enso-conditioned weather resampling method for seasonal ensemble streamflow prediction
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ID: 245470
2016
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Abstract
Oceanic–atmospheric climate modes, such as El Niño–Southern Oscillation (ENSO), are known to affect the local streamflow regime
in many rivers around the world. A new method is proposed to incorporate
climate mode information into the well-known ensemble streamflow prediction (ESP)
method for seasonal forecasting. The ESP is conditioned on an ENSO
index in two steps. First, a number of original historical ESP traces are
selected based on similarity between the index value in the historical year
and the index value at the time of forecast. In the second step, additional
ensemble traces are generated by a stochastic ENSO-conditioned weather
resampler. These resampled traces compensate for the reduction of ensemble
size in the first step and prevent degradation of skill at forecasting
stations that are less affected by ENSO. The skill of the ENSO-conditioned
ESP is evaluated over 50 years of seasonal hindcasts of streamflows at three
test stations in the Columbia River basin in the US Pacific Northwest. An
improvement in forecast skill of 5 to 10 % is found for two test stations. The streamflows at the third station are less affected by ENSO and no change in forecast skill is found here.
| Reference Key |
beckers2016hydrologyenso-conditioned
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|---|---|
| Authors | ;J. V. L. Beckers;A. H. Weerts;E. Tijdeman;E. Welles |
| Journal | materials research bulletin |
| Year | 2016 |
| DOI |
10.5194/hess-20-3277-2016
|
| URL | |
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