Five-Year Variability of Precipitation in the municipality of Serra Branca - Paraíba, Brazil

The aim of this work is to determine the variability of precipitation in the area of the sub-basin of the South Curve up to the hydrological station Korvingrad. Data from the synoptic stations Leskovac, Vranje and Kuršumlija for a period of 30 years (1991-2020) were used. The mean relative variability of monthly, seasonal and annual precipitation and their ten-year values were used to compare the results of all synoptic stations in the sub-basin. The results showed that the highest mean variability of precipitation in the studied period was recorded at the Vranje synoptic station (22.4%) and the lowest value at the station in Leskovac (18.4%). The comparison of ten-year values showed that the lowest values of mean relative variability of annual precipitation in the period 2001-2010 were recorded at all synoptic stations. The study showed that the extreme values of mean relative variability of precipitation occurred earlier or later during the second and third ten-year periods compared to the first ten-year period. The study showed that the values of mean relative variability of monthly precipitation were lowest in months with high precipitation.

Possible link between decadal variability in precipitation in the South China Sea and the North Atlantic Oscillation during the 20th century: A perspective from coral geochemical records

Sensitivity of the Terrestrial Ecosystem to Precipitation and Temperature Variability over China

ABSTRACTSatellite observations of precipitation have greatly improved our understanding of its temporal and spatial distribution. In view of the high spatiotemporal heterogeneity and severely skewed distribution characteristics of precipitation, it is necessary and of considerable application value to understand the ability of satellite-derived precipitation products (SPPs) to characterize the variations of precipitation in the time and space dimensions separately. However, to date, research concerning this is scarce. In this study, we explore the ability of 13 SPPs to characterize the temporal and spatial variations of precipitation based on observations from more than 2400 meteorological stations in Chinese mainland from 2001 to 2018. The results show that (1) SPPs tend to perform better in identifying the temporal than the spatial variation of precipitation. Most SPPs can reliably monitor the temporal and spatial variation of monthly and seasonal precipitation in Chinese mainland, although the identification of the spatial variation of daily precipitation involves larger uncertainty; (2) CMORPH-B, IMERG-F, 3B42, and MSWEP generally had better performance in identifying the temporal and spatial variations of precipitation, while PERSIANN and GSMaP-N performed poorly. However, no single SPP outperformed others in all scenarios; (3) with respect to monitoring the temporal variation of daily precipitation, SPPs performed better in southern China than in the north, with three-quarters and half of median KGE values above 0.5 In comparison, no significant spatial difference was observed in their ability to monitor the spatial variation of daily precipitation; and (4) SPPs had large uncertainties in capturing the temporal and spatial variations of precipitation in winter, while they performed best in identifying the temporal and spatial variations of daily precipitation in summer. The results of this paper provide an important reference for data users needing to select suitable SPPs and for satellite developers desiring to further improve data quality.

The abundance of important providers of ecosystem services such as wild bees likely increases with landscape heterogeneity, but may also fluctuate across the flowering season following varying weather conditions. In the present study, we investigated the combined effect of landscape heterogeneity and intra-annual variability in temperature and precipitation on the spatial and temporal stability of wild bee abundance. We used bee monitoring data from six 4 km × 4 km sites in central Germany and 16 local communities per site. The data were collected six times per year from 2010 to 2013. Following a multimodel inference approach, we identified the importance of landscape heterogeneity, weather variability and their interaction to the stability of wild bee abundance. We found that the stability of wild bee abundance increased with landscape heterogeneity, but decreased with increasing intra-annual variability in both temperature and precipitation. However, our key finding was a buffering mechanism enabling high abundance stability in heterogeneous landscapes even under highly variable temperature conditions. Interestingly, the same mechanism did not apply for high variability in precipitation. Our findings suggest that increasing landscape heterogeneity is beneficial for protecting wild bees against the projected increase in temperature variability until the end of the twenty first century, although we cannot make inferences for extreme events such as heatwaves. Nevertheless, our results equally highlight that landscape heterogeneity should not be treated as a one-size-fits-all solution and the need remains for developing alternative strategies to mitigate the effect of increasing variability in precipitation.

