A global view on stratospheric ice clouds: assessment of processes related to their occurrence based on satellite observations
Bibliographic record
Abstract
Abstract. Ice clouds play an important role in regulating water vapor and influencing the radiative budget in the atmosphere. In this study, stratospheric ice clouds (SICs) and stratospheric aerosols from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), deep convection and gravity waves from Atmospheric Infrared Sounder (AIRS) observations and tropopause temperature from ERA5 are analyzed to investigate their long-term variation and processes potentially related to the formation of SICs on the global scale. SICs with cloud top heights 0.25 km above the first tropopause are mainly detected over the tropical continents. SICs associated with the double tropopause events, where the cloud top is between the first and second thermal tropopause, are mostly located in midlatitudes (between 25°–60°). The seasonal cycle and the inter-annual variability of SIC frequencies from 2007 to 2019 show that high SIC frequencies are mainly observed south of the equator from November to March, and at 10° N–20° N from July to September. At mid- and high latitudes, more SICs are observed from December to May in the northern hemisphere and in the southern hemisphere during May to October. Relations between SICs and first tropopause temperature, deep convection, gravity waves, and stratospheric aerosol were analyzed, respectively, on a global scale. Positive correlations between SIC frequencies and deep convection, gravity waves, and stratospheric aerosol and an inverse correlation between SIC frequency and tropopause temperature were observed worldwide. Overlaps of high correlations/anti-correlations were detected over tropical continents, i.e., tropical South America, equatorial Africa, and western Pacific, suggesting a combined effect of tropopause temperature, deep convection, gravity waves, and stratospheric aerosol on SIC occurrence in these regions. Over Central America, North America, the Asian Monsoon, and mid- and high latitudes deep convection and gravity waves present a strong correlation with the occurrence of SICs, individually or interdependently. Regional analyses demonstrated specific relations of tropopause temperature, deep convection, gravity waves, and stratospheric aerosol with SICs at a finer scale. Low tropopause temperature and high occurrence frequency of stratospheric aerosol show strong correlations with high frequencies of SICs over the Indo-Pacific Warm Pool, tropical South America, and equatorial Africa. Deep convection and gravity waves have the strongest correlation with the occurrence frequency of SICs over the Asian Monsoon and the North American Monsoon. Gravity waves and tropopause temperature are highly correlated with SIC occurrence over South America and the northern Atlantic. Moreover, the El Niño phenomenon in 2009–2010 and 2015–2016 coincides with low SIC occurrences over the Indo-Pacific Warm Pool. High stratospheric aerosol loads related to volcanic eruptions (Puyehue-Cordón Caulle and Nabro in 2011) and wildfires (over the United States and Canada in 2017) are closely related to high occurrence frequencies of SICs. We investigated the global distribution and long-term variation of SICs and present a global view of relations between SIC occurrence and tropopause temperature, deep convection, gravity wave activity, and stratospheric aerosol. This work provides a better understanding of the physical processes and climate variability of SICs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".