Investigation into Recent Temperature and Rainfall Trends in Mali Using Mann-Kendall Trend Test: Case Study of Bamako

Rainfall and temperature variability analysis is important for researchers and policy formulators in making critical decisions on water availability and use in communities. The Western Sahel, which comprises Mali is considered as one of the vulnerable regions to climate change, and also encountered the challenges of climatic shocks such as flood and drought. This research therefore sought to investigate climate change effects on hydrological events and trends in Sahelian rainfall intensity using Bamako (Mali) as a case study from 1991 to 2020, as limited data availability did not allow an extended period of study. Monthly observed data provided by MALI-METEO was used to validate daily rainfalls data from African Rainfall Climatology Version 2 (ARC2) satellite-based rainfall product on monthly basis. The validated model performance used Nash-Sutcliffe Efficiency (NSE) and Percent Bias (PBAIS) and gave results of 0.904 and 1.0506 respectively. Trends in annual maximum temperatures and rainfalls were analyzed using Mann-Kendall trend test. The result indicated that the trend in annual maximum rainfalls was decreasing, while annual total rainfall was increasing but not significant at 5% significance level. The rate of increase in annual total rainfalls was 0.475 mm/year according to the observed annual rainfall series and decreased to 0.68 mm/year in annual maximum. The analysis further found that annual maximum temperatures were increasing at the rate of 0.03°C/year at 5% significance level. To provide more accurate climate predictions, it is recommended that further studies on rainfall and temperature with data sets spanning 60 - 90 years be carried out.

A method to predict rockburst using temporal trend test and its application

Rockbursts have become a significant hazard in underground mining,underscoring the need for a robust early warning model to ensure safety management.This study presents a novel approach for rockburst prediction,integrating the Mann-Kendall trend test(MKT)and multi-indices fusion to enable real-time and quantitative assessment of rockburst hazards.The methodology employed in this study involves the development of a comprehensive precursory index library for rockbursts.The MKT is then applied to analyze the real-time trend of each index,with adherence to rockburst characterization laws serving as the warning criterion.By employing a confusion matrix,the warning effectiveness of each index is assessed,enabling index preference determination.Ultimately,the integrated rockburst hazard index Q is derived through data fusion.The results demonstrate that the proposed model achieves a warning effectiveness of 0.563 for Q,surpassing the performance of any individual index.Moreover,the model’s adaptability and scalability are enhanced through periodic updates driven by actual field monitoring data,making it suitable for complex underground working environments.By providing an efficient and accurate basis for decision-making,the proposed model holds great potential for the prevention and control of rockbursts.It offers a valuable tool for enhancing safety measures in underground mining operations.

Detecting Global Vegetation Changes Using Mann-Kendal(MK) Trend Test for 1982–2015 Time Period

Vegetation is the main component of the terrestrial ecosystem and plays a key role in global climate change. Remotely sensed vegetation indices are widely used to detect vegetation trends at large scales. To understand the trends of vegetation cover, this research examined the spatial-temporal trends of global vegetation by employing the normalized difference vegetation index(NDVI) from the Advanced Very High Resolution Radiometer(AVHRR) Global Inventory Modeling and Mapping Studies(GIMMS) time series(1982–2015). Ten samples were selected to test the temporal trend of NDVI, and the results show that in arid and semi-arid regions, NDVI showed a deceasing trend, while it showed a growing trend in other regions. Mann-Kendal(MK) trend test results indicate that 83.37% of NDVI pixels exhibited positive trends and that only 16.63% showed negative trends(P < 0.05) during the period from 1982 to 2015. The increasing NDVI trends primarily occurred in tree-covered regions because of forest growth and re-growth and also because of vegetation succession after a forest disturbance. The increasing trend of the NDVI in cropland regions was primarily because of the increasing cropland area and the improvement in planting techniques. This research describes the spatial vegetation trends at a global scale over the past 30+ years, especially for different land cover types.

