Monitoring and prediction of hurricane tracks using GPS tropospheric products

AbstractWe have reconstructed integrated water vapor (IWV) using the zenith wet delays to track the properties of hurricanes and explore their spatial and temporal distributions estimated from 922 GPS stations. Our results show that a surge in GPS-derived IWV occurred at least six hours prior to the landfall of two major hurricanes (Harvey and Irma) that struck the Gulf and East Coasts of the USA in 2017. We observed enhanced IWV, in particular, for the two hurricanes landfall locations. The observed variations exhibit a correlation with the precipitation value constructed from GPM/IMERG satellite mission coinciding with hurricane storm front passage. We used GPS-IWV data as inputs for spaghetti line plots for our path predictions, helping us predict the paths of Hurricanes Harvey and Irma. Hence, a directly estimable zenith wet delay sourced from GPS that has not been previously reported can serve as an additional resource for improving the monitoring of hurricane paths.

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KORELASI MUSIMAN ANTARA ZENITH WET DELAY (ZWD) DAN DEBIT SUNGAI DI DAS CIKAPUNDUNG HULU, KAWASAN BANDUNG UTARA, JAWA BARAT

Seminar Nasional Geomatika ◽

10.24895/sng.2018.3-0.1033 ◽

2019 ◽

Vol 3 ◽

pp. 741

Author(s):

Wedyanto Kuntjoro ◽

Z.A.J. Tanuwijaya ◽

A. Pramansyah ◽

Dudy D. Wijaya

Keyword(s):

Water Vapor ◽

Precipitable Water ◽

Precipitable Water Vapor ◽

Zenith Wet Delay

Kandungan total uap air troposfer (precipitable water vapor) di suatu tempat dapat diestimasi berdasarkan karakteristik bias gelombang elektromagnetik dari satelit navigasi GPS, berupa zenith wet delay (ZWD). Pola musiman deret waktu ZWD sangat penting dalam studi siklus hidrologi khususnya yang terkait dengan kejadian-kejadian banjir. Artikel ini menganalisis korelasi musiman antara ZWD dan debit sungai Cikapundung di wilayah Bandung Utara berdasarkan estimasi rataan pola musimannya. Berdasarkan rekonstruksi sejumlah komponen harmonik ditemukan bahwa pola musiman ZWD memiliki kemiripan dan korelasi yang kuat dengan pola musiman debit sungai. Pola musiman ZWD dan debit sungai dipengaruhi secara kuat oleh fenomena pertukaran Monsun Asia dan Monsun Australia. Korelasi linier di antara keduanya menunjukkan hasil yang sangat kuat, dimana hampir 90% fluktuasi debit sungai dipengaruhi oleh kandungan uap air di troposfer dengan level signifikansi 95%. Berdasarkan spektrum amplitudo silang dan koherensi, kedua kuantitas ini nampak didominasi oleh siklus monsun satu tahunan disertai indikasi adanya pengaruh siklus tengah tahunan dan 4 bulanan.

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Drought spatiotemporal propagation via land feedbacks

10.5194/egusphere-egu21-1505 ◽

2021 ◽

Author(s):

Diego G. Miralles ◽

Dominik L. Schumacher ◽

Jessica Keune ◽

Paul A. Dirmeyer

Keyword(s):

