Evaluation of precipitable water vapor from five reanalysis products with ground-based GNSS observations

At present, the global reliability and accuracy of Precipitable Water Vapor (PWV) from different reanalysis products have not been comprehensively evaluated. In this study, PWV values derived by 268 Global Navigation Satellite Systems (GNSS) stations around the world covering the period from 2016 to 2018 are used to evaluate the accuracies of PWV values from five reanalysis products. The temporal and spatial evolution is not taken into account in this analysis, although the temporal and spatial evolution of atmospheric flows is one of the most important information elements available in numerical weather prediction products. The evaluation results present that five reanalysis products with PWV accuracy from high to low are in the order of the fifth generation of European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA5), ERA-Interim, Japanese 55-year Reanalysis (JRA-55), National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), and NCEP/DOE (Department of Energy) according to root mean square error (RMSE), bias and correlation coefficient. The ERA5 has the smallest RMSE value of 1.84 mm, while NCEP/NCAR and NCEP/DOE have bigger RMSE values of 3.34 mm and 3.51 mm, respectively. The findings demonstrate that ERA5 and two NCEP reanalysis products have the best and worst performance, respectively, among five reanalysis products. The differences in the accuracy of the five reanalysis products are mainly attributed to the differences in the spatial resolution of reanalysis products. There are some large absolute biases greater than 4 mm between GNSS PWV values and the PWV values of five reanalysis products in the southwest of South America and western China due to the limit of terrains and fewer observations. The accuracies of five reanalysis products are compared in different climatic zones. The results indicate that the absolute accuracies of five reanalysis products are highest in the polar regions and lowest in the tropics. Furthermore, the effects of different seasons on the accuracies of five reanalysis products are also analyzed, which indicates that RMSE values of five reanalysis products in summer and in winter are the largest and the smallest in the temperate regions. Evaluation results from five reanalysis products can help us to learn more about the advantages and disadvantages of the five released water vapor products and promote their applications.Peer ReviewedPostprint (published version

