Thursday, 31 August 2023

COLD OUTBREAKS NOT CAUSED BY ‘GLOBAL WARMING’

Aug. 31, 2023 CAP ALLON


What the catastrophists always seem to forget is that summer doesn’t last forever; that the brutality of winter is never more than a handful of months away.

The winter of 2023-24 is expected to be a harsh one by most metrics and forecasts, including both the Old and ‘New’ Almanacs–though I would consider the cumulative effect of decades of waning solar activity (since around 2008) to be the informative forcing, not necessarily the chicken bones, caterpillar coats and other weather lore that the Old Farmer’s Almanac relies on.

And so it needs reminding: the looming Arctic outbreaks that will accompany the next 6-or-so months ARE NOT in any way, shape, or form tied to ‘global boiling’, as is increasingly claimed by AGW proponents, likely correlating with the outbreaks’ increasing regularity and so their requirement for a narrative-appeasing explanation.

These descending Arctic fronts, or “polar vortex” as the MSM have confusingly dubbed them, are linked to a weakening of the jet stream, tied to the output of the Sun: less solar energy entering the jets reverts their flow from a tight and stable ‘ZONAL’ flow to weak and wavy ‘MERIDIONAL’ one:

The following is pertinent segment of a Dr. Jay Lehr and Tom Harris article:

What do heat waves, floods, droughts, rising sea levels, forest fires, hurricanes, African wars, mass extinctions, disease outbreaks, and human and animal migrations from South America and the Middle East have in common? According to climate activists, they are all caused by dangerous man-made global warming. And this, in turn, is supposedly caused by rising carbon dioxide (CO2) levels resulting from our use of fossil fuels.

They might as well add alien invasions to the list, because it is all nonsense. Indeed, the climate scare industry has achieved such a level of absurdity that, on February 1, journalist Andrew Revkin reported in a National Geographic article that, “Many stories in recent days highlighted studies concluding that global warming is boosting the odds of cold [weather] outbreaks.”

Among the most absurd of recent climate alarm statements attributing recent cold spells to manmade global warming is one from University of Michigan professor emeritus of environment and sustainability Donald Scavia, who said: “In the past there was a very strong gradient of cold air at the poles and warmer air south of the poles. That gradient kept the cold where it is…. As the poles are warming faster than the rest of the planet, that gradient weakens, allowing the cold air currents to dip south.”

Dr. Tim Ball, an environmental consultant and former climatology professor at the University of Winnipeg in Manitoba, said that Scavia’s statement “is utter rubbish.” Ball explained, “It’s wrong in every aspect, from the basic assumption to the interpretation. In fact, a gradient makes things move. It doesn’t ‘keep the cold where it is.’“

It’s also a mistake to think that, if human-produced CO2 is actually causing global warming, the poles will warm first. “There is no evidence of that; they just are assuming it to be the case,” Dr. Ball emphasized.

And, if the poles did warm first, Ball explained, the reduced temperature difference between the poles and lower latitude regions would reduce extreme weather events, not intensify them, as climate campaigners claim. After all, weather and extreme weather events are driven by the temperature gradient between latitudes. A warming Arctic would result in less intense cold outbreaks and a lesser intrusion of cold arctic air colliding with warm moist air in warmer regions. Climate alarmists have their science backwards.

Ball noted that the real cause of the severe cold outbreaks in the United States is a wavy Jet Stream.

The Jet Stream is a thin band of strong winds that flow rapidly around the planet from west to east at approximately 10 km altitude. The Jet Stream divides warm air masses, typically found at low latitudes towards the tropics, from cold air masses, usually found at high latitudes near the poles.

However, a very wavy jet stream, as we are experiencing now, allows frigid Arctic air to move south to normally warmer latitudes and warm tropical air to push into Polar latitudes. The result is an increase in extreme weather events, including the cold outbreaks in the USA. It has nothing to do with global warming. In fact, the most common cause of a wavy Jet Stream is global cooling. History shows that severe weather increases with a cooling world, not a warming one.

As to fears of more cold outbreaks due to global warming, Ball laughed, “They’re making it all up!”

CHERRY PICKING

Clearly, there is no end to the deceptions that the climate lobby will tell the public in order to deprive the world of reliable, inexpensive fossil fuel-based energy, the foundation of modern living standards. Perhaps the greatest deception of all is what real scientists call cherry picking – highlighting data that advance their theory and agenda, while ignoring data that do not support their politics.

