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105 records · Page 6

Synergy Between Land Use and Climate Change Increases Future Fire Risk in Amazon Forests

Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climate-driven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactions between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change – Representative Concentration Pathway (RCP) 8.5 – projected understory fires increase in frequency and duration, burning 4–28 times more forest in 2080–2100 than during 1990–2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9–5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.

Le Page, Yannick↗

Retrospective on decadal progress of the NOAA/NPS ocean noise reference station network

The National Oceanic and Atmospheric Administration (NOAA), in partnership with the U.S. National Park Service (NPS), established the Ocean Noise Reference Station Network (NRS) in 2014 as a foundational component of NOAA’s Ocean Noise Strategy. This long-term effort aims to characterize baseline ocean ambient sound conditions across diverse marine environments and to inform management of noise impacts on protected species and habitats within U.S. waters. The NRS is now composed of 13 autonomous passive acoustic monitoring stations strategically positioned across the U.S. Exclusive Economic Zone (EEZ), extending from Arctic regions to tropical waters in depths ranging from 33 to 4,790 m. These locations include several National Marine Sanctuaries and National Parks, such as the recently designated Chumash Heritage National Marine Sanctuary off the coast of California. Each station is equipped to continuously sample low-frequency underwater sound at five kHz, enabling the detection of anthropogenic, geophysical, and biological acoustic signals. To date the network has sampled over 72 years of calibrated acoustic data. The spatial breadth and consistent methodology of the NRS allow for comparative acoustic assessments across diverse marine ecosystems. In addition to applied research functions, the NRS has served as a platform for education and training, offering opportunities for students to develop skills for marine science and data analysis. Looking forward, the NRS project team is focused on network expansion, improved data delivery, and broader integration with collaborative scientific initiatives. NRS recordings are being archived in partnership with NOAA’s National Centers for Environmental Information to enhance accessibility and long-term utility. Efforts are underway to develop standardized metadata and summary products to accompany raw audio files, making the data more usable for a wide range of stakeholders in the ocean science community. The NRS is evolving into a fully integrated national framework for ocean sound monitoring that supports scientific inquiry, management decision-making, national security interests, and public engagement with ocean acoustic environments.

Long-term monitoring↗

Tropical Cyclones Feed More Heavy Rain in a Warmer Climate

The possible linkage of tropical cyclones (TC) to global warming is a hotly debated scientific topic, with immense societal impacts. Most of the debate has been focused on the issue of uncertainty in the use of non-research quality data for long-term trend analyses, especially with regard to TC intensity provided by TC forecasting centers. On the other hand, it is well known that TCs are associated with heavy rain during the processes of genesis and intensification, and that there are growing evidences that rainfall characteristics (not total rainfall) are most likely to be affected by global warming. Yet, satellite rainfall data have not been exploited in any recent studies of linkage between tropical cyclones (TC) and global warming. This is mostly due to the large uncertainties associated with detection of long-term trend in satellite rainfall estimates over the ocean. This problem, as we demonstrate in this paper, can be alleviated by examining rainfall distribution, rather than rainfall total. This paper is the first to use research-quality, satellite-derived rainfall from TRMM and GPCP over the tropical oceans to estimate shift in rainfall distribution during the TC season, and its relationships with TCs, and sea surface temperature (SST) in the two major ocean basins, the northern Atlantic and the northern Pacific for 1979-2005. From the rainfall distribution, we derive the TC contributions to rainfall in various extreme rainfall categories as a function to time. Our results show a definitive trend indicating that TCs are contributing increasingly to heavier rain events, i.e., intense TC's are more frequent in the last 27 years. The TC contribution to top 5% heavy rain has nearly doubled in the last two decades in the North Atlantic, and has increased by about 10% in the North Pacific. The different rate of increase in TC contribution to heavy rain may be related to the different rates of different rate of expansion of the warm pool (SST >2S0 C) area in the two oceans.

