The creation and evolution of the Songliao Basin is closely related to the closure of the Paleo-Asian Ocean and the Mongolia-Okhotsk Ocean, and the subduction of the Paleo-Pacific Ocean. In an attempt to demonstrate the various attributes of the lithospheric structure under structural superimposition and transformation of the Songliao Basin, this work used full impedance 3D inversion to obtain a 3D electrical structural model of the northern Songliao Basin for the first time. The results showed there are NE-trending high-resistance anomalies and sporadic low-resistance anomalies at the depth of less than 10 km. At 15-30 km, there are several NE- and NW-trending high-conductivity anomalies and there is a large area of SN-oriented high conductor at 50 km. The outcomes of the investigation demonstrate: 1) The high-resistance anomalies found in the NE direction of the upper crust are consistent with the position of the volcanic rocks predicted by the reflection earthquake, whereas the low-resistance anomalies correspond to the distribution of shallow faults and rifts. They constitute the main components of the upper crust of the Songliao Basin; 2) The high conductivity anomalies occurring at the intersection of the central depression zone and the north plunge zone represent the thinnest position of the lithosphere in the Songliao Basin; 3) The high-conductor anomalies in crust-mantle can be attributed to the paleo-shear zones which were generated in the collage of micro-continents during the Paleo-Asian Ocean closure, and reactivated under the continuous transformation of the Mongolia-Okhotsk and the Paleo-Pacific tectonic systems in the later period.

A document by Omon Obarein. Click on the document to view its contents.

A document by Dr. Hsing-Jui Wang. Click on the document to view its contents.

Causal discovery tools enable scientists to infer meaningful relationships from observational data, spurring advances in fields as diverse as biology, economics, and climate science. Despite these successes, the application of causal discovery to space-time systems remains immensely challenging due to the high-dimensional nature of the data. For example, in climate sciences, modern observational temperature records over the past few decades regularly measure thousands of locations around the globe. To address these challenges, we introduce Causal Space-Time Stencil Learning (CaStLe), a novel algorithm for discovering causal structures in complex space-time systems. CaStLe leverages regularities in local dependence to learn governing global dynamics. This local perspective eliminates spurious confounding and drastically reduces sample complexity, making space-time causal discovery practical and effective. These advances enable causal discovery of geophysical phenomena that were previously unapproachable, including non-periodic, transient phenomena such as volcanic eruption plumes. When applied to ever-larger spatial grids, CaStLe's performance actually improves because it transforms large grids into informative spatial replicates. We successfully apply CaStLe to discover the atmospheric dynamics governing the climate response to the 1991 Mount Pinatubo volcanic eruption. We additionally provide extensive validation experiments to demonstrate the effectiveness of CaStLe over existing causal-discovery frameworks on a range of climate-inspired benchmarks.

This paper presents the first ever observations on aspect-sensitive characteristics of 205 MHz Stratosphere-troposphere radar located at a tropical station Cochin (10.04°N, 76.3°E) using volume scanning. The most significant and new observation is that the signal-to-noise ratio in zenith and off-zenith beams are nearly equal in some height region, indicating the presence of isotropic turbulence. Signal strength decreases by 0.75 dB per degree from 0 to 10 degree off-zenith, 0.9 dB per degree from 10 to 20 degree off-zenith and 0.3 dB per degree beyond 20 degree offzenith. Different causative mechanisms are discussed on the basis of various estimated parameters associated with aspect sensitivity. Maximum aspect sensitivity is observed between 12 and 17 km, indicating the presence of dynamic instability arising due to strong wind shear and atmospheric stability. When both the square of wind shear and stability parameters are above 0.25 × 10 −3 s −2 , the scatterers become mostly isotropic. The study also shows a power difference in the symmetric beams as well as azimuth angle dependency. Analysis suggests that this asymmetry is due to the tilting of layers by the action of atmospheric gravity waves generated through Kelvin-Helmholtz-instability. The

A document by Daniel J Zawada. Click on the document to view its contents.

