Dataset identifier: esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.1-1.S_AUSTRALIA
Data store: cciodp

How to open this dataset in AVL JupyterLab  

cciodp_store = new_data_store('cciodp')
ds = cciodp_store.open_data('esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.1-1.S_AUSTRALIA')

Bounding box map#

Bounding box map
Map tiles and data from OpenStreetMap, under the ODbL.

Basic information#

Parameter Value
Bounding box longitude (°) -30.0 to 160.0
Bounding box latitude (°) -45.0 to 60.0
Time range 2002-01-01 to 2019-12-31
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
distance_to_coast Distance to GSHHS 1.3 coastline m
local_sla_trend Geographical distribution of sea level trends mm/year
local_sla_trend_error Geographical distribution of sea level trends errors mm/year
sla [none] m

Full variable metadata#

distance_to_coast#

Field Value
long_name Distance to GSHHS 1.3 coastline
units m
distance_to_coast_min 4735.17
distance_to_coast_max 19990.3
comment Distance along track to a reference point at the coast
orig_data_type float32
fill_value 1.844674e+19
size 50
shape 50
chunk_sizes 50
file_chunk_sizes 50
data_type float32
dimensions nbpoints
file_dimensions nbpoints

local_sla_trend#

Field Value
long_name Geographical distribution of sea level trends
standard_name tendency_of_sea_surface_height_above_sea_level
units mm/year
comment Sea level trends computed from X-TRACK/ALES monthly sea level anomalies between 2002-06-01 and 2016-05-30
orig_data_type float32
fill_value 1.844674e+19
size 50
shape 50
chunk_sizes 50
file_chunk_sizes 50
data_type float32
dimensions nbpoints
file_dimensions nbpoints

local_sla_trend_error#

Field Value
long_name Geographical distribution of sea level trends errors
units mm/year
add_offset 0.0
scale_factor 1.0
orig_data_type float32
fill_value 1.844674e+19
size 50
shape 50
chunk_sizes 50
file_chunk_sizes 50
data_type float32
dimensions nbpoints
file_dimensions nbpoints

sla#

Field Value
units m
standard_name sea_surface_height_above_mean_sea_level
comment sla is monthly averaged and annual and semi-annual cycles are removed.
orig_data_type float32
fill_value 1.844674e+19
size 9600
shape 50, 192
chunk_sizes 50, 192
file_chunk_sizes 50, 192
data_type float32
dimensions nbpoints, nbcycle
file_dimensions nbpoints, nbcycle

Full dataset metadata#

Field Value
title ESA Sea Level Climate Change Initiative (Sea_Level_cci): A database of coastal sea level anomalies and associated trends from Jason satellite altimetry from 2002 to 2018
source Jason-1 GDR-E, Jason-2 GDR-D, Jason-3 GDR-D, RADS 4.0, ALES
history 2020-06-03 generated by X-TRACK v.1.06
references http://www.esa-sealevel-cci.org/products
product_version 1-1
comment These data were produced at LEGOS as part of the ESA SL_CCI+ project.
project Sea Level Climate Change Initiative – European Space Agency
ecv SEALEVEL
processing_level IND
product_string MERGED
data_type MSLTR
abstract This dataset contains 17-year-long (June 2002 to May 2018 ), high-resolution (20 Hz), along-track sea level dataset in coastal zones of six regions: Mediterranean Sea, Northeast Atlantic, West Africa, North Indian Ocean, Southeast Asia and Australia. Up to now, satellite altimetry has provided global gridded sea level time series up to 10-15 km from the coast only, preventing the estimation of how sea level changes very close to the coast on interannual to decadal time scales. This dataset has been derived from the ESA SL_cci+ v1.1 dataset of coastal sea level anomalies (also available in the catalogue, DOI:10.5270/esa-sl_cci-xtrack_ales_sla-200206_201805-v1.1-202005), which is based on the reprocessing of raw radar altimetry waveforms from the Jason-1, Jason-2 and Jason-3 satellite missions to derive satellite-sea surface ranges as close as possible to the coast (a process called ‘retracking’) and optimization of the geophysical corrections applied to the range measurements to produce sea level time series. This large amount of coastal sea level estimates has been further analysed to produce the present dataset: it consists in a selection of 429 portions of satellite tracks crossing land for which valid sea level time series are provided at monthly interval together with the associated sea level trends over the 17-year time span at each along-track 20-Hz point, from 20 km offshore to the coast. The main objective of this dataset is to analyze the sea level trends close to the coast and compare them with the sea level trends observed in the open ocean and to determine the causes of the potential differences. The product has been developed within the sea level project of the extension phase of the European Space Agency (ESA) Climate Change Initiative (SL_cci+). See 'The Climate Change Coastal Sea Level Team (2020). Sea level anomalies and associated trends estimated from altimetry from 2002 to 2018 at selected coastal sites. Scientific Data (Nature), in press'. This dataset has a DOI: https://doi.org/10.17882/74354
publication_date 2020-10-12T11:08:36
uuid a386504aa8ae492f9f2af04c109346e9
catalog_url https://catalogue.ceda.ac.uk/uuid/a386504aa8ae492f9f2af04c109346e9
sensor_id multi-sensor
platform_id multi-platform
cci_project SEALEVEL