Intercomparison and validation of snow albedo parameterization schemes in climate models

Snow albedo is known to be crucial for heat exchange at high latitudes and high altitudes, and is also an important parameter in General Circulation Models (GCMs) because of its strong positive feedback properties. In this study, seven GCM snow albedo schemes and a multiple linear regression model were intercompared and validated against 59 years of in situ data from Svalbard, the French Alps and six stations in the former Soviet Union. For each site, the significant meteorological parameters for modeling the snow albedo were identified by constructing the 95% confidence intervals. The significant parameters were found to be: temperature, snow depth, positive degree day and a dummy of snow depth, and the multiple linear regression model was constructed to include these. Overall, the intercomparison showed that the modeled snow albedo varied more than the observed albedo for all models, and that the albedo was often underestimated. In addition, for several of the models, the snow albedo decreased at a faster rate or by a greater magnitude during the winter snow metamorphosis than the observed albedo. Both the temperature dependent schemes and the prognostic schemes showed shortcomings.     

Emulating AOGCM results using simple climate models

Three simple climate models (SCMs) are calibrated using simulations from atmosphere ocean general circulation models (AOGCMs). In addition to using two conventional SCMs, results from a third simpler model developed specifically for this study are obtained. An easy to implement and comprehensive iterative procedure is applied that optimises the SCM emulation of global-mean surface temperature and total ocean heat content, and, if available in the SCM, of surface temperature over land, over the ocean and in both hemispheres, and of the global-mean ocean temperature profile. The method gives best-fit estimates as well as uncertainty intervals for the different SCM parameters. For the calibration, AOGCM simulations with two different types of forcing scenarios are used: pulse forcing simulations performed with 2 AOGCMs and gradually changing forcing simulations from 15 AOGCMs obtained within the framework of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. The method is found to work well. For all possible combinations of SCMs and AOGCMs the emulation of AOGCM results could be improved. The obtained SCM parameters depend both on the AOGCM data and the type of forcing scenario. SCMs with a poor representation of the atmosphere thermal inertia are better able to emulate AOGCM results from gradually changing forcing than from pulse forcing simulations. Correct simultaneous emulation of both atmospheric temperatures and the ocean temperature profile by the SCMs strongly depends on the representation of the temperature gradient between the atmosphere and the mixed layer. Introducing climate sensitivities that are dependent on the forcing mechanism in the SCMs allows the emulation of AOGCM responses to carbon dioxide and solar insolation forcings equally well. Also, some SCM parameters are found to be very insensitive to the fitting, and the reduction of their uncertainty through the fitting procedure is only marginal, while other parameters change considerably. The very simple SCM is found to reproduce the AOGCM results as well as the other two comparably more sophisticated SCMs.     

Simulating the diurnal cycle of rainfall in global climate models: resolution versus parameterization

The effects of horizontal resolution and the treatment of convection on simulation of the diurnal cycle of precipitation during boreal summer are analyzed in several innovative weather and climate model integrations. The simulations include: season-long integrations of the Non-hydrostatic Icosahedral Atmospheric Model (NICAM) with explicit clouds and convection; year-long integrations of the operational Integrated Forecast System (IFS) from the European Centre for Medium-range Weather Forecasts at three resolutions (125, 39 and 16 km); seasonal simulations of the same model at 10 km resolution; and seasonal simulations of the National Center for Atmospheric Research (NCAR) low-resolution climate model with and without an embedded two-dimensional cloud-resolving model in each grid box. NICAM with explicit convection simulates best the phase of the diurnal cycle, as well as many regional features such as rainfall triggered by advancing sea breezes or high topography. However, NICAM greatly overestimates mean rainfall and the magnitude of the diurnal cycle. Introduction of an embedded cloud model within the NCAR model significantly improves global statistics of the seasonal mean and diurnal cycle of rainfall, as well as many regional features. However, errors often remain larger than for the other higher-resolution models. Increasing resolution alone has little impact on the timing of daily rainfall in IFS with parameterized convection, yet the amplitude of the diurnal cycle does improve along with the representation of mean rainfall. Variations during the day in atmospheric prognostic fields appear quite similar among models, suggesting that the distinctive treatments of model physics account for the differences in representing the diurnal cycle of precipitation.     

