A single-column model is used to estimate the equilibrium response of sea surface temperature (SST), precipitation, and several variables related to tropical cyclone activity to changes in both local and global forcing. Response to local forcing is estimated using the Weak Temperature Gradient (WTG) approximation. The surface temperature is calculated using a thin slab ocean so as to maintain surface energy balance. Forcing is varied by changing the solar constant, atmospheric CO2 concentration, surface wind speed, and the convergence of upper ocean heat flux. These experiments show that precipitation and variables related to tropical cyclone activity are not unique functions of SST on time scales long enough for surface energy balance to be maintained. Precipitation varies inversely with SST in experiments in which the surface wind speed is varied. At low wind speed, the WTG experiments reveal a regime of high relative SST and low precipitation, which is maintained by increased transmission of longwave radiation from the surface directly to space through a dry troposphere. In general, tropical cyclone potential intensity and genesis potential vary much more rapidly with SST in response to varying surface wind speed than in response to other forcings. Local changes in tropical cyclone potential intensity are highly correlated with local changes in SST, showing that relative SST is a good proxy for potential intensity when forcing is strictly local, but it cannot capture potentially important changes in potential intensity that arise from global-scale changes in forcing.
A nature run is a critical component of an observing system simulation experiment (OSSE), which is a framework for evaluating the potential impact of additional observations, enhanced observing systems, or alternative data assimilation schemes toward improving numerical weather forecasts. The nature run is a period of simulated weather generated by a research-quality numerical model, from which synthetic observations are sampled and provided to the data assimilation system and forecast model. This paper describes the development and validation of a nature run that depicts the life cycle of a strong hurricane over the North Atlantic Ocean. For compatibility with related research projects, the hurricane nature run is generated by a regional model, the Weather Research and Forecasting Model (WRF), embedded within the Joint OSSE global nature run previously generated by the European Center for Medium-Range Weather Forecasting. The domain sizes, resolution, and physical parameterizations used in the WRF simulation are discussed, and the evolution of the storm from tropical wave to recurving hurricane is described. The realism of the simulated hurricane is evaluated by comparing the model output to composited data from real hurricanes obtained from both in-situ and remotely sensed observations. These include the pressure-wind relationship, the kinematic and thermodynamic structure of the boundary layer, the size and outward slope of the radius of maximum winds (RMW), and contours of frequency by altitude diagrams (CFAD) of reflectivity and vertical velocity. The strengths and weaknesses of the nature run hurricane are discussed.
The present paper addresses the origin of natural variability arising internally from the climate system of the global carbon cycle at centennial time scales. The investigation is based on the MPI-M CMIP5 preindustrial control simulations with the MPI Earth System Model (MPI-ESM-LR) supplemented by additional simulations conducted for further analysis. The simulations show a distinct low frequency component in the global terrestrial carbon content that induces atmospheric CO2 variations on centennial time scales of up to 3 ppm. The main drivers for these variations are low frequency fluctuations in net primary production (NPP) of the land biosphere. The signal arises from small regions scattered across the whole globe with a pronounced source in North America. The main reason for the global NPP fluctuations is found in climatic changes leading to long term variations in LAI (leaf area index), which largely determines the strength of photosynthetic carbon assimilation. The underlying climatic changes encompass several, spacial diverse climatic alterations. For the particular case of North America, the carbon storage changes are (besides NPP) also dependent on soil respiration. This second mechanism is strongly connected to low frequency variations in incoming shortwave radiation at the surface.
This paper presents high horizontal resolution solutions of an axisymmetric, constant depth, slab boundary layer model designed to simulate the radial inflow and boundary layer pumping of a hurricane. Shock-like structures of increasing intensity appear for category 1 through 5 hurricanes. For example, in the category 3 case, the u(∂u/∂r) term in the radial equation of motion produces a shock-like structure in the radial wind, i.e., near the radius of maximum tangential wind the boundary layer radial inflow decreases from approximately 22 ms-1 to zero over a radial distance of a few kilometers. Associated with this large convergence is a spike in the radial distribution of boundary layer pumping, with updrafts larger than 22 ms-1 at a height of 1000 m. Based on these model results, it is argued that observed hurricane updrafts of this magnitude so close to the ocean surface are attributable to the dry dynamics of the frictional boundary layer rather than moist convective dynamics. The shock-like structure in the boundary layer radial wind also has important consequences for the evolution of the tangential wind and the vertical component of vorticity. On the inner side of the shock the tangential wind tendency is essentially zero, while on the outer side of the shock the tangential wind tendency is large due to the large radial inflow there. The result is the development of a U-shaped tangential wind profile and the development of a thin region of large vorticity. In many respects the model solutions resemble the remarkable structures observed in the boundary layer of Hurricane Hugo (1989).
