GPS Meteorology Research Articles

Variations in GPS precipitable water vapor and rainfall during the 2006–2019 Mei-yu season in Taiwan

The Mei-yu season contributes 26.3% of the annual precipitation and provides important water resources to Taiwan. GPS meteorology derives continuous, real-time and high spatial coverage of perceptible water vapor (PWV), which supports weather forecasting for rainfall indicators. This study analyzes the long-term spatial–temporal changes in GPS PWV and rainfall data during the Mei-yu season from 2006 to 2019. The daily average data show that the Mei-yu season extended in recent years. Both daily rainfall and PWV increase in mid-May and rainfall reaches a maximum in early June, while PWV maintains stable in June. The yearly results show that the trend of the accumulated rainfall in the Mei-yu season is flat, and that PWV increases by 13% over 14 years, which may be due to global warming as the trend of temperature increases by 8%. Spatially, PWV is significantly higher in southern Taiwan during the Mei-yu season, and rainfall increased the most in both the central and southern mountain regions.

GPS Meteorology : Error in the estimation of precipitable water by ground based GPS system in some meso-scale thunderstorms - A case study

Remote sensing by ground based GPS receivers provide continuous and accurate measurement of precipitable water (PW) of an order of 1.5 mm comparable to radiosondes and water vapour radiometers. In the present work we have examined the amount of PW variation in three thunderstorms accompanied with rain shower that occurred over the GPS station. In all the three thunderstorms event heavy rain was reported. However on comparison of observed rainfall with GPS estimated precipitable water (hourly) in real time, it is observed that among the three, in one event the amount of precipitable water (PW) is much less (~20mm) for the same amount of rainfall. After analysing and taken into account various source of error, we suspect that in a mesoscale thunderstorms or squall lines associated with heavy rainfall, discrepancies arise because the wet mapping functions that used to map the wet delay at any angle to the zenith do not represent the localized atmospheric condition particularly for narrow towering thunder clouds and non-availability of GPS satellites in the zenith direction. On the other hand for the larger thunder cells the atmosphere is very nearly azimuthally symmetric with respect to GPS receiver, the error due to the wet mapping function is minimal.

A GPS water vapour tomography method based on a genetic algorithm

Abstract. Water vapour is an important substituent of the atmosphere but its spatial and temporal distribution is difficult to detect. Global Positioning System (GPS) water vapour tomography, which can sense three-dimensional water vapour distribution, has been developed as a research area in the field of GPS meteorology. In this paper, a new water vapour tomography method based on a genetic algorithm (GA) is proposed to overcome the ill-conditioned problem. The proposed approach does not need to perform matrix inversion, and it does not rely on excessive constraints, a priori information or external data. Experiments in Hong Kong under rainy and rainless conditions using this approach show that there is a serious ill-conditioned problem in the tomographic matrix by grayscale and condition numbers. Numerical results show that the average root mean square error (RMSE) and mean absolute error (MAE) for internal and external accuracy are 1.52∕0.94 and 10.07∕8.44 mm, respectively, with the GAMIT-estimated slant water vapour (SWV) as a reference. Comparative results of water vapour density (WVD) derived from radiosonde data reveal that the tomographic results based on GA with a total RMSE ∕ MAE of 1.43∕1.19 mm are in good agreement with that of radiosonde measurements. In comparison to the traditional least squares method, the GA can achieve a reliable tomographic result with high accuracy without the restrictions mentioned above. Furthermore, the tomographic results in a rainless scenario are better than those of a rainy scenario, and the reasons are discussed in detail in this paper.

