Changes In Model Resolution Research Articles

High temporal resolution generation expansion planning for the clean energy transition

As power systems integrate increasing quantities of wind, solar and energy storage resources, it is important to revisit power system capacity expansion modeling methods and assumptions that have been utilized in thermal-dominated systems. We conduct a series of case study analyses using a simplified representation of the Electric Reliability Council of Texas (ERCOT) system to demonstrate how least-cost capacity expansion outcomes are impacted by changes in model resolution across two temporal dimensions: 1) the number of considered representative periods, and 2) the system dispatch interval. First, we find that the least-cost generation portfolio can differ significantly for small changes in the number of representative days, but largely converges to the 365-day result once 104 representative days are considered. Furthermore, systems with wind, solar and storage resources were more sensitive to changes in the number of representative days than a thermal-dominated system. Second, we find that considering five-minute dispatch resolution consistently results in least-cost generation portfolios with less solar capacity and more energy storage capacity than corresponding scenarios with hourly dispatch intervals. This suggests that hourly dispatch representation fails to capture the intra-hour volatility of solar generation, and therefore also overlooks opportunities for storage resources to provide system value by balancing this volatility. Collectively these results indicate that capacity expansion modelers should revisit conventional approaches to temporal representation when conducting analyses of deeply decarbonized power systems to ensure that such analyses are robust and actionable. To our knowledge, this is the first study to analyze capacity expansion outcomes with five-minute dispatch resolution in this manner.

Sources of Uncertainty in Mid‐Tropospheric Tropical Humidity in Global Storm‐Resolving Simulations

AbstractWe conduct a series of eight 45‐day experiments with a global storm‐resolving model (GSRM) to test the sensitivity of relative humidity in the tropics to changes in model resolution and parameterizations. These changes include changes in horizontal and vertical grid spacing as well as in the parameterizations of microphysics and turbulence, and are chosen to capture currently existing differences among GSRMs. To link the distribution in the tropical free troposphere with processes in the deep convective regions, we adopt a trajectory‐based assessment of the last‐saturation paradigm. The perturbations we apply to the model result in tropical mean changes ranging from 0.5% to 8% (absolute) in the mid troposphere. The generated spread is similar to that in a multi‐model ensemble of GSRMs and smaller than the spread across conventional general circulation models, supporting that an explicit representation of deep convection reduces the uncertainty in tropical . The largest changes result from changes in parameterizations, suggesting that model physics represent a major source of humidity spread across GSRMs. The in the moist tropical regions is particularly sensitive to vertical mixing processes within the tropics, which impact through their effect on the last‐saturation temperature rather than their effect on the evolution of the humidity since last‐saturation. In our analysis the of the dry tropical regions strongly depends on the exchange with the extratropics. The interaction between tropics and extratropics could change with warming and presage changes in the radiatively sensitive dry regions.

Influence of Upper-Troposphere Stratification and Cloud-Radiation Interaction on Convective Overshoots in the Tropical Tropopause Layer

AbstractIt is still debated whether radiative heating observed in the tropical tropopause layer (TTL) is balanced primarily by cooling from convective overshoots, as in an entrainment layer, or by adiabatic cooling from large-scale eddy-driven upwelling. In this study, three-dimensional cloud-resolving model simulations of radiative-convective equilibrium were carried out with three different cloud microphysics schemes and 1-km horizontal resolution. We demonstrate that overshooting cooling in the TTL can be strongly modulated by upper-troposphere stratification. Two of the schemes produce a hard-landing scenario in which convective overshoots reach the TTL with frequent large vertical velocity leading to strong overshooting cooling (~ −0.2 K day-1). The third scheme produces a soft-landing scenario in which convective overshoots rarely reach the TTL with large vertical velocity and produce little overshooting cooling (~ −0.03 K day-1). The difference between the two scenarios is attributed to changes in the upper-troposphere stratification related to different atmospheric cloud radiative effects (ACRE). The microphysics scheme that produces the soft-landing scenario has much stronger ACRE in the upper troposphere leading to a ~3K warmer and more stable layer which acts as a buffer zone to slow down the convective updrafts. The stratification mechanism suggests the possibility for the ozone variation or eddy-driven upwelling in the TTL to modulate convective overshoots. We further test the sensitivity of overshooting cooling to changes in model resolution by increasing the horizontal resolution to 100 m. The corresponding change of overshooting cooling is much smaller compared with the difference between the hard-landing and soft-landing scenarios.

