scholarly journals Application of GNSS derived precipitable water vapour prediction in West Africa

2019 ◽  
Vol 9 (1) ◽  
pp. 41-47
Author(s):  
A. Acheampong ◽  
K. Obeng
Keyword(s):  
West Africa ◽  
Water Vapour ◽  
Prediction Models ◽  
Moving Average ◽  
Weather Prediction ◽  
Precipitable Water ◽  
Ease Of Use ◽  
Quadratic Model ◽  
International Gnss Service ◽  
Precipitable Water Vapour

Abstract Atmospheric water vapour, a major component in weather systems serves as the main source for precipitation, provides latent heat which helps maintain the earth’s energy balance and a major parameter in Numerical Weather Prediction (NWP) models. An observational technique based on the Global Navigation Satellite System (GNSS) has made it possible to easily retrieve Precipitable Water (PW) at station’s antenna position with very high spatial and temporal variabilities. GNSS techniques are superior to ground-based and balloons sensors in terms of accuracy, ease of use, wider coverage and easier assimilation into NWP models. This study sought to use prediction models using daily observational data from Four (4) International GNSS Service stations in West Africa. The best prediction model can be used in cases of station outages and to predict PW over data poor regions using computed Zenith Tropospheric Delays (ZTD). gLAB software was used to process the stations’ data in Precise Point Positioning mode and PW were retrieved using station’s temperature and pressure values. Computed PW were compared against Total Column Water Vapour from ERA-Interim Reanalysis data in 2016. Correlation coefficient (R2) values ranging from 0.947 — 0.995 were obtained for the four stations. With computed PW’s, three regression models were tested to find the best-fit with PW as the dependent variable and ZTD being the independent variable. The quadratic model gave the highest R2 and lowest RMSE values as against the linear and exponential models. Time series forecasts models such as moving average, autoregressive, exponential smoothing and autoregressive integrated moving average were also employed. The forecasts results were compared against ZTD with autoregressive model reporting the highest R2 and lowest RMSE amongst the forecast models developed.

scholarly journals HGPT2: An ERA5-Based Global Model to Estimate Relative Humidity

2021 ◽  
Vol 13 (11) ◽  
pp. 2179
Author(s):  
Pedro Mateus ◽  
Virgílio B. Mendes ◽  
Sandra M. Plecha
Keyword(s):  
Water Vapor ◽  
Relative Humidity ◽  
Real Time ◽  
Prediction Models ◽  
Weather Prediction ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Global Navigation Satellite Systems ◽  
International Gnss Service ◽  
Weighted Mean Temperature

The neutral atmospheric delay is one of the major error sources in Space Geodesy techniques such as Global Navigation Satellite Systems (GNSS), and its modeling for high accuracy applications can be challenging. Improving the modeling of the atmospheric delays (hydrostatic and non-hydrostatic) also leads to a more accurate and precise precipitable water vapor estimation (PWV), mostly in real-time applications, where models play an important role, since numerical weather prediction models cannot be used for real-time processing or forecasting. This study developed an improved version of the Hourly Global Pressure and Temperature (HGPT) model, the HGPT2. It is based on 20 years of ERA5 reanalysis data at full spatial (0.25° × 0.25°) and temporal resolution (1-h). Apart from surface air temperature, surface pressure, zenith hydrostatic delay, and weighted mean temperature, the updated model also provides information regarding the relative humidity, zenith non-hydrostatic delay, and precipitable water vapor. The HGPT2 is based on the time-segmentation concept and uses the annual, semi-annual, and quarterly periodicities to calculate the relative humidity anywhere on the Earth’s surface. Data from 282 moisture sensors located close to GNSS stations during 1 year (2020) were used to assess the model coefficients. The HGPT2 meteorological parameters were used to process 35 GNSS sites belonging to the International GNSS Service (IGS) using the GAMIT/GLOBK software package. Results show a decreased root-mean-square error (RMSE) and bias values relative to the most used zenith delay models, with a significant impact on the height component. The HGPT2 was developed to be applied in the most diverse areas that can significantly benefit from an ERA5 full-resolution model.

Diurnal cycle of GNSS-derived precipitable water vapour in tropical regions

2020 ◽  
Author(s):  
Zofia Bałdysz ◽  
Grzegorz Nykiel ◽  
Dariusz Baranowski ◽  
Beata Latos ◽  
Mariusz Figurski
Keyword(s):  
Water Vapour ◽  
Diurnal Cycle ◽  
Asian Summer Monsoon ◽  
Precipitable Water ◽  
Tropical Atmosphere ◽  
International Gnss Service ◽  
Precipitable Water Vapour ◽  
Water Vapour Content ◽  
Inter Tropical Convergence Zone ◽  
Tropical Regions

