Earth and Space Science最新文献

We study drying trends across the central latitude strip of Europe (47.5–52.5°N and 2.5–27.5°E) during 1980–2019 and their links to atmospheric circulation. Daily differences between potential evapotranspiration and precipitation (PET–P) calculated from the E–OBS data are used to characterize dryness, and atmospheric circulation is represented by circulation types classified using daily sea level pressure patterns from the NCEP/NCAR reanalysis. Circulation types favoring dry conditions in vegetation season (April–September) are identified based on daily PET–P, and their temporal changes, seasonal variations, and links to trends in dryness in individual European regions are analyzed. In the early vegetation season (AMJ), drying trends are observed mainly in Western and Central Europe while in the late vegetation season (JAS), they are located predominantly in Eastern Europe. The dry circulation types include all anticyclonic types in all regions, as well as northeast to south (southwest in Eastern Europe) directional types. Trends of the dry circulation types correspond to those of dryness: the largest increase is found during AMJ in Western and Central Europe but during JAS in Eastern Europe. The results show that trends in dryness in the central latitude strip of Europe in the warm half-year were associated with changes in atmospheric circulation, as the largest increases in frequency of dry circulation types occurred in the regions and months affected by pronounced drying. The increasing frequency of anticyclonic types in AMJ and reduced inflow of moist air masses from the Atlantic are the key factors supporting intensification of dry conditions in European mid-latitudes.

The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) mission has collected surface elevation measurements for over 5 years. ICESat-2 carries an instrument that emits laser light at 532 nm, and ice and snow absorb weakly at this wavelength. Previous modeling studies found that melting snow could induce significant bias to altimetry signals, but there is no formal assessment on ICESat-2 acquisitions during the melting season. We performed two case studies over the Greenland Ice Sheet to quantify bias in ICESat-2 signals over snow: one to validate Airborne Topographic Mapper (ATM) data against Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) grain sizes, and a second to estimate ICESat-2 bias relative to ATM. We used snow optical grain sizes derived from ATM and AVIRIS-NG to attribute altimetry bias to snowpack properties. For the first case study, the mean and standard deviation of optical grain sizes were 340 ± 65 µm (AVIRIS-NG) and 670 ± 420 µm (ATM). A mean altimetry bias of 4.81 ± 1.76 cm was found for ATM, with larger biases linked to increases in grain size. In the second case study, we found a mean grain size of 910 ± 381 µm and biases of 6.42 ± 1.77 cm (ICESat-2) and 9.82 ± 0.97 cm (ATM). The grain sizes and densities needed to recreate biases with a model are uncommon in nature, so we propose that additional surface attributes must be considered to characterize ICESat-2 bias over snow. The altimetry biases are within the accuracy requirements of the ICESat-2 mission, but we cannot rule out more significant errors over coarse-grained snow.

We explore the potential for repeat-pass SAR Interferometry (InSAR) correlation to track volcanic activity on Venus' surface motivated by future SAR missions to Earth's sister planet. We use Hawai'i as a natural laboratory to test whether InSAR can detect lava flows assuming orbital and instrument parameters similar to that of a Venus mission. Hawai'i was chosen because lava flows are frequent, and well documented by the United States Geological Survey, and because Hawai'i is a SAR supersite, where space agencies have offered open radar data sets for analysis. These data sets have different wavelengths (L, C, and X bands), bandwidths, polarizations, look angles, and a variety of orbital baselines, giving opportunity to assess the suitability of parameters for detecting lava flows. We analyze data from ALOS-2 (L-band), Sentinel-1 (C-band), and COSMO-SkyMed (X-band) spanning 2018 and 2022. We perform SAR amplitude and InSAR correlation analysis over temporal baselines and perpendicular baselines similar to those of a Venus mission. Fresh lava flows create a sharp, noticeable decrease in InSAR correlation that persists indefinitely for images spanning the event. The same lava flows are not always visible in the corresponding amplitude images. Moreover, noticeable decorrelation persists in image pairs acquired months after the events due to post-emplacement contraction of flows. Post-emplacement effects are hypothesized to last longer on the Venusian surface, increasing the likelihood of detecting Venus lava flows using InSAR. We argue for further focus on repeat-pass InSAR capabilities in upcoming Venus missions, to detect and quantify volcanic activity on Earth's hotter twin.

