Variation Of Precipitable Water Vapor Research Articles

Seasonal and intraseasonal variability of precipitable water vapour in the Chajnantor plateau, Chile

ABSTRACTThe Chajnantor plateau is located in the Atacama Desert at over 4800 m above sea level. The plateau features a large fraction of days during the year where dry and stable atmospheric conditions predominate. The suitability of the type of astronomy observations routinely made at sites across the Chajnantor region at different times of the year depends on the variability of atmospheric water vapour.In this work, we study seasonal and intraseasonal variability associated with periods of large and low precipitable water vapour (PWV) in the Chajnantor region over 32 years. We establish large‐scale conditions favourable for above‐ and below‐normal PWV for each of the four seasons. We also explore whether intraseasonal PWV variations are related to the Madden–Julian Oscillation (MJO). Below‐normal PWV in winter, spring, and autumn seasons was found associated with mostly zonal 500‐hPa winds, which advect drier than normal air from the anticyclone over the eastern portions of the southeast (SE) Pacific Ocean. In summer, periods with below‐normal PWV were found to have anomalously south‐westerly winds at mid‐levels, also indicating transport of anomalously dry air from the stable SE Pacific. In winter, spring, and autumn seasons, above‐normal PWV was generally associated with north‐westerly mid‐tropospheric wind anomalies, indicating advection of above‐normal PWV from the subtropical and tropical regions of the SE Pacific Ocean. Above‐normal PWV conditions in summer were associated with nearly calm winds at 500 hPa. Months and phases of the MJO for the most extreme anomalies of PWV for each season agreed well with the seasonal anomalies. Furthermore, three independent reanalysis data sets generally agreed on MJO phases associated with largest positive and negative PWV anomalies. This agreement provides evidence for the first time that the MJO modulates the PWV content over the Atacama Desert.

Effect of tropospheric models on derived precipitable water vapor over Southeast Asia

An interesting subject in the field of GPS technology is estimating variation of precipitable water vapor (PWV). This estimation can be used as a data source to assess and monitor rapid changes in meteorological conditions. So far, numerous GPS stations are distributed across the world and the number of GPS networks is increasing. Despite these developments, a challenging aspect of estimating PWV through GPS networks is the need of tropospheric parameters such as temperature, pressure, and relative humidity (Liu et al., 2015). To estimate the tropospheric parameters, global pressure temperature (GPT) model developed by Boehm et al. (2007) is widely used in geodetic analysis for GPS observations. To improve the accuracy, Lagler et al. (2013) introduced GPT2 model by adding annual and semi-annual variation effects to GPT model. Furthermore, Boehm et al. (2015) proposed the GPT2 wet (GPT2w) model which uses water vapor pressure to improve the calculations. The global accuracy of GPT2 and GPT2w models has been evaluated by previous researches (Fund et al., 2011; Munekane and Boehm, 2010); however, investigations to assess the accuracy of global tropospheric models in tropical regions such as Southeast Asia is not sufficient. This study tests and examines the accuracy of GPT2w as one of the most recent versions of tropospheric models (Boehm et al., 2015). We developed a new regional model called Malaysian Pressure Temperature (MPT) model, and compared this model with GPT2w model. The compared results at one international GNSS service (IGS) station located in the south of Peninsula Malaysia shows that MPT model has a better performance than GPT2w model to produce PWV during monsoon season. According to the results, MPT has improved the accuracy of estimated pressure and temperature by 30% and 10%, respectively, in comparison with GPT2w model. These results indicate that MPT model can be a good alternative tool in the absence of meteorological sensors at GPS stations in Peninsula Malaysia. Therefore, for GPS-based studies, we recommend MPT model to be used as a complementary tool for the Malaysia Real-Time Kinematic Network to develop a real-time PWV monitoring system.

