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We investigate the hydroclimate impacts of the major Santa Maria (1902) and Katmai (1912) eruptions, which were among the largest eruptions in the 20th century, in the greater tropical Atlantic region (encompassing the Atlantic Ocean, Africa, and the Americas), usingrecently-updated early instrumental data, historical reanalysis output, and climate models. Long-term observational datasets examined include gridded and station precipitation, tropical-Atlantic-flowing river discharge (Amazon, Congo, Paraná, Niger, and Senegal), and tropical Atlantic sea surface salinity, which provides insight into the marine surface freshwater balance (evaporation minus precipitation and surface runoff). We also study the mechanisms of hydroclimate impacts using latest-generation historical atmospheric reanalysis output and a medium-sized ensemble of prescribed volcanic-forcing experiments with the atmospheric general circulation model ECHAM6. Understanding these eruption impacts allows us to contextualize the hydroclimate impacts of better-observed large eruptions since the second half of the 20th century and better anticipate the impacts of future large eruptions.We find that both these volcanic eruptions caused detectable reductions in precipitation and discharge around the tropical Atlantic Basin; however, there were significant differences due to the eruption location and seasonality. In particular, the high-latitude Katmai eruption induced northern hemisphere cooling, driving a southward displacement of the Atlantic intertropical convergence zone (ITCZ) and Hadley circulation, weakening the West African summer monsoon; in contrast, though much closer in distance to the tropical Atlantic, the low-latitude Santa Maria eruption did not induce a comparable displacement of the marine ITCZ or summer monsoon response., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

The mid-Pliocene warm period has been suggested as an analog to a future warmer climate (Jansen et al., 2007), due to its similarity to present day in terms of land-sea distribution as well as CO2. The Pliocene Model Intercomparison Project (PlioMIP), established by Haywood et al. (2010, 2011), is an internationally coordinated effort to identify strengths and weaknesses of climate models in simulating of mid-Pliocene climate. PlioMIP is currently in its second phase, due to advances in the understanding of palaeogeography, ocean, terrestrial and cryosphere of the Pliocene epoch. Boundary conditions have been updated from PlioMIP1 and experiments were prescribed accordingly for PlioMIP2. In this study, a detailed description of the different components of the utilized Community Earth System Models (COSMOS, version: COSMOS-landveg r2413, 2009) as well as experimental procedures prescribed for PlioMIP2 (Haywood et al., 2016) are provided. Furthermore, the procedures applied to transfer the Pliocene Research, Interpretation and Synoptic Mapping (PRISM) Project mid-Pliocene reconstruction into model forcing is documented. The mid-Pliocene, as simulated by COSMOS and the PlioMIP2 prescribed boundary conditions is warmer than the PI-control simulation by 2.15 K in the global mean, corresponding to -0.08 K colder than the PlioMIP1 simulation by the same model. Higher-latitude warming, which is supported by the proxy evidences is still underestimated in the model outputs. The state of the Bering Strait, which is unknown during the mid-Pliocene (Gladenkov et al., 2002) was opened for PlioMIP1 and closed for PlioMIP2 simulations. This study show that a closed Bering Strait leads to better agreement of COSMOS simulation with the reconstruction in North Atlantic region that is very warm during the MPWP. Data-model discrepancies are not fully resolved even with the closure of the Bering Strait, this study show that uncertainty in the concentration of atmospheric CO2 contributes to the disagreement in various Ocean regions. Furthermore, climate sensitivity is estimated for climate states with two different background geographies, and the results confirmed that the response of global temperature to the doubling of CO2 is dependent on the background climate.

We compare results obtained from modeling the mid-Pliocene warm period using the Community Earth System Models (COSMOS, version: COSMOS-landveg r2413, 2009) with the two different modeling methodologies and sets of boundary conditions prescribed for the two phases of the Pliocene Model Intercomparison Project (PlioMIP), tagged PlioMIP1 and PlioMIP2. Here, we bridge the gap between our contributions to PlioMIP1 (Stepanek and Lohmann, 2012) and PlioMIP2 (Stepanek et al., 2020). We highlight some of the effects that differences in the chosen mid-Pliocene model setup (PlioMIP2 vs. PlioMIP1) have on the climate state as derived with COSMOS, as this information will be valuable in the framework of the model–model and model–data comparison within PlioMIP2. We evaluate the model sensitivity to improved mid-Pliocene boundary conditions using PlioMIP's core mid-Pliocene experiments for PlioMIP1 and PlioMIP2 and present further simulations in which we test model sensitivity to variations in paleogeography, orbit, and the concentration of CO2. Firstly, we highlight major changes in boundary conditions from PlioMIP1 to PlioMIP2 and also the challenges recorded from the initial effort. The results derived from our simulations show that COSMOS simulates a mid-Pliocene climate state that is 0.29 ∘C colder in PlioMIP2 if compared to PlioMIP1 (17.82 ∘C in PlioMIP1, 17.53 ∘C in PlioMIP2; values based on simulated surface skin temperature). On the one hand, high-latitude warming, which is supported by proxy evidence of the mid-Pliocene, is underestimated in simulations of both PlioMIP1 and PlioMIP2. On the other hand, spatial variations in surface air temperature (SAT), sea surface temperature (SST), and the distribution of sea ice suggest improvement of simulated SAT and SST in PlioMIP2 if employing the updated paleogeography. Our PlioMIP2 mid-Pliocene simulation produces warmer SSTs in the Arctic and North Atlantic Ocean than those derived from the respective PlioMIP1 climate state. The difference in prescribed CO2 accounts for 0.5 ∘C of temperature difference in the Arctic, leading to an ice-free summer in the PlioMIP1 simulation, and a quasi ice-free summer in PlioMIP2. Beyond the official set of PlioMIP2 simulations, we present further simulations and analyses that sample the phase space of potential alternative orbital forcings that have acted during the Pliocene and may have impacted geological records. Employing orbital forcing, which differs from that proposed for PlioMIP2 (i.e., corresponding to pre-industrial conditions) but falls into the mid-Pliocene time period targeted in PlioMIP, leads to pronounced annual and seasonal temperature variations. Our result identifies the changes in mid-Pliocene paleogeography from PRISM3 to PRISM4 as the major driver of the mid-Pliocene warmth within PlioMIP and not the minor differences in forcings.

