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Jie Feng

Partner Affiliation
Publon ID
Not available


Corresponding Articles: 5

Jie Feng authored and/or contributed to the following articles/publications.

A New Measure of Ensemble Central Tendency

Ensemble prediction is a widely used tool in weather forecasting. In particular, the arithmetic mean (AM) of ensemble members is used to filter out unpredictable features from a forecast. AM is a pointwise statistical concept, providing the best sample-based estimate of the expected value of any single variable. The atmosphere, however, is a mul...

Jie Feng
Institution National Oceanic and Atmospheric Administration - NOAA

Partition of analysis and forecast error variance into growing and decaying components

Due to the scarcity of and errors in observations, direct measurements of errors in numerical weather prediction (NWP) analyses and forecasts with respect to nature (i.e. “true” error) are lacking. Peña and Toth (2014) introduced an inverse method called SAFE?I where true errors are (a) theoretically assumed to follow exponential error growth, a...

Jie Feng
Institution National Oceanic and Atmospheric Administration - NOAA

Comparison of Nonlinear Local Lyapunov Vectors and Bred Vectors in Estimating the Spatial Distribution of Error Growth

Instabilities play a critical role in understanding atmospheric predictability and improving weather forecasting. The bred vectors (BVs) are dynamically evolved and flow-dependent nonlinear perturbations, indicating the most unstable modes of the underlying flow. Especially over smaller areas, however, BVs with different initial seeds may to som...

Jie Feng
Institution National Oceanic and Atmospheric Administration - NOAA

Spatially extended estimates of analysis and short-range forecast error variances

Accurate estimates of ‘true’ error variance between Numerical Weather Prediction (NWP) analyses and forecasts and the ‘reality’ interpolated to a NWP model grid (Analysis and true Forecast Error Variance, hereafter AFEV) are critical for successful data assimilation and ensemble forecasting applications. Peña and Toth (2014, PT14) introduced a S...

Jie Feng
Institution National Oceanic and Atmospheric Administration - NOAA

Initial-Value vs. Model-Induced Forecast Error: A New Perspective

Numerical models of the atmosphere are based on the best theory available. Understandably, the theoretical assessment of errors induced by the use of such models is confounding. Without clear theoretical guidance, the experimental separation of the model-induced part of the total forecast error is also challenging. In this study, the forecast er...

Jie Feng