Lynker is seeking a talented Hydrological Ensemble Forecast Specialist to support NOAA. The Hydrological Ensemble Forecast Specialist selected will join a team with the goal of implementing the HEFS ensemble forecast modules on NOAA's CHPS forecast models across all US basins, to produce probabilistic ensemble riverflow forecasts for all River Forecasts Centers' (RFCs) basins and locations across the US, and replace the AHPS's current single-value forecasts. HEFS bias-corrects the meteorological forecasts and accounts for meteorologic uncertainty (adding spread to forecasts).
Duties of the Hydrological Ensemble Forecast Specialist will include the following:
- Intake of the stand alones (SAs) from the RFCs for each forecast group for validation.
- Estimation of the MEFP parameters for the locations within the forecast group, using the observational data sent along with the SA.
- Add the parameters to the SA and add HEFS modules and update the configuration, and test and debug where needed.
- Run the SA for a 31-year period. Also run the model for ESP mode, where the HEFS is not used.
- Validate HEFS runs against the ESP runs, with observations as baseline, using the Evaluation Verification System (EVS). This will show whether adding the HEFS increases the forecast skill of the SA for precipitation, temperature, and streamflow.
- Coordinate with the RFC and other POCs, to send and receive models and datasets, and resolve the issues that arise during the tasks.
- Classify the forecast group's location in Pass or Fail conditions, and present the results with the RFC and ask them to add the passed locations to AHPS.
- Implementing the Ensemble Post Processor (EnsPost) on HEFS testbed locations.
- Writing workflows and modules for the testbed SAs to implement the EnsPost modules, to adjust the BV HEFS hindcasts and validate their skill compared to raw (unadjusted) HEFS hindcasts to assess the skill added by EnsPost to the HEFS runs. The process involves estimating EnsPost parameters and tuning the estimation options to determine the optimum parameter estimation settings.
- Implement and test EnsPost on all testbed locations for all RFCs, and if successful, move on to implementing and testing EnsPost on all HEFS locations and validate them to make them operational on AHPS forecasts.
- Develop Python tools and Shell scripts for running models and data analysis and evaluation on CEE, to be used by other team members as well.
The Hydrological Ensemble Forecast Specialist selected should meet the following Qualifications:
Appointment to this position requires an earned doctorate OR an advanced masters degree (with 4+ years working experience) in atmospheric sciences, computer science, applied mathematics, statistics, or a closely related field.
The Ideal Hydrological Ensemble Forecast Specialist will meet the following Qualifications:
Experience in numerical weather prediction, hydrological modeling/forecasting, coupled modeling, ensemble forecasting, statistical post-processing, and verification.
Experience in ensemble design and generating a large set of ensemble reforecasts.
Experience in using NOAA's Unified Forecast System, especially the Global Ensemble Forecast System (GEFS).
Experience in probabilistic verification/evaluation, ensemble based MJO diagnostics/evaluation.
Experience in using High Performance Supercomputers, developing and executing automation scripts, handling large datasets, and familiar with high-performance storage and archiving systems.
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