Analysis of Precipitable Water Vapour in Nigeria using GNSS Observations

Water Vapour estimation using ground-based Global Navigation Satellite System (GNSS) observations is a well-established technology that contributes to weather forecast, research, and climate monitoring. Water vapour in the atmosphere is directly related with precipitation that may lead to extreme event (e.g., floods). The application of GNSS to sense the total amount of water vapour integrated along the signal path in the troposphere is what is referred to as GNSS meteorology. GNSS has the advantage of all-weather condition, low cost with high temporal and spatial resolution when compared to other classical methods of water vapour measuring that are expensive and/or with low spatial and temporal coverage. When GNSS signals are transmitted from GNSS satellites in space to ground-based GNSS receivers, they experience a tropospheric delay (an error source in GNSS positioning) often represented in GNSS meteorology as the Zenith Total Delay (ZTD). The ZTD is the sum of the Zenith Hydrostatic Delay and the Zenith Wet Delay and it is one of the products of GNSS data processing. The ZTD can be converted to Precipitable Water Vapour (PWV) when surface temperature and pressure values are known at the GNSS site using a conversion factor (?) that is dependent on the weighted mean temperature (Tm) and pressure. This dissertation focuses on the estimation and analysis of water vapour in Nigeria using GNSS observations. The Nigerian Permanent GNSS Network (NIGNET) stations observations and products were retrieved from the infrastructure implemented by Office of the Surveyor General of the Federation (OSGoF). Processing of the data was carried out using online software (GipsyX) for the estimation of ZTD. Fifteen GNSS stations were used in this research and the period 2009 to 2021 was considered. The characteristics of the ZTD over the territory of Nigeria was investigated. The range of ZTD variation in Nigeria for the period used in this research was found to be approximately between 1900mm to 2700mm in the NIGNET stations. The two main seasons in Nigeria were significantly noticed as low peaks were found to be occurring during the dry (winter) season while high peaks were remarkably seen during the rainy (summer) season. The amplitude of the seasonal variation within the period under investigation is between a minimum of 36mm to a maximum of 124mm with the Northern region having higher values than the Southern part. It was discovered ultimately by the results obtained from the analyses, that ZTD variation in both the Northern and Southern regions are influenced by the 4 distinct climates and other local weather conditions including temperature and the trade wind from Sahara Desert and the Atlantic Ocean.A estimativa de vapor de água usando observações do Sistema Global de Navegação por Satélite (GNSS) é uma tecnologia bem estabelecida que tem dado um contributo importante para a realização de previsões meteorológicas, investigação e monitorização climática. O vapor de água na atmosfera está diretamente relacionado com a precipitação que pode levar a eventos extremos (por exemplo, inundações). A área de estudo do uso de dados GNSS para detetar a quantidade total de vapor de água integrado ao longo do caminho do sinal na troposfera é designado de meteorologia GNSS. O GNSS tem como vantagem de poder ser utilizado em todas as condições climáticas, apresentar baixo custo e alta resolução temporal e espacial quando comparado a outros métodos clássicos de medição de vapor de água, normalmente mais caros e/ou com baixa cobertura espacial e temporal. Quando os sinais GNSS são transmitidos dose satélites para recetores terrestres, existe um atraso troposférico (uma fonte de erro no posicionamento GNSS) frequentemente representado na meteorologia GNSS como o Atraso Zenital Total (ZTD em Inglês ). O ZTD é a soma do Atraso Zenital e do Atraso Zenital Húmido e é um dos produtos do processamento de dados GNSS. O ZTD pode ser convertido em PWV quando os valores de temperatura e pressão da superfície são conhecidos no local através de um fator de conversão (?) que depende da temperatura média ponderada (Tm) e da pressão. Esta dissertação tem como objetivo a estimativa e análise de vapor de água na Nigéria usando observações GNSS. As observações e produtos das estações da Rede Permanente GNSS da Nigéria (NIGNET) foram obtidos através da infraestrutura implementada pelo OSGoF. O processamento dos dados foi realizado por meio de software online (GipsyX) para a estimativa do ZTD. Dados de quinze estações GNSS foram utilizadas na análise correspondendo ao período entre 2009 a 2021, para avaliar as características da ZTD sobre o território da Nigéria. A faixa de variação de ZTD na Nigéria para o período considerado foi de aproximadamente 1900mm a 2700mm nas estações NIGNET. As duas principais estações climáticas na Nigéria destacaram-se, com picos baixos que ocorreram durante a estação seca (inverno), e picos altos observados durante a estação chuvosa (verão). A amplitude da variação sazonal no período sob investigação é entre um mínimo de 36mm e um máximo de 124mm com a região norte tendo valores mais elevados que a região sul. Pelos resultados obtidos das análises foi ainda possível verificar que a variação da ZTD nas regiões Norte e Sul são influenciadas pelos 4 climas distintos e outras condições climáticas locais, incluindo temperatura e ventos alísios do deserto do Saara e do Oceano Atlântico

Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region

Tropospheric water vapor is one of the most important trace gases of the Earth's climate system, and its temporal and spatial distribution is critical for the genesis of clouds and precipitation. Due to the pronounced dynamics of the atmosphere and the nonlinear relation of air temperature and saturated vapor pressure, it is highly variable, which hampers the development of high-resolution and three-dimensional maps of regional extent. With their complementary high temporal and spatial resolutions, Global Navigation Satellite Systems (GNSS) meteorology and Interferometric Synthetic Aperture Radar (InSAR) satellite remote sensing represent a significant alternative to generally sparsely distributed radio sounding observations. In addition, data fusion with collocation and tomographical methods enables the construction of detailed maps in either two or three dimensions. Finally, by assimilation of these observation-derived datasets with dynamical regional atmospheric models, tropospheric water vapor fields can be determined with high spatial and continuous temporal resolution. In the following, a collection of basic and processed datasets, obtained with the above-listed methods, is presented that describes the state and course of atmospheric water vapor for the extent of the GNSS Upper Rhine Graben Network (GURN) region. The dataset contains hourly 2D fields of integrated water vapor (IWV) and 3D fields of water vapor density (WVD) for four multi-week, variable season periods between April 2016 and October 2018 at a spatial resolution of (2.1 km)2. Zenith total delay (ZTD) from GNSS and collocation and refractivities are provided as intermediate products. InSAR (Sentinel-1A/B)-derived double differential slant total delay phases (ddSTDPs) and GNSS-based ZTDs are available for March 2015 to July 2019. The validation of data assimilation with five independent GNSS stations for IWV shows improving Kling–Gupta efficiency (KGE) scores for all seasons, most notably for summer, with collocation data assimilation (KGE = 0.92) versus the open-cycle simulation (KGE = 0.69). The full dataset can be obtained from https://doi.org/10.1594/PANGAEA.936447 (Fersch et al., 2021)

Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region

Tropospheric water vapor is one of the most important trace gases of the Earth\u27s climate system, and its temporal and spatial distribution is critical for the genesis of clouds and precipitation. Due to the pronounced dynamics of the atmosphere and the nonlinear relation of air temperature and saturated vapor pressure, it is highly variable, which hampers the development of high-resolution and three-dimensional maps of regional extent. With their complementary high temporal and spatial resolutions, Global Navigation Satellite Systems (GNSS) meteorology and Interferometric Synthetic Aperture Radar (InSAR) satellite remote sensing represent a significant alternative to generally sparsely distributed radio sounding observations. In addition, data fusion with collocation and tomographical methods enables the construction of detailed maps in either two or three dimensions. Finally, by assimilation of these observation-derived datasets with dynamical regional atmospheric models, tropospheric water vapor fields can be determined with high spatial and continuous temporal resolution. In the following, a collection of basic and processed datasets, obtained with the above-listed methods, is presented that describes the state and course of atmospheric water vapor for the extent of the GNSS Upper Rhine Graben Network (GURN) region. The dataset contains hourly 2D fields of integrated water vapor (IWV) and 3D fields of water vapor density (WVD) for four multi-week, variable season periods between April 2016 and October 2018 at a spatial resolution of (2.1 km)$^2$. Zenith total delay (ZTD) from GNSS and collocation and refractivities are provided as intermediate products. InSAR (Sentinel-1A/B)-derived double differential slant total delay phases (ddSTDPs) and GNSS-based ZTDs are available for March 2015 to July 2019. The validation of data assimilation with five independent GNSS stations for IWV shows improving Kling–Gupta efficiency (KGE) scores for all seasons, most notably for summer, with collocation data assimilation (KGE = 0.92) versus the open-cycle simulation (KGE = 0.69). The full dataset can be obtained from https://doi.org/10.1594/PANGAEA.936447 (Fersch et al., 2021)

A novel fusion framework embedded with zero-shot super-resolution and multivariate autoregression for precipitable water vapor across the continental Europe

Precipitable water vapor (PWV), as the most abundant greenhouse gas, significantly impacts the evapotranspiration process and thus the global climate. However, the applicability of mainstream satellite PWV products is limited by the tradeoff between spatial and temporal resolutions, as well as some external factors such as cloud contamination. In this study, we proposed a novel PWV spatio-temporal fusion framework based on the zero-shot super-resolution and the multivariate autoregression models (ZSSR-ARF) to improve the accuracy and continuity of PWV. The framework is implemented in a way that the satellite-derived observations (MOD05) are fused with the reanalysis data (ERA5) to generate accurate and seamless PWV of high spatio-temporal resolution (0.01°, daily) across the European continent from 2001 to 2021. Firstly, the ZSSR approach is used to enhance the spatial resolution of ERA5 PWV based on the internal recurrence of image information. Secondly, the optimal ERA5-MOD05 image pairs are selected based on the image similarity as inputs to improve the fusion accuracy. Thirdly, the framework develops a multivariate autoregressive fusion approach to allocate weights adaptively for the high-resolution image prediction, which primely addresses the non-stationarity and autocorrelation of PWV. The results reveal that the accuracies of fused PWV are consistent with those of the GPS retrievals (r = 0.82–0.95 and RMSE = 2.21–4.01 mm), showing an enhancement in the accuracy and continuity compared to the original MODIS PWV. The ZSSR-ARF fusion framework outperforms the other methods with R$^2$ improved by over 24% and RMSE reduced by over 0.61 mm. Furthermore, the fused PWV exhibits similar temporal consistency (mean difference of 0.40 mm and DSTD of 3.22 mm) to the reliable ERA5 products, and substantial increasing trends (mean of 0.057 mm/year and over 0.1 mm/year near the southern and western coasts) are observed over the European continent. As the accuracy and continuity of PWV are improved, the outcome of this paper has potential for climatic analyses during the land-atmosphere cycle process

