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Water resources are essential to the ecosystem and social economy in the desert and oasis of the arid Tarim River basin, northwestern China, and expected to be vulnerable to climate change. It has been demonstrated that regional climate models (RCMs) provide more reliable results for a regional impact study of climate change (e.g., on water resources) than general circulation models (GCMs). However, due to their considerable bias it is still necessary to apply bias correction before they are used for water resources research. In this paper, after a sensitivity analysis on input meteorological variables based on the Sobol' method, we compared five precipitation correction methods and three temperature correction methods in downscaling RCM simulations applied over the Kaidu River basin, one of the headwaters of the Tarim River basin. Precipitation correction methods applied include linear scaling (LS), local intensity scaling (LOCI), power transformation (PT), distribution mapping (DM) and quantile mapping (QM), while temperature correction methods are LS, variance scaling (VARI) and DM. The corrected precipitation and temperature were compared to the observed meteorological data, prior to being used as meteorological inputs of a distributed hydrologic model to study their impacts on streamflow. The results show (1) streamflows are sensitive to precipitation, temperature and solar radiation but not to relative humidity and wind speed; (2) raw RCM simulations are heavily biased from observed meteorological data, and its use for streamflow simulations results in large biases from observed streamflow, and all bias correction methods effectively improved these simulations; (3) for precipitation, PT and QM methods performed equally best in correcting the frequency-based indices (e.g., standard deviation, percentile values) while the LOCI method performed best in terms of the time-series-based indices (e.g., Nash–Sutcliffe coefficient, R2); (4) for temperature, all correction methods performed equally well in correcting raw temperature; and (5) for simulated streamflow, precipitation correction methods have more significant influence than temperature correction methods and the performances of streamflow simulations are consistent with those of corrected precipitation; i.e., the PT and QM methods performed equally best in correcting flow duration curve and peak flow while the LOCI method performed best in terms of the time-series-based indices. The case study is for an arid area in China based on a specific RCM and hydrologic model, but the methodology and some results can be applied to other areas and models.

Neutron star surfaces have extremely high magnetic fields. In the atmosphere, the broadening of spectral lines will be substantial from the dense plasma as well as from the magnetic field. One broadening mechanism of note is due to the motional Stark effect (MSE)—an additional electric field that arises from the motion of the atom in the magnetic field. However, approximate formulae are often used to construct atmosphere models, and the MSE is assumed to be the dominant line-broadening mechanism even in ions. Detailed pressure-broadening models in these extreme magnetic fields are now currently being developed. In these more detailed models, it was suggested that the MSE may not be as large as previously predicted. If correct, this hypothesis implies that neutron star line widths might be dominated by pressure broadening rather than by motional Stark broadening. We find that, in the absence of plasma perturbations, for typical magnetic fields (B = 1012 G), mid-Z elements, such as oxygen, have motional Stark widths of order 1 eV for transitions between dipole-allowed transitions from the ground state, though higher temperatures and transitions to higher-energy states are expected to have more broadening. The MSE also breaks down selection rules, giving rise to forbidden transitions, which have much larger widths. When plasma perturbations are included, we find that the plasma perturbation and motional Stark processes are not independent and, as a result, the spectral lines become narrow in a nontrivial way and display harmonics of the ion cyclotron frequency.

Spectral line-shape fitting is an extremely useful tool in determining the gravity of white dwarf stars. This method is so far limited to nonmagnetic white dwarfs largely because the theory of line broadening in high magnetic fields is not as complete as in the nonmagnetic case. Current Stark+Zeeman models treat plasma particles classically and ignore the motion of the nucleus. We develop the formalism for a quantum-mechanical treatment of the perturbing electrons and include the nuclear motion as part of the broadening and explore their relative importance. The conditions we explore are those found in white dwarf and neutron star atmospheres. We find that, contrary to previous studies, the quantized perturbing electrons create more broadening than perturbers on a straight-path trajectory. Additionally, the quantization of the plasma electrons gives rise to resonances away from the line center. The nuclear motion creates an additional electric field, which also leads to an increase in line broadening; however, this effect in neutron star atmospheres is not as large as previously estimated. This suggests that neutron star spectral lines are sensitive to density and that their mass and radius can be obtained from spectral line fitting, which would help constrain the neutron star equation of state.

