Geo-spatial analysis of temporal trends of temperature and its extremes over India using daily gridded (1°×1°) temperature data of 1969–2005

Daily gridded (1°×1°) temperature data (1969–2005) were used to detect spatial patterns of temporal trends of maximum and minimum temperature (monthly and seasonal), growing degree days (GDDs) over the crop-growing season (kharif, rabi, and zaid) and annual frequencies of temperature extremes over India. The direction and magnitude of trends, at each grid level, were estimated using the Mann–Kendall statistics (α = 0.05) and further assessed at the homogeneous temperature regions using a field significance test (α=0.05). General warming trends were observed over India with considerable variations in direction and magnitude over space and time. The spatial extent and the magnitude of the increasing trends of minimum temperature (0.02–0.04 °C year^?1) were found to be higher than that of maximum temperature (0.01–0.02 °C year^?1) during winter and pre-monsoon seasons. Significant negative trends of minimum temperature were found over eastern India during the monsoon months. Such trends were also observed for the maximum temperature over northern and eastern parts, particularly in the winter month of January. The general warming patterns also changed the thermal environment of the crop-growing season causing significant increase in GDDs during kharif and rabi seasons across India. The warming climate has also caused significant increase in occurrences of hot extremes such as hot days and hot nights, and significant decrease in cold extremes such as cold days and cold nights.     

基于Z指数的江西省旱涝指标与时空分布特征

利用1961—2020年江西省逐日降水资料,基于Z指数分析确定了适用于江西省的旱涝指标。运用M-K检验、小波分析和EOF等方法分析了江西省旱涝时空分布特征。结果表明,1961—2020年江西省降水量年际变化大,20世纪90年代出现突变,但未出现显著的持续增加或减少。江西省干旱、雨涝事件存在准20 a主周期,从90年代开始偏涝年份明显增多,且雨涝呈增强的趋势。江西省旱涝主要存在4种空间分布型,分别为全区型、北涝（旱）南旱（涝）型、西涝（旱）东旱（涝）型、中心涝（旱）南北旱（涝）型,累计贡献率为83.61％。Z指数作为表征江西省旱涝指标的方法具有一定的适用性。     

1960-2011年洞庭湖区年降水量变化特征

以洞庭湖区24个气象站1960-2011年的降水量资料为基础数据,利用气候倾向率、Mann-Kendall突变检验法、小波分析等方法分析了洞庭湖区年降水量的变化特征,并采用正交分解函数EOF、旋转正交分解函数REOF计算了洞庭湖区年尺度的标准化降水指数（SPI）,分析了洞庭湖区的旱涝时空分布特征。结果表明：洞庭湖区年降水量空间上由北向南逐渐增加,时间上没有显著变化趋势。1963年洞庭湖年降水量发生突变。洞庭湖区年降水量存在6a、9a和16-17a振荡周期。洞庭湖区旱涝频繁,极端气候事件有增加的趋势。洞庭湖区年降水量在空间上具有较好的一致性,为普遍干旱或洪涝,但也存在南北反相变化即南部干旱北部洪涝或南部洪涝北部干旱的特点。洞庭湖区年降水量存在南部、西北部和中部3个异常气候区。     

1961-2010 年东北地区降水事件时空均匀性研究

利用1961-2010年东北三省和内蒙古四盟90个气象站逐日降水资料,分析了中国东北地区降水事件的气候特征及时空分布均匀性变化。结果表明：近50 a来,东北地区年降水量略有减少,但冬、春季降水量显著增加;考虑降水日数,冬、春季降水量增加主要是由于降水强度的增加,夏、秋季降水量减少主要是由于降水频次的减少。气候变暖的大背景下,虽然年降水量线性变化趋势并不明显,但是降水量年际间分布不均匀性增加,降水有向极端化发展的趋势,夏、秋季表现更为明显,各等级降水事件尤其是降雪在近20 a时间分布明显不均匀。降水量空间均匀性在1993年发生转折突变,突变后空间不均匀性增加,降水日数空间均匀性在1986年发生变率突变,突变后振荡加剧。降水事件时空不均匀性的增加一定程度上造成了东北地区旱涝事件发生可能性增加,不同地域旱涝事件同发现象加剧。     

