Change Of Precipitable Water Vapor Research Articles

Tracing the physical signatures among the calculated global clear-sky spectral shortwave radiative flux distribution

This study utilized the high-spectral resolution radiative transfer model (MODerate resolution atmospheric TRANsmission, MODTRAN6.0.2.5) to compute global clear-sky shortwave (SW) radiative flux and compared it with NASA’s Clouds and the Earth’s Radiant Energy System (CERES) Synoptic Radiative Fluxes and Clouds (SYN1deg) product. The comparison revealed that the global distributions of clear-sky downwelling SW fluxes at the surface from the M6.0 calculations and SYN1 results are similar, with annual means of 246.51 Wm-2 and 242.42 Wm-2, respectively. Analysis further showed that most of the M6.0 calculations are slightly higher from low to mid-latitudes, particularly in the Northern Hemisphere (NH), but lower in higher latitudes compared to SYN1 results. However, these differences mostly fall within the CERES estimated uncertainty (6 Wm-2) of monthly mean clear-sky downwelling SW flux at the surface. The sensitivity of clear-sky SW/μ0 fluxes to changes in Precipitable Water Vapor (PWV), represented by the clear-sky water vapor radiative kernel, is about -0.7 Wm-2/(kgm-2) over oceans for both M6.0 and CERES SYN1 products, except for SYN1 results over the Southern Hemisphere (SH) ocean. Additionally, the zonal means of land coverage and SW/VIS/NIR albedos from M6.0 calculations indicate that VIS albedos are highest in polar regions (>60°), followed by SW and NIR albedos, while NIR albedos become highest from low to mid-latitudes (<60°). Generally, SW/VIS/NIR albedos and their differences increase monotonically with increased land coverage from 60°S to 60°N. The consistent clear-sky water vapor radiative kernels derived from both products exceeded our expectations, suggesting their potential use to trace physical signatures in climate model calculations. It is recommended that these model-derived radiative kernels should be validated by the long-term global and regional surface observations in order to enhance confidence to implement these radiative kernels in climate models.

A global evaluation of daily to seasonal aerosol and water vapor relationships using a combination of AERONET and NAAPS reanalysis data

Abstract. The co-transport of aerosol particles and water vapor has long been noted in the literature, with a myriad of implications such as air mass characterization, radiative transfer, and data assimilation. Here, the relationship between aerosol optical depth (AOD) and precipitable water vapor (PW) is evaluated to our knowledge for the first time globally, at daily to seasonal levels using approximately 20 years of NASA Aerosol Robotic Network (AERONET) observational data and the 16-year Navy Aerosol Analysis Prediction System (NAAPS) reanalysis v1.0 (NAAPS-RA) model fields. The combination of AERONET observations with small uncertainties and the reanalysis fields with global coverage is used to provide a best estimate of the seasonal AOD and PW relationships, including an evaluation of correlations, slope, and PW probability distributions for identification of statistically significant differences in PW for high-AOD events. The relationships produced from the AERONET and NAAPS-RA datasets were compared against each other and showed consistency, indicating that the NAAPS-RA provides a realistic representation of the AOD and PW relationship. The analysis includes layer AOD and PW relationships for proxies of the planetary boundary layer and the lower, middle, and upper free troposphere. The dominant AOD and PW relationship is positive, supported by both AERONET and model evaluation, which varies in strength by season and location. These relationships were found to be statistically significant and present across the globe, observed on an event-by-event level. Evaluations at individual AERONET sites implicate synoptic-scale transport as a contributing factor in these relationships at daily levels. Negative AOD and PW relationships were identified and predominantly associated with regional dry-season timescales in which biomass burning is the predominant aerosol type. This is not an indication of dry-air association with smoke for an individual event but is a reflection of the overall dry conditions leading to more biomass burning and higher associated AOD values. Stronger correlations between AOD and PW are found when evaluating the data by vertical layers, including the boundary layer and the lower, middle, and upper free troposphere (corresponding to typical water vapor channels), with the largest correlations observed in the free troposphere – indicative of aerosol and water vapor transport events. By evaluating the variability between PW and relative humidity in the NAAPS-RA, hygroscopic growth was found to be a dominant term to (1) amplify positive AOD–PW relationships, particularly in the midlatitudes; (2) diminish negative relationships in dominant biomass burning regions; and (3) lead to statistically insignificant changes in PW for high-AOD events for maritime regions. The importance of hygroscopic growth in these relationships indicates that PW is a useful tracer for AOD or light extinction but not necessarily as strongly for aerosol mass. Synoptic-scale African dust events are an exception where PW is a strong tracer for aerosol transport shown by strong relationships even with hygroscopic effects. Given these results, PW can be exploited in coupled aerosol and meteorology data assimilation for AOD, and the collocation of aerosol and water vapor should be carefully taken into account when conducting particulate matter (PM) retrievals from space and in evaluating radiative impacts of aerosol, with the season and location in mind.

