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The third version of the Regional Atmosphere and Land (RAL3) science configuration is documented. Developed through international partnership, RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator when applied across timescales with kilometre and sub-km scale model grids. The RAL3 configuration represents a major advance compared to previous versions by delivering a common science definition suitable for application to tropical and mid-latitude regions. Developments within RAL3 include the introduction of a double-moment microphysics scheme and a bi-modal cloud scheme, replacing use of a single-moment scheme and different cloud schemes for mid-latitudes and tropics in previous versions. Updates have been implemented to the boundary layer scheme and a consolidation of land model settings to be more consistent with Global Atmosphere and Land (GAL) science configurations. Physics developments aimed to address priorities for model performance improvement identified by users. This paper documents the RAL3 science configuration, including a series of iterative revisions delivered since its first release, and their characteristics. Evidence is provided from the variety of assessments of RAL3, relative to the previous version (RAL2). Collaborative development and evaluation across organisations has enabled evaluation across a range of domains, grid-spacing and timescales. The analysis indicates more realistic precipitation distributions; improved representation of clouds and of visibility; a continued trend to more realistic representation of convection; and reduced near-surface wind speeds, but a persistent cold temperature bias. Overall the convective-scale verification scores and climatological model distributions relative to observations improve for the majority of variables. Ensemble results show improvements to the spread-error relationship. User feedback from subjective assessment activities has also been positive. Differences between RAL3 revisions and RAL2 are further illustrated through process-based analysis of a convective system over the UK. The latest RAL3 configuration (RAL3.3) is therefore recommended for research, operational numerical weather prediction and climate production at km and sub-km scales. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is changing the Earth system processes that control the characteristics of natural hazards both globally and across Australia. Model projections of hazards under future climate change are necessary for effective adaptation. This paper presents BARPA-R (the Bureau of Meteorology Atmospheric Regional Projections for Australia), a regional climate model designed to downscale climate projections over the Australasian region with the purpose of investigating future hazards. BARPA-R, a limited-area model, has a 17 km horizontal grid spacing and makes use of the Met Office Unified Model (MetUM) atmospheric model and the Joint UK Land Environment Simulator (JULES) land surface model. To establish credibility and in compliance with the Coordinated Regional Climate Downscaling Experiment (CORDEX) experiment design, the BARPA-R framework has been used to downscale ERA5 reanalysis. Here, an assessment of this evaluation experiment is provided. Performance-based evaluation results are benchmarked against ERA5, with comparable performance between the free-running BARPA-R simulations and observationally constrained reanalysis interpreted as a good result. First, an examination of BARPA-R's representation of Australia's surface air temperature, precipitation, and 10 m winds finds good performance overall, with biases including a 1 ∘ C cold bias in daily maximum temperatures, reduced diurnal temperature range, and wet biases up to 25 mm per month in inland Australia. Recent trends in daily maximum temperatures are consistent with observational products, while trends in minimum temperatures show overestimated warming and trends in precipitation show underestimated wetting in northern Australia. Precipitation and temperature teleconnections are effectively represented in BARPA-R when present in the driving boundary conditions, while 10 m winds are improved over ERA5 in six out of eight of the Australian regions considered. Secondly, the paper considers the representation of large-scale atmospheric circulation features and weather systems. While generally well represented, convection-related features such as tropical cyclones, the South Pacific Convergence Zone (SPCZ), the Northwest Cloudband, and the monsoon westerlies show more divergence from observations and internal interannual variability than mid-latitude phenomena such as the westerly jets and extratropical cyclones. Having simulated a realistic Australasian climate, the BARPA-R framework will be used to downscale two climate change scenarios from seven CMIP6 global climate models (GCMs). [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is changing the earth system processes that control the characteristics of natural hazards both globally and across Australia. Model projections of hazards under future climate change are necessary for effective adaptation. This paper presents BARPA-R (the Bureau of Meteorology Atmospheric Regional Projections for Australia), a regional climate model designed to downscale climate projections over the Australasian region with the purpose to investigate future hazards. BARPA-R, a limited area model, has a 17 km horizontal grid-spacing and makes use of the Met Office Unified Model (MetUM) atmospheric model and the Joint UK Land Environment Simulator (JULES) land surface model. To establish credibility and in compliance with the Coordinated Regional Climate Downscaling Experiment (CORDEX) experiment design, the BARPA-R framework has been used to downscale ERA-5 reanalysis. Here, an assessment of this evaluation experiment is provided. First, an examination of BARPA-R's representation of Australia's surface air temperature, rainfall and 10-m winds finds good performance overall, with biases including a 1K cold bias in daily maximum temperatures, reduced diurnal temperature range, and wet biases up to 25 mm/month in inland Australia. Recent trends in diurnal maximum temperatures are consistent with observational products, while trends in minimum temperatures show overestimated warming and trends in rainfall show underestimated wetting in northern Australia. Rainfall and temperature teleconnections are effectively represented in BARPA-R when present in the driving boundary conditions, while 10-metre winds are improved over ERA5 in six out of eight of the Australian regions considered. The second section of the paper considers the representation of large-scale atmospheric circulation features and weather systems. While generally well represented, convection-related features such as tropical cyclones, the SPCZ, Northwest Cloud-Bands and the monsoon westerlies show more divergence from observations and internal interannual variability than mid-latitude phenomena such as the westerly jets and extra-tropical cyclones. Having simulated a realistic Australasian climate, the BARPA-R framework will be used to downscale two climate change scenarios from seven CMIP6 GCMs. [ABSTRACT FROM AUTHOR]

