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Objective To evaluate the relationship between local rainfall and frailty in the elderly. MethodsThe information on 10 424 elderly aged 65 years and above were extracted from four rounds of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) conducted between 2005 and 2014 across China. Frailty index (FI) was used to assess frail status of the elderly; generalized linear mixed model and natural cubic spline function were adopted to explore the association of local rainfall with the prevalence of frailty. Results The baseline prevalence of frailty was 18.6% for all the elderly aged 82.84 ± 11.30 years at baseline survey; at the last follow-up, the frailty prevalence increased to 27.8%. The results of multivariate regression analysis showed that the elderly living in regions with higher annual average local rainfall (highest quartile) had a lower risk of frailty (odds ratio = 0.60, 95% confidence interval: 0.50 – 0.71) compared to those living in regions with lower local rainfall (lowest quartile); while the correlation of local rainfall with prefrailty of the elderly was not significant. Conclusion Local rainfall has a protective effect on the frailty of the elderly and specific concern should be paid when developing relevant healthcare strategies for the elderly in regions with different amount of rainfall.

Abstract Africa is highly vulnerable to climate change but emits a small portion of global greenhouse gases. Additionally, decarbonization might lead to a ‘climate penalty’ whereby reductions in cooling aerosols offset temperature benefits from CO2 reductions for several decades. However, climate change impacts conditions other than temperatures, including precipitation. Using the NASA Goddard Institute for Space Studies climate model, we find that although African emissions cuts have weak impacts on projected African temperatures, they significantly impact rainfall. Whereas business-as-usual increasing emissions lead to substantial drying over tropical Northern Hemisphere Africa during local summer, that drying is essentially eliminated under a sustainable development pathway. The reduction in cooling aerosols is responsible for ~33–90% of the avoided drying in our model, with the remainder largely attributable to reduced absorbing aerosols. African policy choices may therefore greatly reduce regional African summer drying, giving parts of Africa substantial leverage over their own climate and air quality future.

The southeastern Indian Ocean (SEIO) exhibits prominent decadal variability in sea surface salinity (SSS), showing salinity decreases during 1995-2000 and 2005-2011 and increases during 2000-2005 and after 2011. These salinity changes are linked to the Indo-Pacific climate and have impacts on the regional marine environment. Yet, the underlying mechanism has not been firmly established. In this study, decadal SSS variability of the SEIO is successfully simulated by a high-resolution regional ocean model, and the mechanism is explored through a series of sensitivity experiments. The results suggest that freshwater transport of the Indonesian throughflow (ITF) and local precipitation are two major drivers for the SSS decadal variability. They mutually cause most of the variability, with a generally larger contribution of precipitation. Other processes, such as evaporation and advection driven by local winds, play a minor role. Further analysis shows that the decadal precipitation in the SEIO is mainly associated with the decadal variability of Ningaloo Niño. Ocean dynamic processes significantly modify the relationship between SSS and precipitation, greatly shortening their lag time. The changes in both volume transport and salinity of the ITF water can cause large salinity changes in the SEIO region. Although local wind forcing gives rise to considerable changes in evaporation rate and ocean current advection, its overall contribution to decadal SSS variability is small compared to local precipitation and the ITF.

This paper describes the development and testing of a simple local seasonal forecast system of rainfall and hydrological conditions. The primary target group is agricultural extension officers who communicate forecasts to small-scale farmers at local level. Two pilot areas within the Limpopo river basin in South Africa were used, one in the Luvuvhu river basin in Vhembe district and the other in the Letaba river basin in Mopani district. Local rainfall and hydrological forecasts of runoff, soil moisture and evapotranspiration were produced, built on readily available deterministic seasonal meteorological forecasts for large-scale rainfall from CSIR (Council for Scientific and Industrial Research, South Africa), produced from an ensemble of seasonal forecasts using the CCAM (Conformal-Cubic Atmospheric Model) global forecast model. Hydrological forecasts were produced through a “proxy” approach, whereby outputs from the ACRU (Agricultural Catchment Research Unit) agrohydrological model provided expected hydrological responses from observed years that are representative of the rainfall anomalies predicted by the global seasonal forecast. Locally monitored soil moisture augmented the hydrological forecasts. The local seasonal forecast system does not require sophisticated calculations or a complex operational environment and complements coarser scale forecasts disseminated by the provincial departments of agriculture. Results of three rainfall seasons from 2013 to 2016 in the pilot areas showed the proxy approach to have relatively good matches between forecasts and available observations, showing better predictability for below normal rainfall seasons with exception for an extreme monthly rainfall event. The forecasts matched observed conditions best during the strong El Niño phase of ENSO (El Niño Southern Oscillation) for 2015/2016.

