A Package of New Universal Non-Iterative Parametrizations for Stable Surface Layer Transfer Coefficients of Momentum, Heat and Moisture in Numerical Earth System Models

2021 ◽  
Author(s):  
Vladimir Gryanik ◽  
Christof Luepkes ◽  
Andrey Grachev ◽  
Dmitry Sidorenko
Keyword(s):  
Climate Models ◽  
Similarity Theory ◽  
Weather Prediction ◽  
Climate Projections ◽  
Transfer Coefficients ◽  
Near Surface ◽  
Stability Functions ◽  
Stable Surface Layer ◽  
Heat And Moisture ◽  
The Impact

<p><span>Results of weather forecast, present-day climate simulations and future climate projections depend among other factors on the interaction between the atmosphere and the underlying sea-ice, the land and the ocean. In numerical weather prediction and climate models some of these interactions are accounted for by transport coefficients describing turbulent exchange of momentum, heat and moisture. Currently used transfer coefficients have, however, large uncertainties in flow regimes being typical for cold nights and seasons, but especially in the polar regions. Furthermore, their determination is numerically complex. It is obvious that progress could be achieved when the transfer coefficients would be given by simple mathematical formulae in frames of an economic computational scheme. Such a new universal, so-called non-iterative parametrization scheme is derived for a package of transfer coefficients.</span></p><p><span>The derivation is based on the Monin-Obukhov similarity theory, which is over the years well accepted in the scientific community. The newly derived non-iterative scheme provides a basis for a cheap systematic study of the impact of near-surface turbulence and of the related transports of momentum, heat and moisture in NWP and climate models. </span></p><p><span>We show that often used transfer coefficients like those of Louis et al. (1982) or of Cheng and Brutsaert (2005) can be applied at large stability only with some caution, keeping in mind that at large stability they significantly overestimate the transfer coefficient compared with most comprehensive measurements. The latter are best reproduced by Gryanik et al. (2020) functions, which are part of the package. We show that the new scheme is flexible, thus, new stability functions can be added to the package, if required. </span></p><p> </p><p> <span>Gryanik, V.M., Lüpkes, C., Grachev, A., Sidorenko, D. (2020) New Modified and Extended Stability Functions for the Stable Boundary Layer based on SHEBA and Parametrizations of Bulk Transfer Coefficients for Climate Models, J. Atmos. Sci., 77, 2687-2716</span></p><p><br><br></p>

scholarly journals New Modified and Extended Stability Functions for the Stable Boundary Layer based on SHEBA and Parametrizations of Bulk Transfer Coefficients for Climate Models

2020 ◽  
Vol 77 (8) ◽  
pp. 2687-2716
Author(s):  
Vladimir M. Gryanik ◽  
Christof Lüpkes ◽  
Andrey Grachev ◽  
Dmitry Sidorenko
Keyword(s):  
Sea Ice ◽  
Richardson Number ◽  
Climate Models ◽  
Turbulent Fluxes ◽  
The Arctic ◽  
Bulk Richardson Number ◽  
Transfer Coefficients ◽  
Near Surface ◽  
Stability Functions ◽  
Stable Surface Layer

Abstract Climate models still have deficits in reproducing the surface energy and momentum budgets in Arctic regions. One of the reasons is that currently used transfer coefficients occurring in parameterizations of the turbulent fluxes are based on stability functions derived from measurements over land and not over sea ice. An improved parameterization is developed using the Monin–Obukhov similarity theory (MOST) and corresponding stability functions that reproduce measurements over sea ice obtained during the Surface Heat Budget of the Arctic Ocean (SHEBA) campaign. The new stability functions for the stable surface layer represent a modification of earlier ones also based on SHEBA measurements. It is shown that the new functions are superior to the former ones with respect to the representation of the measured relationship between the MOST stability parameter and the bulk Richardson number. Nevertheless, the functions fulfill the same criteria of applicability as the earlier functions and contain, as an extension, a dependence on the neutral-limit turbulent Prandtl number. Applying the new functions we develop an efficient noniterative parameterization of the near-surface turbulent fluxes of momentum and heat with transfer coefficients as a function of the bulk Richardson number (Rib) and roughness parameters. A hierarchy of transfer coefficients is recommended for weather and climate models. They agree better with SHEBA data for strong stability (Rib > 0.1) than previous parameterizations and they agree well with those based on the Businger–Dyer functions in the range Rib ≤ 0.1.

