相关文章推荐
坚强的椅子  ·  多国军方人士祝贺中国人民解放军建军93周年- ...·  5 月前    · 
不敢表白的牛肉面  ·  马连良：妻子多年不育，他不纳妾收养一子，后来 ...·  1 年前    · 
不开心的皮带  ·  【图】第三代混动、多款新车亮相 ...·  1 年前    · 
无聊的莴苣  ·  英国“失踪的国王”为何委身停车场？_腾讯新闻·  1 年前    · 
酒量小的冰棍  ·  excel开n次方根的公式 - 抖音·  1 年前    · 
Code  ›  Projected U.S. drought extremes through the twenty-first century with vapor pressure deficit - PMC
doi pubmed pmc
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9124218/
光明磊落的登山鞋
1 年前
The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely. As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more about our disclaimer.

Supplementary Figures. (11M, docx)

Acknowledgements

B. Gamelin, J. Feinstein, J. Wang, J. Bessac, E. Yan, and V.R. Kotamarthi acknowledge support from AT&T Services Inc. under a Strategic Partnership Project agreement A18131 to Argonne National Laboratory through U.S. Department of Energy contract DE-AC02-06CH11357. We acknowledge and thank Argonne's Laboratory Computing Resource Center (LCRC), Argonne’s Leadership Computing Facility (ALCF) and the National Energy Research Scientific Computing (NERSC) at the Lawrence Berkeley National Laboratory for providing the computational resources used to conduct this research.

Author contributions

All authors contributed to the development of the methodology for this work. B.G. processed the data used for this study. B.G. and J.F. implemented the methodology for the analysis. E.Y. supervised methodology implementation. B.G. interpreted results and prepared the manuscript. B.G., J.W., J.B., J.F. and V.R.K contributed to editing the manuscript.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-022-12516-7.

References

1. Zhang M, Yuan X. Rapid reduction in ecosystem productivity caused by flash droughts based on decade-long FLUXNET observations. Hydrol. Earth Syst. Sci. 2020; 24 :5579–5593. doi: 10.5194/hess-24-5579-2020. [ CrossRef ] [ Google Scholar ]
2. Otkin JA, et al. Examining rapid onset drought development using the thermal infrared-based evaporative stress index. J. Hydrometeorol. 2013; 14 (4):1057–1074. doi: 10.1175/JHM-D-12-0144.1. [ CrossRef ] [ Google Scholar ]
3. Otkin JA, et al. Flash droughts: A review and assessment of the challenges imposed by rapid-onset droughts in the United States. Bull. Am. Meteorol. Soc. 2018; 99 (5):911–919. doi: 10.1175/BAMS-D-17-0149.1. [ CrossRef ] [ Google Scholar ]
4. Field, C. B., et al. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, Cambridge University Press , The Edinburgh Building, Shaftesbury Road, Cambridge CB2 8RU ENGLAND, 582 pp (2012).
5. Held IM, Delworth TL, Lu J, Findell KL, Knutson TR. Simulation of Sahel drought in the 20th and 21st centuries. Proc. Natl. Acad. Sci. U.S.A. 2005; 103 :17891–17896. doi: 10.1073/pnas.0509057102. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
6. Dai A. Drought under global warming: A review. WIREs Clim. Change. 2011; 2 :45–65. doi: 10.1002/wcc.81. [ CrossRef ] [ Google Scholar ]
7. Seneviratne, S. I., et al. Changes in climate extremes and their impacts on the natural physical environment. In: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation [Field, C.B., V. Barros, T.F. Stocker, D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-K. Plattner, S.K. Allen, M. Tignor, and P.M. Midgley (eds.)]. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC). Cambridge University Press , Cambridge, 109–230 (2012).
