Precipitable Water Vapor Measurements Research Articles

Thin‐Plate Spline Interpolation Spatial Modelling of GNSS Retrieved Water Vapour Over Northeast Japan

ABSTRACTThe study investigated precipitable water vapour (PWV) variation over Northeast Japan by using more than two decades (2000 to 2022) of measurements. These data have been extracted from 36 Global Navigation Satellite System (GNSS) networks and interpolated with thin‐plate spline interpolation to understand its spatial variation over the region. PWV annual and seasonal variation is studied and correlated with ERA5 reanalysis observations. These PWV variation shows that the northern part of Northeast Japan which is located at higher latitudes showed a smaller magnitude compared to PWV magnitude in the southern part of low latitudes. This is possible because the cold air is drier and the warm air holds more moisture in the lower southern part. The correlation coefficient variation based on geographical area is visible which quantifies the consistency between GNSS PWV and ERA5 and visualises the effects in sampling. The southern part, where the correlation coefficients are very high (more than 0.80), indicates good agreements between GNSS PWV and ERA5 values and can be considered well‐sampled observations. Moreover, the correlation coefficients drop the values to approximately 0.40–0.60 for poorly sampled observations on the northern coast, pointing out the interannual inconsistency of PWV measurements, which are loosely related to ERA5 observations. Finally, the correlation coefficient between PWV with surface temperature and atmospheric pressure over Northeast Japan is investigated. This is clear from the results that the correlation coefficient between PWV and temperature is around 0.98 for each site, indicating that PWV has a very high dependency on surface temperature. The correlation coefficient between PWV and pressure is highly negative around −0.80, indicating their inverse relationship. We believe the outcomes from this study will contribute to a better understanding of PWV over Japan and the future refinements of atmospheric models over the East Asian region.

Predicting Eastern Mediterranean Flash Floods Using Support Vector Machines with Precipitable Water Vapor, Pressure, and Lightning Data

Flash floods in the Eastern Mediterranean (EM) region are considered among the most destructive natural hazards, which pose a significant challenge to model due to their high complexity. Machine learning (ML) methods have made a significant contribution to the advancement of flash flood prediction systems by providing cost-effective solutions with improved performance, enabling the modeling of the complex mathematical expressions underlying physical processes of flash floods. Thus, the development of ML methods for flash flood prediction holds the potential to mitigate risks, inform policy recommendations, minimize loss of human life, and reduce property damage caused by flash floods. Here, we present a novel approach for improving flash flood predictions in the EM region using Support Vector Machines (SVMs) with a combination of precipitable water vapor (PWV) data, derived from ground-based global navigation satellite system (GNSS) receivers, along with surface pressure measurements, and nearby lightning occurrence data to predict flash floods in an arid region of the EM. The SVM model was trained on historical data from 2004 to 2019 and was used to forecast the likelihood of flash floods in the region. The study found that integrating nearby lightning data with the other variables significantly improved the accuracy of flash flood prediction compared to using only PWV and surface pressure measurements. The results of the SVM model were validated using observed flash flood events, and the model was found to have a high predictive accuracy with an area under the receiver operating characteristic curve of 0.93 for the test set. The study provides valuable insights into the potential of utilizing a combination of meteorological and lightning data for improving flash flood forecasting in the Eastern Mediterranean region.

Water vapour products from ERA5, MERSI‐II/FY‐3D, OLCI/Sentinel‐3A, OLCI/Sentinel‐3B, MODIS/Aqua and MODIS/Terra in Australia: A comparison against in situGPS water vapour data

