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We present an accurate method for the calculation of gravitational potential (GP), vector (GV), and gradient tensor (GGT) of a tesseroid, considering a density model in the form of a polynomial up to cubic order along the vertical direction. The method solves volume integral equations for the gravitational effects due to a tesseroid by the Gauss–Legendre quadrature rule. A two-dimensional adaptive subdivision technique, which automatically divides the tesseroids near the computation point into smaller elements, is applied to improve the computational accuracy. For those tesseroids having small vertical dimensions, an extension technique is additionally utilized to ensure acceptable accuracy, in particular for the evaluation of GV and GGT. Numerical experiments based on spherical shell models, for which analytical solutions exist, are implemented to test the accuracy of the method. The results demonstrate that the new method is capable of computing the gravitational effects of the tesseroids with various horizontal and vertical dimensions as well as density models, while the evaluation point can be on the surface of, near the surface of, outside the tesseroid, or even inside it (only suited for GP and GV). Thus, the method is attractive for many geodetic and geophysical applications on regional and global scales, including the computation of atmospheric effects for terrestrial and satellite usage. Finally, we apply this method for computing the topographic effects in the Himalaya region based on a given digital terrain model and the global atmospheric effects on the Earth’s surface by using three polynomial density models which are derived from the US Standard Atmosphere 1976.

The unique P-band synthetic aperture radar (SAR) instrument, BIOMASS, is scheduled for launch in 2024. This satellite will enhance the estimation of subcanopy topography, owing to its strong penetration and fully polarimetric observation capability. In order to conduct global-scale mapping of the subcanopy topography, it is crucial to calibrate systematic errors of different strips through interferometric SAR (InSAR) DEM (digital elevation model) block adjustment. Furthermore, the BIOMASS mission will operate in repeat-pass interferometric mode, facing the atmospheric delay errors introduced by changes in atmospheric conditions. However, the existing block adjustment methods aim to calibrate systematic errors in bistatic mode, which can avoid possible errors from atmospheric effects through interferometry. Therefore, there is still a lack of systematic error calibration methods under the interference of atmospheric effects. To address this issue, we propose a block adjustment model considering atmospheric effects. Our model begins by employing the sub-aperture decomposition technique to form forward-looking and backward-looking interferograms, then multi-resolution weighted correlation analysis based on sub-aperture interferograms (SA-MRWCA) is utilized to detect atmospheric delay errors. Subsequently, the block adjustment model considering atmospheric effects can be established based on the SA-MRWCA. Finally, we use robust Helmert variance component estimation (RHVCE) to build the posterior stochastic model to improve parameter estimation accuracy. Due to the lack of spaceborne P-band data, this paper utilized L-band Advanced Land Observing Satellite (ALOS)-1 PALSAR data, which is also long-wavelength, to emulate systematic error calibration of the BIOMASS mission. We chose climatically diverse inland regions of Asia and the coastal regions of South America to assess the model’s effectiveness. The results show that the proposed block adjustment model considering atmospheric effects improved accuracy by 72.2% in the inland test site, with root mean square error (RMSE) decreasing from 10.85 m to 3.02 m. Moreover, the accuracy in the coastal test site improved by 80.2%, with RMSE decreasing from 16.19 m to 3.22 m.

Accurate representation of heat fluxes is crucial for understanding land–atmosphere interactions and improving atmospheric simulations. However, a common issue arises with flux imbalance, where the measured turbulent heat flux tends to be underestimated due to the nonlocal effects of atmospheric secondary circulations. This study evaluated four flux imbalance prediction models by analyzing data from large eddy simulations performed over heterogeneous land surfaces. For that, a checkerboard pattern of soil moisture was used to define the lower boundary conditions for the atmosphere, across heterogeneity scales ranging from 50 m to 2.4 km. The results show that the selected models can effectively predict flux imbalance when provided with proper semi-empirical factors. The presence of two distinct secondary circulations, thermally-induced mesoscale circulation and turbulent organized structures, account for the nonlinear effect of the heterogeneity scale on the flux imbalance, but it does not affect the performance of the selected models. This study suggests that the flux imbalance prediction models are useful for improving e.g. eddy-covariance measurements. Additionally, a quadrant analysis showed an increasing difference between ejections and sweeps with height, which explains the decrease and increase of the turbulent heat flux and flux imbalance, respectively, and underscores the importance of accounting for vertical variations in turbulent fluxes to represent atmospheric processes accurately.