MPI-ESM is a new version of the global Earth system model developed at the Max Planck Institute for Meteorology. This paper describes the ocean state and circulation as well as basic aspects of variability in simulations contributing to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The performance of the ocean/sea-ice model MPIOM, coupled to a new version of the atmosphere model ECHAM6 and modules for land surface and ocean biogeochemistry, is assessed for two model versions with different grid resolution in the ocean. The low-resolution configuration has a nominal resolution of 1.5° whereas the higher resolution version features a quasi uniform, eddy-permitting global resolution of 0.4°. The paper focuses on important oceanic features, such as surface temperature and salinity, water mass distribution, large-scale circulation, and heat and fresh water transports. In general, these integral quantities are simulated well in comparison with observational estimates, and improvements in comparison with the predecessor system are documented, for example, for tropical variability and sea ice representation. Introducing an eddy-permitting grid configuration in the ocean leads to improvements, in particular in the representation of interior water mass properties in the Atlantic and in the representation of important ocean currents, such as the Agulhas and Equatorial current systems. In general, however, there are more similarities than differences between the two grid configurations and several shortcomings, known from earlier versions of the coupled model, prevail.
This study investigates seasonal modulations of the quasi-biennial oscillation (QBO) of the tropical stratosphere. For this purpose, the Max Planck Institute Earth System Model (MPI-ESM), which internally generates a realistic QBO compared to the ERA-40 dataset, is employed. The modeled QBO is forced with resolved and parametrized waves. At 5 hPa, the seasonal distribution of the onset of QBO westerly jets clusters in spring and fall due to the coupling of the QBO and the semi-annual oscillation. This seasonal clustering of the westerly jets extends throughout the stratosphere, shifting to later months with increasing pressure. QBO westerly jets starting in the upper stratosphere in fall propagate to the middle stratosphere more slowly than westerly jets starting in spring. This is attributed to seasonal modulations of the QBO forcing and enhanced wave filtering by the QBO westerly jet in the lower stratosphere in fall and winter compared to spring and summer. The observed stalling of the QBO easterly jet in the lower stratosphere and the accompanied prolonged persistence of the QBO westerly jet in the vicinity of the tropopause are attributed equally to seasonal variations of the resolved and parametrized wave forcing and the advective forcing.
The purpose of this paper is to give a rather comprehensive description of the models for natural and anthropogenically driven changes in biogeography as implemented in the land component JSBACH of the Max Planck Institute Earth System Model (MPI-ESM). The model for natural land cover change (DYNVEG) features two types of competition: between the classes of grasses and woody types (trees, shrubs) controlled by disturbances (fire, wind-throw), as well as competition within those vegetation classes between different PFTs (plant functional types) based on relative NPP (net primary productivity) advantages. As part of this model, the distribution of land unhospitable to vegetation (hot and cold deserts) is determined dynamically from plant productivity under the prevailing climate conditions. The model for anthropogenic land cover change implements the land use transition approach by Hurtt et al. [2006]. Our implementation is based on the assumption that historically pastures have been preferentially established on former grasslands (“pasture rule”). We demonstrate that due to the pasture rule deforestation reduces global forest area between 1850 and 2005 by 15% less than without. Because of the pasture rule the land cover distribution depends on the full history of land use transitions. This has implications for the dynamics of natural landcover change, because assumptions must be made on how agriculturalists react to a changing natural vegetation in their environment. A separate model representing this process has been developed so that natural and anthropogenic land cover change can be simulated consistently. Certain aspects of our model implementation are illustrated by selected results from the recent CMIP5 simulations.
Climate change sensitivities of subtropical cloud-topped marine boundary layers are analyzed using large-eddy simulation (LES) of three CGILS cases of well-mixed stratocumulus, cumulus under stratocumulus, and shallow cumulus cloud regimes, respectively. For each case, a steadily forced control simulation on a small horizontally doubly-periodic domain is run 10-20 days into quasi-steady state. The LES is rerun to steady-state with forcings perturbed by changes in temperature, free-tropospheric relative humidity, CO2 concentration, subsidence, inversion stability, and wind speed; cloud responses to combined forcings superpose approximately linearly.
For all three cloud regimes and 2×CO2 forcing perturbations estimated from the CMIP3 multimodel mean, the LES predicts positive shortwave cloud feedback, like most CMIP3 global climate models. At both stratocumulus locations, the cloud remains overcast but thins in the warmer, moister, CO2-enhanced climate, due to the combined effects of an increased lower-tropospheric vertical humidity gradient and an enhanced free tropospheric greenhouse effect that reduces the radiative driving of turbulence. Reduced subsidence due to weakening of tropical overturning circulations partly counteracts these two factors by raising the inversion and allowing the cloud layer to deepen. These compensating mechanisms may explain the large scatter in low cloud feedbacks predicted by climate models. CMIP3-predicted changes in wind speed, inversion stability, and free-tropospheric relative humidity have lesser impacts on the cloud thickness.
