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The STIS and ACS instruments onboard HST are widely used to study the giant planet's aurora. Several assumptions have to be made to convert the instrumental counts into meaningful physical values (type and bandwidth of the filters, definition of the physical units, etc…), but these may significantly differ from one author to another, which makes it difficult to compare the auroral characteristics published in different studies. We present a method to convert the counts obtained in representative ACS and STIS imaging modes/filters used by the auroral scientific community to brightness, precipitated power and radiated power in the ultraviolet (700–1800 Å). Since hydrocarbon absorption may considerably affect the observed auroral emission, the conversion factors are determined for several attenuation levels. Several properties of the auroral emission have been determined: the fraction of the H2 emission shortward and longward of the HLy‐α line is 50.3% and 49.7% respectively, the contribution of HLy‐α to the total unabsorbed auroral signal has been set to 9.1% and an input of 1 mW m−2 produces 10 kR of H2 in the Lyman and Werner bands. A first application sets the order of magnitude of Saturn's auroral characteristics in the total UV bandwidth to a brightness of 10 kR and an emitted power of ∼2.8 GW. A second application uses published brightnesses of Europa's footprint to determine the current density associated with the Europa auroral spot: 0.21 and 0.045 μA m−2 assuming no hydrocarbon absorption and a color ratio of 2, respectively. Factors to extend the brightnesses observed with Cassini‐UVIS to total H2 UV brightnesses are also provided. Key Points Gives tools to convert observed data to data in physical units Provides key numbers to characterize auroral parameters Will help to uniformize studies made by different authors

Traditionally, balloon-based radiosonde soundings are used to study the spatial distribution of atmospheric water vapour. However, this approach cannot be frequently employed due to its high cost. In contrast, GPS tomography technique can obtain water vapour in a high temporal resolution. In the tomography technique, an iterative or non-iterative reconstruction algorithm is usually utilised to overcome rank deficiency of observation equations for water vapour inversion. However, the single iterative or non-iterative reconstruction algorithm has their limitations. For instance, the iterative reconstruction algorithm requires accurate initial values of water vapour while the non-iterative reconstruction algorithm needs proper constraint conditions. To overcome these drawbacks, we present a combined iterative and non-iterative reconstruction approach for the three-dimensional (3-D) water vapour inversion using GPS observations and COSMIC profiles. In this approach, the non-iterative reconstruction algorithm is first used to estimate water vapour density based on a priori water vapour information derived from COSMIC radio occultation data. The estimates are then employed as initial values in the iterative reconstruction algorithm. The largest advantage of this approach is that precise initial values of water vapour density that are essential in the iterative reconstruction algorithm can be obtained. This combined reconstruction algorithm (CRA) is evaluated using 10-day GPS observations in Hong Kong and COSMIC profiles. The test results indicate that the water vapor accuracy from CRA is 16 and 14% higher than that of iterative and non-iterative reconstruction approaches, respectively. In addition, the tomography results obtained from the CRA are further validated using radiosonde data. Results indicate that water vapour densities derived from the CRA agree with radiosonde results very well at altitudes above 2.5 km. The average RMS value of their differences above 2.5 km is 0.44 g m−3.

Ultra-sensitive space-borne accelerometers on board of low Earth orbit (LEO) satellites are used to measure non-gravitational forces acting on the surface of these satellites. These forces consist of the Earth radiation pressure, the solar radiation pressure and the atmospheric drag, where the first two are caused by the radiation emitted from the Earth and the Sun, respectively, and the latter is related to the thermospheric density. On-board accelerometer measurements contain systematic errors, which need to be mitigated by applying a calibration before their use in gravity recovery or thermospheric neutral density estimations. Therefore, we improve, apply and compare three calibration procedures: (1) a multi-step numerical estimation approach, which is based on the numerical differentiation of the kinematic orbits of LEO satellites; (2) a calibration of accelerometer observations within the dynamic precise orbit determination procedure and (3) a comparison of observed to modeled forces acting on the surface of LEO satellites. Here, accelerometer measurements obtained by the Gravity Recovery And Climate Experiment (GRACE) are used. Time series of bias and scale factor derived from the three calibration procedures are found to be different in timescales of a few days to months. Results are more similar (statistically significant) when considering longer timescales, from which the results of approach (1) and (2) show better agreement to those of approach (3) during medium and high solar activity. Calibrated accelerometer observations are then applied to estimate thermospheric neutral densities. Differences between accelerometer-based density estimations and those from empirical neutral density models, e.g., NRLMSISE-00, are observed to be significant during quiet periods, on average 22 % of the simulated densities (during low solar activity), and up to 28 % during high solar activity. Therefore, daily corrections are estimated for neutral densities derived from NRLMSISE-00. Our results indicate that these corrections improve model-based density simulations in order to provide density estimates at locations outside the vicinity of the GRACE satellites, in particular during the period of high solar/magnetic activity, e.g., during the St. Patrick's Day storm on 17 March 2015.

