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Merge pull request #822 from sadielbartholomew/student-recipes-5a
Add new recipe (20) started by summer student: current divergence
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| """ | ||
| Calculating and plotting the divergence of sea currents | ||
| ======================================================= | ||
| In this recipe, we will calculate the divergence of depth-averaged | ||
| currents in the Irish Sea, then plot the divergence as a contour | ||
| fill plot underneath the vectors themselves in the form of a vector plot. | ||
| """ | ||
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| # %% | ||
| # 1. Import cf-python and cf-plot: | ||
| import cfplot as cfp | ||
| import cf | ||
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| # %% | ||
| # 2. Read the fields in. This dataset consists of depth-averaged eastward and | ||
| # northward current components plus the sea surface height above sea level and | ||
| # is a gridded dataset, with grid resolution of 1.85 km, covering the entire | ||
| # Irish Sea area. It was found via the CEDA Archive at the location of: | ||
| # https://catalogue.ceda.ac.uk/uuid/1b89e025eedd49e8976ee0721ec6e9b5, with | ||
| # DOI of https://dx.doi.org/10.5285/031e7ca1-9710-280d-e063-6c86abc014a0: | ||
| f = cf.read("~/recipes/POLCOMS_WAM_ZUV_01_16012006.nc") | ||
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| # %% | ||
| # 3. Get the separate vector components, which are stored as separate fields. | ||
| # The first, 'u', corresponds to the eastward component and the second, 'v', | ||
| # the northward component: | ||
| u = f[0] | ||
| v = f[1] | ||
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| # %% | ||
| # 4. Squeeze the fields to remove the size 1 axes in each case: | ||
| u = u.squeeze() | ||
| v = v.squeeze() | ||
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| # %% | ||
| # 5. Consider the currents at a set point in time. To do this we | ||
| # select one of the 720 datetime sample points in the fields to | ||
| # investigate, in this case by subspacing to pick out a particular | ||
| # datetime value we saw within the time coordinate data of the field (but | ||
| # you could also use indexing or filtering to select a specific value). | ||
| # Once we subspace to one datetime, we squeeze out the size 1 time axis | ||
| # in each case: | ||
| chosen_time = "2006-01-15 23:30:00" # 720 choices to pick from, try this one! | ||
| u_1 = u.subspace(T=cf.dt(chosen_time)) | ||
| v_1 = v.subspace(T=cf.dt(chosen_time)) | ||
| u_1 = u_1.squeeze() | ||
| v_1 = v_1.squeeze() | ||
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| # %% | ||
| # 6. | ||
| # When inspecting the u and v fields using cf inspection methods such as | ||
| # from print(u_1.data) and u_1.data.dump(), for example, we can see that there are | ||
| # lots of -9999 values in their data array, apparently used as a | ||
| # fill/placeholder value, including to indicate undefined data over the land. | ||
| # In order for these to not skew the data and dominate the plot, we need | ||
| # to mask values matching this, so that only meaningful values remain. | ||
| u_2 = u_1.where(cf.lt(-9000), cf.masked) | ||
| v_2 = v_1.where(cf.lt(-9000), cf.masked) | ||
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| # %% | ||
| # 7. Calculate the divergence using the 'div_xy' function operating on the | ||
| # vector eastward and northward components as the first and second argument | ||
| # respectively. We need to calculate this for the latitude-longitude plane | ||
| # of the Earth, defined in spherical polar coordinates, so we must specify | ||
| # the Earth's radius for the appropriate calculation: | ||
| div = cf.div_xy(u_2, v_2, radius="earth") | ||
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| # %% | ||
| # 8. Generate the final plot. First we configure the overall plot by | ||
| # making the map higher resolution, to show the coastlines of the UK and | ||
| # Ireland in greater detail, and changing the colourmap to better reflect | ||
| # the data which can be positive or negative, i.e. has 0 as the 'middle' | ||
| # value of significance, so should use a diverging colour map. Then we | ||
| # plot the current vectors, noting we had to play around with the 'stride' | ||
| # and 'scale' parameter values to adjust the vector spacing and size so that | ||
| # the vector field is best represented and visible without over-cluttering | ||
| # the plot. Finally we plot the divergence as a contour plot without any | ||
| # lines showing. This compound plot is saved on one canvas using 'gopen' | ||
| # and 'gclose' to wrap the two plotting calls: | ||
| cfp.mapset(resolution="10m") | ||
| cfp.cscale("ncl_default") | ||
| cfp.gopen( | ||
| file=f"irish-sea-currents-divergence-{chosen_time.replace(' ', '-')}.png") | ||
| cfp.vect(u=u_2, v=v_2, stride=6, scale=3, key_length=1) | ||
| cfp.con( | ||
| div, | ||
| lines=False, | ||
| title=( | ||
| f"Depth-averaged Irish Sea currents at {chosen_time} with " | ||
| "their divergence" | ||
| ) | ||
| ) | ||
| cfp.gclose() |
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