Reliability of ERA5 and ERA5-Land reanalysis data in the Canadian Prairies
Meteorological data are essential in precision agriculture in the Canadian Prairies and are often associated with spatiotemporal discontinuity and scarcity. Reanalysis data products aim to address this challenge and have recently gained popularity. The European Centre for Medium-Range Weather Foreca...
Gespeichert in:
| Veröffentlicht in: | Theoretical and applied climatology 2024-04, Vol.155 (4), p.3087-3098 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 3098 |
|---|---|
| container_issue | 4 |
| container_start_page | 3087 |
| container_title | Theoretical and applied climatology |
| container_volume | 155 |
| creator | Fatolahzadeh Gheysari, Ali Maghoul, Pooneh Ojo, E. RoTimi Shalaby, Ahmed |
| description | Meteorological data are essential in precision agriculture in the Canadian Prairies and are often associated with spatiotemporal discontinuity and scarcity. Reanalysis data products aim to address this challenge and have recently gained popularity. The European Centre for Medium-Range Weather Forecasts’ ERA5, and its high-resolution land component, ERA5-Land, are two reanalysis datasets that provide hourly estimates of many climate variables globally. This paper focuses on evaluating the performance of ERA5 and ERA5-Land over the Canadian prairies, utilizing data from 109 weather stations situated in southern Manitoba, Canada. Various variables are investigated at daily, monthly, and annual aggregation periods, including air temperature, ground temperature, soil water content, wind speed, precipitation, and evaporation. The datasets are evaluated regarding seasonal bias and spatial distribution of errors over the study area. Regression parameters are also presented to address the biases. Among the investigated variables, air temperature and wind speed exhibit the lowest errors. The evaluation further reveals an overall tendency to overpredict ground temperatures and precipitation while underpredicting evaporation. Based on these findings, the ERA5 and ERA5-Land datasets hold significant potential in applications such as climate-smart agriculture, energy demand analysis, assessing renewable energy resources, and facilitating sustainable urban development. |
| doi_str_mv | 10.1007/s00704-023-04771-z |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_3153597314</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2957801335</sourcerecordid><originalsourceid>FETCH-LOGICAL-c352t-f18f10ff95d9282908c85d28a3d4f09cea6832b3dc282904bff281bbbfeca3213</originalsourceid><addsrcrecordid>eNp9UE1LAzEUDKJgrf4BTwEvXqIvX032WEr9oqAUBW8hu5toyna3JttD--tNW0Hw4OW94b2ZgRmELincUAB1m_IAQYBxAkIpSrZHaEAFF0QIzY_RAKhSRBX6_RSdpbQAADYaqQF6mrsm2DI0od_gzuPpfCyxbes9ILMdis62ttmkkHBte4tDi_tPhyf5Wgfb4pdoQwwunaMTb5vkLn72EL3dTV8nD2T2fP84Gc9IxSXriafaU_C-kHXBNCtAV1rWTFteCw9F5exIc1byutp_Rek907QsS-8qyxnlQ3R98F3F7mvtUm-WIVWuaWzrunUynEouC8Vz_CG6-kNddOuY0yTDCqk0UM5lZrEDq4pdStF5s4phaePGUDC7es2hXpPrNft6zTaL-EGUMrn9cPHX-h_VN50Se7k</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2957801335</pqid></control><display><type>article</type><title>Reliability of ERA5 and ERA5-Land reanalysis data in the Canadian Prairies</title><source>Springer Nature - Complete Springer Journals</source><creator>Fatolahzadeh Gheysari, Ali ; Maghoul, Pooneh ; Ojo, E. RoTimi ; Shalaby, Ahmed</creator><creatorcontrib>Fatolahzadeh Gheysari, Ali ; Maghoul, Pooneh ; Ojo, E. RoTimi ; Shalaby, Ahmed</creatorcontrib><description>Meteorological data are essential in precision agriculture in the Canadian Prairies and are often associated with spatiotemporal discontinuity and scarcity. Reanalysis data products aim to address this challenge and have recently gained popularity. The European Centre for Medium-Range Weather Forecasts’ ERA5, and its high-resolution land component, ERA5-Land, are two reanalysis datasets that provide hourly estimates of many climate variables globally. This paper focuses on evaluating the performance of ERA5 and ERA5-Land over the Canadian prairies, utilizing data from 109 weather stations situated in southern Manitoba, Canada. Various variables are investigated at daily, monthly, and annual aggregation periods, including air temperature, ground temperature, soil water content, wind speed, precipitation, and evaporation. The datasets are evaluated regarding seasonal bias and spatial distribution of errors over the study area. Regression parameters are also presented to address the biases. Among the investigated variables, air temperature and wind speed exhibit the lowest errors. The evaluation further reveals an overall tendency to overpredict ground temperatures and precipitation while underpredicting evaporation. Based on these findings, the ERA5 and ERA5-Land datasets hold significant potential in applications such as climate-smart agriculture, energy demand analysis, assessing renewable energy resources, and facilitating sustainable urban development.