Paleoclimate observations constitute the only constraint on climate behavior prior to the instrumental era. However, such observations only provide indirect (proxy) constraints on physical variables. Proxy system models aim to improve the interpretation of such observations and better quantify their inherent uncertainties. However, existing models are currently scattered in the literature, making their integration difficult. Here, we present a comprehensive modeling framework for proxy systems, named PRYSM. For this initial iteration, we focus on water-isotope based climate proxies in ice cores, corals, tree ring cellulose, and speleothem calcite. We review modeling approaches for each proxy class, and pair them with an isotopeenabled climate simulation to illustrate the new scientific insights that may be gained from this framework. Applications include parameter sensitivity analysis, the quantification of archive-specific processes on the recorded climate signal, and the quantification of how chronological uncertainties affect signal detection, demonstrating the utility of PRYSM for a broad array of climate studies.

Paleoclimate data assimilation has recently emerged as a promising technique to estimate past climate states. Here we test two of the underlying assumptions of paleoclimate data assimilation as applied so far: (1) climate proxies can be modeled as linear, univariate recorders of temperature and (2) structural errors in GCMs can be neglected. To investigate these two points and related uncertainties, we perform a series of synthetic, paleoclimate data assimilation‐based reconstructions where “pseudo” proxies are generated with physically based proxy system models (PSMs) for coral δ18O, tree ring width, and ice core δ18O using two isotope‐enabled atmospheric general circulation models. For (1), we find that linear‐univariate models efficiently capture the GCM's climate in ice cores and corals and do not lead to large losses in reconstruction skill. However, this does not hold for tree ring width, especially in regions where the trees' response is dominated by moisture supply; we quantify how the breakdown of this assumption lowers reconstruction skill for each proxy class. For (2), we find that climate model biases can introduce errors that greatly reduce reconstruction skill, with or without perfect proxy system models. We explore possible strategies for mitigating structural modeling errors in GCMs and discuss implications for paleoclimate reanalyses.

The El Niño–Southern Oscillation (ENSO) shapes global climate patterns yet its sensitivity to external climate forcing remains uncertain. Modeling studies suggest that ENSO is sensitive to sulfate aerosol forcing associated with explosive volcanism but observational support for this effect remains ambiguous. Here, we used absolutely dated fossil corals from the central tropical Pacific to gauge ENSO’s response to large volcanic eruptions of the last millennium. Superposed epoch analysis reveals a weak tendency for an El Niño–like response in the year after an eruption, but this response is not statistically significant, nor does it appear after the outsized 1257 Samalas eruption. Our results suggest that those models showing a strong ENSO response to volcanic forcing may overestimate the size of the forced response relative to natural ENSO variability.

Water isotope data from ice cores, particularly δ18O, have long been used in paleoclimatology. Although δ18O has been primarily interpreted as a proxy for local air temperature, isotope‐enabled climate models have established that there are many nonlocal and nontemperature‐related climatic influences on isotopic signals at coring locations. Moreover, recent observational studies have linked ice core isotopes to nonlocal patterns of climate variability, particularly to midlatitude atmospheric circulation patterns and to variations in tropical climate. Therefore, paleoclimate reconstructions may better utilize ice core isotope proxies by combining them with isotope‐enabled climate models. Here we employ a data assimilation‐based technique that fuses isotopic proxy information with the dynamical constraints of climate models. Through several idealized and real proxy experiments we assess the spatial and temporal extent to which isotope records can reconstruct surface temperature, 500 hPa geopotential height, and precipitation. We find local reconstruction skill to be most robust across the reconstructions, particularly for temperature and geopotential height, as well as limited nonlocal skill in the tropics. These results are in agreement with long‐held views that isotopes in ice cores have clear value as local climate proxies, particularly for temperature and atmospheric circulation. These results also show that in principle nonlocal climate information may also be inferred from ice cores. However, the spatial range of this information is nonuniform and depends on skillful modeling of the proxy data within the reconstruction process.

Reconstructions of temperature and hydrology from lake sedimentary archives have made fundamental contributions to our understanding of past, present, and future climate and help evaluate general circulation models (GCMs). However, because paleoclimate observations are an indirect (proxy) constraint on climatic variables, confounding effects of proxy processes complicate interpretations of these archives. To circumvent these uncertainties inherent to paleoclimate data‐model comparison, proxy system models (PSMs) provide transfer functions between climate variables and the proxy. We here present a new PSM for lacustrine sedimentary archives. The model simulates lake energy and water balance, sensors including leaf wax δD and carbonate δ18O, bioturbation, and compaction of sediment to lend insight toward how these processes affect and potentially obfuscate the original climate signal. The final product integrates existing and new models to yield a comprehensive, modular, adaptable, and publicly available PSM for lake systems. Highlighting applications of the PSM, we forward model lake variables with GCM simulations of the last glacial maximum and the modern. The simulations are evaluated with a focus on sensitivity of lake surface temperature and mixing to climate forcing, using Lakes Tanganyika and Malawi as case studies. The PSM highlights the importance of mixing on interpretations of air temperature reconstructions from lake archives and demonstrates how changes in mixing depth alone may induce nonstationarity between in situ lake and air temperatures. By placing GCM output in the same reference frame as lake paleoclimate archives, we aim to improve interpretations of past changes in terrestrial temperatures and water cycling.