Influence of non-stationarity and auto-correlation of climatic records on spatio-temporal trend and seasonality analysis in a region with prevailing arid and semi-arid climate,Iran

Trend and stationarity analysis of climatic variables are essential for understanding climate variability and provide useful information about the vulnerability and future changes,especially in arid and semi-arid regions.In this study,various climatic zones of Iran were investigated to assess the relationship between the trend and the stationarity of the climatic variables.The Mann-Kendall test was considered to identify the trend,while the trend free pre-whitening approach was applied for eliminating serial correlation from the time-series.Meanwhile,time series stationarity was tested by Dickey-Fuller and Kwiatkowski-Phillips-Schmidt-Shin tests.The results indicated an increasing trend for mean air temperature series at most of the stations over various climatic zones,however,after eliminating the serial correlation factor,this increasing trend changes to an insignificant decreasing trend at a 95%confidence level.The seasonal mean air temperature trend suggested a significant increase in the majority of the stations.The mean air temperature increased more in northwest towards central parts of Iran that mostly located in arid and semiarid climatic zones.Precipitation trend reveals an insignificant downward trend in most of the series over various climatic zones;furthermore,most of the stations follow a decreasing trend for seasonal precipitation.Furthermore,spatial patterns of trend and seasonality of precipitation and mean air temperature showed that the northwest parts of Iran and margin areas of the Caspian Sea are more vulnerable to the changing climate with respect to the precipitation shortfalls and warming.Stationarity analysis indicated that the stationarity of climatic series influences on their trend;so that,the series which have significant trends are not static.The findings of this investigation can help planners and policy-makers in various fields related to climatic issues,implementing better management and planning strategies to adapt to climate change and variability over Iran.

基于Mann-Kendall检验和重标极差分析的水质变化趋势

将Mann-Kendall检验和重标极差(R/S)分析相结合,建立了一套综合分析过去和未来水质变化趋势的方法。首先,用季节性Mann-Kendall检验识别水质时间序列的过去变化趋势;然后,用R/S分析方法计算水质时间序列的Hurst指数(IH),0<IH<0.5、0.5<IH<1.0和IH=0.5分别指示反持续性、持续性和白噪声特征;最后,结合水环境保护规划和进展综合推断水质的未来变化趋势。基于2010—2014年珊溪水库及其6条入库支流TN浓度和CODMn,对该方法进行实例研究。结果表明,未来大部分支流的水质将会停止恶化或得到持续改善,然而水库TN浓度仍无明显下降趋势。水库对TN的滞留效应较强,且污染来源较多,水质的根本性改善将是一个长期的过程。除了继续控制入库支流污染,还要控制消落带污染和内源污染。

Hydrological Mann-Kendal Multivariate Trends Analysis in the Upper Yangtze River Basin

Hydrological events should be described through several correlated variables, so multivariate HFA has gained popularity and become an active research field during recent years. However, at present multivariate HFA mainly focuses directly on fitting the frequency distribution without confirming whether the assumptions are satisfied. Neglecting testing these assumptions could get severely wrong frequency distribution. This paper uses multivariate Mann-Kendal testing to detect the multivariate trends of annual flood peak and annual maximum 15 day volume for four control hydrological stations in the?Upper Yangtze River Basin. Results indicate that multivariate test could detect the trends of joint variables, whereas univariate tests can only detect the univariate trends. Therefore, it is recommended to jointly apply univariate and multivariate trend tests to capture all the existing trends.

云南省植被覆盖时空变化特征及影响因素研究

云南省物种资源丰富但生态系统十分脆弱,生态环境脆弱性保护与植被覆盖联系紧密。为此,该文采用2000—2022年MOD13Q1数据集的归一化植被指数(normalized difference vegetation index,NDVI),利用最大值合成法(maximum value composite,MVC)、Theil-Sen中位数趋势分析、Mann-Kendall显著性检验方法动态监测植被的时空格局变化。利用相关分析方法探讨植被对地形地貌、气候变化及土地覆被等影响因素的响应。研究表明:2000—2022年,云南省整体植被覆盖度较高,年均NDVI值在0.74~0.90之间,呈波动上升趋势,其中增加趋势的面积占91.17%,滇东北增长速率最快;植被覆盖在地域上存在差异,滇东南、滇西南的植被覆盖高于滇西北、滇中、滇东北;在海拔3900 m以下,云南省NDVI值比较稳定,3900 m以上随海拔升高而NDVI值呈减少趋势;坡度<3°时,NDVI值最低,随着坡度增加,NDVI值先增加后降低;平面坡向的NDVI值最低,除平面坡向外,其余坡向对植被生长影响较小;2000—2022年,滇中、滇东南、滇东北的植被覆盖与降水呈正相关,表明降水有利于植被生长;而滇西南、滇西北与降水呈负相关。全区及各区域的植被覆盖与气温呈正相关,表明气温有利于植被生长。研究结果可为加强云南省生态环境建设和生态管理提供科学依据。

