In this study we present a methodological framework to obtain statistically downscaled high resolution climate projections over the Attica region in Greece. The framework relies on the construction of a local daily gridded dataset for temperature variables (maximum, minimum and mean daily temperatures) and daily precipitation sums. To this aim, a mosaic of data that includes observations derived from ground stations and a high resolution simulation, performed by the Weather Research and Forecasting (WRF) model, for 1 year (1995) are blended using various gridding techniques to produce a 1 km 1 km high resolution daily gridded dataset for the period 1981–2000. The comparison of the gridded dataset against the observations reveals that the produced dataset maintains the observed long term statistical properties over the period 1981–2000 for both temperature and precipitation variables. Consequently, the produced dataset is used to statistically downscale Regional Climate Model simulations from the EURO-CORDEX initiative for the present (1981–2000) and the future climate (2081–2100) under the Representative Concentration Pathway (RCP) 8.5 climate scenario using two different bias adjustment techniques. The results indicate that the selection of the bias adjustment method is important and can affect the simulated climate change signals in a different way. Thus bias adjustment should be performed with caution and examined thoroughly before any such downscaled climate change projection dataset reach decision and policy makers in order to plan climate change related adaptation strategies.

在这项研究中，我们提出了一个方法框架，以获得对希腊阿提卡地区的统计缩小的高分辨率气候预测。该框架依赖于为温度变量（最高、最低和平均每日温度）和每日降水量总和构建本地每日网格化数据集。为此，使用各种网格化技术将 1 年（1995 年）的地面站观测数据和高分辨率模拟（由天气研究和预报 (WRF) 模型执行）的马赛克数据混合在一起，生成 1 km 1981-2000 年期间的 1 公里高分辨率每日网格化数据集。网格化数据集与观测值的比较表明，生成的数据集保持了 1981-2000 年期间观测到的温度和降水变量的长期统计特性。因此，生成的数据集用于根据 EURO-CORDEX 倡议对当前（1981-2000 年）和未来气候（2081-2100 年）在代表性浓度路径 (RCP) 8.5 气候情景下的统计降级区域气候模型模拟，使用两个不同的偏置调整技术。结果表明，偏差调整方法的选择很重要，可以以不同的方式影响模拟的气候变化信号。