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Dataset Title:  SPI - Bromine monoxide (BrO) measurements made using a MAX-DOAS (Multi-AXis
Differential Optical Absorption Spectroscopy) instrument in the austral summer
of 2016/17 during the Antarctic Circumnavigation Expedition (ACE).
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Institution:  SPI   (Dataset ID: SPI_10_5281_zenodo_3843262)
Information:  Summary ? | License ? | Metadata | Background (external link) | Data Access Form
 
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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  datetime {
    Int32 _ChunkSizes 512;
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.4836752e+9, 1.491588e+9;
    String axis "T";
    String description "time";
    String ioos_category "Time";
    String long_name "Time";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
    String x_spi_emodnet_visualise_variable "False";
  }
  bro_mixing_ratio {
    Int32 _ChunkSizes 512;
    Float64 actual_range 0.579, 14.28;
    String description "Quotient between the number density of bromine monoxide (BrO) and the number density of the air or atmosphere at that same height, expressed in units of parts per trillion (1 out every 1e12 air molecules) or pptv [parts per trillion]";
    String spi_original_name "bro_mixing_ratio (pptv)";
    String units "parts per trillion";
    String x_spi_emodnet_visualise_variable "True";
  }
  bro_mixing_ratio_unc {
    Int32 _ChunkSizes 512;
    Float64 actual_range 0.001, 0.8;
    String description "Uncertainty in the bromine monoxide (BrO) mixing ratio [parts per trillion]";
    String spi_original_name "bro_mixing_ratio_unc (pptv)";
    String units "parts per trillion";
    String x_spi_emodnet_visualise_variable "True";
  }
  bro_vcd {
    Int32 _ChunkSizes 512;
    Float64 actual_range 3.38e+11, 1.69e+13;
    String description "Vertical column density of bromine monoxide (BrO) representing the vertical integration of the trace gas concentration profile [molecules per cm^2]";
    String spi_original_name "bro_vcd (molec/cm^2)";
    String x_spi_emodnet_visualise_variable "True";
  }
  bro_vcd_unc {
    Int32 _ChunkSizes 512;
    Float64 actual_range 1.12e+9, 1.14e+12;
    String description "Uncertainty in the vertical column density of bromine monoxide (BrO) [molecules per cm^2]";
    String spi_original_name "bro_vcd_unc (molec/cm^2)";
    String x_spi_emodnet_visualise_variable "True";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String citation "Benavent, N., Garcia-Nieto, D., Cuevas, C.A. and Saiz-Lopez, A. (2020). Bromine monoxide (BrO) measurements made using a MAX-DOAS (Multi-Axis Differential Optical Absorption Spectroscopy) instrument in the austral summer of 2016/17 during the Antarctic Circumnavigation Expedition (ACE). (Version 1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3843263";
    String contributors "[{'title': 'Nuria Benavent', 'path': 'https://orcid.org/0000-0003-3473-0629', 'role': 'author', 'organisation': 'Department of Atmospheric Chemistry and Climate, Institute of Physical Chemistry Rocasolano, Consejo Superior de Investigaciones Científicas, Spain'}, {'title': 'David Garcia-Nieto', 'path': 'https://orcid.org/0000-0002-0884-5978', 'role': 'author', 'organisation': 'Department of Atmospheric Chemistry and Climate, Institute of Physical Chemistry Rocasolano, Consejo Superior de Investigaciones Científicas, Spain'}, {'title': 'Carlos Alberto Cuevas', 'path': 'https://orcid.org/0000-0002-9251-5460', 'role': 'author', 'organisation': 'Department of Atmospheric Chemistry and Climate, Institute of Physical Chemistry Rocasolano, Consejo Superior de Investigaciones Científicas, Spain'}, {'title': 'Alfonso Saiz-Lopez', 'path': 'https://orcid.org/0000-0002-0060-1581', 'email': 'a.saiz@csic.es', 'role': 'author', 'organisation': 'Department of Atmospheric Chemistry and Climate, Institute of Physical Chemistry Rocasolano, Consejo Superior de Investigaciones Científicas, Spain'}]";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_name "Nuria Benavent";
    String creator_type "institution";
    String creator_url "https://orcid.org/0000-0003-3473-0629";
    String DOI "https://doi.org/10.5281/zenodo.3843263";
    String history 
"2020-11-24T10:00:39Z (local files)
2020-11-24T10:00:39Z https://erddap.emodnet-physics.eu/tabledap/SPI_10_5281_zenodo_3843262.das";
    String infoUrl "https://doi.org/10.5281/zenodo.3843263";
    String institution "SPI";
    String keywords "ACE, Antarctic Circumnavigation Expedition, Antarctica, atmosphere, BrO, bromine monoxide, halogens, MAX-DOAS";
    String license "CC-BY-4.0";
    String platform_code "UBXH3_ACE_3843262";
    String platform_name "R/V Akademik Tryoshnikov";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "To achieve the objectives of the project, we installed a MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) instrument on the vessel “Akademik Tryoshnikov”. This instrument is based on the DOAS technique, which is used to measure trace gas concentrations in the atmosphere. The method consists of the analysis of the spectral absorption lines that each trace gas produces in the solar spectra. The DOAS technique uses the narrowband features that every trace gas has in their spectral absorption coefficients. This differential cross section is unique and acts like a fingerprint for the trace gases, allowing to differentiate between them and to estimate their concentrations (for further details see Platt and Stutz, 2008). In the past decades, atmospheric chemists have come to realize that halogen species (like Cl, Br or I and their oxides ClO, BrO and IO) exert a powerful influence on the chemical composition of the troposphere and through that influence affect the evolution of pollutants, hence having a significant impact on climate. These reactive halogen species are potent oxidizers for organic and inorganic compounds throughout the troposphere. In particular, halogen cycles can act on several compounds (such as methane, ozone, particles…), all of which are climate forcing agents through direct and indirect radiative effects. Dynamic exchange of halogens between ocean, sea ice, snowpack and atmosphere is the main driver for the frequent occurrence of Ozone Depletion Events (ODEs) and Atmospheric Mercury Depletion Events (AMDEs) (Saiz-Lopez and von Glasow, 2012). In this dataset we present the mixing ratio and vertical column density of bromine monoxide (BrO) recorded in the austral summer of 2016/2017 in the Southern Ocean and Atlantic Ocean, averaged over one-hour time periods.";
    String title "SPI - Bromine monoxide (BrO) measurements made using a MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) instrument in the austral summer of 2016/17 during the Antarctic Circumnavigation Expedition (ACE).";
    String type "ferrybox/ship";
  }
}

 

Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.


 
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