Dr. Karina Apodaca

Research Scientist/Scholar II
Fort Collins, Colorado


  • B.S. in Physics and Mathematics with a minor in Music: Voice 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)

- Mary C. Barth (NCAR/ACOM)

Research Interests:
  • Ensemble, variational, and hybrid data assimilation (DA) techniques applied to Geophysical numerical modeling
  • Non-Gaussian probability and statistics as applied to DA
  • Bias correction
  • Forward and adjoint model development for the assimilation of new/future satellite sensors
  • Global to convective scale DA
  • Cloudy-scene DA
  • Advanced DA development for satellite-derived lightning observations 
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
Education and Outreach:
  • Instructor – Course: Introduction to Data Assimilation for the NOAA paid internship training program on data assimilation at CIRA
  • Design of the CIRA DA Group Website



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 – through OAR/Office of Weather and Air Quality

Award number: NA16OAR4590233

Principal Investigator: Karina Apodaca

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

Recent Work

In preparation for the launch of the GOES-R satellite, researchers at the Cooperative Institute for Research in the Atmosphere have been working on the methodology to use the lightning measurements from the GLM instrument. Development efforts include the design ...