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- Author or Editor: Florence Rabier x
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Abstract
To improve the assimilation of Advanced Microwave Sounding Unit-A and -B (AMSU-A and -B) observations over land, three methods, based either on an estimation of the land emissivity or the land skin temperature directly from satellite observations, have been developed. Some feasibility studies have been performed in the Météo-France assimilation system in order to choose the most appropriate method for the system. This study reports on three 2-month assimilation and forecast experiments that use different methods to estimate AMSU-A and -B land emissivities together with the operational run as a control experiment. The experiments and the control have been subjected to several comparisons. The performance of the observation operator for simulating window channel brightness temperatures has been studied. The study shows considerable improvements in the statistics of the window channels’ first-guess departures (bias, standard deviation). The correlations between the observations and the model’s simulations have also been improved, especially over snow-covered areas. The performances of the assimilation system, in terms of cost function change, have been examined: the cost function is generally improved during the screening and remains stable during the minimization. Moreover, comparisons have been made in terms of impacts on both analyses and forecasts.
Abstract
To improve the assimilation of Advanced Microwave Sounding Unit-A and -B (AMSU-A and -B) observations over land, three methods, based either on an estimation of the land emissivity or the land skin temperature directly from satellite observations, have been developed. Some feasibility studies have been performed in the Météo-France assimilation system in order to choose the most appropriate method for the system. This study reports on three 2-month assimilation and forecast experiments that use different methods to estimate AMSU-A and -B land emissivities together with the operational run as a control experiment. The experiments and the control have been subjected to several comparisons. The performance of the observation operator for simulating window channel brightness temperatures has been studied. The study shows considerable improvements in the statistics of the window channels’ first-guess departures (bias, standard deviation). The correlations between the observations and the model’s simulations have also been improved, especially over snow-covered areas. The performances of the assimilation system, in terms of cost function change, have been examined: the cost function is generally improved during the screening and remains stable during the minimization. Moreover, comparisons have been made in terms of impacts on both analyses and forecasts.
Abstract
The aim of this study is to test the feasibility of assimilating microwave observations from the Advanced Microwave Sounding Units (AMSU-A and AMSU-B) through the implementation of an appropriate parameterization of sea ice emissivity. AMSU observations are relevant to the description of air temperature and humidity, and their assimilation into numerical weather prediction (NWP) helps better constrain models in regions where very few observations are assimilated. A sea ice emissivity model suitable for AMSU-A and AMSU-B data is described in this paper and its impact is studied through two assimilation experiments run during the period of the Arctic winter. The first experiment is representative of the operational version of the Météo-France NWP model whereas the second simulation uses the sea ice emissivity parameterization and assimilates a selection of AMSU channels above polar regions. The assimilation of AMSU observations over sea ice is shown to have a significant effect on atmospheric analyses (in particular those of temperature and humidity). The effect on temperature induces a warming in the lower troposphere, especially around 850 hPa. This leads to an increase in the Arctic inversion strength over the ice cap by almost 2 K. An improvement in medium-range forecasts is also noticed when the NWP model assimilates AMSU observations over sea ice.
Abstract
The aim of this study is to test the feasibility of assimilating microwave observations from the Advanced Microwave Sounding Units (AMSU-A and AMSU-B) through the implementation of an appropriate parameterization of sea ice emissivity. AMSU observations are relevant to the description of air temperature and humidity, and their assimilation into numerical weather prediction (NWP) helps better constrain models in regions where very few observations are assimilated. A sea ice emissivity model suitable for AMSU-A and AMSU-B data is described in this paper and its impact is studied through two assimilation experiments run during the period of the Arctic winter. The first experiment is representative of the operational version of the Météo-France NWP model whereas the second simulation uses the sea ice emissivity parameterization and assimilates a selection of AMSU channels above polar regions. The assimilation of AMSU observations over sea ice is shown to have a significant effect on atmospheric analyses (in particular those of temperature and humidity). The effect on temperature induces a warming in the lower troposphere, especially around 850 hPa. This leads to an increase in the Arctic inversion strength over the ice cap by almost 2 K. An improvement in medium-range forecasts is also noticed when the NWP model assimilates AMSU observations over sea ice.
