The solar corona, the outer atmosphere of the Sun, is heated to millions of degrees. This is several orders of magnitude hotter than the photosphere, the optical surface of the Sun, below, and a mystery that has baffled scientists for centuries. The answer to the question of how the solar corona is heated lies in the crucial magnetic connection through the atmosphere of the Sun. The magnetic field that threads the corona extends below the solar photosphere, where the convective motions drag the magnetic field footpoints, tangling and twisting them. The chromosphere is the atmospheric layer above the photosphere, below the corona, and the magnetic field provides an important connection between these layers. The exchange of mass and energy between the chromosphere and corona is an essential piece of this puzzle. The connection between the chromosphere and the corona is a challenging piece of the puzzle both observationally and computationally, as it is highly complex in space and time. We describe the history of the observations and theoretical understanding of the heating of the solar atmosphere, and end with future prospects of the coronal heating problem.

This introductory chapter discusses the atmospheric subgrid processes ─ collectively called "fast 11 physics" or "fast processes", and their parameterizations in large scale atmospheric models. It 12 presents a brief historical progression of the parameterization of fast processes in numerical 13 models. Despite great efforts and notable advances in understanding, progress in improving fast 14 physics parameterizations has been frustratingly slow, the underlying reasons for which are 15 explored. To guide readers, this chapter describes the main objectives and scope of this book and 16 summarizes each chapter. 

Preface Many physical processes that influence Earth's climate and weather occur on spatial (temporal) scales smaller (shorter) than typical grid sizes (time steps) of general circulation models, and thus must be parameterized. Computer models are essential tools for understanding atmospheric phenomena and for making accurate predictions of any changes in the Earth's climate, weather, and resources of renewable energy resulting from anthropogenic activities that generate greenhouse gases and particulates into the atmosphere. This book focuses on the atmospheric subgrid processes ─ collectively called fast physics ─by reviewing and synthesizing relevant physical understanding, parameterization developments, various measurement technologies, and model evaluation framework. The publication is divided into three parts, containing seventeen chapters (Chapters 2-17) to reflect and synthesize the multiple aspects involved. The first chapter briefly introduces the historical development of fast physics parameterizations and the involved complexities; the last chapter summarizes emerging challenges, new opportunities and future research directions. Part I deals with major subgrid processes, with eight chapters (Chapters 2-9) each covering different processes more or less in the conventional compartmentalized format with an emphasis on individual processes, including but, not limited to radiative transfer, aerosols, and aerosol direct & indirect effects, entrainment-mixing processes, their microphysical influences, convection & convective clouds, stratiform clouds such as stratus and stratocumulus clouds, planetary boundary layer processes, land surface and interactions with atmosphere, and gravity waves. On top of the conventional treatments, some promising ideas/approaches have recently emerged to unify the treatment of individual processes and thus allows for consideration of process interactions. Part II is devoted to such unifying efforts, with four chapters (Chapters 10-13) covering four different endeavors: the unifying parameterizations based on assumed probability density functions; the EDMF approach that combines the Eddy Diffusivity and Mass Flux approaches to unify turbulence and convection; application of machine learning techniques; and innovative top-down attempts that consider the involved totality by borrowing ideas from systems theory, statistical physics, and non-linear sciences. Part III (Chapters 14-17) is devoted to assessments, model evaluation, and model-measurement integration, with four chapters that focus on satellite and airborne remote sensing measurements, surface-based remote sensing measurements, in-situ and laboratory measurements, and model evaluation, and model-measurement integration, respectively.

Significant advances have been made over the last two decades in constraining the structure of the continental lithosphere in Alaska, particularly with the EarthScope USArray seismic data collection efforts. This paper distills recent seismic models in Alaska and western Yukon (Canada) and relates them to major faults and tectonic terranes. We synthesize results from eight shear-wave velocity models and seven crustal thickness models. Through objective clustering of seismic velocity profiles, we identify six different velocity domains, separately for the crust (at the depth range of 10-50 km) and the mantle (at the depth range of 40-120 km). The crustal seismic domains show strong correlations with average crustal thickness patterns and the distribution of major faults and tectonic terranes. The mantle seismic velocity domains demonstrate signatures of major faults and tectonic terranes in northern Alaska while in southern Alaska the domains are primarily controlled by the geometry of the subducting lithosphere. The results of this study have significant implications for the tectonics and geodynamics of the overriding continental lithosphere from the margin to the interior. This synthesis will be of interest to future studies of Alaska as well as other modern and ancient systems involving convergent margins and terrane accretions.

