This study examines the impact of ocean advection and surface freshwater flux on the non-seasonal, upper-ocean salinity variability in two climate model simulations with eddy-resolving and eddy-parameterized ocean components (HR and LR, respectively). We assess the realism of each simulation by comparing their sea surface salinity (SSS) variance with satellite and Argo float estimates. Our results show that, in the extratropics, the HR variance is about five times larger than that in LR and agrees with the Argo estimates. In turn, the extratropical satellite SSS variance is smaller than that from HR and Argo by about a factor of two, potentially reflecting the low sensitivity of radiometers to SSS in cold waters. Using a simplified salinity conservation equation for the upper-50-m ocean layer, we find that the advection-driven variance in HR is, on average, one order of magnitude larger than the surface flux-driven variance, reflecting the action of mesoscale processes.

Dynamic influences on summertime seasonal United States rainfall variability are not well understood. A major cause of moisture transport is the Great Plains low-level jet (LLJ). Using observations and a dry atmospheric general circulation model, this study explored the distinct and combined impacts of two prominent atmospheric teleconnections - the East Asian monsoon (EAM) and North Atlantic subtropical high (NASH) - on the Great Plains LLJ in the summer. Separately, a strong EAM and strong western NASH are linked to a strengthened LLJ and positive rainfall anomalies in the Plains/ Midwest. Overall, NASH variability is more important for considering the LLJ impacts, but strong EAM events amplify western NASH-related Great Plains LLJ strengthening and associated rainfall signals. This occurs when the EAM-forced Rossby wave pattern over North America constructively interferes with low-level wind field, providing upper-level support for the LLJ and increasing mid- to upper-level divergence.

Ocean variability is a dominant source of remote rainfall predictability, but in many cases the physical mechanisms driving this predictability are not fully understood. This study examines how ocean mesoscales (i.e., the Gulf Stream SST front) affect decadal southeast US (SEUS) rainfall, arguing that the local imprint of large-scale teleconnections is sensitive to resolved mesoscale features. Based on global coupled model experiments with eddying and eddy-parameterizing ocean, we find that a resolved Gulf Stream improves localized rainfall and remote circulation response in the SEUS. The resolved Gulf Stream influences the boundary layer, driving a barotropic circulation response, thus affecting decadal SEUS rainfall due to a westward extension of the North Atlantic Subtropical High. The eddy-parameterizing simulation fails to capture the sharp SST gradient associated with the Gulf Stream and overestimates the role of tropical SST in the SEUS rainfall due to its classical wintertime connection with the El Niño/Southern Oscillation.

Long-range U.S. summer rainfall prediction skill is low. Monsoon variability, especially over the West North Pacific Monsoon (WNPM) and/or East Asian Monsoon (EAM) region, can influence U.S. Great Plains hydroclimate variability via a forced Rossby wave response. Here we explored subseasonal monsoon variability as a source of predictability for Great Plains rainfall. The boreal summer intraseasonal oscillation is related to Great Plains convection and Great Plains low-level jet (LLJ) anomalies as well as a cross-Pacific wave train. Using a causal effect network, we found that the time between BSISO-related geopotential height anomalies and Great Plains rainfall anomalies is about 2 weeks; therefore, BSISO convection may be a valuable forecast of opportunity for subseasonal prediction of Great Plains convection anomalies. More specifically, causal link patterns/maps revealed that the above-normal weekly EAM rainfall, rather than WNPM rainfall or general geopotential height activity over the East Asia, was causally linked to Great Plains LLJ strengthening and active Great Plains convection the following week.

When will a particular city on the Eastern Seaboard have a 70% chance of flooding at least one hour on at least 70 days of the year? This jam-packed question drives this study, as coastal flooding is becoming increasingly frequent in many East Coast U.S. cities. The frequency of floods that were once categorized as high tide or “nuisance” flooding is rapidly increasing, and many events are escalating to the moderate and major/severe flooding thresholds, putting life and property at risk. This study focuses on flooding events prone to causing property damage and hazardous conditions to make improvements for the subseasonal and seasonal outlooks that are most impactful. A number of East Coast cities are employed as case studies, such as Key West, FL, Charleston, SC, and Annapolis, MD, to analyze current and projected flooding rates. The spatial extent of flooding is considered by using high-resolution topographical data in combination with National Ocean Service tidal datums. NOAA sea level rise scenarios are used to determine the probable time period at which a portion of each city will be experiencing flooding for at least one hour per day frequently throughout the year. Additionally, tide gauge data from the case study cities is decomposed to understand which physical components are contributing to the regional coastal flooding on timescales from subseasonal to seasonal and beyond.

The variability in summer North Pacific subtropical high (NPSH) has a significant impact on the monsoon and typhoon over the East Asia and the drought over the California. However, the future projection of the NPSH through the state-of-art climate models, particularly those pertaining to the tropical precipitation uncertainty remain unclear. In this research, we explore the connection between tropical precipitation uncertainty and the NPSH uncertainty through both fully coupled global circulation models from CMIP5 and a dry-core atmospheric primitive equation model. We have found that the biased condensational heating released through the tropic precipitation interacts with the NPSH through the Rossby wave train and the Kelvin wave response. The source of the tropical precipitation uncertainty can be potentially responsible for the uncertainty of the NPSH under the anthropogenic forced climate change.

This study investigates the influence of oceanic and atmospheric processes in extratropical thermodynamic air-sea interactions resolved by satellite observations (OBS) and by two climate model simulations run with eddy-resolving high-resolution (HR) and eddy-parameterized low-resolution (LR) ocean components. Here, spectral methods are used to characterize the sea surface temperature (SST) and turbulent heat flux (THF) variability and co-variability over scales between 50-10000 km and 60 days-80 years in the Pacific Ocean. The relative roles of the ocean and atmosphere are interpreted using a stochastic upper-ocean temperature evolution model forced by noise terms representing intrinsic variability in each medium, defined using climate model data to produce realistic rather than white spectral power density distributions. The analysis of all datasets shows that the atmosphere dominates the SST and THF variability over zonal wavelengths larger than ~2000-2500 km. In HR and OBS, ocean processes dominate the variability of both quantities at scales smaller than the atmospheric first internal Rossby radius of deformation (R1, ~600-2000 km) due to a substantial ocean forcing coinciding with a weaker atmospheric modulation of THF (and consequently of SST) than at larger scales. The ocean-driven variability also shows a surprising temporal persistence, from intraseasonal to multidecadal, reflecting a red spectrum response to ocean forcing similar to that induced by atmospheric forcing. Such features are virtually absent in LR due to a weaker ocean forcing relative to HR.

Heat waves are among the deadliest natural hazards affecting the United States (US). Therefore, understanding the physical mechanisms modulating their occurrence is essential for improving their predictions and future projections. Using observational data and model simulations, this study finds that the interannual variability of the tropical Atlantic warm pool (AWP, measured as the area enclosed by the 28.5°C sea surface temperature isotherm) modulates heat wave occurrence over the US Great Plains during boreal summer. For example, a larger than normal AWP enhances atmospheric convection over the Caribbean Sea, driving an upper tropospheric anticyclonic anomaly over the Gulf of Mexico and Great Plains, which strengthens subsidence, reduces cloud cover, and increases surface warming. This circulation anomaly thus weakens the Great Plains low-level jet (GPLLJ) and associated moisture transport into the Great Plains, leading to drought conditions and increased heat wave occurrence for most of the US east of the Rockies.