Australian Community Climate Research Articles

A spectral nudging method for the ACCESS1.3 atmospheric model

Abstract. A convolution-based method of spectral nudging of atmospheric fields is developed in the Australian Community Climate and Earth Systems Simulator (ACCESS) version 1.3 which uses the UK Met Office Unified Model version 7.3 as its atmospheric component. The use of convolutions allow for flexibility in application to different atmospheric grids. An approximation using one-dimensional convolutions is applied, improving the time taken by the nudging scheme by 10–30 times compared with a version using a two-dimensional convolution, without measurably degrading its performance. Care needs to be taken in the order of the convolutions and the frequency of nudging to obtain the best outcome. The spectral nudging scheme is benchmarked against a Newtonian relaxation method, nudging winds and air temperature towards ERA-Interim reanalyses. We find that the convolution approach can produce results that are competitive with Newtonian relaxation in both the effectiveness and efficiency of the scheme, while giving the added flexibility of choosing which length scales to nudge.

A regional forecast model evaluation of statistical rainfall properties using the CPOL radar observations in different precipitation regimes over Darwin, Australia

This study evaluates the ability of the regional high‐resolution version of the Australian Community Climate and Earth‐System Simulator (ACCESS‐A) model (horizontal resolution of 12 km, 50 height levels with a 37.5 km top) to simulate statistical rainfall properties during three monsoon seasons using the Darwin C‐band polarimetric (CPOL) radar observation as a reference. The comparison consists of characteristics of precipitation, including the total‐domain accumulated daily rainfall, the daily rain intensity and frequency and the probability distribution function of hourly rain rate. These characteristics are then binned using five large‐scale atmospheric regimes that represent the main weather states in that region to assess the ability of the model to reproduce the variability of the statistical rainfall properties as a function of these defined regimes. The main results are that although the model reproduces the accumulated daily rainfall amount reasonably well, albeit tending to slightly overestimate it, the mean rain rate is too weak, compensated by too large a rain frequency of occurrence. In terms of intensity the model tends to perform worse in the dry regimes but improves in the wet regimes, especially during the ‘Deep Westerly’ regime, when most of the monsoonal precipitation is produced. Probability distribution functions of rain rates reveal that although there are small differences amongst regimes, marked discrepancies are found between model and observations. The ACCESS‐A overestimates light rain rates, underestimates moderate to heavy rain rates and produces spurious very heavy rain rates that are not observed at all by the radar. The evaluation of the diurnal cycle of rainfall properties also reveals a general underestimate of rain rates, compensated by an overestimated rain frequency over the whole cycle, resulting in an overestimated amplitude and a wrong timing of the diurnal cycle. In all regimes, the overestimation of total‐domain daily rainfall and rain frequency is found to be due to an overestimation of low rain rates produced by the ACCESS‐A convective scheme, while the underestimation of mean rain rate is due to an underestimate of high rain rates and high rain rates frequency by the ACCESS‐A convective scheme.

Evaluation of boundary‐layer cloud forecasts over the Southern Ocean in a limited‐area numerical weather prediction system usingin situ, space‐borne and ground‐based observations

Near‐synchronized in situ, space‐borne (A‐Train) and ground‐based lidar observations are employed to evaluate the boundary‐layer clouds (BLCs) over Tasmania and the adjacent Southern Ocean (SO) simulated by the limited‐area version of Australian Community Climate and Earth System Simulator (ACCESS‐C). Two winter cases featuring BLCs associated with a post‐frontal environment and the leading side of a high‐pressure ridge are studied. Previous studies showed that these synoptic conditions contribute to the largest reflected short‐wave radiation biases simulated over the SO.Results of the simulations suggest that the ACCESS‐C model demonstrates an appreciable level of skill in simulating the macrophysical properties of the BLCs over the SO, generally consistent with the in situ and remote‐sensing observations. However, some notable challenges remain: the area cloud fraction of the marine BLCs is consistently underpredicted; the fine‐scale structure of the marine cumuli is poorly represented in the 4 km grid‐length simulations; the capping inversion over the marine boundary layer is generally too high, associated with the marine BLCs being predicted at the wrong altitude and temperature ranges; the liquid water content (LWC) of the BLCs is underestimated; and the model representation of drizzle production can be too efficient.Sensitivity studies are also conducted to test a newly developed autoconversion microphysics scheme and shear‐dominated planetary boundary‐level (PBL) scheme. These parametrizations show notable improvement in cloud prediction for CASE B (i.e. better area cloud fraction and better average and maximum values of LWC). However, none of these tests is able to improve the simulated marine PBL structure. Overall, the simulated cloud biases are jointly influenced by physical parametrizations, poor representations of large‐scale advection, surface fluxes and subsidence. More substantial observations are needed to improve our understanding of the origins and development of these biases and the relative contribution of these errors to the radiation budget over the SO.

