Articles | Volume 19, issue 23
https://doi.org/10.5194/acp-19-15023-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-19-15023-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Dec 2019
Research article |
| 11 Dec 2019
| 11 Dec 2019
How should we aggregate data? Methods accounting for the numerical distributions, with an assessment of aerosol optical depth
GESTAR, Universities Space Research Association, Columbia, MD, USA
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Kirk D. Knobelspiesse
NASA Goddard Space Flight Center, Greenbelt, MD, USA
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Cited
27 citations as recorded by crossref.
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- Multi-star calibration in starphotometry L. Ivănescu & N. O'Neill 10.5194/amt-16-6111-2023
- Sensitivity of aerosol optical depth trends using long-term measurements of different sun photometers A. Karanikolas et al. 10.5194/amt-15-5667-2022
- Quantification of the dust optical depth across spatiotemporal scales with the MIDAS global dataset (2003–2017) A. Gkikas et al. 10.5194/acp-22-3553-2022
- 15-year variability of desert dust optical depth on global and regional scales S. Logothetis et al. 10.5194/acp-21-16499-2021
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27 citations as recorded by crossref.
- How Long Is Too Long? Variogram Analysis of AERONET Data to Aid Aerosol Validation and Intercomparison Studies A. Sayer 10.1029/2020EA001290
- Arctic spring and summertime aerosol optical depth baseline from long-term observations and model reanalyses – Part 1: Climatology and trend P. Xian et al. 10.5194/acp-22-9915-2022
- Investigating the Spatial and Temporal Limitations for Remote Sensing of Wildfire Smoke Using Satellite and Airborne Imagers During FIREX‐AQ Y. Shi et al. 10.1029/2023JD039085
- A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing A. Sayer et al. 10.5194/amt-13-373-2020
- Climatological‐Scale Analysis of Intensive and Semi‐intensive Aerosol Parameters Derived From AERONET Retrievals Over the Arctic Y. AboEl‐Fetouh et al. 10.1029/2019JD031569
- A comprehensive reappraisal of long-term aerosol characteristics, trends, and variability in Asia S. Jin et al. 10.5194/acp-23-8187-2023
- AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations J. Gliß et al. 10.5194/acp-21-87-2021
- Trends in physical, optical and chemical columnar aerosol characteristics and radiative effects over South and East Asia: Satellite and ground-based observations S. Ramachandran & M. Rupakheti 10.1016/j.gr.2021.09.016
- Integration of GOCI and AHI Yonsei aerosol optical depth products during the 2016 KORUS-AQ and 2018 EMeRGe campaigns H. Lim et al. 10.5194/amt-14-4575-2021
- 15-Year Analysis of Direct Effects of Total and Dust Aerosols in Solar Radiation/Energy over the Mediterranean Basin K. Papachristopoulou et al. 10.3390/rs14071535
- Aerosol optical depth regime over megacities of the world K. Papachristopoulou et al. 10.5194/acp-22-15703-2022
- Detection and analysis of Lhù'ààn Mân' (Kluane Lake) dust plumes using passive and active ground-based remote sensing supported by physical surface measurements S. Sayedain et al. 10.5194/amt-16-4115-2023
- Merging regional and global aerosol optical depth records from major available satellite products L. Sogacheva et al. 10.5194/acp-20-2031-2020
- Spatiotemporal Heterogeneity of Aerosol and Cloud Properties Over the Southeast Atlantic: An Observational Analysis I. Chang et al. 10.1029/2020GL091469
- Model-enforced post-process correction of satellite aerosol retrievals A. Lipponen et al. 10.5194/amt-14-2981-2021
- Efficient and Flexible Aggregation and Distribution of MODIS Atmospheric Products Based on Climate Analytics as a Service Framework J. Zheng et al. 10.3390/rs13173541
- Introducing the MISR level 2 near real-time aerosol product M. Witek et al. 10.5194/amt-14-5577-2021
- Long- and short-term temporal variability in cloud condensation nuclei spectra over a wide supersaturation range in the Southern Great Plains site R. Perkins et al. 10.5194/acp-22-6197-2022
- Monitoring multiple satellite aerosol optical depth (AOD) products within the Copernicus Atmosphere Monitoring Service (CAMS) data assimilation system S. Garrigues et al. 10.5194/acp-22-14657-2022
- Present and future aerosol impacts on Arctic climate change in the GISS-E2.1 Earth system model U. Im et al. 10.5194/acp-21-10413-2021
- Aerosol characteristics from earth observation systems: A comprehensive investigation over South Asia (2000–2019) A. Mhawish et al. 10.1016/j.rse.2021.112410
- Optimal estimation framework for ocean color atmospheric correction and pixel-level uncertainty quantification A. Ibrahim et al. 10.1364/AO.461861
- Multi-star calibration in starphotometry L. Ivănescu & N. O'Neill 10.5194/amt-16-6111-2023
- Sensitivity of aerosol optical depth trends using long-term measurements of different sun photometers A. Karanikolas et al. 10.5194/amt-15-5667-2022
- Quantification of the dust optical depth across spatiotemporal scales with the MIDAS global dataset (2003–2017) A. Gkikas et al. 10.5194/acp-22-3553-2022
- 15-year variability of desert dust optical depth on global and regional scales S. Logothetis et al. 10.5194/acp-21-16499-2021
- Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring C. Chen et al. 10.5194/essd-12-3573-2020
Latest update: 23 Apr 2024
Short summary
Data about the Earth are routinely obtained from satellite observations, model simulations, and ground-based or other measurements. These are at different space and timescales, and it is common to average them to reduce gaps and increase ease of use. The question of how the data should be averaged depends on the underlying distribution of the quantity. This study presents a method for determining how to appropriately aggregate data and applies it to data sets about atmospheric aerosol levels.
Data about the Earth are routinely obtained from satellite observations, model simulations, and...
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