scholarly journals Optimal Estimation MSG-SEVIRI Clear-Sky Total Column Water Vapour Retrieval Using the Split Window Difference

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1256
Author(s):  
Jan El Kassar ◽  
Cintia Carbajal Henken ◽  
Rene Preusker ◽  
Jürgen Fischer
Keyword(s):  
Water Vapour ◽  
Large Scale ◽  
Pearson Correlation ◽  
Microwave Radiometer ◽  
Optimal Estimation ◽  
Forward Model ◽  
Observation Data ◽  
Atmospheric Conditions ◽  
Uncertainty Estimates ◽  
Total Column

A new algorithm for the retrieval of day-time total column water vapour (TCWV) from measurements of a MSG-SEVIRI (Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager) instrument is presented. The retrieval is based on a forward operator, at the core of which lies Radiative Transfer for TIROS Operational Vertical Sounder (RTTOV). This forward model relates TCWV and surface temperature to brightness temperatures in the split window at 11 and 12µm with the use of a first guess for temperature and humidity profiles from the ERA5 reanalysis. The forward model is then embedded in a full Optimal Estimation (OE) method, which yields pixel by pixel uncertainty estimates and performance indicators. The algorithm is applicable to any instrument which features the split window configuration, given a first guess for atmospheric conditions (i.e., from NWP) and an estimate of surface emissivity at 11 µm. The algorithm was developed within the framework of RealPEP (Near-Realtime Quantitative Precipitation Estimation and Prediction) in which the advancement of the estimation and nowcasting of extreme precipitation and flooding in Germany are studied. Thus, processing and validation has been limited to the German domain. Three independent ground-based TCWV observation data sets were used as reference, i.e., AERONET (Aerosol Robotic Network), GNSS Germany (Global Navigation Satellite System) and measurements from two MWR (Microwave Radiometer) sites. The validation concludes with good agreement, with absolute biases between 0.11 and 2.85 kg/m2, root mean square deviations (rmsds) between 1.63 and 3.24 kg/m2 and Pearson correlation coefficients ranging from 0.96 to 0.98. The retrievals uncertainty estimates were evaluated against AERONET. The comparison suggests that, in sum, uncertainties are estimated well, while still some error sources seem to be over- and underestimated. In limited case studies it could be shown that SEVIRI TCWV is capable to both display large scale variabilities in water vapour fields and reproduce the daily course of water vapour exposed by ground-based observations.

scholarly journals Statistical analyses and correlation between tropospheric temperature and humidity at Dome C, Antarctica

2013 ◽  
Vol 26 (3) ◽  
pp. 290-308 ◽  
Author(s):  
P. Ricaud ◽  
F. Carminati ◽  
Y. Courcoux ◽  
A. Pellegrini ◽  
J.-L. Attié ◽  
...  
Keyword(s):  
Water Vapour ◽  
Pearson Correlation ◽  
Microwave Radiometer ◽  
Weather Forecast ◽  
Tropospheric Temperature ◽  
Infrared Sensors ◽  
Atmospheric Infrared Sounder ◽  
Medium Range Weather Forecast ◽  
Integrated Water Vapour ◽  
Highly Correlated

AbstractThe Dome C (Concordia) station in Antarctica (75°06′S, 123°21′E, 3233 m above mean sea level) has a unique opportunity to test the quality of remote-sensing measurements and meteorological analyses because it is situated well inside the Eastern Antarctic Plateau and is less affected by local phenomena. Measurements of tropospheric temperature and water vapour (H2O) together with the integrated water vapour (IWV) performed in 2010 are statistically analysed to assess their quality and to study the yearly correlation between temperature and H2O over the entire troposphere. The statistical tools include yearly evolution, seasonally-averaged mean and bias, standard deviation and linear Pearson correlation. The datasets are made of measurements from the ground-based microwave radiometer H2O Antarctica Microwave Stratospheric and Tropospheric Radiometer (HAMSTRAD), radiosonde, in situ sensors, the space-borne infrared sensors Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A platform and the Atmospheric InfraRed Sounder (AIRS) on the Aqua platform, and the analyses from the European Centre for Medium-Range Weather Forecast (ECMWF). Despite some obvious biases within all these datasets, our study shows that temperature and IWV are generally measured with high quality whilst H2O measurement quality is slightly worse. The AIRS and IASI measurements do not have the vertical resolution to correctly probe the lowermost troposphere, whilst HAMSTRAD loses sensitivity in the upper troposphere-lower stratosphere. Within the entire troposphere over the whole year, it is found that the time evolution of temperature and H2O is highly correlated (> 0.8). This suggests that, in addition to the variability of solar radiation producing an obvious diurnal cycle in the planetary boundary layer in summer and an obvious seasonal cycle over the year, the H2O and temperature intra-seasonal variabilities are affected by the same processes, e.g. related to the long-range transport of air masses.

