Global Spatial and Temporal Variation of the Combined Effect of Aerosol and Water Vapour on Solar Radiation

Muñoz, María Ángeles Obregón; Serrano, A.; Costa, María João; Silva, Ana Maria

doi:10.3390/rs13040708

Cited by 10 publications

(8 citation statements)

References 85 publications

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“…Significant positive trends in AOD over parts of South and Southeast Asia along with a steep trend (+0.014/year or +0.6 mean annual AOD shift in the entire study period) concentrated over India and China can be seen in Figure 3b, which are in the tropical regions of NH. These findings of the spatial pattern of trends are analogous to the trends obtained from the CERES (combined data sets of MODIS and ESM) where the aerosol optical thickness over land is found larger than the ocean (Obreg on et al, 2021). The increasing trends of AOD (Figure 3a), particularly in eastern China, are reported to be due to the underestimation of the recent decline in anthropogenic aerosol trends by CMIP6 during the recent decades (Wang et al, 2021).…”

Section: Spatiotemporal Variations Of Aod Simulations and Their Trendssupporting

confidence: 82%

Aerosol characteristics in CMIP6 models' global simulations and their evaluation with the satellite measurements

Bharath,

Kumar,

Salgueiro

et al. 2023

Intl Journal of Climatology

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Global and regional trends of the Aerosol Optical Depth (AOD) from Coupled Model Intercomparison Project (CMIP) Phase 6 simulations for the study period 1971–2014 were compared against the satellite retrievals and the intermodel variations were analysed. The AOD from multimodel mean (MMM) of eight general circulation models (GCMs) has been evaluated against the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi‐angle Imaging Spectro Radiometer (MISR) AOD for the 2001–2014 period. Angstrom exponents (AE and its first derivative) that represent the size distribution of aerosols are estimated globally from the perturbed initial condition ensemble of MRI‐ESM2‐0 and MPI‐ESM‐1‐2‐HAM models to report the aerosol variations through their size distribution. We found that the global AOD obtained from the MMM8 showed an insignificant decreasing trend, while this trend is significantly positive over the northern tropical region. The MMM8 has overestimated the MODIS AOD over North Africa, India, China, and Australia while this overestimation is confined to North Africa and eastern China when compared against MISR AOD. The absolute percent bias of MMM8 is 28.1% and 24.1% over the globe when compared against MODIS and MISR AOD, respectively. The spatial pattern of AE showed the dominance of fine‐ and coarse‐mode particles during the boreal/austral winter and summer seasons, respectively, that replicate the seasonality of aerosols. The AE derived from MPI‐ESM‐1‐2‐HR demonstrated better agreement with AATSR SU's (Advanced Along Track Scanning Radiometer instrument series, with the algorithm developed by Swansea University) AE (550–870 nm). On the other hand, MRI‐ESM2‐0 consistently underestimated AE across different regions and wavelength ranges, suggesting an over representation of larger aerosol particles in the model's portrayal of aerosol size distribution compared to satellite observations.

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Section: Spatiotemporal Variations Of Aod Simulations and Their Trendssupporting

confidence: 82%

Aerosol characteristics in CMIP6 models' global simulations and their evaluation with the satellite measurements

Bharath,

Kumar,

Salgueiro

et al. 2023

Intl Journal of Climatology

Self Cite

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“…The latter plays a major role in the earth's radiation budget through its complex interaction with clouds and large-scale atmospheric circulation patterns ( Wild et al, 2013 ; Wu et al, 2018 ; Zhao et al, 2020 ). Water vapor absorbs incoming solar radiation and through positive climate feedback, causes heating in the climatic system ( Dessler & Sherwood, 2009 ; Obregón et al, 2021 ). A high increase in precipitation over the Iberian Peninsula during March–May 2020 compared to 2015–2019 mean, resulted in contrasting trends in LST (i.e.…”

Section: Discussionmentioning

confidence: 99%

Impact of COVID-19 induced lockdown on land surface temperature, aerosol, and urban heat in Europe and North America

