Although the statistical significances for the trends of integrated water vapor (IWV) are essential for a correct interpretation of climate change signals, obtaining accurate IWV trend estimates with realistic uncertainties remains a challenge. This study evaluates the feasibility of the IWV trends derived from the newly released fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA5) for climate change analysis in continental Europe. This is achieved by comparing the trends derived from in-situ ground-based Global Positioning System (GPS)’s daily IWV series from 1994 to 2019 at 109 stations. The realistic uncertainties and statistical significances of the IWV trends are evaluated with the time series analysis on their noise characteristics and proper noise models. Results show that autoregressive moving average ARMA(1,1) noise model is preferred rather than the commonly assumed white noise (WN) or first-order autoregressive AR(1) noise for about 68% of the ERA5 and GPS IWV series. An improper noise model would misevaluate the trend uncertainty of an IWV time series, compared with its specific preferred noise model. For example, ARMA(1,1) may misevaluate the standard deviations of their trend estimates (0.1–0.3 kg m⁻² decade⁻¹) by 10%. Nevertheless, ARMA(1,1) is recommended as the default noise model for the ERA5 and GPS IWV series. However, the preferred noise model for each ERA5 minus GPS (E-G) IWV series should be specifically determined, because the AR(1)-related models can result in an underestimation on its trend uncertainty by 90%. In contrast, power-law (PL) model can lead to an overestimation by up to nine times. The E-G IWV trends are within −0.2–0.4 kg m⁻² decade⁻¹, indicating that the ERA5 is a potential data source of IWV trends for climate change analysis in continental Europe. The ERA5 and GPS IWV trends are consistent in their magnitudes and geographical patterns, lower in Northwest Europe (0–0.4 kg m⁻² decade⁻¹) but higher around the Mediterranean Sea (0.6–1.4 kg m⁻² decade⁻¹).

尽管对综合水汽（IWV）趋势的统计意义对于正确解释气候变化信号至关重要，但要获得具有实际不确定性的准确IWV趋势估计值仍然是一个挑战。这项研究评估了从最新发布的第五代欧洲中距离天气预报中心（ECMWF）大气再分析（ERA5）进行欧洲大陆气候变化分析得出的IWV趋势的可行性。这是通过比较1994年至2019年109个站点的地基全球定位系统（GPS）每日IWV系列得出的趋势来实现的。通过对噪声特征和适当噪声模型的时间序列分析，评估了IWV趋势的现实不确定性和统计意义。-为ERA5和GPS IWV系列的约68％订购自回归AR（1）噪声。与特定的首选噪声模型相比，不正确的噪声模型会错误评估IWV时间序列的趋势不确定性。例如，ARMA（1,1）可能会将其趋势估计的标准偏差（0.1–0.3 kg m ^-2十年^-1）错误评估10％。不过，建议将ARMA（1,1）作为ERA5和GPS IWV系列的默认噪声模型。但是，应具体确定每个ERA5减去GPS（E -G）IWV系列的首选噪声模型，因为与AR（1）相关的模型可能导致其趋势不确定性低估90％。相反，幂律（PL）模型可能导致高估多达9倍。该Ë-G IWV趋势在-0.2–0.4 kg m ^-2 10 ^-1内，表明ERA5是IWV趋势的潜在数据源，可用于欧洲大陆的气候变化分析。ERA5和GPS IWV趋势在大小和地理格局上是一致的，在西北欧洲较低（0-0.4 kg m ^-2 10 ^-1），而在地中海周围较高（0.6-1.4 kg m ^-2 10 ^-1）。