Dataset: ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable snow (SCFV) from MODIS (2000 - 2019), version 1.0#

Dataset identifier: esacci.SNOW.day.L3C.SCFV.MODIS.Terra.MODIS_TERRA.1-0.r1
Data store: cciodp

How to open this dataset in AVL JupyterLab  ⧉

cciodp_store = new_data_store('cciodp')
ds = cciodp_store.open_data('esacci.SNOW.day.L3C.SCFV.MODIS.Terra.MODIS_TERRA.1-0.r1')

Bounding box map#

Map tiles and data from OpenStreetMap, under the ODbL.

Basic information#

Parameter	Value
Bounding box longitude (°)	-180.0 to 180.0
Bounding box latitude (°)	-90.0 to 90.0
Time range	2000-02-24 to 2019-12-31
Time period	1D

Click here for full dataset metadata.

Variable list#

Click on a variable name to jump to the variable’s full metadata.

Variable	Long name	Units
scfv	Snow Cover Fraction Viewable	percent
scfv_unc	Unbiased Root Mean Square Error for Snow Cover Fraction Viewable	percent
spatial_ref	[none]	[none]

Full variable metadata#

scfv#

Field	Value
_Unsigned	true
long_name	Snow Cover Fraction Viewable
units	percent
valid_range	0, -2
actual_range	0, 100
flag_values	-51, -50, -46, -41, -4, -3, -2
flag_meanings	Cloud Polar_Night_or_Night Water Permanent_Snow_and_Ice Classification_failed Input_Data_Error No_Satellite_Acquisition
missing_value	-1
ancillary_variables	scfv_unc
grid_mapping	spatial_ref
orig_data_type	uint8
fill_value	-1
size	4659120000000
shape	7190, 18000, 36000
chunk_sizes	1, 1385, 2770
file_chunk_sizes	1, 1385, 2770
data_type	uint8
dimensions	time, lat, lon
file_dimensions	time, lat, lon

scfv_unc#

Field	Value
_Unsigned	true
long_name	Unbiased Root Mean Square Error for Snow Cover Fraction Viewable
units	percent
valid_range	0, -2
actual_range	0, 100
flag_values	-51, -50, -46, -41, -4, -3, -2
flag_meanings	Cloud Polar_Night_or_Night Water Permanent_Snow_and_Ice Classification_failed Input_Data_Error No_Satellite_Acquisition
missing_value	-1
grid_mapping	spatial_ref
orig_data_type	uint8
fill_value	-1
size	4659120000000
shape	7190, 18000, 36000
chunk_sizes	1, 1385, 2770
file_chunk_sizes	1, 1385, 2770
data_type	uint8
dimensions	time, lat, lon
file_dimensions	time, lat, lon

spatial_ref#

Field	Value
spatial_ref	GEOGCS[\"WGS 84\",DATUM[\"WGS_1984\",SPHEROID[\"WGS 84\",6378137,298.257223563,AUTHORITY[\"EPSG\",\"7030\"]],AUTHORITY[\"EPSG\",\"6326\"]],PRIMEM[\"Greenwich\",0,AUTHORITY[\"EPSG\",\"8901\"]],UNIT[\"degree\",0.0174532925199433,AUTHORITY[\"EPSG\",\"9122\"]],AUTHORITY[\"EPSG\",\"4326\"]]
longitude_of_prime_meridian	0.0
semi_major_axis	6378137.0
inverse_flattening	298.257223563
grid_mapping_name	latitude_longitude
GeoTransform	-180 0.01 0 90 0 -0.01
orig_data_type	int32
fill_value	9223372036854775807
size	1
shape	1
chunk_sizes	1
file_chunk_sizes	1
data_type	int64
dimensions
file_dimensions

Full dataset metadata#

Field	Value
title	ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable snow (SCFV) from MODIS (2000 - 2019), version 1.0
source	TERRA MODIS, Collection 6.1: calibrated radiances 5-min L1B swath data, 1 km (MOD021KM) and geolocation fields 5-min L1A swath data, 1 km (MOD03)
history	2021-01-29: ESA snow_cci processing line SCFV, version 1.0
references	http://snow-cci.enveo.at/
product_version	1-0
comment	The following auxiliary data set is used for product generation: ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas are masked if more than 30 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map.
project	Climate Change Initiative - European Space Agency
ecv	SNOW
processing_level	L3C
product_string	MODIS_TERRA
data_type	SCFV
sensor_id	MODIS
platform_id	Terra
abstract	This dataset contains Daily Snow Cover Fraction of viewable snow from the MODIS satellite instruments, produced by the Snow project of the ESA Climate Change Initiative programme. Snow cover fraction viewable (SCFV) indicates the area of snow viewable from space over all land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. The global SCFV product is available at about 1 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included. The SCFV time series provides daily products for the period 2000 – 2019. The SCFV product is based on Moderate resolution Imaging Spectroradiometer (MODIS) data on-board the Terra satellite. The retrieval method of the snow_cci SCFV product from MODIS data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module developed by ENVEO. For the SCFV product generation from MODIS, multiple reflective and emissive spectral bands are used. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (Metsämäki et al., 2015). All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 550 nm and 1.6 µm, and an emissive band centred at about 11 µm. The snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFV retrieval method is applied. Improvements to the GlobSnow algorithm implemented for snow_cci version 1 include (i) the utilisation of a background reflectance map derived from statistical analyses of MODIS time series replacing the constant values for snow free ground used in the GlobSnow approach, and (ii) the adaptation of the retrieval method for mapping in forested areas the SCFV. Permanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the pixel spacing of the SCFV product. Water areas are masked if more than 30 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map. The product uncertainty for observed land pixels is provided as unbiased root mean square error (RMSE) per pixel in the ancillary variable. The SCFV product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology. ENVEO is responsible for the SCFV product development and generation from MODIS data, SYKE supported the development. There are a few days without any MODIS acquisitions in the years 2000, 2001, 2002, 2003, 2008, 2016 and 2018. On several days in the years 2000 to 2006, and on a few days in the years 2012, 2015 and 2016, the acquired MODIS data have either only limited coverage, or some of the MODIS data were corrupted during the download process. For these days, the SCFV products are available but have data gaps.
publication_date	2021-05-10T15:24:50
uuid	ef8eb5ff84994f2ca416dbb2df7f72c7
catalog_url	https://catalogue.ceda.ac.uk/uuid/ef8eb5ff84994f2ca416dbb2df7f72c7
cci_project	SNOW