In atmospheric models with kilometer‐scale grids the resolution approaches the scale of convection. As a consequence the most energetic eddies in the atmosphere are partially resolved and partially unresolved. The modeling challenge to represent convection partially explicitly and partially as a subgrid process is called the convective gray zone problem. The gray zone issue has previously been discussed in the context of regional models, but the evolution in regional models is constrained by the lateral boundary conditions. Here we explore the convective gray zone starting from a defined global configuration of the Met Office Unified Model using initialized forecasts and comparing different model formulations to observations. The focus is on convection and turbulence, but some aspects of the model dynamics are also considered. The global model is run at nominal 5 km resolution and thus contributions from both resolved and subgrid turbulent and convective fluxes are non‐negligible. The main conclusion is that in the present assessment, the configurations which include scale‐aware turbulence and a carefully reduced and simplified mass‐flux convection scheme outperform both the configuration with fully parameterized convection as well as a configuration in which the subgrid convection parameterization is switched off completely. The results are more conclusive with regard to convective organization and tropical variability than extratropical predictability. The present study thus endorses the strategy to further develop scale‐aware physics schemes and to pursue an operational implementation of the global 5 km‐resolution model to be used alongside other ensemble forecasts to allow researchers and forecasters to further assess these simulations. Plain Language Summary: An in‐depth exploration of kilometer‐scale global atmospheric modeling in the context of the current Met Office modeling system, the Met Office Unified Model, is presented. All simulations were performed using a global atmosphere model at nominal 5 km resolution. The model resolution thus resides in the so‐called convective gray zone where the grid length approaches the scale of turbulence and convection, and contributions from both resolved and subgrid convective and turbulent fluxes are non‐negligible. A case study approach has been taken in which various testbed cases are defined and model forecasts are evaluated against observations. The focus is on the representation of convection, turbulence and dynamics, the key aspects of the model formulation in the convective gray zone. The main finding is that in the present assessment the configurations which include a scale‐aware representation of turbulence and a carefully reduced and simplified convection scheme outperform both the reference model with fully parameterized convection as well as a configuration in which the subgrid convection parameterization is switched off completely. An outlook on further work toward the development of an adequate kilometer‐scale resolution global coupled modeling system for use across weather and climate time scales is given. Key Points: The representation of turbulence and convection in the convective gray zone is investigated at global 5 km resolutionIn the examined context a reduced mass‐flux convection scheme is beneficial in 5 km‐resolution global model forecastsThe assessment is more conclusive with regard to convective organization and tropical variability than extratropical predictability [ABSTRACT FROM AUTHOR]

In this paper we define RAL2 – the second Regional Atmosphere and Land (RAL) science configuration for regional modelling. RAL2 uses the Unified Model (UM) as the basis for the atmosphere and the Joint UK Land Environment Simulator (JULES) for the land. RAL2 defines the science configuration of the dynamics and physics schemes of the atmosphere and land and builds on the baseline of RAL1. There are two RAL2 sub-releases, one for mid-latitudes (RAL2-M) and one for tropical regions (RAL2-T). We document the differences between them and where appropriate discuss how RAL2 relates to RAL1 and the corresponding configuration of the global forecasting model. Our results show an increase in medium and low cloud amounts in the mid-latitudes leading to improved cloud forecasts. The increase in cloud amount leads to a reduced diurnal cycle of screen temperature. There is also a reduction in the frequency of heavier precipitation rates. RAL2 is expected to be the last RAL science configuration with two sub-releases as research effort is focused on producing a single defined configuration of the model that performs effectively in all regions of the world. [ABSTRACT FROM AUTHOR]