Analysis of Precipitable Water Vapour in Angola Using GNSS Observations

For accurate weather predictions and analysis of extreme events, a good estimate of the amount of water content in the atmosphere is essential. This information is provided by several techniques like radiosondes that measure this parameter at various heights. However, most of them are very limited spatially and temporarily or suffer from measurement specific constraints. To complement these techniques, Precipitable Water Vapor (PWV) can be measured with GNSS (Global Navigation Satellite System) at CORS (Continuously Operating Reference Stations) networks. when the temperature and pressure are also known at the station location. PWV can be derived from the delay in the GNSS signal when it passes through the troposphere. In the framework of SUGGEST-AFRICA, it is being implemented a system to use the national GNSS stations for the automatic computation of PWV in Angola. Thus, this dissertation intends to describe the necessary steps to develop a system to be used for supporting meteorological and climate applications in Angola. SUGGEST-AFRICA also funded the installation of 5 weather stations, collocated with GNSS stations in Angola namely: Benguela, Cabinda, Cuito, Luanda and Namibe, in order to obtain pressure and temperature which is necessary to obtain the PWV estimates. When there are no nearby meteorological stations, the potential alternative is to use values from global/regional models. Methodologies have been optimized to passive and actively access the GNSS data; the PWV estimations are computed using PPP (Precise Point Positioning), which permits the estimation of each station separately; solutions have been validated using internal values. In addition, analyses are presented to evaluate the reliability of the network. This work presents preliminary results for the variation of the ZTD data available all around the territory in Angola and how they relate to the seasonal variations in water vapour. Also, presents preliminary results for the time-series variation of PWV in the Luanda station (collocated by the SEGAL group). This study is supported by SUGGEST-AFRICA, funded by Fundação Aga Khan and FCT. It uses computational resources provided by C4G – Collaboratory for Geosciences (PINFRA/22151/2016). It is also supported by project FCT/UIDB/50019/2020 – IDL funded by FCT.Para precisão da previsão do tempo e análise de eventos extremos é fundamental uma boa estimativa do vapor da água na atmosfera. O vapor da água na atmosfera é fornecido por várias técnicas como radio sondagem que mede este parâmetro em várias alturas. No entanto, muito dessas técnicas são limitadas devido a resolução espacial e temporal ou sofrem restrições específicas de medição. Para completar estas limitações encontrado nas demais técnicas, o vapor da água precipitável (PWV) pode ser medido pelo GNSS (Sistemas de navegação global por satélite) CORS (Rede nacional de estações de referência de operação continua). PWV pode ser obtido a partir do atraso do sinal de GNSS através da troposfera, quando a temperatura e a pressão também são conhecidas derivado da localização duma estação meteorológica. No âmbito da SUGGEST-ÁFRICA, esta ser implementado um sistema de modo a calcular o PWV de uma maneira automática em Angola. Assim, nesta dissertação pretende descrever os passos necessários para desenvolver tal sistema a ser utilizado para apoiar aplicações meteorológicas e climáticas em Angola. SUGGEST-ÁFRICA também financiou a instalação de 5 estações meteorológicas, colocada com estações GNSS em Angola, nomeadamente: Benguela, Cabinda, Cuito, Luanda e Namibe, a fim de obter a pressão e a temperatura necessárias para obter as estimativas PWV. Aconselha-se o uso dos modelos globais/regionais para aquisição de valores de pressão e temperatura quando não existe dados nas estações meteorológicas adjacentes. As metodologias foram otimizadas para o acesso passivo e ativo dos dados GNSS; a estimação do vapor de água precipitável é calculada usando a técnica PPP (Posicionamento do ponto preciso), que permite a determinação de cada estação individualmente e separadamente; as soluções foram validadas usando valor interno. Além disso, são apresentadas análises para avaliar a fiabilidade da rede. Este trabalho, também apresenta resultados preliminares para a variação de todo dados do ZTD disponível em Angola e a forma como se relacionam com as variações sazonais do vapor de água. Também, apresenta variação da série temporal do PWV na estação meteorológica de Luanda (instalado pela SEGAL). Este estudo é suportado pela SUGGEST-ÁFRICA, financiado pela fundação Aga Khan e FCT. Utiliza recurso computacional fornecido pela C4G – Colaboração de Geociências (PINFRA/ 22151/2016). Também é apoiado pelo projecto FCT/UIDB/50019/2020 – IDL financiado pela FCT

