Long-term Trend Analysis Research Articles

Spatial Variability of Rainfall Trends in Sri Lanka from 1989 to 2019 as an Indication of Climate Change

Analysis of long-term rainfall trends provides a wealth of information on effective crop planning and water resource management, and a better understanding of climate variability over time. This study reveals the spatial variability of rainfall trends in Sri Lanka from 1989 to 2019 as an indication of climate change. The exclusivity of the study is the use of rainfall data that provide spatial variability instead of the traditional location-based approach. Henceforth, daily rainfall data available at Climate Hazards Group InfraRed Precipitation corrected with stations (CHIRPS) data were used for this study. The geographic information system (GIS) is used to perform spatial data analysis on both vector and raster data. Sen’s slope estimator and the Mann–Kendall (M–K) test are used to investigate the trends in annual and seasonal rainfall throughout all districts and climatic zones of Sri Lanka. The most important thing reflected in this study is that there has been a significant increase in annual rainfall from 1989 to 2019 in all climatic zones (wet, dry, intermediate, and Semi-arid) of Sri Lanka. The maximum increase is recorded in the wet zone and the minimum increase is in the semi-arid zone. There could be an increased risk of floods in the southern and western provinces in the future, whereas areas in the eastern and southeastern districts may face severe droughts during the northeastern monsoon. It is advisable to introduce effective drought and flood management and preparedness measures to reduce the respective hazard risk levels.

Esophageal cancer: trends in incidence and mortality in China from 2005 to 2015.

BackgroundThe long‐term trend analysis of esophageal cancer is rarely reported in China. Our purpose is to analyze the incidence and mortality trends of esophageal cancer in China from 2005 to 2015.MethodBased on the data in the annual report of the China Cancer Registry, a comprehensive analysis of esophageal cancer cases and deaths from 2005 to 2015 was carried out. The incidence and mortality of esophageal cancer are stratified by gender and region (urban or rural). Long‐term trend analysis was conducted using Joinpoint regression model.ResultIn China, the age‐standardized incidence rates by the world population declined from 13.84/105 in 2005 to 11.64/105 in 2015. Annual percent changes were 3.4% (95% CI: 0.6%, 6.3%) in the period 2005‐2011, −7.4% (95% CI: −10.1%, −4.7%) in the period 2011‐2015, respectively. The age‐standardized mortality rates declined from 10.86/105 in 2005 to 8.57/105 in 2015. And the average annual percent change was −4.1% (95% CI: −6.7%, −1.5%). The incidence and mortality of esophageal cancer in men are higher than those in women, and the incidence and mortality of esophageal cancer in rural areas are much higher than those in urban areas.ConclusionIn China, the incidence of esophageal cancer first increased and then decreased during 2005‐2015, while the mortality rate has been declining.

Long-Term Climate Variability and Drought Characteristics in Tropical Region of India

AbstractThis work reports climate change signals and long-term trend analysis of climate variables, meteorological drought, and extreme climate indexes over the tropical state of Kerala in India. T...

Analysis of Seasonal Price Fluctuations of Paddy (Boro) in Bangladesh

This paper has focused on seasonal variations of price and trend of the price escalation of paddy in Bangladesh using monthly average wholesale price of Boro paddy over a period from 2001 to 2019. Secondary data were used in this study and collected from different secondary sources. The multiplicative model was exercised in this study; the least square method was applied to find out the long-term changes occurring in the price of paddy and the ratio to moving average method was used to measure seasonal fluctuations in price of paddy. It was evidently observed from the study that seasonal fluctuations in price of paddy prevail in Bangladesh as seasonal indices were deviated from hundred in different months. April to August, the price of paddy was lower compare to other months’ price because April and Mayare the harvesting period of Boro paddy and resulted in more supply to the market. From August, it was increasing gradually and reached to the highest position on March with 112.15. Long-term trend analysis showed that prices of paddy will increase Tk. 72.80 per quintal higher annually compare to the country’s average price.
 SAARC J. Agri., 18(2): 219-226 (2020)

A Total Precipitable Water Product and Its Trend Analysis in Recent Years Based on Passive Microwave Radiometers

