Climate Observing System Research Articles

Temporal stability of long-term satellite and reanalysis products to monitor snow cover trends

Abstract. Monitoring snow cover to infer climate change impacts is now feasible using Earth observation data together with reanalysis products derived from Earth system models and data assimilation. Temporal stability becomes essential when these products are used to monitor snow cover changes over time. While the temporal stability of satellite products can be altered when multiple sensors are combined and due to the degradation and orbital drifts in each sensor, the stability of reanalysis datasets can be compromised when new observations are assimilated into the model. This study evaluates the stability of some of the longest satellite-based and reanalysis products (ERA5, 1950–2020, ERA5-Land, 1950–2020, and the National Oceanic and Atmospheric Administration Climate Data Record (NOAA CDR), 1966–2020) by using 527 ground stations as reference data (1950–2020). Stability is assessed with the time series of the annual bias in snow depth and snow cover duration of the products at the different stations. Reanalysis datasets face a trade-off between accuracy and stability when assimilating new data to improve their estimations. The assimilation of new observations in ERA5 improved its accuracy significantly during the recent years (2005–2020) but introduced three negative step discontinuities in 1977–1980, 1991–1992, and 2003–2004. By contrast, ERA5-Land is more stable because it does not assimilate snow observations directly, but this leads to worse accuracy despite having a finer spatial resolution. The NOAA CDR showed a positive artificial trend from around 1992 to 2015 during fall and winter that could be related to changes to the availability of satellite data. The magnitude of most of these artificial trends and/or discontinuities is larger than actual snow cover trends and the stability requirements of the Global Climate Observing System (GCOS). The use of these products in seasons and regions where artificial trends and discontinuities appear should be avoided. The study also updates snow trends (1955–2015) over local sites in the Northern Hemisphere (NH), corroborating the retreat of snow cover, driven mainly by an earlier melt and recently by a later snow onset. In warmer regions such as Europe, snow cover decrease is coincident with a decreasing snow depth due to less snowfall, while in drier regions such as Russia, earlier snowmelt occurs despite increased maximum seasonal snow depth.

Nighttime Midlatitude E‐F Coupling in Geomagnetic Conjugate Ionospheres: A Double Thin Shell Model and a Multi‐Source Data Investigation

AbstractGeomagnetic conjugate mid‐latitude nighttime ionospheres are frequently simultaneously populated with electrified nighttime medium‐scale traveling ionospheric disturbances (MSTIDs). Earlier observations and theoretical analysis have underscored the ionosphere E‐F coupling and the postulation of coupled conjugate hemispheres, playing a pivotal role in the formation of electrified MSTIDs. In this paper, the conjugate MSTIDs are studied to elucidate the causes and effects of E‐F coupling in the interhemispheric coupled ionosphere. The hemisphere‐coupled ionospheres over Japan and Australia are observed and analyzed using total electron content (TEC) measurements, supplemented with multi‐source observations from ionosondes, Ionospheric Connection Explorer (neutral wind), Constellation Observing System for Meteorology, Ionosphere, and Climate (electron density), and Swarm (magnetic field). A double‐thin‐shell model is introduced to analyze the ionospheric responses in E and F regions during the coupling process. For the first time, observation results provide the evidence that F‐region geomagnetic conjugate irregularities in both hemispheres are mainly driven by the Es layers in the summer hemisphere. The Es layer in the summer hemisphere subsequently triggers local E‐F coupling and inter‐hemispheric coupling. In the winter hemisphere, Es layers show amplitude reduction or even dissipation during the interhemispheric coupling process. Furthermore, thermospheric winds, non‐equipotential magnetic field lines, and background TEC are presumed candidates for the inter‐hemispheric asymmetry in MSTIDs amplitudes and growth rates.

