• Adam, J. C., and D. P. Lettenmaier, 2003: Adjustment of global gridded precipitation for systematic bias. J. Geophys. Res., 108, 4257, https://doi.org/10.1029/2002JD002499.

    • Search Google Scholar
    • Export Citation
  • Adcroft, A. J., and Coauthors, 2019: The GFDL global ocean and sea ice model OM4.0: Model description and simulation features. J. Adv. Model. Earth Syst., 11, 31673211, https://doi.org/10.1029/2019MS001726.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Balaji, V., I. Held, M. Winton, S. Malyshev, and R. Stouffer, 2006: The Exchange Grid: A mechanism for data exchange between Earth system components on independent grids. Parallel Computational Fluid Dynamics: Theory and Applications, A. Deane et al., Eds., Elsevier, 179–186, https://doi.org/10.1016/B978-044452206-1/50021-5.

    • Crossref
    • Export Citation
  • Chen, M., P. Xie, J. E. Janowiak, and P. A. Arkin, 2002: Global land precipitation: A 50-yr monthly analysis based on gauge observations. J. Hydrometeor., 3, 249266, https://doi.org/10.1175/1525-7541(2002)003<0249:GLPAYM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dai, A., 2006: Precipitation characteristics in eighteen coupled climate models. J. Climate, 19, 46054630, https://doi.org/10.1175/JCLI3884.1.

