Global Maps of Atmospheric Water Vapor, Cloud Water, and Rainfall Derived From Nimbus-7 Scanning Multichannel Microwave Radiometer Data: A Case Study

1981 ◽  
pp. 683-689
Author(s):  
A. T. C. Chang ◽  
T. T. Wilheit ◽  
P. Gloersen
Keyword(s):  
Water Vapor ◽  
Microwave Radiometer ◽  
Cloud Water ◽  
Atmospheric Water Vapor ◽  
Atmospheric Water ◽  
Vapor Cloud

scholarly journals New Gridded Product for the Total Columnar Atmospheric Water Vapor over Ocean Surface Constructed from Microwave Radiometer Satellite Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2402
Author(s):  
Weifu Sun ◽  
Jin Wang ◽  
Yuheng Li ◽  
Junmin Meng ◽  
Yujia Zhao ◽  
...  
Keyword(s):  
Water Vapor ◽  
Microwave Radiometer ◽  
Atmospheric Water Vapor ◽  
Global Ocean ◽  
Optimal Interpolation ◽  
Fusion Product ◽  
Mean Deviation ◽  
Atmospheric Water ◽  
Absolute Deviation ◽  
Better Than

Based on the optimal interpolation (OI) algorithm, a daily fusion product of high-resolution global ocean columnar atmospheric water vapor with a resolution of 0.25° was generated in this study from multisource remote sensing observations. The product covers the period from 2003 to 2018, and the data represent a fusion of microwave radiometer observations, including those from the Special Sensor Microwave Imager Sounder (SSMIS), WindSat, Advanced Microwave Scanning Radiometer for Earth Observing System sensor (AMSR-E), Advanced Microwave Scanning Radiometer 2 (AMSR2), and HY-2A microwave radiometer (MR). The accuracy of this water vapor fusion product was validated using radiosonde water vapor observations. The comparative results show that the overall mean deviation (Bias) is smaller than 0.6 mm; the root mean square error (RMSE) and standard deviation (SD) are better than 3 mm, and the mean absolute deviation (MAD) and correlation coefficient (R) are better than 2 mm and 0.98, respectively.

scholarly journals A 22-GHz Mobile Microwave Radiometer (MobRa) for the Study of Middle Atmospheric Water Vapor

2008 ◽  
Vol 46 (10) ◽  
pp. 3104-3114 ◽  
Author(s):  
Erwan Motte ◽  
Philippe Ricaud ◽  
Benjamin Gabard ◽  
Mathieu Niclas ◽  
Fabrice Gangneron
Keyword(s):  
Water Vapor ◽  
Microwave Radiometer ◽  
Atmospheric Water Vapor ◽  
Atmospheric Water

scholarly journals Reduction of weather effects in the calculation of sea-ice concentration with the DMSP SSM/I

1995 ◽  
Vol 41 (139) ◽  
pp. 455-464 ◽  
Author(s):  
Donald J. Cavalieri ◽  
Karen M. St. Germain ◽  
Calvin T. Swift
Keyword(s):  
Water Vapor ◽  
Sea Ice ◽  
Microwave Radiometer ◽  
Atmospheric Water Vapor ◽  
Surface Roughening ◽  
Atmospheric Water ◽  
Sea Ice Concentration ◽  
Ice Concentration ◽  
Vapor Line ◽  
Microwave Imager

AbstractA problem in mapping the polar sea-ice covers in both hemispheres has been the sporadic false indication of sea ice over the open ocean and at the ice edge. These spurious sea-ice concentrations result from variations in sea-surface roughening by surface winds, atmospheric water vapor and both precipitating and non-precipitating liquid water. This problem was addressed for sea-ice concentrations derived from the Nimbus-7 scanning multi-channel microwave radiometer (SMMR) data through the development of a weather filter based on spectral information from the 18.0 and 37.0 GHz vertical polarization SMMR channels. Application of a similar filter for use with sea-ice concentration maps derived with the special-sensor microwave imager (SSM/I) sensor is less successful. This results from the position of the 19.35 GHz SSM/I channels, which are closer to the center of the 22.2 GHz atmospheric water-vapor line than are the SMMR 18.0 GHz channels. Thus, the SSM/I 19.35 GHz channels are more sensitive to changes in atmospheric water vapor, which results in greater contamination problems. An additional filter has been developed, based on a combination of the 19.35 and 22.2GHz. SSM/I channels. Examples of the effectiveness of the new filter are presented and limitations are discussed.