On the Variability of Precipitable Water Vapor and Its Probabilistic Modeling of Precipitation Occurrence in Davao City

On the Variability of Precipitable Water Vapor and Its Probabilistic Modeling of Precipitation Occurrence in Davao City

Trends and Variability in Precipitable Water Vapor throughout North China from 1979 to 2015

This study analyzed the variability and trends in precipitable water vapor (PWV) in North China from 1979 to 2015. The spatial distribution of annual mean PWV was generally characterized by two high PWV centers in Eastern China and the Tarim Basin and two low PWV centers in Northern Tibet and Qinghai Province and in Inner Mongolia. The levels of seasonal mean PWV were highest in summer, followed by autumn and spring, and lowest in winter. The maximum monthly mean PWV occurred in July and August, while the minimum occurred in December to February. Increasing trends in PWV, with the trend magnitude ranging from 0.1 to 1.2 mm decade−1 over North China, were observed in the radiosonde, ERA-interim, and MERRA-2 PWV data from 1979 to 1999; but a slightly decreasing trend of −0.4 mm decade−1 from radiosonde was found in most regions of North China from 1979 to 2007. A monotonically increasing PWV trend was detected throughout North China between 1979 and 1999, with the maximum trend occurring in summer and the minimum occurring in winter. For the period of 1979–2007, a slightly but less marked decreasing trend was found at most stations in North China in all four seasons.

Inter annual, spatial, seasonal, and diurnal variability of precipitable water vapour over northeast India using GPS time series

ABSTRACTWe present multi-scale variability of GPS-derived column integrated precipitable water vapour (PWV) estimated over five continuous GPS sites of northeast India from 2004 to 2012. PWV is estimated from GPS-derived zenith total delay using observed surface pressure and temperature from collocated meteorological sensors as well as obtained by interpolating European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis project (ERA-Interim) global reanalysis dataset. PWV estimated using ERA-Interim-derived parameters compare well with the PWV estimated using observed meteorological parameters with bias of less than ± 0.1 mm and highest root mean square error of 0.56 mm. The average PWV for the study period is about 17 mm at Bomdila in the Eastern Himalayas, about 20 mm at Shillong in Shillong plateau, about 31 mm at Lumami in Arokan-Yoma Hill ranges, and about 43 mm at Guwahati and Tezpur in Assam valley. The high altitude sites show low annual PWV variability (around 49%) than the low altitude sites (around 63–67%). Seasonal PWV value coincides with the monsoon with maximum in summer and minimum in the winter. However, percentage seasonal PWV variability is found to be almost same (around 68%) for all the five sites. The Assam valley sites do not show a distinct diurnal cycle whereas the high altitude sites indicate a distinct diurnal cycle coinciding with the daily solar cycle. Insights in to GPS PWV variability and rainfall are presented for the study period.

Retrieval of column-integrated water vapour from MODIS and analysis of its monthly and seasonal variability over several typical cities in China

Column-integrated water vapour also called Precipitable Water Vapour (PWV), is one of the main parameters influencing the global climate change. Due to its high spatial and temporal variability PWV has been found to be a good tracer of atmospheric motions. Retrieving PWV from Moderate Resolution Imaging Spectroradiometer (MODIS) data has the merits of high spatial resolution and low cost. In this paper, an algorithm for retrieving PWV using several MODIS near-IR channels data is first presented. Six typical cities in China with different climate are selected for study. These are Beijing, Shanghai, Guangzhou, Chengdu, Wuhan and Lanzhou. The variations of PWV in recent13 years (2001-2013) over six cities have been analyzed. The study brings out an increasing trend of annual average of water vapour over these cities in recent 13 years. The results also indicate that PWV reaches the highest value in summer, decreases in autumn, further decrease in spring, and is lowest in winter. PWV in summer over the six cities have been increasing in recent 13 years, but PWV in autumn and winter have been decreasing over inland cities, such as Wuhan and Beijing. Possible reasons for such observed trends are given in this paper.

