scholarly journals Water Vapor Radiometry at the Onsala Space Observatory from 1980 to 1987

1988 ◽  
Vol 129 ◽  
pp. 547-548 ◽  
Author(s):  
J. M. Johansson ◽  
G. Elgered ◽  
B. O. Rönnäng
Keyword(s):  
Water Vapor ◽  
Atmospheric Water Vapor ◽  
Atmospheric Water ◽  
Space Observatory ◽  
Brightness Temperatures ◽  
Onsala Space Observatory ◽  
Water Vapor Radiometer ◽  
Sky Brightness

Variations in atmospheric water vapor are difficult to correct for in geodetic, astrometric, and mm-wave astronomy VLBI. The use of a water vapor radiometer (WVR) has given promising results. The algorithm which relates the sky brightness temperatures observed by the WVR to the delay caused by atmopheric water vapor is discussed. Examples of WVR measurements made at the Onsala Space Observatory from 1980 to 1987 are presented.

scholarly journals Methods of Correction for the “Wet” Atmosphere in Estimating Baseline Lengths from VLBI

1988 ◽  
Vol 129 ◽  
pp. 543-544
Author(s):  
G. Elgered ◽  
J. L. Davis ◽  
T. A. Herring ◽  
I. I. Shapiro
Keyword(s):  
Water Vapor ◽  
Propagation Delay ◽  
Propagation Path ◽  
Baseline Length ◽  
Space Observatory ◽  
Owens Valley ◽  
Use Of Data ◽  
Onsala Space Observatory ◽  
Vlbi Data ◽  
Water Vapor Radiometer

The error in VLBI estimates of baseline length caused by unmodelled variations in the propagation path through the atmosphere is greater for longer baselines. We present and discuss series of estimates of baseline lengths obtained using different methods to correct for the propagation delay caused by atmospheric water vapor. The main methods are use of data from a water-vapor radiometer (WVR) and Kalman-filtering of the VLBI data themselves to estimate the propagation delay. Since the longest timespan of WVR data associated with geodetic VLBI experiments was obtained at the Onsala Space Observatory in Sweden, we present results for the following three baselines: (1) Onsala–Wettzell, FRG (920 km), (2) Onsala–Haystack/Westford, MA (5600 km), and (3) Onsala–Owens Valley (7914 km).

Simultaneous Measurements of Atmospheric Water Vapor with MIR, Raman Lidar, and Rawinsondes

1995 ◽  
Vol 34 (7) ◽  
pp. 1595-1607 ◽  
Author(s):  
J. R. Wang ◽  
S. H. Melfi ◽  
P. Racette ◽  
D. N. Whitemen ◽  
L. A. Chang ◽  
...  
Keyword(s):  
Water Vapor ◽  
Atmospheric Water Vapor ◽  
Raman Lidar ◽  
Atmospheric Water ◽  
Millimeter Wave Imaging ◽  
Brightness Temperatures ◽  
Simultaneous Measurements ◽  
Wave Imaging ◽  
Low Sensitivity ◽  
Measured Water

Abstract Simultaneous measurements of atmospheric water vapor were made by the Millimeter-wave Imaging Radiometer (MIR), Raman lidar, and rawinsondes. Two types of rawinsonde sensor packages (AIR and Vaisala) were carried by the same balloon. The measured water vapor profiles from Raman lidar, and the Vaisala and AIR sondes were used in the radiative transfer calculations. The calculated brightness temperatures were compared with those measured from the MIR at all six frequencies (89, 150, 183.3 ± 1, 183.3 ±3, 183.3 ±7, and 220 GHz). The results show that the MIR-measured brightness temperatures agree well (within ±K) with those calculated from the Raman lidar and Vaisala measurements. The brightness temperatures calculated from the AIR sondes differ from the MIR measurements by as much as 10 K, which can be attributed to low sensitivity of the AIR sondes at relative humidity less than 20%. Both calculated and the MIR-measured brightness temperatures were also used to retrieve water vapor profiles. These retrieved profiles were compared with those measured by the Raman lidar and rawinsondes. The results of these comparisons suggest that the MIR can measure the brightness of a target to an accuracy of at most ±K and is capable of retrieving useful water vapor profiles.

Forecast Evaluation of an Observing System Simulation Experiment Assimilating Both Radar and Satellite Data

2014 ◽  
Vol 142 (1) ◽  
pp. 107-124 ◽  
Author(s):  
Thomas A. Jones ◽  
Jason A. Otkin ◽  
David J. Stensrud ◽  
Kent Knopfmeier
Keyword(s):  
Water Vapor ◽  
Satellite Data ◽  
Radar Data ◽  
Radar Reflectivity ◽  
Atmospheric Water Vapor ◽  
Atmospheric Water ◽  
Brightness Temperatures ◽  
Central United States ◽  
Correlation Statistics ◽  
The Impact

Abstract In the first part of this study, Jones et al. compared the relative skill of assimilating simulated radar reflectivity and radial velocity observations and satellite 6.95-μm brightness temperatures TB and found that both improved analyses of water vapor and cloud hydrometeor variables for a cool-season, high-impact weather event across the central United States. In this study, the authors examine the impact of the observations on 1–3-h forecasts and provide additional analysis of the relationship between simulated satellite and radar data observations to various water vapor and cloud hydrometeor variables. Correlation statistics showed that the radar and satellite observations are sensitive to different variables. Assimilating 6.95-μm TB primarily improved the atmospheric water vapor and frozen cloud hydrometeor variables such as ice and snow. Radar reflectivity proved more effective in both the lower and midtroposphere with the best results observed for rainwater, graupel, and snow. The impacts of assimilating both datasets decrease rapidly as a function of forecast time. By 1 h, the effects of satellite data become small on forecast cloud hydrometeor values, though it remains useful for atmospheric water vapor. The impacts of radar data last somewhat longer, sometimes up to 3 h, but also display a large decrease in effectiveness by 1 h. Generally, assimilating both satellite and radar data simultaneously generates the best analysis and forecast for most cloud hydrometeor variables.

