scholarly journals First Three Years of the Microwave Radiometer aboard Envisat: In-Flight Calibration, Processing, and Validation of the Geophysical Products

2006 ◽  
Vol 23 (6) ◽  
pp. 802-814 ◽  
Author(s):  
E. Obligis ◽  
L. Eymard ◽  
N. Tran ◽  
S. Labroue ◽  
P. Femenias
Keyword(s):  
Microwave Radiometer ◽  
Radiative Transfer Model ◽  
Altimeter Data ◽  
Transfer Model ◽  
Path Delay ◽  
Inversion Algorithm ◽  
Weather Forecasts ◽  
Brightness Temperatures ◽  
Medium Range ◽  
Satellite Altimeter Data

Abstract The Envisat microwave radiometer is designed to correct the satellite altimeter data for the excess path delay resulting from tropospheric humidity. Neural networks have been used to formulate the inversion algorithm to retrieve this quantity from the measured brightness temperatures. The learning database has been built with European Centre for Medium-Range Weather Forecasts (ECMWF) analyses and simulated brightness temperatures by a radiative transfer model. The in-flight calibration has been performed in a consistent way by adjusting measurements on simulated brightness temperatures. Finally, coincident radiosonde measurements are used to validate the Envisat wet-tropospheric correction, and this comparison shows the good performances of the method.

scholarly journals Long term Observations minus Background monitoring of ground-based microwave radiometer network. Part 1: Brightness Temperatures

2017 ◽  
Author(s):  
Francesco De Angelis ◽  
Domenico Cimini ◽  
Ulrich Löhnert ◽  
Olivier Caumont ◽  
Alexander Haefele ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Weather Prediction ◽  
Microwave Radiometer ◽  
Scale Model ◽  
Radiative Transfer Model ◽  
Line Center ◽  
High Temporal Resolution ◽  
Transfer Model ◽  
Observation Operator ◽  
Brightness Temperatures

Abstract. Ground-based microwave radiometers (MWRs) offer the capability to provide continuous, high-temporal resolution observations of the atmospheric thermodynamic state in the planetary boundary layer (PBL) with low maintenance. This makes MWR an ideal instrument to supplement radiosonde and satellite observations when initializing numerical weather prediction (NWP) models through data assimilation. State-of-the-art data assimilation systems (e.g., variational schemes) require an accurate representation of the differences between model (background) and observations, which are then weighted by their respective errors to provide the best analysis of the true atmospheric state. In this perspective, one source of information is contained in the statistics of the differences between observations and their background counterparts (O-B). Monitoring of O-B statistics is crucial to detect and remove systematic errors coming from the measurements, the observation operator, and/or the NWP model. This work illustrates a 1-year O-B analysis for MWR observations in clear sky conditions for an European-wide network of six MWRs. Observations include MWR brightness temperatures (TB) measured by the two most common types of MWR instruments. Background profiles are extracted from the French convective scale model AROME-France before being converted into TB. The observation operator used to map atmospheric profiles into TB is the fast radiative transfer model RTTOV-gb. It is shown that O-B monitoring can effectively detect instrument malfunctions. O-B statistics (bias, standard deviation and root-mean-square) for water vapor channels (22.24–30.0 GHz) are quite consistent for all the instrumental sites, decreasing from the 22.24 GHz line center (~ 2–2.5 K) towards the high-frequency wing (~ 0.8–1.3 K). Statistics for zenith and lower elevation observations show a similar trend, though values increase with increasing air mass. O-B statistics for temperature channels show different behaviour for relatively transparent (51–53 GHz) and opaque channels (54-58 GHz). Opaque channels show lower uncertainties (

scholarly journals An assessment of the accuracy of the RTTOV fast radiative transfer model using IASI data

2009 ◽  
Vol 9 (2) ◽  
pp. 9491-9535 ◽  
Author(s):  
M. Matricardi
Keyword(s):  
Radiative Transfer ◽  
Regression Coefficients ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Weather Forecasts ◽  
Medium Range ◽  
Forecasting System ◽  
Relative Differences ◽  
Temperature Water

Abstract. IASI measurements of spectral radiances made between the 1 April 2008 and the 15 April 2008 are compared with simulations performed using the RTTOV fast radiative transfer model utilizing regression coefficients based on different line-by-line models. The comparisons are performed within the framework of the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System using fields of temperature, water vapour and ozone obtained from short-range forecasts. Simulations are performed to assess the accuracy of the RTTOV computations and investigate relative differences between the line-by-line models and the quality of the spectroscopic databases on which the RTTOV coefficients are based.

