AustralieFrV1, PascalFrancis, Corpus, bibRecord, 001400

Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP-ICE

Identifieur interne : 001400 ( PascalFrancis/Corpus ); précédent : 001399; suivant : 001401

Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP-ICE

Auteurs : Charmaine N. Franklin ; Christian Jakob ; Martin Dix ; Alain Protat ; Greg Roff

Source :

Quarterly Journal of the Royal Meteorological Society [ 0035-9009 ] ; 2012.

RBID : Pascal:12-0206678

Descripteurs français

Pascal (Inist)
- Performance, Nuage chaud, Glace, Modèle unifié, Zone tropicale, Nuage aqueux, Champ glace, Mousson, Nébulosité, Humidité relative, Nuage glace, Teneur eau, Variation diurne, Erreur relative, Modèle 3 dimensions, Paramétrisation, Royaume Uni, Australie, Modèle paramétré uni-colonne, Masse chaude.

English descriptors

KwdEn :
- Australia, Cloudiness, Ice cloud, Relative error, Relative humidity, Single-column model, Unified model, United Kingdom, Warm cloud, Warm pool, Water cloud, diurnal variations, ice, ice fields, monsoons, parametrization, performances, three-dimensional models, tropical zone, water content.

Abstract

Single column model simulations using the UK Met Office Unified Model, as used in the Australian Community Climate Earth System Simulator, are presented for the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) field study. Two formulations for the representation of clouds are compared with the extensive observations taken during the campaign, giving insight into the ability of the model to simulate tropical cloud systems. During the active monsoon phase the modelled cloud cover has a stronger dependence on relative humidity than the observations. Observed ice cloud properties during the suppressed monsoon period show that the ice water content is significantly underestimated in the simulations. The profiles of modelled ice fall speeds are faster than those observed in the levels above 12 km, implying that the observations have smaller sized particles in larger concentrations than the models. Both simulations show similar errors in the diurnal cycle of relative humidity during the active monsoon phase, suggesting that the error is less sensitive to the choice of cloud scheme and rather is driven by the convection scheme. However, during the times of suppressed convection the relative humidity error is different between the simulations, with congestus convection drying the environment too much, particularly in the prognostic cloud-scheme simulation. This result shows that the choice of cloud scheme and the way that the cloud and convection schemes interact plays a role in the temperature and moisture errors during the suppressed monsoon phase, which will impact the three-dimensional model simulations of tropical variability.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

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Format Inist (serveur)

NO :	PASCAL 12-0206678 INIST
ET :	Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP-ICE
AU :	FRANKLIN (Charmaine N.); JAKOB (Christian); DIX (Martin); PROTAT (Alain); ROFF (Greg)
AF :	Centre for Australian Weather and Climate Research -A partnership between CSIRO and the Australian Bureau of Meteorology/Australie (1 aut., 3 aut., 4 aut., 5 aut.); School of Mathematical Sciences, Monash University/Australie (2 aut.); Laboratoire A Tmosphère, Milieux, Observations Spatiales/Vélizy/France (4 aut.)
DT :	Publication en série; Niveau analytique
SO :	Quarterly Journal of the Royal Meteorological Society; ISSN 0035-9009; Coden QJRMAM; Royaume-Uni; Da. 2012; Vol. 138; No. 664; Pp. 734-754; Bibl. 3/4 p.
LA :	Anglais
EA :	Single column model simulations using the UK Met Office Unified Model, as used in the Australian Community Climate Earth System Simulator, are presented for the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) field study. Two formulations for the representation of clouds are compared with the extensive observations taken during the campaign, giving insight into the ability of the model to simulate tropical cloud systems. During the active monsoon phase the modelled cloud cover has a stronger dependence on relative humidity than the observations. Observed ice cloud properties during the suppressed monsoon period show that the ice water content is significantly underestimated in the simulations. The profiles of modelled ice fall speeds are faster than those observed in the levels above 12 km, implying that the observations have smaller sized particles in larger concentrations than the models. Both simulations show similar errors in the diurnal cycle of relative humidity during the active monsoon phase, suggesting that the error is less sensitive to the choice of cloud scheme and rather is driven by the convection scheme. However, during the times of suppressed convection the relative humidity error is different between the simulations, with congestus convection drying the environment too much, particularly in the prognostic cloud-scheme simulation. This result shows that the choice of cloud scheme and the way that the cloud and convection schemes interact plays a role in the temperature and moisture errors during the suppressed monsoon phase, which will impact the three-dimensional model simulations of tropical variability.
CC :	001E02H; 001E02D
FD :	Performance; Nuage chaud; Glace; Modèle unifié; Zone tropicale; Nuage aqueux; Champ glace; Mousson; Nébulosité; Humidité relative; Nuage glace; Teneur eau; Variation diurne; Erreur relative; Modèle 3 dimensions; Paramétrisation; Royaume Uni; Australie; Modèle paramétré uni-colonne; Masse chaude
FG :	Europe Ouest; Europe; Australasie
ED :	performances; Warm cloud; ice; Unified model; tropical zone; Water cloud; ice fields; monsoons; Cloudiness; Relative humidity; Ice cloud; water content; diurnal variations; Relative error; three-dimensional models; parametrization; United Kingdom; Australia; Single-column model; Warm pool
EG :	Western Europe; Europe; Australasia
SD :	Nube caliente; Hielo; Zona tropical; Nube acuosa; Monzón; Nebulosidad; Humedad relativa; Nube hielo; Contenido en agua; Variación diurna; Error relativo; Modelo 3 dimensiones; Reino Unido; Australia; Masa caliente
LO :	INIST-3134.354000509839080140
ID :	12-0206678

