NESDIS/STAR’s Satellite Climate Studies Branch (SCSB) and it’s Relationship to CICS – Accomplishments and Future

Focus Areas Ralph Ferraro

Chief, Satellite Climate Studies Branch NOAA/NESDIS/STAR/CoRP

6-7 November 2013 CICS-MD Science Meeting 1

SCSB and CICS • The Satellite Climate Studies Branch

(SCSB), formed in 3/03, exploits the capabilities of Earth-observing satellites to study the climate variations of the atmosphere, the land and the oceans. – Moved to current building May 2008

• The Cooperative Institute for Climate

and Satellites (CICS): – First established 7/83; (CI for Climate

Studies) – Collaborative R&D between NOAA

and UMD utilizing satellite data – A center of excellence – Stimulate training of university

students/post docs for future contributions to NOAA’s workforce

– New CICS grant awarded in 2009, expanded to include CICS-MD, CICS-NC and consortium partners

• Second 5-year award starts in 2014

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Relationship among ESSIC/UMD, NOAA and CICS

GEOG

NWS/CPC ARL NODC

JCSDA

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SCSB Composition • Original SCSB formed in 2003:

– A. Gruber (Chief) – Climate – C. Brown – Oceanography (Biology) – R. Ferraro – Meteorology (Remote Sensing) – B. Ramsay – Geography (Cryosphere) – T. Smith – NCDC Visitor – Meteorology & Oceanography (SST, Climate)

• “Intermediate” SCSB – T. Smith – converted to full time at SCSB via NCDC – A. Gruber retired; we hired H. Meng (Hydrology) – M. Vargas – rotational assignments, now at STAR/SMCD – B. Ramsay – retired – NESDIS WFRP Summer interns (David Price pictured on right)

• SCSB 2013 – Brown, Ferraro, Meng, Rudlosky, Smith, [Deb Baker – HUGE HELP!]

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“Sample” Accomplishments of SCSB and CICS Collaborations

• Precipitation Algorithms/R2O – GPROF Land Rain Rates (TRMM, AMSR-E, AMSR-2, SSMI(S))

• R. Ferraro, N-Y. Wang, P. Meyers, J.J. Wang, (K. Gopalan, J. McCollum, A. Sudradjat) – Snowfall Detection and Rates (AMSU, MHS, ATMS)

• H. Meng, C. Kongoli, N-Y. Wang, J. Dong

• Global Climate Time Series Reconstructions – SST, Precipitation, Ocean Phenology

• T. Smith, P. Arkin, L. Ren, (M. Sapiano)

• Coastal and Open Ocean Ecosystem Monitoring & Prediction – Focus on Chesapeake Bay Watershed

• C. Brown, H. Meng, R. Murtugudde, (B. Zhang, M. Maddox, J. Strack, A. Sexton, A. Sood) – Phytoplankton Phenology

• Brown, S. Schollaert-Uz, (M. Vargas, M. Sapiano)

• Lightning detection, new R&D, R2O – DC Lightning Mapping Array (DCLMA) -

• S. Rudlosky, D. Shea, new student interns – Lightning and Precipitation research

• S. Rudlosky, R. Adler, N-Y. Wang, P. Meyers, (R. Albrecht, E. Brunning, W. Xu)

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CICS Scientists – Career Paths

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Students: Interns

Graduate Summer

Researchers: Post-Docs Scientists

Sr. Scientists Visiting Scientists

NOAA: NESDIS/STAR

NWS NESDIS/NODC

OAR/ARL Government –

NASA, DOE, etc.

Private Sector – Science contractor Insurance industry

Academia –

Faculty Sr. Scientists

Future Goals for SCSB & CICS… My perspective

• Continue to pursue cutting edge R&D – NOAA’s core - Ecosystems, CDR’s, reconstructions, GOES-R, JPSS – Emerging opportunities with NASA programs – GPM, Aquarius, …

• “The other part” of ESSIC…

• Near term/emerging R&D opportunities – Satellite product “fusion” and satellite/surface fusion - GOES-

R/Lightning; JPSS/ATMS and VIIRS; GOES-R/JPSS and GPM, GPM and floods, etc.

– CICS Satellite Proving Ground • Need to get this off the ground!

– Continue to build the student base through emerging, coordinated intern program

– “Beyond” CDR’s CIR’s - Extreme events like AR’s, linking together lightning/fires/precipitation/floods, etc.

6-7 November 2013 CICS-MD Science Meeting 7

GPROF “2010” TRMM 2A12 V7

8

Note the better gradient in the rain rates in V7 compared to V6 and PR

Nai-Yu Wang

Accuracy Precision Correlation StageIV -0.23 0.67 0.42 Station 0.07 0.72 0.30

Validation of AMSU Snowfall Rate

• Validation with five large snowstorms • Validation sources

StageIV: Radar/gauge combined hourly precipitation Station (QCLCD) hourly snow accumulation NEXRAD reflectivity

• Overall statistics

• A large snowstorm system

in the Midwest on Dec 8-9, 2009 (right) Heavy snowfall (1’+) in NE,

IA, MN, WI

Huan Meng Cezar Kongoli

Precipitation Reconstructions

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• Precipitation reconstructions made using “data rich” era (1979 – 2010 from GPCP)

• Different statistical methods used to determine primary modes of the precipitation characteristics

• These are then applied to data such as SST and other variables from 1900 to present – Able to capture major events realted

to ENSO • Similar methods have been applied

to SST and more recently, phytoplankton.

Reconstructed oceanic precipitation anomalies (Recon) with 95% confidence intervals from lack of data alone (red dashed) and from lack of data and model errors (black short dashed). The GPCP is also plotted for comparison. Because of the CCA reconstruction the ocean area is well filled but the filling data have a large model error.

Tom Smith, Phil Arkin, Li Ren

Climatology of Phytoplankton Phenology

• Documenting phenology of phytoplankton biomass is useful to assess the response of marine ecosystems to environmental change

• Fit Generalized Linear Models (GLM) to time-series of SeaWiFS chlorophyll concentrations and extracted phenological markers

• Results represent global climatology of phytoplankton bloom onset, maturity, and termination, and bloom duration

• Establishes a baseline from which to assess future changes and relate these changes to oceanic variables and climate indices

• Sapiano, M. R. P., C. W. Brown, S.

E. Schollaert and M. Vargas. 2012. Establishing a global climatology of marine phytoplankton phenological characteristics. Journal of Geophysical Research 117(C8), C08026. doi: 10.1029/2012jc007958

Spatial distribution of mean phytoplankton bloom duration in the oceans for the period September

1997 to July 2007.

Phytoplankton Bloom Duration Chris Brown, Matt Sapiano, Stephanie Schollaert-Uz

DCLMA Outreach Efforts • Continuing collaborations with the Sterling WFO

• COMET Project • Real-time LMA observations • Discussion of significant events

• Launched “Its Severe” Blog

• Building collaborations with the Washington Post’s Capital Weather Gang

Bladensburg Microburst

Washington D.C. Derecho

Above: DCLMA Observations 6-7 November 2013 CICS-MD Science Meeting 12

Scott Rudlosky, Dustin Shea, Patrick Meyers