The arid and semi-arid regions are highly vulnerable to climate change and variability. Agricultural production in these regions is particularly vulnerable because of its heavy dependence on on climate conditions. Therefore, it is important to improve the projections of future agro-climatic conditions. This study investigates the projections of agroclimatology change during 2031–2050 under the Representative Concentration Pathway (RCP) 8.5 emission scenario in the semi-arid North China. It is simulated by the agro-ecological zone (AEZ) model with climate data provided by the regional climate model (RCM) of Providing regional Climates for Impacts Studies (PRECIS). The Chinese Medicinal Yam (CMY), which is genuinely produced over semi-arid regions, is taken as an example to study the change of its yield and producing area under future climate change. The results show that the high-resolution RCM simulation corresponds better with the observations than the general circulation model (GCM) in precipitation and temperature. In North China, the CMY genuine production area, the precipitation will increase by about 10% and the temperature will increase by about 2oC under the RCP8.5 scenario. After the evaluation and projection of climate models, the potential yield of CMY and the suitable planting regions are simulated by using the AEZ model. The CMY production areas will expand northward in the future, due to the climate warming in the north. The traditional yam production area still maintains the suitability of CMY production. The production of CMY will augment because of the increased production area.

With global warming and increasing water use, tap water resources need sustainable management. We used hydrogen and oxygen isotope measurements (𝛿2H and 𝛿18O) to identify issues associated with tap water resources in Canada. We analyzed 576 summer tap samples collected from across Canada and 76 tap samples from three cities during different seasons and years. We classified the samples based on their sources: groundwater (TapGroundwater), river (TapRiver) and lake (TapLake). 𝛿2H in tap water correlates strongly with values predicted for local precipitation across Canada with a stronger correlation for TapGroundwater and TapRiver than for TapLake. We then constructed water balance models to predict the 𝛿2H of surface water across Canada, and validated it against Canadian river water 𝛿2H data. 𝛿2H in tap water correlates strongly with values predicted for surface water across Canada with a stronger correlation for TapRiver and TapLake than for TapGroundwater. TapGroundwater 𝛿2H values reflect the 𝛿2H of annually averaged precipitation, whereas TapRiver and TapLake 𝛿2H values reflect post-precipitation processes. We used the 𝛿2H residuals between the observed and predicted 𝛿2H values to assess regional processes influencing tap water 𝛿2H values across Canada. Regionally, snow/glacier melt contributes to all tap sources around the Rockies. Tap waters are highly evaporated across Western Canada, irrespective of their sources. In the Great Lakes and East Coast regions, tap waters are evaporated in many localities, particularly those using surface reservoirs and lakes. This study provides baselines for isotopic monitoring of tap water resources and forensic studies in Canada.

This study examines 40 years of monthly precipitation data in Senegal (1979-2018) using CRU observations and ERA5 reanalyses, aiming to understand the influence of oceanic and atmospheric factors on Senegal’s precipitation in July, August and September (JAS). Comparing Senegal’s precipitation variability with the broader Sahel region, it emerges that Senegal’s precipitation is more closely associated with the Northeastern Tropical Atlantic (NETA) Sea Surface Temperature (SST). The increased Senegal’s precipitation is linked to the northward shift of the InterTropical Convergence Zone (ITCZ), consistent with numerous previous studies. Over the continent, this shift corresponds to a northward shift of the African Easterly Jet (AEJ) and, consequently, the Mesoscale Convective Systems responsible for most precipitation. It seems primarily driven by the northward shift of the Heat Low.Over the ocean west of Senegal, there is a comparable shift of the AEJ, accompanied by increased low-level moisture transport convergence within the West African Westerly Jet (WAWJ). This phenomenon is triggered by a negative pressure anomaly in the NETA, located above a positive SST anomaly: we suggest that the latter is the origin of the former, forming a feedback mechanism that potentially significantly influences Senegal’s precipitation. The mechanism involves a geostrophic adjustment of the WAWJ to the southern gradients of the SST anomaly. To validate the NETA SST feedback’s role in Senegal’s precipitation, further investigations using daily data or regional atmospheric models are recommended. The findings hold potential for enhancing seasonal forecasting capabilities.

Direct observations of background diapycnal mixing rates in the Southern Ocean (SO) are limited spatially and temporally, making the choice of an appropriate value to parameterise this mixing in Earth system models a challenge. However, the deployment of Argo floats throughout the SO has provided an extensive range of observations of both physical and biogeochemical parameters. We use an ocean state estimate run with various background diapycnal mixing coefficients to assess if biogeochemical tracer observations can be used to better constrain SO diapycnal mixing rates. We find that vertical tracer distributions in the SO are highly sensitive to the rate of background diapycnal mixing and can provide an upper limit on background mixing rates. This demonstrates the importance of biogeochemical tracer observations throughout the full depth of the water column to validate ocean models.

