Assessment of AOD by 16 CMIP6 Models Based on Satellite-Derived Dataset from 2000-2014 over Eastern Center China

2021 ◽  
Author(s):  
xiao li ◽  
minghuai wang ◽  
yawen liu ◽  
yiquan jiang ◽  
xinyi dong
Keyword(s):  
Climate Models ◽  
Comprehensive Evaluation ◽  
Global Climate ◽  
Chemical Properties ◽  
Sulfate Aerosol ◽  
Global Climate Models ◽  
Aerosol Concentration ◽  
Central China ◽  
Liquid Water Path ◽  
Simulated Precipitation

<h3>Knowledge of aerosol concentration, type, and physical and chemical properties is necessary to understand their role in Earth’s climate system. However, CMIP6 models’ performance of AOD simulation in China lacks a comprehensive evaluation and the potential improvement for CMIP6 models is still unclear. Here, we assess the performance of CMIP6 models in simulating annual mean AOD climatology and its seasonality over China from 2000 to 2014 and explore the underlying reasons for its performance. Compared with CMIP5, CMIP6 models can better capture the annual mean AOD climatology magnitude over Eastern Central China (ECC) with a notable enhancement of 52.98% due to a significant increase in the dominate sulfate aerosol. However, the majority of CMIP6 models fail to capture the observed inverted “V-like” pattern that depicts two centers of maximum AOD in spring over northeast China (NEC) and in summer over southeast China (SEC), respectively. The deficiency of two maximums by CMIP6 models is separately due to the negative bias in the simulation of organic aerosol (OA) AOD and sulfate AOD. Our analysis suggests that the deviation of simulated precipitation, relative humidity (RH), and liquid water path (LWP) in CMIP6 models contributes to the deviation of simulated sulfate AOD through affecting sulfate aerosol concentration by wet deposition and aqueous-phase production. Therefore, this study illustrates the urgent need to improve AOD simulation in global climate models.</h3>

Projected precipitation changes over China for global warming levels at 1.5°C and 2°C in an ensemble of regional climate simulations: Impact of bias-correction algorithms

2020 ◽  
Author(s):  
Lianyi Guo
Keyword(s):  
Global Warming ◽  
Bias Correction ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Comprehensive Evaluation ◽  
Global Climate ◽  
Regional Climate ◽  
Global Climate Models ◽  
Cumulative Distribution ◽  
Mathematical Framework

<p>Four bias-correction methods, i.e. Gamma Cumulative Distribution Function (GamCDF), Quantile-Quantile Adjustment (QQadj), Equidistant CDF Matching (EDCDF) and Transform CDF (CDF-t), were applied to five daily precipitation datasets over China produced by LMDZ4-regional that was nested into five global climate models (GCMs), BCC-CSM1-1m, CNRM-CM5, FGOALS-g2, IPSL-CM5A-MR and MPI-ESM-MR, respectively. A unified mathematical framework can be used to define the four methods, which helps understanding their nature and essence in identifying the most reliable probability distributions of projected climate. CDF-t is shown to be the best bias-correction algorithm based on a comprehensive evaluation of different rainfall indices. Future precipitation projections corresponds to the global warming levels of 1.5°C and 2°C under RCP8.5 were obtained using the bias correction methods. The multi-algorithm and multi-model ensemble characteristics allow to explore the spreading of results, considered as a surrogate of climate projection uncertainty, and to attribute such uncertainties to different sources. It was found that the spread among bias-correction methods is smaller than that among dynamical downscaling simulations. The four bias-correction methods with CDF-t at the top all reduce the spread among the downscaled results. Future projection using CDF-t is thus considered having higher credibility.</p>

scholarly journals Simulations of the 1979–88 polar climates by global climate models

1995 ◽  
Vol 21 ◽  
pp. 83-90 ◽  
Author(s):  
Biao Chen ◽  
David H. Bromwich ◽  
Keith M. Hines ◽  
Xuguang Pan
Keyword(s):  
Climate Models ◽  
Comprehensive Evaluation ◽  
Global Climate ◽  
Precipitable Water ◽  
Atmospheric Model ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Atmospheric Models ◽  
Sea Level Pressure ◽  
Polar Climate