AbstractAustralia is a region of high sensitivity to the El Niño–Southern Oscillation events in association with atmospheric water vapour, which is an essential atmospheric parameter in hydrological cycle, energy transport and climate monitoring. In this article, we thoroughly validated the quality of multisource precipitable water vapour (PWV) products sourced from ERA5 reanalysis, advanced Medium Resolution Spectral Imager (MERSI‐II) sensor on the FY‐3D satellite, Ocean and Land Colour Instrument (OLCI) sensor on the Sentinel‐3A and Sentinel‐3B satellites, and Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on the Aqua and Terra satellites. The PWV estimates measured by 453 in situ Global Positioning System (GPS) sites from 1 June 2019 to 31 May 2020 over Australia were employed as the common reference. The validation results show that all the reanalysis‐based and satellite‐based PWV products had a good agreement with reference GPS‐based PWV data. ERA5 reanalysis had the highest PWV accuracy with a root‐mean‐square error (RMSE) of 2.016 mm and a relative RMSE (RRMSE) of 12.038%, while the MODIS/Terra instrument had the lowest PWV accuracy (RMSE = 4.903 mm and RRMSE = 34.187%). In contrast to the MERSI‐II/FY‐3D instrument that underestimated PWV, the PWV data from ERA5, OLCI/Sentinel‐3A, OLCI/Sentinel‐3B, MODIS/Aqua and MODIS/Terra overestimated the water vapour values. The quality of reanalysis‐based and satellite‐based PWV measurements showed significant dependencies on several variables – location, PWV, solar zenith angle, season, elevation, land surface cover and latitude. It is expected that this research can help enhance the understanding of the quality of reanalysis and satellite water vapour products in Australia, that is, ERA5, OLCI/Sentinel‐3A, OLCI/Sentinel‐3B, MODIS/Aqua and MODIS/Terra. This work could provide an insight into improving the accuracy of reanalysis‐based and satellite‐based PWV data products after exploring the dependency factors that affect PWV performance as presented in our work.

Precise near-infrared photometry, accounting for precipitable water vapour at SPECULOOS Southern Observatory

ABSTRACT The variability induced by precipitable water vapour (PWV) can heavily affect the accuracy of time-series photometric measurements gathered from the ground, especially in the near-infrared. We present here a novel method of modelling and mitigating this variability, as well as open-sourcing the developed tool – Umbrella. In this study, we evaluate the extent to which the photometry in three common bandpasses (r′, i′, z′), and SPECULOOS’ primary bandpass (I + z′), are photometrically affected by PWV variability. In this selection of bandpasses, the I + z′ bandpass was found to be most sensitive to PWV variability, followed by z′, i′, and r′. The correction was evaluated on global light curves of nearby late M- and L-type stars observed by SPECULOOS’ Southern Observatory (SSO) with the I + z′ bandpass, using PWV measurements from the LHATPRO and local temperature/humidity sensors. A median reduction in RMS of 1.1 per cent was observed for variability shorter than the expected transit duration for SSO’s targets. On timescales longer than the expected transit duration, where long-term variability may be induced, a median reduction in RMS of 53.8 per cent was observed for the same method of correction.

GPS Measurements of Precipitable Water Vapor Can Improve Survey Calibration: A Demonstration from KPNO and the Mayall z-band Legacy Survey

Dual-band Global Positioning Satellite (GPS) measurements of precipitable water vapor (PWV) at the Kitt Peak National Observatory predict the overall per-image sensitivity of the Mayall z-band Legacy Survey (MzLS). The per-image variation in the brightness of individual stars is strongly correlated with the measured PWV and the color of the star. Synthetic stellar spectra through TAPAS transmission models successfully predict the observed PWV-induced photometric variation. We find that PWV absorption can be well approximated by a linear relationship with (airmass × PWV)0.6 and present an update on the traditional treatment in the literature. The MzLS zero-point sensitivity in electrons s−1 varies with a normalized-mean absolute deviation of 61 mmag. PWV variation accounts 23 mmag of this zero-point variation. The MzLS per-image absolute sensitivity decreases by 40 mmag per effective mm of PWV. The overall gray offset portion of this variation is corrected by the calibration to a reference catalog. But the relative calibration error between blue (r − z < 0.5 mag) versus red (1.2 mag < r − z) stars increases by 0.3–2 mmag per effective mm of PWV. We argue that GPS systems provide more precise PWV measurements than using differential measurements of stars of different colors and recommend that observatories install dual-band GPS as a low-maintenance, low-cost, auxiliary calibration system. We extend our results of the need for well-calibrated PWV measurements by presenting the calculations of the PWV photometric impact on three science cases of interest: stellar photometry, supernova cosmology, and quasar identification and variability.

