scholarly journals Climatic trends of temperatures and precipitation in Brazilian localities

2020 ◽  
Vol 42 ◽  
pp. e44359
Author(s):  
Júlio César Penereiro
Keyword(s):  
Industrial Development ◽  
Global Climate ◽  
Statistical Tests ◽  
Maximum Temperature ◽  
Climate Trends ◽  
Air Temperatures ◽  
Annual Time Series ◽  
Statistical Trends ◽  
Increasing Trends ◽  
Annual Time

In recent decades, scientific and academic researchers around the world have been concerned with the assessment of regional and global climate trends.  Under the hypothesis of the presence of climate change in Brazil, the aim of this work was to verify annual climate trends of maximum and minimum air temperatures and precipitation in 243 localities over all the Brazilian political regions. The data were obtained from National Institute of Meteorology. In this work there were identified and analysed trends in annual time series distributed between in 1961 and 2017. The detections and analyses were performed by the application of the statistical tests of Mann-Kendall and the Pettitt to evaluate the presence of statistical trends. The statistical results and the trend distributions maps show that, from all the studied localities, for maximum temperature indicate increasing trends in 35% of the series, decreasing trends in 1 and no trends in 64%. The minimum temperature showed increasing trends in 30% of the analysed series, decreasing in 8% and no trends in 63%. The precipitation, showed increasing trends in 6% of the studied series, decreasing in 4 and no trends in 91%. The observed climate trends can be related to anthropological activities like urban spraw, industrial development and increasing population density.

scholarly journals Probability Models and Statistical Tests for Extreme Precipitation Based on Generalized Negative Binomial Distributions

Mathematics ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 604 ◽  
Author(s):  
Victor Korolev ◽  
Andrey Gorshenin
Keyword(s):  
Negative Binomial ◽  
Daily Precipitation ◽  
Global Climate ◽  
Statistical Tests ◽  
Real Data ◽  
Total Precipitation ◽  
Climate Trends ◽  
Probability Models ◽  
Precipitation Volume ◽  
Precipitation Total

Mathematical models are proposed for statistical regularities of maximum daily precipitation within a wet period and total precipitation volume per wet period. The proposed models are based on the generalized negative binomial (GNB) distribution of the duration of a wet period. The GNB distribution is a mixed Poisson distribution, the mixing distribution being generalized gamma (GG). The GNB distribution demonstrates excellent fit with real data of durations of wet periods measured in days. By means of limit theorems for statistics constructed from samples with random sizes having the GNB distribution, asymptotic approximations are proposed for the distributions of maximum daily precipitation volume within a wet period and total precipitation volume for a wet period. It is shown that the exponent power parameter in the mixing GG distribution matches slow global climate trends. The bounds for the accuracy of the proposed approximations are presented. Several tests for daily precipitation, total precipitation volume and precipitation intensities to be abnormally extremal are proposed and compared to the traditional PoT-method. The results of the application of this test to real data are presented.

scholarly journals Trends of Changes of Maximum Air Temperature in Ukraine as an Impact Factor on Population Health

2020 ◽  
Keyword(s):  
Population Health ◽  
Air Temperature ◽  
Thermal Regime ◽  
Climate Changes ◽  
System Analysis ◽  
Global Climate ◽  
Maximum Temperature ◽  
Air Temperatures ◽  
Average Maximum ◽  
Maximum Air Temperature

Purpose. The aim of this research is detection of trends of changes (according to fact and scenario data) of extreme air temperature as a component of thermal regime in different regions of Ukraine because of global climate change. Methods. System analysis, statistical methods. Results. Time distribution of maximum air temperature regime characteristics based on results of observations on the stations located in different regions of Ukraine during certain available periods: Uzhgorod (1946-2018), Kharkiv (1936-2005), Оdessа (1894-2005), аnd also according to scenarios of low (RCP2.6), medium (RCP4.5) and high (RCP8.5) levels of greenhouse gases emissions. Meanwhile, air temperature ≥ 25°С was considered high (days with maximum temperature within 25,0-29,9°С are hot), ≥ 30°С was considered very high (days with such temperature are abnormaly hot). Trends of changes of extreme air temperatures were identified as a component of thermal regime in different regions of Ukraine within global climate changes. Dynamics of maximum air temperature and its characteristics in ХХ and beginning of ХХІ centuries were researched. Expected time changes of maximum air temperature and number of days with high temperature during 2021-2050 were analyzed by RCP2.6, RCP4.5 and RCP8.5 scenarios. There were identified the highest day air temperatures possible once in a century and also possibility of maximum day temperature more than 30°С by RCP4.5 scenario. Well-timed prediction of climate changes will help evaluate their impact on human and natural systems which will be useful for development and taking preventive measures towards minimization of negative influence of such changes. Conclusions. Processes of climate warming in Ukraine are activating. There was determined a strong trend on increasing of average maximum of air temperature in winter with speed 0.17-0,39 degrees centigrade/10 years. According to climatic norm this index mainly increased mostly (up to 3,3 degrees centigrade) in January in North-East of the country. In future such anomalies will grow. Determination of correlation between climate and health is the base for taking protective measures against perils for population health connected with climate.