Sensitivity of Labrador Sea Water Formation to Changes in Model Resolution, Atmospheric Forcing, and Freshwater Input

AbstractLabrador Sea Water (LSW) is one of the main contributors to the lower limb of the Atlantic Meridional Overturning Circulation. In this study, we explore the sensitivity of LSW formation to model resolution, Greenland melt, absence of high‐frequency atmospheric phenomena, and changes in precipitation. We use five numerical model simulations at both (1/4)° and (1/12)° resolutions. A kinematic subduction approach is used to obtain the LSW formation rate over the period 2004 to 2016. The control simulation, with (1/4)° resolution, showed a mean annual production rate of 1.9 Sv (1 Sv = 106 m3/s) in the density range of 27.68–27.80 kg/m3 for the period 2004–2016. Deep convection events that occurred during 2008, 2012, and 2014–2016 were captured. We found that with (1/4)° resolution the LSW formation rate is 19% larger compared with its counterpart at (1/12)° resolution. The presence of Greenland melt and an increase in the precipitation impact the denser LSW layer replenishment but do not decrease the overall LSW formation rate nor the maximum convection depth. A dramatic response was found when filtering the atmospheric forcing, which induced a decrease of 44% in heat loss over the Labrador Sea, strong enough to halt the deep convection and decrease the LSW formation rate by 89%. Even if our experiment was extreme, a decrease in the storms crossing the Labrador Sea with a consequent reduction in the winter heat loss might be a bigger threat to deep convection and LSW formation in the future than the expected increases in the freshwater input.

The influence of model spatial resolution on simulated ozone and fine particulate matter for Europe: implications for health impact assessments

Abstract. We examine the impact of model horizontal resolution on simulated concentrations of surface ozone (O3) and particulate matter less than 2.5 µm in diameter (PM2.5), and the associated health impacts over Europe, using the HadGEM3–UKCA chemistry–climate model to simulate pollutant concentrations at a coarse (∼ 140 km) and a finer (∼ 50 km) resolution. The attributable fraction (AF) of total mortality due to long-term exposure to warm season daily maximum 8 h running mean (MDA8) O3 and annual-average PM2.5 concentrations is then calculated for each European country using pollutant concentrations simulated at each resolution. Our results highlight a seasonal variation in simulated O3 and PM2.5 differences between the two model resolutions in Europe. Compared to the finer resolution results, simulated European O3 concentrations at the coarse resolution are higher on average in winter and spring (∼ 10 and ∼ 6 %, respectively). In contrast, simulated O3 concentrations at the coarse resolution are lower in summer and autumn (∼ −1 and ∼ −4 %, respectively). These differences may be partly explained by differences in nitrogen dioxide (NO2) concentrations simulated at the two resolutions. Compared to O3, we find the opposite seasonality in simulated PM2.5 differences between the two resolutions. In winter and spring, simulated PM2.5 concentrations are lower at the coarse compared to the finer resolution (∼ −8 and ∼ −6 %, respectively) but higher in summer and autumn (∼ 29 and ∼ 8 %, respectively). Simulated PM2.5 values are also mostly related to differences in convective rainfall between the two resolutions for all seasons. These differences between the two resolutions exhibit clear spatial patterns for both pollutants that vary by season, and exert a strong influence on country to country variations in estimated AF for the two resolutions. Warm season MDA8 O3 levels are higher in most of southern Europe, but lower in areas of northern and eastern Europe when simulated at the coarse resolution compared to the finer resolution. Annual-average PM2.5 concentrations are higher across most of northern and eastern Europe but lower over parts of southwest Europe at the coarse compared to the finer resolution. Across Europe, differences in the AF associated with long-term exposure to population-weighted MDA8 O3 range between −0.9 and +2.6 % (largest positive differences in southern Europe), while differences in the AF associated with long-term exposure to population-weighted annual mean PM2.5 range from −4.7 to +2.8 % (largest positive differences in eastern Europe) of the total mortality. Therefore this study, with its unique focus on Europe, demonstrates that health impact assessments calculated using modelled pollutant concentrations, are sensitive to a change in model resolution by up to ∼ ±5 % of the total mortality across Europe.

