Variations In Atmospheric Water Vapor Research Articles

Atmospheric Water Vapor Variability over Houston: Continuous GNSS Tomography in the Year of Hurricane Harvey (2017)

Atmospheric Water Vapor Variability over Houston: Continuous GNSS Tomography in the Year of Hurricane Harvey (2017)

Diurnal variability of atmospheric water vapour, precipitation and cloud top temperature across the global tropics derived from satellite observations and GNSS technique

The diurnal cycle of convection plays an important role in clouds and water vapour distribution across the global tropics. In this study, we utilize integrated moisture derived from the global navigation satellite system (GNSS), satellite precipitation estimates from TRMM and merged infrared dataset to investigate links between variability in tropospheric moisture, clouds development and precipitation at a diurnal time scale. Over 16 years of observations were analysed to estimate the diurnal cycles for 42 sites that span across the global tropics and assess the GNSS precipitable water vapour suitability in tropical moisture variability studies. Results show that the GNSS technique can be successfully used for studies related to the high-resolution temporal variability of integrated atmospheric moisture and, thus, in the analysis of multi-scale interactions and clouds development. For most of the analysed cases, GNSS integrated humidity shows one daily maximum (regardless of the season), which is related to the afternoon precipitation and cloud top temperature daily minimum. Although diurnal integrated moisture variations typically do not exceed 2 mm (usually below 5% of the daily mean value), in favourable large-scale conditions such relatively small changes can lead to the development of convective clouds and can affect precipitation distribution. Thus, GNSS technology allows reliable monitoring of tropospheric moisture variability at a diurnal time scale, which can be leveraged for improved monitoring and prediction of high-impact weather.

Monsoon Fringe Area Moisture Transportation Revealed by Water Stable Isotopes: A Lanzhou River Valley Case Study

Because of global warming, the water cycle has intensified and precipitation has changed, with monsoons evolving to become more complex, particularly in monsoon fringe areas. Therefore, it is important to use stable isotopes to trace moisture sources in monsoon fringe areas, such as semiarid areas. In this study, in situ measurements of water vapor isotopes were obtained in the monsoon fringe areas of Lanzhou (36.1° N, 103.7° E), between May and November 2019 with the aim of analyzing the stable isotope composition and atmospheric water vapor variation to improve our understanding of moisture transport. The following results were obtained: stable isotopic variation of atmospheric water vapor shows an alternation between west and southwest moisture with wind directions and sources of water vapor, with δ18O and δ2H varying from high to low. In the Lanzhou valley, water vapor isotopes show a distinct daily cycle of δ17O, δ18O, and δ2H and are consistent with temperature changes. Water vapor isotopes, particularly d-excess, are correlated with temperature and absolute humidity. With regard to the local atmospheric water vapor line (LAVL), we show that the slope and intercept of the LAVL are affected by sub-cloud secondary evaporation and topography.

The role of ENSO in atmospheric water vapor variability during cold months over Iran

The role of ENSO in atmospheric water vapor variability during cold months over Iran

Multi-Year Variations in Atmospheric Water Vapor in the Baikal Natural Territory According to GPS Observations

The data of GPS measurements at the permanent observation points IRKM (Irkutsk, 52°13′ N, 104°19′ E, h = 509 m), ULAZ (Ulan-Ude, 51°48′ N, 107°37′ E, h = 517 m) and BADG (Badary, 51°46′ N, 102°14′ E, h = 848 m) located within the Baikal natural area (Eastern Siberia) are considered. A comparison was made of the time series of the tropospheric moisture content levels obtained at the IRKM site from GPS observations and radiosonde data, and at the BADG site from GPS observations and measurements with a water vapor radiometer (WVR) during 2020. The average deviation of the difference in total moisture content data during 2020 in the form of precipitable water according to GPS and WVR observations was about 0.12 mm, or about 1.1% relative to the average value, and the cross-correlation coefficient between the data is very high (K = 0.92). The use of GPS observations to obtain continuous data on the moisture content of the troposphere is substantiated. A series of processed data on the total moisture content based on GPS measurements using surface meteorological data for the period 1999–2020 for the IRKM and ULAZ sites and for the period 2006–2020 for the BADG site were obtained. Linear trends of total moisture content were determined for observation points: IRKM (−0.35 mm per decade, –2.7%), ULAZ (+0.47 mm per decade, +3.9%) and BADG (+1.41 mm per decade, 13.4%). Moreover, at the IRKM and ULAZ points, the surface temperature trends in the same period were positive and amounted to +0.4 K and +0.7 K per decade, respectively. The article confirms the trends identified in the work of Ross and Elliott for the territory of Eastern Siberia.