scholarly journals Change in mean and extreme temperature at Yingkou station in Northeast China from 1904 to 2017

2021 ◽  
Vol 164 (3-4) ◽  
Author(s):  
Xiaoying Xue ◽  
Guoyu Ren ◽  
Xiubao Sun ◽  
Panfeng Zhang ◽  
Yuyu Ren ◽  
...  
Keyword(s):  
Northeast China ◽  
Extreme Temperature ◽  
Maximum Temperature ◽  
Data Set ◽  
The Past ◽  
Significant Downward Trend ◽  
Cold Events ◽  
Temperature Indices ◽  
Increasing Trends ◽  
Change In Mean

AbstractThe understanding of centennial trends of extreme temperature has been impeded due to the lack of early-year observations. In this paper, we collect and digitize the daily temperature data set of Northeast China Yingkou meteorological station since 1904. After quality control and homogenization, we analyze the changes of mean and extreme temperature in the past 114 years. The results show that mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin) all have increasing trends during 1904–2017. The increase of Tmin is the most obvious with the rate of 0.34 °C/decade. The most significant warming occurs in spring and winter with the rate of Tmean reaching 0.32 °C/decade and 0.31 °C/decade, respectively. Most of the extreme temperature indices as defined using absolute and relative thresholds of Tmax and Tmin also show significant changes, with cold events witnessing a more significant downward trend. The change is similar to that reported for global land and China for the past six decades. It is also found that the extreme highest temperature (1958) and lowest temperature (1920) records all occurred in the first half of the whole period, and the change of extreme temperature indices before 1950 is different from that of the recent decades, in particular for diurnal temperature range (DTR), which shows an opposite trend in the two time periods.

scholarly journals Observed Trends in Indices of Daily Temperature Extremes in South America 1960–2000

2005 ◽  
Vol 18 (23) ◽  
pp. 5011-5023 ◽  
Author(s):  
L. A. Vincent ◽  
T. C. Peterson ◽  
V. R. Barros ◽  
M. B. Marino ◽  
M. Rusticucci ◽  
...  
Keyword(s):  
Climate Change ◽  
South America ◽  
Climate Extremes ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Increasing Trends

Abstract A workshop on enhancing climate change indices in South America was held in Maceió, Brazil, in August 2004. Scientists from eight southern countries brought daily climatological data from their region for a meticulous assessment of data quality and homogeneity, and for the preparation of climate change indices that can be used for analyses of changes in climate extremes. This study presents an examination of the trends over 1960–2000 in the indices of daily temperature extremes. The results indicate no consistent changes in the indices based on daily maximum temperature while significant trends were found in the indices based on daily minimum temperature. Significant increasing trends in the percentage of warm nights and decreasing trends in the percentage of cold nights were observed at many stations. It seems that this warming is mostly due to more warm nights and fewer cold nights during the summer (December–February) and fall (March–May). The stations with significant trends appear to be located closer to the west and east coasts of South America.

scholarly journals The impact of forest regeneration on streamflow in 12 mesoscale humid tropical catchments

2013 ◽  
Vol 17 (7) ◽  
pp. 2613-2635 ◽  
Author(s):  
H. E. Beck ◽  
L. A. Bruijnzeel ◽  
A. I. J. M. van Dijk ◽  
T. R. McVicar ◽  
F. N. Scatena ◽  
...  
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Forest Regeneration ◽  
Forest Cover ◽  
Impact Analysis ◽  
Forest Area ◽  
Macro Scale ◽  
Annual Time Series ◽  
The Impact ◽  
Annual Time

