scholarly journals Understanding the Varied Influence of Midlatitude Jet Position on Clouds and Cloud Radiative Effects in Observations and Global Climate Models

2016 ◽  
Vol 29 (24) ◽  
pp. 9005-9025 ◽  
Author(s):  
Kevin M. Grise ◽  
Brian Medeiros
Keyword(s):  
Vertical Velocity ◽  
Climate Models ◽  
Global Climate ◽  
Storm Track ◽  
Cloud Amount ◽  
Global Climate Models ◽  
Radiative Effects ◽  
Velocity Anomalies ◽  
Cooling Effects ◽  
Cloud Radiative Effects

Abstract This study examines the dynamical mechanisms responsible for changes in midlatitude clouds and cloud radiative effects (CRE) that occur in conjunction with meridional shifts in the jet streams over the North Atlantic, North Pacific, and Southern Oceans. When the midlatitude jet shifts poleward, extratropical cyclones and their associated upward vertical velocity anomalies closely follow. As a result, a poleward jet shift contributes to a poleward shift in high-topped storm-track clouds and their associated longwave CRE. However, when the jet shifts poleward, downward vertical velocity anomalies increase equatorward of the jet, contributing to an enhancement of the boundary layer estimated inversion strength (EIS) and an increase in low cloud amount there. Because shortwave CRE depends on the reflection of solar radiation by clouds in all layers, the shortwave cooling effects of midlatitude clouds increase with both upward vertical velocity anomalies and positive EIS anomalies. Over midlatitude oceans where a poleward jet shift contributes to positive EIS anomalies but downward vertical velocity anomalies, the two effects cancel, and net observed changes in shortwave CRE are small. Global climate models generally capture the observed anomalies associated with midlatitude jet shifts. However, there is large intermodel spread in the shortwave CRE anomalies, with a subset of models showing a large shortwave cloud radiative warming over midlatitude oceans with a poleward jet shift. In these models, midlatitude shortwave CRE is sensitive to vertical velocity perturbations, but the observed sensitivity to EIS perturbations is underestimated. Consequently, these models might incorrectly estimate future midlatitude cloud feedbacks in regions where appreciable changes in both vertical velocity and EIS are projected.

scholarly journals Examining Southern Ocean Cloud Controlling Factors on Daily Time Scales and Their Connections to Midlatitude Weather Systems

2019 ◽  
Vol 32 (16) ◽  
pp. 5145-5160 ◽  
Author(s):  
Mitchell K. Kelleher ◽  
Kevin M. Grise
Keyword(s):  
Southern Ocean ◽  
Time Scales ◽  
Vertical Velocity ◽  
Climate Models ◽  
Global Climate ◽  
Controlling Factors ◽  
Global Climate Models ◽  
Model Errors ◽  
Radiative Effects ◽  
Daily Time

ABSTRACTClouds and their associated radiative effects are a large source of uncertainty in global climate models. One region with particularly large model biases in shortwave cloud radiative effects (CRE) is the Southern Ocean. Previous research has shown that many dynamical “cloud controlling factors” influence shortwave CRE on monthly time scales and that two important cloud controlling factors over the Southern Ocean are midtropospheric vertical velocity and estimated inversion strength (EIS). Model errors may thus arise from biases in representing cloud controlling factors (atmospheric dynamics) or in representing how clouds respond to those cloud controlling factors (cloud parameterizations), or some combination thereof. This study extends previous work by examining cloud controlling factors over the Southern Ocean on daily time scales in both observations and global climate models. This allows the cloud controlling factors to be examined in the context of transient weather systems. Composites of EIS and midtropospheric vertical velocity are constructed around extratropical cyclones and anticyclones to examine how the different dynamical cloud controlling factors influence shortwave CRE around midlatitude weather systems and to assess how models compare to observations. On average, models tend to produce a realistic cyclone and anticyclone, when compared to observations, in terms of the dynamical cloud controlling factors. The difference between observations and models instead lies in how the models’ shortwave CRE respond to the dynamics. In particular, the models’ shortwave CRE are too sensitive to perturbations in midtropospheric vertical velocity and, thus, they tend to produce clouds that excessively brighten in the frontal region of the cyclone and excessively dim in the center of the anticyclone.