GNSS-based water vapor estimation and validation during the MOSAiC expedition

Abstract. Within the transpolar drifting expedition MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate), the Global Navigation Satellite System (GNSS) was used among other techniques to monitor variations in atmospheric water vapor. Based on 15 months of continuously tracked GNSS data including GPS, GLONASS and Galileo, epoch-wise coordinates and hourly zenith total delays (ZTDs) were determined using a kinematic precise point positioning (PPP) approach. The derived ZTD values agree to 1.1 ± 0.2 mm (root mean square (rms) of the differences 10.2 mm) with the numerical weather data of ECMWF's latest reanalysis, ERA5, computed for the derived ship's locations. This level of agreement is also confirmed by comparing the on-board estimates with ZTDs derived for terrestrial GNSS stations in Bremerhaven and Ny-Ålesund and for the radio telescopes observing very long baseline interferometry in Ny-Ålesund. Preliminary estimates of integrated water vapor derived from frequently launched radiosondes are used to assess the GNSS-derived integrated water vapor estimates. The overall difference of 0.08 ± 0.04 kg m−2 (rms of the differences 1.47 kg m−2) demonstrates a good agreement between GNSS and radiosonde data. Finally, the water vapor variations associated with two warm-air intrusion events in April 2020 are assessed.

Exploring the Relationships of Atmospheric Water Vapor Contents and Different Land Surfaces in a Complex Terrain Area by Using Doppler Radar

Changes in atmospheric water vapor mainly occur in the atmospheric boundary layer. However, due to many factors, such as orography and ground thermal dynamic conditions, the change trends and transformation law of atmospheric water vapor contents above different surfaces are still unclear. In this work, a Doppler weather radar with high spatial-temporal resolution was used to monitor the variations and transformations of water vapor contents over different land surfaces for two years. The results show that the atmospheric water vapor content shows a very good positive correlation with elevation at altitudes between 600 m and 1200 m, while different land surfaces have delicate impacts on atmospheric water vapor contents, such as extreme values appearing above impervious urban surfaces, uniform distributions appearing over water body and vegetated surfaces being wet but avoiding extreme conditions. Compared with previous studies, the results and conclusions of this study are mainly derived from accurate direct observations based on high-resolution radar. Identifying the distribution and transformation of water vapor over different surfaces can enhance our understanding of the movement and variation of atmospheric water vapor over complex terrain and different land surfaces, and improve the planning and construction capacity of different surfaces, such that humankind can mitigate the severe disasters caused by drastic changes in atmospheric water vapor.

Navigator Notes

Navigator Notes

A collocation framework to retrieve tropospheric delays from a combination of GNSS and InSAR

High spatio-temporal variability of atmospheric water vapor affects microwave signals of Global Navigation Satellite Systems (GNSS) and Interferometric Synthetic Aperture Radar (InSAR). A better knowledge of the distribution of water vapor improves both GNSS- and InSAR-derived data products. In this work, we present a collocation framework to combine and retrieve zenith and (relative) slant tropospheric delays. GNSS and InSAR meteorological products are combined aiming at a better retrieval of the atmospheric water vapor. We investigate the combination approach with synthetic and real data acquired in the Alpine region of Switzerland. Based on a closed-loop validation with simulated delays, a few mm accuracy is achieved for the GNSS-InSAR combination in terms of retrieved ZTDs. Furthermore, when real delays are collocated, the combination results are more congruent with InSAR computed products. This research is a contribution to improve the spatio-temporal mapping of tropospheric delays by combining GNSS-derived and InSAR-derived delays.

