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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Projected future daily characteristics of African precipitation based on global (CMIP5, CMIP6) and regional (CORDEX, CORDEX-CORE) climate models

In this work, we provide an assessment of future daily characteristics of African precipitation by explicitly comparing the results of large ensembles of global (CMIP5, CMIP6) and regional (CORDEX, CORE) climate models, specifically highlighting the similarities and inconsistencies between them. Results for seasonal mean precipitation are not always consistent amongst ensembles: in particular, global models tend to project a wetter future compared to regional models, especially over the Eastern Sahel, Central and East Africa. However, results for other precipitation characteristics are more consistent. In general, all ensembles project an increase in maximum precipitation intensity during the wet season over all regions and emission scenarios (except the West Sahel for CORE) and a decrease in precipitation frequency (under the Representative Concentration Pathways RCP8.5) especially over the West Sahel, the Atlas region, southern central Africa, East Africa and southern Africa. Depending on the season, the length of dry spells is projected to increase consistently by all ensembles and for most (if not all) models over southern Africa, the Ethiopian highlands and the Atlas region. Discrepancies exist between global and regional models on the projected change in precipitation characteristics over specific regions and seasons. For instance, over the Eastern Sahel in July–August most global models show an increase in precipitation frequency but regional models project a robust decrease. Global and regional models also project an opposite sign in the change of the length of dry spells. CORE results show a marked drying over the regions affected by the West Africa monsoon throughout the year, accompanied by a decrease in mean precipitation intensity between May and July that is not present in the other ensembles. This enhanced drying may be related to specific physical mechanisms that are better resolved by the higher resolution models and highlights the importance of a process-based evaluation of the mechanisms controlling precipitation over the region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Climate models project increasing precipitation in the US Southwest in 2024–2100

We analyzed the measured precipitation in the southwestern US and found that, from 1900 to 2024, precipitation decreased at an average rate of − 1.2 cm per year per 100 years. The most significant precipitation decreases occurred in the three-month period from February to April. At the same time, precipitation during the southwestern monsoon season (July, August, and September) remained relatively stable. The ensemble mean of all CMIP6 (Coupled Model Intercomparison Project phase 6) climate models, along with the regression model incorporating anthropogenic aerosol (AER) and Pacific Decadal Oscillation (PDO) as predictors, projects precipitation to increase from 2024 to 2100. This projected precipitation increase relies on the anticipated decrease in emissions of anthropogenic aerosols, which is associated with the transition from fossil fuel burning to renewable and nuclear energy sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Amplified drought trends in Nepal increase the potential for Himalayan wildfires

Here we report in the spring 2021, Nepal underwent a record wildfire season in which active fires were detected at a rate 10 times greater than the 2002–2020 average. Prior to these major wildfire events, the country experienced a prolonged precipitation deficit and extreme drought during the post-monsoon period (starting in October 2020). An analysis using observational, reanalysis, and climate model ensemble data indicates that both climate variability and climate change-induced severe drought conditions were at play. Further analysis of climate model outputs suggests the likely reoccurrence of drought conditions, thus favoring active wildfire seasons in Nepal throughout the twenty-first century. While the inter-model uncertainty is large and direct modeling of wildfire spread and suppression has not been completed, the demonstrated relationship between a drought index (the standardized precipitation and evapotranspiration index) and subsequent fire activity may offer actionable opportunities for forest managers to employ the monitoring and projection of climate anomalies at sub-seasonal to decadal timescales to inform their management strategies for Nepal’s wildlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Climate science to inform adaptation policy: Heat waves over India in the 1.5°C and 2°C warmer worlds