Total precipitable water (TPW) is a key parameter in global hydrological cycle and plays an important role in climate change as a kind of green house. Especially, a long-term TPW dataset will help us to better understand its impact on hydrological cycle and our living environment under the background of warming climate. Thus, a long-term global TPW product from 2002 to 2017 was created for the first time at the resolution of 0.25° × 0.25° based on the observations from passive microwave radiometers AMSR-E and AMSR2 and TPW product from AIRS2RET in this study. Based on the newly created TPW product, a long-term trend analysis was carried out on both global and regional scale. According to the long-term trend analysis, the linear trend of global average TPW anomaly is 0.34 mm/decade. Especially, there is a faster increasing speed for TPW in recent decade from 2008 to 2017. For the trend analysis on regional scale, the most noteworthy thing is that there is a negative linear trend of TPW anomaly in the atmosphere over rainforest distributed in the Amazon and central Africa, which means the atmosphere is becoming dryer in these areas. The drying atmosphere will cause a decrease in precipitation and will further cause a great damage to the rainforests in the Amazon and central Africa if the dry trend continues.

Machine Learning Algorithm for Estimating Surface PM2.5 in Thailand

ABSTRACT We have used NASA's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2) reanalysis data of aerosols and meteorology into a machine learning algorithm (MLA) to estimate surface PM2.5 concentration in Thailand. One year of hourly data from 51 ground monitoring stations in Thailand was spatiotemporally collocated with MERRA2 fields. The integrated data then used to train and validate a supervised MLA' random forest' to estimate hourly and daily PM2.5 concentrations. The MLA is cross-validated using a 10-fold random sampling approach. The trained MLA can estimate PM2.5 with close to zero mean bias across the country. The correlation coefficient of 0.95 with slope and intercept values of 0.95 and 0.88 are achieved between observed and estimated PM2.5. The MLA also shows underestimation at hourly scale under very clean conditions (PM2.5 80 µg m–3). The hourly data also demonstrate high skill in following the diurnal cycle during different seasons of the year. The daily mean PM2.5 (24-hour) values follow day-to-day variability very well (correlation coefficient of 0.98, RMSE = 3.14 µg m–3), showing high value during winter months (November–February) and lower during other seasons. The trained MLA has the potential to reprocess the MERRA2 timeseries for the region, and the bias corrected data can be used in other applications such as long-term trend analysis and health exposure studies. The MLA can also be applied to GEOS forecasted fields to generate bias corrected air quality forecasts for the region.

The new dynamics of residential aged care in Australia: continuity and change.

Objective This paper tests the hypothesis that increases in recorded dependency levels of permanent residential aged care clients are associated with reduced length of stay and higher turnover. A secondary objective is to compare the Aged Care Funding Instrument with its predecessor, the Resident Classification Scale, on a common schema. Methods Administrative data for all Commonwealth-subsidised residential aged care services in Australia from 2008-09 to 2018-19 were obtained from the National Aged Care Data Clearinghouse. More than 750000 episodes of permanent residential aged care were analysed. The categories from the two rating systems were mapped to a six-level schema, primarily based on the dollar value of the categories at the time of transition. Results There was a strong trend towards higher dependency ratings across admissions, residents, and separations. However, contrary to expectation, measures of system activity showed a slowing of the system: length of stay increased and turnover decreased. Conclusions The mapping of dependency rating schemes to a common rating enables the analysis of long-term trends in residential care dynamics. There is no evidence that the marked increases in reported dependency ratings led to accelerated system activity, consistent with an earlier study. This analysis forms a solid base for ongoing analysis of care appraisals in the context of a possible new rating scheme. It highlights the interplay between policy changes and provider behaviour, and the need for robust data to monitor care appraisals and system dynamics. What is known about the topic? Residential aged care subsidies are determined by care needs in relation to assessed dependency levels, using the Aged Care Funding Instrument since 2008, and before that, the Resident Classification Scale. Between 2008-09 and 2018-19, there was considerable growth in residents classified at more dependent levels, and this would be expected to result in greater turnover in the system. What does this paper add? This paper maps the rating schemes to a simplified, common rating that enables the analysis of long-term trends in residential care dynamics. It shows that the system is slowing, contrary to the trends expected if residents were more frail as the reported ratings imply. The paper examines possible explanations of these trends, and addresses policy implications. What are the implications for practitioners? In the context of a potential new client-dependency classification, this study shows the importance of robust measures of the dynamics of the system-and the underlying data-vis -à -vis the means by which client dependency is assessed.

