{"info":{"_postman_id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","name":"DTN Marine Weather API","description":"
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DTN Marine Weather API is an all-in-one solution to integrate our marine weather data and analytics services into your systems. Utilising the latest cloud technology, we are able to tune our global suite of Metocean forecast models to match your needs. Models and forecast data are continuously validated, calibrated, and tuned to the latest observations, using satellite, buoy, and observation networks.

Use DTN Marine Weather API to unlock a library of maritime weather data, integrating high-resolution models from global and regional forecast runs on the fly. As additional capabilities launch in the DTN Marine Weather API solution, you can access these features without changing workflow, approach or product by automatically onboarding new product features into your existing account.

Integrated weather data can help you reduce the impact of weather. Improved access to accurate weather data also means faster decisions and streamlined internal communications. We offer an advanced API portfolio for marine, shipping, and offshore sectors. Get the weather data you need into your systems

Marine Weather API

Marine Weather API is a DTN product produced by DTN Utrecht and the Manta Team.

The API provides access to DTN Marine Content Services portfolio of products.

Datasets

The datasets available include

Manta Models

Manta is DTN new marine proprietary forecast engine, which utilises the latest cloud technology to run a global suite of marine forecast models with the ability to integrate high resolution models into global and regional forecast runs. We continuously verify output from our weather models using satellite, buoy and observation networks.

Manta Datasources

Manta dataset has an additional datasource property. You can specify different datasources when requesting information. The default used whenever the property is not specified is Global 6 minute resolution, our most comprehensive datasource. However for some specific use cases it may be better to use a specialized datasource. To know which datasources are available please contact your sales representative. Please note specialized datasources contain only certain parameters and cover only certain areas, therefore they should not be used unless your request has very specific requirements.

Manta Parameters

Please note that the availability flag states which parameters are available(A) or not available(NA). In case the parameters you are looking for figure as not available(NA), please contact your sales representative to request more information.