In the shallow cumulus regime, precipitation regulates the simulated boundary layer depth and vertical structure. Cloud droplet (aerosol) concentration limits the boundary layer depth and affects the simulated cloud feedbacks.
Ocean biogeochemistry is a novel standard component of the CMIP5 experiments which project future climate change caused by anthropogenic emissions of greenhouse gases. Of particular interest here is the evolution of the oceanic sink of carbon and the oceanic contribution to the climate - carbon cycle feedback loop. The global ocean biogeochemistry model HAMOCC a component of the Earth system model MPI-ESM is employed to address these challenges. In this paper we describe the version of HAMOCC used in the CMIP5 experiments (HAMOCC 5.2) and its implementation in the MPI-ESM to provide a documentation and basis for future CMIP5 related studies. Modeled present day distributions of biogeochemical variables calculated in two different horizontal resolutions compare fairly well with observations. Statistical metrics indicate that the model performs better at the ocean surface and worse in the ocean interior. There is a tendency for improvements in the higher resolution model configuration in representing deeper ocean variables; however there is little to no improvement at the ocean surface. An experiment with free carbon cycle driven by emissions of CO2 produces a 25% higher variability in the oceanic carbon uptake over the historical period than the same model forced by prescribed atmospheric CO2 concentrations. Furthermore, a climate warming of 3.5 K projected at atmospheric CO2 concentration of four times the pre-industrial value, reduced the atmosphere - ocean CO2 flux by 1 GtC yr-1. Overall, the model shows consistent results in different configurations, being suitable for the type of simulations required within the CMIP5 experimental design.
The Madden-Julian oscillation (MJO), as represented by the Max Planck Institute for Meteorology Earth System Model (MPI-ESM), is analyzed for the first time over time periods ranging from decades to more than a millennium. Particular attention is paid to the behavior of the MJO index as calculated from the leading pair of EOFs derived from a multivariate EOF analysis. The analysis of thousand year simulations with the MPI-ESM and its predecessor, reveals significant interannual (2-6 yr) to interdecadal (10-20 yr) internal variability of the MJO, but relatively little evidence of significant variability at longer time scales in unforced runs. A 1200 year experiment forced by best estimates of solar variability, volcanism, and changing atmospheric composition, indicates that the MJO simulated in the 20th century is very similar to the MJO simulated since AD 800. The analysis of sensitivity experiments shows the influence of different external forcings: Solar variability may contribute to MJO variability on 11 and 22 year periods, but this is difficult to separate from internal variability; and there is a hint of enhanced decadal variability associated with volcanic forcing. Land use change, and changes associated with anthropogenic forcing over the 20th century have no detectable effect on the simulated MJO. An increase of the CO2 concentrations by 1% per year starting in AD 1850 leads to an increase in the MJO strength in the 21st century, as does the warming associated with an abrupt quadrupling of the atmospheric CO2 concentration, suggesting that the MJO may intensify with warming.
A radiative-convective equilibrium configuration of a comprehensive atmospheric general circulation model, ECHAM6, is coupled to a mixed-layer ocean for the purpose of advancing understanding of climate and climate change. This configuration differs from a standard configuration only through the removal of land-surface processes, spatial gradients in solar insolation, and the effects of rotation. Nonetheless, the model produces a climate that resembles the tropical climate in a control simulation of Earth's atmosphere. In the radiative-convective equilibrium (RCE) configuration regional inhomogeneities in surface temperature develop. These inhomogeneities are transient in time, but sufficiently long lived to establish large-scale overturning circulations with a distribution similar to the pre-industrial tropics in the standard configuration. The vertical structure of the atmosphere, including profiles of clouds and condensate conditioned on the strength of overturning, also resemble those produced by a control simulation of Earth's tropical atmosphere. The equilibrium climate sensitivity of the RCE atmosphere can explain 50% of the global climate sensitivity of a realistic configuration of ECHAM6. Part of the difference is attributed to the lack of polar amplification in RCE. The remainder appears to be related to a less positive cloud shortwave feedback, which results from an increase in low cloudiness with increasing surface temperatures in the RCE configuration. The RCE configuration shows an increase of climate sensitivity in a warmer climate. The increase in climate sensitivity scales with the degree to which the upper-troposphere temperature departs from a moist adiabat.