Abstract
The Concordiasi field experiment, which is taking place in Antarctica, involves the launching of radiosoundings and stratospheric balloons. One of the main goals of this campaign is the validation of the Infrared Atmospheric Sounding Interferometer (IASI) radiance assimilation. Prior to the campaign, it was necessary to improve satellite data assimilation at high latitudes. Two types of sensors, microwave and infrared, have been considered to help with this issue. A major problem associated with microwave satellite data is the calculation of the surface emissivity. An innovative approach, based on satellite observations, improves the surface emissivity modeling over land and sea ice within the constraints of the four-dimensional variational data assimilation (4D-VAR) system. With this new calculation of emissivity, it has been possible to include many more microwave observations during the assimilation. In this study, this method has been applied to high latitudes, after some adjustments have been made to assimilate additional Advanced Microwave Sounding Unit-A/B (AMSU-A/B) data over sea ice and snow. The use of additional data from IASI and the Atmospheric Infrared Sounder (AIRS) sensors over land and sea ice has also been tested. The use of the microwave and infrared data over this polar area has modified the dynamical and thermodynamical model fields such as the snow precipitation quantity. Additional data have been found to have a positive impact on the skill of a model specially tuned for Antarctica.
Abstract
The Concordiasi field experiment, which is taking place in Antarctica, involves the launching of radiosoundings and stratospheric balloons. One of the main goals of this campaign is the validation of the Infrared Atmospheric Sounding Interferometer (IASI) radiance assimilation. Prior to the campaign, it was necessary to improve satellite data assimilation at high latitudes. Two types of sensors, microwave and infrared, have been considered to help with this issue. A major problem associated with microwave satellite data is the calculation of the surface emissivity. An innovative approach, based on satellite observations, improves the surface emissivity modeling over land and sea ice within the constraints of the four-dimensional variational data assimilation (4D-VAR) system. With this new calculation of emissivity, it has been possible to include many more microwave observations during the assimilation. In this study, this method has been applied to high latitudes, after some adjustments have been made to assimilate additional Advanced Microwave Sounding Unit-A/B (AMSU-A/B) data over sea ice and snow. The use of additional data from IASI and the Atmospheric Infrared Sounder (AIRS) sensors over land and sea ice has also been tested. The use of the microwave and infrared data over this polar area has modified the dynamical and thermodynamical model fields such as the snow precipitation quantity. Additional data have been found to have a positive impact on the skill of a model specially tuned for Antarctica.
Abstract
An approach to make use of Atmospheric Infrared Sounder (AIRS) cloud-affected infrared radiances has been developed at Météo-France in the context of the global numerical weather prediction model. The method is based on (i) the detection and the characterization of clouds by the CO2-slicing algorithm and (ii) the identification of clear–cloudy channels using the ECMWF cloud-detection scheme. Once a hypothetical cloud-affected pixel is detected by the CO2-slicing scheme, the cloud-top pressure and the effective cloud fraction are provided to the radiative transfer model simultaneously with other atmospheric variables to simulate cloud-affected radiances. Furthermore, the ECMWF scheme flags each channel of the pixel as clear or cloudy. In the current configuration of the assimilation scheme, channels affected by clouds whose cloud-top pressure ranges between 600 and 950 hPa are assimilated over sea in addition to clear channels. Results of assimilation experiments are presented. On average, 3.5% of additional pixels are assimilated over the globe but additional assimilated channels are much more numerous for mid- to high latitudes (10% of additional assimilated channels on average). Encouraging results are found in the quality of the analyses: background departures of AIRS observations are reduced, especially for surface channels, which are globally 4 times smaller, and the analysis better fits some conventional and satellite data. Global forecasts are slightly improved for the geopotential field. These improvements are significant up to the 72-h forecast range. Predictability improvements have been obtained for a case study: a low pressure system that affected the southeastern part of Italy in September 2006. The trajectory, intensity, and the whole development of the cyclogenesis are better predicted, whatever the forecast range, for this case study.
