Precipitable Water Vapor Trends Research Articles

Assessing the Monthly Trends in Precipitable Water Vapor over the Indian Subcontinent

This study estimates the trends in precipitable water vapor (PWV), atmospheric moisture budget (AMB), and the factors influencing them: air temperature, evapotranspiration (ET), convective available potential energy (CAPE), and vertical velocity (Omega) over the Indian subcontinent using ERA5 reanalysis data sets between 1980 and 2020. PWV is examined across three atmospheric layers (1000–850 hPa: lower layer; 850–500 hPa: middle layer; 500–300 hPa: upper layer), and the entire atmospheric column (EAC; 1000–300 hPa). The observed PWV trends exhibit variability within the EAC, ranging from −0.53 to 1.25 mm/decade across the study area, with the middle layer showing the most pronounced variation (–0.44 to 0.83 mm/decade), followed by the lower layer (0.10 to 0.45 mm/decade), and the upper layer (–0.02 to 0.23 mm/decade). These fluctuations in PWV are attributed to changes in air temperature, ET, CAPE, and Omega. This investigation, however, underscores the necessity of delving into the impacts of these influencing factors on PWV using finer resolution data, to enhance our comprehension of its spatial and temporal dynamics in the region. Furthermore, the annual AMB analysis reveals a declining trend in the study region. These findings collectively contribute to the understanding of regional water-energy cycles and the recent shifts in atmospheric dynamics.

Spatiotemporal distribution and impact factors of GNSS-PWV in China based on climate region

Water vapor plays a pivotal role in the intricate processes of energy exchange and climate dynamics. However, a comprehensive understanding of the spatial distribution and temporal variability of water vapor in distinct climatic regions of China is still limited due to the intricate interplay of complex topography and diverse climatic conditions. This study investigates the multiscale variability of water vapor using 10-year 1-hour data of precipitable water vapor (PWV) from 248 observation stations of the Crustal Movement Observation Network of China (CMONOC). Significant variations in PWV distribution among China's climate regions are observed. Average PWV values vary considerably across regions, with the Tropical and Subtropical Monsoon Climate (TSMC) having the highest mean PWV of 32.09 mm, followed by the Midlatitude Monsoon Climate (MMC) with 15.70 mm, the Humid Continental Climate (HCC) with 9.26 mm, and the Plateau Climate (PC) with 7.66 mm. Seasons exhibit summer concentration and winter reduction across regions. Most stations exhibit increasing PWV trends, while a few show decreasing trends. The amplitude of annual PWV variations is higher in TSMC and MMC regions with a range from 8 to 22 mm, compared to HCC and PC regions with a range from 2 to 15 mm. Semiannual variations range from 0 to 6 mm in each region. PWV negatively correlates with latitude, altitude and pressure, particularly in the TSMC. Positive correlations with temperature exist in all regions, with varying strengths. Thermodynamic factors primarily impact PWV, while dynamic factors have secondary influence, equally significant in the PC region.

Rising trends of global precipitable water vapor and its correlation with flood frequency

Using 4 global reanalysis data sets, significant upward trends of precipitable water vapor (PWV) were found in the 3 time periods of 1958–2020, 1979–2020, and 2000–2020. During 1958–2020, the global PWV trends obtained using the ERA5 and JRA55 data sets are 0.19 ± 0.01 mm per decade (1.15 ± 0.31%) and 0.23 ± 0.01 mm per decade (1.45 ± 0.32%), respectively. The PWV trends obtained using the ERA5, JRA55, NCEP-NCAR, and NCEP-DOE data sets are 0.22 ± 0.01 mm per decade (1.18 ± 0.54%), 0.21 ± 0.00 mm per decade (1.76 ± 0.56%), 0.27 ± 0.01 mm per decade (2.20 ± 0.70%) and 0.28 ± 0.01 mm per decade (2.19 ± 0.70%) for the period 1979–2020. During 2000–2020, the PWV trends obtained using ERA5, JRA55, NCEP-DOE, and NCEP-NCAR data sets are 0.40 ± 0.25 mm per decade (2.66 ± 1.51%), 0.37 ± 0.24 mm per decade (2.19 ± 1.54%), 0.40 ± 0.26 mm per decade (1.96 ± 1.53%) and 0.36 ± 0.25 mm per decade (2.47 ± 1.72%), respectively. Rising PWV has a positive impact on changes in precipitation, increasing the probability of extreme precipitation and then changing the frequency of flood disasters. Therefore, exploring the relationship between PWV (derived from ERA5 and JRA55) change and flood disaster frequency from 1958 to 2020 revealed a significant positive correlation between them, with correlation coefficients of 0.68 and 0.79, respectively, which explains the effect of climate change on the increase in flood disaster frequency to a certain extent. The study can provide a reference for assessing the evolution of flood disasters and predicting their frequency trends.

