Search for: All records

The water vapor transport associated with latent heat flux (LE) in the planetary boundary layer (PBL) is critical for the atmospheric hydrological cycle, radiation balance, and cloud formation. The spatiotemporal variability of LE and water vapor mixing ratio (r_v) are poorly understood due to the scale‐dependent and nonlinear atmospheric transport responses to land surface heterogeneity. Here, airborne in situ measurements with the wavelet technique are utilized to investigate scale‐dependent relationships among LE, vertical velocity (w) variance (), andr_vvariance () over a heterogeneous surface during the Chequamegon Heterogeneous Ecosystem Energy‐balance Study Enabled by a High‐density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign. Our findings reveal distinct scale distributions of LE, , and at 100 m height, with a majority scale range of 120 m–4 km in LE, 32 m–2 km in , and 200 m–8 km in . The scales are classified into three scale ranges, the turbulent scale (8–200 m), large‐eddy scale (200 m–2 km), and mesoscale (2–8 km) to evaluate scale‐resolved LE contributed by and . The large‐eddy scale in PBL contributes over 70% of the monthly mean total LE with equal parts (50%) of contributions from and . The monthly temporal variations mainly come from the first two major contributing classified scales in LE, , and . These results confirm the dominant role of the large‐eddy scale in the PBL in the vertical moisture transport from the surface to the PBL, while the mesoscale is shown to contribute an additional ∼20%. This analysis complements published scale‐dependent LE variations, which lack detailed scale‐dependent vertical velocity and moisture information.

 

Abstract The magnitude of water vapor content within the near-storm inflow can either support or deter the storm’s upscale growth and maintenance. However, the heterogeneity of the moisture field near storms remains poorly understood because the operational observation network lacks detail. This observational study illustrates that near-storm inflow water vapor environments are both significantly heterogeneous and different than the far-inflow storm environment. This study also depicts the importance of temporal variation of water vapor mixing ratio (WVMR) to instability during the peak tornadic seasons in the U.S. Southeast and Great Plains regions during the Verification of the Origins of Rotation in Tornadoes Experiment Southeast 2018 (VSE18) campaign and the Targeted Observation by Radar and UAS of Supercells (TORUS) campaign, respectively. VSE18 results suggest that the surface processes control WVMR variation significantly in lower levels, with the highest WVMR mainly located near the surface in inflows in the southeast region. In contrast, TORUS results show more vertically homogeneous WVMR profiles and rather uniform water vapor distribution variation occurring in deep, moist stratified inflows in the Great Plains region. Temporal water vapor variations within 5-min periods could lead to over 1000 J kg −1 CAPE changes in both VSE18 and TORUS, which represent significant potential buoyancy perturbations for storms to intensify or decay. These temporal water vapor and instability evolutions of moving storms remain difficult to capture via radiosondes and fixed in situ or profiling instrumentation, yet may exert a strong impact on storm evolution. This study suggests that improving observations of the variability of near-storm inflow moisture can accurately refine a potential severe weather threat. Significance Statement It has long been recognized that better observations of the planetary boundary layer (PBL) inflow near convective storms are needed to improve severe weather forecasting. The current operational networks essentially do not provide profile measurements of the PBL, except for the sparsely spaced 12-hourly sounding network. More frequent geostationary satellite observations do not provide adequately high vertical resolution in the PBL. This study uses airborne lidar profiler measurements to examine moisture in the inflow region of convective storms in the Great Plains and the southeastern United States during their respective tornadic seasons. Rapid PBL water vapor variations on a ∼5 min time scale can lead to CAPE perturbations exceeding 1000 J kg −1 , representing significant perturbations that could promote storm intensification or decay. Severe thunderstorms may generate high-impact weather phenomena, such as tornadoes, high winds, hail, and heavy rainfall, which have substantial socioeconomic impacts. Ultimately, by contrasting characteristics of the convective storm inflow in the two regions, this study may lead to a more accurate assessment of severe weather threats. 

Vector-borne diseases, such as chikungunya, dengue, malaria, West Nile virus, yellow fever and Zika, pose a major global public health problem worldwide. In this paper we investigate the propagation dynamics of diffusive vector-borne disease models in the whole space, which characterize the spatial expansion of the infected hosts and infected vectors. Due to the lack of monotonicity, the comparison principle cannot be applied directly to this system. We determine the spreading speed and minimal wave speed when the basic reproduction number of the corresponding kinetic system is larger than one. The spreading speed is mainly estimated by the uniform persistence argument and generalized principal eigenvalue. We also show that solutions converge locally uniformly to the positive equilibrium by employing two auxiliary monotone systems. Moreover, it is proven that the spreading speed is the minimal wave speed of travelling wave solutions. In particular, the uniqueness and monotonicity of travelling waves are obtained. When the basic reproduction number of the corresponding kinetic system is not larger than one, it is shown that solutions approach to the disease-free equilibrium uniformly and there is no travelling wave solutions. Finally, numerical simulations are presented to illustrate the analytical results. 

