TopoSUB: a tool for efficient large area numerical modelling in complex topography at sub-grid scales

Abstract. Mountain regions are highly sensitive to global climate change. However, large scale assessments of mountain environments remain problematic due to the high resolution required of model grids to capture strong lateral variability. To alleviate this, tools are required to bridge the scale gap between gridded climate datasets (climate models and re-analyses) and mountain topography. We address this problem with a sub-grid method. It relies on sampling the most important aspects of land surface heterogeneity through a lumped scheme, allowing for the application of numerical land surface models (LSMs) over large areas in mountain regions or other heterogeneous environments. This is achieved by including the effect of mountain topography on these processes at the sub-grid scale using a multidimensional informed sampling procedure together with a 1-D lumped model that can be driven by gridded climate datasets. This paper provides a description of this sub-grid scheme, TopoSUB, and assesses its performance against a distributed model. We demonstrate the ability of TopoSUB to approximate results simulated by a distributed numerical LSM at around 104 less computations. These significant gains in computing resources allow for: (1) numerical modelling of processes at fine grid resolutions over large areas; (2) efficient statistical descriptions of sub-grid behaviour; (3) a "sub-grid aware" aggregation of simulated variables to coarse grids; and (4) freeing of resources for computationally intensive tasks, e.g., the treatment of uncertainty in the modelling process.

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TopoSUB: a tool for efficient large area numerical modelling in complex topography at sub-grid scales

Geoscientific Model Development Discussions ◽

10.5194/gmdd-5-1041-2012 ◽

2012 ◽

Vol 5 (2) ◽

pp. 1041-1076

Author(s):

J. Fiddes ◽

S. Gruber

Keyword(s):

Numerical Modelling ◽

Land Surface ◽

Large Scale ◽

Climate Models ◽

Global Climate ◽

Distributed Model ◽

Mountain Regions ◽

Large Area ◽

Fine Grid ◽

Lumped Model

Abstract. Mountain regions are highly sensitive to global climate change. However, large scale assessments of mountain environments remain problematic due to the high resolution required of model grids to capture strong lateral variability. To alleviate this, tools are required to bridge the scale gap between gridded climate datasets (climate models and re-analyses) and unresolved (by coarse grids) sub-grid mountain topography. We address this problem with a sub-grid method. It relies on sampling the most important aspects of land surface heterogeneity through a lumped scheme, allowing for the application of numerical land surface models (LSM) over large areas in mountain regions. This is achieved by including the effect of mountain topography on these processes at the sub-grid scale using a multidimensional informed sampling procedure together with a 1-D lumped model that can be driven by gridded climate datasets. This paper provides a description of this sub-grid scheme, TopoSUB, as well as assessing its performance against a distributed model. We demonstrate the ability of TopoSUB to approximate results simulated by a distributed numerical LSM at around 104 less computations. These significant gains in computing resources allow for: (1) numerical modelling of processes at fine grid resolutions over large areas; (2) extremely efficient statistical descriptions of sub-grid behaviour; (3) a "sub-grid aware" aggregation of simulated variables to course grids; and (4) freeing of resources for treatment of uncertainty in the modelling process.

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Terrestrial Aridity and Its Response to Greenhouse Warming across CMIP5 Climate Models

Journal of Climate ◽

10.1175/jcli-d-14-00480.1 ◽

2015 ◽

Vol 28 (14) ◽

pp. 5583-5600 ◽

Cited By ~ 76

Author(s):

Jacob Scheff ◽

Dargan M. W. Frierson

Keyword(s):