Updating a Paleogene magnetobiochronological time scale through graphical integration

All studies focused on the evaluation of paleoecological variability over geological time must be linked to a specific age or time interval, which can be defined using different time scales (biostratigraphic, chronostratigraphic, geochronological or orbital). Therefore, integrated time scales are essential to allow comparisons of data from different locations and/or to assess evolutionary and other events through time. Here we use a new method to update a Paleogene magnetobiochronological time scale, with the following contributions:•The update of the Paleogene magnetobiochronological scale was made by graphical correlation with new age models and adding calcareous nannoplankton and planktonic foraminiferal biozones from different authors.•An excel file structure was proposed to plot any kind of data in MATLAB software, as long as they are associated with some of the scales shown in our updated version of Paleogene magnetobiochronology.•The excel file structure facilitates the analysis of long-term trends of taxonomic groups throughout the Paleogene, and of their evolution in a period characterized by intense climate variability.

Analysis of long-term trends of world prices for agricultural products

The issues related to the long-term pricing process in the world market of agricultural products are discussed in the paper. It is noted that international trade of agro-industrial products, namely the fishery commodities, is one of the key components of the global economy. A detailed analysis of export prices for agricultural products was carried out along with the current trend identification. It is noted that a qualitative analysis of long-term trends of changes of world prices for agricultural products, namely fishery products, can serve as a basis for strategic forecasting of development of the most important sectors of the Russian economy.

Climate change trends in the forest-meadow zone of the Middle Urals and their impact on technological approaches to corn cultivation

The results of the analysis of long-term trends in changes in individual climatic characteristics and variations in weather conditions of the growing season in the forest-meadow zone of the Middle Urals for the period from 1958 to 2020 are presented, their influence on the choice of hybrids and some elements of corn cultivation technology are estimated. As a result of calculating the linear trend, a statistically proven trend has been established to increase the sum of active temperatures above 10 °C for May – September. At the same time, random fluctuations of the analyzed parameters over the years have a direct impact on corn development and productivity, and the limiting factor is the lower limit of these fluctuations, the values of which increase throughout the analyzed period. Nevertheless, the variation over the years remains strong, and the lower limit of these fluctuations does not reach the minimum level for the stable maturation of early-maturing corn hybrids. Therefore, for the conditions of the Middle Urals, the previous recommendations concerning the selection of corn hybrids for early maturity, cold resistance and drought resistance remain relevant. At the same time, the revealed climatic trend allows to predict an increase in the probability of obtaining feed with a high content of exchange energy, which characterizes it as positive one.

Long-term Price Prediction and Trend Analysis of Garlic Using Prophet Model

Long-term Price Prediction and Trend Analysis of Garlic Using Prophet Model

Effects of the prewhitening method, the time granularity, and the time segmentation on the Mann–Kendall trend detection and the associated Sen's slope

Abstract. The Mann–Kendall test associated with the Sen's slope is a very widely used non-parametric method for trend analysis. It requires serially uncorrelated time series, yet most of the atmospheric processes exhibit positive autocorrelation. Several prewhitening methods have therefore been designed to overcome the presence of lag-1 autocorrelation. These include a prewhitening, a detrending and/or a correction of the detrended slope and the original variance of the time series. The choice of which prewhitening method and temporal segmentation to apply has consequences for the statistical significance, the value of the slope and of the confidence limits. Here, the effects of various prewhitening methods are analyzed for seven time series comprising in situ aerosol measurements (scattering coefficient, absorption coefficient, number concentration and aerosol optical depth), Raman lidar water vapor mixing ratio, as well as tropopause and zero-degree temperature levels measured by radio-sounding. These time series are characterized by a broad variety of distributions, ranges and lag-1 autocorrelation values and vary in length between 10 and 60 years. A common way to work around the autocorrelation problem is to decrease it by averaging the data over longer time intervals than in the original time series. Thus, the second focus of this study evaluates the effect of time granularity on long-term trend analysis. Finally, a new algorithm involving three prewhitening methods is proposed in order to maximize the power of the test, to minimize the number of erroneous detected trends in the absence of a real trend and to ensure the best slope estimate for the considered length of the time series.

