Abstract

The impact of several land surface models (LSMs) and microphysics (MP), planetary boundary layer (PBL), and surface layer schemes on the accuracy of simulated brightness temperatures (BTs) from water vapor (WV) sensitive bands was examined via comparison with observations from the GOES-16 Advanced Baseline Imager. Nine parameterization configurations were evaluated. Analysis revealed that, compared to the Thompson MP scheme, the National Severe Storms Laboratory MP scheme produced lower simulated WV BTs in the upper troposphere but higher WV BTs in the middle and lower troposphere. The configuration with the Geophysical Fluid Dynamics Laboratory MP and hybrid eddy-diffusivity mass-flux (EDMF) PBL instead of Mellor–Yamada–Nakanishi–Niino (MYNN) PBL produced higher BTs. Yet, changing the PBL from MYNN to Shin–Hong or EDMF reduced the simulated WV BTs. Changing the LSM from Noah to RUC also resulted in lower simulated WV BTs, which were further enhanced with the MYNN surface layer instead of the GFS. The location and orientation of upper-level jet streams and troughs was assessed using the location of WV gradient objects. Every configuration had an increased translation speed compared to the observations, as forecast WV gradient objects were west of the observation objects early in the forecast and then east later in the forecast.

Highlights

  • There are many operational uses for satellite infrared brightness temperatures (BTs) from bands sensitive to water vapor (WV) and clouds

  • These examples illustrate the fact that efforts to verify and improve the accuracy of WV BTs in high-resolution numerical weather prediction (NWP) models are very beneficial for a range of applications

  • Changing the land surface model from Noah to RUC decreased the accuracy of the 6.2 μm BTs, with further reductions in accuracy occurring when using the MYNN surface layer instead of Global Forecasting System (GFS)

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Summary

Introduction

There are many operational uses for satellite infrared brightness temperatures (BTs) from bands sensitive to water vapor (WV) and clouds (hereafter referred to as WV bands). WV BTs can be used to identify areas of possible aircraft icing [1,2], track disturbances that produce severe weather [3], and derive atmospheric motion vectors [4,5] that can be used to compute tropical cyclone outflow and estimate future intensification [6]. Severe weather can be associated with the exit and entrance regions of jet streams [11] or negatively tilted 500 hPa troughs [12,13]. These examples illustrate the fact that efforts to verify and improve the accuracy of WV BTs in high-resolution numerical weather prediction (NWP) models are very beneficial for a range of applications

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