* The List of All Active Datasets in this ERDDAP *

Summary:
This dataset is a table which has a row of information for each dataset currently active in this ERDDAP.

cdm_data_type = Other
VARIABLES:
datasetID (Dataset ID)
accessible
institution
dataStructure (Data Structure)
cdm_data_type (Common Data Model Type)
class (ERDDAP Class)
title
minLongitude (Minimum Longitude, degrees_east)
maxLongitude (Maximum Longitude, degrees_east)
longitudeSpacing (Average Grid Longitude Spacing, degrees_east)
minLatitude (Minimum Latitude, degrees_north)
maxLatitude (Maximum Latitude, degrees_north)
latitudeSpacing (Average Grid Latitude Spacing, degrees_north)
minAltitude (Minimum Altitude (or negative Depth), m)
maxAltitude (Maximum Altitude (or negative Depth), m)
minTime (Minimum Time, seconds since 1970-01-01T00:00:00Z)
maxTime (Maximum Time, seconds since 1970-01-01T00:00:00Z)
timeSpacing (Average Grid Time Spacing, seconds)
griddap (Base URL of OPeNDAP Grid Service)
subset (URL of Subset Web Page)
tabledap (Base URL of OPeNDAP Table/Sequence Service)
MakeAGraph (URL of Make-A-Graph Web Page)
sos (Base URL of SOS Service)
wcs (Base URL of WCS Service)
wms (Base URL of WMS Service)
files (Base URL of "files" Service)
... (10 more variables)


2 days 1.1 km resolution forecast over Liguria - Animation of waves

Summary:
Hourly 3-dimensional atmospheric gridded data, with a temporal coverage of 48 hours. Data cover Central and Eastern Liguria - Animation of waves

cdm_data_type = Grid
VARIABLES:
url
time (seconds since 1970-01-01T00:00:00Z)
name (File Name)
lastModified (Last Modified, seconds since 1970-01-01T00:00:00Z)
size (bytes)
fileType (File Type)


2 days 1.1 km resolution forecast over Liguria - Animation of wind

Summary:
Hourly 3-dimensional atmospheric gridded data, with a temporal coverage of 48 hours and a spatial resolution of 1.1 km. Data cover Central and Eastern Liguria - Animation of wind

cdm_data_type = Grid
VARIABLES:
url
time (seconds since 1970-01-01T00:00:00Z)
name (File Name)
lastModified (Last Modified, seconds since 1970-01-01T00:00:00Z)
size (bytes)
fileType (File Type)


2 days 3.3 km resolution forecast over Northern and Central Italy - Animation of wind

Summary:
Hourly 3-dimensional atmospheric gridded data, with a temporal coverage of 48 hours and a spatial resolution of 3.3 km. Data cover Northern and Central Italy - Animation of wind

cdm_data_type = Grid
VARIABLES:
url
time (seconds since 1970-01-01T00:00:00Z)
name (File Name)
lastModified (Last Modified, seconds since 1970-01-01T00:00:00Z)
size (bytes)
fileType (File Type)


5 days 10 km resolution forecast over Southern Europe and Mediterranean basin - Animation of wind

Summary:
Hourly 3-dimensional atmospheric gridded data, with a temporal coverage of 5 day and a spatial resolution of 10 km. Data cover Southern Europe and Mediterranean basin - Animation of wind

cdm_data_type = Grid
VARIABLES:
url
time (seconds since 1970-01-01T00:00:00Z)
name (File Name)
lastModified (Last Modified, seconds since 1970-01-01T00:00:00Z)
size (bytes)
fileType (File Type)


AI-based particle dispersion model

Summary:
The particle dispersion model used is Gnome. To drive the dispersion simulations, a neural network is first employed to model the sea current for the next six hours, using the wind and current data from the previous six hours as input. The current signal forecasted by the neural network is then used as a forcing input for Gnome to model the particle dispersion.

cdm_data_type = Point
VARIABLES:
time (time since the beginning of the simulation, seconds since 1970-01-01T00:00:00Z)
latitude (latitude of the particle, degrees_north)
longitude (longitude of the particle, degrees_east)
particle_count (number of particles in a given timestep, 1)
mass (mass of particle, kilograms)
status_codes (particle status code)
age (age of particle from time of release, minutes)
density (emulsion density at end of timestep, kg/m^3)
spill_num (spill to which the particle belongs)
surface_concentration (surface concentration of oil, g m-2)
depth (particle depth below sea surface, m)
id (particle ID)
viscosity (emulsion viscosity at end of timestep, m^2/sec)


Camogli in situ buoy sea water temperature and sub surface current data

Summary:
The dataset represents data automatically collected and trasmitted in real-time by in situ buoy located in Camogli

cdm_data_type = Other
VARIABLES:
time (Timestamp, seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
sw_temperature_3m (SW Temp 3m, degree_Celsius)
sw_temperature_6_5m (SW Temp 6.5m, degree_Celsius)
speed_mean (Speed, cm/s)
speed_std (cm/s)
direction_mean (Direction, degrees_north)
direction_std (degrees_north)
tilt
tilt_std
read_count


