Postdoc or Higher for Multi-Sensor, Multi-Variate Land Data Assimilation Systems (LDAS)

The effort involves development of Earth satellite multi-sensor, multi-variate land data assimilation systems (LDAS) within NASA’s Land Information System (LIS) for improved understanding of global warming impact on terrestrial hydrology water and energy balance processes.

 

Date posted

Jan. 24, 2024 11:45 am

Application deadline

Feb. 24, 2024 5:00 pm

Organization

The University of Maryland

Location

  • United States

Job description

Description of Effort

The effort involves development of Earth satellite multi-sensor, multi-variate land data assimilation systems (LDAS) within NASA’s Land Information System (LIS) for improved understanding of global warming impact on terrestrial hydrology water and energy balance processes. Specific focus will be on further enhancements to the National Climate Assessment-Land Data Assimilation System, or NCA-LDAS over the continental U.S., Alaska, and US. Territories. Land surface models (LSMs) to be used will include mainly Noah-MP and Catchment LM, but others may be added. Current assimilated satellite-based geophysical records include snow water equivalent and depth, soil moisture, surface temperature, vegetation properties, groundwater and surface water height. Work will further enhance the LDAS assimilation and parameterizations for high-latitude processes for Alaska and including glacier accumulation and melt, lake dynamics, and permafrost. NCA-LDAS products will be analyzed for climate change indicators such as hydrologic trends. Research will be conducted under the overall direction of the Sponsor, Dr. Michael Jasinski. Other related terrestrial hydrology studies may also be implemented.

Qualifications: A Ph. D. in Earth Science, hydrology, civil engineering or related field. Knowledge of land surface hydrology modeling, expertise in data assimilation, Fortran90 & C programming, multiple data formats including GRIB, NetCDF and HDF. Desirable expertise includes knowledge of satellite imagery and experience of satellite-observed and/or in-situ data assimilation, including employing diverse hydrologic models and ensemble techniques, processing large amounts of numerical output data on mainframe supercomputers in a FORTRAN/UNIX environment, cloud computing and using advanced statistical and display tools. Additional highly desirable qualties include experience working in a team environment, good written and oral communication skills, and the ability to learn and develop scientific capability and leadership in data assimilation. Ability to obtain all necessary security clearances for access to NASA GSFC and its computer systems is essential.

To Apply: Interested candidates should send a CV with a list of at least 3 professional references and a cover letter explaining how your qualifications meet the posted requirements to anegri@umd.edu.

THE UNIVERSITY OF MARYLAND IS AN EQUAL OPPORTUNITY AFFIRMATIVE ACTION EMPLOYER

For more details

https://webhost.essic.umd.edu/postdoc-or-higher-for-multi-sensor-multi-variate-land-data-assimilation-systems-ldas/