Experiment and observation have established the centrality of oxygen fugacity (fO2) to determining the course of igneous differentiation, and so the development and application of oxybarometers have proliferated for more than half a century. The compositions of mineral, melt, and vapor phases determine the fO2 that rocks record, and the activity models that underpin calculation of fO2 from phase compositions have evolved with time. Likewise, analytical method development has made new sample categories available to oxybarometric interrogation. Here we compile published analytical data from lithologies that constrain fO2 (n=860 volcanic rocks - lavas and tephras and n=326 mantle lithologies- the majority peridotites) from ridges, back-arc basins, forearcs, arcs, and plumes. Because calculated fO2 varies with choice of activity model, we re-calculate fO2 for each dataset from compositional data, applying the same set of activity models and methodologies for each data type. Additionally, we compile trace element concentrations (e.g. vanadium) which serve as an additional fO2-proxy. The compiled data show that, on average, volcanic rocks and mantle rocks from the same tectonic setting yield similar fO2s, but mantle lithologies span a much larger range in fO2 than volcanics. Multiple Fe-based oxybarometric methods and vanadium partitioning vary with statistical significance as a function of tectonic setting, with fO2 ridges < back arcs < arcs. Plume lithologies are more nuanced to interpret, but indicate fO2s  ridges. We discuss the processes that may shift fO2 after melts and mantle lithologies physically separate from one another. We show that the effects of crystal fractionation and degassing on the fO2 of volcanics are smaller than the differences in fO2 between tectonic settings and that effects of subsolidus metamorphism on the fO2 values recorded by mantle lithologies remain poorly understood. Finally, we lay out challenges and opportunities for future inquiry.

The Gulf of Mexico is a prolific petroleum basin with more than a century-long exploration history. Tectonic models proposed for the basin vary dramatically in many aspects, ranging from the pre-rift locations of the crustal blocks, the timing of the break-up to even the order of tectonic events. The reason for these disagreements is in a thick and complex overburden that obscures seismic imaging of crustal structures. To overcome that, we integrated seismic data with gravity and magnetic fields to determine the crustal architecture in different parts of the basin, as well as to map the location of the key tectonic features. The subsequent spatial analysis of potential fields allowed us to trace the tectonic structures outside of seismic coverage. As a result, a set of new geological constraints was derived including the Triassic rifts, regions of Seaward Dipping Reflectors (SDR), and Jurassic pre-salt sedimentary basins in the eastern Gulf of Mexico and along the Yucatan margin, and two distinct crustal zones in the oceanic domain. We ensure the pre-breakup alignment of the crustal blocks based on the mapped geological features on the conjugate margins. Our tectonic reconstruction takes into account an apparent temporal variability of the magmatic regime during basin formation that ranged from CAMP (~200 Ma) to an ultra-slow amagmatic spreading during the initial stage of the GoM opening (~ 165 Ma). Our reconstruction also includes a major ridge reorganization (~ 152 Ma) associated with increased magmatic supply. This second phase of oceanic spreading ceased at early Cretaceous (~ 135 Ma) based on published correlation analysis of seismic and well data. Overall, the tectonic reconstruction presented here takes into account previously known and newly derived geological constraints and integrates various geophysical datasets, namely seismic, gravity, and magnetics.

Changes in precipitation extremes remain a key uncertainty as the climate warms. Improved understanding of their evolution is crucial for effective water management. A number of studies have demonstrated various scaling relationships between precipitation extremes and several different environmental variables. In this chapter, we review recent important advances in two of these relationships primarily based on observations: The scaling of precipitation extremes with surface temperature (both air temperature and dew point temperature) and convective available potential energy (CAPE). Two up-to-date global daily datasets are also used to provide a further check on the generality of earlier findings. Known scaling relationships are used to quantify the impacts of these two factors on precipitation extremes. Results show that both of them play important roles, but their impacts vary over different regions on various time scales, highlighting the challenges of constructing global relationships to explain the changing nature of precipitation extremes.

