Transmittance index characterization at two solar measurement stations in Brazil
This paper constructs probability density distributions of direct normal, diffuse horizontal, and global horizontal irradiance for 1-min clearness indexes k b , k d , and k t , respectively. Previous studies on the clearness index, conditioned to the optical air mass, are analyzed and distributions...
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| Veröffentlicht in: | Theoretical and applied climatology 2020, Vol.139 (1-2), p.205-219 |
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| creator | Relva, Stefania Gomes Gimenes, André Luiz Veiga Udaeta, Miguel Edgar Morales Galvão, Luiz Cláudio Ribeiro |
| description | This paper constructs probability density distributions of direct normal, diffuse horizontal, and global horizontal irradiance for 1-min clearness indexes
k
b
,
k
d
, and
k
t
, respectively. Previous studies on the clearness index, conditioned to the optical air mass, are analyzed and distributions of these three indexes, using data from two solarimetric stations in Brazil, are presented. The pattern found in probability density distributions, in general, matches the patterns found in the literature. The 50th percentile (P50) of
k
b
values from Sao Paulo city (a location with high levels of pollution) is 0.22, and from the countryside region of the state of Sao Paulo (a location with expected low levels of pollution), it is 0.55. Regarding
k
t
values, P50 is 0.57 and 0.72 for these two regions, respectively. We conclude that different atmospheric conditions result in a different dependence relation between probability density distribution and air mass increases. These conditions include not only cloud formation, but also pollution levels and the influence of relative humidity. These specific results endorse the need for local radiation measurements to the characterization of few-minute average of transmittance indexes. |
| doi_str_mv | 10.1007/s00704-019-02941-6 |
| format | Article |
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k
b
,
k
d
, and
k
t
, respectively. Previous studies on the clearness index, conditioned to the optical air mass, are analyzed and distributions of these three indexes, using data from two solarimetric stations in Brazil, are presented. The pattern found in probability density distributions, in general, matches the patterns found in the literature. The 50th percentile (P50) of
k
b
values from Sao Paulo city (a location with high levels of pollution) is 0.22, and from the countryside region of the state of Sao Paulo (a location with expected low levels of pollution), it is 0.55. Regarding
k
t
values, P50 is 0.57 and 0.72 for these two regions, respectively. We conclude that different atmospheric conditions result in a different dependence relation between probability density distribution and air mass increases. These conditions include not only cloud formation, but also pollution levels and the influence of relative humidity. These specific results endorse the need for local radiation measurements to the characterization of few-minute average of transmittance indexes.</description><identifier>ISSN: 0177-798X</identifier><identifier>EISSN: 1434-4483</identifier><identifier>DOI: 10.1007/s00704-019-02941-6</identifier><language>eng</language><publisher>Vienna: Springer Vienna</publisher><subject>Air conditioners ; Air masses ; Analysis ; Aquatic Pollution ; Atmosphere ; Atmospheric conditions ; Atmospheric Protection/Air Quality Control/Air Pollution ; Atmospheric Sciences ; Clearness index ; Climate science ; Climatology ; Cloud formation ; Clouds ; Density ; Density distribution ; Dependence ; Distribution (Probability theory) ; Earth and Environmental Science ; Earth Sciences ; Irradiance ; Measurement ; Measuring instruments ; Original Paper ; Pollution ; Pollution levels ; Probability theory ; Radiation ; Radiation measurement ; Relative humidity ; Rural areas ; Specific humidity ; Stations ; Transmittance ; Waste Water Technology ; Water Management ; Water Pollution Control</subject><ispartof>Theoretical and applied climatology, 2020, Vol.139 (1-2), p.205-219</ispartof><rights>Springer-Verlag GmbH Austria, part of Springer Nature 2019</rights><rights>COPYRIGHT 2020 Springer</rights><rights>Theoretical and Applied Climatology is a copyright of Springer, (2019). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c392t-89f87d408b53fa7e16e0784287131713585879ca8bdf31428c1aa9d5799d80e3</citedby><cites>FETCH-LOGICAL-c392t-89f87d408b53fa7e16e0784287131713585879ca8bdf31428c1aa9d5799d80e3</cites><orcidid>0000-0002-0261-9144</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00704-019-02941-6$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00704-019-02941-6$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27915,27916,41479,42548,51310</link.rule.ids></links><search><creatorcontrib>Relva, Stefania Gomes</creatorcontrib><creatorcontrib>Gimenes, André Luiz Veiga</creatorcontrib><creatorcontrib>Udaeta, Miguel Edgar Morales</creatorcontrib><creatorcontrib>Galvão, Luiz Cláudio Ribeiro</creatorcontrib><title>Transmittance index characterization at two solar measurement stations in Brazil</title><title>Theoretical and applied climatology</title><addtitle>Theor Appl Climatol</addtitle><description>This paper constructs probability density distributions of direct normal, diffuse horizontal, and global horizontal irradiance for 1-min clearness indexes
k
b
,
k
d
, and
k
t
, respectively. Previous studies on the clearness index, conditioned to the optical air mass, are analyzed and distributions of these three indexes, using data from two solarimetric stations in Brazil, are presented. The pattern found in probability density distributions, in general, matches the patterns found in the literature. The 50th percentile (P50) of
k
b
values from Sao Paulo city (a location with high levels of pollution) is 0.22, and from the countryside region of the state of Sao Paulo (a location with expected low levels of pollution), it is 0.55. Regarding
k
t
values, P50 is 0.57 and 0.72 for these two regions, respectively. We conclude that different atmospheric conditions result in a different dependence relation between probability density distribution and air mass increases. These conditions include not only cloud formation, but also pollution levels and the influence of relative humidity. These specific results endorse the need for local radiation measurements to the characterization of few-minute average of transmittance indexes.</description><subject>Air conditioners</subject><subject>Air masses</subject><subject>Analysis</subject><subject>Aquatic Pollution</subject><subject>Atmosphere</subject><subject>Atmospheric conditions</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Atmospheric Sciences</subject><subject>Clearness index</subject><subject>Climate science</subject><subject>Climatology</subject><subject>Cloud formation</subject><subject>Clouds</subject><subject>Density</subject><subject>Density distribution</subject><subject>Dependence</subject><subject>Distribution (Probability theory)</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Irradiance</subject><subject>Measurement</subject><subject>Measuring instruments</subject><subject>Original Paper</subject><subject>Pollution</subject><subject>Pollution levels</subject><subject>Probability theory</subject><subject>Radiation</subject><subject>Radiation measurement</subject><subject>Relative humidity</subject><subject>Rural areas</subject><subject>Specific humidity</subject><subject>Stations</subject><subject>Transmittance</subject><subject>Waste Water Technology</subject><subject>Water Management</subject><subject>Water Pollution Control</subject><issn>0177-798X</issn><issn>1434-4483</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kcFqGzEQhkVpoG6aF-hpIaccNh1ptSvp6IQmNRgaEh9yE-PdWVfGq3UkmTh5-qrZQsmlCGlg-D5pxM_YVw6XHEB9i_kAWQI3JQgjedl8YDMuK1lKqauPbAZcqVIZ_fiJfY5xCwCiadSM3a0C-ji4lNC3VDjf0bFof2HANlFwr5jc6AtMRXoeizjuMBQDYTwEGsinIqY3IGaxuAr46nZf2EmPu0hnf-spW918X13_KJc_bxfX82XZVkakUpteq06CXtdVj4p4Q6C0FFrxiudd61or06Jed33Fc7_liKarlTGdBqpO2fl07T6MTweKyW7HQ_D5RSuEAi0ECJGpy4na4I6s8_2Y8sfy6mhw7eipd7k_bzhoJWWts3DxTshMomPa4CFGu3i4f8-KiW3DGGOg3u6DGzC8WA72Typ2SsXmVOxbKrbJUjVJMcN-Q-Hf3P-xfgO5_Y5X</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Relva, Stefania Gomes</creator><creator>Gimenes, André Luiz Veiga</creator><creator>Udaeta, Miguel 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measurement stations in Brazil</title><author>Relva, Stefania Gomes ; Gimenes, André Luiz Veiga ; Udaeta, Miguel Edgar Morales ; Galvão, Luiz