Analyzing correlations between GNSS retrieved precipitable water vapor and land surface temperature after earthquakes occurrence

Earthquake is a common and destructive natural disaster. The enormous amount of energy released from seismic events can result in anomalous land surface temperature (LST) and catalyze the accumulation of water vapor in the atmosphere. The majority of previous works are not consensual concerning precipitable water vapor (PWV) and LST after the earthquake. Here, we utilized multi-source data to analyze the changes of PWV and LST anomaly after three Ms 4.0–5.3 crustal earthquakes at low depth (8–9 km) that occurred in Qinghai-Tibet Plateau. Firstly, PWV retrieval using Global Navigation Satellite System (GNSS) technology is performed, showing that its root mean square error (RMSE) is less than 1.8 mm against radiosonde (RS) data or European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5) PWV data. The PWV change derived from the nearest GNSS stations around the hypocenter during the earthquakes shows anomalies, and the results reveal that PWV anomalies occurred after the earthquakes, mainly obeying a trend of increasing first and then decreasing. In addition, LST increases three days before PWV peak with a thermal anomaly of 12 °C higher than that of previous days. Robust Satellite Technique (RST) algorithm and ALICE index on Moderate Resolution Imaging Spectroradiometer (MODIS) LST products are introduced to analyze the correlation between the abnormality of LST and PWV. Based on ten-year background field data (2012–2021), the results show that LST during the earthquake has more thermal anomaly occurrences than in previous years. The more severe the LST thermal anomaly is, the higher the probability of a PWV peak occurring.

Retrieval of high spatial resolution precipitable water vapor maps using heterogeneous earth observation data

The determination of the amount of precipitable water vapor (PWV) from global navigation satellite system (GNSS) is restricted to a limited number of ground-based stations with low spatial resolution. The PWV obtained by the multi-source data fusion method has a low spatial resolution because of the low spatial resolution of the data used. Therefore, it is difficult to retrieve PWV maps with sub-km resolution. Therefore, retrieving PWV with high spatial resolution becomes the focus of this study. A dual-scale method for retrieving PWV maps, based on heterogeneous earth data, is proposed, which can obtain sub-kilometer resolution PWV, while maintaining accuracy. First, an approach for analyzing the spatial correlation between land cover types (LCT) and ground-based PWV was proposed, and the meteorological, ecological, topographic, and LCT variables affecting changes in PWV in the near-earth atmosphere were determine, Subsequently, three different regression models, including multiple linear regression (MLR), random forest (RF), and a generalized regression neural network (GRNN), were used to construct the functional model linking heterogeneous earth observation data and ground-based GNSS-derived PWV. Finally, the PWV map with sub-kilometer resolution was generated based on the dual-scale method. Unlike the PWV obtained by data fusion and remote sensing technology, the proposed dual-scale retrieval method can generate PWV maps at 300 m spatial resolution. Statistical analyses demonstrated that the RMS of the PWV derived from the proposed method was less than 2.2 mm, and the bias was close to 0, thereby filling the gap in the sub-kilometer high-precision PWV products.

Atmospheric precipitable water vapor and its correlation with clear-sky infrared temperature observations

Abstract. Precipitable water vapor (PWV) is the vertically integrated amount of water vapor in the atmosphere, and it is a valuable predictor for weather forecasting. Currently, the use of sophisticated instrumentation can limit the number of PWV measurement sites, which affects the accuracy of forecast models in regards to storm formation, strength, and the potential for precipitation. We have analyzed relationships between PWV and zenith sky temperature measurements for the dry climate zone found in the North American Desert Southwest, specifically over Socorro, New Mexico (34∘ N, 107∘ W). Daily measurements of the ground and zenith sky temperatures have been made at Socorro for two complete annual cycles using low-cost infrared thermal sensors. Radiosonde measurements of PWV from National Weather Service stations located in nearby Albuquerque and Santa Teresa, New Mexico, are input into our dataset and analyzed via a newly developed computational tool. Our results show that an exponential relationship between PWV and zenith sky temperature holds for the Desert Southwest, but with parameters that are different than those obtained previously over the more moist climate zone of the North American Gulf Coast. Model simulations can accurately reproduce the observed relationship between PWV and temperature, and the results suggest that half of the signal in temperature is directly related to changes in opacity due to changes in PWV, while the other half is due to changes in air temperature that usually accompany changes in PWV.