This is the sleight-of-hand used by global warming alarmists who want the public to believe that burning fossil fuels and increasing the atmosphere’s carbon dioxide must be stopped at all costs. They want to run the nation and the world on expensive, inconvenient, unreliable wind and solar energy. They ignore the fact that those energy must be totally backed up by dependable energy sources like fossil fuel or nuclear in order to stop the grid from collapsing. It has been calculated that, were the Midwest to be dependent only on wind and solar power, at least one million people would have died of hypothermia during the recent minus-50 degrees F cold spell.

As demonstrated by Climate Change Reconsidered II: Fossil Fuels, the latest report of the Nongovernmental International Panel on Climate Change, the impact of fossil fuels (coal, oil and natural gas) has been overwhelmingly positive. The report’s Summary for Policymakers states:

“Fossil fuels have benefited humanity by making possible the prosperity that occurred since the first Industrial Revolution…. Fossil fuels also power the technologies that reduce the environmental impact of a growing human population, saving space for wildlife…. Nearly all the impacts of fossil fuel use on human well-being are net positive (benefits minus costs), near zero (no net benefit or cost), or are simply unknown.”

Besides raising living standards across the world, fossil fuel use has helped elevate CO2 in our atmosphere from a level dangerously close to the point at which plants start to die – to where we are today, with the Earth once again “greening,” as crops, forests and grasslands grow faster and better.

The global warming scare has never been about science, or even climate for that matter. The long-term goal of many activists is to unite the world under a single socialistic government in which there is no capitalism, no democracy and no freedom. After all, personal freedom is fueled largely by access to affordable energy.

An intermediate goal of climate alarmism is thus to limit the amount of energy that is available and place it under tight government control. Inexpensive fossil fuels remain an obstacle to their vision, and so must be done away with entirely, climate campaigners maintain. We must not let them succeed.

“Global cooling – and global totalitarian socialism – are the catastrophes we should fear most.”

Dr. Jay Lehr passed away in January this year, he was the Science Director of The Heartland Institute.
Tom Harris is Executive Director of the Ottawa-based International Climate Science Coalition.



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How a mere 12% of Americans eat half the nation's beef, creating significant health and environmental impacts

AUGUST 30, 2023, by Tulane U.

Credit: Unsplash/CC0 Public Domain

A new study has found that 12% of Americans are responsible for eating half of all beef consumed on a given day, a finding that may help consumer groups and government agencies craft educational messaging around the negative health and environmental impacts of beef consumption.

Those 12%—most likely to be men or people between the ages of 50 and 65—eat what researchers called a disproportionate amount of beef on a given day, a distinction based on the latest Dietary Guidelines for Americans, which suggest four ounces per day of meat, poultry, and eggs combined for those consuming 2,200 calories per day.

The study, published in the journal Nutrients, analyzed data from the CDC's National Health and Nutrition Examination Survey, which tracked the meals of more than 10,000 adults over a 24-hour period. The global food system emits 17 billion tons of greenhouse gases a year, equivalent to a third of all planet-warming gases produced by human activity. The beef industry contributes heavily to that, producing eight to 10 times more emissions than chicken, and over 50 times more than beans.

"We focused on beef because of its impact on the environment, and because it's high in saturated fat, which is not good for your health," said the study's corresponding and senior author Diego Rose, professor and nutrition program director at Tulane University School of Public Health and Tropical Medicine.

Rose said the study's purpose was to assist in targeting educational programs or awareness campaigns to those eating disproportionate amounts of beef. Honing messaging around the environmental impact of beef production is crucial at a time when climate change awareness is higher than ever.

Rose said he and fellow researchers were "surprised" that a small percentage of people are responsible for such an out-sized consumption of beef, but it's yet to be determined if the findings are encouraging for sustainability advocates.

"On one hand, if it's only 12% accounting for half the beef consumption, you could make some big gains if you get those 12% on board," Rose said. "On the other hand, those 12% may be most resistant to change."

The study also found that those who were not disproportionate beef consumers were more likely to have looked up USDA's MyPlate food guidance system.

"This might indicate that exposure to dietary guidelines can be an effective tool in changing eating behaviors, but it could also be true that those who were aware of healthy or sustainable eating practices were also more likely to be aware of dietary guideline tools," said Amelia Willits-Smith, lead author on the paper and a post-doctoral fellow at the University of North Carolina at Chapel Hill.

