applications of radio occultation data to weather, climate and space weather at ncep “where...
TRANSCRIPT
Applications of Radio Occultation Data to Weather, Climate and Space Weather at
NCEP
“Where America’s Climate, Weather, Ocean and Space Weather Services Begin”
COSMIC 2 Senior Management MeetingTaipei, Taiwan
July 15, 2010
Dr. Louis W. UccelliniNational Centers for Environmental Prediction
Director
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Outline
• NOAA: Mission and Goals
• NCEP Support for the NOAA Mission
• COSMIC’s Contribution– Numerical Weather Prediction– Space Weather Analysis– Climate Monitoring and Analysis
• COSMIC 2– Plans, Preparations, & Prospects
• Summary
NOAA Mission and Next Generation Strategic Goals
NOAA’s Long-Term Goals: • Climate Adaptation and Mitigation: An informed society
anticipating and responding to climate and its impacts
• Weather-Ready Nation: Society is prepared for and responds to weather-related events
• Healthy Oceans: Marine fisheries, habitats, and biodiversity are sustained within healthy and productive ecosystems
• Resilient Coastal Communities and Economies: Coastal and Great Lakes communities are environmentally and economically sustainable 3
NOAA’s Mission: To understand and predict changes in Earth’s environment and conserve and manage coastal and
marine resources to meet our Nation’s economic, social, and environmental needs
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Organization: Central component of NOAA National Weather Service
NCEP Supports the NOAA Seamless Suite of Climate, Weather, and Ocean Products
Vision: The Nation’s trusted source, first alert and preferred partner for environmental prediction services
Mission: NCEP delivers science-based environmental predictions to the nation and the global community. We collaborate with partners and customers to produce reliable, timely, and accurate analyses, guidance, forecasts and warnings for the protection of life and property and the enhancement of the national economy.
Space Weather Prediction Center
NCEP Central OperationsClimate Prediction Center Environmental Modeling Center Hydromet Prediction Center Ocean Prediction Center
Tropical Prediction Center Storm Prediction Center
Aviation Weather Center
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Research, Development and Technology Infusion
Respond & Feedback
Respond & Feedback
NCEP’s Role in NOAA’s Seamless Suite of Products and Forecast Services
IBM Supercomputer Gaithersburg, MD DistributeDistribute
ObserveObserve
Products & Forecast Services
To Serve Diverse Customer Base
e.g., Energy Officials, DHS/FEMA, Emergency
Managers, Water Resource Planning, Transportation,
Health organizations (CDC…)
NCEP
Feedback
- Process- Assimilate- Predict
- Process- Assimilate- Predict
Prediction is now inherently linked to numerical models
CentralGuidanceCentral
GuidanceLocal
OfficesLocal
Offices
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Air Quality
WRF NMM/ARWWorkstation WRF
WRF: ARW, NMMETA, RSM GFS, Canadian Global Model
Regional NAM
WRF NMM
North American Ensemble Forecast System
Hurricane GFDLHWRF
GlobalForecastSystem
Dispersion
ARL/HYSPLIT
Forecast
Severe Weather
Rapid Updatefor Aviation
ClimateCFS
3.5B Obs/Day
Short-RangeEnsemble Forecast
NOAA’s NWS Model Production Suite
MOM3
NOAH Land Surface Model
Coupled
Global DataAssimilation
OceansHYCOM
WaveWatch III
NAM/CMAQ
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Reg
iona
lD
A
Reg
iona
lD
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Satellites + Radar99.9%
Satellite Data used in NWP at NCEP
• HIRS sounder radiances• AMSU-A sounder radiances• AMSU-B sounder radiances• GOES sounder radiances• GOES, Meteosat, GMS
winds• GOES precipitation rate• SSM/I precipitation rates• TRMM precipitation rates• SSM/I ocean surface wind
speeds• ERS-2 ocean surface wind
vectors
• Quikscat ocean surface wind vectors
• AVHRR SST• AVHRR vegetation fraction• AVHRR surface type• Multi-satellite snow cover• Multi-satellite sea ice• SBUV/2 ozone profile and
total ozone• Altimeter sea level
observations (ocean data assimilation)
• AIRS• MODIS Winds• COSMIC
~34 instruments
Through collaborative efforts with the NASA-NOAA-DoD Joint Center for Satellite Data Assimilation
Forecast Performance
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CDAS/Reanl vs GFSNH/SH 500Hpa day 5
Anomaly Correlation (20-80 N/S)
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1979 1989 1999 2009
YEAR
An
om
aly
Co
rre
lati
on
NH GFS
SH GFS
NH CDAS/R1
SH CDAS/R1RecordValues
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Evolution of NWP Skill
• Skill increase results from multiple factors– Model improvements
• Increased resolution, better physics, etc.
– Data assimilation advances• Improved DA systems, QC, etc.
– More and better observations• Satellites provide majority of data used and impact
attributable to observations
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The Impacts of COSMIC on Numerical Models
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• Operational use of COSMIC in GFS commenced on 1 May 2007
• Observations from Metop/GRAS and GRACE-A added in February 2010
• Data from SAC-C is expected to be assimilated operationally soon
• The assimilation of COSMIC (and other GPS RO sensors) into the regional system (NAM) is under pre-operational testing
Impact with COSMIC
• AC scores (the higher the better) as a function of the forecast day for the 500 mb gph in Southern Hemisphere
• 40-day experiments:– expx (NO COSMIC)
– cnt (old RO assimilation code - with COSMIC)
– exp (operational code
- with COSMIC)COSMIC provides 8 hours of gain in model forecast skill starting at day 4 !!!