scholarly journals Optimal Estimation of Water Vapour Profiles using a Combination of Raman Lidar and Microwave Radiometer

2017 ◽  
Author(s):  
Andreas Foth ◽  
Bernhard Pospichal
Keyword(s):  
Kalman Filter ◽  
Water Vapour ◽  
Microwave Radiometer ◽  
Optimal Estimation ◽  
Data Availability ◽  
Lidar Data ◽  
Raman Lidar ◽  
Brightness Temperatures ◽  
Step Algorithm ◽  
Full Height

Abstract. In this work, a two-step algorithm to obtain water vapour profiles from a combination of Raman lidar and microwave radiometer is presented. Both instruments were applied during an intensive two-month measurement campaign (HOPE) close to Jülich, western Germany, during spring 2013. To retrieve reliable water vapour information from inside or above the cloud a two-step algorithm is applied. The first step is a Kalman filter that extends the profiles, truncated at cloud base, to the full height range (up to 10 km) by combining previous information and current measurement. Then the complete water vapour profile serves as input to the one-dimensional variational (1D-VAR) method, also known as optimal estimation. A forward model simulates the brightness temperatures which would be observed by the microwave radiometer for the given atmospheric state. The profile is iteratively modified according to its error bars until the modelled and the actually measured brightness temperatures sufficiently agree. The functionality of the retrieval is presented in detail by means of case studies under different conditions. A statistical analysis shows that the availability of Raman lidar data (night) improves the accuracy of the profiles even under cloudy conditions. During the day, the absence of lidar data results in larger differences in comparison to reference radiosondes. The data availability of the full height water vapour lidar profiles of 17 % during the two-month campaign is significantly enhanced to 60 % by applying the retrieval. The bias with respect to radiosonde and the retrieved a posteriori uncertainty of the retrieved profiles clearly show that the application of the Kalman filter considerably improves the accuracy and quality of the retrieved mixing ratio profiles.

scholarly journals Quality assessment of integrated water vapour measurements at the St. Petersburg site, Russia: FTIR vs. MW and GPS techniques

2017 ◽  
Vol 10 (11) ◽  
pp. 4521-4536 ◽  
Author(s):  
Yana A. Virolainen ◽  
Yury M. Timofeyev ◽  
Vladimir S. Kostsov ◽  
Dmitry V. Ionov ◽  
Vladislav V. Kalinnikov ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Water Vapour ◽  
Measurement Errors ◽  
Microwave Radiometer ◽  
Reference Method ◽  
Atmospheric Conditions ◽  
Assessment Protocol ◽  
Clear Sky ◽  
Integrated Water Vapour ◽  
Sky Conditions