Accurate continuous measurements of relative humidity (RH) vertical profiles in the lower troposphere have become a significant scientific challenge. In recent years a synergy of various ground-based remote sensing instruments have been successfully used for RH vertical profiling, which has resulted in the improvement of spatial resolution and, in some cases, of the accuracy of the measurement. Some studies have also suggested the use of high-resolution model simulations as input datasets into RH vertical profiling techniques. In this paper we apply two synergetic methods for RH profiling, including the synergy of lidar with a microwave radiometer and high-resolution atmospheric modeling. The two methods are employed for RH retrieval between 100 and 6000 m with increased spatial resolution, based on datasets from the HygrA-CD (Hygroscopic Aerosols to Cloud Droplets) campaign conducted in Athens, Greece from May to June 2014. RH profiles from synergetic methods are then compared with those retrieved using single instruments or as simulated by high-resolution models. Our proposed technique for RH profiling provides improved statistical agreement with reference to radiosoundings by 27 % when the lidar–radiometer (in comparison with radiometer measurements) approach is used and by 15 % when a lidar model is used (in comparison with WRF-model simulations). Mean uncertainty of RH due to temperature bias in RH profiling was  ∼ 4.34 % for the lidar–radiometer and  ∼ 1.22 % for the lidar–model methods. However, maximum uncertainty in RH retrievals due to temperature bias showed that lidar-model method is more reliable at heights greater than 2000 m. Overall, our results have demonstrated the capability of both combined methods for daytime measurements in heights between 100 and 6000 m when lidar–radiometer or lidar–WRF combined datasets are available.

The Ground-Based Millimeter-wave Spectrometer (GBMS) was designed and built at the State University of New York at Stony Brook in the early 1990s and since then has carried out many measurement campaigns of stratospheric O3 , HNO3 , CO and N2 O at polar and mid-latitudes. Its HNO3 data set shed light on HNO3 annual cycles over the Antarctic continent and contributed to the validation of both generations of the satellite-based JPL Microwave Limb Sounder (MLS). Following the increasing need for long-term data sets of stratospheric constituents, we resolved to establish a long-term GMBS observation site at the Arctic station of Thule (76.5° N, 68.8° W), Greenland, beginning in January 2009, in order to track the long- and short-term interactions between the changing climate and the seasonal processes tied to the ozone depletion phenomenon. Furthermore, we updated the retrieval algorithm adapting the Optimal Estimation (OE) method to GBMS spectral data in order to conform to the standard of the Network for the Detection of Atmospheric Composition Change (NDACC) microwave group, and to provide our retrievals with a set of averaging kernels that allow more straightforward comparisons with other data sets. The new OE algorithm was applied to GBMS HNO3 data sets from 1993 South Pole observations to date, in order to produce HNO3 version 2 (v2) profiles. A sample of results obtained at Antarctic latitudes in fall and winter and at mid-latitudes is shown here. In most conditions, v2 inversions show a sensitivity (i.e., sum of column elements of the averaging kernel matrix) of 100 ± 20 % from 20 to 45 km altitude, with somewhat worse (better) sensitivity in the Antarctic winter lower (upper) stratosphere. The 1σ uncertainty on HNO3 v2 mixing ratio vertical profiles depends on altitude and is estimated at ~15 % or 0.3 ppbv, whichever is larger. Comparisons of v2 with former (v1) GBMS HNO3 vertical profiles, obtained employing the constrained matrix inversion method, show that v1 and v2 profiles are overall consistent. The main difference is at the HNO3 mixing ratio maximum in the 20-25 km altitude range, which is smaller in v2 than v1 profiles by up to 2 ppbv at mid-latitudes and during the Antarctic fall. This difference suggests a better agreement of GBMS HNO3 v2 profiles with both UARS/ and EOS Aura/MLS HNO3 data than previous v1 profiles.

