Traditional watershed modeling often overlooks the role of vegetation dynamics. While past studies indicate possible improved hydrologic predictions by increasing the physical realism of vegetation dynamics in process-based models, there has been little quantitative evidence to support similar improvements in water quality predictions. To fill this knowledge-gap, we recently applied a modified Soil and Water Assessment Tool (SWAT) to quantify the extent of improvements that the assimilation of remotely sensed Leaf Area Index (LAI) would convey to streamflow, soil moisture, and nitrate load simulations across a 16,860 km2 agricultural watershed in the midwestern United States. We modified the SWAT source code to directly insert spatially distributed and temporally continuous LAI estimates from Moderate Resolution Imaging Spectroradiometer (MODIS). Compared to a “basic” traditional model with limited spatial information, our LAI assimilation model (i) significantly improved daily streamflow simulations during medium-to-low flow conditions, (ii) provided realistic spatial distributions of growing season soil moisture, and (iii) substantially reproduced the long-term observed variability of daily nitrate loads. Further analysis revealed that assimilation of MODIS LAI data corrected the model’s LAI overestimation tendency, which led to a proportionally increased rootzone soil moisture and decreased plant nitrogen uptake. With these new findings, our study confirms that assimilation of MODIS LAI data in watershed models can effectively improve both hydrology and water quality predictions.

Numerical climate model simulations run at high spatial and temporal resolutions generate massive quantities of data. As our computing capabilities continue to increase, storing all of the data is not sustainable, and thus is it important to develop methods for representing the full datasets by smaller compressed versions. We propose a statistical compression and decompression algorithm based on storing a set of summary statistics as well as a statistical model describing the conditional distribution of the full dataset given the summary statistics. We decompress the data by computing conditional expectations and conditional simulations from the model given the summary statistics. Conditional expectations represent our best estimate of the original data but are subject to oversmoothing in space and time. Conditional simulations introduce realistic small-scale noise so that the decompressed fields are neither too smooth nor too rough compared with the original data. Considerable attention is paid to accurately modeling the original dataset--one year of daily mean temperature data--particularly with regard to the inherent spatial nonstationarity in global fields, and to determining the statistics to be stored, so that the variation in the original data can be closely captured, while allowing for fast decompression and conditional emulation on modest computers.

The evidence of bodies of elemental sulfur (S ) beneath acid crater lakes at the summit of composite active volcanoes has been recognized several decades ago (Oppenheimer and Stevenson, 1989; Christenson and Woods, 1993). But S accumulation was already hypothesized a century ago at Kusatzu Shirane (Japan) based on the observation of sulfur spherules floating on its crater-lake (Ohashi, 1919). Since these pioneering works, other studies have focused on understanding key aspects of molten sulfur bodies, considered a feature unique of volcanic lakes. Instead, it is reasonable to assume that S bodies occur in several volcanic settings because a) several reactions may lead to S deposition from S-bearing gases, and b) crater-lakes, surface expressions of hydrothermal systems, are transient features. The scrubbing of several magmatic gases, some of which critical for volcano monitoring, has been attributed to ground/surface waters (Symonds et al. 2001). Nevertheless, gas scrubbing could reflect viscosity variations of impure S within hydrothermal systems. Industrial experiments indicated that impurities (organics, H2S, ammonia, HCl, HF, HBr, HI) hinder S polymerization at T ≥ 160ºC, allowing viscosity to remain low for a long time depending on the maximum T achieved and heating rates (Bacon and Fanelli, 1943). However, a prolonged heating destroys the viscosity-modifying substances (e.g. H2Sx formed by reactions with organics, H2S) and dramatic S viscosity increases occur after a certain number of heating and cooling cycles. A prolonged boiling of S with organics was observed to release H2S, following H2Sx disruption. Some gases (e.g. SO2) do not affect S viscosity. In volcanic environments, non-reactive species (e.g. SO2, CO2) could, therefore, escape under S low viscosity regimes. Also, halogens absence in gas emissions could be caused by their participation in reactions within S-layers causing its viscosity to remain low. More data are needed to validate the hypothesis stated above. References Bacon RF, Fanelli R, J Am Chem Soc 65, 639-648 (1943). Christenson, BW, Wood CP, Bull Volcan 55, 547-565 (1993). Ohashi R, J. Akita Min. Coll 1, 1-10 (1919) Oppenheimer C, Stevenson D, Nature 342, 790-793 (1989) Symonds RB, Gerlach TM, Reed MH, J. Volc Geot Res 108, 303-341 (2001)