Oceanic-atmospheric phenomena can change the patterns of rainfall (R) and potential evapotranspiration (ET 0 ) and, therefore, the water availability of a location, resulting in significant effects on agricultural activity. This study evaluated the trend of the climatic water budget (W) of a river basin in the Brazilian semiarid region, the Pajeú river basin, as a function of variations in R and ET 0 resulting from changes in climate patterns and atmospheric circulation systems. For this, data series of 27 rain gauge and 8 complete weather stations with different time intervals were used (i.e., a maximum range of 1912 to 2019, 108 years). Data from 8 complete weather stations were used to estimate ET 0 , and to calibrate and validate methods for estimating incident solar radiation (Rs) and ET 0 , aiming to fill in gaps in the data series. Seasonal and cyclical trends for R, ET 0 and W were evaluated on ten timescales, using the Mann–Kendall test, Sen Slope test, Pettitt test and the Seasonal Trend decomposition using Loess. The timescales were defined based on an annual basis, in the seasons, dry and rainy periods, and during the agricultural calendar of three important crops in the region. Pearson correlation method was applied to identify the effects of atmospheric circulation systems on the values of R, ET 0 , and W from teleconnection indices for the ten timescales. Significant positive trends of up to + 3.71 mm year −1 for ET 0 , and negative trends up to -3.48 mm year −1 for W were found. The Atlantic Multidecadal Oscillation (AMO) index and El Niño 1 + 2 (N12) index both showed a correlation with R, ET 0 and W only for the annual period. The results indicate the need to adapt the planting times of the main agricultural crops in the region, as well as to reduce water use in irrigated areas, as a strategy for water and food security.

Although extreme adaptive optics (ExAO) systems can greatly reduce the effects of atmospheric turbulence and deliver diffraction-limited images, our ability to observe faint objects such as extrasolar planets or debris disks at small angular separations is greatly limited by the presence of a speckle halo caused by imperfect wavefront corrections. These speckles change with a variety of timescales, from milliseconds to many hours, and various techniques have been developed to mitigate them during observations and during data reduction. Detection limits improve with increased speckle reduction, so an understanding of how speckles evolve (particularly at near-infrared wavelengths, which is where most adaptive optics science instruments operate) is of distinct interest. We used a SAPHIRA detector behind Subaru Telescope's SCExAO instrument to collect H-band images of the ExAO-corrected point-spread function (PSF) at a frame rate of 1.68 kHz. We analyzed these images using two techniques to measure the timescales over which the speckles evolved. In the first technique, we analyzed the images in a manner applicable to predicting performance of real-time speckle-nulling loops. We repeated this analysis using data from several nights to account for varying weather and AO conditions. In our second analysis, which follows the techniques employed by Milli et al. (2016) but using data with three orders of magnitude better temporal resolution, we identified a new regime of speckle behavior that occurs at timescales of milliseconds. It is not purely an instrument effect and likely is an atmospheric timescale filtered by the ExAO response. We also observed an exponential decay in the Pearson's correlation coefficients (which we employed to quantify the change in speckles) on timescales of seconds and a linear decay on timescales of minutes, which is in agreement with the behavior observed by Milli et al. For both of our analyses, we also collected similar data sets using SCExAO's internal light source to separate atmospheric effects from instrumental effects.

The surge in urbanization and industrialization is majorly contributing to ambient air pollution, predominantly in terms of particulate emissions. Human health is highly susceptible to the particles suspended in the air due to their lightweight and small size (≤ 2.5 μm), called atmospheric aerosols. In India, insufficient ground-based instruments hinder continuous aerosol monitoring. However, remote sensing offers earth imagery for in-depth analysis of air quality and weather parameters. In the present study, an attempt is made to retrieve the high-resolution (30 m) AOT using Landsat 8 Operational Land Imager (L8-OLI) imagery for Pune, Maharashtra, from the years 2014 to 2021. For the atmospheric corrections and better spatiotemporal resolution, the dark target spectrum-based Image Corrections for Atmospheric Effects (iCOR) algorithm was executed. The year 2021 showed the highest mean AOT value at the Pashan location (18.537° N, 73.805° E) in Pune, India. Also, seasonal analysis (winter and summer) indicates that the mean AOT in the winter gradually increases every year. The AOT retrieved using L8-OLI with iCOR and AOT retrieved from Aerosol Robotic Network (AERONET) in situ monitoring station (± 30 min) at 440 nm showed R2 = 0.76, r = 0.83, and RMSE = 0.1012. From this, it is summarized that for L8-OLI images, the iCOR algorithm performs well for the atmospheric correction by retrieving AOT at high spatial resolution with minimum cloud cover.