The simulation of the northern and southern polar climates for 1979–88 by 14 global climate models (GCMs), using the observed monthly averaged sea-surface temperatures and sea-ice extents as boundary conditions, is part of an international effort to determine the systematic errors of atmospheric models under realistic conditions, the so-called Atmospheric Model Intercomparison Project (AMIP), In this study, intercomparison of the models’ simulation of polar climate is discussed in terms of selected surface and vertically integrated monthly averaged quantities, such as sea-level pressure, cloudiness, precipitable water, precipitation and evaporation/sublimation. The results suggest that the accuracy of model-simulated climate features in high latitudes primarily depends on the horizontal resolution and the treatment of physical processes in the GCMs. AMIP offers an unprecedented opportunity for the comprehensive evaluation and validation of current atmospheric models and provides valuable information for model improvement.

The Role of Mesoscale Cellular Convective Cloud Morphologies in Low Cloud Feedbacks 

2021 ◽  
Author(s):  
Isabel L. McCoy ◽  
Daniel T. McCoy ◽  
Robert Wood ◽  
Paquita Zuidema ◽  
Frida A.-M. Bender
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Convective Cloud ◽  
Static Stability ◽  
Reanalysis Data ◽  
Global Climate Models ◽  
Liquid Water Path ◽  
Radiative Impacts ◽  
Low Cloud

<p>Mesoscale cellular convective (MCC) clouds occur in large-scale patterns over the ocean, are prevalent in sub-tropical cloud regions and mid-latitudes, and have important radiative impacts on the climate system. On average, closed MCC clouds have higher albedos than open or disorganized MCC clouds for the same cloud fraction which suggests differences in micro- and macro-physical characteristics between MCC morphologies. Marine cold air outbreaks (MCAOs) influence the development of open MCC clouds and the transition from closed to open MCC clouds in the mid-latitudes. A MCAO index, M, combines atmospheric surface forcing and static stability and can be used to examine global MCC morphology dependencies. MCC cloud morphology occurrence is also expected to shift with sea surface temperature (SST) changes as the climate warms. Analysis of MCC identifications (derived from a neural network classifier applied to MODIS satellite collection 6 liquid water path retrievals) and ECMWF ERA5 reanalysis data shows that closed MCC cloud occurrence shifts to open or disorganized MCC within an M-SST space. Global climate models (GCMs) predict that M will change regionally in strength as SSTs increase. Based on our derived MCC-M-SST relationship in the current climate, closed MCC occurrence frequency is expected to increase with a weakening of M but decrease with an increase in SSTs. This results in a shift to cloud morphologies with lower albedos. Cloud controlling factor analysis is used to estimate the resulting low cloud morphology feedback which is found to be spatially varied and between ±0.15 W m<sup>-2</sup> K<sup>-1</sup>. Because the morphology feedback is estimated to be positive in the extra-tropics and is not currently represented in GCMs, this implies a higher climate sensitivity than GCMs currently estimate.</p>

scholarly journals Simulations of the 1979–88 polar climates by global climate models

1995 ◽  
Vol 21 ◽  
pp. 83-90 ◽  
Author(s):  
Biao Chen ◽  
David H. Bromwich ◽  
Keith M. Hines ◽  
Xuguang Pan
Keyword(s):  
Climate Models ◽  
Comprehensive Evaluation ◽  
Global Climate ◽  
Precipitable Water ◽  
Atmospheric Model ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Atmospheric Models ◽  
Sea Level Pressure ◽  
Polar Climate

The simulation of the northern and southern polar climates for 1979–88 by 14 global climate models (GCMs), using the observed monthly averaged sea-surface temperatures and sea-ice extents as boundary conditions, is part of an international effort to determine the systematic errors of atmospheric models under realistic conditions, the so-called Atmospheric Model Intercomparison Project (AMIP), In this study, intercomparison of the models’ simulation of polar climate is discussed in terms of selected surface and vertically integrated monthly averaged quantities, such as sea-level pressure, cloudiness, precipitable water, precipitation and evaporation/sublimation. The results suggest that the accuracy of model-simulated climate features in high latitudes primarily depends on the horizontal resolution and the treatment of physical processes in the GCMs. AMIP offers an unprecedented opportunity for the comprehensive evaluation and validation of current atmospheric models and provides valuable information for model improvement.

