scholarly journals Instantaneous Linkages between Clouds and Large-Scale Meteorology over the Southern Ocean in Observations and a Climate Model

2017 ◽  
Vol 30 (23) ◽  
pp. 9455-9474 ◽  
Author(s):  
Casey J. Wall ◽  
Dennis L. Hartmann ◽  
Po-Lun Ma
Keyword(s):  
Southern Ocean ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Austral Summer ◽  
Vertical Motion ◽  
Cloud Properties ◽  
Low Clouds ◽  
Community Atmosphere Model ◽  
Low Cloud

Instantaneous, coincident, footprint-level satellite observations of cloud properties and radiation taken during austral summer over the Southern Ocean are used to study relationships between clouds and large-scale meteorology. Cloud properties are very sensitive to the strength of vertical motion in the midtroposphere, and low-cloud properties are sensitive to estimated inversion strength, low-level temperature advection, and sea surface temperature. These relationships are quantified. An index for the meteorological anomalies associated with midlatitude cyclones is presented, and it is used to reveal the sensitivity of clouds to the meteorology within the warm and cold sectors of cyclones. The observed relationships between clouds and meteorology are compared to those in the Community Atmosphere Model, version 5 (CAM5), using satellite simulators. Low clouds simulated by CAM5 are too few, are too bright, and contain too much ice. In the cold sector of cyclones, the low clouds are also too sensitive to variations in the meteorology. When CAM5 is coupled with an updated boundary layer parameterization known as Cloud Layers Unified by Binormals (CLUBB), bias in the ice content of low clouds is dramatically reduced. More generally, this study demonstrates that examining the instantaneous time scale is a powerful approach to understanding the physical processes that control clouds and how they are represented in climate models. Such an evaluation goes beyond the cloud climatology and exposes model bias under various meteorological conditions.

scholarly journals Regional Assessments of Low Clouds against Large-Scale Stability in CAM5 and CAM-CLUBB Using MODIS and ERA-Interim Reanalysis Data

2015 ◽  
Vol 28 (4) ◽  
pp. 1685-1706 ◽  
Author(s):  
Terence L. Kubar ◽  
Graeme L. Stephens ◽  
Matthew Lebsock ◽  
Vincent E. Larson ◽  
Peter A. Bogenschutz
Keyword(s):  
Large Scale ◽  
Reanalysis Data ◽  
Smooth Transition ◽  
Cloud Data ◽  
Low Clouds ◽  
Community Atmosphere Model ◽  
Northeastern Pacific ◽  
Low Cloud ◽  
Cloud Parameterization ◽  
Static Energy

Abstract Daily gridded cloud data from MODIS and ERA-Interim reanalysis have been assessed to examine variations of low cloud fraction (CF) and cloud-top height and their dependence on large-scale dynamics and a measure of stability. To assess the stratocumulus (Sc) to cumulus (Cu) transition (STCT), the observations are used to evaluate two versions of the NCAR Community Atmosphere Model version 5 (CAM5), both the base model and a version that has implemented a new subgrid low cloud parameterization, Cloud Layers Unified by Binormals (CLUBB). The ratio of moist static energy (MSE) at 700–1000 hPa (MSEtotal) is a skillful predictor of median CF of screened low cloud grids. Values of MSEtotal less than 1.00 represent either conditionally or absolutely unstable layers, and probability density functions of CF suggest a preponderance of either trade Cu (median CF < 0.4) or transitional Sc clouds (0.4 < CF < 0.9). With increased stability (MSEtotal > 1.00), an abundance of overcast or nearly overcast low clouds exists. While both MODIS and ERA-Interim indicate a fairly smooth transition between the low cloud regimes, CAM5-Base simulates an abrupt shift from trade Cu to Sc, with trade Cu covering both too much area and occurring over excessively strong stabilities. In contrast, CAM-CLUBB simulates a smoother trade Cu to Sc transition (CTST) as a function of MSEtotal, albeit with too extensive coverage of overcast Sc in the primary northeastern Pacific subsidence region. While the overall CF distribution in CAM-CLUBB is more realistic, too few transitional clouds are simulated for intermediate MSEtotal compared to observations.