Long-term changes in climate variability are an important aspect of the climate change with various impacts on society and environment. In contrast to numerous studies which evaluated projected changes in mean values and extremes of precipitation amount, intensity and/or frequency, studies on changes in precipitation variability have been relatively scarce. To understand whether and how the precipitation variability will change in the future, projections of climate models are utilized. However, accurate simulation of this precipitation characteristic by current climate models is pivotal.In our study we analyze outputs from 13 CMIP6 GCMs across the North Atlantic–European region focusing on winter and summer seasons separately. We classify days with a total precipitation amount exceeding 1 mm as wet days, while the remaining days are considered as dry days. Precipitation probability denote the mean probability of a wet day, and precipitation variability is represented by the tendency to cluster wet/dry days into sequences. To quantify this, we use the persistence parameter defined as the 1-lag autocorrelation of a discrete two-state Markov chain.Firstly, we evaluate whether precipitation variability is simulated correctly over the historical period (1980–2010) by comparing model outputs against the ERA5 reanalysis. Subsequently, we analyse projected changes in the future period (2070–2100) using simulations forced by two Shared Socio-economic Pathways (SSP585 and SSP245). This allows for a comparison of possible future climate changes under different climate policies.We identify biases common to all models, notably an overestimated precipitation probability across much of Europe in winter, while its underestimation in summer, and a general tendency of models toward higher autocorrelation of wet/dry days. Projected changes in precipitation characteristics are more pronounced for the more pessimistic SSP585 scenario. We find that the changes in precipitation variability are independent on the changes in precipitation probability. Our findings also indicate that the model biases and simulated changes in precipitation probability and variability can be linked to the biases and changes in synoptic-scale atmospheric circulation.   

Long-term changes in climate variability represent an important aspect of climate change, with various impacts on society and environment. In this study, we analyze outputs from 13 CMIP6 global climate models (GCMs) across the North Atlantic–European domain, focusing on their simulations of precipitation probability and short-term variability in both historical and future climates. Precipitation probability denotes the probability of a wet day (> 1 mm), and precipitation variability reflects the tendency to cluster wet days into sequences. By comparing against the ERA5 reanalysis, we found that the GCMs tend to overestimate precipitation probability across Europe in winter, whereas in summer, they have a tendency to underestimate it around 50°N. Precipitation variability is, on average, underestimated by the GCMs in summer, while overestimated in several regions in winter. Projections for the end of the twenty-first century indicate significant changes in both precipitation probability and variability which are more pronounced under the more pessimistic emission scenario compared to the moderate one. We found that the changes in probability and variability are mutually independent: the former being more latitudinal-dependent while the latter differs between the west and east. After identifying atmospheric circulation conducive and non-conducive to precipitation occurrence, we found that GCMs overestimating the frequency of conducive circulation tend to overestimate precipitation probability, and vice versa. Furthermore, increased precipitation variability is associated with higher circulation variability. Finally, our analysis reveals that projected changes in precipitation probability and variability are often linked to projected changes in atmospheric circulation, especially in winter.

The National Center for Atmospheric Research (NCAR) Community Climate Model, version 3.6 (CCM3) simulation of tropical intraseasonal variability in zonal winds and precipitation can be improved by implementing the microphysics of cloud with relaxed Arakawa–Schubert (McRAS) convection scheme of Sud and Walker. The default CCM3 convection scheme of Zhang and McFarlane produces intraseasonal variability in both zonal winds and precipitation that is much lower than is observed. The convection scheme of Hack produces high tropical intraseasonal zonal wind variability but no coherent convective variability at intraseasonal timescales and low wavenumbers. The McRAS convection scheme produces realistic variability in tropical intraseasonal zonal winds and improved intraseasonal variability in tropical precipitation, although the variability in precipitation is somewhat less than is observed. Intraseasonal variability in CCM3 with the McRAS scheme is highly sensitive to the parameterization of convective precipitation evaporation in unsaturated environmental air and unsaturated downdrafts. Removing these effects greatly reduces intraseasonal variability in the model. Convective evaporation processes in McRAS affect intraseasonal variability mainly through their time-mean effects and not through their variations. Convective rain evaporation and unsaturated downdrafts improve the modeled specific humidity and temperature climates of the Tropics and increase convection on the equator. Intraseasonal variability in CCM3 with McRAS is not improved by increasing the boundary layer relative humidity threshold for initiation of convection, contrary to the results of Wang and Schlesinger. In fact, intraseasonal variability is reduced for higher thresholds. The largest intraseasonal moisture variations during a model Madden–Julian oscillation life cycle occur above the boundary layer, and humidity variations within the boundary layer are small.

