On the Predictability of an Advection Fog Event in North China Plain: Sensitivity of the Simulation to

Initial Errors

Qinghong Zhang 张庆红Collaborator: Huiqin Hu, Baoguo Xie

Department of Atmospheric and Oceanic Science, School of Physics, Peking University

Kunming, Yunnan Province 10-31-2012

Email: qzhang@pku.edu.cn

The 4th THORPEX Asia workshop

“Dense fog raided Beijing !“

Fog coverage from satellite NOAA-17

0228 UTC 21 Feb 2007

Fog is high impact weather on aviation, marine and land transportation (Gultepe et al. 2007)

predictability of Fog

Due to the complexity, diversity and the fine scale of process Fog predictability is limited

Fog simulation is sensitive to

Grid resolution (Ballard et al. 1991; Chibe et al. 2003; Muller 2006;)

Physical process(Bott et al. 1990; Brown 1980; Brown and Roach 1976; Fisher and Caplan 1963; Musson-Genon 1987; Rodhe 1962; Zdunkowski and Nielsen 1969)

Initial condition (Musson- Genon 1987; Bergot and Guedalia 1993 Fitzjarrald and Lala 1990; Ballard et al. 1991; etc)

there are few systematic studies focusing on fog predictability associated with the characteristics of initial errors

Objective: sensitive of fog simulation to initial errors

Sensitivity of fog simulation to different kinds of initial errors

with aspects to different magnitudes,

vertical distributions and variables.

Synoptic overview

1200 UTC 20 0000 UTC 21

500 hPa

surface

Contour: GHT

Contour: slpWind barb: u,vShading: rh

H

Longwave radiation Rrtm

Short wave radiation Dudhia scheme

Surface layer QNSE surface layer

Land surface Thermal diffusion scheme

Boundary layer Qusi-Normal Scale Elimination PBL

Cumulus Kain-Fritsch scheme (Only for D1 and D2)

LANDUSE data: Beijing_30s (d03)

NCEP fnl data: 1deg*1deg

time 0000 UTC 20 — 0000 UTC 22, Feb, 2007

domain D01:159*153D02:232*214D03:448*343

Horizontal resolution 27 km;9 km;3 km

e_vert 39 levels(13 levels below 850 hPa)

p_top 50 hPa

Microphysics WSM 6-classs graupel

WRF Experimental design

Fog coverage (visibility less than 1 km for d03) at 27h 0300 UTC 21, Feb 2007

(at the second vertical model layer, ~ 94 m)

Deterministic simulation

An ensemble of 40 members with initial conditions generated by randomly drawing the background error covariance from a fixed covariance model WRF VAR

The initial perturbations were roughly 0.3 g/kg for mixing ratio,3 m/s for winds and 1.2 K for temperature.

Experimental design

Best: M16 M39

Worst: M38

Ensemble simulation of fog coverage at 27h

Ensemble Forecast

BSTM WSEM

Initial Difference

SPTEXP (0.2, 0.4, 0.6, 0.8)

REPEXP(at 10, 20, 30 bottom vertical model layers)

RMVEXP (Qv, , U and V)

Initial Errors

magnitude

Vertical distributions

Most sensitive variables

Experimental design

0300 UTC 21 Feb 2007

Comparison of BEST & WORST Ensemble simulation

0300 UTC 21 Feb 2007

SPTEXP: sensitivity to the magnitude of initial errors

WORST 0.2 initial error 0.4 initial error

0.6 initial error 0.8 initial error BEST

0300 UTC 21 Feb 2007

(~ 1.7 km) (~ 7 km)

(~ 13 km)

REPEXP: sensitivity of vertical distribution of initial error

WORST

BEST

10 bottom levels 20 bottom levels

30 bottom levels 20 top level

Qv T

U,V U, V ofBSTM

(error = BSTM –WSEM)Initial error for d02

0300 UTC 21 Feb 2007

no Qv no T no u, v

no Qv, T no Qv,u,v no Qv, T ,u,v

RMVEXP: sensitivity of different variable of initial errors

WORST

BEST

Evolution of diff (BSTM-N_UV)

0000 UTC 20—0000 UTC 21

0h 6h 12h 18h 24h

T

U,V

Qv

Although fog simulation was highly sensitive to initial errors, the improvement of simulation due to the linearly decreasing of initial errors is nearly linear.

The initial errors at 20 bottom vertical model layers (~7 km) are sufficient to cause the failure of fog simulation in this case.

Fog simulation is much more sensitive to initial errors of horizontal wind than that of water vapor and temperature in this case.

Results from a series of sensitivity experiments in this study should be verified by data assimilation of real data.

Conclusion and discussion

U,V initial error

*

Observation on Offshore Oil Platform over Bohai Sea

T, Td, P, VIS, RH, Wind speed and direction

Highway observation 47 offshore oil platform 3

GPS 43

***

Observation network for FOG project

Surface observation 2137wind profiler 3

Visibility

Thanks