Met Office Surface Exchange Scheme Research Articles

The impact of changing the land surface scheme in ACCESS(v1.0/1.1) on the surface climatology

Abstract. The Community Atmosphere Biosphere Land Exchange (CABLE) model has been coupled to the UK Met Office Unified Model (UM) within the existing framework of the Australian Community Climate and Earth System Simulator (ACCESS), replacing the Met Office Surface Exchange Scheme (MOSES). Here we investigate how features of the CABLE model impact on present-day surface climate using ACCESS atmosphere-only simulations. The main differences attributed to CABLE include a warmer winter and a cooler summer in the Northern Hemisphere (NH), earlier NH spring runoff from snowmelt, and smaller seasonal and diurnal temperature ranges. The cooler NH summer temperatures in canopy-covered regions are more consistent with observations and are attributed to two factors. Firstly, CABLE accounts for aerodynamic and radiative interactions between the canopy and the ground below; this placement of the canopy above the ground eliminates the need for a separate bare ground tile in canopy-covered areas. Secondly, CABLE simulates larger evapotranspiration fluxes and a slightly larger daytime cloud cover fraction. Warmer NH winter temperatures result from the parameterization of cold climate processes in CABLE in snow-covered areas. In particular, prognostic snow density increases through the winter and lowers the diurnally resolved snow albedo; variable snow thermal conductivity prevents early winter heat loss but allows more heat to enter the ground as the snow season progresses; liquid precipitation freezing within the snowpack delays the building of the snowpack in autumn and accelerates snow melting in spring. Overall we find that the ACCESS simulation of surface air temperature benefits from the specific representation of the turbulent transport within and just above the canopy in the roughness sublayer as well as the more complex snow scheme in CABLE relative to MOSES.

The ACCESS coupled model: description, control climate and evaluation

4OASIS3.2–5 coupling framework. The primary goal of the ACCESS-CM development is to provide the Australian climate community with a new generation fully coupled climate model for climate research, and to participate in phase five of the Coupled Model Inter-comparison Project (CMIP5). This paper describes the ACCESS-CM framework and components, and presents the control climates from two versions of the ACCESS-CM, ACCESS1.0 and ACCESS1.3, together with some fields from the 20 th century historical experiments, as part of model evaluation. While sharing the same ocean sea-ice model (except different setups for a few parameters), ACCESS1.0 and ACCESS1.3 differ from each other in their atmospheric and land surface components: the former is configured with the UK Met Office HadGEM2 (r1.1) atmospheric physics and the Met Office Surface Exchange Scheme land surface model version 2, and the latter with atmospheric physics similar to the UK Met Office Global Atmosphere 1.0 includ ing modifications performed at CAWCR and the CSIRO Community Atmosphere Biosphere Land Exchange land surface model version 1.8. The global average annual mean surface air temperature across the 500-year preindustrial control integrations show a warming drift of 0.35 °C in ACCESS1.0 and 0.04 °C in ACCESS1.3. The overall skills of ACCESS-CM in simulating a set of key climatic fields both globally and over Australia significantly surpass those from the preceding CSIRO Mk3.5 model delivered to the previous coupled model inter-comparison. However, ACCESS-CM, like other CMIP5 models, has deficiencies in various as pects, and these are also discussed.

The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes

Abstract. This manuscript describes the energy and water components of a new community land surface model called the Joint UK Land Environment Simulator (JULES). This is developed from the Met Office Surface Exchange Scheme (MOSES). It can be used as a stand alone land surface model driven by observed forcing data, or coupled to an atmospheric global circulation model. The JULES model has been coupled to the Met Office Unified Model (UM) and as such provides a unique opportunity for the research community to contribute their research to improve both world-leading operational weather forecasting and climate change prediction systems. In addition JULES, and its forerunner MOSES, have been the basis for a number of very high-profile papers concerning the land-surface and climate over the last decade. JULES has a modular structure aligned to physical processes, providing the basis for a flexible modelling platform.

