Earth and Space Science最新文献

Global Climate Models (GCMs) are useful tools for simulating the dynamics of Mars atmosphere on a planetary scale. However their coarse resolution ($��\sim �$100 km) does not allow to capture small-scale phenomena such as slope winds which can occur over scales of just a few kilometers. These local slope winds can be crucial in Mars climate modeling, since they can significantly contribute to dust lifting affecting the amount of dust in the atmosphere, which is the major factor that governs the variability in Mars atmosphere. These winds can also affect the sublimation of water and $��{\text{CO}}_2�$ ice on the surface, both playing a key role in the Martian climate. In this study, we aim to develop a simple and efficient numerical model to simulate slope winds on Mars in single column and global climate models. We compare the model results with those from a mesoscale model with a resolution of a few kilometers capable of resolving these small scale winds (but only for a few days and with a high computational cost). This simple model of slope winds has been included in the Mars Climate Database (MCD v6.1) tool.

Apollo passive seismic data provide a unique resource for studying the lunar interior structure. However, the raw data are frequently contaminated by various artifacts, either related to the seismic sensors and the acquisition system or to issues during data transmission to the Earth. Understanding and exploiting the data set as a whole for seismic analyses remains therefore challenging. In this article, we present different artifacts observed in Apollo passive seismic data. This includes a systematic acquisition error at the Apollo 14 station, which was not investigated in previous studies but could affect most of the records of this station. We describe methods for the removal of this acquisition error as well as the numerous glitches. We conclude by illustrating the efficiency of these cleaning techniques on the collection of major lunar impacts and provide the associated data for future research.

State space models are well-suited for time series in which the evolution of variables cannot be well represented by deterministic basis functions. A key challenge in using state space models is the selection of the noise variance parameters. To better understand their impact on the model's filtering behavior, we derive the frequency response of several commonly used state space models by utilizing the connection between the Kalman smoother and regularized least squares problems. We show that the frequency response reveals distinguishing spectral features between competing state space models and explains the flattening of the log-likelihood function when the ratio of observation to disturbance variance becomes large. Using Dutch tide gauge data, we illustrate how the frequency response can be used to make informed decisions about the variance parameters, which could in turn support more reliable interpretations of time series data.

Coastal watersheds impacted by wildfires experience higher erosion resulting in increased sediment delivery to the ocean that alters limiting factors (i.e., light) for marine organisms. With increasing wildfire magnitude and severity, it is critical to explore changes in riverine discharges to the ocean to assess cascading hazards associated with wildfires. In situ data, remotely sensed turbidity data, and hydrological model (Soil and Water Assessment Tool “SWAT”) simulations have been adapted to capture and investigate fire-related land use change impacts on Malibu Creek, California, USA. Modifying SWAT land cover inputs using burn severity data had minimal impact on simulations, requiring additional parameterization for acceptable model performance. Remotely sensed turbidity, in situ discharge, rating curve sediment loads, and SWAT simulated discharge and sediment loads increased following the Woolsey Fire. When compared to in situ and rating curve data in similar non-fire water years, the 2019 Woolsey Fire water year in situ discharge was 1.8 times higher, SWAT simulated discharges were 1.4–1.7 times higher, and rating curve sediment load was 1.3 times higher. However, the SWAT simulated sediment loads were slightly lower (0.8–0.9 times) than rating curve sediment loads in similar non-fire water years. Mean coastal turbidity increased to 18.2 Formazin Nephelometric Unit (FNU) during the first storm post-fire (mean background value of 4.3 FNU). Synergies between methods demonstrated rapid coastal sediment exports (remote sensing) and ongoing erosion post-fire (SWAT). These data are essential to understanding fire-related marine ecological changes and implementing effective management and conservation initiatives.

