An approach for simulating the phenology of savanna ecosystems in the Laboratoire de Météorologie Dynamique general circulation model
Identifieur interne : 00C834 ( Main/Exploration ); précédent : 00C833; suivant : 00C835An approach for simulating the phenology of savanna ecosystems in the Laboratoire de Météorologie Dynamique general circulation model
Auteurs : C. Ciret [Australie] ; J. Polcher [France] ; X. Le Roux [France]Source :
- Global biogeochemical cycles [ 0886-6236 ] ; 1999.
Descripteurs français
- Pascal (Inist)
- Wicri :
- geographic : Australie.
- topic : Production végétale, Biomasse, Climat, Zone tropicale.
English descriptors
- KwdEn :
Abstract
Plant phenology, defined here as the seasonal variations of green and dead biomasses in response to climatic conditions, is an important parameter for the modeling of biophysical exchanges between vegetation and atmosphere. However, the adequate simulation of plant phenology, particularly in tropical regions, is still lacking in current general circulation models (GCMs). This paper proposes a modeling approach to simulate the phenology of savanna grasses in the Laboratoire de Météorologie Dynamique (LMD) GCM. A plant production and phenology model (PPP) is developed to simulate the temporal variations of green and dead aboveground biomasses and leaf area index (LAI) using climate variables computed by the LMD GCM. In addition, the PPP model simulates the occurrence of savanna fire. Predictions are compared to harvest measurements of grasses from two different regions of savanna: the region of Lamto, West Africa, and the region of Victoria River district, northern Australia. Results show that the PPP model generates reasonably realistic plant seasonal variations in these two regions, despite the existing biases in the simulated climate variables. Both the frequency and timing of fire occurrence are, moreover, realistically simulated. This model, linked to the GCM, could be used as a tool to investigate the effects of fire disturbances and short-term (i.e., seasonal and interannual) savanna vegetation feedbacks on climate.
Affiliations:
- Australie, France
- Auvergne (région administrative), Auvergne-Rhône-Alpes, Île-de-France
- Clermont-Ferrand, Paris
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Le document en format XML
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Polcher</name><affiliation wicri:level="3"><inist:fA14 i1="02"><s1>Laboratoire de Météorologie Dynamique, CNRS</s1><s2>Paris</s2><s3>FRA</s3><sZ>2 aut.</sZ></inist:fA14><country>France</country><placeName><region type="region">Île-de-France</region><region type="old region">Île-de-France</region><settlement type="city">Paris</settlement></placeName></affiliation></author><author><name sortKey="Le Roux, X" sort="Le Roux, X" uniqKey="Le Roux X" first="X." last="Le Roux">X. Le Roux</name><affiliation wicri:level="3"><inist:fA14 i1="03"><s1>Institut Nationale de Recherche Agronomique</s1><s2>Clermont Ferrand</s2><s3>FRA</s3><sZ>3 aut.</sZ></inist:fA14><country>France</country><placeName><region type="region">Auvergne-Rhône-Alpes</region><region type="old region">Auvergne (région administrative)</region><settlement type="city">Clermont-Ferrand</settlement></placeName></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">INIST</idno><idno type="inist">99-0378276</idno><date when="1999">1999</date><idno type="stanalyst">PASCAL 99-0378276 INIST</idno><idno type="RBID">Pascal:99-0378276</idno><idno type="wicri:Area/PascalFrancis/Corpus">006299</idno><idno type="wicri:Area/PascalFrancis/Curation">006D55</idno><idno type="wicri:Area/PascalFrancis/Checkpoint">006149</idno><idno type="wicri:explorRef" wicri:stream="PascalFrancis" wicri:step="Checkpoint">006149</idno><idno type="wicri:doubleKey">0886-6236:1999:Ciret C:an:approach:for</idno><idno type="wicri:Area/Main/Merge">00D862</idno><idno type="wicri:Area/Main/Curation">00C834</idno><idno type="wicri:Area/Main/Exploration">00C834</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">An approach for simulating the phenology of savanna ecosystems in the Laboratoire de Météorologie Dynamique general circulation model</title><author><name sortKey="Ciret, C" sort="Ciret, C" uniqKey="Ciret C" first="C." last="Ciret">C. Ciret</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Climatic Impact Centre, Macquarie University</s1><s2>Sydney, New South Wales</s2><s3>AUS</s3><sZ>1 aut.