We define the f-plane, y-independent, potential vorticity (PV) invertibility principle as a coupled pair of first order partial differential equations relating the balanced wind and mass fields to the known PV. Analytical solutions of this invertibility principle are derived for cases in which an isolated PV anomaly is confined within a region of the vertical plane. The solutions aid in understanding the dynamics of low latitude PV intrusions whose associated cloud patterns are often referred to as cloud surges, or moisture bursts, and whose flow patterns are often referred to as tropical upper tropospheric troughs. The existence of such tongues of high PV air intruding into the upper troposphere are documented using reanalysis data from the ‘Year’ of Tropical Convection data set. The solutions illustrate the phenomenon of isentropic upglide below an upper tropospheric positive anomaly in PV. They also quantify how the partitioning of PV between absolute vorticity and static stability depends on the shape and strength of the PV anomaly. With slight modifications, the solutions apply to the problem of determining the balanced flow induced by a surface temperature anomaly, which is equivalent to a very thin layer of infinite PV at the surface. Through numerical solutions of the fully nonlinear invertibility principle we provide justification for the anelastic-type approximation used in the analytical theory.
[1] To assess the robustness of projected changes of the hydrological cycle simulated by an Earth system model (ESM), it is fundamental to validate the ESM and to characterize its major deficits. As the hydrological cycle is closely coupled to the energy cycle, a common large-scale evaluation of these fundamental components of the Earth system is highly beneficial, even though this has been rarely done up to now. Consequently, the purpose of the present study is the combined evaluation of land surface water and energy fluxes from the newest ESM version of the Max Planck Institute for Meteorology (MPI-ESM), which was used to produce an ensemble of Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations. With regard to energy fluxes, we especially make use of recent satellite data sets. Additionally, MPI-ESM results are compared with CMIP3 results from the predecessor of MPI-ESM, ECHAM5/MPIOM, as well as to results from the atmosphere/land part of MPI-ESM (ECHAM6/JSBACH) forced by observed sea surface temperature (SST). Analyses focus on regions where notable differences occur between the two ESM versions as well as between the fully coupled and the uncoupled SST-driven simulations. In general, our results show a considerable improvement of MPI-ESM in simulating surface shortwave radiation fluxes. The precipitation of the fully coupled simulations notably differs from those of the SST-forced simulations over a few river catchments. Over the Amazon catchment, the coupling to the ocean leads to a large negative precipitation bias, while for the Ganges/Brahmaputra, the coupling significantly improves the simulated precipitation.
]]>[1] Subtropical marine low cloud sensitivity to an idealized climate change is compared in six large-eddy simulation (LES) models as part of CGILS. July cloud cover is simulated at three locations over the subtropical northeast Pacific Ocean, which are typified by cold sea surface temperatures (SSTs) under well-mixed stratocumulus, cool SSTs under decoupled stratocumulus, and shallow cumulus clouds overlying warmer SSTs. The idealized climate change includes a uniform 2 K SST increase with corresponding moist-adiabatic warming aloft and subsidence changes, but no change in free-tropospheric relative humidity, surface wind speed, or CO2. For each case, realistic advective forcings and boundary conditions are generated for the control and perturbed states which each LES runs for 10 days into a quasi-steady state. For the control climate, the LESs correctly produce the expected cloud type at all three locations. With the perturbed forcings, all models simulate boundary-layer deepening due to reduced subsidence in the warmer climate, with less deepening at the warm-SST location due to regulation by precipitation. The models do not show a consistent response of liquid water path and albedo in the perturbed climate, though the majority predict cloud thickening (negative cloud feedback) at the cold-SST location and slight cloud thinning (positive cloud feedback) at the cool-SST and warm-SST locations. In perturbed climate simulations at the cold-SST location without the subsidence decrease, cloud albedo consistently decreases across the models. Thus, boundary-layer cloud feedback on climate change involves compensating thermodynamic and dynamic effects of warming and may interact with patterns of subsidence change.
]]>[1] Radiative transfer is sufficiently well understood that its parameterization in atmospheric models is primarily an effort to balance computational cost and accuracy. The most common approach is to compute radiative transfer with the highest practical spectral accuracy but infrequently in time and/or space, though errors introduced by this approximation are difficult to quantify. An alternative is to perform spectrally sparse calculations frequently in time using randomly chosen spectral quadrature points. Here we show that purely random quadrature points, though effective in some large-eddy simulations, are not a good choice for models in which the land surface responds to radiative fluxes because surface temperature perturbations can be large enough, and persistent long enough, to affect model evolution. These errors may be mitigated by choosing teams of spectral points designed to limit the maximum surface flux error; teams, rather than individual quadrature points, are then chosen randomly. The approach is implemented in the ECHAM6 global model and the results are examined using “perfect-model” experiments on time scales ranging from a day to a month. In this application the approach introduces errors commensurate with the infrequent calculation of broadband calculations for the same computational cost. But because teams need not increase with size, and indeed may become better and more balanced with increased spectral density, improvements in radiative transfer may not need to be traded off against spatiotemporal sampling.