Camogli in situ Camogli buoy wave and wind data

Summary:
The dataset represents data automatically collected and trasmitted in real-time by in situ buoy located in Camogli

cdm_data_type = Other
VARIABLES:
time (Timestamp, seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
significantWaveHeight (Significant Wave Height, m)
peakPeriod (Wave Peak Period, s)
meanPeriod (Wave Mean Period, s)
peakDirection (Wave Peak Direction, degrees)
meanDirection (Wave Mean Direction, degrees)
peakDirectionalSpread (Wave Peak Directional Spread, degrees)
meanDirectionalSpread (Wave Mean Directional Spread, degrees)
wind_direction (degrees_north)
wind_speed (m/s)
air_pressure (Barometric Pressure, hPa)
surfaceTemp (Surface Temp, degree_C)


collection of algal photos collected by the @lgawarning platform - algal bloom participatory environmental monitoring system

Summary:
The @lgawarning platform aims to collect environmental monitoring system for algal blooms, enabling users to transmit reports on the anomalous presence of microalgae in aquatic environments directly from the observation site

cdm_data_type = Point
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
site_name (Position)
latitude (degrees_north)
longitude (degrees_east)
algae_type (Type)
description
sample_volume (Volume, ml)
operator_id (User)
image


Collection of plastic litter photos collected by the Custodians Earth Solution Platform (CESP)

Summary:
The Custodians Earth Solution Platform (CESP) app collects photographic reports of plastic litter as part of a BioDesign Foundation initiative to support environmental cleanup efforts. Developed under the RAISE program and tested in real-world operations, CESP enables the acquisition of georeferenced data that are processed to produce maps illustrating the presence and spatial distribution of plastic litter in urban environments.

cdm_data_type = Other
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
event
event_description
description
image


Data from a local source.

Summary:
Data from a local source.

cdm_data_type = Point
VARIABLES:
EventID (Event ID)
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
Depth_Km (Depth)
Author
Catalog
Contributor
ContributorID (Contributor ID)
MagType (Mag Type)
Magnitude
MagAuthor (Mag Author)
EventLocationName (Event Location Name)


Summary:
Global Forecast System (GFS) model - Animation of wind

cdm_data_type = Grid
VARIABLES:
url
time (seconds since 1970-01-01T00:00:00Z)
name (File Name)
lastModified (Last Modified, seconds since 1970-01-01T00:00:00Z)
size (bytes)
fileType (File Type)


I-Change Acronet Data

Summary:
I-Change Acronet Data. CIMAFOUNDATION data from a local source.

cdm_data_type = Point
VARIABLES:
time (Valid Time GMT, seconds since 1970-01-01T00:00:00Z)
STATION_ID
STATION_NAME
latitude (degrees_north)
longitude (degrees_east)
RAINGAUGE (mm)
TEMP (Temperature, degree_C)
HUMIDITY (relative_humidity, percent)
WSPEED (wind_speed)
PRESS (air_pressure)
WSPEED_GUST (wind_speed_of_gust)


In situ CTD instrument at 3m depth - eLTER-Italy site Portofino Promontory - Italy (LTER_EU_IT_015) - all raw data

Summary:
The dataset represents raw data automatically collected and trasmitted in real-time by in situ CTD instrument at 3m depth, installed on the Meda2 buoy located in the eLTER-Italy site Portofino Promontory - Italy (LTER_EU_IT_015).

cdm_data_type = Other
VARIABLES:
date
hour
time (seconds since 1970-01-01T00:00:00Z)
time_cet (seconds since 1970-01-01T00:00:00Z)
Press
Temp (Temperature)
Cond
Sal (Sal.)
sensor_id


In situ CTD instrument at 3m depth - LTER-Italy site Portofino Promontory - Italy (LTER_EU_IT_015) - last row data

Summary:
The dataset represents last raw data automatically collected and trasmitted in real-time by in situ CTD instrument at 3m depth, installed on the Meda2 buoy located in the LTER-Italy site Portofino Promontory - Italy (LTER_EU_IT_015).

cdm_data_type = Other
VARIABLES:
date
hour
time (seconds since 1970-01-01T00:00:00Z)
time_cet (seconds since 1970-01-01T00:00:00Z)
Press
Temp (Temperature)
Cond
Sal (Sal.)
sensor_id


In situ current in the water column - Nortek AWAC 1Mhz ADCP positioned at a depth of 10m - LTER-Italy site Portofino Promontory - Italy (LTER_EU_IT_015)

Summary:
The dataset represents data automatically collected and trasmitted in real-time by in situ ADCP instrument at 10m depth, installed on the Meda2 buoy located in the LTER-Italy site Portofino Promontory - Italy (LTER_EU_IT_015).

cdm_data_type = Other
VARIABLES:
PLATFORMCODE
String_ID
time (seconds since 1970-01-01T00:00:00Z)
time_cet (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
depth (m)
Date (seconds since 1970-01-01T00:00:00Z)
Time
Cell_number
EWCT (West-east current component, m/s)
NSCT (South-north current component, m/s)
UVCT (Upward current velocity, m/s)
Speed (m/s)
Direction (degrees)


In situ Theodor Friedrichs meteorological station at 7m amsl - LTER-Italy site Portofino Promontory - Italy (LTER_EU_IT_015)

Summary:
The dataset represents data automatically collected and trasmitted in real-time by in situ meteorological station at 7m amsl, installed on the Meda2 buoy located in the LTER-Italy site Portofino Promontory - Italy (LTER_EU_IT_015)

cdm_data_type = Other
VARIABLES:
PLATFORMCODE
String_ID
time (seconds since 1970-01-01T00:00:00Z)
time_cet (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
Date (seconds since 1970-01-01T00:00:00Z)
Time
AIR_PRES (Aire Pressure)
WSPD (Wind Speed, m/s)
WDIR (Direction relative to true north from which the wind is blowing, degrees_north)
AIR_TEMP (Air temperature, degrees_Celsius)
Humidity (Relative humidity)
PSAL (Salinity, psu)