A review on vegetation models and applicability to climate simulations at regional scale

The lack of accurate representations of biospheric components and their biophysical and biogeochemical processes is a great source of uncertainty in current climate models. The interactions between terrestrial ecosystems and the climate include exchanges not only of energy, water and momentum, but also of carbon and nitrogen. Reliable simulations of these interactions are crucial for predicting the potential impacts of future climate change and anthropogenic intervention on terrestrial ecosystems. In this paper, two biogeographical (Neilson’s rule-based model and BIOME), two biogeochemical (BIOME-BGC and PnET-BGC), and three dynamic global vegetation models (Hybrid, LPJ, and MC1) were reviewed and compared in terms of their biophysical and physiological processes. The advantages and limitations of the models were also addressed. Lastly, the applications of the dynamic global vegetation models to regional climate simulations have been discussed.     

A new snow parameterization for the Météo-France climate model

Both observational studies and numerical experiments demonstrate the sensitivity of the atmosphere to variations in the extent and mass of snow cover. There is therefore a need for simple but realistic snow parameterizations in forecast and climate models. This study describes a new physically-based snow hydrology for use in the Météo-France climate model, together with the ISBA land-surface scheme. A restricted number of parameters has been added, while preserving a single surface energy budget. The ageing process of the snow pack has been introduced through prognostic equations for snow density and snow albedo. Snowmelt computation has been modified over partially snow-covered and vegetated areas. The new scheme has been validated against field measurements in stand-alone simulations forced by observed meteorological conditions. The results show a strong improvement in the model's performance, thereby suggesting that a simple one-layer snow model is able to reproduce the main physical mechanisms governing the snow pack evolution. Part II of the present study will concern the validation in a 3-D experiment within the Météo-France climate model.     

Validation of parametrisations for the meridional energy and moisture transport used in simple climate models

Parametrisations of meridional energy and moisture transport used in zonally averaged climate models are validated using reanalysis data and results from a doubling CO₂-experiment from a general circulation model. Global meridional fluxes of moisture and sensible heat are calculated by integrating surface and top-of-the-atmosphere vertical fluxes from one pole to the other. The parametrisations include an eddy-diffusion term, representing down-gradient transport of specific humidity and temperature due to the transient atmospheric eddies at mid- and high latitudes, and simple representations of the mean meridional circulation. Qualitative and quantitative agreement between the increased hydrological cycle in the 2×CO₂-run from the GCM and the parametrisation is found. The performance for the sensible heat flux shows larger differences to the GCM results, particularly at low latitudes. Seasonal variations of the moisture and sensible heat transport are well captured by parametrisations including the influence of the mean meridional circulation. Interannual variability cannot be simulated. An examination of the parametrisations on different spatial scales suggests that they should not be used for small scales. Furthermore, two closures for the zonal distribution of precipitation were examined. They are used in zonally averaged atmosphere models coupled to an ocean model with different ocean basins at one latitudinal belt. An assessment of both the reanalysis data and the GCM results shows that both closures exhibit very similar behaviour and are valid in the long-term mean and seasonal cycle. Interannual variability is not captured well. They become invalid for spatial scales smaller than 10^∘. Received: 30 November 1998 / Accepted: 4 July 1999     

新冠肺炎流行病学模型的最优参数化

现如今,新冠肺炎(COVID-19)严重威胁着世界各国人民的生命健康.许多流行病学模型已经被用于为政策制定者和世界卫生组织提供决策参考.为了更加深刻的理解疫情趋势的变化特征,许多参数优化算法被用于反演模型参数.本文提议使用结合了高斯-牛顿法和梯度下降法的Levenberg-Marquardt(LMA)算法来优化模型参数...     

Moisture-transfer coefficient for climate models

Recent parameterizations of the moisture-transfer coefficient from measurements in the field and from tuning of the ECMWF model are reviewed. A formula for the neutral transfer coefficient varying continuously with the wind velocity is proposed for climate models.     

Formulation and verification of a land surface parameterization for atmospheric models

The need for a well-defined lower boundary condition for atmospheric numerical models is well documented. This paper describes the formulation of a land surface parameterization, which will be used in atmospheric boundary-layer and mesoscale numerical models. The land surface model has three soil layers for the prediction of soil moisture and soil temperature. Model soil properties depend on soil texture and moisture content. A homogeneous distribution of vegetation is also included, so that transpiration may be included, as well as the interception of precipitation by vegetation elements. The simulated vegetation also affects the mean surface albedo and roughness characteristics.First ISLSCP Field Experiment (FIFE) data are used to verify the model. Three cases during the growing season were chosen, each case having different amounts of vegetation cover. Stand alone simulations, where observations of atmospheric and radiation variables are input to the land surface model, were performed. These simulations show that the model is able to reproduce observed surface energy budgets and surface temperatures reasonably well. The RMS differences between modeled and obsered turbulent fluxes of heat and moisture are quite comparable to those reported by more detailed land surface models.     

