Atlantic Tropical Cyclone Activity in Response to the MJO in NOAA’s CFS Model

Author:

Barnston Anthony G.1,Vigaud Nicolas1,Long Lindsey N.2,Tippett Michael K.3,Schemm Jae-Kyung E.4

Affiliation:

1. International Research Institute for Climate and Society, Columbia University, Palisades, New York

2. NOAA/Climate Prediction Center, College Park, and Innovim, LLC, Greenbelt, Maryland

3. International Research Institute for Climate and Society, Columbia University, Palisades, New York, and Center of Excellence for Climate Change Research, Department of Meteorology, King Abdulaziz University, Jeddah, Saudi Arabia

4. NOAA/Climate Prediction Center, College Park, Maryland

Abstract

Abstract The Madden–Julian oscillation (MJO) is known to exert some control on the variations of North Atlantic tropical cyclone (TC) activity within a hurricane season. To explore the possibility of better TC predictions based on improved MJO forecasts, retrospective hindcast data on MJO and on TC activity are examined both in the current operational version of the CFSv2 model (T126 horizontal resolution) and a high-resolution (T382) experimental version of CFS. Goals are to determine how well each CFS version reproduces reality in 1) predicting MJO and 2) reproducing observed relationships between MJO phase and TC activity. For the operational CFSv2, skill of forecasts of TC activity is evaluated directly. Both CFS versions reproduce MJO behavior realistically and also roughly approximate observed relationships between MJO phase and TC activity. Specific biases in the high-resolution CFS are identified and their causes explored. The high-resolution CFS partially reproduces an observed weak tendency for TC activity to propagate eastward during and following the high-activity MJO phases. The operational (T126) CFSv2 shows useful skill (correlation >0.5) in predicting the MJO phase and amplitude out to ~3 weeks. A systematic error of slightly too slow MJO propagation is detected in the operational CFSv2, which still shows usable skill (correlation >0.3) in predicting weekly variations in TC activity out to 10–14 days. A conclusion is that prediction of intraseasonal variations of TC activity by CFSv2 is already possible and implemented in real-time predictions. An advantage of the higher resolution in the T382 version is unable to be confirmed.

Publisher

American Meteorological Society

Subject

Atmospheric Science

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