Abstract. Although regenerating forests make up an increasingly large portion of humid tropical landscapes, little is known of their water use and effects on streamflow (Q). Since the 1950s the island of Puerto Rico has experienced widespread abandonment of pastures and agricultural lands, followed by forest regeneration. This paper examines the possible impacts of these secondary forests on several Q characteristics for 12 mesoscale catchments (23–346 km2; mean precipitation 1720–3422 mm yr−1) with long (33–51 yr) and simultaneous records for Q, precipitation (P), potential evaporation (PET), and land cover. A simple spatially-lumped, conceptual rainfall–runoff model that uses daily P and PET time series as inputs (HBV-light) was used to simulate Q for each catchment. Annual time series of observed and simulated values of four Q characteristics were calculated. A least-squares trend was fitted through annual time series of the residual difference between observed and simulated time series of each Q characteristic. From this the total cumulative change (Â) was calculated, representing the change in each Q characteristic after controlling for climate variability and water storage carry-over effects between years. Negative values of  were found for most catchments and Q characteristics, suggesting enhanced actual evaporation overall following forest regeneration. However, correlations between changes in urban or forest area and values of  were insignificant (p ≥ 0.389) for all Q characteristics. This suggests there is no convincing evidence that changes in the chosen Q characteristics in these Puerto Rican catchments can be ascribed to changes in urban or forest area. The present results are in line with previous studies of meso- and macro-scale (sub-)tropical catchments, which generally found no significant change in Q that can be attributed to changes in forest cover. Possible explanations for the lack of a clear signal may include errors in the land cover, climate, Q, and/or catchment boundary data; changes in forest area occurring mainly in the less rainy lowlands; and heterogeneity in catchment response. Different results were obtained for different catchments, and using a smaller subset of catchments could have led to very different conclusions. This highlights the importance of including multiple catchments in land-cover impact analysis at the mesoscale.

scholarly journals IMPACTS OF SNOWMELT AND CLIMATE CHANGE ON HIMALAYAN RIVERS: THE CASE OF DATA-SCARCE DUDHKOSHI RIVER IN EASTERN NEPAL

2021 ◽  
Vol 5 (12) ◽  
Author(s):  
Sudeep Pokhrel ◽  
Saraswati Thapa
Keyword(s):  
Maximum Temperature ◽  
Climate Projections ◽  
Snow Melt ◽  
Snow Hydrology ◽  
Statistical Downscaling Model ◽  
Snowmelt Runoff ◽  
Annual Average ◽  
Temperature And Precipitation ◽  
Increasing Trends ◽  
Runoff Model

Water from snow-melt is crucial to provide ecosystem services in downstream of the Himalayas. To study the fate of snow hydrology, an integrated modeling system has been developed coupling Statistical Downscaling Model (SDSM) outputs with Snowmelt Runoff Model (SRM) in the Dudhkoshi Basin, Nepal. The SRM model is well-calibrated in 2011 and validated in 2012 and 2014 using MODIS satellite data. The annual average observed and simulated discharges for the calibration year are 177.89 m3 /s and 181.47 m3 /s respectively. To assess future climate projections for the periods 2020s, 2050s, and 2080s, the SDSM model is used for downscaling precipitation, maximum temperature, and minimum temperature from the Canadian GCM model (CanESM2) under three different scenarios RCP2.6, RCP4.5 and RCP8.5. All considered scenarios are significant in predicting increasing trends of maximumminimum temperature and precipitation and the storehouse of freshwater in the mountains is expected to deplete rapidly if global warming continues.

scholarly journals Trend analysis of water quality parameters for the Nisava river

2013 ◽  
Vol 11 (3) ◽  
pp. 199-210 ◽  
Author(s):  
Milan Gocic ◽  
Slavisa Trajkovic
Keyword(s):  
Water Quality ◽  
Trend Analysis ◽  
Kendall Test ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Total Hardness ◽  
Significance Level ◽  
Annual Series ◽  
Annual Time Series ◽  
Annual Time

The data of 12 water quality parameters have been daily monitored at the Nis station on the Nisava River during 2000-2004. The trend analysis was performed on monthly, seasonal and annual time series using the Mann-Kendall test, the Spearman?s Rho test and the linear regression at the 5% significance level. The monthly results showed that significant trends were found only in pH, total hardness, Ca and SO4 data. The results in seasonal series indicated that the significant trends were detected in pH, total hardness, Cl, Ca and SO4 data. In annual series, the trends were insignificant at the 5% significance level.

