Daily GPCP Precip

Load in Python

from intake import open_catalog

cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/precip.NASA-GPCCV1.2.yaml")
ds=cat.netcdf.read()

Metadata

title	Daily GPCP Precip
location	/shared/subx/verif/prsfc/daily/orig
tags	verif,model,daily
catalog_dir	https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/precip.NASA-GPCCV1.2.yaml
last updated	2020-03-31

Dataset Contents

<xarray.Dataset>
Dimensions:  (lat: 180, lon: 360, time: 6148)
Coordinates:
  * lat      (lat) float32 89.5 88.5 87.5 86.5 85.5 ... -86.5 -87.5 -88.5 -89.5
  * lon      (lon) float32 0.5 1.5 2.5 3.5 4.5 ... 355.5 356.5 357.5 358.5 359.5
  * time     (time) float64 2.451e+06 2.451e+06 ... 2.457e+06 2.457e+06
Data variables:
    precip   (time, lat, lon) float32 dask.array<chunksize=(365, 180, 360), meta=np.ndarray>
Attributes:
    title:         Daily GPCP Precip
    long_title:    Version 1.2 GPCP One-Degree Daily Precipitation Data Set
    comments:      none
    institution:   IRI
    source:        IRI
    CreationDate:  2017/11/09 16:25:27
    CreatedBy:     kpegion
    MatlabSource:  getpdailygpcpIRI

xarray.Dataset

Dimensions:
- lat: 180
- lon: 360
- time: 6148

Coordinates: (3)

lat

(lat)

float32

89.5 88.5 87.5 ... -88.5 -89.5

standard_name :: latitude
long_name :: latitude
units :: degrees_north

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
standard_name :
longitude
long_name :
longitude
units :
degrees_east
```
array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5], dtype=float32)
```
time
(time)
float64
2.451e+06 2.451e+06 ... 2.457e+06
standard_name :
time
long_name :
Time of measurements
units :
julian_day
```
array([2451180., 2451181., 2451182., ..., 2457325., 2457326., 2457327.])
```

Data variables: (1)

precip

(time, lat, lon)

float32

dask.array<chunksize=(365, 180, 360), meta=np.ndarray>

name :: precip
long_name :: precip
units :: mm/day

	Array	Chunk
Bytes	1.59 GB	94.87 MB
Shape	(6148, 180, 360)	(366, 180, 360)
Count	51 Tasks	17 Chunks
Type	float32	numpy.ndarray

Attributes: (8)
title :
Daily GPCP Precip
long_title :
Version 1.2 GPCP One-Degree Daily Precipitation Data Set
comments :
none
institution :
IRI
source :
IRI
CreationDate :
2017/11/09 16:25:27
CreatedBy :
kpegion
MatlabSource :
getpdailygpcpIRI