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+## Antarctic Sea Ice Lows
+
+While the global temperature records in 2023 and 2024 made many headlines, also some remarkable events and record breaking events took place in the Antarctic. On 16 February 2023, the Copernicus Marine Service recorded a new record decline in sea ice coverage around Antarctica, standing at [just 1.77 million km2](https://marine.copernicus.eu/news/antarctic-summer-sea-ice-minimum-lowest-ever-observed ), which was 36% less than the 1979-2022 average daily minimum. Since then, the Antarctic sea ice [continued to drop to record lows](https://marine.copernicus.eu/news/2023-northern-hemisphere-summer-record-breaking-oceanic-events ) in May and June 2023, particularly in the Weddell, Bellingshausen, and the Ross Sea's western part (visualized below). Following the summer minimum, the Antarctic sea ice coverage remained exceptionally low during the autumn and winter advance, which led to the largest negative areal extent anomalies observed ever (with satellites) - meaning that not only the annual minimum in February hit a record, also the annual maximum in September [set a new record](https://www.nature.com/articles/s43247-023-00961-9). On september, the Antarctic sea ice reached its annual maximum extent of 16.96 million km2 setting a new record low maximum in the satellite record (i.e. since 1979).
+
+
+
+
+ Antarctic Sea Ice Extent. Credits: National Snow and Ice Data Center, Boulder, CO
+
+
+
+The driver of low sea ice conditions is not a single cause, but El Niño could have partly contributed to this. Historically, large-scale weather patterns, such as ENSO and the Southern Annular Mode, have contributed to the ups-and-downs observed in the Antarctic sea ice, by either amplifying or suppressing sea ice changes, by affecting the ways that sea ice moves, melts and freezes. Multiple factors combined could have been responsible for this lows, [recent studies have pointed to the important role of ocean processes and heat](https://www.nature.com/articles/s43247-022-00624-1) stored below the surface, which for instance kept sea ice extent low since 2016. The warm sea surface temperature in the Southern Ocean during the first half of 2023 probably could also partly explain both the record minimum textent in February and the slow freeze-up afterwards. Although being not be possible to associate the Antarctic sea lows records do ENSO or El Niño, recent observations suggest that ENSO impacts basal melting of West Antarctic ice shelves, suggesting that Antarctic sea ice extent has been [likely exacerbated by the developing El Niño ](https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023GL104518) conditions in the Pacific Ocean. This development in Antarctica is showing a concerning deviation from previous trends, since Antarctida has held considerably steady against progressing climate change, contrary to it counterpart, the Arctic.
+
+
+
+ Antarctic Sea Ice Extent. Credits: National Snow and Ice Data Center, Boulder, CO
+
+
+
+
+## Antarctic Winter Sea Ice Extent Lowest Ever Recorded
+
+The Advanced Microwave Scanning Radiometer (AMSR) series operated by JAXA, conducts oceanographic observations not only in the waters around Japan, but also in the distant Arctic and Antarctic regions. In the Arctic, the North American and Eurasian continents surround the Arctic Ocean, while in the Antarctic, the Antarctic Ocean surrounds Antarctica. Both the Arctic and Antarctic oceans show seasonal variations, with sea ice expanding as seawater freezes in winter and shrinking as sea ice melts in summer. When we think of “Antarctic ice”, the first thing that comes to mind may be the continental ice sheet formed by snow accumulation, but there are also areas of sea ice that surround the continent, formed by seawater and providing a stage for the development of ecosystems. Sea ice is used as an indicator of climate change because it lies between the atmosphere and the ocean and is affected by both air and water temperatures. The AMSR series allows us to capture not only the seasonal advance and retreat of sea ice cover, but also the long-term trend of change over 45 years from 1978 to the present, in combination with U.S. microwave radiometer data.
+The figure below shows the seasonal changes in Arctic and Antarctic sea ice extent for each year obtained from these passive microwave observations. Because the seasons are reversed in the northern and southern hemispheres, the Arctic (Antarctic) sea ice cover shrinks (expands) most during the year in September (Hereinafter referred to as “summer” Arctic sea ice extent and “winter” Antarctic sea ice extent). The Arctic region experienced sea ice loss from the 1990s through the 2010s, with the smallest summer sea ice extent on record in 2012, but no comparable sea ice loss has occurred in 2023. On the other hand, the Antarctic sea ice extent showed almost the same seasonal variation until the 2010s, but in 2023, sea ice did not expand as much as in other years from around June, and in September, when sea ice extent is usually at its maximum, the minimum winter sea ice extent in the history of satellite observations was recorded.
+
+
+
+
+ Seasonal changes in sea ice extent in the (1) Arctic and (2) Antarctic regions. Each year in September, the Arctic region (summer) has the smallest sea ice extent, and the Antarctic region (winter) has the largest sea ice extent.
+Arctic: A record minimum (summer) was recorded in 2012. This year it remains at the same level as in the 2010s.
+Antarctic: Record minimums (summer) continue to be recorded in 2022 and 2023. In addition, sea ice extent is much lower than usual this year between April and September, the period of sea ice expansion.
+(Observation satellites: DMSP/SSM/I [January 1991―June 2002], Aqua/AMSR-E [June 2002―September 2011], Coriolis/WINDSAT [October 2011―July 2012], “SHIZUKU” GCOM-W/AMSR2 [July 2012-])
+
+
+
+
+## Changes in Antarctic sea ice extent
+
+First, let us look at the interannual variability of the Antarctic summer sea ice extent. Figure 2 shows the minimum sea ice extent for the month of February calculated from microwave radiometer data, including the AMSR series. As mentioned above, sea ice extent in the Arctic Ocean has been on a decreasing trend, while in the Antarctic Ocean it has been on a slightly increasing trend until about 2015. The cause of the difference in trend between the two is not entirely clear, but it is thought to be related to the fact that Antarctic sea ice is more affected by natural variability than anthropogenic climate change due to differences in geographic conditions. In any case, the long-term trend in the Antarctic sea ice extent has not been as dramatic as in the Arctic and has not received as much attention.
+The trend in Antarctic sea ice extent began to change in the early spring of 2016 (around November). Higher sea surface temperatures in the Antarctic Ocean and warm air advection from the north led to a decrease in sea ice extent (*2, *3), with a record minimum in February 2017, as shown in Figure 2. The higher ocean surface temperatures are thought to be the result of a combination of changes in two “climate modes (see Supplement 1)”: the remote “El Niño-Southern Oscillation” and the more local “Southern Annular Mode” (*2). Although it has been considered that the minimum may have been caused by a short-term event, sea ice extent has consistently remained low since then, reaching a new record minimum in 2022 and 2023. A very recent study suggests that the dramatic decline in Antarctic sea ice that began in 2016 may be primarily due to long-term warming of the Antarctic Ocean associated with greenhouse gas emissions, rather than a change in climate mode as described above (*4).
+Let us return to Figure 1 to take a closer look at the seasonal changes in sea ice extent this year compared to last year. As shown in Figure 1(2), the sea surface in the Antarctic Ocean usually begins to freeze around March, and the sea ice extent peaks around from September to October. In contrast, this year’s sea ice extent from March to September was consistently well below the historical average. While sea ice extent has been below normal for the past seven years, the year 2023 in particular is characterized by a slowdown in sea ice extent expansion (in the Antarctic winter) not seen in previous years.
+
+
+
+
+ (Upper graph) Annual minimum Antarctic sea ice extent
+Sea ice extent was on a slight upward trend until about 2015, but has been declining since then.(Lower figures) Sea ice concentration distribution observed by AMSR2 in February 2022 and 2023, when sea ice extent continued to be the lowest on record.
+
+
+
+## Causes of sea ice distribution and extent stagnation in winter 2023
+
+Let’s take a closer look at where sea ice extent is stagnating from the June and September 2023 sea ice distributions (Figure 3). As shown in Figure 3(1), Antarctica is bounded on the left by the Bellingshausen Sea, on the top left by the Weddell Sea, and on the bottom by the Ross Sea. Comparing these areas with the sea ice extent in normal years (white line), we can see that the south-to-north sea ice expansion is significantly weakened in June. In September, when sea ice extent is at its maximum, the Bellingshausen Sea has recovered to levels similar to previous years, but the Weddell Sea, Ross Sea, and other areas continue to have generally weak sea ice extensions.
