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At least 127 records · Page 7

Steady global surface warming from 1973 to 2022 but increased warming rate after 1990

The change in global mean surface temperature is a crucial and broadly used indicator of the evolution of climate change. Any decadal scale changes in warming rate are however obfuscated by internal variability. Here we show that the surface temperature increase through the recent La Nina influenced years (2022) is consistent with the 50-year trend of 0.18 °C/decade. We use an Earth System Model based tool to filter out modulations to the warming rate by sea-surface temperature patterns and find consistent warming rates in four major global temperature data series. However, we also find clear indications, in all observational series, of a step-up in warming rate since around 1990. CMIP6 models generally do not capture this observed combination of long-term warming rate and recent increase.

58 GEOSCIENCES↗

Air-coupled tsunamis generated from impacts and airbursts: Our understanding before Hunga-Tonga Hunga-Ha'apai

The effort to prevent or mitigate the effects of an impact on Earth is known as planetary defense. A significant component of planetary defense research involves risk assessment. Much of our understanding of the risk from near-Earth objects comes from the geologic record in the form of impact craters, but not all asteroid impacts are crater-forming events. Small asteroids explode before reaching the surface, generating an airburst, and most impacts into the ocean do not penetrate the water to form a crater in the sea floor. The risk from these non-crater-forming ocean impacts and airbursts is difficult to quantify and represents a significant uncertainty in our assessment of the overall threat. We are currently working to better understand impact scenarios that can generate dangerous tsunamis. One of the suggested mechanisms for the production of asteroid–generated tsunamis is by direct coupling of the pressure wave to the water, analogous to the means by which a moving weather front can generate a meteotsunami. To test this hypothesis, we ran a series of airburst simulations and provided time-resolved pressure and wind profiles to use as source functions for tsunami models. We used the CTH hydrocode to model the various airburst scenarios to compare to the results of other simulations and provide time dependent boundary conditions as input to shallow-water wave propagation codes. The strongest and most destructive meteotsunamis are generated by atmospheric pressure oscillations with amplitudes of only a few hPa1 (mbar), corresponding to changes in sea level of a few cm. The resulting wave is strongest when there is a resonance between the ocean and the atmospheric forcing. A Proudman resonance takes place when the atmospheric disturbance’s translational speed (U) equals the longwave phase speed $\sqrt{gh}$ of shallow water wave. Coupling is strongest when the Froude number (Fr=U/c) is unity. A weather front propagates much slower than the speed of sound, so meteotsunamis are most common and dangerous in shallow bodies of water such as the Mediterranean Sea or Lake Michigan. By contrast, the blast wave from an airburst or crater-forming impact propagates at a speed faster than a tsunami in the deepest ocean, and a Proudman resonance cannot be achieved even though the overpressures are orders of magnitude greater. However, blast wave profiles are N-waves in which a sharp shock wave leading to overpressure is followed by a more gradual rarefaction to a much longer-duration underpressure phase. Even though the blast outruns the water wave it is forcing, the tsunami should continue to be driven by the out-of-resonance gradient associated with the suction phase, which may depend strongly on the details of the airburst or impact scenario. The open question is whether there are any conditions under which such an airburst-driven tsunami can be dangerous enough to contribute to the overall impact risk. We have also identified other potential mechanisms for airburst-generated tsunamis: 1) reaction force at the surface from the plume ejected into space, which carries significant momentum, 2) expanding toroidal vortices at the surface, which travel more slowly than the shock wave and can generate a Proudman resonance in relatively shallow ocean (such as continental shelf), and 3) steam explosion from seawater ablation by a “Type II” (Libyan Desert Glass-type) airburst in which the hot vapor jet descends to the surface. On January 15, 2022, the Hunga-Tonga Hunga-Ha’apai volcano, located approximately 60 km north of Tongatapu, the main island of Tonga, violently erupted with a powerful explosion, culminating the period of volcanic activity that started in December of 2021. This event and resulting tsunamis provided an existence proof for the air pressure wave coupling mechanism we proposed. It also suggests that it can be stronger and more significant over much greater distances than we contemplated, leading to global tsunamis associated with impact events on land as well as in the water. Large atmospheric explosions generate global Lamb waves with larger amplitudes, longer periods, and slower speeds than the local and regional blast waves we modeled prior to that event. This paper reviews our analysis and modeling of airburst-driven tsunamis prior to the 2022 Hunga-Tonga Hunga-Ha’apai tsunami, which was the subject of two presentations at the 2023 Planetary Defense Conference and is the subject of another paper currently in preparation.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of the Planetary Boundary Layer Height From ERA5 Reanalysis With MOSAiC Observations Over the Arctic Ocean