scholarly journals Detection of land-surface-induced atmospheric water vapor patterns

2020 ◽  
Vol 20 (3) ◽  
pp. 1723-1736 ◽  
Author(s):  
Tobias Marke ◽  
Ulrich Löhnert ◽  
Vera Schemann ◽  
Jan H. Schween ◽  
Susanne Crewell
Keyword(s):  
Land Use ◽  
Water Vapor ◽  
Land Surface ◽  
Urban Areas ◽  
Microwave Radiometer ◽  
Atmospheric Water Vapor ◽  
Open Pit ◽  
Atmospheric Water ◽  
Long Term Study ◽  
Large Eddy

Abstract. Finding observational evidence of land surface and atmosphere interactions is crucial for understanding the spatial and temporal evolution of the boundary layer, as well as for model evaluation, and in particular for large-eddy simulation (LES) models. In this study, the influence of a heterogeneous land surface on the spatial distribution of atmospheric water vapor is assessed. Ground-based remote sensing measurements from a scanning microwave radiometer (MWR) are used in a long-term study over 6 years to characterize spatial heterogeneities in integrated water vapor (IWV) during clear-sky conditions at the Jülich ObservatorY for Cloud Evolution (JOYCE). The resulting deviations from the mean of the scans reveal a season- and direction-dependent IWV that is visible throughout the day. Comparisons with a satellite-derived spatial IWV distribution show good agreement for a selection of satellite overpasses during convective situations but no clear seasonal signal. With the help of a land use type classification and information on the topography, the main types of regions with a positive IWV deviation were determined to be agricultural fields and nearby open pit mines. Negative deviations occurred mainly above elevated forests and urban areas. In addition, high-resolution large-eddy simulations (LESs) are used to investigate changes in the water vapor and cloud fields for an altered land use input.

scholarly journals Trend and Variability of the Atmospheric Water Vapor: A Mean Sea Level Issue

2014 ◽  
Vol 31 (9) ◽  
pp. 1881-1901 ◽  
Author(s):  
Soulivanh Thao ◽  
Laurence Eymard ◽  
Estelle Obligis ◽  
Bruno Picard
Keyword(s):  
Water Vapor ◽  
Sea Level ◽  
Microwave Radiometer ◽  
Temporal Distribution ◽  
Quantitative Agreement ◽  
Atmospheric Water Vapor ◽  
Path Delay ◽  
Atmospheric Water ◽  
Mean Sea Level ◽  
The Mean

Abstract The wet tropospheric path delay is presently the main source of error in the estimation of the mean sea level by satellite altimetry. This correction on altimetric measurements, provided by a dedicated radiometer aboard the satellite, directly depends on the atmospheric water vapor content. Nowadays, water vapor products from microwave radiometers are rather consistent but important discrepancies remain. Understanding these differences can help improve the retrieval of water vapor and reduce at the same time the error on the mean sea level. Three radiometers are compared: the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), Jason-1 microwave radiometer (JMR), and Envisat microwave radiometer (MWR). Water vapor products are analyzed both in terms of spatial and temporal distribution over the period 2004–10, using AMSR-E as a reference. The Interim ECMWF Re-Analysis (ERA-Interim) data are also included in the study as an additional point of comparison. Overall, the study confirms the general good agreement between the radiometers: similar patterns are observed for the spatial distribution of water vapor and the correlation of the times series is better than 0.90. However, regional discrepancies are observed and a quantitative agreement on the trend is not obtained. Regional discrepancies are driven by the annual cycle. The JMR product shows discrepancies are highly dependent on water vapor, which might be related to calibration issues. Furthermore, triple collocation analysis suggests a possible drift of JMR. MWR discrepancies are located in coastal regions and follow a seasonal dynamic with stronger differences in summer. It may result from processing of the brightness temperatures.