scholarly journals Validation of brightness and physical temperature from two scanning microwave radiometers in the 60 GHz O<sub>2</sub>-band using radiosonde measurements

2016 ◽  
Author(s):  
Francisco Navas-Guzmán ◽  
Niklaus Kämpfer ◽  
Alexander Haefele
Keyword(s):  
Brightness Temperature ◽  
Microwave Radiometer ◽  
Estimation Method ◽  
Weather Conditions ◽  
Radiative Transfer Model ◽  
Inversion Method ◽  
Transfer Model ◽  
Tropospheric Temperature ◽  
60 Ghz ◽  
Inversion Algorithm

Abstract. In this paper, we address the assessment of the tropospheric performance of a new temperature radiometer (TEMPERA) at 60 GHz.With this goal, an intercomparison campaign was carried out at the aerological station of MeteoSwiss in Payerne (Swizerland). The brightness temperature and the tropospheric temperature were assessed by means of a comparison with simultaneous and collocated radiosondes which are launched twice a day at this station. In addition, the TEMPERA performances are compared with the ones from a commercial microwave radiometer (HATPRO) which has some different instrumental characteristics and uses a different inversion algorithm. Brightness temperatures from both radiometers were compared with the ones simulated using a radiative transfer model and atmospheric profiles from radiosondes. A total of 532 cases were analyzed under all weather conditions and evidenced larger brightness temperature deviations between the two radiometers and the radiosondes for the most transparent channels. Two different retrievals for the TEMPERA radiometer were implemented in order to evaluate the effect of the different channels on the temperature retrievals. The comparison with radiosondes evidenced better results and very similar to the ones from HATPRO when the 8 more opaques channels were used. The study shows the good performance of TEMPERA to retrieve temperature profiles in the troposphere. The inversion method of TEMPERA is based on the Optimal Estimation Method. The main advantage of this algorithm is that there is no necessity for radiosonde information to achieve good results in contrast to conventional methods as neuronal networks or lineal regression. Finally, an assessment of the effect of instrumental characteristics as the filter response and the antenna pattern on the brightness temperature showed that they can have an important impact on the most transparent channels.

scholarly journals Validation of brightness and physical temperature from two scanning microwave radiometers in the 60 GHz O<sub>2</sub> band using radiosonde measurements

2016 ◽  
Vol 9 (9) ◽  
pp. 4587-4600 ◽  
Author(s):  
Francisco Navas-Guzmán ◽  
Niklaus Kämpfer ◽  
Alexander Haefele
Keyword(s):  
Brightness Temperature ◽  
Microwave Radiometer ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Weather Conditions ◽  
Radiative Transfer Model ◽  
Inversion Method ◽  
Transfer Model ◽  
Tropospheric Temperature ◽  
Inversion Algorithm

Abstract. In this paper, we address the assessment of the tropospheric performance of a new temperature radiometer (TEMPERA) at 60 GHz. With this goal, an intercomparison campaign was carried out at the aerological station of MeteoSwiss in Payerne (Switzerland). The brightness temperature and the tropospheric temperature were assessed by means of a comparison with simultaneous and collocated radiosondes that are launched twice a day at this station. In addition, the TEMPERA performances are compared with the ones from a commercial microwave radiometer (HATPRO), which has some different instrumental characteristics and uses a different inversion algorithm. Brightness temperatures from both radiometers were compared with the ones simulated using a radiative transfer model and atmospheric profiles from radiosondes. A total of 532 cases were analyzed under all weather conditions and evidenced larger brightness temperature deviations between the two radiometers and the radiosondes for the most transparent channels. Two different retrievals for the TEMPERA radiometer were implemented in order to evaluate the effect of the different channels on the temperature retrievals. The comparison with radiosondes evidenced better results very similar to the ones from HATPRO, when the eight more opaque channels were used. The study shows the good performance of TEMPERA to retrieve temperature profiles in the troposphere. The inversion method of TEMPERA is based on the optimal estimation method. The main advantage of this algorithm is that there is no necessity for radiosonde information to achieve good results in contrast to conventional methods as neural networks or lineal regression. Finally, an assessment of the effect of instrumental characteristics as the filter response and the antenna pattern on the brightness temperature showed that they can have an important impact on the most transparent channels.

scholarly journals Technical Note: An assessment of the accuracy of the RTTOV fast radiative transfer model using IASI data

2009 ◽  
Vol 9 (18) ◽  
pp. 6899-6913 ◽  
Author(s):  
M. Matricardi
Keyword(s):  
Radiative Transfer ◽  
Technical Note ◽  
Regression Coefficients ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Weather Forecasts ◽  
Medium Range ◽  
Relative Differences ◽  
Temperature Water