Ground-based observations of OH (6, 2) Meinel band nightglow were carried out at Ranchi (23.3° N, 85.3° E), India, during January-March 2011, December 2011-May 2012 and December 2012-March 2013 using an all-sky imaging system. Near the mesopause, OH temperatures were derived from the OH (6, 2) Meinel band intensity information. A limited comparison of OH temperatures (T.sub.OH) with SABER/TIMED measurements in 30 cases was performed by defining almost coincident criterion of ±1.5° latitude-longitude and ±3 min of the ground-based observations. Using SABER OH 1.6 and 2.0 µm volume emission rate profiles as the weighing function, two sets of OH-equivalent temperature (T.sub.1. 6 and T.sub.2. 0 respectively) were estimated from its kinetic temperature profile for comparison with OH nightglow measurements. Overall, fair agreement existed between ground-based and SABER measurements in the majority of events within the limits of experimental errors. Overall, the mean value of OH-derived temperatures and SABER OH-equivalent temperatures were 197.3 ± 4.6, 192.0 ± 10.8 and 192.7 ± 10.3 K, and the ground-based temperatures were 4-5 K warmer than SABER values. A difference of 8 K or more is noted between two measurements when the peak of the OH emission layer lies in the vicinity of large temperature inversions. A comparison of OH temperatures derived using different sets of Einstein transition probabilities and SABER measurements was also performed; however, OH temperatures derived using Langhoff et al. (1986) transition probabilities were found to compare well.

High-precision analyses of the isotopic composition of methane in ambient air can potentially be used to discriminate between different source categories. Due to the complexity of isotope ratio measurements, such analyses have generally been performed in the laboratory on air samples collected in the field. This poses a limitation on the temporal resolution at which the isotopic composition can be monitored with reasonable logistical effort. Here we present the performance of a dual isotope ratio mass spectrometric system (IRMS) and a quantum cascade laser absorption spectroscopy (QCLAS)-based technique for in situ analysis of the isotopic composition of methane under field conditions. Both systems were deployed at the Cabauw Experimental Site for Atmospheric Research (CESAR) in the Netherlands and performed in situ, high-frequency (approx. hourly) measurements for a period of more than 5 months. The IRMS and QCLAS instruments were in excellent agreement with a slight systematic offset of (+0.25 ± 0.04) ‰ for δ13C and (−4.3 ± 0.4) ‰ for δD. This was corrected for, yielding a combined dataset with more than 2500 measurements of both δ13C and δD. The high-precision and high-temporal-resolution dataset not only reveals the overwhelming contribution of isotopically depleted agricultural CH4 emissions from ruminants at the Cabauw site but also allows the identification of specific events with elevated contributions from more enriched sources such as natural gas and landfills. The final dataset was compared to model calculations using the global model TM5 and the mesoscale model FLEXPART-COSMO. The results of both models agree better with the measurements when the TNO-MACC emission inventory is used in the models than when the EDGAR inventory is used. This suggests that high-resolution isotope measurements have the potential to further constrain the methane budget when they are performed at multiple sites that are representative for the entire European domain.

Seismic imaging is one of the most powerful tools available for constraining the internal structure and composition of planetary bodies as well as enabling our understanding planetary evolution, geology, and distribution of natural resources. However, traditional seismic instrumentation can be heavy and voluminous, expensive, and/or difficult to rapidly deploy in large numbers. Distributed acoustic sensing (DAS) provides a promising new alternative given the ease of deployment, light weight and simplicity of fiber optic cables. However, the feasibility and best operational practices for using DAS for planetary exploration are not well‐known. We examine the use of DAS with surface deployed fiber for planetary near‐surface seismic exploration at two lunar geophysical analogue sites in San Francisco Volcanic Field. We compare DAS recordings to 3‐component seismometer recordings and geophone shot recordings and determine empirical response functions for the DAS system with respect to the 3‐component recordings. Shot sections of DAS and traditional seismic equipment compare well visually, with similar moveout of identifiable phases. DAS records first arrivals in good agreement with seismometers making them suitable for refraction work. Multichannel analysis of surface waves is performed on DAS records to estimate shallow shear velocities. The DAS has high spectral coherence with the horizontal components of ∼0.7 in the frequency band of the seismic shot energy. The empirical response functions are stable with amplitudes of ∼1.0–3.0 × 10−10 m per strain. Finally, the phase response is linear but not flat or zero. Our experiment demonstrates that there is potential for surface deployed DAS in planetary landscapes. Key Points Distributed acoustic sensing (DAS) with surface deployed fiber is tested for near surface active‐source seismic imaging for planetary studies Lunar analogue substrates require different fiber coupling strategies and highlight the need for optimizing deployment and DAS parameters DAS records compare reasonably with traditional seismic equipment, highlighting the potential for DAS in future planetary and lunar work