Estimation of Systematic Errors in the GFS Using Analysis Increments

AbstractWe estimate the effect of model deficiencies in the Global Forecast System that lead to systematic forecast errors, as a first step toward correcting them online (i.e., within the model) as in Danforth & Kalnay (2008a, 2008b). Since the analysis increments represent the corrections that new observations make on the 6 h forecast in the analysis cycle, we estimate the model bias corrections from the time average of the analysis increments divided by 6 h, assuming that initial model errors grow linearly and first ignoring the impact of observation bias. During 2012–2016, seasonal means of the 6 h model bias are generally robust despite changes in model resolution and data assimilation systems, and their broad continental scales explain their insensitivity to model resolution. The daily bias dominates the submonthly analysis increments and consists primarily of diurnal and semidiurnal components, also requiring a low dimensional correction. Analysis increments in 2015 and 2016 are reduced over oceans, which we attribute to improvements in the specification of the sea surface temperatures. These results provide support for future efforts to make online correction of the mean, seasonal, and diurnal and semidiurnal model biases of Global Forecast System to reduce both systematic and random errors, as suggested by Danforth & Kalnay (2008a, 2008b). It also raises the possibility that analysis increments could be used to provide guidance in testing new physical parameterizations.

On the Selection of Localization Radius in Ensemble Filtering for Multiscale Quasigeostrophic Dynamics

Covariance localization remedies sampling errors due to limited ensemble size in ensemble data assimilation. Previous studies suggest that the optimal localization radius depends on ensemble size, observation density and accuracy, as well as the correlation length scale determined by model dynamics. A comprehensive localization theory for multiscale dynamical systems with varying observation density remains an active area of research. Using a two-layer quasigeostrophic (QG) model, this study systematically evaluates the sensitivity of the best Gaspari–Cohn localization radius to changes in model resolution, ensemble size, and observing networks. Numerical experiment results show that the best localization radius is smaller for smaller-scale components of a QG flow, indicating its scale dependency. The best localization radius is rather insensitive to changes in model resolution, as long as the key dynamical processes are reasonably well represented by the low-resolution model with inflation methods that account for representation errors. As ensemble size decreases, the best localization radius shifts to smaller values. However, for nonlocal correlations between an observation and state variables that peak at a certain distance, decreasing localization radii further within this distance does not reduce analysis errors. Increasing the density of an observing network has two effects that both reduce the best localization radius. First, the reduced observation error spectral variance further constrains prior ensembles at large scales. Less large-scale contribution results in a shorter overall correlation length, which favors a smaller localization radius. Second, a denser network provides more independent pieces of information, thus a smaller localization radius still allows the same number of observations to constrain each state variable.

Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52)

Abstract. Questions such as what is the contribution of road traffic emissions to climate change? or what is the impact of shipping emissions on local air quality? require a quantification of the contribution of specific emissions sectors to the concentration of radiatively active species and air-quality-related species, respectively. Here, we present a diagnostics package, implemented in the Modular Earth Submodel System (MESSy), which keeps track of the contribution of source categories (mainly emission sectors) to various concentrations. The diagnostics package is implemented as a submodel (TAGGING) of EMAC (European Centre for Medium-Range Weather Forecasts – Hamburg (ECHAM)/MESSy Atmospheric Chemistry). It determines the contributions of 10 different source categories to the concentration of ozone, nitrogen oxides, peroxyacytyl nitrate, carbon monoxide, non-methane hydrocarbons, hydroxyl, and hydroperoxyl radicals ( = tagged tracers). The source categories are mainly emission sectors and some other sources for completeness. As emission sectors, road traffic, shipping, air traffic, anthropogenic non-traffic, biogenic, biomass burning, and lightning are considered. The submodel obtains information on the chemical reaction rates, online emissions, such as lightning, and wash-out rates. It then solves differential equations for the contribution of a source category to each of the seven tracers. This diagnostics package does not feed back to any other part of the model. For the first time, it takes into account chemically competing effects: for example, the competition between NOx, CO, and non-methane hydrocarbons (NMHCs) in the production and destruction of ozone. We show that the results are in-line with results from other tagging schemes and provide plausibility checks for concentrations of trace gases, such as OH and HO2, which have not previously been tagged. The budgets of the tagged tracers, i.e. the contribution from individual source categories (mainly emission sectors) to, e.g., ozone, are only marginally sensitive to changes in model resolution, though the level of detail increases. A reduction in road traffic emissions by 5 % shows that road traffic global tropospheric ozone is reduced by 4 % only, because the net ozone productivity increases. This 4 % reduction in road traffic tropospheric ozone corresponds to a reduction in total tropospheric ozone by ≈ 0.3 %, which is compensated by an increase in tropospheric ozone from other sources by 0.1 %, resulting in a reduction in total tropospheric ozone of ≈ 0.2 %. This compensating effect compares well with previous findings. The computational costs of the TAGGING submodel are low with respect to computing time, but a large number of additional tracers are required. The advantage of the tagging scheme is that in one simulation and at every time step and grid point, information is available on the contribution of different emission sectors to the ozone budget, which then can be further used in upcoming studies to calculate the respective radiative forcing simultaneously.

Scaling of the entropy budget with surface temperature in radiative‐convective equilibrium

AbstractThe entropy budget of the atmosphere is examined in simulations of radiative‐convective equilibrium with a cloud‐system resolving model over a wide range of surface temperatures from 281 to 311 K. Irreversible phase changes and the diffusion of water vapor account for more than half of the irreversible entropy production within the atmosphere, even in the coldest simulation. As the surface temperature is increased, the atmospheric radiative cooling rate increases, driving a greater entropy sink that must be matched by greater irreversible entropy production. The entropy production resulting from irreversible moist processes increases at a similar fractional rate as the entropy sink and at a lower rate than that implied by Clausius‐Clapeyron scaling. This allows the entropy production from frictional drag on hydrometeors and on the atmospheric flow to also increase with warming, in contrast to recent results for simulations with global climate models in which the work output decreases with warming. A set of approximate scaling relations is introduced for the terms in the entropy budget as the surface temperature is varied, and many of the terms are found to scale with the mean surface precipitation rate. The entropy budget provides some insight into changes in frictional dissipation in response to warming or changes in model resolution, but it is argued that frictional dissipation is not closely linked to other measures of convective vigor.

