An evaluation of cloud vertical structure in three reanalyses against CloudSat/cloud‐aerosol lidar and infrared pathfinder satellite observations

Hao, Miao; Wang, Xiaocong; Liu, Yimin; Wu, Guoxiong

doi:10.1002/asl.906

Cited by 34 publications

(27 citation statements)

References 33 publications

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“…Since 2006, with the launch of the CloudSat and CALIPSO satellites, the vertical structure of clouds and their radiative effects over the TP have been the focus of considerable research interest [ 130 , 131 ]. However, current climate models and even reanalysis systems still cannot simulate adequately the vertical structure of clouds [ 132 ]. To improve simulations of clouds and precipitation over the TP, additional efforts are required to reveal the roles of the physical processes of both the planetary boundary layer and the underlying surface of the TP in shaping shallow and deep convective clouds.…”

Section: Prospectsmentioning

confidence: 99%

Land–atmosphere–ocean coupling associated with the Tibetan Plateau and its climate impacts

Liu

Yang

et al. 2020

National Science Review

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143

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This paper reviews recent advances regarding land–atmosphere–ocean coupling associated with the Tibetan Plateau (TP) and its climatic impacts. Thermal forcing over the TP interacts strongly with that over the Iranian Plateau, forming a coupled heating system that elevates the tropopause, generates a monsoonal meridional circulation over South Asia and creates conditions of large-scale ascent favorable for Asian summer monsoon development. TP heating leads to intensification and westward extension (northward movement) of the South Asian High (Atlantic Intertropical Convergence Zone), and exerts strong impacts on upstream climate variations from North Atlantic to West Asia. It also affects oceanic circulation and buoyancy fields via atmospheric stationary wave trains and air–sea interaction processes, contributing to formation of the Atlantic Meridional Overturning Circulation. The TP thermal state and atmospheric–oceanic conditions are highly interactive and Asian summer monsoon variability is controlled synergistically by internal TP variability and external forcing factors.

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Section: Prospectsmentioning

confidence: 99%

Land–atmosphere–ocean coupling associated with the Tibetan Plateau and its climate impacts

Liu

Yang

et al. 2020

National Science Review

Self Cite

143

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“…The accuracy of the shortwave radiation variable from the MERRA-2 product over Africa was recently evaluated against four ground stations in Ethiopia by Stettz et al (2019), who reported a good agreement between the climate reanalysis data and the observed data. Miao et al (2019) compared the cloud cover of MERRA-2 with Cloud-Sat/CALIPSO data, showing that the MERRA-2 underestimates the cloud cover for the ZRB region by a maximum of 10%. Torralba et al (2017) compared the wind speed trends from MERRA-2 and JRA-55 climate reanalysis products, concluding that the two products yield similar trends, thus suggesting MERRA-2 to be a good data source to evaluate the wind speed at 850 hPa.…”

Section: Present Climate Datamentioning

confidence: 99%

“…Miao et al . (2019) compared the cloud cover of MERRA‐2 with Cloud‐Sat/CALIPSO data, showing that the MERRA‐2 underestimates the cloud cover for the ZRB region by a maximum of 10%. Torralba et al .…”

Section: Datamentioning

confidence: 99%

Downscaling climate projections over large and data sparse regions: Methodological application in the Zambezi River Basin

Peleg

Sinclair

Fatichi

et al. 2020

Intl Journal of Climatology

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Climate impact studies often require climate data at a higher space-time resolution than is available from global and regional climate models. Weather generator (WG) models, generally designed for mesoscale applications (e.g., 10 1-10 5 km 2), are popular and widely used tools to downscale climate data to finer resolution. One advantage of using WGs is their ability to generate the necessary climate variables for impact studies in data sparse regions. In this study, we evaluate the ability of a previously established state of the art WG (the AWE-GEN-2d model) to perform in data sparse regions that are beyond the mesoscale, using the Zambezi River basin (10 6 km 2) in southeast Africa as a case study. The AWE-GEN-2d model was calibrated using data from satellite retrievals and climate re-analysis products in place of the absent observational data. An 8-km climate ensemble at hourly resolution, covering the period of 1976-2099 (present climate and RCP4.5 emission scenario from 2020), was then simulated. Using the simulated 30-member ensemble, climate indices for both present and future climates were computed. The high-resolution climate indices allow detailed analysis of the effects of climate change on different areas within the basin. For example, the southwestern area of the basin is predicted to experience the greatest change due to increased temperature, while the southeastern area was found to be already so hot that is less affected (e.g., the number of 'very hot days' per year increase by 18 and 9 days, respectively). Rainfall intensities are found to increase most in the eastern areas of the basin (1 mmÁd −1) in comparison to the western region (0.3 mmÁd −1). As demonstrated in this study, AWE-GEN-2d can be calibrated successfully using data from climate reanalysis products in the absence of ground station data and can be applied at larger scales than the mesoscale.

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“…Previous studies have evaluated the cloud amount in reanalysis datasets using ground‐based remote sensing cloud data or satellite cloud data (Bedacht et al., 2010; Chevallier et al., 2005; Jakob, 1997; Naud et al., 2014; Yousef et al., 2020). Miao and Wang (2019) assessed the cloud products of three widely‐used reanalysis data sets, ERA‐Interim, JRA‐55 and MERRA‐2, based on Cloudsat/CALIPSO (Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations). It was found that ERA‐Interim is closest to CloudSat/CALIPSO, but shows considerable underestimation for high clouds.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of High Cloud Product of ECMWF Over South China Sea Using CALIOP

Yang

Zhu

et al. 2022

Earth and Space Science

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High clouds are globally widespread and are crucially important to global radiative processes and to the thermal balance of the Earth. Active remote sensing measurements can provide more reliable detection of optically thin cirrus clouds than passive remote sensing. The reanalysis datasets from European Centre for Medium‐Range Weather Forecasts (ECMWF) have a variety of applications in different branches of atmospheric science. A careful evaluation of these datasets is a prerequisite for their successful use. In this paper, the high cloud product from ECMWF is compared with Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) observations over the South China Sea from December 2006 to February 2019. The annual average of high cloud amount is analyzed and compared between CALIOP and ECMWF day and night, and the monthly comparison is also conducted. The results show that the distributions of high cloudiness in CALIOP and ECMWF are in fairly good agreement over the study area both day and night. The correlation coefficient between the two products is 0.79 during daytime, 0.75 nighttime. 50.8% of high cloud amount from ECMWF is 8.8% lower than 59.6% from CALIOP during daytime. A larger difference of 16.2% occurred at night with 53.9% from ECMWF, and 70.1% from CALIOP. Quantitative analysis of subvisible cirrus clouds (SVC, optical depth <0.03) is given. The results show that the discrepancies between the two data sets are reduced to 2.3% during daytime, and 5.2% at nighttime after screening out SVC. The correlation coefficients also rise to 0.82 both daytime and nighttime. The distribution and occurrence of SVC are presented over the study area.

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An evaluation of cloud vertical structure in three reanalyses against CloudSat/cloud‐aerosol lidar and infrared pathfinder satellite observations

Cited by 34 publications

References 33 publications

Land–atmosphere–ocean coupling associated with the Tibetan Plateau and its climate impacts

Land–atmosphere–ocean coupling associated with the Tibetan Plateau and its climate impacts

Downscaling climate projections over large and data sparse regions: Methodological application in the Zambezi River Basin

Evaluation of High Cloud Product of ECMWF Over South China Sea Using CALIOP

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