Assessment of Arctic Cloud Cover Anomalies in Atmospheric Reanalysis Products Using Satellite Data

2016 ◽  
Vol 29 (17) ◽  
pp. 6065-6083 ◽  
Author(s):  
Yinghui Liu ◽  
Jeffrey R. Key
Keyword(s):  
Cloud Cover ◽  
Climate Models ◽  
Global Climate ◽  
Correlation Coefficients ◽  
Cloud Amount ◽  
Satellite Observation ◽  
Skill Score ◽  
Global Climate Models ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract Cloud cover is one of the largest uncertainties in model predictions of the future Arctic climate. Previous studies have shown that cloud amounts in global climate models and atmospheric reanalyses vary widely and may have large biases. However, many climate studies are based on anomalies rather than absolute values, for which biases are less important. This study examines the performance of five atmospheric reanalysis products—ERA-Interim, MERRA, MERRA-2, NCEP R1, and NCEP R2—in depicting monthly mean Arctic cloud amount anomalies against Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations from 2000 to 2014 and against Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) observations from 2006 to 2014. All five reanalysis products exhibit biases in the mean cloud amount, especially in winter. The Gerrity skill score (GSS) and correlation analysis are used to quantify their performance in terms of interannual variations. Results show that ERA-Interim, MERRA, MERRA-2, and NCEP R2 perform similarly, with annual mean GSSs of 0.36/0.22, 0.31/0.24, 0.32/0.23, and 0.32/0.23 and annual mean correlation coefficients of 0.50/0.51, 0.43/0.54, 0.44/0.53, and 0.50/0.52 against MODIS/CALIPSO, indicating that the reanalysis datasets do exhibit some capability for depicting the monthly mean cloud amount anomalies. There are no significant differences in the overall performance of reanalysis products. They all perform best in July, August, and September and worst in November, December, and January. All reanalysis datasets have better performance over land than over ocean. This study identifies the magnitudes of errors in Arctic mean cloud amounts and anomalies and provides a useful tool for evaluating future improvements in the cloud schemes of reanalysis products.

scholarly journals Tendency Bias Correction in Coupled and Uncoupled Global Climate Models with a Focus on Impacts over North America

2019 ◽  
Vol 32 (2) ◽  
pp. 639-661 ◽  
Author(s):  
Y. Chang ◽  
S. D. Schubert ◽  
R. D. Koster ◽  
A. M. Molod ◽  
H. Wang
Keyword(s):  
North America ◽  
Bias Correction ◽  
Climate Models ◽  
Global Climate ◽  
Storm Track ◽  
Coupled Model ◽  
Global Climate Models ◽  
Forecast Skill ◽  
Boreal Summer ◽  
Transient Wave

Abstract We revisit the bias correction problem in current climate models, taking advantage of state-of-the-art atmospheric reanalysis data and new data assimilation tools that simplify the estimation of short-term (6 hourly) atmospheric tendency errors. The focus is on the extent to which correcting biases in atmospheric tendencies improves the model’s climatology, variability, and ultimately forecast skill at subseasonal and seasonal time scales. Results are presented for the NASA GMAO GEOS model in both uncoupled (atmosphere only) and coupled (atmosphere–ocean) modes. For the uncoupled model, the focus is on correcting a stunted North Pacific jet and a dry bias over the central United States during boreal summer—long-standing errors that are indeed common to many current AGCMs. The results show that the tendency bias correction (TBC) eliminates the jet bias and substantially increases the precipitation over the Great Plains. These changes are accompanied by much improved (increased) storm-track activity throughout the northern midlatitudes. For the coupled model, the atmospheric TBCs produce substantial improvements in the simulated mean climate and its variability, including a much reduced SST warm bias, more realistic ENSO-related SST variability and teleconnections, and much improved subtropical jets and related submonthly transient wave activity. Despite these improvements, the improvement in subseasonal and seasonal forecast skill over North America is only modest at best. The reasons for this, which are presumably relevant to any forecast system, involve the competing influences of predictability loss with time and the time it takes for climate drift to first have a significant impact on forecast skill.