Atmospheric precipitable water vapor and its correlation with clear-sky infrared temperature observations

Abstract. Precipitable water vapor (PWV) is the vertically integrated amount of water vapor in the atmosphere, and it is a valuable predictor for weather forecasting. Currently, the use of sophisticated instrumentation can limit the number of PWV measurement sites, which affects the accuracy of forecast models in regards to storm formation, strength, and the potential for precipitation. We have analyzed relationships between PWV and zenith sky temperature measurements for the dry climate zone found in the North American Desert Southwest, specifically over Socorro, New Mexico (34∘ N, 107∘ W). Daily measurements of the ground and zenith sky temperatures have been made at Socorro for two complete annual cycles using low-cost infrared thermal sensors. Radiosonde measurements of PWV from National Weather Service stations located in nearby Albuquerque and Santa Teresa, New Mexico, are input into our dataset and analyzed via a newly developed computational tool. Our results show that an exponential relationship between PWV and zenith sky temperature holds for the Desert Southwest, but with parameters that are different than those obtained previously over the more moist climate zone of the North American Gulf Coast. Model simulations can accurately reproduce the observed relationship between PWV and temperature, and the results suggest that half of the signal in temperature is directly related to changes in opacity due to changes in PWV, while the other half is due to changes in air temperature that usually accompany changes in PWV.

Differential absorption lidar measurements of water vapor by the High Altitude Lidar Observatory (HALO): retrieval framework and first results

Abstract. Airborne differential absorption lidar (DIAL) offers a uniquely capable solution to the problem of measuring water vapor (WV) with high precision, accuracy, and resolution throughout the troposphere and lower stratosphere. The High Altitude Lidar Observatory (HALO) airborne WV DIAL was recently developed at NASA Langley Research Center and was first deployed in 2019. It uses four wavelengths near 935 nm to achieve sensitivity over a wide dynamic range and simultaneously employs 1064 nm backscatter and 532 nm high-spectral-resolution lidar (HSRL) measurements for aerosol and cloud profiling. A key component of the WV retrieval framework is flexibly trading resolution for precision to achieve optimal datasets for scientific objectives across scales. An approach to retrieving WV in the lowest few hundred meters of the atmosphere using the strong surface return signal is also presented. The five maiden flights of the HALO WV DIAL spanned the tropics through midlatitudes with a wide range of atmospheric conditions, but opportunities for validation were sparse. Comparisons to dropsonde WV profiles were qualitatively in good agreement, though statistical analysis was impossible due to systematic error in the dropsonde measurements. Comparison of HALO to in situ WV measurements aboard the aircraft showed no substantial bias across 3 orders of magnitude, despite variance (R2=0.66) that may be largely attributed to spatiotemporal variability. Precipitable water vapor measurements from the spaceborne sounders AIRS and IASI compared very well to HALO with R2&gt;0.96 over ocean.

Error Evaluation of L-Band InSAR Precipitable Water Vapor Measurements by Comparison with GNSS Observations in Japan

Interferometric synthetic aperture radar (InSAR) enables us to obtain precipitable water vapor (PWV) maps with high spatial resolution through the phase difference caused by refraction in the atmosphere. Although previous studies have evaluated the error level of InSARPWV observations, they validated it only with C-band InSARPWV observations. Since ionospheric disturbance seriously contaminates the InSAR phase in the case of the lower-frequency SAR system, it is necessary for a PWV error level evaluation correcting the ionospheric effect appropriately if we use lower-frequency SAR systems, such as the Advanced Land Observing Satellite-2 (ALOS-2). In this paper, we evaluated the error level of the L-band InSARPWV observation obtained from ALOS-2 data covering four areas in Japan. We compared the InSAR observations with global navigation satellite system (GNSS) atmospheric observations and estimated the L-band InSARPWV error value by utilizing the error propagation theory. As a result, the L-band InSARPWV absolute error reached 2.83 mm, which was comparable to traditional PWV observations. Moreover, we investigated the impacts of the seasonality, the interferometric coherence, and the height dependence on the PWV observation accuracy in InSAR.

