PDRMIP: A Precipitation Driver and Response Model Intercomparison Project—Protocol and Preliminary Results

Abstract

As the global temperature increases with changing climate, precipitation rates and patterns are affected through a wide range of physical mechanisms. The globally averaged intensity of extreme precipitation also changes more rapidly than the globally averaged precipitation rate. While some aspects of the regional variation in precipitation predicted by climate models appear robust, there is still a large degree of intermodel differences unaccounted for. Individual drivers of climate change initially alter the energy budget of the atmosphere, leading to distinct rapid adjustments involving changes in precipitation. Differences in how these rapid adjustment processes manifest themselves within models are likely to explain a large fraction of the present model spread and better quantifications are needed to improve precipitation predictions. Here, the authors introduce the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where a set of idealized experiments designed to understand the role of different climate forcing mechanisms were performed by a large set of climate models. PDRMIP focuses on understanding how precipitation changes relating to rapid adjustments and slower responses to climate forcings are represented across models. Initial results show that rapid adjustments account for large regional differences in hydrological sensitivity across multiple drivers. The PDRMIP results are expected to dramatically improve understanding of the causes of the present diversity in future climate projections.

Decadal climate variability and the global energy balance

“…However, the changing observing system seriously compromises the global precipitation variability depicted by ERAI as previously reported (Dee et al, 2011;Allan et al, 2014a). Interannual coupling of GPCP precipitation with HadCRUT Ts over this period is 3.0±0.7 %/K (r=0.37), consistent with estimates of temperature dependent precipitation sensitivity (Andrews et al, 2010;Myhre et al, 2017). Global precipitation increases with global Ts primarily due to the enhanced radiative loss for higher surface and atmospheric temperatures, set by the thermodynamics of the coupled system (Roderick et al 2014;Myhre et al, 2017) although this is tempered by the additional absorption of sunlight by higher water vapor loadings (Allan 2009) and modified by sensible heat flux changes.…”

“…This variability can potentially be exploited in elucidating regional feedbacks on internal decadal variability (Brown et al, 2014;Zhou et al, 2016;Xie et al, 2015) as well as in advancing understanding of how the spatial nature of climate change influences how sensitive the global climate is to radiative forcings (Gregory and Andrews, 2016). The regional manifestation of changes in the energy budget and water cycle have been identified globally (Myhre et al, 2017;Bony et al, 2013) and at hemispheric (Hwang et al, 2013;Loeb et al, 2016;Stephens et al, 2017) to continental scales (Bollasina et al, 2011;Dong and Sutton, 2015). Applying a regional energy budget perspective is informative in understanding these water cycle responses (Muller and O'Gorman, 2011) and for tracking energy within the climate system: combining satellite radiation budget measurements with reanalysis energy transports to estimate surface fluxes can be used to identify regional decadal patterns of ocean heating (Liu et al, 2017) and potentially constrain ocean energy transports (Trenberth and Fasullo, 2017) and their changes from one decade to the next.…”

Weak hydrological sensitivity to temperature change over land, independent of climate forcing

“…[16][17][18][19][20] The slow change mainly scales with surface temperature, which in turn scales closely with top-of-atmosphere radiative forcing, while the rapid adjustments scale with the amount of additional energy absorbed through the atmospheric column. [11][12][13] In particular, black carbon has been noted as an anthropogenic climate driver that is significantly different from the others, due mainly to its high atmospheric absorption and regionally heterogeneous radiative forcing.…”

“…13,20 See Methods for a full list. As models performed both fully ocean-atmosphere coupled simulations and prescribed sea-surface temperature (fSST) atmospheric simulations, it is possible to extract and compare the thermal hydrological sensitivity between drivers.…”

Mediterranean Precipitation Response to Greenhouse Gases and Aerosols

“…The nine models used in this study are listed in Table 1. A more detailed description of PDRMIP and its initial findings are given in Samset et al (2016) and Myhre et al (2017). 15…”