A historical weather forecast dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF) for energy forecasting

Solar Energy ◽  
2022 ◽  
Vol 232 ◽  
pp. 263-274
Author(s):  
Dazhi Yang ◽  
Wenting Wang ◽  
Tao Hong
Keyword(s):  
Weather Forecast ◽  
Energy Forecasting ◽  
Weather Forecasts ◽  
European Centre ◽  
Medium Range

One million feet view of Level-2 Processing Facility managed at European Centre for Medium-Range Weather Forecasts (ECMWF)

2020 ◽  
Author(s):  
Rakesh Prithiviraj
Keyword(s):  
Wind Profile ◽  
European Space Agency ◽  
Weather Forecast ◽  
System Perspective ◽  
Weather Forecasts ◽  
European Centre ◽  
Ground Segment ◽  
Processing Facility ◽  
Medium Range ◽  
Level 2

<p><strong>Title:</strong> One million feet view of Level-2 Processing Facility managed at European Centre for Medium-Range Weather Forecasts (ECMWF)</p><p><strong>Authors:</strong> Rakesh Prithiviraj, Ioannis Mallas, Cristiano Zanna </p><p><strong>Affiliation of authors:</strong> European Centre for Medium-Range Weather Forecasts (ECMWF)</p><p><strong>Abstract text</strong><br>Launched in August 2018, European Space Agency’s Aeolus satellite mission measures Earth's wind profile from space. The Aeolus ground segment mainly comprises of:<br>• Flight Operations Segment (FOS) to monitor and control Aeolus satellite and the instrument onboard, <br>• Payload Data Ground Segment (PDGS) for the acquisition and systematic generation of Level-1A and Level-1B products and <br>• Level-2 Processing Facility (L2PF) at ECMWF for the generation and dissemination of Level-2B and Level-2C products. </p><p>ECMWF is both a research institute and a 24/7 operational service, producing global numerical weather predictions and other data for our Member and Co-operating States and the broader community. ECMWF relies on its atmospheric model and data assimilation system which is called the Integrated Forecasting System (IFS) to make weather predictions. ECMWF has one of the largest supercomputer facilities and meteorological data archives in the world.</p><p>This talk focusses on the Aeolus L2PF facility at ECMWF providing an overview of the processing infrastructure, relevant dataflows, monitoring system and presents the technical/system perspective of Aeolus L2PF in the context of weather forecast. The L2PF facility receives L1B data from Aeolus PDGS and systematically generates and disseminates L2B products and L2C products. The centre is also responsible for the generation of meteorological auxiliary data which is one of the critical inputs for the L2B generation.  The talk also shows various components at ECMWF that work together to achieve more than 99% L2B completeness. The components include ECMWF Production Data Store (ECPDS), ECMWF's High Performance Computing Facility (HPCF) and L2PF cluster. </p><p>The talk concludes with references to tests carried out at ECMWF that have demonstrated that new wind profile observations from Aeolus satellite significantly improve weather forecasts, particularly in the southern hemisphere and the tropics. Because the positive impact of Aeolus on the weather predictions, Aeolus data is expected to be part of the operational weather forecast system at ECMWF in January 2020.</p>

Hochaufgelöste Simulation von meteorologischen Feldern in urbanen Räumen mit dem Weather Research and Forecasting (WRF) Modell

2021 ◽  
Author(s):  
Lukas N. Pilz ◽  
Sanam N. Vardag ◽  
Joachim Fallmann ◽  
André Butz
Keyword(s):  
Greenhouse Gas ◽  
Monitoring System ◽  
Weather Research And Forecasting ◽  
Gas Monitoring ◽  
Weather Forecasts ◽  
European Centre ◽  
Medium Range ◽  
Erste Ergebnisse ◽  
Weather Research

