我国冰粒降水天气的观测特征统计分析

研究冰粒降水天气的特征对于更好地认识冰冻天气,提高冰冻天气的预警预报能力有重要意义,但我国相关研究较少。利用2011—2013年中国民航机场的例行观测、特殊观测资料,分析了冰粒降水天气的时空分布、持续时间和地面气象要素等特征。选取2001—2013年50个探空站资料分析了冰粒的垂直环境特征。结果表明:冰粒降水天气集中分布在中纬度的黄河下游、长江中下游地区。冰粒降水发生的次数与其持续时间相关性不强,在少发区,其持续时间也可能较长;冰粒降水天气在1—2月比较常见,单次冰粒降水天气过程的持续时间比较短,一般不超过1 h;我国冰粒天气发生时,同时常会有轻雾或无其他天气情况,一般很少伴随有雪。冰粒的融化参数一般小于冻雨的融化参数,但冰粒冻结参数一般大于冻雨的冻结参数。在冰粒天气发生之前一般温度逐渐降低、气压逐渐升高。冰粒天气发生前后湿度都比较大,发生期间风速变化比较小。     

Scaling of tropical rainfall as observed by TRMM precipitation radar

We used a three-year (1998–2000) dataset of TRMM Precipitation Radar observations to investigate the scaling properties of spatial rainfall fields. This dataset allows consideration of spatial scales ranging from about 4.3 km to 138 km and short temporal scales corresponding to the sensor overpasses. The focus is on the marginal spatial moment scaling, which allows estimation of the scaling parameters from a single scene of data. Here we present a global perspective of the scaling properties of tropical rainfall in terms of its spatial variability, atmospheric forcing, predictability, and applicability. Our results reveal the following: 1) the scaling parameters exhibit strong variability associated with land/ocean contrast and mean precipitation at the synoptic scale; 2) there exists a one-to-one relationship between the scaling parameters and the large-scale spatial average rain rate of a universal functional form; 3) the majority of the scenes are consistent with the hypothesis of scale invariance at the moment orders of 0 and 2; 4) relatively there are more scale-invariant rain scenes over land than over ocean; and 5) for the scenes that are non-scale-invariant, deviation from scale-invariance mainly arises from the increasingly intermittent behavior of rainfall as spatial scale decreases. These results have important implications for the development and calibration of downscaling procedures designed to reproduce rainfall properties at different spatial scales and lead to a better understanding of the nature of tropical rainfall at various spatial resolutions.     

Parsivel激光雨滴谱仪观测降水中异常数据的判别及处理

2009年利用Parsivel激光雨滴谱仪连续观测太湖地区自然降水,发现对流云降水采样的粒子谱数据常常包含有少数异常高、低数据.从Parsivel激光雨滴谱仪的测量原理出发,分析了产生测量误差的原因.然后依据3σ准则(莱以特准则)对采集的一次对流云降水粒子谱数据进行分析,对其是否存在粗大误差进行判别和消除.结果表明:异常数据即为仪器测量的粗大误差,消除误差后的数据在表征降雨量、雷达反射率因子等降水特征量时更加接近于仪器自身输出值.同样地将此方法用来分析层状云降水,有利于消减仪器测量中粒子重叠所造成误差.     

西南地区极端降水变化趋势

利用西南地区90个气象台站1970-2010年逐日降水量资料,依据世界气象组织(WMO)定义的连续5d最大降水量、总降水量、强降水比等6种极端降水指数,采用F检验、11a滑动平均等统计方法,研究了西南地区极端强降水变化趋势的时空变化特征。在时间上,西南地区近41年来冬、春、夏季连续5d最大降水量缓慢波动上升,秋季连续5d最大降水量呈下降趋势;强降水、降水强度及强降水比呈上升趋势,但总降水量和最长持续无降水日数呈减少趋势;另外,各极端降水指数还存在明显的年际、年代际变化。在空间上,西南地区极端降水变化趋势具有显著的地域差异,呈东西或西北东南向梯度变化特征。其中冬季连续5d最大降水量、降水强度、强降水比及最长持续无降水日数,在西南大部分地区呈增加趋势。秋季连续5d最大降水量与总降水量在西南大部分地区呈减少趋势。而春、夏季连续5d最大降水量和强降水的增减区域大致相当。     

