convective indexes calculated from hirlam output st.petersburg the russian state hydrometeorological...

Convective indexes calculated from HIRLAM output

St.PetersburgThe Russian State Hydrometeorological

UniversityFaculty of Meteorology

Meteorological Forecasting DepartmentKanukhina Anna

Aims:

• to estimate possible use of convective indexes calculated on HIRLAM outputs for forecasting of place, beginning time and type of mesoscale convective phenomena

Initial data are HIRLAM analysis and forecast files : • - air temperature at surface and heights at various

periods;• - dew point temperature at surface and heights at

various periods; • - wind parameters at surface and heights at various

periods;• - surface pressure tendencies;• - specific humidity at surface and heights at

various periods;

3 types of indexes:

• diagnostic - atmospheric preparedness for convection development (Г, С, MOCON);

• index having triggering function ( );

• indexes estimating possible type of arising phenomena (CAPE,HEI);

atmosphere statical stability index Г

Ге =

Г =

Ze

eLeU

еГ

moisture convergence

• MOCON=

r –specific humidity, kg/kg;

V – wind speed at 10 m, m/s;

rVVrrV HHHh

generalized index indicating possibility of convective disturbance formation С

Г =

eC 22

еГ

г

г

convective instability indicator (Falkovich’s index) χ

= з

зкнс

EHI energy helicity index

EHI =CAPE*H

Н – relative wind helicity;

CAPE convective available potential energy:

CAP = dzgZh

e

ee

0

Studied cases divided into 3 groups

• 1 group: days with thunderstorms and showers; indexes indicate high possibility of these weather phenomena;

• 2 group: days without any convective phenomena but indexes shows existing possibility of phenomena arising( atmospheric instability);

• 3 group: days associated with thunderstorms and showers; atmosphere is stable according to indexes consideration;

Used data

• HIRLAM forecast;

• HIRLAM analysis;

• sounding data;

• surface observations (synoptic charts OSCAR, registered thunderstorm charts from FMI site http://www.ava.fmi.fi/~tjt/salark.html).

Studied cases

29.06.200019.06.200121-23.11.200103-06.07.200216-20.07.2003

23.11.2001 12UTC

Indexes profiles for

Kardla, Estonia

MOCON, 1/s for Kardla (Estonia) on 23.11.2001 12 UTC

analyse fc=12 fc=24

MOCON and χ scattering graph for 6 h forecast (on base of analisys on 23.11.2001 06:00 UTC and forecast

23.11.2001 00:00 UTC)

С and Γ scattering graph for 6 h forecast (on base of analisys on 23.11.2001 06:00 UTC and forecast

23.11.2001 00:00 UTC)

CAPE and HEI scattering graph for 6 h forecast (on base of analisys on 23.11.2001 06:00 UTC and forecast

23.11.2001 00:00 UTC)

29.06.2000 12UTC

MOCON, CAPE analysis on 29.06.2000 12 UTC

• Thunderstorms chat on 29.06.2000

• (http://www.ava.fmi.fi/~tjt/salark.html)

СAPE and MOCON scattering graph for 24 h forecast (on base of analisys on 29.06.2000 12:00 UTC and forecast

28.06.2000 12:00 )

С and Γ scattering graph for 24 h forecast (on base of analisys on 29.06.2000 12:00 UTC and forecast

28.06.2000 12:00 )

Indexes’ correlation coefficients (forecast and analysis)

• Ряд 1 –С

• Ряд 2 – Γ

• Ряд 3 – χ

• Ряд 4 – СAPE

• Ряд 5 – MOCON

• Ряд 6 – HEI

-0,2

0

0,2

0,4

0,6

0,8

1

1,2

1 2 3 4 5

Number of 3h increament

Co

rre

lati

on

co

eff

icie

nt

0

0,2

0,4

0,6

0,8

1

1,2

1,4

Ряд2

Ряд1

Ряд6

Ряд3

Ряд4

Ряд5

Conclusions

- χ values defined by forecasts have essential distinctions with calculations from analysis and χ can not be used for atmospheric state estimation when forecasting at period more than 6h.

- The same could be said for HEI. - CAPE and MOCON may be used forecasting at

period no more than 12h. - С and Γ forecasts are close to real situation even at

24h forecast period particularly for C values.