Spectral indexes are tools widely used to analyze the composition of planetary surfaces. Many indexes have been formulated over the years to map the lunar surface, but there is no unified database for them. In this work we describe an Open-Source Python package called MoonIndex, that recreates 38 indexes compiled from the literature, using data from the Moon Mineralogy Mapper (M³). The processing started with the filtering of the data cubes to reduce the noise, the continuum of the spectrum was then removed using a convex hull or a second-and-first-order fit method. Later, the indexes were calculated, following as possible the original formulations. The results on spectral indexes calculated before the continuum removal were similar to those of the original formulations. Conversely, the results obtained for spectral indexes calculated after the continual removal were not always coherent. Some indexes, like the band depth, are especially sensitive to the removal method, as well as the derived band areas and asymmetries. We also recreated RGB composite maps, our results highlight the compositional patterns in a similar way as the ones in the literature, even if the color ramps can differ. The products of MoonIndex are open, ready for interpretation, versatile, consistent, and cross-comparable.

The Empty Quarter Desert, one of Earth's major dust sources, frequently experiences dust storms due to wind erosion. Despite its significance as a primary dust source on a global scale, in-situ observations from this region had not been reported until very recently. In summer 2022, the WInd-blown Sand Experiment (WISE) Phase-1 was initiated in the Empty Quarter Desert of the United Arab Emirates, and continued until 7 February 2023. Utilizing a diverse array of instruments, we measured winds, temperature, humidity, radiation fluxes, saltation, and the physical and optical properties of dust aerosols, atmospheric electric fields, and soil characteristics. A total of 38 distinct sand-saltation events were recorded from September 2022 to February 2023, with activity peaking between 13:00 and 14:00 local time. Key findings include the identification of dominant wind patterns, and the measurement of the average aerodynamic roughness length (z₀) at 0.8 ± 0.6 mm, and the thermal roughness length (z_h) at 0.3 ± 0.5 mm—the first estimation of z_h for this area. In-situ observations revealed that dust particle concentrations near the surface increased 1.7-fold on days with saltation compared to days without it. Moreover, we determined a wind-speed threshold for initiating saltation at 7.70 m s⁻¹. This comprehensive data set significantly advances our understanding of atmospheric-soil interactions and sand movement dynamics, providing invaluable insights for ongoing research into desert environments and the global dust cycle.

With the evolution of interferometric synthetic aperture radar into a tool for active hazard monitoring, new methods are sought to quickly and automatically interpret the large number of interferograms that are created. We present a convolutional neural network (CNN) that is able to both classify the type of deformation, and to locate the deformation within an interferogram in a single step. We achieve this through building a “two headed model,” which returns both outputs after one forward pass of an interferogram through the network. We train our model by first creating a data set of synthetic interferograms, but find that our model's performance is improved through the inclusion of real Sentinel-1 data. We also investigate how model performance can be improved by best organizing interferograms such that they can exploit the three channel nature of computer vision models trained on very large databases of labeled color images, but find that using different data in each of the three input channels degrades performance when compared to the simple case of repeating wrapped or unwrapped phase across each channel. We also release our labeled Sentinel-1 interferograms as a database named VolcNet, which consists of ∼500,000 labeled interferograms. VolcNet comprises of time series of unwrapped phase and labels of the magnitude, location, and duration of deformation, which allows for the automatic creation of interferograms between any two acquisitions, and greatly increases the amount of data available compared to other labeling strategies.

