RIHN aphrodite V1101 APHRO_MA_025deg precip: precipitation data
APHRO_MA_025deg precip precipitation from RIHN aphrodite V1101: Asian precipitation products created by the Research Institute for Humanity and Nature and Meteorological Research Institute of Japan Meteorological Agency.Independent Variables (Grids)
- Time (time)
- grid: /T (days since 1960-01-01) ordered (1200 1 Jan 1951 - 1200 2 Jan 1951) to (1200 30 Dec 2007 - 1200 31 Dec 2007) by 1.0 N= 20818 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) ordered (60.125E) to (149.875E) by 0.25 N= 360 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (14.875S) to (54.875N) by 0.25 N= 280 pts :grid
Other Info
- datatype
- realarraytype
- file_missing_value
- -99.900002
- missing_value
- NaN
- pointwidth
- 0
- units
- mm /day
- standard units*
- 1.15740740740741×10-08 meter second-1
References
Hamada, A., O. Arakawa and A. Yatagai, 2011: An automated quality control method for daily rain-gauge data. Global Environmental Research, V15N2, pp183-192.Xie, P., A. Yatagai, M. Chen, T. Hayasaka, Y. Fukushima, C. Liu, and S. Yang (2007). A gauge-based analysis of daily precipitation over East Asia, Journal of Hydrometeorology, 8, 607-627.
Yatagai, A. O. Arakawa, K. Kamiguchi, H. Kawamoto, M. I. Nodzu and A. Hamada (2009): A 44-year daily gridded precipitation dataset for Asia based on a dense network of rain gauges, SOLA, 5, 137-140, doi:10.2151/sola.2009-035.
Yatagai, A., K. Kamiguchi, O. Arakawa, A. Hamada, N. Yasutomi and A. Kitoh (2012): APHRODITE: Constructing a Long-term Daily Gridded Precipitation Dataset for Asia based on a Dense Network of Rain Gauges, Bull. Amer. Meteor. Soc., 93, 1401–1415. doi: http://dx.doi.org/10.1175/BAMS-D-11-00122.1
Last updated: Mon, 16 Feb 2015 21:51:22 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
 RIHN aphrodite V1101 APHRO_MA_025deg precip[ X Y | T] | M | M | M |
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Filters
Here are some filters that are useful for manipulating data. There are actually many more available, but they have to be entered manually. See Ingrid Function Documentation for more information.- Monthly Climatology calculates a monthly climatology by averaging over all years.
- anomalies calculates the difference between the (above) monthly climatology and the original data.
- Integrate along X Y T
- Differentiate along X Y T
- Take differences along X Y T
RMS (root mean square with mean *not* removed) over X Y T | X Y X T Y T | X Y T |
RMSA (root mean square with mean removed) over X Y T | X Y X T Y T | X Y T |
Maximum over X Y T | X Y X T Y T | X Y T |
Minimum over X Y T | X Y X T Y T | X Y T |
Detrend (best-fit-line) over X Y T | X Y X T Y T | X Y T |
Note on units