</description><identifier>ISSN: 0177-798X</identifier><identifier>EISSN: 1434-4483</identifier><identifier>DOI: 10.1007/s00704-023-04771-z</identifier><language>eng</language><publisher>Vienna: Springer Vienna</publisher><subject>Aggregation ; Agriculture ; Air temperature ; Aquatic Pollution ; Atmospheric Protection/Air Quality Control/Air Pollution ; Atmospheric Sciences ; Bias ; Climate ; Climate and weather ; Climate change ; Climate-smart agriculture ; Climatic analysis ; Climatology ; data collection ; Datasets ; Demand analysis ; Digital agriculture ; Earth and Environmental Science ; Earth Sciences ; energy ; Energy demand ; Energy resources ; Energy sources ; Errors ; Evaporation ; Ground temperatures ; Manitoba ; Medium-range forecasting ; Meteorological data ; Moisture content ; Performance evaluation ; Prairies ; Precipitation ; Precision agriculture ; Renewable energy ; renewable energy sources ; Renewable resources ; Seasonal distribution ; Soil temperature ; Soil water ; soil water content ; Spatial distribution ; Sustainable development ; Temperature ; Urban development ; Urbanization ; Waste Water Technology ; Water content ; Water Management ; Water Pollution Control ; Weather ; Weather forecasting ; Weather stations ; Wind ; Wind speed</subject><ispartof>Theoretical and applied climatology, 2024-04, Vol.155 (4), p.3087-3098</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c352t-f18f10ff95d9282908c85d28a3d4f09cea6832b3dc282904bff281bbbfeca3213</citedby><cites>FETCH-LOGICAL-c352t-f18f10ff95d9282908c85d28a3d4f09cea6832b3dc282904bff281bbbfeca3213</cites><orcidid>0000-0003-3812-6883</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00704-023-04771-z$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00704-023-04771-z$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Fatolahzadeh Gheysari, Ali</creatorcontrib><creatorcontrib>Maghoul, Pooneh</creatorcontrib><creatorcontrib>Ojo, E. RoTimi</creatorcontrib><creatorcontrib>Shalaby, Ahmed</creatorcontrib><title>Reliability of ERA5 and ERA5-Land reanalysis data in the Canadian Prairies</title><title>Theoretical and applied climatology</title><addtitle>Theor Appl Climatol</addtitle><description>Meteorological data are essential in precision agriculture in the Canadian Prairies and are often associated with spatiotemporal discontinuity and scarcity. Reanalysis data products aim to address this challenge and have recently gained popularity. The European Centre for Medium-Range Weather Forecasts’ ERA5, and its high-resolution land component, ERA5-Land, are two reanalysis datasets that provide hourly estimates of many climate variables globally. This paper focuses on evaluating the performance of ERA5 and ERA5-Land over the Canadian prairies, utilizing data from 109 weather stations situated in southern Manitoba, Canada. Various variables are investigated at daily, monthly, and annual aggregation periods, including air temperature, ground temperature, soil water content, wind speed, precipitation, and evaporation. The datasets are evaluated regarding seasonal bias and spatial distribution of errors over the study area. Regression parameters are also presented to address the biases. Among the investigated variables, air temperature and wind speed exhibit the lowest errors. The evaluation further reveals an overall tendency to overpredict ground temperatures and precipitation while underpredicting evaporation. Based on these findings, the ERA5 and ERA5-Land datasets hold significant potential in applications such as climate-smart agriculture, energy demand analysis, assessing renewable energy resources, and facilitating sustainable urban development.