In this paper we define RAL2 - the second "Regional Atmosphere and Land" (RAL) science configuration for regional modelling. RAL2 uses the Unified Model (UM) as the basis for the atmosphere and the Joint UK Land Environment Simulator (JULES) for the land. RAL2 defines the science configuration of the dynamics and physics schemes of the atmosphere and land and builds on the baseline of RAL1. There are two RAL2 sub-releases, one for mid-latitudes (RAL2-M) and one for tropical regions (RAL2-T). We document the differences between them and where appropriate discuss how RAL2 relates to RAL1 and the corresponding configuration of the global forecasting model. Our results show an increase in medium and low cloud amounts in the mid-latitudes leading to improved cloud forecasts. The increase in cloud amount leads to a reduced diurnal cycle of screen temperature. There is also a reduction in the frequency of heavier precipitation rates. RAL2 is expected to be the last RAL science configuration with two sub-releases as research effort is focused on producing a single defined configuration of the model that performs effectively in all regions of the world. [ABSTRACT FROM AUTHOR]

A warm rain parameterization has been developed by solving the stochastic collection equation with the use of turbulent collision kernels. The resulting parameterizations for the processes of autoconversion, accretion, and self-collection are functions of the turbulent intensity of the flow and are applicable to turbulent cloud conditions ranging in dissipation rates of turbulent kinetic energy from 100 to 1500 [cm.sup.2] [s.sup-3]. Turbulence has a significant effect on the acceleration of the drop size distribution and can reduce the time to the formation of raindrops. When the stochastic collection equation is solved with the gravitational collision kernel for an initial distribution with a liquid water content of 1 g [m.sup.-3] and 240 drops [cm.sup.-3] with a mean volume radius of 10 [micro]m, the amount of mass that is transferred to drop sizes greater than 40 [micro]m in radius after 20 min is 0.9% of the total mass. When the stochastic collection equation is solved with a turbulent collision kernel for collector drops in the range of 10-30 [micro]m with a dissipation rate of turbulent kinetic energy equal to 100 [cm.sup.2][s.sup.-3], this percentage increases to 21.4. Increasing the dissipation rate of turbulent kinetic energy to 500, 1000, and 1500 [cm.sup.2][s.sup.-3] further increases the percentage of mass transferred to radii greater than 40 [micro]m after 20 min to 41%, 52%, and 58%, respectively, showing a substantial acceleration of the drop size distribution when a turbulent collision kernel that includes both turbulent and gravitational forcing replaces the purely gravitational kernel. The warm rain microphysics parameterization has been developed from direct numerical simulation (DNS) results that are characterized by Reynolds numbers that are orders of magnitude smaller than those of atmospheric turbulence. The uncertainty involved with the extrapolation of the results to high Reynolds numbers, the use of gravitational collision efficiencies, and the range of the droplets for which the effect of turbulence has been included should all be considered when interpreting results based on these new microphysics parameterizations.

Collision statistics of cloud droplets in turbulent flow have been calculated for 12 droplet size combinations in four flow fields with levels of the eddy dissipation rate of turbulent kinetic energy ranging from 95 to 1535 [cm.sup.2] [s.sup.-3]. The flow fields were generated by using a direct numerical simulation technique and large numbers of droplets were explicitly tracked through the flow field for each experiment. The effect of turbulence on the collision kernel increases with both increasing radius ratio and eddy dissipation rate. These increases range from fairly modest values to almost 10 times the gravitational geometric collision Kernel. The two physical processes responsible for these increases are the radial relative velocities and the preferential concentration or clustering of the droplets. The radial relative velocities increased by up to 3 times the corresponding gravitational value and the greatest increase in the clustering, as measured by the radial distribution function, is 4.5 times the value for a random distribution as for the gravitational case. Parameterizations have been developed for the effect of turbulence on the radial relative velocities and the clustering of the droplets. These models reduce the average root-mean-squared errors in the existing velocity parameterization of Saffman and Turner and Wang et al. by 32% and the clustering parameterization of Zhou et al. by up to 58%.

