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At least 235 records · Page 13

Modeling Profiles of Micrometeorological Variables in a Tropical Premontane Rainforest Using Multi-Layered CLM (CLM-ML)

This study updates the multi-layered Community Land Model (CLM-ml) for hillslopes and compares predictions from against observations collected in tropical montane rainforest, Costa Rica. Modifications are made in order to capture a wider array of vertical leaf area distributions, predict CO 2 profiles, account for soil respiration, and adjust wind forcings for difficult topographic settings. Test results indicate that the modified multi-layer CLM model can successfully replicate the shape of various micrometeorological profiles (humidity, CO 2 , temperature, and wind speed) under the canopy. In the single-layer models (CLM4.5 and CLM5), excessive day-to-night differences in leaf temperature and leaf wetness were originally noted, but CLM-ml significantly improved these issues, decreasing the amplitudes of diurnal cycles by 67% and 47%. Sub-canopy considerations, such as canopy shapes and turbulent transfer parameters, also played a significant role in model performance. More importantly, unlike single layer models, the results that CLM-ml produces can be compared to variables measured within the canopy to provide far more detailed diagnostic information. Further observations and model developments, aimed at reflecting surface heterogeneity, will be necessary to adequately capture the complexity and the features of the tropical montane rainforest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tropical Cyclone Frequency

Abstract The frequency with which tropical cyclones (TCs) occur controls all other aspects of tropical cyclone risk since a storm that does not occur can do no harm. Yet this frequency is poorly understood. There is no accepted theory that explains the average number of TCs that occur each year on the Earth, nor how that number will change with global warming. Arguments based on global budgets of heat or moisture do not yet appear helpful, nor does a detailed understanding of the physical processes of TC genesis. Empirical indices that predict TC frequency as a function of large‐scale environmental variables can explain some of its relative variations in space and time, but not its absolute value. Global numerical models with horizontal grid spacings on the order of 25–50 km have allowed much improved simulations of TC activity, however. Many such models project a decrease in frequency with warming, but some project an increase. Idealized simulations, including those at higher resolutions, offer promise by allowing a systematic, deductive investigation of the roles of individual environmental factors. In addition to the larger‐scale environmental modulation of genesis likelihood, precursor disturbances, or “seeds”, may exert an independent influence on TC frequency.

54 ENVIRONMENTAL SCIENCES↗

Quantifying the Effect of Climate Change on Midlatitude Subseasonal Prediction Skill Provided by the Tropics

Abstract Subseasonal timescales (∼2 weeks–2 months) are known for their lack of predictability, however, specific Earth system states known to have a strong influence on these timescales can be harnessed to improve prediction skill (known as “forecasts of opportunity”). As the climate continues warming, it is hypothesized these states may change and consequently, their importance for subseasonal prediction may also be impacted. Here, we examine changes to midlatitude subseasonal prediction skill provided by the tropics under anthropogenic warming using artificial neural networks to quantify skill. The network is tasked to predict the sign of the 500 hPa geopotential height for historical and future time periods in the Community Earth System Model Version 2 ‐ Large Ensemble across the Northern Hemisphere at a 3 week lead using tropical precipitation. We show prediction skill changes substantially in key midlatitude regions and these changes appear linked to changes in seasonal variability with the largest differences in accuracy occurring during forecasts of opportunity.

Mayer, Kirsten J.↗

Variability of Water Vapor in the Tropical Middle Atmosphere Observed From Satellites and Interpreted Using SD-WACCM Simulations

Water vapor in the middle atmosphere plays an essential role in global warming, ozone depletion, and the formation of polar stratospheric and mesospheric clouds. We show that tropical middle atmospheric water vapor simulated with the specified-dynamics version of the Whole Atmosphere Community Climate Model (SD-WACCM) is consistent with changes observed in a merged satellite data set, which encompasses the period 1993–2020. Consistent with previous work, we find no significant trend in the stratosphere in either the observations or the simulation; in the mesosphere, we find a long-term trend of 0.1 ppmv per decade, but only in the observations. We also analyze an SD-WACCM simulation for the longer period 1980–2019 to quantify the contribution of various factors to the decadal variation of middle atmospheric water vapor. Over 1980–1995, the simulated water vapor in the upper stratosphere and mesosphere, averaged zonally and over ±30° latitude, increases by 0.30 ppmv per decade due to increasing methane emissions. After 1995, a significant abrupt decrease of water vapor of 0.37 ppmv per decade and then a gradual increase of 0.33 ppmv per decade result from changes in stratospheric cold point temperature. The cold-point temperature is strongly influenced by the strength of the Brewer-Dobson circulation. The acceleration of the Brewer-Dobson circulation before about 2003 leads to a cooler tropical tropopause and a decrease of water vapor, and the deceleration thereafter leads to corresponding warming of the tropopause and an increase in water vapor.

