Results 41 to 50 of about 467 (147)
The development of a network of ground-based telescopes requires detailed astroclimatic studies. This paper presents the spatial distributions of precipitable water vapor (PWV), total cloud cover (TCC) and cloud base height (CBH).
Artem Yu. Shikhovtsev +3 more
doaj +1 more source
GRENet: GNSS‐Enhanced Radar Extrapolation Network for Precipitation Nowcasting
Abstract Accurate precipitation nowcasting is one of the most challenging tasks in atmospheric sciences. The current methods of nowcasting primarily rely on inferring precipitation from radar reflectivity, which inevitably leads to uncertainties in forecasts due to the limitations of single radar data in capturing the detailed initial conditions of ...
Cuixian Lu +7 more
wiley +1 more source
Unconstrained GNSS Water Vapor Tomography With Real Data and LEO Augmentation
Abstract The availability of four complete GNSS constellations (GPS, GLONASS, BeiDou and Galileo) offers, for the first time, the possibility of performing water vapor tomographic inversions that do not rely on external data. A tomographic model that includes no external constraints and requires no first guess and no virtual observations is described ...
P. M. A. Miranda +3 more
wiley +1 more source
Development of a Local Mean Temperature Equation for GPS-Based Precipitable Water Vapor Over the Korean Peninsula [PDF]
The Bevis' mean temperature equation (MTE) is generally used in estimating Precipitable Water Vapor (PWV) based on GPS measurements. Because the equation was derived from North American meteorological data, however, it may induce errors in PWV if the ...
Juhyun Ha, Kwan-Dong Park, Bok-Haeng Heo
doaj +1 more source
Precipitable Water Vapor Retrieval Based on DPC Onboard GaoFen-5 (02) Satellite
GaoFen-5 (02) (GF5-02) is a new Chinese operational satellite that was launched on 7 September 2021. The Directional Polarimetric Camera (DPC) is one of the main payloads and is mainly used for the remote sensing monitoring of atmospheric components such
Chao Wang +6 more
doaj +1 more source
A Window‐Augmented Machine Learning Approach for Direct GNSS Precipitable Water Vapor Retrieval
Abstract Global Navigation Satellite Systems (GNSS) provide an effective means for remote sensing of precipitable water vapor (PWV). However, conventional GNSS‐based PWV retrieval approaches rely heavily on auxiliary meteorological parameters, which are frequently unavailable in real time, while most direct retrieval methods use station data aggregated
Zhouao Zheng +7 more
wiley +1 more source
Abstract Accurate representation of atmospheric water vapor is crucial for improving numerical weather prediction, particularly over regions with complex topography and sparse observation networks. Although assimilation of Global Navigation Satellite System (GNSS)‐derived integrated products such as zenith total delay or precipitable water vapor can ...
Arash Tayfehrostami +3 more
wiley +1 more source
Impacts of Atmospheric Rivers in Central Greenland: Snowfall, Clouds, and Atmospheric State
Abstract Atmospheric rivers (ARs) are long bands of strong horizontal water vapor transport responsible for over 90% of total integrated vapor transport (IVT) in extratropical and polar regions. Using a 12‐year record (2010–2022) of ground‐based remote sensing, radiosonde, snow stake, and reanalysis data from Summit Station, Greenland, we quantify the ...
A. E. Wedum +5 more
wiley +1 more source
Statistical modelling of atmospheric mean temperature in sub-Sahel West Africa
Atmospheric mean temperature Tm, is a vital parameter in the evaluation of precipitable water vapor (PWV) through the analysis of GPS signal, it is therefore important to have a good way of evaluating Tm for the eventual accurate evaluation of PWV using ...
Oluwasesan Adeniran Falaiye +2 more
doaj +1 more source
Precipitable water vapor (PWV) is a critical factor in precipitation formation, the hydrological cycle, and climate change. In this study, a neural network–based PWV estimation model was established using near‐surface meteorological observation and numerical weather prediction (NWP) products.
Chenghua Xie, Pramita Mishra
wiley +1 more source

