876005
institution PANGAEA
language en
publishDate 2017
publisher PANGAEA
record_format pangaea
spellingShingle 10-minute resolution BACADA-derived cloud amount estimates at the Baseline Surface Radiation Network (1994-2014), link to NetCDF files
Bojanowski, Jedrzej S
Stöckli, Reto
Antarctica; Australia; AWIPEV; AWIPEV_based; BER; Bermuda; BOU; Boulder; Brasilia; Brasilia City, Distrito Federal, Brazil; Brazil; BRB; CAB; Cabauw; Canada; CAR; Carpentras; Cener; CNR; Colorado, United States of America; DAA; DAR; Darwin; De Aar; Dronning Maud Land, Antarctica; E13; Elevation of event; Event label; File format; File name; File size; France; Georg von Neumayer; Germany; GOB; Gobabeb; GVN; Israel; IZA; Izaña; KWA; Kwajalein; Latitude of event; LIN; Lindenberg; Longitude of event; MAN; Momote; Monitoring station; MONS; Namib Desert, Namibia; NAU; Nauru; Nauru Island; Neumayer_based; NEUMAYER III; North Pacific Ocean; NYA; Ny-Ålesund; Ny-Ålesund, Spitsbergen; Oklahoma, United States of America; PAL; Palaiseau, SIRTA Observatory; Papua New Guinea; PAY; Payerne; Petrolina; PTR; REG; Regina; Saudi Arabia; SBO; Sede Boqer; Solar Village; South Africa; Southern Great Plains; South Pole; SOV; Spain, Sarriguren, Navarra; SPO; Switzerland; Tenerife, Spain; The Netherlands; Uniform resource locator/link to file
Automated high-temporal resolution cloud cover measurements can contribute to the weak understanding of the net radiative cloud effect and its evolution with climate change. They can further serve as a reference for satellite-based cloud retrievals. A dataset of 10-minute cloud amount estimates at 24 sites of the Baseline Surface Radiation Network is presented. These sites are located worldwide covering a wide range of climatic zones. The length of cloud amount time series vary among sites from 3 to 22 years (until 2014). Cloud amount was calculated from ground measurements of long-wave incoming radiation, air temperature and relative humidity by means of the Bayesian Automatic Cloud Detection Algorithm (BACADA), which builds on the Automatic Partial Cloud Amount Detection Algorithm (APCADA, Dürr and Philipona, JGR, 2004). Evaluation of cloud fraction (0-100%) was carried out based on comparison with synoptic and total-sky imager cloud observations. It is demonstrated that BACADA improves the performance of partial cloud amount estimates (MBE=1.55%, MAE=15.35%) as compared to the existing APCADA algorithm (MBE=7.18%, MAE=17.89%). Yet, the aim of BACADA is to provide total cloud amount. These estimates are of MBE=-1.53% and MAE=17.86%. Although the study focuses on the need of cloud amount estimates for evaluation of satellite-based retrievals, the dataset demonstrated here may potentially be valuable for other disciplines.
title 10-minute resolution BACADA-derived cloud amount estimates at the Baseline Surface Radiation Network (1994-2014), link to NetCDF files
topic Antarctica; Australia; AWIPEV; AWIPEV_based; BER; Bermuda; BOU; Boulder; Brasilia; Brasilia City, Distrito Federal, Brazil; Brazil; BRB; CAB; Cabauw; Canada; CAR; Carpentras; Cener; CNR; Colorado, United States of America; DAA; DAR; Darwin; De Aar; Dronning Maud Land, Antarctica; E13; Elevation of event; Event label; File format; File name; File size; France; Georg von Neumayer; Germany; GOB; Gobabeb; GVN; Israel; IZA; Izaña; KWA; Kwajalein; Latitude of event; LIN; Lindenberg; Longitude of event; MAN; Momote; Monitoring station; MONS; Namib Desert, Namibia; NAU; Nauru; Nauru Island; Neumayer_based; NEUMAYER III; North Pacific Ocean; NYA; Ny-Ålesund; Ny-Ålesund, Spitsbergen; Oklahoma, United States of America; PAL; Palaiseau, SIRTA Observatory; Papua New Guinea; PAY; Payerne; Petrolina; PTR; REG; Regina; Saudi Arabia; SBO; Sede Boqer; Solar Village; South Africa; Southern Great Plains; South Pole; SOV; Spain, Sarriguren, Navarra; SPO; Switzerland; Tenerife, Spain; The Netherlands; Uniform resource locator/link to file
url https://doi.org/10.1594/PANGAEA.876005