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Record W2509155656 · doi:10.5194/gmd-2016-195

Continuous high resolution mid-latitude belt simulations for July–August 2013 with WRF

2016· article· en· W2509155656 on OpenAlexaboutno aff
Thomas Schwitalla, Hans‐Stefan Bauer, Volker Wulfmeyer, Kirsten Warrach‐Sagi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
Fundersnot available
KeywordsWeather Research and Forecasting ModelClimatologyEnvironmental scienceParametrization (atmospheric modeling)MeteorologyPrecipitationLatitudeNorthern HemisphereConvectionGeologyGeographyGeodesyRadiative transfer

Abstract

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Abstract. The impact of a convection permitting (CP) northern hemisphere latitude-belt simulation with the Weather Research and Forecasting (WRF) model was investigated during the July and August 2013. For this application, the WRF model together with the NOAH land-surface model (LSM) was applied at two different horizontal resolutions, 0.03° (HIRES) and 0.12° (LOWRES). The set-up as a latitude-belt domain avoids disturbances that originate from the western and eastern boundaries and therefore allows to study the impact of model resolution and physical parameterizations on the results. Both simulations were forced by ECMWF operational analysis data at the northern and southern domain boundaries and the high-resolution Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) data at the sea surface. The simulations are compared to the operational ECMWF analysis for the representation of large scale features. To compare the simulated precipitation, the operational ECMWF forecast, the CPC MORPHing (CMORPH), and the ENSEMBLES gridded observation precipitation data set (E-OBS) were used. Compared to the operational high-resolution ECMWF analysis, both simulations are able to capture the large scale circulation pattern though the strength of the Pacific high is considerably overestimated in the LOWRES simulation. Major differences between ECMWF and WRF occur during July 2013 when the lower resolution simulation shows a significant negative bias over the North Atlantic which is not observed in the CP simulation. The analysis indicates deficiencies in the applied combinations of cloud microphysics and convection parametrization on the coarser grid scale in subpolar regions. The overall representation of the 500 hPa geopotential height surface is also improved by the CP simulation compared to the LOWRES simulation apart across Newfoundland where the geopotential height is higher than in the LOWRES simulation due to a northward shift of the location of the Atlantic high pressure system. Both simulations show higher wind speeds in the boundary layer by about 1.5 m s−1 compared to the the ECMWF analysis. Due to the higher surface evaporation, this results in a moist bias of 0.5 g kg−1 at 925 hPa in the planetary boundary layer compared to the ECMWF analysis. Major differences between ECMWF and WRF occur in the simulation of the 2-m temperatures over the Asian desert and steppe regions. They are significantly higher in WRF by about 5 K both during day- and night-time presumably as a result of different soil hydraulic parameters used in the NOAH land surface model for steppe regions. The precipitation of the HIRES simulation shows a better spatial agreement with CMORPH especially over mountainous terrain. The overall bias reduces from 80 mm at the coarser resolution to 50 mm in the HIRES simulation and the root mean square error is reduced by about 35 % when compared to the CMORPH precipitation analysis. The precipitation distribution agrees much better with the CMORPH data than the LOWRES simulation which tends to overestimate precipitation, mainly caused by the convection parametrization. Especially over Europe the CP resolution reduces the precipitation bias by about 30 % to 20 mm as a result of a better terrain representation and due to the avoidance of the convection parameterization.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.236
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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