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- Author or Editor: Peter Schlüssel x
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Abstract
Heat and gas transport in molecular sublayers at the air-sea interface is governed by similar laws. A model of renewal type based on the physics of molecular sublayers allows the derivation of a parameterization of the temperature difference across the cool skin of the ocean and of the coefficient of the direct air-sea gas transfer. The surface Richardson number controls the transition from convective instability to wind-induced instability (“rollers” on breaking wavelets) and the Keulegan number controls the transition from the regime of rollers to long-wave breaking. A critical value of the surface Richardson number and of a nondimensional constant can be evaluated by comparing the parameterizations of the cool skin with field data. The critical value of the Keulegan number is determined from the wind speed at which long-wave breaking appears. The parameterizations have been compared with cool skin data obtained from campaigns in the tropical and subtropical Atlantic Ocean, while the gas transfer data are compiled from several experiments in the global ocean. The cool skin data have been used for an adjustment of the parameterization of the direct gas transfer. The parameterization does not include effects of bubble and droplet production in whitecaps, which can be important at high wind speed conditions.
Abstract
Heat and gas transport in molecular sublayers at the air-sea interface is governed by similar laws. A model of renewal type based on the physics of molecular sublayers allows the derivation of a parameterization of the temperature difference across the cool skin of the ocean and of the coefficient of the direct air-sea gas transfer. The surface Richardson number controls the transition from convective instability to wind-induced instability (“rollers” on breaking wavelets) and the Keulegan number controls the transition from the regime of rollers to long-wave breaking. A critical value of the surface Richardson number and of a nondimensional constant can be evaluated by comparing the parameterizations of the cool skin with field data. The critical value of the Keulegan number is determined from the wind speed at which long-wave breaking appears. The parameterizations have been compared with cool skin data obtained from campaigns in the tropical and subtropical Atlantic Ocean, while the gas transfer data are compiled from several experiments in the global ocean. The cool skin data have been used for an adjustment of the parameterization of the direct gas transfer. The parameterization does not include effects of bubble and droplet production in whitecaps, which can be important at high wind speed conditions.
Abstract
A method of determining ocean–atmosphere latent heat flux using the Special Sensor Microwave/Imager (SSM/I) and the Advanced Very High Resolution Radiometer (AVHRR) is presented and evaluated. While sea surface temperatures are retrieved from AVHRR data with an accuracy of 0.5–1.0 K, the near-surface wind speed and the surface air humidity are retrieved from measurements of the SSM/I with accuracies of 1.4 m s−1 and 1.1 g kg−1, respectively. The latent heat flux is then computed with a stability-dependent bulk parameterization model. The derived fluxes are compared to globally distributed instantaneous shipboard and buoy measurements and to monthly averages of 2° × 2° longitude and latitude bins. The standard error for instantaneous flux estimates is approximately 30 W m−2, and that for monthly averages decreases to 15 W m−2. Additionally, a 1-yr time series of latent heat flux at the weathership M in the North Atlantic and two shorter time series during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) and the Central Equatorial Pacific Experiment (CEPEX) in the tropical Pacific are compared to satellite measurements. The SSM/I-derived parameters, as well as the latent heat flux, are represented very well on the weathership M. During TOGA COARE and CEPEX, the near-surface humidity is sometimes systematically overestimated in the warm pool region, which results in an underestimation of the latent heat flux. Nevertheless, the representation of the latent heat flux is always in the range of the in situ measurements.