In situ wave - Keller High Accuracy OEM Pressure Transmitter positioned at a depth of 10m - LTER-Italy site Portofino Promontory - Italy (LTER_EU_IT_015)

Summary:
The dataset represents data automatically collected and trasmitted in real-time by in situ pressure transmitter positioned at a depth of 10m, installed on the Meda2 buoy located in the LTER-Italy site Portofino Promontory - Italy (LTER_EU_IT_015).

cdm_data_type = Other
VARIABLES:
PLATFORMCODE
String_ID
time (seconds since 1970-01-01T00:00:00Z)
time_cet (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
Date (seconds since 1970-01-01T00:00:00Z)
Time
spectrum_type
processing_method
VGHS (HM0 significant wave height, m)
H3 (H3 Mean 1/3 Height, m)
H10 (H3 Mean 1/10 Height, m)
Hmax (Maximum Height, m)
Tm02 (Mean Period, s)
Tp (Peak Period, s)
Tz (Mean Zero-crossing Period, s)
DirTp (Peak Direction, degrees_north)
SprTp (Directional Spread, degrees_north)
Mdir (Mean Direction, degrees_north)


In situ wave - Nortek AWAC 1Mhz ADCP positioned at a depth of 10m - LTER-Italy site Portofino Promontory - Italy (LTER_EU_IT_015)

Summary:
The dataset represents data automatically collected and trasmitted in real-time by in situ ADCP instrument at 10m depth, installed on the Meda2 buoy located in the LTER-Italy site Portofino Promontory - Italy (LTER_EU_IT_015).

cdm_data_type = Other
VARIABLES:
PLATFORMCODE
String_ID
time (seconds since 1970-01-01T00:00:00Z)
time_cet (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
Date (seconds since 1970-01-01T00:00:00Z)
Time
spectrum_type
processing_method
VGHS (HM0 significant wave height, m)
H3 (H3 Mean 1/3 Height, m)
H10 (H3 Mean 1/10 Height, m)
Hmax (Maximum Height, m)
Tm02 (Mean Period, s)
Tp (Peak Period, s)
Tz (Mean Zero-crossing Period, s)
DirTp (Peak Direction, degrees_north)
SprTp (Directional Spread, degrees_north)
Mdir (Mean Direction, degrees_north)


Summary:
INGVXBT - Collection of sea temperature (TEMP) Profiles - METADATA

cdm_data_type = Other
VARIABLES:
PLATFORMCODE (EMODNET Platform Code)
call_name (Platform Call Name)
latitude (degrees_north)
longitude (degrees_east)
dataFeatureType
firstDateObservation (First Date Observation, seconds since 1970-01-01T00:00:00Z)
lastDateObservation (Last Date Observation, seconds since 1970-01-01T00:00:00Z)
parameters_group_longname (Parameters Info Parameter Groups)
parameters_group_P33 (Parameters Info P33)
parameters (Parameters Info Parameters)
parameters_P01 (Parameters Info P01)
WMO
data_DOI
best_practices_DOI
data_owner_longname (Data Owner Name)
data_owner_country_code
data_owner_country_longname (Data Owner Country Name)
data_owner_EDMO (Data Owner EDMO Code)
data_assembly_center_longname (Data Assembly Center)
platform_type_longname (Platform Type)
platform_type_SDNL06
platformpage_link
integrator_id
IntegrationDate (Integration Date, seconds since 1970-01-01T00:00:00Z)
ingestion
official_repository


Lagrangian dispersal around the Portofino promontory Italy for the month of July 2022

Summary:
During July 2022, a Lagrangian dispersal experiment was carried out around the Portofino Promontory (Italy) to simulate the summer dynamics of gelatinous organism blooms. Virtual particles were released in the coastal circulation field to represent the transport and spreading of these organisms under typical seasonal current conditions. The resulting trajectories highlight how coastal currents can rapidly redistribute biological material along the Portofino coastline, illustrating the potential spatial extent and coastal impact of gelatinous blooms during summer.

cdm_data_type = Point
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)


LTER_EU_IT_015_MEDA2 - CTD

Summary:
LTER_EU_IT_015_MEDA2 - CTD

cdm_data_type = Other
VARIABLES:
PLATFORMCODE
String_ID
time (seconds since 1970-01-01T00:00:00Z)
time_cet (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
date
hour
Press
Temp (Temperature)
Cond
Sal (Sal.)


Meda 2 Image Dataset - Portofino - Station 0002

Summary:
The dataset consits of underwater images showing fish and jellyfish activities in the marine protected area of Portofino (GE). The images are acquired by the autonomous and intelligent imaging device GUARD-1, installed on a Meda buoy in front of Punta Faro, Portofino. The GUARD-1 is deployed at 3m depth and consists of an underwater camera equipped with a lighiting system that allow the image acquisition 24h per day. The device is also equipped with an onboard AI-based image analysis tool capable to recognize the fish and the jellyfish specimens in order to automatically extract abundance time series and to select images with relevant content. The GUARD-1 device is connected to a 4G modem positioned on the Meda buoy, inside a watertight case, that transmit the acquired images together with information extracted by the AI-based tool. Both the image acquisition frequency and the data transmission frequency are programmable by the user and can be managed through a remote connection or automatically by the AI-based tool.