Soil moisture modelling and validation at an agricultural site in Norfolk using the Met Office surface exchange scheme (MOSES)

AbstractThere is an urgent need for improved soil moisture measurements and modelling due to the relevance of surface moisture to the local energy balance (and hence, for example, air temperature forecasting) to flood prediction and to a range of agricultural applications including plant stress and accessibility of heavy machinery onto the land. The UK Met Office Surface Exchanges Scheme (MOSES) represents land surface processes in the Met Office's Unified Model (MetUM). In this research, MOSES was used to simulate soil moisture over an agricultural site in Norfolk, United Kingdom and validate the model estimations against ground truth soil moisture measurements. Two versions of the MOSES model have been used: the Stand‐Alone MOSES (for site‐specific modelling) and the Nimrod nowcasting products (5 km grid data) based on MOSES Probability Distributed Moisture (MOSES‐PDM). The validation results show that both versions of MOSES perform well in soil moisture estimations in general. However, the MOSES model produces a relatively large seasonal bias in the late summer and autumn seasons and the Nimrod‐MOSES‐PDM tends to underestimate soil moisture in general. A model sensitivity study shows that the soil parameters are most likely to contribute to the errors. In addition, the MOSES model treats the vegetation fraction as a constant throughout a year over agricultural fields, which was found partly to cause the seasonal bias. Recommendations on how to improve MOSES soil moisture estimation are discussed, as are the likely application benefits. Copyright © 2010 Royal Meteorological Society

Near‐surface soil moisture retrieval from ASAR Wide Swath imagery using a Principal Component Analysis

The new ENVISAT Advanced Synthetic Aperture Radar (ASAR) Wide Swath Mode (WSM) data provide good potential for routinely monitoring near surface soil moisture due to the increased temporal revisit capability compared with ERS2 SAR. In this paper, we propose a Principal Components Analysis (PCA) to retrieve near‐surface soil moisture from ASAR WSM data. The results demonstrate that PCA transformation can at least partially separate or group the effect factors, such as surface roughness, land cover, vegetation, and topography within the limitations of our datasets. The second principal component which was consistent with soil moisture and rainfall‐runoff dynamics was representative of the soil moisture Saturation Potential Index over a large area. Validation against field measurements and against the UK Met Office Surface Exchange Scheme shows the retrieval performs with reasonable accuracy.

Evaluation of the Urban Tile in MOSES using Surface Energy Balance Observations

The UK Met Office has introduced a new scheme for its urban tile in MOSES 2.2 (Met Office Surface Exchange Scheme version 2.2), which is currently implemented within the operational Met Office weather forecasting model. Here, the performance of the urban tile is evaluated in two urban areas: the historic core of downtown Mexico City and a light industrial site in Vancouver, Canada. The sites differ in terms of building structures and mean building heights. In both cases vegetation cover is less than 5%. The evaluation is based on surface energy balance flux measurements conducted at approximately the blending height, which is the location where the surface scheme passes flux data into the atmospheric model. At both sites, MOSES 2.2 correctly simulates the net radiation, but there are discrepancies in the partitioning of turbulent and storage heat fluxes between predicted and observed values. Of the turbulent fluxes, latent heat fluxes were underpredicted by about one order of magnitude. Multiple model runs revealed MOSES 2.2 to be sensitive to changes in the canopy heat storage and in the ratio between the aerodynamic roughness length and that for heat transfer (temperature). Model performance was optimum with heat capacity values smaller than those generally considered for these sites. The results suggest that the current scheme is probably too simple, and that improvements may be obtained by increasing the complexity of the model.

Comparison of the Met Office's surface exchange scheme, MOSES, against field observations

AbstractResults are presented from a comparison of the Met Office Surface Exchange Scheme (MOSES) with observational data. A stand‐alone version of MOSES is used which can be forced directly with observations rather than model output. The forcing data consist of near‐surface measurements of incident radiation, wind speed, temperature, pressure, humidity and precipitation, and the model output is compared with measured surface fluxes of sensible and latent heat and with soil moisture at several levels below the surface. The dataset spans four years and comes from a grassland site with a shallow water table, the Met Office Research Unit at Cardington in Bedfordshire, UK.The performance of the model is assessed in response to the variation of some key parameters and parametric functions. The model calculation of atmospheric fluxes is found to be robust to variations in the soil thermal properties, and it is shown that there is little overall improvement in model performance as the vegetation height and ratio of scalar to momentum roughness lengths are varied over a range of possible values. The calculation of atmospheric moisture flux and soil‐moisture profile is assessed using two constant subsurface profiles of saturated hydraulic conductivity and one profile which decreases with depth. It is found that the last of these can produce a more physically accurate profile of soil moisture, but with current model tuning this produces less accurate values of atmospheric moisture flux. The model results compare favourably with those of a force–restore model. Copyright © 2006 Crown copyright

