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ABSTRACT

The purpose of this study is to examine local level spatiotemporal rainfall and temperature variability in drought-prone districts of rural Sidama, Central Rift Valley region of Ethiopia. The study used 129 gridded monthly rainfall and temperature data of 32 years (1983–2014). The gridded rainfall and temperature records were encoded into GIS software and evaluated through different statistical and geospatial techniques. Mann-Kendal rank test and F distribution tests were used to test temporal and spatial statistical significance, respectively, of the data. The analysis revealed that Belg and Kiremt are the main rainfall seasons, constituting 81% of the annual rainfall. Although annual, Kiremt, and Belg rainfall amounts appear to have decreased over time, the decreasing trend is statistically significant only for Belg rainfall records. On the other hand, rainfall standard anomaly results indicated seven droughts of different magnitudes: one extreme, two severe, and four moderate. The study also revealed increasing temperature trends over the years under consideration that are statistically significant. The findings of this study on rainfall contradict other findings obtained around the study area. Thus, climate change adaptations need to focus on location-specific climate data analysis so that the intended adaptive interventions can be successful.  相似文献   
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A flood of reliable seismic data will soon arrive. The migration to largertelescopes on the ground may free up 4-m class instruments for multi-sitecampaigns, and several forthcoming satellite missions promise to yieldnearly uninterrupted long-term coverage of many pulsating stars. We willthen face the challenge of determining the fundamental properties of thesestars from the data, by trying to match them with the output of ourcomputer models. The traditional approach to this task is to make informedguesses for each of the model parameters, and then adjust them iterativelyuntil an adequate match is found. The trouble is: how do we know that oursolution is unique, or that some other combination of parameters will notdo even better? Computers are now sufficiently powerful and inexpensivethat we can produce large grids of models and simply compare all ofthem to the observations. The question then becomes: what range ofparameters do we want to consider, and how many models do we want tocalculate? This can minimize the subjective nature of the process, but itmay not be the most efficient approach and it may give us a false sense ofsecurity that the final result is correct, when it is really justoptimal. I discuss these issues in the context of recent advances inthe asteroseismological analysis of white dwarf stars.  相似文献   
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CARBON DYNAMICS OF WETLAND IN THE SANJIANG PLAIN   总被引:2,自引:0,他引:2  
1INTRODUCTIONWetlandsplayanimportant roleintheprocessofcar-bonstorage.Thetotalcarbonstoredindifferentkindsofwetlandsisabout15%-35%ofthetotalcarboninthegloballandsoils(POSTetal.,1982;GORHAM,1991).Inaddition,wetlandsaresignificantnaturalsources fortheatmospheric CH4 (MOORE,1994).It isestimatedthatabout110×1012gCH4 originates fromanaerobicdecompositioninthenaturalwetlands,CH4 emission fromthenaturalwetlandsis15%-30%oftheglobalCH4 emission andtheCH4 emission from thepeat land at hi…  相似文献   
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Tidal effects on temperature front in the Yellow Sea   总被引:5,自引:0,他引:5  
Temperature front (TF) is one of the important features in the Yellow Sea, which forms in spring, thrives in summer, and fades in autumn as thermocline declines. TF intensity ⋎S T ⋎ is defined to describe the distribution of TF. Based on the MASNUM wave-tide-circulation coupled model, temperature distribution in the Yellow Sea was simulated with and without tidal effects. Along 36°N, distribution of TF from the simulated results are compared with the observations, and a quantitative analysis is introduced to evaluate the tidal effects on the forming and maintaining processes of the TF. Tidal mixing and the circulation structure adapting to it are the main causes of the TF. Supported by the National Basic Research Program of China (No. G1999043809) and the National Science Foundation of China (No. 49736190).  相似文献   
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