Abstract. The cross-comparison of different techniques for atmospheric integrated water vapour (IWV) measurements is the essential part of their quality assessment protocol. We inter-compare the synchronised data sets of IWV values measured by the Bruker 125 HR Fourier-transform infrared spectrometer (FTIR), RPG-HATPRO microwave radiometer (MW), and Novatel ProPak-V3 global navigation satellite system receiver (GPS) at the St. Petersburg site between August 2014 and October 2016. As the result of accurate spatial and temporal matching of different IWV measurements, all three techniques agree well with each other except for small IWV values. We show that GPS and MW data quality depends on the atmospheric conditions; in dry atmosphere (IWV smaller than 6 mm), these techniques are less reliable at the St. Petersburg site than the FTIR method. We evaluate the upper bound of statistical measurement errors for clear-sky conditions as 0.29 ± 0.02 mm (1.6 ± 0.3 %), 0.55 ± 0.02 mm (4.7 ± 0.4 %), and 0.76 ± 0.04 mm (6.3 ± 0.8 %) for FTIR, GPS, and MW methods, respectively. We propose the use of FTIR as a reference method under clear-sky conditions since it is reliable on all scales of IWV variability.

scholarly journals Optimal estimation of water vapour profiles using a combination of Raman lidar and microwave radiometer

2017 ◽  
Vol 10 (9) ◽  
pp. 3325-3344 ◽  
Author(s):  
Andreas Foth ◽  
Bernhard Pospichal
Keyword(s):  
Kalman Filter ◽  
Water Vapour ◽  
Microwave Radiometer ◽  
Optimal Estimation ◽  
Data Availability ◽  
Lidar Data ◽  
Raman Lidar ◽  
Brightness Temperatures ◽  
Step Algorithm ◽  
Full Height

Abstract. In this work, a two-step algorithm to obtain water vapour profiles from a combination of Raman lidar and microwave radiometer is presented. Both instruments were applied during an intensive 2-month measurement campaign (HOPE) close to Jülich, western Germany, during spring 2013. To retrieve reliable water vapour information from inside or above the cloud a two-step algorithm is applied. The first step is a Kalman filter that extends the profiles, truncated at cloud base, to the full height range (up to 10 km) by combining previous information and current measurement. Then the complete water vapour profile serves as input to the one-dimensional variational (1D-VAR) method, also known as optimal estimation. A forward model simulates the brightness temperatures which would be observed by the microwave radiometer for the given atmospheric state. The profile is iteratively modified according to its error bars until the modelled and the actually measured brightness temperatures sufficiently agree. The functionality of the retrieval is presented in detail by means of case studies under different conditions. A statistical analysis shows that the availability of Raman lidar data (night) improves the accuracy of the profiles even under cloudy conditions. During the day, the absence of lidar data results in larger differences in comparison to reference radiosondes. The data availability of the full-height water vapour lidar profiles of 17 % during the 2-month campaign is significantly enhanced to 60 % by applying the retrieval. The bias with respect to radiosonde and the retrieved a posteriori uncertainty of the retrieved profiles clearly show that the application of the Kalman filter considerably improves the accuracy and quality of the retrieved mixing ratio profiles.

scholarly journals Validation of stratospheric water vapour measurements from the airborne microwave radiometer AMSOS

2008 ◽  
Vol 8 (1) ◽  
pp. 1635-1671 ◽  
Author(s):  
S. C. Müller ◽  
N. Kämpfer ◽  
D. G. Feist ◽  
A. Haefele ◽  
M. Milz ◽  
...  
Keyword(s):  
Water Vapour ◽  
Microwave Radiometer ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Horizontal Resolution ◽  
Polar Regions ◽  
Upper Troposphere ◽  
Vertical Range ◽  
Stratospheric Water Vapour

Abstract. We present the validation of a water vapour dataset obtained by the Airborne Microwave Stratospheric Observing System AMSOS, a passive microwave radiometer operating at 183 GHz. Vertical profiles are retrieved from spectra by an optimal estimation method. The useful vertical range lies in the upper troposphere up to the mesosphere with an altitude resolution of 8 to 16 km and a horizontal resolution of about 57 km. Flight campaigns were performed once a year from 1998 to 2006 measuring the latitudinal distribution of water vapour from the tropics to the polar regions. The obtained profiles show clearly the main features of stratospheric water vapour in all latitudinal regions. Data are validated against a set of instruments comprising satellite, ground-based, airborne remote sensing and in-situ instruments. It appears that AMSOS profiles have a dry bias of 3–20%, when compared to satellite experiments. A good agreement with a difference of 3.3% was found between AMSOS and in-situ hygrosondes FISH and FLASH and an excellent matching of the lidar measurements from the DIAL instrument in the short overlap region in the upper troposphere.

