Feedstock: chirps20-global-daily

latitude
(latitude)
float32
-49.97 -49.92 ... 49.92 49.97
axis :
Y
long_name :
latitude
standard_name :
latitude
units :
degrees_north
```
array([-49.975   , -49.925   , -49.875   , ...,  49.874992,  49.924995,
        49.975   ], shape=(2000,), dtype=float32)
```
longitude
(longitude)
float32
-180.0 -179.9 ... 179.9 180.0
axis :
X
long_name :
longitude
standard_name :
longitude
units :
degrees_east
```
array([-179.975  , -179.925  , -179.875  , ...,  179.875  ,  179.92499,
        179.975  ], shape=(7200,), dtype=float32)
```

time

(time)

datetime64[ns]

1981-01-01 ... 2024-10-31

axis :: T
standard_name :: time

array(['1981-01-01T00:00:00.000000000', '1981-01-02T00:00:00.000000000',
       '1981-01-03T00:00:00.000000000', ..., '2024-10-29T00:00:00.000000000',
       '2024-10-30T00:00:00.000000000', '2024-10-31T00:00:00.000000000'],
      shape=(16010,), dtype='datetime64[ns]')

precip

(time, latitude, longitude)

float32

dask.array<chunksize=(200, 200, 720), meta=np.ndarray>

geostatial_lat_max :: 50.0
geostatial_lat_min :: -50.0
geostatial_lon_max :: 180.0
geostatial_lon_min :: -180.0
long_name :: Climate Hazards group InfraRed Precipitation with Stations
standard_name :: convective precipitation rate
time_step :: day
units :: mm/day

	Array	Chunk
Bytes	858.84 GiB	109.86 MiB
Shape	(16010, 2000, 7200)	(200, 200, 720)
Dask graph	8100 chunks in 2 graph layers
Data type	float32 numpy.ndarray

latitude

PandasIndex

PandasIndex(Index([-49.974998474121094,  -49.92499923706055,             -49.875,
        -49.82499694824219,  -49.77499771118164, -49.724998474121094,
        -49.67499923706055,             -49.625,  -49.57499694824219,
        -49.52499771118164,
       ...
        49.524993896484375,   49.57499694824219,   49.62499237060547,
         49.67499542236328,  49.724998474121094,  49.774993896484375,
         49.82499694824219,   49.87499237060547,   49.92499542236328,
        49.974998474121094],
      dtype='float32', name='latitude', length=2000))

longitude

PandasIndex

PandasIndex(Index([-179.97500610351562,  -179.9250030517578,            -179.875,
       -179.82501220703125, -179.77500915527344, -179.72500610351562,
        -179.6750030517578,            -179.625, -179.57501220703125,
       -179.52500915527344,
       ...
        179.52499389648438,  179.57501220703125,             179.625,
        179.67498779296875,  179.72500610351562,  179.77499389648438,
        179.82501220703125,             179.875,  179.92498779296875,
        179.97500610351562],
      dtype='float32', name='longitude', length=7200))

time

PandasIndex

PandasIndex(DatetimeIndex(['1981-01-01', '1981-01-02', '1981-01-03', '1981-01-04',
               '1981-01-05', '1981-01-06', '1981-01-07', '1981-01-08',
               '1981-01-09', '1981-01-10',
               ...
               '2024-10-22', '2024-10-23', '2024-10-24', '2024-10-25',
               '2024-10-26', '2024-10-27', '2024-10-28', '2024-10-29',
               '2024-10-30', '2024-10-31'],
              dtype='datetime64[ns]', name='time', length=16010, freq=None))

Conventions :: CF-1.6
acknowledgements :: The Climate Hazards Group InfraRed Precipitation with Stations development process was carried out through U.S. Geological Survey (USGS) cooperative agreement #G09AC000001 "Monitoring and Forecasting Climate, Water and Land Use for Food Production in the Developing World" with funding from: U.S. Agency for International Development Office of Food for Peace, award #AID-FFP-P-10-00002 for "Famine Early Warning Systems Network Support," the National Aeronautics and Space Administration Applied Sciences Program, Decisions award #NN10AN26I for "A Land Data Assimilation System for Famine Early Warning," SERVIR award #NNH12AU22I for "A Long Time-Series Indicator of Agricultural Drought for the Greater Horn of Africa," The National Oceanic and Atmospheric Administration award NA11OAR4310151 for "A Global Standardized Precipitation Index supporting the US Drought Portal and the Famine Early Warning System Network," and the USGS Land Change Science Program.
creator_email :: pete@geog.ucsb.edu
creator_name :: Pete Peterson
documentation :: http://pubs.usgs.gov/ds/832/
faq :: http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ
ftp_url :: ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-latest/
history :: created by Climate Hazards Group
institution :: Climate Hazards Group. University of California at Santa Barbara
pangeo_forge_build_git_hash :: https://github.com/leap-stc/chirps_feedstock/commit/eb9bd016eae20db0b5236c6ce49ebdb0b7a619c1
pangeo_forge_build_timestamp :: 2024-11-19T21:19:44.192735+00:00
pangeo_forge_gh_actions_url :: https://github.com/leap-stc/chirps_feedstock/actions/runs/11921952174
reference :: Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros, D.H., Verdin, J.P., Rowland, J.D., Romero, B.E., Husak, G.J., Michaelsen, J.C., and Verdin, A.P., 2014, A quasi-global precipitation time series for drought monitoring: U.S. Geological Survey Data Series 832, 4 p., http://dx.doi.org/110.3133/ds832.
title :: CHIRPS Version 2.0
version :: Version 2.0
website :: http://chg.geog.ucsb.edu/data/chirps/index.html

latitude
(latitude)
float32
-49.97 -49.92 ... 49.92 49.97
axis :
Y
long_name :
latitude
standard_name :
latitude
units :
degrees_north
```
array([-49.975   , -49.925   , -49.875   , ...,  49.874992,  49.924995,
        49.975   ], shape=(2000,), dtype=float32)
```
longitude
(longitude)
float32
-180.0 -179.9 ... 179.9 180.0
axis :
X
long_name :
longitude
standard_name :
longitude
units :
degrees_east
```
array([-179.975  , -179.925  , -179.875  , ...,  179.875  ,  179.92499,
        179.975  ], shape=(7200,), dtype=float32)
```

time

(time)

datetime64[ns]

