Vary state in WRF smoothly

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Aug 6th, 2022
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How to Vary state in WRF

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members are on so thats perfect and dpr5 is published and dpr3 krista wigginton um might really benefit from yeah the recording so thank you all again for joining and thanks again trisha for um for doing this today yeah yeah um i know thank you everyone for participating i know this is like kind of a this is something thats extra to the regular workload but we think its really important and its also required for anything that is funded by the state of california to be in an accessible format um and it really it shouldnt be too hard especially with the template that was circulated and just to be clear because i know that weve had other wrf slash state water board templates circulated the one that you really should be using for your to format your should be the one that has the accessible in the um title because thats the one that has that we have actually gone through and made sure that all of the different headers and styles are correct for the format of this document okay so um

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It features two dynamical cores, a data assimilation system, and a software architecture supporting parallel computation and system extensibility. The model serves a wide range of meteorological applications across scales from tens of meters to thousands of kilometers.
The default configuration of CLM in WRF divides the land surface into five types: glacier, lake, wetland, urban, and vegetated.
Thats why here MDC is used for LULC classification. Six most important LULC classes including water, agriculture, urban, fallow land, sand, and vegetation were chosen for this study. The classification accuracy can be defined as the number of pixels which are correctly classified to the sum of all pixels.
WRF (Weather Research and Forecasting) model is numerical weather prediction limited area model, provided by National Center for Atmospheric Research, which is widely utilized in research and operation. It is used as both numerical weather prediction model and regional climate model.
Benefits of using remote sensing data for long-term land use monitoring. Among different benefits, these data allow one to not only monitor land use change but also observe the quality of the results, how fast land use has changed over a given period, and what other land cover is present besides the primary observation
Three land surface models (LSMs) namely; Noah, RUC and TD were also considered in the WRF experiments. The Noah LSM uses soil temperature and moisture at four layers with a total depth of 2 m.
The geopotential height is returned as Above Ground Level (AGL) by subtracting the terrain height. This functions extracts the necessary variables from the NetCDF file object in order to perform the calculation. Parameters: wrfin ( netCDF4.
Simply put, land cover is what covers the surface of the earth and land use describes how the land is used. Examples of land cover classes include: water, snow, grassland, deciduous forest, and bare soil. Land use examples include: wildlife management area, agricultural land, urban, and recreation area.

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