+
+Although the cause of the significantly smaller Antarctic winter sea ice extent in 2023 compared to previous years is still unknown, one possible factor is that the heat stored in the ocean (ocean heat content) due to the ongoing summer sea ice retreat since around 2016 (Figure 2) has slowed sea ice production. In particular, if there is less sea ice in the summer than in a normal year, the sea surface is exposed to more solar radiation and absorbs more of it. This increases the ocean heat content, preventing the formation of sea ice in autumn and winter. In this way, the amount of solar radiation absorbed by the ocean increases with the exposed open water fractions, leading to the further decrease in sea ice. This effect is known as the “sea ice/ocean albedo feedback” (albedo: ratio of the energy of reflected light to the energy of incident sunlight). Given that a correlation between minimum Antarctic summer sea ice extent and maximum winter sea ice extent has indeed been observed for the period 2016―2022 (*4), it seems quite possible that the above feedbacks between sea ice and the ocean are related.
+
+
+
+
+ Sea ice concentration distribution in the Antarctic region observed by AMSR2 (1) on June 3, 2023 and (2) on September 9, 2023.
+The gray area in the figure shows the Antarctic continent, and the white line shows the average extent of sea ice on each day over the past 45 years.
+(1) shows significant sea ice loss in the area marked by the yellow circle.
+In the distribution (2), where three months have passed, the overall overhang continues to be weak.
+
+
+
+## Impacts of Antarctic Sea Ice Loss
+What would happen if Antarctic sea ice were to begin to decline at a significant rate? Regarding the impact on ecosystems, we would like to introduce a study on a colony of emperor penguins published in Communications Earth & Environment, a journal in the field of earth and planetary sciences (*5). Emperor penguins lay their eggs from May to June on landfast sea ice that is attached to the shore and does not move as a breeding ground, and the hatched chicks fledge during December and January. Therefore, for successful breeding, the landfast ice must be stable from winter to early spring. However, in 2022, when spring sea ice extent was at an all-time low, it was reported that four of the five colonies had lost all their Emperor penguin chicks due to the loss of solid ice in the Bellingshausen Sea.
+What about the impact on the oceans? As mentioned at the beginning of this article, Antarctica is covered by a thick layer of ice, up to 4000 m thick, called the ice sheet. Ice sheets flow to the sea under their own weight, forming ice shelves (ice that is attached to land and floats in the sea). Since ice shelves are connected to seawater at the bottom, higher temperatures in the Antarctic Ocean due to sea ice loss are likely to accelerate ice shelf melting and contribute to sea level rise.
+In addition, “coastal polynya”, areas that produce large amounts of sea ice, are ubiquitous around Antarctica. When seawater freezes to form sea ice, much of the salt is released into the ocean below, so coastal polynya is also a region where highly saline water forms. The high-salinity, low-temperature water formed there becomes dense water, which sinks to the ocean depths and eventually spreads to the bottom layers of the entire global ocean. Higher surface ocean temperatures due to sea ice loss and subsequent freshening of upper oceans due to melting ice shelves could suppress the formation of high-density water, potentially leading to a weakening of the global deep ocean circulation. In fact, in 2017, a Japanese polar research group found that ice shelf melting was accelerated by increased ocean heat storage due to reduced summer sea ice, which simultaneously affected the formation of high-density water (*6). This year, 2023, the changes are more severe than in 2017. There’s concern about more significant impacts on ice shelves and oceans.
+
+## Looking ahead
+#### Ongoing and future missions, mitigation and adaptation strategies
+
+Future mission for land surface temperature (LSTM) is an ESA mission developed by Airbus Defense and Space, set to join the Copernicus Sentinel system in 2028. The satellite will have Thermal Infrared (TIR) observation capabilities over land and coastal regions in support of agriculture management services, and possibly a range of additional services.
+The optical instrument of LSTM, Land Surface Temperature Radiometer, will acquire high spatio-temporal resolution observations of all land and coastal areas with high radiometric accuracy. The mission’s primary objectives are to monitor evapotranspiration (ET) rates by capturing the variability of Land Surface Temperature (LST), as well as map and monitor soil composition. LSTM also has a range of TIR observational applications and data from the mission will be used to manage water resources for agricultural production, predict droughts; manage coastal and inland water bodies, and monitor High-Temperature Events (HTE) such as heatwaves and urban heat islands .
+
+
+
+
+ Artist’s impression of LSTM Credits: ESA
+
+
+
+
+
+Future mission for sea surface temperature is also prepared for the launch. JAXA plans to launch the successor of current GCOM-W/AMSR2, microwave imager, in Japanese Fiscal Year (JFY) 2024 -- the Advanced Microwave Scanning Radiometer 3 (AMSR3) on board the Global Observing SATellite for Greenhouse gases and Water cycle (GOSAT-GW). AMSR3 will have four additional frequency bands as well as continuation of AMSR2’s observation capability. New high-frequency channels, 166 & 183 GHz, will enable monitoring of global precipitation (rain & snow) and contribute to water vapor analysis in numerical weather prediction in the world’s meteorological centers. Additional 10.25 GHz channels with improved temperature resolution to reduce noises for robust SST retrievals in higher spatial resolution. The GOSAT-GW satellite will also carry the greenhouse gases sensor, TANSO-3, the successor mission of GOSAT-2/TANSO-2, led by the Ministry of Environment, Japan.
+
+
+
+
+
+
+
+ Image of GOSAT-GW satellite. Credits: JAXA
+
+
+
+
+
+
+
+
+ Antarctic Sea Ice Concentration on 16 February 2023 (black-white) with comparison of mean sea ice edge in 1980s (orange) observed by GCOM-W/AMSR2, when the Antarctic sea ice extent marked the minimum value in the satellite observation records,. Credits: National Institute of Polar Research (NIPR) / JAXA
+
+
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+# Extreme air pollution episodes in Northern India and Pakistan in 2023
+
+###### *This story is based on results from the [3rd Earth System Science Challenge]( https://sciencehub.esa.int/2024/05/09/3rd-earth-system-science-challenge/) organised and hosted by ESA's ESRIN Science Hub in February 2024*
+
+The research presented in this story was developed in the frame of the Earth System Science Challenge organised by the European Space Agency and hosted at ESRIN’s Science Hub in February 2024. The scope of this challenge was to identify the days on which severe air pollution episodes occured in northern India and Pakistan, using the percentile technique applied on time series of carbon monoxide (CO) concentrations measured by Copernicus Sentinel-5p TROPOMI. The method was implemented on the [DeepESDL platform](https://earthsystemdatalab.net) by a team of PhD students from University of Edinburgh and University of Leeds. The data and code are made openly available.
+
+## Air Pollution and Health
+Air pollution is a real concern for human health, as poor air quality may lead to breathing difficulties, cardiovascular disease, or cancer. According to the World Health Organization (WHO), "outdoor air pollution is estimated to have caused 4.2 million premature deaths worldwide in 2019". "Some 89% of those premature deaths occurred in low- and middle-income countries, and the greatest number in the WHO South-East Asia and Western Pacific Regions." (WHO 2024)
+
+The region along the Himalayas in Northern India and Pakistan, also know as the Indo-Gangetic Plain (IGP), is a highly populated region of intense agricultural and industrial activities. The region frequently experiences severe air pollution episodes, putting the local population at risk, as documented and reported by the national and international press (Le Monde 2023), (India Today 2022). Understanding the formation of pollution episodes in this region is vital to help the government establish laws limiting pollutant emissions, and thus enable the local population to live in a healthy environment.
+
+The following map shows the population density for 2020, provided by the Center for International Earth Science Information Network - CIESIN - Columbia University. Darker shades indicate higher density, with values ranging from 1-10.000 persons/km2.