Land Surface ◽

Large Scale ◽

Climate Models ◽

Potential Evapotranspiration ◽

Global Climate ◽

Aridity Index ◽

Global Climate Models ◽

Greenhouse Warming ◽

Dimensionless Ratio ◽

The Tropics

Abstract The aridity of a terrestrial climate is often quantified using the dimensionless ratio of annual precipitation (P) to annual potential evapotranspiration (PET). In this study, the climatological patterns and greenhouse warming responses of terrestrial P, Penman–Monteith PET, and are compared among 16 modern global climate models. The large-scale climatological values and implied biome types often disagree widely among models, with large systematic differences from observational estimates. In addition, the PET climatologies often differ by several tens of percent when computed using monthly versus 3-hourly inputs. With greenhouse warming, land P does not systematically increase or decrease, except at high latitudes. Therefore, because of moderate, ubiquitous PET increases, decreases (drying) are much more widespread than increases (wetting) in the tropics, subtropics, and midlatitudes in most models, confirming and expanding on earlier findings. The PET increases are also somewhat sensitive to the time resolution of the inputs, although not as systematically as for the PET climatologies. The changes in the balance between P and PET are also quantified using an alternative aridity index, the ratio , which has a one-to-one but nonlinear correspondence with . It is argued that the magnitudes of changes are more uniformly relevant than the magnitudes of changes, which tend to be much higher in wetter regions. The ratio and its changes are also found to be excellent statistical predictors of the land surface evaporative fraction and its changes.

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Canopy-scale biophysical controls of transpiration and evaporation in the Amazon Basin

10.5194/hess-2015-552 ◽

2016 ◽

Author(s):

Kaniska Mallick ◽

Ivonne Trebs ◽

Eva Boegh ◽

Laura Giustarini ◽

Martin Schlerf ◽

...

Keyword(s):

Land Surface ◽

Water Resource Management ◽

Large Scale ◽

Amazon Basin ◽

Climate Models ◽

Global Climate ◽

Spatial Scales ◽

Analytical Framework ◽

Novel Approach ◽

Combining Data

Abstract. Canopy and aerodynamic conductances (gC and gA) are some of the key land surface variables determining the land surface response of climate models. Their representation is crucial for predicting transpiration (λET) and evaporation (λEE), which has important implications for global climate change and water resource management. Here, we present a novel approach to directly quantify the controls of the canopy-scale conductances on λET and λEE over multiple plant functions types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a physically-based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, λET, and atmospheric vapor pressure deficit (DA), which was originally postulated to occur at the leaf-scale. We show minor biophysical control on λET under wet conditions where net radiation (RN) determines 75 % to 80 % of the variances of λET. However, biophysical control on λET is amplified during the drought year (2005) and dry conditions, explaining 50 % to 65 % of the variances of λET. Despite substantial differences in gA, nearly similar “coupling” was found in forests and pastures due to the increase of gC induced by soil moisture. This suggests that the relative response of gC to per unit change of wetness is significantly higher compared to gA. Our results reveal the occurrence of a larger magnitude of hysteresis between λET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability compared to the rainforest. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework faithfully captures the responses of gC and gA to changing atmospheric radiation, DA, and surface skin temperature, and, thus appears to be promising for the improvement of existing land surface parameterisations at a range of spatial scales.

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Global climatology and trends in convective environments from ERA5 and rawinsonde data

npj Climate and Atmospheric Science ◽

10.1038/s41612-021-00190-x ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Mateusz Taszarek ◽

John T. Allen ◽

Mattia Marchio ◽

Harold E. Brooks

Keyword(s):

Large Scale ◽

Climate Models ◽

Global Climate ◽

Convective Available Potential Energy ◽

Global Climate Models ◽

Convective Precipitation ◽

The Past ◽

The Tropics ◽

Rawinsonde Data

AbstractGlobally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.

