Kalli Furtado

Large contribution of supercooled liquid clouds to the solar radiation budget of the Southern Ocean

The Southern Ocean is a critical region for global climate, yet large cloud and solar radiation biases over the Southern Ocean are a long-standing problem in climate models and are poorly understood, leading to biases in simulated sea surface temperatures. This study shows that supercooled liquid clouds are central to understanding and simulating the Southern Ocean environment. A combination of satellite observational data and detailed radiative transfer calculations is used to quantify the impact of cloud phase and cloud vertical structure on the reflected solar radiation in the Southern Hemisphere summer. It is found that clouds with supercooled liquid tops dominate the population of liquid clouds. The observations show that clouds with supercooled liquid tops contribute between 27% and 38% to the total reflected solar radiation between 40° and 70°S, and climate models are found to poorly simulate these clouds. The results quantify the importance of supercooled liquid clouds in the Southern Ocean environment and highlight the need to improve understanding of the physical processes that control these clouds in order to improve their simulation in numerical models. This is not only important for improving the simulation of present-day climate and climate variability, but also relevant for increasing confidence in climate feedback processes and future climate projections.

A Coupled Cloud Physics–Radiation Parameterization of the Bulk Optical Properties of Cirrus and Its Impact on the Met Office Unified Model Global Atmosphere 5.0 Configuration

AbstractA 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 compar...

Processes Controlling Tropical Tropopause Temperature and Stratospheric Water Vapor in Climate Models

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.

The Impact of Two Coupled Cirrus Microphysics–Radiation Parameterizations on the Temperature and Specific Humidity Biases in the Tropical Tropopause Layer in a Climate Model

AbstractThe 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 qi, and the integral optical properties. The second is based on the integral optical properties being parameterized as functions of qi and temperature, Tc, where the mass coefficients (i.e., scattering and extinction) are parameterized as nonlinear functions of the ratio between qi and Tc. 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 Tc. This same microphysics PSD parameterization ...

Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles

Significance Simulated clouds over the Southern Ocean reflect too little solar radiation compared with observations, which results in errors in simulated surface temperatures and in many other important features of the climate system. Our results show that the radiative properties of the most biased types of clouds in cyclonic systems are highly sensitive to the concentration of ice-nucleating particles. The uniquely low concentrations of ice-nucleating particles in this remote marine environment strongly inhibit precipitation and allow much brighter clouds to be sustained. Large biases in climate model simulations of cloud radiative properties over the Southern Ocean cause large errors in modeled sea surface temperatures, atmospheric circulation, and climate sensitivity. Here, we combine cloud-resolving model simulations with estimates of the concentration of ice-nucleating particles in this region to show that our simulated Southern Ocean clouds reflect far more radiation than predicted by global models, in agreement with satellite observations. Specifically, we show that the clouds that are most sensitive to the concentration of ice-nucleating particles are low-level mixed-phase clouds in the cold sectors of extratropical cyclones, which have previously been identified as a main contributor to the Southern Ocean radiation bias. The very low ice-nucleating particle concentrations that prevail over the Southern Ocean strongly suppress cloud droplet freezing, reduce precipitation, and enhance cloud reflectivity. The results help explain why a strong radiation bias occurs mainly in this remote region away from major sources of ice-nucleating particles. The results present a substantial challenge to climate models to be able to simulate realistic ice-nucleating particle concentrations and their effects under specific meteorological conditions.

The Role of Ice Microphysics Parametrizations in Determining the Prevalence of Supercooled Liquid Water in High-Resolution Simulations of a Southern Ocean Midlatitude Cyclone

AbstractHigh-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...

Chapter 8 – Subgrid Representation of Mixed-Phase Clouds in a General Circulation Model

Abstract The ubiquity and longevity of supercooled liquid-water and mixed-phase clouds in nature is at odds with the relative lack of these cloud types in numerical models of cloudy atmospheres when compared to observations. Amongst the mechanisms proposed for the longevity of mixed-phase conditions in nature is that small-scale turbulent motions compete with ice microphysical processes to maintain a statistical steady state in which a constant amount of liquid water exists for a long of period time. In this chapter we review previous work on understanding this mechanism and show how it can be developed into a parametrization of mixed-phase clouds. The parametrization is based on exact, steady-state solutions for the statistics of supersaturation fluctuations in a turbulent cloud layer from which expressions for the liquid-cloud properties can be derived. We review the implementation of the parametrization in a general circulation model and discuss implications of the parametrization for long-standing biases in the radiative properties of simulated mid- and high-latitude cloud-systems.

Critical Southern Ocean climate model biases traced to atmospheric model cloud errors

The Southern Ocean is a pivotal component of the global climate system yet it is poorly represented in climate models, with significant biases in upper-ocean temperatures, clouds and winds. Combining Atmospheric and Coupled Model Inter-comparison Project (AMIP5/CMIP5) simulations, with observations and equilibrium heat budget theory, we show that across the CMIP5 ensemble variations in sea surface temperature biases in the 40–60°S Southern Ocean are primarily caused by AMIP5 atmospheric model net surface flux bias variations, linked to cloud-related short-wave errors. Equilibration of the biases involves local coupled sea surface temperature bias feedbacks onto the surface heat flux components. In combination with wind feedbacks, these biases adversely modify upper-ocean thermal structure. Most AMIP5 atmospheric models that exhibit small net heat flux biases appear to achieve this through compensating errors. We demonstrate that targeted developments to cloud-related parameterisations provide a route to better represent the Southern Ocean in climate models and projections.The Southern Ocean is critically important for global climate yet poorly represented by climate models. Here the authors trace sea surface temperature biases in this region to cloud-related errors in atmospheric-model simulated surface heat fluxes and provide a pathway to improve the models.

Cloud Microphysical Factors Affecting Simulations of Deep Convection During the Presummer Rainy Season in Southern China

The sensitivity of subtropical deep convection to the parameterization of cloud microphysics is elucidated through high-resolution modeling of extreme presummer rainfall over southern China. An ensemble of physics configuration experiments is used to identify several drivers of model errors in comparison to radar observations from the South China Monsoon Rainfall Experiment (SCMREX) and remotely sensed estimates of cloud, precipitation, and radiation from satellites in the A-train constellation. The benefits of increasing the number of prognostic variables in the microphysics scheme is assessed, relative to the effects of the parameterization of cloud microphysical properties and cloud fraction diagnosis. By matching individual parameterizations between the microphysical configurations, it is shown that a small subset of the parameterization changes can reproduce most of the dependence of model performance on physics configuration. In particular, biases that are due to the low-level clouds and rain are strongly influenced by cloud fraction diagnosis and raindrop size distribution, whereas variations in the effects of high clouds are strongly influenced by differences in the parameterization of ice crystal sedimentation. Hence, for the case studied here, these parameterizations give more insight into the causes of variability in model performance than does the number of model prognostics per se.

How well can a climate model simulate an extreme precipitation event: A case study using the Transpose-AMIP experiment

AbstractA 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 Scien...