Of the beef consumed on a given day, almost a third came from cuts of beef such as steak or brisket. But six of the top 10 sources were mixed dishes such as burgers, burritos, tacos, meatloaf or spaghetti with meat sauce. Some of these foods may offer an easy opportunity for disproportionate beef eaters to alter their dietary habits.

"If you're getting a burrito, you could just as easily ask for chicken instead of beef," Willits-Smith said.

Those below the age of 29 and above the age of 66 were least likely to eat large amounts of beef. Rose said this indicated that the younger generation might be more interested in mitigating the effects of climate change.

"There's hope in the younger generation, because it's their planet they're going to inherit," Rose said. "I've seen in my classes that they're interested in diet, how it impacts the environment, and what can they do about it."

In addition to Rose and Willits-Smith, the study's authors include Tulane clinical assistant professor Dr. Keelia O'Malley and Tulane Masters of Public Health graduate Harmonii Odinga.


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Antibiotics found to promote the growth of antibiotic-resistant bacteria in the gut

AUGUST 30, 2023, by Hayley Dunning, Imperial College London

Bacterial families that were decreased in antibiotic-treated human fecal microbiota were positively correlated with microbial metabolites and negatively correlated with nutrients.
 rCCA model correlating 16S rRNA gene sequencing data (family level) and 1H-NMR spectroscopy data (n = 11 healthy fecal donors). Correlation circle plot showing correlations between variables from antibiotic-treated and antibiotic-naïve samples. 
Nutrients and metabolites are shown in blue and bacterial families are shown in orange. 
The following abbreviations are used for nutrients and metabolites: Ara arabinose, Fru fructose, Fuc fucose, Gal galactose, Glc glucose, Man mannose, Rib ribose, Xyl xylose, GlcNAc N-acetylglucosamine, Mal maltose, Suc sucrose, Tre trehalose, Ala alanine, Arg arginine, Asp aspartate, Glu glutamate, Gly glycine, Ile isoleucine, Leu leucine, Lys lysine, Met methionine, Phe phenylalanine, Pro proline, Thr threonine, Trp tryptophan, Tyr tyrosine, Val valine, Ura uracil, SA succinate, LA lactate, 5-AVA 5-aminovalerate, FA formate, AA acetate, PA propionate, BA butyrate, VA valerate, iso-BA isobutyrate, iso-VA isovalerate, EtOH ethanol, IPM Imipenem/cilastatin, MEM meropenem, ETP ertapenem, TZP piperacillin/tazobactam, CIP ciprofloxacin, CRO ceftriaxone, CAZ ceftazidime, CTX cefotaxime. Credit: Nature Communications (2023).
 DOI: 10.1038/s41467-023-40872-z

Antibiotic-resistant bacteria get extra nutrients and thrive when the drugs kill "good" bacteria in the gut. This is according to new research led by Imperial College London scientists, which could lead to better patient risk assessment and "microbiome therapeutics "treatments to help combat antibiotic-resistant bacteria.

Some antibiotics target specific bacteria, but some are "broad spectrum," meaning they can kill a wide range of bacteria including both "bad" pathogenic bacteria that cause infections and "good" bacteria that live in our guts and help with digestion and other processes.

Carbapenems are broad-spectrum antibiotics that are strong but often used as a last resort, due to their negative impacts on beneficial bacteria. Some pathogenic bacteria in the class Enterobacteriaceae however are even resistant to carbapenems, including strains of E. coli. These pathogenic bacteria colonize the gut but can spread to other sites in the body, causing difficult-to-treat infections such as bloodstream infections or recurrent urinary tract infections.

Now, a new study shows how these resistant bacteria thrive after antibiotic use, allowing them to multiply in the gut, forming a "reservoir" of disease-causing bacteria. The results are published in Nature Communications.

More nutrients, less impairment

To determine the effect of antibiotics, the team tested them on samples of human feces in the lab, alongside experiments in mice and lab tests of carbapenem-resistant Enterobacteriaceae (CRE).

Bacteria in the gut, whether "good" or "bad," need nutrients to grow and reproduce. The experiments showed that when antibiotics killed beneficial bacteria, the pathogenic bacteria were able to take advantage of the extra nutrients available due to less competition.

The team also showed that killing beneficial bacteria reduced the level of metabolites—waste products that inhibit pathogenic bacteria from growing further. This helped the pathogenic bacteria to thrive.

First author Alexander Yip, from the Centre for Bacterial Resistance Biology in the Department of Life Sciences at Imperial, said, "Understanding how antibiotics cause carbapenem-resistant Enterobacteriaceae to grow in the intestine means that we can develop new treatments to restrict their growth in the intestine, which will lead to a reduction in these antibiotic-resistant infections."

