3.6 Exploration of California High Resolution Snowpack Modeling with Realistic Surface-Atmospheric Radiation Physics

Monday, 9 July 2018: 2:45 PM
Regency E/F (Hyatt Regency Vancouver)
Chaincy Kuo, LBNL, Berkeley, CA; and A. M. Rhoades and D. Feldman

Handout (3.9 MB)

CMIP5 multi-model mean surface temperatures exhibit a cold bias at high latitude regions, where atmospheric water vapor is low (Flato et al, 2013). In another dry atmospheric regime, during wintertime California, a surface temperature cold bias exists at high altitudes in models with fine spatial resolution, required to resolve the mountainous topography reaching the highest elevations (Rhoades et al, in review, Journal in Advances Modeling Earth Systems).

Atmospheres with low precipitable water vapor are more transmissive in window bands of the far-infrared (Harries et al, 2008; Feldman et al, 2014), and thus it is essential to correctly model the spectral longwave surface upwelling emission to appropriately represent outgoing longwave radiation in dry atmospheres. In the tropical regions, Global Circulation Models sufficiently represent upward longwave radiation trapped in the moist atmosphere. Recent attention has been directed on modeling spectral surface emissivity of different land surfaces out to the far-infrared bands, in order to improve the description of longwave upward surface fluxes in Global Circulation Models (Chen et al, 2014; Huang et al, 2016). The Arctic wintertime surface temperature cold bias of -7.2 K was alleviated to -1.1 K Kelvin by incorporating these spectral surface emissivity curves and securing consistent long wave upward radiation physics between atmospheric and surface components in a 2°x2° Community Earth System Model (CESM) (Kuo et al, 2018).

We seek to improve the modeled cold biases at high altitudes. However, standard global circulation model (GCM) grids are 1°x1° at the lowest resolution and the digital smoothing operations on topography reduce the elevations of mountainous regions. On the other hand, high resolution grid models are computationally expensive. In this study, a variable resolution gridded Global Circulation Model is implemented (Rhoades et al, in review), with telescopically increasing resolution focused on the California State, with finest resolution in high altitude regions to improve resolution vertically as well as horizontally.

In a control high resolution model with gray-body surface emissivity, total precipitable water averaged over the months December, January and February and years 1999-2015 decreases as a function of increasing altitude, as expected. However, the simulated 2-meter surface temperature is biased low compared to Parameter elevation Regression on Independent Slopes Model (PRISM) data, and the amplitude of the low surface temperature bias increases with altitude. We argue that this qualitative correlation between atmospheric moisture and surface temperature bias as a function of altitude points to imperfect modeling of surface-atmosphere longwave radiative processes. The correlation is stronger in simulations with horizontal resolution <55 km. The atmosphere also becomes drier in the wintertime, and this seasonality is simulated in the control models of various resolutions and microphysics models. The surface temperature biases could be suffering from longwave surface-atmospheric modeling impact in dry atmospheres where the cold bias is pronounced in the wintertime when total precipitable water is low.

Spectral surface emissivity modeling and consistent longwave upward radiation physics between surface and atmospheric components are then implemented in this variable resolution CESM to capture important spectral surface and atmospheric long wave radiative processes in the California high altitudes.

Preliminary results show that there is an improvement in high altitude surface temperature bias. We investigate how this bias improvement impacts hydrological cycle simulations.


Chen, X., Huang, X., & Flanner, M. G. (2014). Sensitivity of modeled far‐IR radiation budgets in polar continents to treatments of snow surface and ice cloud radiative properties. Geophysical Research Letters, 41(18), 6530-6537.

Feldman, D. R., Collins, W. D., Pincus, R., Huang, X., & Chen, X. (2014). Far-infrared surface emissivity and climate. Proceedings of the National Academy of Sciences, 111(46), 16297-16302.

Harries, John, Bruno Carli, Rolando Rizzi, Carmine Serio, M. Mlynczak, Luca Palchetti, T. Maestri, H. Brindley, and Guido Masiello. (2008). The far‐infrared Earth. Reviews of Geophysics 46, no. 4.

Huang, X., Chen, X., Zhou, D. K., & Liu, X. (2016). An observationally based global band-by-band surface emissivity dataset for climate and weather simulations. Journal of the Atmospheric Sciences, 73(9), 3541-3555.

Kuo, C., Feldman, D. R., Huang, X., Flanner, M., Yang, P., & Chen, X. (2018). Time-dependent cryospheric longwave surface emissivity feedback in the Community Earth System Model. Journal of Geophysical Research: Atmospheres, 123, 789–813.

Rhoades, A.M., P. A. Ullrich, C. M. Zarzycki, S. A. Margulis, H. Johansen, Z. Xu, and W. D. Collins, in review, Journal in Advances Modeling Earth Systems.

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