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parameter	description	units	category	Available as Hindcast Parameter
precipitation_probability	The probability of any precipitation at a given moment	1	precipitation
precipitation_amount_1h	The amount of precipitation in the past hour	mm	precipitation
precipitation_amount_3h	The amount of precipitation in the past 3 hours	mm	precipitation
precipitation_amount_6h	The amount of precipitation in the past 6 hours	mm	precipitation
air_pressure_mean_sea_level	-	Pa	pressure	✓
relative_humidity_2m	-	1	humidity
significant_wave_height_risk_p90	Total wave risk Upper limit of expected significant wave height, with 10% excess probability (90-percentile)	m	wave_windwave_swells	✓
windwave_significant_wave_height	Spectral approximation of the observed mean wave height of the largest 33% of the waves within a 20 minute window	m	wave_windwave_swells	✓
windwave_maximum_wave_height	Mean of 1% highest waves or 1.67 * Hm0 according to deep water Rayleigh distribution	m	wave_windwave_swells
windwave_mean_wave_period_tmm10	Tmm10 is usally meant when Tm is not fully specified and is particularly sensitive to energy in the lower frequency range	s	wave_windwave_swells	✓
windwave_mean_wave_period_tm02	Spectral approximation of the observed zero upcrossing wave period	s	wave_windwave_swells	✓
windwave_mean_wave_period_tm01	Tm01 is another candidate when Tm is not fully specified	s	wave_windwave_swells
windwave_peak_frequency	discrete or smoothed frequency of the group of waves with the highest energy	s-1	wave_windwave_swells
windwave_peak_period	discrete or smoothed inverse frequency of the group of waves with the highest energy	s	wave_windwave_swells	✓
windwave_mean_wave_direction	Mean direction where waves are arriving from. Mind the combination of multiple wavetrains	deg	wave_windwave_swells	✓
windwave_mean_wave_directional_spreading	Directional focus of waves	deg	wave_windwave_swells
windwave_peak_wave_directional_spreading	Peak directional focus of waves	deg	wave_windwave_swells
windwave_peak_wave_direction	Wave direction where dominant waves are arriving from	deg	wave_windwave_swells
windwave_mean_wave_length	On deep water(>500m) the mean wave length can be computed as 1.56Tmm10*2. Account for the dispersion relation on shallow water	m	wave_windwave_swells
windwave_mean_wave_steepness	null	m m-1	wave_windwave_swells
windwave_maximum_wave_steepness	null	m m-1	wave_windwave_swells
windwave_negative_first_frequency_moment	null	m2 s	wave_windwave_swells
windwave_zeroth_frequency_moment	null	m2	wave_windwave_swells
windwave_first_frequency_moment	null	m2 s-1	wave_windwave_swells
windwave_second_frequency_moment	null	m2 s-2	wave_windwave_swells
swell_1_of_1_significant_wave_height	Spectral approximation of the observed mean wave height of the largest 33% of the waves within a 20 minute window	m	wave_windwave_swells	✓
swell_1_of_1_maximum_wave_height	Mean of 1% highest waves or 1.67 * Hm0 according to deep water Rayleigh distribution	m	wave_windwave_swells
swell_1_of_1_mean_wave_period_tmm10	Tmm10 is usally meant when Tm is not fully specified and is particularly sensitive to energy in the lower frequency range	s	wave_windwave_swells	✓
swell_1_of_1_mean_wave_period_tm02	Spectral approximation of the observed zero upcrossing wave period	s	wave_windwave_swells	✓
swell_1_of_1_mean_wave_period_tm01	Tm01 is another candidate when Tm is not fully specified	s	wave_windwave_swells
swell_1_of_1_peak_frequency	discrete or smoothed frequency of the group of waves with the highest energy	s-1	wave_windwave_swells
swell_1_of_1_peak_period	discrete or smoothed inverse frequency of the group of waves with the highest energy	s	wave_windwave_swells	✓
swell_1_of_1_mean_wave_direction	Mean direction where waves are arriving from. Mind the combination of multiple wavetrains	deg	wave_windwave_swells	✓
swell_1_of_1_mean_wave_directional_spreading	Directional focus of waves	deg	wave_windwave_swells
swell_1_of_1_peak_wave_directional_spreading	Peak directional focus of waves	deg	wave_windwave_swells
swell_1_of_1_peak_wave_direction	Wave direction where dominant waves are arriving from	deg	wave_windwave_swells
swell_1_of_1_mean_wave_length	On deep water(>500m) the mean wave length can be computed as 1.56Tmm10*2. Account for the dispersion relation on shallow water	m	wave_windwave_swells
swell_1_of_1_mean_wave_steepness	null	m m-1	wave_windwave_swells
swell_1_of_1_maximum_wave_steepness	null	m m-1	wave_windwave_swells
swell_1_of_1_negative_first_frequency_moment	null	m2 s	wave_windwave_swells
swell_1_of_1_zeroth_frequency_moment	null	m2	wave_windwave_swells
swell_1_of_1_first_frequency_moment	null	m2 s-1	wave_windwave_swells
swell_1_of_1_second_frequency_moment	null	m2 s-2	wave_windwave_swells
swell_1_of_2_significant_wave_height	Spectral approximation of the observed mean wave height of the largest 33% of the waves within a 20 minute window	m	wave_windwave_swells
swell_1_of_2_maximum_wave_height	Mean of 1% highest waves or 1.67 * Hm0 according to deep water Rayleigh distribution	m	wave_windwave_swells
swell_1_of_2_mean_wave_period_tmm10	Tmm10 is usally meant when Tm is not fully specified and is particularly sensitive to energy in the lower frequency range	s	wave_windwave_swells
swell_1_of_2_mean_wave_period_tm02	Spectral approximation of the observed zero upcrossing wave period	s	wave_windwave_swells
swell_1_of_2_mean_wave_period_tm01	Tm01 is another candidate when Tm is not fully specified	s	wave_windwave_swells
swell_1_of_2_peak_frequency	discrete or smoothed frequency of the group of waves with the highest energy	s-1	wave_windwave_swells
swell_1_of_2_peak_period	discrete or smoothed inverse frequency of the group of waves with the highest energy	s	wave_windwave_swells
swell_1_of_2_mean_wave_direction	Mean direction where waves are arriving from. Mind the combination of multiple wavetrains	deg	wave_windwave_swells
swell_1_of_2_mean_wave_directional_spreading	Directional focus of waves	deg	wave_windwave_swells
swell_1_of_2_peak_wave_directional_spreading	Peak directional focus of waves	deg	wave_windwave_swells
swell_1_of_2_peak_wave_direction	Wave direction where dominant waves are arriving from	deg	wave_windwave_swells
swell_1_of_2_mean_wave_length	On deep water(>500m) the mean wave length can be computed as 1.56Tmm10*2. Account for the dispersion relation on shallow water	m	wave_windwave_swells
swell_1_of_2_mean_wave_steepness	null	m m-1	wave_windwave_swells
swell_1_of_2_maximum_wave_steepness	null	m m-1	wave_windwave_swells
swell_1_of_2_negative_first_frequency_moment	null	m2 s	wave_windwave_swells
swell_1_of_2_zeroth_frequency_moment	null	m2	wave_windwave_swells
swell_1_of_2_first_frequency_moment	null	m2 s-1	wave_windwave_swells
swell_1_of_2_second_frequency_moment	null	m2 s-2	wave_windwave_swells
swell_2_of_2_significant_wave_height	Spectral approximation of the observed mean wave height of the largest 33% of the waves within a 20 minute window	m	wave_windwave_swells
swell_2_of_2_maximum_wave_height	Mean of 1% highest waves or 1.67 * Hm0 according to deep water Rayleigh distribution	m	wave_windwave_swells
swell_2_of_2_mean_wave_period_tmm10	Tmm10 is usally meant when Tm is not fully specified and is particularly sensitive to energy in the lower frequency range	s	wave_windwave_swells
swell_2_of_2_mean_wave_period_tm02	Spectral approximation of the observed zero upcrossing wave period	s	wave_windwave_swells
swell_2_of_2_mean_wave_period_tm01	Tm01 is another candidate when Tm is not fully specified	s	wave_windwave_swells
swell_2_of_2_peak_frequency	discrete or smoothed frequency of the group of waves with the highest energy	s-1	wave_windwave_swells
swell_2_of_2_peak_period	discrete or smoothed inverse frequency of the group of waves with the highest energy	s	wave_windwave_swells
swell_2_of_2_mean_wave_direction	Mean direction where waves are arriving from. Mind the combination of multiple wavetrains	deg	wave_windwave_swells
swell_2_of_2_mean_wave_directional_spreading	Directional focus of waves	deg	wave_windwave_swells
swell_2_of_2_peak_wave_directional_spreading	Peak directional focus of waves	deg	wave_windwave_swells
swell_2_of_2_peak_wave_direction	Wave direction where dominant waves are arriving from	deg	wave_windwave_swells
swell_2_of_2_mean_wave_length	On deep water(>500m) the mean wave length can be computed as 1.56Tmm10*2. Account for the dispersion relation on shallow water	m	wave_windwave_swells
swell_2_of_2_mean_wave_steepness	null	m m-1	wave_windwave_swells
swell_2_of_2_maximum_wave_steepness	null	m m-1	wave_windwave_swells
swell_2_of_2_negative_first_frequency_moment	null	m2 s	wave_windwave_swells
swell_2_of_2_zeroth_frequency_moment	null	m2	wave_windwave_swells
swell_2_of_2_first_frequency_moment	null	m2 s-1	wave_windwave_swells
swell_2_of_2_second_frequency_moment	null	m2 s-2	wave_windwave_swells
swell_1_of_3_significant_wave_height	Spectral approximation of the observed mean wave height of the largest 33% of the waves within a 20 minute window	m	wave_windwave_swells
swell_1_of_3_maximum_wave_height	Mean of 1% highest waves or 1.67 * Hm0 according to deep water Rayleigh distribution	m	wave_windwave_swells
swell_1_of_3_mean_wave_period_tmm10	Tmm10 is usally meant when Tm is not fully specified and is particularly sensitive to energy in the lower frequency range	s	wave_windwave_swells
swell_1_of_3_mean_wave_period_tm02	Spectral approximation of the observed zero upcrossing wave period	s	wave_windwave_swells
swell_1_of_3_mean_wave_period_tm01	Tm01 is another candidate when Tm is not fully specified	s	wave_windwave_swells
swell_1_of_3_peak_frequency	discrete or smoothed frequency of the group of waves with the highest energy	s-1	wave_windwave_swells
swell_1_of_3_peak_period	discrete or smoothed inverse frequency of the group of waves with the highest energy	s	wave_windwave_swells
swell_1_of_3_mean_wave_direction	Mean direction where waves are arriving from. Mind the combination of multiple wavetrains	deg	wave_windwave_swells
swell_1_of_3_mean_wave_directional_spreading	Directional focus of waves	deg	wave_windwave_swells
swell_1_of_3_peak_wave_directional_spreading	Peak directional focus of waves	deg	wave_windwave_swells
swell_1_of_3_peak_wave_direction	Wave direction where dominant waves are arriving from	deg	wave_windwave_swells
swell_1_of_3_mean_wave_length	On deep water(>500m) the mean wave length can be computed as 1.56Tmm10*2. Account for the dispersion relation on shallow water	m	wave_windwave_swells
swell_1_of_3_mean_wave_steepness	null	m m-1	wave_windwave_swells
swell_1_of_3_maximum_wave_steepness	null	m m-1	wave_windwave_swells
swell_1_of_3_negative_first_frequency_moment	null	m2 s	wave_windwave_swells
swell_1_of_3_zeroth_frequency_moment	null	m2	wave_windwave_swells
swell_1_of_3_first_frequency_moment	null	m2 s-1	wave_windwave_swells
swell_1_of_3_second_frequency_moment	null	m2 s-2	wave_windwave_swells
swell_2_of_3_significant_wave_height	Spectral approximation of the observed mean wave height of the largest 33% of the waves within a 20 minute window	m	wave_windwave_swells
swell_2_of_3_maximum_wave_height	Mean of 1% highest waves or 1.67 * Hm0 according to deep water Rayleigh distribution	m	wave_windwave_swells
swell_2_of_3_mean_wave_period_tmm10	Tmm10 is usally meant when Tm is not fully specified and is particularly sensitive to energy in the lower frequency range	s	wave_windwave_swells
swell_2_of_3_mean_wave_period_tm02	Spectral approximation of the observed zero upcrossing wave period	s	wave_windwave_swells
swell_2_of_3_mean_wave_period_tm01	Tm01 is another candidate when Tm is not fully specified	s	wave_windwave_swells
swell_2_of_3_peak_frequency	discrete or smoothed frequency of the group of waves with the highest energy	s-1	wave_windwave_swells
swell_2_of_3_peak_period	discrete or smoothed inverse frequency of the group of waves with the highest energy	s	wave_windwave_swells
swell_2_of_3_mean_wave_direction	Mean direction where waves are arriving from. Mind the combination of multiple wavetrains	deg	wave_windwave_swells
swell_2_of_3_mean_wave_directional_spreading	Directional focus of waves	deg	wave_windwave_swells
swell_2_of_3_peak_wave_directional_spreading	Peak directional focus of waves	deg	wave_windwave_swells
swell_2_of_3_peak_wave_direction	Wave direction where dominant waves are arriving from	deg	wave_windwave_swells
swell_2_of_3_mean_wave_length	On deep water(>500m) the mean wave length can be computed as 1.56Tmm10*2. Account for the dispersion relation on shallow water	m	wave_windwave_swells
swell_2_of_3_mean_wave_steepness	null	m m-1	wave_windwave_swells
swell_2_of_3_maximum_wave_steepness	null	m m-1	wave_windwave_swells
swell_2_of_3_negative_first_frequency_moment	null	m2 s	wave_windwave_swells
swell_2_of_3_zeroth_frequency_moment	null	m2	wave_windwave_swells
swell_2_of_3_first_frequency_moment	null	m2 s-1	wave_windwave_swells
swell_2_of_3_second_frequency_moment	null	m2 s-2	wave_windwave_swells
swell_3_of_3_significant_wave_height	Spectral approximation of the observed mean wave height of the largest 33% of the waves within a 20 minute window	m	wave_windwave_swells
swell_3_of_3_maximum_wave_height	Mean of 1% highest waves or 1.67 * Hm0 according to deep water Rayleigh distribution	m	wave_windwave_swells
swell_3_of_3_mean_wave_period_tmm10	Tmm10 is usally meant when Tm is not fully specified and is particularly sensitive to energy in the lower frequency range	s	wave_windwave_swells
swell_3_of_3_mean_wave_period_tm02	Spectral approximation of the observed zero upcrossing wave period	s	wave_windwave_swells
swell_3_of_3_mean_wave_period_tm01	Tm01 is another candidate when Tm is not fully specified	s	wave_windwave_swells
swell_3_of_3_peak_frequency	discrete or smoothed frequency of the group of waves with the highest energy	s-1	wave_windwave_swells
swell_3_of_3_peak_period	discrete or smoothed inverse frequency of the group of waves with the highest energy	s	wave_windwave_swells
swell_3_of_3_mean_wave_direction	Mean direction where waves are arriving from. Mind the combination of multiple wavetrains	deg	wave_windwave_swells
swell_3_of_3_mean_wave_directional_spreading	Directional focus of waves	deg	wave_windwave_swells
swell_3_of_3_peak_wave_directional_spreading	Peak directional focus of waves	deg	wave_windwave_swells
swell_3_of_3_peak_wave_direction	Wave direction where dominant waves are arriving from	deg	wave_windwave_swells
swell_3_of_3_mean_wave_length	On deep water(>500m) the mean wave length can be computed as 1.56Tmm10*2. Account for the dispersion relation on shallow water	m	wave_windwave_swells
swell_3_of_3_mean_wave_steepness	null	m m-1	wave_windwave_swells
swell_3_of_3_maximum_wave_steepness	null	m m-1	wave_windwave_swells
swell_3_of_3_negative_first_frequency_moment	null	m2 s	wave_windwave_swells
swell_3_of_3_zeroth_frequency_moment	null	m2	wave_windwave_swells
swell_3_of_3_first_frequency_moment	null	m2 s-1	wave_windwave_swells
swell_3_of_3_second_frequency_moment	null	m2 s-2	wave_windwave_swells
negative_first_frequency_moment	null	m2 s	wave_spectral_moments
zeroth_frequency_moment	null	m2	wave_spectral_moments
first_frequency_moment	null	m2 s-1	wave_spectral_moments
second_frequency_moment	null	m2 s-2	wave_spectral_moments
total_cloud_cover	-	1	cloud
cloud_base_height	-	m	cloud
visibility	The visibility is the distance at which something can be seen.	m	visibility	✓
fog_probability	The probability of the visibility below 1000m	1	visibility
air_temperature_2m	-	K	temperature
air_temperature_10m	-	K	temperature
air_temperature_50m	-	K	temperature
air_temperature_100m	-	K	temperature
sea_temperature_0m	-	K	temperature	✓
dew_point_temperature_2m	-	K	temperature
freezing_level	The altitude in which the temperature is at 0 °C in a free atmosphere	m above ground	temperature
wind_u_component_10m	-	ms-1	wind
wind_v_component_10m	-	ms-1	wind
wind_speed_10m	-	ms-1	wind	✓
wind_speed_30m	-	ms-1	wind
wind_speed_50m	-	ms-1	wind
wind_speed_80m	-	ms-1	wind
wind_speed_110m	-	ms-1	wind
wind_speed_100m	-	ms-1	wind	✓
wind_speed_gust_10m	-	ms-1	wind	✓
wind_speed_gust_30m	-	ms-1	wind
wind_speed_gust_50m	-	ms-1	wind
wind_speed_gust_100m	-	ms-1	wind
wind_speed_10m_risk_p90	Upper limit of expected 10m average wind speed, with 10% excess probability (90-percentile)	ms-1	wind
wind_direction_10m	-	deg	wind	✓
wind_direction_50m	-	deg	wind
wind_direction_100m	-	deg	wind	✓
significant_wave_height	Spectral approximation of the observed mean wave height of the largest 33% of the waves within a 20 minute window	m	wave_total	✓
maximum_wave_height	Mean of 1% highest waves or 1.67 * Hm0 according to deep water Rayleigh distribution	m	wave_total	✓
mean_wave_period_tmm10	Tmm10 is usally meant when Tm is not fully specified and is particularly sensitive to energy in the lower frequency range	s	wave_total	✓
mean_wave_period_tm02	Spectral approximation of the observed zero upcrossing wave period	s	wave_total	✓
mean_wave_period_tm01	Tm01 is another candidate when Tm is not fully specified	s	wave_total
peak_frequency	discrete or smoothed frequency of the group of waves with the highest energy	s-1	wave_total
peak_period	discrete or smoothed inverse frequency of the group of waves with the highest energy	s	wave_total	✓
mean_wave_direction	Mean direction where waves are arriving from. Mind the combination of multiple wavetrains	deg	wave_total	✓
mean_wave_directional_spreading	Directional focus of waves	deg	wave_total
peak_wave_directional_spreading	Peak directional focus of waves	deg	wave_total
peak_wave_direction	Wave direction where dominant waves are arriving from	deg	wave_total
mean_wave_length	On deep water(>500m) the mean wave length can be computed as 1.56Tmm10*2. Account for the dispersion relation on shallow water	m	wave_total
mean_wave_steepness	null	m m-1	wave_total
maximum_wave_steepness	null	m m-1	wave_total
negative_first_frequency_moment	null	m2 s	wave_total
zeroth_frequency_moment	null	m2	wave_total
first_frequency_moment	null	m2 s-1	wave_total
second_frequency_moment	null	m2 s-2	wave_total
partition_1_of_6_significant_wave_height	Spectral approximation of the observed mean wave height of the largest 33% of the waves within a 20 minute window	m	wave_partitions	✓
partition_1_of_6_peak_period	discrete or smoothed inverse frequency of the group of waves with the highest energy	s	wave_partitions	✓
partition_1_of_6_mean_wave_direction	Mean direction where waves are arriving from. Mind the combination of multiple wavetrains	deg	wave_partitions	✓
partition_1_of_6_mean_wave_directional_spreading	Directional focus of waves	deg	wave_partitions
partition_2_of_6_significant_wave_height	Spectral approximation of the observed mean wave height of the largest 33% of the waves within a 20 minute window	m	wave_partitions
partition_2_of_6_peak_period	discrete or smoothed inverse frequency of the group of waves with the highest energy	s	wave_partitions
partition_2_of_6_mean_wave_direction	Mean direction where waves are arriving from. Mind the combination of multiple wavetrains	deg	wave_partitions
partition_2_of_6_mean_wave_directional_spreading	Directional focus of waves	deg	wave_partitions
partition_3_of_6_significant_wave_height	Spectral approximation of the observed mean wave height of the largest 33% of the waves within a 20 minute window	m	wave_partitions
partition_3_of_6_peak_period	discrete or smoothed inverse frequency of the group of waves with the highest energy	s	wave_partitions
partition_3_of_6_mean_wave_direction	Mean direction where waves are arriving from. Mind the combination of multiple wavetrains	deg	wave_partitions
partition_3_of_6_mean_wave_directional_spreading	Directional focus of waves	deg	wave_partitions
partition_4_of_6_significant_wave_height	Spectral approximation of the observed mean wave height of the largest 33% of the waves within a 20 minute window	m	wave_partitions
partition_4_of_6_peak_period	discrete or smoothed inverse frequency of the group of waves with the highest energy	s	wave_partitions
partition_4_of_6_mean_wave_direction	Mean direction where waves are arriving from. Mind the combination of multiple wavetrains	deg	wave_partitions
partition_4_of_6_mean_wave_directional_spreading	Directional focus of waves	deg	wave_partitions
partition_5_of_6_significant_wave_height	Spectral approximation of the observed mean wave height of the largest 33% of the waves within a 20 minute window	m	wave_partitions
partition_5_of_6_peak_period	discrete or smoothed inverse frequency of the group of waves with the highest energy	s	wave_partitions
partition_5_of_6_mean_wave_direction	Mean direction where waves are arriving from. Mind the combination of multiple wavetrains	deg	wave_partitions
partition_5_of_6_mean_wave_directional_spreading	Directional focus of waves	deg	wave_partitions
partition_6_of_6_significant_wave_height	Spectral approximation of the observed mean wave height of the largest 33% of the waves within a 20 minute window	m	wave_partitions
partition_6_of_6_peak_period	discrete or smoothed inverse frequency of the group of waves with the highest energy	s	wave_partitions
partition_6_of_6_mean_wave_direction	Mean direction where waves are arriving from. Mind the combination of multiple wavetrains	deg	wave_partitions
partition_6_of_6_mean_wave_directional_spreading	Directional focus of waves	deg	wave_partitions
geopotential_height_500hpa	Geopotential height at 500 hpa	hPa	atmospheric
northward_current	-	m s-1	oceanographic
eastward_current	-	m s-1	oceanographic
sea_surface_height	-	m	oceanographic
total_current_velocity	total current velocity from tidal and general ocean circulation	m.s-1	-	✓
total_current_to_direction	total current direction (oceanographic convention) from tidal and general ocean circulation	degrees	-	✓