Recent change in the daily temperature variation (DTV) for March in East Asia is investigated. For this purpose, the effects of atmospheric circulation and global warming on the DTV in the region are analyzed using Japanese 55-year reanalysis data. Among the high-frequency variations in surface air temperature (SAT) during spring, the DTV in March showed a significant, increasing trend in East Asia during the four decades from 1979 to 2020. Composite analysis shows that the above-normal March DTV is associated with the anomalous anticyclonic circulation in the North Pacific and the anomalous cyclonic circulation over Russia. These atmospheric circulation anomalies lead to a greater meridional SAT gradient and tend to cause more mid-latitude pressure systems to pass over East Asia. Ultimately, the SAT in March becomes more variable due to enhanced thermal advection over East Asia. In addition, this pattern of circulation anomalies associated with a large March DTV includes features of a weak East Asian winter monsoon (EAWM) system. Meanwhile, regression analysis results using the EAWM and long-term global warming trend indices suggest that both the large-scale atmospheric circulation and global warming contribute significantly to the March DTV change in East Asia. In particular, heterogeneous warming rates and localized soil drying in East Asia during the study period likely explain the role of global warming on East Asian DTV in March.

High spatio‐temporal variability of atmospheric water vapor affects microwave signals of Global Navigation Satellite Systems (GNSS) and Interferometric Synthetic Aperture Radar (InSAR). A better knowledge of the distribution of water vapor improves both GNSS‐ and InSAR‐derived data products. In this work, we present a collocation framework to combine and retrieve zenith and (relative) slant tropospheric delays. GNSS and InSAR meteorological products are combined aiming at a better retrieval of the atmospheric water vapor. We investigate the combination approach with synthetic and real data acquired in the Alpine region of Switzerland. Based on a closed‐loop validation with simulated delays, a few mm accuracy is achieved for the GNSS‐InSAR combination in terms of retrieved ZTDs. Furthermore, when real delays are collocated, the combination results are more congruent with InSAR computed products. This research is a contribution to improve the spatio‐temporal mapping of tropospheric delays by combining GNSS‐derived and InSAR‐derived delays.

The accurate computation of gravitational effects from topographic and atmospheric masses is one of the core issues in gravity field modeling. Using gravity forward modeling based on Newton’s integral, mass distributions are generally decomposed into regular mass bodies, which can be represented by rectangular prisms or polyhedral bodies in a rectangular coordinate system, or tesseroids in a spherical coordinate system. In this study, we prefer the latter representation because it can directly take the Earth’s curvature into account, which is particularly beneficial for regional and global applications. Since the volume integral cannot be solved analytically in the case of tesseroids, approximation solutions are applied. However, one well-recognized issue of these solutions is that the accuracy decreases as the computation point approaches the tesseroid. To overcome this problem, we develop a method that can precisely compute the gravitational potential V and vector Vx,Vy,Vz on the tesseroid surface. In addition to considering a constant density for the tesseroid, we further derive formulas for a linearly varying density. In the near zone (up to a spherical distance of 15 times the horizontal tesseroid dimension from the computation point), the gravitational effects of the tesseroids are computed by Gauss–Legendre quadrature using a two-dimensional adaptive subdivision technique to ensure high accuracy. The tesseroids outside this region are evaluated by means of expanding the integral kernel in a Taylor series up to the second order. The method is validated by synthetic tests of spherical shells with constant and linearly varying density, and the resulting approximation error is less than 10-4m2s-2 for V, 10-5mGal for Vx, 10-7mGal for Vy, and 10-4mGal for Vz. Its practical applicability is then demonstrated through the computation of topographic reductions in the White Sands test area and of global atmospheric effects on the Earth’s surface using the US Standard Atmosphere 1976.

Climate change is occurring, is caused largely by human activities, and poses significant risks for-and in many cases is already affecting-a broad range of human and natural systems. The compelling case for these conclusions is provided in Advancing the Science of Climate Change , part of a congressionally requested suite of studies known as America's Climate Choices. While noting that there is always more to learn and that the scientific process is never closed, the book shows that hypotheses about climate change are supported by multiple lines of evidence and have stood firm in the face of serious debate and careful evaluation of alternative explanations. As decision makers respond to these risks, the nation's scientific enterprise can contribute through research that improves understanding of the causes and consequences of climate change and also is useful to decision makers at the local, regional, national, and international levels. The book identifies decisions being made in 12 sectors, ranging from agriculture to transportation, to identify decisions being made in response to climate change. Advancing the Science of Climate Change calls for a single federal entity or program to coordinate a national, multidisciplinary research effort aimed at improving both understanding and responses to climate change. Seven cross-cutting research themes are identified to support this scientific enterprise. In addition, leaders of federal climate research should redouble efforts to deploy a comprehensive climate observing system, improve climate models and other analytical tools, invest in human capital, and improve linkages between research and decisions by forming partnerships with action-oriented programs.