Ship-based aerosol measurements in the Southern Ocean 

2021 ◽  
Author(s):  
Floortje van den Heuvel ◽  
Thomas Lachlan-Cope ◽  
Jonathan Witherstone ◽  
Dean Hurren ◽  
Anna Jones
Keyword(s):  
Southern Ocean ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Numerical Models ◽  
Cloud Microphysics ◽  
Wave Radiation ◽  
Atlantic Sector ◽  
Radiation Fluxes ◽  
Travel Restrictions

<p><span><span>Our limited understanding of clouds is a major source of uncertainty in climate sensitivity and climate model projections. The Southern Ocean is </span></span><span><span>the largest</span></span><span> </span><span><span>region</span></span><span><span> on Earth where climate models present large biases </span></span><span><span>in</span></span><span><span> short and long wave radiation fluxes which in turn affect the representation of sea surface temperatures, sea ice and ultimately large scale circulation in the S</span></span><span><span>outhern Hemisphere</span></span><span><span>. Evidence suggests that the poor representation of mixed phase clouds at the micro- and macro scales is responsible for the model biases in this region. The Southern Ocean Clouds (SOC) project </span></span><span><span>will be</span></span><span><span> a multi-scale, multi-platform approach with the aim of improving understanding of aerosol and cloud microphysics in this region, and their representation in numerical models. </span></span></p><p><span><span>Although this years’ first SOC measurement season has suffered greatly from travel restrictions, we have installed an Optical Particle Counter (OPC) on a ship (The James Clark Ross – JCR) and recorded aerosol measurements as it was travelling through the Atlantic sector of the Southern Ocean towards the Antarctic Peninsula, and while the ship was moored at South Georgia and Port Stanley. Over the course of one month, the OPC recorded particle sizes between 0.35 and 40 micrometers every six seconds. This study will present the data from this first, rather short Antarctic SOC season. It will present the analyses of the obtained OPC data alongside satellite observations and model reanalyses in the same region.</span></span></p>

scholarly journals Major Characteristics of Southern Ocean Cloud Regimes and Their Effects on the Energy Budget

2011 ◽  
Vol 24 (19) ◽  
pp. 5061-5080 ◽  
Author(s):  
John M. Haynes ◽  
Christian Jakob ◽  
William B. Rossow ◽  
George Tselioudis ◽  
Josephine Brown
Keyword(s):  
Southern Ocean ◽  
Large Scale ◽  
Climate Models ◽  
Satellite Observation ◽  
Radiative Heating ◽  
Radiation Balance ◽  
Heating Rates ◽  
Cloud Systems ◽  
Low Cloud ◽  
Cloud Regimes

Clouds over the Southern Ocean are often poorly represented by climate models, but they make a significant contribution to the top-of-atmosphere (TOA) radiation balance, particularly in the shortwave portion of the energy spectrum. This study seeks to better quantify the organization and structure of Southern Hemisphere midlatitude clouds by combining measurements from active and passive satellite-based datasets. Geostationary and polar-orbiter satellite data from the International Satellite Cloud Climatology Project (ISCCP) are used to quantify large-scale, recurring modes of cloudiness, and active observations from CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) are used to examine vertical structure, radiative heating rates, and precipitation associated with these clouds. It is found that cloud systems are organized into eight distinct regimes and that ISCCP overestimates the midlevel cloudiness of these regimes. All regimes contain a relatively high occurrence of low cloud, with 79% of all cloud layers observed having tops below 3 km, but multiple-layered clouds systems are present in approximately 34% of observed cloud profiles. The spatial distribution of regimes varies according to season, with cloud systems being geometrically thicker, on average, during the austral winter. Those regimes found to be most closely associated with midlatitude cyclones produce precipitation the most frequently, although drizzle is extremely common in low-cloud regimes. The regimes associated with cyclones have the highest in-regime shortwave cloud radiative effect at the TOA, but the low-cloud regimes, by virtue of their high frequency of occurrence over the oceans, dominate both TOA and surface shortwave effects in this region as a whole.