Variability of GPS water vapor associated with warming activity in Peninsular Malaysia during the period of 2008–2011

This study utilizes the precipitable water vapor (PWV) parameter retrieved from ground-based global positioning system (GPS) to detect warming activity in Peninsular Malaysia from 2008 to 2011. Daily average of GPS PWV and surface meteorology data taken from six selected stations over Peninsular Malaysia are analyzed. Prior to warming detection, GPS PWV results are compared with PWV obtained from Radiosonde and found a positive relationship. The daily GPS PWV variability was characterized as high during the inter-monsoon seasons (April-May and October-November) and lower at the beginning, middle and the end of the year. For the monthly variations, GPS PWV increased by about 2.40 mm, which is correlated with an increase in surface temperature of 0.20 °C. We detected variability of PWV with a semiannual variation and the pattern is opposite to the accumulated precipitation, indicating that wet and dry spells coincide with local monsoon and intermonsoon periods. The warming effect in this study was felt over all selected stations with northern parts of Peninsular Malaysia affected significantly. The results imply that GPS is a powerful tool for analysis of warming effects and the mechanism of how it affects the circulation of water vapor is discussed in this study.

Analysis of Temporal and Spatial Variation of Precipitable Water Vapor According to Path of Typhoon EWINIAR using GPS Permanent Stations

In this study, the temporal and spatial variation in precipitable water vapor (PWV) was analyzed for typhoon Ewiniar which had made landfall in the Korean peninsula in 2006. To make a contour map of PWV, zenith total delay (ZTD) was calculated using about 60 GPS permanent stations in Korea, and the pressure and temperature data of nearby AWS stations were interpolated and applied to the equation for calculating the PWV. While Typhoon Ewiniar was migrating north from the southern coast to the eastern coast of Korea, the PWV migrated showing a spatial distribution similar to that of rainfall. Also, the fluctuating pattern of the normalized PWV was analyzed, and the moving speed of the PWV was estimated using the delay time of the increase/decrease pattern in the eight-test stations. The result indicated that the moving speed of the PWV was about 35 km/h, which was similar to the average moving speed of the typhoon (38.9 km/h).

Microwave radiometer observations of interannual water vapor variability and vertical structure over a tropical station

AbstractThe intraseasonal and interannual characteristics and the vertical distribution of atmospheric water vapor from the tropical coastal station Thiruvananthapuram (TVM) located in the southwestern region of the Indian Peninsula are examined from continuous multiyear, multifrequency microwave radiometer profiler (MRP) measurements. The accuracy of MRP for precipitable water vapor (PWV) estimation, particularly during a prolonged monsoon period, has been demonstrated by comparing with the PWV derived from collocated GPS measurements based on regression model between PWV and GPS wet delay component which has been developed for TVM station. Large diurnal and intraseasonal variations of PWV are observed during winter and premonsoon seasons. There is large interannual PWV variability during premonsoon, owing to frequent local convection and summer thunderstorms. During monsoon period, low interannual PWV variability is attributed to the persistent wind from the ocean which brings moisture to this coastal station. However, significant interannual humidity variability is seen at 2 to 6 km altitude, which is linked to the monsoon strength over the station. Prior to monsoon onset over the station, the specific humidity increases up to 5–10 g/kg in the altitude region above 5 km and remains consistently so throughout the active spells.

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.

Precipitable Water from GPS over the Continental United States: Diurnal Cycle, Intercomparisons with NARR, and Link with Convective Initiation

Abstract The variation of precipitable water vapor (PW) over the continental United States is examined at various time scales using spatial maps of a column-averaged mixing ratio (CAMR) that is derived from integrated column PW from both observations and reanalysis data. CAMR spatial maps are generated utilizing PW measurements obtained from a network of ground-based global positioning system (GPS) receivers and the North American Regional Reanalysis (NARR) over a time span of 4 yr (February 2009–January 2013). The effect of topography on PW is mitigated by vertically averaging the mixing ratio instead of integrating the absolute humidity. An ordinary kriging interpolation technique is used to generate spatial maps of CAMR. The observed and predicted PW derived by GPS and NARR correlate well with each other at annual and monthly scales. When focusing on its diurnal cycle, moisture peaks in the late afternoon over the Great Plains and late night over the Rockies. It is also found that atmospheric moisture within NARR generally increases in the second half of the UTC day and is adjusted significantly lower when external observations, such as radiosondes, are assimilated into the analysis system. These adjustments in the analysis introduce nonphysical offsets that are not present within the GPS-derived moisture fields. At meso-β and meso-α scales, GPS PW fields can be used as a precursor to forecast convection up to 3 h prior to initiation. As stated previously, the correlation between GPS and NARR is high (>0.98) at monthly and seasonal time scales, but there is poor correlation at time scales less than a day. This indicates that the water budget within NARR is not in proper balance over these short-term time scales. Over the continental United States, daily cycles of PW and precipitation are coupled differently in different areas.

