Reference evapotranspiration data from atmometers at three locations on the Delmarva Peninsula (USA) were compared to Penman-Monteith reference evapotranspiration (ET_o) data across two growing seasons. Atmometer reference evapotranspiration (ET_a) was found to underestimate ET_o by 22.8% in 2016 and 30.4% in 2017. Stepwise linear regression was used to examine the relationship between both ET datasets and local meteorological conditions measured by Delaware Environmental Observing System (DEOS) mesonet stations that were co-located with the atmometers. Variability of ET_a and ET_o are well explained (R² equal to 0.890 and 0.956, respectively) by a combination of meteorological variables, though the R² in 2017 (R² = 0.754) was notably lower than in 2016 (R² = 0.890). The ET datasets were further examined by partitioning the data into days with similar synoptic conditions using a temporal synoptic index (TSI). Using the TSI results, three dominant synoptic categories were defined during the study period: High Pressure (HP), Southwest Flow (SW), and Cold Fronts (CF). Overall, the similarity between ET_a and ET_o was greatest on HP days, followed by CF and SW days. This relationship was primarily driven by wind speed, which had the greatest influence on ET_a-ET_o differences under all synoptic weather patterns. The 2016 growing season consisted of more days with synoptic conditions that are associated with smaller ET_a -ET_o differences than the 2017 growing season. Thus, changes in synoptic category frequency impact the nature of the ET_a-ET_o relationship from season to season. This study improves upon previous atmometer comparison studies by associating atmometer correction factors with synoptic weather patterns and descriptions in order to improve the utility of atmometers and remove the need for expensive meteorological equipment to correct atmometer data.

将来自德尔马瓦半岛（美国）三个地点的大气计的参考蒸散数据与两个生长季节的 Penman-Monteith 参考蒸散 (ET _o ) 数据进行了比较。大气计参考蒸散量 (ET _a ) 被发现低估了2016 年 22.8% 和 2017 年 30.4% 的ET _o 。使用逐步线性回归来检查 ET 数据集与特拉华州环境观测系统 (DEOS) 测量的当地气象条件之间的关系与大气计位于同一地点的中子站。ET _a和 ET _o的变异性得到了很好的解释（R ²分别等于 0.890 和 0.956），尽管 2017 年的 R ²（R ²  = 0.754）明显低于 2016 年（R ²  = 0.890）。通过使用时间天气指数 (TSI) 将数据划分为具有相似天气条件的天数，进一步检查了 ET 数据集。使用 TSI 结果，在研究期间定义了三个主要的天气类别：高压 (HP)、西南气流 (SW) 和冷锋 (CF)。_{总体而言，ET a}和 ET _o之间的相似性在 HP 日最大，其次是 CF 和 SW 日。这种关系主要由风速驱动，风速对 ET _a -ET _{o的影响最大}所有天气模式下的差异。_{与 2017 年生长季相比，2016 年生长季有更多天数与较小的 ET a} -ET _o差异相关的天气条件。因此，天气类别频率的变化会影响季节之间ET _a -ET _o关系的性质。本研究通过将气压计校正因子与天气模式和描述相关联，改进了以前的气压计比较研究，以提高气压计的实用性，并消除了对昂贵的气象设备来校正气压计数据的需要。