Embed Size (px)
DESCRIPTION
Page 3© Crown copyright 2006 OLR Errors & Saharan Dust Conclusion: OLR errors over the Western Sahara at 1200 UTC during May-August 2004 can be explained by failure to include the strong greenhouse effect of high amounts of desert dust in the model … see Haywood et al. (2004) JGR Aerosol Optical Depth
Citation preview
Page 1© Crown copyright 2006
Modelled & Observed Atmospheric Radiation Balance during the West
African Dry Season.
Sean Milton, Glenn Greed, Malcolm Brooks, R.Allan* & A. Slingo*
Met Office, Exeter, UK
*ESSC, Reading University
AMMA SOP0 Meeting 15 May 2007
Page 2© Crown copyright 2006
Outline1. Systematic Errors in current NWP models & Role of
Aerosols
Global Model evaluation vs ARM (Niamey) & GERB –Dec 05 to Mar 06
2. Evaluating a dust parametrization.
6-9 March Saharan Dust event
Performance in Saharan regional Model
Page 3© Crown copyright 2006
OLR Errors & Saharan Dust
Conclusion: OLR errors over the Western Sahara at 1200 UTC during May-August 2004 can be explained by failure to include the strong greenhouse effect of high amounts of desert dust in the model
…see Haywood et al. (2004) JGR
Aerosol Optical Depth
Page 4© Crown copyright 2006
Observations available over Africa during 2006
SOP1&2
SOP3
Jan-Feb 2006 DABEX/DODO
Aug 2006 DODO2
ARM mobile facility - Niamey
RADAGAST
Page 5© Crown copyright 2006
NWP Forecast Systems – Unified Model
UK 4km
Regional
12km
Global 40km•60 hour forecast twice/day•144 hour forecast twice/day•+EPS 24member, 90km
50 levels
Saharan Regional Model 20km
Page 6
Atmospheric Radiation Balance
© Crown copyright 2006
Page 7© Crown copyright 2006
SW Radiation Balance – SurfaceMid Dec 2005 – mid Apr 2006
Accuracy +/- 9Wm-2
Page 8© Crown copyright 2007
Surface Albedo (Annual): Model – MODIS
UM too dark UM too bright
Page 9© Crown copyright 2006
Importance of Aerosols for NWP
Global UM - ARMAOT 440nm Banizoumbou
AOT
440n
m
8 Mar Dust Event
Page 10© Crown copyright 2006
Near surface Temperatures – Model vs ARM
Page 11© Crown copyright 2006
Dust Parametrization – Woodward 2001
Threshold friction velocity defined for particles from .06 to 2000 microns (previously .06 to 60)
9 Bins in Horizontal Flux (3 sand)
Inhibition of dust from steep slopes – numerical issues
Use of IGBP (1km) soil source data in place of Wilson-Henderson-Sellers (1985) 1 deg data (NWP only).
Reduce threshold friction velocity by 0.15 m/s in NWP
Use global “nudged” soil moisture to initialise Saharan CAMM.
Soils Data
Uplift(v*, soil moisture)
TransportDeposition
Six dust sizes0.03 -30 microns
ConvBL mixing
GravitationalSettling
Wet
Page 12© Crown copyright 200606 March 00Z06 March 12Z07 March 12Z08 March 12Z
SEVERI Images of Dust 6-9 March 2006
Page 13© Crown copyright 2006
1-5 day global model forecastN216 L38Initialised 12UTC 4 March 2006
Page 14© Crown copyright 2006
Impact of Dust on Radiation balance – Day 4 Forecasts 12 UTC 8th March
Page 15© Crown copyright 2006
Net SW
Net LW
ARM200 Wm-2
Reduction SW
Model100 Wm-2
Reduction In SW due to
inclusion of dust
Page 16© Crown copyright 2006
Page 17© Crown copyright 2006
Saharan CAMM Dust loading – Aug 2006
Saharan CAMM TOMS AI (1980-92)
A
B
CA
B
C
(TOMS AI from Engelstaedter et. al, Earth Science Reviews, 2006)
Page 18© Crown copyright 2006
Comparisons of Saharan CAMM with AERONETDakar (Senegal)
Aerosol Optical Thickness at 555 nm - August 2006
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
1 6 11 16 21 26 31
Day of August 2006
AO
T at
555
nm
AERONET (level 1.5 data)
CAMM (re-run)
3.6
Banizoumbou (Niger)Aerosol Optical Thickness at 555 nm - August 2006
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
1 6 11 16 21 26 31
Day of August 2006
AO
T at
555
nm
AERONET (level 1.5 data)
CAMM (re-run)
CAMM (re-run at +2deg N)
CAMM (re-run +4deg N)
3.53.23.1
Andreas KeilGlenn Greed
Page 19© Crown copyright 2006
SummaryAerosols – Failure to account for dust (and biomass
burning?) in current NWP versions causes significant errors in the radiation balance over Africa.
Specification of surface albedo over Africa is poor leading to systematic underestimates of reflected SW- review
Mineral Dust Parametrization Performs well in both Global and Saharan Model – major
Saharan dust outbreak predictable 4 days in advance. Uncertainties
Dust optical properties Dust uplift Vertical distribution Predicted Size distributions
Page 20© Crown copyright 2006
FutureFurther comparison of Dust in model with aircraft data
from DODO/DABEX and GERBIL.
Tuning of dust radiative properties – single scatter albedo.
More work on dust uplift (PDRA Reading D.Ackerley)
Impacts on the circulation – test in THORPEX.
Dust operational in Southern Asia Model by 2008. Global NWP Model? – simplified dust parametrization.
