Copernicus satellites for supporting irrigation and water management in Australia: the COALA H2020 Project.

COALA is a project funded by the Horizon 2020 program of the European Union with the aim of developing Copernicus Earth Observation-based information services for irrigation and nutrient management in Australia, building on consolidated experience of past EU projects and existing operational irrigation advisory services. Earth Observation-based services can provide &#8220;diagnostic&#8221; data and information relevant for integrated input management of irrigation water and nutrients, from subplot level to irrigation scheme or river basin levels.COALA, started on January 2020, is developing Copernicus-based information service for the Australian agricultural systems, based on strong collaboration with Academic Australian institutions and business players. COALA services will provide to farmers, irrigation organisation and basin authorities information about crops development, water and nutrient status, irrigated areas by means of innovative algorithms based on Sentinel Earth Observation data, which will be accessed by means of the new cloud platforms (DIAS) of Copernicus. In-situ and other source of data, such as ground soil moisture probes, meteorological stations and Numerical Weather Prediction models, will be used to improve the information provided to the final users.The advancements beyond the state of art of COALA methodologies for managing irrigation are:COALA will demonstrate that Copernicus data and new DIAS infrastructure can greatly improve the availability of a multi-scale information product shared by the different levels of users. The innovative approach achieves a "converging loop procedure" between water authority, irrigation infrastructure operation and farmers, enabling transparency in all the decision taken at all levels and improving the accuracy of estimation of actual water use.https://www.coalaproject.eu/

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On the barriers limiting the adoption of the Earth Observation Copernicus data and services and their integration with non-conventional (e.g. citizen) observations: the EU CoRdiNet project contribution.

10.5194/egusphere-egu2020-18649 ◽

2020 ◽

Author(s):

Teodosio Lacava ◽

Lucio Bernardini Papalia ◽

Iole Federica Paradiso ◽

Monica Proto ◽

Nicola Pergola

Keyword(s):

Regional Scale ◽

Earth Observation ◽

Small Enterprises ◽

Observation Data ◽

The European Union ◽

Horizon 2020 ◽

New Business ◽

Earth Observation Data ◽

Regional Authorities

The Copernicus User Uptake Initiative is part of the European Union&#8217;s strategy for increasing the level of awareness of the Copernicus Program at European and worldwide level, fostering the adoption of Copernicus-based data/solution in the everyday life of each kind of potential stakeholder, from Local Regional Authorities (LRA) to Big and/or Small Enterprises to normal citizens. The CoRdiNet (Copernicus Relays for digitalization spanning a Network) projects was funded in the frame of Horizon 2020 Space Hubs call (grant agreement n. 821911), to implement and reinforce the user uptake actions among the network of the so called Copernicus Relays. The latter, as part of the Space strategy for Europe of the European Commission, act as Copernicus Ambassadors, providing their contribution for a better dissemination and promotion of Copernicus-based solution at local/regional scale. Among the goals of the Cordinet project there are: i) Supporting, promoting and stimulating digitalization and new business solutions based on Earth observation data from the Copernicus project; ii) bundling the local expertise in the civil use of Earth observation close to the needs and offers of citizens, administration and businesses.Earth Observation data from space, in fact, can provide products and services to citizens and can be profitably integrated with non-conventional data, e.g the ones coming from citizen observatories and sciences. However, presently Copernicus data and information are still under-exploited and further efforts are needed to engage stakeholders (including normal citizens), investigating the causes that have prevented from a more systematic and diffuse use of Copernicus/EO data so far. In fact, an increased awareness about the Copernicus program, its data, products and services, will allow for a better integration of non-conventional (e.g. citizen-based) observations, enabling new services and solutions, more close to the citizen needs and requirements for a better quality of life.With this aim, one of the tasks of the project was specifically devoted to the identification and engagement of the stakeholders within the CoRdiNet partner geographic regions, including also the external ones involved by a specific call for expression of interest, and it was carried out by TeRN in collaboration with CNR-IMAA. In particular, after their engagement, stakeholders were asked to answer to a questionnaire aimed at analyzing their needs and capabilities and evaluating which barriers have prevented for a more systematic use of Copernicus solutions so far in their own activities. Results achieved analyzing collected feedback will be presented and discussed in this work, providing also a few preliminary recommendations about how to cope with the identified gaps.