Lau, K.-M.↗

Managing Fire Risk During Drought: The Influence of Certification and El Nino on Fire-Driven Forest Conversion for Oil Palm in Southeast Asia

Indonesia and Malaysia have emerged as leading producers of palm oil in the past several decades, expanding production through the conversion of tropical forests to industrial plantations. Efforts to produce "sustainable" palm oil, including certification by the Roundtable on Sustainable Palm Oil (RSPO), include guidelines designed to reduce the environmental impact of palm oil production. Fire-driven deforestation is prohibited by law in both countries and a stipulation of RSPO certification, yet the degree of environmental compliance isunclear, especially during El Niño events when drought conditions increase fire risk. Here, we used time series of satellite data to estimate the spatial and temporal patterns of fire-driven deforestation on and around oil palm plantations. In Indonesia, fire-driven deforestation accounted for one-quarter of total forest losses on both certified and noncertified plantations. After the first plantations in Indonesia received RSPO certification in 2009,forest loss and fire-driven deforestation declined on certified plantations but did not stop altogether. Oil palm expansion in Malaysia rarely involved fire; only 5 % of forest loss on certified plantations had coincident activefire detections. Interannual variability in fire detections was strongly influenced by El Nino and the timing of certification. Fire activity during the 2002, 2004, and 2006 El Nino events was similar among oil palm plantations in Indonesia that would later become certified, noncertified plantations, and surrounding areas. However, total fire activity was 75% and 66% lower on certified plantations than noncertified plantations during the 2009 and 2015 El Nino events, respectively. The decline in fire activity on certified plantations, including during drought periods, highlights the potential for RSPO certification to safeguard carbon stocks in peatlands and remaining forests in accordance with legislation banning fires. However, aligning certification standards with satellite monitoring capabilities will be critical to realize sustainable palm oil production and meet industry commitments to zero forestation.

Noojipady, Praveen↗

An Analysis of Fire Dynamics Inside and Outside Indigenous Territories and Protected Areas in a Brazilian Agricultural Frontier

Sustainable land management, including protected areas, is integral to conserving tropical ecosystems and reducing carbon emissions in the Brazilian Amazon. In disturbed Amazon landscapes fire is commonly used to clear land or old fields for agriculture or pastureland. Human-set fires are the most common driver of deforestation and carbon emissions in Amazonia. Evidence suggests that indigenous groups have also used fire for land management since Pre-Columbian times. However, when used unsustainably, fires in this biome can result in degradation of forest ecosystems, decreased ability to store carbon, and health impacts resulting from smoke and particulate matter. Due to the uptick in fire occurrences in 2019, more restrictions on fire use were implemented in 2019 and 2020. Presidential decrees 9.992/2019 and 10.424/2020 banned fire use completely for periods of 60 and 120 days respectively, except by indigenous communities or authorities. Despite these bans, fire use remained high in both years. In the state of Mato Grosso, agricultural activity and expansion influences the anthropogenic fire regime. Indigenous and protected areas cover approximately 25% of its land area.

remote sensing↗

A Tale of Two Rapidly Intensifying Supertyphoons: Hagibis (2019) and Haiyan (2013)