8. Fu Q, Feng S. Responses of terrestrial aridity to global warming. J. Geophys. Res. Atmos. 2014; 119 :7863–7875. doi: 10.1002/2014JD021608. [ CrossRef ] [ Google Scholar ]
9. Prudhomme C, et al. Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment. Proc. Natl. Acad. Sci. U.S.A. 2014; 111 :3262–3267. doi: 10.1073/pnas.1222473110. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
10. Cook BI, Ault TR, Smerdon JE. Unprecedented 21st century drought risk in the American Southwest and Central Plains. Sci. Adv. 2015; 1 :e1400082. doi: 10.1126/sciadv.1400082. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
11. Duffy PB, Brando P, Asner GP, Field CB. Projections of future meteorological drought and wet periods in the Amazon. Proc. Natl. Acad. Sci. U.S.A. 2015; 112 :13172–13177. doi: 10.1073/pnas.1421010112. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
12. Gutowski, W. J., et al. Causes of observed changes in extremes and projections of future changes in weather and climate extremes in a changing climate Regions of Focus: North America, Hawaii, Caribbean, and U.S. Pacific Islands. T.R. Karl, G.A. Meehl, C.D. Miller, S.J. Hassol, A.M. Waple, and W.L. Murray (eds.). A Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research, Washington, DC. (2008).
13. Trenberth KE, et al. Chapter 3, observations: Surface and atmospheric climate change. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL, et al., editors. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press; 2007. [ Google Scholar ]
14. Diffenbaugh NS, Swain DL, Touma D. Anthropogenic warming has increased drought risk in California. Proc. Natl. Acad. Sci. USA. 2015; 112 :3931–3936. doi: 10.1073/pnas.1422385112. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
15. Wilhite DA, Glantz MH. Understanding the drought phenomenon: The role of definitions. Water Int. 1985; 10 (3):111–120. doi: 10.1080/02508068508686328. [ CrossRef ] [ Google Scholar ]
16. Trenberth KE. Changes in precipitation with climate change. Clim. Res. 2011 doi: 10.3354/cr00953,inpress. [ CrossRef ] [ Google Scholar ]
17. Hoerling, Martin & et al. Temperature and Drought: A science assessment by a subgroup of the drought task force. https://cpo.noaa.gov/Portals/0/Docs/MAPP/Reports/2018/TemperatureDrought/Drought_TF_Temp_Drought_Final_Revised.pdf?ver=2018-07-31-104948-243 (2018).
18. Miralles D, Gentine P, Seneviratne SI, Teuling AJ. Land-atmospheric feedbacks during droughts and heatwaves: State of the science and current challenges. Ann. N. Y. Acad. Sci. 2019; 8 :469. [ PMC free article ] [ PubMed ] [ Google Scholar ]
19. Berg N, Hall A. Increased interannual precipitation extremes over California under climate change. J. Clim. 2015; 28 :6324–6334. doi: 10.1175/JCLI-D-14-00624.1. [ CrossRef ] [ Google Scholar ]
20. Seager R, et al. Causes of the 2011 to 2014 California drought. J. Clim. 2015; 28 :6997–7024. doi: 10.1175/JCLI-D-14-00860.1. [ CrossRef ] [ Google Scholar ]
21. Mankin, J. S., Simpson, I., Hoell A., Fu, R., Lisonbee, J., Sheffield, A. & Barrie, D. NOAA Drought Task Force Report on the 2020–2021 Southwestern U.S. Drought. NOAA Drought Task Force, MAPP, and NIDIS, (2021).