Cucurull et al., 2010, WAF
• Skill score dropouts impact NCEP’s global model performance in Northern and Southern Hemispheres
• Dropouts are defined by 5-day anomaly correlation (AC) scores < 0.70
• For example, the 00Z Feb. 03 2008 case, using GPSRO data alleviated a dropout in the Southern Hemisphere.
• Looking into lack of bias in COSMIC as important influence on data analysis
(Courtesy of DaNa Carlis, NCEP)
SH 5-day AC scores:
GFS=0.65 (NCEP’s model)GDAS=0.69ECMWF=0.83
First guess+nodata=0.70First guess+conven=0.68First guess+conven+amsua=0.70First guess+conven+airs=0.75 First guess+conven+amsub=0.77First guess+conven+mhs=0.78First guess+conven+gpsro=0.79First guess+conven+mhs+amsub=0.78First guess+conven+gpsro+mhs+amsub=0.87
COSMIC also Produces Positive Impact on “Dropout” Case
COSMIC capable of alleviating ‘dropouts’ in the Southern
Hemisphere
Collaborative Project with Taiwan
• We are very thankful to Taiwan for sponsoring the visits of three scientists during a 3-year program
• Two visitors from the Central Weather Bureau have visited the Joint Center for Satellite Data Assimilation (JCSDA), and a third visitor will arrive in September.– Yen-Chih Shen (1st visitor)
• assimilation of COSMIC in NAM (under pre-operational testing)• GSI will be operational in Taiwan this month.
– Yu-Chun Chen (current visitor)• effects of incorporating compressibility factors in the GPS RO code
– Ling-Ling Tsao (third visitor, to arrive in September)• analyze the impact of GPS RO on correcting biases associated to the IR and
MW sensors consistent with recent results in Taiwan
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Yu-Chun Chen, Ling-Ling Tsao, Lidia Cucurull, Yen-Chih Shen
Looking Forward
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• Space Weather Applications
• Climate Monitoring Potential
• COSMIC II – data distribution
Space Weather Applications
• COSMIC offers superior:– Accuracy & vertical coverage
for ionosphere; e.g., electron density profile (red line)
– Horizontal coverage
• COSMIC II total electron content (TEC) data to be assimilated near real time– Requires 30 min data latency
for 0-24h fcst of scintillations • 1 of top 2 SWPC priorities
because scintillation may degrade other GPS applications through loss of signal lock 16
Looking forward: Whole Atmosphere ModelLooking forward: Whole Atmosphere Model
Whole Atmosphere Model (WAM) will provide a unified framework for both NWP and SWx applications:
•Extend GFS up to 600 km•Assimilate COSMIC 2data throughout entire model domain (space weather and terrestrial weather applications)
Climate Monitoring Potential
• 30 years NOAA POES data – Microwave Sounding Unit (MSU)– Advanced MSU (AMSU)– Stratospheric Sounding Unit (SSU)
• Issues as climate data record:– Short overlaps, orbital decay,
diurnal drift, variable antenna patterns, etc.
• 3 current methods to construct temperature time series:
– Remote Sensing Systems (RSS)– Univ. of Alabama-Huntsville
(UAH) method– Simultaneous Nadir Overpass
(SNO) at NOAA NESDIS
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Consider a Fourth Method:• Adjust the observed MSU brightness temperatures for the lower stratosphere (TLS) to match bias-free COSMIC GPSRO data • Compare 3 current methods to GPSRO adjustment (next slide)
Which is Best?
LATE AFTERNOON
MORNING
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Mean(RSS‐RO_AMSU) =‐0.99Std (RSS‐RO_AMSU) =1.67R=0.99
Mean(UAH‐RO_AMSU) =0.02Std (UAH‐RO_AMSU) =2.06R=0.99
Mean(NOAA‐RO_AMSU) =-0.49Std (NOAA‐RO_AMSU) =0.5R=0.99
• UAH gives smallest mean TLS difference (0.02 K) compared to COSMIC GPSRO adjustment• NESDIS’ SNO produces smallest std dev (0.5 K) compared to COSMIC Adjustment
• Two years (2006-2008) of COSMIC TLS: -- too short to detect temperature trend
-- provides insight on constructing climate data records from longer time series from other data records (Figure Courtesy B. Ho and C.Z. Zou)
RSS
UAH
SNO
COSMIC-II Data Distribution
Comparison of sounding distribution over three hour periods between COSMIC and COSMIC-II is shown.
• 8000-12000 profiles per day • Average profile within 45 minutes• Full vertical profile• All weather• Day and night• No instrument drift or calibration• Global coverage• 0.001 TEC Unit relative• Electron Density Profile 10%• S4 index uncertainty – 0.1
• Could evolve to 15-20 min max latency with satellite to satellite links
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Summary
• COSMIC has demonstrated ability of GPSRO to help address NOAA’s Mission Goals for weather prediction, climate, and space weather analysis
• COSMIC II can make even greater contribution – via reduced data latency and denser distribution
• NOAA is fully supportive of COSMIC 2 mission• Goal: NOAA will be prepared to make operational
use of COSMIC 2 data at launch for– Space weather
– NWP
– Climate records21