Calibration and validation of lake surface temperature simulations with the coupled WRF-lake model

Gu, Hongping; Jin, Jiming; Wu, Yihua; Ek, Michael; Subin, Z. M.

doi:10.1007/s10584-013-0978-y

Cited by 128 publications

(159 citation statements)

References 30 publications

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“…This lake model is taken from CLM version 4.5 (Subin et al, 2012;Oleson et al, 2013) with some modifications by Gu et al (2015) as discussed further below. Although a version of CLM4 was available as an LSM option within WRF version 3.5, the lake model in CLM4 was disabled in WRF (Table 1).…”

Section: Use Of a Coupled Lake Model Within An Rcmmentioning

confidence: 99%

“…In WRF version 3.6, CLM's Hostetler-based lake model can be applied by using horizontally varying lake depths (which are available in WPS version 3.6) or a uniform lake depth can be assigned to all lakes at runtime. Gu et al (2015) demonstrated WRF-CLM's performance in the Great Lakes region using a previous version of this model configuration (WRF 3.2 and CLM 3.5) to simulate a 16-month period from 2001 to 2002 at 10 km grid spacing. It was shown that the lake model simulated LSTs well in Lake Erie but generated large biases in LSTs when compared to buoy observations in Lake Superior.…”

Section: Use Of a Coupled Lake Model Within An Rcmmentioning

confidence: 99%

“…However, the LST bias was reduced by reformulating the eddy diffusivity parameter in the CLM lake model, and it was concluded that the updated lake model within WRF-CLM was reasonably able to reproduce observed LSTs. However, no ice was observed during the period and the ability of WRF-CLM to accurately simulate ice cover was not examined in Gu et al (2015).…”

Section: Use Of a Coupled Lake Model Within An Rcmmentioning

confidence: 99%

“…Previous work by Subin et al (2012) with the lake model in CLM4 used a 110-year period for the spin-up of their reference simulation. In their experiments with WRF-CLM, Gu et al (2015) used an observed LST field for initialization. The nine sub-surface layers in their model were initialized based on the shape of an observed profile of lake temperatures, valid during that period of the year and taken from Lake Superior.…”

Section: Use Of a Coupled Lake Model Within An Rcmmentioning

confidence: 99%

“…difficulty in simulating deep lakes (e.g., Martynov et al, 2010;Stepanenko et al, 2010;Gu et al, 2015;M14). Some model error can be attributed to the fact that one-dimensional column models cannot represent 2-and 3-D processes (e.g., currents, drifting ice, and formation of a thermal bar).…”

Section: Use Of a Coupled Lake Model Within An Rcmmentioning

confidence: 99%

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Technical challenges and solutions in representing lakes when using WRF in downscaling applications

et al. 2015

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Abstract. The Weather Research and Forecasting (WRF)model is commonly used to make high-resolution future projections of regional climate by downscaling global climate model (GCM) outputs. Because the GCM fields are typically at a much coarser spatial resolution than the target regional downscaled fields, lakes are often poorly resolved in the driving global fields, if they are resolved at all. In such an application, using WRF's default interpolation methods can result in unrealistic lake temperatures and ice cover at inland water points. Prior studies have shown that lake temperatures and ice cover impact the simulation of other surface variables, such as air temperatures and precipitation, two fields that are often used in regional climate applications to understand the impacts of climate change on human health and the environment. Here, alternative methods for setting lake surface variables in WRF for downscaling simulations are presented and contrasted.