GEWEX water vapor assessment (G-VAP): final report

Este es un informe dentro del Programa para la Investigación del Clima Mundial (World Climate Research Programme, WCRP) cuya misión es facilitar el análisis y la predicción de la variabilidad de la Tierra para proporcionar un valor añadido a la sociedad a nivel práctica. La WCRP tiene varios proyectos centrales, de los cuales el de Intercambio Global de Energía y Agua (Global Energy and Water Exchanges, GEWEX) es uno de ellos. Este proyecto se centra en estudiar el ciclo hidrológico global y regional, así como sus interacciones a través de la radiación y energía y sus implicaciones en el cambio global. Dentro de GEWEX existe el proyecto de Evaluación del Vapor de Agua (VAP, Water Vapour Assessment) que estudia las medidas de concentraciones de vapor de agua en la atmósfera, sus interacciones radiativas y su repercusión en el cambio climático global.El vapor de agua es, de largo, el gas invernadero más importante que reside en la atmósfera. Es, potencialmente, la causa principal de la amplificación del efecto invernadero causado por emisiones de origen humano (principalmente el CO2). Las medidas precisas de su concentración en la atmósfera son determinantes para cuantificar este efecto de retroalimentación positivo al cambio climático. Actualmente, se está lejos de tener medidas de concentraciones de vapor de agua suficientemente precisas para sacar conclusiones significativas de dicho efecto. El informe del WCRP titulado "GEWEX water vapor assessment. Final Report" detalla el estado actual de las medidas de las concentraciones de vapor de agua en la atmósfera. AEMET ha colaborado en la generación de este informe y tiene a unos de sus miembros, Xavier Calbet, como co-autor de este informe

A systematic assessment of water vapor products in the Arctic: from instantaneous measurements to monthly means

Water vapor is an important component in the water and energy cycle of the Arctic. Especially in light of Arctic amplification, changes in water vapor are of high interest but are difficult to observe due to the data sparsity of the region. The ACLOUD/PASCAL campaigns performed in May/June 2017 in the Arctic North Atlantic sector offers the opportunity to investigate the quality of various satellite and reanalysis products. Compared to reference measurements at R/V Polarstern frozen into the ice (around 82∘ N, 10∘ E) and at Ny-Ålesund, the integrated water vapor (IWV) from Infrared Atmospheric Sounding Interferometer (IASI) L2PPFv6 shows the best performance among all satellite products. Using all radiosonde stations within the region indicates some differences that might relate to different radiosonde types used. Atmospheric river events can cause rapid IWV changes by more than a factor of 2 in the Arctic. Despite the relatively dense sampling by polar-orbiting satellites, daily means can deviate by up to 50 % due to strong spatio-temporal IWV variability. For monthly mean values, this weather-induced variability cancels out, but systematic differences dominate, which particularly appear over different surface types, e.g., ocean and sea ice. In the data-sparse central Arctic north of 84∘ N, strong differences of 30 % in IWV monthly means between satellite products occur in the month of June, which likely result from the difficulties in considering the complex and changing surface characteristics of the melting ice within the retrieval algorithms. There is hope that the detailed surface characterization performed as part of the recently finished Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) will foster the improvement of future retrieval algorithms