Prediction of the effect of air turbulence on statistics relevant to a collision-coalescence process represents a key challenge in the modeling of cloud microphysics. In this paper, collision-related statistics for gravity-driven motion of droplets are considered and various probability distributions associated with geometric configuration and relative motion of colliding droplets are theoretically derived. The theoretical results agree well with numerical results obtained from direct numerical simulations (DNSs). In the absence of air turbulence, the probability distributions, calculated at the beginning of the time steps used for collision detection, nontrivially depend on the time step size. Next, a novel theory is developed to quantify the effect of turbulence on the angle-of-approach [theta] and radial relative velocity [absolute value of [w.sub.r,c]] for colliding pairs. A logical decomposition is used to construct extended collision volumes for a specific level of radial motion caused by air turbulence. It is shown that the inward relative motion due to turbulent fluctuations dominates the effect of turbulence in modifying the probability distributions of [theta] and [absolute value of [w.sub.r,c]]. Two key dimensionless parameters are identified in the theory: one measures the effect of finite time step size in numerical collision detection and the second measures the relative magnitude of air turbulence. The theory is compared with 11 numerical experiments from DNS. It is shown that the theory captures the essential physics of the effect of air turbulence and provides a quantitatively good representation of the statistics for 0. For most numerical experiments, the theory predicts ([theta]) to within 5%. The probability distribution of [absolute value of [w.sub.r,c]] is more sensitive to the influence of air turbulence and shows larger intermittency at large [absolute value of [w.sub.r,c]] than what is assumed in the theory. The theoretical framework developed here may be of value to other problems involving gravitational settling and weak turbulence, such as parameterization of collision kernel and hydrodynamic interactions of droplets in warm rain processes.

Direct numerical simulations of an evolving turbulent flow field have been performed to explore how turbulence affects the motion and collisions of cloud droplets. Large numbers of droplets are tracked through the flow field and their positions, velocities, and collision rates have been found to depend on the eddy dissipation rate of turbulent kinetic energy. The radial distribution function, which is a measure of the preferential concentration of droplets, increases with eddy dissipation rate. When droplets are clustered there is an increased probability of finding two droplets closely separated; thus. there is an increase in the collision kernel. For the flow fields explored in this study, the clustering effect accounts for an increase in the collision kernel of 8%-42%, as compared to the gravitational collision kernel. The spherical collision kernel is also a function of the radial relative velocities among droplets and these velocities increase from 1.008 to 1.488 times the corresponding gravitational value. For an eddy dissipation rate of about 100 [cm.sup.2] [s.sup.-3], the turbulent collision kernel is 1.06 times the magnitude of the gravitational value, while for an eddy dissipation rate of 1500 [cm.sup.2][s.sup.-3], this increases to 2.08 times. Therefore, these results demonstrate that turbulence could play an important role in the broadening and evolution of the droplet size distribution and the onset of precipitation.

Regional reanalyses provide a dynamically consistent recreation of past weather observations at scales useful for local-scale environmental applications. The development of convection-permitting models (CPMs) in numerical weather prediction has facilitated the creation of kilometre-scale (1–4 km) regional reanalysis and climate projections. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) also aims to realize the benefits of these high-resolution models over Australian sub-regions for applications such as fire danger research by nesting them in BARRA's 12 km regional reanalysis (BARRA-R). Four midlatitude sub-regions are centred on Perth in Western Australia, Adelaide in South Australia, Sydney in New South Wales (NSW), and Tasmania. The resulting 29-year 1.5 km downscaled reanalyses (BARRA-C) are assessed for their added skill over BARRA-R and global reanalyses for near-surface parameters (temperature, wind, and precipitation) at observation locations and against independent 5 km gridded analyses. BARRA-C demonstrates better agreement with point observations for temperature and wind, particularly in topographically complex regions and coastal regions. BARRA-C also improves upon BARRA-R in terms of the intensity and timing of precipitation during the thunderstorm seasons in NSW and spatial patterns of sub-daily rain fields during storm events. BARRA-C reflects known issues of CPMs: overestimation of heavy rain rates and rain cells, as well as underestimation of light rain occurrence. As a hindcast-only system, BARRA-C largely inherits the domain-averaged bias pattern from BARRA-R but does produce different climatological extremes for temperature and precipitation. An added-value analysis of temperature and precipitation extremes shows that BARRA-C provides additional skill over BARRA-R when compared to gridded observations. The spatial patterns of BARRA-C warm temperature extremes and wet precipitation extremes are more highly correlated with observations. BARRA-C adds value in the representation of the spatial pattern of cold extremes over coastal regions but remains biased in terms of magnitude. [ABSTRACT FROM AUTHOR]