<p>Convective processes in the tropical atmosphere and their diurnal cycles have important repercussions for the circulations in the tropical regions and beyond. Monitoring of the water vapour content in the tropical atmosphere remains a challenge due to its high temporal and spatial variability. Global models tend to fail to correctly capture the diurnal convection, limiting forecasting accuracy. In this work, we investigated precipitable water vapour (PWV) diurnal cycle, precipitation and infrared  brightness temperature (TB) data over the tropical area. We used in-situ observations from 44 IGS (International GNSS Service) stations covering time span of 18 years, together with satellite-based precipitation and cloudiness data, taken from the Tropical Rainfall Measurement Mission gridded dataset (TRMM 3B42 v7) and the global, merged infrared (IR) dataset, respectively. The data provided an opportunity to examine the characteristics of a diurnal cycle of PWV, precipitation and TB over the study area in greater detail than before.</p><p>In particular, our results show that the diurnal cycle of PWV and TB were almost entirely dominated by mono-modal distributions. The diurnal cycle of precipitation onshore (continental areas or big islands; continental regime) had a single late afternoon peak, and that offshore (small islands; oceanic regime) had both a midday and a nocturnal peak. Daily amplitude phase shift of PWV and precipitation at onshore stations with a continental regime consistently occurred at the same time, while TB maximum peaked about five hours later. Furthermore, results show that the daily mean and the amplitude of the diurnal cycle of PWV, precipitation and TB appeared smaller on offshore stations, exhibited to an oceanic regime, than on onshore, continental stations. Additional analysis of seasonal variations of GNSS-derived PWV shows the usefulness of such measurements for tracking propagation of longer-scale phenomena, such as Inter Tropical Convergence Zone (ITCZ), Southeast Asian monsoon or East Asian summer monsoon.</p>

scholarly journals EFFECTS OF OCEAN TIDE MODELS ON GNSS-ESTIMATED ZTD AND PWV IN TURKEY

2015 ◽  
Vol XL-1-W5 ◽  
pp. 255-258
Author(s):  
G. Gurbuz ◽  
S. Jin ◽  
C. Mekik
Keyword(s):  
Water Vapour ◽  
Weather Prediction ◽  
Precipitable Water ◽  
Ocean Tide ◽  
Tropospheric Delay ◽  
Precipitable Water Vapour ◽  
Ocean Tide Model ◽  
Tide Model ◽  
Gnss Data ◽  
Ocean Tide Models

Global Navigation Satellite System (GNSS) observations can precisely estimate the total zenith tropospheric delay (ZTD) and precipitable water vapour (PWV) for weather prediction and atmospheric research as a continuous and all-weather technique. However, apart from GNSS technique itself, estimations of ZTD and PWV are subject to effects of geophysical models with large uncertainties, particularly imprecise ocean tide models in Turkey. In this paper, GNSS data from Jan. 1<sup>st</sup> to Dec. 31<sup>st</sup> of 2014 are processed at 4 co-located GNSS stations (GISM, DIYB, GANM, and ADAN) with radiosonde from Turkish Met-Office along with several nearby IGS stations. The GAMIT/GLOBK software has been used to process GNSS data of 30-second sample using the Vienna Mapping Function and 10° elevation cut-off angle. Also tidal and non-tidal atmospheric pressure loadings (ATML) at the observation level are also applied in GAMIT/GLOBK. Several widely used ocean tide models are used to evaluate their effects on GNSS-estimated ZTD and PWV estimation, such as IERS recommended FES2004, NAO99b from a barotropic hydrodynamic model, CSR4.0 obtained from TOPEX/Poseidon altimetry with the model FES94.1 as the reference model and GOT00 which is again long wavelength adjustments of FES94.1 using TOPEX/Poseidon data at 0.5 by 0.5 degree grid. The ZTD and PWV computed from radiosonde profile observations are regarded as reference values for the comparison and validation. In the processing phase, five different strategies are taken without ocean tide model and with four aforementioned ocean tide models, respectively, which are used to evaluate ocean tide models effects on GNSS-estimated ZTD and PWV estimation through comparing with co-located Radiosonde. Results showed that ocean tide models have greatly affected the estimation of the ZTD in centimeter level and thus the precipitable water vapour in millimeter level, respectively at stations near coasts. The ocean tide model FES2004 that is the product of assimilation of the altimetric data of ERS2, TOPEX/POSEIDON and the data of a global tide gauge network, gave the most accurate results when compared to radiosonde with ±1.99 mm in PWV at stations near coastline. While other ocean tides models agree each other at millimeter level in PWV. However, at inland GNSS stations, ocean tide models have less effects on GNSS-estimated ZTD and PWV, e.g., with ±1.0 mm in ZTD and ±0.1 mm in PWV.

scholarly journals On the inclusion of GPS precipitable water vapour in the nowcasting of rainfall

2015 ◽  
Vol 3 (6) ◽  
pp. 3861-3895 ◽  
Author(s):  
P. Benevides ◽  
J. Catalao ◽  
P. M. A. Miranda
Keyword(s):  
Water Vapour ◽  
Meteorological Data ◽  
Simple Algorithm ◽  
Precipitable Water ◽  
False Alarms ◽  
Precipitable Water Vapour ◽  
Temporal Behaviour ◽  
Nearby Region ◽  
Single Station ◽  
Rain Events

Abstract. The temporal behaviour of Precipitable Water Vapour (PWV) retrieved from GPS delay data is analysed in a number of case studies of intense precipitation in the Lisbon area, in the period 2010–2012, and in a continuous annual cycle of 2012 observations. Such behaviour is found to correlate positively with the probability of precipitation, especially in cases of severe rainfall. The evolution of the GPS PWV in a few stations is analysed by a least-squares fitting of a broken line tendency, made by a temporal sequence of ascents and descents over the data. It is found that most severe rainfall event occurs in descending trends after a long ascending period, and that the most intense events occur after steep ascents in PWV. A simple algorithm, forecasting rain in the 6 h after a steep ascent of the GPS PWV in a single station is found to produce reasonable forecasts of the occurrence of precipitation in the nearby region, without significant misses in what concerns larger rain events, but with a substantial amount of false alarms. It is suggested that this method could be improved by the analysis of 2-D or 3-D time varying GPS PWV fields, or by its joint use with other meteorological data relevant to nowcast precipitation.

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