cdm_data_type = Other
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
name
latitude (degrees_north)
longitude (degrees_east)
url


Meteorological data collected by Genoa boat-bus activities using the MeteoTracker device

Summary:
Collection of meteorological data from the MeteoTracker device. MeteoTracker is a low cost tool for participatory science. RAISE developed the data ingestion, data processing and workflow automation for offering added value datasets.

cdm_data_type = Point
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
altitude (m)
speed
temperature
humidity
pressure
dew_point
solar_radiation_index
humidex
tag
potential_temperature
D


Meteorological data collected by Genoa bus activities using the MeteoTracker device

Summary:
Collection of meteorological data from the MeteoTracker device. MeteoTracker is a low cost tool for participatory science. RAISE developed the data ingestion, data processing and workflow automation for offering added value datasets.

cdm_data_type = Point
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
altitude (m)
speed
carbon_dioxide
pressure
humidity
temperature
dew_point
humidex
potential_temperature
tag
D
vertical_temperature_gradient
solar_radiation_index


Meteorological data collected during Citizen Science activities using the MeteoTracker device

Summary:
Collection of meteorological data from the MeteoTracker device. MeteoTracker is a low cost tool for participatory science. RAISE developed the data ingestion, data processing and workflow automation for offering added value datasets.

cdm_data_type = Point
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
altitude (m)
speed
temperature
humidity
pressure
dew_point
solar_radiation_index
humidex
tag
vertical_temperature_gradient
potential_temperature
D


Meteorological data collected during Citizen Science V23 campaign aboard the Swan Hellenic SH Vega ship

Summary:
Meteorological data from the SH Vega ship - Cruising4Oceans project. Cruising4Oceans  is a a Swan Hellenic project supporting scientific research for ocean health in 2025. RAISE developed the data ingestion and processing workflow and its automation.

cdm_data_type = Point
VARIABLES:
DateTimeLocal (Date/time (local), seconds since 1970-01-01T00:00:00Z)
Timezone
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
Report
Voyage_state
Location
Voyage_name
Speed_OG (kn)
Speed_TW (kn)
True_wind_speed (Wind Speed, Bft)
Wind_direction_absolute (Wind From Direction)
Wave_height (Sea Surface Wave Significant Height)
Air_temperature (degree_C)
Draft_midship (m)
Trim (m)
Distance_OG (nm)
Distance_TW (nm)
Speed_OG_QC
Speed_TW_QC
True_wind_speed_QC
Wind_direction_absolute_QC (Wind Direction (absolute) QC)
Wave_height_QC
Air_temperature_QC
... (4 more variables)


Meteorological data collected during Citizen Science V24 campaign aboard the Swan Hellenic SH Vega ship

Summary:
Meteorological data from the SH Vega ship - Cruising4Oceans project. Cruising4Oceans  is a a Swan Hellenic project supporting scientific research for ocean health in 2025. RAISE developed the data ingestion and processing workflow and its automation.

cdm_data_type = Point
VARIABLES:
DateTimeLocal (Date/time (local), seconds since 1970-01-01T00:00:00Z)
Timezone
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
Report
Voyage_state
Location
Voyage_name
Ship_Speed (kn)
True_wind_speed (Wind Speed, Bft)
Wind_direction_absolute (Wind From Direction)
Wave_height (Sea Surface Wave Significant Height)
Air_temperature (degree_C)
Atmosferic_pressure (Air Pressure, hPa)
Ship_Speed_kn_QC (Ship Speed [kn] QC)
True_wind_speed_QC
Wind_direction_absolute_QC (Wind Direction (absolute) QC)
Wave_height_QC
Air_temperature_QC
Draft_midship_QC


Meteorological data collected during Citizen Science V25 campaign aboard the Swan Hellenic SH Vega ship

Summary:
Meteorological data from the SH Vega ship - Cruising4Oceans project. Cruising4Oceans  is a a Swan Hellenic project supporting scientific research for ocean health in 2025. RAISE developed the data ingestion and processing workflow and its automation.

cdm_data_type = Point
VARIABLES:
DateTimeLocal (Date/time (local), seconds since 1970-01-01T00:00:00Z)
Timezone
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
Report
Voyage_state
Location
Voyage_name
Speed_OG (kn)
Ship_Speed (kn)
True_wind_speed (Wind Speed, Bft)
Wind_direction_absolute (Wind From Direction)
Wind_direction_true (degrees)
Wave_height (Sea Surface Wave Significant Height)
Air_temperature (degree_C)
Atmosferic_pressure (hPa)
Speed_OG_QC
Ship_Speed_QC
True_wind_speed_QC
Wind_direction_absolute_QC (Wind Direction (absolute) QC)
Wind_direction_true_QC
Wave_height_QC
Air_temperature_QC
Atmosferic_pressure_QC


Meteorological data collected during Citizen Science V26 campaign aboard the Swan Hellenic SH Vega ship


Meteorological data collected during Citizen Science V27 campaign aboard the Swan Hellenic SH Vega ship


Meteorological data collected during Citizen Science V28 campaign aboard the Swan Hellenic SH Vega ship


Meteorological data collected during Citizen Science V29 campaign aboard the Swan Hellenic SH Vega ship


Meteorological data collected during Citizen Science V30 campaign aboard the Swan Hellenic SH Vega ship


Meteorological data collected during Citizen Science V31 campaign aboard the Swan Hellenic SH Vega ship