  • Dai, A., and K. E. Trenberth, 2004: The diurnal cycle and its depiction in the Community Climate System Model. J. Climate, 17, 930951, https://doi.org/10.1175/1520-0442(2004)017<0930:TDCAID>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Delworth, T. L., and Coauthors, 2012: Simulated climate and climate change in the GFDL CM2.5 high-resolution coupled climate model. J. Climate, 25, 27552781, https://doi.org/10.1175/JCLI-D-11-00316.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Geil, K. L., Y. L. Serra, and X. Zeng, 2013: Assessment of CMIP5 model simulations of the North American monsoon system. J. Climate, 26, 87878801, https://doi.org/10.1175/JCLI-D-13-00044.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gill, A. E., 1980: Some simple solutions for heat-induced tropical circulation. Quart. J. Roy. Meteor. Soc., 106, 447462, https://doi.org/10.1002/qj.49710644905.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffies, S. M., and Coauthors, 2015: Impacts on ocean heat from transient mesoscale eddies in a hierarchy of climate models. J. Climate, 28, 952977, https://doi.org/10.1175/JCLI-D-14-00353.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Held, I. M., and Coauthors, 2019: Structure and performance of GFDL’s CM4.0 climate model. J. Adv. Model. Earth Syst., 11, 36913727, https://doi.org/10.1029/2019MS001829.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jia, L., and Coauthors, 2015: Improved seasonal prediction of temperature and precipitation over land in a high-resolution GFDL climate model. J. Climate, 28, 20442062, https://doi.org/10.1175/JCLI-D-14-00112.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jia, L., and Coauthors, 2016: The roles of radiative forcing, sea surface temperatures, and atmospheric and land initial conditions in U.S. summer warming episodes. J. Climate, 29, 41214135, https://doi.org/10.1175/JCLI-D-15-0471.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiang, X., B. Xiang, M. Zhao, T. Li, S.-J. Lin, Z. Wang, and J.-H. Chen, 2018: Intraseasonal tropical cyclogenesis prediction in a global coupled model system. J. Climate, 31, 62096227, https://doi.org/10.1175/JCLI-D-17-0454.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Johnson, N. C., and Y. Kosaka, 2016: The impact of eastern equatorial Pacific convection on the diversity of boreal winter El Niño teleconnection patterns. Climate Dyn., 47, 37373765, https://doi.org/10.1007/s00382-016-3039-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Johnson, N. C., S.-P. Xie, Y. Kosaka, and X. Li, 2018: Increasing occurrence of cold and warm extremes during the recent global warming slowdown. Nat. Commun., 9, 1724, https://doi.org/10.1038/s41467-018-04040-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kapnick, S. B., and Coauthors, 2018: Potential for western US seasonal snowpack prediction. Proc. Natl. Acad. Sci. USA, 115, 11801185, https://doi.org/10.1073/pnas.1716760115.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Keeley, S. P. E., R. T. Sutton, and L. C. Shaffrey, 2012: The impact of North Atlantic sea surface temperature errors on the simulation of North Atlantic European region climate. Quart. J. Roy. Meteor. Soc., 138, 17741783, https://doi.org/10.1002/qj.1912.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kirtman, B. P., and Coauthors, 2012: Impact of ocean model resolution on CCSM climate simulations. Climate Dyn., 39, 13031328, https://doi.org/10.1007/s00382-012-1500-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Krishnamurthy, L., G. A. Vecchi, R. Msadek, A. Wittenberg, T. L. Delworth, and F. Zeng, 2015: The seasonality of the Great Plains low-level jet and ENSO relationship. J. Climate, 28, 45254544, https://doi.org/10.1175/JCLI-D-14-00590.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Krishnamurthy, L., A. G. Muñoz, G. A. Vecchi, R. Msadek, A. T. Wittenberg, B. Stern, R. Gudgel, and F. Zeng, 2019: Assessment of summer rainfall forecast skill in the Intra-Americas in GFDL high and low-resolution models. Climate Dyn., 52, 19651982, https://doi.org/10.1007/s00382-018-4234-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kucharski, F., I.-S. Kang, R. Farneti, and L. Feudale, 2011: Tropical Pacific response to 20th century Atlantic warming. Geophys. Res. Lett., 38, L03702, https://doi.org/10.1029/2010GL046248.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kushnir, Y., W. A. Robinson, I. Bladé, N. M. J. Hall, S. Peng, and R. Sutton, 2002: Atmospheric GCM response to extratropical SST anomalies: Synthesis and evaluation. J. Climate, 15, 22332256, https://doi.org/10.1175/1520-0442(2002)015<2233:AGRTES>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kushnir, Y., R. Seager, M. Ting, N. Naik, and J. Nakamura, 2010: Mechanisms of tropical Atlantic SST influence on North American precipitation variability. J. Climate, 23, 56105628, https://doi.org/10.1175/2010JCLI3172.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Large, W. G., and G. Danabasoglu, 2006: Attribution and impacts of upper-ocean biases in CCSM3. J. Climate, 19, 23252346, https://doi.org/10.1175/JCLI3740.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, G., and S.-P. Xie, 2014: Tropical biases in CMIP5 multimodel ensemble: The excessive equatorial Pacific cold tongue and double ITCZ problems. J. Climate, 27, 17651780, https://doi.org/10.1175/JCLI-D-13-00337.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, X., S.-P. Xie, S. T. Gille, and C. Yoo, 2016: Atlantic-induced pan-tropical climate change over the past three decades. Nat. Climate Change, 6, 275279, https://doi.org/10.1038/nclimate2840.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liang, X.-Z., J. Zhu, K. E. Kunkel, M. Ting, and J. X. L. Wang, 2008: Do CGCMs simulate the North American monsoon precipitation seasonal-interannual variability? J. Climate, 21, 44244448, https://doi.org/10.1175/2008JCLI2174.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lin, J.-L., 2007: The double-ITCZ problem in IPCC AR4 coupled GFCMs: Ocean–atmosphere feedback analysis. J. Climate, 20, 44974525, https://doi.org/10.1175/JCLI4272.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, Z., A. Mehran, T. J. Phillips, and A. AghaKouchak, 2014: Seasonal and regional biases in CMIP5 precipitation simulations. Climate Res., 60, 3550, https://doi.org/10.3354/cr01221.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McGregor, S., A. Timmermann, M. F. Stuecker, M. H. England, M. Merrifield, F.-F. Jin, and Y. Chikamoto, 2014: Recent Walker circulation strengthening and Pacific cooling amplified by Atlantic warming. Nat. Climate Change, 4, 888892, https://doi.org/10.1038/nclimate2330.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mechoso, C., and Coauthors, 1995: The seasonal cycle over the tropical Pacific in coupled ocean–atmosphere general circulation models. Mon. Wea. Rev., 123, 28252838, https://doi.org/10.1175/1520-0493(1995)123<2825:TSCOTT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mehran, A., A. AghaKouchak, and T. J. Phillips, 2014: Evaluation of CMIP5 continental precipitation simulations relative to satellite-based gauge-adjusted observations. J. Geophys. Res., 119, 16951707, https://doi.org/10.1002/2013JD021152.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mejia, J. F., D. Koračin, and E. M. Wilcox, 2018: Effect of coupled global climate models sea surface temperature biases on simulated climate of the western United States. Int. J. Climatol., 38, 53865404, https://doi.org/10.1002/joc.5817.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murakami, H., G. Villarini, G. A. Vecchi, W. Zhang, and R. Gudgel, 2016: Statistical-dynamical seasonal forecast of North Atlantic and U.S. landfalling tropical cyclones using the high-resolution GFDL FLOR coupled model. Mon. Wea. Rev., 144, 21012123, https://doi.org/10.1175/MWR-D-15-0308.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Okumura, Y. M., C. Deser, A. Hu, A. Timmermann, and S.-P. Xie, 2009: North Pacific climate response to freshwater forcing in the subarctic North Atlantic: Oceanic and atmospheric pathways. J. Climate, 22, 14241445, https://doi.org/10.1175/2008JCLI2511.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pascale, S., V. Lucarini, X. Feng, A. Porporato, and S. ul Hasson, 2015: Analysis of rainfall seasonality from observations and climate models. Climate Dyn., 44, 32813301, https://doi.org/10.1007/s00382-014-2278-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pascale, S., S. Bordoni, S. B. Kapnick, G. A. Vecchi, T. L. Delworth, S. Underwood, and W. Anderson, 2016: The impact of horizontal resolution on North American monsoon Gulf of California moisture surges in a suite of coupled global climate models. J. Climate, 29, 79117936, https://doi.org/10.1175/JCLI-D-16-0199.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pascale, S., W. R. Boos, S. Bordoni, T. L. Delworth, S. B. Kapnick, H. Murakami, G. A. Vecchi, and W. Zhang, 2017: Weakening of the North American monsoon with global warming. Nat. Climate Change, 7, 806812, https://doi.org/10.1038/nclimate3412.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pascale, S., S. B. Kapnick, S. Bordoni, and T. L. Delworth, 2018: The influence of CO2 forcing on North American monsoon moisture surges. J. Climate, 31, 79497968, https://doi.org/10.1175/JCLI-D-18-0007.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peng, S., and J. S. Whitaker, 1999: Mechanisms determining the atmospheric response to midlatitude SST anomalies. J. Climate, 12, 13931408, https://doi.org/10.1175/1520-0442(1999)012<1393:MDTART>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peng, S., W. A. Robinson, and M. P. Hoerling, 1997: The modeled atmospheric response to midlatitude SST anomalies and its dependence on background circulation states. J. Climate, 10, 971987, https://doi.org/10.1175/1520-0442(1997)010<0971:TMARTM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Phillips, T. J., and P. J. Gleckler, 2006: Evaluation of continental precipitation in 20th century climate simulations: The utility of multimodel statistics. Water Resour. Res., 42, W03202, https://doi.org/10.1029/2005WR004313.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rayner, N. A., D. E. Parker, E. B. Horton, C. K. Folland, L. V. Alexander, D. P. Rowell, E. C. Kent, and A. Kaplan, 2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res., 108, 4407, https://doi.org/10.1029/2002JD002670.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Richter, I., 2015: Climate model biases in the eastern tropical oceans: Causes, impacts, and ways forward. Wiley Interdiscip. Rev.: Climate Change, 6, 345358, https://doi.org/10.1002/wcc.338.