锡林郭勒盟近50a降水变化及早涝年分析

利用1961—2010年锡林郭勒盟15个气象站的年及夏季（6—8月）逐月降水量资料,分析了锡林郭勒盟降水的时空变化特征和夏季旱涝年。结果表明：锡林郭勒盟降水量总体上呈南多北少,东多西少的分布特征;近50a降水量没有明显的增减变化趋势,但年际波动特征明显,近10a降水量显著减少。用区域夏季降水指数确定出1998年为涝年,而1980、2001、2005和2010年为夏季旱年。     

我国旬降水量的时空分布特征

用EOF方法分解我国近44a的旬降水场，得知：我国旬降水的6种主要空间型出现的集中时段各不相同，各型均以年际和年内的短周期变化为主，且有各自的长期变化趋势。EOF展开空间型的时间系数间存在显著的统计相关。     

Trends of precipitation extremes during 1960–2008 in Xinjiang, the Northwest China

The spatial–temporal variability of the precipitation extremes defined by eight precipitation indices based on daily precipitation dataset was analyzed using the linear regression method and the Mann–Kendall test. The results indicate that increasing trends in the precipitation amount, rainy days, and the intensity of the extreme precipitation were identified at above 70 % of the total rain stations considered in this study, with more than 30 % of them were significant, while most stations show notable decreasing trend in the annual maximum consecutive no-rain days. Significantly increasing trends of the precipitation extremes are observed mainly in the northern Xinjiang and the north of the southern Xinjiang. Most extreme precipitation indices show a potential regime shift starting from the middle of 1980s. The magnitude of the trends is compatible with their pattern of spatial stability. The generally increasing trends in precipitation extremes are found in this study.     

中国南方夏季降水年际变化与高低纬环流关系的数值模拟

利用区域气候模式RegCM4.4对我国南方夏季降水和大气环流进行30 a的数值模拟,通过与降水观测对比发现,模式能够较好模拟出我国东部地区夏季平均降水和年际变率的空间分布,模拟的南方地区(30 °N以南)年际变率略偏小。观测的我国南方夏季平均降水与模拟降水相关系数为0.51。观测和模拟结果均表明,典型涝年,中纬异常反气旋前方的东北风携带干冷空气,低纬异常反气旋后方的西南风携带暖湿空气,在我国南方汇合,导致南方降水异常增多,模式具有模拟我国夏季南方降水年际变化的能力。通过边界敏感性试验,去除高纬侧边界强迫的年际变化,我国东部降水偏多,南方夏季降水年际变化强度显著变弱;去除低纬度侧边界强迫的年际变化,模拟的我国南方降水偏少,长江及以北降水偏多,降水的空间分布形态发生明显的变化,而我国南方夏季降水年际变化强度基本不变。因此,中高纬环流强迫可较大程度影响我国南方降水年际变化的强度,低纬度环流强迫异常则会改变我国东部降水空间分布形态。      

Intra-seasonal and Inter-annual variability of Bowen Ratio over rain-shadow region of North peninsular India

Intra-seasonal and inter-annual variability of Bowen Ratio (BR) have been studied over the rain-shadow region of north peninsular India during summer monsoon season. Daily grid point data of latent heat flux (LHF), sensible heat flux (SHF) from NCEP/NCAR Reanalysis for the period 1970–2014 have been used to compute daily area-mean BR. Daily grid point rainfall data at a resolution of 0.25° × 0.25° from APHRODITE’s Water Resources for the available period 1970–2007 have been used to study the association between rainfall and BR. The study revealed that BR rapidly decreases from 4.1 to 0.29 in the month of June and then remains nearly constant at the same value (≤0.1) in the rest of the season. High values of BR in the first half of June are indicative of intense thermals and convective clouds with higher bases. Low values of BR from July to September period are indicative of weak thermals and convective clouds with lower bases. Intra-seasonal and inter-annual variability of BR is found to be inversely related to precipitation over the region. BR analysis indicates that the land surface characteristics of the study region during July–September are similar to that over oceanic regions as far as intensity of thermals and associated cloud microphysical properties are concerned. Similar variation of BR is found in El Nino and La Nina years. During June, an increasing trend is observed in SHF and BR and decreasing trend in LHF from 1976 to 2014. Increasing trend in the SHF is statistically significant.