松花江流域陆地水储量时空变异特征与影响因素探究

松花江流域是我国重要的粮食生产基地和生态区,研究其水源供给与水量变化对实现流域科学配水和生态环境保护具有重要意义。研究采用2003-2020年GRACE与GRACE-FO重力卫星反演的CSR RL06 Mascon数据产品,针对GRACE与GRACE-FO之间缺失的数据,采用已发表的重构数据进行填补,并通过GLDAS模拟水储量数据验证其在研究区的准确性。在此基础上,采用Theil-Sen结合Mann-Kendall趋势检验,分析了流域陆地水储量时空变化特征。同时,利用Pearson相关系数与地理探测器方法,深入探究降水(Pre)、蒸散发(ET)、人口密度(POP)、归一化植被指数(NDVI)、生态分区(Ez)以及高程(DEM)等因子对陆地水储量的影响程度及不同因子的综合影响。并针对不同精度遥感数据进行相关性分析时,重采样带来的误差问题,对传统栅格数据重采样方式进行优化。研究结果表明:①GRACE数据产品在研究区具有较好的准确性,变化趋势线性区间与GLDAS数据具有很高的相关性;②优化后的重采样方式更适用于类似Pearson相关性分析的空间研究,相比于直接使用原始数据的方式,多数数据精度有显著提升;③松花江流域水储量在研究期内呈现增长趋势,极值比增加明显,研究末期,区内水储量空间分布趋于稳定,呈现东北多西南少的基本态势;④造成流域水储量变化的主要单一因子是降水和蒸散发,多数因子共同作用产生的效果外在表现形式均为非线性增强。

义昌江流域水质水量演变规律分析

研究义昌江流域降水量、径流量和水质指标演变规律,可为流域水资源开发利用、水环境保护和水生态改善提供数据支撑。运用线性趋势回归检验法研究其变化趋势,采用有序聚类分析法对其进行突变分析;分析水质指标时空变化,并进行水质评价;基于Pearson相关分析和双累积曲线法,研究义昌江流域水质变化的原因。结果表明:降水量、径流量、溶解氧、高锰酸盐指数、氨氮、粪大肠菌群变化趋势不明显。一般情况下,下游大冲口断面水质比上游断面好;从季节变化来看,冬季水质大部分合格、水质较好;从年变化来看,水质变化波动;径流对溶解氧、氨氮的影响比降水和水温更大,水温对高锰酸盐指数、粪大肠菌群的影响比降水和径流更大;水质指标变化受自然因素和人类活动共同影响。

Evaluation of Rainfall Tendency for the Twentieth Century over Indira Sagar Region in Central India

The study investigates long-term changes in annual and seasonal rainfall patterns in the Indira Sagar Region of Madhya Pradesh, India, from 1901 to 2010. Agriculture sustainability, food supply, natural resource development, and hydropower system reliability in the region rely heavily on monsoon rainfall. Monthly rainfall data from three stations (East Nimar, Barwani, and West Nimar) were analyzed. Initially, the pre-whitening method was applied to eliminate serial correlation effects from the rainfall data series. Subsequently, statistical trends in annual and seasonal rainfall were assessed using both parametric (student-t test) and non-parametric tests [Mann-Kendall, Sen’s slope estimator, and Cumulative Sum (CUSUM)]. The magnitude of the rainfall trend was determined using Theil-Sen’s slope estimator. Spatial analysis of the Mann-Kendall test on an annual basis revealed a statistically insignificant decreasing trend for Barwani and East Nimar and an increasing trend for West Nimar. On a seasonal basis, the monsoon season contributes a significant percentage (88.33%) to the total annual rainfall. The CUSUM test results indicated a shift change detection in annual rainfall data for Barwani in 1997, while shifts were observed in West and East Nimar stations in 1929. These findings offer valuable insights into regional rainfall behavior, aiding in the planning and management of water resources and ecological systems.