The development of convection-permitting models (CPMs) in numerical weather prediction has facilitated the creation of km-scale (1-4 km) regional reanalysis and climate projections. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) also aims to realise the benefits of these high-resolution models over Australian sub-regions for applications such as fire danger research, by nesting them in BARRA's 12 km regional reanalysis (BARRA-R). Four mid-latitude sub-regions are centred on Perth in Western Australia, Adelaide in South Australia, Sydney in New South Wales (NSW), and Tasmania. The resulting 29-year 1.5 km downscaled reanalyses (BARRA-C) are assessed for their added skill over BARRA-R and global reanalyses for near-surface parameters (temperature, wind and precipitation) at observation locations and against independent 5 km gridded analyses. BARRA-C demonstrates better agreement with point observations for temperature and wind, particularly in topographically complex regions and coastal regions. BARRA-C also improves upon BARRA-R in terms of intensity and timing of precipitation during the thunderstorm seasons in NSW, and spatial patterns of sub-daily rain fields during storm events. However, as a hindcast-only system, BARRA-C largely inherits the domain-averaged biases and temporal variations of biases from BARRA-R. Further, BARRA-C reflects known issues of CPMs: overestimation of heavy rain rates and rain cells, and underestimation of light rain occurrence. [ABSTRACT FROM AUTHOR]

In this paper we define the first Regional Atmosphere and Land (RAL) science configuration for kilometre-scale modelling using the Unified Model (UM) as the basis for the atmosphere and the Joint UK Land Environment Simulator (JULES) for the land. RAL1 defines the science configuration of the dynamics and physics schemes of the atmosphere and land. This configuration will provide a model baseline for any future weather or climate model developments to be described against, and it is the intention that from this point forward significant changes to the system will be documented in the literature. This reproduces the process used for global configurations of the UM, which was first documented as a science configuration in 2011. While it is our goal to have a single defined configuration of the model that performs effectively in all regions, this has not yet been possible. Currently we define two sub-releases, one for mid-latitudes (RAL1-M) and one for tropical regions (RAL1-T). The differences between RAL1-M and RAL1-T are documented, and where appropriate we define how the model configuration relates to the corresponding configuration of the global forecasting model. [ABSTRACT FROM AUTHOR]

In this paper we define the first "Regional Atmosphere and Land" (RAL) science configuration for kilometre scale modelling using the UM and JULES. "RAL1" defines the science configuration of the dynamics and physics schemes of the atmosphere and land. This configuration will provide a model baseline for any future weather or climate model developments to be described against and it is the intention that from this point forward significant changes to the system will be documented in literature. This is reproducing the process used for global configurations of the UM which was first documented as a science configuration in 2011. While it is our goal to have a single defined configuration of the model that performs effectively in all regions, this has not yet been possible. Currently we define two sub-releases, one for mid-latitudes (RAL1-M) and one for tropical regions (RAL1-T). The differences between RAL1-M and RAL1-T are documented and where appropriate, we define how the model configuration relates to the corresponding configuration of the global forecasting model. [ABSTRACT FROM AUTHOR]

The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) is the first atmospheric regional reanalysis over a large region covering Australia, New Zealand, and Southeast Asia. The production of the reanalysis with approximately 12 km horizontal resolution – BARRA-R – is well underway with completion expected in 2019. This paper describes the numerical weather forecast model, the data assimilation methods, the forcing and observational data used to produce BARRA-R, and analyses results from the 2003–2016 reanalysis. BARRA-R provides a realistic depiction of the meteorology at and near the surface over land as diagnosed by temperature, wind speed, surface pressure, and precipitation. Comparing against the global reanalyses ERA-Interim and MERRA-2, BARRA-R scores lower root mean square errors when evaluated against (point-scale) 2 m temperature, 10 m wind speed, and surface pressure observations. It also shows reduced biases in daily 2 m temperature maximum and minimum at 5 km resolution and a higher frequency of very heavy precipitation days at 5 and 25 km resolution when compared to gridded satellite and gauge analyses. Some issues with BARRA-R are also identified: biases in 10 m wind, lower precipitation than observed over the tropical oceans, and higher precipitation over regions with higher elevations in south Asia and New Zealand. Some of these issues could be improved through dynamical downscaling of BARRA-R fields using convective-scale (<2 km) models. [ABSTRACT FROM AUTHOR]