</sZ></inist:fA14><country>Australie</country><wicri:noRegion>Sydney, New South Wales</wicri:noRegion></affiliation></author><author><name sortKey="Polcher, J" sort="Polcher, J" uniqKey="Polcher J" first="J." last="Polcher">J. Polcher</name><affiliation wicri:level="3"><inist:fA14 i1="02"><s1>Laboratoire de Météorologie Dynamique, CNRS</s1><s2>Paris</s2><s3>FRA</s3><sZ>2 aut.</sZ></inist:fA14><country>France</country><placeName><region type="region">Île-de-France</region><region type="old region">Île-de-France</region><settlement type="city">Paris</settlement></placeName></affiliation></author><author><name sortKey="Le Roux, X" sort="Le Roux, X" uniqKey="Le Roux X" first="X." last="Le Roux">X. Le Roux</name><affiliation wicri:level="3"><inist:fA14 i1="03"><s1>Institut Nationale de Recherche Agronomique</s1><s2>Clermont Ferrand</s2><s3>FRA</s3><sZ>3 aut.</sZ></inist:fA14><country>France</country><placeName><region type="region">Auvergne-Rhône-Alpes</region><region type="old region">Auvergne (région administrative)</region><settlement type="city">Clermont-Ferrand</settlement></placeName></affiliation></author></analytic><series><title level="j" type="main">Global biogeochemical cycles</title><title level="j" type="abbreviated">Glob. biogeochem. cycles</title><idno type="ISSN">0886-6236</idno><imprint><date when="1999">1999</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Global biogeochemical cycles</title><title level="j" type="abbreviated">Glob. biogeochem. cycles</title><idno type="ISSN">0886-6236</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Application</term><term>Australia</term><term>Biomass</term><term>Canopy fire</term><term>Climate</term><term>Development</term><term>Models</term><term>Plant atmosphere relation</term><term>Plant production</term><term>Savannah</term><term>Seasonal variation</term><term>Tropical zone</term><term>Vegetation</term><term>West Africa</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Production végétale</term><term>Développement</term><term>Biomasse</term><term>Climat</term><term>Savane</term><term>Zone tropicale</term><term>Modèle</term><term>Application</term><term>Feu végétation</term><term>Végétation</term><term>Afrique Ouest</term><term>Australie</term><term>Variation saisonnière</term><term>Relation plante atmosphère</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Australie</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Production végétale</term><term>Biomasse</term><term>Climat</term><term>Zone tropicale</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Plant phenology, defined here as the seasonal variations of green and dead biomasses in response to climatic conditions, is an important parameter for the modeling of biophysical exchanges between vegetation and atmosphere. However, the adequate simulation of plant phenology, particularly in tropical regions, is still lacking in current general circulation models (GCMs). This paper proposes a modeling approach to simulate the phenology of savanna grasses in the Laboratoire de Météorologie Dynamique (LMD) GCM. A plant production and phenology model (PPP) is developed to simulate the temporal variations of green and dead aboveground biomasses and leaf area index (LAI) using climate variables computed by the LMD GCM. In addition, the PPP model simulates the occurrence of savanna fire. Predictions are compared to harvest measurements of grasses from two different regions of savanna: the region of Lamto, West Africa, and the region of Victoria River district, northern Australia. Results show that the PPP model generates reasonably realistic plant seasonal variations in these two regions, despite the existing biases in the simulated climate variables. Both the frequency and timing of fire occurrence are, moreover, realistically simulated. This model, linked to the GCM, could be used as a tool to investigate the effects of fire disturbances and short-term (i.e., seasonal and interannual) savanna vegetation feedbacks on climate.</div></front></TEI><affiliations><list><country><li>Australie</li><li>France</li></country><region><li>Auvergne (région administrative)</li><li>Auvergne-Rhône-Alpes</li><li>Île-de-France</li></region><settlement><li>Clermont-Ferrand</li><li>Paris</li></settlement></list><tree><country name="Australie"><noRegion><name sortKey="Ciret, C" sort="Ciret, C" uniqKey="Ciret C" first="C." last="Ciret">C. Ciret</name></noRegion></country><country name="France"><region name="Île-de-France"><name sortKey="Polcher, J" sort="Polcher, J" uniqKey="Polcher J" first="J." last="Polcher">J. Polcher</name></region><name sortKey="Le Roux, X" sort="Le Roux, X" uniqKey="Le Roux X" first="X." last="Le Roux">X. 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