An investigation of the sensitivity of a land surface model to climate change using a reduced form model

 In an illustration of a model evaluation methodology, a multivariate reduced form model is developed to evaluate the sensitivity of a land surface model to changes in atmospheric forcing. The reduced form model is constructed in terms of a set of ten integrative response metrics, including the timing of spring snow melt, sensible and latent heat fluxes in summer, and soil temperature. The responses are evaluated as a function of a selected set of six atmospheric forcing perturbations which are varied simultaneously, and hence each may be thought of as a six-dimensional response surface. The sensitivities of the land surface model are interdependent and in some cases illustrate a physically plausible feedback process. The important predictors of land surface response in a changing climate are the atmospheric temperature and downwelling longwave radiation. Scenarios characterized by warming and drying produce a large relative response compared to warm, moist scenarios. The insensitivity of the model to increases in precipitation and atmospheric humidity is expected to change in applications to coupled models, since these parameters are also strongly implicated, through the representation of clouds, in the simulation of both longwave and shortwave radiation. Received: 27 March 2000 / Accepted: 11 September 2000     

Planetary boundary layer and surface layer sensitivity to land surface parameters

The sensitivity of the development of the convective planetary boundary layer (PBL) and the surface layer are examined using a coupled surface parameterization and detailed PBL model. First, the coupling is verified against observations from the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE). Results of the sensitivity experiments indicate that the PBL is most sensitive to the amount of soil water content, and the proximity of the soil water content to critical soil texture values (field capacity and wilting point). While vegetation cover is not the most sensitive parameter at the surface, its influence on the surface energy and hydrologic balance is crucial. Model sensitivity to minimum stomatal resistance, type of soil parameterization and canopy height (surface roughness and displacement depth) is also discussed.     

Sub-grid scale precipitation in ALCMs: re-assessing the land surface sensitivity using a single column model

The sensitivity of a land surface scheme to the distribution of precipitation within a general circulation model's grid element is investigated. Earlier experiments which showed considerable sensitivity of the runoff and evaporation simulation to the distribution of precipitation are repeated in the light of other results which show no sensitivity of evaporation to the distribution of precipitation. Results show that while the earlier results over-estimated the sensitivity of the surface hydrology to the precipitation distribution, the general conclusion that the system is sensitive is supported. It is found that changing the distribution of precipitation from falling over 100% of the grid square to falling over 10% leads to a reduction in evaporation from 1578 mm y^–1 to 1195 mm y ^–1 while runoff increases from 278 mm y^–1 to 602 mm y^–1. The sensitivity is explained in terms of evaporation being dominated by available energy when precipitation falls over nearly the entire grid square, but by moisture availability (mainly intercepted water) when it falls over little of the grid square. These results also indicate that earlier work using stand-alone forcing to drive land surface schemes off-line, and to investigate the sensitivity of land surface codes to various parameters, leads to results which are non-repeatable in single column simulations.     

The role of surface energy balance complexity in land surface models' sensitivity to increasing carbon dioxide

Global simulations with the Bureau of Meteorology Research Centre climate model coupled to the CHAmeleon Surface Model (CHASM) are used to explore the sensitivity of simulated changes in evaporation, precipitation, air temperature and soil moisture resulting from a doubling of carbon dioxide in the atmosphere. Five simulations, using prescribed sea surface temperatures, are conducted which are identical except in the level of complexity used to represent the surface energy balance. The simulation of air temperature, precipitation, evaporation and soil moisture at 1 2 CO₂ and at 2 2 CO₂ are generally sensitive at statistically significant levels to the complexity of the surface energy balance representation (i.e. the level of complexity used to represent these processes affects the simulated climate). However, changes in mean quantities, resulting from a doubling of atmospheric CO₂, are generally insensitive to the surface energy balance complexity. Conversely, changes in the spatial and temporal variance of evaporation and soil moisture are sensitive to the surface energy balance complexity. The addition of explicit canopy interception to the simplest model examined here enables that model to capture the change in the variance of evaporation simulated by the more complex models. In order to simulate changes in the variability of soil moisture, an explicit parameterization of bare soil evaporation is required. Overall, our results increase confidence that the simulation by climate models of the mean impact of increasing CO₂ on climate are reliable. Changes in the variability resulting from increased CO₂ on air temperature, precipitation or evaporation are also likely to be reliable since climate models typically use sufficiently complex land surface schemes. However, if the impact of increased CO₂ on soil moisture is required, then a more complex surface energy balance representation may be needed in order to capture changes in variability. Overall, our results imply that the level of complexity used by most climate models to represent the surface energy balance is appropriate and does not contribute significant uncertainty in the simulation of changes resulting from increasing CO₂. Our results only relate to surface energy balance complexity, and major uncertainties remain in how to model the surface hydrology and changes in the physiology, structural characteristics and distribution of vegetation. Future developments of land surface models should therefore focus on improving the representation of these processes.     