Links to Exploration step

Pascal:12-0206678

Le document en format XML

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<front><div type="abstract" xml:lang="en">Single column model simulations using the UK Met Office Unified Model, as used in the Australian Community Climate Earth System Simulator, are presented for the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) field study. Two formulations for the representation of clouds are compared with the extensive observations taken during the campaign, giving insight into the ability of the model to simulate tropical cloud systems. During the active monsoon phase the modelled cloud cover has a stronger dependence on relative humidity than the observations. Observed ice cloud properties during the suppressed monsoon period show that the ice water content is significantly underestimated in the simulations. The profiles of modelled ice fall speeds are faster than those observed in the levels above 12 km, implying that the observations have smaller sized particles in larger concentrations than the models. Both simulations show similar errors in the diurnal cycle of relative humidity during the active monsoon phase, suggesting that the error is less sensitive to the choice of cloud scheme and rather is driven by the convection scheme. However, during the times of suppressed convection the relative humidity error is different between the simulations, with congestus convection drying the environment too much, particularly in the prognostic cloud-scheme simulation. This result shows that the choice of cloud scheme and the way that the cloud and convection schemes interact plays a role in the temperature and moisture errors during the suppressed monsoon phase, which will impact the three-dimensional model simulations of tropical variability.</div>
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<fA21><s1>2012</s1>
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<fA23 i1="01"><s0>ENG</s0>
</fA23>
<fA43 i1="01"><s1>INIST</s1>
<s2>3134</s2>
<s5>354000509839080140</s5>
</fA43>
<fA44><s0>0000</s0>
<s1>© 2012 INIST-CNRS. All rights reserved.</s1>
</fA44>
<fA45><s0>3/4 p.</s0>
</fA45>
<fA47 i1="01" i2="1"><s0>12-0206678</s0>
</fA47>
<fA60><s1>P</s1>
</fA60>
<fA61><s0>A</s0>
</fA61>
<fA64 i1="01" i2="1"><s0>Quarterly Journal of the Royal Meteorological Society</s0>
</fA64>
<fA66 i1="01"><s0>GBR</s0>
</fA66>
<fC01 i1="01" l="ENG"><s0>Single column model simulations using the UK Met Office Unified Model, as used in the Australian Community Climate Earth System Simulator, are presented for the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) field study. Two formulations for the representation of clouds are compared with the extensive observations taken during the campaign, giving insight into the ability of the model to simulate tropical cloud systems. During the active monsoon phase the modelled cloud cover has a stronger dependence on relative humidity than the observations. Observed ice cloud properties during the suppressed monsoon period show that the ice water content is significantly underestimated in the simulations. The profiles of modelled ice fall speeds are