]]>[2] A comprehensive 30×30 arc-second resolution gridded soil characteristics data set of China has been developed for use in the land surface modeling. It includes physical and chemical attributes of soils derived from 8979 soil profiles and the Soil Map of China (1:1,000,000). We used the polygon linkage method to derive the spatial distribution of soil properties. The profile attribute database and soil map are linked under the framework of the Genetic Soil Classification of China which avoids uncertainty in taxon referencing. Quality control information (i.e., sample size, soil classification level, linkage level, search radius and texture) is included to provide “confidence” information for the derived soil parameters. The data set includes 28 attributes for 8 vertical layers at the spatial resolution of 30×30 arc-seconds. Based on this data set, the estimated storage of soil organic carbon in the upper 1 m of soil is 72.5 Pg, total N is 6.6 Pg, total P is 4.5 Pg, total K is 169.9 Pg, alkali-hydrolysable N is 0.55 Pg, available P is 0.03 Pg, and available K is 0.61 Pg. These estimates are reasonable compared with previous studies. The distributions of soil properties are consistent with common knowledge of Chinese soil scientists and the spatial variations over large areas are well represented. The data set can be incorporated into land models to better represent the role of soils in hydrological and biogeochemical cycles in China.
]]>[1] ECHAM6, the sixth generation of the atmospheric general circulation model ECHAM, is described. Major changes with respect to its predecessor affect the representation of shortwave radiative transfer, the height of the model top. Minor changes have been made to model tuning and convective triggering. Several model configurations, differing in horizontal and vertical resolution, are compared. As horizontal resolution is increased beyond T63, the simulated climate improves but changes are incremental; major biases appear to be limited by the parameterization of small-scale physical processes, such as clouds and convection. Higher vertical resolution in the middle atmosphere leads to a systematic reduction in temperature biases in the upper troposphere, and a better representation of the middle atmosphere and its modes of variability. ECHAM6 represents the present climate as well as, or better than, its predecessor. The most marked improvements are evident in the circulation of the extratropics. ECHAM6 continues to have a good representation of tropical variability. A number of biases, however, remain. These include a poor representation of low-level clouds, systematic shifts in major precipitation features, biases in the partitioning of precipitation between land and sea (particularly in the tropics), and midlatitude jets that appear to be insufficiently poleward. The response of ECHAM6 to increasing concentrations of greenhouse gases is similar to that of ECHAM5. The equilibrium climate sensitivity of the mixed-resolution (T63L95) configuration is between 2.9 and 3.4 K and is somewhat larger for the 47 level model. Cloud feedbacks and adjustments contribute positively to warming from increasing greenhouse gases.
]]>[1] Over the past decade a new type of global climate model (GCM) has emerged, which is known as a multiscale modeling framework (MMF). Colorado State University's MMF represents a coupling between the Community Atmosphere Model and the System for Atmospheric Modeling (SAM) to serve as the cloud-resolving model (CRM) that replaces traditionally parameterized convection in GCMs. However, due to the high computational expense of the MMF, the grid size of the embedded CRM is typically limited to 4 km for long-term climate simulations. With grid sizes this coarse, shallow convective processes and turbulence cannot be resolved and must still be parameterized within the context of the embedded CRM. This paper describes a computationally efficient closure that aims to better represent turbulence and shallow convective processes in coarse-grid CRMs. The closure is based on the assumed probability density function (PDF) technique to serve as the subgrid-scale (SGS) condensation scheme and turbulence closure that employs a diagnostic method to determine the needed input moments. This paper describes the scheme, as well as the formulation of the eddy length which is empirically determined from large eddy simulation (LES) data. CRM tests utilizing the closure yields good results when compared to LESs for two trade-wind cumulus cases, a transition from stratocumulus to cumulus, and continental cumulus. This new closure improves the representation of clouds through the use of SGS condensation scheme and turbulence due to better representation of the buoyancy flux and dissipation rates. In addition, the scheme reduces the sensitivity of CRM simulations to horizontal grid spacing. The improvement when compared to the standard low-order closure configuration of the SAM is especially striking.
