INTERCOMPARISON – HIRLAM vs. ARPA-SIMCARPE DIEM AREA 1

Per Kållberg Magnus Lindskog

what I want to show here

the HIRLAM system and experiments

comparison of arpa and hirlam analyses

verification of forecasts against own analyses

verification of forecasts against observations

precipitation forecasts

conclusions

•0.1º to 0.4° rotated lat/long grid

•Hydrostatic, hybrid coordinates

•Spectral (double Fourier with extension zone) •Or gridpoints on the C-grid

•Eulerian or semi-Lagrangean time-stepping

•Lateral boundary relaxation - usually ECMWF LBC

•ISBA soil model

•TKE (Turbulent Kinetic Energy) turbulence closure

•Kain-Fritsch convection or ’STRACO’ condensation

HIRLAM (HIgh Resolution Limited Area Model)

•3D-Var or 4D-Var•Multivariate statistical balance: vorticity - divergence - mass - moisture•Scale and latitude dependent geostrophy•Boundary layer friction

•’NMC’-method background error statistics•Ensemble assimilations to replace ’NMC’-method

•Moisture effects with a revised moisture control variable

•Initialization: normal modes or a weak digital filter

•Observation operators include:•Conventional (TEMP PILOT AIREP DRIBU SYNOP SHIP SATOB)

•Raw radiances (TOVS, ATOVS)•Integrated humidity from GPS•Radial winds from Doppler radars

HIRVDA (HIRlam Variational Data Assimilation)

hirlam experiments – nov.3 to nov.8

cdcHIRLAM 6.1. 0.1°/ 0.1° 40 levels3D-Var data assimilationdigital filter initialization (DFI)ECMWF operational analyses on the boundariesECMWF operational conventional observations’straco’ condensation & ’cbr’ turbulence

cddno data assimilation at all, just a +144 forecast from 3 november

cdeas cdc but with revised horizontal structure functions(slightly smaller scales)

comparisons between

the arpa and the hirlam

data assimilations

analysis differences arp – cdc

850 hPa

geopotential6 Nov. 00Z

we have used different

orographies

this affects the post-processing to

pressure levelsand

mean sea level

2 metre temperature analysis differences 00UTC (left) and 12UTC (right)

arpa (left) and hirlam (right) 10 metre wind analyses

mean sea level pressure analysis and SYNOP observations5 November 1999 12ÙTC

arp cdc

mean sea level pressure analysis and SYNOP observations6 November 1999 00ÙTC

arp cdc

comparisons between

the arpa and the hirlam

forecasts

(verified against ’own’ analyses)

the analyses and the +24h forecast errors at the analysis timemean sea level pressure on November 7th 1999

00Z 12Z

cdc

arp arp

cdc

verification against observations

sea level pressure (arp & cdc) fit to SYNOP/SHIP

screen level temperature (arp & cdc) fit to SYNOP/SHIP

screen level dewpoint (top) and total clouds (bottom) (arp & cdc) fit to SYNOP/SHIP

10 metre windspeed (arp & cdc) fit to SYNOP/SHIP (top) and SHIP only (bottom)

850hPa geopotential (arp & cdc) fit to TEMP

850hPa windspeed (arp & cdc) fit to TEMP/PILOT

conclusions from the comparisons with observations

• P_msl: cdc analysis has smaller standard deviation – (arp postprocessing is noisier)

more conclusions from the comparisons with observations

• P_msl: cdc analysis has smaller standard deviation – (arp postprocessing is noisier)

• P_msl 24h forecasts have comparable qualities

more conclusions from the comparisons with observations

• P_msl: cdc analysis has smaller standard deviation – (arp postprocessing is noisier)

• P_msl 24h forecasts have comparable qualities

• 10-metre windspeeds. – cdc biased high, both in anlyses and – worse – in forecasts– arp strong diurnal variations in the analysis biases – good at night, to weak

at day

more conclusions from the comparisons with observations

• P_msl: cdc analysis has smaller standard deviation – (arp postprocessing is noisier)