This paper describes a global monthly gridded Sea Surface Temperature (SST) and Sea Ice Concentration (SIC) dataset for the period 1000 – 1849, which can be used as boundary conditions for atmospheric model simulations. The reconstruction is based on existing coarse-resolution annual temperature ensemble reconstructions, which are then augmented with intra-annual and sub-grid scale variability. The intra-annual component of HadISST.2.0 and oceanic indices estimated from the reconstructed annual mean are used to develop grid-based linear regressions in a monthly stratified approach. Similarly, we reconstruct SIC using analog resampling of HadISST.2.0 SIC (1941 – 2000), for both hemispheres. Analogs are pooled in four seasons, comprising of 3-months each. The best analogs are selected based on the correlation between each member of the reconstructed SST and its target. For the period 1780 to 1849, we assimilate historical observations of SST and night-time marine air temperature from the ICOADS dataset into our reconstruction using an offline Ensemble Kalman Filter approach. The resulting dataset is physically consistent with information from models, proxies, and observations.

We present the Alfred Wegener Institute's contribution to the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2) wherein we employ the Community Earth System Models (COSMOS) that include a dynamic vegetation scheme. This work builds on our contribution to Phase 1 of the Pliocene Model Intercomparison Project (PlioMIP1) wherein we employed the same model without dynamic vegetation. Our input to the PlioMIP2 special issue of Climate of the Past is twofold. In an accompanying paper we compare results derived with COSMOS in the framework of PlioMIP2 and PlioMIP1. With this paper we present details of our contribution with COSMOS to PlioMIP2. We provide a description of the model and of methods employed to transfer reconstructed mid-Pliocene geography, as provided by the Pliocene Reconstruction and Synoptic Mapping Initiative Phase 4 (PRISM4), to model boundary conditions. We describe the spin-up procedure for creating the COSMOS PlioMIP2 simulation ensemble and present large-scale climate patterns of the COSMOS PlioMIP2 mid-Pliocene core simulation. Furthermore, we quantify the contribution of individual components of PRISM4 boundary conditions to characteristics of simulated mid-Pliocene climate and discuss implications for anthropogenic warming. When exposed to PRISM4 boundary conditions, COSMOS provides insight into a mid-Pliocene climate that is characterised by increased rainfall (+0.17 mm d−1) and elevated surface temperature (+3.37 ∘C) in comparison to the pre-industrial (PI). About two-thirds of the mid-Pliocene core temperature anomaly can be directly attributed to carbon dioxide that is elevated with respect to PI. The contribution of topography and ice sheets to mid-Pliocene warmth is much smaller in contrast – about one-quarter and one-eighth, respectively, and nonlinearities are negligible. The simulated mid-Pliocene climate comprises pronounced polar amplification, a reduced meridional temperature gradient, a northwards-shifted tropical rain belt, an Arctic Ocean that is nearly free of sea ice during boreal summer, and muted seasonality at Northern Hemisphere high latitudes. Simulated mid-Pliocene precipitation patterns are defined by both carbon dioxide and PRISM4 paleogeography. Our COSMOS simulations confirm long-standing characteristics of the mid-Pliocene Earth system, among these increased meridional volume transport in the Atlantic Ocean, an extended and intensified equatorial warm pool, and pronounced poleward expansion of vegetation cover. By means of a comparison of our results to a reconstruction of the sea surface temperature (SST) of the mid-Pliocene we find that COSMOS reproduces reconstructed SST best if exposed to a carbon dioxide concentration of 400 ppmv. In the Atlantic to Arctic Ocean the simulated mid-Pliocene core climate state is too cold in comparison to the SST reconstruction. The discord can be mitigated to some extent by increasing carbon dioxide that causes increased mismatch between the model and reconstruction in other regions.

This paper describes a global monthly gridded Sea Surface Temperature (SST) and Sea Ice Concentration (SIC) dataset for the period 1000–1849, which can be used as boundary conditions for atmospheric model simulations. The reconstruction is based on existing coarse-resolution annual temperature ensemble reconstructions, which are then augmented with intra-annual and sub-grid scale variability. The intra-annual component of HadISST.2.0 and oceanic indices estimated from the reconstructed annual mean are used to develop grid-based linear regressions in a monthly stratified approach. Similarly, we reconstruct SIC using analog resampling of HadISST.2.0 SIC (1941–2000), for both hemispheres. Analogs are pooled in four seasons, comprising of 3-months each. The best analogs are selected based on the correlation between each member of the reconstructed SST and its target. For the period 1780 to 1849, We assimilate historical observations of SST and night-time marine air temperature from the ICOADS dataset into our reconstruction using an offline Ensemble Kalman Filter approach. The resulting dataset is physically consistent with information from models, proxies, and observations., Measurement(s)temperature of sea surface • sea ice concentrationTechnology Type(s)computational modeling techniqueSample Characteristic - Environmentocean Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.16592657