Gridded precipitation data sets have become essential for understanding climate variability and long-term trends; however, their accuracy and reliability strongly depend on the availability and the spatial and temporal distribution of in situ meteorological observations. Here, we evaluate the performance of four gridded precipitation products: the Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) v2, the Global Precipitation Climatology Centre (GPCC) Full Data Monthly Product v2022, the Climatic Research Unit (CRU) TS 4.07, and the ERA5-Land (ERA5-L) reanalysis, against a network of weather stations across Central America compiled from the regional meteorological service agencies. Using a point (station)-to-pixel comparison and a grid-by-grid spatial decorrelation analysis, we assess gridded data set accuracy and examine how station coverage affects precipitation trend detection. Results from the point (station)-to-pixel analysis show that CHIRPS consistently outperforms ERA5-Land, GPCC, and CRU across all standard statistical metrics (including correlation coefficient, bias, and root mean square error). CRU exhibits the largest spatial decorrelation distances, suggesting inflated spatial coherence likely resulting from interpolation over data-sparse regions. We find disagreement between the spatial representation of precipitation trends between reanalysis-based and observation-based data sets and show that the observed regional drying trend in eastern Honduras and Nicaragua in the GPCC and CHIRPS products may reflect the influence of one station rather than a broader, spatially coherent climate signal. These findings highlight the importance of considering both spatial station density and temporal data availability when using gridded precipitation products for studies of climate variability and change, especially in data-sparse regions such as Central America.

Saline lakes are expected to have been extensively present on ancient Mars, particularly as the planet dried or cooled. Such lakes likely deposited sulfate salts, as these salts have been widely identified from orbital and in situ Mars data. However, the relationship between martian sulfates and the environmental conditions that formed them (including whether conditions were warm, cool, drying, or freezing), remains under-characterized. To evaluate the relationship between sulfates and climate, we investigated the hypersaline, sulfate-bearing Basque Lakes in British Columbia, Canada, which serve as an analog for both “cold and wet” and “warm and wet” early Mars. We use the rover and orbiter relevant instrument techniques of Raman, Near Infrared, and X-Ray Fluorescence spectroscopy to evaluate seasonal lake mineralogy. We find that temperature-dependent, multi-cation salts form widely within the Basque Lakes' efflorescent crusts in the fall, which transform to meridianiite, mirabilite, a metastable Na-sulfate 7-hydrate, and epsomite in the wintertime. In both seasons, salt assemblages are metastable and persist beyond expected thermodynamic stability fields, suggesting ongoing climatic changes can prevent saline systems from settling into equilibrium phases. Coupled with sedimentological evidence, intimately mixed Mg-sulfates of different hydration states could be an indicator of surface fluids that interacted with an atmosphere, while formation of Na-sulfates could be evidence for brine freezing. Curiosity's exploration of the Gale crater sulfate-bearing unit and Perseverance's exploration of Jezero crater on Mars offer excellent chances to investigate the influence of climate on Mg-sulfate formation.

This paper describes the first field deployment of the Far INfrarEd Spectrometer for Surface Emissivity far-infrared Fourier transform spectrometer to an Arctic environment and shows retrievals of the emissivity of ice and snow in the wavenumber range 400–1,200 cm⁻¹ at viewing angles of 35° and 50°. The retrieved ice emissivity shows a variation of 0.05 between the peak value at around 950 cm⁻¹ and the minimum value at around 750 cm⁻¹. The emissivity is also between 0.01 and 0.02 lower for the higher viewing angle. The emissivity of snow is higher and shows less variation with both viewing angle and wavenumber but it is 0.01 less than one below 900 cm⁻¹. This has implications for remote sensing and climate modeling in this wavenumber range as it implies that both the spectral and angular variation of emissivity must be taken into account. The retrieved ice emissivity agrees well with the emissivity modeled using Fresnel equations. The retrieved snow emissivity agrees well with modeled snow emissivity but further independent measurements of the snow physical properties are needed to test the performance of the model in the far infrared.