Analysis of parameter sensitivity on surface heat exchange in the Noah land surface model at a temperate desert steppe site in China

The dominant parameters in the Noah land surface model (LSM) are identified, and the effects of parameter optimization on the surface heat exchange are investigated at a temperate desert steppe site during growing season in Inner Mongolia, China. The relative impacts of parameters on surface heat flux are examined by the distributed evaluation of local sensitivity analysis (DELSA), and the Noah LSM is calibrated by the global shuffled complex evolution (SCE) against the corresponding observations during May–September of 2008 and 2009. The differences in flux simulations are assessed between the Noah LSM calibrated by the SCE with 27 parameters and 12 dominant parameters. The systematic error, unsystematic error, root mean squared error, and mean squared error decompositions are used to evaluate the model performance. Compared to the control experiment, parameter optimization by the SCE using net radiation, sensible heat flux, latent heat flux, and ground heat flux as the objective criterion, respectively, can obviously reduce the errors of the Noah LSM. The calibrated Noah LSM is further validated against flux observations of growing season in 2010, and it is found that the calibrated Noah LSM can be applied in the longer term at this site. The Noah LSM with 12 dominant parameters calibrated performs similar to that with 27 parameters calibrated.     

东疆黑戈壁陆面过程参数及陆面模式离线模拟

新疆东部黑戈壁气候恶劣、人迹罕至,是具有黑色砾石下垫面的生态脆弱区。利用东疆哈密戈壁陆气相互作用站2018年全年观测资料,给出该戈壁地表动力学与热力学粗糙度、比辐射率和地表反照率等陆面过程特征参数,并将这些参数代入Noah模式对该戈壁热通量、地表温度及土壤温湿度进行模拟。结果表明：（1）东疆黑戈壁下垫面动力学粗糙度为1.13×10-3 m,热力学粗糙度为0.32×10-3 m,比辐射率为0.905。（2）地表反照率日变化呈早晚高,中午低的“U”型曲线。12月因地面积雪,反照率最高,年内极大值出现在12月8日,为0.79,年均反照率为0.29。地表反照率关于太阳高度角的参数化方案为：α=0.78-0.47×(1-e^((-h)/1.12)),地表反照率关于5 cm土壤湿度的参数化方案为α=0.28-0.136w_s。（3）将改进后的陆面过程参数带入Noah模式,大大提高了模式在戈壁区域的模拟能力。     