]]>[1] We describe the evolution of Arctic sea ice as modeled by the Max Planck Institute for Meteorology's Earth System Model (MPI-ESM). The modeled spatial distribution and interannual variability of the sea-ice cover agree well with satellite observations and are improved relative to the model's predecessor ECHAM5/MPIOM. An evaluation of modeled sea-ice coverage based on sea-ice area gives, however, conflicting results compared to an evaluation based on sea-ice extent and is additionally hindered by uncertainties in the observational record. Simulated trends in sea-ice coverage for the satellite period range from more strongly negative than observed to positive. The observed evolution of Arctic sea ice is incompatible with modeled internal variability and probably caused by external forcing. Simulated drift patterns agree well with observations, but simulated drift speed is generally too high. Simulated sea-ice volume agrees well with volume estimates of the PIOMAS reanalysis for the past few years. However, a preceding Arctic wide decrease in sea-ice volume starts much earlier in MPI-ESM than in PIOMAS. Analyzing this behavior in MPI-ESM's ocean model MPIOM, we find that the modeled volume trend depends crucially on the specific choice of atmospheric reanalysis forcing, which casts some doubt on the reliability of estimates of volume trends. In our CMIP5 scenario simulations, we find a substantial delay in sea-ice response to increasing CO2 concentration; a seasonally ice-free Arctic can result for a CO2 concentration of around 500 ppm. Simulated winter sea-ice coverage drops rapidly to near ice-free conditions once the mean Arctic winter temperature exceeds −5°C.
]]>[1] High-resolution climate models have been shown to improve the statistics of tropical storms (TCs) and hurricanes compared to low-resolution models. The impact of increasing horizontal resolution in the TC simulation is investigated exclusively using a series of Atmospheric Global Climate Model (AGCM) runs with idealized aquaplanet steady-state boundary conditions and a fixed operational storm-tracking algorithm. The results show that increasing horizontal resolution helps to detect more hurricanes, simulate stronger extreme rainfall, and emulate better storm structures in the models. However, increasing model resolution does not necessarily produce stronger hurricanes in terms of maximum wind speed, minimum sea-level pressure, and mean precipitation, as the increased number of storms simulated by high-resolution models is mainly associated with weaker storms. The spatial scale at which the analyses are conducted appears to have more important control on these meteorological statistics compared to horizontal resolution of the model grid. When the simulations are analyzed on common low-resolution grids, the statistics of the hurricanes, particularly the hurricane counts, show reduced sensitivity to the horizontal grid resolution and signs of scale invariance.
]]>[1] In the 1990s, scientists at European Centre for Medium-Range Weather Forecasts (ECMWF) suggested that artificially enhancing turbulent diffusion in stable conditions improves the representation of two important aspects of weather forecasts, i.e., near-surface temperatures and synoptic cyclones. Since then, this practice has often been used for tuning the large-scale performance of operational numerical weather prediction (NWP) models, although it is widely recognized to be detrimental for an accurate representation of stable boundary layers. Here we investigate why, 20 years on, such a compromise is still needed in the ECMWF model. We find that reduced turbulent diffusion in stable conditions improves the representation of winds in stable boundary layers, but it deteriorates the large-scale flow and the near-surface temperatures. This suggests that enhanced diffusion is still needed to compensate for errors caused by other poorly represented processes. Among these, we identify the orographic drag, which influences the large-scale flow in a similar way to the turbulence closure for stable conditions, and the strength of the land-atmosphere coupling, which partially controls the near-surface temperatures. We also take a closer look at the relationship between the turbulence closure in stable conditions and the large-scale flow, which was not investigated in detail with a global NWP model. We demonstrate that the turbulent diffusion in stable conditions affects the large-scale flow by modulating not only the strength of synoptic cyclones and anticyclones, but also the amplitude of the planetary-scale standing waves.
]]>[1] A radiative-convective equilibrium (RCE) configuration of a comprehensive atmospheric general circulation model, ECHAM6, is coupled to a mixed-layer ocean for the purpose of advancing understanding of climate and climate change. This configuration differs from a standard configuration only through the removal of land-surface processes, spatial gradients in solar insolation, and the effects of rotation. Nonetheless, the model produces a climate that resembles the tropical climate in a control simulation of Earth's atmosphere. In the RCE configuration, regional inhomogeneities in surface temperature develop. These inhomogeneities are transient in time but sufficiently long-lived to establish large-scale overturning circulations with a distribution similar to the preindustrial tropics in the standard configuration. The vertical structure of the atmosphere, including profiles of clouds and condensate conditioned on the strength of overturning, also resembles those produced by a control simulation of Earth's tropical atmosphere. The equilibrium climate sensitivity of the RCE atmosphere can explain 50% of the global climate sensitivity of a realistic configuration of ECHAM6. Part of the difference is attributed to the lack of polar amplification in RCE. The remainder appears to be related to a less positive cloud shortwave feedback, which results from an increase in low cloudiness with increasing surface temperatures in the RCE configuration. The RCE configuration shows an increase of climate sensitivity in a warmer climate. The increase in climate sensitivity scales with the degree to which the upper-troposphere temperature departs from a moist adiabat.