22. Griffin D, Anchukaitis KJ. How unusual is the 2012–2014 California drought? Geophys. Res. Lett. 2014; 41 :9017–9023. doi: 10.1002/2014GL062433. [ CrossRef ] [ Google Scholar ]
23. Shukla S, Safeeq M, AghaKouchak A, Guan K, Funk C. Temperature impacts on the water year 2014 drought in California. Geophys. Res. Lett. 2015; 42 (11):4384–4393. doi: 10.1002/2015GL063666. [ CrossRef ] [ Google Scholar ]
24. Cheng L, et al. How has human-induced climate change affected california drought risk? J. Clim. 2016; 29 :111–120. doi: 10.1175/JCLI-D-15-0260.1. [ CrossRef ] [ Google Scholar ]
25. Williams AP, et al. Contribution of anthropogenic warming to California drought during 2012–2014. Geophys. Res. Lett. 2015; 42 :6819–6828. doi: 10.1002/2015GL064924. [ CrossRef ] [ Google Scholar ]
26. Grossiord C, et al. Plant responses to rising vapor pressure deficit. New Phytol. 2020; 226 :1550–1566. doi: 10.1111/nph.16485. [ PubMed ] [ CrossRef ] [ Google Scholar ]
27. Park Williams A, Allen C, Macalady A, et al. Temperature as a potent driver of regional forest drought stress and tree mortality. Nat. Clim. Change. 2013; 3 :292–297. doi: 10.1038/nclimate1693. [ CrossRef ] [ Google Scholar ]
28. Kolby Smith W, et al. Large divergence of satellite and Earth system model estimates of global terrestrial CO2 fertilization. Nat. Clim. Change. 2016; 6 :306–310. doi: 10.1038/nclimate2879. [ CrossRef ] [ Google Scholar ]
29. Ficklin DL, Novick KA. Historic and projected changes in vapor pressure deficit suggest a continental-scale drying of the United States atmosphere. J. Geophys. Res. Atmosp. 2017; 122 :2061–2079. doi: 10.1002/2016JD025855. [ CrossRef ] [ Google Scholar ]
30. Abatzoglou JT, Williams AP. Impact of anthropogenic climate change on wildfire across western US forests. Proc. Natl. Acad. Sci. 2016; 113 :11770–11775. doi: 10.1073/pnas.1607171113. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
31. Barkhordarian A, Saatchi SS, Behrangi A, et al. A Recent systematic increase in vapor pressure deficit over tropical South America. Sci. Rep. 2019; 9 :15331. doi: 10.1038/s41598-019-51857-8. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
32. Palmer, W.C. Meteorological drought US Weather Bureau Research Paper, 45 (1965).
33. Vicente-Serrano SM, Begueria S, Lopez-Moreno JI. A multi-scalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index. J. Clim. 2010; 23 :1696–1718. doi: 10.1175/2009JCLI2909.1. [ CrossRef ] [ Google Scholar ]
34. Hobbins MT, et al. The evaporative demand drought index. Part I: Linking Drought Evolution to Variations in Evaporative Demand. J. Hydrometeorol. 2016; 17 (6):1745–1761. doi: 10.1175/JHM-D-15-0121.1. [ CrossRef ] [ Google Scholar ]
35. Svoboda M, et al. The drought monitor. Bull. Am. Meteor. Soc. 2002; 83 :1181–1190. doi: 10.1175/1520-0477-83.8.1181. [ CrossRef ] [ Google Scholar ]
36. World Meteorological Organization (WMO) and Global Water Partnership (GWP) Handbook of Drought Indicators and Indices (M. Svoboda and B.A. Fuchs). Integrated Drought Management Programme (IDMP), Integrated Drought Management Tools and Guidelines Series 2. Geneva (2016).
37. McKee, T. B., Doesken, N. J. & Kleist, J. The relationship of drought frequency and duration to time scales, Proceedings of the 8th Conference on Applied Climatology , 179–183, 17, 22, (1993).