Using PRIMAVERA high-resolution global climate models for European windstorm risk assessment in present and future climates for the (re)insurance industry

2020 ◽  
Author(s):  
Julia Lockwood ◽  
Erika Palin ◽  
Galina Guentchev ◽  
Malcolm Roberts
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Climate Model ◽  
Insurance Industry ◽  
Global Climate ◽  
Storm Track ◽  
Global Climate Models ◽  
Climate Modelling ◽  
Business And Society ◽  
High Resolution Models

<p>PRIMAVERA is a European Union Horizon2020 project about creating a new generation of advanced and well-evaluated high-resolution global climate models, for the benefit of governments, business and society in general. The project has been engaging with several sectors, including finance, transport, and energy, to understand the extent to which any improved process understanding arising from high-resolution global climate modelling can – in turn – help with using climate model output to address user needs.</p><p>In this talk we will outline our work for the finance and (re)insurance industries.  Following consultation with members of the industry, we are using PRIMAVERA climate models to generate a European windstorm event set for use in catastrophe modelling and risk analysis.  The event set is generated from five different climate models, each run at a selection of resolutions ranging from 18-140km, covering the period 1950-2050, giving approximately 1700 years of climate model data in total.  High-resolution climate models tend to have reduced biases in storm track position (which is too zonal in low-resolution climate models) and windstorm intensity.  We will compare the properties of the windstorm footprints and associated risk across the different models and resolutions, to assess whether the high-resolution models lead to improved estimation of European windstorm risk.  We will also compare windstorm risk in present and future climates, to see if a consistent picture emerges between models.  Finally we will address the question of whether the event sets from each PRIMAVERA model can be combined to form a multi-model event set ensemble covering thousands of years of windstorm data.</p>

scholarly journals Effects of Convective Gravity Wave Drag in the Southern Hemisphere Winter Stratosphere

2013 ◽  
Vol 70 (7) ◽  
pp. 2120-2136 ◽  
Author(s):  
Hyun-Joo Choi ◽  
Hye-Yeong Chun
Keyword(s):  
Gravity Wave ◽  
Southern Hemisphere ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Storm Track ◽  
Wave Drag ◽  
Global Climate Models ◽  
Systematic Biases ◽  
Hemisphere Winter

Abstract The excessively strong polar jet and cold pole in the Southern Hemisphere winter stratosphere are systematic biases in most global climate models and are related to underestimated wave drag in the winter extratropical stratosphere—namely, missing gravity wave drag (GWD). Cumulus convection is strong in the winter extratropics in association with storm-track regions; thus, convective GWD could be one of the missing GWDs in models that do not adopt source-based nonorographic GWD parameterizations. In this study, the authors use the Whole Atmosphere Community Climate Model (WACCM) and show that the zonal-mean wind and temperature biases in the Southern Hemisphere winter stratosphere of the model are significantly alleviated by including convective GWD (GWDC) parameterizations. The reduction in the wind biases is due to enhanced wave drag in the winter extratropical stratosphere, which is caused directly by the additional GWDC and indirectly by the increased existing nonorographic GWD and resolved wave drag in response to the GWDC. The cold temperature biases are alleviated by increased downwelling in the winter polar stratosphere, which stems from an increased poleward motion due to enhanced wave drag in the winter extratropical stratosphere. A comparison between two simulations separately using the ray-based and columnar GWDC parameterizations shows that the polar night jet with a ray-based GWDC parameterization is much more realistic than that with a columnar GWDC parameterization.

