4.2 Article

Verification of Convection-Allowing WRF Model Forecasts of the Planetary Boundary Layer Using Sounding Observations

期刊

WEATHER AND FORECASTING
卷 28, 期 3, 页码 842-862

出版社

AMER METEOROLOGICAL SOC
DOI: 10.1175/WAF-D-12-00103.1

关键词

Boundary layer; Mixed layer; Spring season; Storm environments; Forecast verification; skill; Numerical weather prediction; forecasting

资金

  1. NOAA/Office of Oceanic and Atmospheric Research under NOAA-University of Oklahoma [NA11OAR4320072]
  2. U.S. Department of Commerce
  3. NOAA CSTAR program
  4. NSF-ITR [ATM-0331594]
  5. NSF [ATM-0802888]

向作者/读者索取更多资源

This study evaluates forecasts of thermodynamic variables from five convection-allowing configurations of the Weather Research and Forecasting Model (WRF) with the Advanced Research core (WRF-ARW). The forecasts vary only in their planetary boundary layer (PBL) scheme, including three local schemes [Mellor-Yamada-Janji (MYJ), quasi-normal scale elimination (QNSE), and Mellor-Yamada-Nakanishi-Niino (MYNN)] and two schemes that include nonlocal mixing [the asymmetric cloud model version 2 (ACM2) and the Yonei University (YSU) scheme]. The forecasts are compared to springtime radiosonde observations upstream from deep convection to gain a better understanding of the thermodynamic characteristics of these PBL schemes in this regime. The morning PBLs are all too cool and dry despite having little bias in PBL depth (except for YSU). In the evening, the local schemes produce shallower PBLs that are often too shallow and too moist compared to nonlocal schemes. However, MYNN is nearly unbiased in PBL depth, moisture, and potential temperature, which is comparable to the background North American Mesoscale model (NAM) forecasts. This result gives confidence in the use of the MYNN scheme in convection-allowing configurations of WRF-ARW to alleviate the typical cool, moist bias of the MYJ scheme in convective boundary layers upstream from convection. The morning cool and dry biases lead to an underprediction of mixed-layer CAPE (MLCAPE) and an overprediction of mixed-layer convective inhibition (MLCIN) at that time in all schemes. MLCAPE and MLCIN forecasts improve in the evening, with MYJ, QNSE, and MYNN having small mean errors, but ACM2 and YSU having a somewhat low bias. Strong observed capping inversions tend to be associated with an underprediction of MLCIN in the evening, as the model profiles are too smooth. MLCAPE tends to be overpredicted (underpredicted) by MYJ and QNSE (MYNN, ACM2, and YSU) when the observed MLCAPE is relatively small (large).

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