ESE 315 Assignment 4 - Revision history

Atmoschem at 03:28, 22 October 2019

2019-10-22T03:28:08Z

Atmoschem at 03:22, 22 October 2019

2019-10-22T03:22:05Z

Atmoschem at 03:14, 22 October 2019

2019-10-22T03:14:10Z

Atmoschem: Created page with "In this assignment, you will practice reading NetCDF files, manipulate the data and calculate diagnostics, and then make 2D plots. # (20 points) Plot the monthly mean surface..."

2019-10-21T12:58:38Z

Created page with "In this assignment, you will practice reading NetCDF files, manipulate the data and calculate diagnostics, and then make 2D plots. # (20 points) Plot the monthly mean surface..."

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In this assignment, you will practice reading NetCDF files, manipulate the data and calculate diagnostics, and then make 2D plots.

# (20 points) Plot the monthly mean surface air temperature and monthly mean surface winds for January 2018, and plot both data in one 2D plot. Plot the winds as wind barbs in units of knots. Repeat the process for July 2018 in a separate plot.
# (20 points) Plot the monthly mean geopotential height and the monthly mean winds at 500 hPa for January 2018, and plot both data in one 2D plot. Plot the winds as wind barbs in units of knots. Repeat the process for July 2018 in a separate plot.
# (20 points) Plot the surface temperature anomaly for January 2018 relative to the [https://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.derived.surface.html long-term mean for January (1981-2010)]. Repeat the process for July 2018.
# (20 points) Plot the daily surface temperature in Shenzhen for 2018. This would be a 1D plot, with time as the x-axis and temperature as the y-axis.
# (20 points) Calculate the zonal mean surface air temperature for January and July 2018. Plot both data in one plot. This would be a 1D plot, with latitude as the x-axis and temperature as the y-axis.

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 # (20 points) Plot the monthly mean surface air temperature and monthly mean surface winds for January 2018, and plot both data in one 2D plot. Plot the winds as wind barbs in units of knots. Repeat the process for July 2018 in a separate plot.
 # (20 points) Plot the monthly mean geopotential height and the monthly mean winds at 500 hPa for January 2018, and plot both data in one 2D plot. Plot the winds as wind barbs in units of knots. Repeat the process for July 2018 in a separate plot.
-# (20 points) Plot the surface temperature anomaly for January 2018 relative to the [https://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.derived.surface.html long-term mean for January (1981-2010)]. Repeat the process for July 2018. '''''注意：因为1981-2010气候平均数据的解析度较低（144个经度*73个纬度），无法与前面两题使用的数据直接相减。这一题请用[https://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.derived.surface.html 这个网页]的2018年1月数据和气候平均数据，解析度是144个经度*73个纬度。我们也会下载放到课程服务器上。'''''
+# (20 points) Plot the surface temperature anomaly for January 2018 relative to the [https://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.derived.surface.html long-term mean for January (1981-2010)]. Repeat the process for July 2018. '''''注意：因为1981-2010气候平均数据的解析度较低（144个经度*73个纬度），无法与前面两题使用的数据直接相减。这一题请用[https://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.derived.surface.html 这个网页]的2018年1月数据和气候平均数据，解析度是144个经度*73个纬度。我们也会下载放到课程服务器上，路径为 public/T2-dataset/long_term_144x73 '''''
 # (20 points) Plot the daily surface temperature in Shenzhen for 2018. This would be a 1D plot, with time as the x-axis and temperature as the y-axis.
 # (20 points) Calculate the zonal mean surface air temperature for January and July 2018. Plot both data in one plot. This would be a 1D plot, with latitude as the x-axis and temperature as the y-axis.