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Abstract
Observations from Advanced Microwave Sounding Unit-A and -B (AMSU-A and -B) have been more intensively used over sea than over land because of large uncertainties about the land surface emissivity and the skin temperature. Several methods based on a direct estimation of the land emissivity from satellite observations have been found to be very useful for improving the assimilation of sounding channels over land. Feasibility studies have been conducted within the Météo-France global assimilation system in order to examine the possibility of assimilating low-level atmospheric observations receiving a contribution from the land surface. The present study reports on three 2-month assimilation and forecast experiments, which include the assimilation of surface-sensitive observations from AMSU-A and -B together with a control experiment, which represents the operational model. The assimilation experiments have been compared with the control, and important changes in the analyzed atmospheric fields and in the precipitation forecasts over parts of the tropics, and especially over West Africa, have been noticed. The experiments seem to emphasize the atmospheric moistening in India, South America, and in West Africa, together with atmospheric drying over Saudi Arabia and northeast Africa. The drying or moistening of the atmosphere has been successfully evaluated using independent measurements from the GPS African Monsoon Multidisciplinary Analysis (AMMA) network. Precipitation and OLR forecasts have also been examined and compared with independent measurements. Physically, the changes result in a better-organized African monsoon with a stronger ITCZ in terms of ascent, vorticity, and precipitation, but there is no northward shift of the monsoon system. Low-level humidity observations have been found to have important impacts on the analysis and to produce positive impacts on forecast scores over the tropics.
Abstract
Observations from Advanced Microwave Sounding Unit-A and -B (AMSU-A and -B) have been more intensively used over sea than over land because of large uncertainties about the land surface emissivity and the skin temperature. Several methods based on a direct estimation of the land emissivity from satellite observations have been found to be very useful for improving the assimilation of sounding channels over land. Feasibility studies have been conducted within the Météo-France global assimilation system in order to examine the possibility of assimilating low-level atmospheric observations receiving a contribution from the land surface. The present study reports on three 2-month assimilation and forecast experiments, which include the assimilation of surface-sensitive observations from AMSU-A and -B together with a control experiment, which represents the operational model. The assimilation experiments have been compared with the control, and important changes in the analyzed atmospheric fields and in the precipitation forecasts over parts of the tropics, and especially over West Africa, have been noticed. The experiments seem to emphasize the atmospheric moistening in India, South America, and in West Africa, together with atmospheric drying over Saudi Arabia and northeast Africa. The drying or moistening of the atmosphere has been successfully evaluated using independent measurements from the GPS African Monsoon Multidisciplinary Analysis (AMMA) network. Precipitation and OLR forecasts have also been examined and compared with independent measurements. Physically, the changes result in a better-organized African monsoon with a stronger ITCZ in terms of ascent, vorticity, and precipitation, but there is no northward shift of the monsoon system. Low-level humidity observations have been found to have important impacts on the analysis and to produce positive impacts on forecast scores over the tropics.
Abstract
An evaluation of precipitation and evapotranspiration simulated by mesoscale models is carried out within the African Monsoon Multidisciplinary Analysis (AMMA) program. Six models performed simulations of a mesoscale convective system (MCS) observed to cross part of West Africa in August 2005.
Initial and boundary conditions are found to significantly control the locations of rainfall at synoptic scales as simulated with either mesoscale or global models. When initialized and forced at their boundaries by the same analysis, all models forecast a westward-moving rainfall structure, as observed by satellite products. However, rainfall is also forecast at other locations where none was observed, and the nighttime northward propagation of rainfall is not well reproduced. There is a wide spread in the rainfall rates across simulations, but also among satellite products.
The range of simulated meridional fluctuations of evapotranspiration (E) appears reasonable, but E displays an overly strong zonal symmetry. Offline land surface modeling and surface energy budget considerations show that errors in the simulated E are not simply related to errors in the surface evaporative fraction, and involve the significant impact of cloud cover on the incoming surface shortwave flux.