Simulations of atmospheric methane for Cape Grim, Tasmania, to constrain southeastern Australian methane emissions

Abstract. This study uses two climate models and six scenarios of prescribed methane emissions to compare modelled and observed atmospheric methane between 1994 and 2007, for Cape Grim, Australia (40.7° S, 144.7° E). The model simulations follow the TransCom-CH4 protocol and use the Australian Community Climate and Earth System Simulator (ACCESS) and the CSIRO Conformal-Cubic Atmospheric Model (CCAM). Radon is also simulated and used to reduce the impact of transport differences between the models and observations. Comparisons are made for air samples that have traversed the Australian continent. All six emission scenarios give modelled concentrations that are broadly consistent with those observed. There are three notable mismatches, however. Firstly, scenarios that incorporate interannually varying biomass burning emissions produce anomalously high methane concentrations at Cape Grim at times of large fire events in southeastern Australia, most likely due to the fire methane emissions being unrealistically input into the lowest model level. Secondly, scenarios with wetland methane emissions in the austral winter overestimate methane concentrations at Cape Grim during wintertime while scenarios without winter wetland emissions perform better. Finally, all scenarios fail to represent a~methane source in austral spring implied by the observations. It is possible that the timing of wetland emissions in the scenarios is incorrect with recent satellite measurements suggesting an austral spring (September–October–November), rather than winter, maximum for wetland emissions.

Greenhouse gas network design using backward Lagrangian particle dispersion modelling − Part 1: Methodology and Australian test case

Abstract. This paper describes the generation of optimal atmospheric measurement networks for determining carbon dioxide fluxes over Australia using inverse methods. A Lagrangian particle dispersion model is used in reverse mode together with a Bayesian inverse modelling framework to calculate the relationship between weekly surface fluxes, comprising contributions from the biosphere and fossil fuel combustion, and hourly concentration observations for the Australian continent. Meteorological driving fields are provided by the regional version of the Australian Community Climate and Earth System Simulator (ACCESS) at 12 km resolution at an hourly timescale. Prior uncertainties are derived on a weekly timescale for biosphere fluxes and fossil fuel emissions from high-resolution model runs using the Community Atmosphere Biosphere Land Exchange (CABLE) model and the Fossil Fuel Data Assimilation System (FFDAS) respectively. The influence from outside the modelled domain is investigated, but proves to be negligible for the network design. Existing ground-based measurement stations in Australia are assessed in terms of their ability to constrain local flux estimates from the land. We find that the six stations that are currently operational are already able to reduce the uncertainties on surface flux estimates by about 30%. A candidate list of 59 stations is generated based on logistic constraints and an incremental optimisation scheme is used to extend the network of existing stations. In order to achieve an uncertainty reduction of about 50%, we need to double the number of measurement stations in Australia. Assuming equal data uncertainties for all sites, new stations would be mainly located in the northern and eastern part of the continent.

Improved air–sea flux algorithms in an ocean–atmosphere coupled model for simulation of global ocean SST and its tropical Pacific variability

A revised algorithm for air–sea exchange parameterization of momentum, sensible and latent heat flux improves the climate simulation of the global distribution of sea surface temperature (SST) and tropical Pacific variability of SST. Based upon an analysis of studies from field programs, we apply the revised algorithm with new expressions for surface momentum and scalar roughness length dependent on 10-m winds in neutral condition, and evaluate them in the ocean–atmosphere coupled model of the Australian Community Climate and Earth-System Simulator. The revised algorithm improves simulations for mean global SST distribution, demonstrated with Pearson’s correlation indices showing corrections to a net fraction of 28 % over the global oceans. Being focused on the tropical Pacific, the algorithm eases the tropical SST cold tongue bias, and improves predictability of ENSO variability with better representations of the standard deviation of the Nino-3.4 index, especially the skewness of the index for nonlinearity of ENSO variability. Bjerknes and thermodynamical feedbacks are applied to understand the effects of the revised algorithm on the predictability of the Nino indices.