scholarly journals Changes in the Risk of Cool-Season Tornadoes over Southern Australia due to Model Projections of Anthropogenic Warming

2010 ◽  
Vol 23 (9) ◽  
pp. 2440-2449 ◽  
Author(s):  
B. Timbal ◽  
R. Kounkou ◽  
G. A. Mills
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Weather Prediction ◽  
First Century ◽  
Climate Projections ◽  
Cool Season ◽  
Near Surface ◽  
Impact Of Climate Change ◽  
Twenty First Century ◽  
The Impact

Abstract Anthropogenic climate change is likely to be felt most acutely through changes in the frequency of extreme meteorological events. However, quantifying the impact of climate change on these events is a challenge because the core of the climate change science relies on general circulation models to detail future climate projections, and many of these extreme events occur on small scales that are not resolved by climate models. This note describes an attempt to infer the impact of climate change on one particular type of extreme meteorological event—the cool-season tornadoes of southern Australia. The Australian Bureau of Meteorology predicts threat areas for cool-season tornadoes using fine-resolution numerical weather prediction model output to define areas where the buoyancy of a near-surface air parcel and the vertical wind shear each exceed specified thresholds. The diagnostic has been successfully adapted to coarser-resolution climate models and applied to simulations of the current climate, as well as future projections of the climate over southern Australia. Simulations of the late twentieth century are used to validate the models’ ability to reproduce the climatology of the risk of cool-season tornado formation by comparing these with similar computations based on historical reanalyses. Model biases are overcome by setting model specific thresholds to define the cool-season tornado risk. The diagnostic, applied to simulations of the twenty-first century, is then used to quantify the impact of the projected climate change on cool-season tornado risk. The sign of the response is consistent across all models: a decrease of the risk of formation during the twenty-first century is projected, driven by the thermodynamical response. The thermal response is modulated by the dynamical response, which varies between models. The projected decrease in tornadoes risk during the cool season is consistent with the projection of positive southern annular mode trends and the known influence of this mode of variability on interannual to intraseasonal time-scale variations in cool-season tornado occurrence.

scholarly journals Multi-layer coupling between SURFEX-TEB-V9.0 and Meso-NH-v5.3 for modelling the urban climate of high-rise cities

2020 ◽  
Author(s):  
Robert Schoetter ◽  
Yu Ting Kwok ◽  
Cécile de Munck ◽  
Kevin Ka Lun Lau ◽  
Wai Kin Wong ◽  
...  
Keyword(s):  
Weather Prediction ◽  
Grid Point ◽  
Urban Canopy ◽  
Atmospheric Model ◽  
Surface Model ◽  
Point Scale ◽  
Near Surface ◽  
High Rise ◽  
Heat And Moisture ◽  
The Impact

Abstract. Urban Canopy Models (UCMs) represent the exchange of momentum, heat, and moisture between cities and the atmosphere. Single-layer UCMs interact with the lowest atmospheric model level and are suited for low- to mid-rise cities whereas multi-layer UCMs interact with multiple levels and can also be employed for high-rise cities. The present study describes the multi-layer coupling between the UCM Town Energy Balance (TEB) included in the land surface model SURFEX and the mesoscale atmospheric model Meso-NH. This is a step towards better high-resolution weather prediction for urban areas in the future and studies quantifying the impact of climate change adaptation measures in high-rise cities. The effect of the buildings on the wind is considered using a drag force and a production term in the prognostic equation for turbulent kinetic energy. The heat and moisture fluxes from the walls and the roofs to the atmosphere are released at the model levels intersecting these urban facets. No variety of building height at grid point scale is considered to remain the consistency between the modification of the Meso-NH equations and the geometric assumptions of TEB. The multi-layer coupling is evaluated for the heterogeneous high-rise high-density city of Hong Kong. It leads to a strong improvement of model results for near-surface air temperature and relative humidity, which is due to better consideration of the process of horizontal advection in the urban canopy layer. For wind speed, model results are improved on average by the multi-layer coupling, but not for all stations. Future developments of the multi-layer SURFEX-TEB will focus on improving the calculation of radiative exchanges, which will allow a variety of building heights at grid point scale to be taken into account.