Soil Moisture ◽

Water Vapor ◽

Mitigation Strategies ◽

Soil Drought ◽

The Usa ◽

Forecast Models ◽

Atmospheric Feedbacks ◽

Dry Out ◽

Water And Food Security ◽

The Impact

The predicted increase in drought occurrence and intensity will pose serious threats to global future water and food security. This was hinted by several historically unprecedented droughts over the last two decades, taking place in Europe, Australia, Amazonia or the USA. It has been hypothesised that the strength of these events responded to self-reinforcement processes related to land&#8211;atmospheric feedbacks: as rainfall deficits dry out soil and vegetation, the evaporation of land water is reduced, then the local air becomes too dry to yield rainfall, which further enhances drought conditions. Despite the 'local' nature of these feedbacks, their consequences can be remote, as downwind regions may rely on evaporated water transported by winds from drought-affected locations. Following this rationale, droughts may not only self-reinforce locally, due to land atmospheric feedbacks, but self-propagate in the downwind direction, always conditioned on atmospheric circulation. This propagation is not only meteorological but relies on soil moisture drought, and may lead to a downwind cascading of impacts on water resources. However, a global capacity to observe these processes is lacking, and thus our knowledge of how droughts start and evolve, and how this may change as climate changes, remains limited. Furthermore, climate and forecast models are still immature when it comes to representing the influences of land on rainfall.Here, the largest global drought events are studied to unravel the role of land&#8211;atmosphere feedbacks during the spatiotemporal propagation of these events. We based our study on satellite and reanalysis records of soil moisture, evaporation, air humidity, winds and precipitation, in combination with a Lagrangian framework that can map water vapor trajectories and explore multi-dimensional feedbacks. We estimate the reduction in precipitation in the direction of drought propagation that is caused by the upwind soil moisture drought, and isolate this effect from the influence of potential evaporation and circulation changes. By doing so, the downwind lack of precipitation caused by upwind soil drought via water vapor deficits, and hence the impact of drought self-propagation, is determined. We show that droughts occurring in dryland regions are particularly prone to self-propagate, as evaporation there tends to respond strongly to enhanced soil stress and precipitation is frequently convective. This kind of knowledge may be used to improve climate and forecast models and can be exploited to develop geo-engineering mitigation strategies to help prevent drought events from aggravating during their early stages.

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An ERA5-Based Hourly Global Pressure and Temperature (HGPT) Model

Remote Sensing ◽

10.3390/rs12071098 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1098

Author(s):

Pedro Mateus ◽

João Catalão ◽

Virgílio B. Mendes ◽

Giovanni Nico

Keyword(s):

Water Vapor ◽

Air Temperature ◽

Surface Pressure ◽

Surface Air Temperature ◽

Precipitable Water ◽

Weighted Mean ◽

Zenith Wet Delay ◽

Mean Temperature ◽

Weighted Mean Temperature ◽

Zenith Hydrostatic Delay

The Global Navigation Satellite System (GNSS) meteorology contribution to the comprehension of the Earth’s atmosphere’s global and regional variations is essential. In GNSS processing, the zenith wet delay is obtained using the difference between the zenith total delay and the zenith hydrostatic delay. The zenith wet delay can also be converted into precipitable water vapor by knowing the atmospheric weighted mean temperature profiles. Improving the accuracy of the zenith hydrostatic delay and the weighted mean temperature, normally obtained using modeled surface meteorological parameters at coarse scales, leads to a more accurate and precise zenith wet delay estimation, and consequently, to a better precipitable water vapor estimation. In this study, we developed an hourly global pressure and temperature (HGPT) model based on the full spatial and temporal resolution of the new ERA5 reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The HGPT model provides information regarding the surface pressure, surface air temperature, zenith hydrostatic delay, and weighted mean temperature. It is based on the time-segmentation concept and uses the annual and semi-annual periodicities for surface pressure, and annual, semi-annual, and quarterly periodicities for surface air temperature. The amplitudes and initial phase variations are estimated as a periodic function. The weighted mean temperature is determined using a 20-year time series of monthly data to understand its seasonality and geographic variability. We also introduced a linear trend to account for a global climate change scenario. Data from the year 2018 acquired from 510 radiosonde stations downloaded from the National Oceanic and Atmospheric Administration (NOAA) Integrated Global Radiosonde Archive were used to assess the model coefficients. Results show that the GNSS meteorology, hydrological models, Interferometric Synthetic Aperture Radar (InSAR) meteorology, climate studies, and other topics can significantly benefit from an ERA5 full-resolution model.

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Initial Assessment of the COSMIC-2/FORMOSAT-7 Neutral Atmosphere Data Quality in NESDIS/STAR Using In Situ and Satellite Data

Remote Sensing ◽

10.3390/rs12244099 ◽

2020 ◽

Vol 12 (24) ◽

pp. 4099

Author(s):

Shu-Peng Ho ◽

Xinjia Zhou ◽

Xi Shao ◽

Bin Zhang ◽

Loknath Adhikari ◽

...

