Search for: All records

Abstract Modeling experiments and field campaigns have evaluated shallow convective mixing as a potential constraint on the low‐cloud climate feedback, which is critical for establishing climate sensitivity. Yet the apparent relationship between low‐cloud fraction and shallow convective mixing differs substantially among general circulation models (GCMs), large eddy simulations, and both remote sensing and in situ observations. Here, we consider how changes in GCMs' representations of subgrid‐scale vertical moist fluxes can alter the cloud‐mixing relationship. Using vertical profiles of water vapor isotope ratios (δD) to characterize the strength of shallow convective mixing in a manner that can be compared directly to satellite observations, we evaluate the cloud‐mixing relationship produced in tiered experiments with the Community Atmosphere Model (CAM). From versions 5 to 6 of CAM, the most notable physics change is CLUBB, a scheme that unifies the representation of shallow convection and boundary layer turbulence through a joint probability density function (PDF) for subgrid velocity and moisture. CLUBB reduces the covariance between low‐cloud fraction and shallow convective mixing, producing a bivariate distribution that is more similar in character to monthly averaged satellite observations. Using parameter sensitivity experiments, we argue that CLUBB's ability to simulate skewness in the distribution of vertical velocity produces more isolated but stronger moist updrafts, which reduce the grid‐mean low‐cloud fraction while maintaining efficient hydrological connectivity between the boundary layer and the free troposphere. These results suggest that mixing is not an effective predictor of low‐cloud feedback in GCMs with PDF closure schemes. 

Abstract Describing the processes that regulate the flows and exchanges of water within the atmosphere and between the atmosphere and Earth’s surface is critical for understanding environmental change and predicting Earth’s future accurately. The heavy-to-light hydrogen and oxygen isotope ratios of water provide a useful lens through which to evaluate these processes due to their innate sensitivity to evaporation, condensation, and mixing. In this review, we examine how isotopic information advances our understanding about the origin and transport history of moisture in the atmosphere and about convective processes—including cloud mixing and detrainment, precipitation formation, and rain evaporation. Moreover, we discuss how isotopic data can be used to benchmark numerical simulations across a range of scales and improve predictive skill through data assimilation techniques. This synthesis of work illustrates that, when paired with air mass thermodynamic properties that are commonly measured and modeled (such as specific humidity and temperature), water’s isotope ratios help shed light on moist processes that help set the climate state. 

DAMP21ka.nc: NetCDF file containing the model prior, proxy values, and DAMP21ka reconstruction for lake status, precipitation, and temperature variables.\n\nclhancock/DAMP21ka-v1.0.0.zip: Notebooks used to generate figures for Hancock et al. (2024)\n\nHolocene-code_development_hydroclimate.zip: Code used to generate the DAMP21ka reconstruction \n\n \n\nHancock, C. L., Erb, M. P., McKay, N. P., Dee, S. G., and Ivanovic, R.: A global Data Assimilation of Moisture Patterns from 21,000–0 BP (DAMP-21ka) using lake level proxy records" 

The short and biased observational record of tropical cyclones (TCs) limits scientific understanding of how these destructive storms respond to climate forcing. Paleohurricane records use natural archives (tree rings, coarse‐grained sediment) to reconstruct TC properties (frequency and intensity of rainfall, wind) over the past few hundreds to thousands of years. However, different sensitivities and sampling biases in the various paleohurricane proxies restrict our ability to compile these records into regional or basin‐scale TC estimates. Here we test how well pseudo tree‐ring records of paleohurricanes capture TC rainfall and occurrence. Using a large set of statistically downscaled storms forced with the Max Planck Institute (MPI‐ESM‐P) model as boundary conditions for the past millennium, we generate a 1000‐member ensemble of pseudo tree‐ring records of latewood width from southern Mississippi using a Poisson process‐based random draw. Pseudo records convert synthetic TC rainfall into latewood width using a previously published statistical calibration and seasonal sensitivity. We show that fourth quantile thresholds applied to pseudo latewood data successfully identify years with TC strikes. Comparing pseudo tree‐ring records with pseudo sediment records from the Gulf Coast indicates promise in combining proxies sensitive to TC rainfall with proxies sensitive to storm overwash. Sediment records that are sensitive to lower intensity storms (≥Saffir Simpson Category 1) are more compatible with tree‐ring records, suggesting a need for more of these low intensity threshold records in the Gulf to facilitate future multi‐proxy efforts to reconstruct past TC properties. 

Global hydroclimate significantly differed from modern climate during the mid-Holocene (6 ka) and Last Glacial Maximum (21 ka). Consequently, both periods have been described as either a partial or reverse analogue for current climate change. To reconstruct past hydroclimate, an offline paleoclimate data assimilation methodology is applied to a dataset of 216 lake status records which provide relative estimates of water level change. The proxy observations are integrated with the climate dynamics of two transient simulations (TraCE-21ka and HadCM3) using a multivariate proxy system model (PSM) which estimates relative lake status from available climate simulation variables. The resulting DAMP-21ka (Data Assimilation of Moisture Patterns 21 000–0 BP) reanalysis reconstructs annual lake status and precipitation values at 500-year resolution and represents the first application of the methodology to global hydroclimate on timescales spanning the Holocene and longer. Validation using Pearson's correlation coefficients indicates that the reconstruction (0.24) is more skillful, on average, than model simulations (0.09), particularly in portions of North America and east Africa, where data density is high and proxy–model disagreement is prominent during the Holocene. Results of the PSM and assimilation are used to evaluate climatic controls on lake status, spatiotemporal patterns of moisture variability, and proxy–model disagreement. During the mid-Holocene, wetter conditions are reconstructed for northern and eastern Africa, Asia, and southern Australia, but in contrast to the model prior, negative anomalies are observed in North America, resulting in drier-than-modern conditions throughout the Northern Hemisphere midlatitudes. Proxy–model disagreement in western North America may reflect a bias in model simulations to stronger sea level pressure gradients in the North Pacific during the mid-Holocene. The data assimilation framework is able to reconcile these differences by integrating the constraints of proxy observations with the dynamics of the model prior to produce a more robust estimation of hydroclimate variability during the past 21 000 years. 