Studying germination in the native and non-native range of a species can provide unique insights into processes of range expansion and adaptation; however, traits related to germination have rarely been compared between native and nonnative populations.In a series of common garden experiments, we explored whether differences in the seasonality of precipitation, specifically, summer drought vs summer rain, and the amount and variation of annual and seasonal precipitation affect the germination responses of populations of an annual ruderal plant, Centaurea solstitialis, from its native range and from two non-native regions with different climates.We found that seeds from all native populations, irrespective of the precipitation seasonality of the region in which they occurred, and non-native populations from regions with dry summers displayed similarly high germination proportions and rates.In contrast, genotypes from the non-native region with predominantly summer rain exhibited much lower germination fractions and rates.Also, percent germination was strongly correlated with variation in precipitation in winter, the season that follows germination for C. solstitialis.Specifically, germination was lower for native and non-native populations experiencing greater variation in winter precipitation.This correlation, however, was greatly influenced by the non-native region with summer rain, which also exhibited the greatest variation in winter precipitation among studied regions.These results suggest that rather than general climatic patterns, the degree of risk experienced at early developmental stages could exert an important control over the germination strategy of C. solstitialis populations in both native and non-native ranges.Also, these findings reveal a largely unique germination response in C. solstitialis genotypes growing in the non-native region with summer rain and high variation in winter precipitation.Our work raises the possibility that rapid adaptive changes in germination strategies may contribute to the success of globally distributed invaders.

As part of global climate change, variation in precipitation in arid ecosystems is leading to plant adaptation in water-use strategies; significant interspecific differences in response will change the plant composition of desert communities. This integrated study on the ecophysiological and individual morphological scale investigated the response, acclimation and adaptation of two desert shrubs, with different water-use strategies, to variations in water conditions. The experiments were carried out on two native dominant desert shrubs, Tamarix ramosissima and Haloxylon ammodendron, under three precipitation treatments (natural, double and no precipitation, respectively), in their original habitats on the southern periphery of Gurbantonggut Desert, Central Asia, during the growing season in 2005. Changes in photosynthesis, transpiration, leaf water potential, water-use efficiency, above-ground biomass accumulation and root distribution of the two species were examined and compared under the contrasting precipitation treatments. There were significant interspecific differences in water-use strategy and maintenance of photosynthesis under variation in precipitation. For the phreatophyte T. ramosissima, physiological activity and biomass accumulation rely on the stable groundwater, which shields it from fluctuation in the water status of the upper soil layers caused by precipitation. For the non-phreatophyte H. ammodendron, efficient morphological adjustment, combined with strong stomatal control, contributes to its acclimation to variation in precipitation. On account of its positive responses to increased precipitation, H. ammodendron is predicted to succeed in interspecific competition in a future, moister habitat.

