ORCID Profile
0000-0002-9699-8850
Current Organisations
European Centre for Medium-Range Weather Forecasts
,
University of Reading
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Publisher: Copernicus GmbH
Date: 17-09-2019
Abstract: Abstract. The accurate representation of ice particles is essential for both remotely sensed estimates of clouds and precipitation and numerical models of the atmosphere. As it is typical in radar retrievals to assume that all snow is composed of aggregate snowflakes, both denser rimed snow and the mixed-phase cloud in which riming occurs may be under-diagnosed in retrievals and therefore difficult to evaluate in weather and climate models. Recent experimental and numerical studies have yielded methods for using triple-frequency radar measurements to interrogate the internal structure of aggregate snowflakes and to distinguish more dense and homogeneous rimed particles from aggregates. In this study we investigate which parameters of the morphology and size distribution of ice particles most affect the triple-frequency radar signature and must therefore be accounted for in order to carry out triple-frequency radar retrievals of snow. A range of ice particle morphologies are represented, using a fractal representation for the internal structure of aggregate snowflakes and homogeneous spheroids to represent graupel-like particles the mass–size and area–size relations are modulated by a density factor. We find that the particle size distribution (PSD) shape parameter and the parameters controlling the internal structure of aggregate snowflakes both have significant influences on triple-frequency radar signature and are at least as important as that of the density factor. We explore how these parameters may be allowed to vary in order to prevent triple-frequency radar retrievals of snow from being over-constrained, using two case studies from the Biogenic Aerosols – Effects of Clouds and Climate (BAECC) 2014 field c aign at Hyytiälä, Finland. In a case including heavily rimed snow followed by large aggregate snowflakes, we show that triple-frequency radar measurements provide a strong constraint on the PSD shape parameter, which can be estimated from an ensemble of retrievals however, resolving variations in the PSD shape parameter has a limited impact on estimates of snowfall rate from radar. Particle density is more effectively constrained by the Doppler velocity than triple-frequency radar measurements, due to the strong dependence of particle fall speed on density. Due to the characteristic signatures of aggregate snowflakes, a third radar frequency is essential for effectively constraining the size of large aggregates. In a case featuring rime splintering, differences in the internal structures of aggregate snowflakes are revealed in the triple-frequency radar measurements. We compare retrievals assuming different aggregate snowflake models against in situ measurements at the surface and show significant uncertainties in radar retrievals of snow rate due to changes in the internal structure of aggregates. The importance of the PSD shape parameter and snowflake internal structure to triple-frequency radar retrievals of snow highlights that the processes by which ice particles interact may need to be better understood and parameterized before triple-frequency radar measurements can be used to constrain retrievals of ice particle morphology.
Publisher: Copernicus GmbH
Date: 18-03-2019
DOI: 10.5194/AMT-2019-100
Abstract: Abstract. The accurate representation of ice particles is essential for both remotely-sensed estimates of cloud and precipitation and numerical models of the atmosphere. As it is typical in radar retrievals to assume that all snow is composed of unrimed aggregate snowflakes, both denser rimed snow and the mixed-phase cloud in which riming occurs may be under-diagnosed in retrievals, and therefore difficult to evaluate in weather and climate models. Recent experimental and numerical studies have yielded methods for using triple-frequency radar measurements to distinguish fractal aggregate snowflakes from more dense and homogeneous rimed particles. In this study we investigate which parameters of the particle size distribution (PSD) and morphology of ice particles are most important to the triple-frequency radar signature of snow, in order to carry out an optimal estimation retrieval using triple-frequency Doppler radar observations. We represent a range of ice particle morphologies using a fractal model for aggregate snowflakes and homogeneous spheroids to represent rimed graupel-like particles, and modulate the prefactor and exponent of the particles' mass-size relations with a density factor. We find that for both fractal particles and homogeneous spheroids the PSD shape has a greater influence on the triple-frequency radar signature than the density factor, and show that the PSD shape must be allowed to vary to adequately constrain a triple-frequency radar retrieval of snow. We then demonstrate a novel triple-frequency Doppler radar retrieval of three parameters of the PSD as well as particle density, and show that the estimated snow rate, PSD and bulk density compare well against in situ observations at the surface. In a case study of compact rimed snow, we find that triple-frequency radar measurements provide a strong constraint on the estimation of PSD shape, but a relatively weak constraint on particle density, which we find can be more directly estimated from the Doppler velocity due to the relation between particle density and fallspeed. Including variations in PSD shape as well as particle morphology allows for a better representation of the triple-frequency radar signatures of rimed and unrimed snow, and suggests the potential for making new insights into the interaction between particles during aggregation and riming mechanisms. However, we find that improved representation of the PSD shape has a limited impact on improved estimates of snow rate from radar. The importance of the PSD shape to triple-frequency radar retrievals of snow suggests that further work is needed to account for variations in PSD shape before triple-frequency radar measurements can be used to better constrain particle morphology.