scholarly journals Evaluating models' response of tropical low clouds to SST forcings using CALIPSO observations

2019 ◽  
Vol 19 (5) ◽  
pp. 2813-2832 ◽  
Author(s):  
Grégory Cesana ◽  
Anthony D. Del Genio ◽  
Andrew S. Ackerman ◽  
Maxwell Kelley ◽  
Gregory Elsaesser ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Climate Models ◽  
Climate Model ◽  
Cloud Fraction ◽  
Surface Warming ◽  
Low Clouds ◽  
Cloud Radiative Effect ◽  
Low Cloud ◽  
Moist Processes ◽  
Low Cloud Cover

Abstract. Recent studies have shown that, in response to a surface warming, the marine tropical low-cloud cover (LCC) as observed by passive-sensor satellites substantially decreases, therefore generating a smaller negative value of the top-of-the-atmosphere (TOA) cloud radiative effect (CRE). Here we study the LCC and CRE interannual changes in response to sea surface temperature (SST) forcings in the GISS model E2 climate model, a developmental version of the GISS model E3 climate model, and in 12 other climate models, as a function of their ability to represent the vertical structure of the cloud response to SST change against 10 years of CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) observations. The more realistic models (those that satisfy the observational constraint) capture the observed interannual LCC change quite well (ΔLCC/ΔSST=-3.49±1.01 % K−1 vs. ΔLCC/ΔSSTobs=-3.59±0.28 % K−1) while the others largely underestimate it (ΔLCC/ΔSST=-1.32±1.28 % K−1). Consequently, the more realistic models simulate more positive shortwave (SW) feedback (ΔCRE/ΔSST=2.60±1.13 W m−2 K−1) than the less realistic models (ΔCRE/ΔSST=0.87±2.63 W m−2 K−1), in better agreement with the observations (ΔCRE/ΔSSTobs=3±0.26 W m−2 K−1), although slightly underestimated. The ability of the models to represent moist processes within the planetary boundary layer (PBL) and produce persistent stratocumulus (Sc) decks appears crucial to replicating the observed relationship between clouds, radiation and surface temperature. This relationship is different depending on the type of low clouds in the observations. Over stratocumulus regions, cloud-top height increases slightly with SST, accompanied by a large decrease in cloud fraction, whereas over trade cumulus (Cu) regions, cloud fraction decreases everywhere, to a smaller extent.

Influences of Recent Particle Formation on Southern Ocean Aerosol Variability and Low Cloud Properties

2021 ◽  
Author(s):  
Isabel L. McCoy ◽  
Christopher S. Bretherton ◽  
Robert Wood ◽  
Cynthia H. Twohy ◽  
Andrew Gettelman ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Particle Formation ◽  
Cloud Properties ◽  
Low Cloud

Influences of Recent Particle Formation on Southern Ocean Aerosol Variability and Low Cloud Properties

2021 ◽  
Author(s):  
Isabel L. McCoy ◽  
Christopher S. Bretherton ◽  
Robert Wood ◽  
Cynthia H. Twohy ◽  
Andrew Gettelman ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Particle Formation ◽  
Cloud Properties ◽  
Low Cloud

scholarly journals Atmospheric circulation and hydroclimate impacts of alternative warming scenarios for the Eocene

2017 ◽  
Vol 13 (8) ◽  
pp. 1037-1048 ◽  
Author(s):  
Henrik Carlson ◽  
Rodrigo Caballero
Keyword(s):  
Surface Temperature ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Warm Season ◽  
Cloud Albedo ◽  
Cloud Properties ◽  
Atmospheric Co2 Concentrations ◽  
Global Mean

