Methane (CH4) is a potent greenhouse gas with high radiative forcing and a relatively short atmospheric lifetime of around a decade. We used a decade-long dataset (2011-2022) from the Fourier transform spectrometer at the California Laboratory for Atmospheric Remote Sensing (CLARS-FTS) to quantify a dramatic increase in methane observed in 2020. We report an increase of 1.13 ppb/month starting in 2020 until the end of 2021, compared to a growth rate of 0.345 ppb/month from 2016 to 2019. The observed increase in methane concentrations in 2020 is of significant concern due to its potential contribution to global warming. The Total Carbon Column Observing Network (TCCON) is then used to examine the global geospatial variability of the increase in methane. The results suggest an approximately uniform rise in methane globally. Finally, results from a two-box model used to simulate atmospheric chemical processes of methane production and loss indicate that changes in OH alone are insufficient to explain the rise in atmospheric methane. Encouragingly, recent data from 2022 suggest a deceleration in the methane growth rate, indicating a potential slowdown in the methane increase observed in 2020.

Throughout spring and summer 2020, ozone stations in the northern extratropics recorded unusually low ozone in the free troposphere. From April to August, and from 1 to 8 kilometers altitude, ozone was on average 7% (~4 ppbv) below the 2000 to 2020 climatological mean. Such low ozone, over several months, and at so many stations, has not been observed in any previous year since at least 2000. Atmospheric composition re-analyses from the Copernicus Atmosphere Monitoring Service and simulations from the NASA GMI model indicate that the large 2020 springtime ozone depletion in the Arctic stratosphere has contributed less than one quarter to the observed tropospheric anomaly. The observed anomaly is consistent with two recent model simulations, which assume emission reductions similar to those caused by the COVID-19 crisis. COVID-19 related emission reductions appear to be the major cause for the observed low free tropospheric ozone in 2020.

Atmospheric balloon soundings have been made since the end of the 19th century. In recent decades, specific upper-air radiosonde measurements have become important for climate monitoring and atmospheric research. Here we show profiles of solar and terrestrial radiation measured with balloon-borne radiometers through cloud-free and cloudy atmospheres, which experimentally demonstrate the greenhouse effect by water vapor in the Earth’s atmosphere. Absorption and reflection of solar shortwave radiation in the atmosphere and on the ground are shown. Thermal longwave radiation, emitted from Earth’s surface and then absorbed and reemitted in the atmosphere, shows varying absorption/reemission of upward/downward longwave fluxes due to changing temperature and water vapor. Clouds more strongly absorb upward and increase downward longwave radiation. Thermal emission into space is shown to be reduced by water vapor and clouds. Measured radiation profiles are compared to numerically calculated radiation profiles.

Inland waters, such as lakes, reservoirs and rivers, are important sources of greenhouse gases to the atmosphere. A key parameter that regulates the gas exchange between water and the atmosphere is the gas transfer velocity, which itself is controlled by near-surface turbulence in the water. While in lakes and reservoirs, near-surface turbulence is mainly driven by atmospheric forcing, in shallow rivers and streams it is generated by flow-induced bottom friction. Large rivers represent a transition between these two cases. Near-surface turbulence has rarely been observed in rivers and the drivers of turbulence have not been quantified. We obtained continuous measurements of flow velocity and fluctuations from which we quantified turbulence, as the rate of dissipation of turbulent kinetic energy ($\varepsilon$) over the ice-free season in a large regulated river in Northern Finland. Atmospheric forcing was observed simultaneously. Measured values of $\varepsilon$ were well predicted from bulk parameters, including mean flow velocity, wind speed, surface heat flux and a one-dimensional numerical turbulence model. Values ranged from $\sim 10^{-9}$ m$^2$ s$^{-3}$ to $10^{-5}$ m$^2$ s$^{-3}$. Atmospheric forcing and river flow contributed to near-surface turbulence a similar fraction of the time, with variability in near-surface dissipation rate occurring at diel time scales, when the flow velocity was strongly affected by downstream dam operation. By combining scaling relations for boundary-layer turbulence at the river bed and at the air-water interface, we derived a simple model for estimating the relative contributions of wind speed and bottom friction in rivers as a function of flow depth.

In the Antarctic ozone hole, ozone mixing ratios have been decreasing to extremely low values of 0.01-0.1 ppm in nearly all spring seasons since the late 1980s, corresponding to 95-99 % local chemical loss. In contrast, Arctic ozone loss has been much more limited and mixing ratios have never before fallen below 0.5 ppm. In Arctic spring 2020, however, ozone sonde measurements in the most depleted parts of the polar vortex show a highly depleted layer, with ozone loss averaged over sondes peaking at 93 % at 18 km. Typical minimum mixing ratios of 0.2 ppm were observed, with individual profiles showing values as low as 0.13 ppm (96 % loss). The reason for the unprecedented chemical loss was an unusually strong, long-lasting and cold polar vortex, showing that for individual winters the effect of the slow decline of ozone-depleting substances on ozone depletion may be counteracted by low temperatures.

TanSat is the 1st Chinese carbon dioxide (CO) measurement satellite, launched in 2016. In this study, the University of Leicester Full Physics (UoL-FP) algorithm is implemented for TanSat nadir mode XCO retrievals. We develop a spectrum correction method to reduce the retrieval errors by the online fitting of an 8 order Fourier series. The model and a priori is developed by analyzing the solar calibration measurement. This correction provides a significant improvement to the O A band retrieval. Accordingly, we extend the previous TanSat single CO weak band retrieval to a combined O A and CO weak band retrieval. A Genetic Algorithm (GA) has been applied to determine the threshold values of post-screening filters. In total, 18.3% of the retrieved data is identified as high quality compared to the original measurements. The same quality control parameters have been used in a footprint independent multiple linear regression bias correction due to the stronger correlation with the XCO retrieval error. Twenty sites of the Total Column Carbon Observing Network (TCCON) have been selected to validate our new approach for the TanSat XCO retrieval. We show that our new approach produces a significant improvement on the XCO retrieval accuracy and precision when compared to TCCON with an average bias and RMSE of -0.08 ppm and 1.47 ppm, respectively. The methods used in this study can help to improve the XCO retrieval from TanSat and subsequently the Level-2 data production, and hence will be applied in the TanSat operational XCO processing.