一个用于气候模式的简单冻土过程参数化方案的建立和检验

在NCAR／LSM的基础上，发展了一个简单的冻土过程参数化方案，并使用苏联6个站的水气象观测资料考察了耦合了新方案模式的气候效应。在新方案中，加入了对含冰量的求解和在相变过程中的能量变化;并使用Johanson的方案替代了模式中原有的土壤导热率的参数化方案，考虑了含冰量对土壤水热性质的影响。原模式和改进后模式的模拟结果的比较得到，冻土过程方案能够合理的模拟土壤列中的能量收支及水热性质随含冰量的变化。随着入渗的减少和径流的增加，春季的土壤湿度减小。因此，热通量的分配和土壤温度也产生了相应的变化。     

Parametrizations of global thermal emissions for simple climate models

 A new, observationally based, parametrization of the thermal emissions by the Earth-atmosphere system for use in simple climate models is presented and discussed. The parametrization, allowing for the modelling of outgoing longwave fluxes in both clear and cloudy sky conditions, introduces temperature-dependent emissivities in a grey-body formulation, whose expressions are based on data from by the International Satellite Cloud Climatology Program (ISCCP). The proposed parametrization is compared to traditional ones and is used in a simple energy-balance model. It is shown how, unlike the traditional parametrizations, the proposed one correctly reproduces the runaway greenhouse phenomenon, i.e. the impossibility of an equilibrium for values of the solar constant larger than a critical one, which is known to occur in more complex radiative-convective models. It is also seen that the new parametrization induces the existence of a varying number of equilibria, depending on the value of the solar forcing, in agreement with previous studies. Further, the new parametrization is used to explore the effects of clouds on the Earth-atmosphere energy balance. It is found that for certain values of the model parameters the radiative effect of clouds might be either net cooling or net warming, depending on the magnitude of the solar forcing. Received: 12 January 1998 / Accepted: 23 July 1998     

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.     

The dynamics of uncertainty: application to parameterization constants in climate models

Climate models, ranging from statistical-dynamical to the explicit-dynamical, contain a range of uncertainties related to the parameterization constants associated with the various forcing terms used therein. Quantifying the impacts of such uncertainties has heretofore received little attention. The impact of this aspect of the dynamics of uncertainty was revealed in a series of dynamical systems of increasing complexity. The inevitability of climate drift was discussed, with one aspect being revealed as the non-Gaussian nature of most forcing terms. For those dynamical systems which are chaotic in nature, it was shown how stochastic dynamic equations can be used to describe the uncertainty, even with uncertainty in the critical forcing terms. The possibility of climate transitions driven by stochastic forcing occurring on much faster time scales (i.e., weather disturbances) has been shown by numerous authors. The caution shown here is that even very small uncertainty in a forcing term occurring on the slow climate time scales can lead to such transitions more easily. Conversely, a deterministic parameterization on the slowly varying time scale may be just slightly incorrect in a particular model formulation and lead to the wrong climatic state. In view of such concerns, the framework for attacking the difficult nonlinear problem of uncertain parameterization constants in complex GCMs is outlined.The National Center for Atmospheric Research is sponsored by the National Science Foundation     

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.     

A simple hydrologic framework for simulating wetlands in climate and earth system models