The relationship between clouds and dynamics in Southern Hemisphere extratropical cyclones in the real world and a climate model

AbstractThe representation of clouds over the Southern Ocean in contemporary climate models remains a major challenge. A major dynamical influence on the structure of clouds is the passage of extratropical cyclones. They exert significant dynamical influences on the clouds in the dynamically active frontal regions as well as in the dynamically suppressed regions ahead and behind the cyclones. A cyclone compositing methodology is applied to a reanalysis and vertical profiles of cloudiness from CloudSat/CALIPSO to quantify the relationship between clouds and dynamics in extratropical cyclones over the Southern Ocean. It is found that the range of cloud fraction, vertical motion, and relative humidity changes considerably with height. There is a strong quasi‐linear relationship between the three variables which changes with altitude. After establishing the observed relationships, the methodology is applied to the Australian Community Climate and Earth System Simulator to evaluate the model's ability to simulate the identified cloud‐dynamics relationships. While the model is able to qualitatively reproduce the overall cloud structure, the circulation around the cyclone is generally too weak. As a result, the model fails to represent the observed cloud to dynamics relationship. This wrong relationship in the model leads to a misrepresentation of the cloud field manifested as either an error in the cloud fraction or as simulating the “right” clouds for the “wrong” reason. The result underscores the importance of relationship‐oriented model evaluation techniques over simple right or wrong assessments.

Assessment of forced responses of the Australian Community Climate and Earth System Simulator (ACCESS) 1.3 in CMIP5 historical detection and attribution experiments.

The Australian Community Climate and Earth System Simulator (ACCESS) coupled climate model version 1.3 participated in phase five of the Coupled Model Intercomparison Project (CMIP5) with an initial contribution of high priority experiments. Further standard experiments have since been conducted with ACCESS1.3, including an ensemble of three simulations for the historical period (1850-2005) forced with time-evolving natural and anthropogenic forcings. Additional ensembles of simulations have been conducted for the same period with subsets of known forcings, including with natural forcings only ('historicalNat') and with greenhouse gas forcings only ('historicalGHG'). In this study, we describe this ACCESS1.3 contribution to CMIP5 and assess several key aspects of ACCESS1.3 forced responses in these experiments against observations and an ensemble of participating CMIP5 models, consisting of 40 realisations from ten models. Overall, ACCESS1.3 historical experiments demonstrate skill in simulating the global and regional metrics assessed that is comparable to the CMIP5 multi-model ensemble utilised. Global annual average temperature and precipitation trends simulated with ACCESS1.3 (0.05-0.07 K/decade; -0.007 to -0.0004 mm day /decade) largely lie within the CMIP5 ensemble window (0.06 - 0.18 K/decade; -0.01 to 0.009 mm day /decade) and near those observed (0.10 K/decade; -0.0007 to -0.001 mm day-1/decade) over the 1950-2005 period. For the ACCESS1.3 historicalNat and historicalGHG experiments, simulated temperature trends are also predominately within the CMIP5 multi-model ensemble range. Similarly, ACCESS1.3 (-0.07 to -0.12 K) and the CMIP5 models (-0.03 to -0.21 K) largely capture the composited observed decrease in global temperature (-0.04 K) following three major late 20th century volcanic eruptions. However, like all global climate models, ACCESS1.3 has deficiencies that should be considered. In particular, one of most notable features of ACCESS1.3 historical simulations is the reduced warming trend over the period 1950-2005 that is evident in all ACCESS1.3 realisations at the global-scale for Australia, relative to both observations and the CMIP5 multi-model mean. This appears to be related to the overly strong response to increases in anthropogenic aerosols. Overall, these historical period experiments using ACCESS1.3 with various forcings are useful for inclusion with other CMIP5 models for studies aimed at detecting and attributing climatic changes. -1 -1

Forecasting daily reference evapotranspiration for Australia using numerical weather prediction outputs

