Dataset: ESA Land Surface Temperature Climate Change Initiative (LST_cci): Monthly land surface temperature from MODIS (Moderate resolution Infra-red Spectroradiometer) on Aqua, level 3 collated (L3C) global product (2002-2018), version 3.00#
Dataset identifier: esacci.LST.mon.L3C.LST.MODIS.Aqua.MODISA.3-00.DAY
Data store: cciodp
How to open this dataset in AVL JupyterLab
cciodp_store = new_data_store('cciodp')
ds = cciodp_store.open_data('esacci.LST.mon.L3C.LST.MODIS.Aqua.MODISA.3-00.DAY')
Bounding box map#
cciodp_store = new_data_store('cciodp')
ds = cciodp_store.open_data('esacci.LST.mon.L3C.LST.MODIS.Aqua.MODISA.3-00.DAY')
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 | 2002-07-04 to 2018-12-31 |
| Time period | 1M |
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 |
|---|---|---|
| dtime | time difference from reference time | seconds |
| satze | satellite zenith angle | degrees |
| sataz | satellite azimuth angle | degrees |
| solze | solar zenith angle | degrees |
| solaz | solar azimuth angle | degrees |
| lst | land surface temperature | kelvin |
| lst_uncertainty | land surface temperature total uncertainty | kelvin |
| lst_unc_ran | uncertainty from uncorrelated errors | kelvin |
| lst_unc_loc_atm | uncertainty from locally correlated errors on atmospheric scales | kelvin |
| lst_unc_loc_sfc | uncertainty from locally correlated errors on surface scales | kelvin |
| lst_unc_sys | uncertainty from large-scale systematic errors | kelvin |
| lcc | land cover class | 1 |
| n | number of clear-sky pixels | [none] |
| variance | land surface temperature variance | kelvin |
Full variable metadata#
dtime#
| Field | Value |
|---|---|
| long_name | time difference from reference time |
| units | seconds |
| valid_min | 0.0 |
| valid_max | 2592000.0 |
| coordinates | lon lat |
| orig_data_type | float32 |
| fill_value | -32768.0 |
| size | 128304000000 |
| shape | 198, 18000, 36000 |
| chunk_sizes | 1, 1000, 1000 |
| file_chunk_sizes | 1, 1000, 1000 |
| data_type | float32 |
| dimensions | time, lat, lon |
| file_dimensions | time, lat, lon |
satze#
| Field | Value |
|---|---|
| long_name | satellite zenith angle |
| units | degrees |
| add_offset | 0.0 |
| scale_factor | 0.01 |
| valid_min | 0 |
| valid_max | 18000 |
| coordinates | lon lat |
| orig_data_type | int16 |
| fill_value | -32768 |
| size | 128304000000 |
| shape | 198, 18000, 36000 |
| chunk_sizes | 1, 1000, 1000 |
| file_chunk_sizes | 1, 1000, 1000 |
| data_type | int16 |
| dimensions | time, lat, lon |
| file_dimensions | time, lat, lon |
sataz#
| Field | Value |
|---|---|
| long_name | satellite azimuth angle |
| units | degrees |
| add_offset | 0.0 |
| scale_factor | 0.01 |
| valid_min | -18000 |
| valid_max | 18000 |
| coordinates | lon lat |
| orig_data_type | int16 |
| fill_value | -32768 |
| size | 128304000000 |
| shape | 198, 18000, 36000 |
| chunk_sizes | 1, 1000, 1000 |
| file_chunk_sizes | 1, 1000, 1000 |
| data_type | int16 |
| dimensions | time, lat, lon |
| file_dimensions | time, lat, lon |
solze#
| Field | Value |
|---|---|
| long_name | solar zenith angle |
| units | degrees |
| add_offset | 0.0 |
| scale_factor | 0.01 |
| valid_min | 0 |
| valid_max | 18000 |
| coordinates | lon lat |
| orig_data_type | int16 |
| fill_value | -32768 |
| size | 128304000000 |
| shape | 198, 18000, 36000 |
| chunk_sizes | 1, 1000, 1000 |
| file_chunk_sizes | 1, 1000, 1000 |
| data_type | int16 |
| dimensions | time, lat, lon |
| file_dimensions | time, lat, lon |
solaz#
| Field | Value |
|---|---|
| long_name | solar azimuth angle |
| units | degrees |
| add_offset | 0.0 |
| scale_factor | 0.01 |
| valid_min | -18000 |
| valid_max | 18000 |
| coordinates | lon lat |
| orig_data_type | int16 |
| fill_value | -32768 |
| size | 128304000000 |
| shape | 198, 18000, 36000 |
| chunk_sizes | 1, 1000, 1000 |
| file_chunk_sizes | 1, 1000, 1000 |
| data_type | int16 |
| dimensions | time, lat, lon |
| file_dimensions | time, lat, lon |
lst#
