Filter
Reset all

Subjects

Content Types

Countries

Data access

Data access restrictions

Database access

Database licenses

Data licenses

Data upload

Data upload restrictions

Enhanced publication

Institution responsibility type

Institution type

Keywords

PID systems

Provider types

Quality management

Repository languages

Software

Repository types

Versioning

  • * at the end of a keyword allows wildcard searches
  • " quotes can be used for searching phrases
  • + represents an AND search (default)
  • | represents an OR search
  • - represents a NOT operation
  • ( and ) implies priority
  • ~N after a word specifies the desired edit distance (fuzziness)
  • ~N after a phrase specifies the desired slop amount
  • 1 (current)
Found 2 result(s)

Fisheries and Oceans Canada Pacific Region Data Archive

Pêches et Océans Canada Region Pacifique Cataloge de données

Subject(s)
Content type(s)
Country
The Institute of Ocean Sciences (IOS)/Ocean Sciences Division (OSD) data archive contains the holdings of oceanographic data generated by the IOS and other agencies and laboratories, including the Institute of Oceanography at the University of British Columbia and the Pacific Biological Station. The contents include data from B.C. coastal waters and inlets, B.C. continental shelf waters, open ocean North Pacific waters, Beaufort Sea and the Arctic Archipelago.

Perdigao Field Experiment

Subject(s)
Content type(s)
Country
Data repository of a meteorological experiment conducted in Perdigão, Portugal between December 15, 2016 to June 15, 2017. The Perdigao field project is part of a larger joint US/European multi-year program in Portugal. The project is partially funded by the European Union (EU) ERANET+ to provide the wind energy sector with more detailed resource mapping capabilities in the form of a new digital EU wind atlas. A major goal of the Perdigão field project is to quantify errors of wind resource models against a benchmark dataset collected in complex terrain. The US participation will complement this activity by identifying physical and numerical weaknesses of models and developing new knowledge and methods to overcome such deficiencies.