Correlation Analysis between Precipitation and Precipitable Water Vapor over China Based on 1999–2015 Ground-Based GPS Observations

Abstract Correlation analysis between precipitable water vapor (PWV) and precipitation over China was conducted by combining high-quality PWV data based on 1999–2015 ground-based global positioning system (GPS) observations with the measurements at matched meteorological stations in the same period. The mean correlation coefficient at all the stations is approximately 0.73, indicating that there is a significant positive correlation between PWV content and precipitation measurements, and the comparison of correlation among different climate types suggests that the distribution characteristics of the correlation coefficients are distinctively related to different climate types. There is also some positive correlation between PWV and precipitation long-term trends, with the correlation coefficients of monthly anomalies ranging generally from 0.2 to 0.6. Furthermore, the intensity of both PWV and precipitation extremes shows a long-term upward trend overall, with the most-intense events showing more significant increases. The extreme precipitation–temperature scaling rate of changes can reach above Clausius–Clapeyron (CC) scaling, whereas that of the extreme PWV-temperature is sub-CC overall, with regional differences in the specific scaling values. The correlation analysis in this work is of great significance for long-term climate analysis and extreme weather understanding, which provides a valuable reference for better utilizing the advantages of PWV data to carry out the studies above. Significance Statement Atmospheric water vapor is crucial to the climate system, especially in the context of global warming, and accurate knowledge of the correlation between precipitable water vapor (PWV) and precipitation is of great significance for long-term climate analysis and extreme precipitation weather forecasting. We take full advantage of the long-term homogeneity of ground-based GPS to conduct long-term correlation analysis between GPS-derived PWV and precipitation over China. Results show a significant positive correlation between them, and the degree of correlation is related to different climate types. The correlation of monthly anomalies is also positive, and, over the long-term, both water vapor and precipitation extremes have been increasing in intensity, with more significant increases occurring in the most-intense events. Extreme precipitation might increase beyond thermodynamic expectations, whereas PWV increases below expectations.

Investigation of Antarctic Precipitable Water Vapor Variability and Trend from 18 Year (2001 to 2018) Data of Four Reanalyses Based on Radiosonde and GNSS Observations

Precipitable water vapor (PWV) plays a vital role in climate research, especially for Antarctica in which meteorological observations are insufficient due to the adverse climate and topography therein. Reanalysis data sets provide a great opportunity for Antarctic water vapor research. This study investigates the climatological PWV means, variability and trends over Antarctica from four reanalyses, including the fifth generation of European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA5), the Second Modern-Era Retrospective analysis for Research and Applications (MERRA-2), Japanese 55-year Reanalysis (JRA-55) and National Centers for Environmental Prediction/Department of Energy (NCEP/DOE), in the period of 2001–2018 based on radiosonde and GNSS observations. PWV data from the ERA5, MERRA-2, JRA-55 and NCEP/DOE have been evaluated by radiosonde and GNSS observations, showing that ERA5 and MERRA-2 perform better than JRA-55 and NCEP/DOE with mean root mean square (RMS) errors below 1.2 mm. The climatological PWV mean distribution over Antarctica roughly shows a decreasing trend from west to east, with the highest content in summer and the lowest content in winter. The PWV variability is generally small over Antarctica, showing a seasonal dependence that is larger in the cold season and smaller in the warm season. PWV trends for all reanalyses at most Antarctic regions are insignificant and most reanalyses present overall drying trends from 2001 to 2018, except for ERA5 exhibiting a moistening trend. PWV trends also show seasonal and regional dependence. All reanalyses are generally consistent with radiosonde and GNSS observations in reproducing the PWV means (mean differences within 1.1 mm), variability (mean differences within 3%) and trends (mean differences within 6.4% decade−1) over Antarctica, except for NCEP/DOE showing spurious variability and trends in East Antarctica. Results can help us further understand these four reanalysis PWV products and promote climate research in Antarctica.

