Long term variability and trends of precipitable water vapor derived from GPS tropospheric path delays over the Eastern Mediterranean

This paper studies the statistical characteristics of a unique long-term high-resolution precipitable water vapor (PWV) data set at Darwin, Australia, from 12 March 2002 to 28 February 2011. To understand the convective precipitation processes for climate model development, the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) program made high-frequency radar observations of PWV at the Darwin ARM site and released the best estimates from the radar data retrievals for this time period. Based on the best estimates, we produced a PWV data set on a uniform 20-s time grid. The gridded data were sufficient to show the fractal behavior of precipitable water with Hausdorff dimension equal to 1.9. Fourier power spectral analysis revealed modulation instability due to two sideband frequencies near the diurnal cycle, which manifests as nonlinearity of an atmospheric system. The statistics of PWV extreme values and daily rainfall data show that Darwin’s PWV has El Nino Southern Oscillation (ENSO) signatures and has potential to be a predictor for weather forecasting. The right skewness of the PWV data was identified, which implies an important property of tropical atmosphere: ample capacity to hold water vapor. The statistical characteristics of this long-term high-resolution PWV data will facilitate the development and validation of climate models, particularly stochastic models.

Download Full-text

Improved Daytime Column-Integrated Precipitable Water Vapor from Vaisala Radiosonde Humidity Sensors

Journal of Atmospheric and Oceanic Technology ◽

10.1175/2007jtecha1027.1 ◽

2008 ◽

Vol 25 (6) ◽

pp. 873-883 ◽

Cited By ~ 72

Author(s):

K. E. Cady-Pereira ◽

M. W. Shephard ◽

D. D. Turner ◽

E. J. Mlawer ◽

S. A. Clough ◽

...

Keyword(s):

Water Vapor ◽

Great Plains ◽

Weather Prediction ◽

Microwave Radiometer ◽

Precipitable Water ◽

Precipitable Water Vapor ◽

Atmospheric Radiation Measurement ◽

Atmospheric Transmittance ◽

Dry Bias

Abstract Accurate water vapor profiles from radiosondes are essential for long-term climate prediction, weather prediction, validation of remote sensing retrievals, and other applications. The Vaisala RS80, RS90, and RS92 radiosondes are among the more commonly deployed radiosondes in the world. However, numerous investigators have shown that the daytime water vapor profiles measured by these instruments present a significant dry bias due to the solar heating of the humidity sensor. This bias in the column-integrated precipitable water vapor (PWV), along with variability due to calibration, can be removed by scaling the humidity profile to agree with the PWV retrieved from a microwave radiometer (MWR), as has been demonstrated by several previous studies. Infrared radiative closure analyses have shown that the MWR PWV does not present daytime versus nighttime differences; thus, scaling by the MWR is a possible approach for removing the daytime dry bias. However, MWR measurements are not routinely available at all radiosonde launch sites. Starting from a long-term series of sonde and MWR PWV measurements from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site, the authors have developed a simple correction to the column-integrated sonde PWV, derived from an analysis of the ratio of the MWR and sonde measurements; this correction is a function of the atmospheric transmittance as determined by the solar zenith angle, and it effectively removes the daytime dry bias at all solar zenith angles. The correction was validated by successfully applying it to an independent dataset from the ARM tropical western Pacific (TWP) site.

Download Full-text

A low-cost development of automatic weather station based on Arduino for monitoring precipitable water vapor

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v24.i2.pp744-753 ◽

2021 ◽

Vol 24 (2) ◽

pp. 744

Author(s):

Wayan Suparta ◽

Aris Warsita ◽

Ircham Ircham

Keyword(s):

Water Vapor ◽

Meteorological Data ◽

Low Cost ◽

Precipitable Water ◽

Precipitable Water Vapor ◽

Weather Station ◽

Automatic Weather Station ◽

Weather System ◽

Spatial And Temporal Scales

Water vapor is the engine of the weather system. Continuous monitoring of its variability on spatial and temporal scales is essential to help improve weather forecasts. This research aims to develop an automatic weather station at low cost using an Arduino microcontroller to monitor precipitable water vapor (PWV) on a micro-scale. The surface meteorological data measured from the BME280 sensor is used to determine the PWV. Our low-cost systems also consisted of a DS3231 real-time clock (RTC) module, a 16×2 liquid crystal display (LCD) module with an I<sup>2</sup>C, and a micro-secure digital (micro-SD) card. The core of the system employed the Arduino Uno surface mount device (SMD) R3 board. The measurement results for long-term monitoring at the tested sites (ITNY and GUWO) found that the daily mean error of temperature and humidity values were 1.30% and 3.16%, respectively. While the error of air pressure and PWV were 0.092% and 2.61%, respectively. The PWV value is higher when the sun is very active or during a thunderstorm. The developed weather system is also capable of measuring altitude on pressure measurements and automatically stores daily data. With a total cost below 50 dollars, all major and support systems developed are fully functional and stable for long-term measurements.

