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Despite in‐situ observations of perennial firn aquifers (PFAs) at specific locations of the Antarctic ice sheet, a comprehensive continent‐wide mapping of PFA distribution is currently lacking. We present an estimate of their distribution across Antarctica in the form of a probability assessment using a Monte Carlo technique. Our approach involves a novel methodology that combines observations from Sentinel‐1 and Advanced SCATterometer (ASCAT) with output from a regional climate model. To evaluate our method, we conduct an extensive comparison with Operation Ice Bridge observations from the Greenland Ice Sheet. Application to Antarctica reveals high PFA probabilities in the Antarctic Peninsula (AP), particularly along its northern, northwestern, and western coastlines, as well as on the Wilkins, Müller, and George VI ice shelves. Outside the AP, PFA probability is low, except for some locations with marginally higher probabilities, such as on the Abbot, Totten, and Shackleton ice shelves. Plain Language Summary: We explore the presence of subsurface water storage within the firn layer in Antarctica, known as perennial firn aquifers (PFA), using a new method that combines satellite data and climate models. These PFAs, previously identified in Greenland, store and transmit meltwater, and could influence ice‐sheet behavior. Our study maps the likelihood of PFAs across Antarctica, finding high probabilities along the Antarctic Peninsula's northern and western coasts, as well as on specific ice shelves. Outside this region, PFAs are unlikely, except for a few spots with somewhat enhanced probability on Abbot, Totten, and Shackleton ice shelves. This inventory enhances our understanding of Antarctic hydrology and has broader implications for understanding ice‐sheet dynamics. Key Points: An innovative aquifer detection method, combining satellite and regional climate model data, is applied to AntarcticaThe evaluation of the methodology in Greenland, showing 91% correspondence, suggests good adaptability for AntarcticaThe Antarctic Peninsula stands out as the only region with high aquifer probability; in the rest of Antarctica, the likelihood is low [ABSTRACT FROM AUTHOR]

The representation of vegetative sub‐canopy wind is critical in numerical weather prediction (NWP) models for the determination of the air‐surface exchange processes of heat, momentum, and trace gases. Because of the relationship between wind speed and fire behaviors, the influence of the canopy on near‐surface wind speed is critical for prognostic fire spread models used in regional NWP models. In practice, the wind speed at the midflame point of fires (midflame wind speed) is used to determine the rate of fire spread. However, the wind speeds from most in situ measurements and NWP models are taken at some reference height above the canopy and fire flames. Hence, this study develops a modular and computationally‐efficient one‐dimensional model set composed of a canopy wind model and a wind adjustment factor (WAF) model for NWP applications across scales. The model set uses prescribed foliage shape functions to represent the vertical vegetation profile and its impacts on the three‐dimensional structure of horizontal wind speeds. Results from the canopy wind model well agree with ground‐based observations with average mean absolute bias, root mean square error and determination coefficients around 0.18 m s−1, 0.40 m s−1and 0.90, respectively. The WAF model provides midflame wind speeds by estimating the WAF based on canopy, fire and flame characteristics. Various user‐definable options provide flexibility to adapt to variations in canopy characteristics and additional complexities associated with wildfires. The model set is expected to improve NWP models by providing an improved representation of the sub‐grid wind flows at any spatial scale. Plain Language Summary: Compared to bare ground, wind speeds are reduced by the presence of vegetation at the surface by the leaves and woody parts of plants, especially within forest canopies. The altered wind speeds affect the atmosphere's stability and transport processes, as well as the spread of wildfires. Several fire prediction models are connected with weather models; however, most weather models do not consider such sub‐canopy effects on reducing wind speeds as the vertical structure of vegetation are not included in the models. Thus, this study presents a canopy model that can simulate the effects of vegetation, primarily forest canopies, on horizontal wind speeds used in weather models. The canopy model also provides the estimation of the wind speeds at the height of the midpoint of flame above ground level (midflame wind speed), which can better describe fire behaviors for general use in fire prediction models. The model results agree well with both above and below canopy top wind speed observations, and the midflame wind speeds are reliable when compared to previous studies. The canopy model is expected to improve weather modeling by providing a better representation of near‐surface wind flow, particularly for areas covered by dense forest canopies. Key Points: This study presents and evaluates a canopy wind model that simulates horizontal wind speeds above and within vegetation canopiesModel results agree well with observations and should provide a better representation of wind flow in numerical weather prediction modelsThe wind adjustment factor model provides midflame wind speed estimation, which can be used for the estimation of the rate of fire spread [ABSTRACT FROM AUTHOR]