scholarly journals Comparing dynamical, stochastic and combined downscaling approaches – lessons from a case study in the Mediterranean region

2012 ◽  
Vol 9 (8) ◽  
pp. 9847-9884
Author(s):  
N. Guyennon ◽  
E. Romano ◽  
I. Portoghese ◽  
F. Salerno ◽  
S. Calmanti ◽  
...  
Keyword(s):  
Statistical Downscaling ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
Max Planck ◽  
Basin Scale ◽  
Quantile Transform

Abstract. Various downscaling techniques have been developed to bridge the scale gap between global climate models (GCMs) and finer scales required to assess hydrological impacts of climate change. Such techniques may be grouped into two downscaling approaches: the deterministic dynamical downscaling (DD) and the stochastic statistical downscaling (SD). Although SD has been traditionally seen as an alternative to DD, recent works on statistical downscaling have aimed to combine the benefits of these two approaches. The overall objective of this study is to examine the relative benefits of each downscaling approach and their combination in making the GCM scenarios suitable for basin scale hydrological applications. The case study presented here focuses on the Apulia region (South East of Italy, surface area about 20 000 km2), characterized by a typical Mediterranean climate; the monthly cumulated precipitation and monthly mean of daily minimum and maximum temperature distribution were examined for the period 1953–2000. The fifth-generation ECHAM model from the Max-Planck-Institute for Meteorology was adopted as GCM. The DD was carried out with the Protheus system (ENEA), while the SD was performed through a monthly quantile-quantile transform. The SD resulted efficient in reducing the mean bias in the spatial distribution at both annual and seasonal scales, but it was not able to correct the miss-modeled non-stationary components of the GCM dynamics. The DD provided a partial correction by enhancing the trend spatial heterogeneity and time evolution predicted by the GCM, although the comparison with observations resulted still underperforming. The best results were obtained through the combination of both DD and SD approaches.

scholarly journals Investment decisions within the context of financialization: Cointegration evidence from the UK economy

2016 ◽  
Vol 63 (1) ◽  
pp. 113-133 ◽  
Author(s):  
Constantinos Alexiou ◽  
Joseph Nellis
Keyword(s):  
Capital Accumulation ◽  
Investment Decisions ◽  
Causality Tests ◽  
Policy Objectives ◽  
Annual Time Series ◽  
Granger Causality Tests ◽  
Bounds Test ◽  
The Uk ◽  
Annual Time ◽  
Instrumental Role

Within the context of financialization, this empirical study sheds some light on the distributional aspects of the existing intra-capitalist conflict between financial and industrial capital and its concomitant impact, via investment, on the macroeconomy. In doing so, bounds-test cointegration techniques in conjunction with Granger causality tests provide the econometric framework upon which the respective models are tested. Annual time series were used spanning from 1971 to 2012, for the UK. The empirical evidence is in line with the theoretical exposition insofar as investment decisions by industry are significantly conditioned by industrial profit. Moreover, the distribution of profits between industry and finance, in conjunction with policy objectives, appears to be playing an instrumental role in affecting capital accumulation.

scholarly journals Predicting Current Potential Distribution and the Range Dynamics of Pomacea canaliculata in China under Global Climate Change

Biology ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 110
Author(s):  
Yingxuan Yin ◽  
Qing He ◽  
Xiaowen Pan ◽  
Qiyong Liu ◽  
Yinjuan Wu ◽  
...  
Keyword(s):  
Climate Change ◽  
Native Species ◽  
Potential Distribution ◽  
Global Climate ◽  
Social Economy ◽  
Maximum Temperature ◽  
Pomacea Canaliculata ◽  
Climate Conditions ◽  
Jackknife Test ◽  
Recent Climate

Pomacea canaliculata is one of the 100 worst invasive alien species in the world, which has significant effects and harm to native species, ecological environment, human health, and social economy. Climate change is one of the major causes of species range shifts. With recent climate change, the distribution of P. canaliculata has shifted northward. Understanding the potential distribution under current and future climate conditions will aid in the management of the risk of its invasion and spread. Here, we used species distribution modeling (SDM) methods to predict the potential distribution of P. canaliculata in China, and the jackknife test was used to assess the importance of environmental variables for modeling. Our study found that precipitation of the warmest quarter and maximum temperature in the coldest months played important roles in the distribution of P. canaliculata. With global warming, there will be a trend of expansion and northward movement in the future. This study could provide recommendations for the management and prevention of snail invasion and expansion.

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