Business Systems Intelligence: 7. B.I. Methodologies Dr. Brian Mac Namee (.
E. Cuevas, SDS-WAS NAMEE (AEMET, Spain) J.M. Baldasano, SDS-WAS NAMEE (BSC-CNS, Spain)
description
Transcript of E. Cuevas, SDS-WAS NAMEE (AEMET, Spain) J.M. Baldasano, SDS-WAS NAMEE (BSC-CNS, Spain)
WMO
SDS-WAS Research and Development activities
6th meeting of the WWRP JSC(WMO Headquarters, Geneva, 18-19 July 2013)
E. Cuevas, SDS-WAS NAMEE (AEMET, Spain)
J.M. Baldasano, SDS-WAS NAMEE (BSC-CNS, Spain)
X. Zhang, SDS-WAS EA (CAMS, China)
W. Sprigg, SDS-WAS As (Chapman University, USA)
E. Terradellas SDS-WAS NAMEE (AEMET, Spain)
S. Nickovic (Ex-WMO SDS-WAS, Serbia)
WMO; AREP
Improved Weather and Seasonal Climate prediction
Human Health (Asthma, infections, Meningitis in Africa, Valley Fever in the America’s)
Agriculture (negative & positive impacts)
Industry (Semi-conductor, etc.)Energy (Thermal solar energy)
Aviation (air disasters)
Ground Transportation (high speed rail)
Marine productivity (negative & positive impacts)
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Impacts of Sand and DustImpacts of Sand and Dust
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SDS-WAS MissionSDS-WAS Mission
To enhance the ability of countries to deliver timely and quality sand and dust storm forecasts, observationsforecasts, observations, information and knowledge to usersusers through an international partnership in research and operationsresearch and operations
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WMO Research Program ComponentsWMO Research Program Components
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SDS-WAS research issuesSDS-WAS research issues
Sources
physical, optical and chemical properties
interaction with radiation, clouds and precipitation
Model validation and intercomparison
Ensemble forecasting
Impacts of dust (health, transport, agriculture)
Improve weather, climate and air quality modelling
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History and Milestones in SDS-WASHistory and Milestones in SDS-WAS
2004: International Symposium on SDS & a WMO Experts Workshop on SDS (CMA, Beijing-China).
2005: a questionnaire on SDS to WMO Members indicated 40 interested countries.
2006: Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) proposed (CMA, Beijing-China).
2007: the 14th WMO Congress endorsed the launching of the SDS-WAS
2008: WMO SDS-WAS Implementation plan drafted (Athens, Greece).
2010: First SDS-WAS hands-on training Workshop (BSC, Barcelona-Spain).
Regional node Northen Africa,
Midle-East and Europe
Regional Center
Partner 1
Partner 2Partner 3 Partner 4
Partner 5
Partner n
….
Regional node Americas
WMO SDS-WASWMO SDS-WAS
Preliminary steps
Regional node
West Asia
Regional node
East Asia and Pacific
Regional Center
Partner 1
Partner 2Partner 3 Partner 4
Partner 5
Partner n
….
RC
NEWNEW
SDS-WASSDS-WASa federated systema federated system
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Collaboration MechanismsCollaboration Mechanisms
Flow of information between SDS-WAS system components for a regional node consisting of a consortium of partners supported by the Regional Steering Group and Regional Centre
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SDS-WAS Node structureSDS-WAS Node structure
Asian Node _Regional Centre Asian Node _Regional Centre http://www.sds.cma.gov.cnhttp://www.sds.cma.gov.cn
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Na-ME-E Regional Centre; http://sds-was.aemet.esNa-ME-E Regional Centre; http://sds-was.aemet.es
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A Pan-American CenterA Pan-American Center
for the WMO for the WMO SDS-WAS SDS-WAS
• Information relevant to airborne dust (as it impacts socio‐economic and environmental sectors including health, safety, water supplies, air quality, agriculture, fisheries, commerce and defense) is at the Center’s core.
• The Center facilitates research & applications for North, Central and South America.
• The Pan‐Am Center acts as a node to Exchange information, talent, & infrastructure across the Americas to facilitate progress in predicting, adapting to, and avoiding maladies of airborne dust, crossing scales of weather and climate, región & globe.