The trend on runoff variations in the Lhasa River Basin

Taking the Lhasa River Basin above Lhasa hydrological station in Tibetan Plateau as a study area, the characteristics of the annual and monthly mean runoff during 1956-2003 were analyzed, based on the hydro-data of the two hydrological stations （Lhasa and Tanggya） and the meteorological data of the three meteorological stations （Damxung, Lhasa and Tanggya）. The trends and the change points of runoff and climate from 1956 to 2003 were detected using the nonparametric Mann-Kendall test and Pettitt-Mann-Whitney change-point statistics. The correlations between runoff and climate change were analyzed using multiple linear regression. The major results could be summarized as follows： （1） The annual mean runoff during the last 50 years is characterized by a great fluctuation and a positive trend with two change points （around 1970 and the early 1980s）, after which the runoff tended to increase and was increasing intensively in the last 20 years. Besides, the monthly mean runoff with a positive trend is centralized in winter half-year （November to April） and some other months （May, July and September）. （2） The trends of the climate change in the study area are generally consistent with the trend of the runoff, but the leading climate factors which aroused the runoff variation are distinct. Precipitation is the dominant factor influencing the annual and monthly mean runoff in summer half year, while temperature is the primary factor in winter season.

Wavelet Analysis and Nonparametric Test for Climate Change in Tarim River Basin of Xinjiang During 1959-2006

Using wavelet analysis,regression analysis and the Mann-Kendall test,this paper analyzed time-series(1959-2006) weather data from 23 meteorological stations in an attempt to characterize the climate change in the Tarim River Basin of Xinjiang Uygur Autonomous Region,China.Major findings are as follows:1) In the 48-year study period,average annual temperature,annual precipitation and average annual relative humidity all presented nonlinear trends.2) At the 16-year time scale,all three climate indices unanimously showed a rather flat before 1964 and a detectable pickup thereafter.At the 8-year time scale,an S-shaped nonlinear and uprising trend was revealed with slight fluctuations in the entire process for all three indices.Incidentally,they all showed similar pattern of a slight increase before 1980 and a noticeable up-swing afterwards.The 4-year time scale provided a highly fluctuating pattern of periodical oscillations and spiral increases.3) Average annual relative humidity presented a negative correlation with average annual temperature and a positive correlation with annual precipitation at each time scale,which revealed a close dynamic relationship among them at the confidence level of 0.001.4) The Mann-Kendall test at the 0.05 confidence level demonstrated that the climate warming trend,as represented by the rising average annual temperature,was remarkable,but the climate wetting trend,as indicated by the rising annual precipitation and average annual relative humidity,was not obvious.

Trend in pan evaporation and its attribution over the past 50 years in China

Trends in pan evaporation are widely relevant to the hydrological community as indicators of hydrological and climate change. Pan evaporation has been decreasing in the past few decades over many large areas with differing climates globally. This study analyzes pan evaporation data from 671 stations in China over the past 50 years in order to reveal the trends of it and the corresponding trend attribution. Mann-Kendall test shows a significant declining trend in pan evaporation for most stations, with an average decrease of 17.2 mm/10a in China as a whole, the rate of decline was the steepest in the humid region （29.7 mm/10a）, and was 17.6 mm/10a and 5.5 mm/10a in the semi-humid/semi-arid region and arid region, respectively. Complete correlation coefficients of pan evaporation with 7 climate factors were computed, and decreases in diurnal temperature range （DTR）, SD （sunshine duration） and wind speed were found to be the main attributing factors in the pan evaporation declines. Decrease in DTR and SD may relate to the increase of clouds and aerosol as well as the other pollutants, and decrease in wind speed to weakening of the Asian winter and summer monsoons under global climate warming.

The Regions with the Most Significant Temperature Trends During the Last Century

Having analyzed a global grid temperature anomaly data set and some sea level pressure data during the last century, we found the following facts. Firstly, the annual temperature change with a warming trend of about 0.6°C/ 100 years in the tropical area over Indian to the western Pacific Oceans was most closely correlated to the global mean change. Therefore, the temperature change in this area might serve as an indi-cator of global mean change at annual and longer time scales. Secondly, a cooling of about -0.3°C/ 100 years occurred over the northern Atlantic. Thirdly, a two-wave pattern of temperature change, warming over northern Asia and northwestern America and cooling over the northern Atlantic and the northern Pa-cific, occurred during the last half century linked to strengthening westerlies over the northern Atlantic and the weakening Siberian High. Fourthly, a remarkable seasonal difference occurred over the Eurasian con-tinent, with cooling (warming) in winter (summer) during 1896–1945, and warming (cooling) in winter (summer) during 1946-1995. The corresponding variations of the North Atlantic Oscillation and the South-ern Oscillation were also discussed. Key words Temperature trend - Mann-Kendall’s Test - Significance - Regional difference - Correlation coefficient This study was supported by the Ministry of Science and Technology Projects G1999043400 and Na-tional Key Project- “Studies on Short-Term Climate Prediction System in China” under Grant No.96-908-01-04.