The planetary boundary layer height (PBLH) is a crucial indicator reflecting the region of the atmosphere characterized by continuous turbulence. Here, we use radiosonde and surface meteorological observations (4–7 times per day, year-round measurements) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition to derive the PBLH (PBLH MOSAiC ), and further evaluate the PBLH from the ERA5 reanalysis (PBLH ERA5 ). Comparisons between PBLH MOSAiC and PBLH ERA5 from different perspectives reveal that: (a) The overestimation of PBLH ERA5 when the sea ice concentration is >90% is significant with the centered root mean squared error reaching up to 201 m; (b) The difference between the two products is notably pronounced in cold seasons, while it is comparatively diminished in warm seasons; (c) In neutral boundary layers, differences in PBLH ERA5 are larger compared with stable and convective boundary layers. In addition, the analysis of error sources indicates that the bias of PBLH ERA5 is sensitive to the bias of vertical thermal structure and wind speed profiles in ERA5 data sets in all conditions. Finally, we find a Random Forest model effectively reduces the bias of PBLH ERA5 with the index of agreement reaching up to 0.71 in the test data set, while a multiple linear regression demonstrates comparable performance to the Random Forest model.

54 ENVIRONMENTAL SCIENCES↗

Methane flux from transplanted soil monoliths depends on moisture, but not origin

Soils both produce and consume methane (CH 4 ), a potent greenhouse gas that contributes to climate change. In coastal forests, upland soils are shifting from being CH 4 sinks to sources as sea levels rise, increasingly flooding soils with little prior inundation history. Ecosystem CH 4 budgets are highly uncertain due in part to the difficulty in separating fluxes measured at the soil surface into individual production and consumption processes which are likely to have different responses to future environmental conditions. Here, we measured growing season CH 4 fluxes from soil monoliths transplanted four years prior along an inundation and salinity gradient to determine how changes in abiotic conditions control CH 4 flux rates. To parse net fluxes measured at the soil surface into their component gross rates, we paired field measurements with a stable isotope pool dilution incubation of surface soils. Throughout the growing season, net soil surface CH 4 flux was positively correlated with soil moisture (p < 0.01), with lowland-located soils tending towards CH 4 sources (mean 0.349 ± 1.11 mg CH 4 -C m -2 hr -1 , error is standard deviation) and upland-located soils tending towards CH 4 sinks (-0.003 ± 0.003 mg CH 4 -C m -2 hr -1 ). Transplanted soils’ fluxes were statistically identical to their native neighbors once microtopography-driven differences in soil moisture were controlled for. The pool dilution experiment revealed that production and consumption rates were similar in upland and lowland surface soils (2.82 ± 3.29 µmol CH 4 g -1 dry soil d -1 production, 3.47 ± 2.03 µmol CH 4 g -1 dry soil d -1 consumption), indicating the majority of production likely occurs at depth in lowland soils. Both gross and net fluxes from transplanted soils showed no effect of soil origin after four years, suggesting low resistance of CH 4 cycling to global change drivers. Our results indicate the strength of the coastal forest CH 4 sink is likely to decrease in proportion to sea-level rise.