Abstract. Recent work in modelling the warm climates of the early Eocene shows that it is possible to obtain a reasonable global match between model surface temperature and proxy reconstructions, but only by using extremely high atmospheric CO2 concentrations or more modest CO2 levels complemented by a reduction in global cloud albedo. Understanding the mix of radiative forcing that gave rise to Eocene warmth has important implications for constraining Earth's climate sensitivity, but progress in this direction is hampered by the lack of direct proxy constraints on cloud properties. Here, we explore the potential for distinguishing among different radiative forcing scenarios via their impact on regional climate changes. We do this by comparing climate model simulations of two end-member scenarios: one in which the climate is warmed entirely by CO2 (which we refer to as the greenhouse gas (GHG) scenario) and another in which it is warmed entirely by reduced cloud albedo (which we refer to as the low CO2–thin clouds or LCTC scenario) . The two simulations have an almost identical global-mean surface temperature and equator-to-pole temperature difference, but the LCTC scenario has  ∼  11 % greater global-mean precipitation than the GHG scenario. The LCTC scenario also has cooler midlatitude continents and warmer oceans than the GHG scenario and a tropical climate which is significantly more El Niño-like. Extremely high warm-season temperatures in the subtropics are mitigated in the LCTC scenario, while cool-season temperatures are lower at all latitudes. These changes appear large enough to motivate further, more detailed study using other climate models and a more realistic set of modelling assumptions.

Evaluating the Consistency between Statistically Downscaled and Global Dynamical Model Climate Change Projections

2008 ◽  
Vol 21 (22) ◽  
pp. 6052-6059 ◽  
Author(s):  
B. Timbal ◽  
P. Hope ◽  
S. Charles
Keyword(s):  
Global Warming ◽  
Statistical Downscaling ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Specific Humidity ◽  
Model Output ◽  
Winter Rainfall ◽  
Direct Model ◽  
The Impact

Abstract The consistency between rainfall projections obtained from direct climate model output and statistical downscaling is evaluated. Results are averaged across an area large enough to overcome the difference in spatial scale between these two types of projections and thus make the comparison meaningful. Undertaking the comparison using a suite of state-of-the-art coupled climate models for two forcing scenarios presents a unique opportunity to test whether statistical linkages established between large-scale predictors and local rainfall under current climate remain valid in future climatic conditions. The study focuses on the southwest corner of Western Australia, a region that has experienced recent winter rainfall declines and for which climate models project, with great consistency, further winter rainfall reductions due to global warming. Results show that as a first approximation the magnitude of the modeled rainfall decline in this region is linearly related to the model global warming (a reduction of about 9% per degree), thus linking future rainfall declines to future emission paths. Two statistical downscaling techniques are used to investigate the influence of the choice of technique on projection consistency. In addition, one of the techniques was assessed using different large-scale forcings, to investigate the impact of large-scale predictor selection. Downscaled and direct model projections are consistent across the large number of models and two scenarios considered; that is, there is no tendency for either to be biased; and only a small hint that large rainfall declines are reduced in downscaled projections. Among the two techniques, a nonhomogeneous hidden Markov model provides greater consistency with climate models than an analog approach. Differences were due to the choice of the optimal combination of predictors. Thus statistically downscaled projections require careful choice of large-scale predictors in order to be consistent with physically based rainfall projections. In particular it was noted that a relative humidity moisture predictor, rather than specific humidity, was needed for downscaled projections to be consistent with direct model output projections.

scholarly journals Influence of the representation of convection on the mid-Holocene West African Monsoon

2021 ◽  
Vol 17 (4) ◽  
pp. 1665-1684
Author(s):  
Leonore Jungandreas ◽  
Cathy Hohenegger ◽  
Martin Claussen
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Monsoon Season ◽  
West African Monsoon ◽  
West African ◽  
Global Climate Models ◽  
African Monsoon ◽  
Monsoonal Precipitation