Abstract
An approach to make use of Atmospheric Infrared Sounder (AIRS) cloud-affected infrared radiances has been developed at Météo-France in the context of the global numerical weather prediction model. The method is based on (i) the detection and the characterization of clouds by the CO2-slicing algorithm and (ii) the identification of clear–cloudy channels using the ECMWF cloud-detection scheme. Once a hypothetical cloud-affected pixel is detected by the CO2-slicing scheme, the cloud-top pressure and the effective cloud fraction are provided to the radiative transfer model simultaneously with other atmospheric variables to simulate cloud-affected radiances. Furthermore, the ECMWF scheme flags each channel of the pixel as clear or cloudy. In the current configuration of the assimilation scheme, channels affected by clouds whose cloud-top pressure ranges between 600 and 950 hPa are assimilated over sea in addition to clear channels. Results of assimilation experiments are presented. On average, 3.5% of additional pixels are assimilated over the globe but additional assimilated channels are much more numerous for mid- to high latitudes (10% of additional assimilated channels on average). Encouraging results are found in the quality of the analyses: background departures of AIRS observations are reduced, especially for surface channels, which are globally 4 times smaller, and the analysis better fits some conventional and satellite data. Global forecasts are slightly improved for the geopotential field. These improvements are significant up to the 72-h forecast range. Predictability improvements have been obtained for a case study: a low pressure system that affected the southeastern part of Italy in September 2006. The trajectory, intensity, and the whole development of the cyclogenesis are better predicted, whatever the forecast range, for this case study.
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
During the international African Monsoon Multidisciplinary Analysis (AMMA) project, stratospheric balloons carrying gondolas called driftsondes capable of dropping meteorological sondes were deployed over West Africa and the tropical Atlantic Ocean. The goals of the deployment were to test the technology and to study the African easterly waves, which are often the forerunners of hurricanes. Between 29 August and 22 September 2006, 124 sondes were dropped over the seven easterly waves that moved across Africa into the Atlantic between about 10° and 20°N, where almost no in situ vertical information exists. Conditions included waves that developed into Tropical Storm Florence and Hurricanes Gordon and Helene. In this study, a selection of numerical weather prediction model outputs has been compared with the dropsondes to assess the effect of some developments in data assimilation on the quality of analyses and forecasts. By comparing two different versions of the Action de Recherche Petite Echelle Grande Echelle (ARPEGE) model of Météo-France with the dropsondes, first the benefits of the last data assimilation updates are quantified. Then comparisons are carried out using the ARPEGE model and the Integrated Forecast System (IFS) model of the European Centre for Medium-Range Weather Forecasts. It is shown that the two models represent very well the vertical structure of temperature and humidity over both land and sea, and particularly within the Saharan air layer, which displays humidity below 5%–10%. Conversely, the models are less able to represent the vertical structure of the meridional wind. This problem seems to be common to ARPEGE and IFS, and its understanding still requires further investigations.
Abstract
During the international African Monsoon Multidisciplinary Analysis (AMMA) project, stratospheric balloons carrying gondolas called driftsondes capable of dropping meteorological sondes were deployed over West Africa and the tropical Atlantic Ocean. The goals of the deployment were to test the technology and to study the African easterly waves, which are often the forerunners of hurricanes. Between 29 August and 22 September 2006, 124 sondes were dropped over the seven easterly waves that moved across Africa into the Atlantic between about 10° and 20°N, where almost no in situ vertical information exists. Conditions included waves that developed into Tropical Storm Florence and Hurricanes Gordon and Helene. In this study, a selection of numerical weather prediction model outputs has been compared with the dropsondes to assess the effect of some developments in data assimilation on the quality of analyses and forecasts. By comparing two different versions of the Action de Recherche Petite Echelle Grande Echelle (ARPEGE) model of Météo-France with the dropsondes, first the benefits of the last data assimilation updates are quantified. Then comparisons are carried out using the ARPEGE model and the Integrated Forecast System (IFS) model of the European Centre for Medium-Range Weather Forecasts. It is shown that the two models represent very well the vertical structure of temperature and humidity over both land and sea, and particularly within the Saharan air layer, which displays humidity below 5%–10%. Conversely, the models are less able to represent the vertical structure of the meridional wind. This problem seems to be common to ARPEGE and IFS, and its understanding still requires further investigations.
