S5P-LNO2

Core code for the TROPOMI lightning NO2 (LNO2) retrievals. Some useful Jupyter Notebooks are available at S5P-LNO2-Notebook.

Pairing lightning and fire data with TROPOMI NO2 L2 product considering the transport
LNO2 mask
Consecutive swaths with lightning
Retrieval of lightning NO2 vertical column density
LNO2 production efficiency based on consecutive swaths data
TROPOMI CO data for wildfire
Integration of cloud slicing (see forked era-uptrop)

Main workflow

Users need to prepare the Input Data first and then run the scripts one by one.

Please feel free to modify the settings.txt file for your own research.

Detailed explanations of main scripts:

Select lightning-swaths with both lightning and high NO2, and save them to nc files. [s5p_lno2_main.py]
Link the consecutive lightning-swath cases and save variables (case No., filename, and mask label) to csv files. [s5p_lno2_cases.py]
Combine the generated csv file into fresh_lightning_cases.csv or nolightning_cases.csv. [s5p_lno2_cases_sum.py]
(Optional) Plot linked variables and save them as images to filter cases manually [s5p_lno2_plot.py]. We are still thinking how to convert the manual part into an auto one.
Extract TM5 no2_vmr and temperature profiles for consecutive lightning-swaths. [s5p_lno2_tm5_extract.py]
Calculate lightning variables (AMFs, SCD_Bkgd, tropopause_pressure, lno2vis, lno2_geo and lno2) and save them to one netcdf file called "S5P_LNO2.nc" [s5p_lno2_product.py]
Calculate lightning NO2 production efficiency and save all useful variables to one CSV file called "S5P_LNO2_PE.csv". [s5p_lno2_pe_lifetime.py]

Input Data

The used data are listed below.

The input paths are shown in parentheses. Please feel free to modify them in settings.txt.

TROPOMI (<s5p_dir>/<yyymm>/S5P_**__L2__NO2____)

There're three main methods of downloading the TROPOMI NO2 L2 data:
- Sentinel-5P Pre-Operations Data Hub
- GES DISC
- S5P-PAL: this is the reprocessed NO2 data from April 2018 - September 2021. The two sources above will be updated soon.
ERA5 (<era5_dir>/era5_<yyyymm>.nc)

The pressure level (200 - 700 hPa) ERA5 data (u and v) are used to predict the transport of lightning air in the upper troposphere.

Note that for the TROPOMI data on the first day of month, we need the ERA5 data on the last day of the previous month.

e.g. S5P...20220201... needs era5_202201.nc which at least has the data on 2022-01-31.
Lightning Data (<lightning_dir>/<yyymm>/<yyyymmdd>.csv)

The lightning data should be saved in CSV format and have at least three fields: timestamp, longitude, and latitude.
VIIRS S-NPP fire product

The archive VIIRS S-NPP data is available from FIRMS.

Other useful functions

Regrid TROPOMI product (s5p_regrid.py and s5p_regrid_combine.py)

The harp tool is convient for regridding TROPOMI L2 data to Lon/Lat grids with filters.
Calculate the TROPOMI pixel areas (s5p_pixel_area.py)

Usually the areas are same for different swaths. We calculated all possible areas and saved it into one netCDF file for usage.

Calculate lightning within TROPOMI swaths (swath_lightning.py)

It is useful to know how many lightning happened inside the swaths before the TROPOMI overpass.

Grid lightning NO2 product (s5p_lno2_grid.py)
Generate daily and summertime GLD360 data (gld360_daily.py and gld360_summer.py)

Outputs

1. L2 product with new variables (netCDF file)

(Click to expand) s5p_lno2_main.py adds lightning/fire data and lightning masks to simplified L2 product.