Preliminary result of capturing the signature of heavy rainfall events using the 2-d-/4-d water vapour information derived from GNSS measurement in Hong Kong

Apart from the well-known applications like positioning, navigation and timing (PNT), Global Navigation Satellite System (GNSS) has manifested its ability in many other areas that are vital to society largely. With the dense setting of the regional continuously operating reference station (CORS) networks, monitoring the variations in atmospheric water vapour using a GNSS technique has become a focus in the field of GNSS meteorology. Most previous studies mainly concentrate on the analysis of relationship between the two-dimensional (2-d) Precipitable Water Vapour (PWV) and rainfall while the three-dimensional (3-d) variations of atmospheric water vapour derived from the GNSS tomographic technique are more rarely discussed. In this work, we investigate changes in the emerging field of GNSS technology for monitoring changes in 2-d/3-d atmospheric water vapour during rainfall period. The signature of atmospheric water vapour variation was captured using the ground-based GNSS observations from the CORS network of Hong Kong which presents the particularity of being dense. In addition, the corresponding rain gauges and radiosonde stations are also used. Our analysis of the 2-d PWV/3-d water vapour profiles changes during the arrival, occurrence and depression of heavy rainfall shows that: (i) PWV increases before the arrival of heavy rainfall (ii) and decreases to its average value after the depression of rainfall; (iii) rainfall leads to an anomalous variation in relative humidity and temperature while their trends are totally opposite; (iv) atmospheric water vapour presents unstable conditions with intense vertical convective and horizontal convergence motions and hydrometeors are formed before the arrival of rainfall. This study indicates the potential of using GNSS technique to monitor spatio-temporal variations of atmospheric water vapour during rainfall period, which provides a better understanding of the mechanism of convection and rainfall induced by the extreme weather events.

A Tropospheric Tomography Method with a Novel Height Factor Model Including Two Parts: Isotropic and Anisotropic Height Factors

Global Navigation Satellite System (GNSS) tomography has developed into an efficient tool for sensing the high spatiotemporal variability of atmospheric water vapor. The integration of GNSS top signals and side rays for tropospheric tomography systems using a novel height factor model (HFM) is proposed and discussed in this paper. Within the HFM, the sectional slant wet delay (SWD) of inside signals (the part of the side signal inside the tomography area), which is considered a key factor for modeling side rays, is separated into isotropic and anisotropic components. Correspondingly, two height factors are defined to calculate the isotropic and anisotropic part of tropospheric delays in the HFM. In addition, the dynamic tomography top boundary is first analyzed and determined based on 30-year radiosonde data to reasonably divide signals into top and side rays. Four special experimental schemes based on different tomography regions of Hong Kong are performed to assess the proposed HFM method, the results of which show increases of 33.42% in the mean utilization of rays, as well as decreases of 0.46 g/m3 in the average root mean square error (RMSE), compared to the traditional approach, revealing the improvement of tomography solutions when the side signals are included in the modeling. Furthermore, compared with the existing correction model for modeling side rays, the water vapor profiles retrieved from the proposed improved model are closer to the radiosonde data, which highlights the advantages of the proposed HFM for optimizing the GNSS tomography model.

Hourly PWV Dataset Derived from GNSS Observations in China.

The rapid variation of atmospheric water vapor is important for a regional hydrologic cycle and climate change. However, it is rarely investigated in China, due to the lack of a precipitable water vapor (PWV) dataset with high temporal resolution. Therefore, this study focuses on the generation of an hourly PWV dataset using Global Navigation Satellite System (GNSS) observations derived from the Crustal Movement Observation Network of China. The zenith total delay parameters estimated by GAMIT/GLOBK software are used and validated with an average root mean square (RMS) error of 4–5 mm. The pressure (P) and temperature (T) parameters used to calculate the zenith hydrostatic delay (ZHD) and weighted average temperature of atmospheric water vapor (Tm) are derived from the fifth-generation reanalysis dataset of the European Centre for Medium-Range Weather Forecasting (ECMWF ERA5) products. The values of P and T at the GNSS stations are obtained by interpolation in the horizontal and vertical directions using empirical formulas. Tm is calculated at the GNSS stations using the improved global pressure and temperature 2 wet (IGPT2w) model in China with an RMS of 3.32 K. The interpolated P and T are validated by interpolating the grid-based ERA5 data into radiosonde stations. The average RMS and bias of P and T in China are 2.71/−1.11 hPa and 1.88/−0.51 K, respectively. Therefore, the error in PWV with a theoretical RMS of 1.85 mm over the period of 2011–2017 in China can be obtained. Finally, the hourly PWV dataset in China is generated and the practical accuracy of the generated PWV dataset is validated using the corresponding AERONET and radiosonde data at specific stations. Numerical results reveal that the average RMS values of the PWV dataset in the four geographical regions of China are less than 3 mm. A case analysis of the PWV diurnal variations as a response to the EI Niño event of 2015–2016 is performed. Results indicate the capability of the hourly PWV dataset of monitoring the rapid water vapor changes in China.

