Timing and patterns of the ENSO signal in Africa over the last 30 years: Insights from normalized difference vegetation index data

A more complete picture of the timing and patterns of the ENSO signal during the seasonal cycle for the whole of Africa over the three last decades is provided using the normalized difference vegetation index (NDVI). Indeed, NDVI has a higher spatial resolution and is more frequently updated than in situ climate databases, and highlights the impact of ENSO on vegetation dynamics as a combined result of ENSO on rainfall, solar radiation, and temperature. The month-by-month NDVI-Niño-3.4 correlation patterns evolve as follows. From July to September, negative correlations are observed over the Sahel, the Gulf of Guinea coast, and regions from the northern Democratic Republic of Congo to Ethiopia. However, they are not uniform in space and are moderate (~0.3). Conversely, positive correlations are recorded over the winter rainfall region of South Africa. In October-November, negative correlations over Ethiopia, Sudan, and Uganda strengthen while positive correlations emerge in the Horn of Africa and in the southeast coast of South Africa. By December with the settlement of the ITCZ south of the equator, positive correlations over the Horn of Africa spread southward and westward while negative correlations appear over Mozambique, Zimbabwe, and South Africa. This pattern strengthens and a dipole at 18°S is well established in February-March with reduced (enhanced) greenness during ENSO years south (north) of 18°S. At the same time, at ~2°N negative correlations spread northward. Last, from April to June negative correlations south of 18°S spread to the north (to 10°S) and to the east (to the south of Tanzania).

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Main Authors: Philippon, Nathalie, Martiny, Nadège, Camberlin, Pierre, Hoffman, M.T., Gond, Valéry
Format: article biblioteca
Language:eng
Subjects:P40 - Météorologie et climatologie, P01 - Conservation de la nature et ressources foncières, F62 - Physiologie végétale - Croissance et développement, U10 - Informatique, mathématiques et statistiques, climatologie, données climatiques, télédétection, indice de surface foliaire, végétation, modèle mathématique, saison, précipitation, énergie solaire, température, http://aims.fao.org/aos/agrovoc/c_1671, http://aims.fao.org/aos/agrovoc/c_29553, http://aims.fao.org/aos/agrovoc/c_6498, http://aims.fao.org/aos/agrovoc/c_35196, http://aims.fao.org/aos/agrovoc/c_8176, http://aims.fao.org/aos/agrovoc/c_24199, http://aims.fao.org/aos/agrovoc/c_6911, http://aims.fao.org/aos/agrovoc/c_6161, http://aims.fao.org/aos/agrovoc/c_7222, http://aims.fao.org/aos/agrovoc/c_7657, http://aims.fao.org/aos/agrovoc/c_7497, http://aims.fao.org/aos/agrovoc/c_8038, http://aims.fao.org/aos/agrovoc/c_2676, http://aims.fao.org/aos/agrovoc/c_7252, http://aims.fao.org/aos/agrovoc/c_8516, http://aims.fao.org/aos/agrovoc/c_4964, http://aims.fao.org/aos/agrovoc/c_8500, http://aims.fao.org/aos/agrovoc/c_6734, http://aims.fao.org/aos/agrovoc/c_50098, http://aims.fao.org/aos/agrovoc/c_165,
Online Access:http://agritrop.cirad.fr/573015/
http://agritrop.cirad.fr/573015/1/document_573015.pdf
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spelling dig-cirad-fr-5730152024-01-28T21:58:56Z http://agritrop.cirad.fr/573015/ http://agritrop.cirad.fr/573015/ Timing and patterns of the ENSO signal in Africa over the last 30 years: Insights from normalized difference vegetation index data. Philippon Nathalie, Martiny Nadège, Camberlin Pierre, Hoffman M.T., Gond Valéry. 