A simple soil moisture scheme for regional climate simulations in the tropics

Summary A regional climate model (RCM) is described which incorporates an improved scheme for soil moisture availability (SMA) compared to an earlier version. The improvement introduces a sensitivity of SMA to soil type, vegetation cover and ground albedo, making the model more adaptable to divers regions. In addition, the interactive SMA depends on past precipitation, ground temperature and terrain relief. Six RCM simulations of the monthly mean climate over southern Africa are performed at 0.5° grid spacing. Improvements in the RCM climate simulations compared to control runs are attributed to the newer SMA scheme. Only a slight improvement in skill results from driving the RCM with observational analyses as opposed to GCM “predicted” lateral boundary conditions. The high spatial resolution of the RCM provides a distinct advantage in the simulated spatial distribution of precipitation compared with a global model run at an effective grid spacing of 2.8°. The mesoscale precipitation signal in the RCM simulations is more dominant during the rather dry December 1982 than during December 1988. The improved SMA scheme contributed to a realistic partition between latent and sensible heat fluxes at the ground-atmosphere boundary and consequently a realistic diurnal cycle of ground temperature. Simulated differences in the spatial distribution of rainfall between December 1982 and December 1988 are more realistic with the improved scheme. Received June 28, 2001 Revised August 27, 2001     

On the sensitivity of global warming experiments to the parametrisation of sub-grid scale ocean mixing

An ocean general circulation model coupled to an energy-moisture balance atmosphere model is used to investigate the sensitivity of global warming experiments to the parametrisation of sub-grid scale ocean mixing. The climate sensitivity of the coupled model using three different parametrisations of sub-grid scale mixing is 3°C for a doubling of CO₂ (6°C for a quadrupling of CO₂). This suggests that the ocean has only a weak feedback on global mean surface air temperature although significant regional differences, notably at high latitudes, exist with different sub-grid scale parametrisations. In the experiment using the Gent and McWilliams parametrisation for mixing associated with mesoscale eddies, an enhancement of the surface response in the Southern Ocean is found. This enhancement is largely due to the existence of more realistic sea-ice in the climatological control integration and the subsequent enhanced ice-albedo feedback upon warming. In accordance with earlier analyses, the Gent and McWilliams scheme decreases the global efficiency of ocean heat uptake. During the transient phase of all experiments, the North Atlantic overturning initially weakened but ultimately recovered, surpassing its former strength. This suggests that in the region around the North Atlantic the ocean acts as a negative feedback on local warming during the transient phase but a positive feedback at equilibrium. During the transient phase of the experiments with a more sophisticated and realistic parametrisation of sub-grid scale mixing, warmed Atlantic water was found to penetrate at depth into the Arctic, consistent with recent observations in the region. Received: 14 October 1998 / Accepted: 27 April 1999     

A coupled simple climate model and its global analysis

Summary An atmosphere-land coupled simple climate model is constructed and its climatic properties are analyzed by introducing a global analysis method, cell mapping. The simple model is a nonlinear six order simplified climate model featured with chaotic dynamics, dissipation, and forcing source, which are the main features of the real climate system. The cell mapping method is applied with this coupled system. Numerical experiments are carried out for investigating the interactions between the fast-changing atmospheric variables and slow-changing underlying surface variables. The predictability of the system is also investigated via the global analysis, with which the evolution of the system is translated to the evolution of probability transition on a Markov Chain. An effective scheme is proposed for computing the probability transition matrix for the coupled system. Predictions can be made based on the combination of dynamics and statistics. The importance of constructing the coupled model is shown by globally analyzing the predictability of the coupled system. The coupling mechanism prolongs the memorization of initial information, and then the predictability as well.     

Global and regional coupled climate sensitivity to the parameterization of rainfall interception

A coupled land?Catmosphere model is used to explore the impact of seven commonly used canopy rainfall interception schemes on the simulated climate. Multiple 30-year simulations are conducted for each of the seven methods and results are analyzed in terms of the mean climatology and the probability density functions (PDFs) of key variables based on daily data. Results show that the method used for canopy interception strongly affects how rainfall is partitioned between canopy evaporation and throughfall. However, the impact on total evaporation is much smaller, and the impact on rainfall and air temperature is negligible. Similarly, the PDFs of canopy evaporation and transpiration for six selected regions are strongly affected by the method used for canopy interception, but the impact on total evaporation, temperature and precipitation is negligible. Our results show that the parameterization of rainfall interception is important to the surface hydrometeorology, but the seven interception parameterizations examined here do not cause a statistically significant impact on the climate of the coupled model. We suggest that broad scale climatological differences between coupled climate models are not likely the result of how interception is parameterized. This conclusion is inconsistent with inferences derived from earlier uncoupled simulations, or simulations using very simplified climate models.     