Mississippi River floods rank among the costliest climate-related disasters in the world. Improving flood predictability, preparedness, and response at seasonal to decadal time-scales requires an understanding of the climatic controls that govern flood occurrence. Linking flood occurrence to persistent modes of climate variability like the El Niño-Southern Oscillation (ENSO) has proven challenging, due in part to the limited number of high-magnitude floods available for study in the instrumental record. To augment the relatively short instrumental record, we use output from the Community Earth System Model (CESM) Last Millennium Ensemble (LME) to investigate the dynamical controls on discharge extremes of the lower Mississippi River. We show that through its regional influence on surface water storage, the warm phase of ENSO preconditions the lower Mississippi River to be vulnerable to flooding. In the 6-12 months preceding a flood, El Niño generates a positive precipitation anomaly over the lower Mississippi basin that gradually builds up soil moisture and reduces the basin's infiltration capacity, thereby elevating the risk of a major flood during subsequent rainstorms. Our study demonstrates how natural climate variability mediates the formation of extreme floods on one of the world's principal commercial waterways, adding significant predictive ability to near-and long-term forecasts of flood risk.The Mississippi River is an economic artery of the United States, and federal efforts to understand, predict, and manage flooding along its course have been underway since the 19 th century 1 . On the lower Mississippi (below the Mississippi's confluence with the Ohio River), flood protection is provided by a system of earthen levees and spillway structures designed to contain discharges exceeding those associated with the largest floods observed during the early 20 th century 2 . Floods remain costly despite the protection offered by modern river engineering, with economic damages from flooding in 2011 estimated to be $3.2 billion 3 . Failure of key elements of the current flood control system, which nearly occurred during a major flood in 1973, would be an economic and humanitarian disaster of unprecedented severity 4 . Forecasting flood occurrence over seasonal to decadal time-scales, and thus affirming the viability of these flood protection measures, remains a major challenge -especially in light of the brevity of the instrumental record and the confounding effects of flood control infrastructure on the behavior of fluvial systems 5, 6 , both of which limit our ability to characterize hydrological systems' sensitivity to climate variability and change 7,8 .Improving flood forecasting for the lower Mississippi depends on understanding the links between flood occurrence and the slowly varying, more predictable modes of climate variability that influence hydrological processes over central North America, including the Pacific-North American Pattern (PNA), the Atlantic Multi-Decadal Oscillation (AMO), the North At...

General circulation models (GCMs) predict that the global hydrological cycle will change in response to anthropogenic warming. However, these predictions remain uncertain, in particular, for precipitation (Intergovernmental Panel on Climate Change, 2013, https://doi.org/10.1017/CBO9781107415324.004). Held and Soden (2006, https://doi.org/10.1175/JCLI3990.1) suggest that as lower tropospheric water vapor concentration increases in a warming climate, the atmospheric circulation and convective mass fluxes will weaken. Unfortunately, this process is difficult to constrain, as convective mass fluxes are poorly observed and incompletely simulated in GCMs. Here we demonstrate that stable hydrogen isotope ratios in tropical atmospheric water vapor can trace changes in temperature, atmospheric circulation, and convective mass flux in a warming world. We evaluate changes in temperature, the distribution of water vapor, vertical velocity (ω), advection, and water isotopes in vapor (δDV). Using water isotope‐enabled GCM experiments for modern versus high‐CO2 atmospheres, we identify spatial patterns of circulation change over the tropical Pacific. We find that slowing circulation in the tropical Pacific moistens the lower troposphere and weakens convective mass flux, both of which impact the δD of water vapor in the midtroposphere. Our findings constitute a critical demonstration of how water isotope ratios in the tropical Pacific respond to changes in radiative forcing and atmospheric warming. Moreover, as changes in δDV can be observed by satellites, our results develop new metrics for the detection of global warming impacts to the hydrological cycle and, specifically, the strength of the Walker circulation.

The interpretation of variations in the global isotopic composition of precipitation and water vapor can be strengthened using an isotope‐enabled atmospheric general circulation model (AGCM). Here we present a fast‐physics atmospheric circulation model suitable for long ensemble integrations: the efficient AGCM Simplified Parameterizations, Primitive Equation Dynamics (SPEEDY), with newly added water isotope physics. The model (SPEEDY‐isotope‐enabled reconstructions (IER)) simulates the hydrological cycle and isotope ratios in atmospheric water at a fraction of the computational cost of Intergovernmental Panel on Climate Change (IPCC)‐class GCMs. Despite its simplified physics, SPEEDY‐IER captures many key features of the observed range of tropical, subtropical, and midlatitude isotope variability when compared to the Global Network of Isotopes in Precipitation, Stable Water Isotope Intercomparison Group (SWING2) simulations, and satellite observations of isotopes in vapor. The incorporation of water isotopes in SPEEDY required two updates to the model's physics: postcondensational exchange associated with falling rain and soil hydrology. It is evident that these physical processes are essential for a skillful simulation of isotopes in precipitation and vapor. We conduct a suite of sensitivity tests to constrain effective parameters in the rain exchange and land models and assess the impact of the new physics to isotope simulations. The strong sensitivity to parameter choice in these components reaffirms the importance of land‐atmosphere interactions and rain‐vapor exchange on stable water isotope ratios in the atmosphere and thus on the interpretation of paleoclimate records. The utility of SPEEDY‐IER for climate applications is discussed.