Jana Kolassa is a researcher and scientific land model developer at the Global Modeling and Assimilation Office (GMAO) at the NASA Goddard Space Flight Center. Prior to joining the GMAO as a full-time researcher, she worked as a postdoctoral fellow at Columbia University in New York and through the NASA Postdoctoral Program. Her research focusses on improving the representation on land-atmosphere interactions in global Earth System Models through (1) improvements in process representation and (2) data assimilation. She is currently leading the development the next version of the NASA Catchment-CN model, the GMAO's land model with dynamic vegetation and a fully resolved carbon and nitrogen cycle. She also leads a project to investigate the impact of land data assimilation on atmospheric model forecast skill with a particular focus on the impact of soil moisture assimilation on tropical cyclones.
Jana Kolassa
(RESEARCH SCIENTIST)
| Email: | jana.kolassa@nasa.gov |
| Phone: | 301.614.6592 |
| Org Code: | 610.1 |
| Address: |
NASA/GSFC Mail Code 610.1 Greenbelt, MD 20771 |
| Employer: | SCIENCE SYSTEMS AND APPLICATIONS INC |
Brief Bio
Positions/Employment
Senior Scientific Programmer / Research Scientist
Science Systems and Applications Inc. - Lanham, MD
October 2020 - Present
- Scientific development of the NASA GMAO land model and land data assimilation systems with particular focus on the dynamic vegetation as well as carbon and nitrogen cycle components included in the experimental Catchment-CN model
- Assessment of the impact of land data assimilation on model prediction skill with particular focus on the impact of soil moisture assimilation on tropical cyclones
Research Scientist
Universities Space Research Association / Goddard Earth Sciences Technology and Research - Columbia, MD
January 2017 - November 2020
- Calibration of the NASA Catchment-CN model parameters to improve modeled vegetation phenology and physiology
- Joint assimilation of SMAP soil moisture and MODIS vegetation information into the NASA Catchment-CN land surface model for the generation of improved hydrological fields and surface flux estimates
Postdoctoral Research Fellow (NASA Postdoctoral Program, NPP)
Universities Space Research Association - Columbia, MD
January 2015 - January 2017
- Development of Neural Network soil moisture retrieval algorithm for the Soil Moisture Active Passive (SMAP) mission
- Investigation of new bias correction techniques for the assimilation of SMAP soil moisture observations into the NASA Catchment model
Postdoctoral Research Fellow
Columbia University, Department of Earth and Environmental Engineering - New York, NY
January 2014 - January 2015
- Development of a Neural Network based microwave only soil moisture retrieval product from AMSR-E and ASCAT observations
Education
Doctor of Philosophy (PhD)
Environmental Science and Remote Sensing
Université Pierre et Marie Curie (Paris 6), Paris, France
Thesis: Soil moisture retrieval from multi-instrument satellite observations
Supervisors: Dr. Filipe Aires, Dr. Catherine Prigent
Master of Science (MSc)
Space Science and Technology
Luleå University of Technology, Kiruna Sweden
September 2008 - June 2010
Thesis: Investigation of cloud ice water content retrieval from active satellite observations
Bachelor of Science (BSc)
Aerospace Engineering
Technical University Delft, Delft, The Netherlands
September 2005 - June 2008
Thesis: Design of an advanced space-based interferometer at 22 GHz
Publications
Refereed
2023. "A Weakly-Coupled Land Surface Analysis With SMAP Radiance Assimilation Improves GEOS Medium-Range Forecasts of Near-Surface Air Temperature and Humidity." Quarterly Journal of the Royal Meteorological Society 149 1867-1889 [10.1002/qj.4486] [Journal Article/Letter]
2022. "An Agenda for Land Data Assimilation Priorities: Realizing the Promise of Terrestrial Water, Energy, and Vegetation Observations From Space." Journal of Advances in Modeling Earth Systems 14 (11): e2022MS003259 [10.1029/2022ms003259] [Journal Article/Letter]