Forecasts of tropical cyclone (TC) tornadoes are less skillful than their non‐TC counterparts at all lead times. The development of a convection‐allowing regional ensemble, known as the Warn‐on‐Forecast System (WoFS), may help improve short‐fused TC tornado forecasts. As a first step, this study investigates the fidelity of convective‐scale kinematic and thermodynamic environments to a preliminary set of soundings from WoFS forecasts for comparison with radiosondes for selected 2020 landfalling TCs. Our study shows reasonable agreement between TC convective‐scale kinematic environments in WoFS versus observed soundings at all forecast lead times. Nonetheless, WoFS is biased toward weaker than observed TC‐relative radial winds, and stronger than observed near‐surface tangential winds with weaker winds aloft, during the forecast. Analysis of storm‐relative helicity (SRH) shows that WoFS underestimates extreme observed values. Convective‐scale thermodynamic environments are well simulated for both temperature and dewpoint at all lead times. However, WoFS is biased moister with steeper lapse rates compared to observations during the forecast. Both CAPE and, to a lesser extent, 0–3‐km CAPE distributions are narrower in WoFS than in radiosondes, with an underestimation of higher CAPE values. Together, these results suggest that WoFS may have utility for forecasting convective‐scale environments in landfalling TCs with lead times of several hours. Plain Language Summary: Landfalling tropical cyclones (known as tropical depressions, tropical storms, or hurricanes) often spawn tornadoes, which are more challenging to forecast than Great Plains tornadoes. The development of a weather forecast ensemble model, known as the Warn‐on‐Forecast system, may help improve tornado forecasts. This study compares vertical profiles of winds, temperature, moisture, and associated severe weather metrics from the Warn‐on‐Forecast with observed radiosonde data (i.e., balloon‐borne instruments) in landfalling tropical cyclones. Our analysis shows agreement between the observed and forecasted vertical structure of TC winds at all lead times including strong changes in near‐surface wind speed and direction. Nonetheless, forecasted tropical cyclone winds tend to be biased weaker than observed, which is associated with an underestimation of environmental favorability for tornadoes. Similarly, forecasted temperature and moisture are also reasonably represented compared to observations. However, Warn‐on‐Forecast tends to overestimate moisture and near‐surface temperature, with smaller‐than‐observed variability in thermodynamic environmental favorability. Together, these results suggest that the weather forecast model used here may be useful for improving forecasts of supercell environments in landfalling TCs. Key Points: Warn‐on‐Forecast tropical cyclone forecasts show reasonable agreement between observed and forecast convective‐scale kinematic environmentsForecast convective‐scale thermodynamic environments also show reasonable fidelity compared to observationsA case study shows stronger discrepancies than the full sample including weaker than observed winds, temperature inversions, and dry layers [ABSTRACT FROM AUTHOR]