Meteorological data collected during Citizen Science V32 campaign aboard the Swan Hellenic SH Vega ship


Meteorological data collected during Citizen Science V33 campaign aboard the Swan Hellenic SH Vega ship


Meteorological data collected during Citizen Science V34 campaign aboard the Swan Hellenic SH Vega ship


Meteorological data collected during Citizen Science V35 campaign aboard the Swan Hellenic SH Vega ship


Meteorological data collected during Citizen Science V36 campaign aboard the Swan Hellenic SH Vega ship


Meteorological data collected during Citizen Science V56 campaign aboard the Swan Hellenic SH Vega ship


Meteorological data collected during Citizen Science V57 campaign aboard the Swan Hellenic SH Vega ship


Meteorological data collected using the MeteoTracker device


Meteorological observations by Ecowitt Weather Station - ECOWITT001

Summary:
The Ecowitt Weather Station dataset provides real-time and high-frequency meteorological observations collected by a consumer-grade wireless weather station. The environmental variables monitored by the Ecowitt weather station and accessible through the LA SOMMA portal are: temperature, wind direction, wind gust, wind speed, atmospheric pressure, rainfall intensity, and relative humidity .Data are transmitted at regular intervals through the Ecowitt API. Measurements are delivered as minute-level or multi-minute time series, depending on the configured reporting interval.

cdm_data_type = Other
VARIABLES:
ext_id
time (seconds since 1970-01-01T00:00:00Z)
cum
rain_intensity
air_temperature
relative_humidity
air_pressure
wind_speed
wind_from_direction
wind_gust (Wind Speed Of Gust)
wind_gust_from_direction
battery


Meteorological observations by Ecowitt Weather Station - ECOWITT002


Meteorological observations by Ecowitt Weather Station - ECOWITT003


Meteorological observations by Ecowitt Weather Station - ECOWITT004


Multiparametric measurements in a fixed position in the Genova port

Summary:
An IoT - blue box system installed on a 'boat of opportunity'  measured temperature, salinity, pH, redox, chlorophyll, oxygen, phycoerythrin, turbidity and fDOM  at a depth of 0.5 meters initially at  at 5-minute intervals and then at 20 minutes intervals

cdm_data_type = Other
VARIABLES:
ext_id
cruise
station
type
time (seconds since 1970-01-01T00:00:00Z)
temp (Temperature)
psal
alky
cpwc
phyc
tsed
wbrx
cmfl
deph
doxy_mg_l
doxy_perc
qv_odv_sample
temp_qf
psal_qf
alky_qf
cpwc_qf
phyc_qf
tsed_qf
wbrx_qf
cmfl_qf
... (4 more variables)


Multiparametric mission along the eastern ligurian coast from Cinque Terre to Marina di Massa

Summary:
An IoT - blue box system installed on a 'boat of opportunity'  measured temperature, salinity, pH, redox, chlorophyll, oxygen, phycoerythrin and turbidity at a depth of 0.5 meters at 5-minute intervals on the continental shelf off Cinque Terre and La Spezia

cdm_data_type = Other
VARIABLES:
ext_id
cruise
station
type
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
temp (Temperature)
psal
alky
cpwc
phyc
tsed
wbrx
cmfl
deph
doxy_mg_l
doxy_perc
qv_odv_sample


Multiparametric mission along the eastern ligurian coast from Genova to Portofino

Summary:
An IoT - blue box system installed on a 'boat of opportunity'  measured temperature, salinity, pH, redox, chlorophyll, oxygen, phycoerythrin and turbidity at a depth of 0.5 meters at 5-minute intervals on the continental shelf off Genova and in open sea from Genova to Portofino

cdm_data_type = Other
VARIABLES:
ext_id
cruise
station
type
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
temp (Temperature)
psal
alky
cpwc
phyc
tsed
wbrx
cmfl
deph
doxy_mg_l
doxy_perc
qv_odv_sample


Multiparametric mission around Ischia island

Summary:
An IoT - blue box system installed on a 'boat of opportunity'  measured temperature, salinity, pH, redox, chlorophyll, oxygen, phycoerythrin and turbidity at a depth of 0.5 meters at 5-minute intervals on the continental shelf off Ischia island

cdm_data_type = Other
VARIABLES:
ext_id
cruise
station
type
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
temp (Temperature)
psal
alky
cpwc
phyc
tsed
wbrx
cmfl
deph
doxy_mg_l
doxy_perc
qv_odv_sample


Multiparametric mission off Genova April 2025

Summary:
An IoT - blue box system installed on a 'boat of opportunity'  measured temperature, salinity, pH, redox, chlorophyll, oxygen, phycoerythrin and turbidity at a depth of 0.5 meters at 5-minute intervals on the coastal zone off Genova

cdm_data_type = Other
VARIABLES:
ext_id
cruise
station
type
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
temp (Temperature)
psal
alky
cpwc
phyc
tsed
wbrx
cmfl
deph
doxy_mg_l
doxy_perc
qv_odv_sample


Mussel farm image dataset - Gulf of La Spezia - Station 0001

Summary:
The dataset consits of underwater images showing fish activity within the mussel farm in the Gulf of La Spezia. The images are acquired by the autonomous and intelligent imaging device GUARD-1, installed on a surface buoy of the mussel farm in the gulf of La Spezia. The GUARD-1 is deployed at 3m depth and consists of an underwater camera equipped with a lighiting system that allow the image acquisition 24h per day. The device is also equipped with an onboard AI-based image analysis tool capable to recognize the fish specimens in order to automatically extract abundance time series and to select images with relevant content. The GUARD-1 device is connected to a 4G modem positioned on the surface buoy, inside a watertight case, that transmit the acquired images together with information extracted by the AI-based tool. Both the image acquisition frequency and the data transmission frequency are programmable by the user and can be managed through a remote connection or automatically by the AI-based tool.

