{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Using SWOT satellite altimetry"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This example will guide you through each step required to estimate energy cascade rates from a single SWOT KaRIn swath.\n",
"\n",
"**General procedure**\n",
"\n",
"1. Load and visualize the SWOT sea surface height anomaly (SSHA) data\n",
"2. Use SSHA to estimate geostrophic velocities\n",
"3. Subset the data to a small region\n",
"4. Calculate various structure functions from the geostrophic velocities in the subset region\n",
"5. Estimate cascade rates from the structure functions\n",
"6. Plot cascade rates\n",
"7. Plot 2nd order structure functions"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib_inline.backend_inline\n",
"import seaborn as sns\n",
"\n",
"sns.set_style(style=\"white\")\n",
"sns.set_context(\"talk\")\n",
"\n",
"matplotlib_inline.backend_inline.set_matplotlib_formats(\"png\", dpi=200)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load the SWOT NetCDF file and visualize the data\n",
"\n",
"We will use `xarray` to load the `.nc` file. We are using the Expert version of SWOT Level-3 LR SSH v1.0, available through AVISO. This version includes estimates of geostrophic velocity along with improved data post-processing. It is possible to estimate geostrophic velocities from SSH data only, which is available in the Basic version of Level-3 and Level-2. \n",
"\n",
"**_Note:_** The SWOT data is not provided in the FluidSF repository, so you must instead access the data through [PO.DAAC](https://podaac.jpl.nasa.gov/SWOT?tab=mission-objectives§ions=about%2Bdata), [AVISO](https://www.aviso.altimetry.fr/en/data/products/sea-surface-height-products/global.html), or other methods. This example uses L3 data, accessible through AVISO."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import xarray as xr\n",
"\n",
"# Provide the path to the SWOT data you have downloaded\n",
"ds = xr.open_dataset('example_data/SWOT_L3_LR_SSH_Expert_SAMPLE.nc') "
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
Latitude of measurement [-80,80]. Positive latitude is North latitude, negative latitude is South latitude.
long_name :
latitude (positive N, negative S)
standard_name :
latitude
units :
degrees_north
[680340 values with dtype=float64]
longitude
(num_lines, num_pixels)
float64
...
comment :
Longitude of measurement. East longitude relative to Greenwich meridian.
long_name :
longitude (degrees East)
standard_name :
longitude
units :
degrees_east
[680340 values with dtype=float64]
time
(num_lines)
datetime64[ns]
...
comment :
Time of measurement in seconds in the UTC time scale since 1 Jan 2000 00:00:00 UTC. [tai_utc_difference] is the difference between TAI and UTC reference time (seconds) for the first measurement of the data set. If a leap second occurs within the data set, the attribute leap_second is set to the UTC time at which the leap second occurs.
leap_second :
0000-00-00T00:00:00Z
long_name :
time in UTC
standard_name :
time
tai_utc_difference :
37.0
[9860 values with dtype=datetime64[ns]]
mdt
(num_lines, num_pixels)
float64
...
comment :
The mean dynamic topography is the sea surface height above geoid; it is used to compute the absolute dynamic topography ssh=ssha+mdt
units :
m
long_name :
mean dynamic topography
standard_name :
mean_dynamic_topography_cnes_cls
[680340 values with dtype=float64]
ssha
(num_lines, num_pixels)
float64
...
long_name :
sea surface height anomaly
standard_name :
sea_surface_height_above_reference_ellipsoid
comment :
Height of the sea surface anomaly with all corrections applied.
units :
m
[680340 values with dtype=float64]
ssha_noiseless
(num_lines, num_pixels)
float64
...
comment :
Height of the sea surface anomaly with all corrections applied and denoised using Unet model and Gomez algorithm.
long_name :
sea surface height anomaly without noise
standard_name :
sea_surface_height_above_reference_ellipsoid
units :
m
[680340 values with dtype=float64]
ssha_unedited
(num_lines, num_pixels)
float64
...
comment :
Height of the sea surface anomaly with all corrections applied but without editing.
long_name :
sea surface height anomaly without editing
standard_name :
sea_surface_height_above_reference_ellipsoid
units :
m
[680340 values with dtype=float64]
quality_flag
(num_lines, num_pixels)
uint8
...
comment :
Deduced from L3 DUACS processing.
flag_masks :
[ 0 5 10 20 30 50 70 100 101 102]
flag_meanings :
good local_outliers bad_quality_coast ice soft_outliers extremes mission_event bad_swath_extremities not_on_sea no_data
long_name :
Quality Flag
standard_name :
valid_flag_for_data
[680340 values with dtype=uint8]
ocean_tide
(num_lines, num_pixels)
float64
...
comment :
Geocentric ocean tide height. Includes the total sum of the ocean tide, the corresponding load tide and equilibrium long-period ocean tide height. The ssha in this file is already corrected for the ocean_tide; the uncorrected ssha can be computed as follows: [uncorrected ssha]=[ssha from product]+[ocean_tide]; see the product user manual for details
units :
m
long_name :
geocentric ocean tide height (FES)
source :
FES2022
institution :
LEGOS/CNES
[680340 values with dtype=float64]
mss
(num_lines, num_pixels)
float64
...
comment :
Mean sea surface height above the reference ellipsoid. The value is referenced to the mean tide system, i.e. includes the permanent tide (zero frequency).
units :
m
long_name :
mean sea surface height (CNES/CLS)
[680340 values with dtype=float64]
dac
(num_lines, num_pixels)
float32
...
comment :
Model estimate of the effect on sea surface topography due to high frequency air pressure and wind effects and the low-frequency height from inverted barometer effect. The ssha in this file is already corrected for the dac; the uncorrected ssha can be computed as follows: [uncorrected ssha]=[ssha from product]+[dac]; see the product user manual for details
institution :
LEGOS/CNES/CLS
long_name :
dynamic atmospheric correction
source :
MOG2D
units :
m
[680340 values with dtype=float32]
calibration
(num_lines, num_pixels)
float64
...
long_name :
satellite calibration
comment :
phase screen + phase_screen_static + phase_screen_orbit + xcal. the uncorrected ssha can be computed as follows: [uncorrected ssha]=[ssha from product] + [calibration]; see the product user manual for details
Normalized radar cross section (sigma0) from KaRIn in real, linear units (not decibels). The value may be negative due to noise subtraction. The value is corrected for instrument calibration and atmospheric attenuation. A meteorological model provides the atmospheric attenuation (sig0_cor_atmos_model).)
long_name :
normalized radar cross section (sigma0) from KaRIn)