De‐aliasing products are used in the estimation process of satellite‐based gravity field computation to reduce errors from high‐frequency mass variations that alias into monthly gravity fields. The latest official product is AOD1B RL07 and describes non‐tidal atmosphere and oceanic mass variations at 3‐hourly resolution. However, the model‐based de‐aliasing products are inevitably incomplete and prone to temporally and spatially correlated errors that substantially contribute to errors in the estimated gravity fields. Here, we investigate possible enhancement of current de‐aliasing products by nesting a regional high‐resolution atmospheric reanalysis over Europe into a global reanalysis. As further novelty we include almost mass consistent terrestrial water storage variability from a regional hydrological model nested into a global model as additional component of the de‐aliasing product. While we find in agreement with earlier studies only minor contributions from increasing the temporal resolution beyond 3‐hourly data, our investigations suggest that contributions from continental hydrology and from regional non‐hydrostatic atmospheric modeling to sub‐monthly mass variations could be relevant already for gravity fields estimated from current gravity missions. Moreover, in the context of extreme events, we find regionally contributions from additional moisture fields, such as cloud liquid water, in the order of a few mm over Europe. We suggest this needs to be taken into account when preparing data analysis schemes for future space gravimetric missions. Plain Language Summary: Observing temporal variations in the Earth's gravity field with satellite gravimetry plays an essential role for monitoring mass transports on and underneath the Earth's surface. This is crucial for understanding the evolution of floods and droughts, the role of groundwater pumping, and to quantify the melting of ice sheets and glaciers and the resulting sea level rise. In order to isolate the target variable (e.g., terrestrial water storage changes) unwanted signals (e.g., fast mass variations in the atmosphere) need to be removed in the gravity field estimation process using background models, so‐called de‐aliasing models. This paper focuses on improving background models by incorporating regional high‐resolution models, which more specifically resolve certain processes in the atmosphere. Our hypothesis is that this will lead to better gravity fields with increased spatial resolution and less noise. Moreover, we find that considering fast hydrological variations as additional background model could improve gravity fields from the current satellite mission GRACE‐FO. For the first time, we quantify contributions from so far neglected atmospheric moisture fields, such as cloud liquid water, to enhance background models in the context of extreme events—which, however, will likely be in particular relevant for more sensitive gravity missions in the future. Key Points: We provide an atmosphere‐hydrology de‐aliasing product with regional mass‐consistent refinement over EuropeUsing non‐hydrostatic as opposed to hydrostatic numerical weather prediction model output significantly impacts the de‐aliasing productWe found that for extreme events additional moisture fields unaccounted in present Atmosphere and Ocean De‐aliasing (AOD) models can reach magnitudes relevant for de‐aliasing [ABSTRACT FROM AUTHOR]

N2 fixation is a central process of the marine nitrogen cycle, yet little is known about how this process varies from year‐to‐year. Here, we investigate this variability in the Western Tropical Atlantic (WTA), a region where N2 fixation is prevalent, fueled, in part, by the nutrient input from the Amazon River. We use hindcast simulations from 1983 through 2019 with the Regional Oceanic Modeling System (ROMS) coupled to the Biogeochemical Elemental Cycling (BEC) model expanded to include Diatom‐Diazotroph Assemblages (DDAs). Throughout the WTA, we find a substantial level of interannual variability of N2 fixation, altering it by up to 33%, and locally by up to nearly 60%. Part of this interannual variability is driven by variations in the Amazon River discharge, which during high discharge events leads to reduced rates in the upper parts of the plume and strongly enhanced rates in the downstream part. This dipole pattern is a consequence of the riverine inputs of phosphorus and the competition with non‐diazotrophs for this limiting resource. Another part of the N2 fixation variability is driven by the Atlantic Meridional Mode (AMM), and the El Niño‐Southern Oscillation (ENSO). These processes alter N2 fixation primarily through the supply of the limiting nutrients phosphorus and iron by vertical mixing, while the role of top‐down control through grazing is relatively limited in our model. The high, and so far not well recognized interannual N2 fixation variability can lead to erroneous extrapolation of field measurements and inaccuracies in the marine nitrogen budget, if unaccounted for. Plain Language Summary: Nitrogen fixation is a vital biological process in which dinitrogen is transformed into bioavailable nitrogen, which supports phytoplankton growth and ultimately maintains oceanic food webs. The amount of nitrogen fixed in this way can vary substantially due to a complex interplay of changes in environmental conditions, but this variability remains poorly constrained. Here, we focus on the year‐to‐year variability of nitrogen fixation that occurs in the Western Tropical Atlantic, where nitrogen fixation rates are particularly high due to the input of nutrients from the Amazon River. We use a regional ocean model that includes two types of nitrogen‐fixing organisms and analyze the variability from 1983 through 2019. We find that nitrogen fixation in the Western Tropical Atlantic deviates up to a third from the mean. These deviations are related to Amazon River discharge fluctuations and climate variability, in particular the El Niño—Southern Oscillation and the Atlantic Meridional Mode. Discharge and climate variability impact the availability of nutrients, which controls the growth and activity of nitrogen‐fixing organisms. In contrast, zooplankton predation does not drive variations in nitrogen fixation. These findings have implications for the marine nitrogen cycle and underscore the importance of better constraining interannual variability in nitrogen fixation. Key Points: Marine N2 fixation in the Western Tropical Atlantic varies substantially from year‐to‐year, up to a third of the mean rateIn the Amazon River plume, variability is primarily caused by variations in Amazon River discharge, altering the supply of phosphorusIn most of the Western Tropical Atlantic, the Atlantic Meridional Mode and ENSO drive variability by altering the upward nutrient mixing [ABSTRACT FROM AUTHOR]

