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Many studies have found extreme temperature can increase the risk of mortality. However, it is not clear whether extreme diurnal temperature range (DTR) is associated with daily disease-specific mortality, and how season might modify any association. To better understand the acute effect of DTR on mortality and identify whether season is a modifier of the DTR effect. The distributed lag nonlinear model (DLNM) was applied to assess the non-linear and delayed effects of DTR on deaths (non-accidental mortality (NAD), cardiovascular disease (CVD), respiratory disease (RD) and cerebrovascular disease (CBD)) in the full year, the cold season and the warm season. A non-linear relationship was consistently found between extreme DTR and mortality. Immediate effects of extreme low DTR on all types of mortality were stronger than those of extreme high DTR in the full year. The cumulative effects of extreme DTRs increased with the increment of lag days for all types of mortality in cold season, and they were greater for extreme high DTRs than those of extreme low DTRs. In hot season, the cumulative effects for extreme low DTRs increased with the increment of lag days, but for extreme high DTR they reached maxima at a lag of 13 days for all types of mortality except for CBD(at lag6 days), and then decreased. Our findings suggest that extreme DTR is an independent risk factor of daily mortality, and season is a modifier of the association of DTR with daily mortality.

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data.

Ectotherms, such as insects, experience non-constant temperatures in nature. Daily mean temperatures can be derived from the daily maximum and minimum temperatures. However, the converse is not true and environments with the same mean temperature can exhibit very different diurnal temperate ranges. Here we apply a degree-day model for development of the grape berry moth (Paralobesia viteana, a significant vineyard pest in the northeastern USA) to investigate how different diurnal temperature range conditions can influence degree-day accumulation and, hence, insect life history. We first consider changes in diurnal temperature range independent of changes in mean temperatures. We then investigate grape berry moth life history under potential climate change conditions, increasing mean temperature via variable patterns of change to diurnal temperature range. We predict that diurnal temperature range change can substantially alter insect life history. Altering diurnal temperature range independent of the mean temperature can affect development rate and voltinism, with the magnitude of the effects dependent on whether changes occur to the daily minimum temperature (Tmin), daily maximum temperature (Tmax), or both. Allowing for an increase in mean temperature produces more marked effects on life history but, again, the patterns and magnitude depend on the nature of the change to diurnal temperature range together with the starting conditions in the local environment. The study highlights the importance of characterizing the influence of diurnal temperature range in addition to mean temperature alone.

Previous studies have documented the associations between short-term diurnal temperature range (DTR) exposure and cardiovascular disease (CVD) via time-series analyses. However, the long-term impacts of DTR through a population-based prospective cohort have not been elucidated thoroughly. This study aimed to quantify the longitudinal association of DTR exposure with all-cause mortality and CVD in a nationwide prospective cohort and, by extension, project future DTR changes across China under climate change. We included 22,702 adults (median age 56.1 years, 53.7% women) free of CVD at baseline from a nationwide cross-sectional study in China during 2012–2015, and examined three health outcomes during a follow-up survey in 2018–2019. We estimated the chronic DTR exposure as baseline annual mean daily maximum minus minimum temperature. The Cox proportional hazards regression was adopted to assess the multivariable-adjusted hazard ratio and its corresponding 95% confidence interval (95% CI). We employed 31 downscaled global climate models under two shared socioeconomic pathways for future projection. During the median follow-up period of ~5 years, 1096 subjects died due to all causes while 993 and 597 individuals developed fatal or nonfatal CVD and fatal or nonfatal stroke, respectively. The cumulative incidence rates of all-cause mortality, CVD, and stroke were 10.49, 9.45, and 5.64 per 1000 person-years, respectively. In the fully adjusted models, the risks for all-cause mortality, CVD, and stroke would increase by 13% (95% CI: 8–18%), 12% (95% CI: 7–18%), and 9% (95% CI: 2–16%) per 1 °C increment in DTR, respectively. Moreover, linear positive associations for the concentration–response curves between DTR and mortality and CVD were observed. We also found significantly greater DTR-related mortality risks among rural residents than their urban counterparts. The DTR changes featured a dipole pattern across China under a warming climate. The southern (northern) China would experience increased (decreased) DTR exposure by the end of 21st century. The present study indicates that chronic DTR exposure can exert long-term impacts on mortality and CVD risks, which may inform future public health policies on DTR-related susceptible population and regions.