Download Full-text

Precipitable water vapor from GPS tropospheric path delays over the Eastern Mediterranean: trends, diurnal and long-term variability

10.5194/egusphere-egu21-1804 ◽

2021 ◽

Author(s):

Shlomi Ziskin Ziv ◽

Pinhas Alpert ◽

Yoav Yair ◽

Yuval Reuveni

Keyword(s):

Water Vapor ◽

Mediterranean Region ◽

Eastern Mediterranean ◽

Eastern Mediterranean Region ◽

Precipitable Water ◽

Annual Variations ◽

Diurnal Cycles ◽

Mean Trend ◽

Data Period

<p>Global Navigation Satellite System (GNSS) tropospheric path delays provide an important tool for studying Precipitable Water Vapor (PWV) variations. Here, we process and analyze PWV time series extracted from the Survey Of Israel Active Permanent Network (SOI-APN) GNSS ground receivers in the Eastern Mediterranean region. We derive the annual and seasonal PWV diurnal cycles along with the PWV long-term trends, annual and inter-annual variations. The data period spans from 5 to 21 years, ensuring its suitability for studying the PWV variations at different time scales. For the diurnal cycles, we focus on the summer months (JJA), where the Mediterranean Sea Breeze (MSB) plays a dominant role in transporting humidity inland. We find that for most stations, the diurnal amplitude in summer is the highest compared to the seasonal mean. Moreover, using the PWV peak hour in the coastal and highland stations, we detect a frontal MSB propagation from the coastline eastward inland combined with northern winds enhancement due to the Coriolis force. The peak hour is also correlated with the distance from the Mediterranean Sea shore, substantiating the MSB&#8217;s role as a key driver of the PWV diurnal variability during summer months. In addition, a strong correlation between the PWV diurnal cycle and the atmospheric Mixing Layer Height (MLH) diurnal variations is found using ceilometer data, suggesting that the MLH modulates the PWV. For the annual cycles, the PWV monthly mean values and variability are high in the summer months (JJA) however, Sep and Oct supersede the JJA values where Oct has the highest variability in all stations. We suggest that the Red-Sea Trough (RST) synoptical system plays a dominant factor in shifting the mean PWV annual peak values from the summer months to Oct. This is&#160; further substantiated by harmonic analysis which reveals a non-negligible semi-annual mode with peaks at Apr and Oct when the RST synoptical system is most frequent. The PWV inter-annual variations as represented by the monthly mean anomalies are consistent between all stations, thus suggesting a common regional driver. Moreover, a comparison between the PWV station average anomalies and the ERA5 (the European Centre for Medium-Range Weather Forecasts' latest global reanalysis) regional mean anomalies show a correlation of 0.95. Furthermore, a correlation of 0.72 was found between the regional mean moisture flux anomalies at 750 hPa taken from ERA5 and the station average PWV anomalies, implying that moisture flow accounts for most of the inter-annual variability, however the significance of the 750 hPa pressure level remains ambiguous. In the long term, we find an increasing regional mean trend of ~ 0.5 mm/decade for the whole data period (1998-2019) whereas for the last decade (2010-2019) we find a mean trend of ~ 1 mm/decade suggesting an accelerated moistening of the Eastern Mediterranean region.&#160;</p>

Download Full-text

The diurnal variability of precipitable water vapor derived from GPS tropospheric path delays over the Eastern Mediterranean

Atmospheric Research ◽

10.1016/j.atmosres.2020.105307 ◽

2021 ◽

Vol 249 ◽

pp. 105307 ◽

Cited By ~ 1

Author(s):

Shlomi Ziskin Ziv ◽

Yoav Yair ◽

Pinhas Alpert ◽

Leenes Uzan ◽

Yuval Reuveni

Keyword(s):

Water Vapor ◽

Eastern Mediterranean ◽

Precipitable Water ◽

Precipitable Water Vapor ◽

Diurnal Variability

Download Full-text

Evaluation of Precipitable Water Vapor Retrieval from Homogeneously Reprocessed Long-Term GNSS Tropospheric Zenith Wet Delay and Multi-Technique

Remote Sensing ◽

10.3390/rs13214490 ◽

2021 ◽

Vol 13 (21) ◽

pp. 4490

Author(s):

Hang Su ◽

Tao Yang ◽

Kan Wang ◽

Baoqi Sun ◽

Xuhai Yang

Keyword(s):