William A. Sprigg
Chapman University (USA)
A support from the West Asian UNEP officeA support from the West Asian UNEP office
A short-term project to perform an assessment report on skills and needs for establishing a new WMO SDS-WAS node
A technical UNEP/WMO SDS conference was held in Abu Dhabi (May 2013) to discuss further steps
Future West Asia (Gulf Countries + Iran + Turkey) Future West Asia (Gulf Countries + Iran + Turkey)
for the WMO for the WMO SDS-WAS SDS-WAS
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Current research topics in SDS-WAS Regional Centers Current research topics in SDS-WAS Regional Centers
1. Model validation/evaluation
2. High resolution modelling
3. Data assimilation
4. Long term forecasting
5. Improvement/characterization of dust observations
6. Dust impacts
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1. Model validation/evaluation
MODEL INSTITUTION RUN TIME
DOMAIN DATA ASSIMILATION
BSC-DREAM8b BSC-CNS 12 Regional No
CHIMERE LMD 00 Regional No
LMDzT-INCA LSCE 00 Global No
MACC ECMWF 00 Global MODIS AOD
DREAM-NMME-MACC
SEEVCCC 12 Regional MACC analysis
NMMB/BSC-Dust
BSC-CNS 12 Regional No
MetUM U. K. Met Office 00 Global No
GEOS-5 NASA 00 Global MODIS reflectances
NGAC NCEP 00 Global No
• VARIABLES: Dust surface concentration – Dust Optical Depth at 550 nm• LEAD TIME: 0 – 72 hours, every 3 hours• GEOGRAPHICAL DOMAIN: 25ºW – 60ºE, 0 – 65ºN
• VARIABLES: Dust surface concentration – Dust Optical Depth at 550 nm• LEAD TIME: 0 – 72 hours, every 3 hours• GEOGRAPHICAL DOMAIN: 25ºW – 60ºE, 0 – 65ºN
The modelsThe models
Joint visualization. Dust AOD at 550 nmJoint visualization. Dust AOD at 550 nm
Joint visualization. Surface concentrationJoint visualization. Surface concentration
Model outputs are bi-linearly interpolated to a common 0.5ºlon x 0.5ºlat grid mesh. Then, different multi-model products are generated:•CENTRALITY: median - mean•SPREAD: standard deviation – range of variation
Model outputs are bi-linearly interpolated to a common 0.5ºlon x 0.5ºlat grid mesh. Then, different multi-model products are generated:•CENTRALITY: median - mean•SPREAD: standard deviation – range of variation
Generation of multimodel productsGeneration of multimodel products
Homogenization forecasts Homogenization forecasts in the “Asian Node” in the “Asian Node”
CUACE/Dust +CUACE/Dust +
MASINGAR +MASINGAR +
ADAM +ADAM +
..
..
..
N modelN model
Homogenization forecasts Homogenization forecasts in the “Asian Node” in the “Asian Node”
CUACE/Dust +CUACE/Dust +
MASINGAR +MASINGAR +
ADAM +ADAM +
..
..
..
N modelN model
Asian Node _Regional Centre Asian Node _Regional Centre http://www.sds.cma.gov.cnhttp://www.sds.cma.gov.cn
TAMANRASSET_INMSANTA_CRUZ_TENERIFE
NRT evaluation using AERONET dataNRT evaluation using AERONET data
• Bias Error• Root Mean Square Error• Correlation Coefficient• Fractional Gross Error
• Bias Error• Root Mean Square Error• Correlation Coefficient• Fractional Gross Error
• Near Real Time Observations• Common data processing and
calibration procedures
• Near Real Time Observations• Common data processing and
calibration procedures
Model validation with AERONETModel validation with AERONET
http://sds-was.aemet.es/forecast-products/forecast-evaluation/model-evaluation-metrics
Evaluations• Monthly• Seasonal• Annual
Evaluations• Monthly• Seasonal• Annual
Evaluation of Saharan dust transport over the Atlantic
Source: WHOI
NRT evaluation of dust forecasts with MODIS deepblue: NMMB-BSC/Dust Since June 2013
BIAS
CORRELATION FGE
RMSE
Validation of MACC-fszd reanalysis with PM10 from AMMA
Daily mean values.