Time Evolution of Storms Producing Terrestrial Gamma-Ray Flashes Using ERA5 Reanalysis Data, GPS, Lightning and Geostationary Satellite Observations

In this article, we report the first investigation over time of the atmospheric conditions around terrestrial gamma-ray flash (TGF) occurrences, using GPS sensors in combination with geostationary satellite observations and ERA5 reanalysis data. The goal is to understand which characteristics are favorable to the development of these events and to investigate if any precursor signals can be expected. A total of 9 TGFs, occurring at a distance lower than 45 km from a GPS sensor, were analyzed and two of them are shown here as an example analysis. Moreover, the lightning activity, collected by the World Wide Lightning Location Network (WWLLN), was used in order to identify any links and correlations with TGF occurrence and precipitable water vapor (PWV) trends. The combined use of GPS and the stroke rate trends identified, for all cases, a recurring pattern in which an increase in PWV is observed on a timescale of about two hours before the TGF occurrence that can be placed within the lightning peak. The temporal relation between the PWV trend and TGF occurrence is strictly related to the position of GPS sensors in relation to TGF coordinates. The life cycle of these storms observed by geostationary sensors described TGF-producing clouds as intense with a wide range of extensions and, in all cases, the TGF is located at the edge of the convective cell. Furthermore, the satellite data provide an added value in associating the GPS water vapor trend to the convective cell generating the TGF. The investigation with ERA5 reanalysis data showed that TGFs mainly occur in convective environments with unexceptional values with respect to the monthly average value of parameters measured at the same location. Moreover, the analysis showed the strong potential of the use of GPS data for the troposphere characterization in areas with complex territorial morphologies. This study provides indications on the dynamics of con-vective systems linked to TGFs and will certainly help refine our understanding of their production, as well as highlighting a potential approach through the use of GPS data to explore the lightning activity trend and TGF occurrences.

Variability and climatology of precipitable water vapor from 12-year GPS observations in Taiwan

Because of global warming, global sea levels have risen, the frequency of drought in Taiwan is much more frequent in winter and spring, and rainfall tends to concentrate in summer. The probability of disaster-type weather has also increased significantly. Estimating precipitable water vapor (PWV) through GPS signals, related studies and analyses of weather conditions, and the effective use of meteorological forecasts have been valued by many meteorological research organizations and officials. In this study, PWV data from 2006 to 2017 and rainfall data were used for long-term harmonic analysis. PWV data calculated by ECMWF (ECMWF-PWV) and PWV data calculated by GPS (GPS-PWV) were subjected to regression analysis to verify the reliability of the GPS-PWV data. The research results show that GPS-PWV and ECMWF-PWV have extremely high correlations; however, the climatic characteristics of some regions and the high spatial resolution of GPS-PWV are able to accurately calculate the high topographic relief of small areas. It is judged that the GPS-PWV is more accurate than the ECMWF-PWV. It is worth noting that the PWV trend of the regions during the 6-year-before period has not changed very much, but the rainfall trend has changed obviously. Except for the eastern region, most of the regions show a decreasing trend year by year. More long-term observations are still needed to prove whether this phenomenon relates to global warming. Long-term rainfall analysis showed that the topography blocked water vapor to the western, southern, and mountainous regions, making them distinctly wet or dry. The harmonic curve showed great consistency with the peaks of PWV and rainfall. However, in the northern and eastern parts of the windward side, the time when maximum rainfall occurred each year may be one month later than the time when the maximum PWV value occurred each year. The reason for this difference is likely to be a decrease in the number of autumn typhoons, resulting in a nearly one-month difference in PWV peaks and rainfall peaks. Finally, we analyzed the linear trend of GPS-PWV and temperature for all regions in Taiwan, and found that annual increasing rate of GPS-PWV and temperature of all regions are within 0.4–0.5 mm/year and 0.04–0.11 C°/year, respectively.

