skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Attributing Historical Changes in Probabilities of Record-Breaking Daily Temperature and Precipitation Extreme Events

Abstract

Here, 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.

Authors:
 [1];  [2];  [3];  [2];  [4];  [2];  [5];  [6];  [7];  [7];  [2];  [7];  [7]
  1. National Inst. for Environmental Studies, Tsukuba (Japan). Center for Global Environmental Research
  2. Meteorological Research Inst., Tsukuba (Japan)
  3. Univ. of Tokyo (Japan). Research Center for Advanced Science and Technology
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division
  5. Univ. of Tsukuba (Japan). Faculty of Life and Environmental Sciences
  6. Japan Agency for Marine-Earth Science and Technology, Yokohama (Japan)
  7. Univ. of Tokyo (Japan). Atmosphere and Ocean Research Inst.
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); Ministry of Education, Culture, Sports, Science and Technology, Japan
OSTI Identifier:
1378974
Grant/Contract Number:
AC02-05CH11231
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Scientific Online Letters on the Atmosphere
Additional Journal Information:
Journal Volume: 12; Journal Issue: 0; Journal ID: ISSN 1349-6476
Publisher:
Meteorological Society of Japan
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; extreme climate and weather events; record-breaking; attribution; climate simulations

Citation Formats

Shiogama, Hideo, Imada, Yukiko, Mori, Masato, Mizuta, Ryo, Stone, Dáithí, Yoshida, Kohei, Arakawa, Osamu, Ikeda, Mikiko, Takahashi, Chiharu, Arai, Miki, Ishii, Masayoshi, Watanabe, Masahiro, and Kimoto, Masahide. Attributing Historical Changes in Probabilities of Record-Breaking Daily Temperature and Precipitation Extreme Events. United States: N. p., 2016. Web. doi:10.2151/sola.2016-045.
Shiogama, Hideo, Imada, Yukiko, Mori, Masato, Mizuta, Ryo, Stone, Dáithí, Yoshida, Kohei, Arakawa, Osamu, Ikeda, Mikiko, Takahashi, Chiharu, Arai, Miki, Ishii, Masayoshi, Watanabe, Masahiro, & Kimoto, Masahide. Attributing Historical Changes in Probabilities of Record-Breaking Daily Temperature and Precipitation Extreme Events. United States. doi:10.2151/sola.2016-045.
Shiogama, Hideo, Imada, Yukiko, Mori, Masato, Mizuta, Ryo, Stone, Dáithí, Yoshida, Kohei, Arakawa, Osamu, Ikeda, Mikiko, Takahashi, Chiharu, Arai, Miki, Ishii, Masayoshi, Watanabe, Masahiro, and Kimoto, Masahide. 2016. "Attributing Historical Changes in Probabilities of Record-Breaking Daily Temperature and Precipitation Extreme Events". United States. doi:10.2151/sola.2016-045. https://www.osti.gov/servlets/purl/1378974.
@article{osti_1378974,
title = {Attributing Historical Changes in Probabilities of Record-Breaking Daily Temperature and Precipitation Extreme Events},
author = {Shiogama, Hideo and Imada, Yukiko and Mori, Masato and Mizuta, Ryo and Stone, Dáithí and Yoshida, Kohei and Arakawa, Osamu and Ikeda, Mikiko and Takahashi, Chiharu and Arai, Miki and Ishii, Masayoshi and Watanabe, Masahiro and Kimoto, Masahide},
abstractNote = {Here, 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.},
doi = {10.2151/sola.2016-045},
journal = {Scientific Online Letters on the Atmosphere},
number = 0,
volume = 12,
place = {United States},
year = 2016,
month = 8
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Save / Share:
  • This study presents rainfall results from equilibrium 1x- and 2xCO{sub 2} experiments with the CSIRO 4-level general circulation model. The 1xCO{sub 2} results are discussed in relation to observed climate. Discussion of the 2xCO{sub 2} results focuses upon changes in convective and non-convective rainfall as simulated in the model, and the consequences these changes have for simulated daily rainfall intensity and the frequency of heavy rainfall events. The significant shortcomings of GCM simulations of precipitation processes are recognized. Generally, the model results show a marked increase in rainfall originating from penetrative convection and, in the mid-latitudes, a decline in large-scalemore » (non-convective) rainfall. It is argued these changes in rainfall type are a consequence of the increased moisture holding capacity of the warmer atmosphere simulated for 2xCO{sub 2} conditions. Related to changes in rainfall type, rainfall intensity (rain per rain day) increases in the model for most global regions. Increases extend even to regions where total rainfall decreases. Indeed, the greater intensity of daily rainfall is a much clearer response of the model to increased greenhouse gases than the changes in total rainfall. We also find a decrease in the number of rainy days in the middle latitudes of both the Northern and Southern Hemispheres. To further elucidate these results daily rainfall frequency distributions are examined globally and four selected regions of interest. In all regions the frequency of high rainfall events increases, and the return period of such events decreases markedly. If realistic, the findings have potentially serious practical implications in terms of an increased frequency and severity of floods in most regions. However, we discuss various important sources of uncertainty in the results presented, and indicate the need for rainfall intensity results to be examined in enhanced greenhouse experiments with other GCMs. 31 refs., 20 figs.« less