    • Search Google Scholar
    • Export Citation
  • Ruprich-Robert, Y., R. Msadek, F. Castruccio, T. Delworth, and G. Danabasoglu, 2017: Assessing the climate impacts of the observed Atlantic multidecadal variability using GFDL CM2.1 and NCAR CESM1 global coupled models. J. Climate, 30, 27852810, https://doi.org/10.1175/JCLI-D-16-0127.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schneider, U., A. Becker, P. Finger, A. Meyer-Christoffer, M. Ziese, and B. Rudolf, 2014: GPCC’s new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle. Theor. Appl. Climatol., 115, 1540, https://doi.org/10.1007/s00704-013-0860-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seager, R., and N. Henderson, 2013: Diagnostic computation of moisture budgets in the ERA-Interim reanalysis with reference to analysis of CMIP-archived atmospheric model data. J. Climate, 26, 78767901, https://doi.org/10.1175/JCLI-D-13-00018.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sheffield, J., and Coauthors, 2013: North American climate in CMIP5 experiments. Part I: Evaluation of historical simulations of continental and regional climatology. J. Climate, 26, 92099245, https://doi.org/10.1175/JCLI-D-12-00592.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stephens, G. L., and Coauthors, 2010: Dreary state of precipitation in global models. J. Geophys. Res., 115, D24211, https://doi.org/10.1029/2010JD014532.

    • Search Google Scholar
    • Export Citation
  • Sun, Y., S. Solomon, A. Dai, and R. W. Portmann, 2006: How often does it rain? J. Climate, 19, 916934, https://doi.org/10.1175/JCLI3672.1.

