Applications of Radio Occultation Data to Weather, Climate and Space Weather at NCEP “Where America’s Climate, Weather, Ocean and Space Weather Services.

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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 Meeting Taipei, Taiwan July 15, 2010 Dr. Louis W. Uccellini National Centers for Environmental Prediction Director 1

2 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

4 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 Operations Climate Prediction Center Environmental Modeling Center Hydromet Prediction Center Ocean Prediction Center Tropical Prediction Center Storm Prediction Center Aviation Weather Center

5 Research, Development and Technology Infusion Respond & Feedback NCEP’s Role in NOAA’s Seamless Suite of Products and Forecast Services IBM Supercomputer Gaithersburg, MD Distribute Observe 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 Central Guidance Central Guidance Local Offices Local Offices

6 Air Quality WRF NMM/ARW Workstation WRF WRF: ARW, NMM ETA, RSM GFS, Canadian Global Model Regional NAM WRF NMM North American Ensemble Forecast System Hurricane GFDL HWRF Global Forecast System Dispersion ARL/HYSPLIT For eca st Severe Weather Rapid Update for Aviation Climate CFS 3.5B Obs/Day Short-Range Ensemble Forecast NOAA’s NWS Model Production Suite MOM3 NOAH Land Surface Model Coupled Global Data Assimilation Oceans HYCOM WaveWatch III NAM/CMAQ 6 Regional DA Regional DA Satellites + Radar 99.9%

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 8

Record Values 9

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 10

The Impacts of COSMIC on Numerical Models 11 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 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=0.69 ECMWF=0.83 First guess+nodata=0.70 First guess+conven=0.68 First guess+conven+amsua=0.70 First guess+conven+airs=0.75 First guess+conven+amsub=0.77 First guess+conven+mhs=0.78 First guess+conven+gpsro=0.79 First guess+conven+mhs+amsub=0.78 First 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 (1 st 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 14 Yu-Chun Chen, Ling-Ling Tsao, Lidia Cucurull, Yen-Chih Shen

Looking Forward 15 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 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 18 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

19 Mean(RSS ‐ RO_AMSU) = ‐ 0.99 Std (RSS ‐ RO_AMSU) =1.67 R=0.99 Mean(UAH ‐ RO_AMSU) =0.02 Std (UAH ‐ RO_AMSU) =2.06 R=0.99 Mean(NOAA ‐ RO_AMSU) =-0.49 Std (NOAA ‐ RO_AMSU) =0.5 R=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 ( ) 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 profiles per day Average profile within 45 minutes Full vertical profile All weather Day and night No instrument drift or calibration Global coverage TEC Unit relative Electron Density Profile 10% S4 index uncertainty – 0.1 Could evolve to min max latency with satellite to satellite links

21 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 records 21