The results of prior work indicated that the Southeast United States (SEUS) region contains extreme Quantitative Precipitation Forecast (QPF) skill that is lower than other regions in the U.S. (e.g., the Western and Northeast US). A hypothesis is that this skill is influenced by a diversity of storm types such as Atmospheric Rivers (ARs), Mesoscale Convective Systems (MCS) and Tropical Cyclones (TCs) occurring within distinct synoptic patterns, which have resulted in significant floods such as in Nashville (2010) and Waverly (2021) Tennessee. Similarly, previous investigations have identified that synoptic patterns with higher integrated vapor transport (IVT) potentially have greater QPF skill than those with lower IVT. There is further opportunity to investigate pattern-wise contribution of storm types and QPF skill in SEUS. This study identified six synoptic patterns associated with heavy precipitation in Tennessee. These patterns exhibited distinct seasonality, with three patterns occurring in the cool season, two in the warm season, and one in the transition season. Approximately, 66 % of heavy precipitation in cool season and 47 % in transition season is associated with coincident ARs and MCS. Pattern-wise QPF skill derived from the GEFS Reforecast dataset illustrated that the cool season pattern with the highest IVT and largest fraction of ARs has better skill, whereas the warm season pattern with the highest CAPE and integrated water vapor has worse skill at multiple lead times. These results provide insights into the dynamical characteristics and predictability of heavy precipitation by storm type over the SEUS.

MHD avalanches involve small, intensely localized instabilities that spread across neighbouring regions in a magnetic field. Cumulatively, many small events release vast amounts of stored magnetic energy. Straight cylindrical flux tubes, in Parker (1972)’s model of coronal loops, are liable to such avalanches: one unstable flux tube can cause instability to proliferate through reconnection, resulting in an ongoing chain of like events. True coronal loops are curved, arching between different footpoints on one photospheric plane. Using three-dimensional MHD simulations, we here verify the viability of MHD avalanches within the curved magnetic geometry of a multi-threaded coronal arcade. In contrast to the behaviour of straight cylindrical models, a modified ideal MHD kink mode occurs more readily and preferentially upwards in this new geometry. Such instability spreads over a region far wider than the original flux tubes, and wider than their photospheric footpoints. Consequently, substantial and sustained heating is produced, in a series of nanoflare-type events, contributing significantly to coronal heating. Overwhelmingly dominant is viscous heating, attributable to the shocks and jets produced around these small events. Reconnection is not the greatest contributor to heating, but rather the facilitator of those processes that are. Localized and intermittent, the heating shows no strong spatial preference, except for a small bias away from footpoints. Effects of realistic physical plasma parameters and the implications for thermodynamic models, with energetic transport, are discussed.

This work aims at presenting how we have developed the ShakeMap Atlas of historical earthquakes in Italy through the following steps: 1. the collection of macroseismic data for a selected dataset of historical Italian earthquakes with magnitudes equal to or greater than 6. 2. the adoption of two different ShakeMap configurations. 3. the application of the iterative leave-one-out cross-validation procedure within ShakeMap to identify the most appropriate configuration. 4. the analysis of the results. Acknowledgements A d d your information, graphs and images to this section.

Alpine glacier meltwater from the Qilian Mountains (QMs), northeast Tibetan Plateau, is main source of water for the surrounding arid zones. Accurately reconstructing long-term mountain glacier mass balance (MB) and prejecting glacier changes under climate warming are pivotal in cryospheric scientific research. In this study, Laohugou Glacier No. 12 (LHG12), in the western QMs, was selected as a study area. Based on the evaluated and corrected CMIP6 model data, the degree-day and glacier retreat model were used to predict the glacier changes under three scenarios for 2020–2100. The results showed that 1) from 2020–2100, the annual mass loss of LHG12 simulated using CanESM5 and EC-Earth3 increased compared to the measured data in the historical period (2010–2014) (i.e., annual MB of -0.26 m w.e) by a factor of 1.04 and 1.73 under SSP1-2.6, 4.62 and 4.88 under SSP3-7.0, and 6.23 and 7.15 times under SSP5-8.5. 2) By 2100, the ice volume of LHG12 simulated using CanESM5 and EC-Earth3 reduced to 1.00×109 (58.2%) and 1.27×109 (74.0%) m3 under SSP1-2.6, 0.18×109 (10.2%) and 0.15×109 (8.9%) m3 under SSP3-7.0, and 0.03×109 (1.6 %) and 0.01×109 (0.4%) m3 under SSP5-8.5, respectively. 3) Under SSP5-8.5, the LHG12 area simulated using CanESM5 and EC-Earth3 was only 1.87 and 0.75 km2 by 2100. This study lays a foundation for predicting the peak and inflection points of runoff change in the QMs.