]]>[1] This study investigates the role of subgrid vertical transport in global simulations of soil-dust aerosols. The evolution and long-range transport of aerosols are strongly affected by vertical transport. In conventional global models, convective and turbulent transport is highly parameterized. This study applies the superparameterization (SP) framework in which a cloud-resolving model (CRM) is embedded in each grid cell of a global model to replace these parametric treatments with explicit simulation of subgrid processes at the cloud-system scale. We apply the implementation of the SP framework in the National Center for Atmospheric Research community atmospheric model (CAM) denoted by SPCAM for dust simulations. We focus on the effects of subgrid transport on dust simulations; thus, the sources and sinks of dust are calculated in the large-scale CAM grids, and the vertical transport of dust is computed in the CRM. We simulate present-day distributions of soil-dust aerosols using CAM and SPCAM operated in chemical transport mode with large-scale meteorological fields prescribed using the same meteorological reanalysis. Therefore, the differences of dust fields between two models caused by explicit versus parameterized treatments of convective transport are examined. Comparison of dust profiles shows that SPCAM predicts less dust in the low to mid troposphere but relatively higher concentration in the upper troposphere. The larger dust mass in upper troposphere in SPCAM may be related to the dust implementation approach in this study, in which the larger resolved updrafts in CRM for deep convection transport more dust aloft but are not accounted by the removal processes in the CRM grid scale. A slightly higher mobilization flux of less than 5% on an average is shown in SPCAM when compared with CAM. Similar patterns of elevated dry deposition are also produced with increases larger than 100% in some areas. For wet deposition, on average CAM is ∼31% higher than SPCAM. The average burden of dust in the simulated year for SPCAM and CAM is 14.8 and 19.7 Tg, respectively. The time-scale analysis shows the predicted dust lifetimes in SPCAM are shorter than CAM by approximately 1 day. The differences between CAM and SPCAM demonstrate that process-oriented treatments of convection can significantly affect the distributions, sources, and sinks of global soil-dust simulations.
]]>[1] An aquaplanet general circulation model is used to assess the sensitivity of intraseasonal variability to the pattern of sea surface temperature (SST) warming. Three warming patterns are used. Projected SST warming at the end of the 21st century from the Geophysical Fluid Dynamics Laboratory Climate Model 2.1 is one pattern, and zonally symmetric and globally uniform versions of this warming perturbation that have the same global mean SST change are the other two. Changes in intraseasonal variability are sensitive to the pattern of SST warming, with significant decreases in Madden-Julian oscillation (MJO)-timescale precipitation and wind variability for a zonally symmetric warming, and significant increases in MJO precipitation amplitude for a globally uniform warming. The amplitude of the wind variability change does not scale directly with precipitation, but is instead mediated by increased tropical dry static stability associated with SST warming. The patterned SST simulations have a zonal mean SST warming that maximizes on the equator, which fosters increased equatorial boundary layer convergence and also increases equatorial SST relative to the rest of the tropics. Both factors support increased convection, reflected in reduced gross moist stability (GMS). Mean precipitation is decreased and GMS is increased in the off-equatorial Eastern Hemisphere near 10°S in the patterned warming simulations, where the strongest MJO-related intraseasonal precipitation variability is preferred in both the model and observations. It is argued that future changes in MJO activity may be sensitive to the pattern of SST warming, although these results should not be interpreted as a prediction of how MJO activity will change in future climate.
]]>[1] In recent generation Earth system models (ESMs), land-surface grid cells are represented as tiles covered by different plant functional types such as trees or grasses. Here, we present an evaluation of the vegetation-cover module of the ESM developed at the Max Planck Institute for Meteorology in Hamburg, Germany (MPI-ESM) for present-day conditions. The vegetation continuous fields (VCF) product that is based on satellite observations in 2001 is used to evaluate the fractional distributions of woody vegetation cover and bare ground. The model performance is quantified using two metrics: a square of the Pearson correlation coefficient, r2, and the root-mean-square error (RMSE). On a global scale, r2 and RMSE of modeled tree cover are equal to 0.61 and 0.19, respectively, which we consider as satisfactory values. The model simulates tree cover and bare ground with r2 higher for the Northern Hemisphere (0.66) than for the Southern Hemisphere (0.48–0.50). We complement this analysis with an evaluation of the simulated land-surface albedo using the difference in net surface radiation. On a global scale, the correlation between modeled and observed albedos is high during all seasons, whereas the main disagreement occurs in spring in the high northern latitudes. This discrepancy can be attributed to a high sensitivity of the land-surface albedo to the simulated snow cover and snow-masking effect of trees. By contrast, the tropics are characterized by very high correlation and relatively low RMSE (5.4–6.5 W/m2) during all seasons. The presented approach could be applied for an evaluation of vegetation cover and land-surface albedo simulated by different ESMs.