Nautical MeteoBase

DTN Nautical MeteoBase [NMB] is the processor of Manta data. NMB is recognized as the most reliable system on the market and has formed the basis of all our products and services. The NMB technique uses a unique approach to blending global forecast models according to weighted algorithms with continuing verification. An optimized validated model mix is applied to improve forecast quality – where any inconsistences between the different wind and wave data sets are eliminated by harmonizing the data.

NMB Parameters

parameter	description	unit
mwd1	1 st swell direction The direction the dominant or primary swell component is coming from, reference True North	deg
swh1	1 st swell height Significant height of primary swell component	m
mwp1	1 st swell Tm mean period Mean period of the primary swell component	s
mwpp1	1 st swell Tp peak period Peak spectral period of the primary swell component	s
mwd2	2 nd swell direction The direction the secondary component is coming from, reference True North	deg
swh2	2 nd swell height Significant height of secondary swell component	m
mwp2	2nd swell mean period Mean period of the secondary swell component	m
mwpp2	2 nd swell Tp peak period Peak spectral period of the secondary well component	s
tt10	Air temperature at 10, 50, 100 m	C
tt50	Air temperature at 10, 50, 100 m	C
tt100	Air temperature at 10, 50, 100 m	C
nlc	Cloudbase (Low cloud fraction) Height of lowest cloud base with cover > 25%	classes
conf	Confidence Confidence level of the forecast in L (low), M (medium), H (high)	L, M, H dewpoint
frzlev	Freezing level The altitude in which the temperature is at 0 °C (the freezing point of water) in a free atmosphere	ft
p_th	Lightning probability (probability of thunder)	% and NIL, L, M, H ppp
pvv	Probability of fog	%
p_rrr	Probability of precipitation	%
rh	Relative humidity at 10m (RH)	%
ffrisk10x	Risk 10m wind speed Upper limit of expected 10m average wind speed, with 10% excess probability (90-percentile)	kt
ttw	Sea surface temperature	C
icing	Spray ice growth rate	enum(NIL, L, M, S, E)
curr_dir	Surface current direction The mean direction the surface current is going to, reference True North; the current is a combination of global ocean current and tidal current	deg to
curr_spd	Surface current speed The average surface current speed	kt
ds	Swell direction The mean direction the swells are coming from, reference True North	deg
hs	Swell height Significant swell height	m
ps	Swell Tm mean period Mean swell period, defined as the square root of the ratio of the inverse and zero wave moments, TM0,-1 (also known as mean wave period based on inverse moment)	s
tpswell	Swell Tp peak period Peak spectral period of the wind waves - period of wave with maximum wave energy, applied to wind wave spectrum	s
p2sw	Swell Tz zero crossing period Mean zero crossing period of swell - average time interval between similar direction crossings of mean water level, applied to the swell spectrum. Also referred to as \"mean spectral period\" or \"mean wave period based on second moment\"	s
ntot	Total cloud fraction (N)	Octa to %
htw	Total wave height Significant total wave height (Hs)	m
hmax_rayleigh	Total wave maximum height Rayleigh Largest expected single total wave height (equal to 1.86 multiplied by Hs) within 1000 wave cycles	m
htwx	Total wave maximum height Largest expected single total wave height (equal to 1.667 multiplied by Hs), with 1% excess probability (99-percentile)	m
mwd	Total wave mean direction The mean direction the wind waves are coming from, reference True North	deg
htwrisk	Total wave risk Upper limit of expected significant wave height, with 10% excess probability (90-percentile)	m
mwp	Total wave Tm mean period Mean wind wave period, defined as the square root of the ratio of the inverse and zero wave moments, TM0,-1 (also known as mean wave period based on inverse moment)	s
tp	Total wave Tp peak period Peak spectral period of total waves - period of wave with maximum wave energy, applied to entire wave spectrum	s
tz	Total wave Tz zero crossing period Mean zero crossing period of total waves - average time interval between similar direction crossings of mean water level, applied to the entire wave spectrum. Also referred to as \"mean spectral period\" or \"mean wave period based on second moment\"	s
unc	Uncertainty code	enum
vv	Visibility Horizontal visibility at 10m	classes
ww	Weather type	text
dd10	Wind direction Mean direction the wind is blowing from) at 10, reference True North	deg
dd50	Wind direction Mean direction the wind is blowing from) at 50, reference True North	deg
dd100	Wind direction Mean direction the wind is blowing from) at 100m reference True North	deg
ffg10	Wind gusts Highest 3 seconds duration wind speed) at 10m	kt
ffg50	Wind gusts Highest 3 seconds duration wind speed) at 50m	kt
ffg100	Wind gusts Highest 3 seconds duration wind speed) at 100m	kt
ff10	Wind speed 10 minutes average wind speed at 10m	kt
ff50	Wind speed 10 minutes average wind speed at 50m	kt
ff100	Wind speed 10 minutes average wind speed at 100m	kt
dw	Wind wave direction The mean direction the wind waves are coming from, reference True North	deg
hw	Wind wave height Significant wind wave height	m
pw	Wind wave Tm mean period Mean wind wave period, defined as the square root of the ratio of the inverse and zero wave moments, TM0,-1 (also known as mean wave period based on inverse moment)	s
tpsea	Wind wave Tp peak period Peak spectral period of the wind waves - period of wave with maximum wave energy, applied to wind wave spectrum	s
p2sea	Wind wave Tz zero crossing period Mean zero crossing period of swell - average time interval between similar direction crossings of mean water level, applied to the wind wave spectrum. Also referred to as \"mean spectral period\" or \"mean wave period based on second moment\"	s

Nautical

A lower resolution version of DTN NMB database, used for lower bandwidth requirements.