Abstract
A method of determining ocean–atmosphere latent heat flux using the Special Sensor Microwave/Imager (SSM/I) and the Advanced Very High Resolution Radiometer (AVHRR) is presented and evaluated. While sea surface temperatures are retrieved from AVHRR data with an accuracy of 0.5–1.0 K, the near-surface wind speed and the surface air humidity are retrieved from measurements of the SSM/I with accuracies of 1.4 m s−1 and 1.1 g kg−1, respectively. The latent heat flux is then computed with a stability-dependent bulk parameterization model. The derived fluxes are compared to globally distributed instantaneous shipboard and buoy measurements and to monthly averages of 2° × 2° longitude and latitude bins. The standard error for instantaneous flux estimates is approximately 30 W m−2, and that for monthly averages decreases to 15 W m−2. Additionally, a 1-yr time series of latent heat flux at the weathership M in the North Atlantic and two shorter time series during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) and the Central Equatorial Pacific Experiment (CEPEX) in the tropical Pacific are compared to satellite measurements. The SSM/I-derived parameters, as well as the latent heat flux, are represented very well on the weathership M. During TOGA COARE and CEPEX, the near-surface humidity is sometimes systematically overestimated in the warm pool region, which results in an underestimation of the latent heat flux. Nevertheless, the representation of the latent heat flux is always in the range of the in situ measurements.
Abstract
This paper deals with the dynamical aspect of variational data assimilation in the tropics and the role of the background-error covariances in the observing system simulation experiments for the tropics. The study uses a model that describes the horizontal structure of the potential temperature and wind fields in regions of deep tropical convection. The assimilation method is three- and four-dimensional variational data assimilation. The background-error covariance model for the assimilation is a multivariate model that includes the mass–wind couplings representative of equatorial inertio-gravity modes and equatorial Kelvin and mixed Rossby–gravity modes in addition to those representative of balanced equatorial Rossby waves. Spectra of the background errors based on these waves are derived from the tropical forecast errors of the European Centre for Medium-Range Weather Forecasts (ECMWF) model.
Tropical mass–wind (im)balances are illustrated by studying the potential impact of the spaceborne Doppler wind lidar (DWL) Atmospheric Dynamic Mission (ADM)-Aeolus, which measures horizontal line-of-sight (LOS) wind components. Several scenarios with two DWLs of ADM-Aeolus type are compared under different flow conditions and using different assumptions about the quality of the background-error covariances.
Results of three-dimensional variational data assimilation (3DVAR) illustrate the inefficiency of multivariate assimilation in the tropics. The consequence for the assimilation of LOS winds is that the missing part of the wind vector can hardly be reconstructed from the mass-field observations and applied balances as in the case of the midlatitudes.
Results of four-dimensional variational data assimilation (4DVAR) show that for large-scale tropical conditions and using reliable background-error statistics, differences among various DWL scenarios are not large. As the background-error covariances becomes less reliable, horizontal scales become smaller and the flow becomes less zonal, the importance of obtaining information about the wind vector increases. The added value of another DWL satellite increases as the quality of the background-error covariances deteriorates and it can be more than twice as large as in the case of reliable covariances.
Abstract
This paper deals with the dynamical aspect of variational data assimilation in the tropics and the role of the background-error covariances in the observing system simulation experiments for the tropics. The study uses a model that describes the horizontal structure of the potential temperature and wind fields in regions of deep tropical convection. The assimilation method is three- and four-dimensional variational data assimilation. The background-error covariance model for the assimilation is a multivariate model that includes the mass–wind couplings representative of equatorial inertio-gravity modes and equatorial Kelvin and mixed Rossby–gravity modes in addition to those representative of balanced equatorial Rossby waves. Spectra of the background errors based on these waves are derived from the tropical forecast errors of the European Centre for Medium-Range Weather Forecasts (ECMWF) model.
Tropical mass–wind (im)balances are illustrated by studying the potential impact of the spaceborne Doppler wind lidar (DWL) Atmospheric Dynamic Mission (ADM)-Aeolus, which measures horizontal line-of-sight (LOS) wind components. Several scenarios with two DWLs of ADM-Aeolus type are compared under different flow conditions and using different assumptions about the quality of the background-error covariances.
Results of three-dimensional variational data assimilation (3DVAR) illustrate the inefficiency of multivariate assimilation in the tropics. The consequence for the assimilation of LOS winds is that the missing part of the wind vector can hardly be reconstructed from the mass-field observations and applied balances as in the case of the midlatitudes.
Results of four-dimensional variational data assimilation (4DVAR) show that for large-scale tropical conditions and using reliable background-error statistics, differences among various DWL scenarios are not large. As the background-error covariances becomes less reliable, horizontal scales become smaller and the flow becomes less zonal, the importance of obtaining information about the wind vector increases. The added value of another DWL satellite increases as the quality of the background-error covariances deteriorates and it can be more than twice as large as in the case of reliable covariances.