59 BASIC BIOLOGICAL SCIENCES↗

An Ensemble of Neural Networks for Moist Physics Processes, Its Generalizability and Stable Integration

Abstract With the recent advances in data science, machine learning has been increasingly applied to convection and cloud parameterizations in global climate models (GCMs). This study extends the work of Han et al. (2020, https://doi.org/10.1029/2020MS002076 ) and uses an ensemble of 32‐layer deep convolutional residual neural networks, referred to as ResCu‐en, to emulate convection and cloud processes simulated by a superparameterized GCM, SPCAM. ResCu‐en predicts GCM grid‐scale temperature and moisture tendencies, and cloud liquid and ice water contents from moist physics processes. The surface rainfall is derived from the column‐integrated moisture tendency. The prediction uncertainty inherent in deep learning algorithms in emulating the moist physics is reduced by ensemble averaging. Results in 1‐year independent offline validation show that ResCu‐en has high prediction accuracy for all output variables, both in the current climate and in a warmer climate with +4K sea surface temperature. The analysis of different neural net configurations shows that the success to generalize in a warmer climate is attributed to convective memory and the 1‐dimensional convolution layers incorporated into ResCu‐en. We further implement a member of ResCu‐en into CAM5 with real world geography and run the neural‐network‐enabled CAM5 (NCAM) for 5 years without encountering any numerical integration instability. The simulation generally captures the global distribution of the mean precipitation, with a better simulation of precipitation intensity and diurnal cycle. However, there are large biases in temperature and moisture in high latitudes. These results highlight the importance of convective memory and demonstrate the potential for machine learning to enhance climate modeling.

Meteorology & Atmospheric Sciences↗

RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project

Abstract. The radiative–convective equilibrium (RCE) model intercomparison project (RCEMIP) leveraged the simplicity of RCE to focus attention on moist convective processes and their interactions with radiation and circulation across a wide range of model types including cloud-resolving models (CRMs), general circulation models (GCMs), single-column models, global cloud-resolving models, and large-eddy simulations. While several robust results emerged across the spectrum of models that participated in the first phase of RCEMIP (RCEMIP-I), two points that stand out are (1) the strikingly large diversity in simulated climate states and (2) the strong imprint of convective self-aggregation on the climate state. However, the lack of consensus in the structure of self-aggregation and its response to warming is a barrier to understanding. Gaining a deeper understanding of convective aggregation and tropical climate will require reducing the degrees of freedom with which convection can vary. Therefore, we propose phase II of RCEMIP (RCEMIP-II) that utilizes a prescribed sinusoidal sea surface temperature (SST) pattern to provide a constraint on the structure of convection and move one critical step up the model hierarchy. This so-called “mock-Walker” configuration generates features that resemble observed tropical circulations. The specification of the mock-Walker protocol for RCEMIP-II is described, along with example results from one CRM and one GCM. RCEMIP-II will consist of five required simulations: three simulations with the same three mean SSTs as in RCEMIP-I but with an SST gradient and two additional simulations at one of the mean SSTs with different values of the SST gradients. We also test the sensitivity to the imposed SST gradient and the domain size. Under weak SST gradients, unforced self-aggregation emerges across the entire domain, similar to what was found in RCEMIP. As the SST gradient increases, the convective region narrows and is more confined to the warmest SSTs. At warmer mean SSTs and stronger SST gradients, low-frequency variability in the convective aggregation emerges, suggesting that simulations of at least 200 d may be needed to achieve robust equilibrium statistics in this configuration. Simulations with different domain sizes generally have similar mean statistics and convective structures, depending on the value of the SST gradient. The prescribed SST boundary condition is the only difference in the set-up between RCEMIP-II and RCEMIP-I, which enables comparison between the two; however, we also welcome participation in RCEMIP-II from models that did not participate in RCEMIP-I.

