A Climatology of Extreme Convective Storms in Tropical and Subtropical East Asia and Their Ingredients for Heavy Rainfall as Seen by TRMM.

Heavy rainfall is a challenge to forecast due to the variety of rainfall intensities and durations across a wide spectrum of high-impact storm types. In this study, we analyze extreme storms in Tropical and Subtropical East Asia, a moisture-rich environment with complex terrain and oceanic regions. The Tropical Rainfall Measuring Mission's Precipitation Radar is utilized to characterize the frequency and rainfall intensity of four extreme storm types. Extreme storms producing heavy precipitation are categorized into four types: deep convective cores (DCCs), deepwide convective cores (DWCCs), wide convective cores (WCCs), and broad stratiforms regions (BSRs). DCCs and DWCCs occur more frequently and produce stronger rain intensities over land compared to those over ocean. However, WCCs and BSRs occur more frequently over oceans, especially in association with the Meiyu front season and climatological progression in the northern subregions. Although the Convective Cores show higher rain intensities than the BSRs, they show lower volumetric rain rate due to their comparatively smaller horizontal area. An ingredients-based framework is applied to find key similarities across the different heavy rainfall-producing storms near Taiwan using ERA5 reanalysis. The analysis shows that the broader systems (i.e., WCCs and BSRs) are associated with larger in area and longer timescales of vertical moisture flux and low-level wind shear that support the development of the horizontally large, organized storms. Smaller DCCs do not show strong vertical moisture flux on the spatial scales resolved by the reanalysis, suggesting their more local nature and less meso- or synoptic scale support.

Statistical-thermodynamic model for light scattering from eye lens protein mixtures.

We model light-scattering cross sections of concentrated aqueous mixtures of the bovine eye lens proteins γB- and α-crystallin by adapting a statistical-thermodynamic model of mixtures of spheres with short-range attractions. The model reproduces measured static light scattering cross sections, or Rayleigh ratios, of γB-α mixtures from dilute concentrations where light scattering intensity depends on molecular weights and virial coefficients, to realistically high concentration protein mixtures like those of the lens. The model relates γB-γB and γB-α attraction strengths and the γB-α size ratio to the free energy curvatures that set light scattering efficiency in tandem with protein refractive index increments. The model includes (i) hard-sphere α-α interactions, which create short-range order and transparency at high protein concentrations, (ii) short-range attractive plus hard-core γ-γ interactions, which produce intense light scattering and liquid-liquid phase separation in aqueous γ-crystallin solutions, and (iii) short-range attractive plus hard-core γ-α interactions, which strongly influence highly non-additive light scattering and phase separation in concentrated γ-α mixtures. The model reveals a new lens transparency mechanism, that prominent equilibrium composition fluctuations can be perpendicular to the refractive index gradient. The model reproduces the concave-up dependence of the Rayleigh ratio on α/γ composition at high concentrations, its concave-down nature at intermediate concentrations, non-monotonic dependence of light scattering on γ-α attraction strength, and more intricate, temperature-dependent features. We analytically compute the mixed virial series for light scattering efficiency through third order for the sticky-sphere mixture, and find that the full model represents the available light scattering data at concentrations several times those where the second and third mixed virial contributions fail. The model indicates that increased γ-γ attraction can raise γ-α mixture light scattering far more than it does for solutions of γ-crystallin alone, and can produce marked turbidity tens of degrees celsius above liquid-liquid separation.

Computational cardiac electrophysiology: implementing mathematical models of cardiomyocytes to simulate action potentials of the heart.

Mathematical models are now an important tool for studying cardiac electrophysiology and arrhythmias. Utilizing these models to quantify behavior and make predictions requires solving the models computationally using numerical schemes. We discuss different solution methods and other computational considerations for simulating cardiac action potentials in single cells and multicellular preparations.

Q fever diagnosis in domestic ruminants: comparison between complement fixation and commercial enzyme-linked immunosorbent assays.

Q fever is an important zoonotic disease caused by infection with the bacterium Coxiella burnetii. Veterinary diagnostic laboratories, including the Veterinary Laboratories Agency (VLA) in England and Wales, have traditionally relied on the complement fixation test (CFT) for serological diagnosis. However, Q fever has assumed greater significance in recent years following several large human outbreaks linked to exposure to infected ruminants and it is essential that more reliable tests are introduced to detect the presence of C. burnetii infection in animals. The objective of the current study was to evaluate the performance of 3 commercially available enzyme-linked immunosorbent assays (ELISAs) for detection of antibodies to C. burnetii and to compare the findings with the CFT using a sample panel of 548 sera from sheep, goats, and cattle, including animals of known disease status. The statistical analysis using TAGS (test accuracy in the absence of a gold standard) software and receiver operating characteristic techniques demonstrated that the 3 ELISAs all showed improved sensitivity over the CFT. The test based on ovine antigen demonstrated the best overall performance and therefore, the VLA has adopted this test for routine use.

Hurricane intensity and eyewall replacement.

Observations made during the historic 2005 hurricane season document a case of "eyewall replacement." Clouds outside the hurricane eyewall coalesce to form a new eyewall at a greater radius from the storm center, and the old eyewall dies. The winds in the new eyewall are initially weaker than those in the original eyewall, but as the new eyewall contracts, the storm reintensifies. Understanding this replacement mechanism is vital to forecasting variations in hurricane intensity. Processes in the "moat" region between the new and old eyewall have been particularly unclear. Aircraft data now show that the moat becomes dynamically similar to the eye and thus is converted into a region inimical to survival of the inner eyewall. We suggest that targeting aircraft to key parts of the storm to gain crucial input to high-resolution numerical models can lead to improvements in forecasting hurricane intensity.