On the information content of surface meteorology for downward atmospheric long‐wave radiation synthesis
Identifieur interne : 000554 ( Istex/Checkpoint ); précédent : 000553; suivant : 000555On the information content of surface meteorology for downward atmospheric long‐wave radiation synthesis
Auteurs : Gab Abramowitz [Australie] ; Laure Pouyanné [Australie, France] ; Hoori Ajami [Australie]Source :
- Geophysical Research Letters [ 0094-8276 ] ; 2012-02.
English descriptors
- KwdEn :
- Absolute error, Agric, Brunt, Brutsaert, Clear skies, Climate change research centre, Cloud fraction, Cloudiness, Cloudiness correction, Cloudiness correction technique, Cloudiness index, Cloudiness information, Cloudy skies, Cluster centres, Daylight hours, Downward radiation, Empirical approach, Empirical model, Empirical model configurations, Empirical models, Environment canada, Environmental engineering, Flux tower sites, Functional form, Functional forms, Howard springs, Independent variables, Information content, Land surface, Longwave, Lwdown, Meteorol, Meteorological data, Mines paristech, Modeling lwdown, Much information, Parent function, Precipitable water, Predictor variables, Radiation synthesis, Regression parameters, Sample testing, Surface meteorology, Surface temperature, Testing site, Time steps, Vapour pressure, Water resour, Water resource research centre.
- Teeft :
- Absolute error, Agric, Brunt, Brutsaert, Clear skies, Climate change research centre, Cloud fraction, Cloudiness, Cloudiness correction, Cloudiness correction technique, Cloudiness index, Cloudiness information, Cloudy skies, Cluster centres, Daylight hours, Downward radiation, Empirical approach, Empirical model, Empirical model configurations, Empirical models, Environment canada, Environmental engineering, Flux tower sites, Functional form, Functional forms, Howard springs, Independent variables, Information content, Land surface, Longwave, Lwdown, Meteorol, Meteorological data, Mines paristech, Modeling lwdown, Much information, Parent function, Precipitable water, Predictor variables, Radiation synthesis, Regression parameters, Sample testing, Surface meteorology, Surface temperature, Testing site, Time steps, Vapour pressure, Water resour, Water resource research centre.
Abstract
One of the key uncertainties in site‐based evaluations of land surface, hydrological or ecological models stems from the lack of availability of downward long‐wave radiation, even at observational stations where tens of other key variables are measured. State of the art techniques for its synthesis are typically functionally dependent on surface temperature, vapour pressure and some representation of cloudiness. Here we show that existing functional forms for downward long‐wave synthesis underutilise information in these key predictor variables, and that in fact cloudiness variables may be redundant. By using an empirical model at a range of sites globally, we examine the contribution of each of the predictor variables and conclude that an extremely simple empirical model may provide more defensible prediction where noa priori knowledge of site behavior exists.
Url:
DOI: 10.1029/2011GL050726
Affiliations:
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fraction</term><term>Cloudiness</term><term>Cloudiness correction</term><term>Cloudiness correction technique</term><term>Cloudiness index</term><term>Cloudiness information</term><term>Cloudy skies</term><term>Cluster centres</term><term>Daylight hours</term><term>Downward radiation</term><term>Empirical approach</term><term>Empirical model</term><term>Empirical model configurations</term><term>Empirical models</term><term>Environment canada</term><term>Environmental engineering</term><term>Flux tower sites</term><term>Functional form</term><term>Functional forms</term><term>Howard springs</term><term>Independent variables</term><term>Information content</term><term>Land surface</term><term>Longwave</term><term>Lwdown</term><term>Meteorol</term><term>Meteorological data</term><term>Mines paristech</term><term>Modeling lwdown</term><term>Much information</term><term>Parent function</term><term>Precipitable water</term><term>Predictor variables</term><term>Radiation synthesis</term><term>Regression parameters</term><term>Sample testing</term><term>Surface meteorology</term><term>Surface temperature</term><term>Testing site</term><term>Time steps</term><term>Vapour pressure</term><term>Water resour</term><term>Water resource research centre</term></keywords><keywords scheme="Teeft" xml:lang="en"><term>Absolute error</term><term>Agric</term><term>Brunt</term><term>Brutsaert</term><term>Clear skies</term><term>Climate change research centre</term><term>Cloud fraction</term><term>Cloudiness</term><term>Cloudiness correction</term><term>Cloudiness correction technique</term><term>Cloudiness index</term><term>Cloudiness information</term><term>Cloudy skies</term><term>Cluster centres</term><term>Daylight hours</term><term>Downward radiation</term><term>Empirical approach</term><term>Empirical model</term><term>Empirical model configurations</term><term>Empirical models</term><term>Environment canada</term><term>Environmental engineering</term><term>Flux tower sites</term><term>Functional form</term><term>Functional forms</term><term>Howard springs</term><term>Independent variables</term><term>Information content</term><term>Land surface</term><term>Longwave</term><term>Lwdown</term><term>Meteorol</term><term>Meteorological data</term><term>Mines paristech</term><term>Modeling lwdown</term><term>Much information</term><term>Parent function</term><term>Precipitable water</term><term>Predictor variables</term><term>Radiation synthesis</term><term>Regression parameters</term><term>Sample testing</term><term>Surface meteorology</term><term>Surface temperature</term><term>Testing site</term><term>Time steps</term><term>Vapour pressure</term><term>Water resour</term><term>Water resource research centre</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract">One of the key uncertainties in site‐based evaluations of land surface, hydrological or ecological models stems from the lack of availability of downward long‐wave radiation, even at observational stations where tens of other key variables are measured. State of the art techniques for its synthesis are typically functionally dependent on surface temperature, vapour pressure and some representation of cloudiness. Here we show that existing functional forms for downward long‐wave synthesis underutilise information in these key predictor variables, and that in fact cloudiness variables may be redundant. By using an empirical model at a range of sites globally, we examine the contribution of each of the predictor variables and conclude that an extremely simple empirical model may provide more defensible prediction where noa priori knowledge of site behavior exists.</div></front></TEI><affiliations><list><country><li>Australie</li><li>France</li></country><region><li>Île-de-France</li></region><settlement><li>Paris</li></settlement></list><tree><country name="Australie"><noRegion><name sortKey="Abramowitz, Gab" sort="Abramowitz, Gab" uniqKey="Abramowitz G" first="Gab" last="Abramowitz">Gab Abramowitz</name></noRegion><name sortKey="Ajami, Hoori" sort="Ajami, Hoori" uniqKey="Ajami H" first="Hoori" last="Ajami">Hoori Ajami</name><name sortKey="Pouyanne, Laure" sort="Pouyanne, Laure" uniqKey="Pouyanne L" first="Laure" last="Pouyanné">Laure Pouyanné</name></country><country name="France"><region name="Île-de-France"><name sortKey="Pouyanne, Laure" sort="Pouyanne, Laure" uniqKey="Pouyanne L" first="Laure" last="Pouyanné">Laure Pouyanné</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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