The Atmospheric River (AR) Tracking Method Intercomparison Project (ARTMIP) is a community effort to systematically assess how the uncertainties from AR detectors (ARDTs) impact our scientific understanding of ARs. This study describes the ARTMIP Tier 2 experimental design and initial results using the Coupled Model Intercomparison Project (CMIP) Phases 5 and 6 multi-model ensembles. We show that AR statistics from a given ARDT in CMIP5/6 historical simulations compare remarkably well with the MERRA-2 reanalysis. In CMIP5/6 future simulations, most ARDTs project a global increase in AR frequency, counts, and sizes, especially along the western coastlines of the Pacific and Atlantic oceans. We find that the choice of ARDT is the dominant contributor to the uncertainty in projected AR frequency when compared with model choice. These results imply that new projects investigating future changes in ARs should explicitly consider ARDT uncertainty as a core part of the experimental design.

The Distributed Hydrology Soil Vegetation Model (DHSVM) code was parallelized for distributed memory computers using the Global Arrays (GA) programming model. To analyze parallel performance, DHSVM was used to simulate the hydrology in two river basins of significant size located in the northwest continental United States and southwest Canada at 90~m resolution: the (1) Clearwater (25,000~km) and (2) Columbia (668,000~km) River basins. Meteorological forcing applied to both basins was dynamically down-scaled from a regional reanalysis using the Weather Research and Forecasting (WRF) model and read into DHSVM as 2D maps for each time step. Parallel code speedup was significant. Run times for 1-year simulations were reduced by an order of magnitude for both test basins. A maximum parallel speedup of 105 was attained with 480 processors while simulating the Columbia River basin. Speedup was limited by input-dominated tasks, particularly the input of meteorological forcing data.

This work documents version two of the Department of Energy’s Energy Exascale Earth System Model (E3SM). E3SM version 2 (E3SMv2) is a significant evolution from its predecessor E3SMv1, resulting in a model that is nearly twice as fast and with a simulated climate that is improved in many metrics. We describe the physical climate model in its lower horizontal resolution configuration consisting of 110 km atmosphere, 165 km land, 0.5° river routing model, and an ocean and sea ice with mesh spacing varying between 60 km in the mid-latitudes and 30 km at the equator and poles. The model performance is evaluated by means of a standard set of Coupled Model Intercomparison Project Phase 6 (CMIP6) Diagnosis, Evaluation, and Characterization of Klima (DECK) simulations augmented with historical simulations as well as simulations to evaluate impacts of different forcing agents. The simulated climate is generally realistic, with notable improvements in clouds and precipitation compared to E3SMv1. E3SMv1 suffered from an excessively high equilibrium climate sensitivity (ECS) of 5.3 K. In E3SMv2, ECS is reduced to 4.0 K which is now within the plausible range based on a recent World Climate Research Programme (WCRP) assessment. However, E3SMv2 significantly underestimates the global mean surface temperature in the second half of the historical record. An analysis of single-forcing simulations indicates that correcting the historical temperature bias would require a substantial reduction in the magnitude of the aerosol-related forcing.

Floodplain inundation links river and land systems through significant water, sediment, and nutrient exchanges. However, these two-way interactions between land and river are currently missing in most Earth System Models. In this study, we introduced the two-way hydrological coupling between the land component, ELM, and the river component, MOSART, in Energy Exascale Earth System Model (E3SM) to study the impacts of floodplain inundation on land and river processes. We calibrated the river channel geometry and developed a new data-driven inundation scheme to improve the simulation of inundation dynamics in E3SM. The new inundation scheme captures 96% of the spatial variation of inundation area in a satellite inundation product at global scale, in contrast with 7% when the default inundation scheme of E3SM was used. Global simulations including the new inundation scheme performed at resolution with and without two-way land-river coupling were used to quantify the impact of coupling. Comparisons show that two-way coupling modifies the water and energy cycle in 20% of the global land cells. Specifically, riverine inundation is reduced by two-way coupling, but inland inundation is intensified. Wetter periods are more impacted by the two-way coupling at the global scale, while regions with different climates exhibit different sensitivities. The two-way exchange of water between the land and river components of E3SM provides the foundation for enabling two-way coupling of land-river sediment and biogeochemical fluxes. These capabilities will be used to improve understanding of the interactions between water and biogeochemical cycles and their response to human perturbations.