Rainfall Threshold for Shallow Landslides Initiation and Analysis of Long-Term Rainfall Trends in a Mediterranean Area

The effects of climate change on landslide activity may have important environmental, socio-economic, and political consequences. In the last decades, several short-term extreme rainfall events affected Mediterranean regions, resulted in damaging geo-hydrological processes and casualties. It is unequivocal that the impact of landslides in several Mediterranean countries is increasing with time, but until now, there has been little or no quantitative data to support these increases. In this paper, both rainfall conditions for the occurrence of shallow landslides and rainfall trends were investigated in the Portofino promontory, which extends in the Ligurian Sea, where heavy rainfall and related ground effects often occur. Adopting a frequentist approach, the empirical intensity-duration threshold was estimated. Our findings highlight that the rainfall intensity required to trigger landslides is lower for the same duration than those expected in other similar environments, suggesting a high susceptibility to rainfall-induced landslides in the Portofino territory. Further, the Mann-Kendall test and Hurst exponent were used for detecting potential trends. Analysis of long-term rainfall time series showed statistically significant increasing trends in short duration precipitation occurrence and rainfall rates, suggesting a possible future scenario with a more frequent exceedance of the threshold triggering value and an increase of landslide risk.

Analyses of long-term trends in water quality data of the Plitvice Lakes National Park

Water quality management requires monitoring of the condition of natural waters by both biologicaland chemical indicators to assess the ecological health of a catchment. General water quality characteristics areextracted through a low-frequency dataset, which allows analyses of long-term trends and seasonality. PlitviceLakes National Park freshwater ecosystem includes springs, rivers, streams and lakes with its specific process oftufa formation. The aim of this study was to determine, based on long-term water quality data, potential changes inphysico-chemical parameters required for ongoing tufa deposition processes. The dataset encompasses a 12-yearperiod (2006 – 2017), with measurements performed from April to October per each year on a weekly basis, coveringthirteen sites belonging to karst springs, streams or lotic biotopes. Positive trends were observed for dissolvedoxygen, conductivity, water hardness, alkalinity, chemical oxygen demand (COD) and nitrites. Negative trendswere observed for temperature, pH and most nutrients (nitrates, ammonia and orthophosphates). Temperature valuesshowed different trend slopes among monitored types. Negative correlations between water level and/or dischargewith conductivity and alkalinity probably indicate the effect of dilution. Conversely, nutrients and CODhave a positive correlation with discharge, possibly indicating resuspension from sediment during high flows. Theanalyses of spatial and temporal variations in hydrochemistry through a longer period imply annual alterations,correlations between hydrological components and water chemistry, and significant differences among monitoredtypes, while the tufa deposition process is stable. Long-term monitoring and continuous data analyses can help infuture planning of monitoring programs and the improved understanding of climate changes.

Long-Term Trend Analysis in Annual and Seasonal Precipitation, Maximum and Minimum Temperatures in the Southwest United States

The objective of this study is to perform trend analysis in the historic data sets of annual and crop season [May–September] precipitation and daily maximum and minimum temperatures across the southwest United States. Eighteen ground-based weather stations were considered across the southwest United States for a total period from 1902 to 2017. The non-parametric Mann–Kendall test method was used for the significance of the trend analysis and the Sen’s slope estimator was used to derive the long-term average rates of change in the parameters. The results showed a decreasing trend in annual precipitation at 44.4% of the stations with the Sen’s slopes varying from −1.35 to −0.02 mm/year while the other stations showed an increasing trend. Crop season total precipitation showed non-significant variation at most of the stations except two stations in Arizona. Seventy-five percent of the stations showed increasing trend in annual maximum temperature at the rates that varied from 0.6 to 3.1 °C per century. Air cooling varied from 0.2 to 1.0 °C per century with dominant warming phenomenon at the regional scale of the southwest United States. Average annual minimum temperature had increased at 69% of the stations at the rates that varied from 0.1 to 8 °C over the last century, while the annual temperature amplitude showed a decreasing trend at 63% of stations. Crop season maximum temperature had significant increasing trend at 68.8% of the stations at the rates varying from 0.7 to 3.5 °C per century, while the season minimum temperature had increased at 75% of the stations.