Earth and environmental models are relied upon to investigate system responses that cannot otherwise be examined. In simulating physical processes, models have adjustable parameters which may, or may not, have a physical meaning. Determining the values to assign to these model parameters is an enduring challenge for earth and environmental modellers. Selecting different error metrics by which the models results are compared to observations will lead to different sets of calibrated model parameters, and thus different model results. Furthermore, models may exhibit ‘equifinal’ behaviour, where multiple combinations of model parameters lead to equally acceptable model performance against observations. These decisions in model calibration introduce uncertainty that must be considered when model results are used to inform environmental decision-making. This presentation focusses on the uncertainties that derive from the calibration of a four parameter lumped catchment hydrological model (GR4J). The GR models contain an inbuilt automatic calibration algorithm that can satisfactorily calibrate against four error metrics in only a few seconds. However, a single, deterministic model result does not provide information on parameter uncertainty. Furthermore, a modeller interested in extreme events, such as droughts, may wish to calibrate against more low flows specific error metrics. In a comprehensive assessment, the GR4J model has been run with 500,000 Latin Hypercube Sampled parameter sets across 303 catchments in the United Kingdom. These parameter sets have been assessed against six error metrics, including two drought specific metrics. This presentation compares the two approaches, and demonstrates that the inbuilt automatic calibration can outperform the Latin Hypercube experiment approach in single metric assessed performance. However, it is also shown that there are many merits of the more comprehensive assessment, which allows for probabilistic model results, multi-objective optimisation, and better tailoring to calibrate the model for specific applications such as drought event characterisation. Modellers and decision-makers may be constrained in their choice of calibration method, so it is important that they recognise the strengths and limitations of their chosen approach.

Windblown sand produces distinctive bedforms at scales ranging from normal sand ripples to large reversing sand dunes. We explore how aeolian bedforms evolve at both extremes of this range. An investigation of the transition from sand ripples (<1 cm height) to granule-coated megaripples (25 cm height) is underway at Great Sand Dunes National Park and Preserve (GSDNPP) in central Colorado. Sand-to-megaripple transitions at GSDNPP were documented in May and Sept of 2019 using stereophotogrammetry that produced digital terrain models that resolved granule (1-2 mm) particles as well as some sand grains; these data show the spatial distribution of particles across sand ripples whose crests merge directly into crests of megaripples. To date we have not observed that sand ripples are a necessary prerequisite for the initiation and growth of megaripples; the spatial density of granule particles appears to influence the evolution of megaripples. Reversing sand dunes are being monitored using differential navigation satellite system data at GSDNPP (up to 10 m height) and at Bruneau Dunes State Park (BDSP) in central Idaho (individual dunes >100 m height). Surveys of the crests of reversing dunes at GSDNPP reveal a northeastward migration of individual dunes along the southern margin of the main dune mass, consistent with dominant local winds, yet the symmetric reversing dune profile is maintained during the translation. Surveys of the crests of large reversing dunes at BDSP reveal variable adjustments of the crests that may be affected by wind flow altered by the bulk of the dunes themselves, sheltering the southern end of the dunes from one of the seasonal bimodal winds. Results to date indicate that the deformable shape of aeolian bedforms affect wind flow at all spatial scales, influencing the evolution of the features over diverse time scales.

The spatial and time characterisation of trapped charged particle trajectories in magnetospheres has been extensively studied using dipole magnetic field structures. Such studies have allowed the calculation of spatial quantities such as equatorial loss cone size as a function of radial distance, the location of the mirror points along particular field lines (’L shells’) as a function of the particle’s equatorial pitch angle, and time quantities such as the bounce period and drift period as a function of the radial distance and the particle’s pitch angle at the equator. In this study, we present analogous calculations for the ‘disc-like’ field structure associated with the giant rotation-dominated magnetosphere of Jupiter as described by the UCL/Achilleos-Guio-Arridge (UCL/AGA) magnetodisc model. We discuss the effect of the magnetodisc field on various particle parameters, and make a comparison with the analogous motion in a dipole field.