Nautical Parameters

parameter	description	unit
windSpeedInKnots	The speed of the wind at 10 meters above sea level (in knots), averaged over 10 minutes.	kt
windDirectionInDegrees	The direction from which the wind is blowing at 10 meters above sea level (in degrees).	deg
riskWindSpeedInKnots	Wind speed with a 10% exceedance probability (at 10 meters above sea level, in knots).	kt
windGustInKnots	The highest speed of the wind at 10 meters above sea level during the given hour, averaged over 3 seconds (in knots).	kt
windSpeedAt50MetersInKnots	Equivalent of windSpeedInKnots, but at 50 meters above sea level.	kt
windDirectionAt50MetersInDegrees	Equivalent of windDirectionInDegrees, but at 50 meters above sea level.	deg
windGustAt50MetersInKnots	Equivalent of windGustInKnots, but at 50 meters above sea level.	kt
seaHeightInMeters	The significant height of the wind waves (in meters).	m
seaPeriodInSeconds	The mean period of the wind waves (in seconds).	s
swellDirectionInDegrees	The mean direction from which swell waves are coming (in degrees).	deg
swellHeightInMeters	The significant height of swell waves (in meters).	m
swellPeriodInSeconds	The mean period of swell waves (in seconds).	s
totalWaveDirectionInDegrees	The mean direction from which all waves are coming (in degrees).	deg
totalWaveHeightInMeters	The total significant wave height, i.e. of all waves (in meters).	m
riskWaveHeightInMeters	The total significant wave height with a 10% exceedance probability (in meters).	m
seaCurrentSpeedInKnots	The mean speed with which water is moving at sea surface level (in knots).	kt
seaCurrentDirectionInDegrees	The mean direction into which water is moving at sea surface level (in degrees).	deg
seaTemperatureInCelsius	The water temperature at sea or lake surface (in degrees Celsius).	Cel
airTemperatureInCelsius	The air temperature at 2 meters height above surface level (in degrees Celsius).	Cel
airPressureInHectoPascal	The air pressure reduced to mean sea level (in hectoPascal).	hPa
heightOf500HectoPascalLevelInMeters	The height of the 500 hPa pressure level (in geopotential meters).	hPa
precipitationProbabilityInPercent	The likelihood that precipitation will occur during the given hour (percentage)	%
visibilityCode	Index of severity of visibility loss for a ship in this area. Possible values are: Good, Moderate/Good, Moderate, Poor/Moderate, Poor	text
visibility	The textual description of the visibility code.	nm
weatherCode	Index of the weather type in the area. Possible values are:Clear, Partly cloudy, Cloudy, Fog, Drizzle, Rain, Snow, Rain, Freezing rain	nmb
weather	The textual description of the weather code.	nmb
icingClass	Index of the severity of the growth of ice on a ship in this area.	text
icing	The textual description of the Icing class.	text

Layers Endpoint

Raster data tile available as a web service for Data visualisation.

Available layers include,

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

Layers	Technical name
Manta - Mean Sea level Pressure (every 2 hPa)	ISOLINE.mg-manta-production-output/air_pressure_mean_sea_level.default
Manta -Mean Sea level Pressure (every 4 hPa)	ISOLINE.mg-manta-production-output/4_mb_air_pressure_mean_sea_level.default
Manta -Visibility	VECTOR.mg-manta-production-output/dtn/manta/global/6min/visibility.default
Manta -Visibility values	GRID.mg-manta-production-output/dtn/manta/global/6min/visibility.default
Manta -Current speed	VECTOR.mg-manta-production-output/dtn/manta/global/6min/current_speed.default
Manta -Current speed values	GRID.mg-manta-production-output/dtn/manta/global/7p5min/current_speed.default
Manta -Current direction	WIND_SYMBOL.mg-manta-production-output/dtn/manta/global/7p5min/current_direction.default
Manta -Mean Wave Direction	WIND_SYMBOL.mg-manta-production-output/dtn/manta/global/6min/mean_wave_direction.default
Manta -Peak Wave period	VECTOR.mg-manta-production-output/dtn/manta/global/6min/peak_period.default
Manta -Significant wave height	VECTOR.mg-manta-production-output/dtn/manta/global/6min/significant_wave_height.default
Manta -Significant wave height values	GRID.mg-manta-production-output/dtn/manta/global/6min/significant_wave_height.default
Manta -Wind speed	VECTOR.mg-manta-production-output/dtn/manta/global/6min/wind_speed_10m.default
Manta -Wind speed values	GRID.mg-manta-production-output/dtn/manta/global/6min/wind_speed.default
Manta -Wind direction	WIND_SYMBOL.mg-manta-production-output/dtn/manta/global/6min/wind_symbol.default
Satellite - global infrared (GOES)	RASTER.obs-sat.mg.global-composite/data/ir.default
Satellite - North America visible (GOES)	RASTER.obs-sat.noaa.goes-east-75w.sh.s3.mg/north_america/vis.default
Satellite - North America infrared (GOES)	RASTER.obs-sat.noaa.goes-east-75w.sh.s3.mg/north_america/ir.default
Satellite - Europe visible (MeteoSat)	RASTER.obs-sat.ems.meteosat-0e/europe/proj/hrv.default
Satellite - Europe fog (MeteoSat)	RASTER.obs-sat.ems.meteosat-0e/europe/proj/eumetsat-rgb-composite-fog.default
Satellite - Europe infrared (MeteoSat)	RASTER.obs-sat.ems.meteosat-0e/europe/proj/ir108.default
Satellite - Europe water vapor (MeteoSat)	RASTER.obs-sat.ems.meteosat-0e/europe/proj/wv062.default
Precipitation - NASA global precipitation intensity	VECTOR.obs-radar.nasa.global-imerg/01x01/intensity.default

How it works?

It's a rest api, described with swagger and authenticated with oauth.

Overview

All users require DTN oauth clientid.
Swagger definition end point available
Dev json-ld support.

Authentication

Required auth token can be generated with client credentials via auth.weather.mg service.

Response Format

The service allows the default \"Accept\" header to specify which type of response is required.\nThe accepted values are:

application/json the response will be returned in JSON format
application/xml the response will be returned in xml format

if no Accept header is specified, the default response format is application/json.

Rate limit

Throttle presets based on client credentials.

Error Codes

Error Code Name	DTN Error Code	HTTP Status Code	ClientText
ErrNotImplemented	MDS-NI	202	not implemented yet
ErrInvalidBody	MDS-IB	400	invalid json provided
ErrInvalidInput	MDS-II	400	no forecast_time added in parameter
ErrInvalidInput	MDS-II	400	forecast_time' not validly parsed in query parameters
ErrInvalidInput	MDS-II	400	no geo_shape added in parameter
ErrInvalidInput	MDS-II	400	geo_shape' not validly parsed in query parameters
ErrNotFound	MDS-404	404	provided dataset was not found
ErrForbidden	MDS-403	403	access denied
ErrBackendUnavailable	MDS-BU	502	Unable to retrieve NMB forecast
ErrBackendUnavailable	MDS-BU	502	Unable to retrieve Nautical forecast
ErrNoRID	MDS-NORID	500
ErrThrottled	MDS-TMR	429	Too many requests
ErrGetRawPermissions	MDS-T-001	500
ErrCastPermissions	MDS-T-002	500
ErrDatabaseFail	MDS-T-003	500

Get Started

1. Acquire a client id.

DTN customer support team will provide your unique client ID through email. Testing the client id can occur immediately:

Start by accessing the Postman Collection in the top right of this web page.
Edit the collection by selecting the three dots
Click on Authorization
Select the bearer token and add your client id.
Request a token and click the update button.
Your collection is now active, by using the first GET request at the api/forecast endpoint you will receive a valid response for authorized access.

2. Choose a programming language

For programmatic access to the API we provide Postman API collection or alternatively you may choose from the developer examples shown below. The language you wish to use can be selected from a list of programming languages at the center top of the screen. See the Language dropdown menu: C#, Java, Python, etc.

3. Authenticate your API request

Our OAUTH 2.0 inspired authorization approach requires a Bearer token attached to all API requests based on your client id.

By using your client id and customer secret token send a simple REST post request, to DTN Auth Server, https://auth.weather.com

REST example for oauth token request:

POST https://auth.weather.mg/oauth/token\n\nRequest Headers\n    Content-Type: application/x-www-form-urlencoded\n    Authorization: Basic <<Custimer Secred Token>>\n    User-Agent: PostmanRuntime/7.24.1\n    Accept: */*\n    Cache-Control: no-cache\n    Postman-Token: c8053c0e-6944-4e95-9a9b-9f6b516936f4\n    Host: auth.weather.mg\n    Accept-Encoding: gzip, deflate, br\n    Connection: keep-alive\n    Content-Length: 36\nRequest Body\n    grant_type: \"client_credentials\"\n    scope: \"\"\n

Python example for oauth token request:

import requests, json\nimport subprocess\nimport sys\n\n# python 3.6\n\n# DTN Authorization Server providing token.\ntoken_url = \"https://auth.weather.mg/oauth/token\"\n\n# DTN Marine Forecast API.\ntest_api_url = \"https://api.production.prd.marineds.zones.dtn.com/forecast\"\n\n# Customer (application) credentials\nclient_id = '<Customer_Client_ID>'\nclient_secret = '<Customer_Secret_Token>'\n\n# Auth post request.\ndata = {'grant_type': 'client_credentials',\n        'scope': ''}\n\nprint(\"requesting access token\")\naccess_token_response = requests.post(token_url, data=data, verify=False, allow_redirects=False, auth=(client_id, client_secret))\n\n# Response received from auth server.\nprint(\"response\")\nprint(access_token_response.headers)\nprint('body: ' + access_token_response.text)\n\n# we can now use the access_token as much as we want to access protected resources.\ntokens = json.loads(access_token_response.text)\naccess_token = tokens['access_token']\nprint(\"access token: \" + access_token)\n\n# Testing authorised request from DTN server.\napi_call_headers = {'Authorization': 'Bearer ' + access_token}\napi_call_response = requests.get(test_api_url, headers=api_call_headers, verify=False)\n\nprint(api_call_response.text)\n

JAVA example for oauth token request:

HttpClient client= new DefaultHttpClient();\n\nHttpPost requestAuth = new HttpPost(\"https://auth.weather.mg/oauth/token\");\n// add request headers\nrequestAuth.addHeader(\"Authorization\", \"Basic <CustomerSecretToken>\");\nrequestAuth.setEntity(\"{'grant_type': 'client_credentials','scope': ''}\");\nclient.execute(requestAuth);\n\nHttpGet request = new HttpGet(\"https://api.production.prd.marineds.zones.dtn.com/forecast\");\n// add request headers\nrequest.addHeader(\"Authorization\", \"Bearer <ClientTokenReceived>\");\nclient.execute(request);\n

4. Validate access to the forecast api.

Validation endpoint is https://api.production.prd.marineds.zones.dtn.com/forecast. Auth token is required for this endpoint.

5. Postman Usage

Direct API access is available via the postman collection. Single click request examples are provided, including authentication, given that 4 enviromental variables are set.

{{api_url}}
{{client_id}}
{{client_secret}}
{{auth_server}}

6. Release Notes

v3.0 added new Manta parameters

v2.1 We released support for Spectra and Spectra images requests

v2.0 of the Marine Weather API, we released three key features: * Multiple poists: request forecasts for a line or a route or any form of multiple points within a single API request.

* Area requests: request gridded data within an area bounded by Lat/Lon points. The response is a NetCDF file containing all the data.

* Map layers: request map layer tiles that can be directly embedded within any mapping solutions like Mapbox or ArcGIS.

