A document by Matthew Kenneth Brown. Click on the document to view its contents.

The diurnal cycle of precipitation over the Central Himalaya is governed by a complex interaction between the diurnal cycle of tropical convection and local orographic flow. Understanding this interaction is crucial for model evaluation, where the simulation of such processes is highly sensitive to model resolution and choice of parameterisation schemes. In this study, the mean diurnal cycle is computed using GPM-IMERG data and is shown to be bimodal, with one peak in the late afternoon (1700 LT) and a stronger one in the early morning (0200 LT). This structure is an artefact of compositing, as individual days are typically associated with single peaks. The late afternoon ‘convective’ peak is shown to be linked to the diurnal cycle of tropical convection, whereas the early morning ‘katabatic’ peak is shown to be triggered by nocturnal downslope flow converging with the background monsoon circulation. As such, the katabatic peak is strongly favoured by an active monsoon trough, which provides greater southeasterly moisture flux to the foothills, resulting in increased low-level moisture flux convergence upon interaction with the katabatic northerlies. In contrast, when the trough is less active, precipitation is brought to the region by mesoscale convective systems, ranging in scale from tens to thousands of kilometres, resulting in convective peaks. We hypothesise that these peaks may be enhanced by anabatic flow. It is shown that the BSISO does not play a significant role in modulating either the timing or amplitude of the diurnal cycle; however, low-pressure systems do: either by intensifying the trough (and hence the katabatic peak), or, when further north, by providing deep convection (hence supporting the convective peak). Reanalyses and a 17-km model with parameterised convection capture both peaks, but overestimate the magnitude of the convective peak and underestimate the magnitude of the katabatic peak.

Here we use a 3-D climate system model to study the habitability of Earth-like planets orbiting in circumbinary systems. A circumbinary system is one where a planet orbits around two stars simultaneously, resulting in large and rapid changes to both the stellar energy distribution and the total stellar energy received by the planet. We find that Earth-like planets, having abundant surface liquid water, are generally effective at buffering against these time-dependent changes in the stellar irradiation due to the high thermal inertia of oceans compared with the relatively short periods of circumbinary-driven variations in the received stellar flux. Ocean surface temperatures exhibit little to no variation in time, however land surfaces can experience modest changes in temperature, thus exhibiting an additional mode of climate variability driven by the circumbinary variations. Still, meaningful oscillations in surface temperatures are only found for circumbinary system architectures featuring the largest physically possible amplitudes in the stellar flux variation. In the most extreme cases, an Earth-like planet could experience circumbinary-driven variations in the global mean land surface temperature of up to ~5 K, and variations of local daytime maximum temperatures of up to ~12 K, on monthly timescales. Still, habitable planets in circumbinary systems are remarkably resilient against circumbinary driven climate variations.

This paper describes a technique for identifying hydrometeor particle types using airborne HIAPER Cloud Radar (HCR) and High Spectral Resolution Lidar (HSRL) observations. HCR operates at a frequency of 94 GHz (3 mm wavelength), while HSRL is an eye-safe lidar system operating at a wavelength of 532 nm. Both instruments are deployed on the NSF-NCAR HIAPER aircraft. HCR is designed to fly in an underwing pod and HSRL is situated in the cabin. The HCR and HSRL data used in this study were collected during the Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES). Comprehensive observations of the vertical distributions of liquid and mixed-phase clouds were obtained using in-situ probes on the aircraft and remote sensing instruments. Hydrometeor particle types were retrieved from HCR, HSRL, and temperature fields with a newly-developed fuzzy logic particle identification (PID) algorithm. The PID results were validated with in-situ measurements collected onboard the HIAPER aircraft by a 2D-Stereo (2D-S) cloud probe. Particle phases derived from the PID results compare well with those obtained from the 2D-S observations and agree in over 70 % of cases. Size distributions are also consistent between the two methods of observation. Knowledge of the particle type distribution gained from the PID results can be used to constrain microphysical parameterization and improve the representation of cloud radiation effects in weather and climate models.