Simulations of 20th and 21st century Arctic cloud amount in the global climate models assessed in the IPCC AR4

2008 ◽  
Vol 33 (7-8) ◽  
pp. 1099-1115 ◽  
Author(s):  
Steve Vavrus ◽  
Duane Waliser ◽  
Axel Schweiger ◽  
Jennifer Francis
Keyword(s):  
21St Century ◽  
Climate Models ◽  
Global Climate ◽  
Cloud Amount ◽  
Global Climate Models ◽  
Ipcc Ar4

scholarly journals Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models

2018 ◽  
Vol 18 (2) ◽  
pp. 1395-1417 ◽  
Author(s):  
Tianyi Fan ◽  
Xiaohong Liu ◽  
Po-Lun Ma ◽  
Qiang Zhang ◽  
Zhanqing Li ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Secondary Production ◽  
Emission Inventory ◽  
Climate Models ◽  
Global Climate ◽  
Eastern China ◽  
Global Climate Models ◽  
Radiative Effects ◽  
Production Processes ◽  
Secondary Aerosols

Abstract. Global climate models often underestimate aerosol loadings in China, and these biases can have significant implications for anthropogenic aerosol radiative forcing and climate effects. The biases may be caused by either the emission inventory or the treatment of aerosol processes in the models, or both, but so far no consensus has been reached. In this study, a relatively new emission inventory based on energy statistics and technology, Multi-resolution Emission Inventory for China (MEIC), is used to drive the Community Atmosphere Model version 5 (CAM5) to evaluate aerosol distribution and radiative effects against observations in China. The model results are compared with the model simulations with the widely used Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) emission inventory. We find that the new MEIC emission improves the aerosol optical depth (AOD) simulations in eastern China and explains 22–28 % of the AOD low bias simulated with the AR5 emission. However, AOD is still biased low in eastern China. Seasonal variation of the MEIC emission leads to a better agreement with the observed seasonal variation of primary aerosols than the AR5 emission, but the concentrations are still underestimated. This implies that the atmospheric loadings of primary aerosols are closely related to the emission, which may still be underestimated over eastern China. In contrast, the seasonal variations of secondary aerosols depend more on aerosol processes (e.g., gas- and aqueous-phase production from precursor gases) that are associated with meteorological conditions and to a lesser extent on the emission. It indicates that the emissions of precursor gases for the secondary aerosols alone cannot explain the low bias in the model. Aerosol secondary production processes in CAM5 should also be revisited. The simulation using MEIC estimates the annual-average aerosol direct radiative effects (ADREs) at the top of the atmosphere (TOA), at the surface, and in the atmosphere to be −5.02, −18.47, and 13.45 W m−2, respectively, over eastern China, which are enhanced by −0.91, −3.48, and 2.57 W m−2 compared with the AR5 emission. The differences of ADREs by using MEIC and AR5 emissions are larger than the decadal changes of the modeled ADREs, indicating the uncertainty of the emission inventories. This study highlights the importance of improving both the emission and aerosol secondary production processes in modeling the atmospheric aerosols and their radiative effects. Yet, if the estimations of MEIC emissions in trace gases do not suffer similar biases to those in the AOD, our findings will help affirm a fundamental error in the conversion from precursor gases to secondary aerosols as hinted in other recent studies following different approaches.

scholarly journals Changing Northern Hemisphere Storm Tracks in an Ensemble of IPCC Climate Change Simulations

2008 ◽  
Vol 21 (8) ◽  
pp. 1669-1679 ◽  
Author(s):  
U. Ulbrich ◽  
J. G. Pinto ◽  
H. Kupfer ◽  
G. C. Leckebusch ◽  
T. Spangehl ◽  
...  
Keyword(s):  
Climate Change ◽  
Northern Hemisphere ◽  
Climate Models ◽  
Global Climate ◽  
Storm Track ◽  
Global Climate Models ◽  
The North ◽  
Storm Track Activity ◽  
Eastern North Atlantic ◽  
The Individual

Abstract Winter storm-track activity over the Northern Hemisphere and its changes in a greenhouse gas scenario (the Special Report on Emission Scenarios A1B forcing) are computed from an ensemble of 23 single runs from 16 coupled global climate models (CGCMs). All models reproduce the general structures of the observed climatological storm-track pattern under present-day forcing conditions. Ensemble mean changes resulting from anthropogenic forcing include an increase of baroclinic wave activity over the eastern North Atlantic, amounting to 5%–8% by the end of the twenty-first century. Enhanced activity is also found over the Asian continent and over the North Pacific near the Aleutian Islands. At high latitudes and over parts of the subtropics, activity is reduced. Variations of the individual models around the ensemble average signal are not small, with a median of the pattern correlation near r = 0.5. There is, however, no evidence for a link between deviations in present-day climatology and deviations with respect to climate change.