Winter Nighttime Enhancement of the Midlatitude Ionosphere: Contribution From the Diffusive and Wind‐Driven Plasma Transport

AbstractThe characteristics of winter nighttime enhancement (WNE) of the midlatitude ionosphere at 300, 550, and 750 km altitude are presented, based on the radio occultation data from the Constellation Observing System for Meteorology, Ionosphere, and Climate. WNE at 750 km altitude has earlier start time and larger increasing rate than that at 550 km, possibly due to the downward plasma diffusion from above that dominates the most upper part of the ionosphere. Theoretical calculation of the plasma transport at 300 km altitude reveals the largest effect of downward diffusion at 45° geomagnetic latitude, consistent with the latitudinal distribution of WNE. Meanwhile, the wind‐driven plasma transport also contributes to WNE, at 30°W–180°W geographic longitude in the Southern Hemisphere. The strength and end time of WNE vary with longitude, and are correlated with the longitudinal variations of the enhancement in the conjugate (summer) hemisphere. This may be attributed to the transport processes in the interhemispheric geomagnetic flux tubes, which redistribute and balance the plasma between the conjugate hemispheres at night. The plasma flux from above is hence an important plasma source for further understanding of both the winter and summer nighttime enhancements.

Short-Term Variability of Non-Migrating Diurnal Tides in the Stratosphere from CMAM30, ERA-Interim, and FORMOSAT-3/COSMIC

The variability of non-migrating tides in the stratosphere is investigated using temperature data from Canadian Middle Atmosphere Model (CMAM30), ERA-interim reanalysis and Formosa Satellite-3 and Constellation Observing System for Meteorology, Ionosphere, and Climate (FORMOSAT-3/COSMIC) from 2006 to 2010 using a ±10-day window. CMAM30 and ERA results show that the amplitudes of non-migrating tides, DS0 and DW2, are negligible in the mid and high-latitude stratosphere, and the results from satellite datasets are significantly affected by aliasing in this region, in spite of using a smaller window size for analysis (±10 days). Significant short term variability ranging from 30 to 100 days is observed in DS0 and DW2 over the equatorial and tropical latitudes. These tides are seen as two prominent bands around the equator with DS0 maximising during boreal summers and DW2 maximising during boreal winters. These variabilities are compared with the variability in amplitude of the stationary planetary wave with wavenumber one (SPW1) in the high-latitude stratosphere using the continuous wavelet transform (CWT). It is found that during boreal winters, the variability of SPW1 at 10 hPa over 65° N is similar to that of DS0 and DW2 over the equator at 0.0007 hPa. This provides evidence that SPW1 from the high-altitude stratosphere moving upward and equator-ward could be interacting with the migrating diurnal tide and generating the non-migrating tides in the equatorial mesosphere and lower thermosphere (MLT). The variabilities, however, are not comparable during summers, with SPW1 being absent in the Northern Hemisphere. It is thus concluded that non-linear interactions could be a source of non-migrating tidal variability in the equatorial MLT region during boreal winters, but during summers, the tidal variabilities have other sources in the lower atmosphere. The anti-symmetric nature of the vertical global structures indicates that these tides could be the result of global atmospheric oscillations proposed by the classical tidal theory.

Temperature Fusion of TIMED/SABER Data and COSMIC Data in Stratosphere

AbstractThe acquisition of accurate stratospheric temperature data is of great significance for the research on global climate system and numerical weather forecasting. To obtain high‐precision stratospheric temperature, the three‐dimensional variational assimilation method, combined with kriging interpolation, was applied for data fusion of the Thermosphere, Ionosphere, Mesosphere Energetics, and Dynamics/Sounding of the Atmosphere using Broadband Emission Radiometry (TIMED/SABER) temperature data and the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) radio occultation temperature data. As a sample, the two data sets of TIMED/SABER and COSMIC, during the time range from 5 December 2009, 09:00 to 5 December 2009, 15:00, were used to construct global stratospheric temperature field of 5 December 2009, 12:00. The cross‐validation results showed that temperature distribution from the variational fusion method was consistent with COSMIC observations at the height range of 15–35 km, which the mean deviations and standard deviations were within a range of −1 to 1 and 3 to 4 K, respectively. At the height range from 35 to 40 km, the temperature distribution from the variational fusion method was more consistent with TIMED/SABER observations. The mean deviations were within 0 and 0.5 K, and the standard deviations were between 1.8 and 2 K. Overall, the temperature field after variational fusion combines the high‐precision advantage of SABER observations around 40 km and the high‐precision advantage of COSMIC observations at the height range of 15–30 km, the effect of the variational fusion method is significant.