Abstract. IASI measurements of spectral radiances made between the 1st April 2008 and the 15th April 2008 are compared with simulations performed using the RTTOV fast radiative transfer model utilizing regression coefficients based on different line-by-line models. The comparisons are performed within the framework of the European Centre for Medium-Range Weather Forecasts Integrated Forecast System using fields of temperature, water vapour and ozone obtained from short-range forecasts. Simulations are performed to assess the accuracy of the RTTOV computations and investigate relative differences between the line-by-line models and the quality of the spectroscopic databases on which the RTTOV coefficients are based.

scholarly journals A Satellite-Based Assessment of Upper-Tropospheric Water Vapor Measurements during AFWEX

2009 ◽  
Vol 48 (11) ◽  
pp. 2284-2294 ◽  
Author(s):  
Eui-Seok Chung ◽  
Brian J. Soden
Keyword(s):  
Water Vapor ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Raman Lidar ◽  
Test Bed ◽  
Upper Troposphere ◽  
Brightness Temperatures ◽  
Radiation Test ◽  
Humidity Measurements ◽  
Atmospheric Radiation Measurement

Abstract Consistency of upper-tropospheric water vapor measurements from a variety of state-of-the-art instruments was assessed using collocated Geostationary Operational Environmental Satellite-8 (GOES-8) 6.7-μm brightness temperatures as a common benchmark during the Atmospheric Radiation Measurement Program (ARM) First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) Water Vapor Experiment (AFWEX). To avoid uncertainties associated with the inversion of satellite-measured radiances into water vapor quantity, profiles of temperature and humidity observed from in situ, ground-based, and airborne instruments are inserted into a radiative transfer model to simulate the brightness temperature that the GOES-8 would have observed under those conditions (i.e., profile-to-radiance approach). Comparisons showed that Vaisala RS80-H radiosondes and Meteolabor Snow White chilled-mirror dewpoint hygrometers are systemically drier in the upper troposphere by ∼30%–40% relative to the GOES-8 measured upper-tropospheric humidity (UTH). By contrast, two ground-based Raman lidars (Cloud and Radiation Test Bed Raman lidar and scanning Raman lidar) and one airborne differential absorption lidar agree to within 10% of the GOES-8 measured UTH. These results indicate that upper-tropospheric water vapor can be monitored by these lidars and well-calibrated, stable geostationary satellites with an uncertainty of less than 10%, and that correction procedures are required to rectify the inherent deficiencies of humidity measurements in the upper troposphere from these radiosondes.

scholarly journals Comparison of measured brightness temperatures from SMOS with modelled ones from ORCHIDEE and H-TESSEL over the Iberian Peninsula

2015 ◽  
Vol 12 (12) ◽  
pp. 13019-13067
Author(s):  
A. Barella-Ortiz ◽  
J. Polcher ◽  
P. de Rosnay ◽  
M. Piles ◽  
E. Gelati
Keyword(s):  
Soil Moisture ◽  
Radiative Transfer ◽  
Iberian Peninsula ◽  
Land Surface ◽  
Function Analysis ◽  
Microwave Emission ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Brightness Temperatures

Abstract. L-Band radiometry is considered to be one of the most suitable techniques to estimate surface soil moisture by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm. The work exposed compares brightness temperatures measured by the Soil Moisture and Ocean Salinity (SMOS) mission to two different sets of modelled ones, over the Iberian Peninsula from 2010 to 2012. The latter were estimated using a radiative transfer model and state variables from two land surface models: (i) ORganising Carbon and Hydrology In Dynamic EcosystEms (ORCHIDEE) and (ii) Hydrology – Tiled ECMWF Scheme for Surface Exchanges over Land (H-TESSEL). The radiative transfer model used is the Community Microwave Emission Model (CMEM). A good agreement in the temporal evolution of measured and modelled brightness temperatures is observed. However, their spatial structures are not consistent between them. An Empirical Orthogonal Function analysis of the brightness temperature's error identifies a dominant structure over the South-West of the Iberian Peninsula which evolves during the year and is maximum in Fall and Winter. Hypotheses concerning forcing induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for it at the moment. Further hypotheses are proposed at the end of the paper.