The outer heliosphere is an interesting region characterized by the interaction between the solar wind and the interstellar neutral atoms. Having accomplished the mission to Pluto in 2015 and currently on the way to the Kuiper Belt, the New Horizons spacecraft is following the footsteps of the two Voyager spacecraft that previously explored this region lying roughly beyond 30 AU from the Sun. We model the three-dimensional, time-dependent solar wind plasma flow to the outer heliosphere using our own software Multi-Scale Fluid-Kinetic Simulation Suite (MS-FLUKSS), which, in addition to the thermal solar wind plasma, takes into account charge exchange of the solar wind protons with interstellar neutral atoms and treats nonthermal ions (i.e., pickup ions) born during this process as a separate fluid. Additionally, MS-FLUKSS allows us to model turbulence generated by pickup ions. We use MS-FLUKSS to investigate the evolution of plasma and turbulent fluctuations along the trajectory of the New Horizons spacecraft using plasma and turbulence parameters from OMNI data as time-dependent boundary conditions at 1 AU for the Reynolds-averaged MHD equations. We compare the model with in situ plasma observations by New Horizons, Voyager 2, and Ulysses. We also compare the model pickup proton parameters with those derived from the Ulysses-SWICS data.

Abnormally heavy precipitation events can lead to numerous hazards, including flooding, landslides, and avalanches. Their developments require a sufficient supply of moisture and some physical mechanism to produce condensation. Atmospheric rivers (ARs) defined as long and narrow corridors of strong horizontal moisture transport can provide such necessary conditions. The presence and strength of ARs are often described using the integrated water vapor (IWV) and the integrated vapor transport (IVT). However, the associated precipitation is not directly correlated with these two variables. It is the net convergence of moisture that determines the intensity of precipitation. The purpose of this study is to illustrate, in the context of AR analysis, how the converged vapor should be distributed between condensation and air moistening. A simple algorithm is proposed for estimating the heavy precipitation attributable to the IVT convergence. Bearing a strong resemblance to the Kuo-Anthes parameterization scheme for cumulus convection, the proposed algorithm calculates the large-scale primary condensation rate (PCR) as a proportion of the IVT convergence, with a reduction to account for the general moistening in the atmosphere. The amount of reduction is determined by the column relative humidity (CRH), which is defined as the ratio of IWV to its saturation counterpart. It is found that the PCR in an air column with CRH < 0.60 is negligibly small. Based on a one-year dataset from the Canadian global numerical weather prediction (NWP) model, the best cut-off value of CRH for the algorithm is 0.66. It is demonstrated that this diagnosable PCR compares well to the forecast precipitation rate given by the NWP model. Case studies are conducted to illustrate the usefulness of CRH and PCR as two complements to standard AR analysis and impact-based storm classification.

According to the 2020 FEMA Fact Sheet (FEMA, 2020), Puerto Rico and Virgin Islands are located in a high risk region for earthquake damage. In the last year (05-jul-2019 to 05-jul 2020) the Puerto Rico Seismic Network (PRSN) recorded 136 earthquakes with magnitudes greater than 4.0 and two events had magnitudes greater than or equal to 6.0. The last update of the seismic hazard maps for Puerto Rico and the US Virgin Islands was performed in 2003. According to Mueller et al. (2010), the Bunce fault, the Muertos Trough and related fault structures were not included in the hazard map. The Great Southern Puerto Rico fault, was considered largely quiescent, but Piety et al. (2008) through paleoseismic studies, evidenced activity in this one. Otherwise, offshore faults in southern Puerto Rico were not considered, because their rates of activity were poorly known and assumed to be most likely small. However, starting in December 2019 the Southwestern Puerto Rico (SWPR) Seismic Sequence has been active and continues to be active in these southern offshore faults. According to the StEER technical report (Miranda et al., 2020), the events that occurred between December 2019 and January 2020 caused damage to approximately 10,000 structures and more than 8,000 people were displaced. Based on these facts, and considering that previously unknown tectonic fault structures have been revealed by the SWPR Seismic Sequence (Lopez et al., 2020b), a reevaluation of the seismic threat to Puerto Rico is required. This should include the seismic activity that, according to the PRSN catalog, consists of more than 50,000 events since 2002 to date. This new seismic hazard evaluation will include multiple earthquakes with magnitudes greater than M 5 which were not part of the catalog in 2001. The purpose of this study is generating a new Ground Motion Prediction Equation (GMPE) that incorporates the current seismicity for the region, which unlike the local model used in Mueller et al. (2010) the data will be used directly to obtain the ground motion relationships (Motazedian et al., 2005). This new data now permits to obtain a GMPE from a regression analysis. In the first stage of the research, the aim is generating a preliminary GMPE based on crustal seismicity (events less than 25 km deep) which represents more than 60% of the total registered earthquakes in the PRSN catalog.