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Copernicus: the European Earth Observation programme

Revista de Teledetección ◽

10.4995/raet.2020.14346 ◽

2020 ◽

Author(s):

S. Jutz ◽

M.P. Milagro-Pérez

Keyword(s):

Numerical Models ◽

Earth Observation ◽

Environmental Data ◽

Observation Data ◽

The European Union ◽

Global Environmental ◽

In Situ Sensors ◽

Earth Observation Data ◽

Observation Programme

The European Union-led Copernicus programme, born with the aim of developing space-based global environmental monitoring services to ensure a European autonomous capacity for Earth Observation, comprises a Space Component, Core Services, and In-situ measurements. The Space Component, coordinated by ESA, has seven Sentinel satellites in orbit, with further missions planned, and is complemented by contributing missions, in-situ sensors and numerical models, and delivers many terabytes of accurate climate and environmental data, free and open, every day to hundreds of thousands of users. This makes Copernicus the biggest provider of Earth Observation data in the world.

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Towards operational postprocessing of cloud cover at MeteoSwiss

10.5194/egusphere-egu2020-17886 ◽

2020 ◽

Author(s):

Stephan Hemri ◽

Christoph Spirig ◽

Jonas Bhend ◽

Lionel Moret ◽

Mark Liniger

Keyword(s):

Cloud Cover ◽

Prediction Models ◽

Weather Prediction ◽

Weather Forecast ◽

Forecast Errors ◽

Observation Data ◽

Model Output ◽

Ensemble Forecasts ◽

Direct Model ◽

Ensemble Model Output Statistics

Over the last decades ensemble approaches have become state-of-the-art for the quantification of weather forecast uncertainty. Despite ongoing improvements, ensemble forecasts issued by numerical weather prediction models (NWPs) still tend to be biased and underdispersed. Statistical postprocessing has proven to be an appropriate tool to correct biases and underdispersion, and hence to improve forecast skill. Here we focus on multi-model postprocessing of cloud cover forecasts in Switzerland. In order to issue postprocessed forecasts at any point in space, ensemble model output statistics (EMOS) models are trained and verified against EUMETSAT CM SAF satellite data with a spatial resolution of around 2 km over Switzerland. Training with a minimal record length of the past 45 days of forecast and observation data already produced an EMOS model improving direct model output (DMO). Training on a 3 years record of the corresponding season further improved the performance. We evaluate how well postprocessing corrects the most severe forecast errors, like missing fog and low level stratus in winter. For such conditions, postprocessing of cloud cover benefits strongly from incorporating additional predictors into the postprocessing suite. A quasi-operational prototype has been set up and was used to explore meteogram-like visualizations of probabilistic cloud cover forecasts.

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Cyprus enters the space arena with "Excelsior " H2020 Teaming project and the Eratosthenes Centre of Excellence: Why Cyprus? Why Excelsior? What are the needs and opportunities?

10.5194/egusphere-egu2020-21801 ◽

2020 ◽

Author(s):

Kyriakos Themistocleous ◽

Diofantos Hadjimitsis ◽

Gunter Schreier ◽

Haris Kontoes ◽

Albert Ansmann ◽

...

Keyword(s):