Devastating Japan in October 2019, Supertyphoon (STY) Hagibis was an important typhoon in the history of the Pacific. A striking feature of Hagibis was its explosive rapid intensification (RI). In 24 h, Hagibis intensified by 100 knots (kt; 1 kt ≈ 0.51 m s –1 ), making it one of the fastest-intensifying typhoons ever observed. After RI, Hagibis’s intensification stalled. Using the current typhoon intensity record holder, i.e., STY Haiyan (2013), as a benchmark, this work explores the intensity evolution differences of these two high-impact STYs. We found that the extremely high prestorm sea surface temperature reaching 30.5°C, deep/warm prestorm ocean heat content reaching 160 kJ cm –2 , fast forward storm motion of ~8 m s –1 , small during-storm ocean cooling effect of ~0.5°C, significant thunderstorm activity at its center, and rapid eyewall contraction were all important contributors to Hagibis’s impressive intensification. There was 36% more air–sea flux for Hagibis’s RI than for Haiyan’s. After its spectacular RI, Hagibis’s intensification stopped, despite favorable environments. Haiyan, by contrast, continued to intensify, reaching its record-breaking intensity of 170 kt. A key finding here is the multiple pathways that storm size affected the intensity evolution for both typhoons. After RI, Hagibis experienced a major size expansion, becoming the largest typhoon on record in the Pacific. This size enlargement, combined with a reduction in storm translational speed, induced stronger ocean cooling that reduced ocean flux and hindered intensification. Furthermore, the large storm size also contributed to slower eyewall replacement cycles (ERCs), which prolonged the negative impact of the ERC on intensification.

54 ENVIRONMENTAL SCIENCES↗

Have Tropical Cyclones Been Feeding More Extreme Rainfall?

We have conducted a study of the relationship between tropical cyclone (TC) and extreme rain events using GPCP and TRMM rainfall data, and storm track data for July through November (JASON) in the North Atlantic (NAT) and the western North Pacific (WNP). Extreme rain events are defined in terms of percentile rainrate, and TC-rain by rainfall associated with a named TC. Results show that climatologically, 8% of rain events and 17% of the total rain amount in NAT are accounted by TCs, compared to 9% of rain events and 21% of rain amount in WNP. The fractional contribution of accumulated TC-rain to total rain, Omega, increases nearly linearly as a function of rainrate. Extending the analyses using GPCP pentad data for 1979-2005, and for the post-SSM/I period (1988-2005), we find that while there is no significant trend in the total JASON rainfall over NAT or WNP, there is a positive significant trend in heavy rain over both basins for the 1979-2005 period, but not for the post-SSM/I period. Trend analyses of Omega for both periods indicate that TCs have been feeding increasingly more to rainfall extremes in NAT, where the expansion of the warm pool area can explain slight more than 50% of the change in observed trend in total TC rainfall. In WNP, trend signals for Omega are mixed, and the long-term relationship between TC rain and warm pool areas are strongly influenced by interannual and interdecadal variability.

Lau, K.-M.↗

Have Tropical Cyclones been Feeding More Extreme Rainfall?

We have conducted a study of the relationship between tropical cyclone (TC) and extreme rain events using GPCP and TRMM rainfall data ; and storm track data for July through November (JASON) in the North Atlantic (NAT) and the western North Pacific (WNP). Extreme rain events are defined in terms of percentile rainrate, and TC-gain by rainfall associated with a named TC. Results show that climatologically, 8% of rain events and 17% of the total rain amount in NAT are accounted by TCs, compared to 9% of rain events, and 21% of rain amount in WN.P. The fractional contribution of accumulated TC-rain to total rain, Omega, increases nearly linearly as a function of rainrate. Extending the analyses using GPCP pentad data for 1979-2005, and for the post-SSM/I period (1988-2005), we find that while there is no significant trend in the total JASON rainfall over NAT or WNP there is a positive significant trend in heavy rain over both basins for the 1979-2005 period, but not for the post-SSM/I period. Trend analyses of Omega for bout periods indicate that TCs have been feeding increasingly more to rainfall extremes in NAT, where the expansion of the warm pool area can explain slightly more than 50% of the change in observed trend in total TC rainfall. In. WNP, trend signals for Omega are mixed, and the loner term relationship between TC rain and warm pool area is strongly influenced by interannual and interdecadal variability.