The sea surface salinity (SSS) maximum of the South Indian Ocean (the SISSS-max) is a high-salinity feature centered at 30°S, 90°E, near the center of the South Indian subtropical gyre. It is located poleward of a region of strong evaporation and weak precipitation. Using several different satellite and in situ datasets, we track changes in this feature since the early 2000’s. The centroid of the SISSS-max moves seasonally north and south, furthest north in late winter and farthest south in late summer. Interannually, the SISSS-max has moved on a northeast-southwest path about 1500 km in length. The size and maximum SSS of the feature vary in tandem with this motion. It gets larger (smaller) and saltier (fresher) as it moves to the northeast (southwest) closer to (further from) the area of strongest surface freshwater flux. The area of the SISSS-max almost doubles from its smallest to largest extent. It was maximum in area in 2006, decreased steadily until it reached a minimum in 2013, and then increased again. The seasonal variability of the SISSS-max is controlled by the changes that occur on its poleward, or southern, side, whereas intereannual variability is controlled by changes on its equatorward side. The variations in the SISSS-max are a complex dance between changes in evaporation, precipitation, wind forcing, gyre-scale ocean circulation and downward Ekman pumping. Its motion correlated with SSS changes throughout the South Indian Ocean and is a sensitive indicator of changes in the basin’s subtropical circulation.

The radiation belts of the Earth, filled with energetic electrons, comprise complex and dynamic systems that pose a significant threat to a variety of satellite systems. While various models of the relativistic electron flux have been developed for geostationary orbit (GEO), the behaviour of the medium energy (120-600 keV) electrons below GEO remains poorly quantified. In this paper we present a Medium Energy electRon flux In Earth’s outer radiatioN belt (MERLIN) model based on the Light Gradient Boosting (LightGBM) machine learning algorithm. The MERLIN model takes as input the satellite position, a combination of geomagnetic indices and solar wind parameters including the time history of velocity, and does not use persistence. MERLIN is trained and validated on $>$15 years of the GPS electron flux data, and tested on more than $1.5$ years of measurements. 10-fold cross validation (CV) yields that the model predicts the MEO radiation environment well, both in terms of dynamics and amplitudes of flux. Evaluation on the test set yields high correlation between the predicted and observed electron flux (0.8) and low values of absolute error. The MERLIN model can have wide Space Weather applications, providing information for the scientific community in the form of radiation belts reconstructions, as well as industry for satellite mission design, nowcast of the MEO environment and surface charging analysis.

In winter 2013, a sea ice breakout in the Beaufort Sea produced extensive fracturing and contributed to record regional ice export. Rheinlænder et al. (2022) simulated this event using the neXtSIM sea ice model, reproducing a realistic progression of lead opening and ice drift following the track of an anticyclone. In their study, Rheinlænder et al. (2022) highlighted strong winds and thin ice as key factors for breakouts. We draw on observational records to provide additional context for the driving mechanisms of breakout events. We show that wind direction, rather than speed, was the primary control on patterns of lead opening and breakout timing in 2013. Records of similar events over previous decades demonstrate that breakouts are common under anticyclonic forcing, including during years when the ice was thicker. These additional events can be used to further validate models such as neXtSIM and improve predictive capabilities for future breakouts.

Recent studies have demonstrated that the difference in sea surface temperature anomalies (SSTAs) between the tropical Atlantic main development region (MDR) and the tropical Pacific (Niño 3) modulates Atlantic tropical cyclone activity. This study further explores the seasonality of Pacific and Atlantic contributions to Atlantic hurricane activity. Our analysis shows that while MDR and Niño 3 SSTAs are equally important for late-season (September-November) activity, early-season (June-August) activity is largely modulated by MDR SSTAs. This reflects the increased (reduced) variance of MDR (Niño 3) SSTAs in the early-season due to their phase locking to the seasonal cycle. Further analysis yields skillful forecasts using an MDR-Niño 3 interbasin index derived from hindcasts of the North American Multi-Model Ensemble with May initial conditions. However, the prediction skill for MDR SSTAs is lower than that of Niño 3 SSTAs, suggesting that increasing the prediction skill for MDR SSTAs is key to improving seasonal outlooks.