Singular spectrum analysis and modeling of the temporal variations of the global ionospheric F2-layer peak electron density retrieved from COSMIC radio occultation measurements

The singular spectrum analysis (SSA) is a relatively new method for decomposing time series into separable and interpretable series (i.e., trend, periodic, and irregular components). Here, the ionospheric variability in the peak electron density (NmF2) observations provided by FORMOSAT-3/Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation measurements during 2009–2019, which completely covers solar-cycle 24, was examined using the nonparametric method (SSA). This study identified different temporal patterns inherent in the COSMIC data, which can be employed to reconstruct/model noise-free time series. Based on a proper choice of SSA parameters, it was observed that SSA can be employed to extract various components of these datasets. Additionally, the results showed that the slowly varying component (trend) was largely influenced by solar activity and closely followed the behavior of the sunspot cycle. The SSA method demonstrated seasonal patterns (the semiannual component). Based on the patterns, the reconstructed series for each of the selected components were separately modeled with a corresponding fit function using the 10.7 cm solar proxy, which prior be smoothed by Spline fitting. It was observed that the polynomial function efficiently modeled the trend component with R2 = 0.95, while the harmonic function adequately represented the semiannual component with R2 = 0.97. To validate the proposed model, the data were estimated for the time interval from January 2020 to August 2022, which represented the ascending phase of the ongoing solar-cycle 25. The results revealed that the modeled data correlated with the observed COSMIC-2 data with a high correlation coefficient (0.95). These findings indicate that the underlying model can effectively describe the behavior of the electron density during the investigated period, and the SSA method is particularly powerful for analyzing nonstationary time series and capable of identifying sub-time series (trends along with seasonal periodic components).

How adequately are elevated moist layers represented in reanalysis and satellite observations?

Abstract. We assess the representation of elevated moist layers (EMLs) in ERA5 reanalysis, the Infrared Atmospheric Sounding Interferometer (IASI) L2 retrieval Climate Data Record (CDR) and the Atmospheric Infrared Sounder (AIRS)-based Community Long-term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS)-Aqua L2 retrieval. EMLs are free-tropospheric moisture anomalies that typically occur in the vicinity of deep convection in the tropics. EMLs significantly affect the spatial structure of radiative heating, which is considered a key driver for meso-scale dynamics, in particular convective aggregation. To our knowledge, the representation of EMLs in the mentioned data products has not been explicitly studied – a gap we start to address in this work. We assess the different datasets' capability of capturing EMLs by collocating them with 2146 radiosondes launched from Manus Island within the western Pacific warm pool, a region where EMLs occur particularly often. We identify and characterise moisture anomalies in the collocated datasets in terms of moisture anomaly strength, vertical thickness and altitude. By comparing the distributions of these characteristics, we deduce what specific EML characteristics the datasets are capturing well and what they are missing. Distributions of ERA5 moisture anomaly characteristics match those of the radiosonde dataset quite well, and remaining biases can be removed by applying a 1 km moving average to the radiosonde profiles. We conclude that ERA5 is a suitable reference dataset for investigating EMLs. We find that the IASI L2 CDR is subject to stronger smoothing than ERA5, with moisture anomalies being on average 13 % weaker and 28 % thicker than collocated ERA5 anomalies. The CLIMCAPS L2 product shows significant biases in its mean vertical humidity structure compared to the other investigated datasets. These biases manifest as an underestimation of mean moist layer height of about 1.3 km compared to the three other datasets that yields a general mid-tropospheric moist bias and an upper-tropospheric dry bias. Aside from these biases, the CLIMCAPS L2 product shows a similar, if not better, capability of capturing EMLs compared to the IASI L2 CDR. More nuanced evaluations of CLIMCAPS' capabilities may be possible once the underlying cause for the identified biases has been found and fixed. Biases found in the all-sky scenes do not change significantly when limiting the analysis to clear-sky scenes. We calculate radiatively driven vertical velocities ωrad derived from longwave heating rates to estimate the dynamical effect of the moist layers. Moist-layer-associated ωrad values derived from Global Climate Observing System Reference Upper-Air Network (GRUAN) soundings range between 2 and 3 hPa h−1, while mean meso-scale pressure velocities from the EUREC4A (Elucidating the Role of Clouds-Circulation Coupling in Climate) field campaign range between 1 and 2 hPa h−1, highlighting the dynamical significance of EMLs. Subtle differences in the representation of moisture and temperature structures in ERA5 and the satellite datasets create large relative errors in ωrad on the order of 40 % to 80 % with reference to GRUAN, indicating limited usefulness of these datasets to assess the dynamical impact of EMLs.