54 ENVIRONMENTAL SCIENCES↗

Grid Spacing Sensitivities of Simulated Mid-Latitude and Tropical Mesoscale Convective Systems in the Convective Gray Zone

The main objective of this study is to observationally constrain processes in tropical and midlatitude mesoscale convective systems (MCSs), and to use these constraints for model evaluation. To accomplish this, we leverage MCS observations collected at the U.S. DOE Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in Oklahoma and ARM's mobile GoAmazon2014/15 site in Manaus, Brazil (MAO). We simulate 13 and 11 of these observed MCSs at the SGP and MAO site, respectively, using the Weather Research and Forecasting model at 12-, 4-, 2-, and 1-km horizontal grid spacing. Observations from radiosondes, surface meteorology, and radar wind profilers are used to characterize MCS properties, such as MCS timing and location, cold pools, and convective drafts, and evaluate these simulations. SGP cases are found in better agreement with observations than MAO cases, and when simulated at 2 km, outperform simulations at 1 km regarding the timing of MCS overpass and the accuracy of surface variable trends. MAO simulations suggest a consistent improvement in model accuracy with increasing model resolution in depicting the downdraft structure, the timing of MCSs, and the surface variables changes, except for the latter two metrics at 2 km. Deficiencies are still evident at km-scales, suggesting the need for higher resolution to simulate tropical MCSs. Overall, location-dependent improvements in MCS representation are obtained with the increasing model resolution, prompting the evaluation of sub-km scale simulations.

54 ENVIRONMENTAL SCIENCES↗

Exploring the Meteorological Impacts of Surface and Rooftop Heat Mitigation Strategies Over a Tropical City

Different heat mitigation technologies have been developed to improve the thermal environment in cities. However, the regional impacts of such technologies, especially in the context of a tropical city, remain unclear. The deployment of heat mitigation technologies at city-scale can change the radiation balance, advective flow, and energy balance between urban areas and the overlying atmosphere. We used the mesoscale Weather Research and Forecasting model coupled with a physically based single-layer urban canopy model to assess the impacts of five different heat mitigation technologies on surface energy balance, standard surface meteorological fields, and planetary boundary layer (PBL) dynamics for premonsoon typical hot summer days over a tropical coastal city in the month of April in 2018, 2019, and 2020. Results indicate that the regional impacts of cool materials (CMs), super-cool broadband radiative coolers, green roofs (GRs), vegetation fraction change, and a combination of CMs and GRs (i.e., “Cool city (CC)”) on the lower atmosphere are different at diurnal scale. Results showed that super-cool materials have the maximum potential of ambient temperature reduction of 1.6°C during peak hour (14:00 LT) compared to other technologies in the study. During the daytime hours, the PBL height was considerably lower than the reference scenario with no implementation of strategies by 700 m for super-cool materials and 500 m for both CMs and CC cases; however, the green roofing system underwent nominal changes over the urban area. During the nighttime hours, the PBL height increased by CMs and the CC strategies compared to the reference scenario, but minimal changes were evident for super-cool materials. The changes of temperature on the vertical profile of the heat mitigation implemented city reveal a stable PBL over the urban domain and a reduction of the vertical mixing associated with a pollution dome. This would lead to crossover phenomena above the PBL due to the decrease in vertical wind speed. Therefore, assessing the coupled regional impact of urban heat mitigation over the lower atmosphere at city-scale is urgent for sustainable urban planning.