Keyword(s):

Water Vapor ◽

Data Quality ◽

Signal To Noise Ratio ◽

Initial Assessment ◽

Observation System ◽

Neutral Atmosphere ◽

Satellite Mission ◽

Radiosonde Observation ◽

Satellite Applications ◽

The Mean

A COSMIC-1/FORMOSAT-3 (Constellation Observing System for Meteorology, Ionosphere, and Climate-1 and Formosa Satellite Mission 3) follow-on mission, COSMIC-2/FORMOSAT-7, had been successfully launched into low-inclination orbits on 25 June 2019. COSMIC-2 has a significantly increased Signal-to-Noise ratio (SNR) compared to other Radio Occultation (RO) missions. This study summarized the initial assessment of COSMIC-2 data quality conducted by the NOAA (National Oceanic and Atmospheric Administration) Center for Satellite Applications and Research (STAR). We use validated data from other RO missions to quantify the stability of COSMIC-2. In addition, we use the Vaisala RS41 radiosonde observations to assess the accuracy and uncertainty of the COSMIC-2 neutral atmospheric profiles. RS41 is currently the most accurate radiosonde observation system. The COSMIC-2 SNR ranges from 200 v/v to about 2800 v/v. To see if the high SNR COSMIC-2 signals lead to better retrieval results, we separate the COSMIC-2–RS41 comparisons into different SNR groups (i.e., 0–500 v/v group, 500–1000 v/v group, 1000–1500 v/v group, 1500–2000 v/v group, and >2000 v/v group). In general, the COSMIC-2 data quality in terms of stability, precision, accuracy, and uncertainty of the accuracy is very compatible with those from COSMIC-1. Results show that the mean COSMIC-2–RS41 water vapor difference from surface to 5 km altitude for each SNR groups are equal to −1.34 g/kg (0–500 v/v), −1.17 g/kg (500–1000 v/v), −1.33 g/kg (1000–1500 v/v), −0.93 g/kg (1500–2000 v/v), and −1.52 g/kg (>2000 v/v). Except for the >2000 v/v group, the high SNR measurements from COSMIC-2 seem to improve the mean water vapor difference for the higher SNR group slightly (especially for the 1500–2000 v/v group) comparing with those from lower SNR groups.

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Differential responses of carbon and water vapor fluxes to climate among evergreen needleleaf forests in the USA

Ecological Processes ◽

10.1186/s13717-016-0053-5 ◽

2016 ◽

Vol 5 (1) ◽

Cited By ~ 6

Author(s):

Pradeep Wagle ◽

Xiangming Xiao ◽

Thomas E. Kolb ◽

Beverly E. Law ◽

Sonia Wharton ◽

...

Keyword(s):

Water Vapor ◽

The Usa ◽

Differential Responses

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Estimation of Missing GPS Precipitable Water Vapor Data by Zenith Wet Delay and Meteorological Data

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.931-932.703 ◽

2014 ◽

Vol 931-932 ◽

pp. 703-708

Author(s):

Prawit Uang-Aree ◽

Sununtha Kingpaiboon ◽

Kulyakorn Khuanmar

Keyword(s):

Water Vapor ◽

Linear Regression ◽

Vapor Pressure ◽

Surface Temperature ◽

Meteorological Data ◽

Water Vapor Pressure ◽

Precipitable Water ◽

Precipitable Water Vapor ◽

Dew Point ◽

Zenith Wet Delay

This article presents a statistical correlation between GPS precipitable water vapor and meteorological data, i.e., surface temperature, air pressure, relative humidity, dew point temperature, and water vapor pressure by using linear regression. The data, recorded over a 4-year period, was used as an estimation of missing GPS precipitable water vapor data from discontinuous recordings. A multiple linear regression equation showed a correlation among zenith wet delay (ZWD), water vapor pressure (e) and surface temperature (T) was ZWD(e,T) = 17.4952e-0.8281T-93.164, with a coefficient of determination (R2) of 0.725, a mean absolute error of 8.71 mm, a root mean square error of 10.39 mm, and a mean absolute percentage error of 18.63%. The equation obtained can be used to estimate GPS precipitable water vapor data which is missing from recordings due to accident or technological error.

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Tropospheric Refractivity Profile Estimation by GNSS Measurement at China Big-Triangle Points

Atmosphere ◽

10.3390/atmos12111468 ◽

2021 ◽

Vol 12 (11) ◽

pp. 1468

Author(s):

Xiang Dong ◽

Fang Sun ◽

Qinglin Zhu ◽

Leke Lin ◽

Zhenwei Zhao ◽

...

