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Impacts of climate change on temperature, precipitation and hydrology in Finland – studies using bias corrected Regional Climate Model data

机译:气候变化对芬兰温度,降水和水文学的影响–使用偏差校正的区域气候模型数据进行的研究

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摘要

Assessment of climate change impacts on climate and hydrology on catchment scale requires reliable information about the average values and climate fluctuations of the past, present and future. Regional climate models (RCMs) used in impact studies often produce biased time series of meteorological variables. In this study bias correction (BC) of RCM temperature and precipitation for Finland is carried out using different versions of the distribution based scaling (DBS) method. The DBS-adjusted RCM data are used as input of a hydrological model to simulate changes in discharges of four study catchments in different parts of Finland. The annual mean discharges and seasonal variation simulated with the DBS-adjusted temperature and precipitation data are sufficiently close to observed discharges in the control period 1961–2000 and produce more realistic projections for mean annual and seasonal changes in discharges than the uncorrected RCM data. Furthermore, with most scenarios the DBS method used preserves the temperature and precipitation trends of the uncorrected RCM data during 1961–2100. However, if the biases in the mean or the standard deviation of the uncorrected temperatures are large, significant biases after DBS adjustment may remain or temperature trends may change, increasing the uncertainty of climate change projections. The DBS method influences especially the projected seasonal changes in discharges and the use of uncorrected data can produce unrealistic seasonal discharges and changes. The projected changes in annual mean discharges are moderate or small, but seasonal distribution of discharges will change significantly.
机译:在流域尺度上评估气候变化对气候和水文学的影响,需要有关过去,现在和未来的平均值和气候波动的可靠信息。影响研究中使用的区域气候模型(RCM)通常会产生偏差的气象变量时间序列。在本研究中,芬兰的RCM温度和降水偏差校正(BC)是使用不同版本的基于比例缩放(DBS)方法进行的。经过DBS调整的RCM数据用作水文模型的输入,以模拟芬兰不同地区四个研究集水区的流量变化。使用DBS调整后的温度和降水量数据模拟的年平均排放量和季节变化与1961-2000年控制期内的观测排放量非常接近,与未校正的RCM数据相比,可以更实际地预测排放量的年均和季节性变化。此外,在大多数情况下,使用DBS方法可以保留1961-2100年间未经校正的RCM数据的温度和降水趋势。但是,如果未校正温度的平均值或标准偏差的偏差较大,则DBS调整后可能会保留明显的偏差,或者温度趋势可能会改变,从而增加了气候变化预测的不确定性。 DBS方法尤其会影响预计的排放量季节性变化,使用未经校正的数据会产生不切实际的季节性排放量和变化。预计年均排放量的变化为中等或较小,但排放量的季节性分布将发生显着变化。

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