Urban fluvial flood modelling using a two‐dimensional diffusion‐wave treatment, part 1: mesh resolution effects

AbstractHigh‐resolution data obtained from airborne remote sensing is increasing opportunities for representation of small‐scale structural elements (e.g. walls, buildings) in complex floodplain systems using two‐dimensional (2D) models of flood inundation. At the same time, 2D inundation models have been developed and shown to provide good predictions of flood inundation extent, with respect to both full solution of the depth‐averaged Navier–Stokes equations and simplified diffusion‐wave models. However, these models have yet to be applied extensively to urban areas. This paper applies a 2D raster‐based diffusion‐wave model to determine patterns of fluvial flood inundation in urban areas using high‐resolution topographic data and explores the effects of spatial resolution upon estimated inundation extent and flow routing process. Model response shows that even relatively small changes in model resolution have considerable effects on the predicted inundation extent and the timing of flood inundation. Timing sensitivity would be expected, given the relatively poor representation of inertial processes in a diffusion‐wave model. Sensitivity to inundation extent is more surprising, but is associated with: (1) the smoothing effect of mesh coarsening upon input topographical data; (2) poorer representation of both cell blockage and surface routing processes as the mesh is coarsened, where the flow routing is especially complex; and (3) the effects of (1) and (2) upon water levels and velocities, which in turn determine which parts of the floodplain the flow can actually travel to. It is shown that the combined effects of wetting and roughness parameters can compensate in part for a coarser mesh resolution. However, the coarser the resolution, the poorer the ability to control the inundation process, as these parameters not only affect the speed, but also the direction of wetting. Thus, high‐resolution data will need to be coupled to a more sophisticated representation of the inundation process in order to obtain effective predictions of flood inundation extent. This is explored in a companion paper. Copyright © 2005 John Wiley & Sons, Ltd.

Sensitivity studies with the North Atlantic sigma coordinate Princeton Ocean Model

The sigma coordinate, Princeton Ocean Model (POM) has been configured for the North Atlantic Ocean between 5°N and 50°N as part of data assimilation, model predictability and intercomparison studies. The model uses a curvilinear orthogonal grid with higher resolution in the western North Atlantic and lower resolution in the eastern North Atlantic. A series of experiments, each one of a 10-year duration, are performed to evaluate the sensitivity of the ocean mean state and variability to model parameters and model configuration; these experiments include open vs. closed boundary conditions, low vs. high resolution grids, and different choices of diffusion and viscosity. The results show that the use of closed boundaries together with near-boundary buffer zones where temperature and salinity are relaxed towards the observed values give less realistic flows, weaker recirculation gyres and less realistic Gulf Stream separation than do open boundary conditions. The experiments show that the sensitivity of the ocean variability in the model to the choice of the Smagorinsky diffusion and viscosity coefficients significantly differs from one region to another and largely depends on other attributes such as the mean position of the Gulf Stream in each simulation. A 50% change in model resolution in the Gulf Stream region has a larger effect on ocean variability than a change of diffusivity by a factor of 10. In areas where either the high or the low resolution models have sufficient resolution, as in the Gulf of Mexico, they are able to produce variability comparable to that observed from altimeter data; elsewhere, model variability is underestimated.

On the magnitude of transport out of the Antarctic polar vortex

The degree of isolation of the Antarctic stratospheric vortex in late winter and spring is investigated quantitatively by using a three‐dimensional global tracer transport model, in which the transport is computed from European Centre for Medium‐Range Weather Forecasts analyzed data. The evolution of the spatial distribution of passive tracers provides information about variations in the vortex structure, as well as about the magnitude of the transport out of the Antarctic vortex. The vortex structure revealed by tracers released inside the vortex at 72.5 hPa corresponds well with the satellite‐derived distribution of total ozone. The model computations indicate that in late winter and spring of the years 1990–1993, there is a quasi‐horizontal cross‐vortex transport of about 0.24% per day of the total tracer amount, while per day, 0.83% of the vortex mass descends into the troposphere. This indicates that roughly 65% of the vortex air is flushed out during August‐September‐October, the approximate lifetime of the Antarctic vortex. This number is insensitive to changes in model resolution, although the quasi‐horizontal outflow into the midlatitude stratosphere increases at the expense of the downward outflow if a coarser resolution is used. It is concluded that during late winter and early spring (i.e., the period of major ozone depletion), the vortex is a fairly well isolated air mass.