<p>The South Asian summer monsoon (SASM) system is one of the most energetic regional monsoon systems. Its onset and demise timings determine the propagation, duration, and magnitude of precipitation through thermodynamic and dynamic processes in the SASM-prevailing areas. Particularly, anomalous onsets and demises of the SASM could generate a large anomaly in precipitation and serious water-related disasters over the SASM-prevailing areas.</p><p>The South-Central Tibetan Plateau (SCTP), known as the “Asian water tower”, is the origin of several major Asian rivers, including the Yellow River, Yangtze River, Brahmaputra River, Mekong River, and the Indus River, providing a huge amount of freshwater for ecosystems and billions of people in Asia. It is widely known that the SCTP is controlled by the SASM system in summer, accounting for approximately 60% of annual precipitation, but with significant spatiotemporal heterogeneity due to the complex topographic and geographic conditions. Presently, most studies have focused on the effects and physical causes of the linear trend of SASM onset over the SCTP. However, little attention has been paid to the question as to how both anomalous onset and anomalous demise of the SASM influence the interannual precipitation variation in this region. In particular, the spatial manifestation of thermodynamic and dynamic mechanisms for the interannual precipitation variation is largely unknown. Adequate knowledge about these mechanisms is critical for sustainable freshwater management and water disasters control in this region and surrounding areas.</p><p>These call a detailed study to investigate the influences of the early and late onset (demise) of the SASM system on the interannual variations in precipitation and their underlying mechanisms over the SCTP. In this study, we mainly clarify the following key questions: (1) How do the onset and demise of the SASM control the interannual variations in precipitation over the SCTP? (2) Is there an asymmetric effect of the SASM on SCTP precipitation between its onset and demise, and between its early and late onset (demise)? and (3) What are the underlying mechanisms that are responsible for the variations in interannual precipitation? The results would help improve our understanding of the SASM-precipitation relationship over the SCTP and alleviation of water-related disasters in the region.</p>

Long-term variabilities in daily precipitation and temperature are critical for assessing the impacts of climate change on ecosystems. We characterized intra- and interannual variabilities in daily precipitation and temperature obtained from 1960 to 2015 at 78 meteorological stations on the Qinghai-Tibetan Plateau. The results show that 1) The intra-annual variability of daily precipitation increases for 55 meteorological stations with a rate of 0.08 mm per decade. In contrast, the intra-annual variability markedly decreases for daily mean, daytime mean, and nighttime mean temperatures with a rate of 0.09, 0.07, and 0.12 °C per decade, respectively at 90% or more of stations. 2) Variabilities of daily precipitation and temperatures are quite sensitive to high altitudes (> 3500 m). The intra- and interannual variabilities of daily precipitation significantly decrease at 1.0 and 0.07 mm per 1000 m, respectively. However, variations of high altitudes increase the intra- and interannual variabilities of daily mean temperature at 1.0 °C and 0.2 °C per 1000 m. Moreover, the interannual variability of nighttime mean temperature varies at 0.3 °C per 1000 m, the fastest rate among three temperature indices. 3) A larger mean annual precipitation is accompanied by a higher intra- and interannual variability of daily precipitation on the Qinghai-Tibetan Plateau; however, a higher mean annual temperature leads to lower variabilities of daily temperatures. This study illustrates that long-term climatic variability is understudied in alpine ecosystems characterized by high climatic sensitivity. Precipitation and temperature variabilities should be characterized to improve predictions of vulnerable ecosystems responding to climate change.

Using 92-year precipitation data from 400 rain gauge stations located in 48 states throughout the continental United States, the change in precipitation in space and time was investigated. The variability in precipitation was investigated using an entropy-based approach. The Mann-Kendall, Spearman’s rho, and Sen slope tests were applied to assess the existence of a trend in precipitation. Analysis showed that annual precipitation exhibited lower temporal variability than did its constituent seasonal series. The fall precipitation had the highest variability, and the spring precipitation the lowest. Not many stations exhibited trends, and they are concentrated in limited areas of the United States. The greatest part of those exhibiting statistically significant trends showed increasing trends both in precipitation and rainy days. Only in a few cases negative trends were found. Finally, analysis showed that no relationship can be established between trend and variability in precipitation.

Northwestern China has one of the most complex climates due to the complex terrain and complex climate change in China. The environment there is sensitive to the regional climate change, and is also very vulnerable to the global climate change. The present study examines the spatial and temporal variability and trends of precipitation during 1959–2008 in Northwestern China. The methods used include the climate trends coefficient and climate trends. The variability of precipitation is regionally different. It is significantly increasing trends of precipitation in western and middle, however decreasing trends in eastern in northwestern China. The monthly trends of precipitation is different to seasonal precipitation and annual precipitation. However the spring, the summer and the fall trends of precipitation are accordant to trends of annual precipitation.

Decreasing Precipitation Variability Does Not Elicit Major Aboveground Biomass or Plant Diversity Responses in a Mesic Rangeland