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Section: Use Of a Coupled Lake Model Within An Rcmmentioning

confidence: 99%

Section: Use Of a Coupled Lake Model Within An Rcmmentioning

confidence: 99%

Section: Use Of a Coupled Lake Model Within An Rcmmentioning

confidence: 99%

Section: Use Of a Coupled Lake Model Within An Rcmmentioning

confidence: 99%

Section: Use Of a Coupled Lake Model Within An Rcmmentioning

confidence: 99%

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Technical challenges and solutions in representing lakes when using WRF in downscaling applications

et al. 2015

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Effect of a large and very shallow lake on local summer precipitation over the Lake Taihu basin in China

2016

JGR Atmospheres

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Lake Taihu is the third largest freshwater lake in China and is situated in the Middle and lower Yangtze River delta. It is characterized by its shallowness (~1.9 m), large area (~2338 km 2 ), and high turbidity in recent years. The lake's effect on local summer precipitation is first studied in this paper through the use of an atmosphere-lake coupled model. By enlarging the light extinction coefficient, modifying the radiation scheme, and setting the roughness length to constants, the coupled model after adjustment realistically reproduces the thermal stratification and magnitude of diurnal variation over Lake Taihu, with mean biases of 0.7°C for lake surface temperature and 0.4°C for near-surface air temperature, respectively. Based on this calibrated coupled model, two high-resolution numerical simulations with and without the lake (lake grid cells replaced by cropland) were conducted to identify the lake effects. The results show that an overall effect of Lake Taihu on local summer precipitation is negative during daytime and positive during nighttime and the precipitation pattern may be modified to some extent. The lake effect varies between areas and with time of day and occurs primarily on the downwind shore. A composite analysis for a representative decreased precipitation region reveals that during daytime in the summer, the combination of decreased air temperature and latent heat flux, along with intensified divergence and downdraft, acts together to stabilize the lower atmosphere and suppress thermal convective activities, ultimately resulting in less precipitation over this region.China is home to a large number of lakes. According to the latest statistics, there are 2693 natural lakes in China with an area greater than 1.0 km 2 , with a total area of 81,414.6 km 2 , accounting for~0.Key Points: • The coupled model improves the temperature simulations • Lake Taihu has a negative (positive) effect on summer precipitation during daytime (nighttime) • The lake effect varies between areas and with time of day Correspondence to: Z. Ma, mazg@tea.ac.cn Citation: Gu, H., Z. Ma, and M. Li (2016), Effect of a large and very shallow lake on local summer precipitation over the Lake

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Evaluation of the WRF‐lake model over a highland freshwater lake in southwest China

Liu

et al. 2016

JGR Atmospheres

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Evaluation of the Weather Research and Forecasting Model version 3.7.1 lake model performance on lake physical processes and lake‐atmosphere interaction at Erhai Lake was conducted with in situ observation data sets over the lake to verify the model results. The lake model with default parameters presented significant negative bias during the day and positive bias during the night on lake surface temperature. Calibrations of water absorption and extinction coefficients, surface roughness length, and eddy diffusion coefficient were carried out to correct this bias. The added absorption and extinction coefficients increased solar radiation in upper water layer, leading to a little higher surface temperature. Compared to constant surface roughness lengths, parameterization of roughness lengths as functions of friction velocity and fetch length significantly improved simulations of lake surface temperature and sensible heat flux. In Erhai Lake, eddy diffusion coefficient of the Henderson‐Sellers parameterization is smaller than that in deep lakes. The eddy diffusion coefficient was reduced by a factor of 0.05 in dry season and 0.02 in wet season, respectively, to restrict mixing strength, generating a reasonable diurnal range with observed surface temperature. The adjusted parameter simulations matched better with in situ observations in diurnal cycle of temperature and surface heat fluxes but still overestimated wind speed. Topographic correction is effective to correct the bias, indicating that topographic correction over complex terrain was necessary.

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Calibration and validation of lake surface temperature simulations with the coupled WRF-lake model

Cited by 128 publications

References 30 publications

Technical challenges and solutions in representing lakes when using WRF in downscaling applications

Technical challenges and solutions in representing lakes when using WRF in downscaling applications

Effect of a large and very shallow lake on local summer precipitation over the Lake Taihu basin in China

Evaluation of the WRF‐lake model over a highland freshwater lake in southwest China

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