AustralieFrV1, PascalFrancis, Corpus, bibRecord, 001E71

Root zone soil moisture from the assimilation of screen-level variables and remotely sensed soil moisture

Identifieur interne : 001E71 ( PascalFrancis/Corpus ); précédent : 001E70; suivant : 001E72

Root zone soil moisture from the assimilation of screen-level variables and remotely sensed soil moisture

Auteurs : C. S. Draper ; J.-F. Mahfouf ; J. P. Walker

Source :

Journal of geophysical research [ 0148-0227 ] ; 2011.

RBID : Pascal:11-0169610

Descripteurs français

Pascal (Inist)
- Humidité sol, Assimilation, Prévision météorologique, Prévision numérique, Modèle, Température, Humidité relative, Plomb, Surface sol, Etude expérimentale, Transfert turbulent, Variation diurne, Erreur systématique, Inclusion, Observation par satellite, Radiométrie hyperfréquence, Télédétection spatiale.

English descriptors

KwdEn :
- Bias, Ground surface, Microwave radiometry, Numerical forecast, Relative humidity, Satellite observation, Space remote sensing, Turbulent transfer, Weather forecast, assimilation, diurnal variations, experimental studies, inclusions, lead, models, soil moisture, temperature.

Abstract

[1] In most operational NWP models, root zone soil moisture is constrained using observations of screen-level temperature and relative humidity. While this generally improves low-level atmospheric forecasts, it often leads to unrealistic model soil moisture. Consequently, several NWP centers are moving toward also assimilating remotely sensed near-surface soil moisture observations. Within this context, an EKF is used to compare the assimilation of screen-level observations and near-surface soil moisture data from AMSR-E into the ISBA land surface model over July 2006. Several issues regarding the use of each data type are exposed, and the potential to use the AMSR-E data, either in place of or together with the screen-level data, is examined. When the two data types are assimilated separately, there is little agreement between the root zone soil moisture updates generated by each, indicating that for this experiment the AMSR-E data could not have replaced the screen-level data to obtain similar surface turbulent fluxes. For the screen-level variables, there is a persistent diurnal cycle in the model-observations bias, which is not related to soil moisture. The resulting diurnal cycle in the analysis increments demonstrates how assimilating screen-level observations can lead to unrealistic soil moisture updates, reinforcing the need to assimilate alternative data sets. However, when the two data types are assimilated together, the near-surface soil moisture provides a much weaker constraint of the root zone soil moisture than the screen-level observations do, and the inclusion of the AMSR-E data does not substantially change the results compared to the assimilation of screen-level variables alone.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

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A11	`01`	`1`		`@1 DRAPER (C. S.)`
A11	`02`	`1`		`@1 MAHFOUF (J.-F.)`
A11	`03`	`1`		`@1 WALKER (J. P.)`
A14	`01`			`@1 Department of Civil and Environmental Engineering, University of Melbourne @2 Melbourne, Victoria @3 AUS @Z 1 aut. @Z 3 aut.`
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A14	`04`			`@1 Now at Department of Civil Engineering, Monash University @2 Clayton, Victoria @3 AUS @Z 3 aut.`
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A44				`@0 0000 @1 © 2011 INIST-CNRS. All rights reserved.`
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C01	`01`		`ENG`	@0 [1] In most operational NWP models, root zone soil moisture is constrained using observations of screen-level temperature and relative humidity. While this generally improves low-level atmospheric forecasts, it often leads to unrealistic model soil moisture. Consequently, several NWP centers are moving toward also assimilating remotely sensed near-surface soil moisture observations. Within this context, an EKF is used to compare the assimilation of screen-level observations and near-surface soil moisture data from AMSR-E into the ISBA land surface model over July 2006. Several issues regarding the use of each data type are exposed, and the potential to use the AMSR-E data, either in place of or together with the screen-level data, is examined. When the two data types are assimilated separately, there is little agreement between the root zone soil moisture updates generated by each, indicating that for this experiment the AMSR-E data could not have replaced the screen-level data to obtain similar surface turbulent fluxes. For the screen-level variables, there is a persistent diurnal cycle in the model-observations bias, which is not related to soil moisture. The resulting diurnal cycle in the analysis increments demonstrates how assimilating screen-level observations can lead to unrealistic soil moisture updates, reinforcing the need to assimilate alternative data sets. However, when the two data types are assimilated together, the near-surface soil moisture provides a much weaker constraint of the root zone soil moisture than the screen-level observations do, and the inclusion of the AMSR-E data does not substantially change the results compared to the assimilation of screen-level variables alone.
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C03	`15`	`X`	`FRE`	`@0 Observation par satellite @5 15`
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Format Inist (serveur)