</description><subject>Aggregation</subject><subject>Agriculture</subject><subject>Air temperature</subject><subject>Aquatic Pollution</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Atmospheric Sciences</subject><subject>Bias</subject><subject>Climate</subject><subject>Climate and weather</subject><subject>Climate change</subject><subject>Climate-smart agriculture</subject><subject>Climatic analysis</subject><subject>Climatology</subject><subject>data collection</subject><subject>Datasets</subject><subject>Demand analysis</subject><subject>Digital agriculture</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>energy</subject><subject>Energy demand</subject><subject>Energy resources</subject><subject>Energy sources</subject><subject>Errors</subject><subject>Evaporation</subject><subject>Ground temperatures</subject><subject>Manitoba</subject><subject>Medium-range forecasting</subject><subject>Meteorological data</subject><subject>Moisture content</subject><subject>Performance evaluation</subject><subject>Prairies</subject><subject>Precipitation</subject><subject>Precision agriculture</subject><subject>Renewable energy</subject><subject>renewable energy sources</subject><subject>Renewable resources</subject><subject>Seasonal distribution</subject><subject>Soil temperature</subject><subject>Soil water</subject><subject>soil water content</subject><subject>Spatial distribution</subject><subject>Sustainable development</subject><subject>Temperature</subject><subject>Urban development</subject><subject>Urbanization</subject><subject>Waste Water Technology</subject><subject>Water content</subject><subject>Water Management</subject><subject>Water Pollution Control</subject><subject>Weather</subject><subject>Weather forecasting</subject><subject>Weather stations</subject><subject>Wind</subject><subject>Wind speed</subject><issn>0177-798X</issn><issn>1434-4483</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9UE1LAzEUDKJgrf4BTwEvXqIvX032WEr9oqAUBW8hu5toyna3JttD--tNW0Hw4OW94b2ZgRmELincUAB1m_IAQYBxAkIpSrZHaEAFF0QIzY_RAKhSRBX6_RSdpbQAADYaqQF6mrsm2DI0od_gzuPpfCyxbes9ILMdis62ttmkkHBte4tDi_tPhyf5Wgfb4pdoQwwunaMTb5vkLn72EL3dTV8nD2T2fP84Gc9IxSXriafaU_C-kHXBNCtAV1rWTFteCw9F5exIc1byutp_Rek907QsS-8qyxnlQ3R98F3F7mvtUm-WIVWuaWzrunUynEouC8Vz_CG6-kNddOuY0yTDCqk0UM5lZrEDq4pdStF5s4phaePGUDC7es2hXpPrNft6zTaL-EGUMrn9cPHX-h_VN50Se7k</recordid><startdate>20240401</startdate><enddate>20240401</enddate><creator>Fatolahzadeh Gheysari, Ali</creator><creator>Maghoul, Pooneh</creator><creator>Ojo, E. RoTimi</creator><creator>Shalaby, Ahmed</creator><general>Springer Vienna</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7TG</scope><scope>7TN</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>7S9</scope><scope>L.6</scope><orcidid>https://orcid.org/0000-0003-3812-6883</orcidid></search><sort><creationdate>20240401</creationdate><title>Reliability of ERA5 and ERA5-Land reanalysis data in the Canadian Prairies</title><author>Fatolahzadeh Gheysari, Ali ; Maghoul, Pooneh ; Ojo, E. RoTimi ; Shalaby, Ahmed</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c352t-f18f10ff95d9282908c85d28a3d4f09cea6832b3dc282904bff281bbbfeca3213</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Aggregation</topic><topic>Agriculture</topic><topic>Air temperature</topic><topic>Aquatic Pollution</topic><topic>Atmospheric Protection/Air Quality Control/Air Pollution</topic><topic>Atmospheric Sciences</topic><topic>Bias</topic><topic>Climate</topic><topic>Climate and weather</topic><topic>Climate change</topic><topic>Climate-smart agriculture</topic><topic>Climatic analysis</topic><topic>Climatology</topic><topic>data collection</topic><topic>Datasets</topic><topic>Demand analysis</topic><topic>Digital agriculture</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>energy</topic><topic>Energy demand</topic><topic>Energy resources</topic><topic>Energy sources</topic><topic>Errors</topic><topic>Evaporation</topic><topic>Ground temperatures</topic><topic>Manitoba</topic><topic>Medium-range forecasting</topic><topic>Meteorological data</topic><topic>Moisture content</topic><topic>Performance evaluation</topic><topic>Prairies</topic><topic>Precipitation</topic><topic>Precision agriculture</topic><topic>Renewable energy</topic><topic>renewable energy sources</topic><topic>Renewable resources</topic><topic>Seasonal distribution</topic><topic>Soil temperature</topic><topic>Soil water</topic><topic>soil water content</topic><topic>Spatial distribution</topic><topic>Sustainable development</topic><topic>Temperature</topic><topic>Urban development</topic><topic>Urbanization</topic><topic>Waste Water Technology</topic><topic>Water content</topic><topic>Water Management</topic><topic>Water Pollution Control</topic><topic>Weather</topic><topic>Weather forecasting</topic><topic>Weather