Strong earthquakes are a major cause of natural disasters and may also be related to heavy rainfall events. Both phenomena have received considerable attention in seismology and meteorology, two relatively independent disciplines, but we do not yet know whether there is a connection between them. We investigated the characteristics of daily rainfall over seismic areas in China. Our statistical analyses showed that there is a strong correlation between strong earthquakes (Ms ≥ 6.0) and rainfall over the seismic area, with 74.9% of earthquakes in China accompanied by seismic epicenter rainfall and 86.6% by seismic area rainfall. The statistics also showed that the daily precipitation over the seismic area, including the epicenter, was mainly light rain, with only a few instances of torrential or storm rain, with 80% of the rainfall events lasting two or more days. The maximum cumulative precipitation corresponded well with the strong earthquakes occurring over steep terrain, such as the Taiwan central mountains and the eastern Tibetan Plateau. The earthquake area rainfall had a higher frequency than the 30-years climatological average and was dominated by earthquake events in the wet season. The WRF-ARW numerical simulation of seismic local rainfall during the devastating Ms 8.0 Wenchuan earthquake in May 2008 showed that the geothermal heat from the earthquake strengthened the local convergence of moisture and vertical motion near the epicenter and the upward transport of the sensible heat flux, which favored seismic rainfall. The results of this study show that rainfall in the seismic area is closely related to strong earthquakes and can be triggered and enhanced by geothermal heat.

The importance of local climate and biodiversity in tropical forest's ability to provide critical ecosystem services is well documented, whereas the relationship among local climatic factors and biodiversity with soil ecosystem functions largely remain unclear. We investigated the importance of local rainfall regime and indicators of plant (tree, herb, and shrub) diversity (richness and abundance) on soil ecosystem functions in two tropical forest ecosystems of north-east Bangladesh. We considered six soil parameters, i.e. soil water regulation (SWR), soil physical stability (SPS), soil microbial habitat (SMH), soil pH (pH), medium of plant growth (MPG), and soil aggregate stability (SAS) as indicators of soil ecosystem functions. Our study finds four rainfall parameters having significant (p < 0.05) positive effects on soil water regulation, soil physical stability, microbial habitat, soil pH, medium of plant growth, and soil aggregate stability. Tree species abundance had positive effects on SPS (p < 0.001) and MPG (p < 0.05), while tree species richness had negative effects on SMH (p < 0.001) and MPG (p < 0.01). Soil aggregate stability was negatively (p < 0.05) affected by tree species abundance, whereas tree species richness positively (p < 0.0001) affected SAS. We found no significant effects of tree species abundance and richness on pH and SWR. The abundance of herbaceous species had positive impacts on MPG (p

Tropical montane cloud forest may be especially sensitive to climate change. However, our ability to understand effects of climate on montane biodiversity remains limited by the resolution of climate data. We compared 5 years of in situ weather data from cloud forests in northern Peru, regional weather stations, and gridded datasets to examine how climatologies reflect (a) forest microclimate buffering and (b) local rainfall in a sparse data region; we also examined spatiotemporal variability and regional trends. Across a 1,700–3,100 m gradient in which temperature did not covary with relative humidity (RH), in situ data showed interactions between climate and land‐use. Forest humidity buffered warming‐induced evaporative drying across elevations, and inside forest maximum vapour pressure deficit (VPDmax) did not change with elevation, whereas with a 22% reduction in RHmin at stations, VPDmax increased >10‐fold from high to low elevations. Cloud forest dried out on sunny days after 3 days without rain, especially during ENSO‐related drought concurrent with peak solar insolation. Climatologies were twice as precise for temperature as rainfall. Chelsa captured a 3.9°C reduction in maximum temperatures inside forest (MAE 1.6°C, R2 = 0.95) whereas WorldClim reflected drier lapse rates and higher Tmax outside forest. CHIRPS provided the best fit for monthly rainfall (MAE 23 mm, R2 = 48), capturing regional drought but underestimating rainfall >150 mm·month−1. Consistent with stations, CHIRPS showed strong support for regional increases in wet‐season rainfall. Reduced variability and more regular dry seasons were only detected by montane stations, especially south of 6°S, where rainfall seasonality shifted to earlier wet‐season peaks and reduced dry‐season rainfall as part of a transition from the Northern to Central Andes. Our results show that cloud forests may be partly buffered from warming but are likely to become extremely vulnerable under reduced humidity either through forest loss or drought. [ABSTRACT FROM AUTHOR]