Polar  Stratospheric Clouds detection at Belgrano II Antarctic station from DOAS measurements

2021 ◽  
Author(s):  
Laura Gómez Martín ◽  
Daniel Toledo ◽  
Margarita Yela ◽  
Cristina Prados-Román ◽  
José Antonio Adame ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Color Index ◽  
Radiative Transfer Model ◽  
Optical Absorption Spectroscopy ◽  
Transfer Model ◽  
Meteorological Model ◽  
Weather Forecasts ◽  
Stratospheric Temperature ◽  
Stratospheric Clouds

&lt;p&gt;&lt;span&gt;Ground-based zenith DOAS (Differential Optical Absorption Spectroscopy) measurements have been used to detect and estimate the altitude of PSCs over Belgrano II Antarctic station during the polar sunrise seasons of 2018 and 2019. The method used in this work studies the evolution of the color index (CI) during twilights. The CI has been defined here as the ratio of the recorded signal at 520 and 420 nm. In the presence of PSCs, the CI shows a maximum at a given solar zenith angle (SZA). The value of such SZA depends on the altitude of the PSC. By using a spherical Monte Carlo radiative transfer model (RTM), the method has been validated and a function relating the SZA of the CI maximum and the PSC altitude has been calculated. Model simulations also show that PSCs can be detected and their altitude can be estimated even in presence of optically thin tropospheric clouds or aerosols. Our results are in good agreement with the stratospheric temperature evolution obtained through the ERA5 data reanalysis from the global meteorological model ECMWF (European Centre for Medium Range Weather Forecasts) and the PSCs observations from CALIPSO (Cloud-Aerosol-Lidar and Infrared Pathfinder Satellite Observations).&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;The methodology used in this work could also be applied to foreseen and/or historical measurements obtained with ground-based spectrometers such e. g. the DOAS instruments dedicated to trace gas observation in Arctic and Antarctic sites. This would also allow to investigate the presence and long-term evolution of PSCs.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;&lt;strong&gt;Keywords: &lt;/strong&gt;Polar stratospheric clouds; color index; radiative transfer model; visible spectroscopy.&lt;/span&gt;&lt;/p&gt;

scholarly journals Effect of Structural Uncertainty in Passive Microwave Soil Moisture Retrieval Algorithm

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1225
Author(s):  
Lanka Karthikeyan ◽  
Ming Pan ◽  
Dasika Nagesh Kumar ◽  
Eric F. Wood
Keyword(s):  
Soil Moisture ◽  
Global Scale ◽  
Passive Microwave ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Structural Uncertainty ◽  
Three Solutions ◽  
Brightness Temperatures ◽  
Retrieval Algorithms

Passive microwave sensors use a radiative transfer model (RTM) to retrieve soil moisture (SM) using brightness temperatures (TB) at low microwave frequencies. Vegetation optical depth (VOD) is a key input to the RTM. Retrieval algorithms can analytically invert the RTM using dual-polarized TB measurements to retrieve the VOD and SM concurrently. Algorithms in this regard typically use the τ-ω types of models, which consist of two third-order polynomial equations and, thus, can have multiple solutions. Through this work, we find that uncertainty occurs due to the structural indeterminacy that is inherent in all τ-ω types of models in passive microwave SM retrieval algorithms. In the process, a new analytical solution for concurrent VOD and SM retrieval is presented, along with two widely used existing analytical solutions. All three solutions are applied to a fixed framework of RTM to retrieve VOD and SM on a global scale, using X-band Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) TB data. Results indicate that, with structural uncertainty, there ensues a noticeable impact on the VOD and SM retrievals. In an era where the sensitivity of retrieval algorithms is still being researched, we believe the structural indeterminacy of RTM identified here would contribute to uncertainty in the soil moisture retrievals.

scholarly journals Temporal variations of microwave brightness temperatures over Antarctica

1994 ◽  
Vol 20 ◽  
pp. 19-25 ◽  
Author(s):  
I. Sherjal ◽  
M. Fily
Keyword(s):  
Satellite Data ◽  
A Priori ◽  
Temporal Variations ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Brightness Temperatures ◽  
Surface Temperatures ◽  
Air Temperatures ◽  
Microwave Imager ◽  
Snow Temperature

Passive microwave brightness temperatures from the Special Sensor Microwave Imager (SSMI) are studied together with surface air temperatures from two Automatic Weather Stations (AWS) for the year 1989. One station is located on the East Antarctic plateau (Dome C) and the other on the Ross lee Shelf (Lettau).The satellite data for frequencies 19, 22 and 37 GHz with vertical polarization,centered on the two AWS stations, are studied. A simple thermodynamic model and asimple radiative-transfer model, that takes into account the snow temperature profile and assumes a constant annual emissivity, are proposed. The combination of these two models enables us to compute extinction coefficients, penetration depths and toretrieve the measured brightness temperature variations from the AWS surface temperatures. Afterwards, this model is reversed in order to retrieve the snow-surface temperatures from the satellite data. Results are promising but strong approximationsand a priori knowledge of the extinction coefficient are still needed at this point.

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