The prediction of how ice crystals form represents one of the great conundrums in the atmospheric sciences with important implications for the hydrological cycle and climate. Ice-nucleating particles (INPs), typically consisting of sub-and supermicrometer-sized aerosol particles which can be inorganic, organic, biogenic, or biological, initiate heterogeneous ice nucleation processes leading to ice crystal formation. Heterogeneous ice nucleation commences on the nanoscale at the substrate surface and depends on ambient temperature and humidity. Microanalysis techniques are uniquely suited to examine the physicochemical features of the INPs under relevant atmospheric conditions thereby advancing our understanding of the principal processes that promote ice nucleation. In the atmosphere ice crystals experience growth and sublimation resulting in complex microscopic morphologies which, in turn, impact the ice crystal's properties. This chapter provides an overview of microanalysis techniques employed in either a multimodal or in situ manner, which shed light on the atmospheric heterogeneous ice nucleation process and how these techniques are applied to explore the complex morphologies of ice crystals. The first section introduces the various atmospheric ice nucleation pathways, provides a brief outline of the underlying nucleation theory demonstrating that nucleation proceeds on the nanoscale, and describes the different ice crystal habits of growth. Section two provides an overview of the microanalysis techniques and experiments to study INPs or ice-nucleating substrates including multimodal instrument approaches followed by in situ ice nucleation studies. Examples of techniques include Raman, atomic force, electron, and X-ray microscopy with discussion of the techniques’ unique capabilities to examine the physical and chemical properties of the ice-nucleating substrate. The third section presents electron microscopy studies of ice crystals during growth and sublimation displaying the morphological complexities of ice crystals. Lastly, section four discusses typical experimental requirements including sample sizes, radiation effects, and the role of standard INPs.

Rich Briggs1, Robert C. Witter2, Jeffrey T. Freymueller3, Peter M. Powers1, Peter J. Haeussler2, Stephanie L. Ross4, Tina Dura5, Simon E. Engelhart6, Richard D. Koehler7, Hong Kie Thio81 U.S. Geological Survey, Geological Hazards Science Center, Golden, CO, USA2 U.S. Geological Survey, Alaska Science Center, Anchorage, AK, USA3 Department of Earth and Environmental Sciences, Michigan State University, East Lansing, MI, USA4 Pacific Coastal and Marine Science Center, US Geological Survey, Moffett Field, CA, USA5Department of Geosciences, Virginia Tech, Blacksburg, VA, USA6Department of Geography, Durham University, Durham, UK7Nevada Bureau of Mines and Geology, University of Nevada, Reno, Reno, NV, USA8 AECOM, Los Angeles, CA, USACorresponding author: Rich Briggs ([email protected])Key Points:We present earthquake recurrence estimates from geologic and geodetic data for the Alaska-Aleutian subduction zoneRecurrence estimates provide constraints for seismic hazard modelsThe recurrence estimates indicate that the rates of Mw≥ 8 ruptures are higher than previously inferred west of Kodiak Island

