Abstract

The impact of changing the horizontal resolution of a version of the Hadley Centre GCM is investigated in present-day and 2 × CO₂ climate simulations. The use of higher resolution generally produces favorable changes. The main improvements are in the Southern Hemisphere in both solstitial seasons and in the Tropics and Northern Hemisphere in June, July, and August (JJA). Aspects of the model that show no improvement include the general coldness of the troposphere in all seasons and the pressure pattern in Northern Hemisphere winter. The global mean annual-mean warming due to increased CO₂ is very similar, but there are differences in the latitudinal distribution of the zonally averaged temperature response. In winter these differences can be related to the response of the Northern Hemisphere storm tracks. There is a considerable poleward and downstream shift of the high-frequency variability at higher resolution, which is only weakly simulated at low resolution. In JJA, the response of the tropical circulation and precipitation is very different where there were large differences in the unperturbed simulation.

Abstract

The importance of the representation of cloud in a general circulation model is investigated by utilizing four different parameterization schemes for layer cloud in a low-resolution version of the general circulation model at the Hadley Centre for Climate Prediction and Research at the United Kingdom Meteorological Office. The performance of each version of the model in terms of cloud and radiation is assessed in relation to satellite data from the Earth Radiation Budget Experiment (ERBE). Schemes that include a prognostic cloud water variable show some improvement on those with relative humidity-dependent cloud, but all still show marked differences from the ERBE data. The sensitivity of each of the versions of the model to a doubling of atmospheric C0₂ is investigated. Midlevel and lower-level clouds decrease when cloud is dependent on relative humidity, and this constitutes a strong positive feedback. When interactive cloud water is included, however, this effect is almost entirely compensated for by a negative feedback from the change of phase of cloud water from ice to water. Additional negative feedbacks are found when interactive radiative properties of cloud are included and these lead to an overall negative cloud feedback. The global warming produced with the four models then ranges from 5.4° with a relative humidity scheme to 1.9°C with interactive cloud water and radiative properties. Improving the treatment of ice cloud based on observations increases the model's sensitivity slightly to 2.1°C. Using an energy balance model, it is estimated that the climate sensitivity using the relative humidity scheme along with the negative feedback from cloud radiative properties would be 2.8°C. Thus, 2.8°–2.1°C appears to be a better estimate of the range of equilibrium response to a doubling Of C0₂.

Abstract

A comparison of the response to increasing greenhouse gas concentrations of two versions of the Met Office's (Hadley Centre) coupled atmosphere–ocean model reveals differences that result in large local variations in the modeled impact of climate change. With the aim of understanding the important processes and feedbacks associated with climate change, and ultimately reducing uncertainty in predictions, a series of sensitivity experiments were performed using a coupled atmosphere–mixed layer ocean model. The primary differences in the atmospheric response of the coupled models studied are found to be due to changes made to the physical representation of the atmosphere rather than to the ocean. In particular, many of the different patterns of response can be explained through changes made to the boundary layer scheme combining in a nonlinear way with changes to the cloud scheme to alter the tropical temperature and precipitation response in the model. A new land surface exchange scheme largely accounts for the different Northern Hemisphere continental surface temperature response.

Abstract

The effect of changes in atmospheric carbon dioxide concentrations and sulphate aerosols on near-surface temperature is investigated using a version of the Hadley Centre atmospheric model coupled to a mixed layer ocean. The scattering of sunlight by sulphate aerosols is represented by appropriately enhancing the surface albede.

On doubling atmospheric carbon dioxide concentrations, the global mean temperature increases by 5.2 K. An integration with a 39% increase in CO₂, giving the estimated change in radiative heating due to increases in greenhouse gases since 1900, produced an equilibrium warming of 2.3 K, which, even allowing for oceanic inertia, is significantly higher than the observed warming over the same period. Furthermore, the simulation suggests a substantial warming everywhere, whereas the observations indicate isolated regions of cooling including parts of the northern midlatitude continents. The addition of an estimate of the effect of scattering by current industrial aerosols (uncertain by a factor of at least 3) leads to improved agreement with the observed pattern of changes over the northern continents and reduces the global mean warming by about 30%. Doubling the aerosol forcing produces patterns that are still compatible with the observations, but further increase leads to unrealistically extensive cooling in the midlatitudes.