We present a quantum treatment of atom–electron collisions in magnetic fields, demonstrating the significant importance of including the effect of exchange that arises from two interacting electrons. We find strange behaviors that are not encountered in collisions without a magnetic field. In high magnetic fields, exchange can lead to orders of magnitude enhancements of collision cross sections. Additionally, the elastic collision cross sections that involve the ground state become comparable to those involving excited states, and states with large orbits have the largest contribution to the collisions. We anticipate significant changes to spectral line broadening in neutron star surfaces and atmospheres.

The structure and emergent flux of hydrogen atmosphere white dwarfs depend on the opacity of the Lyα and Lyβ spectral lines. The opacity here is set by the strength and broadening of these lines; the latter is dictated by the far line wing, which is in the “quasi-static” limit of electron broadening, placing it in the incomplete collision regime, and describes the transient parts of electron and ion collisions. These transient stages of the collision form resonances: In the case of ions, they manifest as molecular resonances, while for electrons they are H− resonances, both of which can only be captured quantum-mechanically. Quantum-mechanical calculations have historically preserved only a handful of broadening terms that are most important near the center of the line. However, in the wings of the line, the previously neglected terms that describe the transient stages of the collision need to be included. This requirement arises because, in the line wings, the broadening from the 1s ground state, which is generally assumed to be extremely small compared to the broadening of the upper state, is no longer negligible within a quantum-mechanical model that takes into account exchange interactions. The inclusion of all the transient terms results in asymmetries and extra broadening. The increased broadening of Lyα increases the opacity at the energy where most of the flux leaves the star. The broader Lyα lines also impact the visible flux, raising it by an amount that exceeds previously estimated errors.

This paper describes the design and use of a recursive ensemble Kalman filter (REnKF) to assimilate streamflow data in an operational flow forecasting system of seven catchments in New Zealand. The REnKF iteratively updates past and present model states (soil water, aquifer and surface storages), with lags up to the concentration time of the catchment, to improve model initial conditions and hence flow forecasts. We found the REnKF overcame instabilities in the standard EnKF, which were associated with the natural lag time between upstream catchment wetness and flow at the gauging locations. The forecast system performance was correspondingly improved in terms of Nash–Sutcliffe score, persistence index and bounding of the measured flow by the model ensemble. We present descriptions of filter design parameters and explanations and examples of filter behaviour, as an information source for other groups wishing to assimilate discharge observations for operational forecasting.

In this paper we assess the impact of climate change, at a micro-scale for a selection of four sites in New Zealand and Australia. These sites are representative of the key destination ski regions. In contrast to previous work, our work will for the first time, allow for a direct comparison between these two countries and enable both an estimate of the absolute impacts at a given site, as well as the relative impacts between the two countries. This direct comparison is possible because we have used exactly the same snow model, the same 3 global climate models (GCMs) and the same techniques to calibrate the model for all locations. We consider the changes in natural snow at these locations for the 2030–2049 and 2080–2099 time periods, for one mid-range emissions scenario (A1B). This future scenario is compared to simulations of current, 1980–1999, snow at these locations. We did not consider the snowmaking or economic components of the ski industry vulnerability, only the modelled changes in the natural snow component. At our New Zealand sites, our model indicates that by the 2040s there will be on average between 90 % and 102 % of the current maximum snow depth (on 31 August) and by the 2090s this will be on average reduced to between 46 % and 74 %. In Australia, our models estimates that by the 2040s there will be on average between 57 % and 78 % of the current maximum snow depth and by the 2090s this will be on average further reduced to between 21 % and 29 %. In terms of days with snowdepths equal to or exceeding a ski industry useable levels of 0.30 m, at our lowest elevation, and most sensitive sites, we observe a change from 125 days (current) to 99–126 (2040s) and 52–110 (2090s) in New Zealand. In Australia, a reduction from 94 to 155 days (current) to 81–114 (2040s) and 0–75 (2090s) is observed. In each case the changes are highly depended on the GCM used to drive the climate change scenario. While the absolute changes will have direct impacts at each location, so too will the relative changes with respect to future potential Australia–New Zealand tourism flows, and beyond. Our study provides an approach by which other regions or countries with climate sensitive tourism enterprises could assess the relative impacts and therefore the potential wider ranging ramifications with respect to destination attractiveness.