Farmers and irrigation system operators make real-time irrigation decisions based on a range of factors including short-term weather forecasts of rainfall and temperature. The simplest and oldest statistical method for forecasting daily ET0 is to use the long-term monthly mean ET0 based on historical observations. Forecasts of reference crop evapotranspiration (ET0) can be calculated from Numerical Weather Prediction (NWP) outputs and ET0 has the advantage of being more directly relevant to crop water requirements than temperature. This paper evaluates forecasts of ET0 made using the Bureau of Meteorology's operational NWP forecasts derived from the Australian Community Climate and Earth System Simulator – Global (ACCESS-G). The forecast performance for ET0 was quantified using the root mean squared error (RMSE), coefficient of determination (R2), anomaly correlation coefficient (ACC) and mean square skill score (MSSS). Daily ET0 forecasts for lead times up to 9 days were compared against ET0 calculated using hourly observations from the 40 automatic weather stations across Australia.It was found that using NWP forecast daily ET0 was better than using the long-term monthly mean ET0 for lead times up to 6 days, beyond which the long-term monthly mean was better. The average MSSS for ET0 forecasts across all stations varied between 66% and 12% for lead times of 1–6 days, respectively. Further, it was found that forecast performance for daily ET0 was highest in autumn for tropical climates and lowest in spring for temperate climates. Errors in incoming solar radiation were the most important source of ET0 forecast error, followed by air temperature, dew point temperature and wind speed, for all lead times. Also, it was found that the forecast performances for incoming solar radiation and mean wind speed were relatively poor compared with the air and dew point temperatures

Representation of climate extreme indices in the ACCESS1.3b coupled atmosphere–land surface model

Abstract. Climate extremes, such as heat waves and heavy precipitation events, have large impacts on ecosystems and societies. Climate models provide useful tools for studying underlying processes and amplifying effects associated with extremes. The Australian Community Climate and Earth System Simulator (ACCESS) has recently been coupled to the Community Atmosphere Biosphere Land Exchange (CABLE) model. We examine how this model represents climate extremes derived by the Expert Team on Climate Change Detection and Indices (ETCCDI) and compare them to observational data sets using the AMIP framework. We find that the patterns of extreme indices are generally well represented. Indices based on percentiles are particularly well represented and capture the trends over the last 60 years shown by the observations remarkably well. The diurnal temperature range is underestimated, minimum temperatures (TMIN) during nights are generally too warm and daily maximum temperatures (TMAX) too low in the model. The number of consecutive wet days is overestimated, while consecutive dry days are underestimated. The maximum consecutive 1-day precipitation amount is underestimated on the global scale. Biases in TMIN correlate well with biases in incoming longwave radiation, suggesting a relationship with biases in cloud cover. Biases in TMAX depend on biases in net shortwave radiation as well as evapotranspiration. The regions and season where the bias in evapotranspiration plays a role for the TMAX bias correspond to regions and seasons where soil moisture availability is limited. Our analysis provides the foundation for future experiments that will examine how land-surface processes contribute to these systematic biases in the ACCESS modelling system.

ACCESS-TC: Vortex Specification, 4DVAR Initialization, Verification, and Structure Diagnostics

Abstract The Australian Community Climate and Earth System Simulator (ACCESS) has been adapted for operational and research applications on tropical cyclones. The base system runs at a resolution of 0.11° and 50 levels. The domain is relocatable and nested in coarser-resolution ACCESS forecasts. Initialization consists of five cycles of four-dimensional variational data assimilation (4DVAR) over 24 h. Forecasts to 72 h are made. Without vortex specification, initial conditions usually contain a weak and misplaced circulation pattern. Significant effort has been devoted to building physically based, synthetic inner-core structures, validated using historical dropsonde data and surface analyses from the Atlantic. Based on estimates of central pressure and storm size, vortex specification is used to filter the analyzed circulation from the original analysis, construct an inner core of the storm, locate it to the observed position, and merge it with the large-scale analysis at outer radii. Using all available conventional observations and only synthetic surface pressure observations from the idealized vortex to correct the initial location and structure of the storm, the 4DVAR builds a balanced, intense 3D vortex with maximum wind at the radius of maximum wind and with a well-developed secondary circulation. Mean track and intensity errors for Australian region and northwest Pacific storms have been encouraging, as are recent real-time results from the Australian National Meteorological and Oceanographic Centre. The system became fully operational in November 2011. From preliminary diagnostics, some interesting structure change features are illustrated. Current limitations, future enhancements, and research applications are also discussed.