Abstract This observational study documents the consequences of a collision between two converging shallow atmospheric boundaries over the central Great Plains on the evening of 7 June 2015. This study uses data from a profiling airborne Raman lidar (the Compact Raman Lidar, or CRL) and other airborne and ground-based data collected during the Plains Elevated Convection At Night (PECAN) field campaign to investigate the collision between a weak cold front and the outflow from a MCS. The collision between these boundaries led to the lofting of high-CAPE, low-CIN air, resulting in deep convection, as well as an undular bore. Both boundaries behaved as density currents prior to collision. Because the MCS outflow boundary was denser and less deep than the cold-frontal airmass, the bore propagated over the latter. This bore was tracked by the CRL for about three hours as it traveled north over the shallow cold-frontal surface and evolved into a soliton. This case study is unique by using the high temporal and spatial resolution of airborne Raman lidar measurements to describe the thermodynamic structure of interacting boundaries and a resulting bore. 

Recent experimental evidence suggests that spatial heterogeneity plays an important role in within‐host infections caused by different viruses including hepatitis B virus (HBV), hepatitis C virus (HCV), and human immunodeficiency virus (HIV). To examine the spatial effects of viral infections, in this paper we study the asymptotic spreading in a within‐host viral infection model, which describes the spatial expansion speeds of viruses and infected cells within an infected host. We first establish the boundedness of solutions to the Cauchy problem via local ‐estimates and dual arguments. Then the spreading speed is estimated when the basic reproduction number of the corresponding kinetic system is larger than one. More precisely, the upper bounds of the spreading speed are given by constructing suitable upper solutions while the lower bounds of the spreading speed are obtained by introducing an auxiliary equation with nonlocal delay. When the basic reproduction number of the corresponding kinetic system is less than or equal to one, the virus dies out uniformly. Finally, we present some numerical simulations to illustrate our theoretical findings and discuss the biological relevance of these results.

 

Small-scale variations within the low-level outflow and inflow of an MCS can either support or deter the upscale growth and maintenance of the MCS. However, these small-scale variations, in particular in the thermodynamics (temperature and humidity), remain poorly understood, due to a lack of detailed measurements. The compact Raman lidar (CRL) deployed on the University of Wyoming King Air aircraft directly sampled temperature and water vapor profiles at unprecedented vertical and along-track resolutions along the southern margin of a series of mature nocturnal MCSs traveling along a frontal boundary on 1 July 2015 during the Plains Elevated Convection at Night (PECAN) campaign. Here, the capability of the airborne CRL to document interactions between the MCS inflow and outflow currents is illustrated. The CRL reveals the well-defined boundary of a cooler current. This is interpreted as the frontal boundary sharpened by convectively induced cold pools, in particular by the outflow boundary of the downstream MCS. In one CRL transect, the frontal/outflow boundary appeared as a distinct two-layer structure of moisture and aerosols formed by moist stable boundary layer air advected above the boundary. The second transect, one hour later, reveals a single sloping boundary. In both cases, the lofting of the moist stably stratified air over the boundary favors MCS maintenance, through enhanced elevated CAPE and reduced CIN. The CRL data are sufficiently resolved to reveal Kelvin–Helmholtz (KH) billows and the vertical structure of the outflow boundary, which in this case behaved as a density current rather than an undular bore.

 

With lowering costs of sequencing and genetic profiling techniques, genetic drivers can now be detected readily in tumors but current prognostic models for Natural‐killer/T cell lymphoma (NKTCL) have yet to fully leverage on them for prognosticating patients. Here, we used next‐generation sequencing to sequence 260 NKTCL tumors, and trained a genomic prognostic model (GPM) with the genomic mutations and survival data from this retrospective cohort of patients using LASSO Cox regression. The GPM is defined by the mutational status of 13 prognostic genes and is weakly correlated with the risk‐features in International Prognostic Index (IPI), Prognostic Index for Natural‐Killer cell lymphoma (PINK), and PINK‐Epstein–Barr virus (PINK‐E). Cox‐proportional hazard multivariate regression also showed that the new GPM is independent and significant for both progression‐free survival (PFS, HR: 3.73, 95% CI 2.07–6.73;p < .001) and overall survival (OS, HR: 5.23, 95% CI 2.57–10.65;p = .001) with known risk‐features of these indices. When we assign an additional risk‐score to samples, which are mutant for the GPM, the Harrell's C‐indices of GPM‐augmented IPI, PINK, and PINK‐E improved significantly (p < .001, χ²test) for both PFS and OS. Thus, we report on how genomic mutational information could steer toward better prognostication of NKTCL patients.