An analysis of atmospheric water vapor variations over a complex agricultural region using airborne imaging spectrometry.

Understanding atmospheric water vapor patterns can inform regional understanding of water use, climate patterns and hydrologic processes. This research uses Airborne Visible Infrared Imaging Spectrometer (AVIRIS) reflectance and water vapor imagery to investigate spatial patterns of water vapor in California’s Central Valley on a June date in 2013, and 2015, and relates these patterns to surface characteristics and atmospheric properties. We analyze water vapor imagery at two scales: regional and agricultural field, to examine how the slope, intercept, and trajectory of water vapor interact with the landscape in a highly diverse and complex agricultural setting. At the field scale, we found significant quadratic relationships between water vapor slope and wind magnitude in both years (p<0.001). Results showed a positive correlation between crop water use and the frequency with which crops showed directional agreement between wind and water vapor (r = 0.23). At the regional scale, we found patterns of water vapor that indicate advection of moisture across the scene. Water vapor slope was inversely correlated to field size with correlations of -0.37, and -0.28 for 2013 and 2015. No correlation was found between green vegetation fraction and vapor slope (r = 0.001 in 2013, r = 0.02 in 2015), but a weak correlation was found for the intercept (r = 0.11 in 2013, r = 0.26 in 2015). These results lead us to conclude that accumulation of water vapor above fields in these scenes is observable with AVIRIS-derived water vapor imagery whereas advection at the field level was inconsistent. Based on these results, we identify new opportunities to use and apply water vapor imagery to advance our understanding of hydro-climatic patterns and applied agricultural water use.

A New Typhoon-Monitoring Method Using Precipitation Water Vapor

Some seasonal natural floods can be attributed to typhoons that bring a large amount of atmospheric water vapor, and variations in atmospheric water vapor can be reflected in the precipitable water vapor (PWV). Therefore, monitoring typhoons based on the anomalous variations of the PWV is the focus of this paper. The anomalous variations of ERA5(fifth-generation reanalysis dataset of the European Centre for Medium-range Weather Forecasting)-derived PWV with other atmospheric parameters related to typhoons, such as precipitation, pressure, and wind, were first analyzed during typhoon periods. After that, a typhoon-monitoring method with and without considering the typhoon’s acceleration was proposed according to the time of the maximum value of the PWV during the typhoon period in this paper. Corresponding experiments based on the measured and simulated data were performed to evaluate the proposed method. The experimental measurement of Typhoon Hato revealed that the velocity of the typhoon’s movement estimated by the proposed method was close to the observed value, and the maximum difference between the estimated and observed values was less than 3 km/h. A simulated experiment was also carried out in which the acceleration of the typhoon’s movement was also considered. The simulated results verified the reliability and feasibility of the proposed method. The estimated velocity and acceleration of the typhoon’s movement were almost equal to the true values under the cases of using different numbers of stations and selecting various typhoon locations. Such results obtained above indicate that the method proposed in this paper has a significant potential application value for typhoon monitoring.