An annual cycle of vegetation in a GCM. Part II: global impacts on climate and hydrology

The Met Office Hadley Centre Unified Model (HadAM3) with the tiled version of the Met Office Surface Exchange Scheme (MOSES2) land surface scheme is used to assess the impact of a comprehensive imposed vegetation annual cycle on global climate and hydrology. Two 25-year numerical experiments are completed: the first with structural vegetation characteristics (Leaf Area Index, LAI, canopy height, canopy water capacity, canopy heat capacity, albedo) held at annual mean values, the second with realistic seasonally varying vegetation characteristics. It is found that the seasonalities of latent heat flux and surface temperature are widely affected. The difference in latent heat flux between experiments is proportional to the difference in LAI. Summer growing season surface temperatures are between 1 and 4 K lower in the phenology experiment over a majority of grid points with a significant vegetation annual cycle. During winter, midlatitude surface temperatures are also cooler due to brighter surface albedo over low LAI surfaces whereas during the dry season in the tropics, characterized by dormant vegetation, surface temperatures are slightly warmer due to reduced transpiration. Precipitation is not as systematically affected as surface temperature by a vegetation annual cycle, but enhanced growing season precipitation rates are seen in regions where the latent heat flux (evaporation) difference is large. Differences between experiments in evapotranspiration, soil moisture storage, the timing of soil thaw, and canopy interception generate regional perturbations to surface and sub-surface runoff annual cycles in the model.

An annual cycle of vegetation in a GCM. Part I: implementation and impact on evaporation

The sensitivity of evaporation to a prescribed vegetation annual cycle is examined globally in the Met Office Hadley Centre Unified Model (HadAM3) which incorporates the Met Office Surface Exchange Scheme (MOSES2) as the land surface scheme. A vegetation annual cycle for each plant functional type in each grid box is derived based on satellite estimates of Leaf Area Index (LAI) obtained from the nine-year International Satellite Land Surface Climatology Project II dataset. The prescribed model vegetation seasonality consists of annual cycles of a number of structural vegetation characteristics including LAI as well as canopy height, surface roughness, canopy water capacity, and canopy heat capacity, which themselves are based on empirical relationships with LAI. An annual cycle of surface albedo, which in the model is a function of soil albedo, surface soil moisture, and LAI, is also modelled and agrees reasonably with observed estimates of the surface albedo annual cycle. Two 25-year numerical experiments are completed and compared: the first with vegetation characteristics held at annual mean values, the second with prescribed realistic seasonally varying vegetation. Initial analysis uncovered an unrealistically weak relationship between evaporation and vegetation state that is primarily due to the insensitivity of evapotranspiration to LAI. This weak relationship is strengthened by the adjustment of two MOSES2 parameters that together improve the model’s LAI-surface conductance relationship by comparison with observed and theoretical estimates. The extinction coefficient for photosynthetically active radiation, kpar, is adjusted downwards from 0.5 to 0.3, thereby enhancing the LAI-canopy conductance relationship. A canopy shading extinction coefficient, ksh, that controls what fraction of the soil surface beneath a canopy is directly exposed to the overlying atmosphere is increased from 0.5 to 1.0, which effectively reduces soil evaporation under a dense canopy. When the experiments are repeated with the adjusted parameters, the relationship between evaporation and vegetation state is strengthened and is more spatially consistent. At nearly all locations, the annual cycle of evaporation is enhanced in the seasonally varying vegetation experiment. Evaporation is stronger during the peak of the growing season and, in the tropics, reduced transpiration during the dry season when LAI is small leads to significantly lower total evaporation.