NO :	PASCAL 11-0169610 INIST
ET :	Root zone soil moisture from the assimilation of screen-level variables and remotely sensed soil moisture
AU :	DRAPER (C. S.); MAHFOUF (J.-F.); WALKER (J. P.)
AF :	Department of Civil and Environmental Engineering, University of Melbourne/Melbourne, Victoria/Australie (1 aut., 3 aut.); Now at GAME, CNRM, Météo-France/CNRS/Toulouse/France (1 aut.); GAME, CNRM, Météo-France/CNRS/Toulouse/France (2 aut.); Now at Department of Civil Engineering, Monash University/Clayton, Victoria/Australie (3 aut.)
DT :	Publication en série; Niveau analytique
SO :	Journal of geophysical research; ISSN 0148-0227; Etats-Unis; Da. 2011; Vol. 116; No. D2; D02127.1-D02127.13; Bibl. 3/4 p.
LA :	Anglais
EA :	[1] In most operational NWP models, root zone soil moisture is constrained using observations of screen-level temperature and relative humidity. While this generally improves low-level atmospheric forecasts, it often leads to unrealistic model soil moisture. Consequently, several NWP centers are moving toward also assimilating remotely sensed near-surface soil moisture observations. Within this context, an EKF is used to compare the assimilation of screen-level observations and near-surface soil moisture data from AMSR-E into the ISBA land surface model over July 2006. Several issues regarding the use of each data type are exposed, and the potential to use the AMSR-E data, either in place of or together with the screen-level data, is examined. When the two data types are assimilated separately, there is little agreement between the root zone soil moisture updates generated by each, indicating that for this experiment the AMSR-E data could not have replaced the screen-level data to obtain similar surface turbulent fluxes. For the screen-level variables, there is a persistent diurnal cycle in the model-observations bias, which is not related to soil moisture. The resulting diurnal cycle in the analysis increments demonstrates how assimilating screen-level observations can lead to unrealistic soil moisture updates, reinforcing the need to assimilate alternative data sets. However, when the two data types are assimilated together, the near-surface soil moisture provides a much weaker constraint of the root zone soil moisture than the screen-level observations do, and the inclusion of the AMSR-E data does not substantially change the results compared to the assimilation of screen-level variables alone.
CC :	001E; 001E01; 220
FD :	Humidité sol; Assimilation; Prévision météorologique; Prévision numérique; Modèle; Température; Humidité relative; Plomb; Surface sol; Etude expérimentale; Transfert turbulent; Variation diurne; Erreur systématique; Inclusion; Observation par satellite; Radiométrie hyperfréquence; Télédétection spatiale
ED :	soil moisture; assimilation; Weather forecast; Numerical forecast; models; temperature; Relative humidity; lead; Ground surface; experimental studies; Turbulent transfer; diurnal variations; Bias; inclusions; Satellite observation; Microwave radiometry; Space remote sensing
SD :	Humedad suelo; Asimilación; Predicción meteorológica; Previsión numérica; Modelo; Temperatura; Humedad relativa; Plomo; Superficie suelo; Transferencia turbulenta; Variación diurna; Error sistemático; Inclusión; Observación por satélite; Radiometría hiperfrecuencia; Teledetección espacial
LO :	INIST-3144.354000194452620270
ID :	11-0169610