The research data repository of the Environmental Data Initiative (EDI) is a signatory of the FAIR Data Principles. Building on over 30 years of data curation research and experience in the NSF-funded US Long-Term Ecological Research program (LTER), it provides mature functionalities, well established workflows, and support for ‘long-tail’ environmental data publication. High quality scientific metadata are enforced through automatic checks against community developed rules and the Ecological Metadata Language (EML) standard. Although the EDI repository is far along the continuum of making its data FAIR, representatives from EDI and the LTER Information Management community have recently been developing best practices for the edge cases in environmental data publishing. Here we discuss and seek feedback on how to best handle the publication of these ‘long-tail’ data when extensive additional data are available along with e.g., genomics data, physical specimens, or flux tower data. While these latter data are better handled in other discipline-specific repositories such as NCBI, iDigBio, and AmeriFlux, they are frequently associated with other data collected at the same time and location, or even from the same samples. This is particularly relevant across the LTER Network, where sites represent integrative research projects. Questions we address (and seek community input from) include: How to archive documents and images when they are data, e.g., field notebooks, or time-lapse photographs of plant phenology? How to deal with data from Unmanned Vehicle (e.g., drones and underwater gliders), acoustic data, or model outputs, which may be several terabytes in size? How should processing scripts or modeling code be associated with data? Overall, these best practices address issues of Findability and Accessibility of data as well as greater transparency of the research process.

Underwater bedforms in a flow have been shown to cast free-surface signatures that carry important information about these bedforms thus allowing for a novel non-intrusive methodology for bedform inference through measurement of these signatures (Gakhar et al. 2020, J. Fluid Mech. vol.900, A41). We present a method (Polarimetric Height Sensing or PHS) for spatiotemporally reconstructing the two-dimensional height field of a (water) free surface, thereby allowing for characterization of the free-surface signatures of submerged bedforms. The instrumentation for PHS comprises a small, easily portable polarimetric camera. PHS, which incorporates more than just the intensity of the light as in a regular digital image, works as follows. When light is reflected from the water surface, it acquires a polarization that depends on the polarization state of the incident beam, the indices of refraction of the surface and air, and most importantly the angle and plane of incidence. Given that we already know the refractive indices and the incident light’s polarization, using measurements of the polarization of the reflected light, we can quantify the geometric properties of the water surface. We illustrate the technique via laboratory experiments using imaging of the water in an open-channel recirculating water flume.

Engaging high school students in authentic scientific investigations is essential for increasing scientific literacy. Teachers often resort to using textbooks and in-class laboratory experiences that emphasize facts but leave students feeling disengaged. Additional challenges are often added to trying to teach STEM content effectively to students for whom English is not their first language. A collaborative partnership between the author, a former educator who now is an Education and Outreach Specialist with NASA, and a high school teacher who works with underserved students for whom English is not their native language, was formed in order to offer authentic STEM experiences in a public-school setting. They explored the many resources within The GLOBE Program and the GLOBE Observer app, and decided to use these to build the structure around an elective STEM course for 11th grade students. Students learned how NASA satellite data is being used to better understand Earth’s systems and to gather data to help us monitor our changing climate. They used the GLOBE Observer “tools” (Mosquito Habitat Mapper, Trees, Land Cover) as well as several GLOBE atmosphere protocols (precipitation, air temperature, relative humidity, soil moisture) to monitor ongoing environmental conditions. Students formed investigative teams and worked with NASA scientists and data as they designed and conducted research to explore the impact of environmental conditions on active mosquito seasonality and types of mosquitoes, tree growth, and land cover in their schoolyard. They also communicated regularly with other students who were collecting similar data in different countries around the world to compare and contrast the impact of these environmental variables. The goal is for students to submit their research results to GLOBE’s “International Virtual Science Symposium” and also share their projects at their county-level science fair.