Microbiome therapeutics

The team is now working on ways to interfere with this process. First, they want to identify which beneficial bacteria can "outcompete" pathogenic bacteria in the absence of antibiotics, by determinging which good bacteria are able to make better use of the same nutrients and produce metabolites that restrict pathogenic bacterial growth.

With this information they hope to create "microbiome therapeutics." Lead researcher Dr. Julie McDonald, from the Department of Life Sciences at Imperial, explained, "When a patient is taking antibiotics we could give them inhibitory metabolites to restrict the growth of resistant bacteria. After a patient has stopped taking antibiotics we could give them a mixture of beneficial gut bacteria to help their gut microbiome recover, restore depletion of nutrients, and restore production of inhibitory metabolites.

"These microbiome therapeutics could reduce the risk of patients developing invasive antibiotic resistant infections, reduce the recurrence of invasive CRE infections in chronically colonized patients, and reduce the spread of CRE to susceptible patients."

In the short term, the researchers say their results could be used to help reduce the risk of patients harboring reservoirs of CRE in their guts. For example, clinicians could avoid prescribing antibiotics that elevate certain nutrients and deplete certain metabolites. Doctors could also screen patient fecal samples for these nutrients and metabolites, to identify those at increased risk of CRE colonization.



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Health and Wellness News: Rising caffeine levels spark calls for ban on energy drink sales to children

 

Rising caffeine levels spark calls for ban on energy drink sales to children

As caffeine content in energy drinks has climbed over the years, some countries and retailers have banned the products while a few require proof of age for purchase

Wednesday, 30 August 2023

Long-term Solar Variability: ISWAT S1 Cluster Review for COSPAR Space Weather Roadmap

25 August 2023 
https://www.sciencedirect.com/science/article/pii/S0273117723006828

Under a Creative Commons license
open access


Abstract

The Committee on Space Research (COSPAR) is updating its Roadmap on Space Weather. As input for this update, the COSPAR International Space Weather Action Teams (ISWAT) were asked to provide an overview of the current state-of-the-art and advancements since the last Roadmap (Schrijver et al., 2015), identifying gaps and opportunities for moving forward within the next 5 years — based on ongoing and planned missions, available modeling, and observational capabilities — and presenting an outlook beyond 5 years and recommendations on reaching long-term goals. While space weather is typically associated with short-term solar activity, knowledge of past solar variability observed and recorded through various parameters, including historical space weather events, informs us about the range of possible solar fluctuations. This long-term solar variability, belonging to the domain of space climate, is the prime focus of the ISWAT S1 Cluster. The goal of this paper is to describe the key objectives of the three S1 Action Teams, summarize the current state of knowledge of the topic that each team is focusing on, and identify the key science gaps that need to be addressed in each area.

Keywords

sunspot time series
solar total and spectral irradiance
large-scale heliospheric parameters
physical understanding of long-term variability
historical data preservation
long-term observations of the Sun