Constellations of driftsonde systems— gondolas floating in the stratosphere and able to release dropsondes upon command— have so far been used in three major field experiments from 2006 through 2010. With them, high-quality, high-resolution, in situ atmospheric profiles were made over extended periods in regions that are otherwise very difficult to observe. The measurements have unique value for verifying and evaluating numerical weather prediction models and global data assimilation systems; they can be a valuable resource to validate data from remote sensing instruments, especially on satellites, but also airborne or ground-based remote sensors. These applications for models and remote sensors result in a powerful combination for improving data assimilation systems. Driftsondes also can support process studies in otherwise difficult locations—for example, to study factors that control the development or decay of a tropical disturbance, or to investigate the lower boundary layer over the interior Antarctic continent. The driftsonde system is now a mature and robust observing system that can be combined with flight-level data to conduct multidisciplinary research at heights well above that reached by current research aircraft. In this article we describe the development and capabilities of the driftsonde system, the exemplary science resulting from its use to date, and some future applications.
Constellations of driftsonde systems— gondolas floating in the stratosphere and able to release dropsondes upon command— have so far been used in three major field experiments from 2006 through 2010. With them, high-quality, high-resolution, in situ atmospheric profiles were made over extended periods in regions that are otherwise very difficult to observe. The measurements have unique value for verifying and evaluating numerical weather prediction models and global data assimilation systems; they can be a valuable resource to validate data from remote sensing instruments, especially on satellites, but also airborne or ground-based remote sensors. These applications for models and remote sensors result in a powerful combination for improving data assimilation systems. Driftsondes also can support process studies in otherwise difficult locations—for example, to study factors that control the development or decay of a tropical disturbance, or to investigate the lower boundary layer over the interior Antarctic continent. The driftsonde system is now a mature and robust observing system that can be combined with flight-level data to conduct multidisciplinary research at heights well above that reached by current research aircraft. In this article we describe the development and capabilities of the driftsonde system, the exemplary science resulting from its use to date, and some future applications.
The Concordiasi project is making innovative observations of the atmosphere above Antarctica. The most important goals of the Concordiasi are as follows:
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To enhance the accuracy of weather prediction and climate records in Antarctica through the assimilation of in situ and satellite data, with an emphasis on data provided by hyperspectral infrared sounders. The focus is on clouds, precipitation, and the mass budget of the ice sheets. The improvements in dynamical model analyses and forecasts will be used in chemical-transport models that describe the links between the polar vortex dynamics and ozone depletion, and to advance the under understanding of the Earth system by examining the interactions between Antarctica and lower latitudes.
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To improve our understanding of microphysical and dynamical processes controlling the polar ozone, by providing the first quasi-Lagrangian observations of stratospheric ozone and particles, in addition to an improved characterization of the 3D polar vortex dynamics. Techniques for assimilating these Lagrangian observations are being developed.
A major Concordiasi component is a field experiment during the austral springs of 2008–10. The field activities in 2010 are based on a constellation of up to 18 long-duration stratospheric super-pressure balloons (SPBs) deployed from the McMurdo station. Six of these balloons will carry GPS receivers and in situ instruments measuring temperature, pressure, ozone, and particles. Twelve of the balloons will release dropsondes on demand for measuring atmospheric parameters. Lastly, radiosounding measurements are collected at various sites, including the Concordia station.
The Concordiasi project is making innovative observations of the atmosphere above Antarctica. The most important goals of the Concordiasi are as follows:
-
To enhance the accuracy of weather prediction and climate records in Antarctica through the assimilation of in situ and satellite data, with an emphasis on data provided by hyperspectral infrared sounders. The focus is on clouds, precipitation, and the mass budget of the ice sheets. The improvements in dynamical model analyses and forecasts will be used in chemical-transport models that describe the links between the polar vortex dynamics and ozone depletion, and to advance the under understanding of the Earth system by examining the interactions between Antarctica and lower latitudes.
-
To improve our understanding of microphysical and dynamical processes controlling the polar ozone, by providing the first quasi-Lagrangian observations of stratospheric ozone and particles, in addition to an improved characterization of the 3D polar vortex dynamics. Techniques for assimilating these Lagrangian observations are being developed.
A major Concordiasi component is a field experiment during the austral springs of 2008–10. The field activities in 2010 are based on a constellation of up to 18 long-duration stratospheric super-pressure balloons (SPBs) deployed from the McMurdo station. Six of these balloons will carry GPS receivers and in situ instruments measuring temperature, pressure, ozone, and particles. Twelve of the balloons will release dropsondes on demand for measuring atmospheric parameters. Lastly, radiosounding measurements are collected at various sites, including the Concordia station.