The Hamburg Aerosol Module version 2.3 (HAM2.3) from the ECHAM6.3‐HAM2.3 global atmosphere‐aerosol model is coupled to the recently developed icosahedral nonhydrostatic ICON‐A (icon‐aes‐1.3.00) global atmosphere model to yield the new ICON‐A‐HAM2.3 atmosphere‐aerosol model. The ICON‐A and ECHAM6.3 host models use different dynamical cores, parameterizations of vertical mixing due to sub‐grid scale turbulence, and parameter settings for radiation balance tuning. Here, we study the role of the different host models for simulated aerosol optical thickness (AOT) and evaluate impacts of using HAM2.3 and the ECHAM6‐HAM2.3 two‐moment cloud microphysics scheme on several meteorological variables. Sensitivity runs show that a positive AOT bias over the subtropical oceans is remedied in ICON‐A‐HAM2.3 because of a different default setting of a parameter in the moist convection parameterization of the host models. The global mean AOT is biased low compared to MODIS satellite instrument retrievals in ICON‐A‐HAM2.3 and ECHAM6.3‐HAM2.3, but the bias is larger in ICON‐A‐HAM2.3 because negative AOT biases over the Amazon, the African rain forest, and the northern Indian Ocean are no longer compensated by high biases over the sub‐tropical oceans. ICON‐A‐HAM2.3 shows a moderate improvement with respect to AOT observations at AERONET sites. A multivariable bias score combining biases of several meteorological variables into a single number is larger in ICON‐A‐HAM2.3 compared to standard ICON‐A and standard ECHAM6.3. In the tropics, this multivariable bias is of similar magnitude in ICON‐A‐HAM2.3 and in ECHAM6.3‐HAM2.3. In the extra‐tropics, a smaller multivariable bias is found for ICON‐A‐HAM2.3 than for ECHAM6.3‐HAM2.3. Plain Language Summary Aerosols are tiny particles in the air which are either emitted into the atmosphere directly or formed from precursor gases such as sulfur dioxide. Aerosols reflect and absorb solar radiation and affect the radiative properties of clouds. In order to estimate how changing emissions of aerosol precursor gases and aerosols affect the radiation budget of the atmosphere, aerosol models are coupled to global atmosphere models. Here, an aerosol model that has already been part of a well‐established coupled model is coupled to a recently developed atmosphere model. The reasons for differences between the original and the new model are investigated and simulated aerosol optical thickness is evaluated against observations. The aerosol optical thickness over subtropical oceans is lower in the new model, which is in better agreement with estimates from satellite observations. This better agreement is traced back to a parameter setting in the cloud description part in the new model. However, because cancellation of positive and negative biases is reduced in the new model, the global mean aerosol optical thickness is biased lower the new model. A bias score based on several meteorological variables is lower in the new model because of lower biases in the extra‐tropics. Key Points The new ICON‐A‐Hamburg Aerosol Module version 2.3 (HAM2.3) global atmosphere‐aerosol model is introduced The sensitivity of simulated aerosol optical thickness (AOT) to using two different host models but the same aerosol module is investigated A positive AOT bias over subtropical oceans is remedied in ICON‐A‐HAM2.3 because of a different parameter setting in the host model

Following extreme drought during the 2019–2020 bushfire summer, the eastern part of Australia suffered from a week‐long intense rainfall and extensive flooding in March 2021. Understanding how much water storage changes in response to these climate extremes is critical for developing timely water management strategies. To quantify prompt water storage changes associated with the 2021 March flooding, we processed the low‐latency (1–3 days), high‐precision intersatellite laser ranging measurements from GRACE Follow‐On spacecraft and determined instantaneous gravity changes along spacecraft orbital passes. Such new data processing detected an abrupt surge of water storage approaching 60–70 trillion liters (km3 of water) over a week in the region, which concurrently caused land subsidence of ∼5 mm measured by a network of ground GPS stations. This was the highest speed of ground water recharge ever recorded in the region over the last two decades. Compared to the condition in February 2020, the amount of recharged water was similar but the recharge speed was much faster in March 2021. While these two events together replenished the region up to ∼80% of the maximum storage over the last two decades, the wet antecedent condition of soils in 2021 was distinctly different from the dry conditions in 2020 and led to generating extensive runoff and flooding in 2021. Plain Language Summary The monthly mean snapshots of global gravity field and surface mass variation (“mascon”) from the GRACE and GRACE Follow‐On spacecraft missions are problematic to accurately quantify abrupt water storage changes and flooding by intense rainfall. This study demonstrates a new use of the GRACE Follow‐On data to measure immediate water storage changes by computing instantaneous gravity change along spacecraft orbital passes. This new application is also shown for low‐latency (a few days) data processing to assess surface mass changes immediately after extreme events. The results found that the eastern parts of Australia experienced the highest speed of ground water recharge ever recorded in the region and the wet antecedent condition of soils yielded extensive flooding in 2021. Key Points New GRACE Follow‐On gravity data processing quantified prompt changes in water storage by the heavy rainfall and flooding in March 2021 The eastern Australia experienced the highest speed of ground water recharge and wet antecedent soils were responsible for extensive flooding in 2021 The study demonstrated the feasibility of rapid processing (1–3 days) for immediate assessment of mass changes from extreme events