+
+##
+##
+
+
+## Earth Observations
+Agencies such as ESA, NASA and JAXA have Earth-observing satellites whose instruments observe air pollutants around the world. Missions such as NASA's Aura Satellite carrying the [Ozone Monitoring Instrument (OMI)](https://www.earthdata.nasa.gov/learn/find-data/near-real-time/omi) or ESA's Sentinel-5p carrying the [TROPOspheric Monitoring Instrument (TROPOMI)](https://www.tropomi.eu/) provide essential data that is used to study the impact of air pollution on human health and agriculture.
+
+Measurable air pollutants include:
+
+* **Particulate Matter (PM)**: Unhealthy particulate matter are suspended microscopic liquid or solid particles (such as dust or black carbon) in the atmosphere, with a diameter of less than 10 micrometers (able to pass through the throat and nose to enter the lungs). (ECMWF Air Pollution)
+* **Nitrogen Dioxide (NO2)**: NO2 is produced by natural and anthropogenic sources. Globally, the main source of NO2 is fossil fuel combustion. Thus, coal- and gas-fired power plants and automobiles are the main sources.(NASA Air Pollution)
+* **Carbon Monoxide (CO)**: CO is a colorless, odorless gas that can be harmful when inhaled in large amounts. CO is released when something is burned. The greatest sources of CO to outdoor air are vehicles or machinery that burn fossil fuels (EPA 2024)
+* **Ozone (O3)**: Breathing ground-level ozone can also result in a number of health effects. O3 also has a negative impact on plants, reducing crop yields. (EPA)
+* **Sulfur Dioxide (So2)**: Sulfur dioxide (SO2) is a colorless, reactive air pollutant with a strong odor and is unhealthy to breathe. The main sources of SO2 emissions are from fossil fuel combustion and natural volcanic activity.
+
+
+In this challenge, the authors aimed at studying the number of extreme air pollution episodes for the year of 2023 for one pollutant in 3 major cities of the IGP region in India. The pollutant studied was carbon monoxide (CO) measured by TROPOMI. The TROPOMI instrument onboard of Copernicus Sentinel-5P. has a global coverage of 1 day, which can help us to study the daily variation of CO anywhere on the globe. (TROPOMI.eu).
+
+
+
+TROPOMI Instrument. Source: ESA
+
+
+## Data and Method
+The study focuses on 3 densely populated cities in the region of interest: Lahore in Pakistan, New Delhi and Lucknow in India. The analysis was done for 2023, but the same study can be carried out for earlier years.
+
+Carbon Monoxide (CO) is a trace gas, naturally present in the atmosphere and mainly emitted by incomplete combustion processes (anthropogenic activities such as heating, cooking, industrial activities or vegetation fires). This gas is often studied in the field of air quality, as it is a good tracer of pollution due to its long lifespan (from a few weeks to a few months, depending on the season and latitude), which enables it to be transported over long distances.
+
+After identifying the days on which there is a pollution episode, the study team choose one event to explain its formation and evolution over time, using:
+
+1. **Data that identify sources of CO: Active Fires from VIIRS-SNPP**.
+The animation below shows the location of fires detected by Visible Infrared Imaging Radiometer Suite, or VIIRS during the month of October and November 2023 in the IGP. The VIIRS instrument flies on the Joint Polar Satellite System’s Suomi-NPP and NOAA-20 polar-orbiting satellites (NASA VIIRS). This imager has a spatial resolution of 375m and a swath width of 3000, which helps to monitor small fires around the world. This study used day and night time data, which allowed to show the location of fires detected by VIIRS during the month of October and November 2023 in the IGP. The number of fires increased over this period, which could explain the rise of CO concentrations.
+
+We see that the number of fires increases over this period, explaining the observed rise of CO. The VIIRS Active Fires data has some limitations: it give only a hint on the fire location and not their lifetime and their size (i.e., a small temporary fire is counted in the same way as a large fire lasting over time), and is based on optical data which is affected by clouds.
+
+
+
+
+Location of fires detected by Visible Infrared Imaging Radiometer Suite, or VIIRS during the month of October and November 2023 in the IGP
+
+
+Explore [MODIS active fire data on EO Dashboard over the IGP]( https://www.eodashboard.org/explore?indicator=Modis_SNPP_2023&x=8415682.56522&y=3510441.28382&z=4.93607).
+
+2. **Meteorological data horizontal winds at 100m from the ERA5 reanalysis**
+
+The following map shows the horizontal wind from ERA5 hourly data provided by the Copernicus Climate Change Service (C3S) Climate Data Store (CDS). (Hersbach 2023). Values range from [-4, 4] m/s. Blue shades indicate lower values.
+
+##
+##
+
+##
+For each city a rectangle of -0.4 to 0.4° of longitude and -0.4 to 0.4° latitude was generated (from the given coordinates of the chosen city in latitude and longitude) which corresponds to -39.8 to 39.8km in longitude and to -44.5 to 44.5km in latitude. Then the computed time series of each day is the average value of all CO concentration values measured by TROPOMI within that rectangle (with a resolution of 0.025°). The percentile method is a strategy utilized to recognize outliers or extreme values based upon a defined percent limit. It involves calculating the threshold values based on percentiles and the steps are to first determine the percentage threshold (in this case 90%, 95%, and 99%), then calculate the threshold values, and then identify outliers and extreme values above this threshold.
+
+### Daily CO variation in 2023
+
+The following figures display the time series of daily concentration of CO in Lahore, New Delhi and Lucknow. In each of the figures, the yellow line indicates the 90% percentile extreme, the blue one, the 95% percentile extreme, and the green one, the 99% percentile extreme. The points above these lines are the extreme events resulted form the percentile technique. What can be noticed here is that the extreme events seem to happen at the same time for the 3 cities especially for 99% percentile extremes (at the end of October-November).
+
+Furthermore, when these extreme episodes were quantified, the number of days which are considered extremes were almost the same for the 3 cities so there might be a correlation between the extreme pollution events in the 3 cities. We must note that the total number of days in 2023 is not 365 since for some days we do not have measurements because of clouds or other factors.
+
+| City | Total Number of Days in 2023 | Number of Days ≥ 90% | Number of Days ≥ 95% | Number of Days ≥ 99% |
+|------------|-----------------------------|----------------------|----------------------|----------------------|
+| Lahore | 341 | 34 | 17 | 4 |
+| New Delhi | 341 | 34 | 17 | 4 |
+| Lucknow | 346 | 35 | 18 | 4 |
+
+The table indicates the number of days which can be considered as extremes (for 90%, 95%, and 99%). We notice that these number of days are almost the same for the 3 cities, indicating a potential correlation between the extreme pollution events in the 3 cities. Note that the total number of days in 2023 is not 365 since for some days we do not have measurements because of clouds or other factors.
+
+## CO Variation
+
+###
+#### Lahore
+* **Map**: CO concentration measured on 2023-11-09 [[view full time series](https://www.eodashboard.org/explore?indicator=N1_CO&x=0&y=-1224599.44035&z=2.35425)]
+* **Chart**: CO daily variation for 2023
+
+
+
+
+CO daily variation in 2023 for Lahore
+
+
+A first sharp increase in carbon monoxide concentration can be observed at the end of October. The emissions seem to be spontaneous, suggesting they can be linked to unusual antropogenic activities or vegetation fires.
+
+A second peak in CO was detected in Lahore on 11/07. This can be explained by the fact that wind speed was very low in the city and the region of the fires: CO then accumulated again, further increasing the CO concentration, which was already high due to the accumulation around 10/30;
+
+
+###
+#### New Delhi
+* **Map**: CO concentration measured on 2023-11-08 [[view full time series](https://www.eodashboard.org/explore?indicator=N1_CO&x=0&y=-1224599.44035&z=2.35425)]
+* **Chart**: CO daily variation for 2023
+
+Similar to Lahore, the peak observed in New Delhi on 11/04 indicates spontaneous emissions, potentially from fires. Once CO had accumulated, the wind generally blew towards the southeast from where the fires were detected. Being the closest city to the fires (in the southeast direction), New Delhi experiences the first peak in CO concentration.
