iTacs6（iTacs6c）Beta Version Quick Reference

0. Notes

IMPORTANT!! To generate the intended figures in iTacs6, it is essential to understand the concept of dimensions. Data can have up to five dimensions (year, time, lev, lat, lon). By changing the settings for each dimension, dimensions can be reduced to three or fewer (four or more dimensions are currently not supported). Figures shown in Section 3, "Types of Figures Available," are generated according to the remaining dimensions.

Dimension	Setting Item	Options (default in bold)	Selection for Dimension Reduction
year	TimeOption	range / year-to-year / year-to-year-sd	range
time	Dataset1 or 2	ave / range	ave
lev	Vertical	none / range	none
lon	Lon	range / ave	ave
lat	Lat	range / ave	ave

Note: year-to-year is a concept in which the time dimension is leapfrogged year by year. For example, when year = year-to-year, time = range, and lon/lat = ave, time series for a selected period are overlaid for multiple years (e.g., June-August time series from different years on the same graph). When performing statistical analyses of interannual variability, select year-to-year.

Note: year-to-year-sd uses Dataset2 as a standardized value based on the years included in year-to-year. When Dataset2 is specified as an area-mean value and Method = composite is selected, the Threshold option can be used effectively.

Warning! When year = range and time = range, the maximum continuous period that can be loaded is limited for system performance reasons:

For monthly data: 60 months
For daily data: 366 days

Warning! Because pull-down menus are generated dynamically, after changing Dataset or Elem, wait until the browser finishes loading before making the next selection.

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Current Specifications and Known Issues

When Dataset1 and Dataset2 are both one-dimensional time series, they are displayed as separate figures rather than as an overlay plot.
For user_data, only one-dimensional data are currently supported.

2. Available Datasets

For each dataset type, the following information is provided: <Data period type> [Available period]. Dates are based on UTC.

Long-Term Atmospheric Reanalysis Data (JRA-3Q)

jra3q: Basic JRA-3Q variables (positive divergence values indicate divergence). <day, month> [1947/1/1 – two days before the current date]
jra3q_surf: Surface variables excluding the basic JRA-3Q variables (positive vertical flux values indicate upward flux). <day, month> [1947/1/1 – two days before the current date (three days for some variables)]
jra3q_plev: Pressure-level variables. <day, month>[1947/1/1 – two days before the current date]
jra3q_isen: Isentropic-level variables. <day, month>[1947/1/1 – two days before the current date]

Sea Surface Temperature Data

cobe2: COBE SST Ver2 (only use in-situ data. <day, month> [1890/1/1 – previous month]
mgdsst: MGDSST (use both in-situ data and remotely sensed data). <day, month> [1982/1/1 – previous day]

OLR Data

olr: NOAA OLR. <day, month> [1974/6/1 – two days before the current date; some missing data exist in the 1970s]

Global Ocean Data Assimilation (MOVE-G3)

move_ts: Ocean temperature, salinity, etc. <pentad, month> [1947/1 – previous month or pentad]
move_uv: Ocean currents, etc. <pentad, month> [1947/1 – previous month or pentad]

Forecast Data

k1: One-month forecast data. <day> [2 to 32 days after the initial date]
cps: Six-month forecast data <month>[From the month following initialization through six months ahead]

3. Available Figure Types

Note: The primary figure requested will be displayed first. Additional figures, such as the distribution of the selected data itself, may also be displayed for reference.

Note: Data such as OLR and SST are interpolated onto the same grid as JRA-3Q (1.25° resolution) before analysis and plotting.

One-Dimensional Data

Time Series Plot

Two-Dimensional Data

Spatial Distribution Map
Vertical Cross Section (Latitude or Longitude)
Time Cross Section (Latitude, Longitude, or Vertical Level)
Time-Series Spaghetti Plot (Overlay of Multiple One-Dimensional Series)

Three-Dimensional Data

Spatial Spaghetti Plot (Overlay of Multiple Two-Dimensional Fields)

4. Dataset2 and Analysis ( Timeoption and Method )

TimeoptionとMethod

Method = none / difference → Available for all TimeOptions: range / year-to-year / year-to-year-sd
Method = trend / regression / composite / eof / svd → Available only for: year-to-year / year-to-year-sd

Dataset2 = none

Method = none / difference / trend / regression / composite / eof / svd

none: Plot Dataset1 normally (default).
trend: Plot the trend of Dataset1.
eof: Plot EOF results of Dataset1.
difference / composite / regression / svd: Ignored and treated as none.

Dataset2 = others

Method = none / composite / regression / eof / svd

none: Plot overlaid fields of Dataset1 and Dataset2 (default).
difference: Plot the difference between Dataset1 and Dataset2.
trend: Plot trends of Dataset1 and Dataset2 separately.
composite: Plot composites when the one-dimensional Dataset2 exceeds the specified threshold (uses Threshold).
regression: Plot correlation and regression results between Dataset1 and Dataset2.
eof: Perform EOF analyses separately for Dataset1 and Dataset2.
svd: Plot SVD results between Dataset1 and Dataset2.

6. Other Settings

Kind for Analysis

anom / hist / norm

anom: Histrical anomaly data relative to climatology.
hist: Histrical observed data.
norm: Climatological normal data.

Note: forecast datasets (K1/CPS), observed values and anomalies are selected directly as Elem options; therefore, this setting is ignored.

Lon / Lat（range / ave）

range: Analyze and plot within the specified latitude/longitude range.
ave: Calculate and use the average over the specified region.

Vertical（none / range）

none: Use the vertical level specified in Level.
range: Calculate and use the average over the specified region.