Developing a better scientific understanding of anthropogenic climate change and climate variability, especially the prediction/projection of climate futures with useful temporal and geographical resolution and quantified uncertainties, and using that knowledge to inform adaptation planning and action will become crucially important in the coming years. Generating such policy-relevant knowledge may be particularly important for developing countries such as India. It is with this backdrop that, in this paper, we analyze future heat waves in India by using observations and a large number of model simulations of historical, + 1.5 °C, and + 2.0 °C warmer worlds. In both the future scenarios, there is an increased probability of heat waves during June and July when the Indian monsoon is in full swing and humidity is high, which makes the heat events even more of a health risk. While the highest temperatures in heat waves may not increase much in future climates, the duration and areal extent of the heat waves will most likely increase, leading to the emergence of new heat wave-prone zones in India. The results indicate that the joint frequencies of the longest duration and large area events could be nearly threefold greater in the + 1.5 °C and fivefold greater in the + 2.0 °C future scenarios compared to historical simulations. Thus, overall, the study indicates a substantial increase in the risk of heat events that typically elicit warnings from forecasters. The likely widespread and persistent nature of heat wave events in the future, as revealed by this study, will require planning and adaptation measures beyond the short-term disaster planning frameworks currently in place. Exploring what these measures might look like is beyond the scope of this study, but it underlines the importance of developing climate knowledge with high temporal and geographical resolution capable of informing adaptation policy and planning.

+1.5 °C and +2.0 °C↗
DOE OSTI2020

Atmospheric ice nuclei concentration measurements over a high altitude-station in the Western Ghats, India

Mixed-phase and ice clouds play a significant role in modulating the Indian summer monsoon rainfall, and modeling studies suggest that inaccurate representation of ice nucleating particles (INP) is one of the factors, which have resulted in a deficiency in the prediction of cloud properties and hydrological cycle. We do not understand the ice nucleation mechanisms to represent the ice formation in the model, and therefore more INP measurements at various supercooled temperatures are needed. This study reports for the first time real-time INP concentration at a high altitude station in the Western Ghats region of India, and these results will be used to constrain the ice nucleation parameterizations in the model. The variation of INP for any particular cloud condition can have strong microphysical responses of mixed-phase precipitation formation processes. Also, to improve the representation of heterogeneous ice nucleation, INP measurements of various types of aerosols commonly observed over the Indian region are needed. This study presents, the INP concentrations and daily concentration of non-refractory chemical composition (organics, sulfate, nitrate, ammonium, and chloride), cloud condensation nuclei (CCN), and aerosol size distribution. Spectrometer for Ice Nuclei (SPIN) was operated to measure INP concentration at the mountain site from August to December 2018. INP measurements were performed at three different temperatures (-25, -30, and - 34 °C) in the immersion freezing mode relevant for mixed-phase cloud conditions. The average INP concentrations approximately varied from 0.18 to 12.4 L-1, 0.39 to 24 L-1, 1.1 to 40.2 L-1 at -25, -30, and - 34 °C, respectively. These concentrations are within the concentrations reported in the literature from different regions across the globe. The air mass back trajectory analysis showed that continental air mass contains more INP compared to maritime air mass. The information on INP concentration and chemical characteristics of aerosol will help to improve heterogeneous ice nucleation parameterization in numerical models.

Kumar, Anil V.↗
DOE OSTI2022

Quantitative evaluations of subtropical westerly jet simulations over East Asia based on multiple CMIP5 and CMIP6 GCMs

As a salient feature of the Asian monsoon system, the East Asian subtropical westerly jet (EASWJ) exerts significant impacts on weather and climate changes in China and even throughout East Asia. In this paper, we applied a new self-adaptive algorithm to detect the EASWJ, identify its boundaries, and then represent its characteristics by defining three indices: the intensity index, meridional displacement index, and width index. Compared to the reanalysis data, we carried out a comprehensive, objective, and quantitative EASWJ evaluation using historical experiments from multiple global climate models (GCMs) in the Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5 and CMIP6). The results show that the multimodel ensemble mean (MME) of both CMIP5 and CMIP6 can simulate the characteristics of winter EASWJ well. While for the other three seasons, the MME of both phase models underestimate the 200-hPa zonal wind (U200) strength in the jet coverage area and overestimate the U200 outside the jet area, such simulation results weaken the meridional shear of the wind field. The EASWJ simulations from the CMIP5 GCMs had no consistent intensity or location characteristic tendencies, and most CMIP5 GCMs tended to simulate relatively wide-coverage jets. In contrast, most CMIP6 GCMs are inclined to simulate significantly weaker, wider, and more-northward jets. Compared to the predecessors in CMIP5, about half of CMIP6 GCMs significantly minimized the jet intensity bias, but remarkable errors were still observed in their jet location and coverage representations. Furthermore, the comparative analysis performed by classifying models based on their evaluated simulation results suggested that the simulated performance of the meridional temperature gradient was important for capturing the EASWJ characteristics. Further in-depth study of the causes of model differences is warranted to improve simulation results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Investigation on cloud vertical structures based on Ka-band cloud radar observations at Wuhan in Central China