Precipitable water vapour estimation using the permanent single GPS station in Zanjan, Iran

ABSTRACTMeteorological investigations using the global positioning system (GPS) are based on expensive permanent networks and they are not developed globally on the Earth. In this study it is confirmed that single station GPS meteorology is feasible where there is no possibility for development of a sophisticated dense GPS network. Since 1 January 2011 a GPS station has been installed in the Institute for Advanced Studies in Basic Sciences in the province of Zanjan, Iran, where upper air meteorological data are not available. The GPS data were processed in order to estimate the zenith total delay (ZTD) of GPS signals due to the troposphere. The estimated ZTD was then transformed to precipitable water vapour (PWV) using the ERA‐Interim globally available humidity and temperature vertical profiles. Three kinds of validation were applied to the estimated PWV and all of them reasonably proved the validity of the GPS results: (1) the measured surface water vapour pressure and dew point temperature show 87.8 and 86.6% correlation respectively with the estimated PWV; (2) the PWV measured using radiosondes in three neighbouring cities of Zanjan (Tabriz, Tehran and Kermanshah) with nearly the same climatic regime show 81.1, 71.7 and 66.4% correlation respectively with the GPS PWV time series, and (3) the global reanalysis datasets for Zanjan show 89.2% correlation with the GPS results. These validations indicate that, in the absence of permanent GPS networks, if proper data processing strategies are adopted the low cost single station GPS meteorology can be considered as a possibility for meteorological monitoring.

Deep Convection and Column Water Vapor over Tropical Land versus Tropical Ocean: A Comparison between the Amazon and the Tropical Western Pacific

Abstract The relationships between the onset of tropical deep convection, column water vapor (CWV), and other measures of conditional instability are analyzed with 2 yr of data from the DOE Atmospheric Radiation Measurement (ARM) Mobile Facility in Manacapuru, Brazil, as part of the Green Ocean Amazon (GOAmazon) campaign, and with 3.5 yr of CWV derived from global positioning system meteorology at a nearby site in Manaus, Brazil. Important features seen previously in observations over tropical oceans—precipitation conditionally averaged by CWV exhibiting a sharp pickup at high CWV, and the overall shape of the CWV distribution for both precipitating and nonprecipitating points—are also found for this tropical continental region. The relationship between rainfall and CWV reflects the impact of lower-free-tropospheric moisture variability on convection. Specifically, CWV over land, as over ocean, is a proxy for the effect of free-tropospheric moisture on conditional instability as indicated by entraining plume calculations from GOAmazon data. Given sufficient mixing in the lower troposphere, higher CWV generally results in greater plume buoyancies through a deep convective layer. Although sensitivity of buoyancy to other controls in the Amazon is suggested, such as boundary layer and microphysical processes, the CWV dependence is consistent with the observed precipitation onset. Overall, leading aspects of the relationship between CWV and the transition to deep convection in the Amazon have close parallels over tropical oceans. The relationship is robust to averaging on time and space scales appropriate for convective physics but is strongly smoothed for averages greater than 3 h or 2.5°.

Establishment and analysis of global gridded Tm − Ts relationship model

In ground-based GPS meteorology, Tm is a key parameter to calculate the conversion factor that can convert the zenith wet delay (ZWD) to precipitable water vapor (PWV). It is generally acknowledged that Tm is in an approximate linear relationship with surface temperature Ts, and the relationship presents regional variation. This paper employed sliding average method to calculate correlation coefficients and linear regression coefficients between Tm and Ts at every 2° × 2.5° grid point using Ts data from European Centre for Medium-Range Weather Forecasts (ECMWF) and Tm data from “GGOS Atmosphere”, yielding the grid and bilinear interpolation-based TmGrid model. Tested by Tm and Ts grid data, Constellation Observation System of Meteorology, Ionosphere, and Climate (COSMIC) data and radiosonde data, the TmGrid model shows a higher accuracy relative to the Bevis Tm − Ts relationship which is widely used nowadays. The TmGrid model will be of certain practical value in high-precision PWV calculation.

