Quasi-biennial variation of cosmic rays
Quasi-biennial cosmic rays in tropical region estimated from results of meteorological investigation
COSMIC RADIATION↗
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Analysis of Integrated Vapor Transport Biases
Abstract High-fidelity analyses and forecasts of integrated vapor transport (VT) are central to the study of Earth’s hydrological cycle as well as high-impact phenomena such as monsoons and atmospheric rivers. The impact of the in-line analysis correction-based additive inflation (ACAI) on IVT biases and forecast errors is examined within the Navy Earth System Prediction Capability (Navy ESPC) global coupled system. The ACAI technique uses atmospheric analysis corrections from the data assimilation system to approximate model bias and as a representation of stochastic model error to simultaneously reduce systematic and random errors and improve ensemble performance. ACAI reduces the global average magnitude of the 7- and 14-day IVT bias by 16%–17% during Northern Hemisphere summer, reaching 70% reductions in some tropical regions. The global average IVT bias reduction is similar to the bias reduction for low-level wind speed bias and considerably smaller than the bias reduction in total precipitable water. The localized regions where ACAI increases IVT bias occur where the control IVT biases change sign and structure with increasing forecast lead time, such as the South Asian monsoon region. Substituting analyzed wind or moisture fields for the forecast fields when calculating the forecast IVT confirms that, on average, wind errors dominate the IVT error calculation in the tropics, although wind and moisture error contributions are comparable in the extratropics. The existence of regions where using either analyzed winds or analyzed moisture increases IVT bias or mean absolute error reveals areas with compensating errors.
Reynolds, Carolyn A.↗
Effect of Aerosols on Cloud Field with Satellite-Derived Data and GCM Simulation
Numerical experiment was performed using an general circulation model (GCM) including aerosol indirect effect into water cloud and the simulated global distribution of cloud droplet radii was compared with the global distribution of cloud effective radii retrieved from Advanced Very High Resolution Radiometer (AVHRR). Comparisons of GCM calculation with AVHRR retrieval showed that our GCM generally can simulate the global characteristics of cloud droplet radii such as a land-sea contrast associated with difference of aerosol abundance and coastal region feature due to aerosol injection from adjacent continental area. AVHRR retrieval and GCM simulation, however, are turned out to show disagreement over tropical region. AVHRR retrieval may tend to overestimate droplet radii due to the contamination of signal by drizzles and ice particles, whereas our GCM does not treat aerosol indirect effect in deep convective clouds predominant over tropics. Over equatorial central Pacific, where satellite retrieval may suffer from statistical biases, satellite retrieval and GCM simulation are also found to be different. Keywords: aerosol indirect effect
Suzuki, Kentaroh↗
Uncertainties in estimating global potential yields and their impacts for long-term modeling
Estimating realistic potential yields by crop type and region is challenging; such yields depend on both biophysical characteristics (e.g., soil characteristics, climate, etc.), and the crop management practices available in any site or region (e.g., mechanization, irrigation, crop cultivars). A broad body of literature has assessed potential yields for selected crops and regions, using several strategies. In this study we first analyze future potential yields of major crop types globally by two different estimation methods, one of which is based on historical observed yields (“Empirical”), while the other is based on biophysical conditions (“Simulated”). Potential yields by major crop and region are quite different between the two methods; in particular, Simulated potential yields are typically 200% higher than Empirical potential yields in tropical regions for major crops. Applying both of these potential yields in yield gap closure scenarios in a global agro-economic model, GCAM, the two estimates of future potential yields lead to very different outcomes for the agricultural sector globally. In the Simulated potential yield closure scenario, Africa, Asia, and South America see comparatively favorable outcomes for agricultural sustainability over time: low land use change emissions, low crop prices, and high levels of self-sufficiency. In contrast, the Empirical potential yield scenario is characterized by a heavy reliance on production and exports in temperate regions that currently practice industrial agriculture. At the global level, this scenario has comparatively high crop commodity prices, and more land allocated to crop production (and associated land use change emissions) than either the baseline or Simulated potential yield scenarios. This study highlights the importance of the choice of methods of estimating potential yields for agro-economic modeling.