scholarly journals On the link between precipitation and the ice water path over tropical and mid-latitude regimes as derived from satellite observations

2017 ◽  
Author(s):  
Yaniv Tubul ◽  
Ilan Koren ◽  
Orit Altaratz ◽  
Reuven H. Heiblum
Keyword(s):  
Power Law ◽  
Climate Models ◽  
Global Climate ◽  
Mean Value ◽  
Global Climate Models ◽  
Liquid Water Path ◽  
Water Path ◽  
Local Means ◽  
Ice Water Path ◽  
Ice Water

Abstract. In this study, we explored the link between clouds’ integrated water content and surface rain rate (RR), focusing on deep convective clouds with iced tops. We used a 3-year (2006–2008) global dataset of cloud properties and precipitation rates retrieved from the MODerate-Resolution Imaging Spectroradiometer (MODIS) on Aqua and the Tropical Rain Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA). Previous studies focusing on marine stratocumulus clouds showed a robust link between liquid water path and drizzle rates, in the form of a power law. Consistent with this, we show a quantified link between ice water path (IWP) and surface RR. To reduce the problem to one non-dimensional variable (the power law exponent, β), the IWP and RR were normalized by their local means. We examined the geographical variability of β, and found its mean value to be 1.03 ± 0.13 (1.04 ± 0.12) in the tropics and 1.19 ±  0.19 (1.26 ± 0.20) over the mid-latitudes, during June–August (December–February). The results over the tropical belt showed the best correlation (R2 > 0.9) and lowest standard deviation values, thus the estimations of RR based on IWP measurements for this area are expected to be the most reliable. Such a method offers an estimation of RR using IWP information measured by passive polar-orbiting sensors (such as MODIS). Moreover, it can aid in parameterizing rain properties in regional and global climate models. To enable use of this method, we provide global maps (for June–August) of the required parameters to calculate RR using IWP data.

scholarly journals A Regime-Oriented Approach to Observationally Constraining Extratropical Shortwave Cloud Feedbacks

2020 ◽  
Vol 33 (23) ◽  
pp. 9967-9983
Author(s):  
Daniel T. McCoy ◽  
Paul Field ◽  
Alejandro Bodas-Salcedo ◽  
Gregory S. Elsaesser ◽  
Mark D. Zelinka
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Moisture Flux ◽  
Global Climate Models ◽  
Sea Surface ◽  
Liquid Water Path ◽  
Cloud Feedbacks ◽  
Intercomparison Project ◽  
Cloud Liquid Water Path

AbstractThe extratropical shortwave (SW) cloud feedback is primarily due to increases in extratropical liquid cloud extent and optical depth. Here, we examine the response of extratropical (35°–75°) marine cloud liquid water path (LWP) to a uniform 4-K increase in sea surface temperature (SST) in global climate models (GCMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and variants of the HadGEM3-GC3.1 GCM. Compositing is used to partition data into periods inside and out of cyclones. The response of extratropical LWP to a uniform SST increase and associated atmospheric response varies substantially among GCMs, but the sensitivity of LWP to cloud controlling factors (CCFs) is qualitatively similar. When all other predictors are held constant, increasing moisture flux drives an increase in LWP. Increasing SST, holding all other predictors fixed, leads to a decrease in LWP. The combinations of these changes lead to LWP, and by extension reflected SW, increasing with warming in both hemispheres. Observations predict an increase in reflected SW over oceans of 0.8–1.6 W m−2 per kelvin SST increase (35°–75°N) and 1.2–1.9 W m−2 per kelvin SST increase (35°–75°S). This increase in reflected SW is mainly due to increased moisture convergence into cyclones because of increasing available moisture. The efficiency at which converging moisture is converted into precipitation determines the amount of liquid cloud. Thus, cyclone precipitation processes are critical to constraining extratropical cloud feedbacks.