Abstract
Land surface temperature and emissivity spectra are essential variables for improving models of the earth surface–atmosphere interaction or retrievals of atmospheric variables such as thermodynamic profiles, chemical composition, cloud and aerosol characteristics, and so on. In most cases, emissivity spectral variations are not correctly taken into account in climate models, leading to potentially significant errors in the estimation of surface energy fluxes and temperature. Satellite infrared observations offer the dual opportunity of accurately estimating these properties of land surfaces as well as allowing a global coverage in space and time. Here, high-spectral-resolution observations from the Infrared Atmospheric Sounder Interferometer (IASI) over the tropics (30°N–30°S), covering the period July 2007–March 2011, are interpreted in terms of 1° × 1° monthly mean surface skin temperature and emissivity spectra from 3.7 to 14 μm at a resolution of 0.05 μm. The standard deviation estimated for the surface temperature is about 1.3 K. For the surface emissivity, it varies from about 1%–1.5% for the 10.5–14- and 5.5–8-μm windows to about 4% around 4 μm. Results from comparisons with products such as Moderate Resolution Imaging Spectroradiometer (MODIS) low-resolution emissivity and surface temperature or ECMWF forecast data (temperature only) are presented and discussed. Comparisons with emissivity derived from the Airborne Research Interferometer Evaluation System (ARIES) radiances collected during an aircraft campaign over Oman and made at the scale of the IASI field of view offer valuable data for the validation of the IASI retrievals.
Abstract
Land surface temperature and emissivity spectra are essential variables for improving models of the earth surface–atmosphere interaction or retrievals of atmospheric variables such as thermodynamic profiles, chemical composition, cloud and aerosol characteristics, and so on. In most cases, emissivity spectral variations are not correctly taken into account in climate models, leading to potentially significant errors in the estimation of surface energy fluxes and temperature. Satellite infrared observations offer the dual opportunity of accurately estimating these properties of land surfaces as well as allowing a global coverage in space and time. Here, high-spectral-resolution observations from the Infrared Atmospheric Sounder Interferometer (IASI) over the tropics (30°N–30°S), covering the period July 2007–March 2011, are interpreted in terms of 1° × 1° monthly mean surface skin temperature and emissivity spectra from 3.7 to 14 μm at a resolution of 0.05 μm. The standard deviation estimated for the surface temperature is about 1.3 K. For the surface emissivity, it varies from about 1%–1.5% for the 10.5–14- and 5.5–8-μm windows to about 4% around 4 μm. Results from comparisons with products such as Moderate Resolution Imaging Spectroradiometer (MODIS) low-resolution emissivity and surface temperature or ECMWF forecast data (temperature only) are presented and discussed. Comparisons with emissivity derived from the Airborne Research Interferometer Evaluation System (ARIES) radiances collected during an aircraft campaign over Oman and made at the scale of the IASI field of view offer valuable data for the validation of the IASI retrievals.
Abstract
The observed and predicted response of the bulk – skin sea surface temperature difference (δT) to changes in the wind speed and net heat flux is analyzed. Observations of δT from the northern Atlantic and tropical Pacific Oceans demonstrate that the wind speed affects δT through the net heat flux and turbulent mixing. Increased winds typically increase the net heat flux, which increases the size of δT. At the same time, increased winds cause enhanced mixing, which decreases the size of δT. To predict the net change to δT, both effects must be properly modeled. The theoretical development of existing models for δT is traced and compared. All the models can be similarly derived from surface renewal theory with their differences resulting only from the corresponding definition of the dissipation rate. The differences are manifested in the predicted dependence of δT on the wind speed. The predicted δT values and wind speed dependencies are evaluated with the available δT observations to determine the most accurate approach. A new model for δT is developed to better reproduce the observed behavior of δT. The new model follows from surface renewal theory and includes timescales for both the shear-driven and free convection regimes. The model is shown to accurately reproduce both aspects of the observed effect of wind speed on δT and predict the value of δT to better than 0.1 K.