The present study examines the characteristics of the MJO events represented in the Energy Exascale Earth System Model version 1 (E3SMv1), DOE’s new Earth system model. The coupled E3SMv1 realistically simulates the eastward propagation of precipitation and Moist Static Energy (MSE) anomalies associated with the MJO. As in observation, horizontal moisture advection and longwave radiative feedback are found to be the dominant processes in E3SMv1 that lead to the eastward movement and maintenance of the MSE anomalies, respectively. Modulation of the diurnal cycle of precipitation in the Maritime Continent region by the MJO is also well represented in the model despite systematic biases in the magnitude and phase of the diurnal cycle. On the midlatitude impact of the MJO, E3SMv1 reasonably captures the pattern of the MJO teleconnection across the North Pacific and North America, with improvement in the performance in a high-resolution version, despite the magnitude being a bit weaker than the observed feature. About interannual variability of the MJO, the El Niño-Southern Oscillation (ENSO) modulation of the zonal extent of MJO’s eastward propagation, as well as associated changes in the mean state moisture gradient in the tropical west Pacific, is well reproduced in the model. However, MJO in E3SMv1 exhibits no sensitivity to the Quasi-Biennial Oscillation (QBO), with the MJO propagation characteristics being almost identical between easterly QBO and westerly QBO years. Processes that have been suggested as critical to MJO simulation are also examined by utilizing recently developed process-oriented diagnostics.

Sub-grid topographic heterogeneity has large impacts on surface energy balance and land-atmosphere interactions. However, the impacts of representing sub-grid topographic effects in land surface models (LSMs) on surface energy balance and boundary conditions remain unclear. This study analyzed and evaluated the impacts of sub-grid topographic representations on surface energy balance, turbulent heat flux and scalar (co-)variances in the Energy Exascale Earth System Model (E3SM) land model (ELM). Three sub-grid topographic representations in ELM were compared: (1) the default sub-grid structure (D), (2) the recently developed sub-grid topographic structure (T), and (3) high spatial resolution (1KM). Additionally, two different solar radiation schemes in ELM were compared: (1) the default plane-parallel radiative transfer scheme (PP) and (2) the parameterization scheme (TOP) that accounts for sub-grid topographic effects on solar radiation. A series of simulations with the three grid structures (D, T and 1KM) and two treatments of solar radiation (TOP and PP) were carried out in the Sierra Nevada, California. There are significant differences between TOP and PP in the 1-km simulated surface energy balance, but the differences in the mean values and standard deviations become small when aggregated to the grid-scale (i.e., 0.5°). The T configuration better mimics the 1KM simulations than the D configuration, and better captures the sub-grid topographic effects on surface energy balance as well as surface boundary conditions. These results underline the importance of representing sub-grid topographic heterogeneities in LSMs and motivate future research to understand the sub-grid topographic effects on land-atmosphere interactions over mountain areas.

In this paper, we introduce a testbed for evaluating and comparing climate modeling systems at cloud resolving scales using hindcasts of the June 2012 North American derecho. The testbed is applied to two models: the regionally-refined Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) at horizontal resolutions ranging from 6.5 to 1.625 km and the Weather Research and Forecasting (WRF) model with 4 km grid spacing. We find the simulation results to be highly sensitive to the initial conditions, initialization time, and model configurations, with initial conditions from the Rapid Refresh (RAP) producing the best simulation. Significant improvement is identified in the SCREAM simulations as horizontal grid spacing is refined. While a propagation delay of approximately 2 hours is found in both models, SCREAM at 1.625 km simulates the observed bow echo structure of the derecho well and predicts strong surface gusts that exceed 30 m/s. In comparison, WRF hardly produces surface wind over 25 m/s, and the derecho wind gust in WRF is 42-46% lower than in SCREAM. Moreover, WRF has a lower bias in simulating cold clouds but overestimates the precipitation intensity. Both models well reproduce the observed outgoing longwave radiation spatial patterns (Pearson correlation > 0.88) while they simulate larger areas of composite radar reflectivity > 40 dBZ by up to 4 times and underestimate the precipitating area by ~ 70\% in WRF and 47\% in SCREAM compared to observations.

The annual cycle of precipitation is a fundamental aspect of the global water cycle. Climate warming induces amplitude enhancement and phase delay in the zonal-mean tropical precipitation. Here, we report a land-ocean contrast in the phase response of precipitation annual cycle, with a delay over land and an advance over ocean as climate warms. Although two-thirds of the Earth’s surface are covered by ocean, land dominates the zonal-mean phase delay, attributable to an increase in the effective atmospheric heat capacity. The phase advance over ocean is associated with a precipitation shift from land to ocean during the peak rainy season. This shift is well constrained by the energetic and related to a land-ocean contrast in the amplitude change of surface temperature annual cycle: seasonally different wind changes enhance this amplitude over ocean, while increased effective atmospheric heat capacity and surface cooling feedback reduce the amplitude over land.

