TY - JOUR
T1 - Drivers of precipitation change
T2 - An energetic understanding
AU - Richardson, T. B.
AU - Forster, P. M.
AU - Andrews, T.
AU - Boucher, O.
AU - Faluvegi, G.
AU - Fläschner, D.
AU - Hodnebrog,
AU - Kasoar, M.
AU - Kirkevåg, A.
AU - Lamarque, J. F.
AU - Myhre, G.
AU - Olivié, D.
AU - Samset, B. H.
AU - Shawki, D.
AU - Shindell, D.
AU - Takemura, T.
AU - Voulgarakis, A.
N1 - Funding Information:
The PDRMIP model output is publicly available; for data access, visit http://www. cicero.uio.no/en/PDRMIP/PDRMIP-data-access. T.B.R. was supported by a NERC CASE award in collaboration with the Met Office NE/K007483/1. P.M.F. was supported by a Royal Society Wolfson Merit Award and NERC Grant NE/K006038/1. T.A. was supported by the Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil). B.H.S., G.M., and Ø.H. were funded by the Research Council of Norway, through the grant NAPEX (229778). D.S. andG. F. thank NASA GISS for funding and acknowledge the NASA High-End Computing Program through the NASA Center for Climate Simulation at Goddard Space Flight Center for computational resources. O.B. acknowledges HPC resources from TGCC under the gencmip6 allocation provided by GENCI (Grand Equipement National de Calcul Intensif). T.T. is supported by the NEC SX-ACE supercomputer system of the National Institute for Environmental Studies, Japan, the Environmental Research and Technology Development Fund (S-12-3) of the Ministry of Environment, Japan, and JSPS KAKENHI Grants JP15H01728 and JP15K12190. M. K., D.S., and A.V. were supported by the Natural Environment Research Council under Grant NE/K500872/1, and by the Grantham Institute at Imperial College. Simulations with HadGEM2 and HadGEM3-GA4 were performed using the MONSooN system, a collaborative facility supplied under the Joint Weather and Climate Research Programme, which is a strategic partnership between the Met Office and the Natural Environment Research Council. D.O. and A.K. were supported by the Norwegian Research Council through the projects EVA (229771), EarthClim (207711/E10), NOTUR (nn2345k), and NorStore (ns2345k).
Funding Information:
Acknowledgments. The PDRMIP model output is publicly available; for data access, visit http://www. cicero.uio.no/en/PDRMIP/PDRMIP-data-access. T.B.R. was supported by a NERC CASE award in collaboration with the Met Office NE/K007483/1. P.M.F. was supported by a Royal Society Wolfson Merit Award and NERC Grant NE/K006038/1. T.A. was supported by the Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil). B.H.S., G.M., and Ø.H. were funded by the Research Council of Norway, through the grant NAPEX (229778). D.S. and G. F. thank NASA GISS for funding and acknowledge the NASA High-End Computing Program through the NASA Center for Climate Simulation at Goddard Space Flight Center for computational resources. O.B. acknowledges HPC resources from TGCC under the gencmip6 allocation provided by GENCI (Grand Equipement National de Calcul Intensif). T.T. is supported by the NEC SX-ACE supercomputer system of the National Institute for Environmental Studies, Japan, the Environmental Research and Technology Development Fund (S-12-3) of the Ministry of Environment, Japan, and JSPS KAKENHI Grants JP15H01728 and JP15K12190. M. K., D.S., and A.V. were supported by the Natural Environment Research Council under Grant NE/K500872/1, and by the Grantham Institute at Imperial College. Simulations with HadGEM2 and HadGEM3-GA4 were performed using the MONSooN system, a collaborative facility supplied under the Joint Weather and Climate Research Programme, which is a strategic partnership between the Met Office and the Natural Environment Research Council. D.O. and A.K. were supported by the Norwegian Research Council through the projects EVA (229771), EarthClim (207711/E10), NOTUR (nn2345k), and NorStore (ns2345k).
Publisher Copyright:
© 2018 American Meteorological Society.
PY - 2018/12/1
Y1 - 2018/12/1
N2 - The response of the hydrological cycle to climate forcings can be understood within the atmospheric energy budget framework. In this study precipitation and energy budget responses to five forcing agents are analyzed using 10 climate models from the Precipitation Driver Response Model Intercomparison Project (PDRMIP). Precipitation changes are split into a forcing-dependent fast response and a temperature-driven hydrological sensitivity. Globally, when normalized by top-of-atmosphere (TOA) forcing, fast precipitation changes are most sensitive to strongly absorbing drivers (CO2, black carbon). However, over land fast precipitation changes are most sensitive to weakly absorbing drivers (sulfate, solar) and are linked to rapid circulation changes. Despite this, land-mean fast responses to CO2 and black carbon exhibit more intermodel spread. Globally, the hydrological sensitivity is consistent across forcings, mainly associated with increased longwave cooling, which is highly correlated with intermodel spread. The land-mean hydrological sensitivity is weaker, consistent with limited moisture availability. The PDRMIP results are used to construct a simple model for land-mean and sea-mean precipitation change based on sea surface temperature change and TOA forcing. The model matches well with CMIP5 ensemble mean historical and future projections, and is used to understand the contributions of different drivers. During the twentieth century, temperature-driven intensification of land-mean precipitation has been masked by fast precipitation responses to anthropogenic sulfate and volcanic forcing, consistent with the small observed trend. However, as projected sulfate forcing decreases, and warming continues, land-mean precipitation is expected to increase more rapidly, and may become clearly observable by the mid-twenty-first century.
AB - The response of the hydrological cycle to climate forcings can be understood within the atmospheric energy budget framework. In this study precipitation and energy budget responses to five forcing agents are analyzed using 10 climate models from the Precipitation Driver Response Model Intercomparison Project (PDRMIP). Precipitation changes are split into a forcing-dependent fast response and a temperature-driven hydrological sensitivity. Globally, when normalized by top-of-atmosphere (TOA) forcing, fast precipitation changes are most sensitive to strongly absorbing drivers (CO2, black carbon). However, over land fast precipitation changes are most sensitive to weakly absorbing drivers (sulfate, solar) and are linked to rapid circulation changes. Despite this, land-mean fast responses to CO2 and black carbon exhibit more intermodel spread. Globally, the hydrological sensitivity is consistent across forcings, mainly associated with increased longwave cooling, which is highly correlated with intermodel spread. The land-mean hydrological sensitivity is weaker, consistent with limited moisture availability. The PDRMIP results are used to construct a simple model for land-mean and sea-mean precipitation change based on sea surface temperature change and TOA forcing. The model matches well with CMIP5 ensemble mean historical and future projections, and is used to understand the contributions of different drivers. During the twentieth century, temperature-driven intensification of land-mean precipitation has been masked by fast precipitation responses to anthropogenic sulfate and volcanic forcing, consistent with the small observed trend. However, as projected sulfate forcing decreases, and warming continues, land-mean precipitation is expected to increase more rapidly, and may become clearly observable by the mid-twenty-first century.
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UR - http://www.scopus.com/inward/citedby.url?scp=85055926800&partnerID=8YFLogxK
U2 - 10.1175/JCLI-D-17-0240.1
DO - 10.1175/JCLI-D-17-0240.1
M3 - Article
AN - SCOPUS:85055926800
SN - 0894-8755
VL - 31
SP - 9641
EP - 9657
JO - Journal of Climate
JF - Journal of Climate
IS - 23
ER -