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Dr. Karina Apodaca
Associate Scientist
Hurricane Research Division-CIMAS
phone: 303-497-6032
karina.apodaca@noaa.gov

NOAA's Atlantic Oceanographic and Meteorological Laboratory
4301 Rickenbacker Causeway
Miami, FL 33149

Professional Interests

  • 3DVar and hybrid EnVar assimilation methods for lightning observations
  • Non-Gaussian, nonlinear, and coupled data assimilation
  • Optimal parameter estimation and variational bias correction
  • Forward and adjoint model development for the assimilation of new/future satellite sensors
  • Global and convective scale DA

Education:

  • B.S. in Physics, Mathematics, minor Music (voice concentration) from the University of Texas at El Paso
  • Ph.D. in Atmospheric Sciences from Howard University – December 2010
    Dissertation: The Impacts of Chihuahuan Desert Aerosol Intrusions on Convective Clouds and Regional Precipitation
    Thesis Advisors: Vernon R. Morris (Howard University) and Mary C. Barth (NCAR/ACOM)

Current Projects:

  1. Accounting for non-Gaussianity in the background error distributions associated with cloud-related variables (microwave radiances and hydrometeors) in hybrid data assimilation for convective scale prediction
  2. R2O transition of the GOES-R GLM assimilation capability in GSI for use in the NCEP GDAS
  3. Advancing littoral zone aerosol data assimilation in regime-dependent flows
  4. Incorporating the GOES-R Geostationary Lightning Mapper assimilation into the Gridpoint Statistical Interpolation for use in the NCEP Global Forecast System


Previous Projects:

  1. Utility of GOES-R Geostationary Lightning Mapper (GLM) using hybrid variational-ensemble data assimilation in regional applications
  2. Ensemble-based assimilation and downscaling of the Global Precipitation Mission satellite precipitation information
  3. Ensemble data assimilation for nonlinear and non-differentiable problems in geosciences

 

Awarded Proposals as a PI:

 
Accounting for non-Gaussianity in the background error distributions associated with cloud-related variables (microwave radiances and hydrometeors) in hybrid data assimilation for convective-scale prediction

Funding: 304K USD

Funding Agency: NOAA – OAR/Office of Weather and Air Quality

Award number: NA16OAR4590233

Principal Investigator: Karina Apodaca

Co-PI: Steven Fletcher (CSU/CIRA DA group)

 

R2O transition of the GOES-R GLM assimilation capability in GSI for use in the NCEP GDAS

Funding: 11K USD

Funding Agency: Developmental Testbed Center

Award: 2017 DTC Visitor Award

Principal Investigator: Karina Apodaca

 

Awarded Proposals as a Co-PI:

 

Data assimilation of GLM observations in HWRF/GSI system

Funding Source: FY2017 GOES-R Risk Reduction Program

Principal Investigator: Milija Zupanski

Co-PI: Ting-Chi Wu, Karina Apodaca

 

Incorporating the GOES-R Geostationary Lightning Mapper Assimilation into the GSI for use in the NCEP global system

Funding Source: NOAA Sandy Supplemental 

Award: NOAA Sandy Supplemental   #NA14NWS4830034

Principal Investigator: Milija Zupanski

Co-PI: Karina Apodaca

 

Education and Outreach:

Instructor – Course: Introduction to Data Assimilation for the NOAA paid internship training program on data assimilation at CIRA


Advising and Mentorship:

 
Current Students :

Vanderlei Rocha de Vargas Jr., PhD, lightning data assimilation, visiting student at CIRA from CPTEC/INPE, Brazil

Rute Costa Ferreira, PhD, lightning data assimilation, visiting student at CIRA from CPTEC, Brazil

 

Past:

José Negrete Jr. – Undergraduate, atmospheric physics, UTEP, now at École Polytechnique Fédérale de Lausanne, Switzerland

Frances B. Roberts-Gregory – Undergraduate, Spellman College, NCAR/ACOM, now at UC Berkeley

Biljana Orescanin – Intern, data assimilation, CIRA, now at Joint Center for Satellite Data Assimilation

James D. Taylor – Intern, data assimilation, CIRA, now at RIKEN, Japan

Matthew Brothers – Intern, data assimilation, CIRA, now at Cheyenne WFO

Manuscripts in Review

  1. K. Apodaca, Fletcher S. J., Weygandt S., and Lin H.: Non-Gaussian background error covariance matrix modeling of humidity and cloud hydrometeor control variables for the Gridpoint Statistical Interpolation system. In preparation to be submitted to J. Appl. Meteor. Climatol.
  2. Apodaca, K., Zupanski, M., Derber, J. C., Kren A., Cucurull L., Hu M.: Assessing the utility of GOES-16/GLM lightning observations in the NCEP 4DEnVar System. In preparation to be submitted to: Geosci. Model Dev.

Hightlighted Publications

  1. Apodaca, K., Zupanski, M., DeMaria, M., Knaff, J. A., and Grasso, L. D.: Development of a hybrid variational-ensemble data assimilation technique for observed lightning tested in a mesoscale model, Nonlin. Processes Geophys., 21, 1027-1041, doi:10.5194/npg-21- 1027-2014, 2014

      Recent Presentations

      1. Apodaca K., S. J. Fletcher, and M. Zupanski, Advances in new data assimilation methodologies and observations for the benefit of NOAA operations. AOML/HRD Seminar. NOAA/AOML/Hurricane Research Division, Miami, Florida.
      2. Apodaca K. and M. Zupanski, Variational and Hybrid data assimilation methods suitable for GOES-16, 17/GLM lightning observations. GMAO Spring Seminar Series. Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center, Greenbelt, MD, June 26, 2018.
      3. Apodaca, K., S. J. Fletcher, 2017: Implementing non-Gaussian background error statistics for cloud-related control variables in the hybrid GSI for improved convective-scale assimilation and prediction. 7th WMO Symposium on Data Assimilation. Florianopolis, Brazil. September 11-15, 2017.

      Awards and Honors

      2009NCAR Advanced Study Program Graduate Student Fellowship AwardNCAR
      2003NOAA/Educational Partnership Program with MSI Graduate Student FellowshipNOAA
      2000-2002EPA Outstanding Undergraduate Student Assistanship AwardEPA
      1999-2001NSF STEM MSI-REU Award and UTEP College of Science Dean’s listNSF and UTEP College of Science
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