Monitoring precipitable water vapour in near real-time to correct near-infrared observations using satellite remote sensing

Context. In the search for small exoplanets orbiting cool stars whose spectral energy distributions peak in the near infrared, the strong absorption of radiation in this region due to water vapour in the atmosphere is a particularly adverse effect for ground-based observations of cool stars. Aims. To achieve the photometric precision required to detect exoplanets in the near infrared, it is necessary to mitigate the effect of variable precipitable water vapour (PWV) on radial-velocity and photometric measurements. The aim is to enable global PWV correction by monitoring the amount of precipitable water vapour at zenith and along the line of sight of any visible target. Methods. We developed an open-source Python package that uses imagery data obtained with the Geostationary Operational Environmental Satellites (GOES), which provide temperature and relative humidity at different pressure levels to compute the near real-time PWV above any ground-based observatory that is covered by GOES every 5 min or 10 min, depending on the location. Results. We computed PWV values on selected days above Cerro Paranal (Chile) and San Pedro Mártir (Mexico) to benchmark the procedure. We also simulated different pointing at test targets as observed from the sites to compute the PWV along the line of sight. To asses the accuracy of our method, we compared our results with the on-site radiometer measurements obtained from Cerro Paranal. Conclusions. Our results show that our publicly available code proves to be a good supporting tool for measuring the local PWV for any ground-based facility within the GOES coverage, which will help to reduce correlated noise contributions in near-infrared ground-based observations that do not benefit from on-site PWV measurements.

Analysis of precipitable water vapour characteristics from GNSS measurements during the snow season in Liaoning Province, China

Global Navigation Satellite System (GNSS) remote sensing precipitable water vapour (PWV) data from November 2015 to March 2019 were combined with snowfall observation data and used to analyse PWV characteristics in Liaoning Province during the snow season (from November to March the following year) and their relationship with snowfall. The potential of using GNSS for PWV measurements was demonstrated using sounding data with a correlation coefficient higher than 0.9 and a mean bias error lower than 0.5 mm. According to the GNSS PWV data gathered at 30-min intervals from 68 GNSS stations in Liaoning during the snow season, the monthly PWV average was highest in November and lowest in January. Negative correlations were found between PWV and altitude. Most of the water vapour was concentrated in the low layer of the atmosphere, and the contribution of this vapour to the PWV was higher during the snow season than in summer. A total of 43 snow cases were identified using the snowfall records from 53 GNSS stations, and the characteristics of PWV during these snowfalls were analysed. An increase in PWV was observed before snowfall events. Moreover, the influence of synoptic systems and air mass origins on PWV was analysed based on National Centers for Environmental Prediction (NCEP) reanalysis data and the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The results show that the water vapour condition was better when the synoptic systems or air masses came from areas south of Liaoning.

Multi-sensor study of precipitable water vapor and atmospheric profiling from microwave radiometer, GNSS/MET, radiosonde, and ECMWF reanalysis in Beijing