| Field | Value |
|---|---|
| long_name | land surface temperature |
| units | kelvin |
| add_offset | 273.15 |
| scale_factor | 0.01 |
| valid_min | -8315 |
| valid_max | 7685 |
| coordinates | lon lat |
| orig_data_type | int16 |
| fill_value | -32768 |
| size | 128304000000 |
| shape | 198, 18000, 36000 |
| chunk_sizes | 1, 1000, 1000 |
| file_chunk_sizes | 1, 1000, 1000 |
| data_type | int16 |
| dimensions | time, lat, lon |
| file_dimensions | time, lat, lon |
lst_uncertainty#
| Field | Value |
|---|---|
| long_name | land surface temperature total uncertainty |
| units | kelvin |
| add_offset | 0.0 |
| scale_factor | 0.001 |
| valid_min | 0 |
| valid_max | 10000 |
| coordinates | lon lat |
| orig_data_type | int16 |
| fill_value | -32768 |
| size | 128304000000 |
| shape | 198, 18000, 36000 |
| chunk_sizes | 1, 1000, 1000 |
| file_chunk_sizes | 1, 1000, 1000 |
| data_type | int16 |
| dimensions | time, lat, lon |
| file_dimensions | time, lat, lon |
lst_unc_ran#
| Field | Value |
|---|---|
| long_name | uncertainty from uncorrelated errors |
| units | kelvin |
| add_offset | 0.0 |
| scale_factor | 0.001 |
| valid_min | 0 |
| valid_max | 10000 |
| coordinates | lon lat |
| orig_data_type | int16 |
| fill_value | -32768 |
| size | 128304000000 |
| shape | 198, 18000, 36000 |
| chunk_sizes | 1, 1000, 1000 |
| file_chunk_sizes | 1, 1000, 1000 |
| data_type | int16 |
| dimensions | time, lat, lon |
| file_dimensions | time, lat, lon |
lst_unc_loc_atm#
| Field | Value |
|---|---|
| long_name | uncertainty from locally correlated errors on atmospheric scales |
| units | kelvin |
| add_offset | 0.0 |
| scale_factor | 0.001 |
| valid_min | 0 |
| valid_max | 10000 |
| coordinates | lon lat |
| orig_data_type | int16 |
| fill_value | -32768 |
| size | 128304000000 |
| shape | 198, 18000, 36000 |
| chunk_sizes | 1, 1000, 1000 |
| file_chunk_sizes | 1, 1000, 1000 |
| data_type | int16 |
| dimensions | time, lat, lon |
| file_dimensions | time, lat, lon |
lst_unc_loc_sfc#
| Field | Value |
|---|---|
| long_name | uncertainty from locally correlated errors on surface scales |
| units | kelvin |
| add_offset | 0.0 |
| scale_factor | 0.001 |
| valid_min | 0 |
| valid_max | 10000 |
| coordinates | lon lat |
| orig_data_type | int16 |
| fill_value | -32768 |
| size | 128304000000 |
| shape | 198, 18000, 36000 |
| chunk_sizes | 1, 1000, 1000 |
| file_chunk_sizes | 1, 1000, 1000 |
| data_type | int16 |
| dimensions | time, lat, lon |
| file_dimensions | time, lat, lon |
lst_unc_sys#
| Field | Value |
|---|---|
| long_name | uncertainty from large-scale systematic errors |
| units | kelvin |
| add_offset | 0.0 |
| scale_factor | 0.001 |
| valid_min | 0 |
| valid_max | 10000 |
| orig_data_type | int16 |
| fill_value | -32768 |
| size | 1 |
| shape | 1 |
| chunk_sizes | 1 |
| file_chunk_sizes | 1 |
| data_type | int16 |
| dimensions | length_scale |
| file_dimensions | length_scale |
lcc#
| Field | Value |
|---|---|
| long_name | land cover class |
| units | 1 |
| flag_meanings | cropland_rainfed cropland_rainfed_herbaceous_cover cropland_rainfed_tree_or_shrub_cover cropland_irrigated mosaic_cropland mosaic_natural_vegetation tree_broadleaved_evergreen_closed_to_open tree_broadleaved_deciduous_closed_to_open tree_broadleaved_deciduous_closed tree_broadleaved_deciduous_open tree_needleleaved_evergreen_closed_to_open tree_needleleaved_evergreen_closed tree_needleleaved_evergreen_open tree_needleleaved_deciduous_closed_to_open tree_needleleaved_deciduous_closed tree_needleleaved_deciduous_open tree_mixed mosaic_tree_and_shrub mosaic_herbaceous shrubland shrubland_evergreen shrubland_deciduous grassland lichens_and_mosses sparse_vegetation sparse_tree sparse_shrub sparse_herbaceous tree_cover_flooded_fresh_or_brakish_water tree_cover_flooded_saline_water shrub_or_herbaceous_cover_flooded urban Bare_areas_of_soil_types_not_contained_in_biomes_21_to_25 Unconsolidated_bare_areas_of_soil_types_not_contained_in_biomes_21_to_25 Consolidated_bare_areas_of_soil_types_not_contained_in_biomes_21_to_25 Bare_areas_of_soil_type_Entisols_Orthents Bare_areas_of_soil_type_Shifting_sand Bare_areas_of_soil_type_Aridisols_Calcids Bare_areas_of_soil_type_Aridisols_Cambids Bare_areas_of_soil_type_Gelisols_Orthels water snow_and_ice Sea_ice |