Based on vertically pointing observations of Ka-band frequency-modulated continuous millimeter wave cloud radar (MMCR) in 2020, we investigate cloud vertical structures at Wuhan in central China. Case comparison indicates that the cloud top locations in the MMCR observation are largely consistent with those in satellite data. The precipitation has the occurrence frequency of 9.5% over the year, with the maximum value of 16.3% in July and the submaximal value of 14.7% in January, showing the significant influences of monsoons on precipitation at Wuhan. As the humid, cloudy and rainy climate, the probability of precipitation and non-precipitation clouds increases gradually from 53.9% in January to a large value of 71.5% in July. The non-precipitation clouds have the probability of 44.5% in the year, with two prominent peaks at the reflectivities of -35 to -30 dBZ around 12 km in summer and - 37– -32 dBZ around 10 km in spring. The cloud top can reach the heights of 14.49, 16.62, 13.38 and 11.73 km from spring to winter, respectively. The monthly mean cloud layer thickness is the largest (2.18 km) in May and September, and the smallest (1.36 km) in November. The seasonally averaged base and top heights and thickness of clouds have small diurnal variations. The high cloud is predominant in the warm months from May to September, and in the other cool months, the middle cloud has the most fraction. The quantitative investigation of clouds is helpful in improving the cloud parameterization in climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Analysis of heat and mass transfer potential of a dew-point cooling tower in different climatic conditions

In this study, the performance of the Dew-Point Cooling Tower (DPCT) was analyzed for different factors in a variety of climate conditions. For this purpose, a dedicated numerical model describing heat and mass transfer processes was developed and validated. The results of the numerical simulations allowed to analyze the potential of utilizing the heat and mass transfer process with the dew-point phenomenon for water cooling. It was established that the operational parameters that have a high impact on the performance of the DPCT are: inlet water temperature and inlet air humidity ratio. It was also established that DPCT achieves the highest COP and Specific Cooling Capacity for cold subtropical highland climates and that it achieves highest Wet-bulb Effectiveness for monsoon-influenced humid subtropical climates. In conclusion, the regions where all the efficiency factors achieved above-average values included warm, arid, and desert climates.

42 ENGINEERING↗
DOE OSTI2023

Wave climate and energy resources in the Mariana Islands from a 42-year high-resolution hindcast

We report a high-resolution wave hindcast from 1979 to 2020 was developed for Guam and the Commonwealth of the Northern Mariana Islands, which are influenced by mesoscale and synoptic weather systems from the western Pacific Rim to the Central Pacific. The spectral wave modeling utilized structured global and unstructured regional grids with improved resolution in nearshore waters, where wave resources development is most feasible. The hindcast demonstrates its capability in capturing multi-modal seas through reproduction of bulk and partitioned wave parameters derived from altimetry and buoy measurements. The local wave climate is influenced by the year-round trade winds and tropical cyclones as well as seasonal monsoons, frontal systems, and mid-latitude high- and low-pressure systems. The strong intra-annual variation of the significant wave height and power flux reflects transitions between local and distant weather systems, which account for the diverse wave conditions comprised of short-period wind waves, intermediate-period seas, and long-period swells around the islands. Among the Pacific island regions, spectral partitioning is particularly important for describing the dominant wave components by period and direction with pertinent information conducive to energy resources characterization and coastal zone management in the Mariana Islands.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Statistical Characteristics of Raindrop Size Distributions and Parameters in Central China during the Meiyu Seasons