新一代天气雷达定量降水估测集成系统

中国国家气象信息中心研制的多源融合实况分析1 km网格降水(简称为ART_1 km降水)产品可为灾害性天气监测预警、智能网格预报、智慧气象服务等提供更精细的数据支撑。选取广东省2019—2022年5—8月的20例致灾暴雨过程,利用未融合制作ART_1 km降水产品的区域站和水文站等两类独立站的降水资料,评估ART_1 km降水产品在暴雨过程中的准确性。结果表明：ART_1 km降水产品成功反映了广东省暴雨过程的降水落区、强度和变化趋势,且在珠三角、粤东东部和粤北北部表现最佳。降水越强,两类独立站的ART_1 km降水和观测降水的相关性越高,但均方根误差和平均值误差也越大。降水不分级时,全省约60%的独立站的ART_1 km降水和观测降水的相关系数≥0.8,超90%的独立站的均方根误差在[1.0, 5.0) mm范围内,超60%的独立站的平均值误差在±0.1 mm内。降水分级后,当小时降水较弱（< 5 mm）,全省大部分独立站的相关系数 < 0.5、均方根误差在[1.0, 5.0) mm范围内、平均值误差在[0.0, 0.5]mm范围内;当小时降水较强(≥20 mm),全省42%~56%的独立站的相关系数≥0.5,大部分独立站的均方根误差≥10 mm、平均值误差 < 0mm (且当小时降水≥50 mm,平均值误差 < -10 mm)。两类独立站的ART_1 km降水总体表现为低估,更多的站点观测融入制作ART_1 km降水产品,将有助于提升该产品的质量。

     

Temperature and precipitation of Alaska: 50 year trend analysis

Summary  Temperature and precipitation records from 1949 to 1998 were examined for 25 stations throughout the State of Alaska. Mean, maxima, and minima temperatures, diurnal temperature range, and total precipitation were analyzed for linear trends using least squares regressions. Annual and seasonal mean temperature increases were found throughout the entire state, and the majority were found to be statistically significant at the 95% level or better. The highest increases were found in winter in the Interior region (2.2 °C) for the 50 year period of record. Decreases in annual and seasonal mean diurnal temperature range were also found, of which only about half were statistically significant. A state-wide decrease in annual mean diurnal temperature range was found to be 0.3 °C, with substantially higher decreases in the South/Southeastern region in winter. Increases were found in total precipitation for 3 of the 4 seasons throughout most of Alaska, while summer precipitation showed decreases at many stations. Few of the precipitation trends were found to be statistically significant, due to high interannual variability. Barrow, our only station in the Arctic region, shows statistically significant decreases in annual and winter total precipitation. These findings are largely in agreement with existing literature, although they do contradict some of the precipitation trends predicted by the CO₂-doubling GCM’s. Received August 30, 1999/Revised March 21, 2000     

Nonparametric kernel estimation of annual precipitation over Iran

In this paper, annual precipitation data sets from five old rain gauge stations (Bushehr, Isfahan, Meshed, Tehran, and Jask) in Iran were fitted to nonparametric kernel function by using rectangular, triangular, and Gaussian or normal as kernel functions. The smoothing parameter was calculated by four methods including rule of thumb, Adamowski criterion, least squares cross-validation, and Sheater and Jones plug-in. The Adamowski criterion showed a better performance compared to other methods due to goodness of fit tests. The results of these proposed nonparametric methods will be then compared to the results of the parametric density functions including normal, two and three parameter log-normal, two parameter gamma, Pearson and log-Pearson type 3, Gumbel or extreme value type 1 and also Fourier series method which were applied by a previous study for the same stations. It was concluded that the annual precipitation data were fitted to nonparametric methods better than parametric methods.     

长江流域极端降水过程事件的年内分布特征

基于1960-2016年乌江流域41个气象站的逐日降水观测资料,利用线性倾向估计、滑动平均、累积距平等方法计算趋势系数和气候趋势,分析了研究时段内乌江流域年暴雨等级面雨量、年平均最大日降水量、年平均极端持续强降水次数和对应降水量的时空分布特征,分析表明：（1）乌江流域年暴雨等级面雨量和日数呈显著增加趋势（均通过α=0.05显著性水平检验）,而暴雨强度呈不显著性增加趋势;5-10月各旬暴雨等级面雨量及日数变化基本一致,5月中旬至8月上旬呈单峰型分布,暴雨强度呈波动增减分布。（2）近57 a乌江流域年平均最大日降水量年代际变化比较明显。（3）乌江流域发生极端持续强降水年平均次数呈不显著的减少趋势,但极端持续强降水量呈不显著的增加趋势。采用耿贝尔极值Ⅰ型分布法计算了乌江流域5个代表站不同重现期日最大降水量值,发现不同站点日极端最大降水量重现期水平差异明显,重现期时间尺度存在临界点,约为50 a。