Evaluation of hydrometeor frequency of occurrence in a limited‐area numerical weather prediction system using near real‐time CloudSat–CALIPSO observations

Near real‐time measurements from the CloudSat and Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission are used to evaluate the representation of the hydrometeor frequency of occurrence (HFO) in the limited‐area version of the Australian Community Climate and Earth‐System Simulator (ACCESS‐A), using 1 year of collocated satellite data and model forecasts. The ACCESS‐A is found to overpredict the HFO below 12 km height (primarily over the Southern Ocean), and largely underpredict the HFO above 12 km height (primarily in the Tropics). The seasonal variability of these biases was found to be small suggesting that these model problems can be investigated with short‐term simulations. This implies that faster model improvement should be achievable using the technique proposed in this study.Selected skill scores were then analysed as a function of lead time, hydrometeor height in the troposphere and season. The highest forecast skill was found in the subtropics, mostly owing to a low incidence of false positives. Overall the ACCESS‐A forecast skill at the Southern Hemisphere mid‐latitudes is comparable to that of the North Atlantic/European version of the UK Met Office Unified Model at Northern Hemisphere mid‐latitudes. It is also found that mid‐latitude low‐level hydrometeors and tropical low‐level and high‐level hydrometeors during the Southern Hemisphere summer are the most challenging hydrometeors to simulate in the domain.

Effectiveness of the Bjerknes stability index in representing ocean dynamics

The El Nino-Southern Oscillation (ENSO) is a naturally occurring coupled phenomenon originating in the tropical Pacific Ocean that relies on ocean–atmosphere feedbacks. The Bjerknes stability index (BJ index), derived from the mixed-layer heat budget, aims to quantify the ENSO feedback process in order to explore the linear stability properties of ENSO. More recently, the BJ index has been used for model intercomparisons, particularly for the CMIP3 and CMIP5 models. This study investigates the effectiveness of the BJ index in representing the key ENSO ocean feedbacks—namely the thermocline, zonal advective, and Ekman feedbacks—by evaluating the amplitudes and phases of the BJ index terms against the corresponding heat budget terms from which they were derived. The output from Australian Community Climate and Earth System Simulator Ocean Model (a global ocean/sea ice flux-forced model) is used to calculate the heat budget in the equatorial Pacific. Through the model evaluation process, the robustness of the BJ index terms are tested. We find that the BJ index overestimates the relative importance of the thermocline feedback to the zonal advective feedback when compared with the corresponding terms from the heat budget equation. The assumption of linearity between variables in the BJ index formulation is the primary reason for these differences. Our results imply that a model intercomparison relying on the BJ index to explain ENSO behavior is not necessarily an accurate quantification of dynamical differences between models that are inherently nonlinear. For these reasons, the BJ index may not fully explain underpinning changes in ENSO under global warming scenarios.

The Australian Community Climate and Earth System Simulator, ACCESS: scientific justification and options for system development

The Australian Community Climate and Earth System Simulator, ACCESS: scientific justification and options for system development

The application of radio occultation observations for climate monitoring and numerical weather prediction in the Australian region

Space-based GPS radio occultation observations provide significant information related to current and future atmospheric state. They also enable important activities such as examination of radiosonde performance and temperature trends. Three months of radio occultation observations have been assimilated using four dimensional variational assimilation into the global Australian Community Climate Earth Systems Simulator, ACCESS-G, which is employed at the Australian Bureau of Meteorology to provide operational forecasts. The radio occultation data was found to improve the forecasts in the lower, middle and upper troposphere. The improvement varies from small, to up to eight-hours improvement in 48-hour forecasts of mean sea level pressure. Because of the relatively unbiased nature of radio occultation observations, they have been used in a comparative study with radiosonde data to probe mean annual atmospheric temperature changes in the Australian region and the southern hemisphere. In particular, differences between radio occultation data based, area weighted annual average short-term (2007-2010) temperature trends over the Australian region and the southern hemisphere and those obtained by averaging data at radiosonde network sites were noted. In the Australian region a mid and upper tropospheric area averaged temperature increase from 2007 to 2010 was accompanied by an average cooling at radiosonde sites. The radio occultation data have also been used to probe ionospheric content. Results documented here indicate the use of radio occultation data has the potential to improve operational analysis and forecasting in the Australian region and to make a very important and unique contribution to vital tasks such as climate monitoring.