Introduction of a sub-grid hydrology in the ISBA land surface model

In atmospheric models, the partitioning of precipitation between infiltration and runoff has a major influence on the terrestrial water budget, and thereby on the simulated weather or climate. River routing models are now available to convert the simulated runoff into river discharge, offering a good opportunity to validate land surface models at the regional scale. However, given the low resolution of global atmospheric models, the quality of the hydrological simulations is much dependent on various processes occurring on unresolved spatial scales. This paper focuses on the parameterization of sub-grid hydrological processes within the ISBA land surface model. Five off-line simulations are performed over the French Rhône river basin, including various sets of parameterizations related to the sub-grid variability of topography, precipitation, maximum infiltration capacity and land surface properties. Parallel experiments are conducted at a high (8 km by 8 km) and low (1° by 1°) resolution, in order to test the robustness of the simulated water budget. Additional simulations are performed using the whole package of sub-grid parameterizations plus an exponential profile with depth of saturated hydraulic conductivity, in order to investigate the interaction between the vertical soil physics and the horizontal heterogeneities. All simulations are validated against a dense network of gauging measurements, after the simulated runoff is converted into discharge using the MODCOU river routing model. Generally speaking, the new version of ISBA, with both the sub-grid hydrology and the modified hydraulic conductivity, shows a better simulation of river discharge, as well as a weaker sensitivity to model resolution. The positive impact of each individual sub-grid parameterization on the simulated discharges is more obvious at the low resolution, whereas the high-resolution simulations are more sensitive to the exponential profile with depth of saturated hydraulic conductivity.     

陆面过程模式的敏感性试验

本文对文献[1]中提出的陆面过程模式(简称LPM)进行了下列敏感性试验:1)植被的覆盖度,2)土壤湿润程度,3)不同植被类型(半荒漠、草原、混交林、森林和作物地五种)和4)不同气候带(半干旱、半湿润和湿润带三类)。试验结果与相应的观测和气候状况进行了比较,表明了模式对上述参数或参数组变化的敏感程度。模拟的不同植被和气候带的温湿状况和能量平衡关系是合理的。因此可以用于气候模拟的研究。     

区域大气模式中陆面子模式起转过程的研究

模式的起转过程(spin-up)是指在非平衡初值或扰动的条件下,模式进行调整而达到平衡态的过程.以黑河实验(HEIFE) 1991年6月20日到7月20日张掖站观测的地表能量通量和土壤温度资料为基础,用大量数值实验研究了RAMS (Regional Atmospheric Modeling System)陆面子模式起转过程所需的时间范围.数值实验中,为细致考虑土壤初始参数对此过程的影响,共设计了40余组不同的初始土壤水、热参数.通过模拟结果分析,把RAMS陆面模式起转过程的表现归纳为4大类,并说明了这个过程的持续时间可能因为土壤初始参数的不同而产生较大的差异,其范围可能为数小时至一周以上.在判断RAMS模拟地表、低空物理量时,土壤含水量是判断模式是否达到平衡态的重要因子.     

Climate sensitivity to tropical land surface changes with coupled versus prescribed SSTs

Tropical land cover change experiments with fixed sea-surface temperatures (SSTs) and with an interactive ocean are compared to assess the relevance of including the ocean system in sensitivity studies to land surface conditions. The results show that the local response to deforestation is similar with fixed and simulated SSTs. Over Amazonia, all experiments simulate a comparable decrease in precipitation and no change in moisture convergence, implying that there is only a change in local water recycling. Over Africa, the impact on precipitation is not identical for all experiments; however, the signal is smaller than over Amazonia and simulations of more than 50 years would be necessary to statistically discriminate the precipitation change. We observe small but significant changes in SSTs in the coupled simulation in the tropical oceans surrounding the deforested regions. Impacts on mid and high latitudes SSTs are also possible. As remote impacts to deforestation are weak, it has not been possible to establish possible oceanic feedbacks to the atmosphere. Overall, this study indicates that the oceanic feedback to land surface sensitivity studies is of second importance, and that the inclusion of the oceanic system will require ensembles of long climate simulations to properly take into account the low frequency variability of the ocean.     

Soil temperature response in Korea to a changing climate using a land surface model