A regional climate model simulation over West Africa: parameterization tests and analysis of land-surface fields

The West African Monsoon has been simulated with the regional climate model PROMES, coupled to the land-surface model ORCHIDEE and nested in ECMWF analysis, within AMMA-EU project. Three different runs are presented to address the influence of changes in two parameterizations (moist convection and radiation) on the simulated West African Monsoon. Another aim of the study is to get an insight into the relationship of simulated precipitation and 2-m temperature with land-surface fluxes. To this effect, data from the AMMA land-surface model intercomparison project (ALMIP) have been used. In ALMIP, offline simulations have been made using the same land-surface model than in the coupled simulation presented here, which makes ALMIP data particularly relevant for the present study, as it enables us to analyse the simulated soil and land-surface fields. The simulation of the monsoon depends clearly on the two analysed parameterizations. The inclusion of shallow convection parametrization affects the intensity of the simulated monsoon precipitation and modifies some dynamical aspects of the monsoon. The use of a fractional cloud-cover parameterization and a more complex radiation scheme is important for better reproducing the amplitude of the latitudinal displacement of the precipitation band. This is associated to an improved simulation of the surface temperature field and the easterly jets. However, the parameterization changes do not affect the timing of the main rainy and break periods of the monsoon. A better representation of downward solar radiation is associated with a smaller bias in the surface heat fluxes. The comparison with ALMIP land-surface and soil fields shows that precipitation and temperature biases in the regional climate model simulation are associated to certain biases in land-surface fluxes. The biases in soil moisture seem to be driven by atmospheric biases as they are strongly affected by the parameterization changes in atmospheric processes.     

A conceptual framework for time and space scale interactions in the climate system

 Interactions involving various time and space scales, both within the tropics and between the tropics and midlatitudes, are ubiquitous in the climate system. We propose a conceptual framework for understanding such interactions whereby longer time scales and larger space scales set the base state for processes on shorter time scales and smaller space scales, which in turn have an influence back on the longer time scales and larger space scales in a continuum of process-related interactions. Though not intended to be comprehensive, we do cite examples from the literature to provide evidence for the validity of this framework. Decadal time scale base states of the coupled climate system set the context for the manifestation of interannual time scales (El Nino/Southern Oscillation, ENSO and tropospheric biennial oscillation, TBO) which are influenced by and interact with the annual cycle and seasonal time scales. Those base states in turn influence the large-scale coupled processes involved with intraseasonal and submonthly time scales, tied to interactions within the tropics and extratropics, and tropical–midlatitude teleconnections. All of these set the base state for processes on the synoptic and mesoscale and regional/local space scales. Events at those relatively short time scales and small space scales may then affect the longer time scale and larger space scale processes in turn, reaching back out to submonthly, intraseasonal, seasonal, annual, TBO, ENSO and decadal. Global coupled models can capture some elements of the decadal, ENSO, TBO, annual and seasonal time scales with the associated global space scales. However, coupled models are less successful at simulating phenomena at subseasonal and shorter time scales with hemispheric and smaller space scales. In the context of the proposed conceptual framework, the synergistic interactions of the time and space scales suggest that a high priority must be placed on improved simulations of all of the time and space scales in the climate system. This is particularly important for the subseasonal time scales and hemispheric and smaller space scales, which are not well simulated at present, to improve the prospects of successfully forecasting phenomena beyond the synoptic scales. Received: 3 April 2000/ Accepted: 6 November 2000     

On the sensitivity of mesoscale models to surface-layer parameterization constants

The Colorado State University standard mesoscale model is used to evaluate the sensitivity of one-dimensional (1D) and two-dimensional (2D) fields to differences in surface-layer parameterization constants. Such differences reflect the range in the published values of the von Karman constant, Monin-Obukhov stability functions and the temperature roughness length at the surface. The sensitivity of 1D boundary-layer structure, and 2D sea-breeze intensity, is generally less than that found in published comparisons related to turbulence closure schemes generally.