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Pascal:11-0169610

Le document en format XML

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<front><div type="abstract" xml:lang="en">[1] In most operational NWP models, root zone soil moisture is constrained using observations of screen-level temperature and relative humidity. While this generally improves low-level atmospheric forecasts, it often leads to unrealistic model soil moisture. Consequently, several NWP centers are moving toward also assimilating remotely sensed near-surface soil moisture observations. Within this context, an EKF is used to compare the assimilation of screen-level observations and near-surface soil moisture data from AMSR-E into the ISBA land surface model over July 2006. Several issues regarding the use of each data type are exposed, and the potential to use the AMSR-E data, either in place of or together with the screen-level data, is examined. When the two data types are assimilated separately, there is little agreement between the root zone soil moisture updates generated by each, indicating that for this experiment the AMSR-E data could not have replaced the screen-level data to obtain similar surface turbulent fluxes. For the screen-level variables, there is a persistent diurnal cycle in the model-observations bias, which is not related to soil moisture. The resulting diurnal cycle in the analysis increments demonstrates how assimilating screen-level observations can lead to unrealistic soil moisture updates, reinforcing the need to assimilate alternative data sets. However, when the two data types are assimilated together, the near-surface soil moisture provides a much weaker constraint of the root zone soil moisture than the screen-level observations do, and the inclusion of the AMSR-E data does not substantially change the results compared to the assimilation of screen-level variables alone.</div>
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<fC01 i1="01" l="ENG"><s0>[1] In most operational NWP models, root zone soil moisture is constrained using observations of screen-level temperature and relative humidity. While this generally improves low-level atmospheric forecasts, it often leads to unrealistic model soil moisture. Consequently, several NWP centers are moving toward also assimilating remotely sensed near-surface soil moisture observations. Within this context, an EKF is used to compare the assimilation of screen-level observations and near-surface soil moisture data from AMSR-E into the ISBA land surface model over July 2006. Several issues regarding the use of each data type are exposed, and the potential to use the AMSR-E data, either in place of or together with the screen-level data, is examined. When the two data types are assimilated separately, there is little agreement between the root zone soil moisture updates generated by each, indicating that for this experiment the AMSR-E data could not have replaced the screen-level data to obtain similar surface turbulent fluxes. For the screen-level variables, there is a persistent diurnal cycle in the model-observations bias, which is not related to soil moisture. The resulting diurnal cycle in the analysis increments demonstrates how assimilating screen-level observations can lead to unrealistic soil moisture updates, reinforcing the need to assimilate alternative data sets. However, when the two data types are assimilated together, the near-surface soil moisture provides a much weaker constraint of the root zone soil moisture than the screen-level observations do, and the inclusion of the AMSR-E data does not substantially change the results compared to the assimilation of screen-level variables alone.</s0>
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<s5>01</s5>