Effects of Water Vapor and Cloud Fraction in AIRS Retrievals on Arctic Sea Ice Variability

Using the precipitable water vapor (PWV) and cloud fraction (CF) measurements from the Atmospheric Infrared Sounder (AIRS), this study investigates the potential feedback on Arctic sea ice concentration (SIC) caused by variations in PWV and total CF, as well as CFs at low, middle and high levels during December 2002&#x2013;November 2020. We find that increases in PWV and total CF generally coincide with the Arctic sea ice decline in each season, and both PWV and total CF anomalies are typically correlated with SIC anomalies in all seasons except for the PWV anomalies in summer. Additionally, during all seasons except summer, the low CF generally exhibits closer connection than the middle and high CFs with the trend in total CF and sea ice, and the correlation of SIC with total CF anomalies is governed by that with low CF anomalies. The sensitivities of SIC to changes in PWV and total CF are typically negative, and they are generally consistent with each other in each season. Moreover, the negative sensitivities of SIC to low, middle and high CFs are greatest and most extensive in summer. The contribution of PWV is typically much greater and more extensive than that of total CF to Arctic sea ice change in all seasons. Among the CFs at different levels, the positive contribution of low CF is typically most extensive in winter and spring, while the contributions of high and middle CFs are relatively greater in summer and autumn.

Use of GNSS-Derived PWV for Predicting the Path of Typhoon: Case Studies of Soulik and Kongrey in 2018

AbstractThe progress of a typhoon can be investigated by analyzing the significant changes in precipitable water vapor (PWV) in the area of interest. In this study, PWV variations of two typhoons i...

Evaluation of precipitable water vapor variation for east mediterranean using GNSS

The study of climate change is an important field of research. Monitoring of atmospheric variability especially the tropospheric precipitable water vapor (PWV) is a powerful way to investigate climate change. Global navigation satellite systems (GNSS) provide a good tool for studying atmospheric parameters as GNSS signals along its path from the satellites to the ground based receivers suffer a significant delay due to the refractivity of earth’s atmosphere. GNSS signals are not only delayed but also refracted in the neutral atmosphere. The zenith wet delays (ZWD) caused by the troposphere can be estimated during the geodetic processing of GNSS signals. Since the ZWD is tightly correlated to the PWV, GNSS observations can be used to study the changes of PWV. In this study GNSS data from the Egyptian permanent GNSS network (EPGN), International GNSS Service (IGS), EUREF Permanent Network (EPN) and Scripps Orbit and Permanent Array Center (SOPAC), for the years 2013 and 2014, were used. These GNSS stations provided a good geometrical coverage over the respective region. All GNSS data were processed using Bernese V 5.2 software. The needed product from GNSS data processing is the tropospheric zenith total delay (ZTD) over each GNSS site. The ZTD is divided based on physical parameters into zenith hydrostatic delay (ZHD) and zenith wet delay (ZWD). The ZWD is the basic observable used to calculate PWV. The values of the PWV were calculated and its variation over the study area was investigated. The quality of calculated PWV values from GNSS data evaluated against traditional Radiosonde (RS) measurements. The results of GNSS PWV showed good agreement with RS PWV when the PWV values were low, but this agreement became worse at high PWV values as the differences between the two techniques increased. The correlation coefficient between RS PWV and GNSS PWV varied from 0.31 to 0.84. Standard deviation of the differences between RS PWV and GNSS PWV ranged from 2.369 to 5.973 mm. The PWV estimated from GNSS observations had annual cycle, and its cycle in 2013 was different from that in 2014. The PWV differences between the 2 years clarified that the water vapor content over the east Mediterranean in most of 2014 days was higher than that in 2013. Furthermore, PWV variations were noted on both temporal and spatial scales. The highest temporal variation value was 25.41 mm whereas the maximum value of the spatial variation was 19.67 mm. The present study illustrated the importance of using geodetic networks to provide atmospheric information.