60 APPLIED LIFE SCIENCES↗
Limits to forests-based mitigation in integrated assessment modelling: global potentials and impacts under constraining factors
Forests-based measures such as afforestation/reforestation (A/R) and reducing deforestation (RDF) are considered promising options to mitigate climate change, yet their mitigation potentials are limited by economic and biophysical factors that are largely uncertain. The range of mitigation potential estimates from integrated assessment models raises concerns about the capacity of land systems to provide realistic, cost-effective and permanent land-based mitigation. We use the Global Change Analysis Model to quantify the economic mitigation potential of forests-based measures by simulating a climate policy including a tax on greenhouse gas emissions from agriculture, forestry, and other land uses. In addition, we assess how constraining unused arable land (UAL) availability, forestland expansion rates, and global bioenergy demand may influence the forests-based mitigation potential by simulating scenarios with alternative combinations of constraints. Results show that the average forests-based mitigation potential in 2020–2050 increases from 738 MtCO 2 .yr -1 through a forestland increase of 86 Mha in the fully constrained scenario to 1394 MtCO 2 .yr -1 through a forestland increase of 146 Mha when all constraints are relaxed. Regional potentials in terms of A/R and RDF differ strongly between scenarios: unconstrained forest expansion rates mostly increase A/R potentials in northern regions (e.g., +120 MtCO 2 .yr -1 in North America); while unconstrained UAL conversion and low bioenergy demand mostly increase RDF potentials in tropical regions (e.g., +76 and +68 MtCO 2 .yr -1 in Southeast Asia, respectively). This study shows that forests-based mitigation is limited by many factors that constrain the rates of land use change across regions. These factors, often overlooked in modelling exercises, should be carefully addressed for understanding the role of forests in global climate mitigation and defining pledges towards the Paris Agreement.
54 ENVIRONMENTAL SCIENCES↗
Quantification and Mitigation of Long-Term Impacts of Urbanization and Climate Change in the Tropical Coastal City of San Juan, Puerto Rico
Urbanization, along with other cases of land cover and land use changes, has significant climate impacts in tropical regions with the added complexity of occurring within the context of global warming. The individual and combined effects of these two factors on the surface energy balance of a tropical city are investigated by use of an integrated atmospheric modeling approach, taking the San Juan Metropolitan Area (SJMA), Puerto Rico as the test case. To achieve this goal, an ensemble of climate and weather simulations is performed, with the climate scenarios combining urban development and sprawl with regional climate change over the past 50 years, and the short-term simulations designed to test the sensitivity to different urban vegetation configurations as mitigating alternatives. As indicator of change, we use the thermal response number (TRN), which is a measure of the sensible heating to the thermal storage of a surface or region, and the Bowen ratio, which is defined as the ratio of sensible to latent heat fluxes. The TRN of the area occupied by the SJMA has decreased as a consequence of replacing the low land coastal plain vegetation with man made materials, indicating that it takes less energy to raise the surface temperature of the urban area, whereas the TRN of forested regions has remained virtually unchanged. The global warming signal also has effects on the thermal response of the SJMA, where dryer current conditions generate lower TRN values. Differences due to global warming are more evident in the Bowen ratio pattern, mostly associated with the drier present conditions observed and its effects on sensible and latent heat fluxes. In terms of testing different mitigation strategies, the short-term simulations show that the urban area is more efficient in partitioning surface energy balance terms when green roofs are specified, as opposed to including vegetation inside the urban core.
Comarazamy, Daniel↗
Vertical canopy gradients of respiration drive plant carbon budgets and leaf area index
Despite its importance for determining global carbon fluxes, leaf respiration remains poorly constrained in land surface models (LSMs). We tested the sensitivity of the Energy Exascale Earth System Model Land Model – Functionally Assembled Terrestrial Ecosystem Simulator (ELM-FATES) to variation in the canopy gradients of leaf maintenance respiration (R dark ). We ran global and point simulations varying the canopy gradient of R dark to explore the impacts on forest structure, composition, and carbon cycling. In global simulations, steeper canopy gradients of R dark lead to increased understory survival and leaf biomass. Leaf area index (LAI) increased up to 77% in tropical regions compared with the default parameterization, improving alignment with remotely sensed benchmarks. Global vegetation carbon varied from 308 Pg C to 449 Pg C across the ensemble. In tropical forest simulations, steeper gradients of R dark had a large impact on successional dynamics. Results show the importance of canopy gradients in leaf traits and fluxes for determining plant carbon budgets and emergent ecosystem properties such as competitive dynamics, LAI, and vegetation carbon. The high-model sensitivity to canopy gradients in R dark highlights the need for more observations of how leaf traits and fluxes vary along light micro-environments to inform critical dynamics in LSMs.