<p><span>Städte und Kommunen sind für mehr als 70% </span><span>der globalen, fossilen CO2-Emissionen</span><span> verantwortlich, sodass hier ein enormes Mitigationspotential besteht. Informationen über (inner-)städtische CO2-Emissionen stehen allerdings oft nicht </span><span>in hoher zeitlicher und räumlicher Auflösung</span><span> zur Verfügung und sind </span><span>meist</span><span> mit großen Unsicherheiten behaftet. Diese Umstände erschweren eine zielgerichtete und effiziente Mitigation im urbanen Raum. </span><span>Städtische Messnetzwerke können als unabhängige Informationsquelle einen Beitrag leisten, um CO2-Emissionen in Städten zu quantifizieren und Mitigation zu verifizieren</span><span>. </span><span>Verschiedene denkbare Beobachtungsstrategien sollten</span><span> im Vorfeld abgewägt werden, um urbane Emissionen bestmöglich, d.h. mit der erforderlichen Genauigkeit und </span><span>Kosteneffizienz</span><span> zu quantifizieren. So können Messnetzwerke die Basis für zielgerichtete und kosteneffiziente Mitigation legen.</span></p><p><span>Im Rahmen des Verbundvorhabens „Integrated Greenhouse Gas Monitoring System for Germany“ (ITMS) werden wir verschiedene Beobachtungsstrategien für urbane Räume entwerfen und mit Hilfe von Modellsimulation evaluieren und abwägen. Notwendige Voraussetzung für </span><span>die Evaluation der Strategien</span><span> ist eine akkurate Repräsentation des atmosphärischen Transports im Modell.</span></p><p><span>Diese Studie zeigt</span><span> erste Ergebnisse der hochauflösenden (1kmx1km) meteorologischen Simulationen für den Rhein-Neckar-Raum mit dem WRF Modell. </span><span>Die in WRF simulierten meteorologischen Größen werden für verschiedene Modellkonfigurationen mit </span><span>re-analysierten Daten des European Centre for Medium-Range Weather Forecasts (ECMWF) und ausgewählten Messstationen verglichen. Damit evaluieren wir </span><span>den Einfluss unterschiedlicher Nudging-Strategien, Parametrisierungen physikalischer Prozesse und urbaner Interaktionen</span><span> auf </span><span>die Modellperformance</span> <span>von</span><span> Lufttemperatur, Windrichtung, Windgeschwindigkeit und Grenzschichthöhe. Durch diese Analysen gewährleisten wir, dass die Simulation der Beobachtungsstrategien auf robuste</span><span>m</span><span> und realistische</span><span>m</span><span> atmosphärischen Transport basieren und schlussendlich repräsentative Empfehlungen für den Aufbau von Messnetzwerken liefern können. </span></p>

Evaluierung des nichthydrostatischen mesoskaligen Modells GRAMM-SCI anhand der Richtlinie VDI 3783 Blatt 7/Evaluation of the nonhydrostatic mesoscale model GRAMM-SCI based on the guideline VDI 3783 Part 7

Gefahrstoffe ◽  
2020 ◽  
Vol 80 (07-08) ◽  
pp. 318-324
Author(s):  
D. Öttl
Keyword(s):  
Mesoscale Model ◽  
Weather Forecasts ◽  
European Centre ◽  
Medium Range

Aufgrund der komplexen Orografie in den Alpen sind einfache, auf diagnostischen Ansätzen beruhende Windfeldmodelle in Österreich kaum anwendbar. Daher wird in den meisten österreichischen Bundesländern das mesoskalige Modell GRAMM im Rahmen von Luftschadstoffuntersuchungen eingesetzt. In diesem Beitrag werden Ergebnisse der Modellevaluierung anhand jener drei Datensätze der Richtlinie VDI 3783 Blatt 7 präsentiert, die auf teils umfangreichen Messkampagnen basieren. Das Modell GRAMM wurde mittlerweile erweitert (Version GRAMM-SCI) und kann nun auch mit den Reanalysedaten ERA5 des Europäischen Wetterdienstes (European Centre for Medium-Range Weather Forecasts, ECMWF) angetrieben werden. Um die Qualität der ERA5-Daten zu prüfen, wurden zusätzliche Simulationen für die drei Evaluierungsdatensätze aus VDI 3783 Blatt 7 durchgeführt. Es zeigt sich, dass Modellsimulationen mit GRAMM-SCI, die auf ERA5-Daten basieren, die Strömungs- und Temperaturverhältnisse grundsätzlich gut wiedergeben. Allerdings sind die Abweichungen zu den Messungen der Sondermesskampagnen teilweise etwas zu groß, um die hohen Anforderungen von VDI 3783 Blatt 7 an die Modellergebnisse vollständig zu erfüllen.

scholarly journals CARACTERIZAÇÃO ATMOSFÉRICA QUANDO DA OCORRÊNCIA DE EVENTOS EXTREMOS DE CHUVA NA REGIÃO SUL DE MINAS GERAIS

2017 ◽  
Vol 21 ◽  
Author(s):  
Michelle Simões Reboita ◽  
Diogo Malagutti Gonçalves Marietto ◽  
Amanda Souza ◽  
Marina Barbosa
Keyword(s):  
Climate Prediction ◽  
Minas Gerais ◽  
Weather Forecasts ◽  
European Centre ◽  
Medium Range ◽  
Climate Prediction Center