Purpose To describe trends and explore factors associated with quality of life (QoL) and psychological morbidity and assess breast cancer (BC) health service use over a 12-month period for patients joining the supported self-management (SSM)/patient-initiated follow-up (PIFU) pathway. Methods Participants completed questionnaires at baseline, 3, 6, 9 and 12 months that measured QoL (FACT-B, EQ 5D-5L), self-efficacy (GSE), psychological morbidity (GHQ-12), roles and responsibilities (PRRS) and service use (cost diary). Results 99/110 patients completed all timepoints; 32% (35/110) had received chemotherapy. The chemotherapy group had poorer QoL; FACT-B total score mean differences were 8.53 (95% CI: 3.42 to 13.64), 5.38 (95% CI: 0.17 to 10.58) and 8.00 (95% CI: 2.76 to 13.24) at 6, 9 and 12 months, respectively. The odds of psychological morbidity (GHQ12 > 4) were 5.5-fold greater for those treated with chemotherapy. Financial and caring burdens (PRRS) were worse for this group (mean difference in change at 9 months 3.25 (95% CI: 0.42 to 6.07)). GSE and GHQ-12 scores impacted FACT-B total scores, indicating QoL decline for those with high baseline psychological morbidity. Chemotherapy patients or those with high psychological morbidity or were unable to carry out normal activities had the highest service costs. Over the 12 months, 68.2% participants phoned/emailed breast care nurses, and 53.3% visited a hospital breast clinician. Conclusion The data suggest that chemotherapy patients and/or those with heightened psychological morbidity might benefit from closer monitoring and/or supportive interventions whilst on the SSM/PIFU pathway. Reduced access due to COVID-19 could have affected service use.

To determine whether arthropod richness and abundance for combined taxa, feeding guilds and broad taxonomic groups respond in a globally consistent manner to a range of agricultural land-use and management intensification scenarios. Mixed land-use agricultural landscapes, globally. We performed a series of meta-analyses using arthropod richness and abundance data derived from the published literature. Richness and abundance were compared among land uses that commonly occur in agricultural landscapes and that represent a gradient of increasing intensification. These included land-use comparisons, such as wooded native vegetation compared with improved pasture, and a management comparison, reduced-input cropping compared with conventional cropping. Data were analysed using three different meta-analytical techniques, including a simple vote counting method and a formal fixed-effects/random-effects meta-analysis. Arthropod richness was significantly higher in areas of less intensive land use. The decline in arthropod richness was greater between native vegetation and agricultural land uses than among different agricultural land uses. These patterns were evident for all taxa combined, predators and decomposers, but not herbivorous taxa. Overall, arthropod abundance was greater in native vegetation than in agricultural lands and under reduced-input cropping compared with conventional cropping. Again, this trend was largely mirrored by predators and decomposers, but not herbivores. The greater arthropod richness found in native vegetation relative to agricultural land types indicates that in production landscapes still containing considerable native vegetation, retention of that vegetation may well be the most effective method of conserving arthropod biodiversity. Conversely, in highly intensified agricultural landscapes with little remaining native vegetation, the employment of reduced-input crop management and the provision of relatively low-intensity agricultural land uses, such as pasture, may prove effective in maintaining arthropod diversity, and potentially in promoting functionally important groups such as predators and decomposers.

Locally-active growth factors have been implicated in the pathogenesis of many diseases in which organ fibrosis is a characteristic feature. In the setting of chronic kidney disease (CKD), two such pro-fibrotic factors, transforming growth factor-β (TGF-β) and platelet-derived growth factor (PDGF) have emerged as lead potential targets for intervention. Given the incomplete organ protection afforded by blocking the actions of TGF-β or PDGF individually, we sought to determine whether an agent that inhibited the actions of both may have broader effects in ameliorating the key structural and functional abnormalities of CKD. Accordingly, we studied the effects of a recently described, small molecule anti-fibrotic drug, 3-methoxy-4-propargyloxycinnamoyl anthranilate (FT011, Fibrotech Therapeutics, Australia), which should have these effects. In the in vitro setting, FT011 inhibited both TGF-β1 and PDGF-BB induced collagen production as well as PDGF-BB-mediated mesangial proliferation. Consistent with these in vitro actions, when studied in a robust model of non-diabetic kidney disease, the 5/6 nephrectomised rat, FT011 attenuated the decline in GFR, proteinuria and glomerulosclerosis (p<0.05 for all). Similarly, in the streptozotocin-diabetic Ren-2 rat, a model of advanced diabetic nephropathy, FT011 reduced albuminuria, glomerulosclerosis and tubulointerstitial fibrosis. Together these studies suggest that broadly antagonising growth factor actions, including those of TGF-β1 and PDGF-BB, has the potential to protect the kidney from progressive injury in both the diabetic and non-diabetic settings.