Meteorological Detrending of Ozone at Three Sites in the Dallas-Fort Worth Area: Application of KZ Filter Method

The Dallas-Fort Worth (DFW) area that experiences high temperature and intense solar radiation falls into the moderate nonattainment classification. The variation in meteorological parameters plays an important role in ambient ozone levels variation. Meteorological influences need to be decoupled from ozone data for long-term trend analysis. Temporal separation of maximum daily average 8-h ozone (MDA8 ozone), maximum daily temperature (TMAX), daily average solar radiation (DASR), and daily average wind speed (DAWS) were conducted using Kolmogorov-Zurbenko (KZ) filter for ozone records at Keller (C17), Arlington (C61), Red Bird (C402) monitoring stations in the DFW area from 2003 to 2017. Temporal separation, regression analysis, and meteorological detrending were performed. The long-term component had a clear and stable trend. The contribution of the long-term component to total variation was negligible, which is less than 2%. This is due to the removal of the data noise from the original time series data. The seasonal component had a major contribution (55% to 72%) in the total variation of the maximum temperature and solar radiation. However, the short-term component was dominant in the total variation of the MDA8 ozone (41–54%) and wind speed (68–79%). Regression analysis showed the baseline component bears the highest correlation than the short-term and raw. Solar radiation had the highest correlation to the MDA8 ozone, followed by temperature data in all three stations. Meteorological detrending showed the detrended long-term ozone had an increasing trend. The increasing trend was significant at C402 with a trend of 0.19 ± 0.006 ppb/y (0.398 R2), whereas slight increasing trends were found at C17 (0.072 ± 0.006 (0.107 R2)) and at C61 (0.019 ± 0.007 (0.005 R2)). The increasing trend of long-term components of MDA8 ozone was justified by the increasing level of NOx and VOCs from the mobile sources in the DFW area.

Temporal Trends of Persistent Organic Pollutants across Africa after a Decade of MONET Passive Air Sampling

The Global Monitoring Plan of the Stockholm Convention on Persistent Organic Pollutants (POPs) was established to generate long-term data necessary for evaluating the effectiveness of regulatory measures at a global scale. After a decade of passive air monitoring (2008-2019), MONET is the first network to produce sufficient data for the analysis of long-term temporal trends of POPs in the African atmosphere. This study reports concentrations of 20 POPs (aldrin, chlordane, chlordecone, DDT, dieldrin, endrin, endosulfan, HBCDD, HCB, HCHs, heptachlor, hexabromobiphenyl, mirex, PBDEs, PCBs, PCDDs, PCDFs, PeCB, PFOA, and PFOS) monitored in 9 countries (Congo, Ghana, Ethiopia, Kenya, Mali, Mauritius, Morocco, Nigeria, and Sudan). As of January 1, 2019, concentrations were in the following ranges (pg/m3): 0.5-37.7 (∑6PCB), 0.006-0.724 (∑17PCDD/F), 0.05-5.5 (∑9PBDE), 0.6-11.3 (BDE 209), 0.1-1.8 (∑3HBCDD), 1.8-138 (∑6DDT), 0.1-24.3 (∑3endosulfan), 0.6-14.6 (∑4HCH), 9.1-26.4 (HCB), 13.8-18.2 (PeCB). Temporal trends indicate that concentrations of many POPs (PCBs, DDT, HCHs, endosulfan) have declined significantly over the past 10 years, though the rate was slow at some sites. Concentrations of other POPs such as PCDD/Fs and PBDEs have not changed significantly over the past decade and are in fact increasing at some sites, attributed to the prevalence of open burning of waste (particularly e-waste) across Africa. Modeled airflow back-trajectories suggest that the elevated concentrations at some sites are primarily due to sustained local emissions, while the low concentrations measured at Mt. Kenya represent the continental background level and are primarily influenced by long-range transport.