54 ENVIRONMENTAL SCIENCES↗

Environmental Controls on MCS Lifetime Rainfall Over Tropical Oceans

Abstract Mesoscale convective systems (MCSs) contribute a majority of rainfall over tropical oceans. However, our understanding of the environmental controls on tropical oceanic MCS precipitation remains incomplete. Using 20‐year of satellite observations, reanalysis data, and MCS tracking, we found that MCSs initiating in a mesoscale environment with enhanced lower‐free‐tropospheric moisture, warmer middle troposphere, stronger low‐level ascent, and stronger deep‐layer (surface‐400 hPa) wind shear tend to produce more precipitation during their lifetimes. While most of these environmental factors are correlated with one another, the deep‐layer shear is not. A rapid pickup in MCS lifetime rainfall is found when the lower‐free‐tropospheric specific humidity exceeds 10 g kg −1 . This nonlinearity is mostly dominated by the nonlinear increase in MCS area. On the other hand, both MCS area and rain rate increase quasi‐linearly with the deep‐layer shear. The increase in rain rate is related to the enhancement of heavy precipitating convective activity with deep‐layer shear.

54 ENVIRONMENTAL SCIENCES↗

The Role of Bjerknes and Shortwave Feedbacks in the Tropical Pacific SST Response to Global Warming

Abstract The evolution of tropical sea surface temperatures (SSTs) in response to greenhouse warming is of great societal and scientific interest. Most state‐of‐the‐art climate models predict a mean “El Niño‐like” warming pattern by century‐end, characterized by greater warming over the Pacific cold tongue compared to the western warm pool. However, it is unclear which proposed mechanism dominates in this response. Here, we present partially coupled abrupt CO 2 doubling experiments in which surface wind stress and shortwave heating are overridden to values from a control simulation. Contrary to previous studies, we find that experiments with overriding of surface wind stress exhibit only 58% of the full reduction in east‐west SST contrast. When both surface wind stress and shortwave flux are overridden, only 34% of the full reduction remains, controlled by spatially‐varying evaporative cooling. These results underscore the importance of Bjerknes and shortwave feedbacks in the tropical Pacific SST response to global warming.

Geology↗

Resolving Mesoscale Convective Systems: Grid Spacing Sensitivity in the Tropics and Midlatitudes

Abstract Mesoscale convective systems (MCSs) are a critical global water cycle component and drive extreme precipitation events in tropical and midlatitude regions. However, simulating deep convection remains challenging for modern numerical weather and climate models due to the complex interactions of processes from microscales to synoptic scales. Recent models with kilometer‐scale horizontal grid spacings offer notable improvements in simulating deep convection compared to coarser‐resolution models. Still, deficiencies in representing key physical processes, such as entrainment, lead to systematic biases. Additionally, evaluating model outputs using process‐oriented observational data remain difficult. This study presents an ensemble of MCS simulations with spanning the deep convective gray zone ( from 12 km to 125 m) in the Southern Great Plains of the U.S. and the Amazon Basin. Comparing these simulations with Atmospheric Radiation Measurement (ARM) wind profiler observations, we find greater sensitivity in the Amazon Basin compared to the Great Plains. Convective drafts converge structurally at sub‐kilometer scales, but some deficiencies remain. In both regions, simulated up and downdrafts are too deep and extreme downdrafts are not strong enough. Furthermore, Amazonian updrafts are too strong. Overall, we observe higher sensitivity in the tropics, including an artificial buildup in vertical kinetic energy at scales of , suggesting a need for 250 m in this region. Nevertheless, bulk convergence—agreement of storm‐average statistics—is achievable with kilometer‐scale simulations within a 10% error margin with 1 km providing a good balance between accuracy and computational cost.

54 ENVIRONMENTAL SCIENCES↗

Depth-discrete metagenomics reveals the roles of microbes in biogeochemical cycling in the tropical freshwater Lake Tanganyika

Lake Tanganyika (LT) is the largest tropical freshwater lake, and the largest body of anoxic freshwater on Earth’s surface. LT’s mixed oxygenated surface waters float atop a permanently anoxic layer and host rich animal biodiversity. However, little is known about microorganisms inhabiting LT’s 1470 meter deep water column and their contributions to nutrient cycling, which affect ecosystem-level function and productivity. Here, we applied genome-resolved metagenomics and environmental analyses to link specific taxa to key biogeochemical processes across a vertical depth gradient in LT. We reconstructed 523 unique metagenome-assembled genomes (MAGs) from 34 bacterial and archaeal phyla, including many rarely observed in freshwater lakes. We identified sharp contrasts in community composition and metabolic potential with an abundance of typical freshwater taxa in oxygenated mixed upper layers, and Archaea and uncultured Candidate Phyla in deep anoxic waters. Genomic capacity for nitrogen and sulfur cycling was abundant in MAGs recovered from anoxic waters, highlighting microbial contributions to the productive surface layers via recycling of upwelled nutrients, and greenhouse gases such as nitrous oxide. Overall, our study provides a blueprint for incorporation of aquatic microbial genomics in the representation of tropical freshwater lakes, especially in the context of ongoing climate change, which is predicted to bring increased stratification and anoxia to freshwater lakes.