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<fC03 i1="02" i2="2" l="FRE"><s0>Assimilation</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="2" l="ENG"><s0>assimilation</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="2" l="SPA"><s0>Asimilación</s0>
<s5>02</s5>
</fC03>
<fC03 i1="03" i2="X" l="FRE"><s0>Prévision météorologique</s0>
<s5>03</s5>
</fC03>
<fC03 i1="03" i2="X" l="ENG"><s0>Weather forecast</s0>
<s5>03</s5>
</fC03>
<fC03 i1="03" i2="X" l="SPA"><s0>Predicción meteorológica</s0>
<s5>03</s5>
</fC03>
<fC03 i1="04" i2="X" l="FRE"><s0>Prévision numérique</s0>
<s5>04</s5>
</fC03>
<fC03 i1="04" i2="X" l="ENG"><s0>Numerical forecast</s0>
<s5>04</s5>
</fC03>
<fC03 i1="04" i2="X" l="SPA"><s0>Previsión numérica</s0>
<s5>04</s5>
</fC03>
<fC03 i1="05" i2="2" l="FRE"><s0>Modèle</s0>
<s5>05</s5>
</fC03>
<fC03 i1="05" i2="2" l="ENG"><s0>models</s0>
<s5>05</s5>
</fC03>
<fC03 i1="05" i2="2" l="SPA"><s0>Modelo</s0>
<s5>05</s5>
</fC03>
<fC03 i1="06" i2="2" l="FRE"><s0>Température</s0>
<s5>06</s5>
</fC03>
<fC03 i1="06" i2="2" l="ENG"><s0>temperature</s0>
<s5>06</s5>
</fC03>
<fC03 i1="06" i2="2" l="SPA"><s0>Temperatura</s0>
<s5>06</s5>
</fC03>
<fC03 i1="07" i2="X" l="FRE"><s0>Humidité relative</s0>
<s5>07</s5>
</fC03>
<fC03 i1="07" i2="X" l="ENG"><s0>Relative humidity</s0>
<s5>07</s5>
</fC03>
<fC03 i1="07" i2="X" l="SPA"><s0>Humedad relativa</s0>
<s5>07</s5>
</fC03>
<fC03 i1="08" i2="2" l="FRE"><s0>Plomb</s0>
<s5>08</s5>
</fC03>
<fC03 i1="08" i2="2" l="ENG"><s0>lead</s0>
<s5>08</s5>
</fC03>
<fC03 i1="08" i2="2" l="SPA"><s0>Plomo</s0>
<s5>08</s5>
</fC03>
<fC03 i1="09" i2="X" l="FRE"><s0>Surface sol</s0>
<s5>09</s5>
</fC03>
<fC03 i1="09" i2="X" l="ENG"><s0>Ground surface</s0>
<s5>09</s5>
</fC03>
<fC03 i1="09" i2="X" l="SPA"><s0>Superficie suelo</s0>
<s5>09</s5>
</fC03>
<fC03 i1="10" i2="2" l="FRE"><s0>Etude expérimentale</s0>
<s5>10</s5>
</fC03>
<fC03 i1="10" i2="2" l="ENG"><s0>experimental studies</s0>
<s5>10</s5>
</fC03>
<fC03 i1="11" i2="X" l="FRE"><s0>Transfert turbulent</s0>
<s5>11</s5>
</fC03>
<fC03 i1="11" i2="X" l="ENG"><s0>Turbulent transfer</s0>
<s5>11</s5>
</fC03>
<fC03 i1="11" i2="X" l="SPA"><s0>Transferencia turbulenta</s0>
<s5>11</s5>
</fC03>
<fC03 i1="12" i2="2" l="FRE"><s0>Variation diurne</s0>
<s5>12</s5>
</fC03>
<fC03 i1="12" i2="2" l="ENG"><s0>diurnal variations</s0>
<s5>12</s5>
</fC03>
<fC03 i1="12" i2="2" l="SPA"><s0>Variación diurna</s0>
<s5>12</s5>
</fC03>
<fC03 i1="13" i2="X" l="FRE"><s0>Erreur systématique</s0>
<s5>13</s5>
</fC03>
<fC03 i1="13" i2="X" l="ENG"><s0>Bias</s0>
<s5>13</s5>
</fC03>
<fC03 i1="13" i2="X" l="SPA"><s0>Error sistemático</s0>
<s5>13</s5>
</fC03>
<fC03 i1="14" i2="2" l="FRE"><s0>Inclusion</s0>
<s5>14</s5>
</fC03>
<fC03 i1="14" i2="2" l="ENG"><s0>inclusions</s0>
<s5>14</s5>
</fC03>
<fC03 i1="14" i2="2" l="SPA"><s0>Inclusión</s0>
<s5>14</s5>
</fC03>
<fC03 i1="15" i2="X" l="FRE"><s0>Observation par satellite</s0>
<s5>15</s5>
</fC03>
<fC03 i1="15" i2="X" l="ENG"><s0>Satellite observation</s0>
<s5>15</s5>
</fC03>
<fC03 i1="15" i2="X" l="SPA"><s0>Observación por satélite</s0>
<s5>15</s5>
</fC03>
<fC03 i1="16" i2="X" l="FRE"><s0>Radiométrie hyperfréquence</s0>
<s5>16</s5>
</fC03>
<fC03 i1="16" i2="X" l="ENG"><s0>Microwave radiometry</s0>
<s5>16</s5>
</fC03>
<fC03 i1="16" i2="X" l="SPA"><s0>Radiometría hiperfrecuencia</s0>
<s5>16</s5>
</fC03>
<fC03 i1="17" i2="2" l="FRE"><s0>Télédétection spatiale</s0>
<s5>17</s5>
</fC03>
<fC03 i1="17" i2="2" l="ENG"><s0>Space remote sensing</s0>
<s5>17</s5>
</fC03>
<fC03 i1="17" i2="2" l="SPA"><s0>Teledetección espacial</s0>
<s5>17</s5>
</fC03>
<fN21><s1>108</s1>
</fN21>
<fN44 i1="01"><s1>OTO</s1>
</fN44>
<fN82><s1>OTO</s1>
</fN82>
</pA>
</standard>
<server><NO>PASCAL 11-0169610 INIST</NO>