scholarly journals Reducing the aerosol forcing uncertainty using observational constraints on warm rain processes

2020 ◽  
Vol 6 (22) ◽  
pp. eaaz6433 ◽  
Author(s):  
Johannes Mülmenstädt ◽  
Christine Nam ◽  
Marc Salzmann ◽  
Jan Kretzschmar ◽  
Tristan S. L’Ecuyer ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Observational Constraints ◽  
Observational Constraint ◽  
Liquid Water Path ◽  
Anthropogenic Aerosols ◽  
Aerosol Forcing ◽  
Warm Rain ◽  
Atmospheric State

Global climate models (GCMs) disagree with other lines of evidence on the rapid adjustments of cloud cover and liquid water path to anthropogenic aerosols. Attempts to use observations to constrain the parameterizations of cloud processes in GCMs have failed to reduce the disagreement. We propose using observations sensitive to the relevant cloud processes rather than only to the atmospheric state and focusing on process realism in the absence of aerosol perturbations in addition to the process susceptibility to aerosols. We show that process-sensitive observations of precipitation can reduce the uncertainty on GCM estimates of rapid cloud adjustments to aerosols. The feasibility of an observational constraint depends on understanding the precipitation intensity spectrum in both observations and models and also on improving methods to compare the two.

scholarly journals Improving the treatment of subgrid cloud variability in warm rain simulation in CESM2

2021 ◽  
Author(s):  
Hao Wang ◽  
Minghuai Wang ◽  
Daniel Rosenfeld ◽  
Yannian Zhu ◽  
Zhibo Zhang
Keyword(s):  
Liquid Water ◽  
Climate Models ◽  
Global Climate ◽  
Liquid Water Content ◽  
Global Climate Models ◽  
Liquid Water Path ◽  
Cloud Properties ◽  
Warm Rain ◽  
Rain Simulation ◽  
Warm Rain Process

<p>Representing subgrid variability of cloud properties has always been a challenge in global climate models (GCMs). In microphysics schemes, the effects of subgrid cloud variability on warm rain process rates calculated based on mean cloud properties are usually accounted for by scaling process rates by an enhancement factor (EF) that is derived from the subgrid variance of cloud water. In our study, we find that the EF derived from Cloud Layers Unified by Binormals (CLUBB) in Community Earth System Model Version 2 (CESM2) is severely overestimated in most of the oceanic areas, which leads to the strong overestimation in the autoconversion rate. Through an EF formula based on empirical fitting of MODIS, we improve the EF in the liquid phase clouds. Results show that the model has a more reasonable relationship between autoconversion rate, cloud liquid water content (LWC), and droplet number concentration (CDNC) in warm rain simulation. The annual mean liquid cloud fraction (LCF), liquid water path (LWP), and CDNC show obvious increases for marine stratocumulus, where the probability of precipitation (POP) shows an obvious decrease. The annual mean LCF, cloud optical thickness (COT), and shortwave cloud forcing (SWCF) match better with observation. The sensitivity of LWP to aerosol decreases obviously. The sensitivities of LCF, LWP, cloud top droplet effective radius (CER), and COT to aerosol are in better agreement with MODIS, but the model still underestimates the response of cloud albedo to aerosol. These results indicate the importance of representing reasonable subgrid cloud variabilities in the simulation of cloud properties and aerosol-cloud interaction in climate models.</p>

Extreme Events in High Resolution CMCC Regional and Global Climate Models

2011 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Antonella Sanna ◽  
Edoardo Bucchignani ◽  
Myriam Montesarchio
Keyword(s):  
High Resolution ◽  
Extreme Events ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models

TWO SECONDARY SCIENCE TEACHERS IMPLEMENTATION OF A CURRICULAR INTERVENTION WHEN TEACHING WITH GLOBAL CLIMATE MODELS

2019 ◽  
Author(s):  
Kimberly Carroll Steward ◽  
◽  
Devarati Bhattacharya ◽  
Cory Forbes ◽  
Mark Chandler
Keyword(s):  
Science Teachers ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Secondary Science ◽  
Curricular Intervention ◽  
Secondary Science Teachers
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