Abstract. The Mississippi River is a critical waterway in the United States, and hydrologic variability along its course represents a perennial threat to trade, agriculture, industry, the economy, and communities. The Community Earth System Model version 1 (CESM1) complements observational records of river discharge by providing fully coupled output from a state-of-the-art earth system model that includes a river transport model. These simulations of past, historic, and projected river discharge have been widely used to assess the dynamics and causes of changes in the hydrology of the Mississippi River basin. Here, we compare observations and reanalysis datasets of key hydrologic variables to CESM1 output within the Mississippi River basin to evaluate model performance and bias. We show that the seasonality of simulated river discharge in CESM1 is shifted 2–3 months late relative to observations. This offset is attributed to seasonal biases in precipitation and runoff in the region. We also evaluate performance of several CMIP6 models over the Mississippi River basin, and show that runoff in other models — notably CESM2 — more closely simulates the seasonal trends in the reanalysis data. Our results have implications for model selection when assessing hydroclimate variability on the Mississippi River basin, and show that the seasonal timing of runoff can vary widely between models.  Our findings imply that continued improvements in the representation of land surface hydrology in earth system models may improve our ability to assess the causes and consequences of environmental change on terrestrial water resources and major river systems globally. 

Abstract The Mississippi River is a vital economic corridor used for generating hydroelectric power, transporting agricultural products, and municipal and industrial water use. Communities, industries, and infrastructure along the Mississippi River face an uncertain future as it grows more susceptible to climate extremes. A key challenge is determining whether Mississippi river discharge will increase or decrease during the 21st century. Because the 20th century record is limited in time, paleoclimate data and model simulations provide enhanced understanding of the basin's hydroclimate response to external forcing. Here, we investigate how anthropogenic forcing in the 20th century shifts the statistics of river discharge compared to a Last Millennium (LM) baseline using simulations from the Community Earth System Model Last Millennium Ensemble. We present evidence that the 20th century exhibits wetter conditions (i.e., increased river discharge) over the basin compared to the pre‐industrial, and that land use/land cover changes have a significant control on the hydroclimatic response. Conversely, while precipitation is projected to increase in the 21st century, the basin is generally drier (i.e., decreased river discharge) compared to the 20th century. Overall, we find that changes in greenhouse gases contribute to a lower risk of extreme discharge and flooding in the basin during the 20th century, while land use changes contribute to increased risk of flooding. The additional climate information afforded by the LM simulations offers an improved understanding of what drove extreme flooding events in the past, which can help inform the development of future regional flood mitigation strategies. 

Abstract The Asian summer monsoon (ASM) is teleconnected to the El Niño Southern Oscillation (ENSO), but this relationship is nonstationary and has shifted significantly in recent decades. Characterizing the drivers of such shifts is crucial for improving ASM prediction and extreme event preparedness. Paleoclimate records indicate a link between ASM strength and solar activity on multidecadal‐to‐centennial timescales, but 20th‐century data are too short to test mechanisms. Here we evaluate how solar irradiance influences the ASM‐ENSO relationship using last‐millennium paleoclimate data assimilation reconstructions and model simulations. We find that high solar irradiance weakens the ENSO‐East Asian summer monsoon (EASM) correlation, but strengthens the ENSO‐South Asian summer monsoon (SASM) correlation. Solar irradiance likely influences the strength of the ENSO‐EASM and ENSO‐SASM teleconnections via changes in the Western Pacific Subtropical High and the amplitude of ENSO events, respectively. We suggest a need for considering solar activity in decadal ASM rainfall predictions under global warming scenarios. 

Observations show that the teleconnection between the El Niño‐Southern Oscillation (ENSO) and the Asian summer monsoon (ASM) is non‐stationary. However, the underlying mechanisms are poorly understood due to inadequate availability of reliable, long‐term observations. This study uses two state‐of‐the‐art data assimilation‐based reconstructions of last millennium climate to examine changes in the ENSO–ASM teleconnection; we investigate how modes of (multi‐)decadal climate variability (namely, the Pacific Decadal Oscillation, PDO, and the Atlantic Multidecadal Oscillation, AMO) modulate the ENSO–ASM relationship. Our analyses reveal that the PDO exerts a more pronounced impact on ASM variability than the AMO. By comparing different linear regression models, we find that including the PDO in addition to ENSO cycles can improve prediction of the ASM, especially for the Indian summer monsoon. In particular, dry (wet) anomalies caused by El Niño (La Niña) over India become enhanced during the positive (negative) PDO phases due to a compounding effect. However, composite differences in the ENSO–ASM relationship between positive and negative phases of the PDO and AMO are not statistically significant. A significant influence of the PDO/AMO on the ENSO–ASM relationship occurred only over a limited period within the last millennium. By leveraging the long‐term paleoclimate reconstructions, we document and interrogate the non‐stationary nature of the PDO and AMO in modulating the ENSO–ASM relationship.