Cooperation on GPS Meteorology between the United States and Cuba

Abstract In May 2014 a team of atmospheric and geodetic scientists from UNAVCO and the University Corporation for Atmospheric Research (UCAR) sent and helped set up a global positioning system (GPS) receiver to measure atmospheric water vapor at the Grupo de Óptica Atmosférica de Camagüey (GOAC) at the Camagüey Meteorological Center in Camagüey, Cuba. The GPS receiver immediately began to produce observations of precipitable water, which are being shared with the international meteorological community. Obtaining permission from both sides to send a highly sensitive instrument from the United States to Cuba was not easy. This paper describes the series of events that led to this achievement, beginning with a North Atlantic Treaty Organization (NATO) workshop in Rome, Italy, in 1994 in which Alan Robock met a young Cuban scientist named Juan Carlos Antuña and accepted him as a graduate student at the University of Maryland, College Park. The GPS meteorology connection began with a March 2007 visit of a delegation from the United States headed by then American Meteorological Society (AMS) President Richard Anthes to Havana, Cuba, at the invitation of the Cuban Meteorological Society president, Andrés Planas. These two threads led to this remarkable cooperation between Cuban and U.S. scientists. Several visits to Cuba beginning in 2010 by Robock, who met former President of Cuba Fidel Castro and the science advisor to the president of Cuba, played a significant role. This is another instance (the visit of the AMS delegation to China in 1974 was a prime example) of how communication and visits between meteorologists in countries that are at odds on many other issues can lead to lasting collaborations that benefit both countries as well as the international community.

Geostationary Satellite Observation of Precipitable Water Vapor Using an Empirical Orthogonal Function (EOF) based Reconstruction Technique over Eastern China

Water vapor, as one of the most important greenhouse gases, is crucial for both climate and atmospheric studies. Considering the high spatial and temporal variations of water vapor, a timely and accurate retrieval of precipitable water vapor (PWV) is urgently needed, but has long been constrained by data availability. Our study derived the vertically integrated precipitable water vapor over eastern China using Multi-functional Transport Satellite (MTSAT) data, which is in geostationary orbit with high temporal resolution. The missing pixels caused by cloud contamination were reconstructed using an Empirical Orthogonal Function (EOF) decomposition method over both spatial and temporal dimensions. GPS meteorology data were used to validate the retrieval and the reconstructed results. The diurnal variation of PWV over eastern China was analyzed using harmonic analysis, which indicates that the reconstructed PWV data can depict the diurnal cycle of PWV caused by evapotranspiration and local thermal circulation.

Ambiguity Resolution In Precise Point Positioning Technique: A Case Study

Abstract Because of the dynamics of the GPS technique used in different domains like geodesy, near real-time GPS meteorology, geodynamics, the precise point positioning (PPP) becomes more than a powerful method for determining the position, or the delay caused by the atmosphere. The main idea of this method is that we need only one receiver – preferably that have dual frequencies pseudorange and carrier-phase capabilities – to obtain the position. Because we are using only one receiver the majority of the residuals that are eliminated in double differencing method, we have to estimate them in PPP. The development of the PPP method allows us, to use precise satellite clock estimates, and precise orbits, resulting in a much more efficient way to deal with the disadvantages of this technique, like slow convergence time, or ambiguity resolution. Because this two problem are correlated, to achieve fast convergence we need to resolve the problem of ambiguity resolution. But the accuracy of the PPP results are directly influenced by presence of the uncalibrated phase delays (UPD) originating in the receivers and satellites. In this article we present the GPS errors and biases, the zenith wet delay and the necessary time for obtaining the convergence. The necessary correction are downloaded by using the IGS service.

GPS derived Zenith Total Delay (ZTD) observed at tropical locations in South India during atmospheric storms and depressions

Global Positioning System (GPS) monitoring of Zenith Total Delay (ZTD) of the troposphere which is related to water vapor is important as it may help us in weather forecasting. The atmospheric water vapor varies according to the season and it also varies quickly on short temporal and spatial scales during stormy periods. Thus it plays a crucial role in meteorology. GPS is one of the relatively inexpensive tools available to monitor the water vapor content in the atmosphere. In the present study, the efficacy of GPS data to monitor perturbations in tropospheric water content (GPS meteorology) associated with atmospheric storms and depressions is investigated utilizing the data from a tropical region of India, recorded between 15th October, 2010 and 27th December, 2010 during which Southern India was affected by a few significant atmospheric events. The ZTD was estimated for this period at the NGRI operated GPS stations at Hyderabad (HYDE) and MS University, Tirunelveli (MSUN). The accuracy of GPS derived ZTD was validated from the close match seen with ZTD values estimated from numerical weather modeling data. During the stormy periods there were strong variations of the ZTD. Corresponding changes in precipitable water vapor were estimated for the International GNSS Service station HYDE. The average ZTD was found to be higher near the coastal station at MSUN and less at the inland station HYDE. Most of the observed peaks in the ZTD time series were well correlated to the atmospheric events that influenced the region. The study extended to two more locations in the equatorial Indian Ocean region showed spatial variations in the ZTD values, which suggest the weakening of ZTD towards the coast. Our observations are yet another illustration for the application of GPS observations to monitor tropospheric water content variations associated with severe atmospheric events.