     

Evaluation of spatial and temporal characteristics of rainfall in Malawi: a case of data scarce region

This paper presents the methods, procedure and results in studying spatial and temporal characteristics of rainfall in Malawi, a data scarce region, between 1960 and 2006. Rainfall variables and indicators from rainfall readings at 42 stations in Malawi, excluding Lake Malawi, were analysed at monthly, seasonal and annual scales. In the study, the data were firstly subjected to quality checks through the cumulative deviations test and the standard normal homogeneity test. Spatial rainfall variability was investigated using the spatial correlation function. Temporal trends were analysed using Mann?CKendall and linear regression methods. Heterogeneity of monthly rainfall was investigated using the precipitation concentration index (PCI). Finally, inter-annual and intra-annual rainfall variability were tested using normalized precipitation anomaly series of annual rainfall series (|AR|) and the PCI (|APCI|), respectively. The results showed that (1) most stations revealed statistically non-significant decreasing rainfall trends for annual, seasonal, monthly and the individual months from March to December at the 5% significance level. The months of January and February (the highest rainfall months), however, had overall positive but statistically non-significant trends countrywide, suggesting more concentration of the seasonal rainfall around these months. (2) Spatial analysis results showed a complex rainfall pattern countrywide with annual mean of 1,095?mm centred to the south of the country and mean inter-annual variability of 26%. (3) Spatial correlation amongst stations was highest only within the first 20?km, typical of areas with strong small-scale climatic influence. (4) The country was further characterised by unstable monthly rainfall regimes, with all PCIs more than 10. (5) An increase in inter-annual rainfall variability was found.     

Spatial and temporal variability of precipitation indices during 1961–2010 in Hunan Province,central south China

Based on daily precipitation records at 75 meteorological stations in Hunan Province, central south China, the spatial and temporal variability of precipitation indices is analyzed during 1961–2010. For precipitation extremes, most of precipitation indices suggest that both the amount and the intensity of extreme precipitation are increasing, especially the mean precipitation amount on a wet day, showing a significant positive trend. Meanwhile, both of the monthly rainfall heterogeneity and the contribution of the days with the greatest rainfall show an upward trend. When it comes to rainfall erosivity, most of this province is characterized by high values of annual rainfall erosivity. Although the directions of trends in annual rainfall erosivity at most stations are upward, only 6 of the 75 stations have significant trends. Furthermore, the spatial and temporal variation of dryness/wetness has been assessed by the standardized precipitation index (SPI). The principal component analysis (PCA) was applied to the SPI series computed on 24-month time scales. The results demonstrated a noticeable spatial variability with three subregions characterized by different trends: a remarkable wet tendency prevails in the central and southern areas, while the northern areas are dominated by a remarkable dry tendency.     

Changes in daily and monthly rainfall in the Middle Yellow River,China

Highly concentrated precipitation, where a large percentage of annual precipitation occurs over a few days, may include a high risk of flooding and severe soil erosion. Thus, areas with severe erosion such as the Loess Plateau in China are particularly vulnerable to highly concentrated precipitation events due to climate change. In this study, we investigated spatial and temporal patterns in the concentration of rainfall in the Middle Yellow River (MYR) from the last 56 years (1958–2013). We used daily and monthly precipitation data from 26 meteorological stations in the study area to calculate the precipitation concentration index (PCI) and the concentration index (CI). The southern and northern parts of the MYR were characterized by a lower CI with a decreasing trend, while the middle parts had a higher CI with an increasing trend. High PCI values occurred in the southern MYR, while lower PCIs with a more homogenous rainfall distribution were found mainly in the northern parts of the MYR. The annual PCI and CI exhibited positive trends at most stations, although only a minority of stations had significant trends (P < 0.05). At seasonal scales, CI exhibited significantly increasing trends in winter at most stations, while a few stations had significant trends in the other three seasons. These findings provide important reference information to facilitate ecological restoration and farming operations in the study region.     