Climate Change ◽

Eastern Mediterranean ◽

Middle Eastern ◽

Climatic Conditions ◽

Earth Observation ◽

The European Union ◽

African Countries ◽

Horizon 2020 ◽

Centre Of Excellence ◽

The Government

Cyprus enters the space arena with the &#8216;EXCELSIOR&#8217; project. &#8216;EXCELSIOR&#8217; is expected to bring change in many aspects, including new opportunities for researchers, enhanced skills development for future experts in the Earth Observation and Geoinformation sector on a local, national, European and global level. Due to its geographical proximity, &#8216;EXCELSIOR&#8217; can become a hub for partners in Middle Eastern and Northern African countries. Cyprus&#8217;s unique geostrategic position can support Earth Observation from satellites programmes in three continents and provide valuable services in the processes of satellite calibration and validation. The ERATOSTHENES Centre of Excellence (ECoE), with its expertise and infrastructure, could further complement the existing network of international ground stations. Cyprus is ideally located to host the ECoE, due to its climate, which is characterized by 300 days of sunshine a year, providing excellent weather conditions for cloud free satellite images.There are some distinct needs and opportunities that motivate the establishment of an Earth Observation Centre of Excellence in Cyprus. The needs include: i) to establish a Supersite for aerosol and cloud monitoring in the Eastern Mediterranean, Middle East and North Africa (EMMENA): strong demand for EO monitoring to provide data to evaluate the extent of pollution and climate change, especially in the EMMENA region; ii) to observe droughts and water shortages in the EMMENA region; iii) to adopt Rehabilitation programmes in EMMENA; iv) to reduce Disaster Risk and v) to create a Regional Digital Innovation Hub for Earth Observation in Cyprus. The foreseen opportunities include: i) the ECoE has the potential to become a catalyst for facilitating and enabling Regional, European and International cooperation; ii) the Eco E can capitalise on the favourable environmental, weather and climatic conditions of Cyprus to conduct cutting-edge research with impact in various sectors, including climate change, marine, solar energy, etc.; iii) the development of the Cyprus Space Strategy, which can be exploited for further Earth observation research and applications; iv) create a unique European capacity in Cyprus by mobilizing internal national assets and consolidating European EO capabilities in Cyprus to serve EMMENA. The ECoE will procure and develop the European Satellite Ground Stations covering the EMMENA region; v) accessing funding instruments for Earth Observation at the national and European Level and vi) the development of Big Data management and analytics. &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;The EXCELSIOR project has received funding from the European Union&#8217;s Horizon 2020 research and innovation programme under Grant Agreement No 857510 and from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development.

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Performance Characteristics of a Pseudo-Operational Ensemble Kalman Filter

Monthly Weather Review ◽

10.1175/2008mwr2443.1 ◽

2008 ◽

Vol 136 (10) ◽

pp. 3947-3963 ◽

Cited By ~ 65

Author(s):

Ryan D. Torn ◽

Gregory J. Hakim

Keyword(s):

Kalman Filter ◽

Ensemble Kalman Filter ◽

Prediction Models ◽

North Pacific Ocean ◽

Weather Prediction ◽

Limited Area ◽

Observation Data ◽

Error Statistics ◽

Ensemble Forecasts ◽

Ensemble Mean

The 2-yr performance of a pseudo-operational (real time) limited-area ensemble Kalman filter (EnKF) based on the Weather Research and Forecasting Model is described. This system assimilates conventional observations from surface stations, rawinsondes, the Aircraft Communications Addressing and Reporting System (ACARS), and cloud motion vectors every 6 h on a domain that includes the eastern North Pacific Ocean and western North America. Ensemble forecasts from this system and deterministic output from operational numerical weather prediction models during this same period are verified against rawinsonde and surface observation data. Relative to operational forecasts, the forecast from the ensemble-mean analysis has slightly larger errors in wind and temperature but smaller errors in moisture, even though satellite radiances are not assimilated by the EnKF. Time-averaged correlations indicate that assimilating ACARS and cloud wind data with flow-dependent error statistics provides corrections to the moisture field in the absence of direct observations of that field. Comparison with a control experiment in which a deterministic forecast is cycled without observation assimilation indicates that the skill in the EnKF’s forecasts results from assimilating observations and not from lateral boundary conditions or the model formulation. Furthermore, the ensemble variance is generally in good agreement with the ensemble-mean error and the spread increases monotonically with forecast hour.

