Implementation in the NCEP GFS of a Hybrid Eddy-Diffusivity Mass-Flux (EDMF) Boundary Layer Parameterization with Dissipative Heating and Modified Stable Boundary Layer Mixing

Han, Je-Chin; Witek, Marcin; Teixeira, J.; Sun, Ruiyu; Pan, Hua-Lu; Fletcher, Jennifer K.; Bretherton, Christopher S.

doi:10.1175/waf-d-15-0053.1

Cited by 92 publications

(52 citation statements)

References 37 publications

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“…A hybrid eddy‐diffusivity mass‐flux boundary‐layer parametrization was used as described by Han et al . (), but the dissipative heating in tropical cyclones that is used operationally was turned off for 20CRv3 (Pegion, personal communication, 2017 ) The coefficients that determine the auto‐conversion from ice to snow were decreased from the operational values of (6e‐4, 3e‐4) to (2e‐4, 2e‐4) as the larger values were found to give a substantial warm bias in the global mid‐troposphere. These lower values appear to be more consistent with the reduced spatial resolution used here.…”

Section: Appendicesmentioning

confidence: 88%

Towards a more reliable historical reanalysis: Improvements for version 3 of the Twentieth Century Reanalysis system

Slivinski

Compo

Whitaker

et al. 2019

Quart J Royal Meteoro Soc

615

434

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Historical reanalyses that span more than a century are needed for a wide range of studies, from understanding large‐scale climate trends to diagnosing the impacts of individual historical extreme weather events. The Twentieth Century Reanalysis (20CR) Project is an effort to fill this need. It is supported by the National Oceanic and Atmospheric Administration (NOAA), the Cooperative Institute for Research in Environmental Sciences (CIRES), and the U.S. Department of Energy (DOE), and is facilitated by collaboration with the international Atmospheric Circulation Reconstructions over the Earth initiative. 20CR is the first ensemble of sub‐daily global atmospheric conditions spanning over 100 years. This provides a best estimate of the weather at any given place and time as well as an estimate of its confidence and uncertainty. While extremely useful, version 2c of this dataset (20CRv2c) has several significant issues, including inaccurate estimates of confidence and a global sea level pressure bias in the mid‐19th century. These and other issues can reduce its effectiveness for studies at many spatial and temporal scales. Therefore, the 20CR system underwent a series of developments to generate a significant new version of the reanalysis. The version 3 system (NOAA‐CIRES‐DOE 20CRv3) uses upgraded data assimilation methods including an adaptive inflation algorithm; has a newer, higher‐resolution forecast model that specifies dry air mass; and assimilates a larger set of pressure observations. These changes have improved the ensemble‐based estimates of confidence, removed spin‐up effects in the precipitation fields, and diminished the sea‐level pressure bias. Other improvements include more accurate representations of storm intensity, smaller errors, and large‐scale reductions in model bias. The 20CRv3 system is comprehensively reviewed, focusing on the aspects that have ameliorated issues in 20CRv2c. Despite the many improvements, some challenges remain, including a systematic bias in tropical precipitation and time‐varying biases in southern high‐latitude pressure fields.

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Section: Appendicesmentioning

confidence: 88%

Towards a more reliable historical reanalysis: Improvements for version 3 of the Twentieth Century Reanalysis system

Slivinski

Compo

Whitaker

et al. 2019

Quart J Royal Meteoro Soc

615

434

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“…Such schemes can be coupled to a probabilistic cloud scheme (e.g., Sommeria & Deardorff, 1977) to form a complete SGS closure. EDMF schemes have been successfully implemented to represent boundary layer turbulence and shallow convection in several numerical weather prediction models (Han et al, 2016;K€ ohler, 2005;K€ ohler et al, 2011;Suselj et al, 2014).…”

Section: Citationmentioning

confidence: 99%

An Extended Eddy‐Diffusivity Mass‐Flux Scheme for Unified Representation of Subgrid‐Scale Turbulence and Convection

Tan

Kaul

Pressel

et al. 2018

J Adv Model Earth Syst

142

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Large‐scale weather forecasting and climate models are beginning to reach horizontal resolutions of kilometers, at which common assumptions made in existing parameterization schemes of subgrid‐scale turbulence and convection—such as that they adjust instantaneously to changes in resolved‐scale dynamics—cease to be justifiable. Additionally, the common practice of representing boundary‐layer turbulence, shallow convection, and deep convection by discontinuously different parameterizations schemes, each with its own set of parameters, has contributed to the proliferation of adjustable parameters in large‐scale models. Here we lay the theoretical foundations for an extended eddy‐diffusivity mass‐flux (EDMF) scheme that has explicit time‐dependence and memory of subgrid‐scale variables and is designed to represent all subgrid‐scale turbulence and convection, from boundary layer dynamics to deep convection, in a unified manner. Coherent up and downdrafts in the scheme are represented as prognostic plumes that interact with their environment and potentially with each other through entrainment and detrainment. The more isotropic turbulence in their environment is represented through diffusive fluxes, with diffusivities obtained from a turbulence kinetic energy budget that consistently partitions turbulence kinetic energy between plumes and environment. The cross‐sectional area of up and downdrafts satisfies a prognostic continuity equation, which allows the plumes to cover variable and arbitrarily large fractions of a large‐scale grid box and to have life cycles governed by their own internal dynamics. Relatively simple preliminary proposals for closure parameters are presented and are shown to lead to a successful simulation of shallow convection, including a time‐dependent life cycle.

