土壤墒情遥感反演与旱情诊断

土壤墒情与植被生长状况和地表温度之间存在密切联系?贑OST模型算法和单窗算法,开展了TM/ETM+多光谱数据的地表反射率、地表温度(LST)和土壤调整植被指数反演(MSAVI),分析了地表温度和植被指数的线性关系,提出了土壤墒情几何特征指数和旱情诊断函数,结合土壤含水量实测数据,建立了横山县土壤墒情遥感反演模型。实证结果表明,基于TM/ETM+数据反演的长度指数可进行旱情诊断;对土壤含水量的反演模型进行T检验,差异不显著,而基于地面温度的土壤墒情反演模型优于土壤调整植被指数反演模型。     

基于GM(1,1)模型的塔里木盆地南缘孤立绿洲降水灾变预测

我们选取了具有一定代表性的塔里木盆地南缘的孤立绿洲民丰县作为研究区,在对数据有效性的验证之后,利用研究区1980~1999年的降水资料,运用灰色系统理论的季节灾变预测方法,对该地区未来年份的降水量进行预测,并建立灰色季节灾变GM(1,1)预测模型,预测未来旱季到来的年份,为预测未来降水趋势提供了信息。结果表明:该研究区下一个旱灾灾变年大致指向2006年至2007年左右。这对合理利用本地气候资源具有实际意义,并且能够为研究干旱区气候变化提供一定的帮助。     

旱涝灾害灾后经济损失评估模型及对策

在分析呼伦贝尔市旱涝灾害的基础上,为了更好地减轻其损失,建立了“历史相似综合评估”和“气候背景统计评估”两个旱涝灾害经济损失评估模型。经5年的业务应用,效果很好。可以投入辅助决策服务使用。     

Future Changes in Extreme High Temperature over China at 1.5℃-5℃ Global Warming Based on CMIP6 Simulations

Extreme high temperature(EHT)events are among the most impact-related consequences related to climate change,especially for China,a nation with a large population that is vulnerable to the climate warming.Based on the latest Coupled Model Intercomparison Project Phase 6(CMIP6),this study assesses future EHT changes across China at five specific global warming thresholds(1.5℃-5℃).The results indicate that global mean temperature will increase by 1.5℃/2℃ before 2030/2050 relative to pre-industrial levels(1861-1900)under three future scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5),and warming will occur faster under SSP5-8.5 compared to SSP1-2.6 and SSP2-4.5.Under SSP5-8.5,global warming will eventually exceed 5℃ by 2100,while under SSP1-2.6,it will stabilize around 2℃ after 2050.In China,most of the areas where warming exceeds global average levels will be located in Tibet and northern China(Northwest China,North China and Northeast China),covering 50%-70%of the country.Furthermore,about 0.19-0.44 billion people(accounting for 16%-41%of the national population)will experience warming above the global average.Compared to present-day(1995-2014),the warmest day(TXx)will increase most notably in northern China,while the number of warm days(TX90p)and warm spell duration indicator(WSDI)will increase most profoundly in southern China.For example,relative to the present-day,TXx will increase by 1℃-5℃ in northern China,and TX90p(WSDI)will increase by 25-150(10-80)days in southern China at 1.5℃-5℃ global warming.Compared to 2℃-5℃,limiting global warming to 1.5℃ will help avoid about 36%-87%of the EHT increases in China.     

非平稳标准化降水蒸散指数构建及中国未来干旱时空格局

旱灾是一种致灾因子与成害机理均非常复杂的自然灾害,也是目前对其检测与风险防御最为困难的自然灾害种类之一。随着全球气候变化,干旱的变化逐渐趋于非平稳化,水文气象序列的非平稳性已有广泛研究,但在干旱检测指标中却鲜有考虑。基于标准化降水蒸散指数（SPEI）和非平稳性理论,构建非平稳性标准化降水蒸散指数（NSPEI）并进行适用性评价,利用NSPEI评估未来不同排放情景下中国气象干旱时空格局演变规律。结果表明：① 非平稳性站点集中在东北平原、黄淮海平原、长三角地区、青藏高原及周边区域,NSPEI拟合最优的站点占中国气象站点的88%（2177个站点）。② SPEI对温度较为敏感,在评估未来干旱变化时会高估干旱强度和持续时间性,而NSPEI能够克服这一弱点,较SPEI可更好的检测中国气象干旱,且能很好的刻画中国未来干旱变化。③ 低、高排放情景下中国北方干旱加剧,南方呈湿润化趋势;中排放情景下中国北方湿润化趋势明显,而中国南方则呈干旱化。基于NSPEI干旱检测结果,中高排放情景下中国未来极端干湿历时与发生频率均呈增加趋势。     