Lau, K.-M.↗

TRMM Realtime Data Production, Transfer, and Future Plans

The Tropical Rainfall Measuring Mission, a joint US NASA and Japan NASDA mission, was launched on November 27, 1997 from Tanegashima Island, Japan on a NASDA provided H-II launch vehicle. The TRMM objectives are: to obtain and study multi-year science data sets of tropical and sub- tropical rainfall measurement; to understand how interactions between the sea, air, and land masses produce changes in global rainfall and climate; to help improve modeling of tropical rainfall processes; to test, evaluate, and improve the performance of satellite rainfall estimates measurements and techniques. The routine production and quick distribution of standard products provides an important underpinning to these objectives. The determination of standard TRMM algorithms and the requirements for routine production and distribution fall within the authority of the joint US-Japan Science Team. In April of 1998, the Joint TRMM Science team requested that TRMM data be made available in near real-time to approved international agencies and modelers. This request was an addition to the routine production of the standard TRMM data products. The science team requested that near-realtime products be as small as possible to facilitate their transfer via networks. Indeed, it was determined that only network transfer would be available. This presentation provides an overview of the type of products available from the realtime system and how the TRMM system was developed at the lowest cost in the shortest amount of time. It then describes the real-time data flow. The presentation also summarizes how the science quality of real-time data is maintained. It describes how interested groups can get access to this data and the importance of networks for the future of real-time data expansion. The presentation concludes real-time possibilities and improvements possible as part of the proposed Global Precipitation Mission. High speed network access availability is an important catalyst to real-time data flow during the proposed mission.

Stocker, Erich Franz↗

The Role of Background Meridional Moisture Gradient on the Propagation of the MJO over the Maritime Continent

This study investigates the role of the background meridional moisture gradient (MMG) on the propagation of the Madden–Julian oscillation (MJO) across the Maritime Continent (MC) region. It is found that the interannual variability of the seasonal mean MMG over the southern MC area is associated with the meridional expansion and contraction of the moist area in the vicinity of the MC. Sea surface temperature anomalies associated with relatively high and low seasonal mean MMG exhibit patterns that resemble those of El Niño–Southern Oscillation. Therefore, by contrasting the years with anomalously low and high MMG, we show that MJO propagation through the MC is enhanced (suppressed) in years with higher (lower) seasonal mean MMG, although the effect is less robust when MMG anomalies are weak. Column-integrated moisture budget analysis further shows that sufficiently large MMG anomalies affect MJO activity by modulating the meridional advection of the mean moisture via MJO wind anomalies. Our results suggest that the background moisture distribution has a strong control over the propagation characteristics of the MJO in the MC region.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An error covariance model for sea surface topography and velocity derived from TOPEX/POSEIDON altimetry

In order to facilitate the use of satellite-derived sea surface topography and velocity oceanographic models, methodology is presented for deriving the total error covariance and its geographic distribution from TOPEX/POSEIDON measurements. The model is formulated using a parametric model fit to the altimeter range observations. The topography and velocity modeled with spherical harmonic expansions whose coefficients are found through optimal adjustment to the altimeter range residuals using Bayesian statistics. All other parameters, including the orbit, geoid, surface models, and range corrections are provided as unadjusted parameters. The maximum likelihood estimates and errors are derived from the probability density function of the altimeter range residuals conditioned with a priori information. Estimates of model errors for the unadjusted parameters are obtained from the TOPEX/POSEIDON postlaunch verification results and the error covariances for the orbit and the geoid, except for the ocean tides. The error in the ocean tides is modeled, first, as the difference between two global tide models and, second, as the correction to the present tide model, the correction derived from the TOPEX/POSEIDON data. A formal error covariance propagation scheme is used to derive the total error. Our global total error estimate for the TOPEX/POSEIDON topography relative to the geoid for one 10-day period is found tio be 11 cm RMS. When the error in the geoid is removed, thereby providing an estimate of the time dependent error, the uncertainty in the topography is 3.5 cm root mean square (RMS). This level of accuracy is consistent with direct comparisons of TOPEX/POSEIDON altimeter heights with tide gauge measurements at 28 stations. In addition, the error correlation length scales are derived globally in both east-west and north-south directions, which should prove useful for data assimilation. The largest error correlation length scales are found in the tropics. Errors in the velocity field are smallest in midlatitude regions. For both variables the largest errors caused by uncertainty in the geoid. More accurate representations of the geoid await a dedicated geopotential satellite mission. Substantial improvements in the accuracy of ocean tide models are expected in the very near future from research with TOPEX/POSEIDON data.