The Himalayan orogen exposes a range of metamorphosed assemblages, from low-grade Indian shelf sediments of the Tethyan Formation to eclogite and ultra-high pressure rocks documented near the suture zone between the Indian craton and Asian subcontinent. Barrovian-grade pelites and mafic protoliths are exposed in the Himalayan core and include the Greater Himalayan Crystallines and Lesser Himalayan Formations. These units are separated by the Main Central Thrust (MCT). This fault system accommodated a significant amount of India-Asia convergence and is the focus of several models that explore ideas about the development of the range and collisional belts in general. These units provide critical information regarding the mechanisms of heat transfer within collisional belts. Garnets collected across the MCT record their growth history through changes in chemistry. These chemical changes can be extracted and modeled using a variety of thermodynamic approaches. This paper reviews the geological framework of the Himalayas with a focus on the protolith of its metamorphosed assemblages. It describes and applies particular thermobarometric techniques to decipher the metamorphic history of several garnet-bearing rocks collected across the MCT in central Nepal. Comparisons are made between the results of previously-reported conventional rim P-T conditions and P-T paths extracted using the Gibb’s method to isopleth thermobarometry and high-resolution P-T path modeling using the same data and assemblages. Predictions of the paths on garnet zoning are also presented for the high-resolution P-T path modeling and Gibb’s method using the program TheriaG. Although the approaches yield different absolute conditions and P-T path shapes, all are consistent with the development of the MCT shear zone due to imbrication of distinct rock packages. Greater Himalayan Crystalline garnets experienced higher-grade conditions that make extracting its P-T conditions and paths a challenge. Lesser Himalayan garnets appear to behave as closed systems and are ideally suited for thermodynamic approaches.

The latest work on the main African rivers on the Atlantic coast has made it possible to subdivide the multi-year streamflow records into several homogeneous phases. The year 1970 seems to mark both for West and Central Africa the major hydroclimatic event of the 20th century, heralding its main period of deficit flow. For the first time, this article presents a comparative study of the hydro-rainfall records of five drainage systems (those of the Congo River and its main tributaries Lualaba, Kasai, Sangha, Oubangui) based on field data, obtained on both the left and right banks of the Congo River. A reconstitution of the Cuvette Centrale regime is proposed. The 1970 hydro-rainfall disruption is common in most tributaries of the Congo River basin, with significant reductions in flows depending on various factors (geographical location, vegetation cover, surface conditions and land use, etc.). The Oubangui is the most fragile northern tributary that continues to suffer from flow deficits, with an increase in the duration and intensity of its low flows. Since 1995, flows of the Congo River at its main station in Brazzaville/Kinshasa seem to have returned to the interannual average since 1903. However, from the same year onwards, an increase in seasonal variability and a decrease in spring flood flows can also be observed for its bimodal tributaries. This article explains some of the hydrological paradoxes specific to this basin, which illustrate the complexity of its hydrological functioning. Finally, it shows that the period of excess flow in the 1960s is the major hydrological anomaly of the Congo River over a continuous 116-year history. For the whole basin, hydrological variations are attenuated compared to those of precipitation. Finally, the hydrometric regimes reconstructed by spatial altimetry and modelling are compared with those from in situ data.

Conceptual hydrological models imply a simplification of the complexity of the hydrological system; however, it lacks the flexibility in reproducing a wide range of the catchment responses. Usually, a trade-off is done to sacrifice the accuracy of a specific aspect of the system behavior in favor of the accuracy of other aspects. This study evaluates the benefit of using a modular approach, “The fuzzy committee model” of building specialized models (same structure associated with different parameter realization) to reproduce specific responses (high and low flow response) of the catchment. The study also assesses the applicability of using predicted runoff from both specialized models with certain weights based on a fuzzy membership function to form a fuzzy committee model. This research continues to explore the fuzzy committee models first presented by [Solomatine, 2006] and further developed by [Fenicia et al., 2007; Kayastha et al., 2013]. In this paper, weighting schemes with power parameter values are investigated. A thorough study is conducted on the relation between the fuzzy committee variables (the membership functions and the weighting schemes), and their effect on the model performance. Furthermore, the Fuzzy committee concept is applied on a conceptual distributed model with two cases, the first with lumped catchment parameters and the latter with distributed parameters. A comparison between different combinations of the fuzzy committee variables showed the superiority of all Fuzzy Committee models over single models. Fuzzy committee of distributed models performed well, especially in capturing the highest peak in the calibration data set; however, it needs further study of the effect of model parameterization on the model performance and uncertainty.

A variety of smoke model frameworks are used to simulate smoke for research and forecast applications. Here, a comprehensive summary is provided which covers the many different smoke models that are available, while simultaneously highlighting some of the strengths and weaknesses of each model, along with the uncertainties surrounding each of these frameworks. This review also provides an in-depth discussion on coupled wildfire-atmosphere models, which is a relatively newer smoke modeling tool not previously discussed in other review papers. Key processes related to smoke transport and dispersion, such as the wildfire plume rise, are also discussed in length. This review wraps up with a discussion of future smoke modeling needs and potential new research directions for smoke transport and dispersion models.