scholarly journals Evaluation of Hemispheric Asymmetries in Marine Cloud Radiative Properties

2017 ◽  
Vol 30 (11) ◽  
pp. 4131-4147 ◽  
Author(s):  
Frida A.-M. Bender ◽  
Anders Engström ◽  
Robert Wood ◽  
Robert J. Charlson
Keyword(s):  
Hemispheric Asymmetry ◽  
Climate Models ◽  
Global Climate ◽  
Cloud Amount ◽  
Cloud Fraction ◽  
Global Climate Models ◽  
Radiative Properties ◽  
Contributing Factors ◽  
Cloud Albedo ◽  
Clear Sky

Abstract The hemispheric symmetry of albedo and its contributing factors in satellite observations and global climate models is evaluated. The analysis is performed on the annual mean time scale, on which a bimodality in the joint distribution of albedo and cloud fraction is evident, resulting from tropical and subtropical clouds and midlatitude clouds, respectively. Hemispheric albedo symmetry is not found in individual ocean-only latitude bands; comparing the Northern and Southern Hemisphere (NH and SH), regional mean albedo is higher in the NH tropics and lower in the NH subtropics and midlatitudes than in the SH counterparts. This follows the hemispheric asymmetry of cloud fraction. In midlatitudes and tropics the hemispheric asymmetry in cloud albedo also contributes to the asymmetry in total albedo, whereas in the subtropics the cloud albedo is more hemispherically symmetric. According to the observations, cloud contributions to compensation for higher clear-sky albedo in the NH come primarily from cloud albedo in midlatitudes and cloud amount in the subtropics. Current-generation climate models diverge in their representation of these relationships, but common features of the model–data comparison include weaker-than-observed asymmetry in cloud fraction and cloud albedo in the tropics, weaker or reversed cloud fraction asymmetry in the subtropics, and agreement with observed cloud albedo asymmetry in the midlatitudes. Models on average reproduce the NH–SH asymmetry in total albedo over the 60°S–60°N ocean but show higher occurrence of brighter clouds in the SH compared to observations. The albedo bias in both hemispheres is reinforced by overestimated clear-sky albedo in the models.

Using a Multiphysics Ensemble for Exploring Diversity in Cloud–Shortwave Feedback in GCMs

2012 ◽  
Vol 25 (15) ◽  
pp. 5416-5431 ◽  
Author(s):  
Masahiro Watanabe ◽  
Hideo Shiogama ◽  
Tokuta Yokohata ◽  
Youichi Kamae ◽  
Masakazu Yoshimori ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Cloud Amount ◽  
Global Climate Models ◽  
Intercomparison Project ◽  
The Mean ◽  
Radiative Feedbacks ◽  
The Tropics

Abstract This study proposes a systematic approach to investigate cloud-radiative feedbacks to climate change induced by an increase of CO2 concentrations in global climate models (GCMs). Based on two versions of the Model for Interdisciplinary Research on Climate (MIROC), which have opposite signs for cloud–shortwave feedback (ΔSWcld) and hence different equilibrium climate sensitivities (ECSs), hybrid models are constructed by replacing one or more parameterization schemes for cumulus convection, cloud, and turbulence between them. An ensemble of climate change simulations using a suite of eight models, called a multiphysics ensemble (MPE), is generated. The MPE provides a range of ECS as wide as the Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel ensemble and reveals a different magnitude and sign of ΔSWcld over the tropics, which is crucial for determining ECS. It is found that no single process controls ΔSWcld, but that the coupling of two processes does. Namely, changing the cloud and turbulence schemes greatly alters the mean and the response of low clouds, whereas replacing the convection and cloud schemes affects low and middle clouds over the convective region. For each of the circulation regimes, ΔSWcld and cloud changes in the MPE have a nonlinear, but systematic, relationship with the mean cloud amount, which can be constrained from satellite estimates. The analysis suggests a positive feedback over the subsidence regime and a near-neutral or weak negative ΔSWcld over the convective regime in these model configurations, which, however, may not be carried into other models.

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