38. Hayes M, Svoboda M, Wall N, Widhalm M. The lincoln declaration on drought indices: Universal meteorological drought index recommended. Bull. Am. Meteor. Soc. 2011; 92 (4):485–488. doi: 10.1175/2010BAMS3103.1. [ CrossRef ] [ Google Scholar ]
39. Dai, A. Dai Global Palmer Drought Severity Index (PDSI). Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory (2017). 10.5065/D6QF8R93
40. Chen LG, et al. Flash drought characteristics based on U.S. drought monitor. Atmosphere. 2019; 10 (9):498. doi: 10.3390/atmos10090498. [ CrossRef ] [ Google Scholar ]
41. Hunter JD. Matplotlib: A 2D graphics environment. Comput. Sci. Eng. 2007; 9 (3):90–95. doi: 10.1109/MCSE.2007.55. [ CrossRef ] [ Google Scholar ]
42. Abatzoglou JT, Rupp DE, O'Neill LW, Sadegh M. Compound extremes drive the western Oregon wildfires of September 2020. Geophys. Res. Lett. 2021; 48 :e2021GL092520. doi: 10.1029/2021GL092520. [ CrossRef ] [ Google Scholar ]
43. Li S, Banerjee T. Spatial and temporal pattern of wildfires in California from 2000 to 2019. Sci. Rep. 2021; 11 :8779. doi: 10.1038/s41598-021-88131-9. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
44. Skamarock, W. C., et al. A description of the advanced research WRF version 3. NCAR technical note NCAR/TN-475 + STR (2008). 10.5065/D68S4MVH. http://www2.mmm.ucar.edu/wrf/users/docs/arw_v3.pdf
45. Almazroui M, et al. Projected changes in temperature and precipitation over the united states, central America, and the caribbean in CMIP6 GCMs. Earth Syst. Environ. 2021; 5 :1–24. doi: 10.1007/s41748-021-00199-5. [ CrossRef ] [ Google Scholar ]
46. Zobel Z, Wang J, Wuebbles DJ, Rao Kotamarthi V. High-resolution dynamical downscaling ensemble projections of future extreme temperature distributions for the United States. Earth’s Future. 2017; 5 :1234–1251. doi: 10.1002/2017EF000642. [ CrossRef ] [ Google Scholar ]
47. Rusticucci M, Tencer B. Observed changes in return values of annual temperature extremes over Argentina. J. Clim. 2008; 21 :5455–5467. doi: 10.1175/2008JCLI2190.1. [ CrossRef ] [ Google Scholar ]
48. Schubert SD, Chang Y, Suarez MJ, Pegion PJ. ENSO and wintertime extreme precipitation events over the contiguous United States. J. Clim. 2008; 21 :22–39. doi: 10.1175/2007JCLI1705.1. [ CrossRef ] [ Google Scholar ]
49. Yang L, Villarini G, Smith JA, Tian FQ, Hu HP. Changes in seasonal maximum daily precipitation in China over the period 1961–2006. Int. J. Climatol. 2013; 33 (7):1646–1657. doi: 10.1002/joc.3539. [ CrossRef ] [ Google Scholar ]
50. Rulfová Z, Buishand A, Roth M, Kyselý J. A two-component generalized extreme value distribution for precipitation frequency analysis. J. Hydrol. 2016; 534 :659–668. doi: 10.1016/j.jhydrol.2016.01.032. [ CrossRef ] [ Google Scholar ]
51. Wang J, Han Y, Stein ML, Kotamarthi VR, Huang WK. Evaluation of dynamically downscaled extreme temperature using a spatially-aggregated generalized extreme value (GEV) model. Clim. Dyn. 2016; 47 :2833–2849. doi: 10.1007/s00382-016-3000-3. [ CrossRef ] [ Google Scholar ]
52. Coles S. An Introduction to Statistical Modelling of Extreme Values, Springer Series in Statistics. Springer; 2001. [ Google Scholar ]
53. Prescott P, Walden AT. Maximum likelihood estimation of the parameters of the generalized extreme-value distribution. Biometrika. 1980; 67 :723–724. doi: 10.1093/biomet/67.3.723. [ CrossRef ] [ Google Scholar ]
