European GNSS troposphere monitoring for meteorological applications

Abstract Near real-time GNSS double-difference network processing is a traditional method still used within the EUMETNET EIG GNSS Water Vapour Programme (E-GVAP) for the atmosphere water vapour content monitoring in support of Numerical Weather Prediction. The standard production relies on estimating zenith tropospheric path delays (ZTDs) for GNSS ground stations with a 1-hour time resolution and a latency of 90 minutes. The Precise Point Positioning (PPP) method in real-time mode has reached the reliability and the accuracy comparable to the near real-time solution. The effectiveness of the PPP method relies on exploiting undifferenced observations from individual receivers, thus optimal use of all tracked systems, observations and signal bands, possible in-situ processing, high temporal resolution of estimated parameters and almost without any latency. The solution may implicitly include horizontal tropospheric gradients and slant tropospheric path delays for enabling the monitoring of a local asymmetry of the troposphere around each individual site. We have been estimating ZTD and gradients in real-time continuously since 2015 with a limited number of stations. Recently, the solution has been extended to a pan-European and global production consisting of approximately 200 stations. The real-time product has been assessed cross-comparing ZTDs and horizontal gradients at 11 collocated stations and by validating real-time ZTDs with respect to the final post-processing products.

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Atmospheric water vapour content over La Silla Paranal Observatory

Proceedings of the International Astronomical Union ◽

10.1017/s1743921310010598 ◽

2009 ◽

Vol 5 (H15) ◽

pp. 537-537

Author(s):

R. Querel ◽

F. Kerber ◽

R. Hanuschik ◽

G. Lo Curto ◽

D. Naylor ◽

...

Keyword(s):

Real Time ◽

Water Vapour ◽

Atmospheric Water ◽

Water Vapour Content ◽

Atmospheric Water Vapour ◽

Infrared Wavelengths ◽

Long Term Monitoring ◽

Term Monitoring ◽

Principle Source

Water vapour is the principle source of opacity at infrared wavelengths in the earth's atmosphere. Measurements of atmospheric water vapour serve two primary purposes when considering operation of an observatory: long-term monitoring of precipital water vapour (PWV) is useful for characterizing potential observatory sites, and real-time monitoring of PWV is useful for optimizing use, in particular for mid-IR observations.

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Automated Online Flow Cytometry Advances Microalgal Ecosystem Management as in situ, High-Temporal Resolution Monitoring Tool

Frontiers in Bioengineering and Biotechnology ◽

10.3389/fbioe.2021.642671 ◽

2021 ◽

Vol 9 ◽

Author(s):

Iris Haberkorn ◽

Cosima L. Off ◽

Michael D. Besmer ◽

Leandro Buchmann ◽

Alexander Mathys

Keyword(s):

Flow Cytometry ◽

Real Time ◽

Temporal Resolution ◽

High Temporal Resolution ◽

Natural Ecosystems ◽

Biotechnological Production ◽

Microalgal Biomass ◽

Bioprocess Optimization ◽

Related Population

Microalgae are emerging as a next-generation biotechnological production system in the pharmaceutical, biofuel, and food domain. The economization of microalgal biorefineries remains a main target, where culture contamination and prokaryotic upsurge are main bottlenecks to impair culture stability, reproducibility, and consequently productivity. Automated online flow cytometry (FCM) is gaining momentum as bioprocess optimization tool, as it allows for spatial and temporal landscaping, real-time investigations of rapid microbial processes, and the assessment of intrinsic cell features. So far, automated online FCM has not been applied to microalgal ecosystems but poses a powerful technology for improving the feasibility of microalgal feedstock production through in situ, real-time, high-temporal resolution monitoring. The study lays the foundations for an application of automated online FCM implying far-reaching applications to impel and facilitate the implementation of innovations targeting at microalgal bioprocesses optimization. It shows that emissions collected on the FL1/FL3 fluorescent channels, harnessing nucleic acid staining and chlorophyll autofluorescence, enable a simultaneous assessment (quantitative and diversity-related) of prokaryotes and industrially relevant phototrophic Chlorella vulgaris in mixed ecosystems of different complexity over a broad concentration range (2.2–1,002.4 cells ⋅μL–1). Automated online FCM combined with data analysis relying on phenotypic fingerprinting poses a powerful tool for quantitative and diversity-related population dynamics monitoring. Quantitative data assessment showed that prokaryotic growth phases in engineered and natural ecosystems were characterized by different growth speeds and distinct peaks. Diversity-related population monitoring based on phenotypic fingerprinting indicated that prokaryotic upsurge in mixed cultures was governed by the dominance of single prokaryotic species. Automated online FCM is a powerful tool for microalgal bioprocess optimization owing to its adaptability to myriad phenotypic assays and its compatibility with various cultivation systems. This allows advancing bioprocesses associated with both microalgal biomass and compound production. Hence, automated online FCM poses a viable tool with applications across multiple domains within the biobased sector relying on single cell–based value chains.