cdm_data_type = Other
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
name
latitude (degrees_north)
longitude (degrees_east)
url


Mussel farm image dataset - Gulf of La Spezia - Station 0001 and 0022


Mussel farm image dataset - Gulf of La Spezia - Station 0022


Mussel farm image dataset - Gulf of La Spezia - Station 0102

Summary:
The dataset consits of underwater images showing fish activity within the mussel farm in the Gulf of La Spezia. The images are acquired by the autonomous and intelligent imaging device GUARD-1, installed on a fixed boat used as a field laboratory by the mussel farm operators, in the gulf of La Spezia. The GUARD-1 is deployed at 3m depth and consists of an underwater camera equipped with a lighiting system that allow the image acquisition 24h per day. The GUARD-1 device is connected to a 4G modem positioned on the fixed boat that transmit the acquired images. Both the image acquisition frequency and the data transmission frequency are programmable by the user and can be managed through a remote connection.

cdm_data_type = Other
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
name
latitude (degrees_north)
longitude (degrees_east)
url


Particle dispersion model

Summary:
The particle dispersion model used is Pygnome. The forcings used for the forecast are the persistence of the sea current velocity, in its u and v components, and the average wind speed and direction calculated over the previous six hours.  The model generates a forecast output with a six-hour time horizon. Every hour, new current and wind data are acquired, thus updating the forecast hour by hour for the next six hours.

cdm_data_type = Point
VARIABLES:
time (time since the beginning of the simulation, seconds since 1970-01-01T00:00:00Z)
latitude (latitude of the particle, degrees_north)
longitude (longitude of the particle, degrees_east)
particle_count (number of particles in a given timestep, 1)
spill_num (spill to which the particle belongs)
surface_concentration (surface concentration of oil, g m-2)
depth (particle depth below sea surface, m)
id (particle ID)
age (age of particle from time of release, minutes)
status_codes (particle status code)
density (emulsion density at end of timestep, kg/m^3)
viscosity (emulsion viscosity at end of timestep, m^2/sec)
mass (mass of particle, kilograms)


Real-time rainfall intensity and cumulate precipitation maps by SRS - Smart Rainfall System - Bonassola

Summary:
The SRS (Smart Rainfall System) dataset originates from a dense network of microwave sensors designed for satellite down-links and developed by the University of Genoa together with Artys and Darts Engineering (Genoa, Italy). By analysing the attenuation of satellite signals received by standard parabolic antennas, the system retrieves real-time estimates of rainfall intensity along each observation link and produces high-resolution precipitation maps over the monitored area. The resulting dataset provides continuous time series of rainfall intensity and cumulative precipitation (15 minutes, 1-2-8-12, 24 hours), enabling detailed spatio-temporal characterization of rainfall dynamics.

cdm_data_type = Grid
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
srs_id
srs_sat_id
rain_level


Real-time rainfall intensity and cumulate precipitation maps by SRS - Smart Rainfall System - Genova


Real-time rainfall intensity and cumulate precipitation maps by SRS - Smart Rainfall System - La Spezia


Real-time rainfall intensity and cumulate precipitation maps by SRS - Smart Rainfall System - Livorno


Riomaggiore in situ buoy sea water temperature and sub surface current data

Summary:
The dataset represents data automatically collected and trasmitted in real-time by in situ buoy located in Riomaggiore

cdm_data_type = Other
VARIABLES:
time (Timestamp, seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
sw_temperature_3m (SW Temp 3m, degree_C)
sw_temperature_6_5m (SW Temp 6.5m, degree_C)
speed_mean (Speed, cm/s)
speed_std (cm/s)
direction_mean (Direction, degrees_north)
direction_std (degrees_north)
tilt
tilt_std
read_count


Riomaggiore in situ buoy wave and wind data

Summary:
The dataset represents data automatically collected and trasmitted in real-time by in situ buoy located in Riomaggiore

cdm_data_type = Other
VARIABLES:
time (Timestamp, seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
significantWaveHeight (Significant Wave Height, m)
peakPeriod (Wave Peak Period, s)
meanPeriod (Wave Mean Period, s)
peakDirection (Wave Peak Direction, degrees)
meanDirection (Wave Mean Direction, degrees)
peakDirectionalSpread (Wave Peak Directional Spread, degrees)
meanDirectionalSpread (Wave Mean Directional Spread, degrees)
wind_direction (degrees_north)
wind_speed (m/s)
air_pressure (Barometric Pressure, hPa)
surfaceTemp (Surface Temp, degree_C)


Sea Surface Temperature data collected during Citizen Science activities using the Brizo device

Summary:
Brizo is a smart temperature logger to support marine environmental research. The system offers data in near real time.

cdm_data_type = Point
VARIABLES:
platformcode
mission
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
temperature
timestamp (seconds since 1970-01-01T00:00:00Z)
author
command


Sea waves parameters - Andora

Summary:
Sea-waves parameters -Hs (Significant wave height),Tm (Mean Period). And Tp (Peak Period) retrieved from inland micro-seismic measurements - Andora

cdm_data_type = Other
VARIABLES:
ext_id
time (seconds since 1970-01-01T00:00:00Z)
hs
tm
tp
valid


