Wet scavenging of aerosols by continental deep convective clouds is studied for a supercell storm complex observed over Oklahoma during the Deep Convective Clouds and Chemistry campaign. A new passive-tracer-based transport analysis framework is developed to characterize convective transport using vertical profiles of several passive trace gases. For this case, the analysis estimates that observed passive gas mixing ratios in the upper troposphere convective outflow consist of 47% low level (<3 km) inflow air, 32% entrained midtroposphere air, and 21% upper troposphere air. The new analysis framework is used to estimate aerosol wet scavenging efficiencies. Observations yield high overall scavenging efficiencies of 81% for submicron aerosol mass. Organic, sulfate, and ammonium aerosols have similar wet scavenging efficiencies (80%-84%). The apparent scavenging efficiency for nitrate aerosol is much lower (57%), but the scavenging efficiency for nitrate aerosol plus nitric acid combined (84%) is close to the other species. Scavenging efficiencies for aerosol number are high for larger particles (84% for 0.15-2.5 μm diameter) but are lower for smaller particles (64% for 0.03-0.15 μm). The storm is simulated using the chemistry version of the Weather Research and Forecasting model. Compared to the observation-based analysis, the standard model strongly underestimates aerosol scavenging efficiencies by 32% and 41% in absolute differences for submicron mass and number. Adding a new treatment of secondary activation significantly improves simulated aerosol scavenging, producing wet scavenging efficiencies that are only 7% and 8% lower than observed efficiencies. This finding emphasizes the importance of secondary activation for aerosol wet removal in deep convective storms.

Abstract. Realistically representing spatial heterogeneity and lateral land surface processes within and between modeling units in Earth system models is important because of their implications to surface energy and water exchanges. The traditional approach of using regular grids as computational units in land surface models may lead to inadequate representation of subgrid heterogeneity and lateral movements of water, energy and carbon fluxes. Here a subbasin-based framework is introduced in the Community Land Model (CLM), which is the land component of the Community Earth System Model (CESM). Local processes are represented in each subbasin on a pseudo-grid matrix with no significant modifications to the existing CLM modeling structure. Lateral routing of water within and between subbasins is simulated with the subbasin version of a recently developed physically based routing model, Model for Scale Adaptive River Transport (MOSART). The framework is implemented in two topographically and climatically contrasting regions of the US: the Pacific Northwest and the Midwest. The relative merits of this modeling framework, with greater emphasis on scalability (i.e., ability to perform consistently across spatial resolutions) in streamflow simulation compared to the grid-based modeling framework are investigated by performing simulations at 0.125 • , 0.25 • , 0.5 • , and 1 • spatial resolutions. Comparison of the two frameworks at the finest spatial resolution showed that a small difference between the averaged forcing could lead to a larger difference in the simulated runoff and streamflow because of nonlinear processes. More systematic comparisons conducted using statistical metrics calculated between each coarse resolution and the corresponding 0.125 • -resolution simulations showed superior scalability in simulating both peak and mean streamflow for the subbasin based over the grid-based modeling framework. Scalability advantages are driven by a combination of improved consistency in runoff generation and the routing processes across spatial resolutions.

The ability to simulate mixed lubrication problems has greatly improved, especially in concentrated lubricated contacts. A mixed lubrication simulation method was developed by utilizing the semi-system approach which has been proven to be highly useful for improving stability and robustness of mixed lubrication simulations. Then different variants of the model were developed by varying the discretization schemes used to treat the Couette flow terms in the Reynolds equation, varying the evaluation of density derivatives and varying the contribution of terms in the coefficient matrix. The resulting pressure distribution, film thickness distribution, lambda ratio, contact ratio, and the computation time were compared and found to be strongly influenced by the choice of solution scheme. This indicates that the output from mixed lubrication solvers can be readily used for qualitative and parametric studies, but care should be taken when making quantitative predictions.

Extreme heat can be harmful to human health and negatively affect athletic performance. The Tokyo Olympic and Paralympic Games are predicted to be the most oppressively hot Olympics on record. An interdisciplinary multi-scale perspective is provided concerning extreme heat in Tokyofrom planetary atmospheric dynamics, including El Niño Southern Oscillation (ENSO), to fine-scale urban temperatures-as relevant for heat preparedness efforts by sport, time of day, and venue. We utilize stochastic methods to link daytime average wet bulb globe temperature (WBGT) levels in Tokyo in August (from meteorological reanalysis data) with large-scale atmospheric dynamics and regional flows from 1981 to 2016. Further, we employ a mesonet of Tokyo weather stations (2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018) to interpolate the spatiotemporal variability in near-surface air temperatures at outdoor venues. Using principal component analysis, two planetary (ENSO) regions in the Pacific Ocean explain 70% of the variance in Tokyo's August daytime WBGT across 35 years, varying by 3.95°C WGBT from the coolest to warmest quartile. The 10-year average daytime and maximum intra-urban air temperatures vary minimally across Tokyo (<1.2°C and 1.7°C, respectively), and less between venues (0.6-0.7°C), with numerous events planned for the hottest daytime period (1200-1500 hr). For instance, 45% and 38% of the Olympic and Paralympic road cycling events (long duration and intense) occur midday. Climatologically, Tokyo will present oppressive weather conditions, and March-May 2020 is the critical observation period to predict potential anomalous late-summer WBGT in Tokyo. Proactive climate assessment of expected conditions can be leveraged for heat preparedness across the Game's period.