Extreme Heights of 15 January 2022 Tonga Volcanic Plume and Its Initial Evolution Inferred from COSMIC-2 RO Measurements

The Hunga Tonga–Hunga Ha’apai underwater volcano (20.57° S, 175.38° W) violently erupted on 15 January 2022. The volcanic cloud’s top height and initial evolution are delineated by using the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC)-2 radio occultation (RO) measurements. The bending angle (BA) anomaly over the Tonga volcanic plume (within 200 km of the eruption center) at 5:17 UTC on 15 January showed a prominent peak at higher stratospheric heights. The top of the BA anomaly revealed that negative to positive change occurred at ~38 km, indicating the first height where the RO line-of-sight encountered the volcanic plume. The BA anomaly further revealed an increase of ~50% at ~36.1 km, and confirmed that the volcanic plume reached above ~36 km. Furthermore, the evolution of BA perturbations within 24 h after the initial explosion is also discussed herein. From collocated RO profiles with the volcanic plume, we can find a clear descent of the peak altitude of the BA perturbation from ~36.1 km to ~29 km within 24 h after the initial eruption. The results from this study will provide some insights into advancing our understanding of volcanic cloud dynamics and their implementation in volcanic plume modeling.

Solar Intensity Dispersing (SID) Concept for CubeSat Spectral CLARREO‐Like Radiance Measurements

AbstractNRC Decadal Surveys stated that the most critical goal for orbital climate measurements was improving accuracy. This is so comparisons can be better made with models, tuning theory to match the truth. That gives confidence in model predictions of future global cloud albedo warming signals, estimated to be only 0.8%/decade or less. This work considers goals of a future mission CLARREO, currently in the development phase. CLARREO's Earth viewing optics intend to scan lunar radiance for tracking calibration changes, within both a high wavelength and high spatial resolution spectrometer. The current NASA CLARREO design will attempt absolute calibration from the space station by attenuating known solar flux, using pinholes and time under‐sampling. This study presents a cheaper and potentially more effective alternative, instead using the Sun as a near direct absolute calibration target. It does this spreading sunlight over a large solid angle, before integrating signals taken from a spinning orbiting CubeSat. Additionally, after reviewing actual orbital data comparisons, the realistic accuracy of cross‐orbit satellite to satellite calibration is shown several percent at best, even for a perfect CLARREO device (far short of the desired ±0.3% quoted by NASA). That is compared to the accuracy achievable from an absolute lunar spectral characterization from this CubeSat called “MERBE‐Sat,” acting as a transfer for a climate observation system, perhaps better than ±0.3% error. Although discussed individual components of MERBE‐Sat are mostly of high TRL Level, this work suggests experimentation to raise the net TRL level of the new entire concept.

Quality Assessment of Sea Surface Salinity from Multiple Ocean Reanalysis Products

Sea surface salinity (SSS) is one of the Essential Climate Variables (ECVs) as defined by the Global Climate Observing System (GCOS). Acquiring high-quality SSS datasets with high spatial-temporal resolution is crucial for research on the hydrological cycle and the earth climate. This study assessed the quality of SSS data provided by five high-resolution ocean reanalysis products, including the Hybrid Coordinate Ocean Model (HYCOM) 1/12° global reanalysis, the Copernicus Global 1/12° Oceanic and Sea Ice GLORYS12 Reanalysis, the Simple Ocean Data Assimilation (SODA) reanalysis, the ECMWF Oceanic Reanalysis System 5 (ORAS5) product and the Estimating the Circulation and Climate of the Ocean Phase II (ECCO2) reanalysis. Regional comparison in the Mediterranean Sea shows that reanalysis largely depicts the accurate spatial SSS structure away from river mouths and coastal areas but slightly underestimates the mean SSS values. Better SSS reanalysis performance is found in the Levantine Sea while larger SSS uncertainties are found in the Adriatic Sea and the Aegean Sea. The global comparison with CMEMS level-4 (L4) SSS shows generally consistent large-scale structures. The mean ΔSSS between monthly gridded reanalysis data and in situ analyzed data is −0.1 PSU in the open seas between 40° S and 40° N with the mean Root Mean Square Deviation (RMSD) generally smaller than 0.3 PSU and the majority of correlation coefficients higher than 0.5. A comparison with collocated buoy salinity shows that reanalysis products well capture the SSS variations at the locations of tropical moored buoy arrays at weekly scale. Among all of the five products, the data quality of HYCOM reanalysis SSS is highest in marginal sea, GLORYS12 has the best performance in the global ocean especially in tropical regions. Comparatively, ECCO2 has the overall worst performance to reproduce SSS states and variations by showing the largest discrepancies with CMEMS L4 SSS.