2022. "Skillful Seasonal Forecasts of Land Carbon Uptake in Northern Mid‐ and High Latitudes." Geophysical Research Letters 49 (6): e2021GL097117 [10.1029/2021GL097117] [Journal Article/Letter]
2022. "Building a Land Data Assimilation Community to Tackle Technical Challenges in Quantifying and Reducing Uncertainty in Land Model Predictions." Bulletin of the American Meteorological Society 103 (3): E733-E740 [10.1175/bams-d-21-0228.1] [Journal Article/Letter]
2021. "Regional impacts of COVID-19 on carbon dioxide detected worldwide from space." Science Advances 7 (45): eabf9415 [10.1126/sciadv.abf9415] [Journal Article/Letter]
2021. "Assimilation of SMAP Brightness Temperature Observations in the GEOS Land-Atmosphere Data Assimilation System." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14 10628-10643 [10.1109/jstars.2021.3118595] [Journal Article/Letter]
2020. "An observation‐driven approach to improve vegetation phenology in a global land surface model." Journal of Advances in Modeling Earth Systems 12 e2020MS002083 [10.1029/2020ms002083] [Journal Article/Letter]
2019. "Version 4 of the SMAP Level‐4 Soil Moisture Algorithm and Data Product." Journal of Advances in Modeling Earth Systems 11 (10): 3106-3130 [10.1029/2019ms001729] [Journal Article/Letter]
2018. "Global Downscaling of Remotely-Sensed Soil Moisture using Neural Networks." Hydrology and Earth System Sciences Discussions 1-19 [10.5194/hess-2017-680] [Journal Article/Letter]
2018. "Estimating surface soil moisture from SMAP observations using a Neural Network technique." Remote Sensing of Environment 204 43-59 [10.1016/j.rse.2017.10.045] [Journal Article/Letter]
2017. "Global Assessment of the SMAP Level-4 Surface and Root-Zone Soil Moisture Product Using Assimilation Diagnostics." Journal of Hydrometeorology 18 3217-3237 [10.1175/JHM-D-17-0130.1] [Journal Article/Letter]
2017. "Data Assimilation to Extract Soil Moisture Information from SMAP Observations." Remote Sensing 9 (11): 1179 [10.3390/rs9111179] [Journal Article/Letter]
2017. "Water, Energy, and Carbon with Artificial Neural Networks (WECANN): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence." Biogeosciences 14 (18): 4101-4124 [10.5194/bg-14-4101-2017] [Journal Article/Letter]
2017. "Soil moisture retrieval from AMSR-E and ASCAT microwave observation synergy. Part 2: Product evaluation." Remote Sensing of Environment 195 202-217 [10.1016/j.rse.2017.04.020] [Journal Article/Letter]
2017. "Regionally strong feedbacks between the atmosphere and terrestrial biosphere." Nature Geoscience [10.1038/ngeo2957] [Journal Article/Letter]
2017. "Merging active and passive microwave observations in soil moisture data assimilation." Remote Sensing of Environment 191 117-130 [10.1016/j.rse.2017.01.015] [Journal Article/Letter]
2016. "Soil moisture retrieval from AMSR-E and ASCAT microwave observation synergy. Part 1: Satellite data analysis." Remote Sensing of Environment 173 1-14 [10.1016/j.rse.2015.11.011] [Journal Article/Letter]
2015. "Soil Moisture Retrieval Using Neural Networks: Application to SMOS." IEEE Transactions on Geoscience and Remote Sensing 53 (11): 5991-6007 [10.1109/tgrs.2015.2430845] [Journal Article/Letter]
2013. "Evaluation of biospheric components in Earth system models using modern and palaeo-observations: the state-of-the-art." Biogeosciences 10 (12): 8305-8328 [10.5194/bg-10-8305-2013] [Journal Article/Letter]
2013. "A joint analysis of modeled soil moisture fields and satellite observations." Journal of Geophysical Research: Atmospheres 118 (12): 6771-6782 [10.1002/jgrd.50430] [Journal Article/Letter]
2013. "Soil moisture retrieval from multi-instrument observations: Information content analysis and retrieval methodology." Journal of Geophysical Research: Atmospheres 118 (10): 4847-4859 [10.1029/2012jd018150] [Journal Article/Letter]