Feedback control algorithms, an important tool in climate intervention strategy design, are widely used in stratospheric aerosol injection (SAI) simulations but have never been implemented for marine cloud brightening (MCB). Using the Community Earth System Model (CESM2), we present the first simulations of feedback control-regulated MCB. Our controller, which regulates global mean temperature (T0) by varying the area of MCB coverage over time, successfully maintains the desired T0 of 1.5°C above the preindustrial in the SSP2-4.5 global warming scenario comparably to a contemporary SAI controller. After 35 years of intervention, the surface temperature response when MCB has been gradually ramped up over time in this way is similar to a constant intervention with similar global mean temperature (including strong regional heterogeneity), but system memory may cause differences in Arctic sea ice and the Atlantic Meridional Overturning Circulation (AMOC).

In principle, a goal of any regional seismic network (RSN) is simple - detect and review seismicity in the network’s region of interest. Vigorous aftershock sequences however present a unique challenge to an RSN’s mission in that they can overwhelm automated real-time and analyst-driven post-processing systems. This inundation with seismicity can the lead to earthquake catalogs that are incomplete and erroneous in the area around the aftershock sequence. In response to this challenge, this abstract explores integrating machine learning as a tool to expedite the University of Utah Seismogram Station’s (UUSS)’s response to the September, 2017 Soda Springs event in southeast Idaho. In the months following the event the UUSS was able to locate over 1000 aftershocks and was catalog complete to approximately 2.5 M_L. Owing to the fact that a temporary deployment of 6 six-channel and 2 strong-motion instruments were deployed to the area shortly after the event, it is anticipated that many more high-quality locations can be obtained without resorting to template matching. Therefore, it is our goal to attempt to recover the existing UUSS catalog with machine learning enabled workflows that can produce analyst-grade picks for location and subsequent magnitude estimation. Should this be successful then the anticipated consequence is that analysts can quickly screen and approve more events and by extension lower the network’s magnitude completeness during the aftershock sequence.

Mars is the first extraterrestrial planet with seismometers (SEIS) deployed directly on its surface in the framework of the InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) mission. The lack of strong Marsquakes, however, strengthens the need of seismic noise studies to additionally constrain the Martian structure. Seismic noise autocorrelations of single-station recordings permit the determination of the zero-offset reflection response underneath SEIS. We present a new autocorrelation study which employs state-of-the-art approaches to determine a robust reflection response by avoiding bias from aseismic signals which are recorded together with seismic waves due to unfavorable deployment and environmental conditions. Data selection and segmentation is performed in a data-adaptive manner which takes the data root-mean-square amplitude variability into account. We further use the amplitude-unbiased phase cross-correlation and work in the 1.2-8.9 Hz frequency band. The main target are crustal scale reflections, their robustness and convergence. The strongest signal appears at 10.6 s, and, if interpreted as P-wave reflection, would correspond to a discontinuity at about 24 km depth. This signal is a likely candidate for a reflection from the base of the Martian crust due to its strength, polarity, and stability. Additionally we identify, among the stable signals, a signal at about 6.85 s that can be interpreted as a P-wave reflection from the mid-crust at about 9.5 km depth.

Given the role played by the historical and extensive coverage of sea ice concentration (SIC) observations in reconstructing the long-term variability of Antarctic sea ice, and the limited attention given to model-dependent parameters in current sea ice data assimilation studies, this study focuses on enhancing the performance of the Data Assimilation System for the Southern Ocean (DASSO) in assimilating SIC through optimizing the localization and observation error estimate, and two assimilation experiments were conducted from 1979 to 2018. By comparing the results with the sea ice extent of the Southern Ocean and the sea ice thickness in the Weddell Sea, it becomes evident that the experiment with optimizations outperforms that without optimizations due to achieving more reasonable error estimates. Investigating uncertainties of the SIV anomaly modeling reveals the nonnegligible role played by the sea ice-ocean interaction during the SIC assimilation, implying the necessity of assimilating more oceanic and sea-ice observations.