Evaluation of numerical weather prediction model precipitation forecasts for short-term streamflow forecasting purpose

Abstract. The quality of precipitation forecasts from four Numerical Weather Prediction (NWP) models is evaluated over the Ovens catchment in Southeast Australia. Precipitation forecasts are compared with observed precipitation at point and catchment scales and at different temporal resolutions. The four models evaluated are the Australian Community Climate Earth-System Simulator (ACCESS) including ACCESS-G with a 80 km resolution, ACCESS-R 37.5 km, ACCESS-A 12 km, and ACCESS-VT 5 km. The skill of the NWP precipitation forecasts varies considerably between rain gauging stations. In general, high spatial resolution (ACCESS-A and ACCESS-VT) and regional (ACCESS-R) NWP models overestimate precipitation in dry, low elevation areas and underestimate in wet, high elevation areas. The global model (ACCESS-G) consistently underestimates the precipitation at all stations and the bias increases with station elevation. The skill varies with forecast lead time and, in general, it decreases with the increasing lead time. When evaluated at finer spatial and temporal resolution (e.g. 5 km, hourly), the precipitation forecasts appear to have very little skill. There is moderate skill at short lead times when the forecasts are averaged up to daily and/or catchment scale. The precipitation forecasts fail to produce a diurnal cycle shown in observed precipitation. Significant sampling uncertainty in the skill scores suggests that more data are required to get a reliable evaluation of the forecasts. The non-smooth decay of skill with forecast lead time can be attributed to diurnal cycle in the observation and sampling uncertainty. Future work is planned to assess the benefits of using the NWP rainfall forecasts for short-term streamflow forecasting. Our findings here suggest that it is necessary to remove the systematic biases in rainfall forecasts, particularly those from low resolution models, before the rainfall forecasts can be used for streamflow forecasting.

The Operational Generation of Continuous Winds in the Australian Region and Their Assimilation with 4DVAR

Abstract Atmospheric motion vectors (AMVs) have been generated continuously from Multifunctional Transport Satellite 1 Replacement (MTSAT-1R) radiance data (imagery) since 2005, and more recently from MTSAT-2, which are operated by the Japan Meteorological Agency (JMA). These are the primary geostationary meteorological satellites observing the western Pacific, Asia, and the Australian region. The vectors are used operationally, for analysis in the Darwin Regional Forecast Office. The near-continuous AMVs have been stringently error characterized and used in near-real-time trials to gauge their impact on operational regional numerical weather prediction (NWP), using four-dimensional variational data assimilation (4DVAR). The use of these locally generated hourly vectors (the only hourly AMV source in the region at the time) and 4DVAR has resulted in both improved temporal and spatial data coverage in the operational regional forecast domain. The beneficial impact of these data on the Bureau of Meteorology’s (Bureau’s) current operational system is described. After these trials, the hourly MTSAT AMVs were introduced into the Bureau’s National Meteorological and Oceanographic Centre’s (NMOC) operational NWP suite for use by the operational Australian Community Climate Earth System Simulator (ACCESS) regional and global models, ACCESS-R and ACCESS-G, respectively. Examples of their positive impact on both midlatitude and tropical cyclone forecasts are presented.