The water vapour radiometer of Paranal: homogeneity of precipitable water vapour from two years of operations

A Low Humidity and Temperature Profiling (LHATPRO) microwave radiometer, manufactured by Radiometer Physics GmbH (RPG), is used to monitor sky conditions over ESO's Paranal observatory in support of VLT science operations. The unit measures several channels across the strong water vapour emission line at 183 GHz, necessary for resolving the low levels of precipitable water vapour (PWV) that are prevalent on Paranal (median ∼2.4 mm). The instrument consists of a humidity profiler (183-191 GHz), a temperature profiler (51-58 GHz), and an infrared camera (∼10 μm) for cloud detection. We present a statistical analysis of the homogeneity of all-sky PWV using 24 months of PWV observations. The question we tried to address was whether PWV is homogeneous enough across the sky such that service mode observations with the VLT can routinely be conducted with a user-provided constraint for PWV measured at zenith. We find the PWV over Paranal to be remarkably homogeneous across the sky down to 27.5° elevation with a median variation of 0.07 mm (rms). The homogeneity is a function of the absolute PWV but the relative variation is fairly constant at 2 to 3% (rms). Such variations will not be a significant issue for analysis of astronomical data. Users at ESO can specify PWV - measured at zenith - as an ambient constraint in service mode to enable, for instance, very demanding observations in the infrared. We conclude that in general it will not be necessary to add another observing constraint for PWV homogeneity to ensure integrity of observations. For demanding observations requiring very low PWV, where the relative variation is higher, the optimum support could be provided by observing with the LHATPRO in the same line-of-sight simultaneously. Such a mode of operations has already been tested but will have to be justified in terms of scientific gain before implementation can be considered. We plan to extend our analysis of PWV variations covering a larger parameters space for temporal and spatial resolution in the future. Also for climate studies such data sets will be relevant.

A hybrid LS-HE and LS-SVM model to predict time series of precipitable water vapor derived from GPS measurements

Precipitable water vapor (PWV) is one of the key parameters for the analysis of global climate systems, formation of clouds, and short-term forecasts of precipitation. Since water vapor is highly variable both spatially and temporally, it can be problematic, requiring modeling and efficient techniques in order to measure its quantity. Global Positioning System (GPS) stations provide total water column at high quality under all weather conditions with high temporal resolution. The technique used in this work is Precise Point Positioning (PPP) for single dual-frequency GPS receiver aided by precise orbit and clock product. Zenith wet delay (ZWD) is estimated through a stochastic process called random walk at 5-min intervals. The seasonal and diurnal variations of PWV for four GPS stations located in Europe are investigated. Latitude and station height are the most influential factors for the amount of water vapor when we compare their amplitudes and offsets to NASA Water Vapor Dataset-M (NVAP-M) and station heights. The area-averaged accumulated rain time series retrieved from Tropical Rainfall Measuring Mission (TRMM) product also shows that high PWV levels do not necessarily lead to rainfall. The amplitudes of diurnal and semi-diurnal variations are found to be of much lower amount than those of seasonal variations. In order to validate the capability of GPS-sensed PWV measurements, two episodes in wintertime and summertime are simulated using Weather Research Forecast (WRF) model. Both simulated PWV and observational PWV are consistent with each other. The main objective of this paper is to model and forecast the PWV time series which would be useful information on climatology and meteorology. Due to the distinct harmonic characteristics of PWV time series, the least squares harmonic estimation (LS-HE) is applied to time series of PWV derived from 4-year GPS station observations. Subsequently, least squares support vector machine (LS-SVM) optimized by cross-validation strategy is used to model non-harmonic components of the signal. The underlying motivation for using LS-SVM is the proficiency of this methodology to precisely model time series data when the underlying model is usually non-stationary, not defined a priori, and non-linear which are major characteristics of PWV data. The modeled time series shows that the hybrid approach (LS-HE and LS-SVM) can efficiently filter white noise in the observations and then perform forecasting. The bias (∼0.37 mm) and standard deviation (∼3 mm) of observed and predicted values presents the sound capability of the proposed model.