A cloud feedback diagnostic package is implemented in the Australian Community Climate and Earth‐System Simulator General Circulation Model, based on the methodology of "cloud radiative kernels." Using separate increased sea surface temperature and CO2 experiments, both the "rapid response" cloud contribution to forcing and temperature‐mediated cloud feedbacks are analyzed. Under increased temperature and CO2 changes, temperature‐mediated cloud radiative feedback dominates over the rapid response in the final radiative response. Cloud feedback is positive in both long and short wave, with short wave dominating global values. Contributing most to this are low to mid‐level clouds, of medium‐to‐high optical thickness. As a means of illustration of the methodology, a number of key parameters related to clouds, precipitation, and convection that are typically used in "tuning" in the model are modified. These changes result in substantial impacts on the model's current climate, but only modest changes to rapid response and feedbacks occur globally, regionally, and as a function of cloud optical thickness and height. This limited set of experiments shows that cloud adjustments and feedbacks in this model are robust under these changes, lending confidence that both model climate change projections and the conclusions of attribution studies are not overly sensitive to such parameterization tuning. Of course, a considerably larger set of experiments would be needed to demonstrate that feedbacks and rapid response are robust under the wider set of tuning adjustments commonly undertaken. Plain Language Summary: A method using a combination of sea surface temperature and CO2 forced experiments and "cloud radiative kernels" is used to investigate cloud feedbacks and "rapid responses" in the Australian Community Climate and Earth‐System Simulator climate model. The methodology is demonstrated using a small set of changes to cloud parameters that are modified in a modest way as typically "tuned" in the model. These changes substantially alter the model climate but produce only small changes to cloud rapid response and feedbacks. Cloud feedback is positive in both long and short wave, with short wave responses dominating global values, predominantly from low level to midlevel clouds. Rapid responses are weaker in both long and short wave. Key Points: The approach uses "cloud radiative kernels" to investigate cloud feedbacks and "rapid responses" in the ACCESS climate modelA small set of cloud parameters are modified in a modest way as typically "tuned" in the modelThese changes significantly alter the model climate but produce only small changes to cloud rapid response and feedbacks [ABSTRACT FROM AUTHOR]

The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) is the first atmospheric regional reanalysis over a large region covering Australia, New Zealand and southeast Asia. The production of the reanalysis with approximately 12 km lateral resolution - BARRA-R - is well underway with completion expected in 2019. This paper describes the numerical weather forecast model, the data assimilation methods, and the forcing and observational data used to produce BARRA-R, and analyses results from the 2007-2016 reanalysis. BARRA-R provides a realistic depiction of the meteorology at and near the surface over land as diagnosed by temperature, wind speed and precipitation. It shows closer agreement with point-scale observations and gridded analysis of observations, than leading global reanalyses. In particular, BARRA-R improves upon ERA-Interim global reanalysis in several areas at point-scale to 25 km resolution. BARRA-R shows reduced negative biases in (point-scale) 10 m wind speed during strong wind periods, reduced biases in (5 km gridded) daily temperature maximum and minimum, and higher frequency of very heavy precipitation days at 5 km and 25 km resolution. Few issues with BARRA-R are also identified; some of which are common in reanalyses, such as biases in 10 m wind, and others that are more specific to BARRA such as grid point storms. Some of these issues could be improved through dynamical downscaling of BARRA-R fields using convective-scale (< 2 km) models. [ABSTRACT FROM AUTHOR]

Precipitation and cloud properties from the Australian Community Climate and Earth System Simulator ( ACCESS1.3) atmospheric model are evaluated over the Maritime Continent during the monsoon season using satellite observations. The model rainfall errors in December-February are characterized by a wet bias east of 120°E and a dry bias west of that longitude. A closer look at the complex land-sea composition of the Maritime Continent reveals that ACCESS1.3 overestimates rainfall over the islands and underestimates it in the surrounding waters. These rainfall biases are associated with a distinct low-level convergence bias over land, a divergence bias over ocean, and a high-level cloud fraction overestimate over land and ocean. The complementary information offered by CloudSat and CALIPSO evaluations further shows that the model overestimates high- and low-level cloudiness and light rain and drizzle but underestimates the occurrence of mid-level clouds. Sensitivity tests are carried out to study the model response to physics parametrizations to understand these model errors. In particular, modifications to the existing parametrization such as changes to the convection scheme, to the rainfall characteristics or to the circulation, appear to qualitatively help reduce model errors. These results show that rainfall and high-level cloud fraction can be improved, but the model still suffers from a lack of occurrence of hydrometeors in the mid-levels in all sensitivity tests. Increasing cloudiness and moisture in the low- and mid-levels may be crucial to generating deeper convection and higher ice water content in the model. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Simulations of tropical convection from an operational numerical weather prediction model are evaluated with the focus on the model's ability to simulate the observed high ice water contents associated with the outflow of deep convection and to investigate the modelled processes that control the phase composition of tropical convective clouds. The 1 km horizontal grid length model that uses a singlemoment microphysics scheme simulates the intensification and decay of convective strength across the mesoscale convective system. However, deep convection is produced too early, the OLR (outgoing longwave radiation) is underestimated and the areas with reflectivities >30 dBZ are overestimated due to too much rain above the freezing level, stronger updraughts and larger particle sizes in the model. The inclusion of a heterogeneous rain-freezing parameterisation and the use of different ice size distributions show better agreement with the observed reflectivity distributions; however, this simulation still produces a broader profile with many high-reflectivity outliers demonstrating the greater occurrence of convective cells in the simulations. Examining the phase composition shows that the amount of liquid and ice in the modelled convective updraughts is controlled by the following: the size of the ice particles, with larger particles growing more efficiently through riming and producing larger IWC (ice water content); the efficiency of the warm rain process, with greater cloud water contents being available to support larger ice growth rates; and exclusion or limitation of graupel growth, with more mass contained in slower falling snow particles resulting in an increase of in-cloud residence times and more efficient removal of LWC (liquid water content). In this simulated case using a 1 km grid length model, horizontal mass divergence in the mixed-phase regions of convective updraughts is most sensitive to the turbulence formulation. Greater mixing of environmental air into cloudy updraughts in the region of -30 to 0 °C produces more mass divergence indicative of greater entrainment, which generates a larger stratiform rain area. Above these levels in the purely ice region of the simulated updraughts, the convective updraught buoyancy is controlled by the ice particle sizes, demonstrating the importance of the microphysical processes on the convective dynamics in this simulated case study using a single-moment microphysics scheme. The single-moment microphysics scheme in the model is unable to simulate the observed reduction of mean mass-weighted ice diameter as the ice water content increases. The inability of the model to represent the observed variability of the ice size distribution would be improved with the use of a double-moment microphysics scheme. [ABSTRACT FROM AUTHOR]