Asymmetric impact of groundwater use on groundwater droughts

Abstract. Groundwater use affects groundwater storage continuously as the removal of water changes both short-term and long-term groundwater level variation. This has implications for groundwater droughts, i.e. a below-normal groundwater level. The impact of groundwater use on groundwater droughts, however, remains unknown. Hence, the aim of this study is to investigate the impact of groundwater use on groundwater droughts in the absence of actual abstraction data. We present a methodological framework that consists of two approaches. The first approach compared groundwater droughts at monitoring sites that are potentially influenced by abstraction to groundwater droughts at sites that are known to be near natural. Observed groundwater droughts were compared in terms of drought occurrence, duration, and magnitude. The second approach investigated long-term trends in groundwater levels in all monitoring wells. This framework was applied to a case study of the UK, using four regional water management units in which groundwater levels are monitored and abstractions are licensed. Results show two asymmetric responses in groundwater drought characteristics due to groundwater use. The first response is an increase in shorter drought events and is found in three water management units where long-term annual average groundwater abstractions are smaller than recharge. The second response, observed in one water management unit where groundwater abstractions temporarily exceeded recharge, is a lengthening and intensification of groundwater droughts. Analysis of long-term (1984–2014) trends in groundwater levels shows mixed but generally positive trends, while trends in precipitation and potential evapotranspiration are not significant. The overall rising groundwater levels are consistent with changes in water use regulations and with a general reduction in abstractions during the period of investigation. We summarised our results in a conceptual typology that illustrates the asymmetric impact of groundwater use on groundwater drought occurrence, duration, and magnitude. The long-term balance between groundwater abstraction and recharge plays an important role in this asymmetric impact, which highlights the relation between short-term and long-term sustainable groundwater use.

Church Attendance and Religious change Pooled European dataset (CARPE): a survey harmonization project for the comparative analysis of long-term trends in individual religiosity

Despite the long-lasting interest in religious change, debates on the topic have been heated and are still far from being settled. In order to provide a reliable data source through which to study these dynamics, the CARPE project harmonizes well-known international surveys containing items concerning religiosity (the ESS, Eurobarometer, EVS, ISSP and WVS). This makes it possible to broaden the available observation window, both across countries and over time. Moreover, the opportunities this provides for comparing different survey programmes also enable researchers to analyse the consistency of the results, minimizing the impact of random fluctuations and providing useful information with respect to the degree of confidence which can be placed on the relevant estimates. The main focus of this cumulative approach is the variable regarding church attendance, which has been harmonized in various ways. All in all, the CARPE dataset contains figures of religious practice for 45 countries spanning the period of 1970–2016 and derived from 1665 national surveys. This results in a sample of approximately 1.8 million individual observations. The aim of this contribution is to present the dataset’s composition, the harmonization procedure adopted, the strategy used to combine the single datasets and the reliability tests which have been performed. Finally, some possible applications of the CARPE dataset will be introduced.

Annual and Seasonal Rainfall Variability for the Kenyan Highlands from 1900-2012

The study investigated the rainfall variability for Nairobi, Nyeri, Thika, Meru, and Embu which are agriculturally potential zones located in the Kenya Highlands region. The rainfall data were retrieved from the archival documentaries and instrumental rainfall records for 112 years. Using the non-parametric Mann Kendal land regression analysis tests, the coefficient of variance and long-term trend analysis, revealed an insignificant trend in the annual rainfall for all areas under investigation. The study found out a significant deterioration in the long rains (MAM), while the short rains (OND) trend continued significantly increasing over most of the highlands, particularly in Embu and Nairobi since the 1970s. A significant decrease in the long rains was observed in Thika and Meru, which portrays a likely deterioration of agricultural outputs in these areas during the season. The study findings conclude that there are no major observed changes in the annual rainfall amounts in the Highland zones, except a slight increase attributable to the increase of the short rains in some areas. This is a useful record disclosing localized long-term rainfall trends, which can be utilized in simulating the future rainfall events for these areas.