Wetlands are ecosystems of important functions in the earth??s climate system. Through relatively high evapotranspiration, they affect surface water and energy exchange with the atmosphere directly influencing the physical climate. Through CH₄, CO₂ and N₂O fluxes, they regulate the biogeochemical cycles, indirectly influencing the physical climate. However, current models do not explicitly include the water table, present under all large and stable wetlands; model wetlands are identified as flat land with wet soil resulting from precipitation events. That is, the wetlands are only ??wetted?? from above but not from below by the high water table. Furthermore, without the knowledge of the water table position, estimates of CH₄ and other gases (e.g., CO₂ and N₂O) are poorly constrained. We present a simple hydrologic framework for simulating wetlands based on water table depth. A synthesis of hydrologic controls on wetlands highlights the key role that groundwater plays. It directly feeds wetlands, supports surface-water fed wetlands by maintaining a saturated substrate, and links land drainage to sea level by impeding drainage in lowlands. Forced by routine climate model output (precipitation?Cevapotranspiration-surface runoff), land topography, and sea level, we simulate the present-day water table in North America at the 1?km scale. We validate the simulation with water table observations and compare regions of shallow water table to mapped wetlands. Our results show that the framework captures the salient features of wetland distribution and extent at regional and continental scales, a direct result of large-scale groundwater convergence that nourishes the lowlands even in arid climates. The low requirement of forcing and computation make the framework easy to adopt in climate and earth system models for simulating wetland responses to climate and sea level change for the present, paleo reconstructions, and future projections.     

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 statistical representation of sub-grid variation in mixing-length models of the boundary layer

In conventional gradient-transfer models of the atmospheric boundary layer, the fluxes are calculated using the gradients of buoyancy and momentum over the grid interval. When using finite-differences, these gradients are approximated using what are essentially the grid-volume means of the quantities involved. This is unrealistic, as within a large volume of the atmosphere fluxes are supported by an ensemble of small-scale motions, which may be organized by the presence of large coherent eddies. In this paper, a new method of computing the flux is developed, in which the gradients of grid-volume mean buoyancy and momentum are replaced by grid-volume ensembles. The distributional parameters of the ensembles are derived using dimensional arguments, augmented by the results of a large-eddy simulation.     

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.     

A new snow parameterization for the Météo-France climate model

Both observational and numerical studies 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. A new snow hydrology scheme has recently been developed at Météo-France for use in the ARPEGE climate model and has been successfully tested against local field measurements in stand-alone experiments. This study describes the global validation of the parameterization in a 3-year integration for the present-day climate within the T42L30 version of ARPEGE. Results are compared with those from a control simulation and with available observed climatologies, in order to assess the impact of the new snow parameterization on the simulated surface climate. The seasonal cycle of the Northern Hemisphere snow cover is clearly improved when using the new scheme. The snow pack is still slightly overestimated in winter, but its poleward retreat is better reproduced during the melting season. As a consequence, the modified GCM performs well in simulating the springtime continental heating, which may play a strong role in the simulation of the Asian summer monsoon.     

Improving a subgrid runoff parameterization scheme for climate models by the use of high resolution data derived from satellite observations

In this study it is shown that the availability of a very high resolution dataset of land surface characteristics leads to the improvement of a surface runoff parameterization scheme. The improved parameterization scheme was developed for application in global and regional climate models and is a further development of the Arno scheme that is widely used in climate models. Here, surface runoff is computed as infiltration excess from a "bucket" type reservoir which takes the subgrid variability of soil saturation within a model gridbox into account. Instead of prescribing a distribution of subgrid scale soil water capacities as in the original Arno scheme, the array of high resolution soil water capacities taken from a global 1 km dataset of land surface parameters is used to obtain individual fractional saturation curves for each model gridbox. From each saturation curve, the three parameters (a shape parameter describing the shape of the subgrid distribution of soil water capacities, subgrid minimum and maximum soil water capacity) required in the modified formulation of the scheme are derived via optimization. As in the original Arno scheme applied in the ECHAM general circulation model and the REMO regional climate model, topography variations will influence the distribution of saturated subgrid areas within a model gridbox. At most gridboxes the net effect of these changes is such that more runoff is produced for high soil water contents and less runoff for low soil water contents. A validation of simulated discharge computed with a simplified land surface scheme applied to reanalysis data of the European Centre for Medium-Range Weather Forecasts and a hydrological discharge model has shown that these changes lead to a more realistic simulation of the annual cycle of discharge for several catchments. In particular this could be shown for the Yangtze Kiang and Amur catchments where adequate input data are available.     