scholarly journals Envisat MIPAS measurements of CFC-11: retrieval, validation, and climatology

2008 ◽  
Vol 8 (2) ◽  
pp. 4561-4602 ◽  
Author(s):  
L. Hoffmann ◽  
M. Kaufmann ◽  
R. Spang ◽  
R. Müller ◽  
J. J. Remedios ◽  
...  
Keyword(s):  
Large Scale ◽  
Lower Stratosphere ◽  
A Priori ◽  
Michelson Interferometer ◽  
Optimal Estimation ◽  
Atmospheric Conditions ◽  
Data Set ◽  
Mixing Ratios ◽  
Priori Information ◽  
The Individual

Abstract. From July 2002 to March 2004 the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) aboard the European Space Agency's Environmental Satellite (Envisat) measured nearly continuously mid infrared limb radiance spectra. These measurements are utilised to retrieve the global distribution of the chlorofluorocarbon CFC-11 by applying a new fast forward model for Envisat MIPAS and an accompanying optimal estimation retrieval processor. A detailed analysis shows that the total retrieval errors of the individual CFC-11 volume mixing ratios are typically below 10% and that the systematic components are dominating. Contribution of a priori information to the retrieval results are less than 5 to 10%. The vertical resolution of the observations is about 3 to 4 km. The data are successfully validated by comparison with several other space experiments, an air-borne in-situ instrument, measurements from ground-based networks, and independent Envisat MIPAS analyses. The retrieval results from 425 000 Envisat MIPAS limb scans are compiled to provide a new climatological data set of CFC-11. The climatology shows significantly lower CFC-11 abundances in the lower stratosphere compared with the Reference Atmospheres for MIPAS (RAMstan V3.1) climatology. Depending on the atmospheric conditions the differences between the climatologies are up to 30 to 110 ppt (45 to 150%) at 19 to 27 km altitude. Additionally, time series of CFC-11 mean abundance and variability for five latitudinal bands are presented. The observed CFC-11 distributions can be explained by the residual mean circulation and large-scale eddy-transports in the upper troposphere and lower stratosphere. The new CFC-11 data set is well suited for further scientific studies.

scholarly journals Quality assessment of integrated water vapour measurements at St. Petersburg site, Russia: FTIR vs. MW and GPS techniques

2017 ◽  
Author(s):  
Yana A. Virolainen ◽  
Yury M. Timofeyev ◽  
Vladimir S. Kostsov ◽  
Dmitry V. Ionov ◽  
Vladislav V. Kalinnikov ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Water Vapour ◽  
Measurement Errors ◽  
Microwave Radiometer ◽  
Satellite System ◽  
Data Sets ◽  
Atmospheric Conditions ◽  
Assessment Protocol ◽  
Integrated Water Vapour ◽  
Global Navigation Satellite

Abstract. The cross-comparison of different techniques for atmospheric integrated water vapour (IWV) measurements is the essential part of their quality assessment protocol. We inter-compare the synchronised data sets of IWV values measured by Fourier-transform infrared spectrometer Bruker 125 HR (FTIR), microwave radiometer RPG-HATPRO (MW) and global navigation satellite system receiver Novatel ProPak-V3 (GPS) at St. Petersburg site between August 2014 and October 2016. Generally, all three techniques agree well with each other and therefore are suitable for monitoring IWV values at St. Petersburg site. We show that GPS and MW data quality depends on the atmospheric conditions; in dry atmosphere (IWV smaller than 6 mm), these techniques are less reliable at St. Petersburg site than the FTIR method. We evaluate the upper bound of statistical measurement errors for clear-sky conditions as 0.33 ± 0.03 mm (2.0 ± 0.3 %), 0.54 ± 0.03 mm (4.5 ± 0.3 %), and 0.76 ± 0.04 mm (6.3 ± 0.7 %) for FTIR, GPS and MW methods, respectively. We conclude that accurate spatial and temporal matching of different IWV measurements is necessary for achieving the better agreement between various methods for IWV monitoring.