Application of Water Vapor Retrieval Data Acquired by BDS in Analysis of Typhoon

In the paper, the data observed by the Beidou navigation satellite system (BDS), which is based on the continuously operating reference stations (CORS) of Nanning, is processed and analyzed by GAMIT 10.6 software. Also, the inverse distance weighted method (IDW) has been employed to simplify the analysis of data. Besides, the meteorological observation data of the radiosonde station in Nanning is used as an inspection standard to verify the computational accuracy and reliability of the data processing of BDS. Furthermore, combined with both the meteorological observation data of the radiosonde station and the actual rainfall, more emphases are placed on the analysis of time-series changes in precipitable water vapor (PWV) in this paper. Finally, the results show that the PWV obtained by the data inversion of BDS has good consistency with that acquired from the meteorological observation data of the radiosonde station. The overall variation trend of the PWV, which is acquired by the data inversion of BDS, not only can basically keep up with the actual rainfall before and after the typhoon passes through the territory, but also can be better applied in the early warning of extreme weather.

A Novel ENSO Monitoring Method using Precipitable Water Vapor and Temperature in Southeast China

Southeast China, a non-core region influenced by the El Niño–Southern Oscillation (ENSO), has been seldom investigated before. However, the occurrence of ENSO will affect the redistribution of precipitation and the temperature (T) spatial pattern on a global scale. This condition will further lead to flood or drought disasters in Southeast China. Therefore, the method of monitoring the occurrence of ENSO is important and is the focus of this paper. The spatiotemporal characteristics of precipitable water vapor (PWV) and T are first analyzed during ENSO using the empirical orthogonal function (EOF). The results showed that a high correlation spatiotemporal consistency exist between PWV and T. The response thresholds of PWV and T to ENSO are determined by moving the window correlation analysis (MWCA). If the sea surface temperature anomaly (SSTA) at the Niño 3.4 region exceeded the ranges of (−1.17°C, 1.04°C) and (−1.15°C, 1.09°C), it could cause the anomalous change of PWV and T in Southeast China. Multichannel singular spectral analysis (MSSA) is introduced to analyze the multi-type signals (tendency, period, and anomaly) of PWV and T over the period of 1979–2017. The results showed that the annual abnormal signal and envelope line fluctuation of PWV and T agreed well in most cases with the change in SSTA. Therefore, a standard PWV and T index (SPTI) is proposed on the basis of the results to monitor ENSO events. The PWV and T data derived from the grid-based European Center for Medium-Range Weather Forecasting (ECMWF) reanalysis products and GNSS/RS stations in Southeast China were used to validate the performance of the proposed SPTI. Experimental results revealed that the time series of average SPTI calculated in Southeast China corresponded well to that of SSTA with a correlation coefficient of 0.66 over the period of 1979–2017. The PWV values derived from the Global Navigation Satellite System (GNSS) and radiosonde data at two specific stations (WUHN and 45004) were also used to calculate the SPTI. The results showed that the correlation coefficients between SPTI and SSTA were 0.73 and 0.71, respectively. Such results indicate the capacity of the proposed SPTI to monitor the ENSO in Southeast China.

COMPARISON OF GNSS PWV AND ERA5-DERIVED PWV BASED ON GNSS PWV IN HONG KONG, CHINA

Abstract. Water vapor is the most abundant atmospheric gas, and it plays a vital role in the evolution of the Earth's climate. Precipitable water vapor (PWV) is a key factor in monitoring the climate and hydrological cycle. The use of GNSS to estimate PWV is a very effective method. This paper uses 17 satellite positioning reference stations in SatRef, Hong Kong, China, in 2017 to calculate the PWV and introduce the latest reanalysis data set of the European Medium Range Weather Forecast Ingenued Center (ECMWF) ERA5 into this study. The accuracy of THE PWV derived from ERA5 was evaluated using the GNSS-derived PWV. In Hong Kong, the annual bias and RMSE values of GNSS-derived ZTD and ERA5-derived ZTDs are 1.16 cm and 1.78 cm respectively, while the annual RMSE values of GNSS-derived PWV and ERA5-derived PWV are 0.51 cm and 0.57 cm, respectively. The daily changes of GNSS PWV in 2017 are analyzed, and the results show that the ZTD effect of THE ERA5 reanalysis data derived in the small range area is not very ideal, but the accuracy of the PWV derived from ERA5 is better.