The diurnal range of surface temperature decreases over most of the northern extratropics on increasing CO₂, in agreement with recent observations. The addition of the current industrial aerosol had little detectable effect on the diurnal range in the model because the direct effect of reduced solar heating at the surface is approximately balanced by the indirect effects of cooling. Thus, the ratio of the reduction in diurnal range to the mean warming is increased, in closer agreement with observations.

Results from further sensitivity experiments with larger increases in aerosol and CO₂ are presented. Although the aerosol forcing is a strong maximum in the northern midlatitudes in summer, the response is fairly even throughout the year because sea ice feedbacks amplify the cooling in winter. Increasing the aerosol loading produces a consistent increase in the globally averaged diurnal temperature range, associated with the mean reduction in temperature, though the diurnal range decreases slightly where the aerosol loading is greatest. The response to increased CO₂ is compared with that in other models.

Abstract

The Transpose-Atmospheric Model Intercomparison Project (AMIP) is an international model intercomparison project in which climate models are run in “weather forecast mode.” The Transpose-AMIP II experiment is run alongside phase 5 of the Coupled Model Intercomparison Project (CMIP5) and allows processes operating in climate models to be evaluated, and the origin of climatological biases to be explored, by examining the evolution of the model from a state in which the large-scale dynamics, temperature, and humidity structures are constrained through use of common analyses.

The Transpose-AMIP II experimental design is presented. The project requests participants to submit a comprehensive set of diagnostics to enable detailed investigation of the models to be performed. An example of the type of analysis that may be undertaken using these diagnostics is illustrated through a study of the development of cloud biases over the Southern Ocean, a region that is problematic for many models. Several models share a climatological bias for too little reflected shortwave radiation from cloud across the region. This is found to mainly occur behind cold fronts and/or on the leading side of transient ridges and to be associated with more stable lower-tropospheric profiles. Investigation of a case study that is typical of the bias and associated meteorological conditions reveals the models to typically simulate cloud that is too optically and physically thin with an inversion that is too low. The evolution of the models within the first few hours suggests that these conditions are particularly sensitive and a positive feedback can develop between the thinning of the cloud layer and boundary layer structure.

Abstract

The Coupled Model Intercomparison Project (CMIP) is an ongoing coordinated international activity of numerical experimentation of unprecedented scope and impact on climate science. Its most recent phase, the fifth phase (CMIP5), has created nearly 2 PB of output from dozens of experiments performed by dozens of comprehensive climate models available to the climate science research community. In so doing, it has greatly advanced climate science. While CMIP5 has given answers to important science questions, with the help of a community survey we identify and motivate three broad topics here that guided the scientific framework of the next phase of CMIP, that is, CMIP6:

1. How does the Earth system respond to changes in forcing?

2. What are the origins and consequences of systematic model biases?

3. How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios?

CMIP has demonstrated the power of idealized experiments to better understand how the climate system works. We expect that these idealized approaches will continue to contribute to CMIP6. The quantification of radiative forcings and responses was poor, and thus it requires new methods and experiments to address this gap. There are a number of systematic model biases that appear in all phases of CMIP that remain a major climate modeling challenge. These biases need increased attention to better understand their origins and consequences through targeted experiments. Improving understanding of the mechanisms’ underlying internal climate variability for more skillful decadal climate predictions and long-term projections remains another challenge for CMIP6.

Abstract

The reduction of systematic errors is a continuing challenge for model development. Feedbacks and compensating errors in climate models often make finding the source of a systematic error difficult. In this paper, it is shown how model development can benefit from the use of the same model across a range of temporal and spatial scales. Two particular systematic errors are examined: tropical circulation and precipitation distribution, and summer land surface temperature and moisture biases over Northern Hemisphere continental regions. Each of these errors affects the model performance on time scales ranging from a few days to several decades. In both cases, the characteristics of the long-time-scale errors are found to develop during the first few days of simulation, before any large-scale feedbacks have taken place. The ability to compare the model diagnostics from the first few days of a forecast, initialized from a realistic atmospheric state, directly with observations has allowed physical deficiencies in the physical parameterizations to be identified that, when corrected, lead to improvements across the full range of time scales. This study highlights the benefits of a seamless prediction system across a wide range of time scales.