Extreme runoff modeling is hindered by the lack of sufficient and relevant ground information and the low reliability of physically-based models. The authors propose to combine precipitation Remote Sensing (RS) products, Machine Learning (ML) modeling, and hydrometeorological knowledge to improve extreme runoff modeling. The approach applied to improve the representation of precipitation is the object-based Connected Component Analysis (CCA), a method that enables classifying and associating precipitation with extreme runoff events. Random Forest (RF) is employed as a ML model. We used 2.5 years of nearly-real-time hourly RS precipitation from the PERSIANN-CCS and IMERG-early run databases (spatial resolutions of 0.04 o and 0.1 o , respectively), and runoff at the outlet of a 3391 km 2-basin located in the tropical Andes of Ecuador. The developed models show the ability to simulate extreme runoff for the cases of long-duration precipitation events regardless of the spatial extent, obtaining Nash-Sutcliffe efficiencies (NSE) above 0.72. On the contrary, we found an unacceptable model performance for a combination of short-duration and spatially-extensive precipitation events. The strengths/weaknesses of the developed ML models are attributed to the ability/difficulty to represents complex precipitation-runoff responses.

Running Head: Rock uplift west of the Fairweather fault, AlaskaR.C. Witter1, H.M. Kelsey2, R.O. Lease1, A.M. Bender1, K.M. Scharer3, and P.J. Haeussler1, and D.S. Brothers41U.S. Geological Survey Alaska Science Center, Anchorage, AK, USA2Department of Geology, Cal Poly Humboldt, Arcata, CA, USA3U.S. Geological Survey Earthquake Science Center, Pasadena, CA, USA4U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, CA, USAAbstract [286/300 words]Contraction along the Yakutat-(Pacific)-North America plate boundary drives extreme rock uplift along Earth’s fastest slipping (≥49 mm/yr) ocean-continent transform fault, the Fairweather fault. Between Icy Point and Lituya Bay, the near-vertical Fairweather fault focuses rock uplift and rapid right-lateral slip by accommodating both vertical and fault-parallel strain during ruptures with a substantial vertical-slip component and separate, predominantly strike-slip events. We use 1.0 m resolution digital elevation models and offshore seismic reflection profiles to map active faults, uplifted marine and fluvial terraces, and document past reverse fault earthquakes with maximum 3–5 m of coseismic uplift per event. Radiocarbon and luminescence dating provide timing to estimate 4.6–9.0 mm/yr Holocene rock uplift rates, which match 5–10 km/Myr Quaternary exhumation rates estimated from thermochronometry. These unusually high uplift rates result from plate-boundary strain that is partitioned onto reverse faults that form, together with the steeply dipping Fairweather fault, a 10-km-wide, asymmetric, positive flower structure along a 20°, ~30-km-long restraining double bend in the Fairweather fault. The principal reverse fault in the flower structure is the offshore, blind Icy Point-Lituya Bay fault, which ruptures no more than every 460–1040 years evidenced by uplifted Holocene marine shorelines. Evaluated over a range of dips, the uplift on this reverse fault implies maximum 3.1–10 m dip slip per event and estimated earthquake magnitudes of Mw 7.0–7.5. Our model implies oblique slip on the Fairweather fault at seismogenic depths with and without co-rupture on the reverse fault. Oblique slip on the Fairweather fault is evident where it vertically offsets fluvial and marine terraces by >25 m, strikes >20° west of plate boundary motion, juxtaposes near-surface rocks of different strength, and where the Yakutat block collides obliquely into North America.