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. Cooler NH summer temperatures in canopy covered areas are attributed to two factors. Firstly CABLE accounts for aerodynamic and radiative interactions between the canopy and the ground below; this placement of canopy above the ground eliminates the need for a separate bare ground tile in canopy covered areas. Secondly, CABLE produces larger evapotranspiration fluxes and 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 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 snow pack in autumn and accelerates snow melting in spring. [ABSTRACT FROM AUTHOR]

Radiation field and cloud properties over the Southern Ocean area generated by the Australian Community Climate and Earth System Simulator (ACCESS) are evaluated using multiple-satellite products from the Fast Longwave And Shortwave radiative Fluxes (FLASHFlux) project and NASA/GEWEX surface radiation budget (SRB) data. The cloud properties are also evaluated using the observational simulator package COSP, a synthetic brightness temperature model (SBTM) and cloud liquid-water path data (UWisc) from the University of Wisconsin satellite retrievals. All of these evaluations are focused on the Southern Ocean area in an effort to understand the reasons behind the short-wave radiation biases at the surface. It is found that the model overestimates the high-level cloud fraction and frequency of occurrence of small ice-water content and underestimates the middle and low-level cloud fraction and water content. In order to improve the modelled radiation fields over the Southern Ocean area, two main modifications have been made to the physical schemes in the ACCESS model. Firstly the autoconversion rate at which the cloud water is converted into rain and the accretion rate in the warm rain scheme have been modified, which increases the cloud liquid-water content in warm cloud layers. Secondly, the scheme which determines the fraction of supercooled liquid water in mixed-phase clouds in the parametrization of cloud optical properties has been changed to use one derived from CALIPSO data which provides larger liquid cloud fractions and thus higher optical depths than the default scheme. Sensitivity tests of these two schemes in ACCESS climate runs have shown that applying either can lead to a reduction of the solar radiation reaching the surface and reduce the short-wave radiation biases. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

CGILS-the CFMIP-GASS Intercomparison of Large Eddy Models (LESs) and single column models (SCMs)-investigates the mechanisms of cloud feedback in SCMs and LESs under idealized climate change perturbation. This paper describes the CGILS results from 15 SCMs and 8 LES models. Three cloud regimes over the subtropical oceans are studied: shallow cumulus, cumulus under stratocumulus, and well-mixed coastal stratus/stratocumulus. In the stratocumulus and coastal stratus regimes, SCMs without activated shallow convection generally simulated negative cloud feedbacks, while models with active shallow convection generally simulated positive cloud feedbacks. In the shallow cumulus alone regime, this relationship is less clear, likely due to the changes in cloud depth, lateral mixing, and precipitation or a combination of them. The majority of LES models simulated negative cloud feedback in the well-mixed coastal stratus/stratocumulus regime, and positive feedback in the shallow cumulus and stratocumulus regime. A general framework is provided to interpret SCM results: in a warmer climate, the moistening rate of the cloudy layer associated with the surface-based turbulence parameterization is enhanced; together with weaker large-scale subsidence, it causes negative cloud feedback. In contrast, in the warmer climate, the drying rate associated with the shallow convection scheme is enhanced. This causes positive cloud feedback. These mechanisms are summarized as the 'NESTS' negative cloud feedback and the 'SCOPE' positive cloud feedback (Negative feedback from Surface Turbulence under weaker Subsidence-Shallow Convection PositivE feedback) with the net cloud feedback depending on how the two opposing effects counteract each other. The LES results are consistent with these interpretations. [ABSTRACT FROM AUTHOR]