Climate change is implicated in the alteration of the ranges of species worldwide. Such shifts in species distributions may introduce parasites/pathogens, hosts, and vectors associated with disease to new areas. The parasite Angiostrongylus ( = Parastrongylus) cantonensis is an invasive species that causes eosinophilic meningitis in humans and neurological abnormalities in domestic/wild animals. Although native to southeastern Asia, A. cantonensis has now been reported from more than 30 countries worldwide. Given the health risks, it is important to describe areas with potentially favorable climate for the establishment of A. cantonensis, as well as areas where this pathogen might become established in the future. We used the program Maxent to develop an ecological niche model for A. cantonensis based on 86 localities obtained from published literature. We then modeled areas of potential A. cantonensis distribution as well as areas projected to have suitable climatic conditions under four Representative Concentration Pathways (RCP) scenarios by the 2050s and the 2070s. The best model contained three bioclimatic variables: mean diurnal temperature range, minimum temperature of coldest month and precipitation of warmest quarter. Potentially suitable habitat for A. cantonensis was located worldwide in tropical and subtropical regions. Under all climate change RCP scenarios, the center of the projected distribution shifted away from the equator at a rate of 68-152 km per decade. However, the extent of areas with highly suitable habitat (>50%) declined by 10.66-15.66% by the 2050s and 13.11-16.11% by the 2070s. These results conflict with previous studies, which have generally found that the prevalence of tropical pathogens will increase during the 21st century. Moreover, it is likely that A. cantonensis will continue to expand its current range in the near future due to introductions and host expansion, whereas climate change will reduce the total geographic area of most suitable climatic conditions during the coming decades.

One of the most significant signals in the thermometer‐observed temperature record since 1900 is the decrease in the diurnal temperature range over land, largely due to rising of the minimum temperatures. Generally, climate models have not well replicated this change in diurnal temperature range. Thus, the cause for night‐time warming in the observed temperatures has been attributed to a variety of external causes. We take an alternative approach to examine the role that the internal dynamics of the stable nocturnal boundary layer (SNBL) may play in affecting the response and sensitivity of minimum temperatures to added downward longwave forcing. As indicated by previous nonlinear analyses of a truncated two‐layer equation system, the SNBL can be very sensitive to changes in greenhouse gas forcing, surface roughness, heat capacity, and wind speed. A new single‐column model growing out of these nonlinear studies is used to examine the SNBL. Specifically, budget analyses of the model are provided that evaluate the response of the boundary layer to forcing and sensitivity to mixing formulations. Based on these model analyses, it is likely that part of the observed long‐term increase in minimum temperature is reflecting a redistribution of heat by changes in turbulence and not by an accumulation of heat in the boundary layer. Because of the sensitivity of the shelter level temperature to parameters and forcing, especially to uncertain turbulence parameterization in the SNBL, there should be caution about the use of minimum temperatures as a diagnostic global warming metric in either observations or models. Key Points Nonlinear dynamics in the stable boundary layer can amplify radiative forcing Change in the diurnal temperature trend may be due boundary layer dynamics Temperature response in the stable BL to radiative forcing is a function of height

The space-time pattern and environmental drivers (land cover, climate) of bovine anaplasmosis in the Midwestern state of Kansas was retrospectively evaluated using Bayesian hierarchical spatio-temporal models and publicly available, remotely-sensed environmental covariate information. Cases of bovine anaplasmosis positively diagnosed at Kansas State Veterinary Diagnostic Laboratory (n = 478) between years 2005-2013 were used to construct the models, which included random effects for space, time and space-time interaction effects with defined priors, and fixed-effect covariates selected a priori using an univariate screening procedure. The Bayesian posterior median and 95% credible intervals for the space-time interaction term in the best-fitting covariate model indicated a steady progression of bovine anaplasmosis over time and geographic area in the state. Posterior median estimates and 95% credible intervals derived for covariates in the final covariate model indicated land surface temperature (minimum), relative humidity and diurnal temperature range to be important risk factors for bovine anaplasmosis in the study. The model performance measured using the Area Under the Curve (AUC) value indicated a good performance for the covariate model (> 0.7). The relevance of climatological factors for bovine anaplasmosis is discussed.