Tropical Cyclone Planetary Boundary Layer Heights Derived from GPS Radio Occultation over the Western Pacific Ocean

According to GPS radio occultation data from previous studies, the height of the planetary boundary layer (PBLH) is defined as the altitude at which the vertical gradient of refractivity N is at its local minimum, called the gradient approach. As with its density, the atmosphere’s refractivity falls broadly exponentially with height. The spherically symmetric refractivity Nss(r) was established to account for the standard deviation of atmospheric refractivity with altitude. Ni is the residual from the fundamental vertical variations of refractivity, defined as Ni(r) = N(r) − Nss(r). In this study, the vertical gradient of N is replaced by the vertical gradient of Ni to optimize the gradient approach, called the local gradient approach. Using the US radiosonde and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultations (ROs) data from 2007–2011, these two PBLH-determining approaches are evaluated. The PBLHs estimated by the gradient approach and the local gradient approach have RMSE values of 0.73 km and 0.65 km, respectively. The PBLH obtained by the local gradient approach is closer to the radiosonde-derived value. In this paper, the COSMIC-2 ROs data and the western Pacific typhoon best track data are collocated in time and space during 2020–2021, and the axisymmetric composite structural characteristics of the tropical cyclone (TC) PBLs are analyzed. The lowest vertical gradients of N and Ni of TCs correspond closely with the average PBLHs. We find that the mean PBLHs of tropical depressions (TD), tropical storms (TS), and typhoons (TY) all have their local maxima at a radial distance of 125 km with heights of 1.03 km, 1.12 km, and 1.36 km, respectively. After 375 km, 575 km, and 935 km of TD, TS, and TY radial distances, the mean PBLHs become stable and cease to vary. The mean PBLH undulations increase significantly with the increase in tropical cyclone intensity. Niwet is the residual from the fundamental vertical variations of wet refractivity, defined as Niwet(r) = Nwet(r) − Nsswet(r). Local minima of Niwet and Ni vertical gradients of TD, TS, and TY have comparable distributions and are concentrated between 0.5 km and 1 km.

Characterization and Climatological Modeling of Equatorial Ionization Anomaly (EIA) Crest Position

AbstractThe Equatorial Ionization Anomaly (EIA) is characterized by strong ionospheric gradients that complicate ionospheric modeling and mitigation of ionospheric impact on Global Navigation Satellite System applications. In this study, the variation of EIA crest locations as a function of longitude and solar radio flux index F10.7 has been derived and modeled. Seven years (2013–2019) of ionospheric NmF2 and in‐situ ion density data from Constellation Observing System for Meteorology Ionosphere and Climate and Swarm‐A satellites have been used. We find that the distance between the northern and southern crest of EIA grows slightly with increase of solar flux. The position of the crests of EIA follows a wave number 4 structure with peak values at around −130°, 0°, and 100°E. At the altitude of Swarm‐A (∼460 km), the equatorial crests are found closer to the geomagnetic dip equator than they are at the peak density height hmF2 (∼310 km) which may be due to the spatial variations of geomagnetic field strength. Accordingly, two Crest Position climatological Models have been developed, one for the F2 Peak height (CPM_F2P) and the other one for Swarm‐A height (CPM_SAH).

