Machine Learning of Weather Forecasting Rules from Large Meteorological Data Bases

Discovery of useful forecasting rules from observational weather data is an outstanding interesting topic.The traditional methods of acquiring forecasting knowledge are manual analysis and investigation performed by human scientists.This paper presents the experimental results of an automatic machine learning system which derives forecasting rules from real observational data.We tested the system on the two large real data sets from the areas of centra! China and Victoria of Australia.The experimental results show that the forecasting rules discovered by the system are very competitive to human experts.The forecasting accuracy rates are 86.4% and 78% of the two data sets respectively     

一维热扩散湖模式在太湖的应用研究

利用在太湖获得的2010年8月11-28日的观测资料研究了一维热扩散湖模式在太湖的适用性,通过对比模拟进一步研究了影响太湖湖表温度模拟的主要因子。该湖模式对太湖最初的模拟结果并不理想,模拟的湖表面温度与观测有较大的系统性偏差,温度的日变化幅度与观测相比也偏小。通过分析该模式对太湖的模拟效果不理想的可能原因,针对太湖的生态环境和污染情况,设计了18个测试参数的敏感性试验,从敏感性试验的结果分析得到,适用于太湖的、依赖于湖泊类型的3个参数应做如下修改:消光系数（η₀）应放大3倍,湖泊表层吸收的太阳辐射系数（β）应取0.8,粗糙长度（z₀）采用公式计算得到。用新得到的适用于太湖的3个参数,模拟得到的结果与最初的模拟结果和观测资料对比,发现采用新的参数后,模拟结果比最初的模拟结果有了很大的改进,模拟的湖表温度基本接近观测,模拟的湖水垂直剖面时间序列图也跟观测吻合得较好,随之的感热、潜热通量的模拟也都与观测接近。最后,对输入湖模式的主要大气参量（太阳辐射、2 m气温及风场）±10%的误差引起的模式模拟的湖表面温度误差进行分析,结果表明该湖模式对大气强迫场的误差敏感度不高;相比之下,模拟结果对风场敏感性最小,对辐射和气温的敏感度相当。     

一维热扩散湖模式在太湖的应用研究

太湖微气候条件及局地热环境的研究对于太湖周边城市地区可持续发展以及大气宏观调控具有重要意义。为了更准确模拟太湖湖-气交换,将CLM4-LISSS浅水湖泊陆面过程参数化方案耦合进入WRF中的Noah陆面过程模型。采用太湖湖上平台及岸边陆上测站观测的数据,评估了CLM4-LISSS浅水湖泊过程方案对太湖区域近地层气象条件的模拟性能。并基于耦合模型模拟研究了太湖对周边城市区域热环境的影响。结果表明,CLM4-LISSS湖泊陆面过程方案模拟的湖表面温度能反映真实温度的变化趋势。两种陆面过程方案在2 m气温的模拟值也存在一定的差异。CLM4-LISSS与Noah方案计算所得湖上2 m气温的模拟值与观测值的平均均方根误差分别为1.77和2.22℃,平均相关系数分别为0.88和0.84;模拟10 m风速的平均均方根误差分别为1.93和2.78 m/s,平均相关系数为0.72和0.68。太湖对周边城市热环境存在明显的影响。8月太湖对周边地区15时（北京时）近地层平均降温0.5-0.7℃,影响范围达60 km。06时太湖导致周边近地层平均升温达0.7-1℃,影响范围达50 km。湖风带来的冷空气抑制了城市热岛的垂直运动,在高温天气下使得苏州、无锡和常州城市地区昼间边界层下降高度可达300、400和100 m。无锡地区边界层内气温最高降幅可达0.5-0.7℃。通过选取无锡地区2015年8月28日高温小风天气作为背景条件,分析该地区湖风对城市热岛环流的影响机制。结果表明湖风能够破坏无锡地区的热岛环流结构,改变近地面热量和水汽的分布,抑制城市热岛的垂直发展,并影响至整个无锡地区。局地热力环流的变化对于局地气候以及污染物质的输送与扩散有可能产生重要影响,准确的湖泊陆面过程参数化方案对于天气预报、空气污染模拟,以及气候模拟研究等均具有重要意义。     

