Sensitivity Study of Aerosol Direct Radiative Effects on Cloudy EarthCARE Scenes Using 1D and 3D Radiative Transfer Simulations
Bibliographic record
Abstract
The upcoming EarthCARE (Earth Cloud, Aerosol and Radiation Explorer) satellite mission will provide concurrent inferences of aerosol, cloud, and precipitation properties along with radiative fluxes and heating rate profiles. This is essential information to evaluate the representation of all these variables in weather forecasting and climate models and advance our knowledge about cloud and aerosol radiative effects and feedback mechanisms (Wehr et al. 2023). EarthCARE is the first mission to make “operational” use of 3D radiative transfer (RT) models, as well as conventional 1D models. These models will simulate measurements (made and inferred) by EarthCARE’s broadband radiometer (BBR) and compare them against actual BBR measurements in order to assess the quality of aerosol and cloud retrievals derive from other instruments onboard EarthCARE. The scientific goal of the EarthCARE mission is to retrieve cloud and aerosol properties well enough that when used in 3D RT models, predicted and “observed” fluxes differ, on average, by less than ±10 W/m2. This will be a continuous radiative closure assessment of the L2 products, which will be important for both L2-algorithm developers and data users. The RT models to be used, along with their official products, are described in Cole et al. (2023). As pointed out by Cole et al. (2023), the 1D and 3D RT calculations for upwelling shortwave fluxes at 20 km can be expected to differ by more than the target scientific goal in at least 50% of the cases. The assessment of aerosol direct radiative effects on cloudy atmospheres is a difficult task as their properties, which vary with altitude, impact atmospheric RT. The objective of the present study is to use RT models to quantify these effects for 1D and 3D scenes using different vertical distributions of aerosols. The libRadtran RT package (Mayer & Kylling, 2005; Emde et al., 2016) will be used along with its MYSTIC (Mayer 2009) solver for 3D RT simulations. This sensitivity study will employ data from the Halifax, Baja, and Hawaii EarthCARE test frames (~6,200 km-long). For selected cloud scenes, artificial aerosol layers (above and below clouds) will be generated. Differences in simulated shortwave and longwave fluxes and heating rate profiles, along with top of atmosphere radiances, will be evaluated and discussed for different aerosol optical properties based on different aerosol types and their varying vertical distributions. Outcomes of this study will be useful for future radiative closure assessments of EarthCARE using ground-based measurements of aerosol and cloud profiles, thus contributing to post-launch Cal/Val activities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".