Evaluating the Representation of Tropical Stratocumulus and Shallow Cumulus Clouds As Well As Their Radiative Effects in CMIP6 Models Using Satellite Observations

被引:4
|
作者
Crnivec, Nina [1 ,2 ]
Cesana, Gregory [1 ,2 ]
Pincus, Robert [3 ]
机构
[1] Columbia Univ, Ctr Climate Syst Res, New York, NY 10027 USA
[2] NASA Goddard Inst Space Studies, New York, NY 10025 USA
[3] Columbia Univ, Lamont Doherty Earth Observ, Palisades, NY USA
关键词
marine tropical low clouds; stratocumulus; shallow cumulus; radiative effects; climate model validation; satellite observations; A-TRAIN; HEATING RATES; CALIPSO; WEATHER; PARAMETERIZATION; SIMULATIONS; VARIABILITY; MISSION; LAYER; BIAS;
D O I
10.1029/2022JD038437
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Low clouds over tropical oceans reflect a great proportion of solar radiation back to space and thereby cool the Earth, yet this phenomenon has been poorly simulated in several previous generations of climate models. The principal aim of the present study is to employ satellite observations to evaluate the representation of marine tropical low clouds and their radiative effect at the top of the atmosphere in a subset of latest climate models participating in CMIP6. We strive for regime-oriented model validation and hence introduce a qualitative approach to discriminate stratocumulus (Sc) from shallow cumulus (Cu). The novel Sc-Cu categorization has a conceptual advantage of being based on cloud properties, rather than relying on a model response to a cloud-controlling factor. We find that CMIP6 models underestimate low-cloud cover in both Sc-regions and Cu-regions of tropical oceans. A more detailed investigation of cloud biases reveals that most CMIP6 models underestimate the relative frequency of occurrence (RFO) of Sc and overestimate RFO of Cu. We further demonstrate that tropical low cloudiness in CMIP6 models remains too bright. The regime-oriented validation represents the basis for improving parameterizations of physical processes that determine the cloud cover and radiative impact of Sc and Cu, which are still misrepresented in current climate models. Similar as white snow and ice caps, bright low clouds have a high shortwave albedo, reflecting a huge amount of sunlight back to space and thereby helping us counteract global warming. The shadowing effect of bright low clouds is especially pronounced over tropical oceans, since equatorial regions of our planet receive most sunshine, which is in clear skies otherwise practically entirely absorbed within the contrastingly dark ocean. Climate models had traditionally struggled simulating these clouds by underestimating their areal extent and simultaneously overestimating their reflectivity. In other words, simulated clouds were commonly found to be "too few" and "too bright" compared to observations, which introduced a substantial uncertainty to climate projections. Herein, we proposed a novel approach to proficiently decompose tropical low cloudiness into stratocumulus and shallow cumulus regime, which is essential to provide a proper guidance for climate model development. We subsequently showed that the newest generation of climate models still suffers from the "too few, too bright" tropical low-cloud problem within both stratocumulus and shallow cumulus regimes, which thus needs to be further tackled with the greatest possible endeavor. We introduce a new approach to distinguish stratocumulus and shallow cumulus regimes over tropical oceans based on cloud coverThe "too few, too bright" tropical low-cloud problem persists in 12 CMIP6 models within stratocumulus and shallow cumulus regimesMost CMIP6 models underestimate (overestimate) the relative frequency of occurrence of stratocumulus (shallow cumulus)
引用
收藏
页数:14
相关论文
共 50 条
  • [31] Using CMIP6 Models to Assess Future Climate Change Effects on Mine Sites in Kazakhstan
    Golian, Saeed
    El-Idrysy, Houcyne
    Stambuk, Desana
    HYDROLOGY, 2023, 10 (07)
  • [32] Evaluating clouds, aerosols, and their interactions in three global climate models using satellite simulators and observations
    Ban-Weiss, George A.
    Jin, Ling
    Bauer, Susanne E.
    Bennartz, Ralf
    Liu, Xiaohong
    Zhang, Kai
    Ming, Yi
    Guo, Huan
    Jiang, Jonathan H.