Sea waves parameters - Bonassola

Summary:
Sea-waves parameters -Hs (Significant wave height),Tm (Mean Period). And Tp (Peak Period) retrieved from inland micro-seismic measurements - Bonassola

cdm_data_type = Other
VARIABLES:
ext_id
time (seconds since 1970-01-01T00:00:00Z)
hs
tm
tp
valid


Sea waves parameters - Genova CNR

Summary:
Sea-waves parameters -Hs (Significant wave height),Tm (Mean Period). And Tp (Peak Period) retrieved from inland micro-seismic measurements - Genova CNR

cdm_data_type = Other
VARIABLES:
ext_id
time (seconds since 1970-01-01T00:00:00Z)
hs
tm
tp
valid


Sea waves parameters - Livorno

Summary:
Sea-waves parameters -Hs (Significant wave height),Tm (Mean Period). And Tp (Peak Period) retrieved from inland micro-seismic measurements - Livorno

cdm_data_type = Other
VARIABLES:
ext_id
time (seconds since 1970-01-01T00:00:00Z)
hs
tm
tp
valid


Stazioni OMIRL (Osservatorio Meteo Idrologico della Regione Liguria), Osservazioni georiferite di parametri meteo-marini ed idrologici in tempo reale sulla Liguria, Stazioni a mare

Summary:
Stazioni OMIRL (Osservatorio Meteo Idrologico della Regione Liguria) - Osservazioni georiferite di parametri meteo-marini ed idrologici in tempo reale sulla Liguria - Stazioni a mare

cdm_data_type = Point
VARIABLES:
name
shortCode (Short Code)
time (Valid Time GMT, seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
VHZA (Average zero crossing wave height (Hzm), m)
AIR_TEMP (Air temperature, degree_C)
WSPD (Horizontal wind speed, m/s)
GSPD (Gust wind speed, m/s)
WDIR (Wind from direction relative true north, degrees)
WSPD_2d (Horizontal wind speed, m/s)
GSPD_2d (Gust wind speed, m/s)
WDIR_2d (Wind from direction relative true north, degrees)
ATMP (Atmospheric pressure at sea level, hPa)


Stazioni OMIRL (Osservatorio Meteo Idrologico della Regione Liguria), Osservazioni georiferite di parametri meteo-marini ed idrologici in tempo reale sulla Liguria, Stazioni a terra

Summary:
Stazioni OMIRL (Osservatorio Meteo Idrologico della Regione Liguria) - Osservazioni georiferite di parametri meteo-marini ed idrologici in tempo reale sulla Liguria - Stazioni a terra

cdm_data_type = Point
VARIABLES:
name
shortCode (Short Code)
time (Valid Time GMT, seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
RAIN_1h
CUMUL_1h
RAIN_5m
CUMUL_5m
RAIN_7d
CUMUL_7d
RAIN_1d
CUMUL_1d
AIR_TEMP (air_temperature, degree_C)
TMIN (air_temperature, degree_C)
TMAX (air_temperature, degree_C)
RLEV (Water surface height above a specific datum, m)
ATMP (air_pressure)
TENS (Battery voltage, V)
municipality


Temperature and conductivity data collected during Citizen Science campaigns aboard the Swan Hellenic SH Vega using OpenCTD

Summary:
Dataset of Temperature and Salinity data in the water column collected by OpenCTD during Swan Hellenic expeditions. OpenCTD is a oceanographic instrument designed for budget-restricted scientists, educators, and researchers working in nearshore coastal ecosystems.

cdm_data_type = Point
VARIABLES:
ADATAA01 (seconds since 1970-01-01T00:00:00Z)
Hour
time (seconds since 1970-01-01T00:00:00Z)
depth (m)
TEMP (Temperature)
PSLTZZ01
PRESPR01
TEMPPR01
TEMPPR02
TEMPPR03
CNDCZZ01
TEMPPR01_QC
TEMPPR02_QC
TEMPPR03_QC
CNDCZZ01_QC
latitude (degrees_north)
longitude (degrees_east)
notes


Temperature data collected during Citizen Science activities using EnvLogger sensor (0443 0B00 FC09 09)

Summary:
EnvLogger is a miniaturised temperature logger to support marine environmental research. Data is downloaded by a mobile app and RAISE developed the data processing pipeline and its automation

cdm_data_type = Point
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
temp (Temperature, degree_Celsius)
serial_number
sensor_id
latitude (degrees_north)
longitude (degrees_east)
accuracy (GPS Position Accuracy, meter)
depth (Sensor depth, m)
sampling_resolution


Temperature data collected during Citizen Science activities using EnvLogger sensor (0457 9200 461D 0D)


Temperature data collected during Citizen Science activities using EnvLogger sensor (0475 3A00 FF2D 05)


Temperature data collected during Citizen Science activities using EnvLogger sensor (047E 2300 6F1E 0A)


Temperature data collected during Citizen Science activities using EnvLogger sensor (0484 0C00 220F 07)