The growth and development of cotton are closely related to climatic variables such as temperature and solar radiation. Adjusting planting density is one of the most effective measures for maximizing cotton yield under certain climatic conditions. The objectives of this study were (1) to determine the optimum planting density and the corresponding leaf area index (LAI) and yield under the climatic conditions of Henan Province, China, and (2) to learn how climatic conditions influence cotton growth, yield, and yield components. A three-year (2013-2015) field experiment was conducted in Anyang, Henan Province, using cultivar SCRC28 across six planting density treatments: 15,000, 33,000, 51,000, 69,000, 87,000, and 105,000 plants ha-1. The data showed that the yield attributes, including seed cotton yield, lint yield, dry matter accumulation, and the LAI, increased as planting density increased. Consequently, the treatment of the maximum density with 105,000 plants ha-1 was the highest-yielding over three years, with the LAIs averaged across the three years being 0.37 at the bud stage, 2.36 at the flower and boll-forming stage, and 1.37 at the boll-opening stage. Furthermore, the correlation between the cotton yield attributes and meteorological conditions indicated that light interception (LI) and the diurnal temperature range were the climatic factors that most strongly influenced cotton seed yield. Moreover, the influence of the number of growing degree days (GDD) on cotton was different at different growth stages. These observations will be useful for determining best management practices for cotton production under the climatic conditions of Henan Province, China.

Bluetongue virus (BTV) is transmitted by Culicoides biting midges and causes an infectious, non-contagious disease of ruminants. It has been rapidly emerging in southern Europe since 1998. In mainland Portugal, strains of BTV belonging to three serotypes have been detected: BTV-10 (1956-1960), BTV-4 (2004-2006 and 2013) and BTV-1 (2007-2012). This paper describes the design, implementation and results of the Entomological Surveillance Programme covering mainland Portugal, between 2005 and 2010, including 5,650 caches. Culicoides imicola Kieffer was mostly found in central and southern regions of Portugal, although it was sporadically detected in northern latitudes. Its peak activity occurred in the autumn and it was active during the winter months in limited areas of the country. Obsoletus group was present at the highest densities in the north although they were found throughout the country in substantial numbers. Culicoides activity occurred all year round but peaked in the spring. A generalized linear mixed model was developed for the analysis of the environmental factors associated with activity of the species of Culicoides suspected vectors of BTV in the country. For C. imicola Kieffer, the most important variables were month, diurnal temperature range (DTR), the number of frost days (FRS) and median monthly temperature (TMP). For the Obsoletus group, the most important factors were month, diurnal temperature range (DTR), and linear and quadratic terms for median monthly temperature (TMP). The results reported can improve our understanding of climatic factors in Culicoides activity influencing their distribution and seasonal pattern.

This paper describes a global, daily sea surface temperature (SST) analysis based on satellite microwave and infrared measurements. The SST analysis includes a diurnal correction method to estimate foundation SST (SST free from diurnal variability) using satellite sea surface wind and solar radiation data, frequency splitting to reproduce intra-seasonal variability and a quality control procedure repeated twice to avoid operation errors. An optimal interpolation method designed for foundation SST is applied to blend the microwave and infrared satellite measurements. Although in situ SST measurements are not used for bias correction adjustments in the analysis, the output product, with a spatial grid size of 0.1°, has an accuracy of 0.48 ∘ C and 0.46 ∘ C compared to the in situ foundation SST measurements derived by drifting buoys and Argo floats, respectively. The same quality against the two types of in situ foundation SST (drifters and Argo) suggests that the two definitions of foundation SST proposed by past studies can provide same-quality information about the sea surface state underlying the diurnal thermocline.