2012年太湖蒸发量变化特征及蒸发模型评估研究

湖泊蒸发是全球能量分布,水文循环的重要组成部分,同时是气候及生态系统环境变化的指示因子。运用太湖湖上观测平台大浦口站2012年涡度相关数据分析了太湖蒸发量的月变化及日变化特征,并评估了11种蒸发模型。结果表明：太湖2012年总蒸发量为1066.2 mm。潜热通量是太湖净辐射能量分配中的主导项, 2012年太湖地区潜热通量占净辐射通量的91.9%。2～7月为太湖水体储热阶段,当净辐射在7月达到最大值时,蒸发值也达到最大值;净辐射8月开始减少,至12月达到最小值,期间湖体储热释放,使得蒸发量在2月才达到最小值。采用涡度相关系统观测太湖蒸发量的数据评估了11种蒸发模型,分别从年蒸发总量和蒸发量月变化特征来探讨模型对于太湖蒸发量计算的适用性,其中以波文比能量平衡模型表现最好,与涡度相关观测值的相关系数为0.99,中心化均方根误差为4.50 mm month^-1。     

Accumulation Dynamics of Polycyclic Aromatic Hydrocarbons in Lake Baikal Bottom Biocenoses Assessed from Biogeochemical Monitoring Data

The results of long-term biogeochemical monitoring of Lake Baikal are presented. The accumulation is studied of polycyclic aromatic hydrocarbons (PAHs) in bottom sediments and macrozoobenthos that were synchronously sampled at the same stations. The stations are located in the areas where anthropogenic impact on the lake is high: in the area of the former Baikal Pulp and Paper Mill (BPPM), in the footprint of the BAM railway in the north of the lake and in the Selenga River delta front as well as in the zones of coastal fouling in the area of BPPM. It is found that variations in the concentration of PAHs in macrozoobenthos do not directly depend on those in the sediments. It is revealed that the maximum concentration of benzo[a]pyrene in the area of the former BPPM is almost by eight times higher than in the other areas of the lake; shallow-water macrophytes accumulate more polyarenes than deep-water macrozoobenthos.     

临太湖局地平原区人居环境的自然适宜性评价——以吴江区为例

本文以苏州市吴江区为例,利用1971—2016年吴江区常规气象观测资料、2004—2016年吴江区自动气象观测数据、2016年吴江区各镇人口和面积数据、2016年ASTER GDEM 高程数据和Landsat 8 OLI_TIRS卫星遥感数据,将湖陆风指数引入人居自然环境适宜性评价体系,建立缓冲区后,分别计算气候适宜性指数、地被指数、水文指数、湖陆风指数和人居环境自然适宜性综合指数,在此基础上,分区分级评价了吴江区人居环境的自然适宜性。研究结果表明:(1)吴江区人居环境自然适宜度从西部往东部逐渐递减。(2)一般适宜区主要位于吴江区的东北部和东南局地,中度适宜区分布在中北部和南部,较高适宜区位于中部以西太湖沿岸,高度适宜区位于紧临太湖的西南地区,极高适宜区位于西南角局部地区。(3)引入湖陆风指数后,评价结果能更好地反映临湖平原的湖陆风环流对局地气候所起的关键作用。(4)建立缓冲区后的水文指数分布能够更客观地反映吴江区不同尺度水体分布对人居环境自然选择的影响。     

人工神经网络算法在红外高光谱资料反演大气温度廓线中的应用

基于红外高光谱大气探测器AIRS实况观测资料,尝试用人工神经网络算法来实现晴空时大气的温度垂直廓线反演,重点将该算法与目前已经发展比较成熟的特征向量统计反演算法进行比较。结果表明,两种算法在计算时间效率和反演精度上相当。鉴于人工神经网络算法的统计物理本质,误差反向传播BP神经网络可以求解非线性问题,在优化训练样本和继续调试网络种类和网络参数的基础上,有望能进一步提高反演精度。     

用FY-1C/CAVHRR数据估算巢湖蓝藻叶绿素的含量

以巢湖为实验区，以气象卫星FY－1C／CAVHRR数据为信息源，通过遥感监测值与（淮）同步湖区实地采样叶绿素α(chl-α)含量的对比分析，建立基于FY－1C／CAVHRR数据的叶绿素α含量遥感估算模型。研究表明，FY－1C气象卫星可用于内陆大面积湖泊湖面叶绿素含量的遥感监测，在动态监测方面有明显优势，可作为现有湖泊水质采样观测的补充手段。     

利用ATSR/ERS-1资料研究复杂下垫面比辐射率的变化

一定精度地表温度的取得不仅依赖于较好的大气订正,而且还取决于比辐射率随波谱及角度变化的知识。利用AVHRR植被指数资料,参数化了星下点的比辐射率值,得到了对于包括沙漠、绿州、戈壁等不同类型的复杂下垫面上的星下点比辐射率的值。结合ATSR的双角度技术,计算了复杂地形条件下前向地表比辐射率,给出了一种利用ATSR资料获得有关地表比辐射率信息的新方法。     