Emergency Action Plan for Flash Flood Due to Dambreak - Case study: Shahrchai Dam, Urmia (Iran) Seyed M. Heidaria, Seyed Jalal Heidarib a Department of Civil Engineering, Sharif University of Technology, Tehran, Iran. (SeyedMHeidari@gmail.com) b Department of Civil Engineering, Betasaze Corporation, Mashhad, Iran. (j.heidari37@gmail.com) Abstract: A large number of dams have been built on the upstream of residential regions. Flash flood from these dams’ failure is a constant threat to the thousands of lives and million-dollar municipal facilities in downstream. Therefore, it is crucial to identify potentially flooded areas and develop an early warning system for downstream cities to mitigate the loss of life and financial damages. We prepared an emergency action plan (EAP) for flash floods in Iran for the first time in this work. Shahrchai Dam was selected as the case study since it is a large dam with a 220 million m2 capacity reservoir and is located close to a large city, Urmia, with 667,000 population and more than 197,000 households. We used HEC-RAS to model dambreak for two scenarios, piping and overtopping. ArcGIS was employed to identify flooded regions in downstream. The escape time was estimated based on the time that first waves reach residential zones. Time was 170 and 140 minutes for the piping and overtopping scenario, respectively. Water depth and water velocity were mapped for each scenario for flooded areas in downstream to identify secure shelters. EAP was developed for residential, commercial, and municipal buildings located in the flooded areas. Nine hospitals, four hotels, six mosques, more than ten municipal buildings, 54 public, and private schools, and five universities are determined within the flooded regions and considered in the EAP. We divided these regions into five categories, with three to five subcategories based on population and building types. For each subcategory, we identified an evacuation plan with detailed guidelines for residents and involved municipal organizations to avoid chaotic behaviors, which usually happens during flash floods. Results from this study are useful for educating people to be prepared for disasters like flash floods. Municipal policymakers can also use the findings to legislate required rules to protect urban areas from future floods and reduce associated fatality and financial costs. Acknowledgment: Authors would like to appreciate Sharif University of Technology and Dr. Fardin Jafarzadeh for their supports.

Gas transport in dominantly microporous rocks such as coal, shale is significantly controlled by Klinkenberg or slippage effect at low reservoir pressures. Pore size fractions of the concerned reservoir rock control the degree of Klingenberg effect. This study tries to assess the differences in Klinkenberg effect in dissimilar coals owing to their difference in pore-size distributions. We report apparent permeabilities of three Gondowana coal samples from the Bokaro, Jharia, and Bansgara coalfields at room temperature and constant isostatic stress (6.2 MPa). The linear plots of apparent permeability versus inverse pore pressure were modelled using the Klinkenberg equation, and non-linear plots by the Ashrafi equation to determine the slippage coefficient and intrinsic permeabilities. Ashrafi model reports lower values of slippage corrected permeability compared to the Klinkenberg model. The slippage coefficient and intrinsic permeability obtained from N2 and CO2 is different for the Bansgara sample. The trends between transport parameters and pore-size parameters were examined. The slippage coefficient decreased with interconnected porosity and total specific pore volume. Intrinsic permeabilities showed an opposite trend to that of the slippage coefficient. The Bansgara sample having larger volumetric proportion of micropores in the pore volume gamut with open ended interconnected pore network resulted in the lowest slippage coefficient and highest intrinsic permeabiliity. Reporting the slippage coefficients and intrinsic permeabilities with corresponding pore size distributions of coal samples from different global basins will lead to statistically significant empirical relationships between pore size parameters and slippage coefficients.

The Black sea is a deep semi-enclosed dilution basin connected with the Mediterranean Sea by shallow and narrow Turkish Straits with hydraulically controlled two-layer water exchange. The simulation of sea level, temperature and salinity change in the Black Sea in 2000-2100 was carried out using a chain of models, which includes models of the Black and Azov Seas, as well as the Kerch Strait, the Turkish Straits (Bosphorus and Dardanelles) and the Marmara Sea models. The air temperature, wind, evaporation and precipitation for period 2000-2100 over the Black Sea and its catchment area was calculated from regional model CNRM-ALADIN (MED-11) modeling data for RCP4.5 and RCP8.5 scenarios. The neural networks were used to obtain components of freshwater budget from regional model simulations, whereas boundary conditions (sea level, temperature and salinity) in the North Aegean Sea were used from CMIP5 model CNRM CM5.1. The calculated trend of the sea level for period 2000-2100 (3.6 mm/y and 4.6 mm/y for RCP4.5 and RCP8.5, respectively) is close to the corresponding trends in the Mediterranean Sea. The steric correction almost compensates sea-level fall due to the decrease of freshwater influx at 85 km3/y and 99 km3/y in 2100 for RCP4.5 and RCP8.5, respectively. Increasing the air temperature over the sea and reducing the inflow of fresh water are the major factors in changes in the surface layer of the Black Sea. In the period 2000-2100, water temperature of the surface layer of the Black Sea will increase by 2.7 oC, the salinity by 1.7 for the scenario RCP4.5, while the corresponding values will increase by 4.1 oC and by 1.75 for the scenario RCP8.5. These changes in the physical characteristics of the Black and Azov Seas can have a significant impact on the ecosystem of these basins, shores and coastal infrastructure.