Geology↗

Development and evaluation of a new 4DEnVar-based weakly coupled ocean data assimilation system in E3SMv2

The development, implementation, and evaluation of a new weakly coupled ocean data assimilation (WCODA) system for the fully coupled Energy Exascale Earth System Model version 2 (E3SMv2) utilizing the four-dimensional ensemble variational (4DEnVar) method are presented in this study. The 4DEnVar method, based on the dimension-reduced projection four-dimensional variational (DRP-4DVar) approach, replaces the adjoint model with the ensemble technique, thereby reducing computational demands. Monthly mean ocean temperature and salinity data from the EN4.2.1 reanalysis are integrated into the ocean component of E3SMv2 from 1950 to 2021 with the goal of providing realistic initial conditions for decadal predictions and predictability studies. The performance of the WCODA system is assessed using various metrics, including the reduction rate of the cost function, root mean square error (RMSE) differences, correlation differences, and model biases. Results indicate that the WCODA system effectively assimilates the reanalysis data into the climate model, consistently achieving negative reduction rates of the cost function and notable improvements in RMSE and correlation across various ocean layers and regions. Significant enhancements are observed in the upper ocean layers across the majority of global ocean regions, particularly in the north Atlantic, north Pacific, and Indian Ocean. Model biases in sea surface temperature and salinity are also substantially reduced. For sea surface temperature, cold biases in the north Pacific and north Atlantic are diminished by about 1–2 °C, and warm biases in the Southern Ocean are corrected by approximately 1.5–2.5 °C. In terms of salinity, improvements are observed with bias reductions of about 0.5–1 psu in the north Atlantic and north Pacific and up to 1.5 psu in parts of the Southern Ocean. The ultimate goal of the WCODA system is to advance the predictive capabilities of E3SM for subseasonal to decadal climate predictions, thereby supporting research on strategic energy-sector policies and planning.

54 ENVIRONMENTAL SCIENCES↗

Winter precipitation predictability in Central Southwest Asia and its representation in seasonal forecast systems

In Central Southwest Asia (CSWA; 22°N to 40°N and 30°E to 70°E), winter (November to February) precipitation contributes up to 70% of the annual mean, but substantial interannual variations exist. Dynamical models exhibit subpar predictability in this region, but the limits of their skills are not well established. Here, we identify the tropical and extratropical forcings that explain ~75% of area-averaged seasonal variability in CSWA winter precipitation. Tropical forcing comes from the indirect El Niño-Southern Oscillation (ENSO) pathway, the leading mode of tropical Indian Ocean precipitation variability. This mode is coupled with ENSO-related Pacific Ocean sea surface temperature variability. A direct ENSO influence on CSWA does not extend beyond its Indian Ocean connection. Extratropical forcing comes from a large-scale mode of internal atmospheric variability. The spatial structure, variability of tropical forcing, and teleconnection with CSWA winter precipitation are skillfully depicted in two seasonal forecasting systems: the fifth-generation seasonal forecasting system (SEAS5) and Seamless System for Prediction and Earth System Research (SPEAR). Extratropical forcing’s spatial structure is also produced skillfully in the two modelling systems; however, the representation of its interannual variability and teleconnection requires improvement. While SEAS5 displays skill in representing extratropical forcing influence on CSWA winter precipitation and marginal skill in reproducing interannual variability, SPEAR has negligible ability in both areas. Consequently, these models have limited predictive skills over CSWA in winter. While improvements in representing extratropical forcing may be inherently limited as it arises from internal atmospheric variability, further research is needed to establish its predictability limits fully.

54 ENVIRONMENTAL SCIENCES↗

Influence of sea-ice anomalies on Antarctic precipitation using source attribution in the Community Earth System Model