  • It is widely known that the TD3200 (Summary of the Day Cooperative Network) database held by the National Climatic Data Center contains tens of thousands of erroneous daily values resulting from data-entry, data-recording, and data-reformatting errors. TD3200 serves as a major baseline dataset for detecting global climate change. It is of paramount importance to the climate community that these data be as error-free as possible. Many of these errors are systematic in nature. If a deterministic approach is taken, using empirically developed criteria, many if not most of these errors can be corrected or removed. A computer program utilizing Backusmore » Normal Form structure design and a series of chain-linked tests in the form of encoded rules has been developed as a means of modeling the human subjective process of inductive data review. This objective automated correction process has proven extremely effective. A manual review and validation of 138 stations of a 1300-station subset of TD3200 data closely matched the automated correction process. Applications of this technique are expected to be utilized in the production of a nearly error-free TD3200 dataset. 9 refs., 4 figs., 5 tabs.« less
  • The Intergovernmental Panel on Climate Change's Fourth Assessment Report concludes that climate change is now unequivocal, and associated increases in evaporation and atmospheric water content could intensify the hydrological cycle. However, the biases and coarse spatial resolution of global climate models limit their usefulness in hydrological impact assessment. In order to reduce these limitations, we use a high-resolution regional climate model (RegCM3) to drive a hydrological model (variable infiltration capacity) for the full contiguous United States. The simulations cover 1961-1990 in the historic period and 2071-2100 in the future (A2) period. A quantile-based bias correction technique is applied to themore » times series of RegCM3-simulated precipitation and temperature. Our results show that biases in the RegCM3 fields not only affect the magnitude of hydrometeorological variables in the baseline hydrological simulation, but they also affect the response of hydrological variables to projected future anthropogenic increases in greenhouse forcing. Further, we find that changes in the intensity and occurrence of severe wet and hot events are critical in determining the sign of hydrologic change. These results have important implications for the assessment of potential future hydrologic changes, as well as for developing approaches for quantitative impacts assessment.« less
  • Twenty-year return value of annual and seasonal maxima of daily precipitation are calculated from a set of transiently forced coupled general circulation model simulations. The magnitude and pattern of return values are found to be highly dependent on the seasonal cycle. A similar dependence is found for projected future changes in return values. The correlation between the spatial pattern of return value changes and mean precipitation changes is found to be low. Hence, the changes in mean precipitation do not provide significant information about changes in precipitation extreme values.
  • Using a recently homogenized observational daily maximum (TMAX) and minimum temperature (TMIN) dataset for China, the extreme temperatures from the 40-yr ECMWF Re-Analysis (ERA-40), the Japanese 25-year Reanalysis (JRA-25), the NCEP/Department of Energy Global Reanalysis 2 (NCEP-2), and the ECMWF s ERA-Interim (ERAIn) reanalyses for summer (June August) and winter (December February) are assessed by probability density functions for the periods 1979 2001 and 1990 2001. For 1979 2001, no single reanalysis appears to be consistently accurate across eight areas examined over China. The ERA-40 and JRA-25 reanalyses show similar representations and close skill scores over most of the regionsmore » of China for both seasons. NCEP-2 generally has lower skill scores, especially over regions with complex topography. The regional and seasonal differences identified are commonly associated with different geographical locations and the methods used to diagnose these quantities. All the selected reanalysis products exhibit better performance for winter compared to summer over most regions of China. The TMAX values from the reanalysis tend to be systematically underestimated, while TMIN is systematically closer to observed values than TMAX. Comparisons of the reanalyses to reproduce the 99.7 percentiles for TMAX and 0.3 percentiles for TMIN show that most reanalyses tend to underestimate the 99.7 percentiles in maximum temperature both in summer and winter. For the 0.3 percentiles in TMIN, NCEP-2 is relatively inaccurate with a 12 C cold bias over the Qinghai Tibetan Plateau in winter. ERA-40 and JRA-25 generally overestimate the extreme TMIN, and the extreme percentage differences of ERA-40 and JRA-25 are quite similar over all of the regions. The results are generally similar for 1990 2001, but in contrast to the other three reanalysis products the newly released ERAIn is very reasonable, especially for wintertime TMIN, with a skill score greater than 0.83 for each region of China. This demonstrates the great potential of this product for use in future impact assessments on continental scales where those impacts are based on extreme temperatures.« less