Climate Change Monitoring Using TROPOMI

The TROPOMI or Tropospheric Monitoring Instrument is the satellite instrument onboard the Copernicus Sentinel-5 Precursor (S-5P) satellite, allowing scientists to measure and observe the atmosphere from the orbiting satellite above it.

The troposphere is the lowest layer of the Earth’s atmosphere, where 80% of the atmospheric mass resides. Because it is the closest layer of the atmosphere, the troposphere is the most important to all life.

The troposphere comprises various gas, but the two main ones are nitrogen at 78% and oxygen at 21%; the remaining 1% consists of other gasses, including carbon dioxide and methane. 

The amount of carbon dioxide in the troposphere determines the Earth’s temperature. A smaller amount will cause the ice ages, and a more significant amount will produce hot periods on the planet. Carbon dioxide thereby plays a vital role in keeping Earth’s temperatures at levels that live on Earth can survive.

The increased burning of fossil fuels to meet the energy demands of our growing population is harming our natural environment leading to climate change and air pollution. To mitigate its effects on all life forms on our planet will require studying the whole Earth’s systems consisting of land, oceans, and atmosphere and monitoring their interactions.

The S-5P is part of the Sentinel series of satellites developed under the Copernicus Earth Observation Program to monitor various aspects of our planet, including the monitoring of atmospheric composition.

TROPOMI can detect greenhouse gases that impact our air quality and climates, such as carbon dioxide, a significant cause of global warming, and other polluting gases such as nitrogen dioxide (NO2) and sulphur dioxide (SO2) and methane – a more potent than carbon dioxide when it comes to warming the planet.

Long time series of observations from ground and space helps scientists understand the physical and chemical processes and distinguish between natural and man-made contributions to air quality and climate changes.

Scientists can use the daily global observations to improve air quality forecasting and monitor atmospheric concentrations of gasses.

It also helps scientists estimate long-term trends relating to air quality and climate from the regional to the global scale in the troposphere and use daily global observations to improve air quality forecasting and monitor atmospheric concentrations of gasses.

A study by an international team of researchers uses the TROPOMI to measure the atmospheric moisture in relation to the Earth’s radiative budget (the overall balance between the incoming energy from the sun and the outgoing thermal and reflected energy from the Earth, which can only be measured from space) and how it transports energy from low to high latitudes to predict climate better.

Below are excerpts from the study, “Retrieving H2O/HDO columns over cloudy and clear-sky scenes from the Tropospheric Monitoring Instrument (TROPOMI).”

“This paper presents an extension of the scientific HDO/H2O column data product from the Tropospheric Monitoring Instrument (TROPOMI), including clear-sky and cloudy scenes. The retrieval employs a forward model which accounts for scattering, and the algorithm infers the trace gas column information, surface properties and effective cloud parameters from the observations. The extension to cloudy scenes greatly enhances coverage, particularly enabling data over oceans. The data set is validated against co-located ground-based Fourier transform infrared (FTIR) observations by the Total Carbon Column Observing Network (TCCON). The median bias for clear-sky scenes is 1.4 × 1021 molec cm−2 (2.9 %) in H2O columns and 1.1 × 1017 molec cm−2 (−0.3 %) in HDO columns, which corresponds to −17 ‰ (9.9 %) in a posteriori δD. The bias for cloudy scenes is 4.9 × 1021 molec cm−2 (11 %) in H2O, 1.1 × 1017 molec cm−2 (7.9 %) in HDO, and −20 ‰ (9.7 %) in a posteriori δD. At low-altitude stations in low and middle latitudes, the bias is small and has a larger value at high latitude stations. An altitude correction is required to compensate for different partial columns seen by the station and the satellite at high altitude stations. The bias in a posteriori δD after altitude correction depends on sensitivity due to shielding by clouds and on realistic prior profile shapes for both isotopologues. Cloudy scenes generally involve low sensitivity below the clouds, and since the information is filled up by the prior, it plays an important role in these cases. Over oceans, aircraft measurements with the Water Isotope System for Precipitation and Entrainment Research (WISPER) instrument from a field campaign in 2018 are used for validation, yielding a bias of −3.9 % in H2O and −3 ‰ in δD over clouds. To demonstrate the added value of the new data set, a short case study of a cold air outbreak over the Atlantic Ocean in January 2020 is presented, showing the daily evolution of the event with single overpass results.”

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