59 BASIC BIOLOGICAL SCIENCES↗
Microbial community data from throughfall exclusion experiment: Metadata, SI, community composition, LefSe, and FunGuilR data tables from PARCHED Panama tropical forest soils, 2024-2025
Soil contains more carbon (C) than terrestrial vegetation and the atmosphere combined, with some of the largest terrestrial C stocks in tropical rainforests. Soil microbes decompose organic matter, playing a vital role in the storage or loss of soil C. With climate change, drought conditions are predicted to increase in many tropical regions, including both chronic drying and extended drought, potentially influencing these processes. This project explored the effects of chronic and seasonal drying on soil microbial communities across four distinct tropical forests in a long-term drying experiment. We investigated the effects of a chronic drying manipulation on soil microbial community abundance and variation across different forests and seasons. We also compared findings with previously published data from these forests after short-term drying. This project used soils from a long-term drying experiment established in 2018 across four seasonal lowland forests in Panama. Soils were collected from 0 – 10 cm depths during three seasonal periods in control and drying plots in 2024 and 2025 from a total of 32 plots (n = 4 per forest per treatment). The forests varied in baseline rainfall and soil fertility. We calculated alpha and beta diversity indices and compared taxonomic community composition. We found significant biogeographic variation in microbial diversity and taxonomy, with significant differences across the forests and significant effects of the drying treatment. Metadata and sample IDs are within Metadata_16S.csv and Metadata_ITS.csv. Relative abundance tables of every sample at every season are shown in the Excel workbooks 16S Relative Abundance.xlsx and ITS Relative Abundance.xlsx. They are then also shown in CSV files by each taxonomic level. Linear discriminant analysis effect size (LefSe) tables are shown for the full 16S and ITS datasets (n = 96), subsets for every site at every season (n = 8), and then for the forests with each plot merged by season (n = 8). FunGuildR data table of ITS data is uploaded.
Bacteria↗
Large Divergence in Tropical Hydrological Projections Caused by Model Spread in Vegetation Responses to Elevated CO 2
Increasing atmospheric CO 2 and associated global warming are expected to alter the global hydrological cycle, thereby posing widespread threats to freshwater availability. However, future hydrological projections differ greatly between models, particularly over the tropical regions. The large difference between model projections directly limits policy planning efforts, and the responsible modeling processes remain unclear. Here, we identify the primary processes accounting for model differences in tropical hydrological changes using multiple CO 2 sensitivity experiments in the Coupled Model Intercomparison Project. We show that differences in projected changes to tropical evapotranspiration, precipitation, and surface water availability mainly arise from model representations of vegetation cover and stomatal conductance responses to elevated CO 2 and associated changes in atmospheric moisture and circulation. Atmospheric responses to sea surface warming contribute additionally to the divergence in hydrological projections. Given the importance of vegetation responses to elevated CO 2 and associated atmosphere feedbacks, our results underscore the need to improve representations of the vegetation physiological response to rising CO 2 and its coupling to the atmosphere, to provide reliable tropical hydrological projections.