scholarly journals Validation of stratospheric water vapour measurements from the airborne microwave radiometer AMSOS

2008 ◽  
Vol 8 (12) ◽  
pp. 3169-3183 ◽  
Author(s):  
S. C. Müller ◽  
N. Kämpfer ◽  
D. G. Feist ◽  
A. Haefele ◽  
M. Milz ◽  
...  
Keyword(s):  
Water Vapour ◽  
Microwave Radiometer ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Horizontal Resolution ◽  
Polar Regions ◽  
Upper Troposphere ◽  
Vertical Range ◽  
Stratospheric Water Vapour

Abstract. We present the validation of a water vapour dataset obtained by the Airborne Microwave Stratospheric Observing System AMSOS, a passive microwave radiometer operating at 183 GHz. Vertical profiles are retrieved from spectra by an optimal estimation method. The useful vertical range lies in the upper troposphere up to the mesosphere with an altitude resolution of 8 to 16 km and a horizontal resolution of about 57 km. Flight campaigns were performed once a year from 1998 to 2006 measuring the latitudinal distribution of water vapour from the tropics to the polar regions. The obtained profiles show clearly the main features of stratospheric water vapour in all latitudinal regions. Data are validated against a set of instruments comprising satellite, ground-based, airborne remote sensing and in-situ instruments. It appears that AMSOS profiles have a dry bias of 0 to –20%, when compared to satellite experiments. Also a comparison between AMSOS and in-situ hygrosondes FISH and FLASH have been performed. A matching in the short overlap region in the upper troposphere of the lidar measurements from the DIAL instrument and the AMSOS dataset allowed water vapour profiling from the middle troposphere up to the mesosphere.

scholarly journals Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces

2021 ◽  
Vol 13 (5) ◽  
pp. 932
Author(s):  
René Preusker ◽  
Cintia Carbajal Henken ◽  
Jürgen Fischer
Keyword(s):  
Water Vapour ◽  
Near Infrared ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Data Set ◽  
Uncertainty Estimates ◽  
Resolution Imaging ◽  
Retrieval Errors ◽  
Mean Square Errors ◽  
Total Column

A new retrieval of total column water vapour (TCWV) from daytime measurements over land of the Ocean and Land Colour Instrument (OLCI) on-board the Copernicus Sentinel-3 missions is presented. The Copernicus Sentinel-3 OLCI Water Vapour product (COWa) retrieval algorithm is based on the differential absorption technique, relating TCWV to the radiance ratio of non-absorbing band and nearby water vapour absorbing band and was previously also successfully applied to other passive imagers Medium Resolution Imaging Spectrometer (MERIS) and Moderate Resolution Imaging Spectroradiometer (MODIS). One of the main advantages of the OLCI instrument regarding improved TCWV retrievals lies in the use of more than one absorbing band. Furthermore, the COWa retrieval algorithm is based on the full Optimal Estimation (OE) method, providing pixel-based uncertainty estimates, and transferable to other Near-Infrared (NIR) based TCWV observations. Three independent global TCWV data sets, i.e., Aerosol Robotic Network (AERONET), Atmospheric Radiation Measurement (ARM) and U.S. SuomiNet, and a German Global Navigation Satellite System (GNSS) TCWV data set, all obtained from ground-based observations, serve as reference data sets for the validation. Comparisons show an overall good agreement, with absolute biases between 0.07 and 1.31 kg/m2 and root mean square errors (RMSE) between 1.35 and 3.26 kg/m2. This is a clear improvement in comparison to the operational OLCI TCWV Level 2 product, for which the bias and RMSEs range between 1.10 and 2.55 kg/m2 and 2.08 and 3.70 kg/m2, respectively. A first evaluation of pixel-based uncertainties indicates good estimated uncertainties for lower retrieval errors, while the uncertainties seem to be overestimated for higher retrieval errors.

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