A simple model of baroclinic adjustment and parameterization of eddy heat transport

Summary A nonlinear, forced, dissipative quasi-geostrophic, two-level -plane model of baroclinic instability is formulated. The model resolves a baroclinic zonal flow and a wave of arbitrary zonal scale. Multiple equilibrium solutions describing Hadley and eddy circulations coexist. Only the circulation with smaller thermal wind is stable. The most efficient eddy activity occurs at a zonal wavenumber close to the wavelength of maximum instability of linear baroclinic instability theory. For a wide range of forcing and dissipative parameters, the steady baroclinic zonal wind of the eddy regime is close to the critical shear of linear theory. Eddy statistics are obtained analytically in terms of the doparture of the zonally symmetric state from radiative equilibrium. A parameterization for the eddy heat transport is obtained.With 14 Figures     

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...     

数值模式中的大气边界层参数化方案综述

大气边界层对下垫面和自由大气之间的热量、动量和物质交换以及全球辐射的收支平衡有着非常重要的作用,数值模式中对边界层的模拟需要通过参数化方案表现出来。综述了数值模式中常用的边界层参数化方案,从闭合框架以及边界层内的重要物理过程这两个方面对各类方案进行了总结,并讨论了边界层参数化方案的发展方向。     

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.     

A mass-flux cumulus parameterization scheme for large-scale models: description and test with observations

A simple mass-flux cumulus parameterization scheme suitable for large-scale atmospheric models is presented. The scheme is based on a bulk-cloud approach and has the following properties: (1) Deep convection is launched at the level of maximum moist static energy above the top of the boundary layer. It is triggered if there is positive convective available potential energy (CAPE) and relative humidity of the air at the lifting level of convection cloud is greater than 75%; (2) Convective updrafts for mass, dry static energy, moisture, cloud liquid water and momentum are parameterized by a one-dimensional entrainment/detrainment bulk-cloud model. The lateral entrainment of the environmental air into the unstable ascending parcel before it rises to the lifting condensation level is considered. The entrainment/detrainment amount for the updraft cloud parcel is separately determined according to the increase/decrease of updraft parcel mass with altitude, and the mass change for the adiabatic ascent cloud parcel with altitude is derived from a total energy conservation equation of the whole adiabatic system in which involves the updraft cloud parcel and the environment; (3) The convective downdraft is assumed saturated and originated from the level of minimum environmental saturated equivalent potential temperature within the updraft cloud; (4) The mass flux at the base of convective cloud is determined by a closure scheme suggested by Zhang (J Geophys Res 107(D14), doi:10.1029/2001JD001005, 2002) in which the increase/decrease of CAPE due to changes of the thermodynamic states in the free troposphere resulting from convection approximately balances the decrease/increase resulting from large-scale processes. Evaluation of the proposed convection scheme is performed by using a single column model (SCM) forced by the Atmospheric Radiation Measurement Program’s (ARM) summer 1995 and 1997 Intensive Observing Period (IOP) observations, and field observations from the Global Atmospheric Research Program’s Atlantic Tropical Experiment (GATE) and the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). The SCM can generally capture the convective events and produce a realistic timing of most events of intense precipitation although there are some biases in the strength of simulated precipitation.     

A study of abrupt climate change in a simple nonlinear climate model

We use a seasonal energy balance climate model to study the behavior of the snowline cycle as a function of external parameters such as the solar constant. Our studies are confined in this study to cases with zonally symmetric land-sea distributions (bands or caps of land). The model is nonlinear in that the seasonally varying snow/sea ice line modifies the energy receipt through its different albedo from open land or water. The repeating steady-state seasonal cycle of the model is solved by a truncated Fourier series in time. This method is several thousand times faster than a time stepping approach. The results are interesting in that a number of bifurcations in the snowline behavior are found and studied for various geographies. Polar land caps and land bands positioned near the poles exhibit a variety of discontinuous summer snow cover behaviors (abrupt transitions as a parameter such as solar constant is slowly varied), which may be relevant to the inception and decay of continental ice sheets.