• P_msl 24h forecasts have comparable qualities

• 10-metre windspeeds. – cdc biased high, both in anlyses and – worse – in forecasts– arp strong diurnal variations in the analysis biases – good at night, to weak

at day

• screen level temperature - analyses– cdc biased warm at daytime, cool at night– arp biased cool at daytime, warm at night

more conclusions from the comparisons with observations

• P_msl: cdc analysis has smaller standard deviation – (arp postprocessing is noisier)

• P_msl: 24h forecasts have comparable qualities

• 10-metre windspeeds– cdc biased high, both in anlyses and – worse – in forecasts– arp strong diurnal variations in the analysis biases – good at night, to weak

at day

• screen level temperature - analyses– cdc biased warm at daytime, cool at night– arp biased cool at daytime, warm at night

• screen level temperature – forecasts– cdc has a cooling drift (well known in SMHI operations)– arp quite biasfree forecasts

more conclusions from the comparisons with observations

• P_msl: cdc analysis has smaller standard deviation – (arp postprocessing is noisier)

• P_msl: 24h forecasts have comparable qualities

• 10-metre windspeeds– cdc biased high, both in anlyses and – worse – in forecasts– arp strong diurnal variations in the analysis biases – good at night, to weak

at day

• screen level temperature - analyses– cdc biased warm at daytime, cool at night– arp biased cool at daytime, warm at night

• screen level temperature – forecasts– cdc has a cooling drift (well known in SMHI operations)– arp quite biasfree forecasts

• total clouds: arp has more clouds than cdc. cdc has a diurnal cycle

more conclusions from the comparisons with observations

• 850hPa geopotential: analyses and forecast essentially similar fits

• 850hPa windspeed: cdc somewhat smaller bias and standard deviation

accumulated precipitation

• cdc 6 Nov. 06Z + 24h

• cde 6 Nov. 06Z + 24h

• arp 6 Nov. 00Z + 24h

• arp 6 Nov. 12Z + 24h

• Rubel 6 Nov. 06Z - 7 Nov. 06Z

• cdd 6 Nov. 06Z – 7 Nov. 06Z

24-hour accumulated precipitation 6 Nov 06Z to 7 Nov 06Z exp:cdc

24-hour accumulated precipitation 6 Nov 00Z to 7 Nov 00Z exp:arp

24-hour accumulated precipitation 6 Nov 12Z to 7 Nov 12Z exp:arp

24-hour accumulated precipitation 6 Nov 06Z to 7 Nov 06Z(Rubel & Rudolf, Wien )

24-hour accumulated precipitation 6 Nov 06Z to 7 Nov 06Z exp:cdd

the somewhat tighter structure functions used in

the hirlam cde experiment

experiment yields somewhat more intense precipitation

than the cdc control experiment

24-hour accumulated precipitation 6 Nov 06Z to 7 Nov 06Z exp:cdc

24-hour accumulated precipitation 6 Nov 06Z to 7 Nov 06Z exp:cde

general conclusions from the comparisons

• pressure and mean sea level differences due to different orographies and different post-processing algorithms

– arp noisier, especially Pmsl and geopotential at 850

• too large scale of the hirlam background errors (0.4°/ 0.4° grid)– new, smaller scale background errors yield slightly more intense

precipitation

• analysis increments on model levels problematic in steep orography

• dfi initialization not ideally tuned for this resolution and such a small area

• long integration (cdd) without D.A. still skillful, but D.A. improves the quality

• cdc Pmsl forecasts have generally smaller errors against own analysis

• precipitation forecasts qualitatively good, – arp has some very intense spots, cdc is somewhat smoother

• and not bad quantitatively either

what we still want to do

•one more hirlam assimilation with a revised turbulent momentum flux

•run some forecasts from each other’s analyses

Grazie mille per la vostra attenzione!