New modified and extended stability functions for the stable boundary layer based on SHEBA data

2020 ◽  
Author(s):  
Vladimir M. Gryanik ◽  
Andrey Grachev ◽  
Christof Lüpkes ◽  
Dmitry Sidorenko
Keyword(s):  
Boundary Layer ◽  
Sea Ice ◽  
Stable Boundary Layer ◽  
Richardson Number ◽  
Prediction Models ◽  
Weather Prediction ◽  
Bulk Richardson Number ◽  
Transfer Coefficients ◽  
Near Surface ◽  
Stability Functions

<p>The calculation of the near-surface turbulent fluxes of energy and momentum in climate and weather prediction models requires transfer coefficients. Currently used parametrizations of these coefficients are based on stability functions derived from measurements over land and not over sea ice. However, recently, a non-iterative parametrization has been proposed by Gryanik and Lüpkes (2018), which can be applied to climate and weather prediction models as well but uses stability functions of Grachev et al. (2007). These functions had been obtained from measurements during the Surface Heat Budget over the Arctic Ocean campaign (SHEBA) and thus from measurements over sea ice. A drawback of the scheme of Gryanik and Lüpkes (2018) is that there is still some complexity due to the complexity of the SHEBA based functions.</p><p>Thus new stability functions are proposed for the stable boundary layer, which are also based on the SHEBA measurements but avoid the complexity. It is shown that the new functions are superior to the former ones with respect to the representation of the measured relationship between the Obukhov length and the bulk Richardson number. Moreover, the resulting transfer coefficients agree slightly better with the SHEBA observations in the very stable range. Nevertheless, the functions fulfill the same criteria of applicability as the earlier functions and contain furthermore as an extension a dependence on the neutral Prandtl number. Applying the new functions, an efficient non-iterative parametrization of the near-surface turbulent fluxes of momentum and heat is developed where transfer coefficients result as a function of the bulk Richardson number (Ri<sub>b</sub>) and roughness parameters. The new transfer coefficients, which are recommended for weather and climate models, agree well with the SHEBA data in a large range of stability (0< Ri<sub>b</sub><0.5) and with those based on the Dyer-Businger functions in the range Ri<sub>b</sub> <0.08.</p><p><strong>References</strong></p><p><span>Grachev A.A., Andreas E.L, Fairall C.W., Guest P.S., Persson POG (2007) Boundary-Layer Meteorol., </span><span><strong>124</strong></span><span>, 315–333</span><span>.</span></p><p><span>Gryanik, V.M. and Lüpkes C. (2018) An Efficient Non-iterative Bulk Parametrization of Surface Fluxes for Stable Atmospheric Conditions Over Polar Sea-Ice,Boundary-Layer Meteorol 166:301-325</span></p>

scholarly journals Multi-layer coupling between SURFEX-TEB-v9.0 and Meso-NH-v5.3 for modelling the urban climate of high-rise cities

2020 ◽  
Vol 13 (11) ◽  
pp. 5609-5643
Author(s):  
Robert Schoetter ◽  
Yu Ting Kwok ◽  
Cécile de Munck ◽  
Kevin Ka Lun Lau ◽  
Wai Kin Wong ◽  
...  
Keyword(s):  
Weather Prediction ◽  
Grid Point ◽  
Urban Canopy ◽  
Atmospheric Model ◽  
Surface Model ◽  
Point Scale ◽  
Near Surface ◽  
High Rise ◽  
Heat And Moisture ◽  
The Impact