7. Try our features with the API requests below

\n","schema":"https://schema.getpostman.com/json/collection/v2.0.0/collection.json","toc":[{"content":"Marine Weather API","slug":"marine-weather-api"},{"content":"How it works?","slug":"how-it-works"},{"content":"Overview","slug":"overview"},{"content":"Get Started","slug":"get-started"}],"owner":"11810506","collectionId":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","publishedId":"T1DtfFjQ","public":true,"customColor":{"top-bar":"FFFFFF","right-sidebar":"303030","highlight":"FF6C37"},"publishDate":"2024-01-15T15:36:59.000Z"},"item":[{"name":"Start","item":[{"name":"Health Check","id":"0abb7c9e-8f21-484f-be5f-66c9b17f81a7","request":{"method":"GET","header":[],"url":"{{api_url}}/forecast","description":"

Utility and root endpoint for forecast api access. Serves as validation endpoint. Returns success if authorisation is validated.

Data request for Manta forecast, forecast time and geo shape query parameters used.\nExample parameters:\n - {{api_url}} = https://api.production.prd.marineds.zones.dtn.com\n - {{dataset}} = manta, nmb or nautical\n - {{forecastTime}} = 2020-10-30T00:00:00Z UTC Today rounded to hour \n - {{geoShape}} = POINT(42 -12) lon/lat at sea.

time of requested forecast, scope should be between last 24 hours to ten days from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

Geo point location in WKT Form e.g POINT(lon lat)

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(3.0 51.0)"}],"variable":[]}},"response":[],"_postman_id":"b1e949e7-de9a-4ce8-af1c-63dc791c42d1"}],"id":"e5d81786-9ae5-4ef6-9088-cdf8d8e85f7e","description":"

Begin with the following API requests

\n","_postman_id":"e5d81786-9ae5-4ef6-9088-cdf8d8e85f7e","auth":{"type":"oauth2","oauth2":{"basicConfig":[{"key":"accessToken","value":""}],"advancedConfig":[{"key":"useBrowser","value":""},{"key":"tokenType","value":""},{"key":"scope","value":""},{"key":"clientSecret","value":"{{client_secret}}"},{"key":"clientId","value":"{{client_id}}"},{"key":"accessTokenUrl","value":"{{auth_server}}"},{"key":"grant_type","value":""},{"key":"tokenName","value":""}]},"isInherited":true,"source":{"_postman_id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","name":"DTN Marine Weather API","type":"collection"}}},{"name":"Datasets","item":[{"name":"Manta","item":[{"name":"Manta request single forecast all parameters","id":"ae814182-9c83-4408-bff0-c26a2f93d8a7","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/manta?forecast_time={{isoTimeNow}}&geo_shape=POINT(-25.01 25.01)","description":"

Data request for Manta forecast, forecast time and geo shape query parameters used.

time of requested forecast, scope should be between last 24 hours to nine days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

geoshape of requested forecast, in wkt format. Make sure Longitude and Latitude are within the allowed intervals (Latitude must be within the -180,180 range and longitude must be within the -90,90 range). Please note the format is POINT(LONGITUDE LATITUDE) where the strings LONGITUDE and LATITUDE must be replaced by the respective numerical values.

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(-25.01 25.01)"}],"variable":[]}},"response":[],"_postman_id":"ae814182-9c83-4408-bff0-c26a2f93d8a7"},{"name":"Manta request parameters filter","event":[{"listen":"test","script":{"exec":["pm.test(\"Content-Type is present\", function () {"," pm.response.to.have.header(\"Content-Type\");","});","","// xml or json","//var jsonObject = xml2Json(responseBody);","","pm.test(\"Testumber of parameters received.\", function () {"," var jsonData = pm.response.json();",""," if (jsonData.data) {"," pm.expect(jsonData.data.items.dataset == \"manta\")"," tests['Data count: '+jsonData.data.items.length] = true;",""," var parm = jsonData.data.items[0].parameters"," tests['Parameter count: '+Object.keys(parm).length] = true;"," } else if (jsonData.error) {"," tests['Error count: '+jsonData.error.errors.length] = true"," }","});","",""],"type":"text/javascript"}}],"id":"0c7d0ce1-ad99-48b2-a1a7-8ab2762ad664","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/manta?forecast_time={{isoTimeNow}}&geo_shape=POINT(3.01 53.01)¶meters=significant_wave_height","description":"

Data request for Manta forecast, forecast time, geo shape and parameter filter query used.

time of requested forecast, scope should be between last 24 hours to nine days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(3.01 53.01)"},{"description":{"content":"

single parameter

\n","type":"text/plain"},"key":"parameters","value":"significant_wave_height"},{"disabled":true,"description":{"content":"

multiple wave parameters

\n","type":"text/plain"},"key":"parameters","value":"windwave_first_frequency_moment,windwave_maximum_wave_height,windwave_maximum_wave_steepness,windwave_mean_wave_direction,windwave_mean_wave_directional_spreading"}],"variable":[]}},"response":[],"_postman_id":"0c7d0ce1-ad99-48b2-a1a7-8ab2762ad664"},{"name":"Manta request spectra","event":[{"listen":"test","script":{"exec":["pm.test(\"Content-Type is present\", function () {"," pm.response.to.have.header(\"Content-Type\");","});","","// xml or json","//var jsonObject = xml2Json(responseBody);","","pm.test(\"Testumber of parameters received.\", function () {"," var jsonData = pm.response.json();",""," if (jsonData.data) {"," pm.expect(jsonData.data.items.dataset == \"manta\")"," tests['Data count: '+jsonData.data.items.length] = true;",""," var parm = jsonData.data.items[0].parameters"," tests['Parameter count: '+Object.keys(parm).length] = true;"," } else if (jsonData.error) {"," tests['Error count: '+jsonData.error.errors.length] = true"," }","});","",""],"type":"text/javascript"}}],"id":"03f5a26f-71e7-4ad1-8484-8c961d19b9e4","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/manta/spectra?forecast_time={{isoTimeNow}}&geo_shape=POINT(3.01 53.01)¶meters=spectra_2d","description":"

Data request for Manta's Wave Spectra forecasts: forecast time, geo shape and parameter filter query used.\nParameters include spectra_1d or spectra_2d. Output returned is a netcdf4 compliant file.

time of requested forecast, scope should be between last 24 hours to nine days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(3.01 53.01)"},{"description":{"content":"

spectral wave 2d

\n","type":"text/plain"},"key":"parameters","value":"spectra_2d"}],"variable":[]}},"response":[],"_postman_id":"03f5a26f-71e7-4ad1-8484-8c961d19b9e4"},{"name":"Manta request spectra Image","event":[{"listen":"test","script":{"exec":["pm.test(\"Content-Type is present\", function () {"," pm.response.to.have.header(\"Content-Type\");","});","","// xml or json","//var jsonObject = xml2Json(responseBody);","","pm.test(\"Testumber of parameters received.\", function () {"," var jsonData = pm.response.json();",""," if (jsonData.data) {"," pm.expect(jsonData.data.items.dataset == \"manta\")"," tests['Data count: '+jsonData.data.items.length] = true;",""," var parm = jsonData.data.items[0].parameters"," tests['Parameter count: '+Object.keys(parm).length] = true;"," } else if (jsonData.error) {"," tests['Error count: '+jsonData.error.errors.length] = true"," }","});","",""],"type":"text/javascript"}}],"id":"c3df7ba9-e5ad-404b-8def-a337333b6ce3","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[{"key":"Accept","value":"image/png","type":"text"}],"url":"{{api_url}}/forecast/dataset/manta/spectra?forecast_time={{isoTimeNow}}&geo_shape=POINT(3.01 53.01)¶meters=spectra_2d","description":"

Data request for Manta's Wave Spectra forecasts: forecast time, geo shape and parameter filter query used.\nParameters include spectra_1d or spectra_2d. Output returned is a zip file containing PNG compliant images.

time of requested forecast, scope should be between last 24 hours to nine days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(3.01 53.01)"},{"description":{"content":"

spectral wave 2d

\n","type":"text/plain"},"key":"parameters","value":"spectra_2d"}],"variable":[]}},"response":[],"_postman_id":"c3df7ba9-e5ad-404b-8def-a337333b6ce3"},{"name":"Manta request spectra LINESTRING","event":[{"listen":"test","script":{"exec":["pm.test(\"Content-Type is present\", function () {"," pm.response.to.have.header(\"Content-Type\");","});","","// xml or json","//var jsonObject = xml2Json(responseBody);","","pm.test(\"Testumber of parameters received.\", function () {"," var jsonData = pm.response.json();",""," if (jsonData.data) {"," pm.expect(jsonData.data.items.dataset == \"manta\")"," tests['Data count: '+jsonData.data.items.length] = true;",""," var parm = jsonData.data.items[0].parameters"," tests['Parameter count: '+Object.keys(parm).length] = true;"," } else if (jsonData.error) {"," tests['Error count: '+jsonData.error.errors.length] = true"," }","});","",""],"type":"text/javascript"}}],"id":"20463365-d37e-4144-adfe-b74c1ee7f9d6","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/manta/spectra?forecast_time={{isoTimeNow}}&geo_shape=LINESTRING(45.1 -9.2, 48.1 -9.2, 51 -9.2)¶meters=spectra_2d","description":"

Data request for Manta's Wave Spectra forecasts: forecast time, geo shape and parameter filter query used.\nParameters include spectra_1d or spectra_2d. Output returned is a netcdf4 compliant file.

time of requested forecast, scope should be between last 24 hours to nine days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

geoshape of requested forecast, in wkt format. Make sure Longitude and Latitude are within the allowed intervals (Latitude must be within the -180,180 range and longitude must be within the -90,90 range). Please note the format is LINESTRING(LONGITUDE LATITUDE,LONGITUDE LATITUDE, ...) where the strings LONGITUDE and LATITUDE must be replaced by the respective numerical values.

\n","type":"text/plain"},"key":"geo_shape","value":"LINESTRING(45.1 -9.2, 48.1 -9.2, 51 -9.2)"},{"description":{"content":"

spectral wave 2d

\n","type":"text/plain"},"key":"parameters","value":"spectra_2d"}],"variable":[]}},"response":[],"_postman_id":"20463365-d37e-4144-adfe-b74c1ee7f9d6"},{"name":"Manta request spectra POLYGON","event":[{"listen":"test","script":{"exec":["pm.test(\"Content-Type is present\", function () {"," pm.response.to.have.header(\"Content-Type\");","});","","// xml or json","//var jsonObject = xml2Json(responseBody);","","pm.test(\"Testumber of parameters received.\", function () {"," var jsonData = pm.response.json();",""," if (jsonData.data) {"," pm.expect(jsonData.data.items.dataset == \"manta\")"," tests['Data count: '+jsonData.data.items.length] = true;",""," var parm = jsonData.data.items[0].parameters"," tests['Parameter count: '+Object.keys(parm).length] = true;"," } else if (jsonData.error) {"," tests['Error count: '+jsonData.error.errors.length] = true"," }","});","",""],"type":"text/javascript"}}],"id":"82406c29-d7e7-453f-b0e2-0369e1710c18","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/manta/spectra?forecast_time={{isoTimeNow}}&geo_shape=POLYGON ((2 54.1, 3 54, 3 55, 2 55, 2 54.1))¶meters=spectra_2d","description":"

Data request for Manta's Wave Spectra forecasts: forecast time, geo shape and parameter filter query used.\nParameters include spectra_1d or spectra_2d. Output returned is a netcdf4 compliant file.

time of requested forecast, scope should be between last 24 hours to nine days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

geoshape of requested forecast, in wkt format. Make sure Longitude and Latitude are within the allowed intervals (Latitude must be within the -180,180 range and longitude must be within the -90,90 range). Please note the format is POLYGON((LONGITUDE LATITUDE,LONGITUDE LATITUDE, ...)) where the strings LONGITUDE and LATITUDE must be replaced by the respective numerical values.