Monitoring the variability of precipitable water vapor over the Klang Valley, Malaysia during flash flood

Klang Valley is a focal area of Malaysian economic and business activities where the local weather condition is very important to maintain its reputation. Heavy rainfalls for more than an hour were reported up to 40 mm in September 2013 and 35 mm in October 2013. Both events are monitored as the first and second cases of flash flood, respectively. Based on these cases, we investigate the water vapor, rainfall, surface meteorological data (surface pressure, relative humidity, and temperature) and river water level. The precipitable water vapor (PWV) derived from Global Positioning System (GPS) is used to indicate the impact of flash flood on the rainfall. We found that PWV was dropped 4 mm in 2 hours before rainfall reached to 40 mm and dropped 3 mm in 3 hours before 35 mm of rainfall in respective cases. Variation of PWV was higher in September case compared to October case of about 2 mm. We suggest the rainfall phenomena can disturb the GPS propagation and therefore, the impact of PWV before, during and after the flash flood event at three selected GPS stations in Klang Valley is investigated for possible mitigation in the future.

An observation campaign of precipitable water vapor with multiple GPS receivers in western Java, Indonesia

A campaign was conducted from 23 July to 5 August 2010 to measure atmospheric precipitable water vapor (PWV) using five Global Positioning System (GPS) receivers, stationed at four different locations in Jakarta and Bogor, western Java, Indonesia. Radiosondes were launched at an interval of 6 h to validate the GPS-derived PWV data. The validation resulted in a root mean square error of 2 to 3 mm in PWV. The influence of atmospheric pressure and temperature on GPS-derived PWV was evaluated. A regular semi-diurnal pressure oscillation was observed, showing an amplitude ranging from 3 to 5 hPa, which corresponds to 1.1 to 1.8 mm in PWV. A nocturnal temperature inversion layer was observed in the radiosonde profiles, which resulted in an error of about 0.5 mm in PWV. From 26 to 29 July, there was a passage of distributed rain clouds over western Java, moving southwestward from the equator toward the Indian Ocean. A second precipitation event, with scattered rain clouds forming locally near Bogor, occurred on 2 August. Both events were observed also by a C-band Doppler Radar operated near Jakarta. The highest peak of GPS-derived PWV (about 67 mm) registered during the campaign occurred on 27 July, coinciding with the distributed rainfall event. Spatial variations in the estimated PWV between the four sites were enhanced before both the analyzed rainfall events, on 27 July and 2 August. Peaks in the temporal variability of PWV were also observed in conjunction with the two events. The results indicated a relation between the space-time inhomogeneity of GPS-PWV and rainfall events in the tropics.

Estimation of Local-scale Precipitable Water Vapor Distribution Around Each GNSS Station Using Slant Path Delay

A procedure for estimating the precipitable water vapor (PWV) distribution around ground-based stations of the global navigation satellite system (GNSS) on a scale of several kilometers is presented. This procedure utilizes the difference between the zenith total delay above a GNSS station and the zenith mapped slant path delay (SPD). This difference can be used to estimate the PWV gradient in each SPD direction by assuming an exponential distribution for the horizontal water vapor gradient.The procedure was tested using an estimation of the PWV variation associated with the parent storm of an F3 Fujita scale tornado that occurred in Ibaraki prefecture on 6 May, 2012. Differential reflectivity observed by a dual-polarimetric radar indicated the existence of a developed parent cloud approximately 1h before the tornado occurred. A high-resolution numerical weather model simulation suggested the existence of a strong PWV gradient around the parent cloud, made evident by the co-existence of a strong updraft and downdraft within an approximately 5-km radius. The PWV gradient, calculated using the GNSS observation network with an average spacing of approximately 17 km, could not detect such a small-scale, strong PWV gradient. The PWV gradient estimated using the proposed procedure revealed a strong PWV gradient and its enhancement. In this case, a higher-order inhomogeneity component of each SPD played a critical role.

