TY - JOUR
T1 - Predicting Atlantic seasonal hurricane activity using outgoing longwave radiation over Africa
AU - Karnauskas, Kristopher B.
AU - Li, Laifang
N1 - Funding Information:
All data sets used in this study are publicly available: gridded OLR, precipitation, and reanalysis data acquired from NOAA/ESRL/PSD (http://www.esrl.noaa.gov/psd/data/gridded/), gridded surface temperature data acquired from NASA/GISS (http://data.giss.nasa.gov/gistemp/), climate indices (NINO3.4 and AMO) acquired from NOAA/ESRL/PSD (http://www.esrl.noaa.gov/psd/data/climateindices/list/), named Atlantic storm counts acquired from NOAA/NHC (http://www.nhc.noaa.gov/data/#tracks_all), ACE time series acquired from NOAA/HRD (http://www.aoml.noaa.gov/hrd/hurdat/comparison_table.html), NOAA/NHC seasonal predictions acquired from NOAA/CPC (http://www.cpc.ncep.noaa.gov/products/outlooks/hurricane-archive.shtml), CSU seasonal predictions acquired from the CSU Tropical Meteorology Project (http://hurricane.atmos.colostate.edu/forecasts/), and tropical cyclone tracks acquired from HURDAT2 (http://www.nhc.noaa.gov/data/#hurdat). All code and derived data available upon e-mail request to the authors. The authors thank Eric Blake of NOAA/NHC for helpful discussions as this manuscript was being prepared, and Cathy Smith (NOAA/ESRL/PSD) for facilitating the Interpolated OLR data set. The authors also thank Jim Kossin, one anonymous reviewer, and the Editor for constructive comments during peer review. K.B.K. acknowledges support from the Alfred P. Sloan Foundation. L.L. is supported by the Postdoctoral Scholar Program at the Woods Hole Oceanographic Institution, with funding provided by the Ocean and Climate Change Institute. Updated OLR-based predictions will be posted annually at http://www.colorado.edu/oclab/olr.
Publisher Copyright:
©2016. American Geophysical Union. All Rights Reserved.
PY - 2016/7/16
Y1 - 2016/7/16
N2 - Seasonal hurricane activity is a function of the amount of initial disturbances (e.g., easterly waves) and the background environment in which they develop into tropical storms (i.e., the main development region). Focusing on the former, a set of indices based solely upon the meridional structure of satellite-derived outgoing longwave radiation (OLR) over the African continent are shown to be capable of predicting Atlantic seasonal hurricane activity with very high rates of success. Predictions of named storms based on the July OLR field and trained only on the time period prior to the year being predicted yield a success rate of 87%, compared to the success rate of NOAA's August outlooks of 53% over the same period and with the same average uncertainty range (±2). The resulting OLR indices are statistically robust, highly detectable, physically linked to the predictand, and may account for longer-term observed trends.
AB - Seasonal hurricane activity is a function of the amount of initial disturbances (e.g., easterly waves) and the background environment in which they develop into tropical storms (i.e., the main development region). Focusing on the former, a set of indices based solely upon the meridional structure of satellite-derived outgoing longwave radiation (OLR) over the African continent are shown to be capable of predicting Atlantic seasonal hurricane activity with very high rates of success. Predictions of named storms based on the July OLR field and trained only on the time period prior to the year being predicted yield a success rate of 87%, compared to the success rate of NOAA's August outlooks of 53% over the same period and with the same average uncertainty range (±2). The resulting OLR indices are statistically robust, highly detectable, physically linked to the predictand, and may account for longer-term observed trends.
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U2 - 10.1002/2016GL069792
DO - 10.1002/2016GL069792
M3 - Article
AN - SCOPUS:84978289394
SN - 0094-8276
VL - 43
SP - 7152
EP - 7159
JO - Geophysical Research Letters
JF - Geophysical Research Letters
IS - 13
ER -