Abstract. We conduct sensitivity experiments using a general circulation model that has an explicit water source tagging capability forced by prescribed composites of pre-industrial sea-ice concentrations (SICs) and corresponding sea surface temperatures (SSTs) to understand the impact of sea-ice anomalies on regional evaporation, moisture transport and source–receptor relationships for Antarctic precipitation in the absence of anthropogenic forcing. Surface sensible heat fluxes, evaporation and column-integrated water vapor are larger over Southern Ocean (SO) areas with lower SICs. Changes in Antarctic precipitation and its source attribution with SICs have a strong spatial variability. Among the tagged source regions, the Southern Ocean (south of 50° S) contributes the most (40 %) to the Antarctic total precipitation, followed by more northerly ocean basins, most notably the South Pacific Ocean (27%), southern Indian Ocean (16 %) and South Atlantic Ocean (11 %). Comparing two experiments prescribed with high and low pre-industrial SICs, respectively, the annual mean Antarctic precipitation is about 150 Gt yr-1 (or 6 %) more in the lower SIC case than in the higher SIC case. This difference is larger than the model-simulated interannual variability in Antarctic precipitation (99 Gt yr-1). The contrast in contribution from the Southern Ocean, 102 Gt yr-1, is even more significant compared to the interannual variability of 35 Gt yr-1 in Antarctic precipitation that originates from the Southern Ocean. The horizontal transport pathways from individual vapor source regions to Antarctica are largely determined by large-scale atmospheric circulation patterns. Vapor from lower-latitude source regions takes elevated pathways to Antarctica. In contrast, vapor from the Southern Ocean moves southward within the lower troposphere to the Antarctic continent along moist isentropes that are largely shaped by local ambient conditions and coastal topography. This study also highlights the importance of atmospheric dynamics in affecting the thermodynamic impact of sea-ice anomalies associated with natural variability on Antarctic precipitation. Our analyses of the seasonal contrast in changes of basin-scale evaporation, moisture flux and precipitation suggest that the impact of SIC anomalies on regional Antarctic precipitation depends on dynamic changes that arise from SIC–SST perturbations along with internal variability. The latter appears to have a more significant effect on the moisture transport in austral winter than in summer.

54 ENVIRONMENTAL SCIENCES↗

CMIP5 model selection for ISMIP6 ice sheet model forcing: Greenland and Antarctica

Abstract. The ice sheet model intercomparison project for CMIP6 (ISMIP6) effort brings together the ice sheet and climate modeling communities to gain understanding of the ice sheet contribution to sea level rise. ISMIP6 conducts stand-alone ice sheet experiments that use space- and time-varying forcing derived from atmosphere–ocean coupled global climate models (AOGCMs) to reflect plausible trajectories for climate projections. The goal of this study is to recommend a subset of CMIP5 AOGCMs (three core and three targeted) to produce forcing for ISMIP6 stand-alone ice sheet simulations, based on (i) their representation of current climate near Antarctica and Greenland relative to observations and (ii) their ability to sample a diversity of projected atmosphere and ocean changes over the 21st century. The selection is performed separately for Greenland and Antarctica. Model evaluation over the historical period focuses on variables used to generate ice sheet forcing. For stage (i), we combine metrics of atmosphere and surface ocean state (annual- and seasonal-mean variables over large spatial domains) with metrics of time-mean subsurface ocean temperature biases averaged over sectors of the continental shelf. For stage (ii), we maximize the diversity of climate projections among the best-performing models. Model selection is also constrained by technical limitations, such as availability of required data from RCP2.6 and RCP8.5 projections. The selected top three CMIP5 climate models are CCSM4, MIROC-ESM-CHEM, and NorESM1-M for Antarctica and HadGEM2-ES, MIROC5, and NorESM1-M for Greenland. This model selection was designed specifically for ISMIP6 but can be adapted for other applications.

54 ENVIRONMENTAL SCIENCES↗

New Record Ocean Temperatures and Related Climate Indicators in 2023

The global physical and biogeochemical environment has been substantially altered in response to increased atmospheric greenhouse gases from human activities. In 2023, the sea surface temperature (SST) and upper 2000 m ocean heat content (OHC) reached record highs. The 0–2000 m OHC in 2023 exceeded that of 2022 by 15 ± 10 ZJ (1 Zetta Joules = 10 21 Joules) (updated IAP/CAS data); 9 ± 5 ZJ (NCEI/NOAA data). The Tropical Atlantic Ocean, the Mediterranean Sea, and southern oceans recorded their highest OHC observed since the 1950s. Associated with the onset of a strong El Niño, the global SST reached its record high in 2023 with an annual mean of ~0.23°C higher than 2022 and an astounding > 0.3°C above 2022 values for the second half of 2023. The density stratification and spatial temperature inhomogeneity indexes reached their highest values in 2023.