2014. Journal of Climate, 27 (7) : 2509-2532.https://doi.org/10.1175/JCLI-D-13-00365.1 <https://doi.org/10.1175/JCLI-D-13-00365.1> Timing and patterns of the ENSO signal in Africa over the last 30 years: Insights from normalized difference vegetation index data Philippon, Nathalie Martiny, Nadège Camberlin, Pierre Hoffman, M.T. Gond, Valéry eng 2014 Journal of Climate P40 - Météorologie et climatologie P01 - Conservation de la nature et ressources foncières F62 - Physiologie végétale - Croissance et développement U10 - Informatique, mathématiques et statistiques climatologie données climatiques télédétection indice de surface foliaire végétation modèle mathématique saison précipitation énergie solaire température http://aims.fao.org/aos/agrovoc/c_1671 http://aims.fao.org/aos/agrovoc/c_29553 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_35196 http://aims.fao.org/aos/agrovoc/c_8176 http://aims.fao.org/aos/agrovoc/c_24199 http://aims.fao.org/aos/agrovoc/c_6911 http://aims.fao.org/aos/agrovoc/c_6161 http://aims.fao.org/aos/agrovoc/c_7222 http://aims.fao.org/aos/agrovoc/c_7657 Soudan Ouganda Éthiopie Afrique du Sud Zimbabwe Mozambique République démocratique du Congo Sahel golfe de Guinée Afrique http://aims.fao.org/aos/agrovoc/c_7497 http://aims.fao.org/aos/agrovoc/c_8038 http://aims.fao.org/aos/agrovoc/c_2676 http://aims.fao.org/aos/agrovoc/c_7252 http://aims.fao.org/aos/agrovoc/c_8516 http://aims.fao.org/aos/agrovoc/c_4964 http://aims.fao.org/aos/agrovoc/c_8500 http://aims.fao.org/aos/agrovoc/c_6734 http://aims.fao.org/aos/agrovoc/c_50098 http://aims.fao.org/aos/agrovoc/c_165 A more complete picture of the timing and patterns of the ENSO signal during the seasonal cycle for the whole of Africa over the three last decades is provided using the normalized difference vegetation index (NDVI). Indeed, NDVI has a higher spatial resolution and is more frequently updated than in situ climate databases, and highlights the impact of ENSO on vegetation dynamics as a combined result of ENSO on rainfall, solar radiation, and temperature. The month-by-month NDVI-Niño-3.4 correlation patterns evolve as follows. From July to September, negative correlations are observed over the Sahel, the Gulf of Guinea coast, and regions from the northern Democratic Republic of Congo to Ethiopia. However, they are not uniform in space and are moderate (~0.3). Conversely, positive correlations are recorded over the winter rainfall region of South Africa. In October-November, negative correlations over Ethiopia, Sudan, and Uganda strengthen while positive correlations emerge in the Horn of Africa and in the southeast coast of South Africa. By December with the settlement of the ITCZ south of the equator, positive correlations over the Horn of Africa spread southward and westward while negative correlations appear over Mozambique, Zimbabwe, and South Africa. This pattern strengthens and a dipole at 18°S is well established in February-March with reduced (enhanced) greenness during ENSO years south (north) of 18°S. At the same time, at ~2°N negative correlations spread northward. Last, from April to June negative correlations south of 18°S spread to the north (to 10°S) and to the east (to the south of Tanzania). article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/573015/1/document_573015.pdf application/pdf Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1175/JCLI-D-13-00365.1 10.1175/JCLI-D-13-00365.1 info:eu-repo/semantics/altIdentifier/doi/10.1175/JCLI-D-13-00365.1 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1175/JCLI-D-13-00365.1
institution CIRAD FR
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country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic P40 - Météorologie et climatologie
P01 - Conservation de la nature et ressources foncières
F62 - Physiologie végétale - Croissance et développement
U10 - Informatique, mathématiques et statistiques
climatologie
données climatiques
télédétection
indice de surface foliaire
végétation
modèle mathématique
saison
précipitation
énergie solaire
température
http://aims.fao.org/aos/agrovoc/c_1671
http://aims.fao.org/aos/agrovoc/c_29553
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_35196
http://aims.fao.org/aos/agrovoc/c_8176