The land surface processes play an important role in weather and climate systems through its regulation of radiation, heat, water and momentum fluxes. Soil temperature (ST) is one of the most important parameters in the land surface processes; however, there are few extensive measurements of ST with a long time series in the world. According to the CLImatology of Parameters at the Surface (CLIPS) methodology, the output of a trusted Soil-Vegetation- Atmosphere Transfer (SVAT) scheme can be utilized instead of observations to investigate the regional climate of interest. In this study, ST in South Korea is estimated in a view of future climate using the output from a trusted SVAT scheme — the University of TOrino model of land Process Interaction with Atmosphere (UTOPIA), which is driven by a regional climate model. Here characteristic changes in ST are analyzed under the IPCC A2 future climate for 2046-2055 and 2091-2100, and are compared with those under the reference climate for 1996-2005. The UTOPIA results were validated using the observed ST in the reference climate, and the model proved to produce reasonable ST in South Korea. The UTOPIA simulations indicate that ST increases due to environmental change, especially in air temperature (AT), in the future climate. The increment of ST is proportional to that of AT except for winter. In wintertime, the ST variations are different from region to region mainly due to variations in snow cover, which keeps ST from significant changes by the climate change.     

A comparison of a GCM response to historical anthropogenic land cover change and model sensitivity to uncertainty in present-day land cover representations

This study assesses the sensitivity of the fully coupled NCAR-DOE PCM to three different representations of present-day land cover, based on IPCC SRES land cover information. We conclude that there is significant model sensitivity to current land cover characterization, with an observed average global temperature range of 0.21 K between the simulations. Much larger contrasts (up to 5 K) are found on the regional scale; however, these changes are largely offsetting on the global scale. These results show that significant biases can be introduced when outside data sources are used to conduct anthropogenic land cover change experiments in GCMs that have been calibrated to their own representation of present-day land cover. We conclude that hybrid systems that combine the natural vegetation from the native GCM datasets combined with human land cover information from other sources are best for simulating such impacts. We also performed a prehuman simulation, which had a 0.39 K ~higher average global temperature and, perhaps of greater importance, temperature changes regionally of about 2 K. In this study, the larger regional changes coincide with large-scale agricultural areas. The initial cooling from energy balance changes appear to create feedbacks that intensify mid-latitude circulation features and weaken the summer monsoon circulation over Asia, leading to further cooling. From these results, we conclude that land cover change plays a significant role in anthropogenically forced climate change. Because these changes coincide with regions of the highest human population this climate impact could have a disproportionate impact on human systems. Therefore, it is important that land cover change be included in past and future climate change simulations.     

WRF模式中微物理和积云参数化方案的对比试验

基于中尺度大气数值模式WRF,检验分析YSU和MYJ两种边界层参数化方案和分辨率分别为1 km（称为USGS）和500 m（称为MODIS）的两类下垫面资料对2014年5月9—12日青岛一次暴雨过程模拟的影响。分析表明, YSU和MYJ方案都能模拟出强降雨带的位置和强度,MYJ试验对大雨TS评分高达0.88,YSU对暴雨TS评分为0.65;和USGS试验相比,MODIS试验提高了暴雨的TS评分,提高率为6.2%,但对大雨仍易空报。YSU、MYJ和MODIS试验较好地模拟了2 m气温、10 m风向。YSU模拟的2 m气温准确率是降雨前优于降雨开始后,MYJ则相反;MODIS试验预报沿海地区气温偏高。和USGS相比,MODIS提高了近地面风速和风向的模拟精度。总体上,所有试验方案对所考虑气象要素的模拟,基本上是内陆站准确率高于沿海站,YSU优于MYJ,MODIS优于USGS。

     

Storm track sensitivity to sea surface temperature resolution in a regional atmosphere model

A high resolution regional atmosphere model is used to investigate the sensitivity of the North Atlantic storm track to the spatial and temporal resolution of the sea surface temperature (SST) data used as a lower boundary condition. The model is run over an unusually large domain covering all of the North Atlantic and Europe, and is shown to produce a very good simulation of the observed storm track structure. The model is forced at the lateral boundaries with 15–20 years of data from the ERA-40 reanalysis, and at the lower boundary by SST data of differing resolution. The impacts of increasing spatial and temporal resolution are assessed separately, and in both cases increasing the resolution leads to subtle, but significant changes in the storm track. In some, but not all cases these changes act to reduce the small storm track biases seen in the model when it is forced with low-resolution SSTs. In addition there are several clear mesoscale responses to increased spatial SST resolution, with surface heat fluxes and convective precipitation increasing by 10–20% along the Gulf Stream SST gradient.     