  • Sutton, R. T., and D. L. R. Hodson, 2007: Climate response to basin-scale warming and cooling of the North Atlantic Ocean. J. Climate, 20, 891907, https://doi.org/10.1175/JCLI4038.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., A. Dai, R. M. Rasmussen, and D. B. Parsons, 2003: The changing character of precipitation. Bull. Amer. Meteor. Soc., 84, 12051218, https://doi.org/10.1175/BAMS-84-9-1205.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tung, K.-K., and X. Chen, 2018: Understanding the global surface warming slowdown: A review. Climate, 6, 82, https://doi.org/10.3390/cli6040082.

  • Van der Wiel, K., and Coauthors, 2016: The resolution dependence of contiguous U.S. precipitation extremes in response to CO2 forcing. J. Climate, 29, 79918012, https://doi.org/10.1175/JCLI-D-16-0307.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vecchi, G. A., and Coauthors, 2014: On the seasonal forecasting of regional tropical cyclone activity. J. Climate, 27, 79948016, https://doi.org/10.1175/JCLI-D-14-00158.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vecchi, G. A., and Coauthors, 2019: Tropical cyclone sensitivities to CO2 doubling: Roles of atmospheric resolution, synoptic variability and background climate changes. Climate Dyn., 53, 59996033, https://doi.org/10.1007/s00382-019-04913-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, C., S.-K. Lee, and D. B. Enfield, 2007: Impact of the Atlantic warm pool on summer climate of the Western Hemisphere. J. Climate, 20, 50215040, https://doi.org/10.1175/JCLI4304.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, C., S.-K. Lee, and D. B. Enfield, 2008: Climate response to anomalously large and small Atlantic warm pools during the summer. J. Climate, 21, 24372450, https://doi.org/10.1175/2007JCLI2029.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, C., L. Zhang, S.-K. Lee, L. Wu, and C. R. Mechoso, 2014: A global perspective on CMIP5 climate model biases. Nat. Climate Change, 4, 201205, https://doi.org/10.1038/nclimate2118.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wilcox, E. M., and L. J. Donner, 2007: The frequency of extreme rain events in satellite rain-rate estimates and an atmospheric general circulation model. J. Climate, 20, 5369, https://doi.org/10.1175/JCLI3987.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Willmott, C. J., and K. Matsuura, 2001: Terrestrial air temperature and precipitation: Monthly and annual time series (1950–1999). http://climate.geog.udel.edu/~climate/html_pages/README.ghcn_ts2.html.

  • Wittenberg, A. T., and Coauthors, 2018: Improved simulations of tropical Pacific annual-mean climate in the GFDL FLOR and HiFLOR coupled GCMs. J. Adv. Model. Earth Syst., 10, 31763220, https://doi.org/10.1029/2018MS001372.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xiang, B., and Coauthors, 2014: Beyond weather time-scale prediction for Hurricane Sandy and Super Typhoon Haiyan in a global climate model. Mon. Wea. Rev., 143, 524535, https://doi.org/10.1175/MWR-D-14-00227.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xiang, B., S.-J. Lin, M. Zhao, N. C. Johnson, X. Yang, and X. Jiang, 2019: Subseasonal week 3–5 surface air temperature prediction during boreal wintertime in a GFDL model. Geophys. Res. Lett., 46, 416425, https://doi.org/10.1029/2018GL081314.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xu, Z., P. Chang, I. Richter, W. Kim, and G. Tang, 2014: Diagnosing southeast tropical Atlantic SST and ocean circulation biases in the CMIP5 ensemble. Climate Dyn., 43, 31233145, https://doi.org/10.1007/s00382-014-2247-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, X., and Coauthors, 2015: Seasonal predictability of extratropical storm tracks in GFDL’s high-resolution climate prediction model. J. Climate, 28, 35923611, https://doi.org/10.1175/JCLI-D-14-00517.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, Z., L. Jia, S. B. Kapnick, T. L. Delworth, G. A. Vecchi, R. Gudgel, S. Underwood, and F. Zeng, 2018: On the seasonal prediction of the western United States El Niño precipitation pattern during the 2015/16 winter. Climate Dyn., 51, 37653783, https://doi.org/10.1007/S00382-018-4109-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, L., and C. Zhao, 2015: Processes and mechanisms for the model SST biases in the North Atlantic and North Pacific: A link with the Atlantic meridional overturning circulation. J. Adv. Model. Earth Syst., 7, 739758, https://doi.org/10.1002/2014MS000415.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, L., C. Wang, Z. Song, and S.-K. Lee, 2014: Remote effect of the model cold bias in the tropical North Atlantic on the warm bias in the tropical southeastern Pacific. J. Adv. Model. Earth Syst., 6, 10161026, https://doi.org/10.1002/2014MS000338.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, R., and T. L. Delworth, 2005: Simulated tropical response to a substantial weakening of the Atlantic thermohaline circulation. J. Climate, 18, 18531860, https://doi.org/10.1175/JCLI3460.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, R., and T. L. Delworth, 2007: Impact of the Atlantic multidecadal oscillation on the North Pacific climate variability. Geophys. Res. Lett., 34, L23708, https://doi.org/10.1029/2007GL031601.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zuidema, P., and Coauthors, 2016: Challenges and prospects for reducing coupled climate model SST biases in the eastern tropical Atlantic and Pacific Oceans: The U.S. CLIVAR Eastern Tropical Oceans Synthesis Working Group. Bull. Amer. Meteor. Soc., 97, 23052328, https://doi.org/10.1175/BAMS-D-15-00274.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
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The Impact of Sea Surface Temperature Biases on North American Precipitation in a High-Resolution Climate Model

