This study analyzes the effect of the location of the North Atlantic Subtropical High (NASH) western ridge on the daily variability of precipitation organization in the southeastern United States (SE US). The western side of the NASH, also known as the NASH western ridge, plays an important role in the variability of summertime precipitation in this region. In this study, the mean summertime position of the NASH western ridge was determined and used to classify each summer day during 2009–2012 into one of four quadrants. Composites of synoptic‐scale circulation and precipitation from mesoscale and isolated precipitation features (MPF and IPF) were calculated for each NASH western ridge quadrant. MPF contributed most (about 65%) of the total summertime precipitation and accounted for most of the differences between the four NASH quadrants. Domain‐averaged precipitation was highest (lowest) during NASH‐SW (NASH‐NW) when IPF (MPF) precipitation was strongest (weakest). The regionality of MPF precipitation maxima was generally associated with the location of low‐level jets and upper‐level troughs. For instance, positive MPF anomalies occurred across the SE US during NASH‐SW when the Great Plains low‐level jet turned eastward bringing moisture to fuel convection in the SE US. In contrast, IPF rain was distributed more uniformly across the SE US. Finally, this study revealed a dipole of precipitation that is controlled by the position of the NASH western ridge and its associated low‐level jets. In one extreme of the dipole NASH‐SE, periods are associated with enhanced MPF precipitation along the coast and offshore for days at a time, and suppressed MPF precipitation inland. The opposite pattern occurs during NASH‐NW when MPF precipitation is enhanced inland and suppressed along the coast and offshore.
- Award ID(s):
- 2047721
- NSF-PAR ID:
- 10427638
- Date Published:
- Journal Name:
- Journal of Climate
- Volume:
- 35
- Issue:
- 20
- ISSN:
- 0894-8755
- Page Range / eLocation ID:
- 3265 to 3284
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
Abstract -
Abstract Regional ocean–atmospheric interactions in the summer tropical Indo–northwest Pacific region are investigated using a tropical Pacific Ocean–global atmosphere pacemaker experiment with a coupled ocean–atmospheric model (cPOGA) and a parallel atmosphere model simulation (aPOGA) forced with sea surface temperature (SST) variations from cPOGA. Whereas the ensemble mean features pronounced influences of El Niño–Southern Oscillation (ENSO), the ensemble spread represents internal variability unrelated to ENSO. By comparing the aPOGA and cPOGA, this study examines the effect of the ocean–atmosphere coupling on the ENSO-unrelated variability. In boreal summer, ocean–atmosphere coupling induces local positive feedback to enhance the variance and persistence of the sea level pressure and rainfall variability over the northwest Pacific and likewise induces local negative feedback to suppress the variance and persistence of the sea level pressure and rainfall variability over the north Indian Ocean. Anomalous surface heat fluxes induced by internal atmosphere variability cause SST to change, and SST anomalies feed back onto the atmosphere through atmospheric convection. The local feedback is sensitive to the background winds: positive under the mean easterlies and negative under the mean westerlies. In addition, north Indian Ocean SST anomalies reinforce the low-level anomalous circulation over the northwest Pacific through atmospheric Kelvin waves. This interbasin interaction, along with the local feedback, strengthens both the variance and persistence of atmospheric variability over the northwest Pacific. The response of the regional Indo–northwest Pacific mode to ENSO and influences on the Asian summer monsoon are discussed.more » « less
-
Abstract An open question in the study of climate prediction is whether internal variability will continue to contribute to prediction skill in the coming decades, or whether predictable signals will be overwhelmed by rising temperatures driven by anthropogenic forcing. We design a neural network that is interpretable such that its predictions can be decomposed to examine the relative contributions of external forcing and internal variability to future regional sea surface temperature (SST) trend predictions in the near-term climate (2020–2050). We show that there is additional prediction skill to be garnered from internal variability in the Community Earth System Model version 2 Large Ensemble, even in a relatively high forcing future scenario. This predictability is especially apparent in the North Atlantic, North Pacific and Tropical Pacific Oceans as well as in the Southern Ocean. We further investigate how prediction skill covaries across the ocean and find three regions with distinct coherent prediction skill driven by internal variability. SST trend predictability is found to be associated with consistent patterns of decadal variability for the grid points within each region.
-
Stochastic variability of internal atmospheric modes, known as teleconnection patterns, drives large-scale patterns of low-frequency SST variability in the extratropics . To investigate how the decadal component of this stochastically driven variability in the South and North Pacific affects the tropical Pacific and contributes to the observed basinwide pattern of decadal variability, a suite of climate model experiments was conducted . In these experiments, the models are forced with constant surface heat flux anomalies associated with the decadal component of the dominant atmospheric modes, particularly the Pacific–South American (PSA) and North Pacific Oscillation (NPO) patterns . Both the PSA and NPO modes induce basinwide SST anomalies in the tropical Pacific and beyond that resemble the observed interdecadal Pacific oscillation . The subtropical SST anomalies forced by the PSA and NPO modes propagate to the equatorial Pacific mainly through the wind–evaporation–SST feedback . This atmospheric bridge is stronger from the South Pacific than the North Pacific due to the northward displacement of the intertropical convergence zone and the associated northward advection of momentum anomalies. The equatorial ocean dynamics is also more strongly influenced by atmospheric circulation changes induced by the PSA mode than the NPO mode. In the PSA experiment, persistent and zonally coherent wind stress curl anomalies over the South Pacific affect the zonal mean depth of the equatorial thermocline and weaken the equatorial SST anomalies resulting from the atmospheric bridge. This oceanic adjustment serves as a delayed negative feedback and may be important for setting the time scales of tropical Pacific decadal variability.
-
Variability of North Atlantic annual hurricane frequency during 1951–2010 is studied using a 100-member ensemble of climate simulations by a 60-km atmospheric general circulation model that is forced by observed sea surface temperatures (SSTs). The ensemble mean results well capture the interannual-to-decadal variability of hurricane frequency in best track data since 1970, and suggest that the current best track data might underestimate hurricane frequency prior to 1966 when satellite measurements were unavailable. A genesis potential index (GPI) averaged over the main development region (MDR) accounts for more than 80% of the SST-forced variations in hurricane frequency, with potential intensity and vertical wind shear being the dominant factors. In line with previous studies, the difference between MDR SST and tropical mean SST is a useful predictor; a 1°C increase in this SST difference produces 7.05 ± 1.39 more hurricanes. The hurricane frequency also exhibits strong internal variability that is systematically larger in the model than observations. The seasonal-mean environment is highly correlated among ensemble members and contributes to less than 10% of the ensemble spread in hurricane frequency. The strong internal variability is suggested to originate from weather to intraseasonal variability and nonlinearity. In practice, a 20-member ensemble is sufficient to capture the SST-forced variability.