Climate change trend and its effects on reference evapotranspiration at Linhe Station, Hetao Irrigation District

Linhe National Meteorological Station, a representative weather station in the Hetao Irrigation District of China, was selected as the research site for the present study. Changes in climatic variables and reference evapotranspiration （ET0 ） （estimated by the Penman-Monteith method） were detected using Mann-Kendall tests and Sen＇s slope estimator, respectively. The authors analyzed the relationship between the ET0 change and each climatic variable＇s change. From 1954 to 2012, the air temperature showed a significant increasing trend, whereas relative humidity and wind speed decreased dramatically. These changes resulted in a slight increase in ETo. The radiative component of total ET0 increased from 50% to 57%, indicating that this component made a greater contribution to the increase in total ETo than the aerodynamic component, especially during the crop growing season （from April to October）. The sensitivity analysis showed that ETo in Hetao is most sensitive to mean daily air temperature （11.8%）, followed by wind speed （-7.3%） and relative humidity （4.8%）. Changes in sunshine duration had only a minor effect on ET0 over the past 59 years.

Trend Analysis in Standardized Precipitation Index and Standardized Anomaly Index in the Context of Climate Change in Southern Togo

Rainfall and temperature are climatic variables mostly affected by global warming. This study aimed to investigate the temporal trend analysis in annual temperature and rainfall in the Southern Togo for the 1970-2014 period. Daily and annual rainfall and temperature were collected from four weather stations at Atakpame, Kouma-Konda, Lome, and Tabligbo. The temperature variability was determined by the Standardized Anomaly Index (SAI) and the annual rainfall variability was determined using the Standardized Precipitation Index (SPI). The Mann-Kendall test was used for trend analysis. Mann-Kendall statistical test for the mean annual, mean annual minimum and maximum temperature from 1970 to 2014 showed significant warming trends for all stations except Kouma-Konda where mean annual maximum temperature had exhibited non significant cooling trend (P = 0.01). For Standardized Precipitation Index in the 12-month time scale, dry tendency dominates Atakpamé (55.7%) and Kouma-Konda (55.5%) while wet tendency dominates slightly Lomé (50.9%) and Tabligbo (51.4%). The Mann-Kendall test revealed an increasing trend in standardized anomaly index at all the sites, prejudicial to rainfed agriculture practiced by about 90% of Togolese crop growers. The trend analysis in the climate variables indicated a change in climate that necessitates some specific actions for resources management sustainability and conservation.

Detection of Approximate Potential Trend Turning Points in Temperature Time Series (1941-2010) for Asansol Weather Observation Station, West Bengal, India

Researches are being carried out world-wide to understand the nature of temperature change during recent past at different geographical scales so that comprehensive inferences can be drawn about recent temperature trend and future climate. Detection of turning points in time series of meteorological parameters puts challenges to the researches. In this work, the temperature time series from 1941 to 2010 for Asansol observatory, West Bengal, India, has been considered to understand the nature, trends and change points in the data set using sequential version of Mann-Kendall test statistic. Literatures suggest that use of this test statistic is the most appropriate for detecting climatic abrupt changes as compared to other statistical tests in use. This method has been employed upon monthly average temperatures recorded over the said 70 years for detection of abrupt changes in the average temperature of each of the months. The approximate potential trend turning points have been calculated separately for each month (January to December). Sequential version of Mann-Kendall test statistic values for the months of July and August is significant at 95% confidence level (p 0.05). The average temperature for most of the other months has shown an increasing trend but more significant rise in July and August temperature has been recognized since 1960s.