1981-01-01 ... 2024-10-31

axis :: T
standard_name :: time

array(['1981-01-01T00:00:00.000000000', '1981-01-02T00:00:00.000000000',
       '1981-01-03T00:00:00.000000000', ..., '2024-10-29T00:00:00.000000000',
       '2024-10-30T00:00:00.000000000', '2024-10-31T00:00:00.000000000'],
      shape=(16010,), dtype='datetime64[ns]')

precip

(time, latitude, longitude)

float32

dask.array<chunksize=(200, 200, 720), meta=np.ndarray>

geostatial_lat_max :: 50.0
geostatial_lat_min :: -50.0
geostatial_lon_max :: 180.0
geostatial_lon_min :: -180.0
long_name :: Climate Hazards group InfraRed Precipitation with Stations
standard_name :: convective precipitation rate
time_step :: day
units :: mm/day

	Array	Chunk
Bytes	858.84 GiB	109.86 MiB
Shape	(16010, 2000, 7200)	(200, 200, 720)
Dask graph	8100 chunks in 2 graph layers
Data type	float32 numpy.ndarray

latitude

PandasIndex

PandasIndex(Index([-49.974998474121094,  -49.92499923706055,             -49.875,
        -49.82499694824219,  -49.77499771118164, -49.724998474121094,
        -49.67499923706055,             -49.625,  -49.57499694824219,
        -49.52499771118164,
       ...
        49.524993896484375,   49.57499694824219,   49.62499237060547,
         49.67499542236328,  49.724998474121094,  49.774993896484375,
         49.82499694824219,   49.87499237060547,   49.92499542236328,
        49.974998474121094],
      dtype='float32', name='latitude', length=2000))

longitude

PandasIndex

PandasIndex(Index([-179.97500610351562,  -179.9250030517578,            -179.875,
       -179.82501220703125, -179.77500915527344, -179.72500610351562,
        -179.6750030517578,            -179.625, -179.57501220703125,
       -179.52500915527344,
       ...
        179.52499389648438,  179.57501220703125,             179.625,
        179.67498779296875,  179.72500610351562,  179.77499389648438,
        179.82501220703125,             179.875,  179.92498779296875,
        179.97500610351562],
      dtype='float32', name='longitude', length=7200))

time

PandasIndex

PandasIndex(DatetimeIndex(['1981-01-01', '1981-01-02', '1981-01-03', '1981-01-04',
               '1981-01-05', '1981-01-06', '1981-01-07', '1981-01-08',
               '1981-01-09', '1981-01-10',
               ...
               '2024-10-22', '2024-10-23', '2024-10-24', '2024-10-25',
               '2024-10-26', '2024-10-27', '2024-10-28', '2024-10-29',
               '2024-10-30', '2024-10-31'],
              dtype='datetime64[ns]', name='time', length=16010, freq=None))

Conventions :: CF-1.6
acknowledgements :: The Climate Hazards Group InfraRed Precipitation with Stations development process was carried out through U.S. Geological Survey (USGS) cooperative agreement #G09AC000001 "Monitoring and Forecasting Climate, Water and Land Use for Food Production in the Developing World" with funding from: U.S. Agency for International Development Office of Food for Peace, award #AID-FFP-P-10-00002 for "Famine Early Warning Systems Network Support," the National Aeronautics and Space Administration Applied Sciences Program, Decisions award #NN10AN26I for "A Land Data Assimilation System for Famine Early Warning," SERVIR award #NNH12AU22I for "A Long Time-Series Indicator of Agricultural Drought for the Greater Horn of Africa," The National Oceanic and Atmospheric Administration award NA11OAR4310151 for "A Global Standardized Precipitation Index supporting the US Drought Portal and the Famine Early Warning System Network," and the USGS Land Change Science Program.
creator_email :: pete@geog.ucsb.edu
creator_name :: Pete Peterson
documentation :: http://pubs.usgs.gov/ds/832/
faq :: http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ
ftp_url :: ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-latest/
history :: created by Climate Hazards Group
institution :: Climate Hazards Group. University of California at Santa Barbara
pangeo_forge_build_git_hash :: https://github.com/leap-stc/chirps_feedstock/commit/eb9bd016eae20db0b5236c6ce49ebdb0b7a619c1
pangeo_forge_build_timestamp :: 2024-11-19T21:19:44.192735+00:00
pangeo_forge_gh_actions_url :: https://github.com/leap-stc/chirps_feedstock/actions/runs/11921952174
reference :: Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros, D.H., Verdin, J.P., Rowland, J.D., Romero, B.E., Husak, G.J., Michaelsen, J.C., and Verdin, A.P., 2014, A quasi-global precipitation time series for drought monitoring: U.S. Geological Survey Data Series 832, 4 p., http://dx.doi.org/110.3133/ds832.
title :: CHIRPS Version 2.0
version :: Version 2.0
website :: http://chg.geog.ucsb.edu/data/chirps/index.html