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CRU JRA v1.1: A forcings dataset of gridded land surface blend of Climatic Research Unit (CRU) and Japanese reanalysis (JRA) data; Jan.1901 - Dec.2017.

Update Frequency: Not Planned
Status: Completed
Online Status: ONLINE
Publication State: Citable
Publication Date: 2019-02-25
DOI Publication Date: 2019-02-25
Download Stats: last 12 months

This dataset has been superseded. See Latest Version here

The CRU JRA V1.1 dataset is a 6-hourly, land surface, gridded time series of ten meteorological variables produced by the Climatic Research Unit (CRU) at the University of East Anglia (UEA), and is intended to be used to drive models. The variables are provided on a 0.5 deg latitude x 0.5 deg longitude grid, the grid is near global but excludes Antarctica (this is same as the CRU TS grid, though the set of variables is different) . The data are available at a 6 hourly time-step from January 1901 to December 2017.

The dataset is constructed by combining data from the Japanese Reanalysis data (JRA) produced by the Japanese Meteorological Agency (JMA) and adjusted where possible to align with the CRU TS 3.26 data (see the Process section and the ReadMe file for full details).

The CRU JRA data consists of the following ten meteorological variables: 2-metre temperature, 2-metre maximum and minimum temperature, total precipitation, specific humidity, downward solar radiation flux, downward long wave radiation flux, pressure and the zonal and meridional components of wind speed (see the ReadMe file for further details).

The CRU JRA dataset is intended to be a replacement of the CRUNCEP forcing dataset. The CRU JRA dataset follows the style of Nicolas Viovy's original CRUNCEP dataset rather than that which is available from UCAR. A link to the CRU NCEP documentation for comparison is provided in the documentation section.

If this dataset is used in addition to citing the dataset as per the data citation string users must also cite the following:

Harris, I., Jones, P.D., Osborn, T.J. and Lister, D.H. (2014), Updated
high-resolution grids of monthly climatic observations - the CRU TS3.10
Dataset. International Journal of Climatology 34, 623-642.

Kobayashi, S., et. al., The JRA-55 Reanalysis: General Specifications and
Basic Characteristics. J. Met. Soc. Jap., 93(1), 5-48

Citable as:  University of East Anglia Climatic Research Unit; Harris, I.C. (2019): CRU JRA v1.1: A forcings dataset of gridded land surface blend of Climatic Research Unit (CRU) and Japanese reanalysis (JRA) data; Jan.1901 - Dec.2017.. Centre for Environmental Data Analysis, 25 February 2019. doi:10.5285/13f3635174794bb98cf8ac4b0ee8f4ed.
Abbreviation: Not defined
Keywords: CRU, JRA, CRUJRA, atmosphere, earth science, climate


Previous Info:
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Previously used record identifiers:
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Access rules:
Access to these data is available to any registered CEDA user. Please Login or Register for an account to gain access.
Use of these data is covered by the following licence: When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data lineage:

The CRU JRA data are produced by the Climatic Research Unit (CRU) at the University of East Anglia and are passed to the Centre for Environmental Data Analysis (CEDA) for long-term archival and distribution. This is the first formal release and was provided to CEDA in December 2018.

Data Quality:
The data are quality controlled by the Climatic Research Unit (CRU) at the University of East Anglia. Details are given in the paper Harries et al. 2014 and the release notes, links to both can be found in the documentation.
File Format:
The data are provided as gzipped NetCDF files, with one file per variable, per year. Each file is approximately 330MB when compressed.

Process overview

This dataset was generated by the computation detailed below.
Title Climate Research Unit (CRU) procedure to produce the CRU JRA data.
Abstract The CRU JRA (Japanese reanalysis) data is a replacement to the CRU NCEP dataset, CRU JRA data follows the style of Nicolas Viovy's original dataset rather than that which is available from UCAR. The CRU JRA dataset is based on the JRA-55 reanalysis dataset and aligned where appropriate with the CRU TS dataset version 3.26 (1901-2017). All JRA variables are regridded from their native TL319 Gaussian grid to the CRU regular 0.5° x 0.5° grid, using the g2fsh spherical harmonics routine from NCL (NCAR Command Language), based on the 'Spherepack' code. The exception is precipitation, which is regridded using ESMF 'nearest neighbour': all other algorithms tried exhibited unwanted artifacts. The JRA-55 reanalysis dataset starts in 1958. The years 1901-1957 are constructed using randomly-selected years between 1958 and 1967. Where alignment with CRU TS occurs, the relevant CRU TS data is used. Of the ten variables listed above, the last four do not have analogs in the CRU TS dataset. These are simply regridded, masked for land only, and output as CRUJRA. The other six are aligned with CRU TS as follows: TMP is aligned with CRU TS TMP. A monthly mean for the JRA data is calculated and compared with the equivalent CRU TS mean. The difference between the means is added to every JRA value. --- TMAX and TMIN are aligned with CRUJRA TMP and CRU TS DTR. Firstly, at each time step, the TMAX-TMP-TMIN triplets are checked and adjusted so that TMAX is always >= TMP, and TMIN is always <= TMP. This triplet alignment is prioritised above DTR alignment. Secondly, monthly JRA DTR is calculated by first establishing the daily maxima and minima (max and min of the subdaily values in TMAX and TMIN respectively), then monthly maxima and minima, (means of the daily DTR values), giving JRA monthly DTR. This is compared with CRU TS DTR and the fractional difference (factor) calculated as (CRU TS DTR) / (JRA monthly DTR). This factor is then used to adjust the DTR of each pair of subdaily TMAX and TMIN values, though not if the triplet alignment would be broken. --- PRE is aligned with CRU TS PRE and WET (rain day counts). Firstly, the monthly total precipitation is calculated for JRA and compared to CRU TS PRE; an adjustment factor is acquired (crupre/jrapre) and all values adjusted. Precipitation amounts are now aligned at a monthly level, and this alignment is prioritised above WET alignment. Secondly, the number of rain days is calculated for JRA: a day is declared wet if the total precipitation is equal to, or exceeds, 0.1mm (the same threshold as CRU TS WET). If JRA has more wet days than CRU TS, then the driest of those are reduced to a random amount below 0.1 (an adjustment factor is calculated and applied to each time step, to preserve the subdaily distribution). If JRA has fewer wet days than CRU TS, then sufficient dry days are set to a random amount equal to or closely above 0.1mm, again using an adjustment factor to preserve the subdaily distribution. Where wet day alignment threatens precipitation alignment, the process is abandoned and the cell/month reverts to the previously-aligned precip version. Exception handling is very complicated and cannot be summarised here. --- SPFH is aligned with CRU TS VAP. VAP is converted to SPFH, and JRA mean monthly SPFH is calculated. The fractional difference (factor) is calculated as (CRU TS SPFH) / (JRA monthly SPFH), this factor is then applied to the JRA subdaily humidity values. --- DSWRF is aligned with CRU TS CLD. CLD is converted to shortwave radiation, and JRA mean monthly DSWRF is calculated. The fractional difference (factor) is calculated as (CRU TS SWR) / (JRA monthly DSWRF), this factor is then applied to the JRA subdaily radiation values. --- Where appropriate, CRUJRA values are kept within physically-appropriate constraints (such as negative precipitation), which could result from regridding as well as adjustments.
Input Description None
Output Description None
Software Reference None
  • long_name: Air Temperature
  • gcmd_url:
  • gcmd_keyword: Air Temperature
  • names: Air Temperature

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