Drought-busting events in the Colorado River Basin, such as the “Miracle May” of 2015 that greatly alleviated an unprecedented water shortage, have been observed for more than a century. But while such events are much prayed for in times of drought, they have not been well researched or even characterized. In this study, conducted in collaboration with water managers from across the basin, we propose a definition for “miracle events” that reflects real-world, actionable relevance. The resulting characterization offers a framework by which to quantify the frequency and strength of extreme dry-to-wet springtime transitions. While limited by uncertainties in model simulations and the myriad hydrological futures these simulations seek to project, and thus requiring cautious interpretation, this study finds that such transitions may become less frequent and less powerful under climate warming.

The southeast Atlantic Ocean provides an excellent natural laboratory to study smoke-cloud interactions, a large driver of uncertainty in climate projections. The value of studying this in particular region is largely attributable to two factors---the expansive, bright, semi-permanent stratocumulus cloud deck and the fact that southern Africa is the largest source of biomass-burning aerosols in the world. We study this region using the WRF-Chem model with CAM5 aerosols and in situ observations from the ORACLES, LASIC, and CLARIFY field campaigns, all of which overlapped in August 2017. Across these campaigns, we compare aerosol, cloud, and thermodynamic variables to quantify model performance and expand upon observational findings of aerosol-cloud effects. Specifically, our approach is to analyze aerosol and cloud properties along flight tracks, picking out uniform legs within tropospheric smoke plumes and in the boundary layer. This unique approach allows us to sample the high spatiotemporal variability that can get lost to large-scale averaging. It also allows process-level comparison of local cloud responses to aerosol conditions, and measure model performance in those same processes. Along with better quantifying model predictive power, we find and justify updates to model parameters and processes to better emulate observations, notably aerosol size parameters. Preliminary results suggest that WRF-CAM5 is activating a smaller percentage of aerosols into cloud droplets than shown in observations, which could lead to biased modeling of aerosol indirect radiative effects on a larger scale. We explore this effect further with CCN activation tendency, updraft, particle sizing, and composition analysis, as well as broader dynamics like entrainment and removal rates. Comparing the model with similar instrument suites across multiple colocated campaigns also allows us to quantify instrument uncertainty in ways that a focus on a single campaign cannot and gives further context to the model performance.

Nitrate aerosol plays an important role in affecting regional air quality as well as Earth’s climate. However, it is not well represented or even neglected in many global climate models. In this study, we couple the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) module with the four-mode version of the Modal Aerosol Module (MAM4) in DOE’s Energy Exascale Earth System Model version 2 (E3SMv2) to treat nitrate aerosol and its radiative effects. We find that nitrate aerosol simulated by E3SMv2-MAM4-MOSAIC is sensitive to the treatment of gaseous HNO3 transfer to/from interstitial particles related to accommodation coefficients of HNO3 (αHNO3) on dust and non-dust particles. We compare three different treatments of HNO3 transfer: 1) a treatment (MTC_SLOW) that uses a low αHNO3 in the mass transfer coefficient (MTC) calculation; 2) a dust-weighted MTC treatment (MTC_WGT) that uses a high αHNO3 on non-dust particles; and 3) a dust-weighted MTC treatment that also splits coarse mode aerosols into the coarse dust and sea salt sub-modes in MOSAIC (MTC_SPLC). MTC_WGT and MTC_SPLC increase the global annual mean (2005-2014) nitrate burden from 0.096 (MTC_SLOW) to 0.237 and 0.185 Tg N, respectively, mostly in the coarse mode. They also produce stronger nitrate direct radiative forcing (–0.048 and –0.051 W m–2, respectively) and indirect forcing (–0.33 and –0.35 W m–2, respectively) than MTC_SLOW (–0.021 and –0.24 W m–2). All three treatments overestimate nitrate surface concentrations compared with ground-based observations. MTC_WGT and MTC_SPLC improve the vertical profiles of nitrate concentrations against aircraft measurements below 400 hPa.

River networks are important features in surface hydrology. However, accurately representing river networks in spatially distributed hydrologic and Earth system models is often sensitive to the model’s spatial resolution. Specifically, river networks are often misrepresented because of the mismatch between the model’s spatial resolution and river network details, resulting in significant uncertainty in the projected flow direction. In this study, we developed a topological relationships-based river network representation method for spatially distributed hydrologic models. This novel method uses (1) graph theory algorithms to simplify real-world vector-based river networks and assist in mesh generation; and (2) a topological relationship-based method to reconstruct conceptual river networks. The main advantages of our method are that (1) it combines the strengths of vector-based and DEM raster-based river network extraction methods; and (2) it is mesh-independent and can be applied to both structured and unstructured meshes. This method paves a path for advanced terrain analysis and hydrologic modeling across different scales.