TREND IN GROUND-BASED GPS SENSING OF ATMOSPHERIC WATER VAPOUR: THE MALAYSIAN PERSPECTIVE

Atmospheric water vapour is the most variable component of the atmosphere. It plays a crucial role in Earth‘s energy balance and hydrological cycles. Because of its temporal and spatial variability, accurate measurement of atmospheric water vapour has been very challenging in meteorology. However, the Global Positioning System (GPS) offers detailed coverage, all weather and continuous observations. Therefore, exploring this potential to deliver atmospheric information is now termed ‗GPS meteorology‘. This paper presents a brief overview of global trend in GPS meteorology while discussing GPS meteorology research efforts in Malaysia. A summary of the current research activity towards realisation of operational use of GPS meteorology in Malaysia is also highlighted.

Development of Time-dependent mean Temperature Equations for GPS Meteorology

ABSTRACT The mean temperature is one of the key parameters in computing Precipitable Water Vapor (PWV) from Global Positioning System (GPS) measurements and is usually derived as a function of surface temperature through the use of a mean temperature equation (MTE). In this study, two new types of MTEs were developed as functions solely of the observation time so that the mean temperature can be obtained without surface temperature measurements. To validate the new models, we created one-year time series of GPS-derived PWV using the new MTEs and compared them with the radiosonde-observed PWV. The bias and root-mean-square error were on the other of ~1 mm and ~2 mm, respectively. Keywords: GPS, GPS meteorology, mean temperature equation, precipitable water vapor parameter in translating ZWD into PWV. Bevis et al. (1992) suggested that the mean temperature of the atmosphere can be approximated by the surface temperature. The Bevis model (Bevis et al. 1992) was developed using radiosonde measurements taken at 13 sites in North America. Emardson & Derks (2000) developed a model more suited to the climatic conditions of Europe. Liou et al. (2000) developed a local MTE model in addition to monthly MTEs, based on meteorological observations in Taiwan. Woo (2003) and Ha et al. (2006) developed local MTEs based on radiosonde observations in South Korea. All the MTE models mentioned in this paragraph are given as linear functions of the surface temperature and thus temperature-measuring devices should be co-located at the GPS siteIn this study, we propose two new types of mean temperature models, in which surface temperature measurements are unnecessary. The novel concepts behind the newly developed MTE models are introduced in the following section and validation results through the error analysis of GPS PWV values obtained with new models are described in Section 3.

GTm-III: a new global empirical model for mapping zenith wet delays onto precipitable water vapour

SUMMARY The weighted mean temperature (Tm) is a critical parameter in research of GPS meteorology. Recently, we have established two global Tm models, GTm-I and GTm-�, using groundbased radiosonde data. These two models, which directly use the location and the day of year to calculate Tm, consider the annual cycle only. In this study, we further take into account the variation characteristics of Tm in semi-annual and diurnal periodicity and estimate the initial phase of each cycle. A more accurate global empirical Tm model called GTm-III is constructed using high-precision Global Geodetic Observing System (GGOS) AtmosphereTm grid data, and then validated using a new set ofTm grid data, radiosonde data and Constellation Observation System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation data. Results indicate that compared to the existing global Tm models, GTm-III provides Tm estimates of high accuracy on a global scale and the predicted values are close to the true values in every moment of every day.

