Coupled Interannual Variability of Wind and Sea Surface Temperature in the Caribbean Sea and the Gulf of Mexico

This work describes dominant patterns of coupled interannual variability of the 10-m wind and sea surface temperature in the Caribbean Sea and the Gulf of Mexico (CS&GM) during the period 1982-2016. Using a canonical correlation analysis (CCA) between the monthly mean anomalies of these fields, four coupled variability modes are identified: the dipole (March-April), transition (May-June), interocean (July-October), and meridional-wind (November-February) modes. Results show that El Nino-Southern Oscillation (ENSO) influences almost all the CS&GM coupled modes, except the transition mode, and that the North Atlantic Oscillation (NAO) in February has a strong negative correlation with the dipole and transition modes. The antisymmetric relationships found between the dipole mode and the NAO and ENSO indices confirm previous evidence about the competing remote forcings of both teleconnection patterns on the tropical North Atlantic variability. Precipitation in the CS and adjacent oceanic and land areas is sensitive to the wind-SST coupled variability modes from June to October. These modes seem to be strongly related to the interannual variability of the midsummer drought and the meridional migration of the intertropical convergence zone in the eastern Pacific. These findings may eventually lead to improving seasonal predictability in the CS&GM and surrounding land areas.Programa Nacional de Posgrados de Calidad of the Consejo Nacional de Ciencia y Tecnologia of Mexico; CONACYT-SENER-Hidrocarburos Project [201441]6 month embargo; published online: 20 June 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

The Relationship of the North American Monsoon to Tropical and North Pacific Sea Surface Temperatures as Revealed by Observational Analyses

The North American monsoon is a seasonal shift of upper- and low-level pressure and wind patterns that brings summertime moisture into the southwest United States and ends the late spring wet period in the Great Plains. The interannual variability of the North American monsoon is examined using the NCEP–NCAR reanalysis (1948–98). The diurnal and seasonal evolution of 500-mb geopotential height, integrated moisture flux, and integrated moisture flux convergence are constructed using a 5-day running mean for the months May through September. All of the years are used to calculate an average daily Z score that removes the diurnal, seasonal, and intraseasonal variability. The 30-day average Z score centered about the date is correlated with Pacific sea surface temperature anomaly (SSTA) indices associated with the El Niño–Southern Oscillation (ENSO) and the North Pacific oscillation (NPO). These indices are Niño-3, a North Pacific index, and a Pacific index that combines the previous two. Regional time-evolving precipitation indices for the Southwest and Great Plains, which consider the total number of wet or dry stations in a region, are also correlated with the SSTA indices. The use of nonnormally distributed point source precipitation data is avoided. Teleconnections are computed relative to the climatological evolution of the North American monsoon, rather than to calendar months, thus more accurately accounting for the climatological changes in the large-scal

Enhancing the Structure of the WRF-Hydro Hydrologic Model for Semiarid Environments

In August 2016, the National Weather Service Office of Water Prediction (NWS/OWP) of the National Oceanic and Atmospheric Administration (NOAA) implemented the operational National Water Model (NWM) to simulate and forecast streamflow, soil moisture, and other model states throughout the contiguous United States. Based on the architecture of the WRF-Hydro hydrologic model, the NWM does not currently resolve channel infiltration, an important component of the water balance of the semiarid western United States. Here, we demonstrate the benefit of implementing a conceptual channel infiltration function (from the KINEROS2 semidistributed hydrologic model) into the WRF-Hydro model architecture, configured as NWM v1.1. After calibration, the updated WRF-Hydro model exhibits reduced streamflow errors for the Walnut Gulch Experimental Watershed (WGEW) and the Babocomari River in southeast Arizona. Model calibration was performed using NLDAS-2 atmospheric forcing, available from the NOAA National Centers for Environmental Prediction (NCEP), paired with precipitation forcing from NLDAS-2, NCEP Stage IV, or local gauge precipitation. Including channel infiltration within WRF-Hydro results in a physically realistic hydrologic response in the WGEW, when the model is forced with high-resolution, gauge-based precipitation in lieu of a national product. The value of accounting for channel loss is also demonstrated in the Babocomari basin, where the drainage area is greater and the cumulative effect of channel infiltration is more important. Accounting for channel infiltration loss thus improves the streamflow behavior simulated by the calibrated model and reduces evapotranspiration bias when gauge precipitation is used as forcing. However, calibration also results in increased high soil moisture bias, which is likely due to underlying limitations of the NWM structure and calibration methodology.University Corporation for Atmospheric Science (UCAR) COMET Cooperative Project; NOAA Joint Technology Transfer Initiative (JTTI) Federal Grant [NA17OAR4590183]6 month embargo; published online 22 April 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Credibility of Convection-Permitting Modeling to Improve Seasonal Precipitation Forecasting in the Southwestern United States

