<--- Back to Details
First PageDocument Content
Estimation theory / Atmospheric sciences / Prediction / Control theory / Linear filters / Data assimilation / Ensemble Kalman filter / Forecasting / Covariance / Statistics / Statistical forecasting / Bayesian statistics
Date: 2011-10-31 18:50:09
Estimation theory
Atmospheric sciences
Prediction
Control theory
Linear filters
Data assimilation
Ensemble Kalman filter
Forecasting
Covariance
Statistics
Statistical forecasting
Bayesian statistics

Microsoft PowerPoint - HFIP-HYBDA-TC-xuguang-wang.pptx

Add to Reading List

Source URL: rammb.cira.colostate.edu

Download Document from Source Website

File Size: 2,31 MB

Share Document on Facebook

Similar Documents

Intrinsic versus Practical Limits of Multi-Scale Atmospheric Predictability Professor Fuqing Zhang Director, Penn State Center for Advanced Data Assimilation and Predictability

DocID: 1vs3e - View Document

NCMRWF Unified Model and Data Assimilation System NCMRWF Unified model (NCUM) is being used for generating10-day numerical weather forecasts routinely sinceThe NCUM system is based on the Unified Model (UM) develo

DocID: 1vh7f - View Document

HFIP Publications 2017 Journals and Periodicals Aksoy, A., S. Lorsolo, T. Vukicevic, K. J. Sellwood, S. D. Aberson, and F. Zhang, 2012: The HWRF hurricane ensemble data assimilation system (HEDAS) for high-resolution dat

DocID: 1v3Or - View Document

Quantitative Precipitation Forecasting with Polarimetric Radar Data Assimilation: Typhoon SoudelorCHIH-CHIEN TSAI AND YOUNGSUN JUNG 1Taiwan

DocID: 1uUER - View Document

High-rank Ensemble Transform Kalman Filter (HETKF) Bo Huang and Xuguang Wang Multi-scale data Assimilation and Predictability (MAP) Laboratory School of Meteorology, University of Oklahoma, Norman, OK

DocID: 1uOhU - View Document