Impact of on-site atmospheric water vapor estimation methods on the accuracy of local solar irradiance predictions

Various types of precipitable water (PW) measurement are compared for different sites around Tucson, Arizona, where arid conditions prevail, and the sensitivity of irradiance to PW variations is largest. The accuracy of some determinations of this quantity is assessed by comparison with routine GPS meteorology data. Large scatter is obtained with all types of empirical functions relating PW to surface temperature and humidity data, but the climate sensitivity of this kind of determination is found lowest when relating PW to the surface specific humidity, rather than the more usual vapor pressure or dew point temperature. The impact on the accuracy of predicted direct normal irradiance (DNI) and global horizontal irradiance (GHI) of various sources of PW data, at either low or high temporal resolution, is assessed using predictions from the REST2 radiative model, in combination with co-located sunphotometric and radiometric data at Tucson during a 7-month period. Results suggest that the accuracy of the predicted DNI and GHI is only lightly sensitive to the uncertainty in the input PW data. In case PW is not measured locally, a convenient source of data is provided by reanalysis, such as from the MERRA model.

Preliminary Design for near Real-Time GPS Meteorology over Peninsular Malaysia (G-MeM)

This paper presents a conceptual approach for near real time Global Positioning System (GPS) meteorology in Malaysia using combined space- and ground-based GPS observations. Data from a single GPS station is utilised to derive wet refractivities for comparison with radio occultation (RO). This study shows that the wet refractivities from the ground-based GPS present similar patterns and better correlation with the radiosonde data than that from the space-based GPS RO data at altitudes between 0 - 5 km. Similarly, the wet refractivities derived from RO are more highly correlated with the radiosonde data than the ground-based GPS at altitudes above 5 km. The residual Nwvary from -9.25 - 21.136 N-unit at 00 h UTC for the ground-based GPS while for the GPS RO, it is -19 - 9.259 N-unit at 00 h UTC.

Improved one/multi-parameter models that consider seasonal and geographic variations for estimating weighted mean temperature in ground-based GPS meteorology

In ground-based GPS meteorology, weighted mean temperature is the key parameter to calculate the conversion factor which will be used to map zenith wet delay to precipitable water vapor. In practical applications, we can hardly obtain the vertical profiles of meteorological parameters over the site, thus cannot use the integration method to calculate weighted mean temperature. In order to exactly calculate weighted mean temperature from a few meteorological parameters, this paper studied the relation between weighted mean temperature and surface temperature, surface water vapor pressure and surface pressure, and determined the relationship between, on the one hand, the weighted mean temperature, and, on the other hand, the surface temperature and surface water vapor pressure. Considering the seasonal and geographic variations in the relationship, we employed the trigonometry functions with an annual cycle and a semi-annual cycle to fit the residuals (seasonal and geographic variations are reflected in the residuals). Through the above work, we finally established the GTm-I model and the PTm-I model with a $$2^{\circ }\times 2.5^{\circ }(\mathrm{lat}\times \mathrm{lon})$$ resolution. Test results show that the two models both show a consistent high accuracy around the globe, which is about 1.0 K superior to the widely used Bevis weighted mean temperature–surface temperature relationship in terms of root mean square error.