54 ENVIRONMENTAL SCIENCES↗
Seasonal, Spectral, and Regional Characterization of Deep Convective Clouds Top-of-Atmosphere Bidirectional Reflectance for Improved Satellite Intercalibration
The NASA CERES project provides the scientific community with regional broadband fluxes designed for long-term climate monitoring. The CERES climate quality dataset requires that the CERES instrument, as well as the MODIS and VIIRS imager records to be radiometrically stable over time. Deep Convective Clouds (DCCs) are spectrally uniform, near-Lambertian natural diffusers offering high signal-to-noise ratio and stable radiometric response in the VIS-NIR spectrum. For shortwave infrared (SWIR) wavelengths greater than 1.2µm, the DCC response is significantly influenced by cloud particle size and atmospheric absorption. Previous studies improved the characterization of the SWIR band DCC radiance, by using channel specific monthly empirical BRDFs as well as using the probability density function mean statistic to track the SWIR band stability. Also, that the DCC radiance is greater over land than over ocean and that the TWP DCC radiance has the lowest tropical DCC radiance. This study confirms and improves upon the previous studies. The study stratified the tropics regionally into land and ocean domains and applied their respective ocean-only and land-only empirical monthly BRDFs and normalized the land DCC BRDF corrected radiances with their ocean counterpart. This approach provided the most stable DCC response. The DCC BRDF corrected radiance monthly standard error was 0.24%, 0.62%, 0.59%, and 0.43% for the 1.24µm, 1.37µm, 1.61µm, and 2.25µm SWIR bands, which reduced the standard error 20%, 13%, 24%, and 26%, respectively when compared with the all-surface approach. The same approach was attempted over the Tropical Western Pacific and found not to be an improvement over the tropical domain. Further stratification of the tropical domain will need to balance sufficient sampling while accounting for regional DCC radiance differences.
Prathana Khakurel↗
Two Years of Simultaneous K(sub a)-Band Measurements: Goldstone, CA; White Sands, NM; and Guam, USA
In order to statistically characterize the effect of the Earth's atmosphere on Ka-Band links, site test interferometers (STIs) have been deployed at three of NASA s operational sites to directly measure each site's tropospheric phase stability and rain attenuation. These STIs are composed of two antennas on a short baseline (less than 1km) that observe the same unmodulated beacon signal broadcast from a geostationary satellite (e.g., Anik F2). The STIs are used to measure the differential phase between the two received signals as well as the individual signal attenuation at each terminal. There are currently three NASA sites utilizing STIs; the Goldstone Deep Space Communications Complex near Barstow, California; the White Sands Complex in Las Cruces, New Mexico; and the Guam Remote Ground Terminal on the island of Guam. The first two sites are both located in desert regions that have highly similar climates in terms of their seasonal temperatures, average humidity, and annual rain fall (the primary factors in determining phase stability). In contrast, Guam is in a tropical region with drastically higher annual rainfall and humidity. Five station years of data have been collected in Goldstone, three in White Sands, and two in Guam, yielding two years of simultaneous data collection across all three sites. During this period of simultaneous data collection, the root-mean-square (RMS) of the time delay fluctuations stayed under 2.40 picoseconds for 90% of the time in Goldstone, under 2.07 picoseconds for 90% of the time in White Sands, and under 10.13 picoseconds for 90% of the time in Guam. For the 99th percentile, the statistics were 6.32 ps, 6.03 ps, and 24.85 ps, respectively. These values, as well as various other site quality characteristics, will be used to determine the suitability of these sites for NASA s future communication services at Ka-Band.
Acosta, Roberto J.↗
Periodic and aperiodic ozone variations in the middle and upper stratosphere
Umkehr, ozonesonde and satellite observations are used to determine the height/latitude distribution of the amplitude and phase of the periodic components of the variation in the ozone mixing ratio in the middle and upper stratosphere. The amplitude of the first (annual) harmonic is found to be small in the subtropics and to increase to a maximum at polar latitudes. In addition, it increases with height in the mid and upper stratosphere to an apparent maximum just below the stratosphere. The second (semi-annual) harmonic possesses an amplitude that is largest in tropical regions and in subpolar regions at a level of about 40 km. Very little ozone variation is seen above 30 km with dominant periods close to the quasi-biennial period of total ozone observed in the tropics. The percentage of the total variance of the ozone mixing ratio accounted for by the first harmonic is found to be larger than 60 percent at all heights from 20 deg to 60 deg latitude in both hemispheres (except near 40 km in the Northern Hemisphere).