Testing the hypothesis that variations in atmospheric water vapour are the main cause of fluctuations in global temperature

A hypothesis that the increasing application of both surface and ground water for irrigation of crops is a significant source of anthropogenic global warming is tested. In climate models, water is already assigned a major secondary amplifying role in warming, solely as a positive feedback from an atmosphere previously warmed by other GHGs. However, this conclusion ignores the direct anthropogenic forcing from increasing use of water in dry regions to grow crops for the human population. The area irrigated worldwide increased by around 1.5% annually between 1960 and 2000, almost trebling in magnitude. Importantly, though only a small proportion of the Earth’s surface, this additional water vapour is dynamically focussed on dry land, intensifying its potential to elevate the troposphere and reduce the regional OLR. Our modelling analysis suggests that the increase in atmospheric water vapour from irrigation could be significantly more than 1% by 2050 compared to 1950, imposing a global forcing exceeding 1.0 W/m2. Fortunately, this hypothesis can be tested, for example, using the satellite data on OLR acquired since the 1970s, relating this to local trends of increasing irrigation or major floods in arid regions. If found consistent with the data, current proposals to mitigate climate change by limiting combustion of fossil fuels may prove less effective. This prediction regarding the warming effect of increasing irrigation is tested using NCAR reanalysis data made possible by the natural experiments of the periodic flooding of Lake Eyre in Australia's semi-arid interior. It is recommended that this hypothesis be tested using data from local studies in irrigated regions such as changes in outgoing longwave radiation and in increased absorption of incoming shortwave radiation in air.

Multi‐scale observations of atmospheric moisture variability in relation to heavy precipitating systems in the northwestern Mediterranean during HyMeX IOP12

The deployment of special instrumentation for the Hydrological Cycle in the Mediterranean Experiment (HyMeX) provides a valuable opportunity to investigate the spatio‐temporal variability of atmospheric water vapour across scales in relationship with the occurrence of Heavy Precipitation Systems (HPSs) in the north Western Mediterranean (WMed) during the Intensive Observation Period (IOP12), which is the focus of this investigation. High‐resolution convection‐permitting COSMO simulations complement the observational network and allow the calculation of on‐line trajectories.In addition to the presence of a favourable large‐scale situation and low‐level convergence, atmospheric moisture changes resulting in conditionally unstable air are identified as responsible for convective initiation (CI). All HPSs within the north‐WMed form in periods/areas of maximum integrated water vapour (IWV; 35–45 kg/m2) after an increase of about 10–20 kg/m2. The most intense events receive moisture from different sources simultaneously and show a sudden increase of about 10 kg/m2 between 6 and 12 h prior to the event, whereas in the less intense events the increase is larger, about 20 kg/m2, over a period of at least 24–36 h. Changes in the lower (∼900 hPa) and mid‐troposphere (∼700 hPa) control the evolution of the atmospheric moisture and the instability increase prior to CI. Spatial inhomogeneities in the lower boundary layer determine the timing and location of deep convection, whereas enhanced moisture in the mid‐troposphere favours intensification. Moister and deeper boundary layers, with updraughts reaching up to 2 km are identified in those pre‐convective environments leading to HPS, whereas dry, shallow boundary layers are found everywhere else. The build‐up time and vertical distribution of the moisture changes are found to be crucial for the evolution and severity of the HPSs rather than the amount of total column atmospheric moisture.

Sensitivity of Numerical Weather Prediction to the Choice of Variable for Atmospheric Moisture Analysis into the Brazilian Global Model Data Assimilation System

Due to the high spatial and temporal variability of atmospheric water vapor associated with the deficient methodologies used in its quantification and the imperfect physics parameterizations incorporated in the models, there are significant uncertainties in characterizing the moisture field. The process responsible for incorporating the information provided by observation into the numerical weather prediction is denominated data assimilation. The best result in atmospheric moisture depend on the correct choice of the moisture control variable. Normalized relative humidity and pseudo-relative humidity are the variables usually used by the main weather prediction centers. The objective of this study is to assess the sensibility of the Center for Weather Forecast and Climate Studies to choose moisture control variable in the data assimilation scheme. Experiments using these variables are carried out. The results show that the pseudo-relative humidity improves the variables that depend on temperature values but damage the moisture field. The opposite results show when the simulation used the normalized relative humidity. These experiments suggest that the pseudo-relative humidity should be used in the cyclical process of data assimilation and the normalized relative humidity should be used in non-cyclic process (e.g., nowcasting application in high resolution).