54 ENVIRONMENTAL SCIENCES↗

The Strength of Coupling to the Southern Ocean Modulates Tropical Eastern Pacific Variability and Forced Response

Despite rising global-mean temperatures, large parts of the Southern Ocean and tropical eastern Pacific Ocean have cooled during the satellite era. These regions may be linked by teleconnections, with Southern Ocean cooling contributing to tropical eastern Pacific cooling. We demonstrate that, on average, state-of-the-art Earth system models (ESMs) underestimate the magnitude of interaction between the Southern Ocean and tropical eastern Pacific Ocean. The strength of the teleconnection is shown to be mediated by the magnitude of the positive cloud–sea surface temperature (SST) feedback in the subtropical eastern Pacific Ocean and the strength of the wind–evaporation–SST (WES) feedback. We link excessive precipitation in the tropical Pacific south of the equator to the strength of the Southern Ocean–eastern Pacific teleconnection. This model bias, known as the double intertropical convergence zone (ITCZ), is shown to be related to erroneous convection south of the equator, weakened cross-equatorial trade winds, and unfavorable meteorological conditions for marine boundary layer subtropical clouds. We postulate there is a two-way interaction, in which a double-ITCZ occurs with weaker cloud–SST and WES feedbacks, which in turn impact local SSTs and amplify the double-ITCZ. Models with a stronger Southern Ocean to tropical Pacific teleconnection tend to exhibit more multidecadal variability in the Walker circulation, ITCZ, and west–east equatorial SST gradient, as well as greater delayed warming in the tropical eastern Pacific Ocean resulting from delayed Southern Ocean warming under greenhouse gas forcing. These results provide insight into why ESMs struggle to replicate observed tropical Pacific temperature trend patterns and point to ITCZ location as a key target for improvement in future model development.

Climate change↗

Direct and semi-direct radiative forcing of biomass-burning aerosols over the southeast Atlantic (SEA) and its sensitivity to absorbing properties: a regional climate modeling study

Simulations are performed for the period 2000-2015 by two different regional climate models, ALADIN and RegCM, to quantify the direct and semi-direct radiative effects of biomass-burning aerosols (BBAs) in the southeast Atlantic (SEA) region. Different simulations have been performed using strongly absorbing BBAs in accordance with recent in situ observations over the SEA. For the July-August-September (JAS) season, the single scattering albedo (SSA) and total aerosol optical depth (AOD) simulated by the ALADIN and RegCM models are consistent with the MACv2 climatology and MERRA-2 and CAMS-RA reanalyses near the biomass-burning emission sources. However, the above-cloud AOD is slightly underestimated compared to satellite (MODIS and POLDER) data during the transport over the SEA. The direct radiative effect exerted at the continental and oceanic surfaces by BBAs is significant in both models and the radiative effects at the top of the atmosphere indicate a remarkable regional contrast over SEA (in all-sky conditions), with a cooling (warming) north (south) of 10°S, which is in agreement with the recent MACv2 climatology. In addition, the two models indicate that BBAs are responsible for an important shortwave radiative heating of ~0.5-1K per day over SEA during JAS with maxima between 2 and 4 km a.m.s.l. (above mean sea level). At these altitudes, BBAs increase air temperature by ~0.2-0.5 K, with the highest values being co-located with low stratocumulus clouds. Vertical changes in air temperature limit the subsidence of air mass over SEA, creating a cyclonic anomaly. The opposite effect is simulated over the continent due to the increase in lower troposphere stability. The BBA semi-direct effect on the lower troposphere circulation is found to be consistent between the two models. Changes in the cloud fraction are moderate in response to the presence of smoke, and the models differ over the Gulf of Guinea. Finally, the results indicate an important sensitivity of the direct and semi-direct effects to the absorbing properties of BBAs. Over the stratocumulus (Sc) region, DRE varies from +0.94 W m -2 (scattering BBAs) to +3.93 W m -2 (most absorbing BBAs).