O objetivo deste estudo é apresentar uma descrição das características da atmosfera que contribuíram para elevados totais de precipitação no sul de Minas Gerais e que foram precursores de dois episódios de inundação e alagamento na cidade de Itajubá: um em 16 de janeiro de 1991 e outro em 02 de janeiro de 2000. Para tanto, foram utilizados dados do Climate Prediction Center e da reanálise ERA-Interim do European Centre for Medium-Range Weather Forecasts (ECMWF). Entre os resultados, têm-se que os episódios de inundação e alagamento ocorridos na cidade de Itajubá, em ambos os anos, estiveram associados à atuação da Zona de Convergência do Atlântico Sul, que se estendia da Amazônia, passando pelo sudeste do Brasil, e chegava ao Atlântico Sul.

scholarly journals An “island” in the stratosphere – on the enhanced annual variation of water vapour in the middle and upper stratosphere in the southern tropics and subtropics

2017 ◽  
Vol 17 (18) ◽  
pp. 11521-11539 ◽  
Author(s):  
Stefan Lossow ◽  
Hella Garny ◽  
Patrick Jöckel
Keyword(s):  
Water Vapour ◽  
Atmospheric Chemistry ◽  
Annual Variation ◽  
Trace Gases ◽  
Michelson Interferometer ◽  
Full Account ◽  
Weather Forecasts ◽  
European Centre ◽  
Atmospheric Sounding ◽  
Medium Range

Abstract. The amplitude of the annual variation in water vapour exhibits a distinct isolated maximum in the middle and upper stratosphere in the southern tropics and subtropics, peaking typically around 15° S in latitude and close to 3 hPa (∼  40.5 km) in altitude. This enhanced annual variation is primarily related to the Brewer–Dobson circulation and hence also visible in other trace gases. So far this feature has not gained much attention in the literature and the present work aims to add more prominence. Using Envisat/MIPAS (Environmental Satellite/Michelson Interferometer for Passive Atmospheric Sounding) observations and ECHAM/MESSy (European Centre for Medium-Range Weather Forecasts Hamburg/Modular Earth Submodel System) Atmospheric Chemistry (EMAC) simulations we provide a dedicated illustration and a full account of the reasons for this enhanced annual variation.

scholarly journals Scientific motivation for ADM/Aeolus mission

2018 ◽  
Vol 176 ◽  
pp. 02008
Author(s):  
Erland Källén
Keyword(s):  
Weather Forecast ◽  
Weather Forecasts ◽  
Weather And Climate ◽  
Medium Range ◽  
Forecast Models ◽  
Tropical Areas ◽  
Global Coverage ◽  
Wind Lidar ◽  
Wind Profiles

The ADM/Aeolus wind lidar mission will provide a global coverage of atmospheric wind profiles. Atmospheric wind observations are required for initiating weather forecast models and for predicting and monitoring long term climate change. Improved knowledge of the global wind field is widely recognised as fundamental to advancing the understanding and prediction of weather and climate. In particular over tropical areas there is a need for better wind data leading to improved medium range (3-10 days) weather forecasts over the whole globe.

scholarly journals Spatial-Temporal Pattern Changes of UTCI in the China-Pakistan Economic Corridor in Recent 40 Years

Atmosphere ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 858
Author(s):  
Di Zeng ◽  
Jinkui Wu ◽  
Yaqiong Mu ◽  
Mingshan Deng ◽  
Yanqiang Wei ◽  
...  
Keyword(s):  
Thermal Environment ◽  
Linear Trend ◽  
Temporal Variations ◽  
Reanalysis Data ◽  
Climate Index ◽  
Positive Trend ◽  
Growth Trend ◽  
Weather Forecasts ◽  
European Centre ◽  
Medium Range

This paper investigated the spatial and temporal variations of the Universal Thermal Climate Index (UTCI) of the China-Pakistan Economic Corridor (CPEC) from 1979 to 2018. The European Centre for Medium-Range Weather Forecasts Re-Analysis-Interim (ERA-Interim) reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) is selected for UTCI calculation in the region and analyzed by a linear trend and correlation analysis. The results showed that (1) the UTCI of CPEC is decreased with the increase of latitude and altitude. There is obvious spatial heterogeneity in the seasonal scale and the spatial distribution of different thermal stress categories. (2) UTCI generally exhibited a positive trend of 0.33 °C/10a over the past 40 years, and the seasonal variation characteristics of UTCI show an upward trend in all four seasons, of which spring is the fastest. On the space scale, the growth trend has significant spatial variations. (3) Temperature has a positive correlation with UTCI. The influence of temperature on UTCI is greater than that of wind speed. The results of this study will be helpful for regional planning and also contribute to comprehending the characteristics of the thermal environment in CPEC.

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