\n","type":"text/plain"},"key":"geo_shape","value":"POLYGON ((2 54.1, 3 54, 3 55, 2 55, 2 54.1))"},{"description":{"content":"

spectral wave 2d

\n","type":"text/plain"},"key":"parameters","value":"spectra_2d"}],"variable":[]}},"response":[],"_postman_id":"82406c29-d7e7-453f-b0e2-0369e1710c18"},{"name":"Manta job request-POLYGON","event":[{"listen":"test","script":{"exec":[""],"type":"text/javascript"}}],"id":"592e7fc5-78be-400d-9019-9fa7d892df21","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/manta?forecast_time={{isoTimeNow}}&geo_shape=POLYGON ((2 54.1, 3 54, 3 55, 2 55, 2 54.1))¶meters=significant_wave_height","description":"

Data request for Manta forecast, forecast time, geo shape and parameter filter query used.

time of requested forecast, scope should be between last 24 hours to nine days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

geoshape of requested forecast, in wkt format. Make sure Longitude and Latitude are within the allowed intervals (Latitude must be within the -180,180 range and longitude must be within the -90,90 range). Please note the format is POLYGON((LONGITUDE LATITUDE,LONGITUDE LATITUDE, ...)) where the strings LONGITUDE and LATITUDE must be replaced by the respective numerical values.

\n","type":"text/plain"},"key":"geo_shape","value":"POLYGON ((2 54.1, 3 54, 3 55, 2 55, 2 54.1))"},{"description":{"content":"

only one parameter can be requested for polygons, other parameter options can be seen from parameters endpoint (as api/forecast/parameters/manta).

\n","type":"text/plain"},"key":"parameters","value":"significant_wave_height"}],"variable":[]}},"response":[],"_postman_id":"592e7fc5-78be-400d-9019-9fa7d892df21"},{"name":"Manta job request-LINESTRING","event":[{"listen":"test","script":{"exec":[""],"type":"text/javascript"}}],"id":"22770a45-d9d8-4c32-82e3-d8c7692f4fd4","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/manta?forecast_time={{isoTimeNow}}&geo_shape=LINESTRING(45.1 -9.2, 48.1 -9.2, 51 -9.2)¶meters=significant_wave_height","description":"

Data request for Manta forecast, forecast time, geo shape and parameter filter query used.

time of requested forecast, scope should be between last 24 hours to nine days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

geoshape of requested forecast, in wkt format. Make sure Longitude and Latitude are within the allowed intervals (Latitude must be within the -180,180 range and longitude must be within the -90,90 range). Please note the format is LINESTRING(LONGITUDE LATITUDE,LONGITUDE LATITUDE, ...) where the strings LONGITUDE and LATITUDE must be replaced by the respective numerical values.

\n","type":"text/plain"},"key":"geo_shape","value":"LINESTRING(45.1 -9.2, 48.1 -9.2, 51 -9.2)"},{"description":{"content":"

single parameter

\n","type":"text/plain"},"key":"parameters","value":"significant_wave_height"},{"disabled":true,"description":{"content":"

multiple wave parameters

\n","type":"text/plain"},"key":"parameters","value":"windwave_first_frequency_moment,windwave_maximum_wave_height,windwave_maximum_wave_steepness,windwave_mean_wave_direction,windwave_mean_wave_directional_spreading"}],"variable":[]}},"response":[],"_postman_id":"22770a45-d9d8-4c32-82e3-d8c7692f4fd4"},{"name":"Manta request unit conversion","event":[{"listen":"test","script":{"exec":["pm.test(\"Content-Type is present\", function () {"," pm.response.to.have.header(\"Content-Type\");","});","","// xml or json","//var jsonObject = xml2Json(responseBody);","","pm.test(\"Testumber of parameters received.\", function () {"," var jsonData = pm.response.json();",""," if (jsonData.data) {"," pm.expect(jsonData.data.items.dataset == \"manta\")"," tests['Data count: '+jsonData.data.items.length] = true;",""," var parm = jsonData.data.items[0].parameters"," tests['Parameter count: '+Object.keys(parm).length] = true;"," } else if (jsonData.error) {"," tests['Error count: '+jsonData.error.errors.length] = true"," }","});",""],"type":"text/javascript"}}],"id":"519c0ed6-44ff-4a33-96a5-9bdf1df6955a","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/manta?forecast_time={{isoTimeNow}}&geo_shape=POINT(-12 42)¶meters=significant_wave_height:ft","description":"

Data request for Nautical forecast, parameter unit conversion filter query used.

time of requested forecast, scope should be between last 24 hours to nine days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(-12 42)"},{"disabled":true,"description":{"content":"

wave height metric

\n","type":"text/plain"},"key":"parameters","value":"significant_wave_height:m"},{"description":{"content":"

wave height imperial

\n","type":"text/plain"},"key":"parameters","value":"significant_wave_height:ft"}],"variable":[]}},"response":[],"_postman_id":"519c0ed6-44ff-4a33-96a5-9bdf1df6955a"},{"name":"Manta request for timeseries","event":[{"listen":"test","script":{"exec":["pm.test(\"Content-Type is present\", function () {"," pm.response.to.have.header(\"Content-Type\");","});","","// xml or json","//var jsonObject = xml2Json(responseBody);","","pm.test(\"Testumber of parameters received.\", function () {"," var jsonData = pm.response.json();",""," if (jsonData.data) {"," pm.expect(jsonData.data.items.dataset == \"manta\")"," tests['Data count: '+jsonData.data.items.length] = true;",""," var parm = jsonData.data.items[0].parameters"," tests['Parameter count: '+Object.keys(parm).length] = true;"," } else if (jsonData.error) {"," tests['Error count: '+jsonData.error.errors.length] = true"," }","});",""],"type":"text/javascript"}},{"listen":"prerequest","script":{"exec":[""],"type":"text/javascript"}}],"id":"e0ee30ea-8d35-481c-9e9b-3b86e2722b2d","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/manta?forecast_time={{isoTimeNow}}&geo_shape=POINT(42 -12)&forecast_until={{isoTime10days}}&forecast_period=1h¶meters=significant_wave_height","description":"

Data request for Nautical forecast, forecast time and geo shape query parameters used.

forecast time iso utc

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(42 -12)"},{"description":{"content":"

latest time of requested forecast, it can be ten days in the future

\n","type":"text/plain"},"key":"forecast_until","value":"{{isoTime10days}}"},{"description":{"content":"

time between periods

\n","type":"text/plain"},"key":"forecast_period","value":"1h"},{"description":{"content":"

single parameter filter

\n","type":"text/plain"},"key":"parameters","value":"significant_wave_height"}],"variable":[]}},"response":[],"_postman_id":"e0ee30ea-8d35-481c-9e9b-3b86e2722b2d"},{"name":"Manta request Hindcast parameters filter","event":[{"listen":"test","script":{"id":"44695155-2e50-4d0f-99bb-d6e63b1dfb7d","exec":["pm.test(\"Content-Type is present\", function () {"," pm.response.to.have.header(\"Content-Type\");","});","","// xml or json","//var jsonObject = xml2Json(responseBody);","","pm.test(\"Testumber of parameters received.\", function () {"," var jsonData = pm.response.json();",""," if (jsonData.data) {"," pm.expect(jsonData.data.items.dataset == \"manta\")"," tests['Data count: '+jsonData.data.items.length] = true;",""," var parm = jsonData.data.items[0].parameters"," tests['Parameter count: '+Object.keys(parm).length] = true;"," } else if (jsonData.error) {"," tests['Error count: '+jsonData.error.errors.length] = true"," }","});","",""],"type":"text/javascript"}}],"id":"aa797acd-3929-4b8a-bf53-de83c53f97fa","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/hindcast/dataset/manta?start_time=2021-10-13T16:00:00Z&geo_shape=POINT(3.01 53.01)¶meters=significant_wave_height","description":"

Data request for Manta forecast, forecast time, geo shape and parameter filter query used.

time of requested hindcast, scope should be before last 24 hours

\n","type":"text/plain"},"key":"start_time","value":"2021-10-13T16:00:00Z"},{"description":{"content":"

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(3.01 53.01)"},{"description":{"content":"

single parameter

\n","type":"text/plain"},"key":"parameters","value":"significant_wave_height"}],"variable":[]}},"response":[],"_postman_id":"aa797acd-3929-4b8a-bf53-de83c53f97fa"},{"name":"Manta request Hindcast parameters filter [Job]","event":[{"listen":"test","script":{"id":"44695155-2e50-4d0f-99bb-d6e63b1dfb7d","exec":["pm.test(\"Content-Type is present\", function () {"," pm.response.to.have.header(\"Content-Type\");","});","","// xml or json","//var jsonObject = xml2Json(responseBody);","","pm.test(\"Testumber of parameters received.\", function () {"," var jsonData = pm.response.json();",""," if (jsonData.data) {"," pm.expect(jsonData.data.items.dataset == \"manta\")"," tests['Data count: '+jsonData.data.items.length] = true;",""," var parm = jsonData.data.items[0].parameters"," tests['Parameter count: '+Object.keys(parm).length] = true;"," } else if (jsonData.error) {"," tests['Error count: '+jsonData.error.errors.length] = true"," }","});","",""],"type":"text/javascript"}}],"id":"9d54fffd-070a-46f3-8ae6-78369e54c333","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/hindcast/dataset/manta?geo_shape=POINT(3.01 53.01)¶meters=significant_wave_height&start_time=2021-10-13T16:00:00Z&end_time=2021-10-20T23:00:00Z&time_period=1h","description":"

Data request for Manta forecast, forecast time, geo shape and parameter filter query used.

geoshape of requested hindcast, in wkt format. Make sure Longitude and Latitude are within the allowed intervals (Latitude must be within the -180,180 range and longitude must be within the -90,90 range). Please note the format is POINT(LONGITUDE LATITUDE) where the strings LONGITUDE and LATITUDE must be replaced by the respective numerical values.