Evaluation of spatial and temporal characteristics of GNSS-derived ZTD estimates in Nigeria

This study presents an in-depth analysis to comprehend the spatial and temporal variability of zenith tropospheric delay (ZTD) over Nigeria during the period 2010–2014, using estimates from Global Navigation Satellite Systems (GNSS) data. GNSS data address the drawbacks in traditional techniques (e.g. radiosondes) by means of observing periodicities in ZTD. The ZTD estimates show weak spatial dependence among the stations, though this can be attributed to the density of stations in the network. Tidal oscillations are noticed at the GNSS stations. These oscillations have diurnal and semi-diurnal components. The diurnal components as seen from the ZTD are the principal source of the oscillations. This upshot may perhaps be ascribed to temporal variations in atmospheric water vapour on a diurnal scale. In addition, the diurnal ZTD cycles exhibited noteworthy seasonal dependence, with larger amplitudes in the rainy (wet) season and smaller ones in the harmattan (dry) season. Notably, the stations in the northern part of the country reach very high amplitudes in the months of June, July and August at the peak of the wet season, characterized by very high rainfall. This pinpoints the fact that in view of the small amount of atmospheric water vapour in the atmosphere, usually around 10%, its variations greatly influence the corresponding diurnal and seasonal discrepancies of ZTD. This study further affirms the prospective relevance of ground-based GNSS data to atmospheric studies. GNSS data analysis is therefore recommended as a tool for future exploration of Nigerian weather and climate.

Intercomparison of XH2O Data from the GOSAT TANSO-FTS (TIR and SWIR) and Ground-Based FTS Measurements: Impact of the Spatial Variability of XH2O on the Intercomparison

Spatial and temporal variability of atmospheric water vapor (H2O) is extremely high, and therefore it is difficult to accurately evaluate the measurement precision of H2O data by a simple comparison between the data derived from two different instruments. We determined the measurement precisions of column-averaged dry-air mole fractions of H2O (XH2O) retrieved independently from spectral radiances in the thermal infrared (TIR) and the short-wavelength infrared (SWIR) regions measured using a Thermal And Near-infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS) onboard the Greenhouse gases Observing SATellite (GOSAT), by an intercomparison between the two TANSO-FTS XH2O data products and the ground-based FTS XH2O data. Furthermore, the spatial variability of XH2O was also estimated in the intercomparison process. Mutually coincident XH2O data above land for the period ranging from April 2009 to May 2014 were intercompared with different spatial coincidence criteria. We found that the precisions of the TANSO-FTS TIR and TANSO-FTS SWIR XH2O were 7.3%–7.7% and 3.5%–4.5%, respectively, and that the spatial variability of XH2O was 6.7% within a radius of 50 km and 18.5% within a radius of 200 km. These results demonstrate that, in order to accurately evaluate the measurement precision of XH2O, it is necessary to set more rigorous spatial coincidence criteria or to take into account the spatial variability of XH2O as derived in the present study.

A Physics-Based Method to Retrieve Land Surface Temperature From MODIS Daytime Midinfrared Data

The midinfrared (MIR) spectral region (3–5 $\mu\text{m}$ ), which penetrates most haze layers in the atmosphere and is less sensitive to variations in atmospheric water vapor, seems to be appropriate for retrieving land surface temperature (LST). However, there are currently few studies of LST retrieval with MIR data because it is difficult to eliminate solar irradiance from the total energy measured in the MIR during the daytime. This paper proposes a physics-based method to retrieve LST from MODIS daytime MIR data. The bidirectional reflectivity describing the reflected solar direct irradiance is determined using the method by Tang and Li. The directional emissivity, representing the surface emitted radiance, is determined by a kernel-driven bidirectional reflectance distribution function model, i.e., RossThick-LiSparse-R. Intercomparisons using the MODIS-derived LST product MYD11_L2, for the Baotou experimental site in Urad Qianqi, Inner Mongolia, China, have a maximum root-mean-square error (RMSE) of 1.69 K and a minimum RMSE of 1.31 K, for four scenes of MODIS images. Furthermore, in situ LSTs measured at the Hailar field site in northeastern Inner Mongolia, China, were also used to validate the proposed method. Comparisons of the LSTs retrieved from MODIS daytime MIR data and those calculated using in situ measurements have a bias and RMSE of −0.17 K and 1.42 K, respectively, which indicates that the proposed method can accurately retrieve LST from MODIS daytime MIR data.