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Studying the Impact of Saharan Dust on Tropical Cyclone Evolution using WRF/ Chem and EnKF. Jianyu Liang (York U.) Yongsheng Chen (York U.) Zhiquan Liu (NCAR). Acknowledge: Avelino Arellano , Ziqiang Jiang, Yongxin Zhang. Image: NASA. Saharan Air Layer (SAL). - PowerPoint PPT Presentation
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Studying the Impact of Saharan Dust on Tropical Cyclone Evolution
using WRF/Chem and EnKF
Jianyu Liang (York U.)Yongsheng Chen (York U.)
Zhiquan Liu (NCAR)
Acknowledge: Avelino Arellano, Ziqiang Jiang, Yongxin Zhang
Image: NASA
Definition: elevated layer of Saharan air and mineral dust, warm, dry, and enhanced easterly jet to the south
Origin: begin from near the costal of Africa. Under the influence of African easterly waves, the air mass often moved towards west from the North African coast ( Burpee 1972)
Duration : The SAL usually originate form late spring and remain exist to early fall.
Coverage : It cover a very large region in the North Atlantic Ocean
Vertical extend : During the summer, the dry ,well mixed SAL can reach around 500 hPa height (Calson and Prospero, 1972).
Saharan Air Layer (SAL)
Positive impact:Enhance easterly waves growth and potentially cyclongenesis(eg., Karyampudi and Carison, 1988)
Negative impact:1)Bring dry and warm air into tropical storms, thus increase stability2)Enhance the vertical wind shear to suppress the developments of tropical storms(eg., Dunionand Velden2004; Sun et al. 2009)
Objectives:Use WRF-CHEM and DART to quantify the impact of SAL on TCs.Hurricane Earl (2010) is chosen to be the first case.
Impact of SAL on Tropical Cyclones
Methodology
1)WRF-CHEM model• The chemistry component including dust variables in addition
to the meteorological component;• both components use the sametime steps, grid , transport
schemes, and the same physics schemes for subgrid-scale transport (Grell, etc. 2005).
• GOCART dust
2) DART• Assimilate MODIS aerosol optical depth (AOD) at 550 nm in
addition to conventional observations• Localization in variables and space• Fixed prior covariance inflation
Hurricane Earl case
Figure 1 Hurricane Earl best track from 25th , August to 4th September, 2010. ( FromCangialosi 2011)
Figure 2. Forecast from the model from 0000 UTC 26th , August to 0000 UTC 30, August. ( From Cangialosi 2011)
Figure 3. +METEOSAT-7/GOES-11 combined Dry Air/SAL Product (source: University of Wisconsin-CIMSS) ,red A indicate the position of hurricane Earl .
(b) 26th, August.
(a) 25th, August.
Temperature (oC) from AIRS. at 1000hPa
Temperature (oC) from AIRS. at 850hPa
Relative humidity from AIRS. at 1000hPa
Relative humidity from AIRS. at 850hPa
Optical_Depth_Land_And_Ocean_Mean(0~1) from MODIS L3 product . a) 23, August . b) 24th, August
Resolution: 36 km West-east: 310; North-South: 163; Vertical: 57GOCART simple aerosol scheme , RRTMG radiation scheme, Mellor-Yamada Nakanishi and Niino Level 2.5 PBL, Grell 3D cumulus, Lin microphysics schemeEnsemble: 20 members
Experiment Design
1) Generating ensemble perturbations in chemistrya. spin up for 20 days starting from 00UTC, 01 August 2010b. updating meteorological fields by FNL every 6 hoursc. spin-up cycle stops at 20,August , 2012
2) Generating ensemble perturbation in meteorological fieldsRandomly draw from 3DVAR error covariance
3) Data assimilation cycles and forecastFirst, assimilate conventional observations 6-hourly for 1 dayThen, cycle 6-hourly for 4 days
a) Assimilate conventional observations onlyb) Assimilate conventional and MODIS AOD observations
Finally, forecast with/without chemistry using WRF-CHEM
Standard deviation of Modis AOD from model at 00UTC, 21 August 2012.
average observaton error~ 0.2
12UTC, 24,August, 2010
Dust size bin 1
with modis - without modis
Dust size bin 1 (assimilate modis, level 11)
Relative humidity (assimilate modis , level 11)
12UTC, 24,August, 2010
Relative humidity difference
with modis - without modis
12UTC, 24,August, 2010
Temperature difference
with modis - without modis
Temperature (assimilate modis , level 11)
Compare hurricane evolution in different experiments
MU
Assimilate MODIS, with chemistry
Assimilate MODIS, no chemistry
No MODIS assimilation , chemistry
00UTC 27, August ,2010 Surface dry pressure perturbation
00UTC 28 Surface wind speed
Assimilate MODIS, with chemistry
Assimilate MODIS, no chemistry
No MODIS assimilation , chemistry
Summary 1)Simple GOCART scheme in WRF/CHEM can represent the SAL to some extend.2)MODIS AOD product can be assimilated into the model. It can change the chemistry field and impact on the meteorological field through the chemistry interaction with meteorological field 3)Dust can influence the hurricane intensity significantly in this case
Future work1)Use different chemistry schemes such as MOSAIC , which includes interaction between the aerosols and the microphysics processes2)Conduct more case study and understand the physical mechanism of dust impact on the tropical cyclone formation and evolution .