Seminars
Preliminary Investigation of Ensemble Forecast Sensitivity to Observation Impact with GFS and RRFS
May 16, 2023 12:00 am
ATS Large Classroom 101
Presented by: Liao-Fan Lin
Hosted by:
CIRA, CSU; NOAA/OAR/Global Systems Laboratory
Forecast Sensitivity to Observation Impact (FSOI) helps to quantify the impact of assimilated observations on forecast skills in numerical weather prediction systems. At NOAA, an ensemble FSOI (EFSOI) package is available within the Gridpoint Statistical Interpolation (GSI) and the ensemble Kalman filter (EnKF) data assimilation system (i.e., GSI-EnKF). This tool has been upgraded and implemented into… Read more »
CIRA Tropical Cyclone Forecast Uncertainty Product Development for the National Hurricane Center
April 18, 2023 12:00 am
ATS Large Classroom 101
Presented by: Dr. Mark DeMaria
Hosted by:
The National Hurricane Center (NHC) implemented the Hurricane Strike Probability program in 1983 in recognition of the need to provide uncertainty information to complement their deterministic track and intensity forecasts to aid decision makers in mitigation activities. The Strike Probabilities only provided information about track forecast uncertainty and were replaced by the wind speed probabilities… Read more »
Untangling the Amazon Carbon Cycle with Satellite Data
March 21, 2023 12:00 am
ATS West Seminar Room 121
Presented by: Dr. Ian Baker
Hosted by:
In this talk, we will present a ‘farm to table’ description of how satellite data is being used to inform carbon cycle processes in Amazonia, which is both poorly sampled at the surface and critical to the global carbon cycle. We will describe how results from statistical ‘top down’ inversion models are used to confront… Read more »
Non-Gaussian Data Assimilation Developments at CIRA
February 14, 2023 1:30 pm
CIRA Commons
Presented by: Steven Fletcher and Senne Van Loon
Hosted by:
The underlying assumption for variational and Kalman filter based data assimilation algorithms is that the associated errors are Gaussian distributed random variables. Over the last 18 years at CIRA we have worked on relaxing this assumption to allow for lognormally distributed, and recently reverse-lognormally distributed errors. The first part of this talk will be an… Read more »
Non-Gaussian Data Assimilation Developments at CIRA
February 14, 2023 1:30 pm
CIRA Commons
Presented by: Drs. Steven J. Fletcher and Senne Van Loon
Hosted by:
The underlying assumption for variational and Kalman filter based data assimilation algorithms is that the associated errors are Gaussian distributed random variables. Over the last 18 years at CIRA we have worked on relaxing this assumption to allow for lognormally distributed, and recently reverse-lognormally distributed errors. The first part of this talk will be an… Read more »
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