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Retrieval of Stable Water Vapour Isotopologues from the TROPOMI Instrument

10.5194/egusphere-egu21-9864 ◽

2021 ◽

Author(s):

Tim Trent ◽

Hartmut Boesch ◽

Peter Somkuti ◽

Mathhias Schneider ◽

Farahnaz Khosrawi ◽

...

Keyword(s):

Water Vapour ◽

In Situ Measurements ◽

Climate Feedback ◽

Retrieval Algorithm ◽

Unique Contribution ◽

Water Vapour Content ◽

Infrared Measurements ◽

Water Isotopologues ◽

The Impact

Atmospheric moisture is a crucial factor for the redistribution of heat in the atmosphere, with a strong coupling between atmospheric circulation and moisture pathways responsible most climate feedback mechanisms. Conventional satellite and in situ measurements provide information on water vapour content and vertical distribution; however, observations of water isotopologues make a unique contribution to a better understanding of this coupling.In recent years, observations of water vapour isotopologue from satellites have become available from nadir thermal infrared measurements (TES, AIRS, IASI) which are sensitive to the free troposphere and from shortwave-infrared (SWIR) sensors (GOSAT, SCIAMACHY) that provide column-averaged concentrations including sensitivity to the boundary layer. The TROPOMI instrument on-board Sentinel 5P (S5p) measures SWIR radiance spectra that allow retrieval of water isotopologue columns but with much improved spatial and temporal coverage compared to other SWIR sensors promising a step-change for scientific and operational applications.Here we present the retrieval algorithm development for stable water isotopologues from TROPOMI as part of the ESA S5p Innovation programme.&#160; We also discuss the validation of these types of satellite products with fiducial in situ measurements, and challenges compared with other satellite measurements. Finally, we outline the roadmap for assessing the impact of TROPOMI data against state-of-the-art isotope enabled models.

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The International Soil Moisture Network: an open-source data hosting facility in support of meteorology and climate science

10.5194/ems2021-368 ◽

2021 ◽

Author(s):

Ivana Petrakovic ◽

Irene Himmelbauer ◽

Daniel Aberer ◽

Lukas Schremmer ◽

Philippe Goryl ◽

...

Keyword(s):

Soil Moisture ◽

Real Time ◽

International Cooperation ◽

Land Surface ◽

Prediction Models ◽

Weather Prediction ◽

Source Surface ◽

Federal Institute

The International Soil Moisture Network (ISMN, https://ismn.earth) is international cooperation to establish and maintain a unique centralized global data hosting facility, making in-situ soil moisture data easily and freely accessible (Dorigo et al., 2021). Initiated in 2009 as a community effort through international cooperation (ESA, GEWEX, GTN-H, GCOS, TOPC, HSAF, QA4SM, C3S, etc.), the ISMN is an essential means for validating and improving global satellite soil moisture products, land surface-, climate-, and hydrological models.&#160; The ISMN is a widely used, reliable, and consistent in-situ data source (surface and sub-surface) collected by a myriad of data organizations on a voluntary basis. &#160;The in-situ soil moisture measurements are collected, harmonized in terms of units and sampling rates, advanced quality control is applied and the data is then stored in a database and made available online, where users can download it for free. Currently, 71 networks are participating with more than 2800 stations distributed on a global scale and a steadily increasing number of user communities. Long term time series with mainly hourly timestamps from 1952 &#8211; up to near-real-time are stored in the database, including daily near-real-time updates. Besides soil moisture in our database are stored other meteorological variables as well (air temperature, soil temperature, precipitation, snow depth, etc.). The ISMN provides benchmark data for several operational services such as ESA CCI Soil Moisture, the Copernicus Climate Change (C3S) and Global Land Service (CGLS), and the online validation tool QA4SM. ISMN data is widely used in a variety of scientific fields (e.g., climate, water, agriculture, disasters, ecosystems, weather, biodiversity, etc). To validate the land surface representations of meteorological forecasting models soil moisture from the ISMN has often been used. The development of various generations of TESSEL models used both in the Integrated Forecasting Systems and reanalysis products of ECMWF, greatly profited from soil moisture and temperature data from the ISMN. Using ISMN data several studies assessed the soil moisture skill of the Weather Research and Forecasting Model (WRF) and assessed the forecast skill or new implementations of numerical weather prediction models. We greatly acknowledge the financial support provided by ESA through various projects: SMOSnet International Soil Moisture Network, IDEAS+, and QA4EO. To ensure a long-term funding for the ISMN operations, several ideas were perused together with ESA. A partner for this task could be found within the International Center for Water Resources and Global Change (ICWRGC) hosted by the German Federal Institute of Hydrology (BfG).&#160; In this session, we want to give an overview and future outlook of the ISMN, highlighting its unique features and discuss challenges in supporting the hydrological research community in need of freely available, standardized, and quality-controlled datasets.&#160;