+
+
+
+CO daily variation in 2023 for New Delhi
+
+
+###
+#### Lucknow
+* **Map**: CO concentration measured on 2023-11-10 [[view full time series](https://www.eodashboard.org/explore?indicator=N1_CO&x=0&y=-1224599.44035&z=2.35425)]
+* **Chart**: CO daily variation for 2023
+
+The last peak in CO was detected in Lucknow. This city is far from the region where agricultural waste was burned, yet it is impacted by these episodes of extreme pollution. So, the presence of fires may not be the only contributor to this pollution event, another parameter must be taken into account, especially local meteorology.
+
+
+
+
+CO daily variation in 2023 for Lucknow
+
+
+###
+#### Why Lucknow, which is quite a distance from the fires detected by VIIRS, is experiencing high concentrations of CO, like those detected in New Delhi or Lahore?
+
+Hypothesising that the high concentrations could be explained by the transport by the winds, the team looked at meteorological data. To this end they used use ERA5 reanalyses. By averaging the horizontal winds at 100m for each day, at UTC+05, it was possible to analize the evolution of wind direction and speed from October 25th to November 14th.
+
+
+
+Video: ERA5 reanalyses, averaged horizontal winds at 100m for each day, at UTC+05. The animation shows the evolution of wind direction and speed from October 25th to November 14th.
+
+
+In general, wind speed was low during this period. However, it was also noticed a change in wind direction around October 30th: the wind, which was blowing towards the southeast, shifted towards the west around this date. As a result, CO, being trapped against the Pakistani terrain and the Himalayas, accumulated, thus explaining the high levels of CO shown in the time series.
+
+
+
+## Conclusions
+* Severe air pollution episodes can be monitored with satellite observations.
+* Using multiple variables (fires and winds) can help us to describe the formation and the evolution of a severe air pollution episode.
+* IGP experienced extreme CO pollution episodes in October/November 2023 due to the burning of agricultural waste by farmers but also due to stable meteorological conditions (low wind speed), favoring its accumulation along the Himalayas.
+* Limits and perspectives of the study:
+ * Explaining pollution episodes can be complex as they depend on multiple factors (atmospheric chemistry, local meteorology, and local emissions). Therefore, it is necessary to work with various instruments, including those from space. However, space instruments may struggle to detect gases due to clouds or smoke emitted by fires, for example. As a result, there were many days in the time series where there were no CO concentrations. For this reason, pollution episodes for certain days may have been missed. To address this issue, it is important to work with local measurements from air quality stations.
+ * The IGP is a highly polluted region characterized by mixtures of gaseous pollutants and aerosols (such as fine particles, known as PM2.5). CO is one among many pollutants emitted during vegetation fires. In the case of the November 2023 air pollution episode, it was interesting to study this molecule, as the cause of the November 2023 smog was agricultural waste burning. However, for other pollution episodes (such as those occurring in summer), it might be more interesting to study tropospheric ozone, as it is predominantly produced under strong sunlight conditions. Additionally, studying ammonia, a precursor of fine particles, is also important because hot weather leads to high ammonia emissions, thereby promoting smog formation. Furthermore, TROPOMI also measures NO2 and SO2, two other precursor gases of PM2.5, offering the opportunity to track their evolution throughout the year to determine days with smog events.
+
+
+## Open Science
+
+The analysis was carried out on the [ESA DeepESDL (Deep Earth System Data Lab)](https://earthsystemdatalab.net ). For research purposes, ESA is offering this resources under a sponsorship scheme through the Network of Resources.
+* [DeepESDL website](https://earthsystemdatalab.net)
+* [Network of Resources website](https://nor-discover.org/en/portfolio/)
+* [Apply for sponsorsed access to DeepESDL](https://portfolio.nor-discover.org/?textSearch=DeepESDL)
+* [ERA5 Dataset](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-land?tab=form
+)
+* [Sentinel-5p TROPOMI CO Dataset](https://radiantearth.github.io/stac-browser/#/external/eurodatacube.github.io/eodash-catalog/trilateral/CO_3_daily/CO_3_daily/collection.json)
+* [VIIRS Active Fire Dataset](https://firms.modaps.eosdis.nasa.gov/download/)
+* [Jupyter Notebook](https://github.com/eurodatacube/eodash-assets/blob/main/stories/ScienceHub-Challenge-February-2024/AirPollutionIndia/3_OpenChallengeNotebook%5BRMSH%5D-%5BChallenge1%5DSinnathamby_Kaminski_Zoghbi.ipynb#:~:text=AirPollutionIndia-,3_OpenChallengeNotebook,-%5BRMSH%5D%2D%5BChallenge1%5DSinnathamby_Kaminski_Zoghbi)
+
+
+### References
+1. World Health Organization. (n.d.). Ambient (outdoor) air quality and health. [WHO 2024](https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health). Accessed February 29, 2024.
+2. Le Monde, Carole Dieterich, 2023, November 18 [New Delhi's air pollution crisis is poisoning millions of children every winter](https://www.lemonde.fr/en/environment/article/2023/11/18/new-delhi-s-air-pollution-crisis-is-poisoning-millions-of-children-every-winter_6265386_114.html)
+3. India Today, Kumar Kunal. 2022, June 3, [Delhi's new normal: Air pollution not just in winter. India Today]( https://www.indiatoday.in/diu/story/delhi-new-normal-air-pollution-not-just-in-winter-1958072-2022-06-03)
+4. Sembhi et al. 2020 Environ. Res. Lett. 15 104067, [DOI 10.1088/1748-9326/aba714](https://iopscience.iop.org/article/10.1088/1748-9326/aba714)
+5. V.P. Kanawade, A.K. Srivastava, K. Ram, E. Asmi, V. Vakkari, V.K. Soni, V. Varaprasad, C. Sarangi, What caused severe air pollution episode of November 2016 in New Delhi?Atmospheric Environment, Volume 222,
+2020, 117125, ISSN 1352-2310, [https://doi.org/10.1016/j.atmosenv.2019.117125](https://doi.org/10.1016/j.atmosenv.2019.117125).
+(https://www.sciencedirect.com/science/article/pii/S1352231019307642)
+6. Li, Ainong et al. “A geo-spatial database about the eco-environment and its key issues in South Asia.” Big Earth Data 2 (2018): 298 - 319, [https://doi.org/10.1080/20964471.2018.1548053](https://doi.org/10.1080/20964471.2018.1548053)
+7. [NASA Air Pollution](https://airquality.gsfc.nasa.gov/)
+8. [EPA O3 2024](https://www.epa.gov/ozone-pollution-and-your-patients-health/health-effects-ozone-general-population)
+9. [EPA CO 2024](https://www.epa.gov/co-pollution/basic-information-about-carbon-monoxide-co-outdoor-air-pollution)
+10. [ECMWF Air Pollution](https://stories.ecmwf.int/tracking-air-pollution/index.html)
+11. [Copernicus Sentinel-5p]( https://sentinel.esa.int/web/sentinel/copernicus/sentinel-5p)
+12. [TROPOMI.eu](https://www.tropomi.eu/data-products/carbon-monoxide)
+13. [NASA VIIRS](https://www.earthdata.nasa.gov/sensors/viirs)
+14. [MODIS Fire Detections](https://radiantearth.github.io/stac-browser/#/external/eurodatacube.github.io/eodash-catalog/trilateral/Modis_SNPP_2023/Modis_SNPP_2023/collection.json)
+15. Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS) (Accessed on 02-M07-2024)
+16. Story Cover image: NASA image courtesy Jeff Schmaltz, MODIS Rapid Response Team. Caption: NASA/Goddard, Lynn, Jenner, source: [https://www.eurekalert.org/multimedia/575396](https://www.eurekalert.org/multimedia/575396)
+
+
+
diff --git a/app/public/data/storytelling-md/eodashMarkdown_EXTREME_SST.md b/app/public/data/storytelling-md/eodashMarkdown_EXTREME_SST.md
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+# El Niño 2023-2024: rising sea surface temperatures (SST)
+
+The strength and frequency of La Niña and El Niño were once determined entirely by natural factors, but now the climate patterns are evidencing the contribution of human actions. A [new study](https://www.nature.com/articles/s43017-023-00427-8 ) set out to determine the impact of greenhouse gases emissions on the major climate driver ENSO, suggesting that climate change is making La Niña and El Niño [more frequent and more extreme](https://www.nature.com/articles/s41586-023-06236-9 ). Around 40 to 50 million people are currently [affected in 16 countries](https://wmo.int/media/news/un-el-nino-debate-emphasizes-need-integrated-action ), in particular in the regions of eastern and southern Africa, the Horn of Africa, Latin America and the Caribbean as well as the Asia-Pacific region. Severe drought and associated food security, flooding, heavy rains, and high temperatures caused by [El Niño caused a wide range of health problems](https://www.esa.int/Applications/Observing_the_Earth/Our_oceans_are_in_hot_water ), including disease outbreaks, malnutrition and heat stress.