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Cities Exacerbate Climate Warming

Urban Science ◽

10.3390/urbansci5010027 ◽

2021 ◽

Vol 5 (1) ◽

pp. 27

Author(s):

Lahouari Bounoua ◽

Kurtis Thome ◽

Joseph Nigro

Keyword(s):

Surface Temperature ◽

Land Surface ◽

Large Scale ◽

Climate Models ◽

Warming Trend ◽

Climate Mitigation ◽

Temperature Changes ◽

Surface Warming ◽

The Us

Urbanization is a complex land transformation not explicitly resolved within large-scale climate models. Long-term timeseries of high-resolution satellite data are essential to characterize urbanization within land surface models and to assess its contribution to surface temperature changes. The potential for additional surface warming from urbanization-induced land use change is investigated and decoupled from that due to change in climate over the continental US using a decadal timescale. We show that, aggregated over the US, the summer mean urban-induced surface temperature increased by 0.15 °C, with a warming of 0.24 °C in cities built in vegetated areas and a cooling of 0.25 °C in cities built in non-vegetated arid areas. This temperature change is comparable in magnitude to the 0.13 °C/decade global warming trend observed over the last 50 years caused by increased CO2. We also show that the effect of urban-induced change on surface temperature is felt above and beyond that of the CO2 effect. Our results suggest that climate mitigation policies must consider urbanization feedback to put a limit on the worldwide mean temperature increase.

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A new world natural vegetation map for global change studies

Anais da Academia Brasileira de Ciências ◽

10.1590/s0001-37652008000200017 ◽

2008 ◽

Vol 80 (2) ◽

pp. 397-408 ◽

Cited By ~ 31

Author(s):

David M. Lapola ◽

Marcos D. Oyama ◽

Carlos A. Nobre ◽

Gilvan Sampaio

Keyword(s):

Large Scale ◽

New World ◽

Climate Models ◽

Global Climate ◽

Horizontal Resolution ◽

Vegetation Classification ◽

Natural Vegetation ◽

Global Climate Models ◽

Vegetation Map ◽

Vegetation Maps

We developed a new world natural vegetation map at 1 degree horizontal resolution for use in global climate models. We used the Dorman and Sellers vegetation classification with inclusion of a new biome: tropical seasonal forest, which refers to both deciduous and semi-deciduous tropical forests. SSiB biogeophysical parameters values for this new biome type are presented. Under this new vegetation classification we obtained a consensus map between two global natural vegetation maps widely used in climate studies. We found that these two maps assign different biomes in ca. 1/3 of the continental grid points. To obtain a new global natural vegetation map, non-consensus areas were filled according to regional consensus based on more than 100 regional maps available on the internet. To minimize the risk of using poor quality information, the regional maps were obtained from reliable internet sources, and the filling procedure was based on the consensus among several regional maps obtained from independent sources. The new map was designed to reproduce accurately both the large-scale distribution of the main vegetation types (as it builds on two reliable global natural vegetation maps) and the regional details (as it is based on the consensus of regional maps).

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Influence of the representation of convection on the mid-Holocene West African Monsoon

Climate of the Past ◽

10.5194/cp-17-1665-2021 ◽

2021 ◽

Vol 17 (4) ◽

pp. 1665-1684

Author(s):

Leonore Jungandreas ◽

Cathy Hohenegger ◽

Martin Claussen

Keyword(s):

Land Surface ◽

Large Scale ◽

Climate Models ◽

Climate Model ◽

Monsoon Season ◽

West African Monsoon ◽

West African ◽

Global Climate Models ◽

African Monsoon ◽

Monsoonal Precipitation

Abstract. Global climate models experience difficulties in simulating the northward extension of the monsoonal precipitation over north Africa during the mid-Holocene as revealed by proxy data. A common feature of these models is that they usually operate on grids that are too coarse to explicitly resolve convection, but convection is the most essential mechanism leading to precipitation in the West African Monsoon region. Here, we investigate how the representation of tropical deep convection in the ICOsahedral Nonhydrostatic (ICON) climate model affects the meridional distribution of monsoonal precipitation during the mid-Holocene by comparing regional simulations of the summer monsoon season (July to September; JAS) with parameterized and explicitly resolved convection. In the explicitly resolved convection simulation, the more localized nature of precipitation and the absence of permanent light precipitation as compared to the parameterized convection simulation is closer to expectations. However, in the JAS mean, the parameterized convection simulation produces more precipitation and extends further north than the explicitly resolved convection simulation, especially between 12 and 17∘ N. The higher precipitation rates in the parameterized convection simulation are consistent with a stronger monsoonal circulation over land. Furthermore, the atmosphere in the parameterized convection simulation is less stably stratified and notably moister. The differences in atmospheric water vapor are the result of substantial differences in the probability distribution function of precipitation and its resulting interactions with the land surface. The parametrization of convection produces light and large-scale precipitation, keeping the soils moist and supporting the development of convection. In contrast, less frequent but locally intense precipitation events lead to high amounts of runoff in the explicitly resolved convection simulations. The stronger runoff inhibits the moistening of the soil during the monsoon season and limits the amount of water available to evaporation in the explicitly resolved convection simulation.