The impact of new land surface physics on the GCM simulation of climate and climate sensitivity

 Recent improvements to the Hadley Centre climate model include the introduction of a new land surface scheme called “MOSES” (Met Office Surface Exchange Scheme). MOSES is built on the previous scheme, but incorporates in addition an interactive plant photosynthesis and conductance module, and a new soil thermodynamics scheme which simulates the freezing and melting of soil water, and takes account of the dependence of soil thermal characteristics on the frozen and unfrozen components. The impact of these new features is demonstrated by comparing 1×CO₂ and 2×CO₂ climate simulations carried out using the old (UKMO) and new (MOSES) land surface schemes. MOSES is found to improve the simulation of current climate. Soil water freezing tends to warm the high-latitude land in the northern Hemisphere during autumn and winter, whilst the increased soil water availability in MOSES alleviates a spurious summer drying in the mid-latitudes. The interactive canopy conductance responds directly to CO₂, supressing transpiration as the concentration increases and producing a significant enhancement of the warming due to the radiative effects of CO₂ alone. Received: 16 March 1998 / Accepted: 4 August 1998     

Optimal Parameter and Uncertainty Estimation of a Land Surface Model： Sensitivity to Parameter Ranges and Model Complexities

Most previous land-surface model calibration studies have defined global ranges for their parameters to search for optimal parameter sets. Little work has been conducted to study the impacts of realistic versus global ranges as well as model complexities on the calibration and uncertainty estimates. The primary purpose of this paper is to investigate these impacts by employing Bayesian Stochastic Inversion (BSI) to the Chameleon Surface Model (CHASM). The CHASM was designed to explore the general aspects of land-surface energy balance representation within a common modeling framework that can be run from a simple energy balance formulation to a complex mosaic type structure. The BSI is an uncertainty estimation technique based on Bayes theorem, importance sampling, and very fast simulated annealing.The model forcing data and surface flux data were collected at seven sites representing a wide range of climate and vegetation conditions. For each site, four experiments were performed with simple and complex CHASM formulations as well as realistic and global parameter ranges. Twenty eight experiments were conducted and 50 000 parameter sets were used for each run. The results show that the use of global and realistic ranges gives similar simulations for both modes for most sites, but the global ranges tend to produce some unreasonable optimal parameter values. Comparison of simple and complex modes shows that the simple mode has more parameters with unreasonable optimal values. Use of parameter ranges and model complexities have significant impacts on frequency distribution of parameters, marginal posterior probability density functions, and estimates of uncertainty of simulated sensible and latent heat fluxes.Comparison between model complexity and parameter ranges shows that the former has more significant impacts on parameter and uncertainty estimations.     

A simple model of the atmospheric boundary layer; sensitivity to surface evaporation

A simple formulation of the boundary layer is developed for use in large-scale models and other situations where simplicity is required. The formulation is suited for use in models where some resolution is possible within the boundary layer, but where the resolution is insufficient for resolving the detailed boundary-layer structure and overlying capping inversion. Surface fluxes are represented in terms of similarity theory while turbulent diffusivities above the surface layer are formulated in terms of bulk similarity considerations and matching conditions at the top of the surface layer. The boundary-layer depth is expressed in terms of a bulk Richardson number which is modified to include the influence of thermals. Attention is devoted to the interrelationship between predicted boundary-layer growth, the turbulent diffusivity profile, countergradient heat flux and truncation errors.The model predicts growth of the convectively mixed layer reasonably well and is well-behaved in cases of weak surface heat flux and transitions between stable and unstable cases. The evolution of the modelled boundary layer is studied for different ratios of surface evaporation to potential evaporation. Typical variations of surface evaporation result in a much greater variation in boundary-layer depth than that caused by the choice of the boundary-layer depth formulation.     

A study of the performance of a land surface process model (LSPM)

In this paper, a reliable Land-Surface Process Model (LSPM), which is a new version of the LPM of Ji and Hu (1989), is described. The LSPM has been validated with experimental data measured at two stations in the Po Valley (Northern Italy).