Abstract. Global climate models experience difficulties in simulating the northward extension of the monsoonal precipitation over north Africa during the mid-Holocene as revealed by proxy data. A common feature of these models is that they usually operate on grids that are too coarse to explicitly resolve convection, but convection is the most essential mechanism leading to precipitation in the West African Monsoon region. Here, we investigate how the representation of tropical deep convection in the ICOsahedral Nonhydrostatic (ICON) climate model affects the meridional distribution of monsoonal precipitation during the mid-Holocene by comparing regional simulations of the summer monsoon season (July to September; JAS) with parameterized and explicitly resolved convection. In the explicitly resolved convection simulation, the more localized nature of precipitation and the absence of permanent light precipitation as compared to the parameterized convection simulation is closer to expectations. However, in the JAS mean, the parameterized convection simulation produces more precipitation and extends further north than the explicitly resolved convection simulation, especially between 12 and 17∘ N. The higher precipitation rates in the parameterized convection simulation are consistent with a stronger monsoonal circulation over land. Furthermore, the atmosphere in the parameterized convection simulation is less stably stratified and notably moister. The differences in atmospheric water vapor are the result of substantial differences in the probability distribution function of precipitation and its resulting interactions with the land surface. The parametrization of convection produces light and large-scale precipitation, keeping the soils moist and supporting the development of convection. In contrast, less frequent but locally intense precipitation events lead to high amounts of runoff in the explicitly resolved convection simulations. The stronger runoff inhibits the moistening of the soil during the monsoon season and limits the amount of water available to evaporation in the explicitly resolved convection simulation.

scholarly journals Improving climate model coupling through a complete mesh representation: a case study with E3SM (v1) and MOAB (v5.x)

2020 ◽  
Vol 13 (5) ◽  
pp. 2355-2377
Author(s):  
Vijay S. Mahadevan ◽  
Iulian Grindeanu ◽  
Robert Jacob ◽  
Jason Sarich
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Climate Modeling ◽  
System Modeling ◽  
Spectral Element ◽  
Scientific Workflow ◽  
Model Coupling ◽  
Earth System ◽  
Modeling Framework

Abstract. One of the fundamental factors contributing to the spatiotemporal inaccuracy in climate modeling is the mapping of solution field data between different discretizations and numerical grids used in the coupled component models. The typical climate computational workflow involves evaluation and serialization of the remapping weights during the preprocessing step, which is then consumed by the coupled driver infrastructure during simulation to compute field projections. Tools like Earth System Modeling Framework (ESMF) (Hill et al., 2004) and TempestRemap (Ullrich et al., 2013) offer capability to generate conservative remapping weights, while the Model Coupling Toolkit (MCT) (Larson et al., 2001) that is utilized in many production climate models exposes functionality to make use of the operators to solve the coupled problem. However, such multistep processes present several hurdles in terms of the scientific workflow and impede research productivity. In order to overcome these limitations, we present a fully integrated infrastructure based on the Mesh Oriented datABase (MOAB) (Tautges et al., 2004; Mahadevan et al., 2015) library, which allows for a complete description of the numerical grids and solution data used in each submodel. Through a scalable advancing-front intersection algorithm, the supermesh of the source and target grids are computed, which is then used to assemble the high-order, conservative, and monotonicity-preserving remapping weights between discretization specifications. The Fortran-compatible interfaces in MOAB are utilized to directly link the submodels in the Energy Exascale Earth System Model (E3SM) to enable online remapping strategies in order to simplify the coupled workflow process. We demonstrate the superior computational efficiency of the remapping algorithms in comparison with other state-of-the-science tools and present strong scaling results on large-scale machines for computing remapping weights between the spectral element atmosphere and finite volume discretizations on the polygonal ocean grids.

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