Abstract. Urban canopy models (UCMs) represent the exchange of momentum, heat, and moisture between cities and the atmosphere. Single-layer UCMs interact with the lowest atmospheric model level and are suited for low- to mid-rise cities, whereas multi-layer UCMs interact with multiple levels and can also be employed for high-rise cities. The present study describes the multi-layer coupling between the Town Energy Balance (TEB) UCM included in the Surface Externalisée (SURFEX) land surface model and the Meso-NH mesoscale atmospheric model. This is a step towards better high-resolution weather prediction for urban areas in the future and studies quantifying the impact of climate change adaptation measures in high-rise cities. The effect of the buildings on the wind is considered using a drag force and a production term in the prognostic equation for turbulent kinetic energy. The heat and moisture fluxes from the walls and the roofs to the atmosphere are released at the model levels intersecting these urban facets. No variety of building height at grid-point scale is considered to remain the consistency between the modification of the Meso-NH equations and the geometric assumptions of TEB. The multi-layer coupling is evaluated for the heterogeneous high-rise, high-density city of Hong Kong. It leads to a strong improvement of model results for near-surface air temperature and relative humidity, which is due to better consideration of the process of horizontal advection in the urban canopy layer. For wind speed, model results are improved on average by the multi-layer coupling but not for all stations. Future developments of the multi-layer SURFEX-TEB will focus on improving the calculation of radiative exchanges, which will allow a variety of building heights at grid-point scale to be taken into account.

scholarly journals Sensitivity of an Idealized Tropical Cyclone to the Configuration of the Global Forecast System–Eddy Diffusivity Mass Flux Planetary Boundary Layer Scheme

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 284
Author(s):  
Evan A. Kalina ◽  
Mrinal K. Biswas ◽  
Jun A. Zhang ◽  
Kathryn M. Newman
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Weather Prediction ◽  
Intensity Change ◽  
Rapid Intensification ◽  
Forecast System ◽  
Stability Functions ◽  
Non Local ◽  
The Stability ◽  
Heat And Moisture

The intensity and structure of simulated tropical cyclones (TCs) are known to be sensitive to the planetary boundary layer (PBL) parameterization in numerical weather prediction models. In this paper, we use an idealized version of the Hurricane Weather Research and Forecast system (HWRF) with constant sea-surface temperature (SST) to examine how the configuration of the PBL scheme used in the operational HWRF affects TC intensity change (including rapid intensification) and structure. The configuration changes explored in this study include disabling non-local vertical mixing, changing the coefficients in the stability functions for momentum and heat, and directly modifying the Prandtl number (Pr), which controls the ratio of momentum to heat and moisture exchange in the PBL. Relative to the control simulation, disabling non-local mixing produced a ~15% larger storm that intensified more gradually, while changing the coefficient values used in the stability functions had little effect. Varying Pr within the PBL had the greatest impact, with the largest Pr (~1.6 versus ~0.8) associated with more rapid intensification (~38 versus 29 m s−1 per day) but a 5–10 m s−1 weaker intensity after the initial period of strengthening. This seemingly paradoxical result is likely due to a decrease in the radius of maximum wind (~15 versus 20 km), but smaller enthalpy fluxes, in simulated storms with larger Pr. These results underscore the importance of measuring the vertical eddy diffusivities of momentum, heat, and moisture under high-wind, open-ocean conditions to reduce uncertainty in Pr in the TC PBL.

scholarly journals High-resolution fully-coupled atmospheric–hydrological modeling: a cross-compartment regional water and energy cycle evaluation