Abstract Despite in‐situ observations of perennial firn aquifers (PFAs) at specific locations of the Antarctic ice sheet, a comprehensive continent‐wide mapping of PFA distribution is currently lacking. We present an estimate of their distribution across Antarctica in the form of a probability assessment using a Monte Carlo technique. Our approach involves a novel methodology that combines observations from Sentinel‐1 and Advanced SCATterometer (ASCAT) with output from a regional climate model. To evaluate our method, we conduct an extensive comparison with Operation Ice Bridge observations from the Greenland Ice Sheet. Application to Antarctica reveals high PFA probabilities in the Antarctic Peninsula (AP), particularly along its northern, northwestern, and western coastlines, as well as on the Wilkins, Müller, and George VI ice shelves. Outside the AP, PFA probability is low, except for some locations with marginally higher probabilities, such as on the Abbot, Totten, and Shackleton ice shelves.

Abstract The representation of vegetative sub‐canopy wind is critical in numerical weather prediction (NWP) models for the determination of the air‐surface exchange processes of heat, momentum, and trace gases. Because of the relationship between wind speed and fire behaviors, the influence of the canopy on near‐surface wind speed is critical for prognostic fire spread models used in regional NWP models. In practice, the wind speed at the midflame point of fires (midflame wind speed) is used to determine the rate of fire spread. However, the wind speeds from most in situ measurements and NWP models are taken at some reference height above the canopy and fire flames. Hence, this study develops a modular and computationally‐efficient one‐dimensional model set composed of a canopy wind model and a wind adjustment factor (WAF) model for NWP applications across scales. The model set uses prescribed foliage shape functions to represent the vertical vegetation profile and its impacts on the three‐dimensional structure of horizontal wind speeds. Results from the canopy wind model well agree with ground‐based observations with average mean absolute bias, root mean square error and determination coefficients around 0.18 m s−1, 0.40 m s−1and 0.90, respectively. The WAF model provides midflame wind speeds by estimating the WAF based on canopy, fire and flame characteristics. Various user‐definable options provide flexibility to adapt to variations in canopy characteristics and additional complexities associated with wildfires. The model set is expected to improve NWP models by providing an improved representation of the sub‐grid wind flows at any spatial scale.

Changes in tropical cyclones due to greenhouse‐gas forcing in the Shanghai area have been studied in a double‐nesting regional model experiment using the Met Office convection‐permitting model HadREM3‐RA1T at 4 km resolution and the regional model HadREM3‐GA7.05 at 12 km for the intermediate nest. Boundary conditions for the experiment have been constructed from HadGEM2‐ES, a General Circulation Model (GCM) from the 5th Coupled Model Intercomparison Project (CMIP5), directly using high‐frequency data for the atmosphere (6‐hourly) and the ocean (daily), for the historical period (1981–2000) and under the Representative Concentration Pathway 8.5 (2080–2099). These choices identify one of the warmest climate scenarios available from CMIP5. Given the direct use of GCM data for the baseline, large scale conditions relevant for tropical cyclones have been analyzed, demonstrating a realistic representation of environmental conditions off the coast of eastern China. GCM large scale changes show a reduction in wind shear in addition to the expected strong increase in sea‐surface temperature. Tropical cyclones from the 4 km historical simulation have a negative bias in intensity, not exceeding Category 4, and a wet bias in the rainfall associated with these cyclones. However, there is a clear improvement in cyclone intensity and rainfall at 4 km in comparison with the 12 km simulation. Climate change responses in the 4 km simulation include an extension of the tropical cyclone season, and strong increases in frequency of the most intense cyclones (approximately by a factor of 10) and associated rainfall. These are consistent with the results from the 12 km simulation. Plain Language Summary: Since global climate models do not have the spatial resolution to simulate tropical cyclones, higher resolution limited area models are commonly used to improve the representation of these phenomena. In this study, where changes in the Shanghai area have been estimated, this was done in two steps, using a regional model at 12 km resolution as the intermediate step to finally reach a 4 km resolution for the region around Shanghai with a model which can explicitly represent convection processes. This was done by using one of the warmest climate scenarios available from the climate projections run under realistic increases of greenhouse‐gas concentrations, to study climate change at the end of this century. The global climate model reproduces large scale conditions relevant for tropical cyclones which compare well with observations in the historical period and projects changes in the atmosphere and the ocean which are relevant for tropical cyclones. The downscaled model at 4 km reproduces the observation with some biases in intensity, not sufficient to reach Category 4, and in the cyclone precipitation, through marked improvements with respect to the 12 km model. The climate change response shows a strong increase in intense tropical cyclone frequency and rainfall, common to both models. Key Points: Double‐nesting experiment with a 4 km convective scale model driven by a high end Coupled Model Intercomparison Project general circulation model to study changes in tropical storms near ShanghaiImprovement at 4 km over the intermediate 12 km nest on rainfall and intensity of tropical storms, but not sufficient to reach category 4Future changes at 4 km show a marked increase in frequency of intense tropical cyclones and in rainfall, well matched by the 12 km model [ABSTRACT FROM AUTHOR]

