La Salle River Watershed 05OG008 Hourly Weather 1990 to 2013

La Salle River Watershed 05OG008 Hourly Weather 1990 to 2013 This dataset includes hourly data weather data for the La Salle River Watershed Near Elie, Manitoba, Canada (Water Survey of Canada Hydrometric Station 05OG008) created for hydrological modelling as part of Agriculture and Agri-food Canada’s Red-Assiniboine Project. The dataset includes parameters typically required to run hydrological models at an hourly time step including precipitation, temperature, wind speed, solar radiation, and relative humidity. A variety of methods were used to derive the best estimated hourly value from multiple nearby weather stations. These methods include gap-filling (e.g. linear regression) and disaggregation (e.g. Bartlett-Lewis model) techniques, as outlined in Cordeiro et. al. Long-term weather, hydrometric, and water chemistry datasets in high-temporal resolution at the La Salle River watershed in Manitoba, Canada. Earth System Science Data Journal. Not submitted. 2019-10-31 Agriculture and Agri-Food Canada aafc.OpenGovernment-Gouvernementouvert.aac@canada.ca Nature and EnvironmentScience and TechnologyWeatherprecipitationtemperaturewind speedsolar radiationrelative humidityhourlyLa Salle River Hourly Weather 1990 to 2013CSV https://od-do.agr.gc.ca/os-so/ODI-2017-00957-05OG008_Weather_Météo_1990_2013.csv Data DictionaryHTML https://od-do.agr.gc.ca/os-so/ODI-2017-00957-RAPIIHydroLogicalModelWeatherEn.html Data DictionaryHTML https://od-do.agr.gc.ca/os-so/ODI-2017-00957-RAPIIHydroLogicalModelWeatherFr.html

This dataset includes hourly data weather data for the La Salle River Watershed Near Elie, Manitoba, Canada (Water Survey of Canada Hydrometric Station 05OG008) created for hydrological modelling as part of Agriculture and Agri-food Canada’s Red-Assiniboine Project. The dataset includes parameters typically required to run hydrological models at an hourly time step including precipitation, temperature, wind speed, solar radiation, and relative humidity. A variety of methods were used to derive the best estimated hourly value from multiple nearby weather stations. These methods include gap-filling (e.g. linear regression) and disaggregation (e.g. Bartlett-Lewis model) techniques, as outlined in Cordeiro et. al. Long-term weather, hydrometric, and water chemistry datasets in high-temporal resolution at the La Salle River watershed in Manitoba, Canada. Earth System Science Data Journal. Not submitted.

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