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.

Atmospheric opacity using 220 GHz (1.36 mm) radiometer data and water vapor trends over Indian Astronomical Observatory (IAO), Hanle

The present work reports atmospheric opacity at 220 GHz over Indian Astronomical Observatory (IAO)-Hanle during 2006 to 2018. The opacity data were derived from the radiometric measurement of sky-brightness temperature as a function of zenith angle for every 10 min during day and night. Since the operating frequency range is not completely opaque during rainfall or cloudy atmosphere, observations are performed even during rainfall or cloudy sky conditions. The minimum opacities observed at the site varied from 0.06-0.07 at 1st quartile and 0.08-0.09 at 2nd quartile during December-January. Opacity at Hanle is linearly correlated with high temporal resolution GPS (Global Positioning System) Precipitable Water Vapor (PWV) with a correlation coefficient of about 0.8. The observed median opacity at Hanle has increased by 44% during the best observing months (October–March) and 24% over the annual data (October-September) with reference to the opacity observed during 2000–2003. Such increasing opacity trends are apparently due to effects of the dynamics of the regional and global hydrological cycle. In order to assess the impacts of the regional and global hydrological cycle, PWV obtained from AErosol RObotic NETwork (AERONET), satellite and reanalysis data were studied at nine high-altitude astronomical observatories spread spatially across the globe such as Atacama desert in Chile, Mauna Loa Observatory in Hawaii, Hanle and Merak in India, Ali and Yangbajing Observatories in Tibet, LLAMA in Argentina, and Dome A and Dome C in the Antarctic Plateau during 2003-2018. On an average, PWV trend over Atacama desert is increasing by 0.01 to 0.03 mm per year and at IAO-Hanle, Merak and Ali by 0.01 to 0.05 mm per year, indicating non uniform dynamic hydrological cycles. Interestingly, there is no noticeable PWV trend for the sites located in the Antarctic Plateau. During the four best observing months, PWV observed at Hanle, Merak and Ali sites have values lower than the Mauna Loa observatory by 0.14 mm and 0.56 mm at 1st and 2nd quartiles, respectively.

On the Statistical Significance of Climatic Trends Estimated From GPS Tropospheric Time Series

AbstractFor more than two decades, Global Positioning System (GPS) tropospheric delays have successfully been exploited to monitor the tropospheric water vapor in near real time and reprocessing mode. Although reprocessed data are considered reliable for climatic research, it is important to address the often present gaps, inhomogeneities, and to use a proper model to describe the stochastic part of the time series so that trustworthy trends are estimated. Having relatively long time series, daily reprocessed tropospheric Zenith Total Delay, precipitable water vapor (PWV), and gradients from the Tide Gauge benchmark monitoring network are used in this work to estimate climatic trends. We use a first‐order autoregressive model AR(1) to describe the residuals after the trend estimation so that a correct trend uncertainty is estimated. Using the same model, we obtain the number of years of PWV data required to estimate statistically significant trends. For comparison, we produce tropospheric parameters at each Tide Gauge station based on ERA‐Interim refractivity fields. We found that 83% of 64 GPS stations show a positive PWV trend below 1 mm/decade independent of the time interval, with approximately half of the trends indicated significant. There is a strong correlation (86%) between the Global Navigation Satellite Systems and ERA‐Interim PWV trends. The trends tend to increase when moving east and south on the European map. The results show a percentage change of PWV of 3–8% per a degree Celsius rise in temperature. The number of years required to detect significant PWV trends varies between 30 and 40 years.