In this paper we review basic elements of Frequentist inference, specifically maximum likelihood (ML) and M-estimation to point out a critical flaw of Bayesian methods for hydrologic model training and uncertainty quantification. Under model misspecification, the sensitivity $\widehat{\mathbf{A}}_{n}$ and variability $\widehat{\mathbf{B}}_{n}$ matrices of the ML model parameter values $\widehat{\bm{\uptheta}}_{n}$ provide conflicting information about the observed Fisher information $\widehat{\boldsymbol{\mathcal{I}}}\vphantom{\overline{\widehat{\boldsymbol{\mathcal{I}}}}}_{n}$ of the data $\omega_{1},\ldots,\omega_{n}$ for $\bm{\uptheta} = (\theta_{1},\ldots,\theta_{d})^{\top}$. As a result, the ML parameter covariance matrix, $\Var(\widehat{\bm{\uptheta}}_{n})$, does not simplify to the matrix inverse of the observed Fisher information, $\widehat{\boldsymbol{\mathcal{I}}}\vphantom{\overline{\widehat{\boldsymbol{\mathcal{I}}}}}_{n}$, as suggested by naive ML estimators and Bayesian MCMC methods but amounts instead to the so-called sandwich matrix $\Var(\widehat{\bm{\uptheta}}_{n}) = \widehat{\boldsymbol{\mathcal{G}}}\vphantom{\overline{\widehat{\boldsymbol{\mathcal{G}}}}}_{n}^{-1} = \fracn \widehat{\mathbf{A}}_{n}^{-1}\widehat{\mathbf{B}}^{\vphantom{-1}}_{n}\widehat{\mathbf{A}}_{n}^{-1}$, where the observed Godambe information $\widehat{\boldsymbol{\mathcal{G}}}\vphantom{\overline{\widehat{\boldsymbol{\mathcal{G}}}}}_{n}$ is the fundamental currency of data informativeness under model misspecification. The \textit{sandwich} matrix is a metaphor for a \textit{meat} matrix $\widehat{\mathbf{B}}_{n}$ between two \textit{bread} matrices $\widehat{\mathbf{A}}_{n}$ and yields asymptotically valid “robust standard errors” even when the likelihood function $L_{n}(\bm{\uptheta})$ (model) is incorrectly specified. The implications of the sandwich variance estimator are demonstrated in three case studies involving the modeling of soil water infiltration, watershed hydrologic fluxes and the rainfall-discharge transformation. First and foremost, our analytic and numerical results demonstrate that the sandwich variance estimator increases substantially hydrologic model parameter and predictive uncertainty. The sandwich estimator is invariant to likelihood stretching practiced by the GLUE method as a remedy for over-conditioning and requires magnitude and/or curvature adjustments to the likelihood function to yield asymptotically valid sandwich parameter estimates and inference via MCMC simulation.

In late January 2019, a severe cold air outbreak brought the coldest temperatures in over 20 years to Midwestern United States and Eastern Canada. With a newly developed functional analysis tool namely multiscale window transform (MWT), and the MWT-based theory of canonical transfer, it is found, based on the data from National Center for Environmental Prediction, that the cold surge, though initialized by the southward migration of the Arctic air mass, is mainly caused by a synchronization of perturbation temperature and perturbation winds, which leads to a very strong baroclinic instability, and hence an explosive growth of available potential energy on the cold surge scale. The cold event is actually a part of a localized stationary wave train, sandwiched between two warming centers, respectively over western North America and over Atlantic. The synchronization can serve as a precursor for this extremely severe cold surge.

A document by Eshrat Fatima. Click on the document to view its contents.

Studying the daily evolution of turbulent fluxes modulated by snowfall over the Tibetan Plateau (TP) is of importance to understand the features of the change in the TP heat source/sink. Based on observations from 4 sites of the Third TP Atmospheric Scientific Experiment, the process of surface energy balance impacted by snow is investigated. The results show that the surface albedo increases on the first day of snow and then slowly decreases. Correspondingly, the sensible heat (H) flux sharply decreases after snow and then recovers to the original level during the following approximately 10 days. The latent heat (LE) flux becomes more active and stronger after snowfall and persists for a longer period than H, since the soil moisture may still contribute to a high LE after snowmelt. As the synergistic result of H and LE modulated by snow, the surface turbulent heating (i.e., the sum H and LE) of the TP decreases at the early period of snow events and then even enhances to a higher level after the snowmelt than before snow. Comparison analyses reveal that the impact of snow on the H and LE over the TP is much stronger than over similar latitude low-altitude regions in North America and Europe, which may be partly attributed to the larger and more drastic change of the surface net solar radiation associated with snow processes in the TP. This study may help further understand the detailed physical processes of modulation of snow events on Asian weather processes during winter.