1. Introduction

Life on Earth has been in existence from about 3.7–3.8 billion years ago (e.g.Dodd et al., 2017). Over that time period, the solar total luminosity has increased by about 25% as compared to the modern-day Sun (e.g.Ribas, 2009). By comparison, in modern days the total solar luminosity changes by about 0.1% over the 11-year sunspot cycle, indicating a very stable energy flow from the Sun to Earth — a prerequisite for a stable climate. Recent studies of stellar evolution also indicate that the early Sun may have exhibited cycle variability similar to that of modern times, albeit with larger amplitudes and different periods. Studies of solar analogs also suggest that after a star (Sun) enters the main sequence its magnetic activity gradually decreases until it is 6–7 Myr old (e.g.Lorenzo-Oliveira et al., 2018). Thus, the magnetic activity on the Sun will continue similar to what we see today for another 1–2 Myr. Occasionally, this regular cycle variability is interrupted by extended periods of grand minima, the nature of which is still poorly understood. Thus, it is important to understand how solar activity is changing over long periods of time, what conditions affect the long-term variability and trigger the grand minima, and whether these changes could be predicted. The leading polarity of sunspot groups reverses between two consecutive cycles and, in relation to this, the polar fields change polarity shortly after the maximum of each sunspot cycle. This results in a 22-year magnetic (Hale) solar cycle. An analysis of solar activity reveals several other long-term periodicities, the strongest of which are the 90–100 years Gleissberg cycle (Gleissberg, 1939; see Hathaway, 2015 for a review) seen in sunspots and a quasi-210-year variability (sometimes referred to as Suess or de Vries cycle — see Usoskin, 2023) observed in cosmogenic isotopes time series (Suess, 1980Hathaway, 2015). A 210-year variability may play a role in the recurrence of grand minima (e.g.Tlatov and Pevtsov, 2017Usoskin, 2023). The signature of all these periodicities is evident in many astrophysical channels, such as galactic cosmic rays (GCRs) and gamma-rays. Hale cycles directly affect the transport of GCRs in the heliosphere by changing the large-scale drift patterns (see, e.g.Rankin et al., 2022 and Engelbrecht et al., 2022), producing a second-order effect in GCR modulation. Interactions of modulated GCRs with the solar photosphere and corona produce high-energy gamma-rays from the solar disk and halo, whose intensity is thus modulated over the solar cycle (see, e.g.Linden et al., 2022 and Gutiérrez et al., 2022). The Sun also blocks high-energy GCRs, generating the so-called Sun’s shadow, a depletion in the intensity of high-energy GCRs coming from the direction of the Sun. This shadow can be used to constrain coronal magnetic field models and it has been shown to vary with the 11-year and 22-year solar cycles (see, e.g.Amenomori et al., 2000Tjus et al., 2020Aartsen et al., 2021). Most likely, the modulation of the Sun’s shadow and high-energy gamma-rays is also present for longer periodicities. However, observations of these channels started only in the last couple of decades, so they have not been yet detected.

The Committee on Space Research (COSPAR) International Space Weather Action Teams (ISWAT) is a global center for community-coordinated collaborations to address challenges across the field of space weather. ISWAT activities are organized by Clusters and the Action Teams within Clusters. Cluster S1 focuses on reconstructing and establishing the ranges of variations of past solar activity, evaluating the extreme space weather and space climate episodes and, when possible, their impacts, helping to assess predictive models of solar activity ranging from solar dynamo and surface flux transport models to coronal and heliospheric field evolution models, and transition validated data-driven computational models to operational space weather (and space climate) forecasting tools. The Cluster is organized into three action teams: S1-01: Long-term solar variability; S1-02: Worst-case scenario for extreme solar events; and S1-03: Data sets of historical observations of solar and geomagnetic activity. In this paper, the leads of each Action Team and the research community were asked to provide a review of the current understanding of the research field, identifying the key outstanding questions and the current knowledge gaps, as well as the future research developments.

In Section 2 we review the observational and modeling aspects of sunspot time series, solar total and spectral irradiance, large-scale heliospheric parameters, and extreme solar events. Section 3 discusses the physical understanding of long-term variability, including solar cycle predictions and forcing on planetary environments. Section 4 addresses historical data preservation. Section 5 outlines the importance of continuity of long-term observations of the Sun, and Section 6 summarizes our review and high-level recommendations. Specific recommendations for each sub-field are provided at the end of each Section. A includes a list of acronyms used throughout the text.

2. Observational and modeling/theoretical aspects

Solar variability can be probed through the observation of various parameters available in different periods (length of the raw dataset) and timescales. The longest time series available is an index based on the number of spots and sunspot groups that appear on the Sun, called the sunspot number (Owens, 2013): it is available from the beginning of the 17th century. It enables the study of the long-term behavior of the Sun. Other solar-activity indices include, e.g., the radio flux F10.7 (Tapping and Charrois, 1994), coronal index, etc. The spectral solar irradiance and the total solar irradiance have been directly measured since 1978 (see, e.g.Ermolli et al., 2013Kopp, 2016DeLand et al., 2019 and references therein) and can be modeled before that using other long-term parameters, e.g., sunspot (areas, positions, sunspot number) and plage (from white-light or Ca II K images) observations or cosmogenic isotope data (Solanki et al., 2013). The solar wind and heliospheric magnetic field have been directly measured by satellites for only a few decades (since late 1950s – early 1960s, Obridko and Vaisberg, 2017), but can be modeled over centuries and millennia through proxy data sources, e.g., cosmogenic radionuclides. They are used, for example, to understand and anticipate solar eruptive events. Here we discuss only extreme solar events because of the focus on longer timescales of the ISWAT S1 Cluster.

In this section we present the available observations, their compilation, and different modeling approaches used to extend these observations back in time and/or through data gaps, and to estimate their uncertainties.