Lakes have a controversial climate footprint. In fact, they are a sink of CO2 but at the same time they can be an important source of CH4. Indeed, a global synthesis of methane emission data (Bastviken et al., 2011) suggests that freshwater ecosystems - in particular lakes - may be much larger sources of methane than previously thought, questioning current methane budgets and the general role of freshwater ecosystems in the greenhouse gas balance. The main objective of this study is to improve data availability and quality regarding methane emissions from lakes in the Alpine region - a region that presently is heavily under-represented in global data sets - in order to allow a robust assessment of their role in the global greenhouse gas balance. This is of fundamental importance for the assessment of CH4 emissions from regions particularly sensitive to an increasing climatic variability. Aiming at spatial and temporal representativeness of flux measurements, we made use of an innovative mobile eddy covariance system. We installed the instruments on a small boat, and we performed measurements while cruising. Meteorological and bio-physical data got recorded simultaneously to investigate drivers of gas fluxes by means of empirical modelling. Additionally, we made use of classical chamber measurements for validating our approach. In this fashion, we investigated a number of natural and man-made lakes across a transect of two degrees of latitude across the Alps. In fact, the alpine region provides a unique opportunity to assess the role of environmental drivers on GHG emissions over a limited latitudinal range in an altitude-for-time substitution manner. We repeatedly visited target lakes across the ice-free season during the years 2018 and 2019. We demonstrated that our method is valid for capturing methane emissions from different pathways (diffusion but also ebullition and transport through vegetation). We found that most of the lakes are supersaturated and the highest emissions were measured in shallow and eutrophic lakes at low altitude. In conclusion, with this study we were able to develop new insights on the role of freshwater ecosystems in the global methane budget. References: Bastviken D, Tranvik LJ, Downing JA, Crill PM, Enrich‐Prast A (2011). Freshwater methane emissions offset the continental carbon sink. Science 331, 50.

Accurate knowledge of the dependence of anthropogenic atmospheric CO2, the excess over preindustrial, on future emissions is essential to developing approaches to limit climate change. At present, the lifetime of excess CO2, as represented in current carbon cycle models, is uncertain by more than an order of magnitude, 70 to more than 700 years (Schwartz, JGR, 2018). Consequently observation-based top-down analysis provides an important alternative approach. The turnover time of excess CO2 (ratio of stock in the atmosphere and the mixed-layer ocean, which are in near equilibrium, to the net leaving flux into the terrestrial biosphere and deep ocean) is determined as 54 ± 10 years. A simple model for excess CO2, consisting of four compartments with three observationally determined global-mean parameters (deposition velocity of CO2 to the surface ocean, piston velocity describing the rate of exchange of water between the mixed-layer and deep ocean, and the transfer coefficient of CO2 kat from the atmosphere a to the terrestrial biosphere t), and one uncertain adjustable parameter kta, accurately reproduces CO2 mixing ratio over the Anthropocene. This model yields the adjustment time (inverse of fractional removal rate in the absence of emissions) as 65 ± 10 years over the first 100 years, depending on kta, over which time excess CO2 would decrease by 65 to 81%, depending on kta, Figure 1. The reduction of global emissions required to stabilize atmospheric CO2 over this time scale is 50 to 60%.

Warm and dry föhn winds on the lee side of the Antarctic Peninsula (AP) mountain range cause surface melt that can destabilize vulnerable ice shelves. Topographic funneling of these winds through mountain passes and canyons leads to localized wind-induced melt which is difficult to identify without direct measurements. Our Föhn Detection Algorithm (FonDA) identifies the surface Föhn signature using data from twelve Automatic Weather Stations on the AP and uses machine learning to detect föhn in 5km Regional Atmospheric Climate Model 2 (RACMO2.3p2) output and ERA5 reanalysis data. We estimate and compare the climatology and impact of föhns on the AP surface energy budget, surface melt pattern, and melt quantity from 1979-2018. We show that föhn-induced melt is strongest at the eastern base of the AP and the northern portion of the Larsen C ice shelf. We identify previously unknown wind-induced melt possibly katabatic in nature on the Wilkins and George VI ice shelves. Neither RACMO2 nor ERA5 datasets show a significant increase in föhn melt thus far despite a more positive Southern Annular Mode and increasing surface temperatures. The warming climate and associated southward shift of westerly winds on the AP suggest a likely increase in the wind-induced melt that can densify firn, form melt ponds, and weaken ice shelf stability, however that trend remains insignificant for the past 40 years.