arctic_dem = Layer(
id='arctic_dem',
title='Arctic DEM (100m)',
description='Surface elevation in meters using hillshade symbology.',
in_package=False,
tags=[],
style='arctic_dem',
input=LayerInput(
dataset=dataset,
asset=dataset.assets['100m'],
),
steps=[
*warp(
input_file='{input_dir}/arcticdem_mosaic_100m_v3.0.tif',
output_file='{output_dir}/arctic_dem.tif',
cut_file=project.boundaries['data'].filepath,
),
CommandStep(args=[
'gdal_calc.py',
'--calc',
'"A * 100.0"',
'--NoDataValue',
'-9999',
'--type',
'Int32',
'-A',
'{input_dir}/arctic_dem.tif',
'--outfile',
'{output_dir}/arctic_dem_scaled.tif',
], ),
"""Fraction of a grid cell covered by ice (grounded or floating) in
the year 3007. Values less than or equal to 16% are masked."""),
tags=[],
style='future_ice_sheet_coverage',
input=LayerInput(
dataset=dataset,
asset=dataset.assets[f'rcp_{rcp}'],
),
steps=[
*warp(
input_file=(
'NETCDF:{input_dir}/'
f'percent_gris_g1800m_v3a_rcp_{rcp}_0_1000.nc:sftgif'),
output_file='{output_dir}/extracted.tif',
warp_args=(
'-srcnodata',
'0',
'-tr',
'1800',
'1800',
),
cut_file=project.boundaries['data'].filepath,
),
*compress_and_add_overviews(
input_file='{input_dir}/extracted.tif',
output_file='{output_dir}/final.tif',
dtype_is_float=True,
),
],
) for rcp in LAYER_RCPS
]
tags=[],
style=bathymetric_raster_params['style'],
input=LayerInput(
dataset=bathymetric_raster_params['dataset'],
asset=dataset.assets['only'],
),
steps=[
*warp(
input_file='NETCDF:{input_dir}/IBCAO_v4_400m_ice.nc:z',
output_file='{output_dir}/bathymetric_chart.tif',
warp_args=(
'-s_srs', '"+proj=stere +lat_0=90 +lat_ts=75 +datum=WGS84"',
'-dstnodata', '-9999',
'-tr', '400', '400',
# This dataset does not contain CF-compliant fields or
# geotransform array. Set
# `GDAL_NETCDF_IGNORE_XY_AXIS_NAME_CHECKS` to `true` to use
# the provided `x` and `y` dims as coordinate values so that
# gdal can compute the transform on its own. See
# https://github.com/OSGeo/gdal/issues/4075
'--config', 'GDAL_NETCDF_IGNORE_XY_AXIS_NAME_CHECKS', 'true',
),
cut_file=project.boundaries['background'].filepath,
),
*compress_and_add_overviews(
input_file='{input_dir}/bathymetric_chart.tif',
output_file='{output_dir}/bathymetric_chart.tif',
dtype_is_float=True,
),
],
)
id='vegetation_biomass_2010',
title='Vegetation biomass 2010 (12.4km)',
description=(
"""Estimated above ground plant biomass for the tundra biome in
kilograms per square meter. Based on trans-Arctic field data and AVHRR
NDVI. Data provided by ORNL DAAC."""),
tags=[],
style='vegetation_biomass',
input=LayerInput(
dataset=dataset,
asset=dataset.assets['only'],
),
steps=[
*warp(
input_file='{input_dir}/aga_circumpolar_avhrr_biomass_2010.tif',
output_file='{output_dir}/warped.tif',
cut_file=project.boundaries['data'].filepath,
warp_args=(
'-tr',
'12400',
'12400',
),
),
*compress_and_add_overviews(
input_file='{input_dir}/warped.tif',
output_file='{output_dir}/compressed.tif',
dtype_is_float=True,
),
],
)
ice_thickness_change = Layer(
id='ice_thickness_change',
title='Ice column thickness rate of change 2003-2019 (5km)',
description=(
"""Ice column thickness-change-rate estimates in meters per year based
on data from NASA's ICESat and ICESat-2 satellites."""
),
tags=[],
style='ice_thickness_change',
input=LayerInput(
dataset=dataset,
asset=dataset.assets['only'],
),
steps=[
decompress_step(
input_file='{input_dir}/ICESat1_ICESat2_mass_change.zip',
decompress_contents_mask=SOURCE_FP,
),
*warp(
input_file='{input_dir}/' + SOURCE_FP,
output_file='{output_dir}/warped.tif',
cut_file=project.boundaries['data'].filepath,
),
*compress_and_add_overviews(
input_file='{input_dir}/warped.tif',
output_file='{output_dir}/final.tif',
dtype_is_float=True,
),
],
)
from qgreenland.models.config.layer import Layer, LayerInput
nc_dataset = 'GHF'
geothermal_heat_flux = Layer(
id='geothermal_heat_flux',
title='Flux from ice cores (Greve, R.) (5km)',
description=(
"""Geothermal heat flux interpolated from ice core measurements in
miliwatts per square meter."""),
tags=[],
style='geothermal_heat_flux',
input=LayerInput(
dataset=dataset,
asset=dataset.assets['only'],
),
steps=[
*warp(
input_file='NETCDF:{input_dir}/' +
f'GHF_Greenland_Ver2.0_GridEPSG3413_05km.nc:{nc_dataset}',
output_file='{output_dir}/warped.tif',
cut_file=project.boundaries['data'].filepath,
),
*compress_and_add_overviews(
input_file='{input_dir}/warped.tif',
output_file='{output_dir}/final.tif',
dtype_is_float=True,
),
],
)