<ET>Root zone soil moisture from the assimilation of screen-level variables and remotely sensed soil moisture</ET>
<AU>DRAPER (C. S.); MAHFOUF (J.-F.); WALKER (J. P.)</AU>
<AF>Department of Civil and Environmental Engineering, University of Melbourne/Melbourne, Victoria/Australie (1 aut., 3 aut.); Now at GAME, CNRM, Météo-France/CNRS/Toulouse/France (1 aut.); GAME, CNRM, Météo-France/CNRS/Toulouse/France (2 aut.); Now at Department of Civil Engineering, Monash University/Clayton, Victoria/Australie (3 aut.)</AF>
<DT>Publication en série; Niveau analytique</DT>
<SO>Journal of geophysical research; ISSN 0148-0227; Etats-Unis; Da. 2011; Vol. 116; No. D2; D02127.1-D02127.13; Bibl. 3/4 p.</SO>
<LA>Anglais</LA>
<EA>[1] In most operational NWP models, root zone soil moisture is constrained using observations of screen-level temperature and relative humidity. While this generally improves low-level atmospheric forecasts, it often leads to unrealistic model soil moisture. Consequently, several NWP centers are moving toward also assimilating remotely sensed near-surface soil moisture observations. Within this context, an EKF is used to compare the assimilation of screen-level observations and near-surface soil moisture data from AMSR-E into the ISBA land surface model over July 2006. Several issues regarding the use of each data type are exposed, and the potential to use the AMSR-E data, either in place of or together with the screen-level data, is examined. When the two data types are assimilated separately, there is little agreement between the root zone soil moisture updates generated by each, indicating that for this experiment the AMSR-E data could not have replaced the screen-level data to obtain similar surface turbulent fluxes. For the screen-level variables, there is a persistent diurnal cycle in the model-observations bias, which is not related to soil moisture. The resulting diurnal cycle in the analysis increments demonstrates how assimilating screen-level observations can lead to unrealistic soil moisture updates, reinforcing the need to assimilate alternative data sets. However, when the two data types are assimilated together, the near-surface soil moisture provides a much weaker constraint of the root zone soil moisture than the screen-level observations do, and the inclusion of the AMSR-E data does not substantially change the results compared to the assimilation of screen-level variables alone.</EA>
<CC>001E; 001E01; 220</CC>
<FD>Humidité sol; Assimilation; Prévision météorologique; Prévision numérique; Modèle; Température; Humidité relative; Plomb; Surface sol; Etude expérimentale; Transfert turbulent; Variation diurne; Erreur systématique; Inclusion; Observation par satellite; Radiométrie hyperfréquence; Télédétection spatiale</FD>
<ED>soil moisture; assimilation; Weather forecast; Numerical forecast; models; temperature; Relative humidity; lead; Ground surface; experimental studies; Turbulent transfer; diurnal variations; Bias; inclusions; Satellite observation; Microwave radiometry; Space remote sensing</ED>
<SD>Humedad suelo; Asimilación; Predicción meteorológica; Previsión numérica; Modelo; Temperatura; Humedad relativa; Plomo; Superficie suelo; Transferencia turbulenta; Variación diurna; Error sistemático; Inclusión; Observación por satélite; Radiometría hiperfrecuencia; Teledetección espacial</SD>
<LO>INIST-3144.354000194452620270</LO>
<ID>11-0169610</ID>
</server>
</inist>
</record>

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Root zone soil moisture from the assimilation of screen-level variables and remotely sensed soil moisture

Root zone soil moisture from the assimilation of screen-level variables and remotely sensed soil moisture

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