59 BASIC BIOLOGICAL SCIENCES↗

Hot season gets hotter due to rainfall delay over tropical land in a warming climate

Tropical land generally experiences the hottest period (spring) in a year just before the onset of wet season. Previous studies suggested that in a warming climate, the wet season would come later, but its origin is debated and its impact on temperature remains unknown. Here, we find that the warming of hot season would be amplified under global warming, and refer to it as “hot-season-gets-hotter” phenomenon. The amplified hot season warming is closely tied to the amplified warming of hot temperature percentiles. The hot-season-gets-hotter phenomenon is mainly due to the rainfall delay and most evident in the Amazon, where spring is warming by almost 1?K more than the annual mean and the 99th percentile temperatures are warming ~30% more than the mean by the end of 21st century in a high emission scenario. Comparing experiments with and without land-atmosphere coupling, it is further found that the rainfall delay is initially driven by the enhanced effective atmospheric heat capacity and then substantially amplified by positive soil moisture-atmosphere feedback. In the satellite period, observations consistently show that the hot-season-gets-hotter phenomenon has already emerged along with the rainfall delay in the Amazon. Intensified hot and dry spring climate can enhance risks of drought, heatwaves and wildfires, threatening the Amazon forest and habitats in the tropics.

54 ENVIRONMENTAL SCIENCES↗

A North Atlantic synthetic tropical cyclone track, intensity, and rainfall dataset

Tropical Cyclones (TCs) cause significant socio-economic damages to the US and Caribbean coastal regions annually, making it important to understand TC risk at the local-to-regional scales. However, the short length of the observed record and the substantial computational expense associated with high-resolution climate models make it difficult to assess TC risk using either approach. To overcome these challenges, we developed a database of synthetic TCs using the Risk Analysis Framework for Tropical Cyclones (RAFT). The database includes 40,000 synthetic TC tracks, along-track intensities and storm-induced precipitation. TC tracks generated in RAFT are in reasonable agreement with the observed spatial distribution of TC tracks and basin-scale TC statistics. Specifically, along the coast, spatial variations in TC crossing probability and extreme winds upon landfall are well-reproduced by RAFT with R-squared values of 0.81 and 0.73, respectively. In summary, the synthetic TC database constructed with RAFT provides a reasonable pathway for the robust assessment of North Atlantic TC wind and rainfall risks.

54 ENVIRONMENTAL 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↗

Regime shifts of the wet and dry seasons in the tropics under global warming

The main seasonal characteristics in the tropics include both spatial patterns and temporal parameters of onset, cessation, duration, and the number of wet and dry seasons. Previous studies showed that wet seasons shortened and dry seasons extended with global warming, but the changes in spatial distribution and the number of wet and dry seasons are still unclear. Here, we analyze the climatic characteristics of once wet and dry season a year (annual regime) and twice wet and dry seasons a year (biannual regime), and find that regimes of wet and dry seasons have changed from 1935 to 2014. Across the equator and the Tropic of Cancer and Capricorn, some regions where there used to be an annual regime have become a biannual regime; instead, other regions have shifted from a biannual regime into an annual regime. With seasonal regimes shifting, areas of the biannual regime have expanded at a rate of 31 000 km 2 /decade. Meanwhile, in annual regime regions, wet seasons have been shortened in 60.3% of regions, with an average of 7 d; the onset dates of wet seasons have been delayed in 64.8%, with an average of 6 d. Besides, wet seasons have become wetter in 51.1% of regions, and dry seasons have become drier in 59.9%. In biannual regime regions, the shortened wet seasons have occurred in 83.7% of regions, with an average shortening of 8 d, and precipitation has decreased in both wet and dry seasons. Moreover, the shorter wet seasons will amplify further by the end of the 21st century. The continuous seasonal changes will threaten agricultural, ecological security, and even human well-being.

54 ENVIRONMENTAL SCIENCES↗

Can socio-economic indicators of vulnerability help predict spatial variations in the duration and severity of power outages due to tropical cyclones?