+
+
+
+
+
+ El Niño and La Niña. Upper figure: Sea surface temperature anomaly at El Niño status over the tropical pacific. 5-day average from 16 to 20 November 2023, observed by the GCOM-W/AMSR2. Bottom Figure: Sea surface temperature anomaly distribution over the tropical pacific at La Niña status. 5-day average from 16 to 20 November 2022, observed by the GCOM-W/AMSR2. Credit: JAXA
+
+
+
+
+## Europe and Asia’s Marine Heatwave
+The unprecedented sea surface temperatures have been associated with marine heatwaves: periods of unusual high ocean temperatures. These can have significant and sometimes devastating impacts on ocean ecosystems, and biodiversity, potentially leading to socio-economic impacts due to their impact on industry such as fisheries, tourism or aquaculture. Sea surface temperatures and marine heatwaves affected various regions in the summer of 2023, as reported by the Copernicus Climate Change Service during June-July-August.
+The North Atlantic and the Mediterranean basin were particularly impacted by these heatwaves, leading to [significant sea surface temperature anomalies](https://marine.copernicus.eu/news/2023-northern-hemisphere-summer-record-breaking-oceanic-events ) and severe marine heatwaves .
+Of special concerning was the Atlantic Ocean near Ireland and the United Kingdom, where extreme marine heatwave occur in June 2023, with sea temperatures up to 5 °C [above average](https://climate.copernicus.eu/global-sea-surface-temperature-reaches-record-high ) . For the entire year, the average sea surface temperature across European waters was the highest on record, with parts of the Mediterranean Sea and northeastern Atlantic seeing their warmest annual averages [ever recorded](https://climate.copernicus.eu/global-sea-surface-temperature-reaches-record-high ).
+
+
+
+ Ocean heat content anomalies (0-300 metres deep) for June 2023. Credits: Copernicus Marine Service / Mercator Ocean International
+
+
+
+
+Regarding this year, in January 2024 global sea surface temperature [was the highest on record ](https://www.downtoearth.org.in/news/climate-change/at-peak-value-of-2-c-above-average-sea-surface-temperature-2023-24-el-nino-among-strongest-on-record-94825 )for this month . As of late April 2024, positive sea surface temperature anomalies have weakened across most of the Pacific, with below-average temperatures emerging in the far eastern Pacific, [indicating a potential transition to ENSO-neutral conditions](https://www.cpc.ncep.noaa.gov/products/analysis_monitoring/lanina/enso_evolution-status-fcsts-web.pdf ). Model forecasts suggest a transition from El Niño to ENSO-neutral likely to happening in the coming months, with a 60% chance of La Nina developing by June-August 2024 [as the El Niño dissipates](https://www.cpc.ncep.noaa.gov/products/analysis_monitoring/lanina/enso_evolution-status-fcsts-web.pdf ).
+
+
+
+
+## High SSTs in Japan
+Figure below shows a map of SST anomalies for July 2023. Overall, SSTs tend to be higher than normal, especially in the Pacific Ocean off the coast of Tohoku and Hokkaido, where they are more than 5°C higher than normal. The Kuroshio extension, which normally flows eastward from Joban-oki, moved northward to Sanriku-oki this season, bringing high water temperatures. In a recent report of Japan Meteorological Agency (JMA), it was pointed out that this high SST may have been one of the factors that brought record high temperatures to northern Japan this summer.
+
+
+
+
+
+## The Coasts of Tohoku and Hokkaido
+
+###
+#### High Sea Surface Temperatures near Japan
+Overall, SSTs tend to be higher than normal, especially in the Pacific Ocean off the coast of Tohoku and Hokkaido, where they are more than 5°C higher than normal.
+
+###
+#### The Kuroshio extension
+ The Kuroshio extension, which normally flows eastward from Joban-oki, moved northward to Sanriku-oki this season, bringing high water temperatures.
+ The Kuroshio extension, which normally flows eastward from Joban-oki, moved northward to Sanriku-oki this season, bringing high water temperatures.
+
+
+
+ Distribution of AMSR2 monthly mean SST anomalies for July 2023 in the seas around Japan (20-50°N, 120-160°E). Credit: JAXA
+
+
+
+
+
+###
+#### Monthly mean SST anomalies
+ The anomalies in the seas around Japan vary between -1°C and +1°C. In recent years, August 2022 and July 2023 were particularly warm.
+In addition to global warming, SSTs in the ocean around Japan are changing under the influence of complex variations in the ocean current system, which has a significant impact on Japan’s weather, climate, and fisheries. To meet the demand for monitoring and forecasting such oceanic changes, JAXA, in cooperation with the Japan Agency for Marine-Earth Science and Technology, operates the “Ocean Weather Forecast” for the area around Japan, providing forecast results of water temperature and current speed up to about two weeks ahead. The Ocean Weather Forecast uses SST data from the AMSR series to improve forecast accuracy. Figure below shows the monthly mean SST anomalies in the seas around Japan (20-50°N, 120-160°E), which shows the long-term trends of variations, excluding seasonal cycles.
+
+
+
+
+ Time series of monthly mean SST anomalies in the seas around Japan (20-50°N, 120-160°E). Credit: JAXA
+
+
+
+## Open Science
+
+
Here are some key types of variables and datasets from Earth observation satellite missions that can be used to track El Niño and La Niña events, with special attention to ocean-related surface temperatures. This summary focuses on missions from ESA, NASA, and JAXA:
+
+
+
+
+### References
+
+1. Cai, W., Ng, B., Geng, T. et al. Anthropogenic impacts on twentieth-century ENSO variability changes. Nat Rev Earth Environ 4, 407–418 (2023). [doi.org/10.1038/s43017-023-00427-8](https://www.nature.com/articles/s43017-023-00427-8#citeas)
+2. Geng, T., Jia, F., Cai, W. et al. Increased occurrences of consecutive La Niña events under global warming. Nature 619, 774–781 (2023).[doi.org/10.1038/s41586-023-06236-9](https://www.nature.com/articles/s41586-023-06236-9#citeas)
+3. UN El Niño debate emphasizes need for integrated action [World Meterological Organization](https://wmo.int/media/news/un-el-nino-debate-emphasizes-need-integrated-action)
+4. Our oceans are in hot water [ESA](https://www.esa.int/Applications/Observing_the_Earth/Our_oceans_are_in_hot_water)
+5. The 2023 Northern Hemisphere Summer Marks Record-Breaking Oceanic Events [Copernicus Marine Service](https://marine.copernicus.eu/news/2023-northern-hemisphere-summer-record-breaking-oceanic-events)
+6. Global sea surface temperature reaches a record high [Copernicus Climate Change Service](https://climate.copernicus.eu/global-sea-surface-temperature-reaches-record-high)
+7. At peak value of 2°C above average sea surface temperature, 2023-24 El Nino among strongest on record [Down To Earth](https://www.downtoearth.org.in/climate-change/at-peak-value-of-2-c-above-average-sea-surface-temperature-2023-24-el-nino-among-strongest-on-record-94825)
+8. ENSO: Recent Evolution, Current Status and Predictions [NOOA](https://www.cpc.ncep.noaa.gov/products/analysis_monitoring/lanina/enso_evolution-status-fcsts-web.pdf)
+
+
+
+
+
diff --git a/app/public/data/storytelling-md/eodashMarkdown_EXTREME__TEMPERATURES_2.md b/app/public/data/storytelling-md/eodashMarkdown_EXTREME__TEMPERATURES_2.md
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+# Record-breaking temperatures: El Niño 2023-2024
+
+## El Niño 2023-2024
+
+2024 has seen an unprecedented streak of record-breaking global temperatures. The average global surface air temperature in April 2024 - the warmest April on record - [exceeded by 0.67°C](https://climate.copernicus.eu/copernicus-global-temperature-record-streak-continues-april-2024-was-hottest-record) the 1991-2020 average and by 1.58°C the pre-industrial values. It was the eleventh consecutive month of [record-breaking temperatures](https://wmo.int/media/news/global-temperature-record-streak-continues-climate-change-makes-heatwaves-more-extreme ). Just the year before, 2023 was the warmest year back then on record, surpassing the previous record set in 2016, according to the [Copernicus State of the Climate report](https://climate.copernicus.eu/copernicus-2023-hottest-year-record). Over 200 days had new daily global temperatures records for the time of the year in 2023. Also sea surface temperatures were exceptionally high for much of the year, which are believed to contribute to the [lowest sea ice extension in the Antarctic Ocean](https://wmo.int/media/news/wmo-confirms-2023-smashes-global-temperature-record), both for the end-of-summer minimum in February and end-of-winter maximum in September.
