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Kalli Furtado and Paul Field

Abstract

High-resolution simulations of a Southern Ocean cyclone are compared to satellite-derived observations of liquid water path, cloud-top properties, and top-of-atmosphere radiative fluxes. The focus is on the cold-air-outflow region, where there are contributions to the hydrological budget from the microphysical growth of ice particles by riming and vapor deposition and transport by turbulent mixing. The sensitivity of the simulation to the parameterization of these processes is tested and the relative importance of ice-nucleation temperature is identified. It is shown that ice-phase microphysics is a key factor determining the phase composition of Southern Ocean clouds and physically reasonable parameterization changes are identified that affect the liquid water content of these clouds. The information gained from the sensitivity tests is applied to global model development, where it is shown that a modification to the riming parameterization improves climate mean-state biases in the Southern Ocean region.

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Paul R. Field and Kalli Furtado

Abstract

Aircraft are the dominant method for in situ sampling of cloud properties. Resource limitations mean that aircraft tend to follow a sampling strategy when there is more than one cloud from which to choose. This can result in biased cloud statistics that are used for parameterization development and model testing. In this study, order statistics are used to estimate the potential magnitude of this bias when a strategy based on choosing the larger cloud is employed. It is found for cloud properties following gamma distributions that a typical bias of a factor of 1.5 can result when the larger of two clouds is repeatedly chosen for sampling.

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Anthony J. Baran, Peter Hill, Kalli Furtado, Paul Field, and James Manners

Abstract

A new coupled cloud physics–radiation parameterization of the bulk optical properties of ice clouds is presented. The parameterization is consistent with assumptions in the cloud physics scheme regarding particle size distributions (PSDs) and mass–dimensional relationships. The parameterization is based on a weighted ice crystal habit mixture model, and its bulk optical properties are parameterized as simple functions of wavelength and ice water content (IWC). This approach directly couples IWC to the bulk optical properties, negating the need for diagnosed variables, such as the ice crystal effective dimension. The parameterization is implemented into the Met Office Unified Model Global Atmosphere 5.0 (GA5) configuration. The GA5 configuration is used to simulate the annual 20-yr shortwave (SW) and longwave (LW) fluxes at the top of the atmosphere (TOA), as well as the temperature structure of the atmosphere, under various microphysical assumptions. The coupled parameterization is directly compared against the current operational radiation parameterization, while maintaining the same cloud physics assumptions. In this experiment, the impacts of the two parameterizations on the SW and LW radiative effects at TOA are also investigated and compared against observations. The 20-yr simulations are compared against the latest observations of the atmospheric temperature and radiative fluxes at TOA. The comparisons demonstrate that the choice of PSD and the assumed ice crystal shape distribution are as important as each other. Moreover, the consistent radiation parameterization removes a long-standing tropical troposphere cold temperature bias but slightly warms the southern midlatitudes by about 0.5 K.

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Jian Li, Haoming Chen, Xinyao Rong, Jingzhi Su, Yufei Xin, Kalli Furtado, Sean Milton, and Nina Li

Abstract

A high-impact extreme precipitation event over the Yangtze River valley (YRV) in the midsummer of 2016 is simulated using the Climate System Model of Chinese Academy of Meteorological Sciences (CAMS-CSM). After validation of the model’s capability in reproducing the climatological features of precipitation over the YRV, the Transpose Atmospheric Model Intercomparison Project (T-AMIP)–type experiment, which runs the climate model in the weather forecast mode, is applied to investigate the performance of the climate model in simulating the spatial and temporal distribution of rainfall and the related synoptic circulation. Analyses of T-AMIP results indicate that the model realistically reproduces the heavy rainfall centers of accumulated precipitation amount along the YRV, indicating that the climate model has the ability to simulate the severity of the extreme event. However, the frequency–intensity structure shows similar biases as in the AMIP experiment, especially the underestimation of the maximum hourly intensity. The simulation of two typical heavy rainfall periods during the extreme event is further evaluated. The results illustrate that the model shows different performances during periods dominated by circulation systems of different spatial scales. The zonal propagation of heavy rainfall centers during the first two days, which is related to the eastward movement of the southwest vortex, is well reproduced. However, for another period with a smaller vortex, the model produces an artificial steady heavy rainfall center over the upwind slope of the mountains rather than the observed eastward movement of the precipitation centers.

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Puxi Li, Christopher Moseley, Andreas F. Prein, Haoming Chen, Jian Li, Kalli Furtado, and Tianjun Zhou

Abstract

Mesoscale convective systems (MCSs) play an important role in modulating the global water cycle and energy balance and frequently generate high-impact weather events. The majority of existing literature studying MCS activity over East Asia is based on specific case studies and more climatological investigations revealing the precipitation characteristics of MCSs over eastern China are keenly needed. In this study, we use an iterative rain cell tracking method to identify and track MCS precipitation during 2008–16 to investigate regional differences and seasonal variations of MCS precipitation characteristics. Our results show that the middle-to-lower reaches of the Yangtze River basin (YRB-ML) receive the largest amount and exhibit the most pronounced seasonal cycle of MCS precipitation in eastern China. MCS precipitation over YRB-ML can exceed 2.6 mm day−1 in June, contributing over 30.0% of April–July total rainfall. Particularly long-lived MCSs occur over the eastern periphery of the Tibetan Plateau (ETP), with 25% of MCSs over the ETP persisting for more than 18 h in spring. In addition, spring MCSs feature larger rainfall areas, longer durations, and faster propagation speeds. Summer MCSs have a higher precipitation intensity and a more pronounced diurnal cycle except for southeastern China, where MCSs have similar precipitation intensity in spring and summer. There is less MCS precipitation in autumn, but an MCS precipitation center over the ETP still persists. MCSs reach peak hourly rainfall intensities during the time of maximum growth (a few hours after genesis), reach their maximum size around 5 h after genesis, and start decaying thereafter.