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Estimation of Daily Potential Evapotranspiration in Real-Time from GK2A/AMI Data Using Artificial Neural Network for the Korean Peninsula

Hydrology ◽

10.3390/hydrology8030129 ◽

2021 ◽

Vol 8 (3) ◽

pp. 129

Author(s):

Jae-Cheol Jang ◽

Eun-Ha Sohn ◽

Ki-Hong Park ◽

Soobong Lee

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Real Time ◽

Korean Peninsula ◽

Potential Evapotranspiration ◽

Weather Prediction ◽

Spatiotemporal Variability ◽

Artificial Neural ◽

Using Data

Evapotranspiration (ET) is a fundamental factor in energy and hydrologic cycles. Although highly precise in-situ ET monitoring is possible, such data are not always available due to the high spatiotemporal variability in ET. This study estimates daily potential ET (PET) in real-time for the Korean Peninsula, via an artificial neural network (ANN), using data from the GEO-KOMPSAT 2A satellite, which is equipped with an Advanced Meteorological Imager (GK2A/AMI). We also used passive microwave data, numerical weather prediction (NWP) model data, and static data. The ANN-based PET model was trained using data for the period 25 July 2019 to 24 July 2020, and was tested by comparing with in-situ PET for the period 25 July 2020 to 31 July 2021. In terms of accuracy, the PET model performed well, with root-mean-square error (RMSE), bias, and Pearson’s correlation coefficient (R) of 0.649 mm day−1, −0.134 mm day−1, and 0.954, respectively. To examine the efficiency of the GK2A/AMI-derived PET data, we compared it with in-situ ET measured at flux towers and with MODIS PET data. The accuracy of the GK2A/AMI-derived PET, in comparison with the flux tower-measured ET, showed RMSE, bias, and Pearson’s R of 1.730 mm day−1, 1.212 mm day−1, and 0.809, respectively. In comparison with the in-situ PET, the ANN model produced more accurate estimates than the MODIS data, indicating that it is more locally optimized for the Korean Peninsula than MODIS. This study advances the field by applying an ANN approach using GK2A/AMI data and could play an important role in examining hydrologic energy for air-land interactions.

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Real-time in-situ measurement of haemoglobin in wastewater

Water Science & Technology ◽

10.2166/wst.2009.572 ◽

2009 ◽

Vol 60 (7) ◽

pp. 1683-1689 ◽

Cited By ~ 1

Author(s):

L. Sutherland-Stacey ◽

R. Dexter ◽

B. McWilliams ◽

K. Watson

Keyword(s):

Water Quality ◽

Real Time ◽

Wastewater Treatment Plants ◽

Quality Parameters ◽

High Temporal Resolution ◽

Grab Sampling ◽

Time Resolved ◽

Treatment Processes ◽

Haemoglobin Measurement

The meat processing industry generates large volumes of relatively high load wastewater. In New Zealand and Australia this wastewater is often pre-treated on site and then discharged to environmental waters or municipal sewers. Owing to the limited number of water quality parameters which can be measured in real-time it is often difficult for industry to optimise treatment processes or public bodies to monitor for water-quality compliance. Abattoir wastewater is often observed to be red in colour, owing to the presence of haemoglobin. Measurement of visible light absorption spectra of wastewater grab samples has for some time provided information about blood concentration. However such grab sampling techniques are piecemeal and cannot provide instantaneous time resolved signals which are required for process control or comprehensive monitoring. In this work an in-situ UV/VIS spectrometer is used to continuously determine the concentration of haemoglobin in wastewater arriving for treatment at two different Wastewater Treatment Plants (WWTPs). The data is of high temporal resolution- data recorded at the distant WWTPs allows for identification process events, such as the end of shift wash downs.

