TY - JOUR
T1 - Attributing historical changes in probabilities of record-breaking daily temperature and precipitation extreme events
AU - Shiogama, Hideo
AU - Imada, Yukiko
AU - Mori, Masato
AU - Mizuta, Ryo
AU - Stone, Dáithí
AU - Yoshida, Kohei
AU - Arakawa, Osamu
AU - Ikeda, Mikiko
AU - Takahashi, Chiharu
AU - Arai, Miki
AU - Ishii, Masayoshi
AU - Watanabe, Masahiro
AU - Kimoto, Masahide
N1 - Publisher Copyright:
© 2016, the Meteorological Society of Japan.
PY - 2016
Y1 - 2016
N2 - We describe two unprecedented large (100-member), longterm (61-year) ensembles based on MRI-AGCM3.2, which were driven by historical and non-warming climate forcing. These ensembles comprise the "Database for Policy Decision making for Future climate change (d4PDF)". We compare these ensembles to large ensembles based on another climate model, as well as to observed data, to investigate the influence of anthropogenic activities on historical changes in the numbers of record-breaking events, including: the annual coldest daily minimum temperature (TNn), the annual warmest daily maximum temperature (TXx) and the annual most intense daily precipitation event (Rx1day). These two climate model ensembles indicate that human activity has already had statistically significant impacts on the number of record-breaking extreme events worldwide mainly in the Northern Hemisphere land. Specifically, human activities have altered the likelihood that a wider area globally would suffer record-breaking TNn, TXx and Rx1day events than that observed over the 2001- 2010 period by a factor of at least 0.6, 5.4 and 1.3, respectively. However, we also find that the estimated spatial patterns and amplitudes of anthropogenic impacts on the probabilities of record-breaking events are sensitive to the climate model and/or natural-world boundary conditions used in the attribution studies.
AB - We describe two unprecedented large (100-member), longterm (61-year) ensembles based on MRI-AGCM3.2, which were driven by historical and non-warming climate forcing. These ensembles comprise the "Database for Policy Decision making for Future climate change (d4PDF)". We compare these ensembles to large ensembles based on another climate model, as well as to observed data, to investigate the influence of anthropogenic activities on historical changes in the numbers of record-breaking events, including: the annual coldest daily minimum temperature (TNn), the annual warmest daily maximum temperature (TXx) and the annual most intense daily precipitation event (Rx1day). These two climate model ensembles indicate that human activity has already had statistically significant impacts on the number of record-breaking extreme events worldwide mainly in the Northern Hemisphere land. Specifically, human activities have altered the likelihood that a wider area globally would suffer record-breaking TNn, TXx and Rx1day events than that observed over the 2001- 2010 period by a factor of at least 0.6, 5.4 and 1.3, respectively. However, we also find that the estimated spatial patterns and amplitudes of anthropogenic impacts on the probabilities of record-breaking events are sensitive to the climate model and/or natural-world boundary conditions used in the attribution studies.
UR - http://www.scopus.com/inward/record.url?scp=85007564100&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85007564100&partnerID=8YFLogxK
U2 - 10.2151/sola.2016-045
DO - 10.2151/sola.2016-045
M3 - Article
AN - SCOPUS:85007564100
VL - 12
SP - 225
EP - 231
JO - Scientific Online Letters on the Atmosphere
JF - Scientific Online Letters on the Atmosphere
SN - 1349-6476
ER -