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(3.01 53.01)"},{"description":{"content":"

single parameter

\n","type":"text/plain"},"key":"parameters","value":"significant_wave_height"},{"description":{"content":"

time of requested hindcast, scope should be before last 24 hours

\n","type":"text/plain"},"key":"start_time","value":"2021-10-13T16:00:00Z"},{"description":{"content":"

time of requested hindcast, scope should be before last 24 hours

\n","type":"text/plain"},"key":"end_time","value":"2021-10-20T23:00:00Z"},{"description":{"content":"

interval for sampling within the requested hindcast times

\n","type":"text/plain"},"key":"time_period","value":"1h"}],"variable":[]}},"response":[],"_postman_id":"9d54fffd-070a-46f3-8ae6-78369e54c333"}],"id":"2658dfdf-fc0a-4d11-b626-8a1756b3e1a9","description":"

Manta Dataset endpoint

\n","event":[{"listen":"prerequest","script":{"type":"text/javascript","exec":[""]}},{"listen":"test","script":{"type":"text/javascript","exec":[""]}}],"_postman_id":"2658dfdf-fc0a-4d11-b626-8a1756b3e1a9","auth":{"type":"oauth2","oauth2":{"basicConfig":[{"key":"accessToken","value":""}],"advancedConfig":[{"key":"useBrowser","value":""},{"key":"tokenType","value":""},{"key":"scope","value":""},{"key":"clientSecret","value":"{{client_secret}}"},{"key":"clientId","value":"{{client_id}}"},{"key":"accessTokenUrl","value":"{{auth_server}}"},{"key":"grant_type","value":""},{"key":"tokenName","value":""}]},"isInherited":true,"source":{"_postman_id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","name":"DTN Marine Weather API","type":"collection"}}},{"name":"NMB","item":[{"name":"NMB request single forecast all parameters","id":"1e5ea7a5-4776-476f-80ff-b2cdcc99b610","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/nmb?forecast_time={{isoTimeNow}}&geo_shape=POINT(42.0 -12.0)","description":"

Data request for NMB forecast, forecast time and geo shape query parameters used.

time of requested forecast, scope should be between last 24 hours to ten days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(42.0 -12.0)"}],"variable":[]}},"response":[],"_postman_id":"1e5ea7a5-4776-476f-80ff-b2cdcc99b610"},{"name":"NMB request parameter filter","id":"fbe53bef-4f7a-4643-94b3-bce0deb36daa","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/nmb?forecast_time={{isoTimeNow}}&geo_shape=POINT(3.0 51.0)¶meters=dd10¶meters=ff10","description":"

Data request for NMB forecast, parameters filter used in query.

time of requested forecast, scope should be between last 24 hours to ten days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(3.0 51.0)"},{"description":{"content":"

parameter filter

\n","type":"text/plain"},"key":"parameters","value":"dd10"},{"description":{"content":"

parameter filter

\n","type":"text/plain"},"key":"parameters","value":"ff10"}],"variable":[]}},"response":[],"_postman_id":"fbe53bef-4f7a-4643-94b3-bce0deb36daa"},{"name":"NMB request unit conversion","id":"ad928124-4292-4450-9488-eb775ab70aab","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/nmb?forecast_time={{isoTimeNow}}&geo_shape=POINT(3.0 51.0)¶meters=dd10¶meters=ff10:m/s","description":"

Data request for NMB forecast, unit conversion used in query request.

time of requested forecast, scope should be between last 24 hours to ten days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(3.0 51.0)"},{"description":{"content":"

parameter filter

\n","type":"text/plain"},"key":"parameters","value":"dd10"},{"description":{"content":"

parameter filter unit conversion

\n","type":"text/plain"},"key":"parameters","value":"ff10:m/s"}],"variable":[]}},"response":[],"_postman_id":"ad928124-4292-4450-9488-eb775ab70aab"},{"name":"NMB request timeseries","event":[{"listen":"prerequest","script":{"exec":["var moment = require(\"moment\")","","pm.environment.set(\"isoTimestamp10days\", moment().add(10,\"days\").toISOString());",""],"type":"text/javascript"}},{"listen":"test","script":{"exec":["pm.test(\"Content-Type is present\", function () {"," pm.response.to.have.header(\"Content-Type\");","});","","// xml or json","//var jsonObject = xml2Json(responseBody);","","pm.test(\"Testumber of parameters received.\", function () {"," var jsonData = pm.response.json();",""," if (jsonData.data) {"," pm.expect(jsonData.data.items.dataset == \"manta\")"," tests['Data count: '+jsonData.data.items.length] = true;",""," var parm = jsonData.data.items[0].parameters"," tests['Parameter count: '+Object.keys(parm).length] = true;"," } else if (jsonData.error) {"," tests['Error count: '+jsonData.error.errors.length] = true"," }","});",""],"type":"text/javascript"}}],"id":"54abbfc5-f531-4994-b5f5-489fe67c33e6","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/nmb?forecast_time={{isoTimeNow}}&geo_shape=POINT(42 -12)&forecast_until={{isoTime10days}}&forecast_period=1h¶meters=tt10","description":"

Data request for NMB forecast, forecast time and geo shape query parameters used.

time of requested forecast, scope should be between last 24 hours to ten days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(42 -12)"},{"description":{"content":"

latest time of requested forecast, it can be ten days later at last

\n","type":"text/plain"},"key":"forecast_until","value":"{{isoTime10days}}"},{"description":{"content":"

time step

\n","type":"text/plain"},"key":"forecast_period","value":"1h"},{"description":{"content":"

parameter filter

\n","type":"text/plain"},"key":"parameters","value":"tt10"}],"variable":[]}},"response":[],"_postman_id":"54abbfc5-f531-4994-b5f5-489fe67c33e6"}],"id":"b41c2878-474f-44aa-bb68-998ab6c83392","description":"

NMB Dataset Endpoints

\n","event":[{"listen":"prerequest","script":{"type":"text/javascript","exec":[""]}},{"listen":"test","script":{"type":"text/javascript","exec":[""]}}],"_postman_id":"b41c2878-474f-44aa-bb68-998ab6c83392","auth":{"type":"oauth2","oauth2":{"basicConfig":[{"key":"accessToken","value":""}],"advancedConfig":[{"key":"useBrowser","value":""},{"key":"tokenType","value":""},{"key":"scope","value":""},{"key":"clientSecret","value":"{{client_secret}}"},{"key":"clientId","value":"{{client_id}}"},{"key":"accessTokenUrl","value":"{{auth_server}}"},{"key":"grant_type","value":""},{"key":"tokenName","value":""}]},"isInherited":true,"source":{"_postman_id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","name":"DTN Marine Weather API","type":"collection"}}},{"name":"Nautical","item":[{"name":"Nautical request single forecast all parameters","id":"39ccee36-5a99-48f3-9e81-9bfdecbf6100","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/nautical?forecast_time={{isoTimeNow}}&geo_shape=POINT(3.01 51.01)","description":"

Data request for Nautical forecast, forecast time and geo shape query parameters used.

time of requested forecast, scope should be between last 24 hours to nine days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(3.01 51.01)"}],"variable":[]}},"response":[],"_postman_id":"39ccee36-5a99-48f3-9e81-9bfdecbf6100"},{"name":"Nautical request parameters filter","id":"64b00465-8e71-4ab6-a3fe-cbbb1517cdc6","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/nautical?forecast_time={{isoTimeNow}}&geo_shape=POINT(170.1 1)¶meters=airPressureInHectoPascal,swellHeightInMeters","description":"

Data request for Nautical forecast, forecast time, geo shape and parameter filter query used.

time of requested forecast, scope should be between last 24 hours to nine days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(170.1 1)"},{"description":{"content":"

parameter filter

\n","type":"text/plain"},"key":"parameters","value":"airPressureInHectoPascal,swellHeightInMeters"},{"disabled":true,"description":{"content":"

parameter filter

\n","type":"text/plain"},"key":"parameters","value":"swellHeightInMeters"},{"disabled":true,"description":{"content":"

parameter filter

\n","type":"text/plain"},"key":"parameters","value":"ff"}],"variable":[]}},"response":[],"_postman_id":"64b00465-8e71-4ab6-a3fe-cbbb1517cdc6"},{"name":"Nautical request unit conversion","id":"15a5ae4d-9e91-49b3-b594-d3e017aa97c8","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/nautical?forecast_time={{isoTimeNow}}&geo_shape=POINT(173.0 0.0)¶meters=windSpeedInKnots:m/s","description":"

Data request for Nautical forecast, parameter unit conversion filter query used.

time of requested forecast, scope should be between last 24 hours to nine days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(173.0 0.0)"},{"description":{"content":"

wind m/s

\n","type":"text/plain"},"key":"parameters","value":"windSpeedInKnots:m/s"},{"disabled":true,"description":{"content":"

wind km/h

\n","type":"text/plain"},"key":"parameters","value":"windSpeedInKnots:km/h"},{"disabled":true,"description":{"content":"

wind knots

\n","type":"text/plain"},"key":"parameters","value":"windSpeedInKnots:mph"},{"disabled":true,"description":{"content":"

parameter filter

\n","type":"text/plain"},"key":"parameters","value":"windSpeedInKnots"},{"disabled":true,"description":{"content":"

parameter filter unit conversion

\n","type":"text/plain"},"key":"parameters","value":"icing:m/s"}],"variable":[]}},"response":[],"_postman_id":"15a5ae4d-9e91-49b3-b594-d3e017aa97c8"},{"name":"Nautical request timeseries","event":[{"listen":"prerequest","script":{"exec":[""],"type":"text/javascript"}}],"id":"686416f8-8ced-4731-81e2-5dd8bca3e203","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/dataset/nautical?forecast_time={{isoTimeNow}}&geo_shape=POINT(3.01 51.0)&forecast_until={{isoTime9days}}&forecast_period=12h¶meters=airTemperatureInCelsius","description":"

Data request for Nautical forecast, forecast time and geo shape query parameters used.

time of requested forecast, scope should be between last 24 hours to nine days later from now

\n","type":"text/plain"},"key":"forecast_time","value":"{{isoTimeNow}}"},{"description":{"content":"

\n","type":"text/plain"},"key":"geo_shape","value":"POINT(3.01 51.0)"},{"description":{"content":"

latest time of requested forecast, it can be ten days later at last

\n","type":"text/plain"},"key":"forecast_until","value":"{{isoTime9days}}"},{"description":{"content":"

time period

\n","type":"text/plain"},"key":"forecast_period","value":"12h"},{"description":{"content":"

parameter filter

\n","type":"text/plain"},"key":"parameters","value":"airTemperatureInCelsius"}],"variable":[]}},"response":[],"_postman_id":"686416f8-8ced-4731-81e2-5dd8bca3e203"}],"id":"256bf5ad-0bb9-4d85-a293-fff24dae4f57","description":"