We compare the precipitable water vapor (PWV) determined using a domestic ground-based microwave radiometer (MWR PWV) with PWV measurements from radiosondes (RS PWV), the Global Navigation Satellite System (GNSS PWV), and reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) (EC PWV). The MWR PWV is affected by precipitation, and thus it differs greatly from the other three observations. The correlation coefficient between the MWR PWV and RS PWV (EC PWV) is 0.934 (0.933), and the root mean square error (RMSE) is 17.19 mm (16.05 mm), whereas the correlation coefficient between the GNSS PWV and RS PWV (EC PWV) is 0.989 (0.986), and the RMSE is 17.04 mm (15.83 mm). The scatter distributions of the MWR PWV and the other observations show a systematic deviation that is negatively correlated with the surface air temperature. After polynomial fitting and corrections are applied, the correlation coefficients between the MWR PWV and the RS PWV and EC PWV increase to 0.993 and 0.99, and the RMSEs decrease to 14.13 and 15.86 mm, respectively. The temperature and water vapor density profiles are retrieved from the bright temperature and can reflect the quality of the bright temperature. Because the PWV retrieved from the ground-based MWR has a linear relationship with the brightness temperature, the accuracy of the PWV can be analyzed in terms of the quality of the brightness temperature. We found that the differences in the temperature profile below 2000 m are smaller, whereas those in the water vapor density profile below 2000 m show the largest difference. This finding reflects the differences in the brightness temperature, which may be the cause of the inaccurate PWV observations.

Twenty years of precipitable water vapor measurements in the Chajnantor area

Context. Interest in the use of the Chajnantor area for millimeter and submillimeter astronomy is increasing because of its excellent atmospheric conditions. Knowing the general site annual variability in precipitable water vapor (PWV) can contribute to the planning of new observatories in the area. Aims. We seek to create a 20-year atmospheric database (1997−2017) for the Chajnantor area in northern Chile using a single common physical unit, PWV. We plan to extract weather relations between the Chajnantor Plateau and the summit of Cerro Chajnantor to evaluate potential sensitivity improvements for telescopes fielded in the higher site. We aim to validate the use of submillimeter tippers to be used at other sites and use the PWV database to detect a potential signature for local climate change over 20 years. Methods. We revised our method to convert from submillimeter tipper opacity to PWV. We now include the ground temperature as an input parameter to the conversion scheme and, therefore, achieve a higher conversion accuracy. Reults. We found a decrease in the measured PWV at the summit of Cerro Chajnantor with respect to the plateau of 28%. In addition, we found a PWV difference of 1.9% with only 27 m of altitude difference between two sites in the Chajnantor Plateau: the Atacama Pathfinder Experiment and the Cosmic Background Imager near the Atacama Large Millimeter Array center. This difference is possibly due to local topographic conditions that favor the discrepancy in PWV. The scale height for the plateau was extracted from the measurements of the plateau and the Cerro Chajnantor summit, giving a value of 1537 m. Considering the results obtained in this work from the long-term study, we do not see evidence of PWV trends in the 20-year period of the analysis that would suggest climate change in such a timescale.

Intercomparisons of precipitable water vapour derived from radiosonde , GPS and sunphotometer observations

The atmospheric precipitable water vapour (PWV) plays a crucial role in the hydrological cycle and energy transfer on a global scale. Radiosonde (RS), sunphotometer (SP) and GPS (as well as broader GNSS) receivers have gradually been the principal instruments for ground-based PWV observation. This study first co-locates the observation stations configured the three instruments in the globe and in three typical latitudinal climatic regions respectively, then the PWV data from the three instruments are matched each other according to the observing times. After the outliers are removed from the matched data pairs, the PWV intercomparisons for any two instruments are performed. The results show that the PWV estimates from any two instruments have a good agreement with very high correlation coefficients. The latitude and climate have no significant influence on the PWV measurements from the three instruments, indicating that the instruments are very stable and depend on their performance. The PWV differences of any two instruments display the normal distribution, indicating non-systematic biases among the two PWV datasets. The relative differences between SP and GPS are the smallest, the middle between SP and RS, and those between GPS and RS are the largest. This study will be useful to promote GPS (GNSS) and SP PWV to be a substitute for RS PWV as a benchmark because of their high temporal resolutions.

