JRA-25 Atlas > Explanation

Explanation about JRA-25


The Japan Meteorological Agency (JMA) and the Central Research Institute of Electric Power Industry (CRIEPI) completed a cooperative research project named "Japanese 25-year Reanalysis (JRA-25)" in March 2006, 5 years after the start of the project. JRA-25 is a long-term global atmospheric reanalysis produced using JMAfs data assimilation and forecast system and supercomputing resources provided by CRIEPI. JRA-25 covers 26 years from 1979 to 2004. The latest version available in 2004 of JMAfs numerical data assimilation system and specially collected observational data were used to generate a consistent and high quality reanalysis dataset designed for climatological research, operational climate monitoring and seasonal forecasting. The global model used in JRA-25 has a spectral resolution of T106 (equivalent to a horizontal grid spacing of around 120km) and 40 vertical layers with the top at 0.4hPa. Since completion of the project, the JMA Climate Data Assimilation System (JCDAS) has been successively operated with the same data assimilation system as JRA-25, to generate quasi-real-time products. Onogi et al. (2007) provide more details.

Observational data

Observational data used in JRA-25 were collected from the JMA archives and those supplied by many organizations overseas such as the European Centre for Medium-Range Weather Forecasts (ECMWF), the National Center for Environmental Prediction (NCEP), the National Center for Atmospheric Research (NCAR) and the National Climatic Data Center (NCDC). Sets of observational data were also supplied by universities in Japan.

In addition to conventional surface and upper air observations, atmospheric motion vector (AMV) winds retrieved from geostationary satellites, brightness temperatures from the TIROS Operational Vertical Sounder (TOVS) and advanced TOVS (ATOVS), precipitable water retrieved from radiances measured by satellite microwave radiometers and other satellite data were assimilated with a 3-dimensional variational method (3D-Var). JRA-25 introduced some new historical observational data which had not been used in earlier reanalyses. Wind profile retrievals surrounding tropical cyclones were supplied by Dr. M. Fiorino. Chinese daily snow depth data reported in the "Monthly Surface Meteorological Data of China" published by the China Meteorological Administration were digitized and used for the first time in JRA-25.

Distributions of sea surface temperature (SST), sea ice and ozone concentrations are given to the model as boundary data. For SST, daily Centennial in-situ Observation-Based Estimates of variability of SST and marine meteorological variables (COBE) (Ishii et al. 2005) data produced by JMA were used. COBE was produced for the purpose of providing a consistent centennial marine dataset covering the whole of the 20th century. Daily sea ice distribution data were produced from brightness temperatures from the Special Sensor of Microwave Imager (SSM/I) on the Defense Meteorological Satellite Program (DMSP) satellite and the Scanning Multichannel Microwave Radiometer (SMMR) on the NIMBUS-7 satellite (Matsumoto et al. 2006). Daily profiles of ozone concentration were produced with a chemical transport model developed by the Meteorological Research Institute (MRI) of JMA (Shibata et al. 2005) with "nudging" applied towards total ozone data observed by the Total Ozone Mapping Spectrometer (TOMS) on board the NIMBUS and other satellites.

For CO2 concentration, a globally constant value, 375ppm, was used for the whole period in JRA-25.


Firstly, predicted 6-hour accumulated precipitation in JRA-25 compares well with observations, exhibiting little bias, especially in the tropics. The correlation of global total precipitation from JRA-25 with both the Merged Analysis of Precipitation of the Climate Prediction Center (CMAP) (Xie and Arkin, 1997) and Global Precipitation Climatology Project (GPCP) ver.2 (Adler et al. 2003) observational precipitation datasets is quite high compared with other reanalyses, especially for the period when SSM/I precipitable water was available for assimilation. Time series of global-average precipitation in JRA-25 is rather stable throughout the period without being affected much by volcanic eruptions. In JRA-25, TOVS radiance data that may have been affected by bias associated with changes of satellites were excluded. Takahashi et al. (2006) showed that geographical distributions of the frequency of daily heavy rains in JRA-25 are similar to the GPCP over the western tropical Pacific, indicating that JRA-25 has enough potential to represent extreme precipitation events.

Secondly, JRA-25 is the first reanalysis that assimilated wind profiles around tropical cyclones from historical best track information; tropical cyclones were analyzed properly in all the regions in the world(Hatsushika et al., 2006).

Additionally, low-level clouds along the western coast of the subtropical continents are well simulated and snow depth analysis is also of good quality.

On the other hand, there are some problems in JRA-25, as there are in all reanalyses. Precipitation in the Amazon basin is analyzed less well than other reanalyses. Another problem exists in the stratosphere. Temperature in the stratosphere has jumps depending on changes of satellites because the observational data were assimilated with a biased model background.


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