Spatiotemporal patterns of drought at various time scales in Shandong Province of Eastern China

The temporal variations and spatial patterns of drought in Shandong Province of Eastern China were investigated by calculating the standardized precipitation evapotranspiration index (SPEI) at 1-, 3-, 6-, 12-, and 24-month time scales. Monthly precipitation and air temperature time series during the period 1960–2012 were collected at 23 meteorological stations uniformly distributed over the region. The non-parametric Mann-Kendall test was used to explore the temporal trends of precipitation, air temperature, and the SPEI drought index. S-mode principal component analysis (PCA) was applied to identify the spatial patterns of drought. The results showed that an insignificant decreasing trend in annual total precipitation was detected at most stations, a significant increase of annual average air temperature occurred at all the 23 stations, and a significant decreasing trend in the SPEI was mainly detected at the coastal stations for all the time scales. The frequency of occurrence of extreme and severe drought at different time scales generally increased with decades; higher frequency and larger affected area of extreme and severe droughts occurred as the time scale increased, especially for the northwest of Shandong Province and Jiaodong peninsular. The spatial pattern of drought for SPEI-1 contains three regions: eastern Jiaodong Peninsular and northwestern and southern Shandong. As the time scale increased to 3, 6, and 12 months, the order of the three regions was transformed into another as northwestern Shandong, eastern Jiaodong Peninsular, and southern Shandong. For SPEI-24, the location identified by REOF1 was slightly shifted from northwestern Shandong to western Shandong, and REOF2 and REOF3 identified another two weak patterns in the south edge and north edge of Jiaodong Peninsular, respectively. The potential causes of drought and the impact of drought on agriculture in the study area have also been discussed. The temporal variations and spatial patterns of drought obtained in this study provide valuable information for water resources planning and drought disaster prevention and mitigation in Eastern China.     

Large-scale and spatio-temporal extreme rain events over India: a hydrometeorological study

Frequency, intensity, areal extent (AE) and duration of rain spells during summer monsoon exhibit large intra-seasonal and inter-annual variations. Important features of the monsoon period large-scale wet spells over India have been documented. A main monsoon wet spell (MMWS) occurs over the country from 18 June to 16 September, during which, 26.5 % of the area receives rainfall 26.3 mm/day. Detailed characteristics of the MMWS period large-scale extreme rain events (EREs) and spatio-temporal EREs (ST-EREs), each concerning rainfall intensity (RI), AE and rainwater (RW), for 1 to 25 days have been studied using 1° gridded daily rainfall (1951–2007). In EREs, ‘same area’ (grids) is continuously wet, whereas in ST-EREs, ‘any area’ on the mean under wet condition for specified durations is considered. For the different extremes, second-degree polynomial gave excellent fit to increase in values from distribution of annual maximum RI and RW series with increase in duration. Fluctuations of RI, AE, RW and date of occurrence (or start) of the EREs and the ST-EREs did not show any significant trend. However, fluctuations of 1° latitude–longitude grid annual and spatial maximum rainfall showed highly significant increasing trend for 1 to 5 days, and unprecedented rains on 26–27 July 2005 over Mumbai could be a realization of this trend. The Asia–India monsoon intensity significantly influences the MMWS RW.     

Latest update of the climatology and changes in the seasonal distribution of precipitation over China

Based on daily precipitation data from 524 meteorological stations in China during the period 1960–2009, the climatology and the temporal changes (trends, interannual, and decadal variations) in the proportion of seasonal precipitation to the total annual precipitation were analyzed on both national and regional scales. Results indicated that (1) for the whole country, the climatology in the seasonal distribution of precipitation showed that the proportion accounted for 55 % in summer (June–August), for around 20 % in both spring (March–May) and autumn (September–November), and around 5 % in winter (December–February). But the spatial features were region-dependent. The primary precipitation regime, “summer–autumn–spring–winter”, was located in central and eastern regions which were north of the Huaihe River, in eastern Tibet, and in western Southwest China. The secondary regime, “summer–spring–autumn–winter”, appeared in the regions south of the Huaihe River, except Jiangnan where spring precipitation dominated, and the southeastern Hainan Island where autumn precipitation prevailed. (2) For the temporal changes on the national scale, first, where the trends were concerned, the proportion of winter precipitation showed a significantly increasing trend, while that of the other three seasons did not show any significant trends. Second, for the interannual variation, the variability in summer was the largest among the four seasons and that in winter was the smallest. Then, on the decadal scale, China experienced a sharp decrease only in the proportion of summer precipitation in 2000. (3) For the temporal changes on the regional scale, all the concerned 11 geographic regions of China underwent increasing trends in the proportion of winter precipitation. For spring, it decreased over the regions south of the Yellow River but increased elsewhere. The trend in the proportion of summer precipitation was generally opposite to that of spring. For autumn, it decreased over the other ten regions except Inner Mongolia with no trend. It is noted that the interannual variability of precipitation seasonality is large over North China, Huanghuai, and Jianghuai; its decadal variability is large over the other regions, especially over those regions south of the Yangtze River.     

