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2 results for “DayCent”

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zenodo36/100

DayCent-UV grassland productivity across the midwestern and western conterminous United States.

<p>This dataset provides information about daily and annual simulated aboveground plant productivity (ANPP) in grasslands grid cells across the midwestern and western conterminous United States from 1984 to 2015.&nbsp; Annual ANPP estimates from Rangeland Analysis Platform (RAP) are included for comparison.</p> <p><strong>Files Description:</strong></p> <ul> <li><strong>Grid_Cells_Shapefile.zip</strong></li> </ul> <p>Contains<strong>&nbsp;</strong>the spatial distribution for each simulated grassland grid cell. Each grid cell is identified by a <code>grid</code> number ranging from 0 to 2712, a <code>col</code> number increasing from west to east, and a <code>row</code> number increasing from south to north.&nbsp;</p> <ul> <li><strong>Daily_ANPP_DayCent-UV.zip:</strong></li> </ul> <p>Each NetCDF file contains the daily ANPP information for each grid cell during a specifc year. Daily ANPP&nbsp; for a grid cell can be acessed in the <code>cropANPP</code> variable, which depends on the grid cell identifier <code>row</code> and <code>col</code>, and <code>time</code> for&nbsp;the day of the year.</p> <p>For example, using the library <em>xarray</em> from Python, the daily ANPP value&nbsp; for a California grassland grid cell (grid : 1207, row: 78, col: 24) in day 150 in year 2000 can be obtained by using the following command lines:</p> <p>import xarray as xr</p> <p>dataset = xr.open_dataset( folder_directory + '/Daily_ANPP_DayCent-UV/daycent_cwrf_2000.nc')</p> <p>time = 150</p> <p>lon_index = 24</p> <p>lat_index = 78&nbsp;</p> <p>value =&nbsp; dataset.cropANPP[time, lat_index, lon_index].values</p> <p>To calculate annual ANPP for each grid cell, sum the&nbsp;<code>cropANPP</code> values across all days within a file.&nbsp;</p> <ul> <li><strong>Annual_ANPP_DAYCENT-UV_1986-2015.csv</strong></li> </ul> <p>Contains the simulated annual ANPP&nbsp; in the <code>cum_ANPP</code> column (gC/m&sup2;),&nbsp; for each <code>year</code> and each grid cell&nbsp; identified by <code>grid</code>,&nbsp; <code>lon</code>, <code>lat</code> ,<code>row</code>, <code>col</code>&nbsp; (see shapefile description)</p> <ul> <li><strong>Annual_ANPP_RAP_1986-2015.csv</strong></li> </ul> <p>Provides RAP's annual ANPP estimates for each grid cell, identified by its&nbsp;<code>grid</code> number, by using two different equations:&nbsp; </p> <ul> <li> <ul> <li>Gerardhi &amp; Sala equation: RAP-ANPP estimates are located in column <code>RAP_Sala_biomass</code> (g Biomass/m&sup2;), together with the annual fraction of carbon allocated to shoots in&nbsp; <code>fANPP_Sala</code></li> <li>Hiu equation:&nbsp; RAP-ANPP estimates are located in column <code>RAP_Hiu_biomass</code>, together with the annual fraction of carbon allocated to shoots in &nbsp;<code>fANPP_Hiu</code>.</li> </ul> </li> </ul> <p>We assumed a factor of 2.4 (gBiomass/m&sup2;)/(gC) to convert gC/m&sup2; to gBiomass/m&sup2;.</p>

opencc-by-4.0Mar 2024View details →
dryad36/100

DayCent simulations for California annual grasslands: Monthly data outputs

Open the record for dataset details and reuse information.

publicJun 2022View details →

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