Tsaoussi, Lucia S.↗

Envisioning urban environments resilient to vector-borne diseases: a protocol to study dengue in Vietnam

Transmitted primarily by Aedes aegypti (Ae. aegypti) and Aedes albopictus (Ae. albopictus), arboviral diseases pose a major global public health threat. Dengue, chikungunya, and zika are increasingly prevalent in Southeast Asia. Among other arboviruses, dengue and zika are becoming more common in Central and South America. Given human encroachment into previously uninhabited, often deforested areas, to provide new housing in regions of population expansion, conceptualizing built urban environments in a novel way is urgently needed to safeguard against the growing climate change-driven threat of vector-borne diseases. By understanding the spread from a One Health perspective, enhanced control and prevention can be achieved. This is particularly important considering that climate change is likely to significantly impact the persistence of ponded water where mosquitoes breed due to increasing temperature and shifting rainfall patterns with regard to magnitude, duration, frequency, and season. Models can incorporate aquatic mosquito stages and adult spatial dynamics when habitats are heterogeneously available, thereby including dispersal and susceptible-exposed-infected-recovered (SEIR) epidemiology. Coupled with human population distribution (density, locations), atmospheric conditions (air temperature, precipitation), and hydrological conditions (soil moisture distribution, ponding persistence in topographic depressions), modeling has improved predictive ability for infection rates. However, it has not informed interventional approaches from an urban environment perspective which considers the role of ponds/lakes that support green spaces, the density of population that enables rapid spread of disease, and varying micro-habitats for various mosquito stages under climate change. Here, for an example of dengue in Vietnam, a preventive and predictive approach to design resilient urban environments is proposed, which uses data from rapidly expanding metropolitan communities to learn continually. This protocol deploys computational approaches including simulation and machine learning/artificial intelligence, underpinned by surveillance and medical data for validation and adaptive learning. Its application may best inform urban planning in low-middle income countries in tropical zones where arboviral pathogens are prevalent.

60 APPLIED LIFE SCIENCES↗

Soybean rust‐resistant and tolerant varieties identified through the Pan‐African Trial Network

Abstract BACKGROUND The global demand for soybeans is increasing rapidly, with projections indicating an escalation of 70–80 million metric tons over the next decade. Sub‐Saharan Africa (SSA) contributes significantly to this growth, with soybean production increasing by 6.8% per year, outpacing the global average increase of 4.7%. Despite the expansion, soybean productivity in Africa remains less than half of the global average. This yield gap is largely due to diseases and pests, such as soybean rust, which can be particularly severe. Effective management of soybean rust depends on several factors, including resistant cultivars. However, there has been limited information on the rust‐resistance levels of African cultivars. To address this gap, the Pan‐African Trial network conducted soybean varietal trials across diverse locations. RESULT Analyzing data from 370 individual trials conducted between 2015–2022, the network identified 81 cultivars with sufficient rust‐resistance data. Six cultivars including, Black Hawk, Dundee, Egret, Heron, Ibis, and Peka 06 were found to be resistant, and 12 were classified as tolerant. CONCLUSION This research is a significant step forward in improving soybean productivity in Africa, and further assessments are being undertaken to address other crop production challenges in the region. © 2025 Society of Chemical Industry.