| flag_values | 10, 11, 12, 20, 30, 40, 50, 60, 61, 62, 70, 71, 72, 80, 81, 82, 90, 100, 110, 120, 121, 122, 130, 140, 150, 151, 152, 153, 160, 170, 180, 190, 200, 201, 202, 203, 204, 205, 206, 207, 210, 220, 230 |
| valid_min | 10 |
| valid_max | 230 |
| coordinates | lon lat |
| orig_data_type | int16 |
| fill_value | -32768 |
| size | 128304000000 |
| shape | 198, 18000, 36000 |
| chunk_sizes | 1, 1000, 1000 |
| file_chunk_sizes | 1, 1000, 1000 |
| data_type | int16 |
| dimensions | time, lat, lon |
| file_dimensions | time, lat, lon |
n#
| Field | Value |
|---|---|
| long_name | number of clear-sky pixels |
| valid_min | 0 |
| valid_max | 18750 |
| coordinates | lon lat |
| orig_data_type | int16 |
| fill_value | -32768 |
| size | 128304000000 |
| shape | 198, 18000, 36000 |
| chunk_sizes | 1, 1000, 1000 |
| file_chunk_sizes | 1, 1000, 1000 |
| data_type | int16 |
| dimensions | time, lat, lon |
| file_dimensions | time, lat, lon |
variance#
| Field | Value |
|---|---|
| long_name | land surface temperature variance |
| units | kelvin |
| add_offset | 0.0 |
| scale_factor | 0.01 |
| valid_min | 0 |
| valid_max | 10000 |
| coordinates | lon lat |
| orig_data_type | int16 |
| fill_value | -32768 |
| size | 128304000000 |
| shape | 198, 18000, 36000 |
| chunk_sizes | 1, 1000, 1000 |
| file_chunk_sizes | 1, 1000, 1000 |
| data_type | int16 |
| dimensions | time, lat, lon |
| file_dimensions | time, lat, lon |
Full dataset metadata#
| Field | Value |
|---|---|
| title | ESA Land Surface Temperature Climate Change Initiative (LST_cci): Monthly land surface temperature from MODIS (Moderate resolution Infra-red Spectroradiometer) on Aqua, level 3 collated (L3C) global product (2002-2018), version 3.00 |
| source | ESA LST CCI MODISA L3U V3.00 |
| history | Created using software developed at University of Leicester |
| references | https://climate.esa.int/en/projects/land-surface-temperature |
| product_version | 3-00 |
| comment | These data were produced as part of the ESA LST CCI project. |
| project | Climate Change Initiative - European Space Agency |
| ecv | LST |
| institute | University of Leicester |
| processing_level | L3C |
| product_string | MODISA |
| data_type | LST |
| sensor_id | MODIS |
| platform_id | Aqua |
| abstract | This dataset contains monthly-averaged land surface temperatures (LSTs) and their uncertainty estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Earth Observing System – Aqua (Aqua). Satellite land surface temperatures are skin temperatures which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water. Daytime and night-time temperatures are provided in separate files corresponding to the daytime and night-time Aqua equator crossing times which are 13:30 and 01:30 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class. The dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. MODIS achieves full Earth coverage nearly twice per day so the daily files have small gaps primarily close to the equator where the surface is not covered by the satellite swath on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface. Dataset coverage starts on 4th July 2002 and ends on 31st December 2018. There are minor interruptions (1-2 days) during satellite/instrument maintenance periods. The dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using a generalised split window retrieval algorithm and data were processed in the UoL processing chain. The dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards. |
| publication_date | 2022-06-27T15:12:48 |
| uuid | fe98aa1c666d42b9a2a0d19a72bb8a36 |
| catalog_url | https://catalogue.ceda.ac.uk/uuid/fe98aa1c666d42b9a2a0d19a72bb8a36 |
| cci_project | LST |