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Near real-time water vapor tomography using ground-based GPS and meteorological data: long-term experiment in Hong Kong

Annales Geophysicae ◽

10.5194/angeo-32-911-2014 ◽

2014 ◽

Vol 32 (8) ◽

pp. 911-923 ◽

Cited By ~ 20

Author(s):

P. Jiang ◽

S. R. Ye ◽

Y. Y. Liu ◽

J. J. Zhang ◽

P. F. Xia

Keyword(s):

Hong Kong ◽

Water Vapor ◽

Real Time ◽

Time Window ◽

Meteorological Data ◽

Weather Prediction ◽

Radiosonde Data ◽

Double Difference ◽

Statistical Measures ◽

Term Experiment

Abstract. Water vapor tomography is a promising technique for reconstructing the 4-D moisture field, which is important to the weather forecasting and nowcasting as well as to the numerical weather prediction. A near real-time 4-D water vapor tomographic system is developed in this study. GPS slant water vapor (SWV) observations are derived by a sliding time window strategy using double-difference model and predicted orbits. Besides GPS SWV, surface water vapor measurements are also assimilated as real time observations into the tomographic system in order to improve the distribution of observations in the lowest layers of tomographic grid. A 1-year term experiment in Hong Kong was carried out. The feasibility of the GPS data processing strategy is demonstrated by the good agreement between the time series of GPS-derived Precipitable Water Vapor (PWV) and radio-sounding-derived PWV with a bias of 0.04 mm and a root-mean-square error (RMSE) of 1.75 mm. Using surface humidity observations in the tomographic system, the bias and RMSE between tomography and radiosonde data are decreased by half in the ground level, but such improved effects weaken gradually with the rise of altitude until becoming adverse above 4000 m. The overall bias is decreased from 0.17 to 0.13 g m−3 and RMSE is reduced from 1.43 to 1.28 g m−3. By taking the correlation coefficient and RMSE between tomography and radiosonde individual profile as the statistical measures, quality of individual profile is also improved as the success rate of tomographic solution is increased from 44.44 to 63.82% while the failure rate is reduced from 55.56 to 36.18%.

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GNSS storm nowcasting demonstrator for Bulgaria

10.5194/ems2021-349 ◽

2021 ◽

Author(s):

Guergana Guerova ◽

Jan Dousa ◽

Tsvetelina Dimitrova ◽

Pavel Václavovic

Keyword(s):

Real Time ◽

Temporal Resolution ◽

Weather Prediction ◽

Added Value ◽

High Temporal Resolution ◽

Southeast Europe ◽

Convective Storm ◽

Hail Suppression ◽

First Time

GNSS is an established atmospheric monitoring technique delivering water vapour data in near-real time with latency 90 minutes for operational Numerical Weather Prediction in Europe within the EGVAP service. However, nowadays with advancement of GNSS processing the quality of real-time GNSS tropospheric products is well comparable to near-real time solution and in addition they can be provided in a temporal resolution of 5 minutes and low latency, suitable for severe weather nowcasting. The aim of the project is to exploit the added value of GNSS tropospheric product for nowcasting of convective storm by building demonstrators in support of public weather and hail suppression services in Bulgaria. In Bulgaria &#160;thunderstorms and hail events are &#160;occur between May and September with a peak in July. The convective Storm Demonstrator (Storm Demo) is based on GNSS tropospheric products and Instability Indices to derive site specific threshold values integrated and updated in real-time on a publicly accessible geoportal. The demonstrator targets development of service centered at GNSS products for two regions with hail suppression operations namely Northwestern and Central Bulgaria.&#160; As a part of the Storm Demo real-time PPP processing will be conducted with G-Nut software for the first time in Southeast Europe for the hail suppression season May-September 2021. Evaluation of the real-time products will be performed using reprocessed GNSS tropospheric products.&#160; The added value of the high temporal resolution of the GNSS tropospheric products will be investigated for selected storm cases.&#160; This service will be unique in Europe and will serve as a prototype for real-time provision of GNSS products for storm nowcasting.&#160;

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Simulation of convective moistening of the extratropical lower stratosphere using a numerical weather prediction model

Atmospheric Chemistry and Physics ◽

10.5194/acp-20-2143-2020 ◽

2020 ◽

Vol 20 (4) ◽

pp. 2143-2159 ◽

Cited By ~ 2

Author(s):

Zhipeng Qu ◽

Yi Huang ◽

Paul A. Vaillancourt ◽

Jason N. S. Cole ◽

Jason A. Milbrandt ◽

...