In situ observations of the Swiss periglacial environment using GNSS instruments

Abstract. Monitoring of the periglacial environment is relevant for many disciplines including glaciology, natural hazard management, geomorphology, and geodesy. Since October 2022, Rock Glacier Velocity (RGV) is a new Essential Climate Variable (ECV) product within the Global Climate Observing System (GCOS). However, geodetic surveys at high elevation remain very challenging due to environmental and logistical reasons. During the past decades, the introduction of low-cost global navigation satellite system (GNSS) technologies has allowed us to increase the accuracy and frequency of the observations. Today, permanent GNSS instruments enable continuous surface displacement observations at millimetre accuracy with a sub-daily resolution. In this paper, we describe decennial time series of GNSS observables as well as accompanying meteorological data. The observations comprise 54 positions located on different periglacial landforms (rock glaciers, landslides, and steep rock walls) at altitudes ranging from 2304 to 4003 ma.s.l. and spread across the Swiss Alps. The primary data products consist of raw GNSS observables in RINEX format, inclinometers, and weather station data. Additionally, cleaned and aggregated time series of the primary data products are provided, including daily GNSS positions derived through two independent processing tool chains. The observations documented here extend beyond the dataset presented in the paper and are currently continued with the intention of long-term monitoring. An annual update of the dataset, available at https://doi.org/10.1594/PANGAEA.948334 (Beutel et al., 2022),​​​​​​​ is planned. With its future continuation, the dataset holds potential for advancing fundamental process understanding and for the development of applied methods in support of e.g. natural hazard management.

Climatology of TEC Longitudinal Difference in Middle Latitudes of East Asia

In this paper, a statistical analysis of the diurnal, seasonal and solar cycle variation in the TEC longitudinal difference in midlatitudes of East Asia is presented using CODE GIMs data in 2015–2019. Moreover, the empirical neutral wind model HWM-14 and geomagnetic field model IGRF-2020 were employed to analyze the influence of geomagnetic configuration-neutral wind mechanism on the TEC longitudinal difference, and the F2 layer peak electron density (NmF2) data from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) were also used to study the role of local electron density in the TEC longitudinal difference. For the high solar activity year, the results show that east-west TEC longitudinal difference index Re/w is negative in the noon and positive at evening-night. Moreover, the longitudinal difference of daytime TEC is most evident in summer, less in autumn and least in spring and winter, while the nighttime difference is most obvious in equinox, followed by summer and winter during nighttime. The model simulation shows that the TEC longitude difference around noon is mainly caused by the zonal wind-declination mechanism, and a 4-h time delay seems to be an optimal result for the vertical drift velocity to cause the longitudinal TEC difference during pre-noon hours. At night, the uplifting electron flux, which is a product of local electron density and vertical drift velocity, shows a good correlation with Re/w, indicating that the local electron density is also an important factor affecting the TEC longitudinal difference during the nighttime. Moreover, there was about a 3-h time delay between the TEC longitudinal variations and the uplifting electron flux at night. For the low solar activity years, the western TEC is greater than eastern TEC during most of the year except in the summer nighttime. The TEC diurnal variation in the east and west suggested that the nighttime Re/w should be related to other physical process, such as the midlatitude summer nighttime anomaly (MSNA) in the east and the ionospheric nighttime enhancement (INE). The current study provides evidence for the longitudinal difference of NmF2 in East Asian midlatitudes and geomagnetic configuration-neutral wind mechanism proposed in previous studies and finds some new features which need further studying to improve our current understanding of ionospheric longitudinal difference in the low solar activity years. The results provide new insight into TEC longitudinal variations at midlatitudes, and they can contribute to understanding the ionosphere-thermosphere coupling system.

Comparison of GRUAN data products for Meisei iMS-100 and Vaisala RS92 radiosondes at Tateno, Japan

Abstract. A total of 99 dual soundings with Meisei iMS-100 radiosonde and Vaisala RS92 radiosondes were carried out at the Aerological Observatory of the Japan Meteorological Agency, known as Tateno (36.06∘ N, 140.13∘ E, 25.2 m; the World Meteorological Organization, WMO, station number 47646), from September 2017 to January 2020. Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) data products (GDPs) from both sets of radiosonde data for 59 flights were subsequently created using a documented processing programme along with the provision of optimal estimates for measurement uncertainty. Differences in radiosonde performance were then quantified using these GDPs. For daytime observations, the iMS-100 temperature is around 0.5 K cooler than RS92-GDP in the stratosphere, with significant differences in the upper troposphere and lower stratosphere in consideration of combined uncertainties. For nighttime observations, the difference is around −0.1 K, and data are mostly in agreement. For relative humidity (RH), iMS-100 is around 1 % RH–2 % RH higher in the troposphere and 1 % RH smaller in the stratosphere than RS92, but both GDPs are in agreement for most of the profile. The mean pressure difference is ≤0.1 hPa, the wind speed difference is from −0.04 to +0.14 m s−1, the wind direction difference is ≤6.4∘, and the root mean square vector difference (RMSVD) for wind is ≤1.04 m s−1.