Regional precipitation trend analysis at the Langat River Basin,Selangor, Malaysia

Various hydrological and meteorological variables such as rainfall and temperature have been affected by global climate change. Any change in the pattern of precipitation can have a significant impact on the availability of water resources, agriculture, and the ecosystem. Therefore, knowledge on rainfall trend is an important aspect of water resources management. In this study, the regional annual and seasonal precipitation trends at the Langat River Basin, Malaysia, for the period of 1982–2011 were examined at the 95 % level of significance using the regional average Mann–Kendall (RAMK) test and the regional average Mann–Kendall coupled with bootstrap (RAMK–bootstrap) method. In order to identify the homogeneous regions respectively for the annual and seasonal scales, firstly, at-site mean total annual and separately at-site mean total seasonal precipitation were spatialized into 5 km?×?5 km grids using the inverse distance weighting (IDW) algorithm. Next, the optimum number of homogeneous regions (clusters) is computed using the silhouette coefficient approach. Next, the homogeneous regions were formed using the K-mean clustering method. From the annual scale perspective, all three regions showed positive trends. However, the application of two methods at this scale showed a significant trend only in the region AC1. The region AC2 experienced a significant positive trend using only the RAMK test. On a seasonal scale, all regions showed insignificant trends, except the regions I1C1 and I1C2 in the Inter-Monsoon 1 (INT1) season which experienced significant upward trends. In addition, it was proven that the significance of trends has been affected by the existence of serial and spatial correlations.     

Long-term water budget estimation with the modified distributed model – LISFLOOD-WB over the Lushi basin, China

Summary In a modification of the distributed hydrological model, LISFLOOD-WB, a two-source canopy scheme is used to predict both the canopy transpiration and soil evaporation. A revised soil storage capacity curve from the Xinanjiang model is applied to take into account the sub-grid heterogeneity. The modified model is used to estimate the long-term (1980–1997) water budget of the Lushi basin (4423 km²), China. All the input data fields are integrated in a four-dimensional GIS data structure with a raster grid spacing of 1-km. The basin channel network is determined from digital elevation data, and the spatial pattern of canopy leaf area index (LAI) is retrieved from NOAA/AVHRR NDVI images. Generally, the model efficiency for discharge prediction is acceptable, but the discharges are overestimated in the driest years and underestimated in the wettest years. The results indicated that the influence of inter-annual variation of spatial patterns of LAI detected by NOAA/AVHRR NDVI on the estimates of annual evapotranspiration is negligible. Annually averaged ratios of overland flow, infiltration and canopy interception to precipitation are 24±7%, 56±10% and 20±2%, respectively. The inter-annual variations of precipitation and predicted evapotranspiration are relatively high with standard deviations of 5.1 mm day⁻¹ and 2.4 mm day⁻¹, respectively, whereas the inter-annual variation of the net radiation is much less. Monthly temporal patterns of soil moisture follow precipitation strongly. Spatially precipitation and LAI are both significantly correlated with evapotranspiration, although precipitation has a slightly more dominant control. The linear relationship between water yield and LAI is weak on a grid by grid basis.     

Multiscale evolution of surface air temperature in the arid region of Northwest China and its linkages to ocean oscillations

Reference crop evapotranspiration (ETo) is one of the most important links in hydrologic circulation and greatly affects regional agricultural production and water resource management. Its variation has drawn more and more attention in the context of global warming. We used the Penman-Monteith method of the Food and Agriculture Organization, based on meteorological factors such as air temperature, sunshine duration, wind speed, and relative humidity to calculate the ETo over 46 meteorological stations located in the Yangtze River Delta, eastern China, from 1957 to 2014. The spatial distributions and temporal trends in ETo were analyzed based on the modified Mann-Kendall trend test and linear regression method, while ArcGIS software was employed to produce the distribution maps. The multiple stepwise regression method was applied in the analysis of the meteorological variable time series to identify the causes of any observed trends in ETo. The results indicated that annual ETo showed an obvious spatial pattern of higher values in the north than in the south. Annual increasing trends were found at 34 meteorological stations (73.91 % of the total), which were mainly located in the southeast. Among them, 12 (26.09 % of the total) stations showed significant trends. We saw a dominance of increasing trends in the monthly ETo except for January, February, and August. The high value zone of monthly ETo appeared in the northwest from February to June, mid-south area from July to August, and southeast coastal area from September to January. The research period was divided into two stages—stage I (1957–1989) and stage II (1990–2014)—to investigate the long-term temporal ETo variation. In stage I, almost 85 % of the total stations experienced decreasing trends, while more than half of the meteorological stations showed significant increasing trends in annual ETo during stage II except in February and September. Relative humidity, wind speed, and sunshine duration were identified as the most dominant meteorological variables influencing annual ETo changes. The results are expected to assist water resource managers and policy makers in making better planning decisions in the research region.     