The measurement of atmospheric water vapor: radiometer comparison and spatial variations

1991 ◽  
Vol 29 (1) ◽  
pp. 3-8 ◽  
Author(s):  
C. Rocken ◽  
J.M. Johnson ◽  
R.E. Neilan ◽  
M. Cerezo ◽  
J.R. Jordan ◽  
...  
Keyword(s):  
Water Vapor ◽  
Spatial Variations ◽  
Atmospheric Water Vapor ◽  
Atmospheric Water ◽  
Water Vapor Radiometer

scholarly journals Profiling of atmospheric water vapor with MIR and LASE

2002 ◽  
Vol 40 (6) ◽  
pp. 1211-1219 ◽  
Author(s):  
J.R. Wang ◽  
P. Racette ◽  
M.E. Triesky ◽  
E.V. Browell ◽  
S. Ismail ◽  
...  
Keyword(s):  
Water Vapor ◽  
Atmospheric Water Vapor ◽  
Atmospheric Water

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 ARIS-Campaign: intercomparison of three ground based 22 GHz radiometers for middle atmospheric water vapor at the Zugspitze in winter 2009

2011 ◽  
Vol 4 (9) ◽  
pp. 1979-1994 ◽  
Author(s):  
C. Straub ◽  
A. Murk ◽  
N. Kämpfer ◽  
S. H. W. Golchert ◽  
G. Hochschild ◽  
...  
Keyword(s):  
Water Vapor ◽  
Noise Temperature ◽  
Rotational Transition ◽  
Atmospheric Water Vapor ◽  
Transition Line ◽  
Applied Physics ◽  
Atmospheric Water ◽  
Max Planck ◽  
Institute Of Technology ◽  
University Of Bern

Abstract. This paper presents the Alpine Radiometer Intercomparison at the Schneefernerhaus (ARIS), which took place in winter 2009 at the high altitude station at the Zugspitze, Germany (47.42° N, 10.98° E, 2650 m). This campaign was the first direct intercomparison between three new ground based 22 GHz water vapor radiometers for middle atmospheric profiling with the following instruments participating: MIRA 5 (Karlsruhe Institute of Technology), cWASPAM3 (Max Planck Institute for Solar System Research, Katlenburg-Lindau) and MIAWARA-C (Institute of Applied Physics, University of Bern). Even though the three radiometers all measure middle atmospheric water vapor using the same rotational transition line and similar fundamental set-ups, there are major differences between the front ends, the back ends, the calibration concepts and the profile retrieval. The spectrum comparison shows that all three radiometers measure spectra without severe baseline artifacts and that the measurements are in good general agreement. The measurement noise shows good agreement to the values theoretically expected from the radiometer noise formula. At the same time the comparison of the noise levels shows that there is room for instrumental and calibration improvement, emphasizing the importance of low elevation angles for the observation, a low receiver noise temperature and an efficient calibration scheme. The comparisons of the retrieved profiles show that the agreement between the profiles of MIAWARA-C and cWASPAM3 with the ones of MLS is better than 0.3 ppmv (6%) at all altitudes. MIRA 5 has a dry bias of approximately 0.5 ppm (8%) below 0.1 hPa with respect to all other instruments. The profiles of cWASPAM3 and MIAWARA-C could not be directly compared because the vertical region of overlap was too small. The comparison of the time series at different altitude levels show a similar evolution of the H2O volume mixing ratio (VMR) for the ground based instruments as well as the space borne sensor MLS.

scholarly journals Diurnal variations in middle-atmospheric water vapor by ground-based microwave radiometry

2013 ◽  
Vol 13 (14) ◽  
pp. 6877-6886 ◽  
Author(s):  
D. Scheiben ◽  
A. Schanz ◽  
B. Tschanz ◽  
N. Kämpfer
Keyword(s):  
Water Vapor ◽  
Observational Data ◽  
Climate Model ◽  
Correlation Coefficients ◽  
Diurnal Variations ◽  
Atmospheric Water Vapor ◽  
Atmospheric Water ◽  
Data Set ◽  
Diurnal Variability ◽  
Time Periods

Abstract. In this paper, we compare the diurnal variations in middle-atmospheric water vapor as measured by two ground-based microwave radiometers in the Alpine region near Bern, Switzerland. The observational data set is also compared to data from the chemistry–climate model WACCM. Due to the small diurnal variations of usually less than 1%, averages over extended time periods are required. Therefore, two time periods of five months each, December to April and June to October, were taken for the comparison. The diurnal variations from the observational data agree well with each other in amplitude and phase. The linear correlation coefficients range from 0.8 in the upper stratosphere to 0.5 in the upper mesosphere. The observed diurnal variability is significant at all pressure levels within the sensitivity of the instruments. Comparing our observations with WACCM, we find that the agreement of the phase of the diurnal cycle between observations and model is better from December to April than from June to October. The amplitudes of the diurnal variations for both time periods increase with altitude in WACCM, but remain approximately constant at 0.05 ppm in the observations. The WACCM data are used to separate the processes that lead to diurnal variations in middle-atmospheric water vapor above Bern. The dominating processes were found to be meridional advection below 0.1 hPa, vertical advection between 0.1 and 0.02 hPa and (photo-)chemistry above 0.02 hPa. The contribution of zonal advection is small. The highest diurnal variations in water vapor as seen in the WACCM data are found in the mesopause region during the time period from June to October with diurnal amplitudes of 0.2 ppm (approximately 5% in relative units).

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