Real-Time GNSS-Derived PWV for Typhoon Characterizations: A Case Study for Super Typhoon Mangkhut in Hong Kong

Typhoons can be serious natural disasters for the sustainability and development of society. The development of a typhoon usually involves a pre-existing weather disturbance, warm tropical oceans, and a large amount of moisture. This implies that a large variation in the atmospheric water vapor over the path of a typhoon can be used to study the characteristics of the typhoon. This is the reason that the variation in precipitable water vapor (PWV) is often used to capture the signature of a typhoon in meteorology. This study investigates the usability of real-time PWV retrieved from global navigation satellite systems (GNSS) for typhoons’ characterizations, and especially, the following aspects were investigated: (1) The correlation between PWV and atmospheric parameters including pressure, temperature, precipitation, and wind speed; (2) water vapor transportation during a typhoon period; and (3) the correlation between the movement of a typhoon and the transportation of water vapor. The case study selected for this research was Super Typhoon Mangkhut that occurred in mid-September 2018 in Hong Kong. The PWV time series were obtained from a conversion of GNSS-derived zenith total delays (ZTDs) using observations at 10 stations selected from the Hong Kong GNSS continuously operating reference stations (CORS) network, which are also located along the path of the typhoon. The Bernese GNSS Software (ver. 5.2) was used to obtain the ZTDs; and the root mean square (RMS) of the differences between the GNSS-ZTDs and International GNSS Service post-processed ZTDs time series was less than 8 mm. The RMS of the differences between the GNSS-PWVs (i.e., the ZTDs converted PWVs) and radiosonde-derived PWVs (RS-PWVs) time series was less than 2 mm. The changes in PWV reflect the variation in wind speed during the typhoon period to a certain degree, and their correlation coefficient was 0.76, meaning a significant positive correlation. In addition, a new approach was proposed to estimate the direction and speed of a typhoon’s movement using the time difference of PWV arrival at different sites. The direction and speed estimated agreed well with the ones published by the China Meteorological Administration. These results suggest that GNSS-derived PWV has a great potential for the monitoring and even prediction of typhoon events, especially for near real-time warnings.

Evaluating Forecast Skills of Moisture from Convective-Permitting WRF-ARW Model during 2017 North American Monsoon Season

This paper examines the ability of the Weather Research and Forecasting model forecast to simulate moisture and precipitation during the North American Monsoon GPS Hydrometeorological Network field campaign that took place in 2017. A convective-permitting model configuration performs daily weather forecast simulations for northwestern Mexico and southwestern United States. Model precipitable water vapor (PWV) exhibits wet biases greater than 0.5 mm at the initial forecast hour, and its diurnal cycle is out of phase with time, compared to observations. As a result, the model initiates and terminates precipitation earlier than the satellite and rain gauge measurements, underestimates the westward propagation of the convective systems, and exhibits relatively low forecast skills on the days where strong synoptic-scale forcing features are absent. Sensitivity analysis shows that model PWV in the domain is sensitive to changes in initial PWV at coastal sites, whereas the model precipitation and moisture flux convergence (QCONV) are sensitive to changes in initial PWV at the mountainous sites. Improving the initial physical states, such as PWV, potentially increases the forecast skills.

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.

A new weighted mean temperature model in China

The Global Positioning System (GPS) has been applied in meteorology to monitor the change of Precipitable Water Vapor (PWV) in atmosphere, transformed from Zenith Wet Delay (ZWD). A key factor in converting the ZWD into the PWV is the weighted mean temperature (Tm), which has a direct impact on the accuracy of the transformation. A number of Bevis-type models, like Tm-Ts and Tm-Ts,Ps type models, have been developed by statistics approaches, and are not able to clearly depict the relationship between Tm and the surface temperature, Ts. A new model for Tm, called weighted mean temperature norm model (abbreviated as norm model), is derived as a function of Ts, the lapse rate of temperature, δ, the tropopause height, htrop, and the radiosonde station height, hs. It is found that Tm is better related to Ts through an intermediate temperature. The small effects of lapse rate can be ignored and the tropopause height be obtained from an empirical model. Then the norm model is reduced to a simplified form, which causes fewer loss of accuracy and needs two inputs, Ts and hs. In site-specific fittings, the norm model performs much better, with RMS values reduced averagely by 0.45K and the Mean of Absolute Differences (MAD) values by 0.2K. The norm model is also found more appropriate than the linear models to fit Tm in a large area, not only with the RMS value reduced from 4.3K to 3.80K, correlation coefficient R2 increased from 0.84 to 0.88, and MAD decreased from 3.24K to 2.90K, but also with the distribution of simplified model values to be more reasonable. The RMS and MAD values of the differences between reference and computed PWVs are reduced by on average 16.3% and 14.27%, respectively, when using the new norm models instead of the linear model.