Partitioning evapotranspiration (ET) into its primary components, i.e., evaporation (E) and plant transpiration (T), is needed in a range of hydrometeorological applications. Using vegetation index (VI) to obtain spatially resolved T:ET ratio over large areas has emerged as a promising approach in this regard. Here, we assess the effectiveness of this approach in differently managed wheat systems. Results show a weak relation between T:ET and VI in disturbed (i.e., grazed) systems. Flux partitions based on a canonical T:ET vs. VI relation or one derived in a neighboring undisturbed wheat system introduce large errors in disturbed systems, thus underscoring the limits on the transferability of the VI-based ET partitioning approach. The effectiveness of the VI-based approach is found to be related to the strength of correlation between VI and vapor pressure deficit and/or radiation. This correlation metric can help identify settings where the approach is likely to be effective.

The sulfate-rich sandstones of the Burns formation investigated by the Opportunity rover on Meridiani Planum, Mars, are directly underlain by the fine-grained sedimentary rocks of the Grasberg formation. It was recently shown that, except for differing amounts of MgO and SO3, the Burns and Grasberg rocks have nearly identical chemical compositions, suggesting both units are genetically related. Here, quantitative models demonstrate that the chemical composition of the Burns formation can be accurately reproduced by addition of MgO and SO3 to a Grasberg-like precursor, along with small amounts of Ni. Based on this result, a new scenario is proposed for the origin of the Burns formation: (1) deposition of fine-grained airfall deposits with composition similar to the Grasberg rocks; (2) induration of the deposits, resulting in materials that closely resemble the current Grasberg formation in composition and texture; (3) erosion into sand-sized particles, which are then reworked by eolian and fluvial processes to form the bedding features observed in the Burns rocks; (4) infiltration of the deposits by one or more generations of groundwater, resulting in diagenetic alteration that included local element redistribution, dissolution/recrystallization of minerals, cementation, and formation of hematite spherules; (5) evaporation of groundwater at some point during diagenesis enriched the Burns sediments in MgO and SO3, with greater amounts accumulated closer to the surface. This scenario fully accounts for the chemical composition of the Burns sandstones as well as their sedimentary and diagenetic features, while invoking only a known sediment source and sedimentary/diagenetic processes widely observed on Mars.

The location of the Subtropical Front (STF), the boundary between Subtropical and Subantarctic Water in the Southern Ocean is proposed to be controlled by the strength and location of the Southern Hemisphere westerly winds. We use a hydrodynamic hindcast model and recent observations to test if changes in the westerly winds can cause meridional shifts in the STF over interannual to decadal time scales by modulating local Ekman transport. We find that increased, or northward, shifted westerly winds lead to an enhanced northward Ekman transport over large parts of the Southern Ocean, resulting in a northward shift in the STF. Conversely for weaker or southward shifted westerly winds. Regions with strong eddy variability, such as western boundary current systems of the Agulhas and East Australian Current behave differently, as the Sverdrup balance causes an opposite shift. In these regions an increase in westerly winds lead to a southward shift in the STF. A southward shift of STF has been observed between 2004-2019. However, the shift is smaller than the latitudinal shifts in the location of the zero wind stress curl and maximum westerly winds (-0.4° latitude/decade). This discrepancy is due to positive Ekman trends resulting from the intensification of the westerly winds, which oppose the southward migration. Changes in the Ekman transport and the overall southward shift of the STF have also resulted in an observed positive trend in chlorophyll-a concentrations south of the STF, which could have ramifications for the biological pump and carbon uptake in the Southern Ocean.