     

中国近50 a极端降水事件变化特征的季节性差异

强降水极易造成暴雨灾害,尤其是突发性强的短时强降水,动态监测、影响评估和风险预估是灾害防御的重要手段。但目前气象服务业务中,强降水的定量评估和风险预估还是以天为单位,现代气象服务精细化的需求迫切要将时间分辨率提升至小时尺度。本文利用1951-2018年国家气象观测站小时降水观测资料,从小时尺度界定站点、大区域、小区域降水过程的辨识方法。基于改进的降水过程综合强度评估方法,在概率密度分布的基础上,重新划分了极端、特强、强、较强、中等五个等级的降水过程综合强度指数。检验论证显示,基于小时分辨率降水过程的自动提取和评估方法合理,具有可操作性,能够对过程性降水、短时降水过程动态评估和预评估,可实时支撑气象服务业务,提升气象防灾减灾能力,也为后续开展短时强降水影响评估和风险预估建立基础。

     

威宁县气候评述及近期降水动态

威宁县有气候资料近60年,气候经历了前暖期一平温过渡期一冷期一后暖期。前暖期到冷期为湿润期,后暖期为干暖期。过渡期到冷期气候特别反常,旱、涝交替,低温霜灾、冷涝重迭,自然灾害频繁,大灾年均在该期,本文叙述了冷暖期灾变对农业生产的影响。     

Long-term trend and variability of precipitation in Chhattisgarh State,India

Spatial and temporal precipitation variability in Chhattisgarh State in India was examined by using monthly precipitation data for 102 years (1901–2002) from 16 stations. The homogeneity of precipitation data was evaluated by the double-mass curve approach and the presence of serial correlation by lag-1 autocorrelation coefficient. Linear regression analysis, the conventional Mann–Kendall (MK) test, and Spearman’s rho were employed to identify trends and Sen’s slope to estimate the slope of trend line. The coefficient of variation (CV) was used to analyze precipitation variability. Spatial interpolation was done by a Kriging process using ArcGIS 9.3. Results of both parametric and non-parametric tests and trend tests showed that at 5 % significance level, annual precipitation exhibited a decreasing trend at all stations except Bilaspur and Dantewada. For both annual and monsoon precipitation, Sen’s test showed a decreasing trend for all stations, except Bilaspur and Dantewada. The highest percentage of variability was observed in winter precipitation (88.75 %) and minimum percentage variability in annual series (14.01 %) over the 102-year periods.     

基于不同海拔高度的雷达降水估测试验

在国内外雷达定量估测区域降水量一些方法基础上,将降水类型、地理位置和海拔高度同时纳入考虑范畴,在成都CINRAD/SC雷达站(海拔高度596.5 m)200 km范围内选择实验区,并按海拔高度将所选区域分为3区。然后利用2010年7—8月的雷达体扫资料以及同时段、同时次的雨量计数据,采用最优化算法分别在每个区域内修订传统Z-I关系中的"A,b"系数,以得到不同海拔地区的Z-I关系和每小时雨量估测值。研究表明,与直接采用传统的Z-I关系定量测量降水相比,各个区域内,经改善后的Z-I关系准确率提高了20%左右,算法相对简单,适合业务使用。     

江苏省雷达降水估测集合分析

使用2019年、2020年5—8月江苏省降水分析场及站点观测资料,生成具有定量降水估测(Quantitative Precipitation Estimation, QPE)不确定性时间和空间结构的集合QPE,并用观测降水对集合QPE进行了确定性和概率性检验。确定性验证说明集合QPE能在总体上减小降水量的绝对误差和均方根误差,但也加重了某些区域的降水低估。集合平均能提高估测降水的准确率并减小空报率,也会使漏报增多,这使小雨的TS评分有所降低,但各量级降水TS评分仍能保持在较高水平。集合QPE对各量级降水都有较优的Brier评分,降水量级越大,估测效果越好。集合的离散度较小,且将集合成员排序后,观测值落在两头的频率更高,也反映了离散度偏小。此外,观测值大于集合成员最大值的频率更高,说明集合QPE倾向于低估降水。随着概率阈值的增大,集合估测降水发生的命中率(POD)和假警报率(POFD)逐渐增大,但POD增大的程度比POFD大得多,使相对作用特征曲线为折线。不同概率阈值下的POD和POFD体现了集合QPE对各量级降水都有较高的估测技巧,其中对小雨和中雨分辨能力最好。集合估测小雨和特大暴雨发...     