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The "Excelsior" H2020 Widespread Teaming Phase 2 Project: ERATOSTHENES: EXcellence Research Centre for Earth SurveiLlance and Space-Based MonItoring Of the EnviRonment

10.5194/egusphere-egu2020-21836 ◽

2020 ◽

Author(s):

Diofantos Hadjimitsis ◽

Gunter Schreier ◽

Haris Kontoes ◽

Albert Ansman ◽

Giorgos Komodromos ◽

...

Keyword(s):

Water Resource Management ◽

Eastern Mediterranean ◽

Earth Observation ◽

Research Centre ◽

Observation Data ◽

The European Union ◽

Electronic Communications ◽

Research And Innovation ◽

University Of Technology ◽

The Government

The EXCELSIOR project aims to upgrade the existing ERATOSTHENES Research Centre established within the Cyprus University of Technology into a sustainable, viable and autonomous ERATOSTHENES Centre of Excellence (ECoE) for Earth Surveillance and Space-Based Monitoring of the Environment. The ECoE for Earth Surveillance and Space-Based Monitoring of the Environment will provide the highest quality of related services both on the National, European and International levels through the &#8216;EXCELSIOR&#8217; Project under H2020 WIDESPREAD TEAMING. The vision of the ECoE is to become a world-class Digital Innovation Hub (DIH) for Earth observation and Geospatial Information becoming the reference Centre in the Eastern Mediterranean, Middle East and North Africa (EMMENA) within the next 7 years. The ECoE will lead multidisciplinary Earth observation research towards a better understanding, monitoring and sustainable exploitation and protection of the physical, built and human environment, in line with International policy frameworks. Indeed, the scientific potential of the new upgraded ECoE focusing on the integration of novel Earth observation, space and ground based integrated technologies for the efficient systematic monitoring of the environment. Furthermore, ECoE aims to excel in five domains: &#160;i) Access to energy; ii) Disaster Risk Reduction; iii) Water Resource Management; iv) Climate Change Monitoring and v) Big Earth observation Data Analytics. This will be achieved through research and innovation excellence in the respective scientific and technological disciplines and working together with other Earth observation industries, whereby the ECoE will develop a pool of scientific expertise and engineering capability as well as technical facilities. The partners of the EXCELSIOR consortium include the Cyprus University of Technology as the Coordinator, the German Airspace Center (DLR), the Leibniz Institute for Tropospheric Research (TROPOS), the National Observatory of Athens (NOA) and the Department of Electronic Communications, of the Ministry of Transport, Communications and Works of Cyprus.&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;The EXCELSIOR project has received funding from the European Union&#8217;s Horizon 2020 research and innovation programme under Grant Agreement No 857510 and from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development.

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Modelling windfarm wakes in operational forecasting model HARMONIE-AROME

10.5194/egusphere-egu21-7692 ◽

2021 ◽

Author(s):

Natalie Theeuwes ◽

Bart van Stratum ◽

Bert van Ulft ◽

Jan Barkmeijer ◽

Sukanta Basu ◽

...

Keyword(s):

Wind Farm ◽

Prediction Models ◽

Mesoscale Model ◽

Weather Prediction ◽

Wind Farms ◽

Power Production ◽

The European Union ◽

The North ◽

Temperature And Humidity ◽

Monthly Weather Review

Wind power production in the European Union (EU) is steadily increasing, specifically on the North-Sea. Wind farms are growing both in number and size, while weather models evolve to higher resolutions. This means that the effect of wind farms can no longer be ignored by weather prediction models. Wind farms essentially decelerate the wind (blockage and wake effects) and increase turbulence, indirectly influencing temperature and humidity. In this study, we have included the widely used Fitch et al. (2012) windfarm parameterisation in the operational mesoscale model HARMONIE-AROME. Using our method, we are able to include individual turbines both on- and offshore.&#160;The model is evaluated using various datasets, e.g. production data from Elia (Belgium), floating lidar measurements at Borssele Wind Farm, and anemometer measurements from the FINO-towers. The inclusion of the windfarm parameterisation improves the wind forecast near wind farms, also improving the estimate in power production. In addition, we are able to model the effects of wind farms on the boundary-layer temperature and humidity.Fitch, A. C., Olson, J. B., Lundquist, J. K., Dudhia, J., Gupta, A. K., Michalakes, J., & Barstad, I. (2012). Local and mesoscale impacts of wind farms as parameterized in a mesoscale NWP model. Monthly Weather Review, 140(9), 3017&#8211;3038.