A high-resolution tropical cyclone model with explicit cloud microphysics has been used to investigate the dynamics and energetics of tropical cyclone rainbands. Analysis of the vorticity interactions that occur within the simulated rainbands demonstrates that couplets of cyclonic–anticyclonic mesovortices can be produced in outer bands. The primary source of this vorticity is the upward tilting of system-generated horizontal vorticity by diabatic heating gradients. The vertical heating gradient in the stratiform cloud also creates a potential vorticity (PV) dipole that accelerates the tangential flow and develops a midlevel jet. The strength of the jet is enhanced by the vortex pair that is oriented radially across the rainband. The Fourier decomposition of the absolute vorticity field shows two counterpropagating vortex Rossby waves associated with the rainband. The wave located on the inner side of the band transports energy toward the vortex center. The outer wave is made up of high wavenumbers and uses the vorticity gradients generated by the rainband. The results support the hypothesis that the heating profile in the stratiform regions of rainbands generates cyclonic PV across the freezing level, which develops a midlevel jet. This mechanism creates a vorticity gradient that enables the propagation of vortex Rossby waves that could allow the rainbands to interact with the mean flow and potentially influence the evolution of the storm by contributing to the symmetric component of vorticity and the development of secondary eyewalls. [ABSTRACT FROM AUTHOR]

Prediction of the effect of air turbulence on statistics relevant to a collision–coalescence process represents a key challenge in the modeling of cloud microphysics. In this paper, collision-related statistics for gravity-driven motion of droplets are considered and various probability distributions associated with geometric configuration and relative motion of colliding droplets are theoretically derived. The theoretical results agree well with numerical results obtained from direct numerical simulations (DNSs). In the absence of air turbulence, the probability distributions, calculated at the beginning of the time steps used for collision detection, nontrivially depend on the time step size. Next, a novel theory is developed to quantify the effect of turbulence on the angle-of-approach θ and radial relative velocity |wr,c| for colliding pairs. A logical decomposition is used to construct extended collision volumes for a specific level of radial motion caused by air turbulence. It is shown that the inward relative motion due to turbulent fluctuations dominates the effect of turbulence in modifying the probability distributions of θ and |wr,c|. Two key dimensionless parameters are identified in the theory: one measures the effect of finite time step size in numerical collision detection and the second measures the relative magnitude of air turbulence. The theory is compared with 11 numerical experiments from DNS. It is shown that the theory captures the essential physics of the effect of air turbulence and provides a quantitatively good representation of the statistics for θ. For most numerical experiments, the theory predicts 〈θ〉 to within 5%. The probability distribution of |wr,c| is more sensitive to the influence of air turbulence and shows larger intermittency at large |wr,c| than what is assumed in the theory. The theoretical framework developed here may be of value to other problems involving gravitational settling and weak turbulence, such as parameterization of collision kernel and hydrodynamic interactions of droplets in warm rain processes. [ABSTRACT FROM AUTHOR]

A high-resolution tropical cyclone model with explicit cloud microphysics has been used to investigate the dynamics and energetics of tropical cyclone rainbands. As a first step, the model rainbands have been qualitatively compared with observed rainband characteristics. The model-generated rainbands show many of the mesoscale and convective-scale features of observed tropical cyclone rainbands. Sensitivity studies of numerically simulated tropical cyclone convection to ice-phase microphysical parameters showed that the model was most sensitive to changes in the graupel fall speed parameters. Increasing the fall speeds saw graupel being confined to the convective regions and producing higher rain rates in the inner core of the storm. A greater region of stratiform precipitation was produced when the efficiency for the collection of snow and cloud ice by graupel was reduced and when the mean size of graupel was reduced. Both of these simulations resulted in a higher concentration of snow being transported into the stratiform region. Although the precipitation structure changed across the simulations, the surface rainfall rate and the fundamental dynamical variables showed little sensitivity to the parameter variations. [ABSTRACT FROM AUTHOR]