54 ENVIRONMENTAL SCIENCES↗

Development and Evaluation of E3SM‐MOSAIC: Spatial Distributions and Radiative Effects of Nitrate Aerosol

Abstract Nitrate aerosol plays an important role in affecting regional air quality as well as Earth's climate. However, it is not well represented or even neglected in many global climate models. In this study, we couple the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) module with the four‐mode version of the Modal Aerosol Module (MAM4) in DOE's Energy Exascale Earth System Model version 2 (E3SMv2) to simulate nitrate aerosol and its radiative effects. We find that nitrate aerosol simulated by E3SMv2‐MAM4‐MOSAIC is sensitive to the treatment of gaseous HNO 3 transfer to/from interstitial particles related to accommodation coefficients of HNO 3 ( ) on dust and non‐dust particles. We compare three different treatments of HNO 3 transfer: (a) a treatment (MTC_SLOW) that uses a low in the mass transfer coefficient (MTC) calculation; (b) a dust‐weighted MTC treatment (MTC_WGT) that uses a high on non‐dust particles; and (c) a dust‐weighted MTC treatment that also splits coarse mode aerosols into the coarse dust and sea salt sub‐modes in MOSAIC (MTC_SPLC). MTC_WGT and MTC_SPLC increase the global annual mean (2005–2014) nitrate burden from 0.096 (MTC_SLOW) to 0.237 and 0.185 Tg N, respectively, mostly in the coarse mode. MTC_WGT and MTC_SPLC also produce stronger nitrate direct radiative forcing (−0.048 and −0.051 W m −2 , respectively) and indirect forcing (−0.33 and −0.35 W m −2 , respectively) than MTC_SLOW (−0.021 and −0.24 W m −2 ). MTC_WGT and MTC_SPLC improve nitrate surface concentrations over remote oceans based on limited observations and vertical profiles of nitrate concentrations against aircraft measurements below 400 hPa.

54 ENVIRONMENTAL SCIENCES↗

Air‐Ice‐Ocean Coupling During a Strong Mid‐Winter Cyclone: Observing Coupled Dynamic Interactions Across Scales

Abstract Arctic cyclones are key drivers of sea ice and ocean variability. During the 2019–2020 Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, joint observations of the coupled air‐ice‐ocean system were collected at multiple spatial scales. Here, we present observations of a strong mid‐winter cyclone that impacted the MOSAiC site as it drifted in the central Arctic pack ice. The sea ice dynamical response showed spatial structure at the scale of the evolving and translating cyclonic wind field. Internal ice stress and ocean stress play significant roles, resulting in timing offsets between the atmospheric forcing and the ice response and post‐cyclone inertial ringing in the ice and ocean. Ice motion in response to the wind field then forces the upper ocean currents through frictional drag. The strongest impacts to the sea ice and ocean from the passing cyclone occur as a result of the surface impacts of a strong atmospheric low‐level jet (LLJ) behind the trailing cold front and changing wind directions between the warm‐sector LLJ and post cold‐frontal LLJ. Impacts of the cyclone are prolonged through the coupled ice‐ocean inertial response. Local impacts of the approximately 120 km wide LLJ occur over a 12 hr period or less and at scales of a kilometer to a few tens of kilometers, meaning that these impacts occur at combined smaller spatial scales and faster time scales than most satellite observations and coupled Earth system models can resolve.