AMMA PM10 where filtered by wind direction to assure dust conditions
MACC 3h data were averaged to obtain daily mean surface concentration
Cuevas et al. 2013
Comparative AOD climatology at selected AERONET sites
2007-2008
Cuevas et al. 2013
Comparative spatial climatology of AOD
WINTER Cuevas et al. 20132007-2008
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Validation MACC-fszd extinction vertical profiles with lidars at M’Bour (Senegal) and Tenerife (The Canary Islands, Spain)
Cuevas et al. 2013
M’Bour-Senegal lidar station from LOA (CNRS-Univ. Lille)
WINTER2007-2008
LIDAR (LIRIC algorithm) – MODELS comparison
60 – 80 dust events within the period Jan 2011 – Jun 2013
BSC-DREAM8B_v2
NMMB-BSC/Dust
DREAM8-NMME-MACC
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2. High resolution modelling
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Model nesting strategy
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7:45 PM Phoenix as the dust storm neared.
W.A.Sprigg, S. Nickovic, G. Pejanovic, J. Galgiani, A. Vukovic
Phoenix (Arizona) Haboob, 5 July 2005
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DUST SIMULATION
– 6-km model 10m WIND MAGNITUDE
W.A.Sprigg, S. Nickovic, G. Pejanovic, A. Vukovic
NASA Applied Science support led
to this high-resolution forecast &
simulation capability
Successful simulation of the Phoenix haboob
(Chapman University dust modelling group)
Phoenix
Phoenix
10m WIND MAGNITUDE
NASA Applied Science support led to this high-resolution forecast & simulation capability
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3.3. Data assimilationData assimilation
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Operational Dust assimilation at CMA
36WWRP JSC 21-24 February 2011
Assimilation MODIS AOD in ECMWF MACC
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4.4. Long-term forecastingLong-term forecasting
• (average=15)
SDS Seasonal Prediction : DGAE/SSDS
Yellow is anomaly from average number
of SDS
Yellow is anomaly from average number
of SDS
Light blue and dark blue represents the first and second level (13-14cases) respectively for less than average
Light blue and dark blue represents the first and second level (13-14cases) respectively for less than average
Light red, peach blow and red wine represents the first,
second and third level (16 cases)
respectively for more than average.
Light red, peach blow and red wine represents the first,
second and third level (16 cases)
respectively for more than average.
2007200720072007
2009200920092009
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5.5. Improvement/Characterization of dust Improvement/Characterization of dust observationsobservations
AOD distribution of CARSNET stations
Station name
Ake
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Da
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Da
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Gu
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Ha
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Ho
tan
Hu
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Jiu
qu
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La
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Lh
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Lin
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Min
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Mt.G
ao
lan
Mt.L
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ng
Mt.T
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Mt.W
alig
ua
nN
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nin
gS
ha
ng
dia
nzi
Sh
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gri-
La
Ta
zho
ng
Tia
njin
Uru
mq
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on
gq
iX
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Xili
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Ya
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inch
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nY
ulin
Yu
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Zh
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gb
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Zh
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Zh
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AO
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0n
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0.0
.2
.4
.6
.8
1.0
1.2
1.4
Quality Assured AOD results
CARSNET Mean AOD from 40 stations since 2002
Zhang XY et al., ACP, 2012
Aerosol/dust climatologies
Aerosol characterization in Northern Africa, Northeastern Atlantic, Mediterranean Basin and Middle East from direct-sun AERONET observations
S.Basart, C. Pérez, E. Cuevas, J.M. Baldasano, and G.P. Gobbi
(Atmos. Chem. Phys. October-2009)
Tamanrasset- Argelia
Cairo (Egypt)
Thala (Tunisia)
Ouazarzate (Morocco)
Sand and Dust Storm Sand and Dust Storm Warning System Regional Warning System Regional Center for Norther Africa, Center for Norther Africa, Middle East and EuropeMiddle East and Europe
Increasing the observation capacity in North Africa
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6.6. Dust impactsDust impacts
Improve Weather Forecast via Dust Radiative Forcing (RF) Feedback by CUACE/Dust Operational Forecasting System in
Asian Regional Centre
With dust RFfeedback
Forecastedsurface T
ForecastedVertical T
With dust RFfeedback
Wang et al., JGR, 2010
75%
78%
S/Ca ratio
Normal: 0.73 ; Fog: 6.11
Li et al., 2009 无定形的覆盖物无法使用SAED确定其晶体类型
Individual particle analysis show that 70% of aerosol particles in North China Plain are internally mixed with other two or three sourced aerosols, in which mineral dust play a key role.