+
+
+
+ Ed Hawkins Stripes: each stripe represents a single year, blue and red representing cooler or warmer, respectively than the long-term average. Credits: showyourstripes
+
+
+
+The extreme temperatures experienced in 2023 and 2024 could be linked to El Niño, a climate pattern that warms the central and eastern tropical Pacific Ocean, [influencing global weather](https://www.esa.int/Applications/Observing_the_Earth/El_Nino ). This warming is associated with changes in atmospheric circulation which may result in extreme events [around the world](https://ncas.ac.uk/what-does-el-nino-mean-for-our-weather-climate-economy-and-health/ ) including heatwaves, floods and droughts. El Niño is part of the El Niño Southern Oscillation (ENSO), which refers to the entire cycle of these temperature fluctuations, and occurs irregularly every three to seven years. It starts when warm water from the Pacific Ocean moves eastward, replacing the cooler, nutrient-rich waters along the South American coast. This warmer water releases more moisture into the air, increasing rainfall and disturbing [global atmospheric circulation patterns](https://www.esa.int/Applications/Observing_the_Earth/El_Nino ). ENSO affects [most intensely the tropics, including vulnerable countries](https://www.who.int/news-room/fact-sheets/detail/el-nino-southern-oscillation-%28enso%29 ) and areas in Africa, Latin America, and South and South-East Asia. El Niño’s counterpart, known as ‘La Niña’, is considered the ‘cool phase’ of ENSO, and describes the unusual cooling of the region’s surface waters.
+
+
+
+
+ El Niño and La Niña. Credit: NOOA
+
+
+
+
+
+Despite the La Niña conditions in early 2023, global temperatures continued to rise, raising concerns among scientists about the potential for even more extreme heat with the onset of the upcoming El Niño. The 2023 El Niño event officially started on July 4, 2023, as declared by the World Meteorological Organization (WMO) after its development [was confirmed in June 2023](https://www.esa.int/Applications/Observing_the_Earth/Copernicus/Sentinel-3/Europe_braces_for_sweltering_July ). As of August 2024, ENSO-neutral conditions persist in the equatorial Pacific, but [forecasts](https://iri.columbia.edu/our-expertise/climate/forecasts/enso/current/) indicate a transition to La Niña later this year.
+
+## Earth observations of El Niño
+
+
To monitor El Niño, or study its impacts on global climate patterns, including heatwaves, and urban heat islands, scientists focus on several key variables using observations from satellites missions. These missions help monitor these variables, providing essential data for understanding for instance the terrestrial impacts of El Niño, particularly in how it influences heat distribution and exacerbates temperature extremes in populated areas.
+
+
+
+ Artist's impression of Sentinel-3 satellite. Credit: J.Huart
+
+
+
The map below shows Copernicus Sentinel-3 (S3) data acquired for the whole globe. Sentinel-3 is an operational mission that is part of the [Copernicus programme](https://www.copernicus.eu/en) and it plays a crucial role in monitoring El Niño events through its ability to provide accurate and timely measurements of land and sea surface temperatures. The instrument on-board, the [Sea and Land Surface Temperature Radiometer (SLSTR)](https://sentiwiki.copernicus.eu/web/s3-slstr-instrument) is a dual-view scanning temperature radiometer, which flies in low Earth orbit (800 - 830 km altitude). There are currently two instruments in orbit, on board the Sentinel-3A and Sentinel-3B satellites.
+
+As intense heat waves gripped regions including the southern USA, Mediterranean, North Africa, the Middle East, and parts of Asia, including China, the World Meteorological Organization announced plans to monitor potential new temperature records.
+
+## Heatwaves worldwide
+
+#
+
+
+
+* Southern USA: The Southwest and parts of the southern US have faced extreme heat conditions,[ with temperatures exceeding 50°C](https://www.worldweatherattribution.org/extreme-heat-in-north-america-europe-and-china-in-july-2023-made-much-more-likely-by-climate-change/) in Death Valley and record highs in states like Nevada and Arizona. The heat has resulted in multiple heat-related fatalities, particularly impacting vulnerable populations.
+* Mediterranean and North Africa: Countries such as Algeria, Tunisia, and Morocco [have reported unprecedented temperatures](https://crisis24.garda.com/alerts/2023/07/north-africa-heatwave-forecast-to-persist-across-much-of-algeria-morocco-and-tunisia-through-at-least-july-14), with readings reaching up to 50°C. In July, Algeria recorded 48.7°C, while Tunisia saw temperatures of 49°C. These extreme conditions have led to power outages and significant health risks, including heat-related deaths.
+* Middle East: The region has also been severely impacted, with temperatures in Mecca reaching 50.5°C. The extreme heat has coincided with the Hajj pilgrimage, [leading to casualties among pilgrims](https://timesofindia.indiatimes.com/travel/travel-news/heatwave-claims-lives-of-550-hajj-pilgrims-in-mecca-temperature-crosses-50-degrees-celsius/articleshow/111111469.cms). In Iran, a staggering heat index of 66.7°C was recorded, illustrating the severity of the situation.
+* Asia: Also China experienced [record heat](https://edition.cnn.com/2024/01/05/china/2023-hottest-year-china-climate-intl-hnk/index.html), with temperatures surpassing 40°C in several regions.
+
+
+## Urban heat islands
+Living in a city during a heatwave can be particularly difficult as people have to deal with the [urban heat island effect](https://https://www.rff.org/publications/explainers/urban-heat-islands-101/). Buildings, roads, pavements and other surfaces absorb and re-emit the Sun’s heat more than natural landcover such as forests and water bodies, causing urban areas to become ‘islands’ of higher temperatures compared to outlying rural areas. The difference between urban temperatures and rural temperatures tends to be more pronounced at night. Here, measurements of land-surface temperature are important to understand and monitor urban heat islands, and to plan mitigation strategies to reduce the effects of this phenomenon. It is worth noting the difference between air temperature and land-surface temperature. Air temperature, given in daily weather forecasts, is a measure of how hot the air is around 1 m above the ground. Land-surface temperature instead is a measure of how hot the actual surface would feel to the touch.