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An evaluation of the importance of spatial resolution in a global climate and hydrological model based on the Rhine and Mississippi basin

10.5194/hess-2017-473 ◽

2017 ◽

Cited By ~ 1

Author(s):

Imme Benedict ◽

Chiel C. van Heerwaarden ◽

Albrecht H. Weerts ◽

Wilco Hazeleger

Keyword(s):

High Resolution ◽

Spatial Resolution ◽

Large Scale ◽

Climate Models ◽

Hydrological Cycle ◽

Global Climate ◽

Global Scale ◽

Global Climate Models ◽

Convective Processes ◽

Parameter Values

Abstract. The hydrological cycle of river basins can be simulated by combining global climate models (GCMs) and global hydrological models (GHMs). The spatial resolution of these models is restricted by computational resources and therefore limits the processes and level of detail that can be resolved. To further improve simulations of precipitation and river-runoff on a global scale, we assess and compare the benefits of an increased resolution for a GCM and a GHM. We focus on the Rhine and Mississippi basin. Increasing the resolution of a GCM (1.125° to 0.25°) results in more realistic large-scale circulation patterns over the Rhine and an improved precipitation budget. These improvements with increased resolution are not found for the Mississippi basin, most likely because precipitation is strongly dependent on the representation of still unresolved convective processes. Increasing the resolution of vegetation and orography in the high resolution GHM (from 0.5° to 0.05°) shows no significant differences in discharge for both basins, because the hydrological processes depend highly on other parameter values that are not readily available at high resolution. Therefore, increasing the resolution of the GCM provides the most straightforward route to better results. This route works best for basins driven by large-scale precipitation, such as the Rhine basin. For basins driven by convective processes, such as the Mississippi basin, improvements are expected with even higher resolution convection permitting models.

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Understanding Intermodel Variability in Future Projections of a Sahelian Storm Proxy and Southern Saharan Warming

Journal of Climate ◽

10.1175/jcli-d-20-0382.1 ◽

2021 ◽

Vol 34 (2) ◽

pp. 509-525

Author(s):

David P. Rowell ◽

Rory G. J. Fitzpatrick ◽

Lawrence S. Jackson ◽

Grace Redmond

Keyword(s):

Large Scale ◽

Climate Models ◽

Global Climate ◽

Vertical Wind Shear ◽

Global Climate Models ◽

Tropospheric Temperature ◽

Storm Activity ◽

Convective Systems ◽

The North ◽

Projected Changes

AbstractProjected changes in the intensity of severe rain events over the North African Sahel—falling from large mesoscale convective systems—cannot be directly assessed from global climate models due to their inadequate resolution and parameterization of convection. Instead, the large-scale atmospheric drivers of these storms must be analyzed. Here we study changes in meridional lower-tropospheric temperature gradient across the Sahel (ΔTGrad), which affect storm development via zonal vertical wind shear and Saharan air layer characteristics. Projected changes in ΔTGrad vary substantially among models, adversely affecting planning decisions that need to be resilient to adverse risks, such as increased flooding. This study seeks to understand the causes of these projection uncertainties and finds three key drivers. The first is intermodel variability in remote warming, which has strongest impact on the eastern Sahel, decaying toward the west. Second, and most important, a warming–advection–circulation feedback in a narrow band along the southern Sahara varies in strength between models. Third, variations in southern Saharan evaporative anomalies weakly affect ΔTGrad, although for an outlier model these are sufficiently substantive to reduce warming here to below that of the global mean. Together these uncertain mechanisms lead to uncertain southern Saharan/northern Sahelian warming, causing the bulk of large intermodel variations in ΔTGrad. In the southern Sahel, a local negative feedback limits the contribution to uncertainties in ΔTGrad. This new knowledge of ΔTGrad projection uncertainties provides understanding that can be used, in combination with further research, to constrain projections of severe Sahelian storm activity.