The use of higher horizontal resolution (a few km) enhances the variability of precipitation, evapotranspiration, and precipitable water (PW) at the mesoscale. It also leads to a weakening of the daytime precipitation, less evapotranspiration, and smaller PW amounts. The simulated MCS propagates farther northward and somewhat faster within an overall drier atmosphere. These changes are associated with a strengthening of the links between PW and precipitation.
Abstract
An evaluation of precipitation and evapotranspiration simulated by mesoscale models is carried out within the African Monsoon Multidisciplinary Analysis (AMMA) program. Six models performed simulations of a mesoscale convective system (MCS) observed to cross part of West Africa in August 2005.
Initial and boundary conditions are found to significantly control the locations of rainfall at synoptic scales as simulated with either mesoscale or global models. When initialized and forced at their boundaries by the same analysis, all models forecast a westward-moving rainfall structure, as observed by satellite products. However, rainfall is also forecast at other locations where none was observed, and the nighttime northward propagation of rainfall is not well reproduced. There is a wide spread in the rainfall rates across simulations, but also among satellite products.
The range of simulated meridional fluctuations of evapotranspiration (E) appears reasonable, but E displays an overly strong zonal symmetry. Offline land surface modeling and surface energy budget considerations show that errors in the simulated E are not simply related to errors in the surface evaporative fraction, and involve the significant impact of cloud cover on the incoming surface shortwave flux.
The use of higher horizontal resolution (a few km) enhances the variability of precipitation, evapotranspiration, and precipitable water (PW) at the mesoscale. It also leads to a weakening of the daytime precipitation, less evapotranspiration, and smaller PW amounts. The simulated MCS propagates farther northward and somewhat faster within an overall drier atmosphere. These changes are associated with a strengthening of the links between PW and precipitation.
The Mediterranean region is frequently affected by heavy precipitation events associated with flash floods, landslides, and mudslides that cause hundreds of millions of euros in damages per year and, often, casualties. A major field campaign was devoted to heavy precipitation and f lash f loods from 5 September to 6 November 2012 within the framework of the 10-yr international Hydrological Cycle in the Mediterranean Experiment (HyMeX) dedicated to the hydrological cycle and related high-impact events. The 2-month field campaign took place over the northwestern Mediterranean Sea and its surrounding coastal regions in France, Italy, and Spain. The observation strategy of the field experiment was devised to improve knowledge of the following key components leading to heavy precipitation and flash flooding in the region: 1) the marine atmospheric f lows that transport moist and conditionally unstable air toward the coasts, 2) the Mediterranean Sea acting as a moisture and energy source, 3) the dynamics and microphysics of the convective systems producing heavy precipitation, and 4) the hydrological processes during flash floods. This article provides the rationale for developing this first HyMeX field experiment and an overview of its design and execution. Highlights of some intensive observation periods illustrate the potential of the unique datasets collected for process understanding, model improvement, and data assimilation.
The Mediterranean region is frequently affected by heavy precipitation events associated with flash floods, landslides, and mudslides that cause hundreds of millions of euros in damages per year and, often, casualties. A major field campaign was devoted to heavy precipitation and f lash f loods from 5 September to 6 November 2012 within the framework of the 10-yr international Hydrological Cycle in the Mediterranean Experiment (HyMeX) dedicated to the hydrological cycle and related high-impact events. The 2-month field campaign took place over the northwestern Mediterranean Sea and its surrounding coastal regions in France, Italy, and Spain. The observation strategy of the field experiment was devised to improve knowledge of the following key components leading to heavy precipitation and flash flooding in the region: 1) the marine atmospheric f lows that transport moist and conditionally unstable air toward the coasts, 2) the Mediterranean Sea acting as a moisture and energy source, 3) the dynamics and microphysics of the convective systems producing heavy precipitation, and 4) the hydrological processes during flash floods. This article provides the rationale for developing this first HyMeX field experiment and an overview of its design and execution. Highlights of some intensive observation periods illustrate the potential of the unique datasets collected for process understanding, model improvement, and data assimilation.