Keyword(s):

Refractive Index ◽

Water Vapor ◽

Vapor Pressure ◽

Water Vapor Pressure ◽

Pressure Profile ◽

Radiosonde Data ◽

Machine Method ◽

Zenith Wet Delay ◽

Comparison Results ◽

Temperature And Pressure

Atmospheric radio refractivity has an obvious influence on the signal transmission path and communication group delay effect. The uncertainty of water vapor distribution is the main reason for the large error of tropospheric refractive index modeling. According to the distribution and characteristics of water vapor pressure, temperature, and pressure, which are the basic components of the refractive index, a method for retrieving atmospheric refractivity profile based on GNSS (Global Navigation Satellite System) and meteorological sensor measurement is introduced and investigated in this study. The variation of the correlation between zenith wet delay and water vapor pressure is investigated and analyzed in detail. The partial pressure profiles of water vapor are retrieved with relevance vector machine method based on tropospheric zenith wet delay calculated by single ground-based GPS (Global Positioning System) receiver. The atmospheric temperature and pressure is calculated with the least square method, which is used to fit the coefficients of the polynomial model based on a large number of historical meteorological radiosonde data of local stations. By combining the water vapor pressure profile retrieving from single ground-based GPS and temperature and pressure profile from reference model, the refractivity profile can be obtained, which is compared to radiosonde measurements. The comparison results show that results of the proposed method are consistent with the results of radiosonde. By using over ten years’ (through 2008 to 2017) historical radiosonde meteorological data of different months at China Big-Triangle Points, i.e., Qingdao, Sanya, Kashi, and Jiamusi radiosonde stations, tropospheric radio refractivity profiles are retrieved and modeled. The comparison results present that the accuracies of refractivity profile of the proposed method at Qingdao, Sanya, Kashi, and Jiamusi are about 5.48, 5.63, 3.58, and 3.78 N-unit, respectively, and the annual average relative RMSE of refractivity at these stations are about 1.66, 1.53, 1.49, and 1.23%, respectively.

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Evaluation of Precipitable Water Vapor Retrieval from Homogeneously Reprocessed Long-Term GNSS Tropospheric Zenith Wet Delay and Multi-Technique

Remote Sensing ◽

10.3390/rs13214490 ◽

2021 ◽

Vol 13 (21) ◽

pp. 4490

Author(s):

Hang Su ◽

Tao Yang ◽

Kan Wang ◽

Baoqi Sun ◽

Xuhai Yang

Keyword(s):

Water Vapor ◽

Precipitable Water ◽

Precipitable Water Vapor ◽

Systematic Bias ◽

Navigation Satellite ◽

A Posteriori ◽

Zenith Wet Delay ◽

Global Navigation ◽

Global Navigation Satellite

Water vapor is one of the most important greenhouse gases in the world. There are many techniques that can measure water vapor directly or remotely. In this work, we first study the Global Positioning System (GPS)- and the Global Navigation Satellite System (GLONASS)-derived Zenith Wet Delay (ZWD) time series based on 11 years of the second reprocessing campaign of International Global Navigation Satellite Systems (GNSS) Service (IGS) using 320 globally distributed stations. The amount of measurement, the local environment, and the antenna radome are shown to be the main factors that affect the GNSS ZWDs and the corresponding a posteriori formal errors. Furthermore, antenna radome is able to effectively reduce the systematic bias of ZWDs and a posteriori formal errors between the GPS- and GLONASS-based solutions. With the development of the GLONASS, the ZWD differences between the GPS- and the GLONASS-based solutions have gradually decreased to sub-mm-level after GLONASS was fully operated. As the GPS-based Precipitable Water Vapor (PWV) is usually used as the reference to evaluate the other PWV products, the PWV consistency among several common techniques is evaluated, including GNSSs, spaceborne sensors, and numerical products from the European Center for Medium-Range Weather Forecasts (ECMWF). As an example of the results from a detailed comparison analysis, the long-term global analysis shows that the PWV obtained from the GNSS and the ECMWF have great intra-agreements. Based on the global distribution of the magnitude of the PWV and the PWV drift, most of the techniques showed superior agreement and proved their ability to do climate research. With a detailed study performed for the ZWDs and PWV on a long-term global scale, this contribution provides a useful supplement for future research on the GNSS ZWD and PWV.