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A simple approach to mimic the effect of active vegetation in hydrological models to better estimate hydrological variables under climate change

10.5194/egusphere-egu21-12025 ◽

2021 ◽

Author(s):

Thedini Asali Peiris ◽

Petra Döll

Keyword(s):

Climate Change ◽

Land Surface ◽

Climate Models ◽

Potential Evapotranspiration ◽

Global Climate ◽

Global Climate Models ◽

Hydrological Models ◽

Net Radiation ◽

Ensemble Mean ◽

The Impact

Unlike global climate models, hydrological models cannot simulate the feedbacks among atmospheric processes, vegetation, water, and energy exchange at the land surface. This severely limits their ability to quantify the impact of climate change and the concurrent increase of atmospheric CO2 concentrations on evapotranspiration and thus runoff. Hydrological models generally calculate actual evapotranspiration as a fraction of potential evapotranspiration (PET), which is computed as a function of temperature and net radiation and sometimes of humidity and wind speed. Almost no hydrological model takes into account that PET changes because the vegetation responds to changing CO2 and climate. This active vegetation response consists of three components. With higher CO2 concentrations, 1) plant stomata close, reducing transpiration (physiological effect) and 2) plants may grow better, with more leaves, increasing transpiration (structural effect), while 3) climatic changes lead to changes in plants growth and even biome shifts, changing evapotranspiration. Global climate models, which include dynamic vegetation models, simulate all these processes, albeit with a high uncertainty, and take into account the feedbacks to the atmosphere.Milly and Dunne (2016) (MD) found that in the case of RCP8.5 the change of PET (computed using the Penman-Monteith equation) between 1981- 2000 and 2081-2100 is much higher than the change of non-water-stressed evapotranspiration (NWSET) computed by an ensemble of global climate models. This overestimation is partially due to the neglect of active vegetation response and partially due to the neglected feedbacks between the atmosphere and the land surface.The objective of this paper is to present a simple approach for hydrological models that enables them to mimic the effect of active vegetation on potential evapotranspiration under climate change, thus improving computation of freshwater-related climate change hazards by hydrological models. MD proposed an alternative approach to estimate changes in PET for impact studies that is only a function of the changes in energy and not of temperature and achieves a good fit to the ensemble mean change of evapotranspiration computed by the ensemble of global climate models in months and grid cells without water stress. We developed an implementation of the MD idea for hydrological models using the Priestley-Taylor equation (PET-PT) to estimate PET as a function of net radiation and temperature. With PET-PT, an increasing temperature trend leads to strong increases in PET. Our proposed methodology (PET-MD) helps to remove this effect, retaining the impact of temperature on PET but not on long-term PET change.We implemented the PET-MD approach in the global hydrological model WaterGAP2.2d. and computed daily time series of PET between 1981 and 2099 using bias-adjusted climate data of four global climate models for RCP 8.5. We evaluated, computed PET-PT and PET-MD at the grid cell level and globally, comparing also to the results of the Milly-Dunne study. The global analysis suggests that the application of PET-MD reduces the PET change until the end of this century from 3.341 mm/day according to PET-PT to 3.087 mm/day (ensemble mean over the four global climate models).Milly, P.C.D., Dunne K.A. (2016). DOI:10.1038/nclimate3046.

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