Web-based Reanalyses Intercomparison Tools (WRIT)
PSD has created a set of web-based reanalyses comparison tools:
Monthly/seasonal plotting page: Allows users to make maps and vertical cross-sections from various reanalyses. Statistics include means, anomalies and climatologies. Users can also difference the various reanalyses for all three types of statistics (for any overlapping date in the reanalyses). Composites (averaging multiple dates) are also available.
Monthly timeseries extractor/analyzer: Extracts timeseries at specified lat/lon or lat/lon ranges and either plots the time-series, time-series differences, and scatter plots. Various statistics are returned in addition to numeric values of the time-series plotted. Ability to plot and compare climate index time-series such as the PNA or Niño3.4 or upload your own.
Monthly correlation plotter: Calculates correlations (and regressions) of the reanalysis and observational dataset with supplied atmospheric/ocean indices or user uploaded time-series. Users can plot correlations at different lead/lags. They can also create vertical cross-section correlation plots.
Trajectory generator: Allows users to plot forward and backward air trajectories from different reanalyses (currently NCEP R1, NCEP R2, and 20CR, and ERA-Interim). Users can plot the trajectories of one or more levels on a single plot. The output is plotted on a map and is available as netCDF and as KMZ files suitable for Google Earth.
Distribution analyzer: Allows users to plot and compare the distributions of daily data during a season from different sources including different reanalyses (currently NCEP R1 and 20CR) and observed data. Users can see where data values have fallen historically and can see how different distribution assumptions impact the tails of the distribution.
Vertical Profiles: Allows users to plot different vertical products from reanalyses including skew-T, variable/height, timeXheight, and vertical transects (daily data).
We are exploring the feasibility of various tools. The features we hope to have are:
- Daily time scale composites
- Sub-Daily composites
- Spatial correlation comparing different reanalyses