ARIMA-LSTM组合模型在基于SPI干旱预测中的应用——以青海省为例

开展干旱预测是有效应对干旱风险的前提基础。利用1958—2017年青海省38个气象站点逐日降水量数据计算多尺度标准化降水指数（SPI）,并建立了SPI序列自回归移动平均模型（ARIMA）、长短时记忆神经网络模型（LSTM）和基于二者优点提出的ARIMA-LSTM组合模型;对模型参数进行率定和验证后,利用所建立的模型,以西宁站点为例,对多尺度SPI值进行预测,借助均方根误差（RMSE）、平均绝对百分比误差（MAPE）和决定系数R²对所有预测模型的有效性进行判定。结果表明：ARIMA-LSTM组合模型在SPI1和SPI12的RMSE值分别为0.159 7和0.181 0,均低于ARIMA模型的1.265 4和0.293 3,说明ARIMA模型与ARIMA-LSTM组合模型对SPI的预测精度都与时间尺度有关,ARIMA模型的预测精度随着时间尺度的增加而逐渐提高;结合GIS并利用实测数据与模型的预测数据相比较说明ARIMA-LSTM组合模型相比于单一ARIMA模型的预测精度更高,且能够很好拟合不同时间尺度的SPI值。     

Effect of farmland expansion on drought over the past century in Songnen Plain,Northeast China

The effects of human activities on climate change are a significant area of research in the field of global environmental change. Land use and land cover change(LUCC) has a greater effect on climate than greenhouse gases, and the effect of farmland expansion on regional drought is particularly important. From the 1910 s to the 2010 s, cultivated land in Songnen Plain increased by 2.67 times, the area of cultivated land increased from 4.92×10~4 km~2 to 13.14×10~4 km~2, and its percentage of all land increased from 25% to 70%. This provides an opportunity to study the effects of the conversion of natural grassland to farmland on climate. In this study, the drought indices in Songnen Plain were evaluated from the 1910 s to the 2010 s, and the effect of farmland expansion on drought was investigated using statistical methods and the Weather Research and Forecasting Model based on UK's Climatic Research Unit data. The resulting dryness index, Palmer drought severity index, and standardized precipitation index values indicated a significant drying trend in the study area from 1981 to 2010. This trend can be attributed to increases in maximum temperature and diurnal temperature range, which increased the degree of drought. Based on statistical analysis and simulation, the maximum temperature, diurnal temperature range, and sensible heat flux increased during the growing season in Songnen Plain over the past 100 years, while the minimum temperature and latent heat flux decreased. The findings indicate that farmland expansion caused a drying trend in Songnen Plain during the study period.     

厚壳贻贝(Mytilus coruscus)足丝蛋白mcofp3和mcofp6的cDNA克隆及序列分析

通过设计特异性引物,采用PCR扩增的方法对厚壳贻贝足腺细胞cDNA文库进行筛选,共克隆得到14条厚壳贻贝mcofp3的cDNA序列和8条mcofp6的cDNA序列,并对其基因序列及推导的氨基酸序列进行了序列比对和变异位点初步分析。结果表明,14条mcofp3cDNA序列分属于厚壳贻贝mcofp3家族的两个亚家族,其成熟肽序列变异相对活跃;而8条mcofp6 cDNA序列并无明显的亚家族划分,序列相对保守。本次实验所获得的mcofp cDNA序列初步显示了厚壳贻贝足丝蛋白家族基因的分子多样性,为将来深入了解厚壳贻贝足丝蛋白的分子多样性机制以及在此基础上开发相关的新型生物黏附剂奠定了基础。     

Response of the mesozooplankton community of the St Lucia estuary,South Africa,to a mouth-opening event during an extended drought

Mesozooplankton samples were collected between March 2005 and November 2008 in St Lucia, the largest estuarine lake system in South Africa. St Lucia experienced an extended period of drought before and during the present study. This drought led to natural closing of the estuary mouth as a result of flood-tide marine sediment deposition in 2002. In March 2007 the mouth was washed open by exceptionally high tidal and wave conditions. This resulted in an influx of a large volume of seawater. The mouth closed again in August 2007. Before opening of the mouth salinities in the Estuary were below 10 and large parts of North Lake dried up while South Lake retained a relatively stable waterbody with salinities between 10 and 30. When the mouth opened seawater flooded the system and salinities changed to about 35. After the mouth had closed again in August 2007 salinities increased in the lakes and decreased in the Estuary. The mesozooplankton community was dominated by copepods during all sampling sessions, especially by the estuarine calanoids Pseudodiaptomus stuhlmanni and Acartia natalensis. Mean mesozooplankton densities were significantly higher in South Lake before the mouth opened in March 2007. While zooplankton density decreased when the mouth opened species richness increased with the influx of coastal marine species, especially in the Estuary. Overall zooplankton densities declined progressively as salinity increased to hypersaline levels after mouth closure. Multivariate analyses supported significant differences between the lakes and the Estuary in terms of mesozooplankton community composition. Taxa mostly responsible for the similarities within and dissimilarity between sections of the system were the copepods P. stuhlmanni and A. natalensis with the meroplankton, crab zoeae and mollusc larvae, also contributing significantly after the mouth-opening event.