54. Srivastava AK, Grotjahn R, Ullrich PA, Sadegh M. pooling data improves multimodel IDF estimates over median-based IDF estimates: Analysis over the Susquehanna and Florida. J. Hydrometeorol. 2021; 22 (4):971–995. doi: 10.1175/JHM-D-20-0180.1. [ CrossRef ] [ Google Scholar ]
55. Christian JI, et al. Global distribution, trends, and drivers of flash drought occurrence. Nat. Commun. 2021; 12 :6330. doi: 10.1038/s41467-021-26692-z. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
56. Wang J, Kotamarthi VR. Downscaling with a nested regional climate model in near-surface fields over the contiguous United States. J. Geophys. Res. Atmos. 2014; 119 :8778–8797. doi: 10.1002/2014JD021696. [ CrossRef ] [ Google Scholar ]
57. Zobel Z, Wang J, Wuebbles DJ, Kotamarthi VR. Evaluations of high-resolution dynamically downscaled ensembles over the contiguous United States. Clim. Dyn. 2018; 50 :863–884. doi: 10.1007/s00382-017-3645-6. [ CrossRef ] [ Google Scholar ]
58. Taylor KE, Stouffer RJ, Meehl GA. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 2012; 93 :485. doi: 10.1175/BAMS-D-11-00094.1. [ CrossRef ] [ Google Scholar ]
59. Dunne JP, et al. GFDL’s ESM2 global coupled climate carbon earth system models. part I: Physical formulation and baseline simulation characteristics. J. Clim. 2012; 25 :6646–6665. doi: 10.1175/jcli-d-11-00560.1. [ CrossRef ] [ Google Scholar ]
60. Gent PR, et al. The community climate system model version 4. J. Clim. 2011; 24 (19):4973–4991. doi: 10.1175/2011jcli4083.1. [ CrossRef ] [ Google Scholar ]
61. Jones CD, et al. The HadGEM2-ES implementation of CMIP5 centennial simulations. Geosci. Model Dev. 2011; 4 (3):543–570. doi: 10.5194/gmd-4-543-2011. [ CrossRef ] [ Google Scholar ]
62. Guttman NB. Accepting the standardized precipitation index: A calculation algorithm. J. Am. Water Resour. Assoc. 1999; 35 :311–322. doi: 10.1111/j.1752-1688.1999.tb03592.x. [ CrossRef ] [ Google Scholar ]
63. Xia, Y., et al., NCEP/EMC NLDAS Primary Forcing Data L4 Hourly 0.125 x 0.125 degree V002, Edited by David Mocko, NASA/GSFC/HSL, Greenbelt, Maryland, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), (2009). 10.5067/6J5LHHOHZHN4
64. Xia YK, et al. Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products. J. Geophys. Res. 2012; 117 :D03109. doi: 10.1029/2011JD016048. [ CrossRef ] [ Google Scholar ]
65. Gumbel EJ. Statistics of Extremes. Columbia Univ. Press; 1958. [ Google Scholar ]
66. Pickands J. Statistical inference using extreme order statistics. Ann. Stat. 1975; 3 :119–131. [ Google Scholar ]
67. Robeson SM. Revisiting the recent California drought as an extreme value. Geophys. Res. Lett. 2015; 42 :6771–6779. doi: 10.1002/2015GL064593. [ CrossRef ] [ Google Scholar ]
68. Hosking JRM, Wallis JR. Regional Frequency Analysis: An Approach Based on L-moments. Cambridge University Press; 1997. [ Google Scholar ]
Articles from Scientific Reports are provided here courtesy of Nature Publishing Group
 
推荐文章
坚强的椅子  ·  多国军方人士祝贺中国人民解放军建军93周年-中国法院网
5 月前
不敢表白的牛肉面  ·  马连良：妻子多年不育，他不纳妾收养一子，后来妻子连生七个孩子|京剧|梅兰芳|老旦|丑角_网易订阅
1 年前
不开心的皮带  ·  【图】第三代混动、多款新车亮相 奇瑞集团新能源战略将4月7日开幕_汽车之家
1 年前
无聊的莴苣  ·  英国“失踪的国王”为何委身停车场？_腾讯新闻
1 年前
酒量小的冰棍  ·  excel开n次方根的公式 - 抖音
1 年前
今天看啥   ·   Py中国   ·   codingpro   ·   藏经阁   ·   小百科   ·   link之家   ·   卧龙AI搜索
删除内容请联系邮箱 2879853325@qq.com
Code - 代码工具平台
© 2024 ~ 沪ICP备11025650号