Estimating trends in atmospheric water vapor and temperature time series over Germany

Abstract. Ground-based GNSS (Global Navigation Satellite System) has efficiently been used since the 1990s as a meteorological observing system. Recently scientists have used GNSS time series of precipitable water vapor (PWV) for climate research. In this work, we compare the temporal trends estimated from GNSS time series with those estimated from European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA-Interim) data and meteorological measurements. We aim to evaluate climate evolution in Germany by monitoring different atmospheric variables such as temperature and PWV. PWV time series were obtained by three methods: (1) estimated from ground-based GNSS observations using the method of precise point positioning, (2) inferred from ERA-Interim reanalysis data, and (3) determined based on daily in situ measurements of temperature and relative humidity. The other relevant atmospheric parameters are available from surface measurements of meteorological stations or derived from ERA-Interim. The trends are estimated using two methods: the first applies least squares to deseasonalized time series and the second uses the Theil–Sen estimator. The trends estimated at 113 GNSS sites, with 10 to 19 years temporal coverage, vary between −1.5 and 2.3 mm decade−1 with standard deviations below 0.25 mm decade−1. These results were validated by estimating the trends from ERA-Interim data over the same time windows, which show similar values. These values of the trend depend on the length and the variations of the time series. Therefore, to give a mean value of the PWV trend over Germany, we estimated the trends using ERA-Interim spanning from 1991 to 2016 (26 years) at 227 synoptic stations over Germany. The ERA-Interim data show positive PWV trends of 0.33 ± 0.06 mm decade−1 with standard errors below 0.03 mm decade−1. The increment in PWV varies between 4.5 and 6.5 % per degree Celsius rise in temperature, which is comparable to the theoretical rate of the Clausius–Clapeyron equation.

Water vapor variation and the effect of aerosols in China

This study analyzes the annual and seasonal trends in precipitable water vapor (PWV) and surface temperature (Ts) over China from 1979 to 2015, and the relationships between PWV and Ts and between PWV and aerosol absorption optical depth (AAOD), using data from radiosonde stations, weather stations and multiple satellite observations. The results revealed a positive PWV trend between 1979 and 1999, and a negative PWV trend between 2000 and 2015. Analysis of the differences in the PWV trend among different stations types showed that the magnitude of the trends were in the order main urban stations > provincial capital stations > suburb stations, suggesting that anthropogenic activities have a strong influence on the PWV trend. The AAOD exhibited a significant positive trend in most regions of China from 2005 to 2015 (confidence level 95%). Using spatial correlation analysis, we showed that PWV trend derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations is correlated with Ts, with an annual correlation coefficient of 0.596. In addition, the spatial correlation between PWV and AAOD showed a negative relationship, with the highest correlation coefficients of −0.76 and −0.71 observed in mid-eastern China and central northwest China, respectively, suggesting that the increase in AAOD in recent years may be one of the reasons for the decrease in PWV since the 2000s in China.

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.

Global water vapor variability and trend from the latest 36 year (1979 to 2014) data of ECMWF and NCEP reanalyses, radiosonde, GPS, and microwave satellite

AbstractThe variability and trend in global precipitable water vapor (PWV) from 1979 to 2014 are analyzed using the PWV data sets from the ERA‐Interim reanalysis of the European Centre for Medium‐Range Weather Forecasts (ECMWF), reanalysis of the National Centers for Environmental Prediction (NCEP), radiosonde, Global Positioning System (GPS), and microwave satellite observations. PWV data from the ECMWF and NCEP have been evaluated by radiosonde, GPS, and microwave satellite observations, showing that ECMWF has higher accuracy than NCEP. Over the oceans, ECMWF has a much better agreement with the microwave satellite than NCEP. An upward trend in the global PWV is evident in all the five PWV data sets over three study periods: 1979–2014, 1992–2014, and 2000–2014. Positive global PWV trends, defined as percentage normalized by annual average, of 0.61 ± 0.33% decade−1, 0.57 ± 0.28% decade−1, and 0.17 ± 0.35% decade−1, have been derived from the NCEP, radiosonde, and ECMWF, respectively, for the period 1979–2014. It is found that ECMWF overestimates the PWV over the ocean prior to 1992. Thus, two more periods, 1992–2014 and 2000–2014, are studied. Increasing PWV trends are observed from all the five data sets in the two periods: 1992–2014 and 2000–2014. The linear relationship between PWV and surface temperature is positive over most oceans and the polar region. Steep positive/negative regression slopes are generally found in regions where large regional moisture flux divergence/convergence occurs.