Keyword(s):

High Resolution ◽

Water Vapour ◽

Lower Stratosphere ◽

Grid Spacing ◽

Water Vapour Content ◽

In Situ Observations ◽

Horizontal Grid ◽

Stratospheric Water Vapour ◽

Resolution Simulation

Abstract. Stratospheric water vapour (SWV) is a climatically important atmospheric constituent due to its impacts on the radiation budget and atmospheric chemical composition. Despite the important role of SWV in the climate system, the processes controlling the distribution and variation in water vapour in the upper troposphere and lower stratosphere (UTLS) are not well understood. In order to better understand the mechanism of transport of water vapour through the tropopause, this study uses the high-resolution Global Environmental Multiscale model of the Environment and Climate Change Canada to simulate a lower stratosphere moistening event over North America. Satellite remote sensing and aircraft in situ observations are used to evaluate the quality of model simulation. The main focus of this study is to evaluate the processes that influence the lower stratosphere water vapour budget, particularly the direct water vapour transport and the moistening due to the ice sublimation. In the high-resolution simulations with horizontal grid spacing of less than 2.5 km, it is found that the main contribution to lower stratospheric moistening is the upward transport caused by the breaking of gravity waves. In contrast, for the lower-resolution simulation with horizontal grid spacing of 10 km, the lower stratospheric moistening is dominated by the sublimation of ice. In comparison with the aircraft in situ observations, the high-resolution simulations predict the water vapour content in the UTLS well, while the lower-resolution simulation overestimates the water vapour content. This overestimation is associated with the overly abundant ice in the UTLS along with a sublimation rate that is too high in the lower stratosphere. The results of this study affirm the strong influence of overshooting convection on the lower stratospheric water vapour and highlight the importance of both dynamics and microphysics in simulating the water vapour distribution in the UTLS region.

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Real Time Rainfall Monitoring for Pipeline Geohazards

ASME-ARPEL 2021 International Pipeline Geotechnical Conference ◽

10.1115/ipg2021-63162 ◽

2021 ◽

Author(s):

Gerry Ferris ◽

Patrick Grover ◽

Aron Zahradka

Keyword(s):

Real Time ◽

Large Scale ◽

Oil And Gas ◽

Weather Prediction ◽

Extreme Rainfall ◽

Rainfall Data ◽

Annual Rainfall ◽

Extreme Rainfall Event ◽

Pipeline Failures

Abstract Oil and gas pipelines are subjected to multiple types of geohazards which cause pipeline failures (loss of containment); two of the most common types occur at watercourse crossings and at landslides. At watercourse crossings, the most common geohazard which causes pipeline failures is flooding during which excessive scour may result in the exposure of the buried pipeline and if the exposure results in a free spanning pipeline, then this may fail due to fatigue caused by cyclic loading from vortex-induced vibration. Fortunately the free span length and water velocity combinations that lead to failure can be defined and can be used to identify the flood discharge that should be monitored for in order to trigger actions to manage the hazard and avoid failure. Most watercourse crossings in a pipeline network are on ungauged watercourses and necessitate the use of a proxy gauged watercourse. The “proxy” gauged watercourse is used to infer whether flooding is occurring on the ungauged crossing, and the owner can take appropriate actions. Often the proxy gauged watercourse is too far away or the watercourse may not be representative of the crossing of concern (e.g. large difference in the drainage areas). Real-time rainfall data can be used in conjunction with streamflow monitoring to determine when extreme precipitation has occurred within the ungauged watercourses catchment which may result in flooding. Where pipelines cross landslide prone areas, large scale movements can be initiated, or slow on-going movement rates increased when extreme rainfall occurs. The definition of the extreme rainfall event for slope sites is the key component of providing a suitable warning of potentially dangerous conditions; shallow slides can be caused by short term events from sub-hourly to 3 day duration precipitation events whereas large deep seated (creeping) landslides can be driven by annual and intra-annual rainfall amounts. Monitoring of real time rainfall can be used to determine when extreme rainfall occurs at a landslide site. The density of in-situ weather stations collecting real-time rainfall data prevents the application along remote sections of pipeline routes and within large sections of Canada. Gridded real time rainfall from quantitative precipitation estimations which integrate a multiple data sources including in-situ, numerical weather prediction, satellite and weather radar, can be used to overcome this problem and provide warnings when pre-determined rainfall thresholds are exceeded on a site-specific basis.

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