Favoretto, Vitor Rampazzo [Cenex Harvest States (C↗

Terrestrial Waters and Sea Level Variations on Interannual Time Scale

On decadal to multi-decadal time scales, thermal expansion of sea waters and land ice loss are the main contributors to sea level variations. However, modification of the terrestrial water cycle due to climate variability and direct anthropogenic forcing may also affect sea level. For the past decades, variations in land water storage and corresponding effects on sea level cannot be directly estimated from observations because these are almost non-existent at global continental scale. However, global hydrological models developed for atmospheric and climatic studies can be used for estimating total water storage. For the recent years (since mid-2002), terrestrial water storage change can be directly estimated from observations of the GRACE space gravimetry mission. In this study, we analyse the interannual variability of total land water storage, and investigate its contribution to mean sea level variability at interannual time scale. We consider three different periods that, each, depend on data availability: (1) GRACE era (2003-2009), (2) 1993-2003 and (3) 1955-1995. For the GRACE era (period 1), change in land water storage is estimated using different GRACE products over the 33 largest river basins worldwide. For periods 2 and 3, we use outputs from the ISBA-TRIP (Interactions between Soil, Biosphere, and Atmosphere-Total Runoff Integrating Pathways) global hydrological model. For each time span, we compare change in land water storage (expressed in sea level equivalent) to observed mean sea level, either from satellite altimetry (periods 1 and 2) or tide gauge records (period 3). For each data set and each time span, a trend has been removed as we focus on the interannual variability. We show that whatever the period considered, interannual variability of the mean sea level is essentially explained by interannual fluctuations in land water storage, with the largest contributions arising from tropical river basins.

Llovel, W.↗

Monthly averages of ED2 model simulations initialized with airborne lidar structure, Jan 1981-Dec 2018, Brazilian Amazon

Deforestation and forest degradation (selective logging, fires, fragmentation) have impacted nearly 40% of the original extent of the Brazilian Amazon, and have markedly impacted forest structure across the region. To date, few studies analysed how shifts in forest structure from degradation influence the forest sensitivity to climate extremes, because of the complex interactions between forest structure and micro-environmental conditions. To address this knowledge gap, we carried out a series of simulations across the Brazilian Amazon using the Ecosystem Demography Model (ED2), using observed forest structure derived from 541 airborne lidar transects (375 ha each) and two scenarios representing forest recovery and expansion of degradation to investigate how shifts in forest structure impact ecosystem function under near-average and extreme climate conditions, as part of the manuscript Longo et al 2025 "Degradation and Deforestation Increase the Sensitivity of the Amazon Forest to Climate Extremes". This dataset provides the output results from the ED2 model simulations for the three simulations at monthly time scales, in NetCDF format. For all simulations, we used bias-corrected hourly reanalyses (WFDE5) for most meteorological drivers, except for precipitation, which was obtained from CHIRPS. The meteorological drivers used in the study span 38 years (Jan 1981–Dec 2018). The output results correspond to the last 38 years of simulation (one full cycle of meteorological drivers), in which ED2 simulations used static stand structure (i.e., the forest structure was held constant). The following files are provided:ED2_emean_Global_R004_BrAmaz_s1c0t0l0f0.nc. This corresponds to the Control simulation. The forest structure was obtained from the airborne lidar.ED2_emean_Global_R005_BrAmaz_s1c0t1l1f0.nc. This corresponds to the Degraded simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that expanded deforestation and selective logging across the Amazon.ED2_emean_Global_R006_BrAmaz_s1c0t1l0f0.nc. This corresponds to the Recovery simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that completely halted deforestation and degradation, allowing degraded forests to recover for 38 years.We also provide file ED2_zones_R004_BrAmaz_s1c0t0l0f0.nc, which classifies each grid cell into zones used in the reference manuscript: 1: Southeast. 2: South. 3: West. 4: Central. 5: Northeast. 6: North. 7: Northwest". Index 0 corresponds to grid cells excluded from sub-region analyses because they were dominated by flooded forests, deforestation, and naturally non-forest vegetation.

54 ENVIRONMENTAL SCIENCES↗