Homogeneity and Trend Analysis of Hydrometeorological Data of the Eastern Black Sea Region, Turkey

Eastern Black Sea Region in northeastern part of Turkey has the highest precipitation total in the country, approaching 2500 mm per a year. It is therefore an important region as it frequently encounters with flash floods due to heavy rains. For future planning of water resources, environment and urbanization, it is important to know the expected behavior of hydrometeorological processes, mainly precipitation and flow. Due to these facts, in this study, homogeneity of long-term annual precipitation and streamflow series of the Eastern Black Sea Region, Turkey is checked using double mass curve method and trends are determined by means of the Mann-Kendall test. The data network consists of 38 precipitation gauging stations and 40 flow gauging stations across the Eastern Black Sea Region. It is found that 27 precipitation stations out of 38 are homogeneous and no trend is available. Out of the remaining stations, nine are found non-homogeneous and four with trend. For annual flow data, it is found that 22 stations out of 40 are homogeneous and no trend is available. The remaining 18 stations are found non-homogeneous, among which 5 stations have trend at the same time.

Trends in major and minor meteorological variables and their influence on reference evapotranspiration for mid Himalayan region at east Sikkim, India

Abstract： Estimation of evapotranspiration （ET） for mountain ecosystem is of absolute importance since it serves as an important component in balancing the hydrologic cycle. The present study evaluates the performance of original and location specific calibrated Hargreaves equation （HARG） with the estimates of Food and Agricultural Organization （FAO） Penman Monteith （PM） method for higher altitudes in East Sikkim, India. The results show that the uncalibrated HARG model underestimates ET0 by 0.35 mm day^-1 whereas the results are significantly improved by regional calibration of the model. In addition, this paper also presents the variability in the trajectory associated with the climatic variables with the changing climate in the study site. Non- parametric Mann-Kendall （MK） test was used to investigate and understand the mean monthly trend of eight climatic parameters including reference evapotranspiration （ET0） for the period of 1985 - 2009. Trend of ET0 was estimated for the calculations done by FAO PM equation. The outcomes of the trend analysis show significant increasing （p ≤ 0.05） trend represented by higher Z-values, through MK test, for net radiation （Rn）, maximum temperature （Tmax） and minimum temperature （Train）, especially in the first months of the year. Whereas, significant （0.01 ≥ p ≤0.05） decreasing trend in vapor pressure deficit （VPD） and precipitation （P） is observed throughout the year. Declining trend in sunshine duration, VPD and ET0 is found in spring （March - May） and monsoon （June - November） season. The result displays significant （0.01≤ p ≤0.05） decreasing ET0 trend between （June - December） except in July, exhibiting the positive relation with VPD followed by sunshine duration at the station. Overall, the study emphasizes the importance of trend analysis of ET0 and other climatic variables for efficient planning and managing the agricultural practices, in identifying the changes in the meteorological parameters and to accurately assess the hydrologic water balance of the hilly regions.

Trend and Periodicity of Temperature Time Series in Ontario

The trends and periodicities in the annual and seasonal temperature time series at fifteen weather stations within Ontario Great Lakes Basins have been analyzed, for the period 1941-2005, using the statistical analyses (Fourier series analysis, t-test, and Mann-Kendall test). The stations were spatially divided into three regions: northwest (NW), southwest (SW), and southeast (SE) to evaluate spatial variability in temperature. The results of the study reveal that the annual maximum mean temperature showed increasing trend for NW, and mixed trends for SW and SE regions. The variability was found to be more for northern stations as compared to southern stations for annual extreme minimum temperature. In addition, the trend slope per 100 years for the average annual extreme minimum temperature increased within the range of -0.8°C (Stratford) to 15°C (Porcupine). The seasonal analysis demonstrated that extreme maximum temperature has an increasing trend and maximum mean temperature has a decreasing trend during summer and winter. The extreme minimum temperature for winter illustrated an increasing trend (90%) with 22% statistically significant for NW region. For the SW region, the trend is also increasing (80%) for most of the temperature variables and 25% of temperature data were significantly increased in the SW region. The SE region stations showed overall very clear increasing trends (95%) for all the temperature variables. The data also showed that 47% of data were statistically significant in the SE region. The analysis of variance accounted for by trend, significant periodicities, and random component show that the pattern is similar for the percent of variance accounted for periodicities, and random component contribute dominantly for the four temperature variables and frost free days (FFD) for all three regions. Overall, the study reveals that the extreme minimum temperature is increasing annually and seasonally, with statistically significant at many stations.