Parida

Bar

Kaskaoutis

et al. 2021

Sustainable Cities and Society

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The outbreak of SARS CoV-2 (COVID-19) has posed a serious threat to human beings, society, and economic activities all over the world. Worldwide rigorous containment measures for limiting the spread of the virus have several beneficial environmental implications due to decreased anthropogenic emissions and air pollutants, which provide a unique opportunity to understand and quantify the human impact on atmospheric environment. In the present study, the associated changes in Land Surface Temperature (LST), aerosol, and atmospheric water vapor content were investigated over highly COVID-19 impacted areas, namely, Europe and North America. The key findings revealed a large-scale negative standardized LST anomaly during nighttime across Europe (–0.11°C to –2.6°C), USA (–0.70°C) and Canada (–0.27°C) in March–May of the pandemic year 2020 compared to the mean of 2015–2019, which can be partly ascribed to the lockdown effect. The reduced LST was corroborated with the negative anomaly of air temperature measured at meteorological stations (i.e. –0.46°C to –0.96°C). A larger decrease in nighttime LST was also seen in urban areas (by ∼1–2°C) compared to rural landscapes, which suggests a weakness of the urban heat island effect during the lockdown period due to large decrease in absorbing aerosols and air pollutants. On the contrary, daytime LST increased over most parts of Europe due to less attenuation of solar radiation by atmospheric aerosols. Synoptic meteorological variability and several surface-related factors may mask these changes and significantly affect the variations in LST, aerosols and water vapour content. The changes in LST may be a temporary phenomenon during the lockdown but provides an excellent opportunity to investigate the effects of various forcing controlling factors in urban microclimate and a strong evidence base for potential environmental benefits through urban planning and policy implementation.

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“…In the troposphere, PW influences the optical properties of aerosols, which results in water cycles, the transfer of energy, clouds and rain [1][2][3]. By contributing to cloud formation, PW in the atmosphere not only affects the water balance but also significantly affects the heat balance in the atmosphere by modifying radiation through mechanisms such as absorption, scattering and reflection [4]. In clear skies, PW makes up 60% of all natural greenhouse effects and roughly 70% of the total atmospheric irradiance absorbed [5].…”

Section: Introductionmentioning

confidence: 99%

Evaluation and mapping of precipitable water in Southeast Asia using ground-based and satellite data for solar energy application

Sabooding

Taweekun

Fawzi

2023

Preprint

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This article presents column integrated precipitable water (PW) readings from a NASA satellite and fourteen sites of the Aerosol Robotic Network (AERONET). The Terra satellite was compared with that obtained from ground-based observations in the tropics. It was found that the PW from the MODIS aboard the Terra satellite and those obtained from ground-based observations were in good agreement, with a root mean square error (RMSE) of 4.27% and a mean bias error (MBE) of 0.03% for the monthly. Develop empirical model to estimate the PW using data from relative humidity (AIRS) and temperature (AIRS) of ambient air. The model was developed to determine the daily and monthly PW based on PW data obtained from these stations over a 5-year period (2012–2016) and it was then validated against independent data for the previous 4-year period (2017–2020). It can be seen that the monthly PW values calculated using the empirical model had a RMSE of 3.64%. Develop a model2 to allow users to estimate the PW, namely relative humidity (AIRS) and temperature (GLDAS Model) of ambient air. This model2 performs reasonably when tested against an independent data set with the root mean square error (RMSE) and mean bias error (MBE) of 9.30% and − 0.05%, respectively (daily) and 3.58% and 0.02%, respectively (monthly). This research presents PW resource maps generated with the Geographic Information System (GIS) by satellite-based data from the Terra satellite for the 21-year period (2000–2020) and from AIRS (relative humidity and temperature) for the nineteen-year period (2002–2020). According to the monthly PW maps, Southeast Asia's PW values are generally high during the wet season (May to October) and low during the dry season (November to April) and according to the annual PW map, areas near the sea have high PW.

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Global Spatial and Temporal Variation of the Combined Effect of Aerosol and Water Vapour on Solar Radiation

Cited by 10 publications

References 85 publications

Aerosol characteristics in CMIP6 models' global simulations and their evaluation with the satellite measurements

Aerosol characteristics in CMIP6 models' global simulations and their evaluation with the satellite measurements

Impact of COVID-19 induced lockdown on land surface temperature, aerosol, and urban heat in Europe and North America

Evaluation and mapping of precipitable water in Southeast Asia using ground-based and satellite data for solar energy application

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