- Award ID(s):
- NSF-PAR ID:
- Date Published:
- Journal Name:
- Monthly Weather Review
- Page Range / eLocation ID:
- 4479 to 4495
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Extratropical cyclones develop in regions of enhanced baroclinicity and progress along climatological storm tracks. Numerous studies have noted an influence of terrestrial snow cover on atmospheric baroclinicity. However, these studies have less typically examined the role that continental snow cover extent and changes anticipated with anthropogenic climate change have on cyclones’ intensities, trajectories, and precipitation characteristics. Here, we examined how projected future poleward shifts in North American snow extent influence extratropical cyclones. We imposed 10th, 50th, and 90th percentile values of snow retreat between the late 20th and 21st centuries as projected by 14 Coupled Model Intercomparison Project Phase Five (CMIP5) models to alter snow extent underlying 15 historical cold-season cyclones that tracked over the North American Great Plains and were faithfully reproduced in control model cases, providing a comprehensive set of model runs to evaluate hypotheses. Simulations by the Advanced Research version of the Weather Research and Forecast Model (WRF-ARW) were initialized at four days prior to cyclogenesis. Cyclone trajectories moved on average poleward (μ = 27 +/− σ = 17 km) in response to reduced snow extent while the maximum sea-level pressure deepened (μ = −0.48 +/− σ = 0.8 hPa) with greater snow removed. A significant linear correlation was observed between the area of snow removed and mean trajectory deviation (r2 = 0.23), especially in mid-winter (r2 = 0.59), as well as a similar relationship for maximum change in sea-level pressure (r2 = 0.17). Across all simulations, 82% of the perturbed simulation cyclones decreased in average central sea-level pressure (SLP) compared to the corresponding control simulation. Near-surface wind speed increased, as did precipitation, in 86% of cases with a preferred phase change from the solid to liquid state due to warming, although the trends did not correlate with the snow retreat magnitude. Our results, consistent with prior studies noting some role for the enhanced baroclinity of the snow line in modulating storm track and intensity, provide a benchmark to evaluate future snow cover retreat impacts on mid-latitude weather systems.more » « less
We examine the distribution of aerosol optical depth (AOD) across 27,707 northern hemisphere (NH) midlatitude cyclones for 2005–2018 using retrievals from the Moderate Resolution Spectroradiometer (MODIS) sensor on the Aqua satellite. Cyclone‐centered composites show AOD enhancements of 20%–45% relative to background conditions in the warm conveyor belt (WCB) airstream. Fine mode AOD accounts for 68% of this enhancement annually. Relative to background conditions, coarse mode AOD is enhanced by more than a factor of two near the center of the composite cyclone, co‐located with high surface wind speeds. Within the WCB, MODIS AOD maximizes in spring, with a secondary maximum in summer. Cyclone‐centered composites of AOD from the Modern Era Retrospective analysis for Research and Applications, version 2 Global Modeling Initiative (M2GMI) simulation reproduce the magnitude and seasonality of the MODIS AOD composites and enhancements. M2GMI simulations show that the AOD enhancement in the WCB is dominated by sulfate (37%) and organic aerosol (25%), with dust and sea salt each accounting for 15%. MODIS and M2GMI AOD are 60% larger in North Pacific WCBs compared to North Atlantic WCBs and show a strong relationship with anthropogenic pollution. We infer that NH midlatitude cyclones account for 355 Tg yr−1of sea salt aerosol emissions annually, or 60% of the 30–80°N total. We find that deposition within WCBs is responsible for up to 35% of the total aerosol deposition over the NH ocean basins. Furthermore, the cloudy environment of WCBs leads to efficient secondary sulfate production.
The properties of diurnal variability in tropical cyclones (TCs) and the mechanisms behind them remain an intriguing aspect of TC research. This study provides a comprehensive analysis of diurnal variability in two simulations of TCs to explore these mechanisms. One simulation is a well-known Hurricane Nature Run (HNR1), which is a realistic simulation of a TC produced using the Weather Research and Forecasting (WRF) Model. The other simulation is a realistic simulation produced using WRF of Hurricane Florence (2018) using hourly ERA5 data as input. Empirical orthogonal functions and Fourier filtering are used to analyze diurnal variability in the TCs. In both simulations a diurnal squall forms at sunrise in the inner core and propagates radially outward and intensifies until midday. At midday the upper-level outflow strengthens, surface inflow weakens, and the cirrus canopy reaches its maximum height and radial extent. At sunset and overnight, the surface inflow is stronger, and convection inside the RMW peaks. Therefore, two diurnal cycles of convection exist in the TCs with different phases of maxima: eyewall convection at sunset and at night, and rainband convection in the early morning. This study finds that the diurnal pulse in the cirrus canopy is not advectively driven, nor can it be attributed to weaker inertial stability at night; rather, the results indicate direct solar heating as a mechanism for cirrus canopy lifting and enhanced daytime outflow. These results show a strong diurnal modulation of tropical cyclone structure, and are consistent with other recent observational and modeling studies of the TC diurnal cycle.
Tropical cyclone intensification processes are explored in six high-resolution climate models. The analysis framework employs process-oriented diagnostics that focus on how convection, moisture, clouds, and related processes are coupled. These diagnostics include budgets of column moist static energy and the spatial variance of column moist static energy, where the column integral is performed between fixed pressure levels. The latter allows for the quantification of the different feedback processes responsible for the amplification of moist static energy anomalies associated with the organization of convection and cyclone spinup, including surface flux feedbacks and cloud-radiative feedbacks. Tropical cyclones (TCs) are tracked in the climate model simulations and the analysis is applied along the individual tracks and composited over many TCs. Two methods of compositing are employed: a composite over all TC snapshots in a given intensity range, and a composite over all TC snapshots at the same stage in the TC life cycle (same time relative to the time of lifetime maximum intensity for each storm). The radiative feedback contributes to TC development in all models, especially in storms of weaker intensity or earlier stages of development. Notably, the surface flux feedback is stronger in models that simulate more intense TCs. This indicates that the representation of the interaction between spatially varying surface fluxes and the developing TC is responsible for at least part of the intermodel spread in TC simulation.
This paper develops a mathematical model and statistical methods to quantify trends in presence/absence observations of snow cover (not depths) and applies these in an analysis of Northern Hemispheric observations extracted from satellite flyovers during 1967–2021. A two-state Markov chain model with periodic dynamics is introduced to analyze changes in the data in a cell by cell fashion. Trends, converted to the number of weeks of snow cover lost/gained per century, are estimated for each study cell. Uncertainty margins for these trends are developed from the model and used to assess the significance of the trend estimates. Cells with questionable data quality are explicitly identified. Among trustworthy cells, snow presence is seen to be declining in almost twice as many cells as it is advancing. While Arctic and southern latitude snow presence is found to be rapidly receding, other locations, such as eastern Canada, are experiencing advancing snow cover.
This project quantifies how the Northern Hemisphere’s snow cover has recently changed. Snow cover plays a critical role in the global energy balance due to its high albedo and insulating characteristics and is therefore a prominent indicator of climate change. On a regional scale, the spatial consistency of snow cover influences surface temperatures via variations in absorbed solar radiation, while continental-scale snow cover acts to maintain thermal stability in the Arctic and subarctic regions, leading to spatial and temporal impacts on global circulation patterns. Changing snow presence in Arctic regions could influence large-scale releases of carbon and methane gas. Given the importance of snow cover, understanding its trends enhances our understanding of climate change.