Preliminary study of GNSS meteorology techniques in Algeria

Northern Algeria has a Mediterranean type of climate with cool, wet winters and hot, dry summers, like several other countries in the world, and it is exposed to the problems of desertification. Along its coast, mean annual precipitation is 384 mm, so more than 75% of its territory has an annual precipitation below 384 mm. This is an issue of global scale affecting vast numbers of people and land area, and is now one of the most significant environmental problems in Algeria. Algeria is still not covered by the global navigation satellite system (GNSS) permanent stations network, despite its advantages as a novel technology for environmental development and strategy. The work presented here aims to show a preliminary study of GNSS meteorology techniques in Algeria. We propose a method to develop the available Algerian weighted mean temperature equation (AWMTE) for application in the region, by using the Algerian radiosonde network in the World Meteorological Organization (WMO). The relationship between AWMTE and surface temperature was obtained using radiosonde observations for a period of 3 years (2005–2007). The weighted mean temperature estimated from the regressed formula is higher than that from the formula of Bevis, Businger, and Chiswell [1994. “GPS Meteorology: Mapping Zenith Wet Delays Onto Precipitable Water.” Journal of Applied Meteorology 33: 379–386]. The GNSS approach requires prior knowledge of the relationship between the weighted mean temperature of the atmosphere and surface temperature, where the regression relationship is derived based on the same period of climatological data observed by radiosonde and surface meteorological instruments. Similarly, the water vapour radio sound (WVR) scheme needs prior information on the relationship between sky brightness temperature and precipitable water (PW), whose regression relationship is characterized based on the same data set. It suggests that the regressed formula for estimation of the weighted mean temperature equation will be beneficial for the estimation of the GNSS precipitable water vapour (PWV). The water vapour content of the atmosphere plays an essential role in the water budget of the Earth. This study in Algeria was carried out in order to better understand climate variability by using radio sounding and space technology (GNSS) to enhance society's skills to plan and respond, to serve society's needs for weather, and to provide information on water and environment, taking into account the socio-economic hazards and the study of the hydrologic and socio-economic processes.

A High-Resolution, Precipitable Water Vapor Monitoring System Using a Dense Network of GNSS Receivers

This work describes a system aimed at the near realtimemonitoring of precipitable water vapor (PWV) by means of a dense network of Global Navigation Satellite System (GNSS) receivers. These receivers are deployed with a horizontal spacing of 1-2 km around the Uji campus of Kyoto University, Japan. The PWV observed using a standard GPS meteorology technique, i.e., by using all satellites above a low elevation cutoff, is validated against radiosonde and radiometer measurements. The result is a RMS difference of about 2 mm. A more rigorous validation is done by selecting single GPS slant delays as they pass close to the radiosonde or the radiometer measuring directions, and higher accuracy is obtained. This method also makes it possible to preserve short-term fluctuations that are lost in the standard technique due to the averaging of several slant delays. Geostatistical analysis of the PWV observations shows that they are spatially correlated within the area of interest; this confirms that such a dense network can detect inhomogeneous distributions in water vapor. The PWV horizontal resolution is improved by using high-elevation satellites only, with the aim of exploiting at best the future Quasi-Zenith Satellite System (QZSS), which will continuously provide at least one satellite close to the zenith over Japan.

Analysis of the weighted mean temperature of china based on sounding and ECMWF reanalysis data

Weighted mean temperature (Tm) is one of the most important conversion parameters for calculating precipitable water vapor by the signal path wet delay in ground-based GPS meteorology. This paper first discusses the Tm regression models for Hong Kong (HK) and the associated error statistics relative to the true values of Tm from the numerical method. The results show that there is little difference in precision between annual and seasonal Tm regression models for HK. The Bevis Tm-Ts (surface temperature) regression model is more suitable for northeastern China and the Qinghai-Tibetan Plateau than the local models. For areas lack of historical sounding data, the Kriging interpolation method and the ECMWF reanalysis product ERA-interim were employed to set up local Tm-Ts models. The results indicate that the Tm derived by the ERA-interim data coincides well with that by the sounding data, and the Kriging interpolation method can successfully obtain the coefficients of local Tm-Ts models, suggesting that these two approaches may serve as effective ways in the acquisition and localization of Tm.

GPS meteorology: An investigation of ocean‐based precipitable water estimates

A study of ship‐based precipitable water (PW) estimation using the global positioning system (GPS) is presented for a field experiment in the coastal waters of Hawai‘i. GPS precipitable water estimates, with a temporal resolution of 30 min, are shown to agree with radiosonde observations with an RMS error of 2.16 mm. The GPS PW time series is shown to possess significant value in identifying atmospheric features at both synoptic and mesoscale resolution throughout the experiment. Examples include influences from an upper level low‐pressure system, shear lines, island blocking, and zones of low level convergence. Given PW's high spatial and temporal variability and the fact that it is not dynamically tied to other variables such as pressure or temperature, future PW estimates from ships could provide an important constraint for numerical weather prediction (NWP) models over ocean regions.