whoi_oaflux_lh (Monthly)

  1. main
  2. obs
  3. gridded
  4. fluxes
  5. LH (Monthly)
  6. whoi_oaflux_lh (Monthly)

Load in Python

from intake import open_catalog

cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/whoi_oaflux_lh.yaml")
ds=cat.netcdf.read()

Metadata

title whoi_oaflux_lh (Monthly)
location /project/airsea/WHOI_OA/LH_oaflux
tags gridded, obs, flux, monthly, global
catalog_dir https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/whoi_oaflux_lh.yaml
last updated 2017-08-01

Dataset Contents

Show/Hide data repr Show/Hide attributes
xarray.Dataset
    • lat: 180
    • lon: 360
    • time: 726
    • lat
      (lat)
      float32
      -89.5 -88.5 -87.5 ... 88.5 89.5
      long_name :
      latitude
      units :
      degrees
      range :
      89.5S to 89.5N
      array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,
       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,
       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,
       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,
       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,
       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,
       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,
       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,
        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,
         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,
        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,
        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,
        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,
        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,
        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,
        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,
        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,
        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5],
      dtype=float32)
    • lon
      (lon)
      float32
      0.5 1.5 2.5 ... 357.5 358.5 359.5
      long_name :
      longitude
      units :
      degrees
      range :
      0.5 to 359.5
      array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5], dtype=float32)
    • time
      (time)
      int64
      1 2 3 4 5 6 7 8 ... 12 1 2 3 4 5 6
      units :
      month
      array([1, 2, 3, ..., 4, 5, 6])
    • lhtfl
      (time, lat, lon)
      float32
      dask.array<chunksize=(12, 180, 360), meta=np.ndarray>
      comments :
      monthly mean surface latent heat flux, positive upward
      units :
      W/m^2
      

      


      
  
    
        Array  Chunk 
      
        
  
    
       Bytes  188.18 MB   3.11 MB 
      
    
       Shape  (726, 180, 360)   (12, 180, 360) 
      
    
       Count  183 Tasks  61 Chunks 
      
    
       Type  float32  numpy.ndarray 
      
        

      
      		



  
  
  

  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  

  
  

  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  

  
  
  

  
  

  
  
  

  
  
  

  
  

  
  360
  180
  726
    • err
      (time, lat, lon)
      float32
      dask.array<chunksize=(12, 180, 360), meta=np.ndarray>
      comments :
      monthly mean estimated error of surface latent heat flux
      units :
      W/m^2
      

      


      
  
    
        Array  Chunk 
      
        
  
    
       Bytes  188.18 MB   3.11 MB 
      
    
       Shape  (726, 180, 360)   (12, 180, 360) 
      
    
       Count  183 Tasks  61 Chunks 
      
    
       Type  float32  numpy.ndarray 
      
        

      
      		



  
  
  

  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  

  
  

  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  

  
  
  

  
  

  
  
  

  
  
  

  
  

  
  360
  180
  726
  • creation_date :
    Dec 2007
    description :
    WHOI Objectively Analyzed air-sea Fluxes (OAFlux) Project
    project_PIs :
    Lisan Yu, Bob Weller
    website :
    http://oaflux.whoi.edu