NOAA PMEL Easy Access to PMEL Scientific Data
The Pacific Marine Environmental Laboratory's ERDDAP data server for public access to scientific data
?    
NOAA OAR PMEL    

ERDDAP > tabledap > Make A Graph ?

Dataset Title:  PMEL Atmospheric Chemistry WACS-2 CCN data Subscribe RSS
Institution:  NOAA   (Dataset ID: ACG_WACS-2_Knorr_ccn)
Range: longitude = -70.8943 to -60.59°E, latitude = 33.1884 to 42.4999°N, altitude = 18.0 to 18.0m, time = 2014-05-20T22:00:00Z to 2014-06-04T12:00:00Z
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Subset | Data Access Form | Files
 
Graph Type:  ?
X Axis: 
Y Axis: 
Color: 
-1+1
 
Constraints ? Optional
Constraint #1 ?
Optional
Constraint #2 ?
       
       
       
       
       
 
Server-side Functions ?
 distinct() ?
? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")
 
Graph Settings
Marker Type:   Size: 
Color: 
Color Bar:   Continuity:   Scale: 
   Minimum:   Maximum:   N Sections: 
Draw land mask: 
Y Axis Minimum:   Maximum:   
 
(Please be patient. It may take a while to get the data.)
 
Optional:
Then set the File Type: (File Type information)
and
or view the URL:
(Documentation / Bypass this form ? )
    Click on the map to specify a new center point. ?
Zoom: 
Time range:    |<   -       
[The graph you specified. Please be patient.]

 

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 {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.4006232e+9, 1.4018832e+9;
    String axis "T";
    String comment "Start of sampling period";
    String coords "time";
    String ioos_category "Time";
    String long_name "Datetime UTC";
    String source_name "datetime_utc";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  trajectory_id {
    String cf_role "trajectory_id";
    String coords "time";
    String ioos_category "Identifier";
    String long_name "Trajectory ID";
  }
  duration {
    Int32 _FillValue 2147483647;
    Int32 actual_range 600, 600;
    String coords "time";
    String ioos_category "Time";
    String long_name "Duration";
    String units "second";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range 33.1884, 42.4999;
    String axis "Y";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String coords "time";
    String instrument "GPS";
    String ioos_category "Location";
    String long_name "Latitude";
    String source "surface observation";
    String standard_name "latitude";
    String units "degrees_north";
    Float64 valid_max 90.0;
    Float64 valid_min -90.0;
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range -70.8943, -60.59;
    String axis "X";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String coords "time";
    String instrument "GPS";
    String ioos_category "Location";
    String long_name "Longitude";
    String source "surface observation";
    String standard_name "longitude";
    String units "degrees_east";
    Float64 valid_max 180.0;
    Float64 valid_min -180.0;
  }
  altitude {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "up";
    Float64 actual_range 18.0, 18.0;
    String axis "Z";
    Float64 colorBarMinimum 0.0;
    String coords "time";
    String ioos_category "Location";
    String long_name "height above mean sea level";
    String positive "up";
    String standard_name "altitude";
    String units "m";
    Float64 valid_min 0.0;
  }
  ccn_ss {
    Float64 _FillValue NaN;
    Float64 actual_range 0.1, 2.0;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String coords "time";
    String instrument "Cloud Condensation Nuclei Counter";
    String ioos_category "Unknown";
    String long_name "Supersaturation of CCN measurement";
    String source "surface observation";
    String units "percent";
  }
  ccn {
    Float64 _FillValue NaN;
    Float64 actual_range 3.422, 1893.04;
    Float64 colorBarMaximum 60000.0;
    Float64 colorBarMinimum 0.0;
    String coords "time";
    String instrument "Cloud Condensation Nuclei Counter";
    String ioos_category "Meteorology";
    String long_name "Cloud Condensation Nuclei Concentration at ccn_ss";
    String source "surface observation";
    String units "cm-3";
    Float64 valid_max 50000.0;
    Float64 valid_min 0.0;
  }
  ccn_cn_ratio {
    Float64 _FillValue NaN;
    Float64 actual_range 0.00642298, 1.04705;
    Float64 colorBarMaximum 1.5;
    Float64 colorBarMinimum 0.0;
    String coords "time";
    String instrument "Cloud Condensation Nuclei Counter";
    String ioos_category "Unknown";
    String long_name "Ratio of CCN to CN";
    String source "surface observation";
    Float64 valid_max 1.0;
    Float64 valid_min 0.0;
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Trajectory";
    String cdm_trajectory_variables "trajectory_id";
    String comment 
"CCN Measurements:
A Droplet Measurement Technologies CCN Counter (DMT CCNC) was used to determine CCN concentrations of sub-1 um particles at supersaturations ranging from 0.1 to 0.62%.  A multijet cascade impactor with a 50% aerodynamic cut-off diameter of 1.1 um was upstream of the CCNC. The sampled air was dried prior to reaching the CCNC.  Details concerning the characteristics of the DMT CCN counter can be found in Roberts and Nenes [2005] and Lance et al. [2006]. The CCN counter was calibrated before and during the experiment as outlined by Lance et al. [2006]. The uncertainty associated with the CCN number concentration is estimated to be less than +/- 10% [Roberts and Nenes, 2005]. Uncertainty in the instrumental supersaturation is less than +/- 10% for the operating conditions of this experiment [Roberts and Nenes, 2005].