Abstract
The observed and predicted response of the bulk – skin sea surface temperature difference (δT) to changes in the wind speed and net heat flux is analyzed. Observations of δT from the northern Atlantic and tropical Pacific Oceans demonstrate that the wind speed affects δT through the net heat flux and turbulent mixing. Increased winds typically increase the net heat flux, which increases the size of δT. At the same time, increased winds cause enhanced mixing, which decreases the size of δT. To predict the net change to δT, both effects must be properly modeled. The theoretical development of existing models for δT is traced and compared. All the models can be similarly derived from surface renewal theory with their differences resulting only from the corresponding definition of the dissipation rate. The differences are manifested in the predicted dependence of δT on the wind speed. The predicted δT values and wind speed dependencies are evaluated with the available δT observations to determine the most accurate approach. A new model for δT is developed to better reproduce the observed behavior of δT. The new model follows from surface renewal theory and includes timescales for both the shear-driven and free convection regimes. The model is shown to accurately reproduce both aspects of the observed effect of wind speed on δT and predict the value of δT to better than 0.1 K.
The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System is the European contribution to the European–U.S. operational polar meteorological satellite system (Initial Joint Polar System). It serves the midmorning (a.m.) orbit 0930 Local Solar Time (LST) descending node. The EUMETSAT satellites of this new polar system are the Meteorological Operational Satellite (Metop) satellites, jointly developed with ESA. Three Metop satellites are foreseen for at least 14 years of operation from 2006 onward and will support operational meteorology and climate monitoring.
The Metop Programme includes the development of some instruments, such as the Global Ozone Monitoring Experiment, Advanced Scatterometer, and the Global Navigation Satellite System (GNSS) Receiver for Atmospheric Sounding, which are advanced instruments of recent successful research missions. Core components of the Metop payload, common with the payload on the U.S. satellites, are the Advanced Very High Resolution Radiometer and the Advanced Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (ATOVS) package, composed of the High Resolution Infrared Radiation Sounder (HIRS), Advanced Microwave Sounding Unit A (AMSU-A), and Microwave Humidity Sounder (MHS). They provide continuity to the NOAA-K, -L, -M satellite series (in orbit known as NOAA-15, -16 and -17). MHS is a EUMETSAT development and replaces the AMSU-B instrument in the ATOVS suite. The Infrared Atmospheric Sounding Interferometer (IASI) instrument, developed by the Centre National d'Etudes Spatiales, provides hyperspectral resolution infrared sounding capabilities and represents new technology in operational satellite remote sensing.
The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System is the European contribution to the European–U.S. operational polar meteorological satellite system (Initial Joint Polar System). It serves the midmorning (a.m.) orbit 0930 Local Solar Time (LST) descending node. The EUMETSAT satellites of this new polar system are the Meteorological Operational Satellite (Metop) satellites, jointly developed with ESA. Three Metop satellites are foreseen for at least 14 years of operation from 2006 onward and will support operational meteorology and climate monitoring.
The Metop Programme includes the development of some instruments, such as the Global Ozone Monitoring Experiment, Advanced Scatterometer, and the Global Navigation Satellite System (GNSS) Receiver for Atmospheric Sounding, which are advanced instruments of recent successful research missions. Core components of the Metop payload, common with the payload on the U.S. satellites, are the Advanced Very High Resolution Radiometer and the Advanced Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (ATOVS) package, composed of the High Resolution Infrared Radiation Sounder (HIRS), Advanced Microwave Sounding Unit A (AMSU-A), and Microwave Humidity Sounder (MHS). They provide continuity to the NOAA-K, -L, -M satellite series (in orbit known as NOAA-15, -16 and -17). MHS is a EUMETSAT development and replaces the AMSU-B instrument in the ATOVS suite. The Infrared Atmospheric Sounding Interferometer (IASI) instrument, developed by the Centre National d'Etudes Spatiales, provides hyperspectral resolution infrared sounding capabilities and represents new technology in operational satellite remote sensing.
