TY - JOUR
T1 - Downscaled rainfall projections in south Florida using self-organizing maps
AU - Sinha, Palash
AU - Mann, Michael E.
AU - Fuentes, Jose D.
AU - Mejia, Alfonso
AU - Ning, Liang
AU - Sun, Weiyi
AU - He, Tao
AU - Obeysekera, Jayantha
N1 - Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2018/9/1
Y1 - 2018/9/1
N2 - We make future projections of seasonal precipitation characteristics in southern Florida using a statistical downscaling approach based on Self Organized Maps. Our approach is applied separately to each three-month season: September–November; December–February; March–May; and June–August. We make use of 19 different simulations from the Coupled Model Inter-comparison Project, phase 5 (CMIP5) and generate an ensemble of 1500 independent daily precipitation surrogates for each model simulation, yielding a grand ensemble of 28,500 total realizations for each season. The center and moments (25%ile and 75%ile) of this distribution are used to characterize most likely scenarios and their associated uncertainties. This approach is applied to 30-year windows of daily mean precipitation for both the CMIP5 historical simulations (1976–2005) and the CMIP5 future (RCP 4.5) projections. For the latter case, we examine both the “near future” (2021–2050) and “far future” (2071–2100) periods for three scenarios (RCP2.6, RCP4.5, and RCP8.5).
AB - We make future projections of seasonal precipitation characteristics in southern Florida using a statistical downscaling approach based on Self Organized Maps. Our approach is applied separately to each three-month season: September–November; December–February; March–May; and June–August. We make use of 19 different simulations from the Coupled Model Inter-comparison Project, phase 5 (CMIP5) and generate an ensemble of 1500 independent daily precipitation surrogates for each model simulation, yielding a grand ensemble of 28,500 total realizations for each season. The center and moments (25%ile and 75%ile) of this distribution are used to characterize most likely scenarios and their associated uncertainties. This approach is applied to 30-year windows of daily mean precipitation for both the CMIP5 historical simulations (1976–2005) and the CMIP5 future (RCP 4.5) projections. For the latter case, we examine both the “near future” (2021–2050) and “far future” (2071–2100) periods for three scenarios (RCP2.6, RCP4.5, and RCP8.5).
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U2 - 10.1016/j.scitotenv.2018.04.144
DO - 10.1016/j.scitotenv.2018.04.144
M3 - Article
C2 - 29710566
AN - SCOPUS:85045731169
SN - 0048-9697
VL - 635
SP - 1110
EP - 1123
JO - Science of the Total Environment
JF - Science of the Total Environment
ER -