faster than those observed in the levels above 12 km, implying that the observations have smaller sized particles in larger concentrations than the models. Both simulations show similar errors in the diurnal cycle of relative humidity during the active monsoon phase, suggesting that the error is less sensitive to the choice of cloud scheme and rather is driven by the convection scheme. However, during the times of suppressed convection the relative humidity error is different between the simulations, with congestus convection drying the environment too much, particularly in the prognostic cloud-scheme simulation. This result shows that the choice of cloud scheme and the way that the cloud and convection schemes interact plays a role in the temperature and moisture errors during the suppressed monsoon phase, which will impact the three-dimensional model simulations of tropical variability.</s0>
</fC01>
<fC02 i1="01" i2="2"><s0>001E02H</s0>
</fC02>
<fC02 i1="02" i2="2"><s0>001E02D</s0>
</fC02>
<fC03 i1="01" i2="2" l="FRE"><s0>Performance</s0>
<s5>01</s5>
</fC03>
<fC03 i1="01" i2="2" l="ENG"><s0>performances</s0>
<s5>01</s5>
</fC03>
<fC03 i1="02" i2="X" l="FRE"><s0>Nuage chaud</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="X" l="ENG"><s0>Warm cloud</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="X" l="SPA"><s0>Nube caliente</s0>
<s5>02</s5>
</fC03>
<fC03 i1="03" i2="2" l="FRE"><s0>Glace</s0>
<s5>03</s5>
</fC03>
<fC03 i1="03" i2="2" l="ENG"><s0>ice</s0>
<s5>03</s5>
</fC03>
<fC03 i1="03" i2="2" l="SPA"><s0>Hielo</s0>
<s5>03</s5>
</fC03>
<fC03 i1="04" i2="3" l="FRE"><s0>Modèle unifié</s0>
<s5>04</s5>
</fC03>
<fC03 i1="04" i2="3" l="ENG"><s0>Unified model</s0>
<s5>04</s5>
</fC03>
<fC03 i1="05" i2="2" l="FRE"><s0>Zone tropicale</s0>
<s5>05</s5>
</fC03>
<fC03 i1="05" i2="2" l="ENG"><s0>tropical zone</s0>
<s5>05</s5>
</fC03>
<fC03 i1="05" i2="2" l="SPA"><s0>Zona tropical</s0>
<s5>05</s5>
</fC03>
<fC03 i1="06" i2="X" l="FRE"><s0>Nuage aqueux</s0>
<s5>06</s5>
</fC03>
<fC03 i1="06" i2="X" l="ENG"><s0>Water cloud</s0>
<s5>06</s5>
</fC03>
<fC03 i1="06" i2="X" l="SPA"><s0>Nube acuosa</s0>
<s5>06</s5>
</fC03>
<fC03 i1="07" i2="2" l="FRE"><s0>Champ glace</s0>
<s5>07</s5>
</fC03>
<fC03 i1="07" i2="2" l="ENG"><s0>ice fields</s0>
<s5>07</s5>
</fC03>
<fC03 i1="08" i2="2" l="FRE"><s0>Mousson</s0>
<s5>08</s5>
</fC03>
<fC03 i1="08" i2="2" l="ENG"><s0>monsoons</s0>
<s5>08</s5>
</fC03>
<fC03 i1="08" i2="2" l="SPA"><s0>Monzón</s0>
<s5>08</s5>
</fC03>
<fC03 i1="09" i2="X" l="FRE"><s0>Nébulosité</s0>
<s5>09</s5>
</fC03>
<fC03 i1="09" i2="X" l="ENG"><s0>Cloudiness</s0>
<s5>09</s5>
</fC03>
<fC03 i1="09" i2="X" l="SPA"><s0>Nebulosidad</s0>
<s5>09</s5>
</fC03>
<fC03 i1="10" i2="X" l="FRE"><s0>Humidité relative</s0>
<s5>10</s5>
</fC03>
<fC03 i1="10" i2="X" l="ENG"><s0>Relative humidity</s0>
<s5>10</s5>
</fC03>
<fC03 i1="10" i2="X" l="SPA"><s0>Humedad relativa</s0>
<s5>10</s5>
</fC03>
<fC03 i1="11" i2="X" l="FRE"><s0>Nuage glace</s0>
<s5>11</s5>
</fC03>
<fC03 i1="11" i2="X" l="ENG"><s0>Ice cloud</s0>
<s5>11</s5>
</fC03>
<fC03 i1="11" i2="X" l="SPA"><s0>Nube hielo</s0>
<s5>11</s5>
</fC03>
<fC03 i1="12" i2="2" l="FRE"><s0>Teneur eau</s0>
<s5>12</s5>