Abstract

The future change in dry and humid heatwaves is assessed in 10-yr pan-African convective-scale (4.5 km) and parameterized convection (25 km) climate model simulations. Compared to reanalysis, the convective-scale simulation is better able to represent humid heatwaves than the parameterized simulation. Model performance for dry heatwaves is much more similar. Both model configurations simulate large increases in the intensity, duration, and frequency of heatwaves by 2100 under RCP8.5. Present-day conditions that occur on 3–6 heatwave days per year will be normal by 2100, occurring on 150–180 days per year. The future change in dry heatwaves is similar in both climate model configurations, whereas the future change in humid heatwaves is 56% higher in intensity and 20% higher in frequency in the convective-scale model. Dry heatwaves are associated with low rainfall, reduced cloud, increased surface shortwave heating, and increased sensible heat flux. In contrast, humid heatwaves are predominately controlled by increased humidity, rainfall, cloud, longwave heating, and evaporation, with dry-bulb temperature gaining more significance in the most humid regions. Approximately one-third (32%) of humid heatwaves commence on wet days. Moist processes are known to be better represented in convective-scale models. Climate models with parameterized convection, such as those in CMIP, may underestimate the future change in humid heatwaves, which heightens the need for mitigation and adaptation strategies and indicates there may be less time available to implement them to avoid future catastrophic heat stress conditions than previously thought.

Abstract

A new coupled general circulation climate model developed at the Met Office's Hadley Centre is presented, and aspects of its performance in climate simulations run for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) documented with reference to previous models. The Hadley Centre Global Environmental Model version 1 (HadGEM1) is built around a new atmospheric dynamical core; uses higher resolution than the previous Hadley Centre model, HadCM3; and contains several improvements in its formulation including interactive atmospheric aerosols (sulphate, black carbon, biomass burning, and sea salt) plus their direct and indirect effects. The ocean component also has higher resolution and incorporates a sea ice component more advanced than HadCM3 in terms of both dynamics and thermodynamics. HadGEM1 thus permits experiments including some interactive processes not feasible with HadCM3. The simulation of present-day mean climate in HadGEM1 is significantly better overall in comparison to HadCM3, although some deficiencies exist in the simulation of tropical climate and El Niño variability. We quantify the overall improvement using a quasi-objective climate index encompassing a range of atmospheric, oceanic, and sea ice variables. It arises partly from higher resolution but also from greater fidelity in modeling dynamical and physical processes, for example, in the representation of clouds and sea ice. HadGEM1 has a similar effective climate sensitivity (2.8 K) to a CO₂ doubling as HadCM3 (3.1 K), although there are significant regional differences in their response patterns, especially in the Tropics. HadGEM1 is anticipated to be used as the basis both for higher-resolution and higher-complexity Earth System studies in the near future.

Abstract

Pan-Africa convection-permitting regional climate model simulations have been performed to study the impact of high resolution and the explicit representation of atmospheric moist convection on the present and future climate of Africa. These unique simulations have allowed European and African climate scientists to understand the critical role that the representation of convection plays in the ability of a contemporary climate model to capture climate and climate change, including many impact-relevant aspects such as rainfall variability and extremes. There are significant improvements in not only the small-scale characteristics of rainfall such as its intensity and diurnal cycle, but also in the large-scale circulation. Similarly, effects of explicit convection affect not only projected changes in rainfall extremes, dry spells, and high winds, but also continental-scale circulation and regional rainfall accumulations. The physics underlying such differences are in many cases expected to be relevant to all models that use parameterized convection. In some cases physical understanding of small-scale change means that we can provide regional decision-makers with new scales of information across a range of sectors. We demonstrate the potential value of these simulations both as scientific tools to increase climate process understanding and, when used with other models, for direct user applications. We describe how these ground-breaking simulations have been achieved under the U.K. Government’s Future Climate for Africa Programme. We anticipate a growing number of such simulations, which we advocate should become a routine component of climate projection, and encourage international coordination of such computationally and human-resource expensive simulations as effectively as possible.