Constarium
← Search

Data · dataset · 2026

Evaluation of WRF-forecasts over Siberia: Air mass formation, clouds and precipitation

Listed in National Center for Atmospheric Research

The Weather Research and Forecasting (WRF) model was run as a regional model without data assimilation or nudging (31 36h-simulations) for July and December 2005 over a limited area domain covering Siberia to examine weather formation in an air-mass source region.

Description

The WRF-results were compared to NCEP1/NCAR-reanalysis, International Satellite Cloud Climatology Project, Global Precipitation Climatology Centre and Canadian Meteorological Centre data to assess model performance and identify shortcomings.

WRF is capable of predicting air-mass formation. Simulation errors are within the error range of other models. The timing of best/worst agreement differs among quantities depending on their sensitivity to systematic (model deficiencies) and/or unsystematic errors (e.g. initial conditions).

Read the rest (4 more)

Overall, the WRF-results agree better with reanalysis for July than December. WRF-results and reanalysis agree best under persistent high pressure and worst during frontal passages and transition from one pressure regime to another. In July, WRF provides smaller diurnal amplitudes of 2m-temperature with up to 5.4 K lower, and 3.5 K higher values at 0000 and 1200 UTC than the reanalysis.

In December, WRF overestimates 2m-temperature by 1.4 K. WRF-temperatures excellently agree with the reanalysis from 700 hPa to 300 hPa. Except during frontal passages, wind-speed shows positive bias. Typically root-mean-square errors and standard deviation of errors of wind-speed (temperature) increase (decrease) with height.

In December, WRF has difficulty predicting the position and strength of the polar jet. WRF underestimates cloudiness and snow-depth, but overestimates precipitation. In July, predicted convective precipitation is related strongly to boundaries between different land-cover.

WRF-predicted snow-depth strongly correlates with terrain and misses the observed fine features.

Links

Get the data

Where it is published

Catalogue records · 1

Topics

Inferred from text
Simulation 75%
Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
National Center for Atmospheric Researche6e6b8af-91fe-418c-a849-634ecfd381cf10 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].local:field:earth-environmentalmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[field].local:field:ocean-atmosphericmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[method].local:method:simulationenrichment · data ucar edukeyword-concept-rules@1.0.0title+description (75%)
created_datesource · data ucar educonnector:data_ucar_edu@1.0.0
descriptionsource · data ucar educonnector:data_ucar_edu@1.0.0/notes
publication_datesource · data ucar educonnector:data_ucar_edu@1.0.0
titlesource · data ucar educonnector:data_ucar_edu@1.0.0/title
updated_datesource · data ucar educonnector:data_ucar_edu@1.0.0