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“…The performance of turbulence parameterizations was studied by various research teams 146 (e.g., Banks et al 2016, Tastula et al 2016, Han et al, 2016, Sakradzija et al 2016) but a 147 general understanding has still not been achieved. Sensitivity studies indicate that the non-148 local approach is more suitable for the CBL and turbulence driven primarily by buoyancy 149 (e.g., Pleim 2007).…”

Section: Santanello Et Al 2017) Precipitation Can Be Influenced Dirmentioning

confidence: 99%

A New Research Approach for Observing and Characterizing Land–Atmosphere Feedback

Wulfmeyer

Turner

Baker

et al. 2018

Bulletin of the American Meteorological Society

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38Forecast errors with respect to wind, temperature, moisture, clouds, and precipitation largely 39 correspond to the limited capability of current earth system models to capture and simulate 40 land-atmosphere feedback. To facilitate its realistic simulation in next generation models, an 41 improved process understanding of the related complex interactions is essential. To this end, 42 accurate 3D observations of key variables in the land-atmosphere (L-A) system with high 43 vertical and temporal resolution from the surface to the free troposphere are indispensable. 44Recently, we developed a synergy of innovative ground-based, scanning active remote sens-45 ing systems for 2D to 3D measurements of wind, temperature, and water vapor from the sur-46 face to the lower troposphere that is able to provide comprehensive data sets for characteriz-47 Motivation 71The land-atmosphere (L-A) system includes the soil, the land cover such as vegetation, and 72 the overlying atmosphere. The interaction of variables, e.g. related to the water and energy 73 budgets, results in characteristic natural variabilities and regimes as well as their changes due 74 to anthropogenic influences. The planetary boundary layer (PBL) is part of the L-A system 75 and represents the interface between the land surface and the free troposphere. Through an 76 exchange of momentum, energy and water, the dynamics, the thermodynamic structure, and 77 the evolution of the PBL affect the formation of shallow and deep clouds, convection initia-78 tion, and thus precipitation (Sherwood et al. 2010, Behrendt et al. 2011, Santanello et al. 79 2011, van den Hurk et al. 2011. One of the most complex feedback 80 loops is between soil moisture and precipitation (Seneviratne et al. 2010, Guillod et al. 2015, 81 Santanello et al. 2017). Precipitation can be influenced directly by the surface fluxes (Ek and 82Holtslag 2004), and indirectly via PBL dynamics and mesoscale circulations (Taylor et al. 83 2012). 84The PBL state and its evolution are strongly influenced by non-linear feedbacks in the L-A 85 system. These are due to two-way interactions between radiation, soil, vegetation, and atmos-86 pheric variables, which result in the diurnal cycles of surface fluxes. The feedbacks are rele-87 vant from local to global scales (Mahmood et al. 2013, Stéfanon et al. 2014, and their 88 strength varies both regionally and seasonally in dependence of soil moisture, advection, and 89 climate regimes. In locations where these feedbacks play an important role, it is likely that 90 they will become even more important due to anthropogenic climate change (Dirmeyer et al. 91 2012). Thus, to improve our understanding of the state and the evolution of the L-A system as 92 well as the dynamics and thermodynamics of the PBL, it is critical that feedbacks and fluxes 93 between the different components, including entrainment at the top of the PBL, are well char-94 4 acterized and appropriately represented in weather, climate, and earth system models (e.g., 95 Se...

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Implementation in the NCEP GFS of a Hybrid Eddy-Diffusivity Mass-Flux (EDMF) Boundary Layer Parameterization with Dissipative Heating and Modified Stable Boundary Layer Mixing

Cited by 92 publications

References 37 publications

Towards a more reliable historical reanalysis: Improvements for version 3 of the Twentieth Century Reanalysis system

Towards a more reliable historical reanalysis: Improvements for version 3 of the Twentieth Century Reanalysis system

An Extended Eddy‐Diffusivity Mass‐Flux Scheme for Unified Representation of Subgrid‐Scale Turbulence and Convection

A New Research Approach for Observing and Characterizing Land–Atmosphere Feedback

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