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_6911
http://aims.fao.org/aos/agrovoc/c_6161
http://aims.fao.org/aos/agrovoc/c_7222
http://aims.fao.org/aos/agrovoc/c_7657
http://aims.fao.org/aos/agrovoc/c_7497
http://aims.fao.org/aos/agrovoc/c_8038
http://aims.fao.org/aos/agrovoc/c_2676
http://aims.fao.org/aos/agrovoc/c_7252
http://aims.fao.org/aos/agrovoc/c_8516
http://aims.fao.org/aos/agrovoc/c_4964
http://aims.fao.org/aos/agrovoc/c_8500
http://aims.fao.org/aos/agrovoc/c_6734
http://aims.fao.org/aos/agrovoc/c_50098
http://aims.fao.org/aos/agrovoc/c_165
P40 - Météorologie et climatologie
P01 - Conservation de la nature et ressources foncières
F62 - Physiologie végétale - Croissance et développement
U10 - Informatique, mathématiques et statistiques
climatologie
données climatiques
télédétection
indice de surface foliaire
végétation
modèle mathématique
saison
précipitation
énergie solaire
température
http://aims.fao.org/aos/agrovoc/c_1671
http://aims.fao.org/aos/agrovoc/c_29553
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_35196
http://aims.fao.org/aos/agrovoc/c_8176
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_6911
http://aims.fao.org/aos/agrovoc/c_6161
http://aims.fao.org/aos/agrovoc/c_7222
http://aims.fao.org/aos/agrovoc/c_7657
http://aims.fao.org/aos/agrovoc/c_7497
http://aims.fao.org/aos/agrovoc/c_8038
http://aims.fao.org/aos/agrovoc/c_2676
http://aims.fao.org/aos/agrovoc/c_7252
http://aims.fao.org/aos/agrovoc/c_8516
http://aims.fao.org/aos/agrovoc/c_4964
http://aims.fao.org/aos/agrovoc/c_8500
http://aims.fao.org/aos/agrovoc/c_6734
http://aims.fao.org/aos/agrovoc/c_50098
http://aims.fao.org/aos/agrovoc/c_165
spellingShingle P40 - Météorologie et climatologie
P01 - Conservation de la nature et ressources foncières
F62 - Physiologie végétale - Croissance et développement
U10 - Informatique, mathématiques et statistiques
climatologie
données climatiques
télédétection
indice de surface foliaire
végétation
modèle mathématique
saison
précipitation
énergie solaire
température
http://aims.fao.org/aos/agrovoc/c_1671
http://aims.fao.org/aos/agrovoc/c_29553
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_35196
http://aims.fao.org/aos/agrovoc/c_8176
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_6911
http://aims.fao.org/aos/agrovoc/c_6161
http://aims.fao.org/aos/agrovoc/c_7222
http://aims.fao.org/aos/agrovoc/c_7657
http://aims.fao.org/aos/agrovoc/c_7497
http://aims.fao.org/aos/agrovoc/c_8038
http://aims.fao.org/aos/agrovoc/c_2676
http://aims.fao.org/aos/agrovoc/c_7252
http://aims.fao.org/aos/agrovoc/c_8516
http://aims.fao.org/aos/agrovoc/c_4964
http://aims.fao.org/aos/agrovoc/c_8500
http://aims.fao.org/aos/agrovoc/c_6734
http://aims.fao.org/aos/agrovoc/c_50098
http://aims.fao.org/aos/agrovoc/c_165
P40 - Météorologie et climatologie
P01 - Conservation de la nature et ressources foncières
F62 - Physiologie végétale - Croissance et développement
U10 - Informatique, mathématiques et statistiques
climatologie
données climatiques
télédétection
indice de surface foliaire
végétation
modèle mathématique
saison
précipitation
énergie solaire
température
http://aims.fao.org/aos/agrovoc/c_1671
http://aims.fao.org/aos/agrovoc/c_29553
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_35196
http://aims.fao.org/aos/agrovoc/c_8176
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_6911
http://aims.fao.org/aos/agrovoc/c_6161
http://aims.fao.org/aos/agrovoc/c_7222
http://aims.fao.org/aos/agrovoc/c_7657
http://aims.fao.org/aos/agrovoc/c_7497
http://aims.fao.org/aos/agrovoc/c_8038
http://aims.fao.org/aos/agrovoc/c_2676
http://aims.fao.org/aos/agrovoc/c_7252
http://aims.fao.org/aos/agrovoc/c_8516
http://aims.fao.org/aos/agrovoc/c_4964
http://aims.fao.org/aos/agrovoc/c_8500
http://aims.fao.org/aos/agrovoc/c_6734
http://aims.fao.org/aos/agrovoc/c_50098
http://aims.fao.org/aos/agrovoc/c_165
Philippon, Nathalie
Martiny, Nadège
Camberlin, Pierre
Hoffman, M.T.