Investigation of gravity wave characteristics in the equatorial ionosphere during the passage of the 15 January 2010 solar eclipse over Tirunelveli

Solar eclipses are known to produce gravity wave disturbances in the atmosphere–ionosphere system in addition to density reduction due to temporary changes in solar radiation. The magnetic equator is ideally located to investigate these waves and their coupling to the equatorial ionosphere due to its unique geometry. Accordingly, the response of the equatorial ionosphere to a rare Annular Solar Eclipse (ASE) observed on 15 January 2010 is investigated using high-resolution observations from Canadian Advanced Digital Ionosonde (CADI) located at Tirunelveli which is a magnetic equator and on the eclipse totality path in India. In addition, simultaneous observations of GPS TEC from Tirunelveli, electron density profiles from Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC), and Equatorial Electrojet (EEJ) strength were analysed. The real height analysis has been performed on the ionosonde data using POLynomial ANalysis (POLAN). The isoheight/isofrequency analysis has been performed using real height on eclipse and control days. The results indicate a reduction of ∼33% in the lower ionosphere whereas no change has been noticed close to the F layer peak on the eclipse day. The isoheight analysis further indicates the presence of gravity waves with dominant periods in the range of 5–30 min. Further analyses have been performed on the altitude variation of dominant waves and their amplitudes/phases using ionosonde to identify whether they are generated in situ or propagated from below. The altitude variation of group and phase velocities showed opposite propagation indicating that they were propagated from the below. In addition, the simultaneous presence of gravity waves in the fmin, TEC, and EEJ strength on eclipse day supports our finding that these waves were propagated from the lower atmosphere.

Seasonal Variation of Stratospheric Gravity Waves in the Asian Monsoon Region Derived from COSMIC-2 Data

COSMIC-2 (Constellation Observing System for Meteorology, Ionosphere and Climate- 2) dry temperature profile data from December 2019 to November 2021 are used to study stratospheric gravity waves (GWs) in the Asian monsoon region. The stratosphere between 20 and 50 km is divided into the lower, middle, and high layers based on the vertical distribution of the mean potential energy (Ep) and the horizontal distribution of GW Ep in these three layers, and their seasonal changes are analyzed. The source and propagating mechanism of GWs in middle latitudes in winter are revealed. The results show that GWs in the stratosphere have distinct distribution features during different seasons. The significant Ep in winter appears mainly in middle latitudes north of 30°N, whereas in summer, it appears in the low latitudes south of 30°N. There are significant areas of GW activity in both low and middle latitudes in spring and autumn, but their intensity is significantly weaker than in winter and summer. Areas with significant GWs and the seasonal variation of their intensity are accompanied by the Asian monsoon activity. In winter, there is a northward and upward propagating column for GWs above the Sichuan Basin, and in summer, there is an eastward and upward propagating column for GWs in the zonal band 15–25°N. The occurrence of GWs in northwestern China in winter is the result of the subtropical jet stream and topography. Once GWs enter the stratosphere, they are regulated by the winter stratospheric environment, and the GWs acquire a northerly component by the wind shear. The meridional wind shear in the background field is an important factor affecting the development and propagation of GWs.

Assessment and characterization of sources of error impacting the accuracy of global burned area products