Sub-seasonal to seasonal (S2S) forecasts are critical for planning and management decisions in multiple sectors. This study shows results from dynamical downscaling using a regional climate model at a convection-permitting scale driven by boundary conditions from the global reanalysis of the Climate Forecast System Model (CFSR). Convection-permitting modeling (CPM) enhances the representation of regional climate by better resolving the regional forcings and processes, associated with topography and land cover, in response to variability in the large-scale atmospheric circulation. We performed dynamically downscaled simulations with the Weather Research and Forecasting (WRF) model over the Upper and Lower Colorado basin at 12 km and 3 km grid spacing from 2000 to 2010 to investigate the potential of dynamical downscaling to improved the modeled representation of precipitation the Southwestern United States. Employing a convection-permitting nested domain of 3 km resolution significantly reduces the bias in mean (∼2 mm/day) and extreme (∼4 mm/day) summer precipitation when compared to coarser domain of 12 km resolution and coarse resolution CFSR products. The convection-permitting modeling product also better represents eastward propagation of organized convection due to mesoscale convective systems at a sub-daily scale, which largely account for extreme summer rainfall during the North American monsoon. In the cool season both coarse and high-resolution simulations perform well with limited bias of ∼1 mm/day for the mean and ∼2 mm/day for the extreme precipitation. Significant correlation was found (∼0.85 for summer and ∼0.65 for winter) for both coarse and high-resolution model with observed regionally and seasonally averaged precipitation. Our findings suggest that the use of CPM is necessary in a dynamical modeling system for S2S prediction in this region, especially during the warm season when precipitation is mostly convectively driven

A combined approach for comparative exoproteome analysis of Corynebacterium pseudotuberculosis

Background: Bacterial exported proteins represent key components of the host-pathogen interplay. Hence, we sought to implement a combined approach for characterizing the entire exoproteome of the pathogenic bacterium Corynebacterium pseudotuberculosis, the etiological agent of caseous lymphadenitis (CLA) in sheep and goats. Results: An optimized protocol of three-phase partitioning (TPP) was used to obtain the C. pseudotuberculosis exoproteins, and a newly introduced method of data-independent MS acquisition (LC-MSE) was employed for protein identification and label-free quantification. Additionally, the recently developed tool SurfG+ was used for in silico prediction of sub-cellular localization of the identified proteins. In total, 93 different extracellular proteins of C. pseudotuberculosis were identified with high confidence by this strategy; 44 proteins were commonly identified in two different strains, isolated from distinct hosts, then composing a core C. pseudotuberculosis exoproteome. Analysis with the SurfG+ tool showed that more than 75% (70/93) of the identified proteins could be predicted as containing signals for active exportation. Moreover, evidence could be found for probable non-classical export of most of the remaining proteins. Conclusions: Comparative analyses of the exoproteomes of two C. pseudotuberculosis strains, in addition to comparison with other experimentally determined corynebacterial exoproteomes, were helpful to gain novel insights into the contribution of the exported proteins in the virulence of this bacterium. The results presented here compose the most comprehensive coverage of the exoproteome of a corynebacterial species so far

Age-specific diastolic dysfunction improves prediction of symptomatic heart failure by Stage B heart failure