London, J.↗
Near-term tropical cyclone risk and coupled Earth system model biases
Most current climate models predict that the equatorial Pacific will evolve under greenhouse gas–induced warming to a more El Niño-like state over the next several decades, with a reduced zonal sea surface temperature gradient and weakened atmospheric Walker circulation. Yet, observations over the last 50 y show the opposite trend, toward a more La Niña-like state. Recent research provides evidence that the discrepancy cannot be dismissed as due to internal variability but rather that the models are incorrectly simulating the equatorial Pacific response to greenhouse gas warming. This implies that projections of regional tropical cyclone activity may be incorrect as well, perhaps even in the direction of change, in ways that can be understood by analogy to historical El Niño and La Niña events: North Pacific tropical cyclone projections will be too active, North Atlantic ones not active enough, for example. Other perils, including severe convective storms and droughts, will also be projected erroneously. While it can be argued that these errors are transient, such that the models’ responses to greenhouse gases may be correct in equilibrium, the transient response is relevant for climate adaptation in the next several decades. Given the urgency of understanding regional patterns of climate risk in the near term, it would be desirable to develop projections that represent a broader range of possible future tropical Pacific warming scenarios—including some in which recent historical trends continue—even if such projections cannot currently be produced using existing coupled earth system models.
Science & Technology - Other Topics↗
A Global Methane Observation System to Reduce Uncertainty for Anthropogenic and Natural Sources and Sinks for Detecting and Attributing Climate Feedbacks
Atmospheric methane (CH4) concentrations are accelerating global warming as net emissions increase. Observing systems that quantify sources remain too sparse and fragmented to detect trends—especially in remote regions where climate‐driven natural emissions may be rising. We provide a framework for quantifying uncertainty reductions through the implementation of a global ecosystem‐methane observing system designed to: (i) substantially lower uncertainty in sectoral and regional emissions, (ii) separate co‐occurring anthropogenic and natural fluxes, and (iii) trend detection at regional scales to verify mitigation progress and provide early warning of natural feedbacks. Using bottom‐up inventories and process‐model ensembles for 2014–2023, we show that anthropogenic emissions remain uncertain by ∼32% globally, while natural sources—tropical and boreal‐arctic wetlands, fires, and inland waters—carry far larger uncertainties (+ 70%) and trend uncertainties reaching ∼200%. Additional observations must match spatial emission structure to increase observability of emissions: high‐resolution satellite constellations for point sources combined with expanded flux networks and wetland mapping for diffuse sources, and denser ground‐based atmospheric column measurements to restore observability in under‐sampled tropics and high latitudes. Notional analyses indicate that targeted additions of flux towers and ∼20 in situ atmospheric column concentration instruments per key tropical region could reduce continental‐scale uncertainties at modest cost. Conceptual illustration of a Global Ecosystem Methane Observing System (GEM‐OS) integrating satellites, aircraft, atmospheric networks, and ecosystem measurements to quantify methane emissions from anthropogenic and natural sources. The multi‐scale observing framework improves source attribution, reduces uncertainty in regional methane budgets, and enables early detection of climate‐driven feedbacks from wetlands, fires, permafrost, agriculture, and fossil‐fuel emissions.
Ciais, P↗
Scientific Impacts of Wind Direction Errors
An assessment on the scientific impact of random errors in wind direction (less than 45 deg) retrieved from space-based observations under weak wind (less than 7 m/s ) conditions was made. averages, and these weak winds cover most of the tropical, sub-tropical, and coastal oceans. Introduction of these errors in the semi-daily winds causes, on average, 5% changes of the yearly mean Ekman and Sverdrup volume transports computed directly from the winds, respectively. These poleward movements of water are the main mechanisms to redistribute heat from the warmer tropical region to the colder high- latitude regions, and they are the major manifestations of the ocean's function in modifying Earth's climate. Simulation by an ocean general circulation model shows that the wind errors introduce a 5% error in the meridional heat transport at tropical latitudes. The simulation also shows that the erroneous winds cause a pile-up of warm surface water in the eastern tropical Pacific, similar to the conditions during El Nino episode. Similar wind directional errors cause significant change in sea-surface temperature and sea-level patterns in coastal oceans in a coastal model simulation. Previous studies have shown that assimilation of scatterometer winds improves 3-5 day weather forecasts in the Southern Hemisphere. When directional information below 7 m/s was withheld, approximately 40% of the improvement was lost
Liu, W. Timothy↗
Scientific impacts of wind direction errors
An assessment on the scientific impact of random errors in wind direction (< 45°) retrieved from space-based observations under weak wind (< 7 m/s) conditions was made. Half of the winds over global oceans are below 7 m/s, in their long-term averages, and these weak winds cover most of the tropical, sub-tropical, and coastal oceans. Introduction of these errors in the semi-daily winds causes, on average, 5% changes of the yearly mean Ekman and Sverdrup volume transports computed directly from the winds, respectively. These poleward movements of water are the main mechanisms to redistribute heat from the warmer tropical region to the colder highlatitude regions, and they are the major manifestations of the ocean’s function in modifying Earth’s climate. Simulation by an ocean general circulation model shows that the wind errors introduce a 5% error in the meridional heat transport at tropical latitudes. The simulation also shows that the erroneous winds cause a pile-up of warm surface water in the eastern tropical Pacific, similar to the conditions during El Niño episode. Similar wind directional errors cause significant change in sea-surface temperature and sea-level patterns in coastal oceans in a coastal model simulation. Previous studies have shown that assimilation of scatterometer winds improves 3–5 day weather forecasts in the Southern Hemisphere. When directional information below 7 m/s was withheld, approximately 40% of the improvement was lost.