Understanding the sources of error that affect the accuracy of current coarse burned area products is crucial to identifying weaknesses and limitations of burned area (BA) algorithms. In this paper, we propose methods to analyse sources of errors of global BA products, which are applied to assess a widely used product, (FireCCI51), created under the ESA climate change initiative programme. The effect of several variables related to product accuracy are quantified by comparing the FireCCI51 BA product with a large global reference BA dataset for the years 2017–2019. These reference data were obtained from multitemporal analysis of Landsat-8 data. Error maps (commission and omission error layers) were generated for a sample of 316 units (100 km × 100 km) and associations between errors and potential explanatory sources of error were spatially analysed to provide a comprehensive error assessment of the FireCCI51 product. Active fire density, burned severity, burned patch size and land cover class were selected as explanatory variables for omission and commission errors. The results indicated that the largest contribution to the commission errors (70–80%) was related to the pixel size, particularly when pixels are only partially burned. Active fire densities were also associated to error distribution, with higher densities from products derived from the VIIRS sensors versus those generated from MODIS, indicating the potential benefit of the former as an alternative source in upcoming BA algorithms. Burn severity was also associated with error distribution, but this relation varied substantially across biomes. Land cover was also related to errors, with lowest accuracies for croplands with omission error percentages >85%. Fire size and, to a lesser extent, the shape of burned areas also played a crucial role in determining the accuracy of the BA products. BA accuracy increased for larger and more compact burned patches. Although our results suggest that further improvement of global BA products is possible, they also indicate that the ability of coarse spatial resolution BA sensors to meet the accuracy recommendations of the Global Climate Observing System (GCOS) programme is limited.

Comparison and evaluation of multiple satellite aerosol products over China in different scenarios under a unified criterion: Preparation for consistent and high-quality dataset construction

Aerosol optical depth (AOD) products provided by satellite sensors are widely used in climate modeling and climate change research. However, inconsistencies between products can cause large biases. It is necessary to integrate multiple satellite aerosol products to produce a consistent and high-quality aerosol record that satisfies the requirements of climate research users. To effectively combine the advantages of different datasets, their performance under different conditions needs to be compared during overlapping periods using uniform methods and criteria. Based on Aerosol Robotic Network (AERONET) measurements from 2019 to 2021, this study is the first to systematically compare the accuracy of 16 publicly released products from multiple satellite sensors in China under various scenarios using the same criteria to support the construction of a harmonized and high-quality dataset. Compared with AERONET AOD, the average retrieval percentage of 16 products satisfying the Global Climate Observing System (GCOS) accuracy requirement is 26.51%, with MISR and VIIRS Deep Blue (DB) products exceeding 40%, while MODIS 3 km Dark Target (DT), VIIRS DT, VIIRS Enterprise Processing System (EPS), and Sentinel-3 products are below 20%. By quantifying the accuracy of the products under different surface conditions, aerosol loadings, and particle size types, the accuracy ranking matrix of 16 products under different scenarios is established to provide a priori knowledge for the construction of a merged dataset. Finally, AOD products from October 2020 are merged based on the accuracy ranking matrix. The merged results show that, compared to the commonly used MODIS DT product, the percentage of retrievals satisfying GCOS requirement is improved by 22.55%, the correlation coefficient and mean absolute error are also improved, and the national average AOD coverage increases from 22.18% to 47.73%. These results are expected to provide guidance for the construction of high-quality datasets and the application of satellite aerosol products in climate research.

A Novel Deep Learning Model for Sea State Classification Using Visual-Range Sea Images

Wind-waves exhibit variations both in shape and steepness, and their asymmetrical nature is a well-known feature. One of the important characteristics of the sea surface is the front-back asymmetry of wind-wave crests. The wind-wave conditions on the surface of the sea constitute a sea state, which is listed as an essential climate variable by the Global Climate Observing System and is considered a critical factor for structural safety and optimal operations of offshore oil and gas platforms. Methods such as statistical representations of sensor-based wave parameters observations and numerical modeling are used to classify sea states. However, for offshore structures such as oil and gas platforms, these methods induce high capital expenditures (CAPEX) and operating expenses (OPEX), along with extensive computational power and time requirements. To address this issue, in this paper, we propose a novel, low-cost deep learning-based sea state classification model using visual-range sea images. Firstly, a novel visual-range sea state image dataset was designed and developed for this purpose. The dataset consists of 100,800 images covering four sea states. The dataset was then benchmarked on state-of-the-art deep learning image classification models. The highest classification accuracy of 81.8% was yielded by NASNet-Mobile. Secondly, a novel sea state classification model was proposed. The model took design inspiration from GoogLeNet, which was identified as the optimal reference model for sea state classification. Systematic changes in GoogLeNet’s inception block were proposed, which resulted in an 8.5% overall classification accuracy improvement in comparison with NASNet-Mobile and a 7% improvement from the reference model (i.e., GoogLeNet). Additionally, the proposed model took 26% less training time, and its per-image classification time remains competitive.