The rain parameters measured by the laser OTT Parsivel raindrop disdrometer (Parsivel), the two-dimensional video disdrometer (2DVD) and DZZ5 tipping-bucket rain gauge (RG) during the Integrative Monsoon Frontal Rainfall Experiment (IMFRE) in summer 2018 are compared. The total rain amounts observed by Parsivel, 2DVD, and RG during IMFRE are 178.07 mm, 176.76 mm and 182.5 mm, while their total rainy hours are 113, 113 and 90. The mean Dm (mass-weighted mean diameter) and liquid water content values derived from Parsivel and 2DVD are 0.9 mm and 1.02 mm, and 0.247 g m-3 and 0.223 g m-3, respectively, and Parsivel is more sensitive to small raindrops (< 1 mm) than 2DVD. The raindrop spectra measured by Parsivel and 2DVD have excellent agreement for both convective rain (CR) and stratiform rain (SR) within a range of Dm from 1 to 3.5 mm. The rain samples from six Parsivel sites over the middle reaches of the Yangtze River during the 2016–2018 meiyu seasons have been collected and processed. The frequency occurrences for rain rates (RR) < 5 and > 10 mm h-1 are 83.9% and 7.4%, respectively, but they contribute 30.5% and 52.1 % of the total accumulated rainfall. Comparing the results with those over the lower reaches, the RR and total accumulated rainfall over the middle reaches are greater, especially for heavy rainfall. The rain drop size distributions (DSDs) in this study are wider and have higher number concentration than those from the lower reaches.

Raindrop size distribution, Meiyu front, disdromet↗
DOE OSTI2020

Structure of an Atmospheric River over Australia and the Southern Ocean. Part I: Tropical and Midlatitude Water Vapor Fluxes

An atmospheric river (AR) impacting Australia-Tasmania and the Southern Ocean during the Austral summer on 28-29 January 2018 during the SOCRATES campaign is analyzed using both a modeling and observational approach. Gulfstream-V dropsonde measurements and GPM radar analyses were used in conjunction with Weather Research and Forecasting model simulations with water vapor tracers to investigate the relative contributions of tropical and mid-latitude moisture sources to the AR. Moisture associated with a monsoonal tropical depression became entrained into a mid-latitude frontal system that extended to 60°S over the Southern Ocean reaching the associated low pressure system 850 km off the east coast of Antarctica – effectively connecting the tropics and the polar region. Tropical moisture contributed to about 50% of the precipitable water within the AR. The tropical contribution to precipitation decreased with latitude, from > 70% over the Australian continent, to ~50% off the Australian coast, to less than 10% poleward of 60°S. Precipitation in the AR conformed to a seeder-feeder model, the seeder precipitation forming primarily from tropical sourced moisture above the altitude of the 0°C isotherm, and the feeder precipitation sourced from mid-latitude sourced moisture below the altitude of the 0°C isotherm. The integrated vapor transport (IVT) through the core of the AR reached above 500 kg m-1s-1 during 1200 UTC 28 January to 0600 UTC 29 January 29, 1.29 times the average amount of water carried by the world’s largest river, the Amazon. The high IVT strength might be attributed to the higher water vapor content associated with the warmer temperatures in Austral summer.

Rauber, Robert M.↗
DOE OSTI2021

New Particle Formation and Growth to Climate-Relevant Aerosols at a Background Remote Site in the Western Himalaya

New particle formation (NPF) can influence the Earth’s radiative budget when the newly formed particles grow to climate-relevant sizes. Here, we present analysis of 21-months of continuous aerosol size distribution measurements at a background remote site in the western Himalaya and provide observational evidence that newly formed particles grow to cloud condensation nuclei (CCN)-active sizes (i.e. >20-100 nm in diameter). Out of total 55 NPF events, 38 (66%) events occurred in the pre-monsoon season (March-May). NPF events were classified into those with and without pollution influence as polluted and cleaner, respectively, using black carbon data. The analysis of air mass age, based on the ratio of number concentration of Aitken to accumulation mode aerosols, indicated that NPF occurred in the relatively cleaner air masses reaching to the site. The median formation rate of 10 nm particles and particle growth rates for cleaner events were three-fold and two-fold, respectively, higher than polluted events. We present the first estimates of the survival probability of newly formed particles to 50 nm and 100 nm size, which was not attempted in an Indian environment previously. The survival probability to 50 nm particles ranged from 44 to 98%, with a mean and standard deviation of 82 ± 18%. On average, ~60% of the particles surviving to 50 nm survived to 100 nm, making the overall survival probability of 100 nm to 53 ± 31%. This indicates that the probability of nucleated particles growing to CCN-active sizes under a large source of condensing vapor (transported from nearby lower-altitude regions) and low pre-existing particle concentrations (background mountain site) is high compared to the previous studies. These findings highlight the importance of the efficiency of nucleation events for producing CCN, which is a critical basis of aerosol indirect effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Soil Respiration Response to Rainfall Modulated by Plant Phenology in a Montane Meadow, East River, Colorado, USA