Probabilistic projections of regional temperature and precipitation extending from observed time series

Probabilistic projections of change in regional temperature and precipitation previously derived allow for the range of sensitivities to global warming simulated by CMIP3 models. However, the changes were relative to an idealized base climate for 1980–1999, disregarding observed trends, such as those in rainfall in some Australian regions. Here we propose a method that represents projections for both forced change and decadal means as time series that extend from the observed series, illustrated using data for central Victoria. The main idea is to estimate the time-evolving underlying (or forced) past climate then convert this to a series of absolute values, by using the mean of the full observational record. We again use the pattern scaling assumption, and combine the CMIP3 sensitivities used for future change with a global warming series beginning at 1900. Like the confidence interval of regression theory, the analysis gives an estimate of the range of the underlying climate at each decade. This range can be augmented to allow for natural variability. A Bayesian theory can be applied to combine the model-based sensitivity with that estimated from observations. The time series are modified and the persistence of current observed anomalies considered, ultimately merging the probabilistic projections with the observed record. For some other cases, such as rainfall in southwest and north Australia and temperature in the state of Iowa, the two sensitivity estimates appear less compatible, and possible additional forcings are considered. Examples of the potential use of such time series are presented.     

Climatology and trend analysis of extreme precipitation in subregions of Northeast Brazil

The present paper aims of computing climatology and trend analysis of occurrence and intensity of extreme events of precipitation in subregions of Northeast Brazil (NEB). We used daily rainfall data of 148 rain gauges collected from the hydrometeorological network managed by the National Water Agency during 1972 to 2002 and used quantiles technique in order to select rainfall events. Defining heavy rainfall events as those when at least one rain gauge recorded rainfall above the 95th percentile, normal rainfall was between the 45th and 55th percentiles, and weak rainfall events were under the 5th percentile. The Mann-Kendall nonparametric test was used to calculate the linear trend of the quantity and intensity of rainfall events. The NEB was divided in five subregions using the cluster analysis based on Euclidean distance and Ward’s method: Northern coast, Northern semiarid, Northwest, Southern semiarid, and Southern coast. The results suggest that the subregions are less influenced by El Niño and La Niña, and dry areas have higher variability, with the greatest number of intense events.     

SST and circulation trend biases cause an underestimation of European precipitation trends

Clear precipitation trends have been observed in Europe over the past century. In winter, precipitation has increased in north-western Europe. In summer, there has been an increase along many coasts in the same area. Over the second half of the past century precipitation also decreased in southern Europe in winter. An investigation of precipitation trends in two multi-model ensembles including both global and regional climate models shows that these models fail to reproduce the observed trends. In many regions the model spread does not cover the trend in the observations. In contrast, regional climate model (RCM) experiments with observed boundary conditions reproduce the observed precipitation trends much better. The observed trends are largely compatible with the range of uncertainties spanned by the ensemble, indicating that the boundary conditions of RCMs are responsible for large parts of the trend biases. We find that the main factor in setting the trend in winter is atmospheric circulation, for summer sea surface temperature (SST) is important in setting precipitation trends along the North Sea and Atlantic coasts. The causes of the large trends in atmospheric circulation and summer SST are not known. For SST there may be a connection with the well-known ocean circulation biases in low-resolution ocean models. A quantitative understanding of the causes of these trends is needed so that climate model based projections of future climate can be corrected for these precipitation trend biases.     

近50 a来中国不同流域降水的变化趋势分析

利用我国612个气象站1961—2010年逐日降水量资料,借助地理信息系统Arc GIS,分析了我国十大流域的年、季节降水量的时空变化趋势特征。结果表明,我国降水主要集中在珠江、东南诸河和长江流域,西北诸河流域降水最少;四季降水量与年降水量的空间分布特征高度相似;降水量均为夏季最多,冬季最少。就年降水量而言,西北诸河流域有变湿趋势,海河流域和黄河流域有变干趋势。就降水季节而言,西南诸河、松花江、西北诸河流域春季有变湿趋势;东南诸河流域和长江流域夏季有变湿趋势,海河流域和西南诸河流域夏季有变干趋势;西北诸河流域秋季有变湿趋势,长江流域、黄河流域和淮河流域秋季有变干趋势;松花江流域、西北诸河流域和长江流域冬季有变湿趋势。