Publisher: Copernicus GmbH
Date: 06-07-2017
Publisher: Copernicus GmbH
Date: 06-07-2017
Publisher: American Meteorological Society
Date: 07-08-2014
DOI: 10.1175/JCLI-D-14-00139.1
Abstract: Clouds strongly affect the absorption and reflection of shortwave and longwave radiation in the atmosphere. A key bias in climate models is related to excess absorbed shortwave radiation in the high-latitude Southern Ocean. Model evaluation studies attribute these biases in part to midtopped clouds, and observations confirm significant midtopped clouds in the zone of interest. However, it is not yet clear what cloud properties can be attributed to the deficit in modeled clouds. Present approaches using observed cloud regimes do not sufficiently differentiate between potentially distinct types of midtopped clouds and their meteorological contexts. This study presents a refined set of midtopped cloud subregimes for the high-latitude Southern Ocean, which are distinct in their dynamical and thermodynamic background states. Active satellite observations from CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) are used to study the macrophysical structure and microphysical properties of the new cloud regimes. The subgrid-scale variability of cloud structure and microphysics is quantified within the cloud regimes by identifying representative physical cloud profiles at high resolution from the radar–lidar (DARDAR) cloud classification mask. The midtopped cloud subregimes distinguish between stratiform clouds under a high inversion and moderate subsidence an optically thin cold-air advection cloud regime occurring under weak subsidence and including altostratus over low clouds optically thick clouds with frequent deep structures under weak ascent and warm midlevel anomalies and a midlevel convective cloud regime associated with strong ascent and warm advection. The new midtopped cloud regimes for the high-latitude Southern Ocean will provide a refined tool for model evaluation and the attribution of shortwave radiation biases to distinct cloud processes and properties.
Publisher: Copernicus GmbH
Date: 06-07-2017
Publisher: Copernicus GmbH
Date: 06-07-2017
Publisher: Copernicus GmbH
Date: 06-07-2017
Publisher: American Geophysical Union (AGU)
Date: 03-2022
DOI: 10.1029/2021MS002550
Abstract: The treatment of cloud structure in numerical weather and climate models is often greatly simplified to make them computationally affordable. Here we propose to correct the European Centre for Medium‐Range Weather Forecasts 1D radiation scheme ecRad for 3D cloud effects using computationally cheap neural networks. 3D cloud effects are learned as the difference between ecRad's fast 1D Tripleclouds solver that neglects them and its 3D SPARTACUS (SPeedy Algorithm for Radiative TrAnsfer through CloUd Sides) solver that includes them but is about five times more computationally expensive. With typical errors between 20% and 30% of the 3D signal, neural networks improve Tripleclouds' accuracy for about 1% increase in runtime. Thus, rather than emulating the whole of SPARTACUS, we keep Tripleclouds unchanged for cloud‐free parts of the atmosphere and 3D‐correct it elsewhere. The focus on the comparably small 3D correction instead of the entire signal allows us to improve predictions significantly if we assume a similar signal‐to‐noise ratio for both.
Publisher: Copernicus GmbH
Date: 06-07-2017
Publisher: American Meteorological Society
Date: 04-03-2016
Abstract: A comparison of marine cold air outbreaks (MCAOs) in the Northern and Southern Hemispheres is presented, with attention to their seasonality, frequency of occurrence, and strength as measured by a cold air outbreak index. When considered on a gridpoint-by-gridpoint basis, MCAOs are more severe and more frequent in the Northern Hemisphere (NH) than the Southern Hemisphere (SH) in winter. However, when MCAOs are viewed as in idual events regardless of horizontal extent, they occur more frequently in the SH. This is fundamentally because NH MCAOs are larger and stronger than those in the SH. MCAOs occur throughout the year, but in warm seasons and in the SH they are smaller and weaker than in cold seasons and in the NH. In both hemispheres, strong MCAOs occupy the cold air sector of midlatitude cyclones, which generally appear to be in their growth phase. Weak MCAOs in the SH occur under generally zonal flow with a slight northward component associated with weak zonal pressure gradients, while weak NH MCAOs occur under such a wide range of conditions that no characteristic synoptic pattern emerges from compositing. Strong boundary layer deepening, warming, and moistening occur as a result of the surface heat fluxes within MCAOs.