Evaluation of ACCESS climate model ocean diagnostics in CMIP5 simulations

Global and regional diagnostics are used to evaluate the ocean performance of the Australian Community Climate and Earth System Simulator coupled model (ACCESS-CM) contributions to the Climate Model Intercomparison Project phase 5 (CMIP5). Two versions of ACCESS-CM have been submitted to CMIP; namely CSIRO-BOM ACCESS1.0 and CSIRO-BOM ACCESS1.3. Results from six of the core CMIP5 experiments (piControl, historical, rcp45, rcp85, 1pctCO2, and abrupt4xCO2) are evaluated for each of the two ACCESS-CM model versions. Overall, both model versions exhibit a reasonable and stable representation of key diagnostics of ocean climate performance in the pre-industrial control simulations, including a meridional overturning circulation with North Atlantic Deep Water maxima in the range 22–24 Sv, and a poleward heat transport maximum of around 1.5 PW. For the projected climate change scenarios considered the ACCESS-CM results are in reasonable agreement with responses found in other CMIP models, with the familiar ocean warming, and reduction in strength of meridional overturning and poleward heat transport. Drifts in the control simulations of both global ocean salinity and global sea-level are opposite in sign for ACCESS1.0 and ACCESS1.3, suggesting problems exist in the closure of the hydrological cycle. The simulation of ocean climate change over the historical period shows a weak response compared to observations, which manifests as a late response of ocean warming and sea level rise starting around 1990 in the model, compared to the mid 1960s in observations. Further historical simulations are underway to ascertain if this late response in ACCESS is a robust model feature, or just low frequency variability. If the weak response over the historical period proves robust, the likely cause is a too strong cooling from atmospheric aerosols. Broadening the set of experiments to further investigate the relative warming response of the ACCESS-CM to greenhouse gases compared to the cooling response to aerosols is underway, and preliminary results do suggest that the cooling due to aerosols is strong in the historical simulations.

Evaluation of clouds in ACCESS using the satellite simulator package COSP: Global, seasonal, and regional cloud properties

Cloud properties from the Australian Community Climate and Earth System Simulator (ACCESS1.3) are evaluated using the Cloud Feedback Model Intercomparison Project (CFMIP) Observational Simulator Package (COSP). CloudSat, CALIPSO, and International Satellite Cloud Climatology Project (ISCCP) observations are used to evaluate the modeled cloud cover, condensate properties, and cloud optical depths for two seasons. The global distribution of cloud in the model is generally well represented with maximum high cloud in the tropics and low cloud over the eastern edges of the ocean basins. The model captures the observed position of the midlatitude storm track clouds and the modeled cloud top heights compare well with the observations in the upper troposphere. However, there is a lack of modeled midlevel cloud in the tropics and midlatitudes. The average high cloud cover in the Tropical Warm Pool region shows good agreement with CALIPSO. However, the modeled radar reflectivities and lidar scattering ratios are biased toward lower values, suggesting that the ice water contents and particles sizes of these clouds in the model are too small. Over the Southern Ocean the modeled cloud cover is underestimated due to a lack of mid‐ and low‐level cloud. The low clouds over the Southern Ocean and the California stratocumulus clouds in the model have too little condensate and optical thickness and too much rain and drizzle. A sensitivity experiment showed that reducing the ice fall speeds improves aspects of the modeled cloud properties by increasing the frequency of occurrence of high clouds with large scattering ratios and optically thick low clouds. ACCESS1.3 has a reasonable representation of cloud. However, the underestimate of ice water content and particles sizes in high clouds and the too frequent occurrence of drizzle may impact the modeled cloud feedbacks and regional precipitation associated with current and perturbed climates.

Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP–ICE

AbstractSingle column model simulations using the UK Met Office Unified Model, as used in the Australian Community Climate Earth System Simulator, are presented for the Tropical Warm Pool–International Cloud Experiment (TWP–ICE) field study. Two formulations for the representation of clouds are compared with the extensive observations taken during the campaign, giving insight into the ability of the model to simulate tropical cloud systems. During the active monsoon phase the modelled cloud cover has a stronger dependence on relative humidity than the observations. Observed ice cloud properties during the suppressed monsoon period show that the ice water content is significantly underestimated in the simulations. The profiles of modelled ice fall speeds are faster than those observed in the levels above 12 km, implying that the observations have smaller sized particles in larger concentrations than the models. Both simulations show similar errors in the diurnal cycle of relative humidity during the active monsoon phase, suggesting that the error is less sensitive to the choice of cloud scheme and rather is driven by the convection scheme. However, during the times of suppressed convection the relative humidity error is different between the simulations, with congestus convection drying the environment too much, particularly in the prognostic cloud‐scheme simulation. This result shows that the choice of cloud scheme and the way that the cloud and convection schemes interact plays a role in the temperature and moisture errors during the suppressed monsoon phase, which will impact the three‐dimensional model simulations of tropical variability. Copyright © 2011 Royal Meteorological Society