Abstract Tropical cyclones are the leading cause of major power outages in the U.S., and their effects can be devastating for communities. However, few studies have holistically examined the degree to which socio-economic variables can explain spatial variations in disruptions and reveal potential inequities thereof. Here, we apply machine learning techniques to analyze 20 tropical cyclones and predict county-level outage duration and percentage of customers losing power using a comprehensive set of weather, environmental, and socio-economic factors. Our models are able to accurately predict these outage response variables, but after controlling for the effects of weather conditions and environmental factors in the models, we find the effects of socio-economic variables to be largely immaterial. However, county-level data could be overlooking effects of socio-economic disparities taking place at more granular spatial scales, and we must remain aware of the fact that when faced with similar outage events, socio-economically vulnerable communities will still find it more difficult to cope with disruptions compared to less vulnerable ones.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Characterizing Uncertainty in Synthetic Tropical Cyclone Hazard Models for U.S. Energy Infrastructure Resilience

Tropical Cyclones (TCs) are intense storms that pose a persistent and considerable risk to coastal communities and infrastructure in the global tropics and subtropics, including the United States (US). With known limitations associated with observations and high-resolution earth system models, synthetic TC models that capture a wide spectrum of storm possibilities have been developed to robustly quantify TC risk. Here we examine the simulation of various TC features in the North Atlantic relevant for US coastal risk in three synthetic TC models forced with ERA5 reanalysis: MIT, CHAZ and RAFT. While there is a broad agreement among these models in terms of their representation of salient TC characteristics, certain differences do exist. To connect these modeling uncertainties with energy infrastructure resilience, we apply fragility curves that link simulated TC intensities to damage probabilities, demonstrating how uncertainty in storm states may translate into that in coastal impacts. Our study indicates that acknowledging and accounting for inter-model uncertainty leads to more reliable risk assessments, strengthening science-to-action pathways for managing risks associated with TCs.

Baby John, Effy↗

Tropical Indian Ocean drives Hadley circulation change in a warming climate

ABSTRACT The weakening and poleward expansion of the Hadley circulation (HC) are considered robust responses of atmospheric meridional circulation to anthropogenic warming. Climate impacts arising from these changes enhance drought conditions and reduce food production in the affected regions. Therefore, understanding the mechanisms of HC changes is critical to anticipating the resultant climate risks. First, we demonstrate that robust future HC changes in boreal winter, and the uncertainty in their future projections, are both largely related to sea surface temperature (SST) warming. Next, we investigate the impact of anthropogenic regional ocean warming on the future HC. Accordingly, we conduct a large ensemble of individual ocean basin perturbation experiments at 1.5°C, 2°C, and 3°C warming thresholds (as in the Paris Agreement). These experiments highlight (i) the leading role of tropical Indian Ocean warming in HC changes and (ii) inter-model differences in tropical Pacific warming as a source of uncertainty in HC projections.

Sun, Yong (ORCID:0000000210876060)↗

The effect of relative humidity and temperature on the response of stomatal conductance to vapor pressure deficit in tropical trees

Understanding how leaf gas exchange responds to changes in vapor pressure deficit (VPD) is key to predicting tropical forest resilience to climate change. Stomata regulate leaf water and CO2 diffusion, and respond to changes in temperature and relative humidity (RH), two drivers of VPD. At high temperatures, the cuticular pathway may also become significant and participate in the overall leaf conductance. Here, we measured gas exchange under light and dark conditions to investigate the stomatal and cuticular responses to temperature and RH on detached branches in five tropical tree species. Leaf conductance in the dark, when stomata are essentially closed, was not markedly impacted by temperature and RH, suggesting a minimal response of the cuticular pathway to these conditions. We compared six steady-state conductance models incorporating different effects of photosynthesis and evaporative demand on stomatal control. All models performed well (residual standard deviation, σ, < 0.025 mol m-2 s-1), but the best-fitting model (σ = 0.017 mol m-2 s-1) used a nonlinear relationship between photosynthesis and stomatal conductance and incorporated RH rather than vapor pressure difference. All models overestimated the steady-state conductance at high RH. Furthermore, leaf conductance immediately increased after a decrease in RH (wrong-way response), but not after an increase in leaf temperature. This suggests that the mechanisms underlying stomatal response to VPD need further investigation. The non-linear coupling between photosynthetic rate and stomatal conductance indicates a sharper physiological response than previously acknowledged.

Lamour, Julien↗