</fC03>
<fC03 i1="12" i2="2" l="ENG"><s0>water content</s0>
<s5>12</s5>
</fC03>
<fC03 i1="12" i2="2" l="SPA"><s0>Contenido en agua</s0>
<s5>12</s5>
</fC03>
<fC03 i1="13" i2="2" l="FRE"><s0>Variation diurne</s0>
<s5>13</s5>
</fC03>
<fC03 i1="13" i2="2" l="ENG"><s0>diurnal variations</s0>
<s5>13</s5>
</fC03>
<fC03 i1="13" i2="2" l="SPA"><s0>Variación diurna</s0>
<s5>13</s5>
</fC03>
<fC03 i1="14" i2="X" l="FRE"><s0>Erreur relative</s0>
<s5>14</s5>
</fC03>
<fC03 i1="14" i2="X" l="ENG"><s0>Relative error</s0>
<s5>14</s5>
</fC03>
<fC03 i1="14" i2="X" l="SPA"><s0>Error relativo</s0>
<s5>14</s5>
</fC03>
<fC03 i1="15" i2="2" l="FRE"><s0>Modèle 3 dimensions</s0>
<s5>15</s5>
</fC03>
<fC03 i1="15" i2="2" l="ENG"><s0>three-dimensional models</s0>
<s5>15</s5>
</fC03>
<fC03 i1="15" i2="2" l="SPA"><s0>Modelo 3 dimensiones</s0>
<s5>15</s5>
</fC03>
<fC03 i1="16" i2="2" l="FRE"><s0>Paramétrisation</s0>
<s5>16</s5>
</fC03>
<fC03 i1="16" i2="2" l="ENG"><s0>parametrization</s0>
<s5>16</s5>
</fC03>
<fC03 i1="17" i2="2" l="FRE"><s0>Royaume Uni</s0>
<s2>NG</s2>
<s5>21</s5>
</fC03>
<fC03 i1="17" i2="2" l="ENG"><s0>United Kingdom</s0>
<s2>NG</s2>
<s5>21</s5>
</fC03>
<fC03 i1="17" i2="2" l="SPA"><s0>Reino Unido</s0>
<s2>NG</s2>
<s5>21</s5>
</fC03>
<fC03 i1="18" i2="2" l="FRE"><s0>Australie</s0>
<s2>NG</s2>
<s5>23</s5>
</fC03>
<fC03 i1="18" i2="2" l="ENG"><s0>Australia</s0>
<s2>NG</s2>
<s5>23</s5>
</fC03>
<fC03 i1="18" i2="2" l="SPA"><s0>Australia</s0>
<s2>NG</s2>
<s5>23</s5>
</fC03>
<fC03 i1="19" i2="2" l="FRE"><s0>Modèle paramétré uni-colonne</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC03 i1="19" i2="2" l="ENG"><s0>Single-column model</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC03 i1="20" i2="2" l="FRE"><s0>Masse chaude</s0>
<s4>CD</s4>
<s5>97</s5>
</fC03>
<fC03 i1="20" i2="2" l="ENG"><s0>Warm pool</s0>
<s4>CD</s4>
<s5>97</s5>
</fC03>
<fC03 i1="20" i2="2" l="SPA"><s0>Masa caliente</s0>
<s4>CD</s4>
<s5>97</s5>
</fC03>
<fC07 i1="01" i2="2" l="FRE"><s0>Europe Ouest</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="01" i2="2" l="ENG"><s0>Western Europe</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="01" i2="2" l="SPA"><s0>Europa del Oeste</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="02" i2="2" l="FRE"><s0>Europe</s0>
<s2>564</s2>
</fC07>
<fC07 i1="02" i2="2" l="ENG"><s0>Europe</s0>
<s2>564</s2>
</fC07>
<fC07 i1="02" i2="2" l="SPA"><s0>Europa</s0>
<s2>564</s2>
</fC07>
<fC07 i1="03" i2="2" l="FRE"><s0>Australasie</s0>
</fC07>
<fC07 i1="03" i2="2" l="ENG"><s0>Australasia</s0>
</fC07>
<fC07 i1="03" i2="2" l="SPA"><s0>Australasia</s0>
</fC07>
<fN21><s1>163</s1>
</fN21>
<fN44 i1="01"><s1>OTO</s1>
</fN44>
<fN82><s1>OTO</s1>
</fN82>
</pA>
</standard>
<server><NO>PASCAL 12-0206678 INIST</NO>
<ET>Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP-ICE</ET>
<AU>FRANKLIN (Charmaine N.); JAKOB (Christian); DIX (Martin); PROTAT (Alain); ROFF (Greg)</AU>
<AF>Centre for Australian Weather and Climate Research -A partnership between CSIRO and the Australian Bureau of Meteorology/Australie (1 aut., 3 aut., 4 aut., 5 aut.); School of Mathematical Sciences, Monash University/Australie (2 aut.); Laboratoire A Tmosphère, Milieux, Observations Spatiales/Vélizy/France (4 aut.)</AF>