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GPS radio occultation with CHAMP: monitoring of climate change parameters

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-4-7837-2004 ◽

2004 ◽

Vol 4 (6) ◽

pp. 7837-7857 ◽

Cited By ~ 3

Author(s):

T. Schmidt ◽

S. Heise ◽

J. Wickert ◽

G. Beyerle ◽

C. Reigber

Keyword(s):

Water Vapor ◽

Radio Occultation ◽

Radiosonde Data ◽

Temperature Profiles ◽

Satellite Mission ◽

Data Set ◽

Gps Radio Occultation ◽

Temperature Bias ◽

Retrieval Scheme ◽

Data Source

Abstract. The Global Positioning System (GPS) radio occultation (RO) technique offers a valuable new data source for global and continuous monitoring of the Earth's atmosphere. Refractivity, temperature and water vapor profiles with high accuracy and vertical resolution can be derived from this method. The GPS RO technique requires no calibration, is not affected by clouds, aerosols or precipitation, and the occultations are almost uniformly distributed over the globe. In this paper the potential of GPS RO for monitoring of the temperature is demonstrated exemplarily for the tropical upper troposphere and lower stratosphere (UTLS) region using GPS RO data from the German CHAMP (CHAllenging Minisatellite Payload) satellite mission. In addition, results of a 1DVAR retrieval scheme to derive tropospheric water vapor profiles using ECMWF data as background will be discussed. CHAMP RO data are available since 2001 with up to 200 high resolution temperature profiles per day. The temperature bias between CHAMP temperature profiles and radiosonde data as well as ECMWF analyses is less than 0.5 K between 300–30 hPa. The CHAMP RO experiment generates the first long-term RO data set. Other satellite missions will follow (GRACE, TerraSAR-X, COSMIC, METOP) generating some thousand profiles of atmospheric parameters daily.

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Kinematic GNSS Estimation of Zenith Wet Delay over a Range of Altitudes

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-14-00111.1 ◽

2016 ◽

Vol 33 (1) ◽

pp. 3-15 ◽

Cited By ~ 6

Author(s):

Samuel R. Webb ◽

Nigel T. Penna ◽

Peter J. Clarke ◽

Stuart Webster ◽

Ian Martin ◽

...

Keyword(s):

Water Vapor ◽

Prediction Models ◽

Weather Prediction ◽

Precipitable Water ◽

Atmospheric Water Vapor ◽

Double Difference ◽

Atmospheric Water ◽

Total Delay ◽

Kinematic Gps ◽

Zenith Wet Delay

AbstractAtmospheric water vapor estimates from static ground-based Global Navigation Satellite System (GNSS) receivers are now operationally assimilated into numerical weather prediction models, either as total precipitable water vapor (PWV) or zenith total delay. To extend this concept, the estimation of water vapor using kinematic GNSS has been investigated for over a decade. Previous kinematic GNSS PWV studies suggest a 2–3-mm PWV measurement agreement with radiosondes, almost commensurate with static GNSS PWV measurement accuracy, but the only comprehensive experiments undertaken have been shipborne. As a first step toward extending sea level–based studies to airborne experiments that obtain atmospheric profiles, the authors considered the kinematic GNSS estimation of atmospheric water vapor along a repeatable trajectory spanning substantial topographic relief, namely, the Snowdon Mountain Railway, United Kingdom. The atmospheric water vapor was indirectly quantified through the GNSS estimation of zenith wet delay (ZWD). Static GNSS [GPS+ Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS)] reference receivers were installed at the 950-m-altitude profile’s extremities, providing ZWD reference values that were interpolated to the train’s altitude, together with profiles from 100-m-resolution runs of the Met Office Unified Model. Similar GNSS ZWD accuracies to those from shipborne studies are demonstrated, namely, 12.1 mm (RMS) using double-difference relative kinematic GPS and 16.2 mm using kinematic GPS precise point positioning (PPP), but which is improved to 11.6 mm when using kinematic GPS+GLONASS PPP, commensurate with the relative kinematic GPS. The PPP solution represents a more typical airborne estimation scenario, that is, without relying on nearby GNSS reference stations.

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