stations</topic><topic>Wind</topic><topic>Wind speed</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fatolahzadeh Gheysari, Ali</creatorcontrib><creatorcontrib>Maghoul, Pooneh</creatorcontrib><creatorcontrib>Ojo, E. RoTimi</creatorcontrib><creatorcontrib>Shalaby, Ahmed</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Theoretical and applied climatology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fatolahzadeh Gheysari, Ali</au><au>Maghoul, Pooneh</au><au>Ojo, E. RoTimi</au><au>Shalaby, Ahmed</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Reliability of ERA5 and ERA5-Land reanalysis data in the Canadian Prairies</atitle><jtitle>Theoretical and applied climatology</jtitle><stitle>Theor Appl Climatol</stitle><date>2024-04-01</date><risdate>2024</risdate><volume>155</volume><issue>4</issue><spage>3087</spage><epage>3098</epage><pages>3087-3098</pages><issn>0177-798X</issn><eissn>1434-4483</eissn><abstract>Meteorological data are essential in precision agriculture in the Canadian Prairies and are often associated with spatiotemporal discontinuity and scarcity. Reanalysis data products aim to address this challenge and have recently gained popularity. The European Centre for Medium-Range Weather Forecasts’ ERA5, and its high-resolution land component, ERA5-Land, are two reanalysis datasets that provide hourly estimates of many climate variables globally. This paper focuses on evaluating the performance of ERA5 and ERA5-Land over the Canadian prairies, utilizing data from 109 weather stations situated in southern Manitoba, Canada. Various variables are investigated at daily, monthly, and annual aggregation periods, including air temperature, ground temperature, soil water content, wind speed, precipitation, and evaporation. The datasets are evaluated regarding seasonal bias and spatial distribution of errors over the study area. Regression parameters are also presented to address the biases. Among the investigated variables, air temperature and wind speed exhibit the lowest errors. The evaluation further reveals an overall tendency to overpredict ground temperatures and precipitation while underpredicting evaporation. Based on these findings, the ERA5 and ERA5-Land datasets hold significant potential in applications such as climate-smart agriculture, energy demand analysis, assessing renewable energy resources, and facilitating sustainable urban development.</abstract><cop>Vienna</cop><pub>Springer Vienna</pub><doi>10.1007/s00704-023-04771-z</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0003-3812-6883</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0177-798X |
| ispartof | Theoretical and applied climatology, 2024-04, Vol.155 (4), p.3087-3098 |
| issn | 0177-798X 1434-4483 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_3153597314 |
| source | Springer Nature - Complete Springer Journals |
| subjects | Aggregation Agriculture Air temperature Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution Atmospheric Sciences Bias Climate Climate and weather Climate change Climate-smart agriculture Climatic analysis Climatology data collection Datasets Demand analysis Digital agriculture Earth and Environmental Science Earth Sciences energy Energy demand Energy resources Energy sources Errors Evaporation Ground temperatures Manitoba Medium-range forecasting Meteorological data Moisture content Performance evaluation Prairies Precipitation Precision agriculture Renewable energy renewable energy sources Renewable resources Seasonal distribution Soil temperature Soil water soil water content Spatial distribution Sustainable development Temperature Urban development Urbanization Waste Water Technology Water content Water Management Water Pollution Control Weather Weather forecasting Weather stations Wind Wind speed |
| title | Reliability of ERA5 and ERA5-Land reanalysis data in the Canadian Prairies |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-15T23%3A06%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Reliability%20of%20ERA5%20and%20ERA5-Land%20reanalysis%20data%20in%20the%20Canadian%20Prairies&rft.jtitle=Theoretical%20and%20applied%20climatology&rft.au=Fatolahzadeh%20Gheysari,%20Ali&rft.date=2024-04-01&rft.volume=155&rft.issue=4&rft.spage=3087&rft.epage=3098&rft.pages=3087-3098&rft.issn=0177-798X&rft.eissn=1434-4483&rft_id=info:doi/10.1007/s00704-023-04771-z&rft_dat=%3Cproquest_cross%3E2957801335%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2957801335&rft_id=info:pmid/&rfr_iscdi=true |