Soil respiration is a primary component of the terrestrial carbon cycle. However, predicting the response of soil respiration to climate change remains a challenge due to the complex interactions between environmental drivers, especially plant phenology, temperature, and soil moisture. In this study, we use a 1-D diffusion-reaction model to calculate depth-resolved CO 2 production rates from soil CO 2 concentrations and surface efflux observations in a subalpine meadow in the East River watershed, CO. Modeled rates are compared to in situ soil temperature and moisture conditions and MODIS satellite enhanced vegetation index (EVI) representing plant phenology across three hydrologically distinct growing seasons from 2016-2018. While soil respiration correlated with temperature on diel timescales (p<0.05), seasonal variability was dominated by soil moisture and plant phenology (p<0.05). We observed significant respiration increases in response to precipitation events; however, magnitude and duration were significantly higher in 2017 than 2016 despite similar wetting characteristics. Based on MODIS EVI, we suggest the respiration response to rainfall is controlled by plant phenology, which in turn reflects the capacity of plants to respond to precipitation via increased photosynthesis and autotrophic respiration, behavior that is not captured in typical soil respiration pulse models. Projected changes in montane climate such as earlier snowmelt and prolonged fore-summer drought may decrease soil respiration fluxes by decreasing the overlap between peak productivity and the summer monsoon. Lastly, we observed significant late-season CO 2 fluxes from the deep sub-soil (>165 cm) that support growing evidence for the importance of sub-soil processes in driving integrated respiration fluxes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Simulated Precipitation Diurnal Variation With a Deep Convective Closure Subject to Shallow Convection in Community Atmosphere Model Version 5 Coupled With CLUBB

In order to improve the physical consistency between shallow and deep convection, we modify the deep convective closure in the Community Atmosphere Model version 5 (CAM5) coupled with a third-order turbulence closure parameterization (i.e., Cloud Layers Unified by Binormals; CLUBB). The revised closure reserves a portion of the total convective available potential energy for shallow convection via utilizing the heating and moistening profiles from CLUBB to distribute moisture and energy between shallow and deep convection. Simulations at two resolutions (i.e. 2° and 0.5°, respectively) are conducted to investigate the impacts of convective closure on the simulated precipitation diurnal variations. Results from low-resolution simulations show that the revised closure suppresses deep convection until the lower troposphere is sufficiently moistened by shallow convection, which improves the precipitation diurnal variation simulations compared to the default closure, with the precipitation diurnal peak over tropical lands delayed from 12LST to 19LST. The revised closure better simulates the diurnal variations for precipitation over the Asian monsoon region, such as the delayed precipitation onset, but still fails to well capture the nighttime peak for precipitation there. This deficiency is alleviated to some extent when applying the revised closure in highresolution simulations, but nighttime precipitation is still underestimated probably because key processes responsible for nighttime convection are missing. Altogether, our results indicate that establishing the consistency between shallow and deep convection is critical for the precipitation diurnal cycle simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Moist Physics Parameterization Based on Deep Learning