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Kwinten Van Weverberg, Cyril J. Morcrette, Ian Boutle, Kalli Furtado, and Paul R. Field

Abstract

Cloud fraction parameterizations are beneficial to regional, convection-permitting numerical weather prediction. For its operational regional mid-latitude forecasts, the UK Met Office uses a diagnostic cloud fraction scheme which relies on a unimodal, symmetric subgrid saturation-departure distribution. This scheme has been shown before to underestimate cloud cover and hence an empirically-based bias correction is used operationally to improve performance. This first of a series of two papers proposes a new diagnostic cloud scheme as a more physically-based alternative to the operational bias correction. The new cloud scheme identifies entrainment zones associated with strong temperature inversions. For model grid boxes located in this entrainment zone, co-located moist and dry Gaussian modes are used to represent the subgrid conditions. The mean and width of the Gaussian modes, inferred from the turbulent characteristics, are then used to diagnose cloud water content and cloud fraction. It is shown that the new scheme diagnoses enhanced cloud cover for a given grid-box mean humidity, similar to the current operational approach. It does so, however, in a physically meaningful way. Using observed aircraft data and ground-based retrievals over the Southern Great Plains in the US, it is shown that the new scheme improves the relation between cloud fraction, relative humidity and liquid water content. An emergent property of the scheme is its ability to infer skewed and bimodal distributions from the large-scale state that qualitatively compare well against observations. A detailed evaluation and resolution sensitivity study will follow in part II.

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Anthony J. Baran, Peter Hill, David Walters, Steven C. Hardiman, Kalli Furtado, Paul R. Field, and James Manners

Abstract

The impact of two different coupled cirrus microphysics–radiation parameterizations on the zonally averaged temperature and humidity biases in the tropical tropopause layer (TTL) of a Met Office climate model configuration is assessed. One parameterization is based on a linear coupling between a model prognostic variable, the ice mass mixing ratio q i, and the integral optical properties. The second is based on the integral optical properties being parameterized as functions of q i and temperature, T c, where the mass coefficients (i.e., scattering and extinction) are parameterized as nonlinear functions of the ratio between q i and T c. The cirrus microphysics parameterization is based on a moment estimation parameterization of the particle size distribution (PSD), which relates the mass moment (i.e., second moment if mass is proportional to size raised to the power of 2) of the PSD to all other PSD moments through the magnitude of the second moment and T c. This same microphysics PSD parameterization is applied to calculate the integral optical properties used in both radiation parameterizations and, thus, ensures PSD and mass consistency between the cirrus microphysics and radiation schemes. In this paper, the temperature-non-dependent and temperature-dependent parameterizations are shown to increase and decrease the zonally averaged temperature biases in the TTL by about 1 K, respectively. The temperature-dependent radiation parameterization is further demonstrated to have a positive impact on the specific humidity biases in the TTL, as well as decreasing the shortwave and longwave biases in the cloudy radiative effect. The temperature-dependent radiation parameterization is shown to be more consistent with TTL and global radiation observations.

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Steven C. Hardiman, Ian A. Boutle, Andrew C. Bushell, Neal Butchart, Mike J. P. Cullen, Paul R. Field, Kalli Furtado, James C. Manners, Sean F. Milton, Cyril Morcrette, Fiona M. O’Connor, Ben J. Shipway, Chris Smith, David N. Walters, Martin R. Willett, Keith D. Williams, Nigel Wood, N. Luke Abraham, James Keeble, Amanda C. Maycock, John Thuburn, and Matthew T. Woodhouse

Abstract

A warm bias in tropical tropopause temperature is found in the Met Office Unified Model (MetUM), in common with most models from phase 5 of CMIP (CMIP5). Key dynamical, microphysical, and radiative processes influencing the tropical tropopause temperature and lower-stratospheric water vapor concentrations in climate models are investigated using the MetUM. A series of sensitivity experiments are run to separate the effects of vertical advection, ice optical and microphysical properties, convection, cirrus clouds, and atmospheric composition on simulated tropopause temperature and lower-stratospheric water vapor concentrations in the tropics. The numerical accuracy of the vertical advection, determined in the MetUM by the choice of interpolation and conservation schemes used, is found to be particularly important. Microphysical and radiative processes are found to influence stratospheric water vapor both through modifying the tropical tropopause temperature and through modifying upper-tropospheric water vapor concentrations, allowing more water vapor to be advected into the stratosphere. The representation of any of the processes discussed can act to significantly reduce biases in tropical tropopause temperature and stratospheric water vapor in a physical way, thereby improving climate simulations.

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