Representing atmospheric moisture content along mountain slopes: Examination using distributed sensors in the Sierra Nevada, California
Representing atmospheric moisture content along mountain slopes: Examination using distributed sensors in the Sierra Nevada, California
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表示山坡上的大气湿度：使用加利福尼亚州内华达山脉的分布式传感器进行检查
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发表时间：
2013
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通讯作者：
J. Lundquist
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作者：
Shara I. Feld;N. Cristea;J. Lundquist
大气湿度在水文模拟中至关重要，但在山区环境中测量很少。我们比较了内华达州、加州的Sierra两个研究地点的露点温度的密集分布测量值，并与（1）简单的经验算法、（2）独立斜坡模型（PRISM）参数高程回归、（3）无线电探空仪数据和（4）天气研究和预报（WRF）中尺度模型进行了比较。仅使用一个海平面测量露点来外推到更高海拔的经验算法通常与当地的露点递减率不匹配，并且可能偏差高达9.9°C。PRISM改进了这些方法，使用当地观测来确定当地平均露点递减率，在我们的两个研究地点中，中间偏差值为-0.3 °C和3.3°C。从空气温度得出露点的经验算法显示出性能的季节性变化;夏季的中值偏差值比冬季偏差值潮湿0.6°C-8.2°C。无线电探空仪读数显示，与我们研究地点的观测结果相比，中位偏差为−6.5°C和−8.0°C。WRF改进了无线电探空仪数据，在代表盆地的总体趋势方面表现良好（在我们的研究地点，中位数偏差为-0.9 °C和-1.0 °C）。盆地内的一个基站与PRISM递减率配对，显示出与整体湿度趋势的小偏差。然而，一个物理解决的模式，如WRF更好地装备代表每日露点变化和流域的非线性趋势。
Atmospheric moisture content is critical in hydrological modeling yet is sparsely measured in mountainous environments. We compared densely distributed measurements of dew point temperature in two study sites in the Sierra Nevada, California, against (1) simple empirical algorithms, (2) the Parameter‐elevation Regressions on Independent Slopes Model (PRISM), (3) radiosonde data, and (4) the Weather Research and Forecasting (WRF) mesoscale model. Empirical algorithms that used only one sea‐level measurement of dew point to extrapolate to higher elevations often did not match local dew point lapse rates and could be biased as high as 9.9°C. PRISM improved upon these methods by using local observations to determine the local average dew point lapse rate, with median bias values of −0.3°C and 3.3°C in our two study sites. Empirical algorithms that derived dew point from air temperature showed a seasonal variation in performance; summer median bias values were 0.6°C–8.2°C wetter than winter bias values. Radiosonde readings showed median biases of −6.5°C and −8.0°C from observations in our study sites. WRF improved on the radiosonde data, performing well in representing both the overall trends in the basin (with median biases of −0.9°C and −1.0°C in our study sites). One base station within the basin paired with PRISM lapse rates showed small biases from overall moisture trends. However, a physically resolved model such as WRF was better equipped to represent daily dew point variations and in basins with nonlinear trends.