scholarly journals Quantifying the value of redundant measurements at GRUAN sites

2014 ◽  
Vol 7 (6) ◽  
pp. 6327-6357 ◽  
Author(s):  
F. Madonna ◽  
M. Rosoldi ◽  
J. Güldner ◽  
A. Haefele ◽  
R. Kivi ◽  
...  
Keyword(s):  
Time Series ◽  
Water Vapor ◽  
Global Climate ◽  
Microwave Radiometer ◽  
Atmospheric Water Vapor ◽  
Raman Lidar ◽  
Atmospheric Water ◽  
Mutual Correlation ◽  
Random Uncertainty ◽  
Lidar Measurements

Abstract. The potential for measurement redundancy to reduce uncertainty in atmospheric variables has not been investigated comprehensively for climate observations. We evaluated the usefulness of entropy and mutual correlation concepts, as defined in information theory, for quantifying random uncertainty and redundancy in time series of atmospheric water vapor provided by five highly instrumented GRUAN (GCOS [Global Climate Observing System] Reference Upper-Air Network) Stations in 2010–2012. Results show that the random uncertainties for radiosonde, frost-point hygrometer, Global Positioning System, microwave and infrared radiometers, and Raman lidar measurements differed by less than 8%. Comparisons of time series of the Integrated Water Vapor (IWV) content from ground-based remote sensing instruments with in situ soundings showed that microwave radiometers have the highest redundancy and therefore the highest potential to reduce random uncertainty of IWV time series estimated by radiosondes. Moreover, the random uncertainty of a time series from one instrument should be reduced of ~ 60% by constraining the measurements with those from another instrument. The best reduction of random uncertainty resulted from conditioning of Raman lidar measurements with microwave radiometer measurements. Specific instruments are recommended for atmospheric water vapor measurements at GRUAN sites. This approach can be applied to the study of redundant measurements for other climate variables.

scholarly journals MITIGATION ATMOSPHERIC EFFECTS IN INTERFEROGRAM WITH USING INTEGRATED MERIS/MODIS DATA AND A CASE STUDY OVER SOUTHERN CALIFORNIA

2018 ◽  
Vol XLII-3 ◽  
pp. 1799-1803
Author(s):  
X. Wang ◽  
P. Zhang ◽  
Z. Sun
Keyword(s):  
Water Vapor ◽  
Synthetic Aperture Radar ◽  
Atmospheric Water Vapor ◽  
Synthetic Aperture ◽  
Atmospheric Effects ◽  
Interferometric Synthetic Aperture Radar ◽  
Atmospheric Water ◽  
Resolution Imaging ◽  
Aperture Radar

Interferometric synthetic aperture radar(InSAR), as a space geodetictechnology, had been testified a high potential means of earth observation providing a method fordigital elevation model (DEM) and surface deformation monitoring of high precision. However, the accuracy of the interferometric synthetic aperture radar is mainly limited by the effects of atmospheric water vapor. In order to effectively measure topography or surface deformations by synthetic aperture radar interferometry (InSAR), it is necessary to mitigate the effects of atmospheric water vapor on the interferometric signals. This paper analyzed the atmospheric effects on the interferogram quantitatively, and described a result of estimating Precipitable Water Vapor (PWV) from the the Medium Resolution Imaging Spectrometer (MERIS), Moderate Resolution Imaging Spectroradiometer (MODIS) and the ground-based GPS, compared the MERIS/MODIS PWV with the GPS PWV. Finally, a case study for mitigating atmospheric effects in interferogramusing with using the integration of MERIS and MODIS PWV overSouthern California is given. The result showed that such integration approach benefits removing or reducing the atmospheric phase contribution from the corresponding interferogram, the integrated Zenith Path Delay Difference Maps (ZPDDM) of MERIS and MODIS helps reduce the water vapor effects efficiently, the standard deviation (STD) of interferogram is improved by 23 % after the water vapor correction than the original interferogram.

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