A case study of relationship between GPS PWV and solar variability during the declining phase of solar cycle 23

Water vapor plays an important role in the global climate system. A clear relationship between water vapor and solar activity can explain some physical mechanisms of how solar activity influences terrestrial weather/climate changes. To gain insight of this possible relationship, the atmospheric precipitable water vapor (PWV) as the terrestrial climate response was observed by ground-based GPS receivers over the Antarctic stations. The PWV changes analyzed for the period from 2003 to 2008 coincided with the declining phase of solar cycle 23 exhibited following the solar variability trend. Their relationship showed moderate to strong correlation with 0.45 < R2 < 0.93 (p < 0.01), on a monthly basis. This possible relationship suggests that when the solar-coupled geomagnetic activity is stronger, the Earth’s surface will be warmer, as indicated by electrical connection between ionosphere and troposphere.

Analysis of precipitable water vapor from GPS measurements in Chengdu region: Distribution and evolution characteristics in autumn

The rainfall process of Chengdu region in autumn has obvious regional features. Especially, the night-time rain rate of this region in this season is very high in China. Studying the spatial distribution and temporal variation of regional atmospheric precipitable water vapor (PWV) is important for our understanding of water vapor related processes, such as rainfall, evaporation, convective activity, among others in this area. Since GPS detection technology has the unique characteristics, such as all-weather, high accuracy, high spatial and temporal resolution as well as low cost, tracking and monitoring techniques on water vapor has achieved rapid developments in recent years. With GPS–PWV data at 30-min interval gathered from six GPS observational stations in Chengdu region in two autumns (September 2007–December 2007 and September 2008–December 2008), it is revealed that negative correlations exist between seasonally averaged value of GPS–PWV as well as its variation amplitude and local terrain altitude. The variation of PWV in the upper atmosphere of this region results from the water vapor variation from surface to 850hPa. With the help of Fast Fourier Transform (FFT), it is found that the autumn PWV in Chengdu region has a multi-scale feature, which includes a seasonal cycle, 22.5days period (quasi-tri-weekly oscillation). The variation of the GPS–PWV is related to periodical change in the transmitting of the water vapor caused by zonal and meridional wind strengths’ change and to the East Asian monsoon system. According to seasonal variation characteristics, we concluded that the middle October is the critical turning point in PWV content. On a shorter time scale, the relationship between autumn PWV and ground meteorological elements was obtained using the composite analysis approach.

Where is Ridge A?

AbstractFirst identified in 2009 as the site with the lowest precipitable water vapour (PWV) and best terahertz transmission on Earth, “Ridge A” is located approximately 150 km south of Dome A, Antarctica. We use three years of data from the Microwave Humidity Sensor (MHS) on the NOAA-18 satellite and recent ground-based measurements from Ridge A to probe the PWV variations and stability over the high Antarctic plateau.

Study of seasonal-scale atmospheric water cycle with ground-based GPS receivers, radiosondes and NWP models over Morocco

This study investigates the seasonal variation of precipitable water vapor, moisture transport and precipitation over Morocco and the Canary Islands using data from ground-based GPS receivers, radiosondes, GPCP and NCEP reanalysis II. In a first part, the datasets are inter-compared. Humidity biases are evidenced in both radiosonde observations (dry) and NCEP reanalysis (dry and wet) compared to GPS. Moisture transport and precipitation from the reanalysis and observations show a good agreement. Precipitable water shows a maximum in late summer whereas precipitation is peaking in winter and spring over Morocco. Moisture transport occurs preferentially in two layers, below and above 850hPa. The monthly mean precipitable water variation over Morocco is controlled by the upper layer zonal and meridional moisture flux. Precipitation is rather controlled by the lower layer moisture flux and the upper layer meridional flux. The GPS tropospheric gradients show also a consistent seasonal evolution, which is explained by gradients both in the thickness of the troposphere and in the precipitable water vapor. Tropospheric gradients are correlated with moisture fluxes, mostly in the upper layer, and may therefore provide valuable information for meteorology and climatology.