Spatiotemporal variations in rainfall erosivity during the period of 1960–2011 in Guangdong Province,southern China

Rainfall erosivity, which shows a potential risk of soil loss caused by water erosion, is an important factor in soil erosion process. In consideration of the critical condition of soil erosion induced by rainfall in Guangdong Province of southern China, this study analyzed the spatial and temporal variations in rainfall erosivity based on daily rainfall data observed at 25 meteorological stations during the period of 1960–2011. The methods of global spatial autocorrelation, kriging interpolation, Mann–Kendall test, and continuous wavelet transform were used. Results revealed that the annual rainfall erosivity in Guangdong Province, which spatially varied with the maximum level observed in June, was classified as high erosivity with two peaks that occur in spring and summer. In the direction of south–north, mean annual rainfall erosivity, which showed significant relationships with mean annual rainfall and latitude, gradually decreased with the high values mainly distributed in the coastal area and the low values mainly occurring in the lowlands of northwestern Guangdong. Meanwhile, a significant positive spatial autocorrelation which implied a clustered pattern was observed for annual rainfall erosivity. The spatial distribution of seasonal rainfall erosivity exhibited clustering tendencies, except spring erosivity with Moran’s I and Z values of 0.1 and 1.04, respectively. The spatial distribution of monthly rainfall erosivity presented clustered patterns in January–March and July–October as well as random patterns in the remaining months. The temporal trend of mean rainfall erosivity in Guangdong Province showed no statistically significant trend at the annual, seasonal, and monthly scales. However, at each station, 1 out of 25 stations exhibited a statistically significant trend at the annual scale; 4 stations located around the Pearl River Delta presented significant trends in summer at the seasonal scale; significant trends were observed in March (increasing trends at 3 stations), June (increasing trends at 4 stations located in the Beijiang River Basin), and October (decreasing trends at 4 stations) at the monthly scale. In accordance with the mean annual rainfall over Guangdong Province, the mean annual rainfall erosivity showed two significant periodicities of 3–6 and 10–12 years at a confidence level of 95 %. In conclusion, the results of this study provide insights into the spatiotemporal variation in rainfall erosivity in Guangdong Province and support for agrolandscape planning and water and soil conservation efforts in this region.     

1961-2014年石家庄地区降水量的时空变化特征

利用石家庄地区5个代表站1961-2014年的逐日降水资料,采用多种统计分析方法,分析了石家庄地区降水量的时空变化特征,结果表明石家庄地区年降水量从20世纪70年代开始下降,80年代达到最低,90年代有所增加,但也没有明显的上升趋势,21世纪初又开始下降.20世纪70年代降水量的减少春季和秋季贡献最大,80年代降水量的减少和90年代降水量的增加主要是夏季的贡献.石家庄地区年降水量起伏较大,1963年降水量最多,为1038.4 mm,2014年最少,仅为276.2 mm.近54年石家庄年降水量在波动中呈现下降趋势,线性趋势为-11.0 mm/（10 a）,但下降趋势并不明显.石家庄北部年降水量呈上升趋势,市区及东部、南部和西部年降水量均呈下降趋势,变化趋势均不明显.近54年,石家庄春季降水量呈上升趋势,线性趋势为0.9 mm/（10 a）,夏季、秋季和冬季降水量均呈下降趋势,线性趋势分别为-11.9,-1.1和-0.3 mm/（10 a）,上升或下降趋势均不明显.夏季降水减少是导致石家庄年降水减少的主要原因.石家庄四季降水量变化趋势的空间分布具有明显的季节特征和区域特征.石家庄四季降水量均存在显著周期变化.