The data are in 10 second time intervals and include CCN concentration (in n/cm^3), CCN/CN ratio, and Supersaturation (in %).

Lance, S., J. Medina, J.N. Smith, and A. Nenes, Mapping the operation of the DMT continuous flow CCN counter, Aer. Sci. Tech., 40, 242 - 254, 2006.
Roberts, G.C. and A. Nenes, A continuous-flow streamwise thermal gradient CCN chamber for atmospheric measurements, Aer. Sci. Tech., 39, 206 - 221, 2005.";
    String contributor_name "Coffman, Derek/NOAA-PMEL/Address: 7600 Sand Pt. Wy. NE,Seattle,WA 98115 /email: derek.coffman@noaa.gov";
    String Conventions "COARDS, CF-1.6, ACDD-1.3, NCCSV-1.0";
    String creator_email "derek.coffman@noaa.gov";
    String creator_name "Coffman, Derek";
    String creator_url "https://www.pmel.noaa.gov/";
    String dimensions "time=126001";
    Float64 Easternmost_Easting -60.59;
    String featureType "Trajectory";
    Float64 geospatial_lat_max 42.4999;
    Float64 geospatial_lat_min 33.1884;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -60.59;
    Float64 geospatial_lon_min -70.8943;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 18.0;
    Float64 geospatial_vertical_min 18.0;
    String geospatial_vertical_positive "up";
    String geospatial_vertical_units "m";
    String history 
"2025-05-09T20:51:51Z (local files)
2025-05-09T20:51:51Z https://data.pmel.noaa.gov/pmel/tabledap/ACG_WACS-2_Knorr_ccn.das";
    String infoUrl "https://www.pmel.noaa.gov/acg/data/index.html";
    String institution "NOAA";
    String keywords "above, altitude, atmosphere, atmospheric, ccn, ccn_cn_ratio, ccn_ss, chemistry, chla, chlorophyll, chlorophyll-a, cloud, cloud cover, cloudiness, commerce, concentration, condensation, cover, data, datetime, department, doc, duration, earth, Earth Science > Atmosphere > Altitude > Station Height, environmental, height, identifier, laboratory, latitude, level, longitude, marine, mean, measurement, meteorology, noaa, nuclei, pacific, pmel, ratio, science, sea, station, supersaturation, time, trajectory, trajectory_id, wacs, wacs-2";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "These data were produced by NOAA and are not subject to copyright protection in the United States. NOAA waives any potential copyright and related rights in these data worldwide through the Creative Commons Zero 1.0 Universal Public Domain Dedication (CC0-1.0).";
    Float64 Northernmost_Northing 42.4999;
    String platform "Knorr";
    String product_version "0";
    String project "WACS-2";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 33.1884;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String subsetVariables "trajectory_id, duration, altitude";
    String summary 
"Core WACS 2014 Objectives

    1. Characterization of freshly emitted SSA. Freshly emitted SSA will be generated with
NOAA Pacific Marine Environmental Laboratory's (PMEL) Sea Sweep particle
generator. Sea Sweep allows for the generation and sampling of nascent
particles without contamination and modification by existing atmospheric particles
and gases (Bates et al., J. Geophys. Res., 2012). Properties of the particles to be
characterized include chemical composition, size distribution, number concentration,
cloud-nucleating ability, light scattering as a function of relative humidity, and light
absorption.

2. Characterization of surface and column seawater properties. Surface seawater
properties to be measured include fluorescence (chlorophyll-a), particulate organic
carbon (POC), dissolved organic carbon (Department of Commerce (DOC)), dimethylsulfide (DMS), temperature,
salinity, bubble surface tension, exopolymer gels, phytoplankton species composition,
and nutrients.

3. Assessment of the impact of surface seawater properties on SSA. The response of
nascent SSA properties (composition, size distribution, cloud-nucleating ability) to
changes in ocean biological regime will be determined.";
    String target_sample_rh "47-55%";
    String time_coverage_end "2014-06-04T12:00:00Z";
    String time_coverage_start "2014-05-20T22:00:00Z";
    String title "PMEL Atmospheric Chemistry WACS-2 CCN data";
    Float64 Westernmost_Easting -70.8943;
  }
}

 

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.


 
ERDDAP, Version 2.18
Disclaimers | Privacy Policy | Contact