Varname	Group	Units	Description
time	S5P	days since <yyyy-mm-dd>	time using proleptic gregorian calendar
latitude	S5P	degrees_north	pixel center latitude
longitude	S5P	degrees_east	pixel center longitude
air_mass_factor_clear	S5P	1	Air mass factor for the cloud-free part of the scene
air_mass_factor_cloudy	S5P	1	Air mass factor for the cloud-covered part of the scene
air_mass_factor_stratosphere	S5P	1	Stratospheric air mass factor
air_mass_factor_total	S5P	1	Total air mass factor
air_mass_factor_troposphere	S5P	1	Tropospheric air mass factor
Apparent_scene_pressure	S5P	Pa	Scene pressure from the cloud product
assembled_lat_bounds	S5P	degrees_north	assembled_latitude_bounds calculated by Satpy
assembled_lon_bounds	S5P	degrees_east	assembled_longitude_bounds calculated by Satpy
Averaging_kernel	S5P	1	Averaging kernel
cloud_albedo_crb	S5P	1	Cloud albedo in the cloud product
cloud_fraction_crb_nitrogendioxide_window	S5P	1	Cloud fraction at 440 nm for NO2 retrieval
cloud_pressure_crb	S5P	Pa	Cloud optical centroid pressure
cloud_radiance_fraction_nitrogendioxide_window	S5P	1	Cloud radiance fraction at 440 nm for NO2 retrieval
Geolocation_flags	S5P	1	Some flags (see ATBD)
lightning_mask	S5P	1	<0: labeled lightning with fire; 0: no lightning; >0: labeled lightning without fire
nitrogendioxide_ghost_column	S5P	mol m-2	Ghost column NO2: modelled NO2 column below the cloud top
nitrogendioxide_segmentation	S5P	1	0: no high NO2; >=1: labeled high NO2
nitrogendioxide_slant_column_density	S5P	mol m-2	Stratospheric vertical column of nitrogen dioxide, derived from the TM5-MP vertical profiles
nitrogendioxide_stratospheric_column	S5P	mol m-2	Stratospheric vertical column of nitrogen dioxide, derived from the TM5-MP vertical profile
nitrogendioxide_total_column	S5P	mol m-2	Total vertical column of nitrogen dioxide derived from the total slant column and TM5 profile in stratosphere and troposphere
nitrogendioxide_tropospheric_column	S5P	mol m-2	Tropospheric vertical column of nitrogen dioxide
processing_quality_flags	S5P	1	Processing quality flags (See ATBD)
qa_value	S5P	1	Quality value
scene_albedo	S5P	1	Scene albedo in the cloud product
snow_ice_flag	S5P	1	Snow-ice mask (See ATBD)
solar_azimuth_angle	S5P	degree clockwise from the North (East = 90, South = 180, West = 270)	Solar azimuth angle at the ground pixel location on the reference ellipsoid.
solar_zenith_angle	S5P	degree measured away from the vertical	Solar zenith angle at the ground pixel location on the reference ellipsoid.
surface_albedo_nitrogendioxide_window	S5P	1	Surface albedo in the NO2 fit window
surface_pressure	S5P	Pa	Surface pressure
time_utc	S5P	1	Time of observation as ISO 8601 date-time string
tm5_constant_a	S5P	Pa	TM5 hybrid A coefficient at upper and lower interface levels
tm5_constant_b	S5P	Pa	TM5 hybrid B coefficient at upper and lower interface levels
tm5_tropopause_layer_index	S5P	1	TM5 layer index of the highest layer in the tropopause
viewing_azimuth_angle	S5P	degree measured clockwise from the North (East = 90, South = 180, West = 270)	Satellite azimuth angle at the ground pixel location on the reference ellipsoid.
viewing_zenith_angle	S5P	degree measured away from the vertical	Zenith angle of the satellite at the ground pixel location on the reference ellipsoid.




cluster_label	Lightning	1	Clustered lightning labeled by DBSCAN
time	Lightning	minutes since
longitude	Lightning	degrees_east	Longitude of lightning
latitude	Lightning	degrees_north	Latitude of lightning
delta	Lightning	minute	The time difference between detected lightning and TROPOMI overpass time
level	Lightning	hPa	Pressure levels used for lightning NO2 air parcel
longitude_pred	Lightning	degrees_east	Longitude of lightning at different pressure levels predicted by ERA5 data
latitude_pred	Lightning	degrees_north	Latitude of lightning at different pressure levels predicted by ERA5 data
lightning_label	Lightning	1	Lightning label paired with lightning mask



time	Fire	1
longitude	Fire	degrees_north	Longitude of fire
latitude	Fire	degrees_north	Longitude of fire
type	Fire	1	Fire type

2. Lightning NO2 production and lifetime (netCDF file)

The lightning no2 data (S5P_LNO2_production.nc and S5P_LNO2_lifetime.nc) includes the products of netCDF file and other new retrievals (see S5P-WRFCHEM, but we use a priori NO2 profiles assuming guassian distributions instead of WRF--Chem results).

(Click to expand) Data Structure

- Case 1
	-	Swath xxx
		- S5P
		 - .......... (official S5P data as shown above)
		 - scdTrop
		 - lightning_mask
		 - area
		 - amfTrop
		 - amfTropVis
		 - swClr
		 - swCld
		 - avgKernel
		 - no2apriori
		 - no2Trop
		 - no2TropVis
		 - scdClr
		 - scdCld
		 - vcdGnd
		 - tropopause_pressure
		 - plevels
		 - scdBkgd
		 - amflno2
		 - lno2_mask
		 - lno2vis
		 - lno2geo
		 - lno2
		- Lightning
	- Swath xxx
	...
- Case 2
.....

3. Lightning NO2 production and lifetime (csv file)

The csv files contain two kinds of variable:

Data from previous netcdf files.
Lightning NO2 production efficiency based on consecutive swaths.

csv head: time,case,swath,longitude,latitude,region,nlightning,area,apparent_scene_pressure,no2,lno2geo,lno2vis,lno2,pe_lno2geo,pe_lno2vis,pe_lno2

Publications

Zhang et al., Spaceborne observations of lightning NO2 in the Arctic, Environ. Sci. Technol.

License

zxdawn/S5P-LNO2

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