The Black Sea Waters (BSW) exported into the Aegean Sea largely control its overturning circulation as well as the regional biogeochemical characteristics. Observational evidence from ARGO floats and satellite-derived sea surface temperature (SST) and chlorophyll indicate a recent drastic reduction of Black Sea Water presence in the surface layer of the North Aegean Sea. This evidence is also supported by the long-term negative sea level difference trend between the southwestern Black Sea and the northeastern Aegean Sea. The role of the Black Sea in hindering deep water formation processes in the North Aegean seems to be diminishing. The future evolution of the Aegean overturning cell will depend on whether this trend will continue, in addition to the variability of local atmospheric forcing.

Paleomagnetic results obtained from 38 Pliocene—Pleistocene volcanic flows from the Knot of the Pastos and surroundings of Puracé volcano and Popayán (southwestern Colombia) are presented. Using stringent quality criteria and excluding sites that classify as representatives of transitional states of Earth's field, a selected group of 27 sites (16 with normal polarity and 11 with reversed polarity) was obtained with a mean direction (Dec = 357.8°, Inc = 6.4°, α₉₅ = 7.5° and κ = 15) that coincides with the geocentric axial dipole field (GAD: Dec = 0^o, Inc = 3.2^o) and, unlike similar studies at similar latitudes, does not coincide with the GAD plus a 5% axial quadrupolar component (Dec = 0°, Inc = −1.08°). However, when serial correlation (SC) among several sites with high inclination anomalies is taken into consideration, the mean direction of two resulting groups of sites shows greater consistency with a field that includes a quadrupolar component. It is interpreted that the sites treated for SC record states of the field similar to today's field in the area of study, which is being affected by the South Atlantic Anomaly.

Extracting volatiles from lunar regolith for analysis or utilization is one of the most important aspects of future lunar exploration. However, the low thermal conductivity of lunar regolith poses a challenge. Here, we conduct simulations to analyze the heat and mass transfer processes within the sample inside the oven. We identify three main factors affecting oven heat-up rate: water ice content (WIC) in the regolith, oven diameter, and power supply. Taking these factors into account, we devise an oven design and apply it to three case studies: (a) assessing water ice and isotopic composition in Permanently Shadowed Regions, akin to Chang'e-7 mini-fly probe missions; (b) measuring noble gases, as Chang'e-7 and Luna-27 landers; and (c) large-scale in-situ resources utilization (ISRU). The simulation results indicate that water ice can be extracted using sufficiently high heating power without issues. However, the complete extraction of noble gases is challenging and may require alternative heating methods. For ISRU purposes, large ovens can be subdivided into smaller ones by adding internal structures, for example, honeycomb, to improve the heat-up rate by at least 1.5 times. Additionally, we find that the oven can serve as a scientific payload for WIC measurement using the heating curve. A flowchart of this new WIC measurement method is provided, offering an alternative method to mass spectrometry or spectroscopy measurements.

Identifying how aerosol particles interact with atmospheric water is critical to understand climate and precipitation. Ice-nucleating particles (INP) trigger the formation of atmospheric ice crystals at higher temperatures than pure water. They are difficult to characterize because of their scarce occurrence, and variability, in the atmosphere, especially at temperatures above −20°C. It has been demonstrated that at these temperatures, biological aerosol particles can contribute significantly to INP number concentration. This study incorporates a series of offline, size-segregated measurements of INPs collected at the Puy de Dôme station (PUY, 1,465 m a.s.l.) over a 6 month period from October to May, covering the transitions from autumn, winter, to spring. These measurements show a general trend of decreasing particle number concentrations during the winter months and higher concentration during autumn and spring. INP concentrations measured in the range of −5 and −18°C, had concentrations of 0.001 INP/L_air at the warmest temperatures, and between 0.01 and 0.1 INP/L_air at the coldest temperatures. The majority of INP measured at temperatures warmer than −15°C were heat labile, suggesting a biological or organic origin. The INP variability was compared with collocated aerosol physical and chemical properties, allowing us to associate highest INP concentrations with local and marine origins. Following these comparisons, we use aerosol total number concentration to develop a new parameterization. In addition, this parameterization is specifically optimized for warmer temperature INP measurements, and demonstrated a good performance when tested on independent data sets.