Publisher: Monash University
Date: 2017
Publisher: Copernicus GmbH
Date: 12-04-2017
DOI: 10.5194/ACP-2017-280
Abstract: Abstract. Satellite radar remote-sensing of rain is important for quantifying of the global hydrological cycle, atmospheric energy budget, and many microphysical cloud and precipitation processes however, radar estimates of rain rate are sensitive to assumptions about the raindrop size distribution. The upcoming EarthCARE satellite will feature a 94-GHz Doppler radar alongside lidar and radiometer instruments, presenting opportunities for enhanced global retrievals of the rain drop size distribution. In this paper we demonstrate the capability to retrieve both rain rate and a parameter of the rain drop size distribution from an airborne 94-GHz Doppler radar using CAPTIVATE, the variational retrieval algorithm developed for EarthCARE radar–lidar synergy. For a range of rain regimes observed during the Tropical Composition, Cloud and Climate Coupling (TC4) field c aign in the eastern Pacific in 2007, we explore the contributions of Doppler velocity and path-integrated attenuation (PIA) to the retrievals, and evaluate the retrievals against independent measurements from a second, less attenuated, Doppler radar aboard the same aircraft. Retrieved drop number concentration varied over five orders of magnitude between light rain from melting ice, and warm rain from liquid clouds. Doppler velocity can be used to estimate rain rate over land, and retrievals of rain rate and drop number concentration are possible in profiles of light rain over land in moderate warm rain, drop number concentration can be retrieved without Doppler velocity. These results suggest that EarthCARE rain retrievals facilitated by Doppler radar will make substantial improvements to the global understanding of the interaction of clouds and precipitation.
Publisher: American Meteorological Society
Date: 30-07-2015
DOI: 10.1175/JCLI-D-14-00846.1
Abstract: A deficit of shortwave cloud forcing over the Southern Ocean is persistent in many global climate models. Cloud regimes have been widely used in model evaluation studies to make a process-oriented diagnosis of cloud parameterization errors, but cloud regimes have some limitations in resolving both observed and simulated cloud behavior. A hybrid methodology is developed for identifying cloud regimes from observed and simulated cloud simultaneously. Through this methodology, 11 hybrid cloud regimes are identified in the ACCESS1.3 model for the high-latitude Southern Ocean. The hybrid cloud regimes resolve the features of observed cloud and characterize cloud errors in the model. The simulated properties of the hybrid cloud regimes, and their occurrence over the Southern Ocean and in the context of extratropical cyclones, are evaluated, and their contributions to the shortwave radiation errors are quantified. Three errors are identified: an overall deficit of cloud fraction, a tendency toward optically thin low and midtopped cloud, and an absence of a shallow frontal-type cloud at high latitudes and in the warm fronts of extratropical cyclones. To demonstrate the utility of the hybrid cloud regimes for the evaluation of changes to the model, the effects of selected changes to the model microphysics are investigated.
Publisher: American Meteorological Society
Date: 31-08-2016
Abstract: A climatology of clouds within marine cold air outbreaks, primarily using long-term satellite observations, is presented. Cloud properties between cold air outbreaks in different regions in both hemispheres are compared. In all regions marine cold air outbreak clouds tend to be low level with high cloud fraction and low-to-moderate optical thickness. Stronger cold air outbreaks have clouds that are optically thicker, but not geometrically thicker, than those in weaker cold air outbreaks. There is some evidence that clouds deepen and break up over the course of a cold air outbreak event. The top-of-the-atmosphere longwave cloud radiative effect in cold air outbreaks is small because the clouds have low tops. However, their surface longwave cloud radiative effect is considerably larger. The rarity of cold air outbreaks in summer limits their shortwave cloud radiative effect. They do not contribute substantially to global shortwave cloud radiative effect and are, therefore, unlikely to be a major source of shortwave cloud radiative effect errors in climate models.
Publisher: Copernicus GmbH
Date: 05-08-2019
Publisher: Copernicus GmbH
Date: 05-08-2019
Publisher: American Geophysical Union (AGU)
Date: 18-12-2018
DOI: 10.1029/2018JD028603
Publisher: Copernicus GmbH
Date: 27-09-2017
DOI: 10.5194/ACP-17-11567-2017
Abstract: Abstract. Satellite remote sensing of rain is important for quantifying the hydrological cycle, atmospheric energy budget, and cloud and precipitation processes however, radar retrievals of rain rate are sensitive to assumptions about the raindrop size distribution. The upcoming EarthCARE satellite will feature a 94 GHz Doppler radar alongside lidar and radiometer instruments, presenting opportunities for enhanced retrievals of the raindrop size distribution.
Publisher: Copernicus GmbH
Date: 05-08-2019
Publisher: Copernicus GmbH
Date: 05-08-2019
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: No location found
No related grants have been discovered for Shannon Mason.