A mathematical and numerical framework is developed for modeling Earth's magnetic field and optimizing the trajectory of the whole system using geomagnetic observations. The conventional approach is adopted to model Earth's magnetic field in the source-free region via the Gauss coefficient, for which the fast dynamical component for the mantle-induced field in the mantle region is further constrained by the underlying physical laws of magnetic induction. A spectral approach is adopted to represent the total geomagnetic field. It thereafter yields a rapid convergence of the solution and a smooth and stable continuation of the geomagnetic field from the observational points to all space. Central to the mathematical development of this work is an adjoint formulation for optimizing the trajectory of the coupled dynamical system for an observation time window in variable magnetic boundary conditions, partially determined by other components. We demonstrate the effectiveness of our framework by optimizing a representative geomagnetic system comprising the primary and secondary components of the internal geomagnetic field and a simplified external field using a set of synthetic observations and show that all components of the system can be accurately determined in a variety of space weather conditions. We intend to construct the framework to model the geomagnetic field in a broad region from Earth's interior to the magnetosphere and describe the nonlinear nature and the dynamical balance of Earth's magnetic system in different magnetic weather conditions by utilizing a realistic space current model.

We provide trend estimates for total, stratospheric, and tropospheric ozone columns over Reunion (21.1°S, 55.5°E) from 1998 to 2021, using only Système d’Analyze par Observation Zénithale and Southern Hemisphere Additional OZonesonde observations. Trends are derived using Trend-Run, a multiple linear regression model, and a dynamic linear model (DLM) to identify potential turning points. Overall, total ozone exhibits a positive trend (3.0 $��\pm �$ 1.5 DU/decade), with increases in both stratospheric (1.1 $��\pm �$ 1.6 DU/decade) and tropospheric ozone (2.2 $��\pm �$ 1.0 DU/decade). DLM identifies a turning point in stratospheric ozone in 2008, with a clear decrease in stratospheric ozone before this point and an increase afterward. We also determined changes in the lapse rate tropopause (LRT), the subtropical barrier position, and ERA5 wind and geopotential fields during the same period to investigate possible links between mid-tropospheric ozone increase and transport-related perturbations. Although trends in LRT height and temperature are barely significant, they suggest a recent deepening of the troposphere, indicative of climate change. Intensification of the anticyclonic gyre over Southern Africa and a weakening of the Mascarene anticyclone are found. This suggests that, independent of possible changes in ozone precursor emissions over Africa or South America, dynamics are driving increases of ozone and ozone precursors over Reunion from 1998 to 2021. Furthermore, the rate of Reunion's free tropospheric trends exceeds that observed at all other southern hemisphere ozonesonde stations, including those in tropical, subtropical and mid-latitude regions.

The low-Earth orbit Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) instruments, spanning 1995–2023, have spatiotemporal patterns within their metadata that are consistent with the South Atlantic Anomaly (SAA). While the SAA had a known influence on these instruments, this study details new variability and impacts. A large volume of radiation-triggered events can cause the First-In First-Out (FIFO) buffer overflow to occur, which temporarily “blinded” LIS and OTD. Patterns of FIFO and the instrument status flags displayed an evolving intensity and areal extent of SAA interference, affecting climatological view-time records. The interference had a strong relationship to the sunspot number with Pearson correlation values of −0.50 and −0.48 (p < 0.0001 for both) for the view-time anomaly and FIFO occurrence, respectively, over the entire record. For the LIS instruments, the size of the affected region was zero in their early respective records then peaked at millions of square kilometers during solar minimum. LIS on the Tropical Rainfall Measuring Mission (TRMM, TLIS) observed a seasonal cycle with the worst interference during the JJA season and least during DJF. All three instruments found a westward drift of the SAA, at 0.54° y⁻¹, 0.22° y⁻¹, and 0.70° y⁻¹ for TLIS, OTD, and International Space Station LIS (ILIS), respectively. However, while both LIS instruments noted a northward drift, OTD had a southward drift. The influence of external factors including the thermosphere, properties of the radiation, orbital characteristics, and hardware degradation remain to be examined to describe the implications for the SAA itself.