The Sensitivity of Global Climate Model Simulations to the Representation of Soil Moisture Heterogeneity

Improving the treatment of subgrid-scale soil moisture variations is recognized as a priority for the next generation of land surface schemes. Here, the impact of an improved representation of subgrid-scale soil moisture heterogeneity on global climate model (GCM) simulations of current and future climates is carried out using Version three of the Hadley Centre Atmospheric Climate Model (HadAM3) coupled to the Met Office Surface Exchange Scheme (MOSES). MOSES was adapted to make use of the rainfall runoff model TOPMODEL algorithms, which relate the local water table depth to the grid box mean water table depth, assuming that subgrid-scale topography is the primary cause of soil moisture heterogeneity. This approach was also applied to produce a novel model for wetland area, which can ultimately be used to interactively model methane emissions from wetlands. The modified scheme was validated offline by forcing with near-surface Global Soil Wetness Project (GSWP) data, and online within the HadAM3 global climate model. In both cases it was found to improve the present-day simulation of runoff and produce realistic distributions of global wetland area. (Precipitation was also improved in the online simulation.) The new scheme results in substantial differences in the modeled sensitivity of runoff to climate change, with implications for the modeling of hydrological impacts.

Developments in the MOSES 2 land-surface model for PILPS 2e

Improved representations of snow processes in vegetation canopies and snow hydrology are implemented in the Met Office Surface Exchange Scheme 2 (MOSES 2) land-surface model. Snow falling on forests is partitioned between interception and throughfall; the intercepted snow is removed by sublimation, melt and unloading. A reduction in sublimation of wind-blown snow through trapping by shrubs is simply represented by reducing the scalar roughness length for shrubs with snow cover. Melt water may be retained and refrozen within snow packs. By reducing the amount of snow lost through sublimation and delaying the runoff of melt water, these modifications are found to improve the simulations of runoff for two Swedish catchments used in the PILPS 2e intercomparison project.

Modelling soil moisture for a grassland and a woodland site in south-east England

Abstract. This paper describes a comparison between two soil moisture prediction models. One is MORECS (Met Office Rainfall and Evaporation Calculation Scheme), the Met Office soil moisture model that is used by agriculture, flood modellers and weather forecasters to initialise their models. The other is MOSES (Met Office Surface Exchange Scheme), modified with a runoff generation module. The models are made compatible by increasing the vegetation information available to MOSES. Both models were run with standard parameters and were driven using meteorological observations at Wallingford (1995-1997). Detailed soil moisture measurements were available at a grassland site and a woodland site in this area. The comparison between the models and the observed soil moisture indicated that, for the grassland site, MORECS dried out too quickly in the spring and, for the woodland site, was too wet. Overall, the performance of MOSES was superior. The soil moisture predicted by the new, modified MOSES will be included as a product of Nimrod - the 5 km x 5km gridded network of observed meteorological data across the UK. Keywords: Soil moisture, model, observation, field capacity

Modelling the local surface exchange over a grass-field site under stable conditions

Observations of near-surface variables are used with the Met Office Surface Exchange Scheme to calculate the exchange of heat and moisture between the surface and the atmosphere for a grass-field site at the Met Office, Cardington, UK. Different methods for modelling the stability near the surface are investigated with the surface temperatures and turbulent heat fluxes compared with data collected from the site. The results show that, whilst using Monin-Obukhov similarity theory can give good results in stable conditions, the form of the stability functions can significantly affect the accuracy in certain stability regimes. The use of log-linear stability functions can cause the turbulent fluxes of heat and moisture to cut off at stabilities which are too close to neutral compared with the observations. The results also show that unrealistically high surface temperatures are obtained in clear-sky nocturnal conditions with the standard surface energy balance. An alternative energy balance which includes a canopy of vegetation above the underlying soil gives better agreement with the observations in these conditions.

Modelling the local surface exchange over a grass‐field site under stable conditions

AbstractObservations of near‐surface variables are used with the Met Office Surface Exchange Scheme to calculate the exchange of heat and moisture between the surface and the atmosphere for a grass‐field site at the Met Office, Cardington, UK. Different methods for modelling the stability near the surface are investigated with the surface temperatures and turbulent heat fluxes compared with data collected from the site. The results show that, whilst using Monin‐Obukhov similarity theory can give good results in stable conditions, the form of the stability functions can significantly affect the accuracy in certain stability regimes. The use of log‐linear stability functions can cause the turbulent fluxes of heat and moisture to cut off at stabilities which are too close to neutral compared with the observations. The results also show that unrealistically high surface temperatures are obtained in clear‐sky nocturnal conditions with the standard surface energy balance. An alternative energy balance which includes a canopy of vegetation above the underlying soil gives better agreement with the observations in these conditions.

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.