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- Author or Editor: K. Sakaguchi x
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Abstract
Eight Earth System Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated, focusing on both the net carbon dioxide flux and its components and their relation with climatic variables (temperature, precipitation, and soil moisture) in the historical (1850–2005) and representative concentration pathway 4.5 (RCP4.5; 2006–2100) simulations. While model results differ, their median globally averaged production and respiration terms from 1976 to 2005 agree reasonably with available observation-based products. Disturbances such as land use change are roughly represented but crucial in determining whether the land is a carbon source or sink over many regions in both simulations. While carbon fluxes vary with latitude and between the two simulations, the ratio of net to gross primary production, representing the ecosystem carbon use efficiency, is less dependent on latitude and does not differ significantly in the historical and RCP4.5 simulations. The linear trend of increased land carbon fluxes (except net ecosystem production) is accelerated in the twenty-first century. The cumulative net ecosystem production by 2100 is positive (i.e., carbon sink) in all models and the tropical and boreal latitudes become major carbon sinks in most models. The temporal correlations between annual-mean carbon cycle and climate variables vary substantially (including the change of sign) among the eight models in both the historical and twenty-first-century simulations. The ranges of correlations of carbon cycle variables with precipitation and soil moisture are also quite different, reflecting the important impact of the model treatment of the hydrological cycle on the carbon cycle.
Abstract
Eight Earth System Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated, focusing on both the net carbon dioxide flux and its components and their relation with climatic variables (temperature, precipitation, and soil moisture) in the historical (1850–2005) and representative concentration pathway 4.5 (RCP4.5; 2006–2100) simulations. While model results differ, their median globally averaged production and respiration terms from 1976 to 2005 agree reasonably with available observation-based products. Disturbances such as land use change are roughly represented but crucial in determining whether the land is a carbon source or sink over many regions in both simulations. While carbon fluxes vary with latitude and between the two simulations, the ratio of net to gross primary production, representing the ecosystem carbon use efficiency, is less dependent on latitude and does not differ significantly in the historical and RCP4.5 simulations. The linear trend of increased land carbon fluxes (except net ecosystem production) is accelerated in the twenty-first century. The cumulative net ecosystem production by 2100 is positive (i.e., carbon sink) in all models and the tropical and boreal latitudes become major carbon sinks in most models. The temporal correlations between annual-mean carbon cycle and climate variables vary substantially (including the change of sign) among the eight models in both the historical and twenty-first-century simulations. The ranges of correlations of carbon cycle variables with precipitation and soil moisture are also quite different, reflecting the important impact of the model treatment of the hydrological cycle on the carbon cycle.
Abstract
Atmospheric properties in a convective boundary layer vary over a wide range of spatial scales and are commonly studied using large-eddy simulations (LES) in various configurations. We examine how the boundary layer depth and distribution of variability across scales are affected by LES grid spacing, domain size, inhomogeneity of surface properties, and external forcing. Two different setups of the Weather Research and Forecasting (WRF) Model are analyzed. A semi-idealized configuration uses a periodic domain, flat surface, prescribed homogeneous surface heat fluxes, and horizontally uniform profiles of large-scale advective tendencies. A nested LES setup employs a larger domain and realistic initial and boundary conditions, including an interactive land surface model with representative topography and vegetation and soil types. Subdomains of identical size are analyzed for all simulations. Characteristic structure sizes are quantified using the variability scales L 50 and L 95, defined such that features smaller than that contain 50% and 95% of the total variance, respectively. Progressive increase in L 50 from vertical velocity to temperature and moisture structures is systematically reproduced in all simulation configurations. This dependence of L 50 on the considered variable complicates the development of scale-aware parameterizations for models with grid spacing in the “terra incognita.” In simulations using a larger domain with heterogeneous surface properties, the development of internal mesoscale patterns significantly affects variance distributions inside analyzed subdomains. Sizes of boundary layer structures also strongly depend on the LES grid spacing and, in case of heterogeneous surface and topography, on location of the subdomain inside a larger computational domain.
Abstract
Atmospheric properties in a convective boundary layer vary over a wide range of spatial scales and are commonly studied using large-eddy simulations (LES) in various configurations. We examine how the boundary layer depth and distribution of variability across scales are affected by LES grid spacing, domain size, inhomogeneity of surface properties, and external forcing. Two different setups of the Weather Research and Forecasting (WRF) Model are analyzed. A semi-idealized configuration uses a periodic domain, flat surface, prescribed homogeneous surface heat fluxes, and horizontally uniform profiles of large-scale advective tendencies. A nested LES setup employs a larger domain and realistic initial and boundary conditions, including an interactive land surface model with representative topography and vegetation and soil types. Subdomains of identical size are analyzed for all simulations. Characteristic structure sizes are quantified using the variability scales L 50 and L 95, defined such that features smaller than that contain 50% and 95% of the total variance, respectively. Progressive increase in L 50 from vertical velocity to temperature and moisture structures is systematically reproduced in all simulation configurations. This dependence of L 50 on the considered variable complicates the development of scale-aware parameterizations for models with grid spacing in the “terra incognita.” In simulations using a larger domain with heterogeneous surface properties, the development of internal mesoscale patterns significantly affects variance distributions inside analyzed subdomains. Sizes of boundary layer structures also strongly depend on the LES grid spacing and, in case of heterogeneous surface and topography, on location of the subdomain inside a larger computational domain.
ABSTRACT
Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. This paper highlights examples of current approaches to and innovative uses of regional climate modeling that deepen understanding of the climate system. High-resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that fine-scale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region’s climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding physical processes governing regional climate variability and change. The deeper understanding of regional climate processes also benefits stakeholders and policymakers who need physically robust, high-resolution climate information to guide societal responses to changing climate. Key scientific questions that will continue to require regional climate models, and opportunities are emerging for addressing those questions.
ABSTRACT
Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. This paper highlights examples of current approaches to and innovative uses of regional climate modeling that deepen understanding of the climate system. High-resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that fine-scale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region’s climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding physical processes governing regional climate variability and change. The deeper understanding of regional climate processes also benefits stakeholders and policymakers who need physically robust, high-resolution climate information to guide societal responses to changing climate. Key scientific questions that will continue to require regional climate models, and opportunities are emerging for addressing those questions.