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Comparisons of Satellite-Derived Atmospheric Motion Vectors, Rawinsondes, and NOAA Wind Profiler Observations

Journal of Applied Meteorology and Climatology ◽

10.1175/2009jamc1867.1 ◽

2009 ◽

Vol 48 (8) ◽

pp. 1542-1561 ◽

Cited By ~ 31

Author(s):

Kristopher M. Bedka ◽

Christopher S. Velden ◽

Ralph A. Petersen ◽

Wayne F. Feltz ◽

John R. Mecikalski

Keyword(s):

Boundary Layer ◽

Prediction Models ◽

Weather Prediction ◽

Information Service ◽

Wind Profiler ◽

Motion Vectors ◽

Processing Methods ◽

Atmospheric Motion ◽

The Individual ◽

Atmospheric Motion Vectors

Abstract Geostationary satellite-derived atmospheric motion vectors (AMVs) have been used over several decades in a wide variety of meteorological applications. The ever-increasing horizontal and vertical resolution of numerical weather prediction models puts a greater demand on satellite-derived wind products to monitor flow accurately at smaller scales and higher temporal resolution. The focus of this paper is to evaluate the accuracy and potential applications of a newly developed experimental mesoscale AMV product derived from Geostationary Operational Environmental Satellite (GOES) imagery. The mesoscale AMV product is derived through a variant on processing methods used within the University of Wisconsin—Madison Cooperative Institute for Meteorological Satellite Studies (UW-CIMSS) AMV algorithm and features a significant increase in vector density throughout the troposphere and lower stratosphere over current NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) processing methods for GOES-12 Imager data. The primary objectives of this paper are to 1) highlight applications of experimental GOES mesoscale AMVs toward weather diagnosis and forecasting, 2) compare the coverage and accuracy of mesoscale AMVs with the NOAA/NESDIS operational AMV product, and 3) demonstrate the utility of 6-min NOAA Wind Profiler Network observations for satellite-derived AMV validation. Although the more conservative NOAA/NESDIS AMV product exhibits closer statistical agreement to rawinsonde and wind profiler observations than do the experimental mesoscale AMVs, a comparison of these two products for selected events shows that the mesoscale product better depicts the circulation center of a midlatitude cyclone, boundary layer confluence patterns, and a narrow low-level jet that is well correlated with subsequent severe thunderstorm development. Thus, while the individual experimental mesoscale AMVs may sacrifice some absolute accuracy, they show promise in providing greater temporal and spatial flow detail that can benefit diagnosis of upper-air flow patterns in near–real time. The results also show good agreement between 6-min wind profiler and rawinsonde observations within the 700–200-hPa layer, with larger differences in the stratosphere, near the mean top of the planetary boundary layer, and just above the earth’s surface. Despite these larger differences within select layers, the stability of the difference profile with height builds confidence in the use of 6-min, ∼404-MHz NOAA Wind Profiler Network observations to evaluate and better understand satellite AMV error characteristics.

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A Synergistic Use of a High-Resolution Numerical Weather Prediction Model and High-Resolution Earth Observation Products to Improve Precipitation Forecast

Remote Sensing ◽

10.3390/rs11202387 ◽

2019 ◽

Vol 11 (20) ◽

pp. 2387 ◽

Cited By ~ 8

Author(s):

Martina Lagasio ◽

Antonio Parodi ◽

Luca Pulvirenti ◽

Agostino Meroni ◽

Giorgio Boni ◽

...