We present the crustal fault model for Alaska, based on geologic observations, as a primary input for the 2023 revision of the U.S. Geological Survey National Seismic Hazard Model (NSHM). We update the 2013 Alaska Quaternary fault and fold database (Koehler, 2013) with subsequent findings to produce a simplified model of 105 fault sections and four fault zone polygons with basic geologic parameters including slip sense and rate. Significant updates from prior maps include: 1) A slip rate of ~53 mm/yr on the Queen Charlotte Fault system indicating it accommodates all of the plate boundary motion. 2) Quantified long-term slip rates on megathrust splay faults in the southern Prince William Sound region and near Kodiak Island. 3) Improved details of structures in the Chugach-St. Elias orogen. 4) Revised characterization of Castle Mountain Fault from right-lateral slip to a predominantly reverse fault. 5) Improved Interior Alaska tectonic models that clarify relationships between the Denali Fault, Totschunda Fault, and thrust faults on both sides of the Alaska Range. 6) Identified large earthquake sources in the eastern Brooks Range. 7) Omission of the Chatham Strait section of the Denali Fault. We also describe the growing body of Alaskan lacustrine paleoseismic records of strong shaking, which may offer a test of ground motion recurrence predicted by the 2023 NSHM for crustal, megathrust, and intraslab events. The fault model underscores that the collision of the Yakutat microplate is the dominant driver of active crustal faulting in most of Alaska.

Intraslab earthquakes do not produce primary paleoseismic evidence at the Earth’s surface, making efforts to develop an event chronology challenging. However, the strong ground motion from intraslab events may initiate gravity-driven turbidity flows in subaqueous basins; the resulting deposits (turbidites) can provide a paleoseismic proxy if the conditions that initiate these flows are known. To better constrain the initiating conditions, we use two recent intraslab earthquakes in southcentral Alaska, the Mw 7.1 November 30, 2018, Anchorage and the Mw 7.1 January 24, 2016, Iniskin earthquakes, as calibration events. Through a multi-lake investigation spanning a range of shaking intensities and based on a combined geological and geophysical dataset, we document the occurrence, or absence, of earthquake-generated turbidity flows from these two earthquakes. The 2018 and 2016 earthquakes are recorded by centimeter-scale turbidites that can be differentiated from climatically generated deposits, as well as other seismic sources (i.e., the 1964 Alaska megathrust earthquake) based on deposit thickness, sedimentological properties, and deposit age. We show that a Modified Mercalli Intensity (MMI) of ~V-V1/2 is the minimum shaking intensity required to generate localized sediment remobilization from deltaic slopes, and a MMI of ~V1/2 is required to produce a deposit of sufficient thickness that a seismic origin can be confidently assigned. Deltaic slopes are the major source of remobilized sediment that record the 2018 and 2016 events, however sediment from non-tributary sourced basin slopes may become remobilized in steep-sloped, high sedimentation areas, and under elevated shaking intensity. The documentation of seismically generated deposits in quick succession (~2 years) with diagnostic features that can be assigned to the seismic source highlights the utility of using recent earthquakes as calibration events to investigate the subaqueous response to strong ground motion. 

Finding optimum balances between conflicting interests in multipurpose reservoirs often represents an important challenge for decision makers. This study assesses the use of different computational tools to obtain optimal reservoir operations applied to the Hatillo dam in the Dominican Republic. A multiobjective optimization approach is used, in which non-dominated sorting genetic algorithm II (NSGAII) and multi-objective evolutionary algorithm based on decomposition (MOEA/D) optimizers are applied to models that simulate reservoir operations. Three different Machine Learning (ML) models, namely, the multilayer perceptron (MLP), the radial basis network (RBN) and the linear function (LF), are employed to learn the current operation of the system. Subsequently, a general model is proposed to simulate daily reservoir operations (2009-2019), integrating water balances, physical constraints of the dam components and the ML models, the latter defining daily controlled discharges. In the optimization process, the ML parameters are the decision variables, while the objectives evaluated are irrigation, hydropower generation and flood control. The results are compared with the actual operation of the reservoir. Three dimensional Pareto fronts are obtained, from which, the wide variety of operations can be evidenced. The flood control objective was found to have a wide room for improvement over the current operation of the reservoir, and several of the solutions found improve the current operation for the three proposed objectives. The MLP models tend to generate the best results for this case study and the NSGAII optimizer generates the best optimization results.