Greece is characterized by a significant warming trend in recent decades, accompanied by increasing frequency, intensity, and duration of heat waves (HWs). A particularly devastating HW that affected the country was the late July/early August 2021 event (JA2021HW), which lasted for 9 days (July 28–August 5). Focusing on the hottest day of the event (August 3), the main characteristics of JA2021HW are presented in the current study, using model reanalysis data and up to 11‐year observations derived from the dense network of ground‐based weather stations operated by the Meteo Unit at the National Observatory of Athens (NOA). This analysis highlights the severity of JA2021HW, especially in the central and southernmost regions of Greece. Most importantly, the impact of the direct effect of anthropogenic greenhouse gases to the examined extreme event, in terms of intensity and probability of occurrence, is examined by employing a regional 31‐member ensemble (ENS) modeling approach based on Weather Research and Forecasting (WRF) model, which is operationally used by NOA/Meteo. Firstly, WRF is validated under 7‐day lead‐time ENS simulations with current‐state greenhouse gas (GHG) concentrations (GHG_2021 ENS), showing a robust model performance in replicating the JA2021HW's magnitude on August 3rd. Then, 7‐day lead‐time ENS simulations with the GHG concentrations reduced to the pre‐industrial (1854) levels (GHG_1854 ENS) are performed and compared to the GHG_2021 ENS experiment. The results reveal a contribution of the immediate anthropogenic warming due to the increased GHG concentrations to the JA2021HW intensity in West and South continental and insular Greece, which can be important in the framework of the human health impacts of extreme temperatures. For the event's occurrence probability, no robust evidence of any change could be derived. These statements are partially constrained by the fact that only the direct GHG effect on the timescale of a few days was examined. [ABSTRACT FROM AUTHOR]