Keyword(s):

High Resolution ◽

Numerical Weather Prediction ◽

Weather Prediction ◽

Earth Observation ◽

Precipitation Forecast ◽

Observation Data ◽

Rainfall Events ◽

Numerical Weather ◽

Wide Range ◽

Gnss Observations

The Mediterranean region is frequently struck by severe rainfall events causing numerous casualties and several million euros of damages every year. Thus, improving the forecast accuracy is a fundamental goal to limit social and economic damages. Numerical Weather Prediction (NWP) models are currently able to produce forecasts at the km scale grid spacing but unreliable surface information and a poor knowledge of the initial state of the atmosphere may produce inaccurate simulations of weather phenomena. The STEAM (SaTellite Earth observation for Atmospheric Modelling) project aims to investigate whether Sentinel satellites constellation weather observation data, in combination with Global Navigation Satellite System (GNSS) observations, can be used to better understand and predict with a higher spatio-temporal resolution the atmospheric phenomena resulting in severe weather events. Two heavy rainfall events that occurred in Italy in the autumn of 2017 are studied—a localized and short-lived event and a long-lived one. By assimilating a wide range of Sentinel and GNSS observations in a state-of-the-art NWP model, it is found that the forecasts benefit the most when the model is provided with information on the wind field and/or the water vapor content.

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From crowdsourcing environmental measurements to their integration in the GEOSS portal

10.5194/egusphere-egu2020-21328 ◽

2020 ◽

Author(s):

Valantis Tsiakos ◽

Maria Krommyda ◽

Athanasia Tsertou ◽

Angelos Amditis

Keyword(s):

Environmental Monitoring ◽

Citizen Science ◽

Low Cost ◽

Earth Observation ◽

Observation System ◽

Observation Data ◽

The European Union ◽

Science Data ◽

Portable Sensors ◽

Areas Of Interest

Environmental monitoring is based on time-series of data collected over long periods of time from expensive and hard to maintain in-situ sensors available only in specific areas. Due to the climate change it is important to monitor extended areas of interest. This need has raised the question of whether such monitoring can be complemented or replaced by Citizen Science.Crowdsourced measurements from low-cost and easy to use portable sensors and devices can facilitate the collection of the needed information with the support of volunteers, enabling the monitoring of environmental ecosystems and extended areas of interest. In particular, during the last years there has been a rapid increase of citizen-generated knowledge that has been facilitated by the wider use of mobile devices and low-cost portable sensors. To enable their easy integration to existing models and systems as well as their utilisation in the context of new applications, citizen science data should be easily discoverable, re-usable, accessible and available for future use.The Global Earth Observation System of Systems (GEOSS) offers a single access point to Earth Observation data (GEOSS Portal), connecting users to various environmental monitoring systems around the world while promoting the use of common technical standards to support their utilisation.&#160;Such a connection was demonstrated in the context of SCENT project. SCENT is a EU project which has implemented an integrated toolbox of smart collaborative and innovating technologies that allows volunteers to collect environmental measurements as part of their everyday activities.These measurements may include images that include information about the land cover and land use of the area, air temperature and soil moisture measurements from low-cost portable environmental sensors or river measurements, water level and water velocity extracted from multimedia, images and video, through dedicated tools.The collected measurements are provided to policy makers and scientists to facilitate the decision making regarding needed actions and infrastructure improvements as well as the monitoring of environmental phenomena like floods through the crowdsourced information.In order to ensure that the provided measurements are of high quality, a dedicated control mechanism has been implemented that uses a custom mechanism, based on spatial and temporal clustering, to identify biased or low quality contributions and remove them from the system.Finally, recognising the importance of making the collected data available all the validated measurements are modelled, stored and provisioned using the Open Geospatial Consortium (OGC) standards Web Feature Service (WFS) and Web Map Service (WMS) as applicable.This allows the spatial and temporal discovery of information among the collected measurements, encourages their re-usability and allows their integration to systems and platforms utilizing the same standards. The data collected by the SCENT Campaigns organized at the Kifisos river basin and the Danube Delta can be found at the GEOSS portal under the WFS here https://www.geoportal.org/?f:sources=wfsscentID and under the WMS here https://www.geoportal.org/?f:sources=wmsSCENTID. &#160;This activity is showcased as part of WeObserve project that has received funding from the European Union&#8217; s Horizon 2020 research and innovation programme under grant agreement No 776740.

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