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Impact of Saharan dust clouds over North Atlantic on trop-O3
Andrey et al., 2013
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Cuevas et al; 2011: Meningitis linked to mineral dust transport in the Sahel (MACC Report)
Pérez et al; 2013: Soil dust aerosols as predictors of seasonal meningitis incidence in Niger (Environmental Health Perspectives (EPH))
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WMO
Capacity buildingCapacity building• 8-12 Nov 2010: Training Week on Satellite Meteorology. Barcelona-Spain
• 13 Nov 2010: Lectures on Atmospheric Mineral Dust and its Impact on Human Health, Environment and Economy. Barcelona-Spain
• 15-19 Nov 2010 Training Week on WMO SDS-WAS products. Barcelona-Spain
• 22-26 Feb 2011: Training on Meteorological Services, SDS Forecast and Early Warning System. Istanbul-Turkey
• 21-25 Nov 2011: 2nd Training Course on WMO SDS-WAS (satellite and ground observation and modelling of atmospheric dust). Antalya-Turkey
• 5-9 Nov 2012: II Lectures on Atmospheric Mineral Dust. Barcelona-Spain
• 26-28 Nov 2012: Workshop on Meteorology, Sand and Dust Storm (SDS), Combating Desertification and Erosion. Ankara-Turkey
• 8-12 Nov 2010: Training Week on Satellite Meteorology. Barcelona-Spain
• 13 Nov 2010: Lectures on Atmospheric Mineral Dust and its Impact on Human Health, Environment and Economy. Barcelona-Spain
• 15-19 Nov 2010 Training Week on WMO SDS-WAS products. Barcelona-Spain
• 22-26 Feb 2011: Training on Meteorological Services, SDS Forecast and Early Warning System. Istanbul-Turkey
• 21-25 Nov 2011: 2nd Training Course on WMO SDS-WAS (satellite and ground observation and modelling of atmospheric dust). Antalya-Turkey
• 5-9 Nov 2012: II Lectures on Atmospheric Mineral Dust. Barcelona-Spain
• 26-28 Nov 2012: Workshop on Meteorology, Sand and Dust Storm (SDS), Combating Desertification and Erosion. Ankara-Turkey
WMO
Capacity buildingCapacity building
CAS CBS
Research
SDS-WAS
Op
eration
al fo
recasts
SDS-WAS
Exp
erimen
tal fo
recasts
Current
Future
Research
From Research to OperationsFrom Research to Operations
WMO
Successful transition from Research to OperationsSuccessful transition from Research to Operations
The mandatory functions of the Regional Specialized Meteorological Centre (s) with activity specialization in Atmospheric Sand and Dust storm Forecasts (RSMC-ASDF) have been defined and accepted
The consortium AEMET / BSC-CNS designated to host the first RSMC with specialization on atmospheric sand and dust forecast (Dec 2013)
EC-65 Geneva, May 2013EC-65 accepts Spain’s bid and designates Barcelona to host the first RSMC-ASDF
RSMC Barcelona (Northern Africa, Middle East and Europe)
SDS-WAS Research Implementation Plan SDS-WAS Research Implementation Plan
Postponed deadline for final draft (early Spring 2013 ?)
To be reviewed by the Regional Nodes partners
To be submitted to WWRP/JSC (July 2013) for approval• Updated regulations for the RSG and Steering Committee
membership• Emphasizing establishing the SDS-WAS Trust Fund
www.wmo.int
Thank you for your attentionWMO SDS-WAS ([email protected])
SDS-WAS NAMEE ([email protected])
SDS-WAS EA ([email protected])
SDS-WAS As ([email protected])