+
+
+
+ Heatwaves across Europe
+
+
+
+Data from the [Copernicus Sentinel-3 mission](https://sentiwiki.copernicus.eu/web/s3-mission) revealed land surface temperatures exceeding 45°C in several Italian cities on 9-10 July, with some areas, such as the eastern slopes of Mount Etna in Sicily, recording temperatures surpassing 50°C. Such summer heatwaves can have significant impacts on population health. A [study published in Nature Medicine](https://www.nature.com/articles/s41591-023-02419-z ) highlighted the severe impact of 2022's summer heatwaves in Europe, resulting in over 60,000 deaths, with Italy, Greece, Spain, and Portugal having experienced the highest mortality rates. The 2023 European State of the Climate report indicates an increase in the number of “adverse health impacts” [caused by extreme weather and climate events](https://turkiye.un.org/en/266674-heat-related-deaths-increased-across-almost-all-europe-2023-says-un-weather-agency).
+
+### Night time temperatures
+During heatwaves the temperature of the surface tends to be hotter than the temperature of the air. Images of night-time surface temperatures, taken in July by an instrument called ECOSTRESS showed the land-surface temperature over several European capitals in the evening or night-time on different dates in July 2023.
+
+## Night time temperatures
+
+
+###
+#### Night time temperatures measurements
+ The ECOSTRESS instrument, owned by NASA’s Jet Propulsion Laboratory, is important because it is helping in the development of a new Copernicus Sentinel Expansion satellite – the Land Surface Temperature Monitoring (LSTM) mission – so images such as these offer a glimpse of what the new mission will [deliver operationally ]( https://www.esa.int/Applications/Observing_the_Earth/Sensing_city_night_heat_from_space ).
+
+
+
+
+
+###
+#### Athens
+In Athens, the land-surface temperature was approximately 35°C at 20:02 CEST. This measurement reflects the intense heat experienced in urban areas, exacerbated by the urban heat island effect, where cities retain heat more than surrounding rural areas due to human activities and infrastructure.
+
+
+###
+#### Rome
+In Rome, the urban heat island effect was also prominent. On July 17, 2023, at 22:23 local time, the land-surface temperatures indicated that while the city remained a hotspot, the cooling effects of surrounding vegetation were visible, helping to moderate temperatures somewhat compared to the built-up areas.
+
+
+
+
+
+## Open Science
+
+
Here are some key types of variables and datasets from Earth observation satellite missions that can be used to track El Niño and La Niña events, with special attention to land-related surface temperatures. This summary focuses on missions from ESA, NASA, and JAXA:
+
+
+Himawari-8 satellite images of the 15 January 2022 eruption of Hunga Tonga-Hunga Haʻapai.
+Animation produced by the Japan Meteorological Agency (https://www.jma.go.jp/jma/kishou/info/coment.html). Legal notice (http://www.jma.go.jp/jma/en/copyright.html). Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/).
+
+
+
+## Satellite Observations
+
+###
+#### SO2 Plume
+Observations from several satellites such as ESA’s TROPOspheric Monitoring Instrument, TROPOMI onboard the Copernicus Sentinel-5p showed enhanced levels of stratospheric sulfur dioxide (SO2). The map illustrates the SO2 concentration observed by Sentinel-5p TROPOMI. Note that in this map the SO2 from potential anthropogenic sources has not been filtered out. The Copernicus Sentinel-5P SO2 measurements are those retrieved assuming SO2 at an altitude of 7km and explicitly filtering for pixels where a volcanic source is most likely (sulfurdioxide_detection_flag > 0) and where the solar zenith angle is within limits (SZA < 70°).
+
+Map information: SO2 plume observed by Copernicus Sentinel-5p TROPOMI on 17 of January 2022
+
+###
+#### Impact on the Hunga Tonga Island
+The eruption caused significant damages to Tonga and neighbouring countries in the South Pacific.
+
+This map shows the Hunga Tonga - Hunga Ha'apai island before the eruption observed by the Copernicus Sentinel-2 on 08 December 2021.
+###
+#### Dissapearance of the island
+This map shows the Hunga Tonga - Hunga Ha'apai island after the eruption observed by the Copernicus Sentinel-2 on 27 January 2022.
+
+###
+In the context of this disaster, [Advanced Land Observing Satellite-2 “DAICHI-2” (ALOS-2)]( https://global.jaxa.jp/projects/sat/alos2/) PALSAR-2 synthetic aperture radar provided emergency observations due to its capability of imaging under clouds and plumes. The images below made available on the [Sentinel-Asia website](https://sentinel-asia.org/EO/2022/article20220115TO.html) show the main island of Tonga before (2020/03/07) and after (2022/01/22) the eruption observed by JAXA’s ALOS-2 PALSAR-2.
+
+
+
+
+
+
+## Data and Methods
+
+This section presents the method to track the plume of the Hunga erruption that was developed by the team of students during the Science Hub Challenge.
+
+In order to precisely monitor the movement of the sulfur dioxide plume from the Hung a erruption, the students used sulfate aerosol data (Siddans et al., 2022) produced by RAL (Rutherford Appleton Laboratory) with co-located satellite data from by IASI (Infrared Atmospheric Sounding Interferometer), AMSU (Advanced Microwave Sounding Unit) and MHS(Microwave Humidity Sounder) on MetOp-B spacecraft. They were interested in the optical properties of the components of the plume, especially the sulfate aerosols optical depth (SAOD). The injected SO2 was rapidly converted into sulfate aerosols thanks to the abundant presence of water vapor in the stratosphere (Legras et al., 2022). The SAOD measurements allowed them to understand where the plume is located and its displacement. In order to track the plume they tracked the sulfate aerosols within the plume.
+
+However, because of the satellite geometry, particularly the swath wide, the gaps in their datasets made it hard to follow efficiently the movement of the aerosols.
+
+
+
+Visualisation of the plume between 13/01/2022 and 29/01/2022 (no interpolation)
+
+The students’ idea was to use temporal interpolation techniques to be able to fill in those missing data.
+To do so they constructed their research following these four steps:
+1. Selection of consecutive time series data of days before, during and after the event.
+2. Introduction of temporal gaps of different periods
+3. Interpolation using different algorithms: namely linear regression and second-degree polynomial regression* methods to fill in the temporal gaps
+4. Comparison of interpolation methods
+
+Starting from the selection of time series data, consecutive time series data were selected by choosing a single pixel within the aerosol plume, ensuring it has no temporal gaps, and retrieving data from a random pixel within the plume. Temporal gaps of various durations were then introduced by randomly removing points from the dataset. Subsequently, different interpolation algorithms, such as linear regression and second-degree polynomial regression, were applied to fill these gaps, followed by a comparison of their effectiveness. The chosen interpolation method was then adapted to the dataset, creating linear interpolation functions based on SAOD and date time series.
+The linear interpolation function for one pixel involved looping over the time series, addressing gaps where both adjacent points or a single point are missing, and implementing interpolation based on general cases and boundary conditions.
+
+Finally, new maps were computed by generating interpolated time series and plotting SAOD to visualize the results, aiming to accurately fill temporal gaps in satellite data and produce detailed maps of the aerosol plume's characteristics. By following these steps, the project aimed to effectively fill in temporal gaps in the satellite data and produce accurate interpolated maps of the aerosol plume.
+To reproduce this experiment, the data and code are made openly available.
+
+
+
+Visualisation of the plume between 13/01/2022 and 31/01/2022 (after interpolation)
+
+## Conclusions
+In this work, the students concluded that relevant interpolation is possible with linear regression, and that gap filling by interpolation allows to improve the precision of the evolution of the plume. This strenghtens the evaluation of the radiative impact of the sulfates (especially for satellite tracks). The method still has a few weaknesses at this stage. From a technical point of view the team suggests further improvements by implementing a 2nd degree interpolation with more points and develop the function to handle 3 or maybe more consecutive gaps, as well as potentially implementing a shift to take into account the rapid horizontal displacement of the plume with the wind angular rotation speed from ERA5 reanalysis.
+
+In the context of climate change, monitoring and understanding the impacts of such extremes is essential for adaptation and mitigation. In fact, studies of stratospheric volcanic eruptions and their long term radiative impacts can provide important results for geoengineering. With the warming climate, solutions such as injecting highly diffusive particles such as sulfate aerosols directly into the stratosphere are being explored to limit rising temperatures. In this context, stratospheric volcanic eruptions provide important real-world case studies to see the impact of gases or particles injected directly at high altitude.
