cosmo-next overview - c2sm wiki

Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss

Marco Arpagaus for the COSMO-NExT project team

Swiss COSMO User Workshop December 3, 2014

COSMO-NExT

overview

5 COSMO-NExT overview | Swiss COSMO User Workshop; December 3, 2014 Marco.Arpagaus [at] MeteoSwiss.ch

COSMO-1: O(24 hour) forecasts, 8x per day 1.1km grid size (convection permitting)

Lateral boundary conditions: IFS-HRES

10km 4x per day

Project COSMO-NExT

COSMO-E: 5 day forecasts, 2x per day 2.2km grid size (convection permitting) O(21) ensemble members

Lateral boundary conditions: IFS-ENS

20km 2x per day

ensemble data assimilation: LETKF


Project COSMO-NExT: Sub-Projects and timeline • 4 Sub-Projects

• Ensemble Data Assimilation • COSMO-1 see also talks by Davide, Michael, and Sandie

• COSMO-E see also talk by Christina

• Infrastructure see also talks by Xavier, Stefan, Andrea, and Carlos

• 4 yrs project (2012 – 2015); all systems planned to be operational in 2016


KENDA: km-scale ensemble data assimilation Replace current COSMO nudging assimilation system with a new, state-of-the-art Ensemble Kalman Filter (LETKF: Local Ensemble Transform Kalman Filter)

First Guess

Observations

Analysis

Better analysis through • optimal combination of model

and observations based on error statistics;

• flow-dependent background error statistics based on ensemble;

• much more flexibility in using new observations!

Latest LETKF Experiments: Results

LETKF LETKF_RTPP LETKF_RTPP_SOIL

Wind speed Temperature Humidity

Spread (dashed) and RMSE (solid) wrt 21 radiosondes


KENDA: What we are currently working on …

• validate and tune LETKF for (probabilistic) COSMO-E

analysis • try 12h-23h old IFS-ENS perturbations as LBC • assimilate 2m humidity • use Latent Heat Nudging in LETKF

• next milestones

• compare forecasts from LETKF deterministic analyses against those from nudging analyses (benchmark)

• start regular experimental LETKF analysis (COSMO-E) • start working on (deterministic) COSMO-1 analysis


COSMO-1: Keywords

• Deterministic forecasts with convection-permitting

resolution (1.1 km mesh-size) • Targeted for the very short-range (+24h) • Rapid update cycle with new forecast every 3 hours • On demand mode for key clients • ICs from LETKF, LBCs from IFS-HRES • COSMO-1 has the best representation of the …

• complex Alpine topography • physical processes of extreme weather events


COSMO-1: Developments

• stability of dynamical core over complex topography • external parameters (higher resolution!) • turbulence at O(1km) mesh-size

( “Turbi-Sim” at C2SM; “Turb-i-Box” at Uni Innsbruck) • satellite verification (brightness temperatures) • tuning of COSMO-1: COSMO Priority Project CALMO • …

Mean diurnal cycle of valley winds COSMO-2 vs COSMO-1

Visp (Rhone valley) Cevio (Maggia valley)

average over 18-days (9-27 July; strong diurnal cycle)

“Diurnal wind” stations

Mean maximum wind > 4 m/s 21 stations

“Top-six” stations

Influence of resolution on diurnal cycle: RMSE of wind speed

2km 1km: Improvement for most stations!

“Diurnal wind” stations (21) “Top six” stations

Influence of surface data

“Diurnal wind” stations (21)

Coarse surface data: Only minor improvement for 1km! Need high-resolution surface data for 1km simulation!

Valley Winds: Summary

Large improvement of diurnal valley winds using COSMO-1 only with high-resolution surface data good skill for major valleys with COSMO-1 further improvement with less filtering of topography

Skill related to valley size and grid resolution good skill requires accurate representation of valley topography


COSMO-1: What we are currently working on …

• porting COSMO-1 code to GPU;

regular runs on Tödi (on GPUs!) since a few days …

• Turbi-Sim and Turb-i-Box • investigate choice of LBCs • near-surface winds and roughness length • ice sedimentation (removes high-cloud bias) • more tests in sandbox


