Mitigating errors in surface temperature forecasts using approximate radiation updates

Hogan, Robin J.; Bozzo, Alessio

doi:10.1002/2015ms000455

Cited by 26 publications

(23 citation statements)

References 17 publications

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“…Hierarchies of complexity are a promising idea in the context of scalability, where ensembles clearly offer a high level of parallelization that can naturally be exploited on many‐core supercomputers. Already, coarsening of the radiation calculations in time and space has been used to reduce the cost of the ensemble (Morcrette et al , 2008b; Hogan and Bozzo, 2015). An interesting question to investigate is whether the knowledge of model error or its existence could be exploited to improve either the scalability and/or time to solution of individual ensemble members.…”

Section: Discussionmentioning

confidence: 99%

Stochastic representations of model uncertainties at ECMWF: state of the art and future vision

Leutbecher

Lock

Ollinaho

et al. 2017

Quart J Royal Meteoro Soc

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214

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Members in ensemble forecasts differ due to the representations of initial uncertainties and model uncertainties. The inclusion of stochastic schemes to represent model uncertainties has improved the probabilistic skill of the ECMWF ensemble by increasing reliability and reducing the error of the ensemble mean. Recent progress, challenges and future directions regarding stochastic representations of model uncertainties at ECMWF are described in this article. The coming years are likely to see a further increase in the use of ensemble methods in forecasts and assimilation. This will put increasing demands on the methods used to perturb the forecast model. An area that is receiving greater attention than 5–10 years ago is the physical consistency of the perturbations. Other areas where future efforts will be directed are the expansion of uncertainty representations to the dynamical core and other components of the Earth system, as well as the overall computational efficiency of representing model uncertainty.

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Section: Discussionmentioning

confidence: 99%

Stochastic representations of model uncertainties at ECMWF: state of the art and future vision

Leutbecher

Lock

Ollinaho

et al. 2017

Quart J Royal Meteoro Soc

Self Cite

214

250

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“…Climate models with a 3h radiation time step include ACCESS [Bi et al, 2013], EC-Earth [Hazeleger et al, 2011], GFDL [Anderson et al, 2004], HadGEM3 [Walters et al, 2014] and INM-CM4 [Zhou et al, 2015]. This has been found to lead to errors in the diurnal cycle of temperature [Yang and Slingo, 2001;Hogan and Bozzo, 2015] and to change the climate sensitivity of the model [Morcrette, 2000]. It is hardly surprising that this is problematic in the shortwave since eight radiation calls in 24 h implies typically only four for which the sun is above the horizon, and four discrete angles are clearly a poor approximation to the path of the sun through the sky.…”

Section: Introductionmentioning

confidence: 99%

Effect of solar zenith angle specification in models on mean shortwave fluxes and stratospheric temperatures

Hogan

Hirahara

2016

Geophysical Research Letters

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Many weather and climate models call their radiation schemes only every 3 h, which we show can lead to a stratospheric temperature overestimate of 3–5 K and wavenumber 8 fluctuations in top‐of‐atmosphere (TOA) net shortwave flux around the tropics of amplitude 1.6 W m−2. Solving this problem while retaining a 3h radiation time step requires careful treatment of the cosine of the solar zenith angle, μ0, which appears twice in the calculation of shortwave fluxes, scaling the following: (1) TOA incident flux and (2) the path length of the direct solar beam through the atmosphere. If μ0 is calculated as the average over the radiation time step, rather than at the central time, then the fluctuations are removed, but the stratosphere is still too warm by 2–3 K. It is only if the second μ0 is averaged only over the sunlit part of the radiation time step that the temperature bias is removed.

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“…It is well known that NWP models can have large temperature errors at coastlines (Hogan and Bozzo, 2015). Due to their high computational cost, the radiation schemes are often applied on a coarser spatial grid (compared to the grid of NWP dynamical core).…”

Section: Dependence On Surface Albedomentioning

confidence: 99%

Quantifying the bias of radiative heating rates in NWP models for shallow cumulus clouds

Črnivec

Mayer

2019

Preprint

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Abstract. The interaction between radiation and clouds represents a source of uncertainty in numerical weather prediction (NWP) due to both intrinsic problems of one-dimensional radiation schemes and poor representation of clouds. The underlying question addressed in this study is how large is the NWP radiative bias for shallow cumulus clouds and how does it scale with various input parameters of radiation schemes, such as solar zenith angle, surface albedo, cloud cover and liquid water path. A set of radiative transfer calculations was carried out for a realistically evolving shallow cumulus cloud field stemming from a large-eddy simulation (LES). The benchmark experiments were performed on the highly-resolved LES cloud scenes using a three-dimensional Monte Carlo radiation model. An absence of middle and high cloud is assumed above the shallow cumulus cloud layer. In order to imitate poor representation of shallow cumulus in NWP models, cloud optical properties were horizontally averaged over the cloudy part of the boxes with dimensions comparable to NWP horizontal grid spacing (several km) and the common &#948;-Eddington two-stream method with maximum-random overlap assumption for partial cloudiness was applied (denoted as <q>1-D</q> experiment). The bias of the 1-D experiment relative to the benchmark was investigated in the solar and thermal part of the spectrum, examining the vertical profile of heating rate within the cloud layer and net surface flux. It is found that during daytime and nighttime, the destabilization of the cloud layer in the benchmark experiment is artifically enhanced by an overestimation of the cooling at cloud top and an overestimation of the warming at cloud bottom in the 1-D experiment (bias of about &#8722;15&#8201;K&#8201;day&#8722;1 is observed locally for stratocumulus scenarios). This destabilization, driven by the thermal radiation, is maximized during nighttime, since during daytime the solar radiation has a stabilizing tendency. The daytime bias at the surface is governed by the solar fluxes, where the 1-D solar net flux overestimates (underestimates) the corresponding benchmark at low (high) sun. The overestimation at low sun (bias up to 80&#8201;% over land and ocean) is largest at intermediate cloud cover, while underestimation at high sun (bias up to &#8722;40&#8201;% over land and ocean) is peaked at larger cloud cover (80&#8201;% and beyond). At nighttime, the 1-D experiment overestimates the amount of benchmark surface cooling with the maximal bias of about 50&#8201;% peaked at intermediate cloud cover. Moreover, an additional experiment was carried out by running the Monte Carlo radiation model in the independent column mode on cloud scenes preserving their LES structure (denoted as <q>ICA</q> experiment). The ICA is predominantly more accurate than the 1-D experiment (with respect to the same benchmark). This highlights the importance of an improved representation of clouds even at the resolution of today's regional (limited-area) numerical models, which needs to be considered if NWP radiative biases are to be efficiently reduced. All in all, this paper provides a systematic documentation of NWP radiative biases, which is a necessary first step towards an improved treatment of radiation&#8211;cloud interaction in atmospheric models.

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Mitigating errors in surface temperature forecasts using approximate radiation updates

Cited by 26 publications

References 17 publications

Stochastic representations of model uncertainties at ECMWF: state of the art and future vision

Stochastic representations of model uncertainties at ECMWF: state of the art and future vision

Effect of solar zenith angle specification in models on mean shortwave fluxes and stratospheric temperatures

Quantifying the bias of radiative heating rates in NWP models for shallow cumulus clouds

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