Variations in Water Vapor From AIRS and MODIS in Response to Arctic Sea Ice Change in December 2002–November 2016

Water vapor plays a vital role in the Arctic sea ice and climate change. The Atmospheric Infrared Sounder (AIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are useful tools for studying the water vapor variations over the entire Arctic. In this paper, we discuss precipitable water vapor (PWV) variations from the AIRS and MODIS Level-3 data products in response to Arctic sea ice change during December 2002–November 2016. The results indicate that both AIRS- and MODIS-derived PWV measurements tend to be underestimated, and this underestimation is generally greater for the latter than the former over both land and ocean. Additionally, both the AIRS and MODIS retrievals suggest that the atmospheres are drier in the solid sea ice pack and, to a lesser extent, in the marginal ice zone, than in the open ocean in each season. Moreover, statistically significant correlations between the PWV and sea ice concentration (SIC) anomalies are generally observed in all seasons under different ice conditions except in the open ocean, where variations in the PWV may be attributed to the poleward moisture transport from lower latitudes. The Arctic PWV and SIC variation patterns are also dominated by the atmospheric and ice conditions in the solid sea ice pack, respectively. The monthly mean PWV and SIC time series analysis further reveals that the Arctic PWV variations tend to be affected by a delayed effect of approximately 1.2–1.3 months from SIC changes from a climatological perspective.

Evaluation of HY-2A satellite-borne water vapor radiometer with shipborne GPS and GLONASS observations over the Indian Ocean

The Chinese Haiyang-2A (HY-2A) altimetry satellite is equipped with a calibration microwave radiometer (CMR) for correcting atmospheric water vapor path delay in radar altimeter observations. To evaluate the satellite-borne CMR, we retrieved 1 Hz high-frequency precipitable water vapor (PWV) using shipborne GPS and GLONASS from a two-month cruise in the Indian Ocean. This open-sea evaluation of the satellite-borne radiometer is free of the contamination of the satellite footprints induced by coastal lands, which occurs inevitably in ground-based or coastal stations. The estimates and errors of the retrieved PWV from shipborne GNSS kinematic precise point positioning were analyzed and then compared to the CMR-retrieved PWV. The results show that the shipborne GNSS kinematic precise point positioning can obtain marine PWV with an uncertainty of about 2.8 mm. When the HY-2A sub-satellite point and the ship cross, the HY-2A CMR-retrieved PWV is in good agreement with the GNSS PWV with the difference of about 0.8 mm, which demonstrates that the HY-2A satellite can contribute high-precision precipitable water vapor measurements to weather and atmospheric studies.

GPS Precipitable Water Vapor Estimations over Costa Rica: A Comparison against Atmospheric Sounding and Moderate Resolution Imaging Spectrometer (MODIS)

The quantification of water vapor in tropical regions like Central America is necessary to estimate the influence of climate change on its distribution and the formation of precipitation. This work reports daily estimations of precipitable water vapor (PWV) using Global Positioning System (GPS) delay data over the Pacific region of Costa Rica during 2017. The GPS PWV measurements were compared against atmospheric sounding and Moderate Resolution Imaging Spectrometer (MODIS) data. When GPS PWV was calculated, relatively small biases between the mean atmospheric temperatures (Tm) from atmospheric sounding and the Bevis equation were found. The seasonal PWV fluctuations were controlled by two of the main circulation processes in Central America: the northeast trade winds and the latitudinal migration of the Intertropical Convergence Zone (ITCZ). No significant statistical differences were found for MODIS Terra during the dry season with respect GPS-based calculations (p &gt; 0.05). A multiple linear regression model constructed based on surface meteorological variables can predict the GPS-based measurements with an average relative bias of −0.02 ± 0.19 mm/day (R2 = 0.597). These first results are promising for incorporating GPS-based meteorological applications in Central America where the prevailing climatic conditions offer a unique scenario to study the influence of maritime moisture inputs on the seasonal water vapor distribution.

