Web-based Reanalysis Intercomparison Tools (WRIT): Comparing Reanalyses and Observational data.
Wednesday, 17 December 2014
While atmospheric reanalysis datasets are widely used in climate science, many technical issues hinder comparing them to each other and to observations. The reanalysis fields are stored in diverse file architectures, data formats, and resolutions, with metadata, such as variable name and units, that also differ. Individual users have to download the fields, convert them to a common format, store them locally, change variable names, re-grid if needed, and convert units. Comparing reanalyses with observational datasets is difficult for similar reasons. Even if a dataset can be read via Open-source Project for a Network Data Access Protocol (OPeNDAP) or a similar protocol, most of this work is still needed. All of these tasks take time, effort, and money. To overcome some of the obstacles in reanalysis intercomparison, our group at the Cooperative Institute for Research in the Environmental Sciences (CIRES) at the University of Colorado and affiliated colleagues at National Oceanic and Atmospheric Administration’s (NOAA’s) Earth System Research Laboratory Physical Sciences Division (ESRL/PSD) have created a set of Web-based Reanalysis Intercomparison Tools (WRIT) at http://www.esrl.noaa.gov/psd/data/writ/
. WRIT allows users to easily plot and compare reanalysis and observational datasets, and to test hypotheses. Currently, there are tools to plot monthly mean maps and vertical cross-sections, timeseries, and trajectories for standard pressure level and surface variables. Users can refine dates, statistics, and plotting options. Reanalysis datasets currently available include the NCEP/NCAR R1, NCEP/DOE R2, MERRA, ERA-Interim, NCEP CFSR and the 20CR. Observational datasets include those containing precipitation (e.g. GPCP), temperature (e.g. GHCNCAMS), winds (e.g. WASWinds), precipitable water (e.g. NASA NVAP), SLP (HadSLP2), and SST (NOAA ERSST). WRIT also facilitates the mission of the Reanalyses.org
website as a convenient toolkit for studying the reanalysis datasets.