served from IRI/LDEO Climate Data Library
Models NMME Cansips FORECAST MONTHLY vgrd: Meridional Wind data
Cansips FORECAST MONTHLY Meridional Wind from Models NMME: North American Multi-Model Ensemble (NMME).Independent Variables (Grids)
- Lead
- grid: /L (months) ordered (0.5 months) to (11.5 months) by 1.0 N= 12 pts :grid
- Ensemble Member (realization)
- grid: /M (unitless) ordered (1.0) to (20.0) by 1.0 N= 20 pts :grid
- Pressure Level (air_pressure)
- grid: /P (hPa) ordered (200 hPa) to (850 hPa) N= 2 pts :grid
- Forecast Start Time (forecast_reference_time)
- grid: /S (months since 1960-01-01) ordered (0000 1 Sep 2015) to (0000 1 Jul 2019) by 1.0 N= 47 pts :grid
- longitude (longitude)
- grid: /X (degree_east) periodic (0) to (1W) by 1.0 N= 360 pts :grid
- latitude (latitude)
- grid: /Y (degree_north) ordered (90S) to (90N) by 1.0 N= 181 pts :grid
Other Info
- bufferwordsize
- 4
- datatype
- realarraytype
- grib_name
- VGRD
- gribPDSpattern
- 04XXXX
- missing_value
- 9.99900026E20
- pointwidth
- 650.0
- standard_name
- northward_wind
- units
- m s-1
- standard units*
- meter second-1
References
Kirtman_etal2014Last updated: Tue, 08 Dec 2020 21:56:07 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| L | M | P | S | X | Y | |
 Models NMME Cansips FORECAST MONTHLY vgrd[ X Y | L M P S] | M | M | M | 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 L M P S
- Differentiate along X Y L M P S
- Take differences along X Y L M P S
RMS (root mean square with mean *not* removed) over X Y L M P S | X Y X L X M X P X S Y L Y M Y P Y S L M L P L S M P M S P S | X Y L X Y M X Y P X Y S X L M X L P X L S X M P X M S X P S Y L M Y L P Y L S Y M P Y M S Y P S L M P L M S L P S M P S | X Y L M X Y L P X Y L S X Y M P X Y M S X Y P S X L M P X L M S X L P S X M P S Y L M P Y L M S Y L P S Y M P S L M P S | X Y L M P X Y L M S X Y L P S X Y M P S X L M P S Y L M P S | X Y L M P S |
RMSA (root mean square with mean removed) over X Y L M P S | X Y X L X M X P X S Y L Y M Y P Y S L M L P L S M P M S P S | X Y L X Y M X Y P X Y S X L M X L P X L S X M P X M S X P S Y L M Y L P Y L S Y M P Y M S Y P S L M P L M S L P S M P S | X Y L M X Y L P X Y L S X Y M P X Y M S X Y P S X L M P X L M S X L P S X M P S Y L M P Y L M S Y L P S Y M P S L M P S | X Y L M P X Y L M S X Y L P S X Y M P S X L M P S Y L M P S | X Y L M P S |
Maximum over X Y L M P S | X Y X L X M X P X S Y L Y M Y P Y S L M L P L S M P M S P S | X Y L X Y M X Y P X Y S X L M X L P X L S X M P X M S X P S Y L M Y L P Y L S Y M P Y M S Y P S L M P L M S L P S M P S | X Y L M X Y L P X Y L S X Y M P X Y M S X Y P S X L M P X L M S X L P S X M P S Y L M P Y L M S Y L P S Y M P S L M P S | X Y L M P X Y L M S X Y L P S X Y M P S X L M P S Y L M P S | X Y L M P S |
Minimum over X Y L M P S | X Y X L X M X P X S Y L Y M Y P Y S L M L P L S M P M S P S | X Y L X Y M X Y P X Y S X L M X L P X L S X M P X M S X P S Y L M Y L P Y L S Y M P Y M S Y P S L M P L M S L P S M P S | X Y L M X Y L P X Y L S X Y M P X Y M S X Y P S X L M P X L M S X L P S X M P S Y L M P Y L M S Y L P S Y M P S L M P S | X Y L M P X Y L M S X Y L P S X Y M P S X L M P S Y L M P S | X Y L M P S |
Detrend (best-fit-line) over X Y L M P S | X Y X L X M X P X S Y L Y M Y P Y S L M L P L S M P M S P S | X Y L X Y M X Y P X Y S X L M X L P X L S X M P X M S X P S Y L M Y L P Y L S Y M P Y M S Y P S L M P L M S L P S M P S | X Y L M X Y L P X Y L S X Y M P X Y M S X Y P S X L M P X L M S X L P S X M P S Y L M P Y L M S Y L P S Y M P S L M P S | X Y L M P X Y L M S X Y L P S X Y M P S X L M P S Y L M P S | X Y L M P S |
Note on units