Editorial for Special Issue “Remote Sensing of Precipitation”

This Special Issue hosts papers on all aspects of remote sensing of precipitation, including applications that embrace the use of remote-sensing techniques of precipitation in tackling issues, such as precipitation estimations and retrievals, along with their methodologies and corresponding error assessment; precipitation modelling including validation, instrument comparison, and calibration; understanding of cloud and precipitation microphysical properties; precipitation downscaling; precipitation droplet size distribution; assimilation of remotely sensed precipitation into numerical weather prediction models; and measurement of precipitable water vapor.

Pwv_kpno: A Python Package for Modeling the Atmospheric Transmission Function Due to Precipitable Water Vapor

We present a Python package, pwv_kpno, which provides models for the atmospheric transmission due to precipitable water vapor (PWV) at user-specified sites. Using the package, ground-based photometric observations taken between 3000 and 12,000 Å can be corrected for atmospheric effects due to PWV. Atmospheric transmission in the optical and near-infrared is highly dependent on the PWV column density along the line of sight. By measuring the delay of dual-band GPS signals through the atmosphere, the SuomiNet project provides accurate PWV measurements for hundreds of locations around the world. The pwv_kpno package uses published SuomiNet data in conjunction with MODTRAN models to determine the modeled, time-dependent atmospheric transmission. A dual-band GPS system was installed at Kitt Peak National Observatory (KPNO) in the spring of 2015. Using measurements from this receiver we demonstrate that we can successfully predict the PWV at KPNO from nearby dual-band GPS stations on the surrounding desert floor. The pwv_kpno package can thus provide atmospheric transmission functions for observations taken before the KPNO receiver was installed. Using PWV measurements from the desert floor, we correctly model PWV absorption features present in spectra taken at KPNO. We also demonstrate how to configure the package for use at other observatories.

Assessments of GMI-Derived Precipitable Water Vapor Products over the South and East China Seas Using Radiosonde and GNSS

Satellite remote sensing of the atmospheric water vapor distribution over the oceans is essential for both weather and climate studies. Satellite onboard microwave radiometer is capable of measuring the water vapor over the oceans under all weather conditions. This study assessed the accuracies of precipitable water vapor (PWV) products over the south and east China seas derived from the Global Precipitation Measurement Microwave Imager (GMI), using radiosonde and GNSS (Global Navigation Satellite System) located at islands and coasts as truth. PWV measurements from 14 radiosonde and 5 GNSS stations over the period of 2014–2017 were included in the assessments. Results show that the GMI 3-day composites have an accuracy of better than 5 mm. A further evaluation shows that RMS (root mean square) errors of the GMI 3-day composites vary greatly in the range of 3∼14 mm at different radiosonde/GNSS sites. GMI 3-day composites show very good agreements with radiosonde and GNSS measured PWVs with correlation coefficients of 0.896 and 0.970, respectively. The application of GMI products demonstrates that it is possible to reveal the weather front, moisture advection, transportation, and convergence during the Meiyu rainfall. This work indicates that the GMI PWV products can contribute to various studies such as climate change, hydrologic cycle, and weather forecasting.

Precipitable water vapor (PWV) estimations from the site of the Eastern Anatolia Observatory∗ (DAG), a new astronomical observatory in Turkey

We present preliminary statistics on the precipitable water vapor (PWV) content over the Karakaya Hills in Erzurum city, where the largest optical and near-infrared astronomical telescope in Turkey will be operated. Since the observatory will observe in the near-infrared (NIR), it is intended to perform PWV measurements of the atmosphere above the site by using signal delays in Global Positioning System (GPS) communication. The analysis of the GPS data recorded on the summit for almost one year shows that the atmosphere over the site of the observatory, which has an altitude of 3170 m, has favorable conditions for NIR observations. From GPS measurements, we report that the site had an average PWV of 3.2 mm and a median PWV of 2.7 mm between October 6, 2016, and June 15, 2017. We also present the time dependency of the PWV content and the correlations between the amount of PWV and the other meteorological records gathered from radiosonde flights and ground-based measurements.