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  • 1 Atmospheric and Oceanic Sciences Program, Princeton University, Princeton, New Jersey
  • 2 National Oceanic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey
  • 3 University Corporation for Atmospheric Research, Boulder, Colorado
  • 4 Princeton Environmental Institute, Princeton University, Princeton, New Jersey
  • 5 Department of Earth System Science, Stanford University, Stanford, California
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Abstract

Positive precipitation biases over western North America have remained a pervasive problem in the current generation of coupled global climate models. These biases are substantially reduced, however, in a version of the Geophysical Fluid Dynamics Laboratory Forecast-Oriented Low Ocean Resolution (FLOR) coupled climate model with systematic sea surface temperature (SST) biases artificially corrected through flux adjustment. This study examines how the SST biases in the Atlantic and Pacific Oceans contribute to the North American precipitation biases. Experiments with the FLOR model in which SST biases are removed in the Atlantic and Pacific are carried out to determine the contribution of SST errors in each basin to precipitation statistics over North America. Tropical and North Pacific SST biases have a strong impact on northern North American precipitation, while tropical Atlantic SST biases have a dominant impact on precipitation biases in southern North America, including the western United States. Most notably, negative SST biases in the tropical Atlantic in boreal winter induce an anomalously strong Aleutian low and a southward bias in the North Pacific storm track. In boreal summer, the negative SST biases induce a strengthened North Atlantic subtropical high and Great Plains low-level jet. Each of these impacts contributes to positive annual mean precipitation biases over western North America. Both North Pacific and North Atlantic SST biases induce SST biases in remote basins through dynamical pathways, so a complete attribution of the effects of SST biases on precipitation must account for both the local and remote impacts.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-19-0417.s1.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Nathaniel C. Johnson, nathaniel.johnson@noaa.gov

Abstract

Positive precipitation biases over western North America have remained a pervasive problem in the current generation of coupled global climate models. These biases are substantially reduced, however, in a version of the Geophysical Fluid Dynamics Laboratory Forecast-Oriented Low Ocean Resolution (FLOR) coupled climate model with systematic sea surface temperature (SST) biases artificially corrected through flux adjustment. This study examines how the SST biases in the Atlantic and Pacific Oceans contribute to the North American precipitation biases. Experiments with the FLOR model in which SST biases are removed in the Atlantic and Pacific are carried out to determine the contribution of SST errors in each basin to precipitation statistics over North America. Tropical and North Pacific SST biases have a strong impact on northern North American precipitation, while tropical Atlantic SST biases have a dominant impact on precipitation biases in southern North America, including the western United States. Most notably, negative SST biases in the tropical Atlantic in boreal winter induce an anomalously strong Aleutian low and a southward bias in the North Pacific storm track. In boreal summer, the negative SST biases induce a strengthened North Atlantic subtropical high and Great Plains low-level jet. Each of these impacts contributes to positive annual mean precipitation biases over western North America. Both North Pacific and North Atlantic SST biases induce SST biases in remote basins through dynamical pathways, so a complete attribution of the effects of SST biases on precipitation must account for both the local and remote impacts.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-19-0417.s1.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Nathaniel C. Johnson, nathaniel.johnson@noaa.gov

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