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2014, 119 (18) : 10876 - 10901
  • [33] Evaluating the Effects of Climate Change on Thermal Bioclimatic Indices in a Tropical Region Using Climate Projections from the Bias-Corrected CMIP6 Model
    Mohammad Kamruzzaman
    H. M. Touhidul Islam
    Sharif Ahmed
    Debu Kumar Bhattacharjya
    Md. Shah Kamal Khan
    Golam Iftekhar Mahmud
    Mansour Almazroui
    Shamsuddin Shahid
    Earth Systems and Environment, 2023, 7 : 699 - 722
  • [34] Evaluating the Effects of Climate Change on Thermal Bioclimatic Indices in a Tropical Region Using Climate Projections from the Bias-Corrected CMIP6 Model
    Kamruzzaman, Mohammad
    Islam, H. M. Touhidul
    Ahmed, Sharif
    Bhattacharjya, Debu Kumar
    Khan, Md. Shah Kamal
    Mahmud, Golam Iftekhar
    Almazroui, Mansour
    Shahid, Shamsuddin
    EARTH SYSTEMS AND ENVIRONMENT, 2023, 7 (04) : 699 - 722
  • [35] Historic global biomass burning emissions for CMIP6 (BB4CMIP) based on merging satellite observations with proxies and fire models (1750-2015)
    van Marle, Margreet J. E.
    Kloster, Silvia
    Magi, Brian I.
    Marlon, Jennifer R.
    Daniau, Anne-Laure
    Field, Robert D.
    Arneth, Almut
    Forrest, Matthew
    Hantson, Stijn
    Kehrwald, Natalie M.
    Knorr, Wolfgang
    Lasslop, Gitta
    Li, Fang
    Mangeon, Stephane
    Yue, Chao
    Kaiser, Johannes W.
    van der Werf, Guido R.
    GEOSCIENTIFIC MODEL DEVELOPMENT, 2017, 10 (09) : 3329 - 3357
  • [36] Evaluating the effect of the uncertainty of CMIP6 models on extreme flows of the Caspian Hyrcanian forest watersheds using the BMA method
    Lotfirad, Morteza
    Adib, Arash
    Riyahi, Mohammad Mehdi
    Jafarpour, Mohammad
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2023, 37 (02) : 491 - 505
  • [37] Evaluating the effect of the uncertainty of CMIP6 models on extreme flows of the Caspian Hyrcanian forest watersheds using the BMA method
    Morteza Lotfirad
    Arash Adib
    Mohammad Mehdi Riyahi
    Mohammad Jafarpour
    Stochastic Environmental Research and Risk Assessment, 2023, 37 : 491 - 505
  • [38] Evaluating the aptitude of global climate models from CMIP5 and CMIP6 in capturing the historical observations of monsoon rainfall over Sudan from 1946 to 2005
    Hamadalnel, Monzer
    Zhu, Zhiwei
    Lu, Rui
    Almazroui, Mansour
    Shahid, Shamsuddin
    INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2022, 42 (05) : 2717 - 2738
  • [39] Low-Level Marine Tropical Clouds in Six CMIP6 Models Are Too Few, Too Bright but Also Too Compact and Too Homogeneous
    Konsta, Dimitra
    Dufresne, Jean-Louis
    Chepfer, Helene
    Vial, Jessica
    Koshiro, Tsuyoshi
    Kawai, Hideaki
    Bodas-Salcedo, Alejandro
    Roehrig, Romain
    Watanabe, Masahiro
    Ogura, Tomoo
    GEOPHYSICAL RESEARCH LETTERS, 2022, 49 (11)
  • [40] Evaluation and comparison of CMIP6 models and MERRA-2 reanalysis AOD against Satellite observations from 2000 to 2014 over China
    Md.Arfan Ali
    Muhammad Bilal
    Yu Wang
    Zhongfeng Qiu
    Janet E.Nichol
    Gerrit de Leeuw
    Song Ke
    Alaa Mhawish
    Mansour Almazroui
    Usman Mazhar
    Birhanu Asmerom Habtemicheal
    M.Nazrul Islam
    Geoscience Frontiers, 2022, 13 (02) : 171 - 191