Meteorology & Atmospheric Sciences↗

Unveiling four decades of intensifying precipitation from tropical cyclones using satellite measurements

Increases in precipitation rates and volumes from tropical cyclones (TCs) caused by anthropogenic warming are predicted by climate modeling studies and have been identified in several high intensity storms occurring over the last half decade. However, it has been difficult to detect historical trends in TC precipitation at time scales long enough to overcome natural climate variability because of limitations in existing precipitation observations. We introduce an experimental global high-resolution climate data record of precipitation produced using infrared satellite imagery and corrected at the monthly scale by a gauge-derived product that shows generally good performance during two hurricane case studies but estimates higher mean precipitation rates in the tropics than the evaluation datasets. General increases in mean and extreme rainfall rates during the study period of 1980–2019 are identified, culminating in a 12–18%/40-year increase in global rainfall rates. Overall, all basins have experienced intensification in precipitation rates. Increases in rainfall rates have boosted the mean precipitation volume of global TCs by 7–15% over 40 years, with the starkest rises seen in the North Atlantic, South Indian, and South Pacific basins (maximum 59–64% over 40 years). In terms of inland rainfall totals, year-by-year trends are generally positive due to increasing TC frequency, slower decay over land, and more intense rainfall, with an alarming increase of 81–85% seen from the strongest global TCs. As the global trend in precipitation rates follows expectations from warming sea surface temperatures (11.1%/°C), we hypothesize that the observed trends could be a result of anthropogenic warming creating greater concentrations of water vapor in the atmosphere, though retrospective studies of TC dynamics over the period are needed to confirm.

54 ENVIRONMENTAL SCIENCES↗

An increase in marine heatwaves without significant changes in surface ocean temperature variability

Marine heatwaves (MHWs)—extremely warm, persistent sea surface temperature (SST) anomalies causing substantial ecological and economic consequences—have increased worldwide in recent decades. Concurrent increases in global temperatures suggest that climate change impacted MHW occurrences, beyond random changes arising from natural internal variability. Moreover, the long-term SST warming trend was not constant but instead had more rapid warming in recent decades. Here we show that this nonlinear trend can—on its own—appear to increase SST variance and hence MHW frequency. Using a Linear Inverse Model to separate climate change contributions to SST means and internal variability, both in observations and CMIP6 historical simulations, we find that most MHW increases resulted from regional mean climate trends that alone increased the probability of SSTs exceeding a MHW threshold. Our results suggest the need to carefully attribute global warming-induced changes in climate extremes, which may not always reflect underlying changes in variability.

54 ENVIRONMENTAL SCIENCES↗

Assessing Global Ocean Circulation Sensitivity to Changes in Antarctic Ice Discharge

The principal goal of this research is to assess how projected increases in meltwater discharge and iceberg calving from the Antarctic Ice Sheet will impact climate in the next 250 years. In short, the sensitivity of the global ocean circulation and climate, and in particular the Atlantic Meridional Overturning Circulation (AMOC), to large increases in iceberg calving and meltwater discharges to the Southern Ocean are poorly understood. The requirement to investigate this topic is heightened by growing evidence that the West Antarctic Ice Sheet (WAIS) is vulnerable to rapid retreat and collapse through marine-ice-sheet-instability (MISI) on multidecadal-to-centennial timescales. Future model simulations of the AIS show the potential for rapid ice sheet retreat in the next 50 – 300 years, with such a collapse associated with the discharge of enormous volumes of ice and meltwater to the Southern Ocean. This project uses a combination of an ice sheet/shelf model and a fully coupled (ocean-atmosphere-seaice) model (CESM 1.2) to explore the sensitive of global climate to future changes in runoff from the Antarctic continent under future greenhouse gas emissions scenarios IPCC RCP4.5 and 8.5. Overall, accounting for Antarctic meltwater reduces the projected global mean anthropogenic greenhouse warming by up to 2 deg C. during peak WAIS collapse and by ~1 deg. for most of the simulation. In addition, the increased meltwater contribution raises sub-surface ocean temperatures at the Antarctic ice sheet margin by more than 1ºC, such that the ice shelf basal melt rates increase beyond those currently projected. In contrast, the model predicts a strong cooling of both the surface air and ocean temperatures over the Southern Ocean that results in a massive expansion and thickening of the perennial sea-ice. The slow-down in anthropogenic warming also results in the onset of ice-free conditions in the Arctic being delayed in the model by several decades, and the projected slowdown in the AMOC to reduce.

58 GEOSCIENCES↗