2017
DOI: 10.1175/waf-d-17-0023.1
|View full text |Cite
|
Sign up to set email alerts
|

Performance of the New NCEP Global Ensemble Forecast System in a Parallel Experiment

Abstract: A new version of the Global Ensemble Forecast System (GEFS, v11) is tested and compared with the operational version (v10) in a 2-yr parallel run. The breeding-based scheme with ensemble transformation and rescaling (ETR) used in the operational GEFS is replaced by the ensemble Kalman filter (EnKF) to generate initial ensemble perturbations. The global medium-range forecast model and the Global Forecast System (GFS) analysis used as the initial conditions are upgraded to the GFS 2015 implementation version. Th… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

2
91
0

Year Published

2019
2019
2023
2023

Publication Types

Select...
7

Relationship

0
7

Authors

Journals

citations
Cited by 139 publications
(93 citation statements)
references
References 35 publications
2
91
0
Order By: Relevance
“…Initialization was accomplished in cold-start mode, using an arbitrary but consistent set of 12 members of the randomized Global Ensemble Forecast System (GEFS; Zhou et al 2017) data. To eliminate model spinup effects, and to focus unambiguously and without redundancy on the local daily convective cycle, analyses were limited to forecast times from 6 to 30 h inclusive.…”
Section: Methodsmentioning
confidence: 99%
“…Initialization was accomplished in cold-start mode, using an arbitrary but consistent set of 12 members of the randomized Global Ensemble Forecast System (GEFS; Zhou et al 2017) data. To eliminate model spinup effects, and to focus unambiguously and without redundancy on the local daily convective cycle, analyses were limited to forecast times from 6 to 30 h inclusive.…”
Section: Methodsmentioning
confidence: 99%
“…These global data consist of a 21‐member ensemble (20 perturbed members and 1 control member) at 1° × 1° horizontal grid spacing spanning temporally from initialization to 384 hr (16 days). Native horizontal grid spacing is T574 (∼34 km) for the first 8 days and T382 (∼52 km) for the second 8 days (Zhou et al, 2017/07/19, ). SCP was calculated on the 6‐hourly post processed GEFS output following a fixed‐layer approach similar to equation (3) in Thompson et al () SCP=muCAPE1,0000.1emnormalJfalse/kg0.1em×0.1em030.1emkm0.1emSRH1000.1emm2false/s20.1em×0.1em060.1emkm0.1emBWS200.1emnormalmfalse/normals where muCAPE (J/kg) represents convective available potential energy (CAPE) associated with the most unstable parcel in the lowest 255 mb of the model.…”
Section: Methodsmentioning
confidence: 99%
“…These global data consist of a 21-member ensemble (20 perturbed members and 1 control member) at 1 • × 1 • horizontal grid spacing spanning temporally from initialization to 384 hr (16 days). Native horizontal grid spacing is T574 (∼34 km) for the first 8 days and T382 (∼52 km) for the second 8 days (Zhou et al, 2017(Zhou et al, /07/19, 2017. SCP was calculated on the 6-hourly post processed GEFS output following a fixed-layer approach similar to equation (3) in Thompson et al (2003)…”
Section: Gefs Datamentioning
confidence: 99%
“…The GEFS is produced four times per day with a 6 hr interval starting at 0000 GMT. The resolution of the IBC data is approximately 34 km horizontally and 64 hybrid vertical levels (Zhou et al, 2017). The ensemble system has 20 perturbation members and one control member.…”
Section: Forecast Modelmentioning
confidence: 99%