2020 ◽  
Author(s):  
Benjamin Fersch ◽  
Alfonso Senatore ◽  
Bianca Adler ◽  
Joël Arnault ◽  
Matthias Mauder ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Land Surface ◽  
Hydrological Modeling ◽  
Weather Prediction ◽  
Surface Model ◽  
Near Surface ◽  
Ground Heat Flux ◽  
The Impact ◽  
Fully Coupled ◽  
Regional Water

<p>The land surface and the atmospheric boundary layer are closely intertwined with respect to the exchange of water, trace gases and energy. Nonlinear feedback and scale dependent mechanisms are obvious by observations and theories. Modeling instead is often narrowed to single compartments of the terrestrial system or bound to traditional viewpoints of definite scientific disciplines. Coupled terrestrial hydrometeorological modeling systems attempt to overcome these limitations to achieve a better integration of the processes relevant for regional climate studies and local area weather prediction. We examine the ability of the hydrologically enhanced version of the Weather Research and Forecasting Model (WRF-Hydro) to reproduce the regional water cycle by means of a two-way coupled approach and assess the impact of hydrological coupling with respect to a traditional regional atmospheric model setting. It includes the observation-based calibration of the hydrological model component (offline WRF-Hydro) and a comparison of the classic WRF and the fully coupled WRF-Hydro models both with identical calibrated parameter settings for the land surface model (Noah-MP). The simulations are evaluated based on extensive observations at the pre-Alpine Terrestrial Environmental Observatory (TERENO Pre-Alpine) for the Ammer (600 km²) and Rott (55 km²) river catchments in southern Germany, covering a five month period (Jun–Oct 2016).</p><p>The sensitivity of 7 land surface parameters is tested using the <em>Latin-Hypercube One-factor-At-a-Time</em> (LH-OAT) method and 6 sensitive parameters are subsequently optimized for 6 different subcatchments, using the Model-Independent <em>Parameter Estimation and Uncertainty Analysis software</em> (PEST).</p><p>The calibration of the offline WRF-Hydro leads to Nash-Sutcliffe efficiencies between 0.56 and 0.64 and volumetric efficiencies between 0.46 and 0.81 for the six subcatchments. The comparison of classic WRF and fully coupled WRF-Hydro shows only tiny alterations for radiation and precipitation but considerable changes for moisture- and energy fluxes. By comparison with TERENO Pre-Alpine observations, the fully coupled model slightly outperforms the classic WRF with respect to evapotranspiration, sensible and ground heat flux, near surface mixing ratio, temperature, and boundary layer profiles of air temperature. The subcatchment-based water budgets show uniformly directed variations for evapotranspiration, infiltration excess and percolation whereas soil moisture and precipitation change randomly.</p>

scholarly journals Effect of the uncertainty in meteorology on air quality model predictions

Időjárás ◽  
2021 ◽  
Vol 125 (4) ◽  
pp. 625-646
Author(s):  
Zita Ferenczi ◽  
Emese Homolya ◽  
Krisztina Lázár ◽  
Anita Tóth
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Weather Prediction ◽  
Horizontal Resolution ◽  
Model System ◽  
Air Quality Model ◽  
Quality Model ◽  
Near Surface ◽  
The Impact

An operational air quality forecasting model system has been developed and provides daily forecasts of ozone, nitrogen oxides, and particulate matter for the area of Hungary and three big cites of the country (Budapest, Miskolc, and Pécs). The core of the model system is the CHIMERE off-line chemical transport model. The AROME numerical weather prediction model provides the gridded meteorological inputs for the chemical model calculations. The horizontal resolution of the AROME meteorological fields is consistent with the CHIMERE horizontal resolution. The individual forecasted concentrations for the following 2 days are displayed on a public website of the Hungarian Meteorological Service. It is essential to have a quantitative understanding of the uncertainty in model output arising from uncertainties in the input meteorological fields. The main aim of this research is to probe the response of an air quality model to its uncertain meteorological inputs. Ensembles are one method to explore how uncertainty in meteorology affects air pollution concentrations. During the past decades, meteorological ensemble modeling has received extensive research and operational interest because of its ability to better characterize forecast uncertainty. One such ensemble forecast system is the one of the AROME model, which has an 11-member ensemble where each member is perturbed by initial and lateral boundary conditions. In this work we focus on wintertime particulate matter concentrations, since this pollutant is extremely sensitive to near-surface mixing processes. Selecting a number of extreme air pollution situations we will show what the impact of the meteorological uncertainty is on the simulated concentration fields using AROME ensemble members.