Nautical Dataset enpoints

\n","event":[{"listen":"prerequest","script":{"type":"text/javascript","exec":[""]}},{"listen":"test","script":{"type":"text/javascript","exec":[""]}}],"_postman_id":"256bf5ad-0bb9-4d85-a293-fff24dae4f57","auth":{"type":"oauth2","oauth2":{"basicConfig":[{"key":"accessToken","value":""}],"advancedConfig":[{"key":"useBrowser","value":""},{"key":"tokenType","value":""},{"key":"scope","value":""},{"key":"clientSecret","value":"{{client_secret}}"},{"key":"clientId","value":"{{client_id}}"},{"key":"accessTokenUrl","value":"{{auth_server}}"},{"key":"grant_type","value":""},{"key":"tokenName","value":""}]},"isInherited":true,"source":{"_postman_id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","name":"DTN Marine Weather API","type":"collection"}}}],"id":"48671537-ad95-4b63-b1bd-2671e53d49d7","description":"

API endpoint serving DTN weather datasets

\n","event":[{"listen":"prerequest","script":{"type":"text/javascript","exec":[""]}},{"listen":"test","script":{"type":"text/javascript","exec":[""]}}],"_postman_id":"48671537-ad95-4b63-b1bd-2671e53d49d7","auth":{"type":"oauth2","oauth2":{"basicConfig":[{"key":"accessToken","value":""}],"advancedConfig":[{"key":"useBrowser","value":""},{"key":"tokenType","value":""},{"key":"scope","value":""},{"key":"clientSecret","value":"{{client_secret}}"},{"key":"clientId","value":"{{client_id}}"},{"key":"accessTokenUrl","value":"{{auth_server}}"},{"key":"grant_type","value":""},{"key":"tokenName","value":""}]},"isInherited":true,"source":{"_postman_id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","name":"DTN Marine Weather API","type":"collection"}}},{"name":"Layers","item":[{"name":"Tile metadata","id":"1ebece00-bc58-4d6c-be1e-92ab88d475ff","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/layers/metadata?layerIds=VECTOR.mg-fcst-nwp-ecmwf-hres-prod-euw1/0.125x0.125-global/air_temperature.default&attributes=availableIssueTimes,latestFullIssueTime,legends,licenseInformation,style","description":"

Description endpoint for tiled raster images of Manta data.

Layer service endpoint for tiled raster images of Manta data.

forecast issue time filter

\n","type":"text/plain"},"key":"issueTime","value":"2020-10-27T00:00:00Z"},{"key":"layerIds","value":"VECTOR.mg-fcst-nwp-ecmwf-hres-prod-euw1/0.125x0.125-global/air_temperature.default"}],"variable":[]}},"response":[],"_postman_id":"c130cee0-c1de-4b14-a5eb-fd6108f646d4"}],"id":"f088d74f-a693-4efe-bbd9-71fb78da8d40","description":"

API endpoint serving tile and raster data for Manta datasets.

\n","event":[{"listen":"prerequest","script":{"type":"text/javascript","exec":[""]}},{"listen":"test","script":{"type":"text/javascript","exec":[""]}}],"_postman_id":"f088d74f-a693-4efe-bbd9-71fb78da8d40","auth":{"type":"oauth2","oauth2":{"basicConfig":[{"key":"accessToken","value":""}],"advancedConfig":[{"key":"useBrowser","value":""},{"key":"tokenType","value":""},{"key":"scope","value":""},{"key":"clientSecret","value":"{{client_secret}}"},{"key":"clientId","value":"{{client_id}}"},{"key":"accessTokenUrl","value":"{{auth_server}}"},{"key":"grant_type","value":""},{"key":"tokenName","value":""}]},"isInherited":true,"source":{"_postman_id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","name":"DTN Marine Weather API","type":"collection"}}},{"name":"Jobs","item":[{"name":"Summary of requested jobs","id":"5b806f3f-6ecf-430a-9e8c-cf4157993489","request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/jobs","description":"

All jobs pending or available accessable by api.

Asyncronous job request requested for processing by api.

API Endpont serving asyncronous workflow for time restricted jobs. Route and polygon data is computed.

\n","event":[{"listen":"prerequest","script":{"type":"text/javascript","exec":[""]}},{"listen":"test","script":{"type":"text/javascript","exec":[""]}}],"_postman_id":"83bed392-10e2-40a5-acdf-bbc74242b02a","auth":{"type":"oauth2","oauth2":{"basicConfig":[{"key":"accessToken","value":""}],"advancedConfig":[{"key":"useBrowser","value":""},{"key":"tokenType","value":""},{"key":"scope","value":""},{"key":"clientSecret","value":"{{client_secret}}"},{"key":"clientId","value":"{{client_id}}"},{"key":"accessTokenUrl","value":"{{auth_server}}"},{"key":"grant_type","value":""},{"key":"tokenName","value":""}]},"isInherited":true,"source":{"_postman_id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","name":"DTN Marine Weather API","type":"collection"}}},{"name":"Utils","item":[{"name":"parameters","item":[{"name":"api/forecast/parameters","id":"6a51e158-53a5-493e-9042-55c48a7129b8","request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/parameters","description":"

Parameters endpoint, request full list of dataset parameters available.

Request full list of NMB parameters.

Request full list of Nautical/SPOS parameters.

API endpoint serving all parameters available in Marine Data Service datasets.

\n","event":[{"listen":"prerequest","script":{"type":"text/javascript","exec":[""]}},{"listen":"test","script":{"type":"text/javascript","exec":[""]}}],"_postman_id":"7f29510e-deb8-4298-a25d-06ca8cc1c51d","auth":{"type":"oauth2","oauth2":{"basicConfig":[{"key":"accessToken","value":""}],"advancedConfig":[{"key":"useBrowser","value":""},{"key":"tokenType","value":""},{"key":"scope","value":""},{"key":"clientSecret","value":"{{client_secret}}"},{"key":"clientId","value":"{{client_id}}"},{"key":"accessTokenUrl","value":"{{auth_server}}"},{"key":"grant_type","value":""},{"key":"tokenName","value":""}]},"isInherited":true,"source":{"_postman_id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","name":"DTN Marine Weather API","type":"collection"}}},{"name":"api/forecast/swagger","id":"19489357-fc96-402e-b590-5da05301c409","request":{"method":"GET","header":[],"url":"{{api_url}}/forecast/swagger","description":"

Util endpoint provides Swagger/OpenAPI3.0 rest specification for the instance of the api. Use to generate API clients.

Lists all datasets and related metadata content provided for this version of the forecast api.

Full list of units used by with dataset parameters. WMO and CF convention covered.

Util endpoint serving a vocabulary of terms used within api datasets.

API endpoints serving metadata information and API utilities.

\n","event":[{"listen":"prerequest","script":{"type":"text/javascript","exec":[""]}},{"listen":"test","script":{"type":"text/javascript","exec":[""]}}],"_postman_id":"7995ee7a-4cbb-4573-a1ac-ecb46e0523f9","auth":{"type":"oauth2","oauth2":{"basicConfig":[{"key":"accessToken","value":""}],"advancedConfig":[{"key":"useBrowser","value":""},{"key":"tokenType","value":""},{"key":"scope","value":""},{"key":"clientSecret","value":"{{client_secret}}"},{"key":"clientId","value":"{{client_id}}"},{"key":"accessTokenUrl","value":"{{auth_server}}"},{"key":"grant_type","value":""},{"key":"tokenName","value":""}]},"isInherited":true,"source":{"_postman_id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","name":"DTN Marine Weather API","type":"collection"}}},{"name":"Hurricanes","item":[{"name":"Hurricanes","id":"b6357ed7-df04-47be-ab14-15ce5ca4a5e1","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"GET","header":[],"url":"{{api_url}}/hurricanes","description":"

Utility and root endpoint for forecast api access. Serves as validation endpoint. Returns success if authorisation is validated.

\n","auth":{"type":"oauth2","oauth2":{"basicConfig":[{"key":"accessToken","value":""}],"advancedConfig":[{"key":"useBrowser","value":""},{"key":"tokenType","value":""},{"key":"scope","value":""},{"key":"clientSecret","value":"{{client_secret}}"},{"key":"clientId","value":"{{client_id}}"},{"key":"accessTokenUrl","value":"{{auth_server}}"},{"key":"grant_type","value":""},{"key":"tokenName","value":""}]},"isInherited":true,"source":{"_postman_id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","name":"DTN Marine Weather API","type":"collection"}},"urlObject":{"path":["hurricanes"],"host":["{{api_url}}"],"query":[],"variable":[]}},"response":[],"_postman_id":"b6357ed7-df04-47be-ab14-15ce5ca4a5e1"}],"id":"bb1c6261-a086-423b-a9b9-5cbb0dde28e1","_postman_id":"bb1c6261-a086-423b-a9b9-5cbb0dde28e1","description":"","auth":{"type":"oauth2","oauth2":{"basicConfig":[{"key":"accessToken","value":""}],"advancedConfig":[{"key":"useBrowser","value":""},{"key":"tokenType","value":""},{"key":"scope","value":""},{"key":"clientSecret","value":"{{client_secret}}"},{"key":"clientId","value":"{{client_id}}"},{"key":"accessTokenUrl","value":"{{auth_server}}"},{"key":"grant_type","value":""},{"key":"tokenName","value":""}]},"isInherited":true,"source":{"_postman_id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","id":"a0df04d0-827b-495d-b7eb-4d95b0e8b599","name":"DTN Marine Weather API","type":"collection"}}}],"auth":{"type":"oauth2","oauth2":{"basicConfig":[{"key":"accessToken","value":""}],"advancedConfig":[{"key":"useBrowser","value":""},{"key":"tokenType","value":""},{"key":"scope","value":""},{"key":"clientSecret","value":"{{client_secret}}"},{"key":"clientId","value":"{{client_id}}"},{"key":"accessTokenUrl","value":"{{auth_server}}"},{"key":"grant_type","value":""},{"key":"tokenName","value":""}]}},"event":[{"listen":"prerequest","script":{"id":"3ea93b2e-fd8c-4743-bb05-16e7e3a66b6a","type":"text/javascript","exec":["var moment = require(\"moment\")","pm.environment.set(\"isoTimeNow\", moment().toISOString());","pm.environment.set(\"isoTime9days\", moment().add(9,\"days\").toISOString());","pm.environment.set(\"isoTime10days\", moment().add(10,\"days\").toISOString());"]}},{"listen":"test","script":{"id":"cd2b23a0-6cbd-4d0c-9b05-520e9e05a191","type":"text/javascript","exec":[""]}}]}