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Author ORCID ID is 0000000232219467
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  1. Sediment yield (SY) plays an important role in the global carbon cycle for carrying particulate carbon into rivers and oceans, but it is rarely represented in Earth system models (ESMs). Existing SY models have mostly been tested over a few small catchments in specific regions or in large river basins globally. By comparing the performance of eight well–known SY models in 454 small catchments with various land covers and uses across the United States, Canada, Puerto Rico, U.S. Virgin Islands, and Guam, we identified the simple Morgan model for its better performance in representing the spatial variability of continental scalemore » SY at spatial scales relevant to ESMs (several to hundreds of square kilometers) than other models because of a more realistic representation of runoff–driven erosion and sediment transport capacity in the context of current data availability. The results also indicated that runoff–driven erosion should be formulated using a power function of runoff, shear stress, or stream power to better represent the total effect of concentrated flow if gully erosion and channel erosion are not explicitly modeled. We also demonstrated that the Morgan model can be further improved by removing snowmelt–driven runoff in modeling runoff–driven erosion and to a minor degree by integrating a landslide model. The improved Morgan model explains 57% of the spatial variability of the measured SY. In conclusion, the new model also demonstrated the capability to simulate SY in cross–validation catchments at fine temporal scales, which is important for coupling SY with other biogeochemistry processes in ESMs.« less
  2. Here, we show that 21st century increase in radiative forcing does not significantly impact the frequency of South Asian summer monsoon depressions (MDs) or their trajectories in the Coupled Model Intercomparison Project Phase 5 general circulation models (GCMs). A significant relationship exists between the climatological occurrences of MDs and the strength of the background upper (lower) tropospheric meridional (zonal) winds and tropospheric moisture in the core genesis region of MDs. Likewise, there is a strong relationship between the strength of the meridional tropospheric temperature gradient in the GCMs and the trajectories of MDs over land. While monsoon dynamics progressively weakensmore » in the future, atmospheric moisture exhibits a strong increase, limiting the impact of changes in dynamics on the frequency of MDs. Moreover, the weakening of meridional tropospheric temperature gradient in the future is substantially weaker than its inherent underestimation in the GCMs. Our results also indicate that future increases in the extreme wet events are dominated by nondepression day occurrences, which may render the monsoon extremes less predictable in the future.« less
  3. Convection permitting simulations using the Model for Prediction Across Scales-Atmosphere (MPAS-A) are used to examine how microphysical processes affect large-scale precipitation variability and extremes. An episode of the Madden-Julian Oscillation is simulated using MPAS-A with a refined region at 4-km grid spacing over the Indian Ocean. It is shown that cloud microphysical processes regulate the precipitable water (PW) statistics. Because of the non-linear relationship between precipitation and PW, PW exceeding a certain critical value (PWcr) contributes disproportionately to precipitation variability. However, the frequency of PW exceeding PWcr decreases rapidly with PW, so changes in microphysical processes that shift the columnmore » PW statistics relative to PWcr even slightly have large impacts on precipitation variability. Furthermore, precipitation variance and extreme precipitation frequency are approximately linearly related to the difference between the mean and critical PW values. Thus observed precipitation statistics could be used to directly constrain model microphysical parameters as this study demonstrates using radar observations from DYNAMO field campaign.« less
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