2.1. Sunspot number time series

2.1.1. Historical compilation of sunspot observations

The sunspot number (SN, Clette et al., 2014Clette et al., 2015Clette and Lefèvre, 2016) and group number (GN, Hoyt and Schatten, 1998aHoyt and Schatten, 1998bSvalgaard and Schatten, 2016Usoskin et al., 2016Chatzistergos et al., 2017) are time series (1610 – present) that trace solar activity over more than 400 years. SN was computed in near real-time by Rudolf Wolf (1816–1893, Friedli, 2016) and his successors from 1849 onward and is a compilation of records from 1700 to 1848 (Friedli, 2016Bhattacharya et al., 2023). Today it is produced and maintained by the WDC-SILSO1), since its transfer from Zürich to Brussels in 1981. For SN, the original formula of Rudolf Wolf for the daily sunspot number of a single observer is given by (Wolf, 1851Wolf, 1856):SN=(10×)+,where G is the number of sunspot groups on the solar disk on a given day, S denotes the total number of individual spots within those groups, and k is a normalization factor that brings different observers to a common scale (k is the time-averaged ratio of daily SN of the primary reference observer to that of a secondary observer). Because there were about 10 spots per group on average in the nineteenth century, i.e.10 (Waldmeier, 1968Clette et al., 2014), the two parameters have about equal weight in SN. Despite its simplicity, historical SN time series may be non-uniform. Thus, for example, early observations by Wolf did not include small sunspots. In 1947, Waldmeier introduced unequal weights to sunspot counts to reflect their size and presence/absence of penumbra (Svalgaard et al., 2017). These non-uniformities are corrected in the most recent SN time series.

On the other hand, the group number series GN, built from the available raw source data, was compiled in 1995 (Hoyt and Schatten, 1998aHoyt and Schatten, 1998b). Its undeniable advantage is that it goes back to the first telescopic observations in 1610 (Vaquero and Vázquez, 2009Arlt and Vaquero, 2020), and it is easier to compute with respect to SN. Because of the amount of work necessary to actually gather and compile all the data required for SN calculations, Hoyt and Schatten, 1998aHoyt and Schatten, 1998b created an index based on the number of groups which does not take the number of individual spots into account. In order for GN to be comparable with SN, Hoyt and Schatten, 1998aHoyt and Schatten, 1998b introduced a linear relationship where GN has to be multiplied by 12.08 to reach the level of SN. We note, however, that the approach of using SN as a proxy for GN needs to be taken with caution because the number of sunspots per group varies with phase of the solar cycle (e.g.Tlatov, 2013). Georgieva et al. (2017) devised a correction function for the GN series that takes into account the changes in the number of sunspots per sunspot group from 1700–2017.

2.1.2. Observational data compilation

SN is a time series built by aggregating data from a number of observers with different quality and/or methods over a very long period of time (hundreds of years). The factor k mentioned above is the key to assembling all data, but as the methods and understanding of the physics of the Sun evolved, so did the compilation methods.Table 1

Table 1. Key questions the S1 Action Teams are focused on.

QuestionTeamOn the WebSections
What are the reliable estimates of long-term solar variability, based on proxy data, including uncertainty assessments?S1-01Link2.1 Sunspot number time series2.2 Solar total and spectral irradiance time series, and 2.3
Nature of the extreme events: What is an extreme event? How often can they occur? Does the Sun have a limit in producing extreme events?S1-02Link2.4
What is a comprehensive inventory of solar and geomagnetic datasets relevant for long-term space weather and space climate research; a standardized method for processing and preservation of historical data, their quality, and current state? What resources are needed to preserve these critical datasets?S1-03Link4
Physical understanding of long-term variability and its consequencesS1-01, S1-023

Table 2 presents the evolution of the compilation methods of SN over time in Zürich and Brussels. From 1700 to 1848, SN was compiled from historical sources that can be found in the journals compiled by Rudolf Wolf (Wolf, 1848). From 18482 to 1876, Wolf used only his observations with gaps filled in by secondary observers (Bhattacharya et al., 2021Bhattacharya et al., 2023). From 1877, Wolf introduced averaging of several observers for each daily observation.

Table 2. Key dates in sunspot number observations from 1700. Before 1848, the number of observations per day was highly variable. For that period, information can be found in Hoyt and Schatten, 1998aHoyt and Schatten, 1998bVaquero et al., 2016Svalgaard and Schatten, 2016Cliver, 2016. Table adapted from Dudok de Wit et al. (2016).


continued at   https://www.sciencedirect.com/science/article/pii/S0273117723006828


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