Abstract Current moist physics parameterization schemes in general circulation models (GCMs) are the main source of biases in simulated precipitation and atmospheric circulation. Recent advances in machine learning make it possible to explore data‐driven approaches to developing parameterization for moist physics processes such as convection and clouds. This study aims to develop a new moist physics parameterization scheme based on deep learning. We use a residual convolutional neural network (ResNet) for this purpose. It is trained with 1‐year simulation from a superparameterized GCM, SPCAM. An independent year of SPCAM simulation is used for evaluation. In the design of the neural network, referred to as ResCu, the moist static energy conservation during moist processes is considered. In addition, the past history of the atmospheric states, convection, and clouds is also considered. The predicted variables from the neural network are GCM grid‐scale heating and drying rates by convection and clouds, and cloud liquid and ice water contents. Precipitation is derived from predicted moisture tendency. In the independent data test, ResCu can accurately reproduce the SPCAM simulation in both time mean and temporal variance. Comparison with other neural networks demonstrates the superior performance of ResNet architecture. ResCu is further tested in a single‐column model for both continental midlatitude warm season convection and tropical monsoonal convection. In both cases, it simulates the timing and intensity of convective events well. In the prognostic test of tropical convection case, the simulated temperature and moisture biases with ResCu are smaller than those using conventional convection and cloud parameterizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Linking Deep and Shallow Convective Mass Fluxes via an Assumed Entrainment Distribution in CAM5‐CLUBB: Parameterization and Simulated Precipitation Variability

Abstract We modify the Zhang‐McFarlane (ZM) deep convection scheme in the Community Atmosphere Model version 5 to couple it with a unified parameterization for boundary‐layer turbulence and shallow convection, that is, Cloud Layers Unified by Binormals (CLUBB). By assuming a lognormal distribution of entrainment rate across the entire moist convective regimes, we link mass fluxes between shallow and deep convection, which are partitioned by the entrainment rate of the shallowest deep convective plume. Hence, a new deep convective closure is established which is coupled to the sub‐grid vertical motion variability in CLUBB. The convection feedback (or memory) effects are also considered to decrease the entrainment spectrum width and enhance the vertical velocity variability that further affect deep convection. Results show that the revised scheme improves the precipitation simulations in terms of the mean state and variability at various timescales, such as the alleviated double‐intertropical convergence zone and more realistic simulations of the seasonal variation of monsoon precipitation over East Asia, Madden‐Julian Oscillation, and precipitation diurnal phase propagations downstream of large terrains. The improvements are still seen in many aspects such as the mean‐state precipitation when turning off the convection feedback impacts in the revised scheme, emphasizing the benefits of using the modified mass‐flux closure. However, the convection feedbacks have considerable effects on the precipitation diurnal cycle simulations over regions with late‐afternoon precipitation peaks. Overall, the revised scheme provides a unified treatment for sub‐grid vertical motions across regimes of boundary‐layer turbulence, shallow convection, and deep convection, leading to better‐simulated precipitation at various timescales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

New Insights Into Error Decomposition for Precipitation Products

Abstract It is very important to quantify errors of precipitation estimation products. However, the existing methods do not describe all error components and are therefore not comprehensive enough. In this study, we propose a four‐component error decomposition method (4CED) that decomposes the total errors of precipitation products into four independent parts: hit positive bias, hit negative bias, false bias, and missed bias. And we use it to evaluate the performance of the three latest satellite precipitation products in the eastern monsoon region of China. Our study reveals 4CED has apparent improvements compared with the previous method. Results also provide new insights for tracking error sources and quantifying the error magnitudes of precipitation products. Moreover, the proposed 4CED can be extended to different spatial and temporal scales. Our new method will not only contribute to product upgrades, but also provide guidance for potential applications.

58 GEOSCIENCES↗
DOE OSTI2021

The Oceanic Barrier Layer in the Eastern Indian Ocean as a Predictor for Rainfall Over Indonesia and Australia

Barrier layers in the tropics trap heat in a shallow and stable near-surface layer and limit entrainment of cooler water from below. Both processes act to increase sea surface temperature and enhance atmospheric convection. The high resolution fully coupled pre-industrial Energy Exascale Earth System Model version 0 (E3SMv0) is used to investigate the relationship between barrier layers in the eastern Indian Ocean during the wet season with local atmospheric convection and remote rainfall. A partial least squares regression reveals a significant relationship between Australasian rainfall and the barrier layer thickness (BLT) west of Sumatra, occurring one month earlier. Furthermore, the largest positive regression coefficients are over northern Australia. The region west of Sumatra is strategically located where the East-Asian monsoon moisture flows toward northern Australia. Thickening of the west Sumatra BLT intensifies evaporation and local convection and amplifies the moisture transported to Australia acting to increase the terrestrial rainfall.

58 GEOSCIENCES↗