<DT>Publication en série; Niveau analytique</DT>
<SO>Quarterly Journal of the Royal Meteorological Society; ISSN 0035-9009; Coden QJRMAM; Royaume-Uni; Da. 2012; Vol. 138; No. 664; Pp. 734-754; Bibl. 3/4 p.</SO>
<LA>Anglais</LA>
<EA>Single column model simulations using the UK Met Office Unified Model, as used in the Australian Community Climate Earth System Simulator, are presented for the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) field study. Two formulations for the representation of clouds are compared with the extensive observations taken during the campaign, giving insight into the ability of the model to simulate tropical cloud systems. During the active monsoon phase the modelled cloud cover has a stronger dependence on relative humidity than the observations. Observed ice cloud properties during the suppressed monsoon period show that the ice water content is significantly underestimated in the simulations. The profiles of modelled ice fall speeds are faster than those observed in the levels above 12 km, implying that the observations have smaller sized particles in larger concentrations than the models. Both simulations show similar errors in the diurnal cycle of relative humidity during the active monsoon phase, suggesting that the error is less sensitive to the choice of cloud scheme and rather is driven by the convection scheme. However, during the times of suppressed convection the relative humidity error is different between the simulations, with congestus convection drying the environment too much, particularly in the prognostic cloud-scheme simulation. This result shows that the choice of cloud scheme and the way that the cloud and convection schemes interact plays a role in the temperature and moisture errors during the suppressed monsoon phase, which will impact the three-dimensional model simulations of tropical variability.</EA>
<CC>001E02H; 001E02D</CC>
<FD>Performance; Nuage chaud; Glace; Modèle unifié; Zone tropicale; Nuage aqueux; Champ glace; Mousson; Nébulosité; Humidité relative; Nuage glace; Teneur eau; Variation diurne; Erreur relative; Modèle 3 dimensions; Paramétrisation; Royaume Uni; Australie; Modèle paramétré uni-colonne; Masse chaude</FD>
<FG>Europe Ouest; Europe; Australasie</FG>
<ED>performances; Warm cloud; ice; Unified model; tropical zone; Water cloud; ice fields; monsoons; Cloudiness; Relative humidity; Ice cloud; water content; diurnal variations; Relative error; three-dimensional models; parametrization; United Kingdom; Australia; Single-column model; Warm pool</ED>
<EG>Western Europe; Europe; Australasia</EG>
<SD>Nube caliente; Hielo; Zona tropical; Nube acuosa; Monzón; Nebulosidad; Humedad relativa; Nube hielo; Contenido en agua; Variación diurna; Error relativo; Modelo 3 dimensiones; Reino Unido; Australia; Masa caliente</SD>
<LO>INIST-3134.354000509839080140</LO>
<ID>12-0206678</ID>
</server>
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Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP-ICE

Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP-ICE

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