+
+#### Precursors to underwater volcanic eruptions
+
+Satellites can provide essential information about volcanic activtiy long before eruptions occur.
+
+Observations from JAXA’s [Global Change Observation Mission – Climate “SHIKISAI” (GCOM-C)]( https://global.jaxa.jp/projects/sat/gcom_c/) offered information about precursor processes such as the presence of discolored seawater originated by the reaction of hot water caused by volcanic activity with seawater, suggesting enhancement of volcanic activity. Read more about this on the [JAXA website]( https://earth.jaxa.jp/en/earthview/2022/01/20/6701/index.html).
+
+Other precursor information about volcanic activity comes from below the Earth’s crust. Understanding of the natural processes such as the buildup in the mantle supports the development of methods for better characterisation and prediction of eruptions. Satellite data from GOCE – ESA’s gravity mission – provided essential information to improve our understanding of the processes beneath the Hunga Tonga-Hunga Ha‘apai. [ESA’s Science for Society 3D Earth project](https://eo4society.esa.int/projects/stse-3d-earth/) developed a model of the lithosphere combining different satellite data, such as gravity data from ESA’s GOCE mission, with in-situ observations, which showed differences in temperature, or thermal structures, indicating that the Tonga volcano was due to erupt at some point. Read more about this on the [ESA website]( https://www.esa.int/Applications/Observing_the_Earth/FutureEO/GOCE/Deep_down_temperature_shifts_give_rise_to_eruptions).
+
+
+ 
+ 
+ 
+ 
+ 
+ 
+ 
+ 
+
+TROPOMI Instrument. Source: ESA
+
+
+CO daily variation in 2023 for Lahore
+
+
+CO daily variation in 2023 for New Delhi
+
+
+CO daily variation in 2023 for Lucknow
+
+ 
+ 
+ 
+ 
+ 
+ 
+ 
+ 
+
+
+
+###
+#### Athens
+In Athens, the land-surface temperature was approximately 35°C at 20:02 CEST. This measurement reflects the intense heat experienced in urban areas, exacerbated by the urban heat island effect, where cities retain heat more than surrounding rural areas due to human activities and infrastructure.
+
+
+###
+#### Rome
+In Rome, the urban heat island effect was also prominent. On July 17, 2023, at 22:23 local time, the land-surface temperatures indicated that while the city remained a hotspot, the cooling effects of surrounding vegetation were visible, helping to moderate temperatures somewhat compared to the built-up areas.
+
+
+
+
+
+## Open Science
+
+
+
+Himawari-8 satellite images of the 15 January 2022 eruption of Hunga Tonga-Hunga Haʻapai.
+Animation produced by the Japan Meteorological Agency (https://www.jma.go.jp/jma/kishou/info/coment.html). Legal notice (http://www.jma.go.jp/jma/en/copyright.html). Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/).
+ 
+
+
+
+
+## Data and Methods
+
+This section presents the method to track the plume of the Hunga erruption that was developed by the team of students during the Science Hub Challenge.
+
+In order to precisely monitor the movement of the sulfur dioxide plume from the Hung a erruption, the students used sulfate aerosol data (Siddans et al., 2022) produced by RAL (Rutherford Appleton Laboratory) with co-located satellite data from by IASI (Infrared Atmospheric Sounding Interferometer), AMSU (Advanced Microwave Sounding Unit) and MHS(Microwave Humidity Sounder) on MetOp-B spacecraft. They were interested in the optical properties of the components of the plume, especially the sulfate aerosols optical depth (SAOD). The injected SO2 was rapidly converted into sulfate aerosols thanks to the abundant presence of water vapor in the stratosphere (Legras et al., 2022). The SAOD measurements allowed them to understand where the plume is located and its displacement. In order to track the plume they tracked the sulfate aerosols within the plume.
+
+However, because of the satellite geometry, particularly the swath wide, the gaps in their datasets made it hard to follow efficiently the movement of the aerosols.
+
+
+
+Visualisation of the plume between 13/01/2022 and 29/01/2022 (no interpolation)
+
+The students’ idea was to use temporal interpolation techniques to be able to fill in those missing data.
+To do so they constructed their research following these four steps:
+1. Selection of consecutive time series data of days before, during and after the event.
+2. Introduction of temporal gaps of different periods
+3. Interpolation using different algorithms: namely linear regression and second-degree polynomial regression* methods to fill in the temporal gaps
+4. Comparison of interpolation methods
+
+Starting from the selection of time series data, consecutive time series data were selected by choosing a single pixel within the aerosol plume, ensuring it has no temporal gaps, and retrieving data from a random pixel within the plume. Temporal gaps of various durations were then introduced by randomly removing points from the dataset. Subsequently, different interpolation algorithms, such as linear regression and second-degree polynomial regression, were applied to fill these gaps, followed by a comparison of their effectiveness. The chosen interpolation method was then adapted to the dataset, creating linear interpolation functions based on SAOD and date time series.
+The linear interpolation function for one pixel involved looping over the time series, addressing gaps where both adjacent points or a single point are missing, and implementing interpolation based on general cases and boundary conditions.
+
+Finally, new maps were computed by generating interpolated time series and plotting SAOD to visualize the results, aiming to accurately fill temporal gaps in satellite data and produce detailed maps of the aerosol plume's characteristics. By following these steps, the project aimed to effectively fill in temporal gaps in the satellite data and produce accurate interpolated maps of the aerosol plume.
+To reproduce this experiment, the data and code are made openly available.
+
+
+
+Visualisation of the plume between 13/01/2022 and 31/01/2022 (after interpolation)
+
+## Conclusions
+In this work, the students concluded that relevant interpolation is possible with linear regression, and that gap filling by interpolation allows to improve the precision of the evolution of the plume. This strenghtens the evaluation of the radiative impact of the sulfates (especially for satellite tracks). The method still has a few weaknesses at this stage. From a technical point of view the team suggests further improvements by implementing a 2nd degree interpolation with more points and develop the function to handle 3 or maybe more consecutive gaps, as well as potentially implementing a shift to take into account the rapid horizontal displacement of the plume with the wind angular rotation speed from ERA5 reanalysis.
+
+In the context of climate change, monitoring and understanding the impacts of such extremes is essential for adaptation and mitigation. In fact, studies of stratospheric volcanic eruptions and their long term radiative impacts can provide important results for geoengineering. With the warming climate, solutions such as injecting highly diffusive particles such as sulfate aerosols directly into the stratosphere are being explored to limit rising temperatures. In this context, stratospheric volcanic eruptions provide important real-world case studies to see the impact of gases or particles injected directly at high altitude.
+
+#### Precursors to underwater volcanic eruptions
+
+Satellites can provide essential information about volcanic activtiy long before eruptions occur.
+
+Observations from JAXA’s [Global Change Observation Mission – Climate “SHIKISAI” (GCOM-C)]( https://global.jaxa.jp/projects/sat/gcom_c/) offered information about precursor processes such as the presence of discolored seawater originated by the reaction of hot water caused by volcanic activity with seawater, suggesting enhancement of volcanic activity. Read more about this on the [JAXA website]( https://earth.jaxa.jp/en/earthview/2022/01/20/6701/index.html).
+
+Other precursor information about volcanic activity comes from below the Earth’s crust. Understanding of the natural processes such as the buildup in the mantle supports the development of methods for better characterisation and prediction of eruptions. Satellite data from GOCE – ESA’s gravity mission – provided essential information to improve our understanding of the processes beneath the Hunga Tonga-Hunga Ha‘apai. [ESA’s Science for Society 3D Earth project](https://eo4society.esa.int/projects/stse-3d-earth/) developed a model of the lithosphere combining different satellite data, such as gravity data from ESA’s GOCE mission, with in-situ observations, which showed differences in temperature, or thermal structures, indicating that the Tonga volcano was due to erupt at some point. Read more about this on the [ESA website]( https://www.esa.int/Applications/Observing_the_Earth/FutureEO/GOCE/Deep_down_temperature_shifts_give_rise_to_eruptions).
+
+
+