Gond, Valéry
Timing and patterns of the ENSO signal in Africa over the last 30 years: Insights from normalized difference vegetation index data
description A more complete picture of the timing and patterns of the ENSO signal during the seasonal cycle for the whole of Africa over the three last decades is provided using the normalized difference vegetation index (NDVI). Indeed, NDVI has a higher spatial resolution and is more frequently updated than in situ climate databases, and highlights the impact of ENSO on vegetation dynamics as a combined result of ENSO on rainfall, solar radiation, and temperature. The month-by-month NDVI-Niño-3.4 correlation patterns evolve as follows. From July to September, negative correlations are observed over the Sahel, the Gulf of Guinea coast, and regions from the northern Democratic Republic of Congo to Ethiopia. However, they are not uniform in space and are moderate (~0.3). Conversely, positive correlations are recorded over the winter rainfall region of South Africa. In October-November, negative correlations over Ethiopia, Sudan, and Uganda strengthen while positive correlations emerge in the Horn of Africa and in the southeast coast of South Africa. By December with the settlement of the ITCZ south of the equator, positive correlations over the Horn of Africa spread southward and westward while negative correlations appear over Mozambique, Zimbabwe, and South Africa. This pattern strengthens and a dipole at 18°S is well established in February-March with reduced (enhanced) greenness during ENSO years south (north) of 18°S. At the same time, at ~2°N negative correlations spread northward. Last, from April to June negative correlations south of 18°S spread to the north (to 10°S) and to the east (to the south of Tanzania).
format article
topic_facet P40 - Météorologie et climatologie
P01 - Conservation de la nature et ressources foncières
F62 - Physiologie végétale - Croissance et développement
U10 - Informatique, mathématiques et statistiques
climatologie
données climatiques
télédétection
indice de surface foliaire
végétation
modèle mathématique
saison
précipitation
énergie solaire
température
http://aims.fao.org/aos/agrovoc/c_1671
http://aims.fao.org/aos/agrovoc/c_29553
http://aims.fao.org/aos/agrovoc/c_6498
http://aims.fao.org/aos/agrovoc/c_35196
http://aims.fao.org/aos/agrovoc/c_8176
http://aims.fao.org/aos/agrovoc/c_24199
http://aims.fao.org/aos/agrovoc/c_6911
http://aims.fao.org/aos/agrovoc/c_6161
http://aims.fao.org/aos/agrovoc/c_7222
http://aims.fao.org/aos/agrovoc/c_7657
http://aims.fao.org/aos/agrovoc/c_7497
http://aims.fao.org/aos/agrovoc/c_8038
http://aims.fao.org/aos/agrovoc/c_2676
http://aims.fao.org/aos/agrovoc/c_7252
http://aims.fao.org/aos/agrovoc/c_8516
http://aims.fao.org/aos/agrovoc/c_4964
http://aims.fao.org/aos/agrovoc/c_8500
http://aims.fao.org/aos/agrovoc/c_6734
http://aims.fao.org/aos/agrovoc/c_50098
http://aims.fao.org/aos/agrovoc/c_165
author Philippon, Nathalie
Martiny, Nadège
Camberlin, Pierre
Hoffman, M.T.
Gond, Valéry
author_facet Philippon, Nathalie
Martiny, Nadège
Camberlin, Pierre
Hoffman, M.T.
Gond, Valéry
author_sort Philippon, Nathalie
title Timing and patterns of the ENSO signal in Africa over the last 30 years: Insights from normalized difference vegetation index data
title_short Timing and patterns of the ENSO signal in Africa over the last 30 years: Insights from normalized difference vegetation index data
title_full Timing and patterns of the ENSO signal in Africa over the last 30 years: Insights from normalized difference vegetation index data
title_fullStr Timing and patterns of the ENSO signal in Africa over the last 30 years: Insights from normalized difference vegetation index data
title_full_unstemmed Timing and patterns of the ENSO signal in Africa over the last 30 years: Insights from normalized difference vegetation index data
title_sort timing and patterns of the enso signal in africa over the last 30 years: insights from normalized difference vegetation index data
url http://agritrop.cirad.fr/573015/
http://agritrop.cirad.fr/573015/1/document_573015.pdf
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