Marine heatwaves (MHWs) have been recognized as a serious threat to marine life, yet, most studies so far have focused on the surface only. Here, we investigate the vertical dimension and propagation of surface MHWs in the Eastern Pacific (EP) using results from a high‐resolution hindcast simulation (1979–2019), performed with the Regional Ocean Modeling System. We detect MHWs using a seasonally varying percentile threshold on a fixed baseline and track their vertical propagation across the upper 500 m. We find that nearly a third (∼29%) of the MHWs extend beyond the surface mixed layer depth (MLD). On average, these deep‐reaching MHWs (dMHWs) extend to 110 m below the MLD and last five times longer than MHWs that are confined to the mixed layer (184 vs. 36 days). The dMHWs can cause stronger temperature anomalies at depth than at the surface (maximum intensity of 5.0 vs. 1.9°C). This general subsurface MHW intensification even holds when scaling the temperatures with the respective local variability. A clustering of dMHWs reveals that 41% of them are block‐like, that is, continually remain in contact with the sea surface, 24% propagate downward, 20% propagate upward, while 15% appear at the surface multiple times. Although the water column MHW duration, intensity and severity are only moderately correlated with their corresponding surface‐based MHW characteristics, dMHWs have the potential to be detected from the surface. Our study can help to augment the remote sensing‐based monitoring of upper ocean exposure to MHWs. Plain Language Summary: Periods of extremely warm water temperatures, referred to as marine heatwaves (MHWs), pose a serious threat to marine life. While many studies have analyzed MHW properties at the sea surface, little is known about their subsurface nature. We here use a new approach to define MHWs throughout the water column and study the vertical structure and propagation behavior of MHWs in the Eastern Pacific based on a high‐resolution numerical hindcast simulation (1979–2019). We find that nearly a third of MHWs that are discernible at the sea surface reach below the layer of well‐mixed waters near the sea surface, the so‐called mixed layer (ML). These deep‐reaching MHWs (dMHWs) last on average longer than ML confined MHWs (184 vs. 36 days) and are marked by larger temperature threshold exceedances (maximum intensity of 5.0 vs. 1.9°C). We furthermore identify four distinct vertical propagation patterns associated with the dMHWs: 41% continually affect the sea surface, 24% propagate downwards, 20% propagate upward, while 15% appear at the surface multiple times. Overall, these analyses show that MHWs can affect the water column to a larger degree than diagnosed based on the sea surface only. Key Points: About a third of marine heatwaves (MHW) in the Eastern Pacific extend below the mixed layer. Ten percent of MHWs extend on average deeper than 150 m59% of deep‐reaching MHWs (dMHWs) are partly invisible at the surface, as they either deepen, shoal or exhibit multi‐surfacing behaviorAs initial tests indicate that the surface‐based detection of dMHWs seems feasible, dMHWs might be detectable using remote sensing data [ABSTRACT FROM AUTHOR]

Marine biofouling is considered one of the major biophysical processes influencing the vertical dynamics of plastic debris in seawater. We numerically implement, for the first time, this mechanism within a fine-resolution, regional model of the Tyrrhenian Sea, in order to simulate the dispersion of microplastics (MPs) released at the mouth of a highly polluting river. Four polymers and three particle sizes are used to quantify algal concentration influence on the trajectories, fates, and accumulation spots of the tracked MPs, by comparing 2002 winter and summer runs encompassing or not biofouling. Besides a marked seasonality for most of the MP types and radii tested, biofouling effects are prominently observed for only 2 polymers and particles bigger than 1 μ m. Thus, further realistic applications of the biofouling mechanism in oceanic circulation models are required to achieve a thorough assessment of its impact on plastic density within distinctive basins of the world seas. • Marine biofouling is explicitly resolved in a realistic regional model (ROMS). • Microplastic (MP) particles are released at the outlet of a highly polluted river. • Biofouling strongly affects the horizontal and vertical dispersion of MPs. • Biofouling effects are significant for a limited range of MPs' sizes and polymers. • A marked seasonality is observed in the biofilm growth over the MP particles. [Display omitted] [ABSTRACT FROM AUTHOR]

The Brazilian Equatorial Shelf (BES) is one among the macrotidal regions worldwide. This study used a high-resolution numerical configuration of the ocean model ROMS (Regional Ocean Modeling System) forced with realistic surface and lateral forcing, as well as with tides and river discharges. Tidal heights of more than 2 m were found in three regions in BES due to the large tidal amplification across the estuarine channels inside each region: Amazon, Pará, and Maranhão, and for a considerable time fraction. Heights between 4 and 5 m occurred with a frequency greater than 20%–30% in some regions. All hypothetical barrages proposed in this study were capable of an annual power production, in two-way mode, higher than La Rance (533 GWh year−1, two-way operation, France) and Sihwa (553 GWh year−1, flood-only operation, South Korea), except one with the same production as Sihwa barrage. The installation effort was evaluated using the Gibrat ratio, the ratio between the length of the barrage and its annual energy production. Among the proposed barrages, the most efficient ones have an annual power generation greater than 1500 GWh year−1 and a Gibrat ratios between 1.17 and 3.26, much lower than the Gibrat ratio of Sihwa tidal barrage. • Tidal Heights between 4 and 5 m occurred with a frequency greater than 20–30%. • Most proposed barrages had an annual power production higher than La Rance. • The most efficient proposed barrages had a lower installation cost than Sihwa. • Brazilian Equatorial Shelf is a source of clean energy to be explored. [ABSTRACT FROM AUTHOR]