Aims: We investigated whether addition of diastolic dysfunction (DD) and longitudinal strain (LS) to Stage B heart failure (SBHF) criteria (structural or systolic abnormality) improves prediction of symptomatic HF in participants of the SCReening Evaluation of the Evolution of New Heart Failure study, a self-selected population at increased cardiovascular disease risk recruited from members of a health insurance fund in Melbourne and Shepparton, Australia. Both American Society of Echocardiography and European Association of Cardiovascular Imaging (ASE/EACVI) criteria and age-specific Atherosclerosis Risk in Communities (ARIC) study criteria, for SBHF and DD, and ARIC criteria for abnormal LS, were examined. Methods and results: Inclusion criteria were age ≥60 years with one or more of self-reported ischaemic or other heart disease, irregular or rapid heart rhythm, cerebrovascular disease, renal impairment, or treatment for hypertension or diabetes for ≥2 years. Exclusion criteria were known HF, or ejection fraction mild valve abnormality detected on previous echocardiography or other imaging. Echocardiography was performed in 3190 participants who were followed for a median of 3.9 (interquartile range: 3.4, 4.5) years after echocardiography. Symptomatic HF was diagnosed in 139 participants at a median of 3.1 (interquartile range: 2.1, 3.9) years after echocardiography. ARIC structural, systolic, and diastolic abnormalities predicted HF in univariate and multivariable proportional hazards analyses, whereas ASE/EACVI structural and systolic, but not diastolic, abnormalities predicted HF. ARIC and ASE/EACVI SBHF criteria predicted HF with sensitivities of 81% and 55%, specificities of 39% and 76%, and C statistics of 0.60 (95% confidence interval: 0.57, 0.64) and 0.66 (0.61, 0.71), respectively. Adding ARIC DD to SBHF increased sensitivity to 94% with specificity of 24% and C statistic of 0.59 (0.57, 0.61), whereas addition of ASE/EACVI DD to SBHF increased sensitivity to 97% but reduced specificity to 9% and the C statistic to 0.52 (0.50, 0.54, P < 0.0001). Addition of LS to ARIC or ASE/EACVI SBHF criteria had minimal impact on prediction of HF. Conclusions: Age-specific ARIC DD criteria, but not ASE/EACVI DD criteria, predicted symptomatic HF, and addition of age-specific ARIC DD criteria to ARIC SBHF criteria improved prediction of symptomatic HF in asymptomatic individuals with cardiovascular disease risk factors. Addition of LS to ASE/EACVI or ARIC SBHF criteria did not improve prediction of symptomatic HF

Sea Ice and Substratum Shape Extensive Kelp Forests in the Canadian Arctic

The coastal zone of the Canadian Arctic represents 10% of the world’s coastline and is one of the most rapidly changing marine regions on the planet. To predict the consequences of these environmental changes, a better understanding of how environmental gradients shape coastal habitat structure in this area is required. We quantified the abundance and diversity of canopy forming seaweeds throughout the nearshore zone (5–15 m) of the Eastern Canadian Arctic using diving surveys and benthic collections at 55 sites distributed over 3,000 km of coastline. Kelp forests were found throughout, covering on average 40.4% (±29.9 SD) of the seafloor across all sites and depths, despite thick sea ice and scarce hard substrata in some areas. Total standing macroalgal biomass ranged from 0 to 32 kg m–2 wet weight and averaged 3.7 kg m–2 (±0.6 SD) across all sites and depths. Kelps were less abundant at depths of 5 m compared to 10 or 15 m and distinct regional assemblages were related to sea ice cover, substratum type, and nutrient availability. The most common community configuration was a mixed assemblage of four species: Agarum clathratum (14.9% benthic cover ± 12.0 SD), Saccharina latissima (13% ± 14.7 SD), Alaria esculenta (5.4% ± 1.2 SD), and Laminaria solidungula (3.7% ± 4.9 SD). A. clathratum dominated northernmost regions and S. latissima and L. solidungula occurred at high abundance in regions with more open water days. In southeastern areas along the coast of northern Labrador, the coastal zone was mainly sea urchin barrens, with little vegetation. We found positive relationships between open water days (days without sea ice) and kelp biomass and seaweed diversity, suggesting kelp biomass could increase, and the species composition of kelp forests could shift, as sea ice diminishes in some areas of the Eastern Canadian Arctic. Our findings demonstrate the high potential productivity of this extensive coastal zone and highlight the need to better understand the ecology of this system and the services it provides.publishedVersio