The present study examined the influence of the Hydroelectric Power Plant (HPP) of Passo Fundo dam lake on local rainfall pattern. Daily rainfall data were obtained from the National Water Agency for two different periods: prior to the lake filling, 1960-1970 (pre-filling) and later to the lake filling, 1971-1981 (post-filling). Statistical measures (mean, maximum, minimum, standard deviation and coefficient of variation) and the Student’s t-test were applied to both periods regarding the monthly rainfall total. The Student's t-test was also applied to days with cumulative rainfall greater than 1 mm, 10 mm, 20 mm, 30 mm, 50 mm, 80 mm and 100 mm, to the number of dry days and to the monthly largest dry period. The results showed that only days with cumulative rainfall exceeding 50 mm (July), number of dry days in the month (June) and the monthly largest dry period (May and Nov) were influenced due to the formation of the dam lake

The hydroclimatic response of the El Niño‐Southern Oscillation (ENSO) to external radiative forcing remains controversial and difficult to project with confidence for the 21st century. Annually resolved paleoclimatic reconstructions spanning the pre‐ and post‐industrial eras from the Indonesian maritime continent may provide hindcasting and diagnostic targets. Here we report δ18O observations from dendrochronologically dated teak (Tectona grandis L. f.) α‐cellulose samples collected at Muna Island, Sulawesi (5.3°S, 123°E, elevation 10 m), for November‐April growing seasons during the period 1969/70–2004/5. Age‐modeled, annually averaged α‐cellulose δ18O anomalies are significantly correlated with simulated α‐cellulose δ18O at the study site. We show that the correlation is largely explained by the amount effect in local and regional precipitation δ18O. Significant correlation with SST anomalies over the study period suggest that replicated multicentury α‐cellulose records from this archive may be interpreted as ENSO indicators. Plain Language Summary: Does El Niño change when the energy balance of the climate is altered? This study sets the stage for addressing this question by developing an indirect record of El Niño from the oxygen isotopic composition of Indonesian trees growing adjacent to the warm equatorial western Pacific Ocean. The data are consistent with modeling of the record as a function of local precipitation amount, and the pattern of ocean surface temperature changes El Niño events produce. Extension of these records hundreds of years into the past should enable us to detect hypothesized changes in El Niño event occurrence over the recent geological past. Key Points: We developed a modern composite oxygen isotopic record from cross‐dated teak samples from Muna, Sulawesi (5.3°S, 123°E)Observations are consistent with data simulations, and a primary response to rainfall amountSignificantly correlated with ENSO, the data point to future analysis of its forced response and the unforced variation over centuries [ABSTRACT FROM AUTHOR]

The relation between the atmospheric entropy flow field and local rainfall is examined in terms of the theory of dissipative structures. In this paper, the entropy balance equation in a form suitable for describing the entropy budget of the Earth’s atmosphere is derived starting from the Gibbs relation, and, as examples, the entropy flows of the two severe weather events associated with the development of an extratropical cyclone and a tropical storm are calculated, respectively. The results show that negative entropy flow (NEF) has a significant effect on the precipitation intensity and scope with an apparent matching of the NEF’s pattern with the rainfall distribution revealed and, that the diagnosis of NEF is able to provide a good indicator for precipitation forecasting.