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Diagnostics of the Nature run By ECMWF PeriodMay1, 2005-May31, 2006 Resolution: T511 91 levels Model: IFS cy31r1 November 16, 2006. Cyclone tracs in the Nature run Thoman Jung, ECMWF. Annual total cyclone track. June. August. September. July. October. December. November. - PowerPoint PPT Presentation
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Diagnostics of the Nature runBy ECMWF
PeriodMay1, 2005-May31, 2006Resolution: T511 91 levels
Model: IFS cy31r1
November 16, 2006
Annual total cyclone track
Cyclone tracs in the Nature runThoman Jung, ECMWF
June
July
August
September
October
November
December
January
February
March
April
May
Comparison between the ECMWF T511 Nature Run against climatology.
20050601-20060531, exp=eskb, cycle=31r1
Adrian Tompkins, ECMWF
TechMemo 452 Tompkins et al. (2004) http://www.emc.ncep.noaa.gov/research/osse/NR/ECMWF_T511_diag/ tm452.pdfJung et al. (2005) TechMemo 471http://www.emc.ncep.noaa.gov/research/osse/NR/ECMWF_T511_diag/tm471.pdfYearly, quarterly and monthly mean files are also posted athttp://www.emc.ncep.noaa.gov/research/osse/NR/ECMWF_NR_Diag/ECMWF_T511_diag
The description of the datahttp://www.emc.ncep.noaa.gov/research/osse/NR/ECMWF_T511_diag/climplot_README.html
SSMI 10m wind Quickscat SFC wind
- Quikscat does not provide winds in rainy areas- Shows known bias in the W Pacific. Model winds are too low indeep convective areas.
SSMIJJA DJFSON MAM
QuickscatJJA DJFSON MAM
Ice Water TOA LW NR-CERES TOA LWCFTop of the atmosphere long-wave cloud forcing
- the NOAA product is only for thin cirrus clouds, with a narrow optical septh range, which makes the comparison unreliable
- Shows lack of deep convection over the tropical land masses. This agrees with evidence from other data sets. Also agrees with earliercomparisons with ERBE data. A long-standing bias that has improved withrecent model changes, but require further attention.
- No product where continually cloudy.- Proves that the IR biases in net radiation are due to clouds.
- This is now dramatically improved compared to earlier cycle of the model, and compared to ERA-40 (for example). - Still small problem in the stratocumulus regions close to the coasts, despite of recent improvements.
**Top of the atmosphere short-wave cloud forcing**Top of the atmosphere short-wave radiation
**Liquid water pathTrmm and SSMI- This is now much better in the trade cumulus regions, than in previous model cycles.- Clear underestimation in western Pacific
**Total-column water vaporTRMM and SSMI- Remarkable agreement in the extra-tropics. Underestimation in the ITCZ.
**Total precipitation, against
GPCP, SSMI, and XieArkin
TRMM, NASDA and RSS
- These comparisons confirm the lack of rainfall over the tropical land masses.- We have an overestimation of precip over the high-SST regions in the tropics.- There is a tendency for deep convection to become locked in with the highest SSTs, which in the east Pacific results in a narrow ITCZ- The TRMM NASDA-3b43 algorithm is presumed to be the most accurate of the two TRMM retrieval products.
SfcfluxAnomalyESKBTop: Latent, Net Bottom: Sensible solar,infrared
- Surface fluxes observations are indirect measurements and are less reliable on a month-by-month basis. Ask Anton Beljaars.
TCC
ICCP MODIS
- This has improved greatly in recent cycles of the model. In particular, the stratocumulus regions have improved.- The apparent underestimation relative to ISCCP over the Sahara is because this product is thought to overestimate cloud cover there. MODIS shows betteragreement with the model over the deserts.- The MODIS product over sea ice is unreliable