Water Vapor ◽

Precipitable Water ◽

Precipitable Water Vapor ◽

Systematic Bias ◽

Navigation Satellite ◽

A Posteriori ◽

Zenith Wet Delay ◽

Global Navigation ◽

Global Navigation Satellite

Water vapor is one of the most important greenhouse gases in the world. There are many techniques that can measure water vapor directly or remotely. In this work, we first study the Global Positioning System (GPS)- and the Global Navigation Satellite System (GLONASS)-derived Zenith Wet Delay (ZWD) time series based on 11 years of the second reprocessing campaign of International Global Navigation Satellite Systems (GNSS) Service (IGS) using 320 globally distributed stations. The amount of measurement, the local environment, and the antenna radome are shown to be the main factors that affect the GNSS ZWDs and the corresponding a posteriori formal errors. Furthermore, antenna radome is able to effectively reduce the systematic bias of ZWDs and a posteriori formal errors between the GPS- and GLONASS-based solutions. With the development of the GLONASS, the ZWD differences between the GPS- and the GLONASS-based solutions have gradually decreased to sub-mm-level after GLONASS was fully operated. As the GPS-based Precipitable Water Vapor (PWV) is usually used as the reference to evaluate the other PWV products, the PWV consistency among several common techniques is evaluated, including GNSSs, spaceborne sensors, and numerical products from the European Center for Medium-Range Weather Forecasts (ECMWF). As an example of the results from a detailed comparison analysis, the long-term global analysis shows that the PWV obtained from the GNSS and the ECMWF have great intra-agreements. Based on the global distribution of the magnitude of the PWV and the PWV drift, most of the techniques showed superior agreement and proved their ability to do climate research. With a detailed study performed for the ZWDs and PWV on a long-term global scale, this contribution provides a useful supplement for future research on the GNSS ZWD and PWV.

Download Full-text

KORELASI MUSIMAN ANTARA ZENITH WET DELAY (ZWD) DAN DEBIT SUNGAI DI DAS CIKAPUNDUNG HULU, KAWASAN BANDUNG UTARA, JAWA BARAT

Seminar Nasional Geomatika ◽

10.24895/sng.2018.3-0.1033 ◽

2019 ◽

Vol 3 ◽

pp. 741

Author(s):

Wedyanto Kuntjoro ◽

Z.A.J. Tanuwijaya ◽

A. Pramansyah ◽

Dudy D. Wijaya

Keyword(s):

Water Vapor ◽

Precipitable Water ◽

Precipitable Water Vapor ◽

Zenith Wet Delay

Kandungan total uap air troposfer (precipitable water vapor) di suatu tempat dapat diestimasi berdasarkan karakteristik bias gelombang elektromagnetik dari satelit navigasi GPS, berupa zenith wet delay (ZWD). Pola musiman deret waktu ZWD sangat penting dalam studi siklus hidrologi khususnya yang terkait dengan kejadian-kejadian banjir. Artikel ini menganalisis korelasi musiman antara ZWD dan debit sungai Cikapundung di wilayah Bandung Utara berdasarkan estimasi rataan pola musimannya. Berdasarkan rekonstruksi sejumlah komponen harmonik ditemukan bahwa pola musiman ZWD memiliki kemiripan dan korelasi yang kuat dengan pola musiman debit sungai. Pola musiman ZWD dan debit sungai dipengaruhi secara kuat oleh fenomena pertukaran Monsun Asia dan Monsun Australia. Korelasi linier di antara keduanya menunjukkan hasil yang sangat kuat, dimana hampir 90% fluktuasi debit sungai dipengaruhi oleh kandungan uap air di troposfer dengan level signifikansi 95%. Berdasarkan spektrum amplitudo silang dan koherensi, kedua kuantitas ini nampak didominasi oleh siklus monsun satu tahunan disertai indikasi adanya pengaruh siklus tengah tahunan dan 4 bulanan.

Download Full-text

HGPT2: An ERA5-Based Global Model to Estimate Relative Humidity

Remote Sensing ◽

10.3390/rs13112179 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2179

Author(s):

Pedro Mateus ◽

Virgílio B. Mendes ◽

Sandra M. Plecha

Keyword(s):

Water Vapor ◽

Relative Humidity ◽

Real Time ◽

Prediction Models ◽

Weather Prediction ◽

Precipitable Water ◽

Precipitable Water Vapor ◽

Global Navigation Satellite Systems ◽

International Gnss Service ◽

Weighted Mean Temperature

The neutral atmospheric delay is one of the major error sources in Space Geodesy techniques such as Global Navigation Satellite Systems (GNSS), and its modeling for high accuracy applications can be challenging. Improving the modeling of the atmospheric delays (hydrostatic and non-hydrostatic) also leads to a more accurate and precise precipitable water vapor estimation (PWV), mostly in real-time applications, where models play an important role, since numerical weather prediction models cannot be used for real-time processing or forecasting. This study developed an improved version of the Hourly Global Pressure and Temperature (HGPT) model, the HGPT2. It is based on 20 years of ERA5 reanalysis data at full spatial (0.25° × 0.25°) and temporal resolution (1-h). Apart from surface air temperature, surface pressure, zenith hydrostatic delay, and weighted mean temperature, the updated model also provides information regarding the relative humidity, zenith non-hydrostatic delay, and precipitable water vapor. The HGPT2 is based on the time-segmentation concept and uses the annual, semi-annual, and quarterly periodicities to calculate the relative humidity anywhere on the Earth’s surface. Data from 282 moisture sensors located close to GNSS stations during 1 year (2020) were used to assess the model coefficients. The HGPT2 meteorological parameters were used to process 35 GNSS sites belonging to the International GNSS Service (IGS) using the GAMIT/GLOBK software package. Results show a decreased root-mean-square error (RMSE) and bias values relative to the most used zenith delay models, with a significant impact on the height component. The HGPT2 was developed to be applied in the most diverse areas that can significantly benefit from an ERA5 full-resolution model.

Download Full-text