COSMO-E: Keywords

• COSMO: convection-permitting resolution (2.2 km

mesh-size, 60 vertical levels); 21 members; Alpine area; runs twice a day up to +120h; ICs from LETKF, LBCs from IFS-ENS

• perturbations • initial conditions: from ensemble data assimilation system

lateral boundary conditions: from IFS-ENS • model errors: Stochastic Perturbation of Physical

Tendencies (SPPT) provides “best estimate” and forecast uncertainty

SPPT: Stochastic Perturbation of Physical Tendencies

𝜕𝜕𝜕𝜕

= 𝐷𝑋 + 𝐾𝑋 + 1 + 𝑟𝑟𝑟𝑟 �𝑃𝑖𝑋𝑁

𝑖=1

horizontal diffusion

physics local tendency

dynamics

𝜕 prognostic variable (u, v, T, qv, qc, qi, qr, qs, qg) 𝑃𝑖𝑋 physical parameterisation scheme i (turbulence, radiation, microphysics, shallow convection, …)

random pattern

copied and adapted from Shutts

every timestep Δt draw N(0,σ) random numbers within a given range on coarse grid Δi, Δj

generate smooth pattern on COSMO grid by interpolating in time and horizontally in space

if required: vertical tapering at model top and close to the surface

random pattern (1+rand)

Δi

Δj

SPPT: Generation of random pattern

copied and adapted from Torrisi

0 1

~ 850 hPa

~ 100 hPa

~ 50 hPa

spread / error: temperature sp

read

/ er

ror

lead-time [h]

winter summer

RMEV STDE RMSE abs(BIAS)

LBCs plus SPPT LBCs

k=59 / ~10 m

spread / error: temperature, 19e110 k-

leve

l

lead-time [h]

RMEV

RMSE abs(BIAS)

STDE

spread / error: temperature, 19e111 k-

leve

l

lead-time [h]

RMEV

abs(BIAS)

STDE

RMSE

spread / error: T, 19e111-19e110 k-

leve

l

lead-time [h]

RMSE abs(BIAS))

STDE RMEV


COSMO-E: Experimental real-time runs

• One forecasts per day (12 UTC) to +120h since mid of

June 2014 • Initial conditions as well as lateral boundary conditions

from IFS-ENS (except free cycling of soil) • lateral boundary conditions: IFS-ENS members 0-20 • model errors: SPPT

COSMO-E vs COSMO-LEPS: BSS Brier Skill Score wrt climatology (2001-2010) based on 300 stations COSMO-E

COSMO-LEPS

• COSMO-E shows significant skill until end of forecast range • clearly better than COSMO-LEPS, even though 9 grid-points

averages used for both


COSMO-E: What we are currently working on …

• include IC perturbations from KENDA • continue work on SPPT (try to increase spread near the

surface)

• comprehensive ensemble verification

Infrastructure: Strategy • ambitious plans for the next generation forecasting system

realized in COSMO-NExT • KENDA • COSMO-1 • COSMO-E

• not feasible both in terms of costs and power envelope • our way out: accelerators and single precision

Today COSMO-NExT on todays hardware

25%

~40x larger problem than current forecasting system


COSMO-NExT: Next steps

• mid 2015

start of pre-operational runs • early 2016

start of operational runs • mid 2016

decommissioning of COSMO-2 & COSMO-7


COSMO-NExT: Summary

• Locally more detailed and more accurate

deterministic forecasts: COSMO-1! • probabilistic forecasts that provide information on

forecast uncertainty and complement the deterministic forecasts (out to +24h): COSMO-E!

• better data assimilation system, eventually including more observational data (e.g., satellites), resulting in more accurate analyses and forecasts: KENDA!

• all systems planned to be pre-operational in mid 2015, operational in 2016; discontinuation of COSMO-2 and COSMO-7 by mid 2016


COSMO-NExT: People André Walser Anne Roches Christina Klasa Daliah Maurer Daniel Leuenberger Guy de Morsier Francis Schubiger Jean-Marie Bettems Jürg Schmidli Luca Weber Marco Arpagaus

Martina Messmer Michael Keller Oliver Fuhrer Petra Baumann Philippe Steiner Pirmin Kaufmann Sandie Moody Steef Böing Stefan Rüdisühli Thomas Leutert …

cosmo-next overview - c2sm wiki

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