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Systematic Errors (Part II). Thomas Jung European Centre for Medium-Range Weather Forecasts. Scope of Part II. Sensitivity to horizontal resolution some recent results some more diagnostics Some methods for understanding the origin of systematic model. Experimental Setup.
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Systematic Errors (Part II) Thomas Jung European Centre for Medium-Range Weather Forecasts
Scope of Part II • Sensitivity to horizontal resolution • some recent results • some more diagnostics • Some methods for understanding the origin of systematic model
Experimental Setup • Cycle 31R1 (oper: 12/09/06-04/06/07) + other cycles for ref • Various horizontal resolutions: • TL95 (200 km = climate prediction) • TL159 (120km = seasonal forecasting) • TL255 (80 km = monthly forecasting) • TL511 (40km = NWP) • 91 levels in the vertical • Period considered: 1990-2005 (-2006) • Two seasons • DJFM with start on 1st November • JJAS with start on 1st May Seasonal integration with the ECMWF model:
Computational Effort • 12% of all CPUs on HPCE cluster • Wall clock time about 20 hours • About 70 times more expensive than TL95! 1 Integration (151 days) @ TL511L91:
Zonal Mean U Error (DJFM) TL95-ERA40 TL159-ERA40 TL255-ERA40 TL511-ERA40
Zonal Mean U Error @ TL95 (DJFM) 31R1 31R1modGWD
TL95L60 TL255L60 TL799L60 Orographic Gravity Waves over Greenland Jung and Rhines, JAS
Weak-Strong Polar Vortex Stratospheric Origin of Mean Z500 Error (DJFM) 31R1modGWD-31R1
Synoptic Z500 Activity (DJFM) TL95-ERA04 TL511-TL95
Extratropical Cyclone Tracking • 6-hourly MSLP data • All data truncated to T40 prior to tracking • Searching for and tracking of MSLP minima • Application of selection criteria (e.g., migratory long-lived systems only) Method of Gulev et al.:
Number of Extratropical Cyclones (Winter) Lifetime > 1day
Number of Extratropical Cyclones (DJFM) Lifetime > 1day
Sensitivity: Different Model Cycles 29R1 31R1
Cy31R1 (T159L91) Cy30R2-Cy31R1 (T159L91) Sensitivity to Model Formulation • Revised cloud scheme • Implicit calculation of convective transports • Modifications to the treatment of orography
Tropical Cyclone Tracking • Detection: • Find area with MSLP below a certain threshold • Check whether there is a warm core above the MSL minimum • Tracking: • Compute trajectories from “different” low pressure minima • Tuning based on ERA-40 data
2005 2006 TL511 TL255 TL159 TL95 Tropical Cyclone Tracks (Atlantic)
TL95-ERA40 TL511-ERA40 TL511-TL95 Vertical Wind Shear (JJAS)
ERA40 TL95-ERA40 TL511-ERA40 TL511-TL95 Synoptic Activity: Vrot @ 700hPa (JJAS)
Madden-and-Julian Oscillation (DJFM) ERA40 TL95 TL159 TL255 TL511
NOAA TL95 TL511 Convectively Coupled Tropical Waves: Sym. OLR Anomalies (JJAS)
Convectively Coupled Tropical Waves: Sym. OLR Anomalies (JJA) NOAA 32R2 @ TL159 32R3 @ TL159
Some Methods for Identifying Model Error • Diagnosing your model output (e.g., climate run) • Easy to perform/diagnose • Everything becomes entangled later in the forecast (difficult to understand causes of errors) • Sensitivity experiments • Suitable to study the response to specific changes • “Fishing”-type experiments (changes usually not optimal) • Comes for free @ ECMWF due to the frequent introduction of new model cycles (“E-suites”) • “Entanglement” might be an issue (studying transient response can help) • Initial tendency and analysis increment approach • Powerful approach to understand model error due to “locality” (see Mark Rodwell’s presentation) • Excellent approach for model assessments (data assimilation system required) • Adjoint sensitivity studies • Provides a set of optimal forcing perturbations which reduce random and systematic forecast error • Relaxation experiments
Perturbation Growth: E-O, SN, Urot and Precip Precipitation Urot and Stream Function Tropical Kelvin waves c=30 m/s -> 2500 km/d
Tropical-Extratropical Interactions: Motivation El Nino Multi-model biases: Similar precipitation biases may lead to similar biases in the extratropics La Nina
Question (and solution?) How do forecast errors in the tropics influence the extratropical flow?
Experimental Setup • Seasonal integrations with prescribed SSTs • Relaxation details: • U, V, T and lnps • Tropics only (20S-20N) • Relaxation strength λ=0.1 • Experimental setup: • TL95L60 (32R1) • Start 10th November • Diagnostics for DJFM 1982-2001
Mask used for localization Mask 0.10 0.09 0.08 0.07 0.06 0.05 0.04 0.03 0.02 0.01 0.00
MJO in ERA40, control and relaxed forecasts ERA-40 Control Relaxed
Systematic Z500 Error: Control vs relaxed forecasts Control Relaxed
Conclusions I • Influence of increasing resolution from TL95 to TL511 has been studied • High resolution is beneficial (e.g, tropical and extratropical cyclones) • Care has to be taken, though, when interpreting results from resolution studies (See GWD example) • Simply increasing resolution alone is not necessarily a cure (see MJO) • The impact of resolution seems to be model dependent (cyclones in 30r2 vs 31r1) • Important: Increasing resolution has to go hand in hand with further model development!
Conclusions II • An overview has been given of techniques, which can be used to identify the origin model problems. • Systematic error: • Simple to do • Not necessarily easy to understand + pitfalls • Sensitivity experiments • Good way to study the impact of model changes • Not necessary optimal (adjoint techniques?) • Initial tendency method (see M Rodwell’s lecture) • Looking at short-range forecasts is a powerful approach (locality, coupling between processes) • Requires a data assimilation system • Relaxation technique: • Potentially powerful tool • More to come (particularly on predictability aspects)