The "Smart Bay Santa Teresa Underwater Observatory" - CDT calibrated data

Summary:
In July 2024 a preliminary real-time monitoring and transmission system based on wireless underwater networking (IoUT) has been implemented in the harbour of La Spezia, aiming to create an early warning system for temperature increase and to monitor oxygen and pH level. Currently the Smart Bay Santa Teresa Underwater Observatory is equipped with a system of transmission nodes (EMBRC-UP) connected to advanced probes (RAISE), distributed in 12 stations throughout the Gulf. Physical-chemical data (temperature, dissolved oxygen, pH, conductivity, current, turbidity, chlorophyll) are acquired with a frequency of 1 data per hour and transmitted in real time, validated with analytical approaches and weekly and monthly measurement campaigns conducted by ENEA. Biogeochemical are analytically measured (total alkalinity, pH) and derived (pCO2, saturation state, dissolved inorganic carbon) weekly and monthly, together with high precision data profiles (measured by means of a CTD probe).

cdm_data_type = Point
VARIABLES:
time (Date Time(UTC), seconds since 1970-01-01T00:00:00Z)
Depth (m)
Pressure (db)
Temperature (degrees_C)
Conductivity (Sea Water Electrical Conductivity, mS/cm)
Oxygen_mg_l (Oxygen, mg/l)
Chlorophyll (Concentration Of Chlorophyll In Sea Water, ug/l)
Turbidity
pH_NBS
Salinity (Sea Water Practical Salinity, PSU)
Density_Kg_m3 (Density, Kg/m^3)
Oxygen_ml_l (Oxygen, ml/l)
Oxygen_umol_l (Oxygen, umol/l)
Oxygen_percentage (Oxygen, %)
Density_Kg_m3_1000 (Density, Kg/m^3-1000))
Sound_Velocity (m/s)
pH_T
... (7 more variables)


The "Smart Bay Santa Teresa Underwater Observatory" - Current data

Summary:
In July 2024 a preliminary real-time monitoring and transmission system based on wireless underwater networking (IoUT) has been implemented in the harbour of La Spezia, aiming to create an early warning system for temperature increase and to monitor oxygen and pH level. Currently the Smart Bay Santa Teresa Underwater Observatory is equipped with a system of transmission nodes (EMBRC-UP) connected to advanced probes (RAISE), distributed in 12 stations throughout the Gulf. Physical-chemical data (temperature, dissolved oxygen, pH, conductivity, current, turbidity, chlorophyll) are acquired with a frequency of 1 data per hour and transmitted in real time, validated with analytical approaches and weekly and monthly measurement campaigns conducted by ENEA. Biogeochemical are analytically measured (total alkalinity, pH) and derived (pCO2, saturation state, dissolved inorganic carbon) weekly and monthly, together with high precision data profiles (measured by means of a CTD probe).

cdm_data_type = Point
VARIABLES:
time (Date Time(UTC), seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
Temperature (Temperature(degrees C), degrees C)
Direction (degrees)
Velocity (m/s)
Heading (degrees)
North_Velocity_m_s (North Velocity, m/s)
East_Velocity_m_s (East Velocity, m/s)
Echo_Amplitude_dB (d B)
Echo_Amplitude_mW (Echo Amplitude, mW)
Station
Name
Profondita
Bottom_depth
Declinazione_Magnetica
Probe_S_N


The "Smart Bay Santa Teresa Underwater Observatory"- Carbon dioxide data

Summary:
In July 2024 a preliminary real-time monitoring and transmission system based on wireless underwater networking (IoUT) has been implemented in the harbour of La Spezia, aiming to create an early warning system for temperature increase and to monitor oxygen and pH level. Currently the Smart Bay Santa Teresa Underwater Observatory is equipped with a system of transmission nodes (EMBRC-UP) connected to advanced probes (RAISE), distributed in 12 stations throughout the Gulf. Physical-chemical data (temperature, dissolved oxygen, pH, conductivity, current, turbidity, chlorophyll) are acquired with a frequency of 1 data per hour and transmitted in real time, validated with analytical approaches and weekly and monthly measurement campaigns conducted by ENEA. Biogeochemical are analytically measured (total alkalinity, pH) and derived (pCO2, saturation state, dissolved inorganic carbon) weekly and monthly, together with high precision data profiles (measured by means of a CTD probe).

cdm_data_type = Point
VARIABLES:
time (Date Time(UTC), seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
CO2 (ppm)
Internal_Temperature_IRGA (degrees_C)
Relative_Humidity
Internal_Temperature_Sensore_Humidity (degrees_C)
Cell_Pressure (h Pa)
Battery_Voltage (V)
pCO2_mbar (pCO2, mbar)
pCO2_Pa (pCO2, Pa)
pCO2_uatm (pCO2, uatm)
Station
Name
Profondita
Bottom_depth
Probe_S_N


Wave Forecast for Coastal Erosion Applications - east point

Summary:
Five days hourly forecast of ocean waves in the proximity of the Ligurian coastline for coastal risk applications- east point

cdm_data_type = Grid
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
dir (Wave mean direction, degree)
dp (Peak direction, degree)
fp (Wave peak frequency, s-1)
hs (Significant height of wind and swell waves, m)
tm (Mean period, s)
forecast_date


Wave Forecast for Coastal Erosion Applications - ovest point

Summary:
Five days hourly forecast of ocean waves in the proximity of the Ligurian coastline for coastal risk applications- ovest point

cdm_data_type = Grid
VARIABLES:
time (seconds since 1970-01-01T00:00:00Z)
latitude (degrees_north)
longitude (degrees_east)
dir (Wave mean direction, degree)
dp (Peak direction, degree)
fp (Wave peak frequency, s-1)
hs (Significant height of wind and swell waves, m)
tm (Mean period, s)
forecast_date