]]>[1] This study explores the viability of parameter estimation in the comprehensive general circulation model ECHAM6 using ensemble Kalman filter data assimilation techniques. Four closure parameters of the cumulus-convection scheme are estimated using increasingly less idealized scenarios ranging from perfect-model experiments to the assimilation of conventional observations. Updated parameter values from experiments with real observations are used to assess the error of the model state on short 6 h forecasts and on climatological timescales. All parameters converge to their default values in single parameter perfect-model experiments. Estimating parameters simultaneously has a neutral effect on the success of the parameter estimation, but applying an imperfect model deteriorates the assimilation performance. With real observations, single parameter estimation generates the default parameter value in one case, converges to different parameter values in two cases, and diverges in the fourth case. The implementation of the two converging parameters influences the model state: Although the estimated parameter values lead to an overall error reduction on short timescales, the error of the model state increases on climatological timescales.
]]>[1] The Madden-Julian oscillation (MJO), as represented by the Max Planck Institute for Meteorology Earth System Model (MPI-ESM), is analyzed for the first time over time periods ranging from decades to more than a millennium. Particular attention is paid to the behavior of the MJO index as calculated from the leading pair of empirical orthogonal functions (EOFs) derived from a multivariate EOF analysis. The analysis of 1000 year simulations with the MPI-ESM and its predecessor reveals significant interannual (2–6 years) to interdecadal (10–20 years) internal variability of the MJO but relatively little evidence of significant variability at longer timescales in unforced runs. A 1200 year experiment forced by the best estimates of solar variability, volcanism, and changing atmospheric composition indicates that the MJO simulated in the twentieth century is very similar to the MJO simulated since AD 800. The analysis of sensitivity experiments shows the influence of different external forcings: solar variability may contribute to MJO variability on 11 and 22 year periods, but this is difficult to separate from internal variability; and there is a hint of enhanced decadal variability associated with volcanic forcing. Land use change and changes associated with anthropogenic forcing over the twentieth century have no detectable effect on the simulated MJO. An increase of the CO2 concentrations by 1% per year starting in AD 1850 leads to an increase in the MJO strength in the twenty-first century, as does the warming associated with an abrupt quadrupling of the atmospheric CO2 concentration, suggesting that the MJO may intensify with warming.
]]>[1] In this study, the sensitivity of tropical precipitation and convection to CO2 forcing is examined. In order to test the robustness of the response, two simulations with idealized CO2 forcings following CMIP5, one with a smooth and one with an abrupt CO2 increase, are analyzed. The simulations are performed with the Max Planck Institute Earth system model (MPI-ESM). Beyond investigating the mean precipitation response, high-frequency (30 min) direct output of the convection scheme is considered to better assess the ability of the convection scheme to reproduce results from cloud-resolving simulations or physical argumentation. Over the tropics, precipitation increases by 1.7% K−1 almost independently of the CO2 forcing. Over land, the response under transient CO2 forcing is also positive, but negative under an abrupt CO2 increase. In both cases precipitation tends to follow evaporation, but the latter reacts differently due to land surface processes. The Madden-Julian oscillation also shows different sensitivities for the two CO2 forced climates. As the climate warms, deep convection gets more intense, less frequent, and deeper. The cloud top temperatures remain constant, whereas cumulus congestus and shallow clouds warm. As such, the MPI-ESM and its convection scheme hold for the fixed-anvil temperature hypothesis. This implies an enhancement of the deep convective cloud height by 3–4% K−1. Changes in precipitation intensity and convective cloud base properties scale with the Clausius-Clapeyron equation, whereas the energy constraint determines changes in precipitation frequency. This is true over the tropics considered as a whole and over the tropical oceans, but breaks down over land.
]]>[1] The ECHAM6 atmospheric general circulation model is the atmosphere component of the Max Planck Institute Earth System Model (MPI-ESM) that is used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations. As ECHAM6 has its uppermost layer centered at 0.01 hPa in the upper mesosphere, these simulations offer the opportunity to study the middle atmosphere climate change and its relation to the troposphere on the basis of a very comprehensive set of state-of-the-art model simulations. The goals of this paper are (a) to introduce those new features of ECHAM6 particularly relevant for the middle atmosphere, including external forcing data, and (b) to evaluate the simulated middle atmosphere and describe the simulated response to natural and anthropogenic forcings. New features in ECHAM6 with respect to ECHAM5 include a new short-wave radiation scheme, the option to vary spectral irradiance independent of total solar irradiance, and a latitude-dependent gravity-wave source strength. The description of external forcing data focuses on solar irradiance and ozone. Stratospheric temperature trends simulated with the MPI-ESM for the last decades of the 20th century agree well with observations. The future projections depend strongly on the scenario. Under the high emission scenario RCP8.5, simulated temperatures are locally lower by more than 20 K than preindustrial values. Many of the simulated patterns of the responses to natural forcings as provided by solar variability, volcanic aerosols, and El Niño–Southern Oscillation, largely agree with the observations.
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