Cláudio Ribeiro</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c392t-89f87d408b53fa7e16e0784287131713585879ca8bdf31428c1aa9d5799d80e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Air conditioners</topic><topic>Air masses</topic><topic>Analysis</topic><topic>Aquatic Pollution</topic><topic>Atmosphere</topic><topic>Atmospheric conditions</topic><topic>Atmospheric Protection/Air Quality Control/Air Pollution</topic><topic>Atmospheric Sciences</topic><topic>Clearness index</topic><topic>Climate science</topic><topic>Climatology</topic><topic>Cloud formation</topic><topic>Clouds</topic><topic>Density</topic><topic>Density distribution</topic><topic>Dependence</topic><topic>Distribution (Probability theory)</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Irradiance</topic><topic>Measurement</topic><topic>Measuring instruments</topic><topic>Original Paper</topic><topic>Pollution</topic><topic>Pollution levels</topic><topic>Probability theory</topic><topic>Radiation</topic><topic>Radiation measurement</topic><topic>Relative humidity</topic><topic>Rural areas</topic><topic>Specific humidity</topic><topic>Stations</topic><topic>Transmittance</topic><topic>Waste Water Technology</topic><topic>Water Management</topic><topic>Water Pollution Control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Relva, Stefania Gomes</creatorcontrib><creatorcontrib>Gimenes, André Luiz Veiga</creatorcontrib><creatorcontrib>Udaeta, Miguel Edgar Morales</creatorcontrib><creatorcontrib>Galvão, Luiz Cláudio Ribeiro</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central 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Climatol</stitle><date>2020</date><risdate>2020</risdate><volume>139</volume><issue>1-2</issue><spage>205</spage><epage>219</epage><pages>205-219</pages><issn>0177-798X</issn><eissn>1434-4483</eissn><abstract>This paper constructs probability density distributions of direct normal, diffuse horizontal, and global horizontal irradiance for 1-min clearness indexes
k
b
,
k
d
, and
k
t
, respectively. Previous studies on the clearness index, conditioned to the optical air mass, are analyzed and distributions of these three indexes, using data from two solarimetric stations in Brazil, are presented. The pattern found in probability density distributions, in general, matches the patterns found in the literature. The 50th percentile (P50) of
k
b
values from Sao Paulo city (a location with high levels of pollution) is 0.22, and from the countryside region of the state of Sao Paulo (a location with expected low levels of pollution), it is 0.55. Regarding
k
t
values, P50 is 0.57 and 0.72 for these two regions, respectively. We conclude that different atmospheric conditions result in a different dependence relation between probability density distribution and air mass increases. These conditions include not only cloud formation, but also pollution levels and the influence of relative humidity. These specific results endorse the need for local radiation measurements to the characterization of few-minute average of transmittance indexes.</abstract><cop>Vienna</cop><pub>Springer Vienna</pub><doi>10.1007/s00704-019-02941-6</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-0261-9144</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0177-798X |
| ispartof | Theoretical and applied climatology, 2020, Vol.139 (1-2), p.205-219 |
| issn | 0177-798X 1434-4483 |
| language | eng |
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| source | SpringerLink Journals - AutoHoldings |
| subjects | Air conditioners Air masses Analysis Aquatic Pollution Atmosphere Atmospheric conditions Atmospheric Protection/Air Quality Control/Air Pollution Atmospheric Sciences Clearness index Climate science Climatology Cloud formation Clouds Density Density distribution Dependence Distribution (Probability theory) Earth and Environmental Science Earth Sciences Irradiance Measurement Measuring instruments Original Paper Pollution Pollution levels Probability theory Radiation Radiation measurement Relative humidity Rural areas Specific humidity Stations Transmittance Waste Water Technology Water Management Water Pollution Control |
| title | Transmittance index characterization at two solar measurement stations in Brazil |
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