利用ATSR/ERS-1资料研究复杂下垫面比辐射率的变化

一定精度地表温度的取得不仅信赖于较好的大气订正,而且还取决于比辐射率随波主角度变化的知识。利用ＡＶＨＲＲ植被指数资料,参数化了星下点的比辐射率值,得到了对于包括沙漠,绿洲,戈壁等不同类型的复杂下垫面上的星下点比辐射率的值。     

An Assessment of the Quality of Surface Sensible Heat Flux Derived from Reanalysis Data through Comparison with Station Observations in Northwest China

The present study compares seasonal and interdecadal variations in surface sensible heat flux over Northwest China between station observations and ERA-40 and NCEP-NCAR reanalysis data for the period 1960-2000.While the seasonal variation in sensible heat flux is found to be consistent between station observations and the two reanalysis datasets,both land-air temperatures difference and surface wind speed show remarkable systematic differences.The sensible heat flux displays obvious interdecadal variability that is season-dependent.In the ERA-40 data,the sensible heat flux in spring,fall,and winter shows interdecadal variations that are similar to observations.In the NCEP-NCAR reanalysis data,sensible heat flux variations are inconsistent with and sometimes even opposite to observations.While surface wind speeds from the NCEP-NCAR reanalysis data show interdecadal changes consistent with station observations,variations in land-air temperature difference differ greatly from the observed dataset.In terms of land-air temperature difference and surface wind speed,almost no consistency with observations can be identified in the ERA-40 data,apart from the land-air temperature difference in fall and winter.These inconsistencies pose a major obstacle to the application in climate studies of surface sensible heat flux derived from reanalysis data.     

Forecasting the evolution in the mixing regime of a deep subalpine lake under climate change scenarios through numerical modelling (Lake Maggiore,Northern Italy/Southern Switzerland)

Climate Dynamics - The impact of air temperature rise is eminent for the large deep lakes in the Italian subalpine district, climate change being caused there by both natural phenomena and...     

Multifractal analysis of 1-min summer rainfall time series from a monsoonal watershed in eastern China

Multifractal analysis can provide parameters associated with different scales of rainfall, which may be useful for setting up parsimonious downscaling models of rainfall, or for revealing climate-specific properties. Time series of rain rate with 1-min resolution collected from ten stations over a monsoon watershed in eastern China were used to study the multifractal properties. The power spectra estimated by fast Fourier transform (FFT) and discrete Haar wavelet transform (DWT) showed three scaling regimes: the sub-hourly scaling regime with β?≈?1.2, the scaling regime from 1 h to 1 day with β close to 0.6, and the low-frequency spectra plateau with β?≈?0.1. From the hyperbolic tails of exceeding probability distributions, the estimated values of parameter q _c are in 2–2.5, which were consistent with the critical order of K(q) curves. The statistical moments display two main scaling regimes: the high-frequency regime from 3 min to 5 days and the scaling regime beyond 5 days. The scales of 5–10 days seem a transitional regime. The reason that the regimes, revealed by the power spectra, disagree with the statistical moments may be that both FFT and DWT power spectra have limited abilities of analyzing low-frequency scaling but are sensitive to the properties in high-frequency scales. The H values estimated for the regime of sub-hourly scales are larger than 0.4, and the values for the regime 1 h–1 day are close to 0.1. For the low-frequency scales beyond 1 day, negative H is obtained by DWT power spectra. The parameters of universal multifractal models were also estimated. The values of α for the scaling range of 1 min–5 days are 0.486?±?0.047, and for the low-frequency scaling range, its values are 0.808?±?0.323. For the high- and low-frequency scaling ranges, the values of C ₁ are 0.5 and 0.169, respectively, which is different from the values for daily rainfall series collected at the same rain gages.     

风廓线雷达和雨滴谱仪资料在北京一次弱雨雪天气中的特征分析

利用北京市海淀区风廓线雷达、OTT Parsivel 2多功能激光雨滴谱仪和自动气象站观测资料,对2016年11月20日北京一次雨雪天气过程的演变特征进行了初步分析。结果表明:(1)风廓线(低模式)雷达反射率因子与雨滴谱仪反射率因子序列的变化趋势一致。当风廓线雷达反射率因子亮带消失后,雨滴谱反射率因子序列出现先降后升的小幅波动,降水相态转为降雪。(2)降水相态发生雨雪转换时,风廓线雷达谱宽600 m高度分散的大值区减弱并随高度降低后,雨滴谱仪数浓度出现先降后升的小幅度波动。(3)本次弱降水相态转换发生时,风廓线雷达所探测的垂直径向速度变化不明显,而雨滴谱仪降雨强度变化却有明显减弱特征,其雨强由5 mm·h^-1下降至1 mm·h^-1左右,这对临近降水相态变化的监测预报有一定指示意义。