Comparison of different infiltration schemes in the regional climate model REMO

2021 ◽  
Author(s):  
Daniel Abel ◽  
Katrin Ziegler ◽  
Felix Pollinger ◽  
Heiko Paeth
Keyword(s):  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Root Zone ◽  
Regional Climate ◽  
Climate Projections ◽  
Soil Hydrology ◽  
Spatiotemporal Resolution ◽  
Development Fund ◽  
Near Surface

<p>The European Regional Development Fund-Project BigData@Geo aims to create highly resolved climate projections for the model region of Lower Franconia in Bavaria, Germany. These projections are analyzed and made available to local stakeholders of agriculture, forestry, and viniculture as well as general public. Since regional climate models’ spatiotemporal resolution often is too coarse to deal with such local issues, the regional climate model REMO is improved within the frame of the project in cooperation with the Climate Service Center Germany (GERICS).</p><p>Accurate and highly resolved climate projections require realistic modeling of soil hydrology. Thus, REMO’s original bucket scheme is replaced by a 5-layer soil scheme. It allows for the representation of water below the root zone. Evaporation is possible solely from the top layer instead of the entire bucket and water can flow vertically between the layers. Consequently, the properties and processes change significantly compared to the bucket scheme. Both, the bucket and the 5-layer scheme, use the improved Arno scheme to separate throughfall into infiltration and surface runoff.</p><p>In this study, we examine if this scheme is suitable for use with the improved soil hydrology or if other schemes lead to better results. For this, we (1) modify the improved Arno scheme and further introduce the infiltration equations of (2) Philip as well as (3) Green and Ampt. First results of the comparison of these four different schemes and their influence on soil moisture and near-surface atmospheric variables are presented.</p>

scholarly journals Calculating the turbulent fluxes in the atmospheric surface layer with neural networks

2018 ◽  
Author(s):  
Lukas Hubert Leufen ◽  
Gerd Schädler
Keyword(s):  
Land Surface ◽  
Field Experiments ◽  
Climate Models ◽  
Similarity Theory ◽  
Turbulent Fluxes ◽  
Global Climate Models ◽  
Surface Model ◽  
Time Step ◽  
One Dimensional ◽  
Stability Functions

Abstract. The turbulent fluxes of momentum, heat and water vapour link the Earth's surface with the atmosphere. The correct modelling of the flux interactions between these two systems with very different time scales is therefore vital for climate (resp. Earth system) models. Conventionally, these fluxes are modelled using Monin–Obukhov similarity theory (MOST) with stability functions derived from a small number of field experiments; this results in a range of formulations of these functions and thus also in the flux calculations; furthermore, the underlying equations are non-linear and have to be solved iteratively at each time step of the model. For these reasons, we tried here a different approach, namely using an artificial neural network (ANN) to calculate the fluxes resp. the scaling quantities u* and θ*, thus avoiding explicit formulas for the stability functions. The network was trained and validated with multi-year datasets from seven grassland, forest and wetland sites worldwide using the Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton backpropagation algorithm and six-fold cross validation. Extensive sensitivity tests showed that an ANN with six input variables and one hidden layer gave results comparable to (and in some cases even slightly better than) the standard method. Similar satisfying results were obtained when the ANN routine was implemented in a one-dimensional stand alone land surface model (LSM), opening the way to implementation in three-dimensional climate models. In case of the one-dimensional LSM, no CPU time was saved when using the ANN version, since the small time step of the standard version required only one iteration in most cases. This could be different in models with longer time steps, e.g. global climate models.

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