Atlas, Robert↗
El Niño Related Tropical Land Surface Water and Energy Response in MERRA-2
Though El Niño events each have distinct evolutionary character they typically provide systematic large scale forcing for warming and increased drought frequency across the tropical continents. We assess this response in the MERRA-2 reanalysis and in a ten-member model AMIP ensemble. The lagged response (3-4 months) of mean tropical land temperature to El Niño warming in the Pacific Ocean is well represented. MERRA-2 reproduces the patterns of precipitation in the tropical regions, while the AMIP ensemble reproduces some regional responses better than others. Model skill is dependent on event forcing strength and temporal proximity to the peak of the sea surface warming. A composite approach centered on maximum Niño3.4 SSTs and lag relationships to energy fluxes and transports is used to identify mechanisms supporting tropical land warming. The composite necessarily moderates weather scale variability of the individual events, while retaining the systematic features across all events. We find that that reduced continental upward motions lead to reduced cloudiness and more shortwave radiation at the surface, as well as reduced precipitation. The increased shortwave heating at the land surface, along with reduced soil moisture leads to warmer surface temperature, more sensible heating and warming of the lower troposphere. While the composite provides a broad picture of the mechanisms governing the hydrologic response to El Niño forcing, the regional and temporal response in any given event can be quite variable. The 2015-16 El Niño, one of the strongest events, demonstrates some of the forced response noted in the composite, but with shifts in the evolution that depart from the composite, demonstrating the limitations of the composite and individuality of El Niño.
Michael G Bosilovich↗
Global and regional hydrological impacts of global forest expansion
Abstract. Large-scale reforestation, afforestation, and forest restoration schemes have gained global support as climate change mitigation strategies due to their significant carbon dioxide removal (CDR) potential. However, there has been limited research into the unintended consequences of forestation from a biophysical perspective. In the Community Earth System Model version 2 (CESM2), we apply a global forestation scenario, within a Paris Agreement-compatible warming scenario, to investigate the land surface and hydroclimate response. Compared to a control scenario where land use is fixed to present-day levels, the forestation scenario is up to 2 °C cooler at low latitudes by 2100, driven by a 10 % increase in evaporative cooling in forested areas. However, afforested areas where grassland or shrubland are replaced lead to a doubling of plant water demand in some tropical regions, causing significant decreases in soil moisture (∼ 5 % globally, 5 %–10 % regionally) and water availability (∼ 10 % globally, 10 %–15 % regionally) in regions with increased forest cover. While there are some increases in low cloud and seasonal precipitation over the expanded tropical forests, with enhanced negative cloud radiative forcing, the impacts on large-scale precipitation and atmospheric circulation are limited. This contrasts with the precipitation response to simulated large-scale deforestation found in previous studies. The forestation scenario demonstrates local cooling benefits without major disruption to global hydrodynamics beyond those already projected to result from climate change, in addition to the cooling associated with CDR. However, the water demands of extensive forestation, especially afforestation, have implications for its viability, given the uncertainty in future precipitation changes.
Environmental Sciences & Ecology↗