A global assessment of NASA AIRS v6 and EUMETSAT IASI v6 precipitable water vapor using ground‐based GPS SuomiNet stations

AbstractSatellite remote sensing of precipitable water vapor (PWV) is essential for monitoring moisture in real time for weather applications, as well as tracking the long‐term changes in PWV for climate change trend detection. This study assesses the accuracies of the current satellite observing system, specifically the National Aeronautics and Space Administration (NASA) Atmospheric Infrared Sounder (AIRS) v6 PWV product and the European Organization for the Exploitation of Meteorological Satellite Studies (EUMETSAT) Infrared Atmospheric Sounding Interferometer (IASI) v6 PWV product, using ground‐based SuomiNet Global Positioning System (GPS) network as truth. Elevation‐corrected collocated matchups to each SuomiNet GPS station in North America and around the world were created, and results were broken down by station, ARM region, climate zone, and latitude zone. The greatest difference, exceeding 5%, between IASI and AIRS retrievals occurred in the tropics. Generally, IASI and AIRS fall within a 5% error in the PWV range of 20–40 mm (a mean bias less than 2 mm), with a wet bias for extremely low PWV values (less than 5 mm) and a dry bias for extremely high PWV values (greater than 50 mm). The operational IR satellite products are able to capture the mean PWV but degrade in the extreme dry and wet regimes.

Bridging InSAR and GPS Tomography: A New Differential Geometrical Constraint

The integration of interferometric synthetic aperture radar (InSAR) and GPS tomography techniques for the estimation of the 3-D distribution of atmosphere refractivity is discussed. A methodology to use the maps of the temporal changes of precipitable water vapor (PWV) provided by InSAR as a further constraint in the GPS tomography is described. The aim of the methodology is to increase the accuracy of the GPS tomography reconstruction of the atmosphere's refractivity. The results, which are obtained with SAR and GPS data acquired over the Lisbon area, Portugal, are presented and assessed. It has been found that the reconstruction of the atmospheric refractivity is closer to the real atmospheric state with a mitigation of the smoothing effects due to the usual geometrical constraints of the GPS tomography.

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.

Nowcasting the lightning activity in Peninsular Malaysia using the GPS PWV during the 2009 inter-monsoons

&lt;p&gt;The spatial and temporal radio wave delay of the Global Positioning System (GPS) signal can be manipulated to estimate the precipitable water vapor (PWV) which favorable for meteorological applications. A rapid change of the water vapor amount was a precondition for the unbalanced atmospheric charges, which noticeably associated with the development of convective cloud as a lightning chamber. According to this fact, GPS derived PWV will be utilized to nowcasting the lightning event for the next couple of hours. The variances of PWV of four-selected station of the Peninsular Malaysia during the past two inter-monsoons events in May and November 2009 were analyzed. To clarify the response, the changes of PWV in hourly Δ (max-min) before the lightning event was investigated with minimum value 2 mm and is maintained at least three consecutive hours. There are 177 samples were extracted from this method and 69% of the sample showed the lightning occurrence with an average duration was after the six consecutive hours. The lightning day with 2 mm Δ was also higher than the fair weather of 6.3%. These findings suggest that the GPS data can be proposed further as a guide to nowcast the occurrence of lightning activity.&lt;/p&gt;

Modifications to the Water Vapor Continuum in the Microwave Suggested by Ground-Based 150-GHz Observations

Ground-based observations from two different radiometers are used to evaluate commonly used microwave/millimeter-wave propagation models at 150 GHz. This frequency has strong sensitivity to changes in precipitable water vapor (PWV) and cloud liquid water. The observations were collected near Hesselbach, Germany, as part of the Atmospheric Radiation Measurement program's support of the General Observing Period and the Convective and Orographic Precipitation Study. The observations from the two radiometers agree well with each other, with a slope of 0.993 and a mean bias of 0.12 K. The observations demonstrate that the relative sensitivity of the different absorption models to PWV in clear-sky conditions at 150 GHz is significant and that four models differ significantly from the observed brightness temperature. These models were modified to get agreement with the 150-GHz observations, where the PWV ranged from 0.35 to 2.88 cm. The models were modified by adjusting the strength of the foreign- and self-broadened water vapor continuum coefficients, where the magnitude was model dependent. In all cases, the adjustment to the two components of the water vapor continuum was in opposite directions (i.e., increasing the contribution from the foreign-broadened component while decreasing contribution from the self-broadened component or vice versa). While the original models had significant disagreements relative to each other, the resulting modified models show much better agreement relative to each other throughout the microwave spectrum. The modified models were evaluated using independent observations at 31.4 GHz.