Water vapor‐weighted mean temperature and its impact on the determination of precipitable water vapor and its linear trend

AbstractWater vapor‐weighted mean temperature, Tm, is a vital parameter for retrieving precipitable water vapor (PWV) from the zenith wet delay (ZWD) of Global Navigation Satellite Systems (GNSS) signal propagation. In this study, the Tm at 368 GNSS stations for 2000–2012 were calculated using three methods: (1) temperature and humidity profiles from ERA‐Interim, (2) the Bevis Tm–Ts relationship, and (3) the Global Pressure and Temperature 2 wet model. Tm derived from the first method was used as a reference to assess the errors of the other two methods. Comparisons show that the relative errors of the Tm derived from these two methods are in the range of 1–3% across more than 95% of all the stations. The PWVs were calculated using the aforementioned three types of Tm and the GNSS‐derived ZWD at 107 stations. Again, the PWVs calculated using Tm from the first method were used as the reference of the other two PWVs. The root‐mean‐square errors of these two PWVs are both in the range of 0.1–0.7 mm. The second method is recommended in real‐time applications, since its performance is slightly better than the third method. In addition, the linear trends of the PWV time series from the first method were also used as the reference to evaluate the trends from the other two methods. Results show that 13% and 23% of the PWV trends from the respective second and third methods have a relative error of larger than 10%. For climate change studies, the first method, if available, is always recommended.

Assessment of Regional Global Climate Model Water Vapor Bias and Trends Using Precipitable Water Vapor (PWV) Observations from a Network of Global Positioning Satellite (GPS) Receivers in the U.S. Great Plains and Midwest

Abstract Precipitable water vapor (PWV) observations from the National Center of Atmospheric Research (NCAR) SuomiNet networks of ground-based global positioning system (GPS) receivers and the National Oceanic and Atmospheric Administration (NOAA) Profiler Network (NPN) are used in the regional assessment of global climate models. Study regions in the U.S. Great Plains and Midwest highlight the differences among global climate model output from the Fourth Assessment Report (AR4) Special Report on Emissions Scenarios (SRES) A2 scenario in their seasonal representation of column water vapor and the vertical distribution of moisture. In particular, the Community Climate System model, version 3 (CCSM3) is shown to exhibit a dry bias of over 30% in the summertime water vapor column, while the Goddard Institute for Space Studies Model E20 (GISS E20) agrees well with PWV observations. A detailed assessment of vertical profiles of temperature, relative humidity, and specific humidity confirm that only GISS E20 was able to represent the summertime specific humidity profile in the atmospheric boundary layer (<3%) and thus the correct total column water vapor. All models show good agreement in the winter season for the region. Regional trends using station-elevation-corrected GPS PWV data from two complimentary networks are found to be consistent with null trends predicted in the AR4 A2 scenario model output for the period 2000–09. The time to detect (TTD) a 0.05 mm yr−1 PWV trend, as predicted in the A2 scenario for the period 2000–2100, is shown to be 25–30 yr with 95% confidence in the Oklahoma–Kansas region.

Systematic errors between VLBI and GPS precipitable water vapor estimations from 5-year co-located measurements

Space geodetic techniques (e.g., Global Positioning System, GPS and very long baseline interference, VLBI) have been widely used to determine the precipitable water vapor (PWV) for meteorology and climatology, which was verified by comparing with co-located independent technique observations. However, most of these comparisons have been conducted using only short-time spanning observations at several stations. The goal of this study is to identify and quantify the systematic errors between VLBI and GPS PWV estimates using a 5-year (2002–2007), PWV data set constructed from co-located measurements and radiosonde data as well. It has found systematic errors between VLBI and GPS PWV estimations from comparisons with long-term co-located GPS measurements. The total mean VLBI PWVs are systematically smaller than GPS estimates with 0.8–2.2 mm for all sites, but can be as much as 15–30%. The subdiurnal PWV variation magnitudes and long-term trends between VLBI and GPS are nearly similar, but the VLBI-derived PWV trends are systematically smaller than GPS estimates with about 0.1±0.02 mm/year. These systematic errors in PWV estimates between VLBI and GPS are probably due to technique own problems, different used elevation angles and co-location separation.