Isolating significant signals from temporal variations in autotrophic and heterotrophic components of ecosystem respiration (Reco) is required to better quantify the temperature sensitivity of the land carbon cycle processes. Here we present diurnal and seasonal patterns in field and model-based components of respiration and investigate their responses to environmental conditions at a dry eucalypt forest, the Cumberland Plain SuperSite of the Australian Terrestrial Ecosystem Research Network. We conducted measurement campaigns of total CO2 flux from the soil surface (Rsoil), soil microbial respiration (Rmicrobe), root respiration (Rroot), litter respiration (Rlitter), and stem respiration (Rstem) in 2018. In total, six infrared gas analyzers with closed, dynamic auto-chambers and six forced diffusion auto-chambers were used for periodic campaigns. Further, Reco and its components were simulated using the Community Atmosphere-Biosphere Land Exchange model (CABLE), constrained by eddy covariance measurements and chamber measurements of Rsoil. A new version of CABLE was implemented with the Dual Arrhenius Michaelis Menten (DAMM) formulation to assess the importance of substrate availability for simulating Rmicrobe. We found that respiration rates showed similar diurnal patterns among the components, showing diurnal hysteresis between respiration components and temperature. In this dry ecosystem, the respiratory components were more responsive to seasonally increasing temperature in wet than in dry periods, and the responses were dependent on atmospheric relative humidity affecting the litter layer moisture content. The temperature sensitivity was significantly higher in Rstem than in other components. Based on observed fluxes of Rmicrobe in trenched plots and Rsoil in intact soil plots, the mean contribution of Rroot to Rsoil was less than 20 % for the dry seasons, while mean Rstem was two times greater than mean Rsoil suggesting that Rstem should be not overlooked in ecosystem flux estimations. This study highlights that partitioning the respiratory components and accounting for their different temperature-responses will be necessary to reduce uncertainty in modelling carbon-climate feedbacks.

Modelling the planetary heat transport of small bodies in the early Solar System allows us to understand the geological context of meteorite samples. Conductive cooling in planetesimals is controlled by thermal conductivity, heat capacity, and density, which are functions of temperature (T). We investigate if the incorporation of the T-dependence of thermal properties and the introduction of a non-linear term to the heat equation could result in different interpretations of the origin of different classes of meteorites. We have developed a finite difference code to perform numerical models of a conductively cooling planetesimal with T-dependent properties and find that including T-dependence produces considerable differences in thermal history, and in turn the estimated timing and depth of meteorite genesis. We interrogate the effects of varying the input parameters to this model and explore the non-linear T-dependence of conductivity with simple linear functions. Then we apply non-monotonic functions for conductivity, heat capacity and density fitted to published experimental data. For a representative calculation of a 250 km radius pallasite parent body, T-dependent properties delay the onset of core crystallisation and dynamo activity by ~40 Myr, approximately equivalent to increasing the planetary radius by 10 %, and extend core crystallisation by ~3 Myr. This affects the range of planetesimal radii and core sizes for the pallasite parent body that are compatible with paleomagnetic evidence. This approach can also be used to model the T-evolution of other differentiated minor planets and primitive meteorite parent bodies and constrain the formation of associated meteorite samples.

This study quantifies the contribution to Arctic winter surface warming from changes in the tropospheric energy transport (Ftrop) and the efficiency with which Ftrop heats the surface in the RCP8.5 warming scenario of the CESM Large Ensemble. A metric for this efficiency, Etrop, measures the fraction of anomalous Ftrop that is balanced by an anomalous net surface flux (NSF). Drivers of Etrop are identified in synoptic-scale events during which Ftrop is the dominant driver of NSF. Etrop is sensitive to the vertical structure of Ftrop and pre-existing Arctic lower-tropospheric stability (LTS). In RCP8.5, winter mean Ftrop decreases by 9.5 Wm–2, while Etrop increases by 5.7%, likely driven by decreased Arctic LTS, indicating an increased coupling between Ftrop and the surface energy budget. The net impact of decreasing Ftrop and increasing efficiency is a positive 0.7 Wm–2 contribution to winter-season surface heating.